id
float64
706
1.8k
title
stringlengths
1
343
abstract
stringlengths
6
6.09k
categories
stringlengths
5
125
processed_abstract
stringlengths
2
5.96k
tokenized_abstract
stringlengths
8
8.74k
centroid
stringlengths
2.1k
2.17k
1,802.0906
On higher direct images of convergent isocrystals
Let k be a perfect field of characteristic p>0 and W the ring of Witt vectors of k. In this article, we give a new proof of the Frobenius descent for convergent isocrystals on a variety over k relative to W. This proof allows us to deduce an analogue of the de Rham complexes comparaison theorem of Berthelot without assuming a lifting of the Frobenius morphism. As an application, we prove a version of Berthelot's conjecture on the preservation of convergent isocrystals under the higher direct image by a smooth proper morphism of k-varieties.
math.AG math.NT
let k be a perfect field of characteristic p0 and w the ring of witt vectors of k in this article we give a new proof of the frobenius descent for convergent isocrystals on a variety over k relative to w this proof allows us to deduce an analogue of the de rham complexes comparaison theorem of berthelot without assuming a lifting of the frobenius morphism as an application we prove a version of berthelots conjecture on the preservation of convergent isocrystals under the higher direct image by a smooth proper morphism of kvarieties
[['let', 'k', 'be', 'a', 'perfect', 'field', 'of', 'characteristic', 'p0', 'and', 'w', 'the', 'ring', 'of', 'witt', 'vectors', 'of', 'k', 'in', 'this', 'article', 'we', 'give', 'a', 'new', 'proof', 'of', 'the', 'frobenius', 'descent', 'for', 'convergent', 'isocrystals', 'on', 'a', 'variety', 'over', 'k', 'relative', 'to', 'w', 'this', 'proof', 'allows', 'us', 'to', 'deduce', 'an', 'analogue', 'of', 'the', 'de', 'rham', 'complexes', 'comparaison', 'theorem', 'of', 'berthelot', 'without', 'assuming', 'a', 'lifting', 'of', 'the', 'frobenius', 'morphism', 'as', 'an', 'application', 'we', 'prove', 'a', 'version', 'of', 'berthelots', 'conjecture', 'on', 'the', 'preservation', 'of', 'convergent', 'isocrystals', 'under', 'the', 'higher', 'direct', 'image', 'by', 'a', 'smooth', 'proper', 'morphism', 'of', 'kvarieties']]
[-0.22291686724712875, -0.011917463635983679, -0.18906900973524898, 0.02437853870140587, -0.09750270004324774, -0.10974237415506108, 0.00427858599528492, 0.2964112253740747, -0.3812510483561361, -0.20245360482008534, 0.04122777533236931, -0.14607532139625426, -0.07767377618175159, 0.23420761799578496, -0.17715254149578036, -0.07285653264757166, 0.04720807235757325, 0.09633245671594, -0.11073537526572956, -0.2932604793483946, 0.396444451202579, -0.008666330136041692, 0.21980726526693461, 0.04719388233980738, 0.15633092379752309, 0.06377067439694037, -0.004282383287840701, -0.04175429220777005, -0.19541667576165908, 0.15785179266884447, 0.29598105465002517, 0.08787597833508427, 0.2578633156099773, -0.33508260413370233, -0.09744049412287534, 0.20876900276089919, 0.11399995770919671, 0.05862591165722288, -0.03147054493007438, -0.2748649483447538, 0.1987260359121447, -0.1743962667545581, -0.1486325468719402, -0.08675175042268127, 0.04086638488521938, 0.024399894371410793, -0.28297031354753577, -0.019853279955605877, 0.15402179016978443, 0.16946128604220265, -0.07376478575826424, -0.09328071032947999, -0.018710495413657515, 0.006392895392677251, -0.03625618379582909, 0.07781414056513855, 0.08026601004592598, -0.08220742135110529, -0.12215540193496867, 0.3395718004395987, -0.1557812091319802, -0.1425343794807633, 0.11844245441495738, -0.10532203301827008, -0.12183687722984146, 0.15553003975854038, 0.06602207441477383, 0.2149032797030312, 0.012063406843771326, 0.2003714260936249, -0.15590649204170134, 0.0964924792234013, 0.14473877056561252, -0.0038687979921381522, 0.13063912847862044, 0.040521753248461384, 0.14081751022697178, 0.14078851237749443, -0.008264415139490937, -0.0014210894897064947, -0.37214922476956186, -0.26591567782328485, -0.11845518658284415, 0.206013469520877, -0.12929810496233526, -0.18276555324964067, 0.37549370252824527, 0.06630763261420454, 0.21621302153142366, 0.1327078898258983, 0.23480731359821685, 0.05474535309328163, 0.020788039165013966, -0.006602445805564206, 0.08519043399892906, 0.29561451977326914, 0.00949290630957508, -0.14028076722752303, -0.02632622186594861, 0.20275371526665192]
1,802.09061
Velocity Memory Effect for Polarized Gravitational Waves
Circularly polarized gravitational sandwich waves exhibit, as do their linearly polarized counterparts, the Velocity Memory Effect: freely falling test particles in the flat after-zone fly apart along straight lines with constant velocity. In the inside zone their trajectories combine oscillatory and rotational motions in a complicated way. For circularly polarized periodic gravitational waves some trajectories remain bounded, while others spiral outward. These waves admit an additional "screw" isometry beyond the usual five. The consequences of this extra symmetry are explored.
gr-qc astro-ph.HE hep-th
circularly polarized gravitational sandwich waves exhibit as do their linearly polarized counterparts the velocity memory effect freely falling test particles in the flat afterzone fly apart along straight lines with constant velocity in the inside zone their trajectories combine oscillatory and rotational motions in a complicated way for circularly polarized periodic gravitational waves some trajectories remain bounded while others spiral outward these waves admit an additional screw isometry beyond the usual five the consequences of this extra symmetry are explored
[['circularly', 'polarized', 'gravitational', 'sandwich', 'waves', 'exhibit', 'as', 'do', 'their', 'linearly', 'polarized', 'counterparts', 'the', 'velocity', 'memory', 'effect', 'freely', 'falling', 'test', 'particles', 'in', 'the', 'flat', 'afterzone', 'fly', 'apart', 'along', 'straight', 'lines', 'with', 'constant', 'velocity', 'in', 'the', 'inside', 'zone', 'their', 'trajectories', 'combine', 'oscillatory', 'and', 'rotational', 'motions', 'in', 'a', 'complicated', 'way', 'for', 'circularly', 'polarized', 'periodic', 'gravitational', 'waves', 'some', 'trajectories', 'remain', 'bounded', 'while', 'others', 'spiral', 'outward', 'these', 'waves', 'admit', 'an', 'additional', 'screw', 'isometry', 'beyond', 'the', 'usual', 'five', 'the', 'consequences', 'of', 'this', 'extra', 'symmetry', 'are', 'explored']]
[-0.21176713958892476, 0.26087317478572625, -0.05892245116631819, 0.05896106969912925, -0.16179498357556854, -0.14035116695457056, -0.014857320887326922, 0.48239070252527166, -0.29778900967698685, -0.22519592357699206, 0.04897740387941322, -0.27462335041712355, -0.05923064541118809, 0.17656588994255407, 0.03243306841512647, 0.023482472033098434, 0.01870331390984828, -0.00711376869703254, -0.040250574592265144, -0.16616893496034266, 0.2545684463745337, 0.02634914407412274, 0.24962102734967123, -0.08672579998280146, 0.07710389768751928, -0.005523465055076382, -0.04607140724370374, 0.009926836595788031, -0.1096966398608741, 0.042236178890135895, 0.15726255400318512, 0.016753573701540125, 0.1781451162245549, -0.5219318263138397, -0.2373767249710575, 0.052874064432527824, 0.18389117402684746, 0.164902363461737, -0.050695045361931944, -0.33725897439672975, -0.026841040453107298, -0.09485081653258044, -0.2989113986303535, -0.02722684940606167, 0.06677305217997372, 0.05084055076762916, -0.10640784551955382, 0.09763973058920496, 0.11776987185017972, 0.06762386507154265, -0.0884699522034277, -0.05345490855412393, -0.12157587219277231, 0.06593375347401428, 0.12703124479216796, 0.04796658562425571, 0.18386160836502013, -0.121648229346198, -0.09684015038906585, 0.39511987076529975, -0.09493638536173708, -0.23062883398813916, 0.18301244820409182, -0.20720313738182752, -0.07574084293851747, 0.2532754617542783, 0.17386282350915142, 0.1377698116688223, -0.07354169852347879, 0.0811982142165763, -0.04649641050049399, 0.10551412304556823, 0.2301986653275222, 0.05133113062563293, 0.3346063039866807, 0.015690855210340474, 0.07621456727774555, 0.09881053765118712, -0.09930858554766525, -0.06989663809867977, -0.3054292303969777, -0.09914625183785264, -0.06676600373621229, 0.03719211025811921, -0.05950231166373013, -0.18719280325465754, 0.3462446061540631, 0.05874846433584072, 0.14432117990159157, 0.043520985591914974, 0.3076904713282291, 0.022481304229402185, 0.05428461222084168, 0.13093388329342573, 0.32383286148859364, 0.139514427098646, 0.08684363240034237, -0.20718040601998755, -0.005040917197784669, -0.018518352711056004]
1,802.09062
Stability of Low-Rank Tensor Representations and Structured Multilevel Preconditioning for Elliptic PDEs
Folding grid value vectors of size $2^L$ into $L$th order tensors of mode sizes $2\times \cdots\times 2$, combined with low-rank representation in the tensor train format, has been shown to lead to highly efficient approximations for various classes of functions. These include solutions of elliptic PDEs on nonsmooth domains or with oscillatory data. This tensor-structured approach is attractive because it leads to highly compressed, adaptive approximations based on simple discretizations. Standard choices of the underlying basis, such as piecewise multilinear finite elements on uniform tensor product grids, entail the well-known matrix ill-conditioning of discrete operators. We demonstrate that for low-rank representations, the use of tensor structure itself additionally introduces representation ill-conditioning, a new effect specific to computations in tensor networks. We analyze the tensor structure of a BPX preconditioner for second-order linear elliptic operators and construct an explicit tensor-structured representation of the preconditioner, with ranks independent of the number $L$ of discretization levels. The straightforward application of the preconditioner yields discrete operators whose matrix conditioning is uniform with respect to the discretization parameter, but in decompositions that suffer from representation ill-conditioning. By additionally eliminating certain redundancies in the representations of the preconditioned discrete operators, we obtain reduced-rank decompositions that are free of both matrix and representation ill-conditioning. For an iterative solver based on soft thresholding of low-rank tensors, we obtain convergence and complexity estimates and demonstrate its reliability and efficiency for discretizations with up to $2^{50}$ nodes in each dimension.
math.NA cs.NA
folding grid value vectors of size 2l into lth order tensors of mode sizes 2times cdotstimes 2 combined with lowrank representation in the tensor train format has been shown to lead to highly efficient approximations for various classes of functions these include solutions of elliptic pdes on nonsmooth domains or with oscillatory data this tensorstructured approach is attractive because it leads to highly compressed adaptive approximations based on simple discretizations standard choices of the underlying basis such as piecewise multilinear finite elements on uniform tensor product grids entail the wellknown matrix illconditioning of discrete operators we demonstrate that for lowrank representations the use of tensor structure itself additionally introduces representation illconditioning a new effect specific to computations in tensor networks we analyze the tensor structure of a bpx preconditioner for secondorder linear elliptic operators and construct an explicit tensorstructured representation of the preconditioner with ranks independent of the number l of discretization levels the straightforward application of the preconditioner yields discrete operators whose matrix conditioning is uniform with respect to the discretization parameter but in decompositions that suffer from representation illconditioning by additionally eliminating certain redundancies in the representations of the preconditioned discrete operators we obtain reducedrank decompositions that are free of both matrix and representation illconditioning for an iterative solver based on soft thresholding of lowrank tensors we obtain convergence and complexity estimates and demonstrate its reliability and efficiency for discretizations with up to 250 nodes in each dimension
[['folding', 'grid', 'value', 'vectors', 'of', 'size', '2l', 'into', 'lth', 'order', 'tensors', 'of', 'mode', 'sizes', '2times', 'cdotstimes', '2', 'combined', 'with', 'lowrank', 'representation', 'in', 'the', 'tensor', 'train', 'format', 'has', 'been', 'shown', 'to', 'lead', 'to', 'highly', 'efficient', 'approximations', 'for', 'various', 'classes', 'of', 'functions', 'these', 'include', 'solutions', 'of', 'elliptic', 'pdes', 'on', 'nonsmooth', 'domains', 'or', 'with', 'oscillatory', 'data', 'this', 'tensorstructured', 'approach', 'is', 'attractive', 'because', 'it', 'leads', 'to', 'highly', 'compressed', 'adaptive', 'approximations', 'based', 'on', 'simple', 'discretizations', 'standard', 'choices', 'of', 'the', 'underlying', 'basis', 'such', 'as', 'piecewise', 'multilinear', 'finite', 'elements', 'on', 'uniform', 'tensor', 'product', 'grids', 'entail', 'the', 'wellknown', 'matrix', 'illconditioning', 'of', 'discrete', 'operators', 'we', 'demonstrate', 'that', 'for', 'lowrank', 'representations', 'the', 'use', 'of', 'tensor', 'structure', 'itself', 'additionally', 'introduces', 'representation', 'illconditioning', 'a', 'new', 'effect', 'specific', 'to', 'computations', 'in', 'tensor', 'networks', 'we', 'analyze', 'the', 'tensor', 'structure', 'of', 'a', 'bpx', 'preconditioner', 'for', 'secondorder', 'linear', 'elliptic', 'operators', 'and', 'construct', 'an', 'explicit', 'tensorstructured', 'representation', 'of', 'the', 'preconditioner', 'with', 'ranks', 'independent', 'of', 'the', 'number', 'l', 'of', 'discretization', 'levels', 'the', 'straightforward', 'application', 'of', 'the', 'preconditioner', 'yields', 'discrete', 'operators', 'whose', 'matrix', 'conditioning', 'is', 'uniform', 'with', 'respect', 'to', 'the', 'discretization', 'parameter', 'but', 'in', 'decompositions', 'that', 'suffer', 'from', 'representation', 'illconditioning', 'by', 'additionally', 'eliminating', 'certain', 'redundancies', 'in', 'the', 'representations', 'of', 'the', 'preconditioned', 'discrete', 'operators', 'we', 'obtain', 'reducedrank', 'decompositions', 'that', 'are', 'free', 'of', 'both', 'matrix', 'and', 'representation', 'illconditioning', 'for', 'an', 'iterative', 'solver', 'based', 'on', 'soft', 'thresholding', 'of', 'lowrank', 'tensors', 'we', 'obtain', 'convergence', 'and', 'complexity', 'estimates', 'and', 'demonstrate', 'its', 'reliability', 'and', 'efficiency', 'for', 'discretizations', 'with', 'up', 'to', '250', 'nodes', 'in', 'each', 'dimension']]
[-0.08701929444456862, 0.05611122734953824, -0.07384505978552625, 0.017565322426283576, -0.10811817625265879, -0.1290417609932774, -0.02193375088487907, 0.3864730611288299, -0.3367245654342696, -0.25161425148956673, 0.15970251784456196, -0.23823020981120255, -0.16222442291909828, 0.1382965648782071, -0.06666961548035033, 0.09408494040811395, 0.09561645739789432, 0.012807252411342536, -0.16854015403126443, -0.2288683293600722, 0.34347779328915445, 0.03097725100427245, 0.28026044761936647, 0.006863593706899943, 0.14542705720377852, -0.021999623218531876, -0.07187684804666787, -0.025828504371505308, -0.030816707266755353, 0.16462771066871937, 0.27948555508628486, 0.10960907221521363, 0.2666326926089823, -0.43762936343361314, -0.1597012249432737, 0.1122943289214163, 0.147643150985823, 0.08173001496664559, -0.020733267994364722, -0.24732461408226905, 0.10229910018000131, -0.1848398660775274, -0.10128223778835187, -0.19618975567185165, -0.024136762829342236, 0.01718928993990024, -0.3431047191673618, 0.078735834294154, 0.05993832494908323, 0.030690441913126656, -0.07629955241912588, -0.19919682514543335, 0.033379851566375386, 0.04721093138068681, 0.0263627194740972, -0.042325061132820946, 0.06407275685148003, -0.0986223075723198, -0.09432082784478553, 0.3690469761786517, -0.040177723061545594, -0.3188672942497457, 0.15608102227755202, -0.0691116622784951, -0.12568417755828704, 0.13771278343629093, 0.22064685327204642, 0.1214723280975401, -0.07109697106886112, 0.1306333308716906, -0.02659638396774729, 0.16873240276763682, 0.06962289087532554, 0.03064650218002498, 0.06257136190591457, 0.13189512349878593, 0.14532329928479157, 0.13507290516475526, -0.01263188819818121, -0.08464827305579092, -0.2801173779274298, -0.11668202175060287, -0.2041924260075272, 0.02707799281924963, -0.20475999575858925, -0.2567511323532623, 0.4037604247724327, 0.1298189223870698, 0.18878791428602806, 0.09853667956000815, 0.29681915282271804, 0.1559086220159467, 0.1014449344521078, 0.09535152656802287, 0.1404315598406053, 0.20107429360893245, 0.05732075796580224, -0.19691246204602067, 0.031961028570852555, 0.18850316541890302]
1,802.09063
Conditions for defocusing around more general metrics in Infinite Derivative Gravity
Infinite Derivative Gravity is able to resolve the Big Bang curvature singularity present in general relativity by using a simplifying ansatz. We show that it can also avoid the Hawking- Penrose singularity, by allowing defocusing of null rays through the Raychaudhuri equation. This occurs not only in the minimal case where we ignore the matter contribution, but also in the case where matter plays a key role. We investigate the conditions for defocusing for the general case where this ansatz applies and also for more specific metrics, including a general Friedmann-Robertson-Walker (FRW) metric and three specific choices of the scale factor which produce a bouncing FRW universe.
gr-qc
infinite derivative gravity is able to resolve the big bang curvature singularity present in general relativity by using a simplifying ansatz we show that it can also avoid the hawking penrose singularity by allowing defocusing of null rays through the raychaudhuri equation this occurs not only in the minimal case where we ignore the matter contribution but also in the case where matter plays a key role we investigate the conditions for defocusing for the general case where this ansatz applies and also for more specific metrics including a general friedmannrobertsonwalker frw metric and three specific choices of the scale factor which produce a bouncing frw universe
[['infinite', 'derivative', 'gravity', 'is', 'able', 'to', 'resolve', 'the', 'big', 'bang', 'curvature', 'singularity', 'present', 'in', 'general', 'relativity', 'by', 'using', 'a', 'simplifying', 'ansatz', 'we', 'show', 'that', 'it', 'can', 'also', 'avoid', 'the', 'hawking', 'penrose', 'singularity', 'by', 'allowing', 'defocusing', 'of', 'null', 'rays', 'through', 'the', 'raychaudhuri', 'equation', 'this', 'occurs', 'not', 'only', 'in', 'the', 'minimal', 'case', 'where', 'we', 'ignore', 'the', 'matter', 'contribution', 'but', 'also', 'in', 'the', 'case', 'where', 'matter', 'plays', 'a', 'key', 'role', 'we', 'investigate', 'the', 'conditions', 'for', 'defocusing', 'for', 'the', 'general', 'case', 'where', 'this', 'ansatz', 'applies', 'and', 'also', 'for', 'more', 'specific', 'metrics', 'including', 'a', 'general', 'friedmannrobertsonwalker', 'frw', 'metric', 'and', 'three', 'specific', 'choices', 'of', 'the', 'scale', 'factor', 'which', 'produce', 'a', 'bouncing', 'frw', 'universe']]
[-0.11337133459246361, 0.09140854021403765, -0.10745037062350382, 0.15967840944508213, -0.1330659545144223, -0.18134131742354098, -0.055142538624197664, 0.29464190435012644, -0.20949369118870975, -0.23117158723838419, 0.07207557763229777, -0.25018093273670317, -0.1417414961887576, 0.1446707175922728, -0.046043499198820545, 0.006667224572814792, 0.02207228611332199, 0.04736079727343031, -0.058010134861203974, -0.2740103918547681, 0.4463403287526464, 0.091272652053457, 0.23900527218966006, 0.07188443419584464, 0.11160126069961028, -0.011786906344589785, -0.005992202558250071, 0.028200279416464198, -0.1935823774403837, 0.027982840305803534, 0.21084527671554726, 0.1180595371819963, 0.24224813895247807, -0.4388437048819299, -0.2959199780685322, 0.16231299495481163, 0.1747346637492007, 0.17098611467365593, -0.07377830840863188, -0.2708919153387754, 0.05225227015075561, -0.15076989819356632, -0.17399097599576566, -0.06504706787728817, 0.005756127265081784, -0.08614255606292565, -0.2064498856655, 0.1328709016994151, 0.07387929131651175, -0.060588015626384835, -0.06865782642989446, -0.0017901557654351275, 0.04071992347626207, 0.033613902320824215, 0.08401157827743233, -0.00870225851850532, 0.08971525714341029, -0.13934589016945406, -0.03529010511604007, 0.44509500715986033, -0.10972785886168201, -0.25543530484678867, 0.10186129074900577, -0.1728456110267021, -0.15020376011711833, 0.06615425432057033, 0.11133242418410727, 0.14715258906939216, -0.15506787257808669, 0.1839962229861608, 0.019770380170476214, 0.12062500974938065, 0.17807937873022578, -0.0246159381360451, 0.2221864669923192, 0.1136312963676021, 0.06209381991805874, 0.13302371339332836, -0.030816736326457185, -0.1250947970748992, -0.409128043870224, -0.1880854990455174, -0.11804639968464029, 0.10085766444161695, -0.1843305320615519, -0.17271849645353923, 0.3547984829398795, 0.13645373550803994, 0.1571089094504714, 0.025297679774088908, 0.2584578070580681, 0.07072836141456702, 0.011138442947276842, 0.11666573939200874, 0.2732435623140327, 0.07903986451625128, 0.13704865958724416, -0.20932234014018883, 0.0011829043625392647, 0.04686159592678892]
1,802.09064
Model Agnostic Time Series Analysis via Matrix Estimation
We propose an algorithm to impute and forecast a time series by transforming the observed time series into a matrix, utilizing matrix estimation to recover missing values and de-noise observed entries, and performing linear regression to make predictions. At the core of our analysis is a representation result, which states that for a large model class, the transformed time series matrix is (approximately) low-rank. In effect, this generalizes the widely used Singular Spectrum Analysis (SSA) in time series literature, and allows us to establish a rigorous link between time series analysis and matrix estimation. The key to establishing this link is constructing a Page matrix with non-overlapping entries rather than a Hankel matrix as is commonly done in the literature (e.g., SSA). This particular matrix structure allows us to provide finite sample analysis for imputation and prediction, and prove the asymptotic consistency of our method. Another salient feature of our algorithm is that it is model agnostic with respect to both the underlying time dynamics and the noise distribution in the observations. The noise agnostic property of our approach allows us to recover the latent states when only given access to noisy and partial observations a la a Hidden Markov Model; e.g., recovering the time-varying parameter of a Poisson process without knowing that the underlying process is Poisson. Furthermore, since our forecasting algorithm requires regression with noisy features, our approach suggests a matrix estimation based method - coupled with a novel, non-standard matrix estimation error metric - to solve the error-in-variable regression problem, which could be of interest in its own right. Through synthetic and real-world datasets, we demonstrate that our algorithm outperforms standard software packages (including R libraries) in the presence of missing data as well as high levels of noise.
cs.LG stat.ML
we propose an algorithm to impute and forecast a time series by transforming the observed time series into a matrix utilizing matrix estimation to recover missing values and denoise observed entries and performing linear regression to make predictions at the core of our analysis is a representation result which states that for a large model class the transformed time series matrix is approximately lowrank in effect this generalizes the widely used singular spectrum analysis ssa in time series literature and allows us to establish a rigorous link between time series analysis and matrix estimation the key to establishing this link is constructing a page matrix with nonoverlapping entries rather than a hankel matrix as is commonly done in the literature eg ssa this particular matrix structure allows us to provide finite sample analysis for imputation and prediction and prove the asymptotic consistency of our method another salient feature of our algorithm is that it is model agnostic with respect to both the underlying time dynamics and the noise distribution in the observations the noise agnostic property of our approach allows us to recover the latent states when only given access to noisy and partial observations a la a hidden markov model eg recovering the timevarying parameter of a poisson process without knowing that the underlying process is poisson furthermore since our forecasting algorithm requires regression with noisy features our approach suggests a matrix estimation based method coupled with a novel nonstandard matrix estimation error metric to solve the errorinvariable regression problem which could be of interest in its own right through synthetic and realworld datasets we demonstrate that our algorithm outperforms standard software packages including r libraries in the presence of missing data as well as high levels of noise
[['we', 'propose', 'an', 'algorithm', 'to', 'impute', 'and', 'forecast', 'a', 'time', 'series', 'by', 'transforming', 'the', 'observed', 'time', 'series', 'into', 'a', 'matrix', 'utilizing', 'matrix', 'estimation', 'to', 'recover', 'missing', 'values', 'and', 'denoise', 'observed', 'entries', 'and', 'performing', 'linear', 'regression', 'to', 'make', 'predictions', 'at', 'the', 'core', 'of', 'our', 'analysis', 'is', 'a', 'representation', 'result', 'which', 'states', 'that', 'for', 'a', 'large', 'model', 'class', 'the', 'transformed', 'time', 'series', 'matrix', 'is', 'approximately', 'lowrank', 'in', 'effect', 'this', 'generalizes', 'the', 'widely', 'used', 'singular', 'spectrum', 'analysis', 'ssa', 'in', 'time', 'series', 'literature', 'and', 'allows', 'us', 'to', 'establish', 'a', 'rigorous', 'link', 'between', 'time', 'series', 'analysis', 'and', 'matrix', 'estimation', 'the', 'key', 'to', 'establishing', 'this', 'link', 'is', 'constructing', 'a', 'page', 'matrix', 'with', 'nonoverlapping', 'entries', 'rather', 'than', 'a', 'hankel', 'matrix', 'as', 'is', 'commonly', 'done', 'in', 'the', 'literature', 'eg', 'ssa', 'this', 'particular', 'matrix', 'structure', 'allows', 'us', 'to', 'provide', 'finite', 'sample', 'analysis', 'for', 'imputation', 'and', 'prediction', 'and', 'prove', 'the', 'asymptotic', 'consistency', 'of', 'our', 'method', 'another', 'salient', 'feature', 'of', 'our', 'algorithm', 'is', 'that', 'it', 'is', 'model', 'agnostic', 'with', 'respect', 'to', 'both', 'the', 'underlying', 'time', 'dynamics', 'and', 'the', 'noise', 'distribution', 'in', 'the', 'observations', 'the', 'noise', 'agnostic', 'property', 'of', 'our', 'approach', 'allows', 'us', 'to', 'recover', 'the', 'latent', 'states', 'when', 'only', 'given', 'access', 'to', 'noisy', 'and', 'partial', 'observations', 'a', 'la', 'a', 'hidden', 'markov', 'model', 'eg', 'recovering', 'the', 'timevarying', 'parameter', 'of', 'a', 'poisson', 'process', 'without', 'knowing', 'that', 'the', 'underlying', 'process', 'is', 'poisson', 'furthermore', 'since', 'our', 'forecasting', 'algorithm', 'requires', 'regression', 'with', 'noisy', 'features', 'our', 'approach', 'suggests', 'a', 'matrix', 'estimation', 'based', 'method', 'coupled', 'with', 'a', 'novel', 'nonstandard', 'matrix', 'estimation', 'error', 'metric', 'to', 'solve', 'the', 'errorinvariable', 'regression', 'problem', 'which', 'could', 'be', 'of', 'interest', 'in', 'its', 'own', 'right', 'through', 'synthetic', 'and', 'realworld', 'datasets', 'we', 'demonstrate', 'that', 'our', 'algorithm', 'outperforms', 'standard', 'software', 'packages', 'including', 'r', 'libraries', 'in', 'the', 'presence', 'of', 'missing', 'data', 'as', 'well', 'as', 'high', 'levels', 'of', 'noise']]
[-0.04499169500837713, -0.003376398334663024, -0.10087074334492328, 0.06518776654312236, -0.10432465901309303, -0.161394945925487, 0.055328994713209824, 0.3762074435354564, -0.2957967771779232, -0.3089015188267663, 0.1386211738199124, -0.2503737231982964, -0.17630823034761023, 0.1559996859901103, -0.06695945368565875, 0.08478912024318185, 0.09145448393597878, 0.024612594584649396, -0.07487246679977097, -0.23865674012059604, 0.28220934296861805, 0.08119553309576265, 0.29386093800180946, -0.027599159096656688, 0.1313707862695647, 0.03822502285234052, -0.09345127431523248, -0.015260407107015109, -0.03230146914369282, 0.12239121425222477, 0.28215354302705364, 0.15709723829500505, 0.2905256361933425, -0.3960181538174922, -0.21699036263122126, 0.12359402340210589, 0.1260516254089829, 0.10069732284619963, -0.006565138553911499, -0.2999799046440628, 0.08203758949028521, -0.1533934129608779, -0.07945691799696791, -0.116901455587579, -0.026118107316694384, -0.03792642687672171, -0.37092708312878225, 0.09697763990562666, 0.04194403728028631, 0.009708034290514629, -0.03351292668792604, -0.12730836130413709, 0.047091214247208475, 0.13680994994908266, 0.05861269066066096, 0.011949064894900496, 0.10061933032702655, -0.07738570737861225, -0.10274823574260969, 0.3454619749264535, -0.08356435425556466, -0.22207170948065047, 0.15599069786820047, -0.12202318690652991, -0.1659928273273118, 0.11504198919323369, 0.1830418907370868, 0.08820712481753837, -0.1455130221077807, 0.0767384190606114, -0.06113195920860844, 0.19128171645731118, -0.001224551889403113, -0.017604142382082626, 0.1312472680230336, 0.18324659753044875, 0.06067364111157327, 0.12747899863250747, -0.1035651471851201, -0.09336234939260536, -0.2627111145038286, -0.1392767623901881, -0.22557189463123936, -0.0010411352681393479, -0.14588067206987662, -0.203531346325602, 0.4214087337030676, 0.19867310763882665, 0.24534621300368473, 0.10169956459230262, 0.32276860361212284, 0.10738748187893712, 0.042118432895272395, 0.07952170217377616, 0.1291211722916442, 0.15263659853632722, 0.09068577521684347, -0.17332603027160953, 0.12480751180073953, 0.05873456200070936]
1,802.09065
Perceptual Quality Assessment of Immersive Images Considering Peripheral Vision Impact
Conventional images/videos are often rendered within the central vision area of the human visual system (HVS) with uniform quality. Recent virtual reality (VR) device with head mounted display (HMD) extends the field of view (FoV) significantly to include both central and peripheral vision areas. It exhibits the unequal image quality sensation among these areas because of the non-uniform distribution of photoreceptors on our retina. We propose to study the sensation impact on the image subjective quality with respect to the eccentric angle $\theta$ across different vision areas. Often times, image quality is controlled by the quantization stepsize $q$ and spatial resolution $s$, separately and jointly. Therefore, the sensation impact can be understood by exploring the $q$ and/or $s$ in terms of the $\theta$, resulting in self-adaptive analytical models that have shown quite impressive accuracy through independent cross validations. These models can further be applied to give different quality weights at different regions, so as to significantly reduce the transmission data size but without subjective quality loss. As demonstrated in a gigapixel imaging system, we have shown that the image rendering can be speed up about 10$\times$ with the model guided unequal quality scales, in comparison to the the legacy scheme with uniform quality scales everywhere.
cs.MM
conventional imagesvideos are often rendered within the central vision area of the human visual system hvs with uniform quality recent virtual reality vr device with head mounted display hmd extends the field of view fov significantly to include both central and peripheral vision areas it exhibits the unequal image quality sensation among these areas because of the nonuniform distribution of photoreceptors on our retina we propose to study the sensation impact on the image subjective quality with respect to the eccentric angle theta across different vision areas often times image quality is controlled by the quantization stepsize q and spatial resolution s separately and jointly therefore the sensation impact can be understood by exploring the q andor s in terms of the theta resulting in selfadaptive analytical models that have shown quite impressive accuracy through independent cross validations these models can further be applied to give different quality weights at different regions so as to significantly reduce the transmission data size but without subjective quality loss as demonstrated in a gigapixel imaging system we have shown that the image rendering can be speed up about 10times with the model guided unequal quality scales in comparison to the the legacy scheme with uniform quality scales everywhere
[['conventional', 'imagesvideos', 'are', 'often', 'rendered', 'within', 'the', 'central', 'vision', 'area', 'of', 'the', 'human', 'visual', 'system', 'hvs', 'with', 'uniform', 'quality', 'recent', 'virtual', 'reality', 'vr', 'device', 'with', 'head', 'mounted', 'display', 'hmd', 'extends', 'the', 'field', 'of', 'view', 'fov', 'significantly', 'to', 'include', 'both', 'central', 'and', 'peripheral', 'vision', 'areas', 'it', 'exhibits', 'the', 'unequal', 'image', 'quality', 'sensation', 'among', 'these', 'areas', 'because', 'of', 'the', 'nonuniform', 'distribution', 'of', 'photoreceptors', 'on', 'our', 'retina', 'we', 'propose', 'to', 'study', 'the', 'sensation', 'impact', 'on', 'the', 'image', 'subjective', 'quality', 'with', 'respect', 'to', 'the', 'eccentric', 'angle', 'theta', 'across', 'different', 'vision', 'areas', 'often', 'times', 'image', 'quality', 'is', 'controlled', 'by', 'the', 'quantization', 'stepsize', 'q', 'and', 'spatial', 'resolution', 's', 'separately', 'and', 'jointly', 'therefore', 'the', 'sensation', 'impact', 'can', 'be', 'understood', 'by', 'exploring', 'the', 'q', 'andor', 's', 'in', 'terms', 'of', 'the', 'theta', 'resulting', 'in', 'selfadaptive', 'analytical', 'models', 'that', 'have', 'shown', 'quite', 'impressive', 'accuracy', 'through', 'independent', 'cross', 'validations', 'these', 'models', 'can', 'further', 'be', 'applied', 'to', 'give', 'different', 'quality', 'weights', 'at', 'different', 'regions', 'so', 'as', 'to', 'significantly', 'reduce', 'the', 'transmission', 'data', 'size', 'but', 'without', 'subjective', 'quality', 'loss', 'as', 'demonstrated', 'in', 'a', 'gigapixel', 'imaging', 'system', 'we', 'have', 'shown', 'that', 'the', 'image', 'rendering', 'can', 'be', 'speed', 'up', 'about', '10times', 'with', 'the', 'model', 'guided', 'unequal', 'quality', 'scales', 'in', 'comparison', 'to', 'the', 'the', 'legacy', 'scheme', 'with', 'uniform', 'quality', 'scales', 'everywhere']]
[-0.08600954706723825, 0.07333852282339116, -0.07139891032356678, 0.01961119534425074, -0.061170577793949986, -0.14348340601683027, 0.007031293967511596, 0.4482708146295896, -0.24846088276159517, -0.3770052655682354, 0.07451962345029886, -0.23848756344125766, -0.12083347779357942, 0.20593233673078032, -0.17019168956655292, 0.062316312230612354, 0.08385436331353537, 0.04070901609275763, -0.045296313832286834, -0.26467343016709316, 0.25910824970115065, 0.07350935552541803, 0.3517764557698151, 0.03236133480932927, 0.0889778699434828, -0.010807945720976354, -0.030117700900882484, 0.05052423156888747, -0.06133399008377171, 0.12040989065610963, 0.2761737661997336, 0.1317043586210674, 0.269396116227911, -0.41525433961665487, -0.22089439248666168, 0.040923594540303074, 0.18443506079975788, 0.01842787259190184, -0.03646960473823838, -0.32310177534477924, 0.10409437892277067, -0.1485154050799859, -0.07139633088826952, -0.07547029155965258, 0.003982824169485489, 0.03327265867350123, -0.2624797465711287, 0.05829043375220286, -0.0006719892299393328, 0.09622761823418664, -0.031233449798168205, -0.11403192042872855, -0.012987818901722388, 0.1845358559225754, 0.07073813504312278, 0.08842180250098974, 0.17530110637180327, -0.19788017152785892, -0.06868723221577522, 0.3806510807083147, -0.008878946047639702, -0.2308123699060028, 0.21084887035440927, -0.15263072094403027, -0.05989560803693787, 0.1497027074418417, 0.2054347797245832, 0.07430844850037474, -0.11459263874808463, 0.024284054188159997, 0.010056116073051603, 0.21199364333822415, 0.1060327961041433, 0.056270694586153074, 0.21795749094609806, 0.15307716637872523, 0.03198573450989476, 0.1277152367907281, -0.1265555048321669, -0.05783512067254178, -0.20892300556198035, -0.09311280859770571, -0.13339802542837656, 0.015492391269426883, -0.13014231530201292, -0.12458932010326307, 0.37181747558407086, 0.19121809453794325, 0.21857903784981406, 0.046367137704652214, 0.35952772672129113, 0.07309154383099933, 0.12369454314977657, 0.03049113949669934, 0.22612762939548348, 0.010788346461315707, 0.1363838329939626, -0.18512246723218662, 0.08565357690052379, 0.012396677277936804]
1,802.09066
On asymptotic formulae in some sum-product questions
In this paper we obtain a series of asymptotic formulae in the sum--product phenomena over the prime field $\mathbf{F}_p$. In the proofs we use usual incidence theorems in $\mathbf{F}_p$, as well as the growth result in ${\rm SL}_2 (\mathbf{F}_p)$ due to Helfgott. Here some of our applications: $\bullet~$ a new bound for the number of the solutions to the equation $(a_1-a_2) (a_3-a_4) = (a'_1-a'_2) (a'_3-a'_4)$, $\,a_i, a'_i\in A$, $A$ is an arbitrary subset of $\mathbf{F}_p$, $\bullet~$ a new effective bound for multilinear exponential sums of Bourgain, $\bullet~$ an asymptotic analogue of the Balog--Wooley decomposition theorem, $\bullet~$ growth of $p_1(b) + 1/(a+p_2 (b))$, where $a,b$ runs over two subsets of $\mathbf{F}_p$, $p_1,p_2 \in \mathbf{F}_p [x]$ are two non--constant polynomials, $\bullet~$ new bounds for some exponential sums with multiplicative and additive characters.
math.NT math.CO
in this paper we obtain a series of asymptotic formulae in the sumproduct phenomena over the prime field mathbff_p in the proofs we use usual incidence theorems in mathbff_p as well as the growth result in rm sl_2 mathbff_p due to helfgott here some of our applications bullet a new bound for the number of the solutions to the equation a_1a_2 a_3a_4 a_1a_2 a_3a_4 a_i a_iin a a is an arbitrary subset of mathbff_p bullet a new effective bound for multilinear exponential sums of bourgain bullet an asymptotic analogue of the balogwooley decomposition theorem bullet growth of p_1b 1ap_2 b where ab runs over two subsets of mathbff_p p_1p_2 in mathbff_p x are two nonconstant polynomials bullet new bounds for some exponential sums with multiplicative and additive characters
[['in', 'this', 'paper', 'we', 'obtain', 'a', 'series', 'of', 'asymptotic', 'formulae', 'in', 'the', 'sumproduct', 'phenomena', 'over', 'the', 'prime', 'field', 'mathbff_p', 'in', 'the', 'proofs', 'we', 'use', 'usual', 'incidence', 'theorems', 'in', 'mathbff_p', 'as', 'well', 'as', 'the', 'growth', 'result', 'in', 'rm', 'sl_2', 'mathbff_p', 'due', 'to', 'helfgott', 'here', 'some', 'of', 'our', 'applications', 'bullet', 'a', 'new', 'bound', 'for', 'the', 'number', 'of', 'the', 'solutions', 'to', 'the', 'equation', 'a_1a_2', 'a_3a_4', 'a_1a_2', 'a_3a_4', 'a_i', 'a_iin', 'a', 'a', 'is', 'an', 'arbitrary', 'subset', 'of', 'mathbff_p', 'bullet', 'a', 'new', 'effective', 'bound', 'for', 'multilinear', 'exponential', 'sums', 'of', 'bourgain', 'bullet', 'an', 'asymptotic', 'analogue', 'of', 'the', 'balogwooley', 'decomposition', 'theorem', 'bullet', 'growth', 'of', 'p_1b', '1ap_2', 'b', 'where', 'ab', 'runs', 'over', 'two', 'subsets', 'of', 'mathbff_p', 'p_1p_2', 'in', 'mathbff_p', 'x', 'are', 'two', 'nonconstant', 'polynomials', 'bullet', 'new', 'bounds', 'for', 'some', 'exponential', 'sums', 'with', 'multiplicative', 'and', 'additive', 'characters']]
[-0.18728458702274126, 0.09793722216913704, -0.10449703436877046, 0.057049744980528005, -0.07020369487341553, -0.10660661801710607, 0.02074917898576204, 0.27901490383027566, -0.32329115868797376, -0.18883818274156916, 0.12836552490221542, -0.27552604763990357, -0.12070410893416948, 0.25436391308903694, -0.09017317866285642, 0.026770949151204336, -0.0069660697250612195, 0.07837259005348657, -0.02259492836449118, -0.302473354637475, 0.2916863097232722, -0.09265355895909053, 0.16594905904050739, 0.012295939508707278, 0.07153661040559647, 0.0349741682654158, 0.0030375056537903017, -0.04294497323118978, -0.2220429321972742, 0.10269213305963647, 0.2566321271338633, 0.12021702238255078, 0.2807622079900096, -0.3697154177426701, -0.09163497579062269, 0.16230995904669046, 0.18955610345472537, 0.03425450389835215, -0.032910062702343104, -0.23461582180526522, 0.10887237156312617, -0.1793699198742471, -0.1535135042846262, -0.02371251798837283, 0.08124527504153935, 0.1002632113079363, -0.34107485034369994, 0.0704575647802798, 0.1509551990875191, 0.07569386643387141, -0.06383108392372609, -0.18212577137756086, 0.07027368864325421, 0.026837879747507117, 0.019564095609230062, 0.05165886248753864, 0.01193923605162473, -0.11868999812877663, -0.1420731137225789, 0.3155366224606359, -0.08691379815406565, -0.1784352423504941, 0.10969129717716622, -0.17052120328067788, -0.18623012629160213, 0.08536277869568458, 0.11838506945290618, 0.13388013826786643, -0.048300959833247205, 0.19805358753803867, -0.14208101170758405, 0.0877760492915672, 0.17496010186224584, 0.06073178769281459, 0.06370543797189991, 0.05979684734022215, 0.08760272008958199, 0.128102132392722, 0.006265519105548423, 0.0049192816691680085, -0.34997660912100287, -0.2066622966658398, -0.16598755547717686, 0.148516022969806, -0.1890259677920045, -0.2220865348973016, 0.33292449237630956, 0.0391450500695981, 0.18659371000138067, 0.1314006450600804, 0.21374693859575522, 0.09738952139787938, 0.021169366731238183, 0.06699496344513065, 0.08696564026260083, 0.24364863940706802, -0.03509814939371565, -0.1326572979534311, 0.005449247546494007, 0.16061891921027194]
1,802.09067
Characterizations of some domains via Carath\'eodory extremals
In this paper we characterize the unit disc, the bidisc and the symmetrized bidisc \[ G =\{(z+w,zw):|z|<1,\ |w|<1\} \] in terms of the possession of small classes of analytic maps into the unit disc that suffice to solve all Carath\'eodory extremal problems in the domain.
math.CV
in this paper we characterize the unit disc the bidisc and the symmetrized bidisc g zwzwz1 w1 in terms of the possession of small classes of analytic maps into the unit disc that suffice to solve all caratheodory extremal problems in the domain
[['in', 'this', 'paper', 'we', 'characterize', 'the', 'unit', 'disc', 'the', 'bidisc', 'and', 'the', 'symmetrized', 'bidisc', 'g', 'zwzwz1', 'w1', 'in', 'terms', 'of', 'the', 'possession', 'of', 'small', 'classes', 'of', 'analytic', 'maps', 'into', 'the', 'unit', 'disc', 'that', 'suffice', 'to', 'solve', 'all', 'caratheodory', 'extremal', 'problems', 'in', 'the', 'domain']]
[-0.10344712990661, 0.007304895301024581, -0.0010811961580847586, 0.06245586751191335, -0.08829127023602988, -0.02587310159795506, 0.015389552440082784, 0.361642085968755, -0.30445112669190694, -0.18671850608878357, 0.12458314851933527, -0.2683989775562009, -0.11456682329434295, 0.17951463580911242, -0.14328953363867694, 0.06885424622356198, 0.04305737015661285, -0.03844239255196826, -0.07452382307044815, -0.31098053267842896, 0.3930364270196405, -0.09118563595206239, 0.11708480643844882, 0.06207452073346737, 0.08350733236604652, -0.0024179702971217245, -0.0016932328080022058, 0.02014632653011832, -0.23569917694620143, 0.14415155834150176, 0.2830285393567972, 0.14048677115419575, 0.27218220388343517, -0.4123240034420823, -0.14698185210744308, 0.2168016814908316, 0.1490469553756939, -0.07221641473818657, 0.06434798285874083, -0.17709729946110137, 0.07366092288650053, -0.10276932468594507, -0.12675421721800123, -0.0010749808144430782, 0.04582376594027115, 0.013856258449079685, -0.2184328458510166, 0.05070170736330193, 0.1610108216747988, -0.012371580268061438, -0.14721864053632977, -0.09635994563875504, -0.021743298075053583, 0.14573508128523827, -0.017732390917317813, 0.13828816856149323, 0.09619742778108217, -0.10441055455310054, -0.07344858143965952, 0.3701797637568657, -0.04369023017758547, -0.26768390415236354, 0.1095281213868496, -0.2685044143608836, -0.1350358532265175, 0.08349429766192686, 0.17293130827331266, 0.16149946371483248, -0.10299406124842028, 0.21518864566974646, -0.11383433150517386, 0.09564153822869885, 0.15055602041701244, 0.018775367286316184, 0.15680022524713083, 0.01691233312039701, 0.08722668841682905, 0.2477577646631141, -0.020984332965210427, -0.053386299037049674, -0.3503579423048122, -0.18351295230866865, -0.1990887348155686, 0.0476954264003177, -0.12592142440214874, -0.23257880707726228, 0.405160395287757, 0.06603145031908224, 0.21590376664819413, 0.07651429729492859, 0.24338389915782352, 0.06778300027254709, 0.09455488529733144, 0.1395571826913849, 0.15596778036723302, 0.1394250255164712, 0.039054007421052736, -0.19417209550738335, -0.0013211211514507616, 0.10675863516625277]
1,802.09068
Interplay of spin-dependent delocalization and magnetic anisotropy in the ground and excited states of [Gd$_2$@C$_{78}$]$^{-1}$ and [Gd$_2$@C$_{80}$]$^{-1}$
The magnetic properties and electronic structure of the ground and excited states of two recently characterized endohedral metallo-fullerenes, [Gd$_2$@C$_{78}$]$^{-}$ (1) and [Gd$_2$@C$_{80}$]$^{-}$ (2), have been studied by theoretical methods. The systems can be considered as [Gd$_2$]$^{5+}$ dimers encapsulated in a fullerene cage with the fifteen unpaired electrons ferromagnetically coupled into an $S=15/2$ high-spin configuration in the ground state. The microscopic mechanisms governing the Gd--Gd interactions leading to the ferromagnetic ground state are examined by a combination of density functional and ab initio calculations and the full energy spectrum of the ground and lowest excited states is constructed by means of ab initio model Hamiltonians. The ground state is characterized by strong electron delocalization bordering on a $\sigma$ type one-electron covalent bond and minor zero-field splitting (ZFS) which is successfully described as a second order spin-orbit coupling effect. We have shown that the observed ferromagnetic interaction originates from Hund's rule coupling and not from the conventional double exchange mechanism. The calculated ZFS parameters of 1 and 2 in their optimized geometries are in qualitative agreement with experimental EPR results. The higher excited states display less electron delocalization but at the same time they possess unquenched first-order angular momentum. This leads to strong spin-orbit coupling and highly anisotropic energy spectrum. The analysis of the excited states presented here constitutes the first detailed study of the effects of spin-dependent delocalization in the presence of first order orbital angular momentum and the obtained results can be applied to other mixed valence lanthanide systems.
physics.chem-ph
the magnetic properties and electronic structure of the ground and excited states of two recently characterized endohedral metallofullerenes gd_2c_78 1 and gd_2c_80 2 have been studied by theoretical methods the systems can be considered as gd_25 dimers encapsulated in a fullerene cage with the fifteen unpaired electrons ferromagnetically coupled into an s152 highspin configuration in the ground state the microscopic mechanisms governing the gdgd interactions leading to the ferromagnetic ground state are examined by a combination of density functional and ab initio calculations and the full energy spectrum of the ground and lowest excited states is constructed by means of ab initio model hamiltonians the ground state is characterized by strong electron delocalization bordering on a sigma type oneelectron covalent bond and minor zerofield splitting zfs which is successfully described as a second order spinorbit coupling effect we have shown that the observed ferromagnetic interaction originates from hunds rule coupling and not from the conventional double exchange mechanism the calculated zfs parameters of 1 and 2 in their optimized geometries are in qualitative agreement with experimental epr results the higher excited states display less electron delocalization but at the same time they possess unquenched firstorder angular momentum this leads to strong spinorbit coupling and highly anisotropic energy spectrum the analysis of the excited states presented here constitutes the first detailed study of the effects of spindependent delocalization in the presence of first order orbital angular momentum and the obtained results can be applied to other mixed valence lanthanide systems
[['the', 'magnetic', 'properties', 'and', 'electronic', 'structure', 'of', 'the', 'ground', 'and', 'excited', 'states', 'of', 'two', 'recently', 'characterized', 'endohedral', 'metallofullerenes', 'gd_2c_78', '1', 'and', 'gd_2c_80', '2', 'have', 'been', 'studied', 'by', 'theoretical', 'methods', 'the', 'systems', 'can', 'be', 'considered', 'as', 'gd_25', 'dimers', 'encapsulated', 'in', 'a', 'fullerene', 'cage', 'with', 'the', 'fifteen', 'unpaired', 'electrons', 'ferromagnetically', 'coupled', 'into', 'an', 's152', 'highspin', 'configuration', 'in', 'the', 'ground', 'state', 'the', 'microscopic', 'mechanisms', 'governing', 'the', 'gdgd', 'interactions', 'leading', 'to', 'the', 'ferromagnetic', 'ground', 'state', 'are', 'examined', 'by', 'a', 'combination', 'of', 'density', 'functional', 'and', 'ab', 'initio', 'calculations', 'and', 'the', 'full', 'energy', 'spectrum', 'of', 'the', 'ground', 'and', 'lowest', 'excited', 'states', 'is', 'constructed', 'by', 'means', 'of', 'ab', 'initio', 'model', 'hamiltonians', 'the', 'ground', 'state', 'is', 'characterized', 'by', 'strong', 'electron', 'delocalization', 'bordering', 'on', 'a', 'sigma', 'type', 'oneelectron', 'covalent', 'bond', 'and', 'minor', 'zerofield', 'splitting', 'zfs', 'which', 'is', 'successfully', 'described', 'as', 'a', 'second', 'order', 'spinorbit', 'coupling', 'effect', 'we', 'have', 'shown', 'that', 'the', 'observed', 'ferromagnetic', 'interaction', 'originates', 'from', 'hunds', 'rule', 'coupling', 'and', 'not', 'from', 'the', 'conventional', 'double', 'exchange', 'mechanism', 'the', 'calculated', 'zfs', 'parameters', 'of', '1', 'and', '2', 'in', 'their', 'optimized', 'geometries', 'are', 'in', 'qualitative', 'agreement', 'with', 'experimental', 'epr', 'results', 'the', 'higher', 'excited', 'states', 'display', 'less', 'electron', 'delocalization', 'but', 'at', 'the', 'same', 'time', 'they', 'possess', 'unquenched', 'firstorder', 'angular', 'momentum', 'this', 'leads', 'to', 'strong', 'spinorbit', 'coupling', 'and', 'highly', 'anisotropic', 'energy', 'spectrum', 'the', 'analysis', 'of', 'the', 'excited', 'states', 'presented', 'here', 'constitutes', 'the', 'first', 'detailed', 'study', 'of', 'the', 'effects', 'of', 'spindependent', 'delocalization', 'in', 'the', 'presence', 'of', 'first', 'order', 'orbital', 'angular', 'momentum', 'and', 'the', 'obtained', 'results', 'can', 'be', 'applied', 'to', 'other', 'mixed', 'valence', 'lanthanide', 'systems']]
[-0.14602990955035963, 0.20331615138548303, -0.024418150265083403, 0.07331497279109851, 0.010592168086797606, -0.12851844667552076, 0.04259697841812989, 0.3791658866238229, -0.23286096271797443, -0.3088056703155138, -0.013810659987300786, -0.31614707356356847, -0.07728709513226487, 0.11148140344730749, 0.11699073933087507, 0.01610891457114901, 0.04073376493595008, -0.004866865366621285, -0.08431015833594589, -0.16058204255009792, 0.305551254705583, 0.042351002708001406, 0.2712289980118524, 0.104343055629371, 0.031213307145944967, 0.008105998635244537, 0.09143810701765576, 0.024703014450033707, -0.12239948267949274, 0.10485180541682912, 0.2316922475092056, -0.04376898338633342, 0.21180936333020123, -0.46314926421916, -0.17562515213895513, 0.00048371659667820346, 0.1330502764264844, 0.16574979895602304, -0.03882513545995236, -0.31685156854515784, 0.014840917331071532, -0.1917332840836322, -0.13648124755816343, -0.14449960493615696, -0.006842548245259998, 0.017381207448221286, -0.25289239314959705, 0.11776883449994636, 0.051772490129521, 0.04639328866410045, -0.13160650832673573, -0.17217497554683717, -0.11603798569959341, 0.08812260063963809, 0.0349090358665289, 0.03538288831501743, 0.11002024866222423, -0.0902899887593349, -0.13926532648750867, 0.393306984661185, -0.04968606587024216, -0.139331370966547, 0.17347014034547065, -0.17061802728519757, -0.08727698800895287, 0.1780234868590701, 0.09075537722709835, 0.10974194693678457, -0.12729452928333373, 0.07577020417716548, 0.005625407631052848, 0.187256840300005, 0.019484325463180335, 0.08678042280594034, 0.20411665188148617, 0.14042784637790554, 0.0006357614673217949, 0.11314163850549114, -0.11237964194971231, -0.13347857571492086, -0.2134156440517732, -0.11493112905407134, -0.24915125564272914, 0.06230237515535139, -0.01946080920116605, -0.1348548006231906, 0.4157330332590001, 0.07398652481865518, 0.14865103357908677, -0.0807153012703306, 0.2369417783024968, 0.12656631525510884, 0.05653483809960284, 0.025031623994570453, 0.30906614398545756, 0.19505962722801737, 0.06355942677972572, -0.29719574555638245, 0.07358259246399512, 0.02090235909314028]
1,802.09069
Active Learning with Logged Data
We consider active learning with logged data, where labeled examples are drawn conditioned on a predetermined logging policy, and the goal is to learn a classifier on the entire population, not just conditioned on the logging policy. Prior work addresses this problem either when only logged data is available, or purely in a controlled random experimentation setting where the logged data is ignored. In this work, we combine both approaches to provide an algorithm that uses logged data to bootstrap and inform experimentation, thus achieving the best of both worlds. Our work is inspired by a connection between controlled random experimentation and active learning, and modifies existing disagreement-based active learning algorithms to exploit logged data.
cs.LG stat.ML
we consider active learning with logged data where labeled examples are drawn conditioned on a predetermined logging policy and the goal is to learn a classifier on the entire population not just conditioned on the logging policy prior work addresses this problem either when only logged data is available or purely in a controlled random experimentation setting where the logged data is ignored in this work we combine both approaches to provide an algorithm that uses logged data to bootstrap and inform experimentation thus achieving the best of both worlds our work is inspired by a connection between controlled random experimentation and active learning and modifies existing disagreementbased active learning algorithms to exploit logged data
[['we', 'consider', 'active', 'learning', 'with', 'logged', 'data', 'where', 'labeled', 'examples', 'are', 'drawn', 'conditioned', 'on', 'a', 'predetermined', 'logging', 'policy', 'and', 'the', 'goal', 'is', 'to', 'learn', 'a', 'classifier', 'on', 'the', 'entire', 'population', 'not', 'just', 'conditioned', 'on', 'the', 'logging', 'policy', 'prior', 'work', 'addresses', 'this', 'problem', 'either', 'when', 'only', 'logged', 'data', 'is', 'available', 'or', 'purely', 'in', 'a', 'controlled', 'random', 'experimentation', 'setting', 'where', 'the', 'logged', 'data', 'is', 'ignored', 'in', 'this', 'work', 'we', 'combine', 'both', 'approaches', 'to', 'provide', 'an', 'algorithm', 'that', 'uses', 'logged', 'data', 'to', 'bootstrap', 'and', 'inform', 'experimentation', 'thus', 'achieving', 'the', 'best', 'of', 'both', 'worlds', 'our', 'work', 'is', 'inspired', 'by', 'a', 'connection', 'between', 'controlled', 'random', 'experimentation', 'and', 'active', 'learning', 'and', 'modifies', 'existing', 'disagreementbased', 'active', 'learning', 'algorithms', 'to', 'exploit', 'logged', 'data']]
[-0.0333244905685601, 0.04788049640976723, -0.06450264931494451, 0.05126115626088627, -0.17590114430564902, -0.1992808637249729, 0.15785055065770512, 0.43573934429365657, -0.26518309845629595, -0.320924223003828, 0.11551614167857105, -0.2965977743146536, -0.1397521202371496, 0.21077544409718424, -0.1458984255871695, 0.0457919835396435, 0.10148164982219106, 0.05540663469405643, -0.01232671722891214, -0.31072128719812175, 0.31600691683833365, 0.06273492094453262, 0.31712162139137157, -0.03613610871784065, 0.11839314535685369, 0.0410760838781362, -0.10305520856510038, -0.003286120668053627, -0.07790715567566424, 0.15293528204277643, 0.32903881967067716, 0.24905015617690007, 0.3655031391783901, -0.4258689613531991, -0.189439599847664, 0.13196987756730422, 0.13729800651275106, 0.09304343588326289, -0.06120137824049301, -0.3261555676550969, 0.07542561496526974, -0.13060561664523962, 0.005509412041662828, -0.09306996458250544, -0.06544993236479375, -0.027788413461783658, -0.3408081427823914, -0.028449753299355507, 0.07377116635603749, 0.08237021865890078, -0.04629525897781486, -0.06152879802267189, 0.03189579374966738, 0.18769744567132718, 0.05144493938929847, 0.055670740613308935, 0.19892670092851167, -0.0963515776735933, -0.1736794918289651, 0.3203729669280026, -0.006587738968917857, -0.18650879229661887, 0.19169015387154142, -0.03593796858887958, -0.13553706596645973, 0.08151985407685457, 0.26836013748998877, 0.13439431253253767, -0.17884523759092427, 0.0610227991361171, -0.0700971971306464, 0.19238257956812563, -0.01161869543645045, -0.07267419578426558, 0.12655274652794976, 0.239226855367989, 0.04870950113981962, 0.1096343920039742, -0.049698268280000145, -0.12045088461195322, -0.23911680710380492, -0.06208827574939831, -0.26605679534537635, -0.00918372078867042, -0.05851783766968014, -0.13944285216743796, 0.3265631595707458, 0.22432074013125639, 0.24934404186256554, 0.10473533512052635, 0.3581736598001874, -0.0012294647111759885, 0.06677361237614052, 0.15655908342653319, 0.18244778576468967, -0.005212501855567098, 0.1423978881303059, -0.15227750251069666, 0.1534081768831643, -0.01097426583342578]
1,802.0907
Attention-Aware Generative Adversarial Networks (ATA-GANs)
In this work, we present a novel approach for training Generative Adversarial Networks (GANs). Using the attention maps produced by a Teacher- Network we are able to improve the quality of the generated images as well as perform weakly object localization on the generated images. To this end, we generate images of HEp-2 cells captured with Indirect Imunofluoresence (IIF) and study the ability of our network to perform a weakly localization of the cell. Firstly, we demonstrate that whilst GANs can learn the mapping between the input domain and the target distribution efficiently, the discriminator network is not able to detect the regions of interest. Secondly, we present a novel attention transfer mechanism which allows us to enforce the discriminator to put emphasis on the regions of interest via transfer learning. Thirdly, we show that this leads to more realistic images, as the discriminator learns to put emphasis on the area of interest. Fourthly, the proposed method allows one to generate both images as well as attention maps which can be useful for data annotation e.g in object detection.
cs.CV
in this work we present a novel approach for training generative adversarial networks gans using the attention maps produced by a teacher network we are able to improve the quality of the generated images as well as perform weakly object localization on the generated images to this end we generate images of hep2 cells captured with indirect imunofluoresence iif and study the ability of our network to perform a weakly localization of the cell firstly we demonstrate that whilst gans can learn the mapping between the input domain and the target distribution efficiently the discriminator network is not able to detect the regions of interest secondly we present a novel attention transfer mechanism which allows us to enforce the discriminator to put emphasis on the regions of interest via transfer learning thirdly we show that this leads to more realistic images as the discriminator learns to put emphasis on the area of interest fourthly the proposed method allows one to generate both images as well as attention maps which can be useful for data annotation eg in object detection
[['in', 'this', 'work', 'we', 'present', 'a', 'novel', 'approach', 'for', 'training', 'generative', 'adversarial', 'networks', 'gans', 'using', 'the', 'attention', 'maps', 'produced', 'by', 'a', 'teacher', 'network', 'we', 'are', 'able', 'to', 'improve', 'the', 'quality', 'of', 'the', 'generated', 'images', 'as', 'well', 'as', 'perform', 'weakly', 'object', 'localization', 'on', 'the', 'generated', 'images', 'to', 'this', 'end', 'we', 'generate', 'images', 'of', 'hep2', 'cells', 'captured', 'with', 'indirect', 'imunofluoresence', 'iif', 'and', 'study', 'the', 'ability', 'of', 'our', 'network', 'to', 'perform', 'a', 'weakly', 'localization', 'of', 'the', 'cell', 'firstly', 'we', 'demonstrate', 'that', 'whilst', 'gans', 'can', 'learn', 'the', 'mapping', 'between', 'the', 'input', 'domain', 'and', 'the', 'target', 'distribution', 'efficiently', 'the', 'discriminator', 'network', 'is', 'not', 'able', 'to', 'detect', 'the', 'regions', 'of', 'interest', 'secondly', 'we', 'present', 'a', 'novel', 'attention', 'transfer', 'mechanism', 'which', 'allows', 'us', 'to', 'enforce', 'the', 'discriminator', 'to', 'put', 'emphasis', 'on', 'the', 'regions', 'of', 'interest', 'via', 'transfer', 'learning', 'thirdly', 'we', 'show', 'that', 'this', 'leads', 'to', 'more', 'realistic', 'images', 'as', 'the', 'discriminator', 'learns', 'to', 'put', 'emphasis', 'on', 'the', 'area', 'of', 'interest', 'fourthly', 'the', 'proposed', 'method', 'allows', 'one', 'to', 'generate', 'both', 'images', 'as', 'well', 'as', 'attention', 'maps', 'which', 'can', 'be', 'useful', 'for', 'data', 'annotation', 'eg', 'in', 'object', 'detection']]
[-0.0019441491623704709, 0.006643333580878595, -0.0664014884773014, 0.09392502628988848, -0.12008470840218445, -0.1516265666891894, 0.036663776871177965, 0.459563176576676, -0.25845323341998033, -0.3316422211571356, 0.060065661189460266, -0.23937201127164678, -0.20355936990569481, 0.18165891038337617, -0.14150468970837302, 0.052960799470690365, 0.09102804755420539, 0.05304817345615979, -0.01964064221305961, -0.2316011656768976, 0.33752725610321155, 0.058474934063433265, 0.3305860698599829, 0.01396122987099578, 0.13898302048374114, -0.028085426191977236, -0.022600591331824994, -0.002672960591277505, -0.06400979469372339, 0.21952326821158064, 0.2812641878034187, 0.18862425481764536, 0.2912863192117114, -0.43997958351680067, -0.25083714407826824, 0.10897503708151765, 0.12570839237022471, 0.11918934955120379, -0.08729897734875532, -0.35718684727221395, 0.10273298286320118, -0.1684931279500172, 0.01897927221653753, -0.15167335409597818, -0.05589801814404494, -0.010736887322953284, -0.32386607395516437, -0.02240252173558045, 0.08659317177259938, -0.009228960613542225, -0.03524657677835523, -0.019351771700436646, -0.028937938480554252, 0.22825566082512647, 0.02702330974283173, 0.06262566954331744, 0.13060698659797565, -0.18487156704499835, -0.08017407339772607, 0.3669258789734894, -0.05714429373162265, -0.23217956525577085, 0.22173470493636271, -0.08623967911744637, -0.11217102686105443, 0.09376515119285532, 0.25774077750909863, 0.14860537410007393, -0.13530884880972815, -0.013672576971964261, -0.04347567156276383, 0.16808722410978896, 0.028739538627122058, 0.0007577543460837241, 0.19913054887582077, 0.21977522286973641, 0.04179210365577234, 0.21819391933445076, -0.19438273641359313, -0.035534865285657094, -0.2322308741813379, -0.10350943310186267, -0.20595514954308444, 0.006420949591128182, -0.022153663543004572, -0.13126991325153856, 0.440076697889841, 0.2512276894674542, 0.286130734752037, 0.0871870246234486, 0.3088376541423161, 0.028382692036082905, 0.12428407707602163, 0.018735374099041305, 0.20337441832538736, 0.06074983626996491, 0.1127351737879426, -0.159610922481038, 0.08029709697120269, 0.059511507576164066]
1,802.09071
Robust Control for Renewable-Integrated Power Networks Considering Input Bound Constraints and Worst-Case Uncertainty Measure
Uncertainty from renewable energy and loads is one of the major challenges for stable grid operation. Various approaches have been explored to remedy these uncertainties. In this paper, we design centralized or decentralized state-feedback controllers for generators while considering worst-case uncertainty. Specifically, this paper introduces the notion of $\mathcal{L}_{\infty}$ robust control and stability for uncertain power networks. Uncertain and nonlinear differential algebraic equation model of the network is presented. The model includes unknown disturbances from renewables and loads. Given an operating point, the linearized state-space presentation is given. Then, the notion of $\mathcal{L}_{\infty}$ robust control and stability is discussed, resulting in a nonconvex optimization routine that yields a state feedback gain mitigating the impact of disturbances. The developed routine includes explicit input-bound constraints on generators' inputs and a measure of the worst-case disturbance. The feedback control architecture can be centralized, distributed, or decentralized. Algorithms based on successive convex approximations are then given to address the nonconvexity. Case studies are presented showcasing the performance of the $\mathcal{L}_{\infty}$ controllers in comparison with automatic generation control and $\mathcal{H}_{\infty}$ control methods.
cs.SY
uncertainty from renewable energy and loads is one of the major challenges for stable grid operation various approaches have been explored to remedy these uncertainties in this paper we design centralized or decentralized statefeedback controllers for generators while considering worstcase uncertainty specifically this paper introduces the notion of mathcall_infty robust control and stability for uncertain power networks uncertain and nonlinear differential algebraic equation model of the network is presented the model includes unknown disturbances from renewables and loads given an operating point the linearized statespace presentation is given then the notion of mathcall_infty robust control and stability is discussed resulting in a nonconvex optimization routine that yields a state feedback gain mitigating the impact of disturbances the developed routine includes explicit inputbound constraints on generators inputs and a measure of the worstcase disturbance the feedback control architecture can be centralized distributed or decentralized algorithms based on successive convex approximations are then given to address the nonconvexity case studies are presented showcasing the performance of the mathcall_infty controllers in comparison with automatic generation control and mathcalh_infty control methods
[['uncertainty', 'from', 'renewable', 'energy', 'and', 'loads', 'is', 'one', 'of', 'the', 'major', 'challenges', 'for', 'stable', 'grid', 'operation', 'various', 'approaches', 'have', 'been', 'explored', 'to', 'remedy', 'these', 'uncertainties', 'in', 'this', 'paper', 'we', 'design', 'centralized', 'or', 'decentralized', 'statefeedback', 'controllers', 'for', 'generators', 'while', 'considering', 'worstcase', 'uncertainty', 'specifically', 'this', 'paper', 'introduces', 'the', 'notion', 'of', 'mathcall_infty', 'robust', 'control', 'and', 'stability', 'for', 'uncertain', 'power', 'networks', 'uncertain', 'and', 'nonlinear', 'differential', 'algebraic', 'equation', 'model', 'of', 'the', 'network', 'is', 'presented', 'the', 'model', 'includes', 'unknown', 'disturbances', 'from', 'renewables', 'and', 'loads', 'given', 'an', 'operating', 'point', 'the', 'linearized', 'statespace', 'presentation', 'is', 'given', 'then', 'the', 'notion', 'of', 'mathcall_infty', 'robust', 'control', 'and', 'stability', 'is', 'discussed', 'resulting', 'in', 'a', 'nonconvex', 'optimization', 'routine', 'that', 'yields', 'a', 'state', 'feedback', 'gain', 'mitigating', 'the', 'impact', 'of', 'disturbances', 'the', 'developed', 'routine', 'includes', 'explicit', 'inputbound', 'constraints', 'on', 'generators', 'inputs', 'and', 'a', 'measure', 'of', 'the', 'worstcase', 'disturbance', 'the', 'feedback', 'control', 'architecture', 'can', 'be', 'centralized', 'distributed', 'or', 'decentralized', 'algorithms', 'based', 'on', 'successive', 'convex', 'approximations', 'are', 'then', 'given', 'to', 'address', 'the', 'nonconvexity', 'case', 'studies', 'are', 'presented', 'showcasing', 'the', 'performance', 'of', 'the', 'mathcall_infty', 'controllers', 'in', 'comparison', 'with', 'automatic', 'generation', 'control', 'and', 'mathcalh_infty', 'control', 'methods']]
[-0.17401859036710282, 0.014516303858892405, -0.026107679891124877, 0.04450322001569227, -0.09086767267118293, -0.1826282322898888, 0.04644370784014675, 0.38645516793158924, -0.31244186035738414, -0.29413002608767286, 0.16644172360181322, -0.23212401762562382, -0.13665062115548857, 0.1980647287369224, -0.18575869474708187, 0.1607471126137005, 0.0532242642022373, -0.0186891674450387, -0.05529362275873692, -0.2217151496376821, 0.3060714245584677, 0.08617138449335471, 0.29200899300667515, -0.016130272516007113, 0.14826017258350144, -0.029302753047390565, -0.05026393653613261, 0.02331719671002991, -0.09040113090176502, 0.1290931937454099, 0.29858109207469335, 0.16236963506459937, 0.34535454004071653, -0.4225887446823022, -0.20110980244035917, 0.11658558266241346, 0.09834397548349277, 0.0760625411309196, -0.06392209362820722, -0.2610210255198498, 0.08889627812062496, -0.20360750602082012, -0.07523826502835039, -0.07297612787872575, -0.04066610751694746, 0.061072882221796215, -0.34100205018396745, 0.026207312732863516, 0.05847518291028047, 0.05514192547971933, -0.09849825485104123, -0.10686500320166074, -0.017250581812483935, 0.11494782044478184, 0.008607293301875788, -0.03852298170518638, 0.15580466534480697, -0.0827909689608284, -0.16057164333721052, 0.3671389815069481, 0.05189028115075251, -0.23889294999058952, 0.1167197056122611, -0.021240090041167357, -0.14244373333217067, 0.1177853713108396, 0.27328730895533226, 0.09220805117564107, -0.19966401160292496, 0.08130992317092023, 0.02936405422621068, 0.16698394221632704, 0.0008731944557935508, 0.04047866769674742, 0.11480605781120672, 0.22954272555150304, 0.1722185167005095, 0.14856788269654234, -0.01478898678959178, -0.15321676641575654, -0.28261446792748757, -0.05857981869220649, -0.11097234137758444, -0.013957471221643076, -0.07746783998969807, -0.1443847464715046, 0.39529726035173307, 0.1690276566236083, 0.10875263310630214, 0.10519863311227792, 0.4092082750708373, 0.16019142251488203, 0.0054289487525238656, 0.11971181985096667, 0.2290770105861487, 0.09874460622416915, 0.1051703516674355, -0.2409181663930543, 0.11923024782365908, 0.036557627380137674]
1,802.09072
Hardy, weighted Trudinger-Moser and Caffarelli-Kohn-Nirenberg type inequalities on Riemannian manifolds with negative curvature
In this paper we obtain Hardy, weighted Trudinger-Moser and Caffarelli-Kohn-Nirenberg type inequalities with sharp constants on Riemannian manifolds with non-positive sectional curvature and, in particular, a variety of new estimates on hyperbolic spaces. Moreover, in some cases we also show their equivalence with Trudinger-Moser inequalities. As consequences, the relations between the constants of these inequalities are investigated yielding asymptotically best constants in the obtained inequalities. We also obtain the corresponding uncertainty type principles.
math.FA math.AP
in this paper we obtain hardy weighted trudingermoser and caffarellikohnnirenberg type inequalities with sharp constants on riemannian manifolds with nonpositive sectional curvature and in particular a variety of new estimates on hyperbolic spaces moreover in some cases we also show their equivalence with trudingermoser inequalities as consequences the relations between the constants of these inequalities are investigated yielding asymptotically best constants in the obtained inequalities we also obtain the corresponding uncertainty type principles
[['in', 'this', 'paper', 'we', 'obtain', 'hardy', 'weighted', 'trudingermoser', 'and', 'caffarellikohnnirenberg', 'type', 'inequalities', 'with', 'sharp', 'constants', 'on', 'riemannian', 'manifolds', 'with', 'nonpositive', 'sectional', 'curvature', 'and', 'in', 'particular', 'a', 'variety', 'of', 'new', 'estimates', 'on', 'hyperbolic', 'spaces', 'moreover', 'in', 'some', 'cases', 'we', 'also', 'show', 'their', 'equivalence', 'with', 'trudingermoser', 'inequalities', 'as', 'consequences', 'the', 'relations', 'between', 'the', 'constants', 'of', 'these', 'inequalities', 'are', 'investigated', 'yielding', 'asymptotically', 'best', 'constants', 'in', 'the', 'obtained', 'inequalities', 'we', 'also', 'obtain', 'the', 'corresponding', 'uncertainty', 'type', 'principles']]
[-0.0992384782118391, 0.06316820170239175, -0.029450101777911186, 0.14691348694590214, -0.09399141965127766, -0.1656991230285637, 0.04112076675615031, 0.3711822561613501, -0.27463086059218117, -0.25312993279977203, 0.15617674101807483, -0.3014407159939204, -0.1808292695053228, 0.27766548337618985, -0.1287274082153015, 0.06260279190968977, 0.04393623634688046, 0.05181657299654533, -0.1739925278274164, -0.27299474859737777, 0.4370950438681837, -0.07300735366441412, 0.21250304027958072, 0.13221584433970385, 0.05743878718771755, -0.05232556076235559, 0.0012590728751192355, 0.02602771587834007, -0.34240148444851376, 0.23141815128404494, 0.23024796398535166, 0.06276816494558772, 0.24504939138200388, -0.37430880560654484, -0.17546089126230918, 0.17885922916131478, 0.09203793654977407, 0.018866617717359164, -0.05988964336694614, -0.3407938163663733, 0.010089461844771693, -0.03430359685563878, -0.19067075756722934, -0.12923074630726997, -0.030194765365082924, 0.08604205209659795, -0.2693601063618513, 0.1327731056411572, 0.0924630362336358, 0.054267177562395186, -0.17369150853243798, -0.14664786838135388, 0.04378287585401167, 0.06770038114835138, 0.06702819974353053, -0.051619414685051636, 0.021535223751800926, -0.029428197354818247, -0.14702841052657936, 0.2847409870041764, -0.09397785301792295, -0.29292036398722193, 0.09123997581637885, -0.16626597812067564, -0.20525506116475348, -0.014762229136229581, 0.14952068592179313, 0.16334306032792345, -0.12082798591470473, 0.14029381448269043, -0.04580449145159697, 0.07486347241760934, 0.13497157001306545, 0.12270769234491538, -0.014570168685168028, 0.027921878684898965, 0.1487866273861098, 0.13850694446990344, 0.017877307293293933, -0.0877188994152127, -0.406959756647479, -0.21192568418097824, -0.13747798802079123, 0.12807869476470332, -0.24128443211889572, -0.1582690493254731, 0.28858001451071813, -0.014286849328814305, 0.18506237518756766, 0.17228550342715357, 0.13466763236138918, 0.0790540774421422, 0.0284132058126214, 0.07326798300475698, 0.30754306538178816, 0.23814194800000485, 0.10605102160639346, -0.09524149312446378, 0.03302459810439446, 0.20520719490970854]
1,802.09073
Noether's stars in $f(\cal {R})$ gravity
The Noether Symmetry Approach can be used to construct spherically symmetric solutions in $f({\cal R})$ gravity. Specifically, the Noether conserved quantity is related to the gravitational mass and a gravitational radius that reduces to the Schwarzschild radius in the limit $f({\cal R})\rightarrow {\cal R}$. We show that it is possible to construct the $M-R$ relation for neutron stars depending on the Noether conserved quantity and the associated gravitational radius. This approach enables the recovery of extreme massive stars that could not be stable in the standard Tolman-Oppenheimer-Volkoff based on General Relativity. Examples are given for some power law $f({\cal R})$ gravity models.
gr-qc
the noether symmetry approach can be used to construct spherically symmetric solutions in fcal r gravity specifically the noether conserved quantity is related to the gravitational mass and a gravitational radius that reduces to the schwarzschild radius in the limit fcal rrightarrow cal r we show that it is possible to construct the mr relation for neutron stars depending on the noether conserved quantity and the associated gravitational radius this approach enables the recovery of extreme massive stars that could not be stable in the standard tolmanoppenheimervolkoff based on general relativity examples are given for some power law fcal r gravity models
[['the', 'noether', 'symmetry', 'approach', 'can', 'be', 'used', 'to', 'construct', 'spherically', 'symmetric', 'solutions', 'in', 'fcal', 'r', 'gravity', 'specifically', 'the', 'noether', 'conserved', 'quantity', 'is', 'related', 'to', 'the', 'gravitational', 'mass', 'and', 'a', 'gravitational', 'radius', 'that', 'reduces', 'to', 'the', 'schwarzschild', 'radius', 'in', 'the', 'limit', 'fcal', 'rrightarrow', 'cal', 'r', 'we', 'show', 'that', 'it', 'is', 'possible', 'to', 'construct', 'the', 'mr', 'relation', 'for', 'neutron', 'stars', 'depending', 'on', 'the', 'noether', 'conserved', 'quantity', 'and', 'the', 'associated', 'gravitational', 'radius', 'this', 'approach', 'enables', 'the', 'recovery', 'of', 'extreme', 'massive', 'stars', 'that', 'could', 'not', 'be', 'stable', 'in', 'the', 'standard', 'tolmanoppenheimervolkoff', 'based', 'on', 'general', 'relativity', 'examples', 'are', 'given', 'for', 'some', 'power', 'law', 'fcal', 'r', 'gravity', 'models']]
[-0.13899741882421807, 0.10032105824782275, -0.09507064498029649, 0.11617838402904168, -0.14251372162435277, -0.14323882487894712, -0.0571814709087359, 0.28348658647954317, -0.19209136938055357, -0.2708184106969366, 0.06616335786883627, -0.28191415437579376, -0.10818536386496443, 0.16561226013536548, -0.10846693627079766, 0.037287408595576006, -0.01110063885525782, 0.10079336137163873, -0.12461253921512752, -0.22321941655051583, 0.3478849903844735, 0.07724497377799422, 0.2087502690470394, -0.00801428230753278, 0.05993611446819177, -0.06415626414430638, 0.0033874214152056796, 0.07590655710630338, -0.20645552292783168, 0.03713920323963405, 0.20074230108077565, 0.18419517070858502, 0.17023018405170126, -0.3607718651548174, -0.19273353569830456, 0.12762968860310958, 0.12375244819193933, 0.12802750579830185, -0.049469826790942424, -0.2559761258718722, 0.13427395480411017, -0.24464764803940175, -0.18064700936505973, -0.07968552982178974, 0.11328011551214491, -0.020326754397840475, -0.2964914957399243, 0.14950841133181444, 0.03429324231019207, -0.06440811113947455, -0.09273755252384124, -0.06561982500430781, -0.05660770024063394, 0.021544686066644156, 0.1105136662292495, 0.0708908749534292, 0.17743231738374257, -0.08085254177807227, -0.03708229003149979, 0.4162081496096125, -0.09425876533393474, -0.2608949311314991, 0.12806660920500243, -0.1832412261442811, -0.14683466732921993, 0.04096331615594453, 0.11595483775725406, 0.21910008572776146, -0.17702796464493753, 0.16736252487102962, -0.0063346039889581205, 0.15245094325954972, 0.11588732237635437, 0.015561983403042141, 0.33173497008871944, 0.06540320054901873, 0.059416987074940815, 0.07744528585816642, -0.059612367115572426, -0.08396556737488044, -0.376296355320579, -0.14206122592155473, -0.1744829849568287, 0.10035932561004302, -0.16939552660601204, -0.12378732652366892, 0.3271380897574857, 0.15205261758163424, 0.07518585594644879, 0.08157235035197992, 0.22655576378034026, 0.1437877546299669, 0.0959903076747615, 0.11077808853531, 0.3154219654083421, 0.17632851789833284, 0.0815231482470956, -0.24712823928269906, -0.07211456203595827, 0.10937073691656776]
1,802.09074
Large arboreal Galois representations
Given a field $K$, a polynomial $f \in K[x]$, and a suitable element $t \in K$, the set of preimages of $t$ under the iterates $f^{\circ n}$ carries a natural structure of a $d$-ary tree. We study conditions under which the absolute Galois group of $K$ acts on the tree by the full group of automorphisms. When $K=\mathbb{Q}$ we exhibit examples of polynomials of every even degree with maximal Galois action on the preimage tree, partially affirming a conjecture of Odoni. We also study the case of $K=F(t)$ and $f \in F[x]$ in which the corresponding Galois groups are the monodromy groups of the ramified covers $f^{\circ n}: \mathbb{P}^1_F \to \mathbb{P}^1_F$.
math.NT
given a field k a polynomial f in kx and a suitable element t in k the set of preimages of t under the iterates fcirc n carries a natural structure of a dary tree we study conditions under which the absolute galois group of k acts on the tree by the full group of automorphisms when kmathbbq we exhibit examples of polynomials of every even degree with maximal galois action on the preimage tree partially affirming a conjecture of odoni we also study the case of kft and f in fx in which the corresponding galois groups are the monodromy groups of the ramified covers fcirc n mathbbp1_f to mathbbp1_f
[['given', 'a', 'field', 'k', 'a', 'polynomial', 'f', 'in', 'kx', 'and', 'a', 'suitable', 'element', 't', 'in', 'k', 'the', 'set', 'of', 'preimages', 'of', 't', 'under', 'the', 'iterates', 'fcirc', 'n', 'carries', 'a', 'natural', 'structure', 'of', 'a', 'dary', 'tree', 'we', 'study', 'conditions', 'under', 'which', 'the', 'absolute', 'galois', 'group', 'of', 'k', 'acts', 'on', 'the', 'tree', 'by', 'the', 'full', 'group', 'of', 'automorphisms', 'when', 'kmathbbq', 'we', 'exhibit', 'examples', 'of', 'polynomials', 'of', 'every', 'even', 'degree', 'with', 'maximal', 'galois', 'action', 'on', 'the', 'preimage', 'tree', 'partially', 'affirming', 'a', 'conjecture', 'of', 'odoni', 'we', 'also', 'study', 'the', 'case', 'of', 'kft', 'and', 'f', 'in', 'fx', 'in', 'which', 'the', 'corresponding', 'galois', 'groups', 'are', 'the', 'monodromy', 'groups', 'of', 'the', 'ramified', 'covers', 'fcirc', 'n', 'mathbbp1_f', 'to', 'mathbbp1_f']]
[-0.26313365842941977, 0.11746005579261024, -0.1086677471773887, -0.002714963480317538, -0.06047226161559309, -0.09568765268174059, 0.06501567317172885, 0.3233752729576252, -0.35824639640680145, -0.21721021375200206, 0.0704911239744258, -0.25789036693846074, -0.12040040911487175, 0.18004833948755755, -0.08499648285294892, -0.007109313769641956, 0.010621224072924174, 0.20035717877721704, -0.07004900965967788, -0.32422344204371606, 0.35012246360745997, -0.04131139472656704, 0.16129367000534447, 0.009978921510441519, 0.1416616733570438, 0.01493651858197713, 0.011833062711590474, -0.011909236371038703, -0.140046593912561, 0.05116595248179083, 0.2890885850722226, 0.09701603154626189, 0.23737174864012509, -0.3232696660986029, -0.1224334153684215, 0.25329946362575806, 0.08927460581730676, -0.024288603038433085, -0.00711628682313299, -0.2420161667027844, 0.14459813000856464, -0.0912315388918489, -0.1425805241809389, -0.019998082352819246, 0.0903302429622005, 0.012600701545800912, -0.28573813370414025, -0.022103259564482034, 0.11738119345295046, 0.18950386158267565, -0.008093562229203249, -0.15953198337602778, -0.07072421176777725, 0.08378370124510268, -0.0270744069658835, 0.0742919946755838, 0.08883381224346322, -0.12946270362670542, -0.06258785531326376, 0.3883159652591572, -0.12788579798807656, -0.16041715637943066, 0.10662757432613727, -0.21412385308499868, -0.1992728969535081, 0.15199576754447655, 0.1130943484091704, 0.20038475926299024, -0.018413968605481713, 0.2632322074031594, -0.18927360960889025, 0.10615492814622067, 0.11729010243669426, -0.03670962206985152, 0.10132067796663133, 0.07548275427388694, 0.13012767356282118, 0.15484434849830395, 0.01971162425422477, 0.021740289913370795, -0.3592683925900027, -0.1726875419241436, -0.0959764364508724, 0.1045364450060959, -0.12754206266654697, -0.1768744274965325, 0.41808012980591813, 0.0831901576164939, 0.18803023778055922, 0.12690299962339666, 0.1630061329726916, 0.0679758173775904, 0.05886344545854068, 0.0862703969992629, 0.025648519430958895, 0.22780781596634161, -0.07566734694730524, -0.19891053138176884, 0.01331602879468813, 0.17158623037586382]
1,802.09075
Experimental observation of the Aubry transition in two-dimensional colloidal monolayers
The possibility to achieve entirely frictionless, i.e. superlubric, sliding between solids, holds enormous potential for the operation of mechanical devices. At small length scales, where mechanical contacts are well-defined, Aubry predicted a transition from a superlubric to a pinned state when the mechanical load is increased. Evidence for this intriguing Aubry transition (AT), which should occur in one dimension (1D) and at zero temperature, was recently obtained in few-atom chains. Here, we experimentally and theoretically demonstrate the occurrence of the AT in an extended two-dimensional (2D) system at room temperature using a colloidal monolayer on an optical lattice. Unlike the continuous nature of the AT in 1D, we observe a first-order transition in 2D leading to a coexistence regime of pinned and unpinned areas. Our data demonstrate that the original concept of Aubry does not only survive in 2D but is relevant for the design of nanoscopic machines and devices at ambient temperature.
cond-mat.soft cond-mat.other
the possibility to achieve entirely frictionless ie superlubric sliding between solids holds enormous potential for the operation of mechanical devices at small length scales where mechanical contacts are welldefined aubry predicted a transition from a superlubric to a pinned state when the mechanical load is increased evidence for this intriguing aubry transition at which should occur in one dimension 1d and at zero temperature was recently obtained in fewatom chains here we experimentally and theoretically demonstrate the occurrence of the at in an extended twodimensional 2d system at room temperature using a colloidal monolayer on an optical lattice unlike the continuous nature of the at in 1d we observe a firstorder transition in 2d leading to a coexistence regime of pinned and unpinned areas our data demonstrate that the original concept of aubry does not only survive in 2d but is relevant for the design of nanoscopic machines and devices at ambient temperature
[['the', 'possibility', 'to', 'achieve', 'entirely', 'frictionless', 'ie', 'superlubric', 'sliding', 'between', 'solids', 'holds', 'enormous', 'potential', 'for', 'the', 'operation', 'of', 'mechanical', 'devices', 'at', 'small', 'length', 'scales', 'where', 'mechanical', 'contacts', 'are', 'welldefined', 'aubry', 'predicted', 'a', 'transition', 'from', 'a', 'superlubric', 'to', 'a', 'pinned', 'state', 'when', 'the', 'mechanical', 'load', 'is', 'increased', 'evidence', 'for', 'this', 'intriguing', 'aubry', 'transition', 'at', 'which', 'should', 'occur', 'in', 'one', 'dimension', '1d', 'and', 'at', 'zero', 'temperature', 'was', 'recently', 'obtained', 'in', 'fewatom', 'chains', 'here', 'we', 'experimentally', 'and', 'theoretically', 'demonstrate', 'the', 'occurrence', 'of', 'the', 'at', 'in', 'an', 'extended', 'twodimensional', '2d', 'system', 'at', 'room', 'temperature', 'using', 'a', 'colloidal', 'monolayer', 'on', 'an', 'optical', 'lattice', 'unlike', 'the', 'continuous', 'nature', 'of', 'the', 'at', 'in', '1d', 'we', 'observe', 'a', 'firstorder', 'transition', 'in', '2d', 'leading', 'to', 'a', 'coexistence', 'regime', 'of', 'pinned', 'and', 'unpinned', 'areas', 'our', 'data', 'demonstrate', 'that', 'the', 'original', 'concept', 'of', 'aubry', 'does', 'not', 'only', 'survive', 'in', '2d', 'but', 'is', 'relevant', 'for', 'the', 'design', 'of', 'nanoscopic', 'machines', 'and', 'devices', 'at', 'ambient', 'temperature']]
[-0.14345608920534597, 0.20923952228299136, -0.06101607911142649, -0.00989571802951152, 0.008251679884695929, -0.17313121187080646, 0.10439751191776903, 0.3753003568504176, -0.2759554457722926, -0.25329335192157554, 0.07117874315769405, -0.29852215604235727, -0.13713451298684173, 0.1928948099813211, 0.005698795103942793, 0.06931581031044129, -0.015202159923349137, 0.0198174730229368, -0.08308092592545828, -0.1875533463457733, 0.25813967563528445, 0.016304079368649648, 0.34051130325807366, 0.09576297040535685, 0.09357367860521586, -0.03087783866452382, 0.13770563328133445, 0.05314201853402397, -0.16928234326774352, 0.03345190265765292, 0.2454888526414174, -0.07347309474492433, 0.25543188901459857, -0.4443857573167561, -0.23740766377240005, 0.06392171096857151, 0.12420100379306093, 0.15911276467537105, -0.03501605979407364, -0.2580282859370307, 0.08119114304990112, -0.1009569619827922, -0.15560258632458082, -0.06491741434339239, 0.05050620530713715, -0.015286528277119585, -0.223094171336152, 0.08908476568515004, 0.07799793353906888, 0.0999703388326357, -0.07600358384908663, -0.04091523695368855, -0.051140110789086014, 0.100051837722395, -0.02913493845760944, 0.0003547981819685768, 0.15319382257187386, -0.12611366776837754, -0.10130120630777788, 0.3997095470389753, -0.030864981512898227, -0.1027561890850075, 0.26123642127693086, -0.1760037963908604, -0.09533833721013484, 0.18469414975664583, 0.15991648058315702, 0.0598804024980233, -0.10771919525842094, 0.04872949005506348, -0.011846706325955251, 0.17358230927873866, 0.08587618115102398, 0.02988369550762905, 0.2761695908467754, 0.24038740466584702, 0.05095834260063818, 0.1693727961601385, -0.08678908740912923, -0.09383171528054315, -0.24376352287804573, -0.1655289493371836, -0.25184165327535835, 0.0369007172690913, -0.0411313324128095, -0.17705326126827522, 0.3504338219177489, 0.17050485411244962, 0.20326105350616322, 0.02727161540255693, 0.2539589420734034, 0.08496921446084599, 0.07714856940046184, 0.05352499768490982, 0.2773453677864441, 0.0749057939441972, 0.12264157453661456, -0.2259602598310296, 0.038530729249959775, 0.012516633680492056]
1,802.09076
NanoMap: Fast, Uncertainty-Aware Proximity Queries with Lazy Search over Local 3D Data
We would like robots to be able to safely navigate at high speed, efficiently use local 3D information, and robustly plan motions that consider pose uncertainty of measurements in a local map structure. This is hard to do with previously existing mapping approaches, like occupancy grids, that are focused on incrementally fusing 3D data into a common world frame. In particular, both their fragile sensitivity to state estimation errors and computational cost can be limiting. We develop an alternative framework, NanoMap, which alleviates the need for global map fusion and enables a motion planner to efficiently query pose-uncertainty-aware local 3D geometric information. The key idea of NanoMap is to store a history of noisy relative pose transforms and search over a corresponding set of depth sensor measurements for the minimum-uncertainty view of a queried point in space. This approach affords a variety of capabilities not offered by traditional mapping techniques: (a) the pose uncertainty associated with 3D data can be incorporated in motion planning, (b) poses can be updated (i.e., from loop closures) with minimal computational effort, and (c) 3D data can be fused lazily for the purpose of planning. We provide an open-source implementation of NanoMap, and analyze its capabilities and computational efficiency in simulation experiments. Finally, we demonstrate in hardware its effectiveness for fast 3D obstacle avoidance onboard a quadrotor flying up to 10 m/s.
cs.RO
we would like robots to be able to safely navigate at high speed efficiently use local 3d information and robustly plan motions that consider pose uncertainty of measurements in a local map structure this is hard to do with previously existing mapping approaches like occupancy grids that are focused on incrementally fusing 3d data into a common world frame in particular both their fragile sensitivity to state estimation errors and computational cost can be limiting we develop an alternative framework nanomap which alleviates the need for global map fusion and enables a motion planner to efficiently query poseuncertaintyaware local 3d geometric information the key idea of nanomap is to store a history of noisy relative pose transforms and search over a corresponding set of depth sensor measurements for the minimumuncertainty view of a queried point in space this approach affords a variety of capabilities not offered by traditional mapping techniques a the pose uncertainty associated with 3d data can be incorporated in motion planning b poses can be updated ie from loop closures with minimal computational effort and c 3d data can be fused lazily for the purpose of planning we provide an opensource implementation of nanomap and analyze its capabilities and computational efficiency in simulation experiments finally we demonstrate in hardware its effectiveness for fast 3d obstacle avoidance onboard a quadrotor flying up to 10 ms
[['we', 'would', 'like', 'robots', 'to', 'be', 'able', 'to', 'safely', 'navigate', 'at', 'high', 'speed', 'efficiently', 'use', 'local', '3d', 'information', 'and', 'robustly', 'plan', 'motions', 'that', 'consider', 'pose', 'uncertainty', 'of', 'measurements', 'in', 'a', 'local', 'map', 'structure', 'this', 'is', 'hard', 'to', 'do', 'with', 'previously', 'existing', 'mapping', 'approaches', 'like', 'occupancy', 'grids', 'that', 'are', 'focused', 'on', 'incrementally', 'fusing', '3d', 'data', 'into', 'a', 'common', 'world', 'frame', 'in', 'particular', 'both', 'their', 'fragile', 'sensitivity', 'to', 'state', 'estimation', 'errors', 'and', 'computational', 'cost', 'can', 'be', 'limiting', 'we', 'develop', 'an', 'alternative', 'framework', 'nanomap', 'which', 'alleviates', 'the', 'need', 'for', 'global', 'map', 'fusion', 'and', 'enables', 'a', 'motion', 'planner', 'to', 'efficiently', 'query', 'poseuncertaintyaware', 'local', '3d', 'geometric', 'information', 'the', 'key', 'idea', 'of', 'nanomap', 'is', 'to', 'store', 'a', 'history', 'of', 'noisy', 'relative', 'pose', 'transforms', 'and', 'search', 'over', 'a', 'corresponding', 'set', 'of', 'depth', 'sensor', 'measurements', 'for', 'the', 'minimumuncertainty', 'view', 'of', 'a', 'queried', 'point', 'in', 'space', 'this', 'approach', 'affords', 'a', 'variety', 'of', 'capabilities', 'not', 'offered', 'by', 'traditional', 'mapping', 'techniques', 'a', 'the', 'pose', 'uncertainty', 'associated', 'with', '3d', 'data', 'can', 'be', 'incorporated', 'in', 'motion', 'planning', 'b', 'poses', 'can', 'be', 'updated', 'ie', 'from', 'loop', 'closures', 'with', 'minimal', 'computational', 'effort', 'and', 'c', '3d', 'data', 'can', 'be', 'fused', 'lazily', 'for', 'the', 'purpose', 'of', 'planning', 'we', 'provide', 'an', 'opensource', 'implementation', 'of', 'nanomap', 'and', 'analyze', 'its', 'capabilities', 'and', 'computational', 'efficiency', 'in', 'simulation', 'experiments', 'finally', 'we', 'demonstrate', 'in', 'hardware', 'its', 'effectiveness', 'for', 'fast', '3d', 'obstacle', 'avoidance', 'onboard', 'a', 'quadrotor', 'flying', 'up', 'to', '10', 'ms']]
[-0.06617419452470887, 0.03475259636197573, -0.0770376198783422, 0.03019160852858702, -0.11599629523389174, -0.14057777842004016, 0.053295856466376745, 0.43493719686407895, -0.3187041495044806, -0.36600422090232637, 0.1307307517607243, -0.24559009746355787, -0.10886102601931126, 0.20239960271978455, -0.15368515930387844, 0.10765769805906514, 0.1351046435842991, 0.0278696981126049, -0.06617429962127255, -0.19917623886083402, 0.2491444581939295, 0.06623661273006613, 0.2708839650154608, 0.0034522803493083117, 0.127183272781992, 0.005075612836373162, -0.035780428621332794, 0.04804585586120148, -0.08346008316777798, 0.17864516503909042, 0.27729905125544924, 0.20535612912576612, 0.26167576225676403, -0.46991343310399525, -0.20363776936644967, 0.0894236168216304, 0.14802950581193663, 0.10636397310176172, -0.05081905694153011, -0.3272373337438742, 0.08063921321954051, -0.16901263486659895, -0.09955557809310216, -0.14619305230516413, -0.011575863420534713, -0.014183740761539016, -0.2889226474915116, 0.010685745802856323, 0.015846780590066303, 0.0444959788624428, -0.056612980023512734, -0.03852507359022687, 0.005926615997440124, 0.1939042390971156, -0.04081986345344561, 0.06474695996220628, 0.16745911335646776, -0.14892296011114609, -0.13603273156074297, 0.41164818516545065, -0.01327757812563569, -0.23777560964824251, 0.19823582706904963, -0.07854321004670377, -0.11885543708664785, 0.1539920430591297, 0.23214325621884843, 0.08592150910691548, -0.162073824990209, 0.07138138486765762, 0.003880252166387452, 0.16928805081628107, 0.007104428634418389, -0.0015980166514956318, 0.2060960307665812, 0.20052172530718576, 0.10185472348568944, 0.11429212496160587, -0.15930377602200146, -0.07977552938612953, -0.2329935425546317, -0.16693358687723603, -0.1536657480168593, -0.0068946988599357375, -0.08611914919092026, -0.1008442207486822, 0.35440102652069677, 0.24016381310200138, 0.1957436397453292, 0.07262823793499326, 0.3720933282294566, 0.04244049641658373, 0.0772974939006731, 0.0854009649782252, 0.17054429472747581, 0.00974986171947413, 0.09699585200498598, -0.19150158583775856, 0.05756628756881156, 0.044134501237999155]
1,802.09077
Growth of periodic Grigorchuk groups
On torsion Grigorchuk groups we construct random walks of finite entropy and power-law tail decay with non-trivial Poisson boundary. Such random walks provide near optimal volume lower estimates for these groups. In particular, for the first Grigorchuk group $G$ we show that its volume growth function $v_{G,S}(n)$ satisfies that $\lim_{n\to\infty}\log\log v_{G,S}(n)/\log n=\alpha_{0}$, where $\alpha_{0}=\frac{\log2}{\log\lambda_{0}}\approx0.7674$, $\lambda_{0}$ is the positive root of the polynomial $X^{3}-X^{2}-2X-4$.
math.GR math.PR
on torsion grigorchuk groups we construct random walks of finite entropy and powerlaw tail decay with nontrivial poisson boundary such random walks provide near optimal volume lower estimates for these groups in particular for the first grigorchuk group g we show that its volume growth function v_gsn satisfies that lim_ntoinftyloglog v_gsnlog nalpha_0 where alpha_0fraclog2loglambda_0approx07674 lambda_0 is the positive root of the polynomial x3x22x4
[['on', 'torsion', 'grigorchuk', 'groups', 'we', 'construct', 'random', 'walks', 'of', 'finite', 'entropy', 'and', 'powerlaw', 'tail', 'decay', 'with', 'nontrivial', 'poisson', 'boundary', 'such', 'random', 'walks', 'provide', 'near', 'optimal', 'volume', 'lower', 'estimates', 'for', 'these', 'groups', 'in', 'particular', 'for', 'the', 'first', 'grigorchuk', 'group', 'g', 'we', 'show', 'that', 'its', 'volume', 'growth', 'function', 'v_gsn', 'satisfies', 'that', 'lim_ntoinftyloglog', 'v_gsnlog', 'nalpha_0', 'where', 'alpha_0fraclog2loglambda_0approx07674', 'lambda_0', 'is', 'the', 'positive', 'root', 'of', 'the', 'polynomial', 'x3x22x4']]
[-0.16742230544945128, 0.18847448885310114, -0.1089215727947783, 0.0633457425364963, -0.09332226285825304, -0.155136114974882, 0.02532254373491333, 0.37272437410674203, -0.2874196227149744, -0.18396757669714198, 0.11752252595441971, -0.29354455374311983, -0.15960196186706685, 0.20115902554243803, -0.073647258599011, 0.03450672439475168, -0.005524953353431141, 0.1283741114265898, -0.035161521547196206, -0.2992587935816693, 0.3490097990684342, -0.018161852811381482, 0.2267599962855967, 0.05545656985946392, 0.1105370677419399, -0.013728308891714142, -0.012210683051594779, 0.0040837059189614494, -0.24453006259277013, 0.049442766994041834, 0.19799995716465146, 0.01344271969017491, 0.2551986454544883, -0.34603433330592354, -0.1733009542109804, 0.21493148039046087, 0.13026659854017852, 0.012161595322061004, -0.09264094630264465, -0.26363473910871044, 0.15816434512012884, -0.1563272944798595, -0.15029605365309276, 0.00022953085339905922, 0.08126653920401607, 0.04475523130008297, -0.2575924670397255, 0.11387519616421246, 0.032325322944017354, 0.061598112610609906, -0.0312888397316432, -0.11931109219266657, -0.006319360456249693, 0.1524994360577119, 0.013015675501440439, -0.03330917088845908, 0.11911761533599674, -0.06727047323396332, -0.12513792998435205, 0.34114858988476426, -0.09048117739720303, -0.19024508593505934, 0.12299149549615226, -0.2355786153491129, -0.21351353245738305, 0.11406921344531472, 0.16516206838321268, 0.09015197943275173, -0.024334249593186797, 0.180896754506281, -0.10429853127999722, 0.08811298444082863, 0.09196093805918568, -0.024357682518791734, 0.09058277441286727, 0.0700579362659993, 0.18904521389815368, 0.14935254800468356, 0.03707327990253505, -0.04184989221067282, -0.3822340193008514, -0.17698990159847758, -0.21985149393348316, 0.1426413042078677, -0.23007973359480066, -0.28475972986371634, 0.3393774269834945, 0.04938975210187205, 0.15572666410324082, 0.2156235438428427, 0.16924487923582396, 0.14136849299661422, 0.0071541447715278254, 0.1250828230965948, 0.06399592237645074, 0.17117743124254048, -0.03625518863759281, -0.19630336576843993, 0.04547826620635756, 0.20382491839036607]
1,802.09078
Generation of Internal Waves by Buoyant Bubbles in Galaxy Clusters and Heating of Intracluster Medium
Buoyant bubbles of relativistic plasma in cluster cores plausibly play a key role in conveying the energy from a supermassive black hole to the intracluster medium (ICM) - the process known as radio-mode AGN feedback. Energy conservation guarantees that a bubble loses most of its energy to the ICM after crossing several pressure scale heights. However, actual processes responsible for transferring the energy to the ICM are still being debated. One attractive possibility is the excitation of internal waves, which are trapped in the cluster's core and eventually dissipate. Here we show that a sufficient condition for efficient excitation of these waves in stratified cluster atmospheres is flattening of the bubbles in the radial direction. In our numerical simulations, we model the bubbles phenomenologically as rigid bodies buoyantly rising in the stratified cluster atmosphere. We find that the terminal velocities of the flattened bubbles are small enough so that the Froude number ${\rm Fr}\lesssim 1$. The effects of stratification make the dominant contribution to the total drag force balancing the buoyancy force. In particular, clear signs of internal waves are seen in the simulations. These waves propagate horizontally and downwards from the rising bubble, spreading their energy over large volumes of the ICM. If our findings are scaled to the conditions of the Perseus cluster, the expected terminal velocity is $\sim100-200{\,\rm km\,s^{-1}}$ near the cluster cores, which is in broad agreement with direct measurements by the Hitomi satellite.
astro-ph.HE astro-ph.GA
buoyant bubbles of relativistic plasma in cluster cores plausibly play a key role in conveying the energy from a supermassive black hole to the intracluster medium icm the process known as radiomode agn feedback energy conservation guarantees that a bubble loses most of its energy to the icm after crossing several pressure scale heights however actual processes responsible for transferring the energy to the icm are still being debated one attractive possibility is the excitation of internal waves which are trapped in the clusters core and eventually dissipate here we show that a sufficient condition for efficient excitation of these waves in stratified cluster atmospheres is flattening of the bubbles in the radial direction in our numerical simulations we model the bubbles phenomenologically as rigid bodies buoyantly rising in the stratified cluster atmosphere we find that the terminal velocities of the flattened bubbles are small enough so that the froude number rm frlesssim 1 the effects of stratification make the dominant contribution to the total drag force balancing the buoyancy force in particular clear signs of internal waves are seen in the simulations these waves propagate horizontally and downwards from the rising bubble spreading their energy over large volumes of the icm if our findings are scaled to the conditions of the perseus cluster the expected terminal velocity is sim100200rm kms1 near the cluster cores which is in broad agreement with direct measurements by the hitomi satellite
[['buoyant', 'bubbles', 'of', 'relativistic', 'plasma', 'in', 'cluster', 'cores', 'plausibly', 'play', 'a', 'key', 'role', 'in', 'conveying', 'the', 'energy', 'from', 'a', 'supermassive', 'black', 'hole', 'to', 'the', 'intracluster', 'medium', 'icm', 'the', 'process', 'known', 'as', 'radiomode', 'agn', 'feedback', 'energy', 'conservation', 'guarantees', 'that', 'a', 'bubble', 'loses', 'most', 'of', 'its', 'energy', 'to', 'the', 'icm', 'after', 'crossing', 'several', 'pressure', 'scale', 'heights', 'however', 'actual', 'processes', 'responsible', 'for', 'transferring', 'the', 'energy', 'to', 'the', 'icm', 'are', 'still', 'being', 'debated', 'one', 'attractive', 'possibility', 'is', 'the', 'excitation', 'of', 'internal', 'waves', 'which', 'are', 'trapped', 'in', 'the', 'clusters', 'core', 'and', 'eventually', 'dissipate', 'here', 'we', 'show', 'that', 'a', 'sufficient', 'condition', 'for', 'efficient', 'excitation', 'of', 'these', 'waves', 'in', 'stratified', 'cluster', 'atmospheres', 'is', 'flattening', 'of', 'the', 'bubbles', 'in', 'the', 'radial', 'direction', 'in', 'our', 'numerical', 'simulations', 'we', 'model', 'the', 'bubbles', 'phenomenologically', 'as', 'rigid', 'bodies', 'buoyantly', 'rising', 'in', 'the', 'stratified', 'cluster', 'atmosphere', 'we', 'find', 'that', 'the', 'terminal', 'velocities', 'of', 'the', 'flattened', 'bubbles', 'are', 'small', 'enough', 'so', 'that', 'the', 'froude', 'number', 'rm', 'frlesssim', '1', 'the', 'effects', 'of', 'stratification', 'make', 'the', 'dominant', 'contribution', 'to', 'the', 'total', 'drag', 'force', 'balancing', 'the', 'buoyancy', 'force', 'in', 'particular', 'clear', 'signs', 'of', 'internal', 'waves', 'are', 'seen', 'in', 'the', 'simulations', 'these', 'waves', 'propagate', 'horizontally', 'and', 'downwards', 'from', 'the', 'rising', 'bubble', 'spreading', 'their', 'energy', 'over', 'large', 'volumes', 'of', 'the', 'icm', 'if', 'our', 'findings', 'are', 'scaled', 'to', 'the', 'conditions', 'of', 'the', 'perseus', 'cluster', 'the', 'expected', 'terminal', 'velocity', 'is', 'sim100200rm', 'kms1', 'near', 'the', 'cluster', 'cores', 'which', 'is', 'in', 'broad', 'agreement', 'with', 'direct', 'measurements', 'by', 'the', 'hitomi', 'satellite']]
[-0.1348175176825533, 0.21433720065161904, -0.07503952170385325, 0.10541842732151402, -0.08375403860266856, -0.031419197970287915, 0.030762021080590785, 0.3740638619328433, -0.26861669247749537, -0.304599611232295, 0.06505573229725532, -0.2676906973737827, -0.03407736829670265, 0.19752172408328253, 0.0144339318937087, -0.016497247778325085, 0.06212008070161051, -0.026827551435401782, 0.024400039478898683, -0.21788785360119445, 0.31356919076085643, 0.1245963112203444, 0.22327867295256162, 0.0484834440884755, 0.06804048000696175, -0.11179489713320706, -0.024480528359925573, 0.03663311346701564, -0.14777202832424627, 0.04423244896770871, 0.1993591726286971, 0.05668945416827944, 0.28267173811872587, -0.4791799693507083, -0.24635138252076316, 0.06304498293902724, 0.18505121939419272, 0.09607057916694023, -0.07549252423229924, -0.21698194247412872, 0.06064707111923936, -0.18627779816098985, -0.20024561632147178, 0.027482581332801504, 0.04404458193643455, 0.06596736447212065, -0.20651530326552134, 0.16958290690833583, 0.05378966422038192, 0.012295956234943043, -0.11812418295179514, -0.060130433217087324, -0.10868115323456995, 0.10136011307365558, 0.06937439571607838, 0.026545068873290684, 0.23581672527609354, -0.17130700229726573, -0.008569436615451854, 0.4207215038227274, -0.02778759346531823, -0.0885231358474715, 0.22727220149294652, -0.1966358145441305, -0.10171873131667838, 0.18472381027841425, 0.17451933999446795, 0.07070507114515343, -0.0831021064614996, -0.006190709207464565, -0.06383472602180344, 0.1500937133395866, 0.08580306152357382, -0.002090280616260877, 0.2954660909745763, 0.10827491678832535, 0.07074750995540872, 0.11107980339847347, -0.14724045737071875, -0.08848617382377306, -0.2919641015169389, -0.12653148316263044, -0.12359328903208308, 0.015429339578816112, -0.10937271924575474, -0.15504074580391541, 0.30711171005832705, 0.11817048554645573, 0.17771465033689077, -0.0006728070421501042, 0.3269716126963179, 0.08499436973534683, 0.08244940855771309, 0.16593536917774127, 0.3190300572782438, 0.17850242373632624, 0.11065575168022213, -0.2491271501862781, 0.04999994547998018, 0.01235883691078151]
1,802.09079
User Satisfaction-Driven Bandwidth Allocation for Image Transmission in a Crowded Environment
A major portion of postings on social networking sites constitute high quality digital images and videos. These images and videos require a fairly large amount of bandwidth during transmission. Accordingly, high quality image and video postings become a challenge for the network service provider, especially in a crowded environment where bandwidth is in high demand. In this paper we present a user satisfaction driven bandwidth allocation scheme for image transmission in such environments. In an image, there are always objects that stand out more than others. The reason behind some set of objects being more important in a scene is based on a number of visual, as well as, cognitive factors. Being motivated by the fact that user satisfaction is more dependent on the quality of these salient objects in an image than non-salient ones, we propose a quantifiable metric for measuring user-satisfiability (based on image quality and delay of transmission). The bandwidth allocation technique proposed thereafter, ensures that this user-satisfiability is maximized. Unlike the existing approaches that utilize some fixed set of non-linear functions for framing the user-satisfiability index, our metric is modelled over customer survey data, where the unknown parameters are trained with machine learning methods.
cs.MM
a major portion of postings on social networking sites constitute high quality digital images and videos these images and videos require a fairly large amount of bandwidth during transmission accordingly high quality image and video postings become a challenge for the network service provider especially in a crowded environment where bandwidth is in high demand in this paper we present a user satisfaction driven bandwidth allocation scheme for image transmission in such environments in an image there are always objects that stand out more than others the reason behind some set of objects being more important in a scene is based on a number of visual as well as cognitive factors being motivated by the fact that user satisfaction is more dependent on the quality of these salient objects in an image than nonsalient ones we propose a quantifiable metric for measuring usersatisfiability based on image quality and delay of transmission the bandwidth allocation technique proposed thereafter ensures that this usersatisfiability is maximized unlike the existing approaches that utilize some fixed set of nonlinear functions for framing the usersatisfiability index our metric is modelled over customer survey data where the unknown parameters are trained with machine learning methods
[['a', 'major', 'portion', 'of', 'postings', 'on', 'social', 'networking', 'sites', 'constitute', 'high', 'quality', 'digital', 'images', 'and', 'videos', 'these', 'images', 'and', 'videos', 'require', 'a', 'fairly', 'large', 'amount', 'of', 'bandwidth', 'during', 'transmission', 'accordingly', 'high', 'quality', 'image', 'and', 'video', 'postings', 'become', 'a', 'challenge', 'for', 'the', 'network', 'service', 'provider', 'especially', 'in', 'a', 'crowded', 'environment', 'where', 'bandwidth', 'is', 'in', 'high', 'demand', 'in', 'this', 'paper', 'we', 'present', 'a', 'user', 'satisfaction', 'driven', 'bandwidth', 'allocation', 'scheme', 'for', 'image', 'transmission', 'in', 'such', 'environments', 'in', 'an', 'image', 'there', 'are', 'always', 'objects', 'that', 'stand', 'out', 'more', 'than', 'others', 'the', 'reason', 'behind', 'some', 'set', 'of', 'objects', 'being', 'more', 'important', 'in', 'a', 'scene', 'is', 'based', 'on', 'a', 'number', 'of', 'visual', 'as', 'well', 'as', 'cognitive', 'factors', 'being', 'motivated', 'by', 'the', 'fact', 'that', 'user', 'satisfaction', 'is', 'more', 'dependent', 'on', 'the', 'quality', 'of', 'these', 'salient', 'objects', 'in', 'an', 'image', 'than', 'nonsalient', 'ones', 'we', 'propose', 'a', 'quantifiable', 'metric', 'for', 'measuring', 'usersatisfiability', 'based', 'on', 'image', 'quality', 'and', 'delay', 'of', 'transmission', 'the', 'bandwidth', 'allocation', 'technique', 'proposed', 'thereafter', 'ensures', 'that', 'this', 'usersatisfiability', 'is', 'maximized', 'unlike', 'the', 'existing', 'approaches', 'that', 'utilize', 'some', 'fixed', 'set', 'of', 'nonlinear', 'functions', 'for', 'framing', 'the', 'usersatisfiability', 'index', 'our', 'metric', 'is', 'modelled', 'over', 'customer', 'survey', 'data', 'where', 'the', 'unknown', 'parameters', 'are', 'trained', 'with', 'machine', 'learning', 'methods']]
[-0.12368321513364355, 0.016448225438120925, -0.03596522742317933, 0.05144913136639228, -0.10992323191874105, -0.1613430441122013, 0.07667815883707424, 0.47384885564973256, -0.23183339043059434, -0.3248606989762247, 0.10591468276312536, -0.2849930784467495, -0.14645832693415947, 0.20893782338908298, -0.1776750019299939, 0.04920952943990929, 0.07063603992726786, 0.06463329403454231, 0.011872529673079649, -0.28283666834385707, 0.3193709987893023, 0.06654142115189872, 0.33848234995578724, 0.023110831165780322, 0.09714715009745718, -0.0012084404759184278, -0.06283747518612684, 0.017088672710639057, -0.04082160362414663, 0.1540892095971033, 0.3425384848707854, 0.22029079046486078, 0.3316347076336505, -0.38909369341163624, -0.22844293443631614, 0.07968347998350069, 0.1284132965198351, 0.04176982258437107, -0.07926479237784122, -0.29229948375223563, 0.10623311749400778, -0.1716486632569947, 0.007753251122652948, -0.06143671782649677, 0.003031161019926646, 0.007855644752977021, -0.2757442024621097, 0.025785688606015586, -0.003697294357933593, 0.0908445978132688, -0.0533167371747432, -0.075311250551933, 0.024194163293812913, 0.18096162698841936, 0.03609779012281297, 0.03249184625703051, 0.14455315991507073, -0.2237771319771054, -0.07750550769222429, 0.42940415361557494, -0.005494789651511566, -0.19988589983132451, 0.1644238049100915, -0.06961097624717337, -0.14683091636709492, 0.1351100592973943, 0.21271285384122018, 0.11264536308002367, -0.16986176087003615, -0.009704085867710863, -0.048322206722911105, 0.21879043358712072, 0.0848528509054126, 0.07028511373768326, 0.19129128304528864, 0.223730541482295, 0.10668067783916915, 0.11345265665905306, -0.08051274679695265, -0.04270927273113318, -0.22286824073943526, -0.11441075342538004, -0.20541426784716396, 0.011152624087925587, -0.10924479910002015, -0.13848827821567108, 0.37550209315835525, 0.1784269584253468, 0.1989206344634765, 0.08278884383881549, 0.3564391728970363, 0.05899456265512407, 0.08468207951183572, 0.09588580289055978, 0.14756598406044455, -0.026257817604052224, 0.15868071976501139, -0.13192678270379382, 0.0959014129775548, 0.004846790142244462]
1,802.0908
Minimizing Flow Completion Times using Adaptive Routing over Inter-Datacenter Wide Area Networks
Inter-datacenter networks connect dozens of geographically dispersed datacenters and carry traffic flows with highly variable sizes and different classes. Adaptive flow routing can improve efficiency and performance by assigning paths to new flows according to network status and flow properties. A popular approach widely used for traffic engineering is based on current bandwidth utilization of links. We propose an alternative that reduces bandwidth usage by up to at least 50% and flow completion times by up to at least 40% across various scheduling policies and flow size distributions.
cs.NI cs.DC cs.PF cs.SY
interdatacenter networks connect dozens of geographically dispersed datacenters and carry traffic flows with highly variable sizes and different classes adaptive flow routing can improve efficiency and performance by assigning paths to new flows according to network status and flow properties a popular approach widely used for traffic engineering is based on current bandwidth utilization of links we propose an alternative that reduces bandwidth usage by up to at least 50 and flow completion times by up to at least 40 across various scheduling policies and flow size distributions
[['interdatacenter', 'networks', 'connect', 'dozens', 'of', 'geographically', 'dispersed', 'datacenters', 'and', 'carry', 'traffic', 'flows', 'with', 'highly', 'variable', 'sizes', 'and', 'different', 'classes', 'adaptive', 'flow', 'routing', 'can', 'improve', 'efficiency', 'and', 'performance', 'by', 'assigning', 'paths', 'to', 'new', 'flows', 'according', 'to', 'network', 'status', 'and', 'flow', 'properties', 'a', 'popular', 'approach', 'widely', 'used', 'for', 'traffic', 'engineering', 'is', 'based', 'on', 'current', 'bandwidth', 'utilization', 'of', 'links', 'we', 'propose', 'an', 'alternative', 'that', 'reduces', 'bandwidth', 'usage', 'by', 'up', 'to', 'at', 'least', '50', 'and', 'flow', 'completion', 'times', 'by', 'up', 'to', 'at', 'least', '40', 'across', 'various', 'scheduling', 'policies', 'and', 'flow', 'size', 'distributions']]
[-0.1287409075038423, 0.10455303858923964, -0.03313713644059713, -0.010400603894430044, -0.07721106180476701, -0.15893332522748757, 0.11115849473175, 0.4462270634248853, -0.2874184462919154, -0.3779237637592649, 0.13240831135243009, -0.26494662480598147, -0.0804930920871398, 0.198842525746758, -0.11756669026693668, 0.09650204567746683, 0.07425473398788282, -0.03558098289861598, -0.017154577270213685, -0.26377568433103576, 0.2741461090244312, 0.07113414990652184, 0.41553468219089235, 0.05129792521686547, 0.0884371127044274, -0.010737595529380169, -0.05692431700564074, 0.03330931740087677, -0.09527834262793146, 0.14821133892771535, 0.29088072084546596, 0.14728867644126611, 0.292649007905063, -0.4362883725843858, -0.26358811829281464, 0.07512055138464678, 0.14313876562201502, -0.0031688043725973166, 0.0255769547829087, -0.2209939524896485, 0.15738234126845121, -0.22434930192751132, -0.06360960302514616, -0.0777617978905751, 0.0038021533136171374, 0.07272620541466908, -0.24016793838977304, 0.017829871389866723, -0.09546759512952784, 0.02566048806660216, 0.011302771750541235, -0.09877635403642092, 0.017955552774682557, 0.17693013260776008, 0.04520247017022815, -0.011014607041777874, 0.16469463486414912, -0.13401245524768124, -0.16687486010645938, 0.3942982863888822, -0.020129592004443773, -0.169792066804472, 0.23156109028125435, 0.026107768681619993, -0.08445331046823412, 0.1726159109649333, 0.2751048361109993, 0.10907603072171862, -0.18955649887423284, -0.07471278924574355, 0.02190319793722169, 0.169191605665467, 0.10212597636167299, 0.02062459547728808, 0.1766097454634622, 0.22808977646689693, 0.177480043113147, 0.12437712125723589, -0.09343173637171276, -0.115560114658861, -0.18642555899515917, -0.09646323848177087, -0.125362139607949, 0.03490128108850596, -0.12756588320487275, -0.07235938824967227, 0.4148373447189277, 0.1675594877213536, 0.18486852437490597, 0.10649620939214154, 0.325777786207089, 0.03853267205836759, 0.12267844384239818, 0.24816204589495267, 0.11163467313797976, 0.07030183953942139, 0.17452096672389994, -0.17480838410450483, 0.07523538737388497, 0.012370448779124259]
1,802.09081
Temporal Difference Models: Model-Free Deep RL for Model-Based Control
Model-free reinforcement learning (RL) is a powerful, general tool for learning complex behaviors. However, its sample efficiency is often impractically large for solving challenging real-world problems, even with off-policy algorithms such as Q-learning. A limiting factor in classic model-free RL is that the learning signal consists only of scalar rewards, ignoring much of the rich information contained in state transition tuples. Model-based RL uses this information, by training a predictive model, but often does not achieve the same asymptotic performance as model-free RL due to model bias. We introduce temporal difference models (TDMs), a family of goal-conditioned value functions that can be trained with model-free learning and used for model-based control. TDMs combine the benefits of model-free and model-based RL: they leverage the rich information in state transitions to learn very efficiently, while still attaining asymptotic performance that exceeds that of direct model-based RL methods. Our experimental results show that, on a range of continuous control tasks, TDMs provide a substantial improvement in efficiency compared to state-of-the-art model-based and model-free methods.
cs.LG
modelfree reinforcement learning rl is a powerful general tool for learning complex behaviors however its sample efficiency is often impractically large for solving challenging realworld problems even with offpolicy algorithms such as qlearning a limiting factor in classic modelfree rl is that the learning signal consists only of scalar rewards ignoring much of the rich information contained in state transition tuples modelbased rl uses this information by training a predictive model but often does not achieve the same asymptotic performance as modelfree rl due to model bias we introduce temporal difference models tdms a family of goalconditioned value functions that can be trained with modelfree learning and used for modelbased control tdms combine the benefits of modelfree and modelbased rl they leverage the rich information in state transitions to learn very efficiently while still attaining asymptotic performance that exceeds that of direct modelbased rl methods our experimental results show that on a range of continuous control tasks tdms provide a substantial improvement in efficiency compared to stateoftheart modelbased and modelfree methods
[['modelfree', 'reinforcement', 'learning', 'rl', 'is', 'a', 'powerful', 'general', 'tool', 'for', 'learning', 'complex', 'behaviors', 'however', 'its', 'sample', 'efficiency', 'is', 'often', 'impractically', 'large', 'for', 'solving', 'challenging', 'realworld', 'problems', 'even', 'with', 'offpolicy', 'algorithms', 'such', 'as', 'qlearning', 'a', 'limiting', 'factor', 'in', 'classic', 'modelfree', 'rl', 'is', 'that', 'the', 'learning', 'signal', 'consists', 'only', 'of', 'scalar', 'rewards', 'ignoring', 'much', 'of', 'the', 'rich', 'information', 'contained', 'in', 'state', 'transition', 'tuples', 'modelbased', 'rl', 'uses', 'this', 'information', 'by', 'training', 'a', 'predictive', 'model', 'but', 'often', 'does', 'not', 'achieve', 'the', 'same', 'asymptotic', 'performance', 'as', 'modelfree', 'rl', 'due', 'to', 'model', 'bias', 'we', 'introduce', 'temporal', 'difference', 'models', 'tdms', 'a', 'family', 'of', 'goalconditioned', 'value', 'functions', 'that', 'can', 'be', 'trained', 'with', 'modelfree', 'learning', 'and', 'used', 'for', 'modelbased', 'control', 'tdms', 'combine', 'the', 'benefits', 'of', 'modelfree', 'and', 'modelbased', 'rl', 'they', 'leverage', 'the', 'rich', 'information', 'in', 'state', 'transitions', 'to', 'learn', 'very', 'efficiently', 'while', 'still', 'attaining', 'asymptotic', 'performance', 'that', 'exceeds', 'that', 'of', 'direct', 'modelbased', 'rl', 'methods', 'our', 'experimental', 'results', 'show', 'that', 'on', 'a', 'range', 'of', 'continuous', 'control', 'tasks', 'tdms', 'provide', 'a', 'substantial', 'improvement', 'in', 'efficiency', 'compared', 'to', 'stateoftheart', 'modelbased', 'and', 'modelfree', 'methods']]
[0.0044745448200653, -0.004075273905461382, -0.09198730169354301, 0.09095503519866506, -0.17118082911712906, -0.19795888534894115, 0.07536399684715689, 0.46726358196649115, -0.27078045364360365, -0.3288614658410089, 0.08287479674584186, -0.22878656026836464, -0.1600614435622218, 0.23721962694993667, -0.16025496251085958, 0.09093761192028797, 0.09256631833343217, 0.012810012839131373, -0.09028153390043595, -0.2381141406847491, 0.2553176548732281, -0.0045574726918113165, 0.34978062510953356, -0.029122758014073147, 0.17791589463064283, -0.03745114229526235, 0.034394033517339946, 0.03944841802817339, -0.04473752435743543, 0.15430068453431417, 0.39539753799068444, 0.20311421527641646, 0.3975079409146344, -0.3466612677746749, -0.23106511973786817, 0.1614335508409844, 0.18106127652334192, 0.06428894868164121, -0.0633950300919088, -0.28938457698081976, 0.06081963186366729, -0.1885301850188785, 0.0010201410289679528, -0.18870914977980635, -0.03740542463424523, -0.014575140434657687, -0.33752330630331445, 0.06500781672783414, 0.08912361319563543, 0.02497420547943976, -0.006579430857591592, -0.1477150661068865, 0.07259549095692952, 0.13839659092359638, 0.047944695329326284, 0.048747738573444215, 0.17230880266186177, -0.20439466937684742, -0.200728164414592, 0.3130747889293145, -0.05697156431572784, -0.17969744069207655, 0.22457353757934, -0.048537477284495596, -0.14516039836977485, 0.11807629853154789, 0.24739255140159735, 0.16624200013221094, -0.14741017314883179, 0.055359745054023766, -0.013351035734627679, 0.2007075668746954, -0.04998611693123454, 0.023495411616409667, 0.11445604425471015, 0.2732122549269762, 0.08931032654949142, 0.09109805286684951, -0.025372653762532168, -0.15062238337752568, -0.180759441905399, -0.0843332252868217, -0.17396343285823784, -0.005915532302440209, -0.15729906987587783, -0.14150405335296232, 0.3376425851942503, 0.2355867220818648, 0.19877672680430333, 0.1615857459490367, 0.38970714760127295, 0.08545634932802412, 0.07684044511335199, 0.1260490656329308, 0.26185985850251947, 0.036482744451274564, 0.1265496756399475, -0.21854448447559485, 0.15356774327116446, -0.0077005414883143195]
1,802.09082
Robustly Complete Synthesis of Memoryless Controllers for Nonlinear Systems with Reach-and-Stay Specifications
This paper proposes a finitely terminating algorithm to solve reach-and-stay control problems for nonlinear systems. The algorithm is guaranteed to return a control strategy if the specification is robustly realizable. Such a feature is desirable as the commonly used abstraction-based methods are sound but not complete for systems that are not incrementally stable. Fundamental to the proposed method is a fixed-point characterization of the winning set of the system with respect to a given specification, i.e., the initial states that can be controlled to satisfy the specification. The use of an adaptive partitioning scheme not only guarantees the approximation precision of the winning set but also reduces computational time. The effectiveness and efficiency are illustrated by several benchmarking examples.
math.OC
this paper proposes a finitely terminating algorithm to solve reachandstay control problems for nonlinear systems the algorithm is guaranteed to return a control strategy if the specification is robustly realizable such a feature is desirable as the commonly used abstractionbased methods are sound but not complete for systems that are not incrementally stable fundamental to the proposed method is a fixedpoint characterization of the winning set of the system with respect to a given specification ie the initial states that can be controlled to satisfy the specification the use of an adaptive partitioning scheme not only guarantees the approximation precision of the winning set but also reduces computational time the effectiveness and efficiency are illustrated by several benchmarking examples
[['this', 'paper', 'proposes', 'a', 'finitely', 'terminating', 'algorithm', 'to', 'solve', 'reachandstay', 'control', 'problems', 'for', 'nonlinear', 'systems', 'the', 'algorithm', 'is', 'guaranteed', 'to', 'return', 'a', 'control', 'strategy', 'if', 'the', 'specification', 'is', 'robustly', 'realizable', 'such', 'a', 'feature', 'is', 'desirable', 'as', 'the', 'commonly', 'used', 'abstractionbased', 'methods', 'are', 'sound', 'but', 'not', 'complete', 'for', 'systems', 'that', 'are', 'not', 'incrementally', 'stable', 'fundamental', 'to', 'the', 'proposed', 'method', 'is', 'a', 'fixedpoint', 'characterization', 'of', 'the', 'winning', 'set', 'of', 'the', 'system', 'with', 'respect', 'to', 'a', 'given', 'specification', 'ie', 'the', 'initial', 'states', 'that', 'can', 'be', 'controlled', 'to', 'satisfy', 'the', 'specification', 'the', 'use', 'of', 'an', 'adaptive', 'partitioning', 'scheme', 'not', 'only', 'guarantees', 'the', 'approximation', 'precision', 'of', 'the', 'winning', 'set', 'but', 'also', 'reduces', 'computational', 'time', 'the', 'effectiveness', 'and', 'efficiency', 'are', 'illustrated', 'by', 'several', 'benchmarking', 'examples']]
[-0.09630001605077947, 0.0434564180422813, -0.09551537751172812, 0.05533470765991389, -0.08869323845542336, -0.1837013385661136, 0.060749809179747066, 0.38821889422202516, -0.29758695257290946, -0.2999554478816917, 0.15201704226970925, -0.20985856654627597, -0.13461598146300352, 0.23138147843528098, -0.1378198202839516, 0.1436255333858337, 0.09274278885006147, 0.03950810145736688, -0.03168648609623187, -0.29311117551179006, 0.28811169760814725, 0.0358480671835053, 0.2835861465151785, 0.02035468064990463, 0.13535960125184412, -0.045408053361116196, 0.014798354187790873, 0.07133114958276689, -0.06363907044862448, 0.10685313728162467, 0.27648656316480397, 0.2208931803884837, 0.3379164640476012, -0.3649292831009222, -0.15243052785537378, 0.13445374192630524, 0.13609289252830636, 0.12161409182442447, -0.04183893919906626, -0.2596716280095279, 0.1461931143579531, -0.16157396634156673, -0.10391591096265336, -0.1563312714974696, -0.022697648834594984, 0.032628020624851144, -0.3281565865746431, -0.02114615475160062, 0.08530224676409705, 0.01757044557450434, -0.047622185316868126, -0.05198285752469358, -0.01214421279649487, 0.1193988098155202, -0.031913725209375056, 0.011963958461311156, 0.11778915740581135, -0.07548406658402124, -0.1471917927107316, 0.4163822427360436, -0.005406899361918538, -0.256954428155796, 0.19538799884444955, -0.03580211375255959, -0.1266208493616432, 0.16333675983369791, 0.15854715456854615, 0.14131920927567249, -0.1594374259633912, 0.07756005578735543, -0.052730154305286076, 0.21595848736874126, 0.0331784695252713, 0.021790417597897477, 0.13634358112842349, 0.19067453655366928, 0.1600962717567523, 0.11430072420379304, 0.013496798546037685, -0.09723797384491664, -0.3123929851049147, -0.14583559851241062, -0.18884331772648494, -0.054135228240476736, -0.042094656984372085, -0.19278464043686577, 0.40409867440939706, 0.19046218092237616, 0.14173076461242923, 0.11009518231138966, 0.34296698595586594, 0.15285559185367212, 0.029381421829230484, 0.09824437955473313, 0.1967928555273151, 0.07504581898239725, 0.05285582651968224, -0.21837097277343906, 0.14264785878012998, 0.08217793177434449]
1,802.09083
Classification of Tensor Decompositions of II$_1$ Factors Associated With Poly-Hyperbolic Groups
We demonstrate von Neumann algebra arising from an icc group $\Gamma$ in Chifan's, Ioana's, and Kida's class of poly-$\mathcal{C}_\text{rss} $, such as a poly-hyperbolic group with no amenable factors in its composition series, satisfies the following rigidity phenomenon discovered in DHI16 (see also CdSS17): every tensor decomposition of the II$_1$ factor $L(\Gamma) $ must arise from direct product decomposition of $\Gamma $ by groups which are poly-$ \mathcal{C}_\text{rss}$. Through heavy usage and developments of the techniques in CdSS15, we improve the second author's and their collaborator's work in CKP14 by providing group-level criteria for determining whether a group von Neumann algebra is prime: $L(\Gamma) $ is prime precisely when the group is indecomposable as a direct product of non-amenable groups. We further demonstrate that all tensor decompositions of finite index subalgebras of $L(\Gamma) $ correspond to a splitting of $\Gamma $ as a product by groups which are also poly-$\mathcal{C}_\text{rss}$ up to commensurability.
math.OA
we demonstrate von neumann algebra arising from an icc group gamma in chifans ioanas and kidas class of polymathcalc_textrss such as a polyhyperbolic group with no amenable factors in its composition series satisfies the following rigidity phenomenon discovered in dhi16 see also cdss17 every tensor decomposition of the ii_1 factor lgamma must arise from direct product decomposition of gamma by groups which are poly mathcalc_textrss through heavy usage and developments of the techniques in cdss15 we improve the second authors and their collaborators work in ckp14 by providing grouplevel criteria for determining whether a group von neumann algebra is prime lgamma is prime precisely when the group is indecomposable as a direct product of nonamenable groups we further demonstrate that all tensor decompositions of finite index subalgebras of lgamma correspond to a splitting of gamma as a product by groups which are also polymathcalc_textrss up to commensurability
[['we', 'demonstrate', 'von', 'neumann', 'algebra', 'arising', 'from', 'an', 'icc', 'group', 'gamma', 'in', 'chifans', 'ioanas', 'and', 'kidas', 'class', 'of', 'polymathcalc_textrss', 'such', 'as', 'a', 'polyhyperbolic', 'group', 'with', 'no', 'amenable', 'factors', 'in', 'its', 'composition', 'series', 'satisfies', 'the', 'following', 'rigidity', 'phenomenon', 'discovered', 'in', 'dhi16', 'see', 'also', 'cdss17', 'every', 'tensor', 'decomposition', 'of', 'the', 'ii_1', 'factor', 'lgamma', 'must', 'arise', 'from', 'direct', 'product', 'decomposition', 'of', 'gamma', 'by', 'groups', 'which', 'are', 'poly', 'mathcalc_textrss', 'through', 'heavy', 'usage', 'and', 'developments', 'of', 'the', 'techniques', 'in', 'cdss15', 'we', 'improve', 'the', 'second', 'authors', 'and', 'their', 'collaborators', 'work', 'in', 'ckp14', 'by', 'providing', 'grouplevel', 'criteria', 'for', 'determining', 'whether', 'a', 'group', 'von', 'neumann', 'algebra', 'is', 'prime', 'lgamma', 'is', 'prime', 'precisely', 'when', 'the', 'group', 'is', 'indecomposable', 'as', 'a', 'direct', 'product', 'of', 'nonamenable', 'groups', 'we', 'further', 'demonstrate', 'that', 'all', 'tensor', 'decompositions', 'of', 'finite', 'index', 'subalgebras', 'of', 'lgamma', 'correspond', 'to', 'a', 'splitting', 'of', 'gamma', 'as', 'a', 'product', 'by', 'groups', 'which', 'are', 'also', 'polymathcalc_textrss', 'up', 'to', 'commensurability']]
[-0.11845459396937404, 0.14579204569557644, -0.10844653488838694, 0.007437999504517116, -0.11016985167330806, -0.11022332634277426, 0.025274574034509882, 0.37304909889876464, -0.3393409393383595, -0.2309568373054482, 0.13927566706948658, -0.26315838448784273, -0.1309020757945963, 0.21933343090737858, -0.09047983388038541, -0.018838429111950234, 0.07341239532133445, 0.11121554121685524, -0.09054308681769054, -0.20856045204488075, 0.395797258178852, -0.002937969818088712, 0.2339229421281809, 0.03798765747848412, 0.04148160390542361, 0.0191820144140418, -0.0774063919333444, 0.03940068143487409, -0.1455412273233747, 0.107953035987178, 0.27698765796325775, 0.10614527199093414, 0.2554939838274035, -0.3388055126219431, -0.14290467602457257, 0.17011380403815513, 0.12469790141482878, -0.020133827637081318, -0.0396452623848007, -0.26852485830423195, 0.10369455211701384, -0.28122879663968214, -0.07756330375559628, -0.07494677482948948, 0.07991338461853456, -0.020513734962467268, -0.2569357122470071, 0.09480449648707281, 0.0794141098478998, 0.0934126106414782, -0.048416282935236726, -0.12024425869753612, -0.00207378216209295, 0.1578075607381913, 0.012212003660523265, -0.04151434785740423, 0.11071163342643084, -0.08264530662015296, -0.16692821744262523, 0.40334554244696663, -0.04153499882195847, -0.16801035480497428, 0.1554769331899782, -0.1858831845237401, -0.2072347082717317, 0.0941666097117021, 0.10271650450337894, 0.077333933172707, -0.05716225643107833, 0.15446272226804664, -0.11319124969262359, 0.08700834398421095, 0.07348361431850471, -0.018500483892621822, 0.07494058382724399, 0.0815591312745802, 0.08197019681118536, 0.13917318443713736, 0.06580452168819265, 0.06896526992415497, -0.3349293884348826, -0.22807318429071186, -0.1357447190886782, 0.1327390097844266, -0.09882075080500015, -0.16516964822379954, 0.35489613782239915, 0.028201336694030982, 0.1591365703363039, 0.05798174926093307, 0.19209421544835187, 0.0839866623560817, 0.11042142923698534, 0.08768648587747653, 0.1453297522663058, 0.24310298146430295, -0.048452183816824916, -0.17891380646155533, -0.010372065710396493, 0.16634984935998268]
1,802.09084
Trace semantics via determinization for probabilistic transition systems
A coalgebraic definition of finite and infinite trace semantics for probabilistic transition systems has recently been given using a certain Kleisli category. In this paper this semantics is developed using a coalgebraic method which is an instance of general determinization. Once applied to discrete systems, this point of view allows the exploitation of the determinized structure by up-to techniques. Thereby it becomes possible to algorithmically check the equivalence of two finite probabilistic transition systems.
cs.LO
a coalgebraic definition of finite and infinite trace semantics for probabilistic transition systems has recently been given using a certain kleisli category in this paper this semantics is developed using a coalgebraic method which is an instance of general determinization once applied to discrete systems this point of view allows the exploitation of the determinized structure by upto techniques thereby it becomes possible to algorithmically check the equivalence of two finite probabilistic transition systems
[['a', 'coalgebraic', 'definition', 'of', 'finite', 'and', 'infinite', 'trace', 'semantics', 'for', 'probabilistic', 'transition', 'systems', 'has', 'recently', 'been', 'given', 'using', 'a', 'certain', 'kleisli', 'category', 'in', 'this', 'paper', 'this', 'semantics', 'is', 'developed', 'using', 'a', 'coalgebraic', 'method', 'which', 'is', 'an', 'instance', 'of', 'general', 'determinization', 'once', 'applied', 'to', 'discrete', 'systems', 'this', 'point', 'of', 'view', 'allows', 'the', 'exploitation', 'of', 'the', 'determinized', 'structure', 'by', 'upto', 'techniques', 'thereby', 'it', 'becomes', 'possible', 'to', 'algorithmically', 'check', 'the', 'equivalence', 'of', 'two', 'finite', 'probabilistic', 'transition', 'systems']]
[-0.08991252131621681, 0.05467359221566349, -0.14017090882879454, 0.1042258168768918, -0.13534630884139523, -0.15057694544461933, 0.08430482783335941, 0.3569677739429313, -0.3415429929674074, -0.2654530850390123, 0.09729320103321476, -0.17901756059133755, -0.13990396887970133, 0.14657944834765954, -0.11338441130528981, 0.09655275349379391, 0.037459533560920404, 0.06063566494707924, -0.11621558937681462, -0.226700120917018, 0.36507112695206256, 0.03821483559000331, 0.28352048355028836, 0.03393011734619535, 0.13117674281317238, 0.01472210229651348, 0.0025313761387322402, 0.084727224151327, -0.09086499375612098, 0.14411421773351124, 0.3373523255797556, 0.1736541347219483, 0.30116190359694883, -0.36117879004293196, -0.188671598387127, 0.12082831262661195, 0.11067759005252172, 0.1534206469313594, -0.018866549321525806, -0.31493063502617785, 0.11576465810523243, -0.25794050715410627, -0.07566350491440578, -0.11070235796599977, 0.052387162262724864, -0.05346221712141021, -0.24125714684172683, -0.05741890789815099, 0.15061364366635177, 0.1298168941426116, -0.04446664860399717, -0.016854826427801083, 0.018931789248174912, 0.11044513019481422, -0.04229923010476538, 0.01138112529313091, 0.07386908534838743, -0.05085017611713123, -0.17329793713193992, 0.39712452022610484, -0.034993728830453916, -0.17340622318757548, 0.2134482025080738, -0.06411177251563482, -0.18150699921455737, 0.14341911430646842, 0.07721125512270609, 0.15770450683929674, -0.18566638801476565, 0.1699557032843586, -0.07156842783395503, 0.14417472174839507, 0.0753525280821565, 0.009904544747818413, 0.1955071289935527, 0.2000411390578626, 0.06477813079726656, 0.1967042195547775, 0.017986344713151355, -0.12753311569906292, -0.27620087501064344, -0.16861363816251224, -0.10537240079390137, 0.0071953385564926505, -0.053695604337082, -0.21264042336072117, 0.3482702031630922, 0.18675307859037374, 0.1502073064723329, 0.12779068178339936, 0.30076268032142844, 0.1533933657290716, 0.07297901483881916, 0.0027221682988031693, 0.1411148450570181, 0.18844756241447316, 0.09401178076183675, -0.11816215756619852, 0.09836751591993144, 0.15845780672404813]
1,802.09085
SgxPectre Attacks: Stealing Intel Secrets from SGX Enclaves via Speculative Execution
This paper presents SgxPectre Attacks that exploit the recently disclosed CPU bugs to subvert the confidentiality and integrity of SGX enclaves. Particularly, we show that when branch prediction of the enclave code can be influenced by programs outside the enclave, the control flow of the enclave program can be temporarily altered to execute instructions that lead to observable cache-state changes. An adversary observing such changes can learn secrets inside the enclave memory or its internal registers, thus completely defeating the confidentiality guarantee offered by SGX. To demonstrate the practicality of our SgxPectre Attacks, we have systematically explored the possible attack vectors of branch target injection, approaches to win the race condition during enclave's speculative execution, and techniques to automatically search for code patterns required for launching the attacks. Our study suggests that any enclave program could be vulnerable to SgxPectre Attacks since the desired code patterns are available in most SGX runtimes (e.g., Intel SGX SDK, Rust-SGX, and Graphene-SGX). Most importantly, we have applied SgxPectre Attacks to steal seal keys and attestation keys from Intel signed quoting enclaves. The seal key can be used to decrypt sealed storage outside the enclaves and forge valid sealed data; the attestation key can be used to forge attestation signatures. For these reasons, SgxPectre Attacks practically defeat SGX's security protection. This paper also systematically evaluates Intel's existing countermeasures against SgxPectre Attacks and discusses the security implications.
cs.CR
this paper presents sgxpectre attacks that exploit the recently disclosed cpu bugs to subvert the confidentiality and integrity of sgx enclaves particularly we show that when branch prediction of the enclave code can be influenced by programs outside the enclave the control flow of the enclave program can be temporarily altered to execute instructions that lead to observable cachestate changes an adversary observing such changes can learn secrets inside the enclave memory or its internal registers thus completely defeating the confidentiality guarantee offered by sgx to demonstrate the practicality of our sgxpectre attacks we have systematically explored the possible attack vectors of branch target injection approaches to win the race condition during enclaves speculative execution and techniques to automatically search for code patterns required for launching the attacks our study suggests that any enclave program could be vulnerable to sgxpectre attacks since the desired code patterns are available in most sgx runtimes eg intel sgx sdk rustsgx and graphenesgx most importantly we have applied sgxpectre attacks to steal seal keys and attestation keys from intel signed quoting enclaves the seal key can be used to decrypt sealed storage outside the enclaves and forge valid sealed data the attestation key can be used to forge attestation signatures for these reasons sgxpectre attacks practically defeat sgxs security protection this paper also systematically evaluates intels existing countermeasures against sgxpectre attacks and discusses the security implications
[['this', 'paper', 'presents', 'sgxpectre', 'attacks', 'that', 'exploit', 'the', 'recently', 'disclosed', 'cpu', 'bugs', 'to', 'subvert', 'the', 'confidentiality', 'and', 'integrity', 'of', 'sgx', 'enclaves', 'particularly', 'we', 'show', 'that', 'when', 'branch', 'prediction', 'of', 'the', 'enclave', 'code', 'can', 'be', 'influenced', 'by', 'programs', 'outside', 'the', 'enclave', 'the', 'control', 'flow', 'of', 'the', 'enclave', 'program', 'can', 'be', 'temporarily', 'altered', 'to', 'execute', 'instructions', 'that', 'lead', 'to', 'observable', 'cachestate', 'changes', 'an', 'adversary', 'observing', 'such', 'changes', 'can', 'learn', 'secrets', 'inside', 'the', 'enclave', 'memory', 'or', 'its', 'internal', 'registers', 'thus', 'completely', 'defeating', 'the', 'confidentiality', 'guarantee', 'offered', 'by', 'sgx', 'to', 'demonstrate', 'the', 'practicality', 'of', 'our', 'sgxpectre', 'attacks', 'we', 'have', 'systematically', 'explored', 'the', 'possible', 'attack', 'vectors', 'of', 'branch', 'target', 'injection', 'approaches', 'to', 'win', 'the', 'race', 'condition', 'during', 'enclaves', 'speculative', 'execution', 'and', 'techniques', 'to', 'automatically', 'search', 'for', 'code', 'patterns', 'required', 'for', 'launching', 'the', 'attacks', 'our', 'study', 'suggests', 'that', 'any', 'enclave', 'program', 'could', 'be', 'vulnerable', 'to', 'sgxpectre', 'attacks', 'since', 'the', 'desired', 'code', 'patterns', 'are', 'available', 'in', 'most', 'sgx', 'runtimes', 'eg', 'intel', 'sgx', 'sdk', 'rustsgx', 'and', 'graphenesgx', 'most', 'importantly', 'we', 'have', 'applied', 'sgxpectre', 'attacks', 'to', 'steal', 'seal', 'keys', 'and', 'attestation', 'keys', 'from', 'intel', 'signed', 'quoting', 'enclaves', 'the', 'seal', 'key', 'can', 'be', 'used', 'to', 'decrypt', 'sealed', 'storage', 'outside', 'the', 'enclaves', 'and', 'forge', 'valid', 'sealed', 'data', 'the', 'attestation', 'key', 'can', 'be', 'used', 'to', 'forge', 'attestation', 'signatures', 'for', 'these', 'reasons', 'sgxpectre', 'attacks', 'practically', 'defeat', 'sgxs', 'security', 'protection', 'this', 'paper', 'also', 'systematically', 'evaluates', 'intels', 'existing', 'countermeasures', 'against', 'sgxpectre', 'attacks', 'and', 'discusses', 'the', 'security', 'implications']]
[-0.18158806396412408, 0.01229757933088682, -0.10520122513911122, 0.08341294946962374, -0.12564025283282762, -0.30652850367536555, 0.12103050756552887, 0.3515246624318175, -0.2922771010455354, -0.3335900202739982, 0.17775024390803837, -0.2788092826968913, -0.08686984310081172, 0.1995942094548825, -0.17269655234713155, 0.12133054720267336, 0.04136833310479046, -0.04274666143325056, 0.0392790712321108, -0.3303561761048033, 0.2614224441034321, 0.09584751226796918, 0.28945222755336897, 0.0981258867922601, -0.00228099456193194, -0.02228235950833034, 0.01140005956912275, -0.06474705802111004, -0.046564818257857396, 0.06962403956823321, 0.32898882250850575, 0.29154547173367185, 0.2932737520956902, -0.4941511553382769, -0.11999371753371113, 0.0849138935051826, 0.13753169636244889, 0.13591415849697316, -0.05438625858283264, -0.35885144481598097, 0.1796910731837674, -0.2901016525653756, -0.09340394750709227, -0.13960160244475872, -0.04984170228942383, 0.00017570387422082757, -0.2137040976042489, -0.10475905624527879, 0.03778612084865192, 0.043802782430569745, 0.033073583819626884, -0.04158071386546515, -0.05672119876499975, 0.17811724094038028, 0.04187960899740002, 0.015343903702191651, 0.2753680678354942, -0.08701818086019836, -0.17195483121114039, 0.3349659029601801, 0.01928036550759423, -0.1344253395081144, 0.15587148000892886, 0.025923989253631066, -0.12859381213387694, 0.07467498309609347, 0.22530056901406254, 0.0663630094515301, -0.14413047451496697, 0.01832334558819075, 0.011234561690052068, 0.2575850354240166, 0.08836097617767849, 0.06448751032214173, 0.19766797602794836, 0.11295402126984598, 0.04432247566083633, 0.16290129238498646, -0.05941747715869536, -0.06281873761034697, -0.2302037372078958, -0.1650904181807843, -0.11875947700166774, -0.02152421137808078, -0.025445909155598804, -0.12369211909634938, 0.3488914282162832, 0.28480648493199046, 0.07307861147928316, 0.04688756482057501, 0.4516481265067794, -0.06134527840643438, 0.1937569069038613, 0.23490769383965232, 0.18131107694467358, -0.045050379755097444, 0.11856994594500185, -0.1827688357161407, 0.26292801796108906, -0.05334792869759309]
1,802.09086
Conditionally Independent Multiresolution Gaussian Processes
The multiresolution Gaussian process (GP) has gained increasing attention as a viable approach towards improving the quality of approximations in GPs that scale well to large-scale data. Most of the current constructions assume full independence across resolutions. This assumption simplifies the inference, but it underestimates the uncertainties in transitioning from one resolution to another. This in turn results in models which are prone to overfitting in the sense of excessive sensitivity to the chosen resolution, and predictions which are non-smooth at the boundaries. Our contribution is a new construction which instead assumes conditional independence among GPs across resolutions. We show that relaxing the full independence assumption enables robustness against overfitting, and that it delivers predictions that are smooth at the boundaries. Our new model is compared against current state of the art on 2 synthetic and 9 real-world datasets. In most cases, our new conditionally independent construction performed favorably when compared against models based on the full independence assumption. In particular, it exhibits little to no signs of overfitting.
stat.ML
the multiresolution gaussian process gp has gained increasing attention as a viable approach towards improving the quality of approximations in gps that scale well to largescale data most of the current constructions assume full independence across resolutions this assumption simplifies the inference but it underestimates the uncertainties in transitioning from one resolution to another this in turn results in models which are prone to overfitting in the sense of excessive sensitivity to the chosen resolution and predictions which are nonsmooth at the boundaries our contribution is a new construction which instead assumes conditional independence among gps across resolutions we show that relaxing the full independence assumption enables robustness against overfitting and that it delivers predictions that are smooth at the boundaries our new model is compared against current state of the art on 2 synthetic and 9 realworld datasets in most cases our new conditionally independent construction performed favorably when compared against models based on the full independence assumption in particular it exhibits little to no signs of overfitting
[['the', 'multiresolution', 'gaussian', 'process', 'gp', 'has', 'gained', 'increasing', 'attention', 'as', 'a', 'viable', 'approach', 'towards', 'improving', 'the', 'quality', 'of', 'approximations', 'in', 'gps', 'that', 'scale', 'well', 'to', 'largescale', 'data', 'most', 'of', 'the', 'current', 'constructions', 'assume', 'full', 'independence', 'across', 'resolutions', 'this', 'assumption', 'simplifies', 'the', 'inference', 'but', 'it', 'underestimates', 'the', 'uncertainties', 'in', 'transitioning', 'from', 'one', 'resolution', 'to', 'another', 'this', 'in', 'turn', 'results', 'in', 'models', 'which', 'are', 'prone', 'to', 'overfitting', 'in', 'the', 'sense', 'of', 'excessive', 'sensitivity', 'to', 'the', 'chosen', 'resolution', 'and', 'predictions', 'which', 'are', 'nonsmooth', 'at', 'the', 'boundaries', 'our', 'contribution', 'is', 'a', 'new', 'construction', 'which', 'instead', 'assumes', 'conditional', 'independence', 'among', 'gps', 'across', 'resolutions', 'we', 'show', 'that', 'relaxing', 'the', 'full', 'independence', 'assumption', 'enables', 'robustness', 'against', 'overfitting', 'and', 'that', 'it', 'delivers', 'predictions', 'that', 'are', 'smooth', 'at', 'the', 'boundaries', 'our', 'new', 'model', 'is', 'compared', 'against', 'current', 'state', 'of', 'the', 'art', 'on', '2', 'synthetic', 'and', '9', 'realworld', 'datasets', 'in', 'most', 'cases', 'our', 'new', 'conditionally', 'independent', 'construction', 'performed', 'favorably', 'when', 'compared', 'against', 'models', 'based', 'on', 'the', 'full', 'independence', 'assumption', 'in', 'particular', 'it', 'exhibits', 'little', 'to', 'no', 'signs', 'of', 'overfitting']]
[-0.042887311087116686, 0.027209264463221534, -0.07504352911777751, 0.08328318431566908, -0.0746485581483758, -0.13258202268863262, 0.042023478209498456, 0.38825757357639057, -0.2385952280622152, -0.3204272657346267, 0.12145475765825221, -0.25341323829502604, -0.11842099455400155, 0.21522011752267914, -0.12008957679141886, 0.05374170017853026, 0.10528000917825737, 0.0017528997888490998, -0.07118290087577374, -0.27793865907143733, 0.30177459778032023, 0.09324083151158012, 0.36664747547071713, 0.00929739546355724, 0.09848684790480838, -0.018441702549197, -0.06392344623974927, 0.003119706373996106, -0.06899595167849505, 0.11234825208353308, 0.23515663507241052, 0.13842758130637436, 0.2834525944543837, -0.4010382162836882, -0.23627130025632667, 0.10245860919677349, 0.11073118902346087, 0.13499591232164826, -0.0009322861642108338, -0.269719258788422, 0.10883247713453671, -0.1478855807730961, -0.09722131189818566, -0.10472193259481319, -0.02971641958509324, -0.010105261956644658, -0.2947361198523958, 0.07898426271242107, 0.06919940460415436, 0.038608954982424275, -0.01888928815485502, -0.14270488206109794, -0.03142132561312184, 0.0995190402779786, 0.08543747340755388, 0.03220057054340134, 0.10953778691986608, -0.15466738006474792, -0.10897904964778352, 0.34106236694590053, -0.05607631602586308, -0.23420016672021363, 0.25570291166810993, -0.11500961523084245, -0.17803586820504191, 0.14233171108548018, 0.13679639317547165, 0.09162073418740514, -0.09042502861353224, 0.06406603440726397, -0.01789922989662406, 0.18343472971509284, 0.05789892683659829, 0.015437924229407672, 0.1549552755220931, 0.19642333336141424, 0.07623807512039109, 0.10377591521721664, -0.09765889590672223, -0.1414692399929658, -0.2925659208861593, -0.061963069661501134, -0.17808902018962527, 0.015987627074596358, -0.11557093828328618, -0.15758939304515807, 0.3721378432922947, 0.2600354879003393, 0.2128756209138847, 0.09859272612902176, 0.35704221441989115, 0.047907811000918385, 0.08926887222044425, 0.0856735653241548, 0.2266433340491804, 0.08190302993308686, 0.06306676777112766, -0.15961067277501398, 0.1296972132249344, -0.03380944216317365]
1,802.09087
Cache-Aided Fog Radio Access Networks with Partial Connectivity
Centralized coded caching and delivery is studied for a partially-connected fog radio access network (F-RAN), whereby a set of H edge nodes (ENs) (without caches), connected to a cloud server via orthogonal fronthaul links, serve K users over the wireless edge. The cloud server is assumed to hold a library of N files, each of size F bits; and each user, equipped with a cache of size MF bits, is connected to a distinct set of r ENs; or equivalently, the wireless edge from the ENs to the users is modeled as a partial interference channel. The objective is to minimize the normalized delivery time (NDT), which refers to the worst case delivery latency, when each user requests a single file from the library. An achievable coded caching and transmission scheme is proposed, which utilizes maximum distance separable (MDS) codes in the placement phase, and real interference alignment (IA) in the delivery phase, and its achievable NDT is presented for r = 2 and arbitrary cache size M, and also for arbitrary values of r when the cache capacity is sufficiently large.
cs.IT math.IT
centralized coded caching and delivery is studied for a partiallyconnected fog radio access network fran whereby a set of h edge nodes ens without caches connected to a cloud server via orthogonal fronthaul links serve k users over the wireless edge the cloud server is assumed to hold a library of n files each of size f bits and each user equipped with a cache of size mf bits is connected to a distinct set of r ens or equivalently the wireless edge from the ens to the users is modeled as a partial interference channel the objective is to minimize the normalized delivery time ndt which refers to the worst case delivery latency when each user requests a single file from the library an achievable coded caching and transmission scheme is proposed which utilizes maximum distance separable mds codes in the placement phase and real interference alignment ia in the delivery phase and its achievable ndt is presented for r 2 and arbitrary cache size m and also for arbitrary values of r when the cache capacity is sufficiently large
[['centralized', 'coded', 'caching', 'and', 'delivery', 'is', 'studied', 'for', 'a', 'partiallyconnected', 'fog', 'radio', 'access', 'network', 'fran', 'whereby', 'a', 'set', 'of', 'h', 'edge', 'nodes', 'ens', 'without', 'caches', 'connected', 'to', 'a', 'cloud', 'server', 'via', 'orthogonal', 'fronthaul', 'links', 'serve', 'k', 'users', 'over', 'the', 'wireless', 'edge', 'the', 'cloud', 'server', 'is', 'assumed', 'to', 'hold', 'a', 'library', 'of', 'n', 'files', 'each', 'of', 'size', 'f', 'bits', 'and', 'each', 'user', 'equipped', 'with', 'a', 'cache', 'of', 'size', 'mf', 'bits', 'is', 'connected', 'to', 'a', 'distinct', 'set', 'of', 'r', 'ens', 'or', 'equivalently', 'the', 'wireless', 'edge', 'from', 'the', 'ens', 'to', 'the', 'users', 'is', 'modeled', 'as', 'a', 'partial', 'interference', 'channel', 'the', 'objective', 'is', 'to', 'minimize', 'the', 'normalized', 'delivery', 'time', 'ndt', 'which', 'refers', 'to', 'the', 'worst', 'case', 'delivery', 'latency', 'when', 'each', 'user', 'requests', 'a', 'single', 'file', 'from', 'the', 'library', 'an', 'achievable', 'coded', 'caching', 'and', 'transmission', 'scheme', 'is', 'proposed', 'which', 'utilizes', 'maximum', 'distance', 'separable', 'mds', 'codes', 'in', 'the', 'placement', 'phase', 'and', 'real', 'interference', 'alignment', 'ia', 'in', 'the', 'delivery', 'phase', 'and', 'its', 'achievable', 'ndt', 'is', 'presented', 'for', 'r', '2', 'and', 'arbitrary', 'cache', 'size', 'm', 'and', 'also', 'for', 'arbitrary', 'values', 'of', 'r', 'when', 'the', 'cache', 'capacity', 'is', 'sufficiently', 'large']]
[-0.30736477151307284, 0.025516361209839834, -0.010094638255254999, -0.01906657840951104, -0.06030594809392457, -0.2956505449288087, 0.18040808730691835, 0.3758756390654415, -0.2930465407401982, -0.26943006275931775, 0.07853580721479053, -0.28003947814226726, -0.08765935768033713, 0.07058331282624142, -0.11736721721817404, 0.05840402699401409, 0.022614790872667975, 0.093931436397197, 0.0028409914201053465, -0.31858053564824657, 0.26551075746017144, 0.10493107412771954, 0.3357045786540173, 0.038817011022513205, 0.022648617776383478, 0.0474735950132657, -0.042541380734980434, -0.014025769819690748, -0.09656482179216959, 0.05433345259198127, 0.35658092151565773, 0.22143747694070004, 0.23273126822664758, -0.4071684813651755, -0.19312404161473498, 0.07879395355876967, 0.1558427414593148, 0.001880738687397943, 0.001532558812271001, -0.2529767573944895, 0.17683773585569462, -0.23668270239359518, -0.004536336141211387, 0.09992799144855685, 0.008379214445195928, 0.07821988866237399, -0.38836946564814, -0.0812587408088109, -0.0578933541207299, -0.0015057087322769079, -0.010763996713588951, -0.0965730015301655, -0.009814285243557796, 0.1772410048442656, -0.044283228276589454, 0.06574510903617377, 0.1238029868372855, -0.06569669909456241, -0.0752005769243433, 0.4057227090896411, 0.023823797028738162, -0.19080420165677756, 0.10030633103274818, -0.05074442061724255, -0.06024371851647262, 0.16635406297986596, 0.2358841158151215, 0.054921835028046734, -0.1507446570214185, 0.07305708268910739, -0.04477312673592055, 0.19309591280183244, 0.12359389074620127, 0.12974953481114537, 0.15687085325232816, 0.18270771913436237, 0.16636318654768703, 0.15488989970991543, -0.10998076953775975, -0.075268205687486, -0.22014984161237985, -0.16225082271999952, -0.3005142370856352, 0.02968852774842092, -0.1650358467347224, -0.10387517336900062, 0.32342193618317333, 0.0476967255193843, 0.13969686921706514, 0.12581165620506593, 0.4231753035535964, 0.05653771351992657, 0.12131440920629204, 0.23365387845866753, 0.04581396536932466, 0.0780572963116989, 0.14702527427425846, -0.20008393542233915, 0.1014505042154239, 0.005239923186188574]
1,802.09088
Adversarially Learned One-Class Classifier for Novelty Detection
Novelty detection is the process of identifying the observation(s) that differ in some respect from the training observations (the target class). In reality, the novelty class is often absent during training, poorly sampled or not well defined. Therefore, one-class classifiers can efficiently model such problems. However, due to the unavailability of data from the novelty class, training an end-to-end deep network is a cumbersome task. In this paper, inspired by the success of generative adversarial networks for training deep models in unsupervised and semi-supervised settings, we propose an end-to-end architecture for one-class classification. Our architecture is composed of two deep networks, each of which trained by competing with each other while collaborating to understand the underlying concept in the target class, and then classify the testing samples. One network works as the novelty detector, while the other supports it by enhancing the inlier samples and distorting the outliers. The intuition is that the separability of the enhanced inliers and distorted outliers is much better than deciding on the original samples. The proposed framework applies to different related applications of anomaly and outlier detection in images and videos. The results on MNIST and Caltech-256 image datasets, along with the challenging UCSD Ped2 dataset for video anomaly detection illustrate that our proposed method learns the target class effectively and is superior to the baseline and state-of-the-art methods.
cs.CV
novelty detection is the process of identifying the observations that differ in some respect from the training observations the target class in reality the novelty class is often absent during training poorly sampled or not well defined therefore oneclass classifiers can efficiently model such problems however due to the unavailability of data from the novelty class training an endtoend deep network is a cumbersome task in this paper inspired by the success of generative adversarial networks for training deep models in unsupervised and semisupervised settings we propose an endtoend architecture for oneclass classification our architecture is composed of two deep networks each of which trained by competing with each other while collaborating to understand the underlying concept in the target class and then classify the testing samples one network works as the novelty detector while the other supports it by enhancing the inlier samples and distorting the outliers the intuition is that the separability of the enhanced inliers and distorted outliers is much better than deciding on the original samples the proposed framework applies to different related applications of anomaly and outlier detection in images and videos the results on mnist and caltech256 image datasets along with the challenging ucsd ped2 dataset for video anomaly detection illustrate that our proposed method learns the target class effectively and is superior to the baseline and stateoftheart methods
[['novelty', 'detection', 'is', 'the', 'process', 'of', 'identifying', 'the', 'observations', 'that', 'differ', 'in', 'some', 'respect', 'from', 'the', 'training', 'observations', 'the', 'target', 'class', 'in', 'reality', 'the', 'novelty', 'class', 'is', 'often', 'absent', 'during', 'training', 'poorly', 'sampled', 'or', 'not', 'well', 'defined', 'therefore', 'oneclass', 'classifiers', 'can', 'efficiently', 'model', 'such', 'problems', 'however', 'due', 'to', 'the', 'unavailability', 'of', 'data', 'from', 'the', 'novelty', 'class', 'training', 'an', 'endtoend', 'deep', 'network', 'is', 'a', 'cumbersome', 'task', 'in', 'this', 'paper', 'inspired', 'by', 'the', 'success', 'of', 'generative', 'adversarial', 'networks', 'for', 'training', 'deep', 'models', 'in', 'unsupervised', 'and', 'semisupervised', 'settings', 'we', 'propose', 'an', 'endtoend', 'architecture', 'for', 'oneclass', 'classification', 'our', 'architecture', 'is', 'composed', 'of', 'two', 'deep', 'networks', 'each', 'of', 'which', 'trained', 'by', 'competing', 'with', 'each', 'other', 'while', 'collaborating', 'to', 'understand', 'the', 'underlying', 'concept', 'in', 'the', 'target', 'class', 'and', 'then', 'classify', 'the', 'testing', 'samples', 'one', 'network', 'works', 'as', 'the', 'novelty', 'detector', 'while', 'the', 'other', 'supports', 'it', 'by', 'enhancing', 'the', 'inlier', 'samples', 'and', 'distorting', 'the', 'outliers', 'the', 'intuition', 'is', 'that', 'the', 'separability', 'of', 'the', 'enhanced', 'inliers', 'and', 'distorted', 'outliers', 'is', 'much', 'better', 'than', 'deciding', 'on', 'the', 'original', 'samples', 'the', 'proposed', 'framework', 'applies', 'to', 'different', 'related', 'applications', 'of', 'anomaly', 'and', 'outlier', 'detection', 'in', 'images', 'and', 'videos', 'the', 'results', 'on', 'mnist', 'and', 'caltech256', 'image', 'datasets', 'along', 'with', 'the', 'challenging', 'ucsd', 'ped2', 'dataset', 'for', 'video', 'anomaly', 'detection', 'illustrate', 'that', 'our', 'proposed', 'method', 'learns', 'the', 'target', 'class', 'effectively', 'and', 'is', 'superior', 'to', 'the', 'baseline', 'and', 'stateoftheart', 'methods']]
[-0.018867592737078668, -0.009249487998248596, -0.016523969661082244, 0.07989020690765755, -0.11357588417621123, -0.17796826895533335, 0.020578586742178433, 0.42539850806196533, -0.2531053634753658, -0.3424632725476598, 0.0834943369589746, -0.29201316775961056, -0.1978236092088951, 0.1737167188297543, -0.16258717710152268, 0.07334429539119204, 0.13531363552229272, 0.061990123889926405, -0.05709923632960353, -0.31563419168815016, 0.3405882859468046, 0.04556859919245148, 0.3762006652044753, -0.012072102111350331, 0.11739016980398446, -0.03507997682318091, -0.045500467060547736, -0.010954269147995445, 0.009796367426849126, 0.16135984032207892, 0.31529146030617994, 0.20709534478270344, 0.3089221405589746, -0.3661136214838674, -0.2369579323557102, 0.11981147138401865, 0.1295380782129036, 0.10237136433269674, -0.027283910658831397, -0.3864515036344528, 0.09892896892347683, -0.12228617839411729, -0.0010074833635654713, -0.10728895040073742, -0.03861052720652272, -0.025681609457565677, -0.29427181512324346, 0.04615857364816798, 0.09961795229102588, 0.03065462073104249, -0.07346320543231236, -0.11353755641314718, 0.02606642814249628, 0.12864345820517176, 0.05992338291511664, 0.07144545359537005, 0.13186646362973584, -0.20319211953940491, -0.1279523023042, 0.3646531903785136, -0.0526046518436245, -0.20221753852752347, 0.22589191323146224, -0.023875364929230678, -0.16071509742798903, 0.11488815706119769, 0.21090689939136306, 0.14797622870860827, -0.15859631841795313, -0.0051211191923357545, -0.04234125300827953, 0.1527985057855646, 0.01233629102508227, -0.023893518007049957, 0.15157415821294612, 0.2773079522934535, 0.03858811030164361, 0.1535262286127545, -0.1661755032464862, -0.05314135482327806, -0.22934217522127762, -0.09807263800563912, -0.23897467045734325, -0.046633010674203335, -0.09397523865873356, -0.13019338981041478, 0.40873232003792914, 0.23218462720306382, 0.22792215279717412, 0.11629648885844897, 0.35634774558142657, -0.011025743935153716, 0.1338391225420249, 0.08646822464316048, 0.20512700960104768, 0.007693661959427926, 0.08946540891917215, -0.1740483003314067, 0.1293115282472637, 0.024634801445321906]
1,802.09089
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection
Neural networks have become an increasingly popular solution for network intrusion detection systems (NIDS). Their capability of learning complex patterns and behaviors make them a suitable solution for differentiating between normal traffic and network attacks. However, a drawback of neural networks is the amount of resources needed to train them. Many network gateways and routers devices, which could potentially host an NIDS, simply do not have the memory or processing power to train and sometimes even execute such models. More importantly, the existing neural network solutions are trained in a supervised manner. Meaning that an expert must label the network traffic and update the model manually from time to time. In this paper, we present Kitsune: a plug and play NIDS which can learn to detect attacks on the local network, without supervision, and in an efficient online manner. Kitsune's core algorithm (KitNET) uses an ensemble of neural networks called autoencoders to collectively differentiate between normal and abnormal traffic patterns. KitNET is supported by a feature extraction framework which efficiently tracks the patterns of every network channel. Our evaluations show that Kitsune can detect various attacks with a performance comparable to offline anomaly detectors, even on a Raspberry PI. This demonstrates that Kitsune can be a practical and economic NIDS.
cs.CR cs.AI cs.LG
neural networks have become an increasingly popular solution for network intrusion detection systems nids their capability of learning complex patterns and behaviors make them a suitable solution for differentiating between normal traffic and network attacks however a drawback of neural networks is the amount of resources needed to train them many network gateways and routers devices which could potentially host an nids simply do not have the memory or processing power to train and sometimes even execute such models more importantly the existing neural network solutions are trained in a supervised manner meaning that an expert must label the network traffic and update the model manually from time to time in this paper we present kitsune a plug and play nids which can learn to detect attacks on the local network without supervision and in an efficient online manner kitsunes core algorithm kitnet uses an ensemble of neural networks called autoencoders to collectively differentiate between normal and abnormal traffic patterns kitnet is supported by a feature extraction framework which efficiently tracks the patterns of every network channel our evaluations show that kitsune can detect various attacks with a performance comparable to offline anomaly detectors even on a raspberry pi this demonstrates that kitsune can be a practical and economic nids
[['neural', 'networks', 'have', 'become', 'an', 'increasingly', 'popular', 'solution', 'for', 'network', 'intrusion', 'detection', 'systems', 'nids', 'their', 'capability', 'of', 'learning', 'complex', 'patterns', 'and', 'behaviors', 'make', 'them', 'a', 'suitable', 'solution', 'for', 'differentiating', 'between', 'normal', 'traffic', 'and', 'network', 'attacks', 'however', 'a', 'drawback', 'of', 'neural', 'networks', 'is', 'the', 'amount', 'of', 'resources', 'needed', 'to', 'train', 'them', 'many', 'network', 'gateways', 'and', 'routers', 'devices', 'which', 'could', 'potentially', 'host', 'an', 'nids', 'simply', 'do', 'not', 'have', 'the', 'memory', 'or', 'processing', 'power', 'to', 'train', 'and', 'sometimes', 'even', 'execute', 'such', 'models', 'more', 'importantly', 'the', 'existing', 'neural', 'network', 'solutions', 'are', 'trained', 'in', 'a', 'supervised', 'manner', 'meaning', 'that', 'an', 'expert', 'must', 'label', 'the', 'network', 'traffic', 'and', 'update', 'the', 'model', 'manually', 'from', 'time', 'to', 'time', 'in', 'this', 'paper', 'we', 'present', 'kitsune', 'a', 'plug', 'and', 'play', 'nids', 'which', 'can', 'learn', 'to', 'detect', 'attacks', 'on', 'the', 'local', 'network', 'without', 'supervision', 'and', 'in', 'an', 'efficient', 'online', 'manner', 'kitsunes', 'core', 'algorithm', 'kitnet', 'uses', 'an', 'ensemble', 'of', 'neural', 'networks', 'called', 'autoencoders', 'to', 'collectively', 'differentiate', 'between', 'normal', 'and', 'abnormal', 'traffic', 'patterns', 'kitnet', 'is', 'supported', 'by', 'a', 'feature', 'extraction', 'framework', 'which', 'efficiently', 'tracks', 'the', 'patterns', 'of', 'every', 'network', 'channel', 'our', 'evaluations', 'show', 'that', 'kitsune', 'can', 'detect', 'various', 'attacks', 'with', 'a', 'performance', 'comparable', 'to', 'offline', 'anomaly', 'detectors', 'even', 'on', 'a', 'raspberry', 'pi', 'this', 'demonstrates', 'that', 'kitsune', 'can', 'be', 'a', 'practical', 'and', 'economic', 'nids']]
[-0.12352973986658884, 0.023702948071652515, -0.08406746652903, 0.0723779227602597, -0.12409988446566074, -0.23109212823230144, 0.0627620097802016, 0.44966831888805553, -0.27578319307272703, -0.3255969370008955, 0.0961157779916806, -0.2871075958319476, -0.2376552756599056, 0.18418596379722105, -0.12155051140231643, 0.08196543401179178, 0.11605629279415443, 0.07000052256077743, 0.0018258737568892, -0.2571537970588599, 0.2807893558467959, 0.04725748079194539, 0.34404276837347353, 0.012118668146971344, 0.09281151834425432, -0.06662450166045719, -0.0023366458512109295, -0.011726466953826974, 0.012653764276035583, 0.14663182562532057, 0.35454669947436, 0.20911027015308323, 0.32528256808952, -0.5007912040780049, -0.24471807553419384, 0.16451807114057207, 0.16044628780654627, 0.11384646799854016, -0.010028108478996763, -0.33960466354563473, 0.1253357195623831, -0.21032491218352664, -0.012263701134178549, -0.16377161094549916, -0.0186425752584611, -0.0006218232953435053, -0.2778202909931253, -0.029215835066341258, 0.05653260973904165, 0.02174459865703675, 0.0010248221839291092, -0.030277682040876525, 0.002939393494732606, 0.16780511361413528, 0.012047799813093231, 0.029671531025509255, 0.1795472655819891, -0.18047552648481827, -0.14612327150073676, 0.3303423297393545, -0.014202786287841733, -0.20365620535491305, 0.2091826837881612, 0.043626825894894986, -0.12861901358082656, 0.10272274804998927, 0.263167888171305, 0.09123156379440413, -0.19970768396652658, -0.06111161843935423, -0.012609218666779894, 0.2228245530007542, 0.03043596290618829, 0.0012550285988113875, 0.19489800730205012, 0.2376956409563261, 0.08695909991980742, 0.09404626063404128, -0.1155576668772509, -0.045757588705470885, -0.1809931251530846, -0.12488628503223116, -0.17450158148869008, 0.014955012925441043, -0.08728726622855217, -0.15998012150036325, 0.3803519538675709, 0.1986644001821605, 0.2040847706347524, 0.12379543782956448, 0.3512249412195046, 0.014412013997474533, 0.1572875827809589, 0.1486308874791839, 0.17117288136170897, -0.0029194133236986283, 0.16112195940211343, -0.15200344748892888, 0.151172936813015, 0.009083384288034001]
1,802.0909
Exponential sums with reducible polynomials
Hooley proved that if $f\in \Bbb Z [X]$ is irreducible of degree $\ge 2$, then the fractions $\{ r/n\}$, $0<r<n$ with $f(r)\equiv 0\pmod n$, are uniformly distributed in $(0,1)$. In this paper we study such problems for reducible polynomials of degree $2$ and $3$ and for finite products of linear factors. In particular, we establish asymptotic formulas for exponential sums over these normalized roots.
math.NT
hooley proved that if fin bbb z x is irreducible of degree ge 2 then the fractions rn 0rn with frequiv 0pmod n are uniformly distributed in 01 in this paper we study such problems for reducible polynomials of degree 2 and 3 and for finite products of linear factors in particular we establish asymptotic formulas for exponential sums over these normalized roots
[['hooley', 'proved', 'that', 'if', 'fin', 'bbb', 'z', 'x', 'is', 'irreducible', 'of', 'degree', 'ge', '2', 'then', 'the', 'fractions', 'rn', '0rn', 'with', 'frequiv', '0pmod', 'n', 'are', 'uniformly', 'distributed', 'in', '01', 'in', 'this', 'paper', 'we', 'study', 'such', 'problems', 'for', 'reducible', 'polynomials', 'of', 'degree', '2', 'and', '3', 'and', 'for', 'finite', 'products', 'of', 'linear', 'factors', 'in', 'particular', 'we', 'establish', 'asymptotic', 'formulas', 'for', 'exponential', 'sums', 'over', 'these', 'normalized', 'roots']]
[-0.17768485581532853, 0.145517088259097, -0.01690269864668123, -0.009568891923141773, 0.023572402281045426, -0.14411285293639683, -0.01036993281144771, 0.36522536285862817, -0.3150404678871397, -0.1590635722319855, 0.10378025596785802, -0.30204446296222875, -0.12840446870636624, 0.194866011552818, -0.05350701970341196, 0.04802140125577323, -0.005557881927758944, 0.07439556601838987, -0.0921524755740691, -0.36254836032625104, 0.3153357784145466, -0.1269653501813529, 0.14005377154308754, 0.061757667539793934, 0.12326450361946567, 0.01609470041041247, -0.02112793823948405, -0.031196654667375517, -0.21118002534964692, 0.09200236349381873, 0.32786049815963525, 0.13501098021467933, 0.2573257194923573, -0.3547376826039103, -0.09092991298339406, 0.2773347248888162, 0.20972425032971945, -0.06361224429040659, -0.002117871215231106, -0.16391946814313044, 0.2029253989458084, -0.14184098493462413, -0.19559653227019017, -0.038719096596994, 0.13391083309457438, 0.11479201584245216, -0.35507454368911806, 0.0643338803965293, 0.15624683032758901, 0.13039197882667916, -0.02313812700726214, -0.22040297474223572, 0.03159866287357739, 0.051375876547249615, -0.007799506328664109, 0.04827922178417078, -0.013041704421725551, -0.08468148293599609, -0.07382817893884465, 0.3211992391858433, -0.0521976180607453, -0.246569514060851, 0.08849900589919969, -0.24685790021827475, -0.2016840816406747, 0.12062889073410483, 0.1891382123724382, 0.16457650633376153, -0.03945099296750593, 0.22797154166285316, -0.0960925560383523, 0.136603518404433, 0.15067523359855423, 0.012935800401524443, 0.07096265544962199, 0.012110946115991865, 0.06550656723194435, 0.12373523136264965, 0.019967217303690363, 0.026459452497666, -0.34634389817432243, -0.2029830983336099, -0.13960007853714412, 0.16560749989002943, -0.18678882088250726, -0.12230600139553674, 0.33596268824500136, 0.04270898014856655, 0.15421803725394803, 0.1938735991563709, 0.16816364016506027, 0.11648904443642155, -0.031512785535000386, 0.11272119045071256, 0.07648071883719598, 0.17756129460806241, -0.029914739085590374, -0.09034939746937302, 0.02008513881076799, 0.14380497624334254]
1,802.09091
Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks
Syntactic rules in natural language typically need to make reference to hierarchical sentence structure. However, the simple examples that language learners receive are often equally compatible with linear rules. Children consistently ignore these linear explanations and settle instead on the correct hierarchical one. This fact has motivated the proposal that the learner's hypothesis space is constrained to include only hierarchical rules. We examine this proposal using recurrent neural networks (RNNs), which are not constrained in such a way. We simulate the acquisition of question formation, a hierarchical transformation, in a fragment of English. We find that some RNN architectures tend to learn the hierarchical rule, suggesting that hierarchical cues within the language, combined with the implicit architectural biases inherent in certain RNNs, may be sufficient to induce hierarchical generalizations. The likelihood of acquiring the hierarchical generalization increased when the language included an additional cue to hierarchy in the form of subject-verb agreement, underscoring the role of cues to hierarchy in the learner's input.
cs.CL
syntactic rules in natural language typically need to make reference to hierarchical sentence structure however the simple examples that language learners receive are often equally compatible with linear rules children consistently ignore these linear explanations and settle instead on the correct hierarchical one this fact has motivated the proposal that the learners hypothesis space is constrained to include only hierarchical rules we examine this proposal using recurrent neural networks rnns which are not constrained in such a way we simulate the acquisition of question formation a hierarchical transformation in a fragment of english we find that some rnn architectures tend to learn the hierarchical rule suggesting that hierarchical cues within the language combined with the implicit architectural biases inherent in certain rnns may be sufficient to induce hierarchical generalizations the likelihood of acquiring the hierarchical generalization increased when the language included an additional cue to hierarchy in the form of subjectverb agreement underscoring the role of cues to hierarchy in the learners input
[['syntactic', 'rules', 'in', 'natural', 'language', 'typically', 'need', 'to', 'make', 'reference', 'to', 'hierarchical', 'sentence', 'structure', 'however', 'the', 'simple', 'examples', 'that', 'language', 'learners', 'receive', 'are', 'often', 'equally', 'compatible', 'with', 'linear', 'rules', 'children', 'consistently', 'ignore', 'these', 'linear', 'explanations', 'and', 'settle', 'instead', 'on', 'the', 'correct', 'hierarchical', 'one', 'this', 'fact', 'has', 'motivated', 'the', 'proposal', 'that', 'the', 'learners', 'hypothesis', 'space', 'is', 'constrained', 'to', 'include', 'only', 'hierarchical', 'rules', 'we', 'examine', 'this', 'proposal', 'using', 'recurrent', 'neural', 'networks', 'rnns', 'which', 'are', 'not', 'constrained', 'in', 'such', 'a', 'way', 'we', 'simulate', 'the', 'acquisition', 'of', 'question', 'formation', 'a', 'hierarchical', 'transformation', 'in', 'a', 'fragment', 'of', 'english', 'we', 'find', 'that', 'some', 'rnn', 'architectures', 'tend', 'to', 'learn', 'the', 'hierarchical', 'rule', 'suggesting', 'that', 'hierarchical', 'cues', 'within', 'the', 'language', 'combined', 'with', 'the', 'implicit', 'architectural', 'biases', 'inherent', 'in', 'certain', 'rnns', 'may', 'be', 'sufficient', 'to', 'induce', 'hierarchical', 'generalizations', 'the', 'likelihood', 'of', 'acquiring', 'the', 'hierarchical', 'generalization', 'increased', 'when', 'the', 'language', 'included', 'an', 'additional', 'cue', 'to', 'hierarchy', 'in', 'the', 'form', 'of', 'subjectverb', 'agreement', 'underscoring', 'the', 'role', 'of', 'cues', 'to', 'hierarchy', 'in', 'the', 'learners', 'input']]
[-0.057734653213707035, 0.05837876608024246, -0.06617058551887427, 0.16841754909430523, -0.18957416982921355, -0.16967919192054062, 0.07498034018097571, 0.4349212055351654, -0.32184778883527576, -0.3302996892459188, 0.042546497310791735, -0.21081861003410596, -0.2010793435277326, 0.10278968500441935, -0.11074297245666156, 0.019934403315826427, 0.11038733218179479, 0.05124822606623995, -0.05251185233173378, -0.274349614542529, 0.31028558813218327, 0.0701858918039711, 0.2836267434723355, -0.035168913473015186, 0.12155556035720161, -0.036240451443551876, -0.06632029538705625, -0.026946338682979677, -0.044993164855736865, 0.15837621460824083, 0.32761592449237553, 0.18455299916977141, 0.31395671316822477, -0.44892690095913373, -0.20600992121785147, 0.09592558057018859, 0.1561186505950119, 0.11432376013000273, 0.017022537178234227, -0.2731317615399331, 0.1033205261705386, -0.18901232376329005, -0.012151085731624826, -0.14205540099861158, -0.030540214891494052, -0.017068117103493697, -0.2851620890029443, 0.04093053923966488, 0.16764114714553294, 0.04387572355201665, -0.05198913078149495, -0.10403293215218315, -0.009802285343282884, 0.1216677148489673, 0.034155671277649104, 0.034249227856817235, 0.11430145916171898, -0.16063149274109742, -0.13637872781330274, 0.3686081028651972, -0.023593002566753493, -0.26069205551425373, 0.2011936868339537, -0.05885016573650157, -0.22506940045588267, 0.044407795297633286, 0.18115343601711414, 0.044477330286668594, -0.18265693832377752, 0.012798173255587077, -0.061823113587187846, 0.21155251489175153, 0.0906953752809347, 0.010583602445815373, 0.26476188801069017, 0.22537822203647825, -0.016087038282510693, 0.0910241973587809, -0.026343522574809704, -0.13124517352245976, -0.22152038654769582, -0.0793466071392541, -0.11405678491388088, -0.01679635364876523, -0.10509405801052361, -0.17601975516594326, 0.3536102685440286, 0.21196045444355535, 0.2204566548749493, 0.13254632935730706, 0.26748980681177664, 0.06283728142827463, 0.16906972673573056, 0.0387022926784949, 0.1664263536602593, 0.05709904588421841, 0.10208855202832928, -0.17541435062156796, 0.1293176673466991, 0.03909020110153439]
1,802.09092
Noncommutative quasi-resolutions
The notion of a noncommutative quasi-resolution is introduced for a noncommutative noetherian algebra with singularities, even for a non-Cohen-Macaulay algebra. If A is a commutative normal Gorenstein domain, then anoncommutative quasi-resolution of A naturally produces a noncommutative crepant resolution (NCCR) of A in the sense of Van den Bergh, and vice versa. Under some mild hypotheses, we prove that (i) in dimension two, all noncommutative quasi-resolutions of a given non-commutative algebra are Morita equivalent, and (ii) in dimension three, all noncommutative quasi-resolutions of a given non-commutative algebra are derived equivalent. These assertions generalize important results of Van den Bergh, Iyama-Reiten and Iyama-Wemyss in the commutative and central-finite cases.
math.RA
the notion of a noncommutative quasiresolution is introduced for a noncommutative noetherian algebra with singularities even for a noncohenmacaulay algebra if a is a commutative normal gorenstein domain then anoncommutative quasiresolution of a naturally produces a noncommutative crepant resolution nccr of a in the sense of van den bergh and vice versa under some mild hypotheses we prove that i in dimension two all noncommutative quasiresolutions of a given noncommutative algebra are morita equivalent and ii in dimension three all noncommutative quasiresolutions of a given noncommutative algebra are derived equivalent these assertions generalize important results of van den bergh iyamareiten and iyamawemyss in the commutative and centralfinite cases
[['the', 'notion', 'of', 'a', 'noncommutative', 'quasiresolution', 'is', 'introduced', 'for', 'a', 'noncommutative', 'noetherian', 'algebra', 'with', 'singularities', 'even', 'for', 'a', 'noncohenmacaulay', 'algebra', 'if', 'a', 'is', 'a', 'commutative', 'normal', 'gorenstein', 'domain', 'then', 'anoncommutative', 'quasiresolution', 'of', 'a', 'naturally', 'produces', 'a', 'noncommutative', 'crepant', 'resolution', 'nccr', 'of', 'a', 'in', 'the', 'sense', 'of', 'van', 'den', 'bergh', 'and', 'vice', 'versa', 'under', 'some', 'mild', 'hypotheses', 'we', 'prove', 'that', 'i', 'in', 'dimension', 'two', 'all', 'noncommutative', 'quasiresolutions', 'of', 'a', 'given', 'noncommutative', 'algebra', 'are', 'morita', 'equivalent', 'and', 'ii', 'in', 'dimension', 'three', 'all', 'noncommutative', 'quasiresolutions', 'of', 'a', 'given', 'noncommutative', 'algebra', 'are', 'derived', 'equivalent', 'these', 'assertions', 'generalize', 'important', 'results', 'of', 'van', 'den', 'bergh', 'iyamareiten', 'and', 'iyamawemyss', 'in', 'the', 'commutative', 'and', 'centralfinite', 'cases']]
[-0.1550009686779231, 0.024618523558601738, -0.10616559032350778, 0.1380381663632579, -0.08070149775594473, -0.24575528647750616, -0.09503187518566847, 0.3113594940607436, -0.34246521348599346, -0.14760507717728616, 0.10311559677589685, -0.20567382985726, -0.1630165622010827, 0.18164357274770737, -0.24751653918996452, -0.07978785160463303, 0.0286550486064516, 0.053857106589712204, -0.1490942977461964, -0.32824765014927837, 0.45932680562138556, 0.0043000257387757305, 0.20686049019452185, 0.0385729968175292, 0.13715810685418547, 0.03313752708490938, -0.05154489065520465, 0.09835040208779901, -0.18713361710346363, 0.07912120485678314, 0.3281861374899745, 0.06989164049969986, 0.2679554948443547, -0.3519740692246705, -0.07472288363613189, 0.14805361023172736, 0.1222216927818954, 0.0336552110966295, -0.0413084964978043, -0.28392294811084867, 0.11860415370203554, -0.24114341422915458, -0.12886469532735645, -0.05686734197195619, 0.09553335409611463, 0.019916414385661482, -0.2757238234393299, 0.02988833886804059, 0.1744470870681107, 0.13420056520961224, -0.08582372691482305, -0.029586225962266326, -0.05970344885950908, -0.0038326512672938406, -0.11300776952062734, -0.0196853250823915, 0.10105449949478498, -0.06742148631019518, -0.15319017468602397, 0.309649096778594, -0.000458307416702155, -0.23515431408770382, 0.14146759546129034, -0.18711741008795799, -0.16082004499388858, 0.06076330416835844, -0.06482075390405953, 0.14517353609437122, -0.01133477546274662, 0.2643279588711448, -0.1564172098133713, 0.05269064076244831, 0.17726352136582135, 0.04147121777292341, 0.1438789292424917, 0.05214717025868595, 0.046499697485705836, 0.104507167248521, 0.03920783711597323, -0.06303932880051434, -0.37182955724187194, -0.22470906077884137, -0.08895916708977893, 0.20432403622195125, -0.14271965719701257, -0.18687894648872316, 0.3783113453537226, 0.11210580128245055, 0.18675034986808897, 0.09197395777329803, 0.20394073948962613, 0.028104099738411607, 0.053360630222596225, 0.018483917973935605, 0.1433037527502165, 0.2635152079537511, 0.029837398221716285, -0.07910683289635927, -0.07188086754176766, 0.2293427780084312]
1,802.09093
Brunella-Khanedani-Suwa variational residues for invariant currents
In this work we prove a Brunella-Khanedani-Suwa variational type residue theorem for currents invariant by holomorphic foliations. As a consequence, we give conditions for the leaves of a singular holomorphic foliation to accumulate in the intersection of the singular set of the foliation with the support of an invariant current.
math.CV math.AG math.DS
in this work we prove a brunellakhanedanisuwa variational type residue theorem for currents invariant by holomorphic foliations as a consequence we give conditions for the leaves of a singular holomorphic foliation to accumulate in the intersection of the singular set of the foliation with the support of an invariant current
[['in', 'this', 'work', 'we', 'prove', 'a', 'brunellakhanedanisuwa', 'variational', 'type', 'residue', 'theorem', 'for', 'currents', 'invariant', 'by', 'holomorphic', 'foliations', 'as', 'a', 'consequence', 'we', 'give', 'conditions', 'for', 'the', 'leaves', 'of', 'a', 'singular', 'holomorphic', 'foliation', 'to', 'accumulate', 'in', 'the', 'intersection', 'of', 'the', 'singular', 'set', 'of', 'the', 'foliation', 'with', 'the', 'support', 'of', 'an', 'invariant', 'current']]
[-0.2362144529743462, 0.057156867321820605, -0.12539599535568635, 0.07480661505215554, -0.06854029464991573, -0.08545290155108182, -0.013193970446341805, 0.25752379897297645, -0.3012678072673782, -0.15345138303783476, 0.090780552899541, -0.23877470309332927, -0.1395887993656251, 0.16889709416700868, -0.13669935269851466, 0.06735482431796132, 0.0846448365826996, 0.13853324430861644, -0.10379960637881744, -0.2031065487892044, 0.4972505551211688, -0.030888000294109996, 0.1909789471525927, 0.1330010233713048, 0.15431328615819923, -0.0005547279320961358, 0.005954745852825593, -0.008500361273407328, -0.16269500726567848, 0.13029541815060894, 0.26785868687593206, 0.07766738885120318, 0.21757382435762151, -0.39617112005243493, -0.15260610597360194, 0.185268209106764, 0.11019249964619474, 0.048587020220501084, -0.020887401415871417, -0.2931069092093302, 0.13463773173565158, -0.09840493945747006, -0.27567421279999677, -0.11758899025390951, 0.014868788250094774, 0.00721982938750666, -0.24255356926242916, 0.042510882533174386, 0.1655535439067349, 0.16363764506745704, -0.10635845357438131, -0.04344398811535568, -0.07275533394612448, 0.03349921602413666, 0.05273533939402931, 0.09944032960362276, 0.14082253902998507, -0.09043048780734594, -0.1296433167323014, 0.2867710472996898, -0.12012682284931747, -0.2984476362412073, 0.10726855178268588, -0.14183337027587148, -0.22397698365075855, 0.11658881908776808, 0.13590211048722267, 0.19070922583341599, -0.1117068783437111, 0.15651046334556779, -0.08793819700462782, -0.003703305336209584, 0.1324398053467882, -0.026514395729315524, 0.17624040770971652, 0.11243838383531084, 0.19417060470702696, 0.13441842062664883, -0.03706661351405236, -0.043280615794415375, -0.39874620735645294, -0.2436444169262006, -0.1131687592524959, 0.2036713763919412, -0.07707489260985535, -0.2548909028992057, 0.4449088117107749, 0.06945983474427948, 0.28006155126162674, 0.14011984196852664, 0.23579065741172858, 0.08941200405522012, 0.07611174373982513, 0.08419075566438997, 0.18409297288376458, 0.18314800016601018, 0.021232305284665555, -0.10275863767696583, -0.026564134417900016, 0.17948919595504292]
1,802.09094
On the polynomial Wolff axioms
We confirm a conjecture of Guth concerning the maximal number of $\delta$-tubes, with $\delta$-separated directions, contained in the $\delta$-neighborhood of a real algebraic variety. Modulo a factor of $\delta^{-\varepsilon}$, we also prove Guth and Zahl's generalized version for semialgebraic sets. Although the applications are to be found in harmonic analysis, the proof will employ deep results from algebraic and differential geometry, including Tarski's projection theorem and Gromov's algebraic lemma.
math.CA math.AG
we confirm a conjecture of guth concerning the maximal number of deltatubes with deltaseparated directions contained in the deltaneighborhood of a real algebraic variety modulo a factor of deltavarepsilon we also prove guth and zahls generalized version for semialgebraic sets although the applications are to be found in harmonic analysis the proof will employ deep results from algebraic and differential geometry including tarskis projection theorem and gromovs algebraic lemma
[['we', 'confirm', 'a', 'conjecture', 'of', 'guth', 'concerning', 'the', 'maximal', 'number', 'of', 'deltatubes', 'with', 'deltaseparated', 'directions', 'contained', 'in', 'the', 'deltaneighborhood', 'of', 'a', 'real', 'algebraic', 'variety', 'modulo', 'a', 'factor', 'of', 'deltavarepsilon', 'we', 'also', 'prove', 'guth', 'and', 'zahls', 'generalized', 'version', 'for', 'semialgebraic', 'sets', 'although', 'the', 'applications', 'are', 'to', 'be', 'found', 'in', 'harmonic', 'analysis', 'the', 'proof', 'will', 'employ', 'deep', 'results', 'from', 'algebraic', 'and', 'differential', 'geometry', 'including', 'tarskis', 'projection', 'theorem', 'and', 'gromovs', 'algebraic', 'lemma']]
[-0.14523017846102662, -0.010549873432062347, -0.14257175615485346, 0.08093127354924731, -0.10300221744760432, -0.1004504305721425, 0.03168194404433427, 0.24067173451733062, -0.30981180054026053, -0.249014412292608, 0.1363417356624268, -0.26608005581724953, -0.15361661321195938, 0.2896937813048306, -0.17502411335761495, 0.03267271477071678, 0.06658211474731456, 0.026959451127742583, -0.07214479950968833, -0.2856161845317247, 0.36151706547859835, -0.07728828189711374, 0.2258203123586581, 0.14308893601136172, 0.0998626496293582, 0.058125503039371, -0.0837262533737778, 0.02498158671797308, -0.1601097619654063, 0.16167365580194576, 0.30071556995458465, 0.14530815815155887, 0.22398385096012668, -0.3767500619458802, -0.12697895659092703, 0.1451246598324574, 0.11250601995818536, 0.09233630582799807, -0.021174907537095028, -0.28225141763687134, 0.12224334441399311, -0.09014575112172786, -0.22698993141324642, -0.09902486885788248, 0.01843277830630541, 0.050234760774080366, -0.2268249326632084, 0.028785483907781514, 0.14762888392022647, 0.14646825005355127, -0.023998794892309782, -0.1350969461234533, 0.020236299647127882, -0.01747561417355695, 0.007862652857404421, 0.061492442810798395, 0.08499393009525888, -0.03429863104761085, -0.14959434299346278, 0.3271249962203643, -0.025044405952725998, -0.20041863828459205, 0.11773139431470019, -0.133866774959161, -0.21216259984409108, 0.06821149660904399, 0.13693956991054995, 0.10479756686425604, -0.03210078421226867, 0.1821051319446483, -0.15390649322173833, 0.11038200739387642, 0.17454482055515708, 0.014127906952875064, 0.08739105423035867, 0.08280184360388804, 0.09269492302829509, 0.1694798990690341, -0.010630799183512436, -0.06264047725947902, -0.30939066325149994, -0.17520041139933334, -0.14349128117935514, 0.12241123218315325, -0.1498267146108607, -0.16490072936422245, 0.36063134321011603, 0.07353890879654928, 0.15317164412151804, 0.12185104238896576, 0.25013789292151, 0.07209469594390076, 0.02911291762446875, 0.0857948415008757, 0.16025482896058, 0.26406489842680886, 0.03626871906111345, -0.09635747701737701, -0.024510383811395836, 0.20770097543786772]
1,802.09095
Ginzburg-Landau Type Approach to the 1+1 Gross Neveu Model - Beyond Lowest Non-Trivial Order
This paper presents a case study of the effects of increasing the order of a Ginzburg-Landau type expansion, by using the well known Gross-Neveu model in 1+1 dimensions as a test case. It is found that as the order of expansion increases, the predicted phase diagram increasingly resembles the known exact phase diagram. Finally, some properties of arbitrary large order phase diagrams are examined.
hep-th
this paper presents a case study of the effects of increasing the order of a ginzburglandau type expansion by using the well known grossneveu model in 11 dimensions as a test case it is found that as the order of expansion increases the predicted phase diagram increasingly resembles the known exact phase diagram finally some properties of arbitrary large order phase diagrams are examined
[['this', 'paper', 'presents', 'a', 'case', 'study', 'of', 'the', 'effects', 'of', 'increasing', 'the', 'order', 'of', 'a', 'ginzburglandau', 'type', 'expansion', 'by', 'using', 'the', 'well', 'known', 'grossneveu', 'model', 'in', '11', 'dimensions', 'as', 'a', 'test', 'case', 'it', 'is', 'found', 'that', 'as', 'the', 'order', 'of', 'expansion', 'increases', 'the', 'predicted', 'phase', 'diagram', 'increasingly', 'resembles', 'the', 'known', 'exact', 'phase', 'diagram', 'finally', 'some', 'properties', 'of', 'arbitrary', 'large', 'order', 'phase', 'diagrams', 'are', 'examined']]
[-0.16196495754411444, 0.1478018663910916, -0.052184103144099936, 0.10439942895027343, -0.04359833142370917, -0.06141937827487709, 0.05638848732087354, 0.2885065438458696, -0.18928414472043187, -0.3151282576727681, 0.15204532713505614, -0.2805369344423525, -0.22437210614589276, 0.14600202411747887, 0.027538017133338144, 0.0197391021574731, -0.029455841478920775, 0.07926355727249756, -0.12136103701413958, -0.23426321399165317, 0.31209902912087273, -0.0005685686483047903, 0.27680714923189953, -0.005303171071318502, 0.02979458794288803, -0.024092088910947496, -0.01210011485090945, 0.09134480298962444, -0.17109693899385547, 0.03294736046882463, 0.20628398416374694, -0.0005040131763962563, 0.18556350062135607, -0.33054859093681443, -0.2408342765265843, 0.09947588199793245, 0.21764741575316293, 0.12956847394707438, -0.04217794243595563, -0.2400515586414258, 0.04151291611196939, -0.21957325311086606, -0.2224865708485595, -0.07473368509090506, 0.007465933536877856, 0.024615674159576884, -0.26283618443994783, 0.08750135845912155, 0.043034372307374724, 0.05914885434322059, -0.037613062260788865, -0.10387742344391881, -0.022262473477894673, 0.11671862582443282, 0.04966174029141257, 0.07226541179625201, 0.02759163193695713, -0.16154214943162515, -0.09261878280085512, 0.4352697864960646, -0.05155021742666577, -0.11394294389720017, 0.1736475035577314, -0.1749253858361044, -0.09688426607544898, 0.10606182904302841, 0.09967648511519656, 0.14743349532363936, -0.12819471104739932, 0.1189083924255101, -0.0032627397595206276, 0.18191417423076928, 0.032597952005744446, 0.006898632116644876, 0.14241171459434554, 0.1957066128961742, -0.016747060828492977, 0.25971429464698303, -0.07529647099727299, -0.15193586207169574, -0.31952322454890236, -0.1483266867489874, -0.1598228305374505, -0.008211315078369807, -0.13243584203883074, -0.2163563926005736, 0.3733954831986921, 0.15004126160783926, 0.2022962872156313, 0.026029542161268182, 0.26919126514258096, 0.14699904717326717, 0.02909475628985092, 0.011339404351019766, 0.21834148275456755, 0.15181741073683952, 0.11262731280294247, -0.21003361058683367, 0.0785465947665216, 0.12182400922756642]
1,802.09096
Blindsight: Blinding EM Side-Channel Leakage using Built-In Fully Integrated Inductive Voltage Regulator
Modern high-performance as well as power-constrained System-on-Chips (SoC) are increasingly using hardware accelerated encryption engines to secure computation, memory access, and communication operations. The electromagnetic (EM) emission from a chip leaks information of the underlying logical operations and can be collected using low-cost non-invasive measurements. EM based side-channel attacks (EMSCA) have emerged as a major threat to security of encryption engines in a SoC. This paper presents the concept of Blindsight where a high-frequency inductive voltage regulator (IVR) integrated on the same chip with an encryption engine is used to increase resistance against EMSCA. High-frequency (~100MHz) IVRs are present in modern microprocessors to improve energy-efficiency. We show that an IVR with a randomized control loop (R-IVR) can reduce EMSCA as the integrated inductance acts as a strong EM emitter and blinds an adversary from EM emission of the encryption engine. The EM measurements are performed on a test-chip containing two architectures of a 128-bit Advanced Encryption Standard (AES) engine powered by a high-frequency R-IVR and under two attack scenarios, one, where an adversary gains complete physical access of the target device and the other, where the adversary is only in proximity of the device. In both attack modes, an adversary can observe information leakage in Test Vector Leakage Assessment (TVLA) test in a baseline IVR (B-IVR, without control loop randomization). However, we show that EM emission from the R-IVR blinds the attacker and significantly reduces SCA vulnerability of the AES engine. A range of practical side-channel analysis including TVLA, Correlation Electromagnetic Analysis (CEMA), and a template based CEMA shows that R-IVR can reduce information leakage and prevent key extraction even against a skilled adversary.
cs.CR
modern highperformance as well as powerconstrained systemonchips soc are increasingly using hardware accelerated encryption engines to secure computation memory access and communication operations the electromagnetic em emission from a chip leaks information of the underlying logical operations and can be collected using lowcost noninvasive measurements em based sidechannel attacks emsca have emerged as a major threat to security of encryption engines in a soc this paper presents the concept of blindsight where a highfrequency inductive voltage regulator ivr integrated on the same chip with an encryption engine is used to increase resistance against emsca highfrequency 100mhz ivrs are present in modern microprocessors to improve energyefficiency we show that an ivr with a randomized control loop rivr can reduce emsca as the integrated inductance acts as a strong em emitter and blinds an adversary from em emission of the encryption engine the em measurements are performed on a testchip containing two architectures of a 128bit advanced encryption standard aes engine powered by a highfrequency rivr and under two attack scenarios one where an adversary gains complete physical access of the target device and the other where the adversary is only in proximity of the device in both attack modes an adversary can observe information leakage in test vector leakage assessment tvla test in a baseline ivr bivr without control loop randomization however we show that em emission from the rivr blinds the attacker and significantly reduces sca vulnerability of the aes engine a range of practical sidechannel analysis including tvla correlation electromagnetic analysis cema and a template based cema shows that rivr can reduce information leakage and prevent key extraction even against a skilled adversary
[['modern', 'highperformance', 'as', 'well', 'as', 'powerconstrained', 'systemonchips', 'soc', 'are', 'increasingly', 'using', 'hardware', 'accelerated', 'encryption', 'engines', 'to', 'secure', 'computation', 'memory', 'access', 'and', 'communication', 'operations', 'the', 'electromagnetic', 'em', 'emission', 'from', 'a', 'chip', 'leaks', 'information', 'of', 'the', 'underlying', 'logical', 'operations', 'and', 'can', 'be', 'collected', 'using', 'lowcost', 'noninvasive', 'measurements', 'em', 'based', 'sidechannel', 'attacks', 'emsca', 'have', 'emerged', 'as', 'a', 'major', 'threat', 'to', 'security', 'of', 'encryption', 'engines', 'in', 'a', 'soc', 'this', 'paper', 'presents', 'the', 'concept', 'of', 'blindsight', 'where', 'a', 'highfrequency', 'inductive', 'voltage', 'regulator', 'ivr', 'integrated', 'on', 'the', 'same', 'chip', 'with', 'an', 'encryption', 'engine', 'is', 'used', 'to', 'increase', 'resistance', 'against', 'emsca', 'highfrequency', '100mhz', 'ivrs', 'are', 'present', 'in', 'modern', 'microprocessors', 'to', 'improve', 'energyefficiency', 'we', 'show', 'that', 'an', 'ivr', 'with', 'a', 'randomized', 'control', 'loop', 'rivr', 'can', 'reduce', 'emsca', 'as', 'the', 'integrated', 'inductance', 'acts', 'as', 'a', 'strong', 'em', 'emitter', 'and', 'blinds', 'an', 'adversary', 'from', 'em', 'emission', 'of', 'the', 'encryption', 'engine', 'the', 'em', 'measurements', 'are', 'performed', 'on', 'a', 'testchip', 'containing', 'two', 'architectures', 'of', 'a', '128bit', 'advanced', 'encryption', 'standard', 'aes', 'engine', 'powered', 'by', 'a', 'highfrequency', 'rivr', 'and', 'under', 'two', 'attack', 'scenarios', 'one', 'where', 'an', 'adversary', 'gains', 'complete', 'physical', 'access', 'of', 'the', 'target', 'device', 'and', 'the', 'other', 'where', 'the', 'adversary', 'is', 'only', 'in', 'proximity', 'of', 'the', 'device', 'in', 'both', 'attack', 'modes', 'an', 'adversary', 'can', 'observe', 'information', 'leakage', 'in', 'test', 'vector', 'leakage', 'assessment', 'tvla', 'test', 'in', 'a', 'baseline', 'ivr', 'bivr', 'without', 'control', 'loop', 'randomization', 'however', 'we', 'show', 'that', 'em', 'emission', 'from', 'the', 'rivr', 'blinds', 'the', 'attacker', 'and', 'significantly', 'reduces', 'sca', 'vulnerability', 'of', 'the', 'aes', 'engine', 'a', 'range', 'of', 'practical', 'sidechannel', 'analysis', 'including', 'tvla', 'correlation', 'electromagnetic', 'analysis', 'cema', 'and', 'a', 'template', 'based', 'cema', 'shows', 'that', 'rivr', 'can', 'reduce', 'information', 'leakage', 'and', 'prevent', 'key', 'extraction', 'even', 'against', 'a', 'skilled', 'adversary']]
[-0.1775600655856075, 0.011934572236006993, -0.06614705532716525, 0.05821411095522379, -0.07788626163017323, -0.2518663997554175, 0.09596960156849589, 0.35431978482316806, -0.24788976270276153, -0.3234430052215393, 0.13188753585087926, -0.2985544350088252, -0.11037811766409741, 0.2647103939662414, -0.10677596061353288, 0.07874356018774017, 0.01303502789438446, -0.01405866870778164, 0.015634551346579005, -0.18910978495127775, 0.2340480962769928, 0.1124939942597429, 0.3302648965248554, 0.017516843473225432, 0.08221958754701042, 0.020623743565247626, -0.013893789601370304, -0.017810064281287626, 0.006418995023039681, 0.07520049841309374, 0.2879088860901841, 0.1740282601521084, 0.30218865465871353, -0.4613404024953237, -0.18963926257115535, 0.06893118085221951, 0.12533610807489395, 0.10788573701363957, -0.08534984535461493, -0.30012014558318945, 0.0869051234417536, -0.2535223676762492, -0.010325040100778532, -0.06657257131352799, -0.020378012993878453, 0.018010255331467825, -0.2865553417945883, -0.03239611874085238, 0.04618632977051127, 0.06562175166656412, 0.013930349422923417, -0.03079726561284226, 0.01969985157981875, 0.13276543112164, -0.034714902493216404, 0.02856155338335339, 0.2565713322082652, -0.12644950063253466, -0.18505955503394025, 0.32402555373887126, -0.04560105114237, -0.13340907223604023, 0.13978029141500314, -0.01353868261346642, -0.08983598125070251, 0.11661721937978108, 0.20696351610532646, 0.057725403728794485, -0.15831164169068132, 0.035555006657488175, 0.02793731935388066, 0.25558362751082625, 0.044028356399553305, 0.09920503763260397, 0.16601741209376922, 0.17508137350396485, 0.0699742658100122, 0.17188862939326258, -0.12181557218291447, -0.059165159813353456, -0.2540852577095768, -0.15383227928420426, -0.1847280891842406, 0.07165065956939026, -0.05850006666410538, -0.16104226670709185, 0.3559587678125682, 0.2039306455925384, 0.114122677170308, 0.016483581564337237, 0.42900427054876955, 0.04251769354474319, 0.12336307218848801, 0.14648700512073187, 0.24561540840269797, 0.04405856037211213, 0.11581644653706191, -0.1938574348068294, 0.12371446496675477, -0.015591429766322933]
1,802.09097
Rotation Groups
A query, about the orbit $P{\cal W}$ in real 3-space of a point $P$ under an isometry group ${\cal W}$ generated by edge rotations of a tetrahedron, leads to contrasting notions, ${\cal W}$ versus ${\cal S}$, of "rotation group". The set R $=\{r_{{\sf A}_1},r_{{\sf A}_2}\}$ of rotations $r_{{\sf A} _i}$ about axes ${\sf A}_i$ generates two manifestations of an isometry group on $\Re^3$: (1). In the {\em stationary} group ${\cal S:=S}$(R), all axes {\sf B} are fixed under a rotation $r_{\sf A}$ about {\sf A}. (2). In the {\em peripatetic} group ${\cal W:=W}$(R), each $r_{\sf A}$ transforms every rotational axis ${\sf B\not=A}$. {\bf Theorem.} \ If the line ${\sf A}_1$ is skew to ${\sf A}_2$, if each $r_{{\sf A}_i}$ is of infinite order, and if $P\in\Re^3$, then both of the orbits $P{\cal S}$ and $P{\cal W}$ are dense in $\Re^3$.
math.MG
a query about the orbit pcal w in real 3space of a point p under an isometry group cal w generated by edge rotations of a tetrahedron leads to contrasting notions cal w versus cal s of rotation group the set r r_sf a_1r_sf a_2 of rotations r_sf a _i about axes sf a_i generates two manifestations of an isometry group on re3 1 in the em stationary group cal ssr all axes sf b are fixed under a rotation r_sf a about sf a 2 in the em peripatetic group cal wwr each r_sf a transforms every rotational axis sf bnota bf theorem if the line sf a_1 is skew to sf a_2 if each r_sf a_i is of infinite order and if pinre3 then both of the orbits pcal s and pcal w are dense in re3
[['a', 'query', 'about', 'the', 'orbit', 'pcal', 'w', 'in', 'real', '3space', 'of', 'a', 'point', 'p', 'under', 'an', 'isometry', 'group', 'cal', 'w', 'generated', 'by', 'edge', 'rotations', 'of', 'a', 'tetrahedron', 'leads', 'to', 'contrasting', 'notions', 'cal', 'w', 'versus', 'cal', 's', 'of', 'rotation', 'group', 'the', 'set', 'r', 'r_sf', 'a_1r_sf', 'a_2', 'of', 'rotations', 'r_sf', 'a', '_i', 'about', 'axes', 'sf', 'a_i', 'generates', 'two', 'manifestations', 'of', 'an', 'isometry', 'group', 'on', 're3', '1', 'in', 'the', 'em', 'stationary', 'group', 'cal', 'ssr', 'all', 'axes', 'sf', 'b', 'are', 'fixed', 'under', 'a', 'rotation', 'r_sf', 'a', 'about', 'sf', 'a', '2', 'in', 'the', 'em', 'peripatetic', 'group', 'cal', 'wwr', 'each', 'r_sf', 'a', 'transforms', 'every', 'rotational', 'axis', 'sf', 'bnota', 'bf', 'theorem', 'if', 'the', 'line', 'sf', 'a_1', 'is', 'skew', 'to', 'sf', 'a_2', 'if', 'each', 'r_sf', 'a_i', 'is', 'of', 'infinite', 'order', 'and', 'if', 'pinre3', 'then', 'both', 'of', 'the', 'orbits', 'pcal', 's', 'and', 'pcal', 'w', 'are', 'dense', 'in', 're3']]
[-0.23687863141574242, 0.18541058701898525, -0.02512993150977073, -0.020183293626609224, -0.05176343950787904, -0.1472856520726863, 0.027329115905040117, 0.4058808221033326, -0.2776074267509911, -0.14933053367529756, 0.08237145076919761, -0.2990238529940446, -0.05491939150141897, 0.0986965049058199, -0.0653627804790934, -0.05415698682751369, -0.024697303596918505, 0.1168022459829916, -0.13313421732573597, -0.21998463727499323, 0.2551257536884535, -0.10842090549154414, 0.18255519367478512, -0.06742901779038625, 0.08445874388433165, 0.039478750195768145, 0.026263831418731974, -0.020533022325899868, -0.16881265265660153, 0.048482752308525424, 0.19356155230629224, 0.11925867551385805, 0.20834958953782917, -0.3180840629349135, -0.050532264607372104, 0.15690710541136837, 0.13449188976514118, -0.031008282959185264, -0.002929341812894024, -0.2583818364922923, 0.15480106115617134, -0.16410139905875204, -0.09817653334423623, 0.011971707552395485, 0.20114402481251292, -0.031212549808400648, -0.32006267028412333, 0.05213061647696628, 0.11786311675828916, 0.0830001190373743, 0.013642652355203474, -0.09213908419047517, -0.1257803277336751, 0.03614707155739544, 0.0034392250770771946, 0.16407756212132948, 0.12450924435138909, -0.04962444682778032, -0.1278782546416753, 0.45848771300580765, -0.018246801824446907, -0.17891293420074766, 0.09243932483993747, -0.21498605585312125, -0.1589820022298092, 0.12469352792120642, 0.07617227961826656, 0.13421750653241935, -0.018975318371559736, 0.20116424813814876, -0.10530209539251195, 0.15116475626796105, 0.09608429084635443, 0.006306093351708518, 0.1576250713594534, 0.022818074941083236, 0.08110224276229187, 0.05413370947526009, -0.021745842500348334, 0.012179075700610324, -0.3761921026088573, -0.15903943403865453, -0.1248412138549611, 0.1444058846268389, -0.14747831137760337, -0.1261474065663707, 0.3316167464893725, -0.0038916959875711686, 0.24414698749573693, 0.04280581772672357, 0.1659264284496506, 0.050596405999601336, 0.03982803320589786, 0.12619001319528453, 0.09856594469467247, 0.21460955628124928, -0.08876152737411085, -0.23072297158133653, -0.0001904601852099101, 0.13655698426085075]
1,802.09098
SAFFRON: an adaptive algorithm for online control of the false discovery rate
In the online false discovery rate (FDR) problem, one observes a possibly infinite sequence of $p$-values $P_1,P_2,\dots$, each testing a different null hypothesis, and an algorithm must pick a sequence of rejection thresholds $\alpha_1,\alpha_2,\dots$ in an online fashion, effectively rejecting the $k$-th null hypothesis whenever $P_k \leq \alpha_k$. Importantly, $\alpha_k$ must be a function of the past, and cannot depend on $P_k$ or any of the later unseen $p$-values, and must be chosen to guarantee that for any time $t$, the FDR up to time $t$ is less than some pre-determined quantity $\alpha \in (0,1)$. In this work, we present a powerful new framework for online FDR control that we refer to as SAFFRON. Like older alpha-investing (AI) algorithms, SAFFRON starts off with an error budget, called alpha-wealth, that it intelligently allocates to different tests over time, earning back some wealth on making a new discovery. However, unlike older methods, SAFFRON's threshold sequence is based on a novel estimate of the alpha fraction that it allocates to true null hypotheses. In the offline setting, algorithms that employ an estimate of the proportion of true nulls are called adaptive methods, and SAFFRON can be seen as an online analogue of the famous offline Storey-BH adaptive procedure. Just as Storey-BH is typically more powerful than the Benjamini-Hochberg (BH) procedure under independence, we demonstrate that SAFFRON is also more powerful than its non-adaptive counterparts, such as LORD and other generalized alpha-investing algorithms. Further, a monotone version of the original AI algorithm is recovered as a special case of SAFFRON, that is often more stable and powerful than the original. Lastly, the derivation of SAFFRON provides a novel template for deriving new online FDR rules.
stat.ME cs.LG math.ST stat.TH
in the online false discovery rate fdr problem one observes a possibly infinite sequence of pvalues p_1p_2dots each testing a different null hypothesis and an algorithm must pick a sequence of rejection thresholds alpha_1alpha_2dots in an online fashion effectively rejecting the kth null hypothesis whenever p_k leq alpha_k importantly alpha_k must be a function of the past and cannot depend on p_k or any of the later unseen pvalues and must be chosen to guarantee that for any time t the fdr up to time t is less than some predetermined quantity alpha in 01 in this work we present a powerful new framework for online fdr control that we refer to as saffron like older alphainvesting ai algorithms saffron starts off with an error budget called alphawealth that it intelligently allocates to different tests over time earning back some wealth on making a new discovery however unlike older methods saffrons threshold sequence is based on a novel estimate of the alpha fraction that it allocates to true null hypotheses in the offline setting algorithms that employ an estimate of the proportion of true nulls are called adaptive methods and saffron can be seen as an online analogue of the famous offline storeybh adaptive procedure just as storeybh is typically more powerful than the benjaminihochberg bh procedure under independence we demonstrate that saffron is also more powerful than its nonadaptive counterparts such as lord and other generalized alphainvesting algorithms further a monotone version of the original ai algorithm is recovered as a special case of saffron that is often more stable and powerful than the original lastly the derivation of saffron provides a novel template for deriving new online fdr rules
[['in', 'the', 'online', 'false', 'discovery', 'rate', 'fdr', 'problem', 'one', 'observes', 'a', 'possibly', 'infinite', 'sequence', 'of', 'pvalues', 'p_1p_2dots', 'each', 'testing', 'a', 'different', 'null', 'hypothesis', 'and', 'an', 'algorithm', 'must', 'pick', 'a', 'sequence', 'of', 'rejection', 'thresholds', 'alpha_1alpha_2dots', 'in', 'an', 'online', 'fashion', 'effectively', 'rejecting', 'the', 'kth', 'null', 'hypothesis', 'whenever', 'p_k', 'leq', 'alpha_k', 'importantly', 'alpha_k', 'must', 'be', 'a', 'function', 'of', 'the', 'past', 'and', 'can', 'not', 'depend', 'on', 'p_k', 'or', 'any', 'of', 'the', 'later', 'unseen', 'pvalues', 'and', 'must', 'be', 'chosen', 'to', 'guarantee', 'that', 'for', 'any', 'time', 't', 'the', 'fdr', 'up', 'to', 'time', 't', 'is', 'less', 'than', 'some', 'predetermined', 'quantity', 'alpha', 'in', '01', 'in', 'this', 'work', 'we', 'present', 'a', 'powerful', 'new', 'framework', 'for', 'online', 'fdr', 'control', 'that', 'we', 'refer', 'to', 'as', 'saffron', 'like', 'older', 'alphainvesting', 'ai', 'algorithms', 'saffron', 'starts', 'off', 'with', 'an', 'error', 'budget', 'called', 'alphawealth', 'that', 'it', 'intelligently', 'allocates', 'to', 'different', 'tests', 'over', 'time', 'earning', 'back', 'some', 'wealth', 'on', 'making', 'a', 'new', 'discovery', 'however', 'unlike', 'older', 'methods', 'saffrons', 'threshold', 'sequence', 'is', 'based', 'on', 'a', 'novel', 'estimate', 'of', 'the', 'alpha', 'fraction', 'that', 'it', 'allocates', 'to', 'true', 'null', 'hypotheses', 'in', 'the', 'offline', 'setting', 'algorithms', 'that', 'employ', 'an', 'estimate', 'of', 'the', 'proportion', 'of', 'true', 'nulls', 'are', 'called', 'adaptive', 'methods', 'and', 'saffron', 'can', 'be', 'seen', 'as', 'an', 'online', 'analogue', 'of', 'the', 'famous', 'offline', 'storeybh', 'adaptive', 'procedure', 'just', 'as', 'storeybh', 'is', 'typically', 'more', 'powerful', 'than', 'the', 'benjaminihochberg', 'bh', 'procedure', 'under', 'independence', 'we', 'demonstrate', 'that', 'saffron', 'is', 'also', 'more', 'powerful', 'than', 'its', 'nonadaptive', 'counterparts', 'such', 'as', 'lord', 'and', 'other', 'generalized', 'alphainvesting', 'algorithms', 'further', 'a', 'monotone', 'version', 'of', 'the', 'original', 'ai', 'algorithm', 'is', 'recovered', 'as', 'a', 'special', 'case', 'of', 'saffron', 'that', 'is', 'often', 'more', 'stable', 'and', 'powerful', 'than', 'the', 'original', 'lastly', 'the', 'derivation', 'of', 'saffron', 'provides', 'a', 'novel', 'template', 'for', 'deriving', 'new', 'online', 'fdr', 'rules']]
[-0.07976534139690583, 0.08397197001682218, -0.113984596055082, 0.1163793098070976, -0.12159864393997587, -0.21758847736561185, 0.11652125075119514, 0.38162663569538924, -0.25042443155594496, -0.2885788133894296, 0.1271455873599431, -0.23563689157700815, -0.13883469395121842, 0.2325436021800261, -0.1152265244619111, 0.039082364450197034, 0.040587683904247926, 0.08724173157141828, -0.0379894958864695, -0.2932142220451024, 0.26095218570106593, 0.10514080349779417, 0.24589898650605313, -0.057504318004340756, 0.09926207232511723, 0.02798247401116659, -0.017619120976356182, 0.013457788803835696, -0.08611837282963582, 0.0839990395575971, 0.2453382951443664, 0.22970291378948351, 0.38663090816766454, -0.3574970326794689, -0.1546468934608603, 0.14839895597011174, 0.1700670574428986, 0.08695277445350666, -0.048852363543488354, -0.24337249493987326, 0.14184963295533173, -0.1510277198761722, -0.08741684517050433, -0.07279094870951351, -0.0007461379632793293, -0.010077413694976924, -0.3410523666618932, 0.06177530930606578, 0.07362636207245236, 0.0293537932380602, -0.03457573305501643, -0.1330530913884117, 0.043641446472105126, 0.10130073334195017, 0.07281505598549974, 0.05200120403120915, 0.12841919192663004, -0.09913192974298896, -0.15632418403233253, 0.3395292531105055, -0.03231140866937231, -0.18231071736258658, 0.16715613559421583, -0.07870137778724935, -0.16942234036421566, 0.13097665522060276, 0.16412005520059197, 0.17924586409429574, -0.16707641098722545, 0.034277183163161994, -0.04473741099903144, 0.17860728077658164, 0.07993183884621206, 0.005234264564511461, 0.1479151824630959, 0.1462158945366315, 0.1329914068493594, 0.11225330921466145, -0.06099387245890482, -0.047201484227485525, -0.2916768704687812, -0.17084078567363642, -0.17192900637282815, 0.05009698495484991, -0.11927858665317678, -0.15993263374000072, 0.3249378581970012, 0.15961627417266794, 0.17754380546514015, 0.13135131019837412, 0.305941644401384, 0.10776764706394676, 0.06717663684284544, 0.12231154740362873, 0.1906291784356311, 0.03286834713683187, 0.04406905789653757, -0.1421004868402699, 0.14149457902269627, 0.05892467681163301]
1,802.09099
Pareto optimal multi-robot motion planning
This paper studies a class of multi-robot coordination problems where a team of robots aim to reach their goal regions with minimum time and avoid collisions with obstacles and other robots. A novel numerical algorithm is proposed to identify the Pareto optimal solutions where no robot can unilaterally reduce its traveling time without extending others'. The consistent approximation of the algorithm in the epigraphical profile sense is guaranteed using set-valued numerical analysis. Experiments on an indoor multi-robot platform and computer simulations show the anytime property of the proposed algorithm; i.e., it is able to quickly return a feasible control policy that safely steers the robots to their goal regions and it keeps improving policy optimality if more time is given.
math.OC cs.RO cs.SY
this paper studies a class of multirobot coordination problems where a team of robots aim to reach their goal regions with minimum time and avoid collisions with obstacles and other robots a novel numerical algorithm is proposed to identify the pareto optimal solutions where no robot can unilaterally reduce its traveling time without extending others the consistent approximation of the algorithm in the epigraphical profile sense is guaranteed using setvalued numerical analysis experiments on an indoor multirobot platform and computer simulations show the anytime property of the proposed algorithm ie it is able to quickly return a feasible control policy that safely steers the robots to their goal regions and it keeps improving policy optimality if more time is given
[['this', 'paper', 'studies', 'a', 'class', 'of', 'multirobot', 'coordination', 'problems', 'where', 'a', 'team', 'of', 'robots', 'aim', 'to', 'reach', 'their', 'goal', 'regions', 'with', 'minimum', 'time', 'and', 'avoid', 'collisions', 'with', 'obstacles', 'and', 'other', 'robots', 'a', 'novel', 'numerical', 'algorithm', 'is', 'proposed', 'to', 'identify', 'the', 'pareto', 'optimal', 'solutions', 'where', 'no', 'robot', 'can', 'unilaterally', 'reduce', 'its', 'traveling', 'time', 'without', 'extending', 'others', 'the', 'consistent', 'approximation', 'of', 'the', 'algorithm', 'in', 'the', 'epigraphical', 'profile', 'sense', 'is', 'guaranteed', 'using', 'setvalued', 'numerical', 'analysis', 'experiments', 'on', 'an', 'indoor', 'multirobot', 'platform', 'and', 'computer', 'simulations', 'show', 'the', 'anytime', 'property', 'of', 'the', 'proposed', 'algorithm', 'ie', 'it', 'is', 'able', 'to', 'quickly', 'return', 'a', 'feasible', 'control', 'policy', 'that', 'safely', 'steers', 'the', 'robots', 'to', 'their', 'goal', 'regions', 'and', 'it', 'keeps', 'improving', 'policy', 'optimality', 'if', 'more', 'time', 'is', 'given']]
[-0.12031959589706578, 0.024813152823602042, -0.10412373448877285, 0.025452172196431398, -0.12842694219046583, -0.16642905191595977, 0.11661143189509554, 0.4274161159895205, -0.2709567139701297, -0.3339665895793587, 0.10764572552967971, -0.2451407749361048, -0.1604452401244392, 0.16383509713535507, -0.13048767675548636, 0.12963705847068924, 0.0988676649236974, 0.032424672367051245, 0.019549500289334294, -0.2583105889168413, 0.22081933023097614, 0.08587381402224613, 0.2551215195814924, 0.023347623382384577, 0.12841446227394043, -0.021225615210520726, 0.00994500375042359, 0.03502937489344428, -0.11429546266863326, 0.08208623766574116, 0.34338657931851535, 0.20964060874733453, 0.37365689243500433, -0.4282231972940887, -0.14678337462246419, 0.15996618602269638, 0.15573584700274903, 0.05916946082919215, -0.04770269326363632, -0.32966042309223365, 0.13804800813862433, -0.13797283566285234, -0.1570822710947444, -0.06228624131763354, -0.021843882153431575, 0.020813796482980252, -0.32629427053810406, -0.03791531494935043, 0.026173665886744857, 0.012881594360806048, -0.08660098265875907, -0.03227947923975686, 0.01722125036176294, 0.1642937135543131, 0.04039811264568319, 0.05690868329644824, 0.15566919248861572, -0.12923943118560904, -0.16211492133443245, 0.4093879597261548, 0.045106825088926904, -0.21678142149467022, 0.21038999629284566, -0.07445616361219436, -0.08574974334721143, 0.1453505936699609, 0.20977947043332582, 0.18174234358981872, -0.16479966018038492, 0.052736224150673174, -0.05640184173826128, 0.15637817687044542, 0.034188410761998966, -0.041059021629431904, 0.12378008760279044, 0.210516626186048, 0.23613552696770057, 0.11421314234661016, -0.01987618432419064, -0.15805389750748872, -0.24891474288888277, -0.12752921343708296, -0.17338028754262874, -0.0743103215538819, -0.09745354028176129, -0.08950308605562896, 0.3391716691432521, 0.21532768883820003, 0.13602316534767547, 0.14195919335422028, 0.3455275712757915, 0.07562515437214946, 0.027370033234668276, 0.17225525740068406, 0.2076289001813469, 0.014926256161804001, 0.12875888551740597, -0.25620187636232006, 0.13277493700249277, 0.03533436368452385]
1,802.091
Can a Chatbot Determine My Diet?: Addressing Challenges of Chatbot Application for Meal Recommendation
Poor nutrition can lead to reduced immunity, increased susceptibility to disease, impaired physical and mental development, and reduced productivity. A conversational agent can support people as a virtual coach, however building such systems still have its associated challenges and limitations. This paper describes the background and motivation for chatbot systems in the context of healthy nutrition recommendation. We discuss current challenges associated with chatbot application, we tackled technical, theoretical, behavioural, and social aspects of the challenges. We then propose a pipeline to be used as guidelines by developers to implement theoretically and technically robust chatbot systems.
cs.AI cs.HC
poor nutrition can lead to reduced immunity increased susceptibility to disease impaired physical and mental development and reduced productivity a conversational agent can support people as a virtual coach however building such systems still have its associated challenges and limitations this paper describes the background and motivation for chatbot systems in the context of healthy nutrition recommendation we discuss current challenges associated with chatbot application we tackled technical theoretical behavioural and social aspects of the challenges we then propose a pipeline to be used as guidelines by developers to implement theoretically and technically robust chatbot systems
[['poor', 'nutrition', 'can', 'lead', 'to', 'reduced', 'immunity', 'increased', 'susceptibility', 'to', 'disease', 'impaired', 'physical', 'and', 'mental', 'development', 'and', 'reduced', 'productivity', 'a', 'conversational', 'agent', 'can', 'support', 'people', 'as', 'a', 'virtual', 'coach', 'however', 'building', 'such', 'systems', 'still', 'have', 'its', 'associated', 'challenges', 'and', 'limitations', 'this', 'paper', 'describes', 'the', 'background', 'and', 'motivation', 'for', 'chatbot', 'systems', 'in', 'the', 'context', 'of', 'healthy', 'nutrition', 'recommendation', 'we', 'discuss', 'current', 'challenges', 'associated', 'with', 'chatbot', 'application', 'we', 'tackled', 'technical', 'theoretical', 'behavioural', 'and', 'social', 'aspects', 'of', 'the', 'challenges', 'we', 'then', 'propose', 'a', 'pipeline', 'to', 'be', 'used', 'as', 'guidelines', 'by', 'developers', 'to', 'implement', 'theoretically', 'and', 'technically', 'robust', 'chatbot', 'systems']]
[-0.08322209527341329, 0.0649193506372588, -0.025698440100920077, 0.11205547760255286, -0.16737803160989037, -0.18039390114912143, 0.08529363165750208, 0.3899749137150745, -0.25190803412503254, -0.31596717827293713, 0.13485241840802095, -0.2703005682657628, -0.2874906873330474, 0.20390127388721643, -0.21438950705730045, 0.07432197450361855, 0.09139893527996416, 7.887635244211803e-05, 0.0037722864702421552, -0.27678121566714253, 0.2953527282079449, 0.04802956084313337, 0.32630853654942865, 0.09637245703682613, 0.08302337880498574, -0.02779231528256787, -0.033065570358303376, -0.0003073885745834559, -0.07507747973310568, 0.18434475711850004, 0.3974027263466269, 0.24957452058636895, 0.3930912512150826, -0.46515133992458385, -0.18251702261234945, 0.06197314897629743, 0.15439824298179397, 0.0992775571163899, -0.05990516008265937, -0.34732458236006397, 0.07812587323132902, -0.26615536616494256, -0.15321119344541026, -0.12938308319765687, -0.028756225387041923, -0.008702433957902636, -0.2188509949677003, -0.0009404818702023476, 0.01146945179789327, 0.12200060118145, -0.04114844358628034, -0.11709888429807809, 0.019477617883239873, 0.23299886035783857, 0.08609159483845967, 0.02132406951568555, 0.18805540520406794, -0.20843437352596084, -0.17202594581370553, 0.39875825484341476, 0.011319270124658942, -0.18335685254714917, 0.23374269420552687, -0.017184653244233534, -0.16281834739493206, 0.0255065303996768, 0.24675326397361155, -0.0007585031368459264, -0.21464261958317365, -0.005081847129379942, 0.0860427185689332, 0.16280237379639098, 0.004079493205381368, 0.018695373825418454, 0.217954528365226, 0.2502859991994531, 0.03303149334533373, 0.10072881341936106, 0.03375916557342862, -0.036060959231690504, -0.1998266113223508, -0.16963395686858954, -0.06480444740736857, 0.034532433424222596, -0.004884317007054051, -0.1176327999849794, 0.3786309650555874, 0.25573906051674083, 0.09087567194607497, 0.03962260830303421, 0.3311099484465861, 0.04592299204523442, 0.05324470320192631, 0.03400076550800198, 0.1344187313952716, 0.019049941466619202, 0.19297297584125772, -0.21225350640694765, 0.14508515946605863, -0.04240422869437074]
1,802.09101
EuPRAXIA@SPARC_LAB: the high-brightness RF photo-injector layout proposal
At EuPRAXIA@SPARC_LAB, the unique combination of an advanced high-brightness RF injector and a plasma-based accelerator will drive a new multi-disciplinary user-facility. The facility, that is currently under study at INFN-LNF Laboratories (Frascati, Italy) in synergy with the EuPRAXIA collaboration, will operate the plasma-based accelerator in the external injection configuration. Since in this configuration the stability and reproducibility of the acceleration process in the plasma stage is strongly influenced by the RF-generated electron beam, the main challenge for the RF injector design is related to generating and handling high quality electron beams. In the last decades of R&D activity, the crucial role of high-brightness RF photo-injectors in the fields of radiation generation and advanced acceleration schemes has been largely established, making them effective candidates to drive plasma-based accelerators as pilots for user facilities. An RF injector consisting in a high-brightness S-band photo-injector followed by an advanced X-band linac has been proposed for the EuPRAXIA@SPARC_LAB project. The electron beam dynamics in the photo-injector has been explored by means of simulations, resulting in high-brightness, ultra-short bunches with up to 3 kA peak current at the entrance of the advanced X-band linac booster. The EuPRAXIA@SPARC_LAB high-brightness photo-injector is described here together with performance optimisation and sensitivity studies aiming to actual check the robustness and reliability of the desired working point.
physics.acc-ph
at eupraxiasparc_lab the unique combination of an advanced highbrightness rf injector and a plasmabased accelerator will drive a new multidisciplinary userfacility the facility that is currently under study at infnlnf laboratories frascati italy in synergy with the eupraxia collaboration will operate the plasmabased accelerator in the external injection configuration since in this configuration the stability and reproducibility of the acceleration process in the plasma stage is strongly influenced by the rfgenerated electron beam the main challenge for the rf injector design is related to generating and handling high quality electron beams in the last decades of rd activity the crucial role of highbrightness rf photoinjectors in the fields of radiation generation and advanced acceleration schemes has been largely established making them effective candidates to drive plasmabased accelerators as pilots for user facilities an rf injector consisting in a highbrightness sband photoinjector followed by an advanced xband linac has been proposed for the eupraxiasparc_lab project the electron beam dynamics in the photoinjector has been explored by means of simulations resulting in highbrightness ultrashort bunches with up to 3 ka peak current at the entrance of the advanced xband linac booster the eupraxiasparc_lab highbrightness photoinjector is described here together with performance optimisation and sensitivity studies aiming to actual check the robustness and reliability of the desired working point
[['at', 'eupraxiasparc_lab', 'the', 'unique', 'combination', 'of', 'an', 'advanced', 'highbrightness', 'rf', 'injector', 'and', 'a', 'plasmabased', 'accelerator', 'will', 'drive', 'a', 'new', 'multidisciplinary', 'userfacility', 'the', 'facility', 'that', 'is', 'currently', 'under', 'study', 'at', 'infnlnf', 'laboratories', 'frascati', 'italy', 'in', 'synergy', 'with', 'the', 'eupraxia', 'collaboration', 'will', 'operate', 'the', 'plasmabased', 'accelerator', 'in', 'the', 'external', 'injection', 'configuration', 'since', 'in', 'this', 'configuration', 'the', 'stability', 'and', 'reproducibility', 'of', 'the', 'acceleration', 'process', 'in', 'the', 'plasma', 'stage', 'is', 'strongly', 'influenced', 'by', 'the', 'rfgenerated', 'electron', 'beam', 'the', 'main', 'challenge', 'for', 'the', 'rf', 'injector', 'design', 'is', 'related', 'to', 'generating', 'and', 'handling', 'high', 'quality', 'electron', 'beams', 'in', 'the', 'last', 'decades', 'of', 'rd', 'activity', 'the', 'crucial', 'role', 'of', 'highbrightness', 'rf', 'photoinjectors', 'in', 'the', 'fields', 'of', 'radiation', 'generation', 'and', 'advanced', 'acceleration', 'schemes', 'has', 'been', 'largely', 'established', 'making', 'them', 'effective', 'candidates', 'to', 'drive', 'plasmabased', 'accelerators', 'as', 'pilots', 'for', 'user', 'facilities', 'an', 'rf', 'injector', 'consisting', 'in', 'a', 'highbrightness', 'sband', 'photoinjector', 'followed', 'by', 'an', 'advanced', 'xband', 'linac', 'has', 'been', 'proposed', 'for', 'the', 'eupraxiasparc_lab', 'project', 'the', 'electron', 'beam', 'dynamics', 'in', 'the', 'photoinjector', 'has', 'been', 'explored', 'by', 'means', 'of', 'simulations', 'resulting', 'in', 'highbrightness', 'ultrashort', 'bunches', 'with', 'up', 'to', '3', 'ka', 'peak', 'current', 'at', 'the', 'entrance', 'of', 'the', 'advanced', 'xband', 'linac', 'booster', 'the', 'eupraxiasparc_lab', 'highbrightness', 'photoinjector', 'is', 'described', 'here', 'together', 'with', 'performance', 'optimisation', 'and', 'sensitivity', 'studies', 'aiming', 'to', 'actual', 'check', 'the', 'robustness', 'and', 'reliability', 'of', 'the', 'desired', 'working', 'point']]
[-0.10957415401813178, 0.15980651717415137, -0.044471541143274895, 0.009826919543501449, -0.025897972454386544, -0.17150283333514688, -0.03383524517667976, 0.4272065103471836, -0.1941286279106182, -0.3105628682718238, 0.08561602521553922, -0.2686601899744873, 0.02487445239899201, 0.2896326398517758, 0.010126898287160097, 0.09786990849153251, 0.04859808517759231, -0.05203923004435671, -0.007545857734882456, -0.19203189707678855, 0.23880290815815608, 0.25991464049389984, 0.37385604297089453, 0.07284345806692727, 0.159333771581013, -0.006724445718391168, -0.0014924672736882048, -0.10304205761199695, -0.04849259783203086, 0.06021130689480734, 0.3221685570288258, 0.12042379158409748, 0.3157090942753984, -0.46107293728077525, -0.20518100429565655, 0.021930893015978146, 0.11255502257774645, 0.046155442427147496, -0.14373076067602036, -0.2458644299680872, 0.05892075185863101, -0.21354885138223104, -0.19160466028973636, 0.015898644459794522, -0.037864116945295276, 0.11095067359198094, -0.28182895708133937, -0.0873146873228872, 0.011583612919693963, 0.07456374438653622, -0.02142168172835329, -0.09915724351880288, 0.07862343490515426, 0.06745920133413573, 0.007102886471482838, 0.12459916410811037, 0.15596631538121805, -0.1257810582859424, -0.14730515509460854, 0.3348822112795766, -0.014307550296609543, -0.06517510185296709, 0.17549787842215445, -0.20032723359415464, -0.06985297501870544, 0.14973272188679776, 0.20415755022082163, 0.039642220031930825, -0.18481987716807444, 0.038704131727214854, 0.07685916730263662, 0.12935504690533456, 0.12716696216729165, -0.004054074880675735, 0.24200924069546687, 0.2679476856447704, 0.06653745150820256, 0.11792539057640629, -0.1446357515422142, 0.003683173541571492, -0.26572299235561325, -0.12758355394493195, -0.13594162542694987, 0.03035954046218844, 0.07086862322847712, -0.051977273380050926, 0.46073099596003747, 0.1300805005708396, 0.04371085672238929, -0.11812914656537746, 0.3828778563711409, 0.07150689648218435, 0.06547621626077246, 0.040799140465602485, 0.2830401969220594, 0.10875222579441164, 0.16886880084280378, -0.2358509448800828, 0.0334285095521188, -0.014281400509840139]
1,802.09102
Many-Particle Interferometry and Entanglement by Path Identity
We introduce a general scheme of many-particle interferometry in which two identical sources are used and "which-way information" is eliminated by making the paths of one or more particles identical (path identity). The scheme allows us to generate many-particle entangled states. We provide general forms of these states and show that they can be expressed as superpositions of various Dicke states. We illustrate cases in which the scheme produces maximally entangled two-qubit states (Bell states) and maximally three-tangled states (three-particle Greenberger-Horne-Zeilinger-class states). A striking feature of the scheme is that the entangled states can be manipulated without interacting with the entangled particles; for example, it is possible to switch between two distinct Bell states. Furthermore, each entangled state corresponds to a set of many-particle interference patterns. The visibility of these patterns and the amount of entanglement in a quantum state are connected to each other. The scheme also allows us to change the visibility and the amount of entanglement without interacting with the entangled particles and, therefore, has the potential to play an important role in quantum information science.
quant-ph
we introduce a general scheme of manyparticle interferometry in which two identical sources are used and whichway information is eliminated by making the paths of one or more particles identical path identity the scheme allows us to generate manyparticle entangled states we provide general forms of these states and show that they can be expressed as superpositions of various dicke states we illustrate cases in which the scheme produces maximally entangled twoqubit states bell states and maximally threetangled states threeparticle greenbergerhornezeilingerclass states a striking feature of the scheme is that the entangled states can be manipulated without interacting with the entangled particles for example it is possible to switch between two distinct bell states furthermore each entangled state corresponds to a set of manyparticle interference patterns the visibility of these patterns and the amount of entanglement in a quantum state are connected to each other the scheme also allows us to change the visibility and the amount of entanglement without interacting with the entangled particles and therefore has the potential to play an important role in quantum information science
[['we', 'introduce', 'a', 'general', 'scheme', 'of', 'manyparticle', 'interferometry', 'in', 'which', 'two', 'identical', 'sources', 'are', 'used', 'and', 'whichway', 'information', 'is', 'eliminated', 'by', 'making', 'the', 'paths', 'of', 'one', 'or', 'more', 'particles', 'identical', 'path', 'identity', 'the', 'scheme', 'allows', 'us', 'to', 'generate', 'manyparticle', 'entangled', 'states', 'we', 'provide', 'general', 'forms', 'of', 'these', 'states', 'and', 'show', 'that', 'they', 'can', 'be', 'expressed', 'as', 'superpositions', 'of', 'various', 'dicke', 'states', 'we', 'illustrate', 'cases', 'in', 'which', 'the', 'scheme', 'produces', 'maximally', 'entangled', 'twoqubit', 'states', 'bell', 'states', 'and', 'maximally', 'threetangled', 'states', 'threeparticle', 'greenbergerhornezeilingerclass', 'states', 'a', 'striking', 'feature', 'of', 'the', 'scheme', 'is', 'that', 'the', 'entangled', 'states', 'can', 'be', 'manipulated', 'without', 'interacting', 'with', 'the', 'entangled', 'particles', 'for', 'example', 'it', 'is', 'possible', 'to', 'switch', 'between', 'two', 'distinct', 'bell', 'states', 'furthermore', 'each', 'entangled', 'state', 'corresponds', 'to', 'a', 'set', 'of', 'manyparticle', 'interference', 'patterns', 'the', 'visibility', 'of', 'these', 'patterns', 'and', 'the', 'amount', 'of', 'entanglement', 'in', 'a', 'quantum', 'state', 'are', 'connected', 'to', 'each', 'other', 'the', 'scheme', 'also', 'allows', 'us', 'to', 'change', 'the', 'visibility', 'and', 'the', 'amount', 'of', 'entanglement', 'without', 'interacting', 'with', 'the', 'entangled', 'particles', 'and', 'therefore', 'has', 'the', 'potential', 'to', 'play', 'an', 'important', 'role', 'in', 'quantum', 'information', 'science']]
[-0.1471644814309038, 0.24827615947057796, -0.12324206743094712, 0.06044267728795839, 0.00199486268684268, -0.2136527487855552, 0.055044138459436134, 0.3675262488130122, -0.24094109782266054, -0.28738732397093275, 0.012731878799886185, -0.29571473469584786, -0.10521201196581778, 0.174606912220844, -0.01505607274481974, 0.08542961956627962, 0.09442614140199487, 0.031339417152681605, -0.011469272971297956, -0.23789323454243946, 0.3491608557879736, 0.0052932233689089786, 0.28955492801901145, 0.035001119730289035, 0.10644468307326742, 0.021793807272688818, 0.03482504484196335, -0.005645924490425716, -0.038335220996533144, 0.13410199805008943, 0.2872959722654294, 0.1522784937899244, 0.23050350827654287, -0.43873728955911717, -0.17692662712375998, 0.13782619550761024, 0.1249513989748528, 0.21952890205896844, 0.0037721933616623863, -0.35233620908847973, -0.017928662804602567, -0.18371423052118743, -0.14830521403254132, -0.1281224414120865, -0.005817269090836668, -0.04662575921876419, -0.2741505322993686, 0.08709477200840421, 0.037125774698679226, -0.039837904842728276, 0.013520924297508672, -0.02371256850465164, -0.03449372193410382, 0.16207789559453978, -0.07912820007120612, -0.01841262973303049, 0.10120734042293356, -0.14552767673937478, -0.18823145269968752, 0.3586264900563253, -0.003180776804285703, -0.2419628540624859, 0.2158118682245245, -0.10280867036179465, -0.08042570998323924, 0.10063524835474663, 0.12779786022469444, 0.10758397473011819, -0.12059170353926171, -0.011057464347357762, -0.05889858808473679, 0.19397909008229605, 0.0853721519911104, 0.18088875936494225, 0.22462752680702822, 0.045548576956330716, 0.10468265158979295, 0.22499092945225252, -0.0637252900096993, -0.16406225447581113, -0.3043653979939593, -0.2109646753692147, -0.21698029042553094, 0.061838620516115085, -0.04979218810084434, -0.10398668252519663, 0.42767631455347527, 0.11903187395389175, 0.15332157548390707, -0.04057111386551737, 0.22835386279275863, 0.09986698796512562, 0.05467063416647962, 0.06714327910311237, 0.2399444790336035, 0.1368468867385981, 0.02871712856783958, -0.22585433348750242, 0.05954980792604008, -0.0010167012270013828]
1,802.09103
Helical micropumps near surfaces
Recent experiments proposed to use confined bacteria in order to generate flows near surfaces. We develop a mathematical and a computational model of this fluid transport using a linear superposition of fundamental flow singularities. The rotation of a helical bacterial flagellum induces both a force and a torque on the surrounding fluid, both of which lead to a net flow along the surface. The combined flow is in general directed at an angle to the axis of the flagellar filament. The optimal pumping is thus achieved when bacteria are tilted with respect to the direction in which one wants to move the fluid, in good agreement with experimental results. We further investigate the optimal helical shapes to be used as micropumps near surfaces and show that bacterial flagella are nearly optimal, a result which could be relevant to the expansion of bacterial swarms.
physics.bio-ph cond-mat.soft physics.flu-dyn
recent experiments proposed to use confined bacteria in order to generate flows near surfaces we develop a mathematical and a computational model of this fluid transport using a linear superposition of fundamental flow singularities the rotation of a helical bacterial flagellum induces both a force and a torque on the surrounding fluid both of which lead to a net flow along the surface the combined flow is in general directed at an angle to the axis of the flagellar filament the optimal pumping is thus achieved when bacteria are tilted with respect to the direction in which one wants to move the fluid in good agreement with experimental results we further investigate the optimal helical shapes to be used as micropumps near surfaces and show that bacterial flagella are nearly optimal a result which could be relevant to the expansion of bacterial swarms
[['recent', 'experiments', 'proposed', 'to', 'use', 'confined', 'bacteria', 'in', 'order', 'to', 'generate', 'flows', 'near', 'surfaces', 'we', 'develop', 'a', 'mathematical', 'and', 'a', 'computational', 'model', 'of', 'this', 'fluid', 'transport', 'using', 'a', 'linear', 'superposition', 'of', 'fundamental', 'flow', 'singularities', 'the', 'rotation', 'of', 'a', 'helical', 'bacterial', 'flagellum', 'induces', 'both', 'a', 'force', 'and', 'a', 'torque', 'on', 'the', 'surrounding', 'fluid', 'both', 'of', 'which', 'lead', 'to', 'a', 'net', 'flow', 'along', 'the', 'surface', 'the', 'combined', 'flow', 'is', 'in', 'general', 'directed', 'at', 'an', 'angle', 'to', 'the', 'axis', 'of', 'the', 'flagellar', 'filament', 'the', 'optimal', 'pumping', 'is', 'thus', 'achieved', 'when', 'bacteria', 'are', 'tilted', 'with', 'respect', 'to', 'the', 'direction', 'in', 'which', 'one', 'wants', 'to', 'move', 'the', 'fluid', 'in', 'good', 'agreement', 'with', 'experimental', 'results', 'we', 'further', 'investigate', 'the', 'optimal', 'helical', 'shapes', 'to', 'be', 'used', 'as', 'micropumps', 'near', 'surfaces', 'and', 'show', 'that', 'bacterial', 'flagella', 'are', 'nearly', 'optimal', 'a', 'result', 'which', 'could', 'be', 'relevant', 'to', 'the', 'expansion', 'of', 'bacterial', 'swarms']]
[-0.14379050349165406, 0.14886249779730504, -0.09681597874024427, -0.01605188215421708, -0.07475184129511976, -0.1333158708525939, -0.0019352932923011013, 0.37650157898742626, -0.3073461846272637, -0.26624953174854504, 0.05810850908510856, -0.2545003843024842, -0.1606488419709714, 0.20927446486486995, -0.08314011291555175, 0.052753895812202245, 0.05241286949909103, 0.007345642907531945, 0.019003479150482096, -0.17608384455886336, 0.22541591159224353, 0.06525009914164569, 0.29621337756670857, 0.03244185216490414, 0.13375878799706697, -0.0403147012750794, 0.04790107358468475, 0.08515979819182125, -0.18428375642817715, 0.14037565517701678, 0.22896753648992862, -0.00667977775284252, 0.21225915117176264, -0.48200907323743913, -0.2258193757520562, 0.060888422481966825, 0.15936130616110522, 0.17394581006699847, -0.0527859197732491, -0.2173112768458424, 0.07031021780380002, -0.13633399144778927, -0.16743314874495244, -0.06245121124470802, -0.0019660587113194323, 0.05523464132802092, -0.2617519801625839, 0.08698887480390291, 0.05350165307266195, 0.06210000225557731, -0.07556986234027084, -0.03254276468708356, -0.07272920258330194, 0.14973223328503285, 0.10133115832540825, 0.08103680007902163, 0.197883124112386, -0.15438972361600742, -0.1133412379719369, 0.40321362023795404, -0.06508739004432634, -0.24344393392126043, 0.21160394755123718, -0.14505593065771608, -0.0493950948080087, 0.1556234111475361, 0.22323375628362377, 0.10906459536025678, -0.11008131176355812, -0.02593795469452438, -0.08147444492336232, 0.13534348876495567, 0.09128587134019635, -0.0791206418429652, 0.24588764558539733, 0.16420633646731192, 0.09695332400237008, 0.14544363739294605, -0.10339025890461162, -0.12357818171824816, -0.25105278487675464, -0.17108908004511694, -0.12715084527267495, 0.02285354030220867, -0.06429952869512925, -0.14941688931801103, 0.391506121057522, 0.09914357560992866, 0.21795209859322, 0.031681434961257283, 0.2873879575619956, 0.02836438160881374, 0.047372965663150475, 0.09608247473354002, 0.2683388161883279, 0.14312585307874592, 0.09641927004615952, -0.2746606690392315, 0.05574740985346554, 0.01570715858125603]
1,802.09104
A New Algorithm for Finding Closest Pair of Vectors
Given $n$ vectors $x_0, x_1, \ldots, x_{n-1}$ in $\{0,1\}^{m}$, how to find two vectors whose pairwise Hamming distance is minimum? This problem is known as the \emph{Closest Pair Problem}. If these vectors are generated uniformly at random except two of them are correlated with Pearson-correlation coefficient $\rho$, then the problem is called the \emph{Light Bulb Problem}. In this work, we propose a novel coding-based scheme for the Closest Pair Problem. We design both randomized and deterministic algorithms, which achieve the best-known running time when the length of input vectors $m$ is small and the minimum distance is very small compared to $m$. Specifically, the running time of our randomized algorithm is $O(n\log^{2}n\cdot 2^{c m} \cdot \mathrm{poly}(m))$ and the running time of our deterministic algorithm is $O(n\log{n}\cdot 2^{c' m} \cdot \mathrm{poly}(m))$, where $c$ and $c'$ are constants depending only on the (relative) distance of the closest pair. When applied to the Light Bulb Problem, our result yields state-of-the-art deterministic running time when the Pearson-correlation coefficient $\rho$ is very large. Specifically, when $\rho \geq 0.9933$, our deterministic algorithm runs faster than the previously best deterministic algorithm (Alman, SOSA 2019).
cs.DS cs.IT math.IT
given n vectors x_0 x_1 ldots x_n1 in 01m how to find two vectors whose pairwise hamming distance is minimum this problem is known as the emphclosest pair problem if these vectors are generated uniformly at random except two of them are correlated with pearsoncorrelation coefficient rho then the problem is called the emphlight bulb problem in this work we propose a novel codingbased scheme for the closest pair problem we design both randomized and deterministic algorithms which achieve the bestknown running time when the length of input vectors m is small and the minimum distance is very small compared to m specifically the running time of our randomized algorithm is onlog2ncdot 2c m cdot mathrmpolym and the running time of our deterministic algorithm is onlogncdot 2c m cdot mathrmpolym where c and c are constants depending only on the relative distance of the closest pair when applied to the light bulb problem our result yields stateoftheart deterministic running time when the pearsoncorrelation coefficient rho is very large specifically when rho geq 09933 our deterministic algorithm runs faster than the previously best deterministic algorithm alman sosa 2019
[['given', 'n', 'vectors', 'x_0', 'x_1', 'ldots', 'x_n1', 'in', '01m', 'how', 'to', 'find', 'two', 'vectors', 'whose', 'pairwise', 'hamming', 'distance', 'is', 'minimum', 'this', 'problem', 'is', 'known', 'as', 'the', 'emphclosest', 'pair', 'problem', 'if', 'these', 'vectors', 'are', 'generated', 'uniformly', 'at', 'random', 'except', 'two', 'of', 'them', 'are', 'correlated', 'with', 'pearsoncorrelation', 'coefficient', 'rho', 'then', 'the', 'problem', 'is', 'called', 'the', 'emphlight', 'bulb', 'problem', 'in', 'this', 'work', 'we', 'propose', 'a', 'novel', 'codingbased', 'scheme', 'for', 'the', 'closest', 'pair', 'problem', 'we', 'design', 'both', 'randomized', 'and', 'deterministic', 'algorithms', 'which', 'achieve', 'the', 'bestknown', 'running', 'time', 'when', 'the', 'length', 'of', 'input', 'vectors', 'm', 'is', 'small', 'and', 'the', 'minimum', 'distance', 'is', 'very', 'small', 'compared', 'to', 'm', 'specifically', 'the', 'running', 'time', 'of', 'our', 'randomized', 'algorithm', 'is', 'onlog2ncdot', '2c', 'm', 'cdot', 'mathrmpolym', 'and', 'the', 'running', 'time', 'of', 'our', 'deterministic', 'algorithm', 'is', 'onlogncdot', '2c', 'm', 'cdot', 'mathrmpolym', 'where', 'c', 'and', 'c', 'are', 'constants', 'depending', 'only', 'on', 'the', 'relative', 'distance', 'of', 'the', 'closest', 'pair', 'when', 'applied', 'to', 'the', 'light', 'bulb', 'problem', 'our', 'result', 'yields', 'stateoftheart', 'deterministic', 'running', 'time', 'when', 'the', 'pearsoncorrelation', 'coefficient', 'rho', 'is', 'very', 'large', 'specifically', 'when', 'rho', 'geq', '09933', 'our', 'deterministic', 'algorithm', 'runs', 'faster', 'than', 'the', 'previously', 'best', 'deterministic', 'algorithm', 'alman', 'sosa', '2019']]
[-0.16074795071395803, 0.1272672718025497, -0.02546747534430344, 0.012516515034904384, -0.04101413206547211, -0.22273249436267625, 0.04900682126544931, 0.39724321260749884, -0.30243787537097355, -0.29820869341801376, 0.07274441554169916, -0.2888293383920884, -0.13218083674890807, 0.1815750250690591, -0.036202502164228184, 0.06679347308753933, 0.06367446627089682, 0.09639682763292151, -0.05563714604011804, -0.3279417884325125, 0.24925493628676795, 0.02624993424512734, 0.21904087918218823, -0.014292370296438425, 0.11929463613932716, 0.0020296132315505934, 0.0038595115148477794, -0.018402573010673263, -0.10697690356594834, 0.06710755506540694, 0.21985514963673458, 0.16324333824186446, 0.2737915217336164, -0.3452131649407234, -0.10235352924309712, 0.1759721614910516, 0.13627939636289085, 0.06963176949487392, 0.019287518989063224, -0.2297700257349286, 0.13794737638074658, -0.05736878627489285, -0.06060635652431693, 0.0222506835356931, 0.09769735918817682, -0.0003360292272261493, -0.3455968162518262, 0.04581106792188646, 0.04612995161391436, -0.0373320515159497, 0.016610066519628243, -0.20319196785728122, 0.05107347714555198, 0.09601867401995567, 0.013914082317679956, 0.15805905545644916, 0.0659648689251002, -0.03194044054954091, -0.10514700901437324, 0.37598385938149953, -0.08057467264770621, -0.18989779452345648, 0.13346015512283205, -0.0899723438515189, -0.10075016591173097, 0.11218028032807478, 0.1732860371619669, 0.19654406791871917, -0.094746613367242, 0.1252480273929975, -0.11398896202959573, 0.19141167635484008, 0.07861299531981966, 0.023715869292040555, 0.0644926418195278, 0.1470338053337571, 0.1263436566657536, 0.10810024395214589, -0.06774902202781335, -0.06393045910700991, -0.27447090083887565, -0.11726754598154877, -0.23262286995079637, 0.029742024152009692, -0.17361009490093504, -0.11590340621229159, 0.3311825825091159, 0.11183662076599031, 0.24765980057466586, 0.15205392992260316, 0.30351826369286306, 0.07870291528171083, -0.008068546883051813, 0.1983827076535878, 0.1600325691657789, 0.06973544377331925, 0.04576581018302816, -0.2203015966922333, 0.09301069120037786, 0.10685792816957222]
1,802.09105
Configurational entropy and $\rho$ and $\phi$ mesons production in QCD
In the present work the electroproduction for diffractive $\rho$ and $\phi$ mesons by considering AdS/QCD correspondence and Color Glass Condensate (CGC) approximation are studied with respect to the associated dipole cross section, whose parameters are studied and analysed in the framework of the configurational entropy. Our results suggest different quantum states of the nuclear matter, showing that the extremal points of the nuclear configurational entropy is able to reflect a true description of the $\rho$ and $\phi$ mesons production, using current data concerning light quark masses. During the computations parameters, obtained in fitting procedure, coincide to the experimental within 0.1 %.
nucl-th hep-ph
in the present work the electroproduction for diffractive rho and phi mesons by considering adsqcd correspondence and color glass condensate cgc approximation are studied with respect to the associated dipole cross section whose parameters are studied and analysed in the framework of the configurational entropy our results suggest different quantum states of the nuclear matter showing that the extremal points of the nuclear configurational entropy is able to reflect a true description of the rho and phi mesons production using current data concerning light quark masses during the computations parameters obtained in fitting procedure coincide to the experimental within 01
[['in', 'the', 'present', 'work', 'the', 'electroproduction', 'for', 'diffractive', 'rho', 'and', 'phi', 'mesons', 'by', 'considering', 'adsqcd', 'correspondence', 'and', 'color', 'glass', 'condensate', 'cgc', 'approximation', 'are', 'studied', 'with', 'respect', 'to', 'the', 'associated', 'dipole', 'cross', 'section', 'whose', 'parameters', 'are', 'studied', 'and', 'analysed', 'in', 'the', 'framework', 'of', 'the', 'configurational', 'entropy', 'our', 'results', 'suggest', 'different', 'quantum', 'states', 'of', 'the', 'nuclear', 'matter', 'showing', 'that', 'the', 'extremal', 'points', 'of', 'the', 'nuclear', 'configurational', 'entropy', 'is', 'able', 'to', 'reflect', 'a', 'true', 'description', 'of', 'the', 'rho', 'and', 'phi', 'mesons', 'production', 'using', 'current', 'data', 'concerning', 'light', 'quark', 'masses', 'during', 'the', 'computations', 'parameters', 'obtained', 'in', 'fitting', 'procedure', 'coincide', 'to', 'the', 'experimental', 'within', '01']]
[-0.04031224144389853, 0.20589218131732195, -0.14272849128581583, 0.10329963514232077, 0.023705070689320564, -0.09536946303676813, 0.039628218087600545, 0.35493558287620547, -0.18406864125281572, -0.24382119953457732, -0.016749761452665553, -0.3141092968173325, -0.03298710860777646, 0.12694014734588563, 0.003957325757946819, 0.12851903280243276, 0.0513060378737282, 0.07927783210761845, -0.06669405483757146, -0.21631848551449365, 0.33142336073564366, -0.006410343368770555, 0.23675086461938918, 0.14638827186310663, 0.05776629439671524, 0.0461306452518329, -0.043012239776435306, 0.006816289299167693, -0.16934593762074657, 0.1241554166021524, 0.25094058552233034, 0.09619137001398485, 0.10044957876205445, -0.3869777598418295, -0.1702083723875694, 0.0991849130578339, 0.09691965430509299, 0.08058869246509857, -0.04062294344417751, -0.2817097187926993, 0.07683745639573317, -0.1732961010094732, -0.15159762042108924, -0.12556267673149704, 0.00950577061274089, 0.0009921527095139028, -0.2754617161722854, 0.0970973420701921, -0.006361552588641644, 0.023310784755740315, -0.10788789220387116, -0.19127113095019013, -0.04739956836914644, 0.02945390991400927, 0.08482615106731828, 0.10774754997342825, 0.19117844849359245, -0.17405123860109598, -0.10786826243624091, 0.3772481303475797, -0.028348519364371896, -0.15883077930891887, 0.11393555679242126, -0.17983052767813207, -0.11070363795035519, 0.11088845827616751, 0.15875023499684177, 0.1001574357994832, -0.16731688561849295, 0.09861019000876695, -0.028040816315915436, 0.1653620942332782, 0.09298318972229026, 0.05229297971818596, 0.2030223357770592, 0.14304576763883234, -0.08050288198865019, 0.12394219874637201, -0.06594130675366613, -0.17572229498066008, -0.36815218959003687, -0.11131338530220092, -0.15162727741524576, 0.005142484856769443, -0.11732635294029023, -0.10100067704450338, 0.3793293591775, 0.08949834022670984, 0.2778446991648525, 0.027074079383164643, 0.3051840091496706, 0.09196563871228136, 0.03998279325198382, 0.08491101360414177, 0.3065148472134024, 0.23440174367511646, 0.10397781897336245, -0.2853492080653086, 0.02559309630189091, 0.05609801234677434]
1,802.09106
Quenched invariance principles for orthomartingale-like sequences
In this paper we study the central limit theorem and its functional form for random fields which are not started from their equilibrium, but rather under the measure conditioned by the past sigma field. The initial class considered is that of orthomartingales and then the result is extended to a more general class of random fields by approximating them, in some sense, with an orthomartingale. We construct an example which shows that there are orthomartingales which satisfy the CLT but not its quenched form. This example also clarifies the optimality of the moment conditions used for the validity of our results. Finally, by using the so called orthomartingale-coboundary decomposition, we apply our results to linear and nonlinear random fields.
math.PR
in this paper we study the central limit theorem and its functional form for random fields which are not started from their equilibrium but rather under the measure conditioned by the past sigma field the initial class considered is that of orthomartingales and then the result is extended to a more general class of random fields by approximating them in some sense with an orthomartingale we construct an example which shows that there are orthomartingales which satisfy the clt but not its quenched form this example also clarifies the optimality of the moment conditions used for the validity of our results finally by using the so called orthomartingalecoboundary decomposition we apply our results to linear and nonlinear random fields
[['in', 'this', 'paper', 'we', 'study', 'the', 'central', 'limit', 'theorem', 'and', 'its', 'functional', 'form', 'for', 'random', 'fields', 'which', 'are', 'not', 'started', 'from', 'their', 'equilibrium', 'but', 'rather', 'under', 'the', 'measure', 'conditioned', 'by', 'the', 'past', 'sigma', 'field', 'the', 'initial', 'class', 'considered', 'is', 'that', 'of', 'orthomartingales', 'and', 'then', 'the', 'result', 'is', 'extended', 'to', 'a', 'more', 'general', 'class', 'of', 'random', 'fields', 'by', 'approximating', 'them', 'in', 'some', 'sense', 'with', 'an', 'orthomartingale', 'we', 'construct', 'an', 'example', 'which', 'shows', 'that', 'there', 'are', 'orthomartingales', 'which', 'satisfy', 'the', 'clt', 'but', 'not', 'its', 'quenched', 'form', 'this', 'example', 'also', 'clarifies', 'the', 'optimality', 'of', 'the', 'moment', 'conditions', 'used', 'for', 'the', 'validity', 'of', 'our', 'results', 'finally', 'by', 'using', 'the', 'so', 'called', 'orthomartingalecoboundary', 'decomposition', 'we', 'apply', 'our', 'results', 'to', 'linear', 'and', 'nonlinear', 'random', 'fields']]
[-0.06316351923318106, 0.1029818283053119, -0.1139820143738288, 0.07204796323233079, -0.05006532824274658, -0.0815964599763501, 0.042726094609075144, 0.358620765437451, -0.2488437623764246, -0.23826692116415224, 0.15208450850628127, -0.20501177853478467, -0.18659776878558984, 0.20663663770182658, -0.05961309102466488, 0.027839459418674332, 0.029676982404869365, 0.06594501525731915, -0.04550454022867952, -0.2699957661551692, 0.36242860097090823, 0.00995149730973072, 0.2478325755958903, 0.032344040277382455, 0.08747119726060684, 0.019741825167468544, -0.003596312295392913, 0.06926263638345873, -0.13749938837898268, 0.11979023995414628, 0.21003203216143015, 0.11196779366188003, 0.2912296979072488, -0.4023739086006279, -0.17781844860637339, 0.13564327434770826, 0.08507161244150188, 0.1116041365657712, -0.0694357482663413, -0.27619968462040867, 0.1311306901141938, -0.13667804526038846, -0.17045081251742855, -0.09830700720549893, -0.0012119413596199098, 0.053854497368605335, -0.2967857777425167, 0.05859971166192751, 0.1591850931596374, 0.02821466283304459, -0.059729474571028375, -0.08922386913801054, 0.0007521151604478137, 0.11621709077390131, 0.06806848167295773, 0.031139951256514226, 0.09224803373217583, -0.11732502351514995, -0.07994005942650108, 0.3682949676462528, -0.07266124162548696, -0.2293844885997853, 0.19238771426972887, -0.14595925541578839, -0.1714164930241877, 0.07313440110676496, 0.12962001923400657, 0.13260748384173138, -0.18168595438365334, 0.10037168134960851, -0.09216133451041908, 0.1238305921650539, 0.05375996714268448, 0.02164253343332764, 0.14466708824354207, 0.08960432724601006, 0.08865835497124215, 0.16051329350714588, -0.057326398432990776, -0.1202830739074655, -0.3355284831328791, -0.1371181253728583, -0.18948097828720398, 0.07934636000560605, -0.07325341954979733, -0.17554972028770185, 0.37244420716049687, 0.1831421551997063, 0.18276039064246213, 0.10783387503440697, 0.2152889441043707, 0.1710220225652585, 0.04600863569017531, 0.10492286646454516, 0.2215285904193001, 0.17775860194992907, 0.07764121908220951, -0.14004686223027313, 0.05471988259893605, 0.05925994393242113]
1,802.09107
Prehawking radiation
Using the 2-D quantum energy momentum tensor expectation value near a black hole, the value near a collapsing shell which stops collapsing just outside the putative horizon is calculated and shown not to have any evidence of preHawking radiation.
gr-qc
using the 2d quantum energy momentum tensor expectation value near a black hole the value near a collapsing shell which stops collapsing just outside the putative horizon is calculated and shown not to have any evidence of prehawking radiation
[['using', 'the', '2d', 'quantum', 'energy', 'momentum', 'tensor', 'expectation', 'value', 'near', 'a', 'black', 'hole', 'the', 'value', 'near', 'a', 'collapsing', 'shell', 'which', 'stops', 'collapsing', 'just', 'outside', 'the', 'putative', 'horizon', 'is', 'calculated', 'and', 'shown', 'not', 'to', 'have', 'any', 'evidence', 'of', 'prehawking', 'radiation']]
[-0.09477089923054266, 0.12813878546540552, -0.09214102966376604, 0.09309589284030387, -0.08028808078513695, -0.10844033357138053, 0.028186470311946977, 0.3104528779020676, -0.1666523712263323, -0.26075745808581513, 0.10915089981296124, -0.2888566838243069, 0.00192806693032766, 0.15202420629943028, 0.03523939625861553, 0.020007045067942295, 0.05483168334915088, 0.1131509538166798, -0.13952624821701112, -0.11736980319405213, 0.35938152169975907, 0.14654221578250423, 0.23899794014123005, 0.08322488934470293, 0.09295695905502026, -0.03547996047955866, 0.10273730133373576, 0.09194249459184133, -0.17567580716851622, -0.014264226174698426, 0.19205689556204164, 0.09993048511350001, 0.2622927917788426, -0.4018904221459077, -0.24897157775763518, 0.13784428540235147, 0.14365781074724135, 0.16112696676431462, -0.08809144448679991, -0.26536800292057866, 0.09269986046143831, -0.21585063140791577, -0.19814483830944085, 0.016136739808970537, 0.04943034573434255, -0.1184338715691597, -0.21028128708115754, 0.09389655046069469, 0.0379043473647191, -0.0930476089557394, -0.15627834358467504, -0.06894347979090153, -0.11578435074681273, 0.05545991327231511, 0.09489887355205913, 0.04719262359848914, 0.2699878447068234, -0.16206114786939743, -0.07137811310493793, 0.3310697011840649, -0.027931984131916974, -0.14184365603022087, 0.1185638837229747, -0.23829597709939265, -0.00722977839028224, 0.22314339785430676, 0.08058153122711258, 0.1762352115713442, -0.10351300337471259, 0.1181547687588952, -0.011570297563687349, 0.17574658417530978, 0.13784366566687822, 0.012142169456451368, 0.4438389976723836, 0.07466538310146485, 0.003274523635179951, 0.11799373131436415, -0.12449200441822028, -0.17262487848981833, -0.3601732062987792, -0.16271411541562814, -0.23957744349415103, 0.13390016011954942, -0.11793062763060264, -0.21564363444877716, 0.2726650193142585, 0.08156724287292515, 0.21212332886912358, 0.012420535401011316, 0.2613392090663696, 0.14673159875644323, 0.11967891014109437, 0.234429479110986, 0.38158371882178843, 0.0937498315440443, 0.13944387092040136, -0.23961975091160873, -0.010114677596646242, 0.07140817555288474]
1,802.09108
Dense molecular gas in the starburst nucleus of NGC 1808
Dense molecular gas tracers in the central 1 kpc region of the superwind galaxy NGC 1808 have been imaged by ALMA at a resolution of 1" (~50 pc). Integrated intensities and line intensity ratios of HCN (1-0), H$^{13}$CN (1-0), HCO$^+$ (1-0), H$^{13}$CO$^+$ (1-0), HOC$^+$ (1-0), HCO$^+$ (4-3), CS (2-1), C$_2$H (1-0), and previously detected CO (1-0) and CO (3-2) are presented. SiO (2-1) and HNCO (4-3) are detected toward the circumnuclear disk (CND), indicating the presence of shocked dense gas. There is evidence that an enhanced intensity ratio of HCN(1-0)/HCO$^+$(1-0) reflects star formation activity, possibly in terms of shock heating and electron excitation in the CND and a star-forming ring at radius ~300 pc. A non-LTE analysis indicates that the molecular gas traced by HCN, H$^{13}$CN, HCO$^+$, and H$^{13}$CO$^+$ in the CND is dense ($n_{\mathrm{H}_2}$~$10^5$ cm$^{-3}$) and warm (20 K$<T_\mathrm{k}$<100 K). The calculations yield a low average gas density of $n_{\mathrm{H}_2}$~$10^2\mathrm{-}10^3$ cm$^{-3}$ for a temperature of $T_\mathrm{k}\geq30$ K in the nuclear outflow. Dense gas tracers HCN (1-0), HCO$^+$ (1-0), CS (2-1), and C$_2$H (1-0) are detected for the first time in the superwind of NGC 1808, confirming the presence of a velocity gradient in the outflow direction.
astro-ph.GA
dense molecular gas tracers in the central 1 kpc region of the superwind galaxy ngc 1808 have been imaged by alma at a resolution of 1 50 pc integrated intensities and line intensity ratios of hcn 10 h13cn 10 hco 10 h13co 10 hoc 10 hco 43 cs 21 c_2h 10 and previously detected co 10 and co 32 are presented sio 21 and hnco 43 are detected toward the circumnuclear disk cnd indicating the presence of shocked dense gas there is evidence that an enhanced intensity ratio of hcn10hco10 reflects star formation activity possibly in terms of shock heating and electron excitation in the cnd and a starforming ring at radius 300 pc a nonlte analysis indicates that the molecular gas traced by hcn h13cn hco and h13co in the cnd is dense n_mathrmh_2105 cm3 and warm 20 kt_mathrmk100 k the calculations yield a low average gas density of n_mathrmh_2102mathrm103 cm3 for a temperature of t_mathrmkgeq30 k in the nuclear outflow dense gas tracers hcn 10 hco 10 cs 21 and c_2h 10 are detected for the first time in the superwind of ngc 1808 confirming the presence of a velocity gradient in the outflow direction
[['dense', 'molecular', 'gas', 'tracers', 'in', 'the', 'central', '1', 'kpc', 'region', 'of', 'the', 'superwind', 'galaxy', 'ngc', '1808', 'have', 'been', 'imaged', 'by', 'alma', 'at', 'a', 'resolution', 'of', '1', '50', 'pc', 'integrated', 'intensities', 'and', 'line', 'intensity', 'ratios', 'of', 'hcn', '10', 'h13cn', '10', 'hco', '10', 'h13co', '10', 'hoc', '10', 'hco', '43', 'cs', '21', 'c_2h', '10', 'and', 'previously', 'detected', 'co', '10', 'and', 'co', '32', 'are', 'presented', 'sio', '21', 'and', 'hnco', '43', 'are', 'detected', 'toward', 'the', 'circumnuclear', 'disk', 'cnd', 'indicating', 'the', 'presence', 'of', 'shocked', 'dense', 'gas', 'there', 'is', 'evidence', 'that', 'an', 'enhanced', 'intensity', 'ratio', 'of', 'hcn10hco10', 'reflects', 'star', 'formation', 'activity', 'possibly', 'in', 'terms', 'of', 'shock', 'heating', 'and', 'electron', 'excitation', 'in', 'the', 'cnd', 'and', 'a', 'starforming', 'ring', 'at', 'radius', '300', 'pc', 'a', 'nonlte', 'analysis', 'indicates', 'that', 'the', 'molecular', 'gas', 'traced', 'by', 'hcn', 'h13cn', 'hco', 'and', 'h13co', 'in', 'the', 'cnd', 'is', 'dense', 'n_mathrmh_2105', 'cm3', 'and', 'warm', '20', 'kt_mathrmk100', 'k', 'the', 'calculations', 'yield', 'a', 'low', 'average', 'gas', 'density', 'of', 'n_mathrmh_2102mathrm103', 'cm3', 'for', 'a', 'temperature', 'of', 't_mathrmkgeq30', 'k', 'in', 'the', 'nuclear', 'outflow', 'dense', 'gas', 'tracers', 'hcn', '10', 'hco', '10', 'cs', '21', 'and', 'c_2h', '10', 'are', 'detected', 'for', 'the', 'first', 'time', 'in', 'the', 'superwind', 'of', 'ngc', '1808', 'confirming', 'the', 'presence', 'of', 'a', 'velocity', 'gradient', 'in', 'the', 'outflow', 'direction']]
[-0.06954043802179136, 0.058905588659060364, 0.08823778581385708, 0.010450366412776817, 0.05540902360458255, -0.05793515877759595, 0.02542772979374222, 0.49246823973953724, -0.10881519244037993, -0.3204068469156275, 0.03991221648899095, -0.2518276605812997, 0.05267226547147558, 0.06054492079088262, 0.08120433665878969, -0.0901925115040238, -0.017389723055132235, -0.1675573935234012, -0.033051014579579215, -0.17755551642371545, 0.2109497614600575, 0.1049066201585871, 0.10653613263818344, 0.08763781331064556, 0.03632783533648197, -0.3022082979897027, -0.05842861634500595, -0.07217366634650937, -0.13166510070822807, 0.05180116929596416, 0.29065951136534385, 0.10908470177236423, 0.1888111999229446, -0.3950354436176004, -0.25438119533925363, 0.012237403505612069, 0.24608335366781434, -0.008434485718897433, 0.007263158901638009, -0.2871082025855162, 0.059668068318034236, -0.21656105459373387, -0.21258800629878638, 0.1093536520028762, 0.1078707896995749, 0.014391519901357166, -0.22162930581627, 0.21156194355396718, -0.0028893663644443215, 0.2058022262903948, -0.1162559819320902, -0.17536046825966994, -0.07276147131571653, -0.025898128817306704, -0.0760123438824335, 0.1617561568900547, 0.37194797655065676, -0.09554076258459857, 0.014809405762301709, 0.41014337919078225, -0.16020034851296444, 0.04753106051737471, 0.2896977033987255, -0.2590491038402108, -0.2463722449825073, 0.31870758924343734, 0.044001719891455585, 0.10705464124592706, -0.07690350605297648, -0.06184304633960152, -0.08489891489089461, 0.2719150751809845, 0.146294499856029, 0.06312414648506243, 0.30465522885004087, 0.023595833844490773, 0.059736969498489195, 0.08605402049492716, -0.34340454326759196, -0.06645988701200933, -0.16180553596582592, -0.14316756239672399, -0.10301044616797563, 0.12912957833590072, -0.19630018541270594, 0.034602952479273856, 0.22796125307985596, 0.04766017858691784, 0.27761414679433244, -0.041081927780066786, 0.33358983879841364, 0.048278586312264705, 0.06916435173630638, 0.20551876714839143, 0.27905694939620757, 0.26562421712204043, 0.1531565611207269, -0.2651137568061409, 0.06295689822951515, -0.0273058190205921]
1,802.09109
Unilateral global bifurcation for a class of quasilinear elliptic systems and applications
In this paper we establish a unilateral bifurcation result for a class of quasilinear elliptic system strongly coupled, extending a bifurcation theorem due to J. L\'opez-G\'omez. To this aim, we use several results, such that Fredholm operator of index $0$ theory, eigenvalues of elliptic operators and the Krein-Rutman theorem. Lastly, we apply this result to some particular systems arising from population dynamics and determine a region of existence of coexistence states.
math.AP
in this paper we establish a unilateral bifurcation result for a class of quasilinear elliptic system strongly coupled extending a bifurcation theorem due to j lopezgomez to this aim we use several results such that fredholm operator of index 0 theory eigenvalues of elliptic operators and the kreinrutman theorem lastly we apply this result to some particular systems arising from population dynamics and determine a region of existence of coexistence states
[['in', 'this', 'paper', 'we', 'establish', 'a', 'unilateral', 'bifurcation', 'result', 'for', 'a', 'class', 'of', 'quasilinear', 'elliptic', 'system', 'strongly', 'coupled', 'extending', 'a', 'bifurcation', 'theorem', 'due', 'to', 'j', 'lopezgomez', 'to', 'this', 'aim', 'we', 'use', 'several', 'results', 'such', 'that', 'fredholm', 'operator', 'of', 'index', '0', 'theory', 'eigenvalues', 'of', 'elliptic', 'operators', 'and', 'the', 'kreinrutman', 'theorem', 'lastly', 'we', 'apply', 'this', 'result', 'to', 'some', 'particular', 'systems', 'arising', 'from', 'population', 'dynamics', 'and', 'determine', 'a', 'region', 'of', 'existence', 'of', 'coexistence', 'states']]
[-0.1754970220649349, 0.05848851323659931, -0.11391777126118541, 0.0713611476406056, -0.07281801071616688, -0.13337022300277437, 0.06321742778777012, 0.2587942345999181, -0.3067507686891726, -0.22778682584342147, 0.13343652842865725, -0.28817996245675853, -0.2173346890668784, 0.18831979780058775, -0.10506624724158818, 0.04764805672956365, 0.08175214668735861, -0.007211859194960977, -0.04029350619031383, -0.14415791151113808, 0.4407437974919698, -0.07090372405946255, 0.17346686250738066, 0.09968449957668782, 0.031173206636283014, 0.02248245181981474, 0.010056373230846865, -0.007584467131112303, -0.2036497784151704, 0.15546093115699477, 0.31133153337453096, 0.038282167588892795, 0.28640951253193114, -0.35317786248134714, -0.1840880367040102, 0.17635137353624616, 0.12702830139813678, 0.1108346520723509, -0.036484563377286706, -0.26028459463268516, 0.08540681686718017, -0.1977968187071383, -0.2690106260324163, -0.06638478132496987, -0.01584634891312037, 0.04111620606854558, -0.2872379674044039, 0.09606160897362445, 0.1535043099096843, 0.08058877250711832, -0.10422110121165003, -0.03554698307832171, -0.01784125032967755, 0.07872484851229404, 0.04276517942946936, -0.024430801779297847, 0.052795986452006866, -0.07172433112282306, -0.11890726940972464, 0.30198325786041097, -0.07294438800308853, -0.1886748550925404, 0.1942534763232938, -0.15194406312491213, -0.17356483577085394, 0.08930054736722792, 0.1972928833615567, 0.18433494259869412, -0.10876944291937564, 0.1047706108091266, -0.09264620613040668, 0.13973465527274778, 0.07182203682937792, 0.009984795077304756, 0.08713801790560995, 0.1043814581519525, 0.131450781332595, 0.1609838510231514, -0.004991770615535123, -0.1334394103581352, -0.3340218638735158, -0.14215898255684545, -0.12228469014433878, 0.12610518164001405, -0.05896126061769402, -0.18271021615447744, 0.42684323832924875, 0.16172665866823602, 0.19657559916377068, 0.09506037461105735, 0.1790652083232999, 0.16989038790177022, -0.03477538164172854, 0.05309315551338451, 0.1988001203650908, 0.23751237047836185, 0.13207056991356825, -0.20484599642389054, -0.0460990220640919, 0.1615344760939479]
1,802.0911
Submodularity on Hypergraphs: From Sets to Sequences
In a nutshell, submodular functions encode an intuitive notion of diminishing returns. As a result, submodularity appears in many important machine learning tasks such as feature selection and data summarization. Although there has been a large volume of work devoted to the study of submodular functions in recent years, the vast majority of this work has been focused on algorithms that output sets, not sequences. However, in many settings, the order in which we output items can be just as important as the items themselves. To extend the notion of submodularity to sequences, we use a directed graph on the items where the edges encode the additional value of selecting items in a particular order. Existing theory is limited to the case where this underlying graph is a directed acyclic graph. In this paper, we introduce two new algorithms that provably give constant factor approximations for general graphs and hypergraphs having bounded in or out degrees. Furthermore, we show the utility of our new algorithms for real-world applications in movie recommendation, online link prediction, and the design of course sequences for MOOCs.
cs.DS
in a nutshell submodular functions encode an intuitive notion of diminishing returns as a result submodularity appears in many important machine learning tasks such as feature selection and data summarization although there has been a large volume of work devoted to the study of submodular functions in recent years the vast majority of this work has been focused on algorithms that output sets not sequences however in many settings the order in which we output items can be just as important as the items themselves to extend the notion of submodularity to sequences we use a directed graph on the items where the edges encode the additional value of selecting items in a particular order existing theory is limited to the case where this underlying graph is a directed acyclic graph in this paper we introduce two new algorithms that provably give constant factor approximations for general graphs and hypergraphs having bounded in or out degrees furthermore we show the utility of our new algorithms for realworld applications in movie recommendation online link prediction and the design of course sequences for moocs
[['in', 'a', 'nutshell', 'submodular', 'functions', 'encode', 'an', 'intuitive', 'notion', 'of', 'diminishing', 'returns', 'as', 'a', 'result', 'submodularity', 'appears', 'in', 'many', 'important', 'machine', 'learning', 'tasks', 'such', 'as', 'feature', 'selection', 'and', 'data', 'summarization', 'although', 'there', 'has', 'been', 'a', 'large', 'volume', 'of', 'work', 'devoted', 'to', 'the', 'study', 'of', 'submodular', 'functions', 'in', 'recent', 'years', 'the', 'vast', 'majority', 'of', 'this', 'work', 'has', 'been', 'focused', 'on', 'algorithms', 'that', 'output', 'sets', 'not', 'sequences', 'however', 'in', 'many', 'settings', 'the', 'order', 'in', 'which', 'we', 'output', 'items', 'can', 'be', 'just', 'as', 'important', 'as', 'the', 'items', 'themselves', 'to', 'extend', 'the', 'notion', 'of', 'submodularity', 'to', 'sequences', 'we', 'use', 'a', 'directed', 'graph', 'on', 'the', 'items', 'where', 'the', 'edges', 'encode', 'the', 'additional', 'value', 'of', 'selecting', 'items', 'in', 'a', 'particular', 'order', 'existing', 'theory', 'is', 'limited', 'to', 'the', 'case', 'where', 'this', 'underlying', 'graph', 'is', 'a', 'directed', 'acyclic', 'graph', 'in', 'this', 'paper', 'we', 'introduce', 'two', 'new', 'algorithms', 'that', 'provably', 'give', 'constant', 'factor', 'approximations', 'for', 'general', 'graphs', 'and', 'hypergraphs', 'having', 'bounded', 'in', 'or', 'out', 'degrees', 'furthermore', 'we', 'show', 'the', 'utility', 'of', 'our', 'new', 'algorithms', 'for', 'realworld', 'applications', 'in', 'movie', 'recommendation', 'online', 'link', 'prediction', 'and', 'the', 'design', 'of', 'course', 'sequences', 'for', 'moocs']]
[-0.09184622640496345, 0.0385071369954468, -0.054884435426044674, 0.0784629114953402, -0.13223561499738595, -0.11733321239148359, 0.05771887829209995, 0.4260888024627303, -0.28896780223534496, -0.3113744597639607, 0.08139021688199775, -0.27852985957780707, -0.18875672126439616, 0.15340187962955007, -0.14399072619738404, 0.07230172037648466, 0.09141316219197157, 0.07306271283836155, -0.023981801786199006, -0.31432552251739015, 0.3210091508738185, 0.02952739617858942, 0.25975445263435715, 0.06833712765332925, 0.09646298940956163, 0.038607821213900224, -0.04088124854536215, 0.06914279272186231, -0.1350400457915864, 0.14714428715428318, 0.3605384113098198, 0.20553679335708883, 0.3736998447738997, -0.3778030560249565, -0.19714272961501483, 0.16587104051723145, 0.14043258705462974, 0.0979875480112681, -0.04846748109308204, -0.2266493835838276, 0.08435276691458997, -0.1561729718285298, -0.004409511198780939, -0.09267428743815789, 0.03894535999919114, 0.03538125277826931, -0.2948445612078553, -0.021932490634383982, 0.10615893365344503, 0.060157688723488166, 0.0022658600950367994, -0.1386514979556643, 0.05991897936321918, 0.13631848506450367, 0.0664849290854533, 0.05330079893458758, 0.09120641545658666, -0.16287926771386352, -0.20206145478404833, 0.3807506978378764, -0.014155628708457308, -0.18771846120752353, 0.1706063549487166, -0.07466035969760064, -0.21912910224317195, 0.08978058223274875, 0.2442487777274097, 0.15203785182841653, -0.1511036863852456, 0.07648252472211095, -0.12445412406820681, 0.16857713946028724, 0.06744658173660614, 0.05465954430510065, 0.15218123701493164, 0.18862818005228682, 0.1158135294252853, 0.16024663050436405, 0.010226099619163445, -0.09177317086397414, -0.24449008116805618, -0.13267668753997985, -0.2075473416729697, 0.02792850171945347, -0.12194256151869322, -0.19728145762704885, 0.404769414519011, 0.17752431354301235, 0.20689241947340115, 0.09182107237303261, 0.2895931489995916, 0.06606453860621224, 0.08777054165973543, 0.10118134648303737, 0.16292836347333883, 0.07296079223729916, 0.11053266616763321, -0.09054048496533881, 0.12007237652222022, 0.054728945003612]
1,802.09111
Dynamic Effective Resistances and Approximate Schur Complement on Separable Graphs
We consider the problem of dynamically maintaining (approximate) all-pairs effective resistances in separable graphs, which are those that admit an $n^{c}$-separator theorem for some $c<1$. We give a fully dynamic algorithm that maintains $(1+\varepsilon)$-approximations of the all-pairs effective resistances of an $n$-vertex graph $G$ undergoing edge insertions and deletions with $\tilde{O}(\sqrt{n}/\varepsilon^2)$ worst-case update time and $\tilde{O}(\sqrt{n}/\varepsilon^2)$ worst-case query time, if $G$ is guaranteed to be $\sqrt{n}$-separable (i.e., it is taken from a class satisfying a $\sqrt{n}$-separator theorem) and its separator can be computed in $\tilde{O}(n)$ time. Our algorithm is built upon a dynamic algorithm for maintaining \emph{approximate Schur complement} that approximately preserves pairwise effective resistances among a set of terminals for separable graphs, which might be of independent interest. We complement our result by proving that for any two fixed vertices $s$ and $t$, no incremental or decremental algorithm can maintain the $s-t$ effective resistance for $\sqrt{n}$-separable graphs with worst-case update time $O(n^{1/2-\delta})$ and query time $O(n^{1-\delta})$ for any $\delta>0$, unless the Online Matrix Vector Multiplication (OMv) conjecture is false. We further show that for \emph{general} graphs, no incremental or decremental algorithm can maintain the $s-t$ effective resistance problem with worst-case update time $O(n^{1-\delta})$ and query-time $O(n^{2-\delta})$ for any $\delta >0$, unless the OMv conjecture is false.
cs.DS
we consider the problem of dynamically maintaining approximate allpairs effective resistances in separable graphs which are those that admit an ncseparator theorem for some c1 we give a fully dynamic algorithm that maintains 1varepsilonapproximations of the allpairs effective resistances of an nvertex graph g undergoing edge insertions and deletions with tildeosqrtnvarepsilon2 worstcase update time and tildeosqrtnvarepsilon2 worstcase query time if g is guaranteed to be sqrtnseparable ie it is taken from a class satisfying a sqrtnseparator theorem and its separator can be computed in tildeon time our algorithm is built upon a dynamic algorithm for maintaining emphapproximate schur complement that approximately preserves pairwise effective resistances among a set of terminals for separable graphs which might be of independent interest we complement our result by proving that for any two fixed vertices s and t no incremental or decremental algorithm can maintain the st effective resistance for sqrtnseparable graphs with worstcase update time on12delta and query time on1delta for any delta0 unless the online matrix vector multiplication omv conjecture is false we further show that for emphgeneral graphs no incremental or decremental algorithm can maintain the st effective resistance problem with worstcase update time on1delta and querytime on2delta for any delta 0 unless the omv conjecture is false
[['we', 'consider', 'the', 'problem', 'of', 'dynamically', 'maintaining', 'approximate', 'allpairs', 'effective', 'resistances', 'in', 'separable', 'graphs', 'which', 'are', 'those', 'that', 'admit', 'an', 'ncseparator', 'theorem', 'for', 'some', 'c1', 'we', 'give', 'a', 'fully', 'dynamic', 'algorithm', 'that', 'maintains', '1varepsilonapproximations', 'of', 'the', 'allpairs', 'effective', 'resistances', 'of', 'an', 'nvertex', 'graph', 'g', 'undergoing', 'edge', 'insertions', 'and', 'deletions', 'with', 'tildeosqrtnvarepsilon2', 'worstcase', 'update', 'time', 'and', 'tildeosqrtnvarepsilon2', 'worstcase', 'query', 'time', 'if', 'g', 'is', 'guaranteed', 'to', 'be', 'sqrtnseparable', 'ie', 'it', 'is', 'taken', 'from', 'a', 'class', 'satisfying', 'a', 'sqrtnseparator', 'theorem', 'and', 'its', 'separator', 'can', 'be', 'computed', 'in', 'tildeon', 'time', 'our', 'algorithm', 'is', 'built', 'upon', 'a', 'dynamic', 'algorithm', 'for', 'maintaining', 'emphapproximate', 'schur', 'complement', 'that', 'approximately', 'preserves', 'pairwise', 'effective', 'resistances', 'among', 'a', 'set', 'of', 'terminals', 'for', 'separable', 'graphs', 'which', 'might', 'be', 'of', 'independent', 'interest', 'we', 'complement', 'our', 'result', 'by', 'proving', 'that', 'for', 'any', 'two', 'fixed', 'vertices', 's', 'and', 't', 'no', 'incremental', 'or', 'decremental', 'algorithm', 'can', 'maintain', 'the', 'st', 'effective', 'resistance', 'for', 'sqrtnseparable', 'graphs', 'with', 'worstcase', 'update', 'time', 'on12delta', 'and', 'query', 'time', 'on1delta', 'for', 'any', 'delta0', 'unless', 'the', 'online', 'matrix', 'vector', 'multiplication', 'omv', 'conjecture', 'is', 'false', 'we', 'further', 'show', 'that', 'for', 'emphgeneral', 'graphs', 'no', 'incremental', 'or', 'decremental', 'algorithm', 'can', 'maintain', 'the', 'st', 'effective', 'resistance', 'problem', 'with', 'worstcase', 'update', 'time', 'on1delta', 'and', 'querytime', 'on2delta', 'for', 'any', 'delta', '0', 'unless', 'the', 'omv', 'conjecture', 'is', 'false']]
[-0.18793396924069383, 0.11351280991817475, -0.06320176891225855, 0.022981469549122266, -0.08986317508271896, -0.23674401703756304, 0.12556906379410065, 0.4127638008445501, -0.28246875543147326, -0.33002160689793525, 0.09609165113652125, -0.25502117201329383, -0.13184534553904087, 0.14432768387254327, -0.09226713210402522, 0.06618762914469699, 0.11648745360958855, 0.08422407418082002, -0.01846131991245784, -0.3068686187542335, 0.22153326912084595, 0.008993836550507695, 0.1646901021071244, 0.09027207937906497, 0.1016356685300707, 0.05107785663567484, 0.0036657334538176658, 0.09047331856214441, -0.10545196258903161, 0.024237553272396326, 0.28980515616945923, 0.19905622058922745, 0.2536117117386311, -0.40480561236850915, -0.12503483498003334, 0.20283283603901509, 0.12229900541715324, 0.08403852424591605, -0.005774783988599665, -0.20951436275150626, 0.16226412760675885, -0.0889931817771867, -0.05810371528379619, -0.057940703638596464, 0.083382712258026, -0.03656515753595158, -0.35571819465607407, 0.02660288276252686, 0.11030690272367792, -0.016893162364140152, -0.020438393024960533, -0.13389133804943412, 0.011670967965619639, 0.10126998607534915, -0.033465582747303414, 0.11761691021732985, 0.06980134658748284, -0.05218823973438703, -0.18794235162436962, 0.33750395889859647, -0.045068088686675764, -0.17675808175816202, 0.08597805733326823, -0.05295012252638116, -0.161220023361966, 0.1449440302932635, 0.1311915986915119, 0.1538985211774707, -0.10917530751088635, 0.15488810928247404, -0.07917675246950238, 0.1395172674988862, 0.11227599467383698, 0.01675568640290294, 0.0907145843480248, 0.1298431998421438, 0.20404491576598957, 0.11980844061647077, 0.026810435655061155, -0.016970903093460946, -0.2733201987785287, -0.14021274361759425, -0.20423593590734526, 0.04757725209230557, -0.21650690575086629, -0.2042046600091271, 0.365902579347603, 0.12319381547393277, 0.17473393651307562, 0.21990197234765219, 0.2901065542921424, 0.10465745717352547, 0.04590169800212607, 0.2542348237452097, 0.12991953274191473, 0.08088312900275924, 0.03602358725387603, -0.2147312432748731, 0.1487867854036449, 0.12899365153629333]
1,802.09112
More Virtuous Smoothing
In the context of global optimization of mixed-integer nonlinear optimization formulations, we consider smoothing univariate functions $f$ that satisfy $f(0)=0$, $f$ is increasing and concave on $[0,+\infty)$, $f$ is twice differentiable on all of $(0,+\infty)$, but $f'(0)$ is undefined or intolerably large. The canonical examples are root functions $f(w):=w^p$, for $0<p<1$. We consider the earlier approach of defining a smoothing function $g$ that is identical with $f$ on $(\delta,+\infty)$, for some chosen $\delta>0$, then replacing the part of $f$ on $[0,\delta]$ with the unique homogeneous cubic, matching $f$, $f'$ and $f''$ at $\delta$. The parameter $\delta$ is used to control (i.e., upper bound) the derivative at 0 (which controls it on all of $[0,+\infty)$ when $g$ is concave). Our main results: (i) we weaken an earlier sufficient condition to give a necessary and sufficient condition for the piecewise function $g$ to be increasing and concave; (ii) we give a general sufficient condition for $g'(0)$ to be decreasing in the smoothing parameter $\delta$; under the same condition, we demonstrate that the worst-case error of $g$ as an estimate of $f$ is increasing in $\delta$; (iii) we give a general sufficient condition for $g$ to underestimate $f$; (iv) we give a general sufficient condition for $g$ to dominate the simple `shift smoothing' $h(w):=f(w+\lambda)-f(\lambda)$ ($\lambda>0$), when the parameters $\delta$ and $\lambda$ are chosen `fairly' --- i.e., so that $g'(0)=h'(0)$. In doing so, we solve two natural open problems of Lee and Skipper (2016), concerning (iii) and (iv) for root functions.
math.OC
in the context of global optimization of mixedinteger nonlinear optimization formulations we consider smoothing univariate functions f that satisfy f00 f is increasing and concave on 0infty f is twice differentiable on all of 0infty but f0 is undefined or intolerably large the canonical examples are root functions fwwp for 0p1 we consider the earlier approach of defining a smoothing function g that is identical with f on deltainfty for some chosen delta0 then replacing the part of f on 0delta with the unique homogeneous cubic matching f f and f at delta the parameter delta is used to control ie upper bound the derivative at 0 which controls it on all of 0infty when g is concave our main results i we weaken an earlier sufficient condition to give a necessary and sufficient condition for the piecewise function g to be increasing and concave ii we give a general sufficient condition for g0 to be decreasing in the smoothing parameter delta under the same condition we demonstrate that the worstcase error of g as an estimate of f is increasing in delta iii we give a general sufficient condition for g to underestimate f iv we give a general sufficient condition for g to dominate the simple shift smoothing hwfwlambdaflambda lambda0 when the parameters delta and lambda are chosen fairly ie so that g0h0 in doing so we solve two natural open problems of lee and skipper 2016 concerning iii and iv for root functions
[['in', 'the', 'context', 'of', 'global', 'optimization', 'of', 'mixedinteger', 'nonlinear', 'optimization', 'formulations', 'we', 'consider', 'smoothing', 'univariate', 'functions', 'f', 'that', 'satisfy', 'f00', 'f', 'is', 'increasing', 'and', 'concave', 'on', '0infty', 'f', 'is', 'twice', 'differentiable', 'on', 'all', 'of', '0infty', 'but', 'f0', 'is', 'undefined', 'or', 'intolerably', 'large', 'the', 'canonical', 'examples', 'are', 'root', 'functions', 'fwwp', 'for', '0p1', 'we', 'consider', 'the', 'earlier', 'approach', 'of', 'defining', 'a', 'smoothing', 'function', 'g', 'that', 'is', 'identical', 'with', 'f', 'on', 'deltainfty', 'for', 'some', 'chosen', 'delta0', 'then', 'replacing', 'the', 'part', 'of', 'f', 'on', '0delta', 'with', 'the', 'unique', 'homogeneous', 'cubic', 'matching', 'f', 'f', 'and', 'f', 'at', 'delta', 'the', 'parameter', 'delta', 'is', 'used', 'to', 'control', 'ie', 'upper', 'bound', 'the', 'derivative', 'at', '0', 'which', 'controls', 'it', 'on', 'all', 'of', '0infty', 'when', 'g', 'is', 'concave', 'our', 'main', 'results', 'i', 'we', 'weaken', 'an', 'earlier', 'sufficient', 'condition', 'to', 'give', 'a', 'necessary', 'and', 'sufficient', 'condition', 'for', 'the', 'piecewise', 'function', 'g', 'to', 'be', 'increasing', 'and', 'concave', 'ii', 'we', 'give', 'a', 'general', 'sufficient', 'condition', 'for', 'g0', 'to', 'be', 'decreasing', 'in', 'the', 'smoothing', 'parameter', 'delta', 'under', 'the', 'same', 'condition', 'we', 'demonstrate', 'that', 'the', 'worstcase', 'error', 'of', 'g', 'as', 'an', 'estimate', 'of', 'f', 'is', 'increasing', 'in', 'delta', 'iii', 'we', 'give', 'a', 'general', 'sufficient', 'condition', 'for', 'g', 'to', 'underestimate', 'f', 'iv', 'we', 'give', 'a', 'general', 'sufficient', 'condition', 'for', 'g', 'to', 'dominate', 'the', 'simple', 'shift', 'smoothing', 'hwfwlambdaflambda', 'lambda0', 'when', 'the', 'parameters', 'delta', 'and', 'lambda', 'are', 'chosen', 'fairly', 'ie', 'so', 'that', 'g0h0', 'in', 'doing', 'so', 'we', 'solve', 'two', 'natural', 'open', 'problems', 'of', 'lee', 'and', 'skipper', '2016', 'concerning', 'iii', 'and', 'iv', 'for', 'root', 'functions']]
[-0.14427716391440865, 0.07393384932738216, -0.04476740077634269, 0.07210462106345797, -0.10038032065770386, -0.21087848051420485, 0.01914032284791271, 0.37734162702068014, -0.2704869012957738, -0.2559224997451644, 0.09781812130614402, -0.2549873853563197, -0.1204281078274036, 0.18979900074383022, -0.08543091632881865, 0.04125473013247359, 0.022495551849236337, 0.06939907683157305, -0.10417967249276193, -0.269543478750229, 0.32402914443432734, -0.022540795749030364, 0.17534024172861112, 0.07760931205252615, 0.09410563618741899, -0.0013294922966391965, 0.02845005499708769, 0.009928323709359968, -0.2358332734629023, 0.029048347129216303, 0.21147518433389012, 0.14709688604372428, 0.32525643874956256, -0.36392316691684745, -0.14716753031364538, 0.196664730889853, 0.09516229811258645, 0.00016236742536840124, 0.0035445983957598914, -0.2077118121911561, 0.12547043933902738, -0.07479871622547354, -0.14225999459695193, -0.037856092620468525, 0.09026938890884995, 0.06271806191614687, -0.3895511010493087, 0.0744855142324979, 0.10751076409623886, 0.03967370852957855, -0.057146982819708106, -0.15887892555968583, -0.04382289852084661, 0.05271131317864207, 0.0016080945760870175, 0.1099931043745191, 0.05976839012125269, -0.09992320168334147, 0.007732130962696095, 0.3330967408732354, -0.10521467279167578, -0.2436664225286881, 0.12148456181755957, -0.14573596258275978, -0.1539759600876137, 0.08743808415196992, 0.1353162944703957, 0.15276604854222003, -0.08130041060553875, 0.1668213407699222, -0.051052187344273976, 0.12770151561691423, 0.08386739726665089, -0.007752187576177511, 0.09297507670861305, 0.08204639033479577, 0.18603781793063406, 0.1342810276060254, -0.0035150015217428375, -0.001211070229487164, -0.39419239380783994, -0.12104973490488881, -0.1838561892568147, 0.06344801374450479, -0.08848425089013945, -0.18687955878958595, 0.34885495542376127, 0.09708870897680874, 0.207981940732556, 0.11670211180440944, 0.22409979631135493, 0.19123663887771522, 0.030828849626408025, 0.07768140292828021, 0.15460938697457102, 0.11895916328972413, 0.019194532921652734, -0.19355130763753192, 0.058809895123979807, 0.06908792655899691]
1,802.09113
GPU Accelerated Sub-Sampled Newton's Method
First order methods, which solely rely on gradient information, are commonly used in diverse machine learning (ML) and data analysis (DA) applications. This is attributed to the simplicity of their implementations, as well as low per-iteration computational/storage costs. However, they suffer from significant disadvantages; most notably, their performance degrades with increasing problem ill-conditioning. Furthermore, they often involve a large number of hyper-parameters, and are notoriously sensitive to parameters such as the step-size. By incorporating additional information from the Hessian, second-order methods, have been shown to be resilient to many such adversarial effects. However, these advantages of using curvature information come at the cost of higher per-iteration costs, which in \enquote{big data} regimes, can be computationally prohibitive. In this paper, we show that, contrary to conventional belief, second-order methods, when implemented appropriately, can be more efficient than first-order alternatives in many large-scale ML/ DA applications. In particular, in convex settings, we consider variants of classical Newton\textsf{'}s method in which the Hessian and/or the gradient are randomly sub-sampled. We show that by effectively leveraging the power of GPUs, such randomized Newton-type algorithms can be significantly accelerated, and can easily outperform state of the art implementations of existing techniques in popular ML/ DA software packages such as TensorFlow. Additionally these randomized methods incur a small memory overhead compared to first-order methods. In particular, we show that for million-dimensional problems, our GPU accelerated sub-sampled Newton\textsf{'}s method achieves a higher test accuracy in milliseconds as compared with tens of seconds for first order alternatives.
cs.LG cs.DC math.OC
first order methods which solely rely on gradient information are commonly used in diverse machine learning ml and data analysis da applications this is attributed to the simplicity of their implementations as well as low periteration computationalstorage costs however they suffer from significant disadvantages most notably their performance degrades with increasing problem illconditioning furthermore they often involve a large number of hyperparameters and are notoriously sensitive to parameters such as the stepsize by incorporating additional information from the hessian secondorder methods have been shown to be resilient to many such adversarial effects however these advantages of using curvature information come at the cost of higher periteration costs which in enquotebig data regimes can be computationally prohibitive in this paper we show that contrary to conventional belief secondorder methods when implemented appropriately can be more efficient than firstorder alternatives in many largescale ml da applications in particular in convex settings we consider variants of classical newtontextsfs method in which the hessian andor the gradient are randomly subsampled we show that by effectively leveraging the power of gpus such randomized newtontype algorithms can be significantly accelerated and can easily outperform state of the art implementations of existing techniques in popular ml da software packages such as tensorflow additionally these randomized methods incur a small memory overhead compared to firstorder methods in particular we show that for milliondimensional problems our gpu accelerated subsampled newtontextsfs method achieves a higher test accuracy in milliseconds as compared with tens of seconds for first order alternatives
[['first', 'order', 'methods', 'which', 'solely', 'rely', 'on', 'gradient', 'information', 'are', 'commonly', 'used', 'in', 'diverse', 'machine', 'learning', 'ml', 'and', 'data', 'analysis', 'da', 'applications', 'this', 'is', 'attributed', 'to', 'the', 'simplicity', 'of', 'their', 'implementations', 'as', 'well', 'as', 'low', 'periteration', 'computationalstorage', 'costs', 'however', 'they', 'suffer', 'from', 'significant', 'disadvantages', 'most', 'notably', 'their', 'performance', 'degrades', 'with', 'increasing', 'problem', 'illconditioning', 'furthermore', 'they', 'often', 'involve', 'a', 'large', 'number', 'of', 'hyperparameters', 'and', 'are', 'notoriously', 'sensitive', 'to', 'parameters', 'such', 'as', 'the', 'stepsize', 'by', 'incorporating', 'additional', 'information', 'from', 'the', 'hessian', 'secondorder', 'methods', 'have', 'been', 'shown', 'to', 'be', 'resilient', 'to', 'many', 'such', 'adversarial', 'effects', 'however', 'these', 'advantages', 'of', 'using', 'curvature', 'information', 'come', 'at', 'the', 'cost', 'of', 'higher', 'periteration', 'costs', 'which', 'in', 'enquotebig', 'data', 'regimes', 'can', 'be', 'computationally', 'prohibitive', 'in', 'this', 'paper', 'we', 'show', 'that', 'contrary', 'to', 'conventional', 'belief', 'secondorder', 'methods', 'when', 'implemented', 'appropriately', 'can', 'be', 'more', 'efficient', 'than', 'firstorder', 'alternatives', 'in', 'many', 'largescale', 'ml', 'da', 'applications', 'in', 'particular', 'in', 'convex', 'settings', 'we', 'consider', 'variants', 'of', 'classical', 'newtontextsfs', 'method', 'in', 'which', 'the', 'hessian', 'andor', 'the', 'gradient', 'are', 'randomly', 'subsampled', 'we', 'show', 'that', 'by', 'effectively', 'leveraging', 'the', 'power', 'of', 'gpus', 'such', 'randomized', 'newtontype', 'algorithms', 'can', 'be', 'significantly', 'accelerated', 'and', 'can', 'easily', 'outperform', 'state', 'of', 'the', 'art', 'implementations', 'of', 'existing', 'techniques', 'in', 'popular', 'ml', 'da', 'software', 'packages', 'such', 'as', 'tensorflow', 'additionally', 'these', 'randomized', 'methods', 'incur', 'a', 'small', 'memory', 'overhead', 'compared', 'to', 'firstorder', 'methods', 'in', 'particular', 'we', 'show', 'that', 'for', 'milliondimensional', 'problems', 'our', 'gpu', 'accelerated', 'subsampled', 'newtontextsfs', 'method', 'achieves', 'a', 'higher', 'test', 'accuracy', 'in', 'milliseconds', 'as', 'compared', 'with', 'tens', 'of', 'seconds', 'for', 'first', 'order', 'alternatives']]
[-0.038366895760560966, 0.031822217552642515, -0.04966739868571058, 0.08628486740597849, -0.09697886908566958, -0.17636083146913084, 0.02057313014198534, 0.44933058460795783, -0.3080649611230644, -0.34823605892574033, 0.15088877840889467, -0.24624154947928106, -0.16409205780099562, 0.2515635028030966, -0.1312455544002142, 0.11586375794292057, 0.1162744200990982, 0.011038275663665215, -0.12108264569601525, -0.3192312884782403, 0.24726010136149174, 0.055965881435034, 0.31146227180715497, 0.010647904932332353, 0.07058233890693816, -0.05684315646067262, 0.009476759350324823, 0.06674965744557965, -0.03217179461793924, 0.11259086124695519, 0.3203379177039762, 0.18032909485765133, 0.3508272357701468, -0.45788595759559697, -0.21586321671651884, 0.12075087105537333, 0.17481981026485743, 0.13378556827660573, -0.04701179692909033, -0.23453360332206377, 0.11645372992625641, -0.18108905248942112, -0.022502457311308784, -0.16901515911208329, -0.08439834375971762, 0.06729630028783548, -0.27872216980241815, 0.09099021039778231, 0.04490897695418462, 0.029188524750894222, 0.02945149785174602, -0.19593121980059497, 0.03852075219582161, 0.07063748189439804, 0.0771372307643741, 0.022874112377734478, 0.13514766191526095, -0.12637027843719978, -0.1575773727353208, 0.3850369192498956, -0.07022085828959565, -0.20793751698730056, 0.22665902342348232, -0.018162671142500045, -0.15582939707749804, 0.14162348696159396, 0.24774478244163642, 0.15650649336772418, -0.12389790278234059, 0.07389129716957393, 0.07288527116747345, 0.1653602802700068, 0.05869766294850203, 0.06251842567481374, 0.1026829153846389, 0.15690051595494908, 0.07559406158856942, 0.10433607539578485, -0.06670138820943354, -0.11775960947000762, -0.1919195485960056, -0.12466840429337529, -0.21228685465071548, -0.02157224759476532, -0.12386189023492057, -0.15302427930081153, 0.3260596929519339, 0.2315845157446177, 0.172071267830348, 0.07632231770785586, 0.3900016519066885, 0.08778843849561567, 0.1315321704747564, 0.15441849408860553, 0.22662757026794464, 0.024063621560995167, 0.10240535494115212, -0.17381869431356028, 0.10339409313391804, 0.006197314728945834]
1,802.09114
Loop Quantum Corrected Einstein Yang-Mills Black Holes
In this paper we study the homogeneous interiors of black holes possessing SU(2) Yang-Mills fields subject to corrections inspired by loop quantum gravity. The systems studied possess both magnetic and induced electric Yang-Mills fields. We consider the system of equations both with and without Wilson loop corrections to the Yang-Mills potential. The structure of the Yang-Mills Hamiltonian along with the restriction to homogeneity allows for an anomaly free effective quantization. In particular we study the bounce which replaces the classical singularity and the behavior of the Yang-Mills fields in the quantum corrected interior, which possesses topology $R\times S^{2}$. Beyond the bounce the magnitude of the Yang-Mills electric field asymptotically grows monotonically. This results in an ever expanding $R$ sector even though the two-sphere volume is asymptotically constant. The results are similar with and without Wilson loop corrections on the Yang-Mills potential.
gr-qc
in this paper we study the homogeneous interiors of black holes possessing su2 yangmills fields subject to corrections inspired by loop quantum gravity the systems studied possess both magnetic and induced electric yangmills fields we consider the system of equations both with and without wilson loop corrections to the yangmills potential the structure of the yangmills hamiltonian along with the restriction to homogeneity allows for an anomaly free effective quantization in particular we study the bounce which replaces the classical singularity and the behavior of the yangmills fields in the quantum corrected interior which possesses topology rtimes s2 beyond the bounce the magnitude of the yangmills electric field asymptotically grows monotonically this results in an ever expanding r sector even though the twosphere volume is asymptotically constant the results are similar with and without wilson loop corrections on the yangmills potential
[['in', 'this', 'paper', 'we', 'study', 'the', 'homogeneous', 'interiors', 'of', 'black', 'holes', 'possessing', 'su2', 'yangmills', 'fields', 'subject', 'to', 'corrections', 'inspired', 'by', 'loop', 'quantum', 'gravity', 'the', 'systems', 'studied', 'possess', 'both', 'magnetic', 'and', 'induced', 'electric', 'yangmills', 'fields', 'we', 'consider', 'the', 'system', 'of', 'equations', 'both', 'with', 'and', 'without', 'wilson', 'loop', 'corrections', 'to', 'the', 'yangmills', 'potential', 'the', 'structure', 'of', 'the', 'yangmills', 'hamiltonian', 'along', 'with', 'the', 'restriction', 'to', 'homogeneity', 'allows', 'for', 'an', 'anomaly', 'free', 'effective', 'quantization', 'in', 'particular', 'we', 'study', 'the', 'bounce', 'which', 'replaces', 'the', 'classical', 'singularity', 'and', 'the', 'behavior', 'of', 'the', 'yangmills', 'fields', 'in', 'the', 'quantum', 'corrected', 'interior', 'which', 'possesses', 'topology', 'rtimes', 's2', 'beyond', 'the', 'bounce', 'the', 'magnitude', 'of', 'the', 'yangmills', 'electric', 'field', 'asymptotically', 'grows', 'monotonically', 'this', 'results', 'in', 'an', 'ever', 'expanding', 'r', 'sector', 'even', 'though', 'the', 'twosphere', 'volume', 'is', 'asymptotically', 'constant', 'the', 'results', 'are', 'similar', 'with', 'and', 'without', 'wilson', 'loop', 'corrections', 'on', 'the', 'yangmills', 'potential']]
[-0.17593590254030117, 0.19087644358820294, -0.0662729042538455, 0.0668169853850499, -0.04414487624844761, -0.11544119554789777, -0.028514845147299586, 0.3129036037370245, -0.16272696740396903, -0.2604622338759772, 0.09855703411851713, -0.3026307235416793, -0.1537217120012493, 0.11779080311510157, -0.04585073341397529, 0.040875859499136184, -0.00036996147918997083, 0.10331533322976043, -0.13242449238400986, -0.26067636072873435, 0.36385773400386384, 0.04657166535926468, 0.25307729663921796, 0.059573667077677896, 0.09314516763011298, 0.010139961494132876, 0.02359212717662255, 0.08277595361879637, -0.12325472030656558, 0.0842812491146557, 0.14587772705968707, 0.016595119217423893, 0.1621224102745797, -0.4635995025185089, -0.24523623102073763, 0.10138669106052488, 0.15174237730853418, 0.1357885191332861, -0.027764255052980642, -0.273544902629252, 0.04011828717049079, -0.1448629247916347, -0.1950051909847621, -0.0765789279017386, -0.010268979909803374, -0.08660922324819927, -0.23442870410075015, 0.05713958382265517, 0.03554360698892055, 0.030372514259004106, -0.07117048466408044, -0.06327115995264514, -0.04381741203965474, 0.10689446336015108, 0.11865226833475093, 0.09405901097091483, 0.13840313937766016, -0.21137402022046084, -0.11185828738363711, 0.3854027968395422, -0.12197067415513468, -0.1988319850308781, 0.11747017885386574, -0.20173087021573743, -0.10946070975524948, 0.10947227323333261, 0.10789167941448853, 0.1527397036222173, -0.10534828103102863, 0.24220629732441554, 0.01960674768432658, 0.10895209769381488, 0.10419805883595072, 0.019581811859252604, 0.2408643680895474, 0.0732932804624636, 0.07426794717445019, 0.15041996128749802, -0.022259435654413087, -0.18222435842538978, -0.378428894742425, -0.1569869318458496, -0.10426805090284676, 0.11143976231336805, -0.15355611711051909, -0.23266784025435436, 0.3481446656766711, 0.12669849854766835, 0.1291722283642475, 0.037674622940467604, 0.2416487343900423, 0.1251739858061815, 0.0883995707044444, 0.11440943663358583, 0.26633090923494057, 0.2153152771647491, 0.12215282876913086, -0.2950814489509699, -0.11517096885169546, 0.13807514231942647]
1,802.09115
Magnetoentropic signatures of skyrmionic phase behavior in FeGe
We demonstrate that magnetocaloric measurements can rapidly reveal details of the phase diagrams of high-temperature skyrmion hosts, concurrently yielding quantitative latent heats of the field-driven magnetic phase transitions. Our approach addresses an outstanding issue in the phase diagram of the skyrmion host FeGe by showing that dc magnetic anomalies can be explained in terms of entropic signatures consistent with a phase diagram containing a single pocket of skyrmionic order and a Brazovskii transition.
cond-mat.mtrl-sci
we demonstrate that magnetocaloric measurements can rapidly reveal details of the phase diagrams of hightemperature skyrmion hosts concurrently yielding quantitative latent heats of the fielddriven magnetic phase transitions our approach addresses an outstanding issue in the phase diagram of the skyrmion host fege by showing that dc magnetic anomalies can be explained in terms of entropic signatures consistent with a phase diagram containing a single pocket of skyrmionic order and a brazovskii transition
[['we', 'demonstrate', 'that', 'magnetocaloric', 'measurements', 'can', 'rapidly', 'reveal', 'details', 'of', 'the', 'phase', 'diagrams', 'of', 'hightemperature', 'skyrmion', 'hosts', 'concurrently', 'yielding', 'quantitative', 'latent', 'heats', 'of', 'the', 'fielddriven', 'magnetic', 'phase', 'transitions', 'our', 'approach', 'addresses', 'an', 'outstanding', 'issue', 'in', 'the', 'phase', 'diagram', 'of', 'the', 'skyrmion', 'host', 'fege', 'by', 'showing', 'that', 'dc', 'magnetic', 'anomalies', 'can', 'be', 'explained', 'in', 'terms', 'of', 'entropic', 'signatures', 'consistent', 'with', 'a', 'phase', 'diagram', 'containing', 'a', 'single', 'pocket', 'of', 'skyrmionic', 'order', 'and', 'a', 'brazovskii', 'transition']]
[-0.22715670399827093, 0.2342594584423414, -0.07013588250704007, -0.003755831025693923, -0.09037525364044696, -0.09684120344033159, 0.1560646439200803, 0.3670101307638704, -0.2565144179771616, -0.3273361558222199, 0.03185659010371525, -0.28798733858315095, -0.16122332559770916, 0.18210452361262008, 0.00961087793366958, -0.016594811355414456, -0.03239987882441037, 0.0070906652820181765, -0.11736739231018375, -0.17798090179652942, 0.2612920764144765, -0.032356567234311205, 0.27683022877915875, 0.06623682682721378, 0.03500937538425604, -0.08145974396109223, 0.0856068902840353, 0.08088744408132074, -0.15960924895835102, -0.027613337202737592, 0.2466579742653117, -0.03648454426590047, 0.11783238302929046, -0.4193056214039456, -0.24960571424142547, 0.04565970857040829, 0.19931423148277458, 0.1332635430823246, -0.11335230870044803, -0.30945228509706996, 0.04102291671992981, -0.14664967857900854, -0.1287736773222991, -0.16893443558365107, -0.055929257241013934, -0.015117384720263681, -0.23835312441144496, 0.13424896998713687, 0.07004359519517381, 0.08152219406903198, -0.09667316495045407, -0.07693696220099211, -0.050261825970565416, 0.07879322660729697, 0.028306697485713312, 0.09445751386643579, 0.15463231152484883, -0.150034543330947, -0.17026382138671942, 0.3576934907636414, -0.03156034388955785, -0.018310462992179068, 0.10868583208792014, -0.21116429042351775, -0.12164220567920232, 0.19807434478800182, 0.08422681209567474, 0.0898444883410551, -0.13241965985818677, 0.028009156836037306, 0.01866100760406419, 0.20977309371714722, -0.01960372609048061, 0.03781110822695167, 0.33866163289608203, 0.21539263332849495, -0.056944872354705856, 0.2494756768550086, -0.12902497616277575, -0.11909544569988774, -0.22734921497024901, -0.1761367177951137, -0.187583217167691, -0.007820304700058617, -0.13730594760093245, -0.21058717526396584, 0.41398831862599067, 0.15734501794133693, 0.20327221089455758, -0.10821449048562001, 0.27153980263113364, 0.05520187983646581, 0.05207777324400536, 0.020614375985444407, 0.24079294991998434, 0.14459525676737603, 0.1395334494363976, -0.3249868973068995, 0.1195953123379907, 0.04287964885110316]
1,802.09116
Partial Distance Correlation Screening for High Dimensional Time Series
High dimensional time series datasets are becoming increasingly common in various fields such as economics, finance, meteorology, and neuroscience. Given this ubiquity of time series data, it is surprising that very few works on variable screening discuss the time series setting, and even fewer works have developed methods which utilize the unique features of time series data. This paper introduces several model free screening methods based on the partial distance correlation and developed specifically to deal with time dependent data. Methods are developed both for univariate models, such as nonlinear autoregressive models with exogenous predictors (NARX), and multivariate models such as linear or nonlinear VAR models. Sure screening properties are proved for our methods, which depend on the moment conditions, and the strength of dependence in the response and covariate processes, amongst other factors. Dependence is quantified by functional dependence measures (Wu [Proc. Natl. Acad. Sci. USA 102 (2005) 14150-14154]) and $\beta$-mixing coefficients, and the results rely on the use of Nagaev and Rosenthal type inequalities for dependent random variables. Finite sample performance of our methods is shown through extensive simulation studies, and we include an application to macroeconomic forecasting.
stat.ME
high dimensional time series datasets are becoming increasingly common in various fields such as economics finance meteorology and neuroscience given this ubiquity of time series data it is surprising that very few works on variable screening discuss the time series setting and even fewer works have developed methods which utilize the unique features of time series data this paper introduces several model free screening methods based on the partial distance correlation and developed specifically to deal with time dependent data methods are developed both for univariate models such as nonlinear autoregressive models with exogenous predictors narx and multivariate models such as linear or nonlinear var models sure screening properties are proved for our methods which depend on the moment conditions and the strength of dependence in the response and covariate processes amongst other factors dependence is quantified by functional dependence measures wu proc natl acad sci usa 102 2005 1415014154 and betamixing coefficients and the results rely on the use of nagaev and rosenthal type inequalities for dependent random variables finite sample performance of our methods is shown through extensive simulation studies and we include an application to macroeconomic forecasting
[['high', 'dimensional', 'time', 'series', 'datasets', 'are', 'becoming', 'increasingly', 'common', 'in', 'various', 'fields', 'such', 'as', 'economics', 'finance', 'meteorology', 'and', 'neuroscience', 'given', 'this', 'ubiquity', 'of', 'time', 'series', 'data', 'it', 'is', 'surprising', 'that', 'very', 'few', 'works', 'on', 'variable', 'screening', 'discuss', 'the', 'time', 'series', 'setting', 'and', 'even', 'fewer', 'works', 'have', 'developed', 'methods', 'which', 'utilize', 'the', 'unique', 'features', 'of', 'time', 'series', 'data', 'this', 'paper', 'introduces', 'several', 'model', 'free', 'screening', 'methods', 'based', 'on', 'the', 'partial', 'distance', 'correlation', 'and', 'developed', 'specifically', 'to', 'deal', 'with', 'time', 'dependent', 'data', 'methods', 'are', 'developed', 'both', 'for', 'univariate', 'models', 'such', 'as', 'nonlinear', 'autoregressive', 'models', 'with', 'exogenous', 'predictors', 'narx', 'and', 'multivariate', 'models', 'such', 'as', 'linear', 'or', 'nonlinear', 'var', 'models', 'sure', 'screening', 'properties', 'are', 'proved', 'for', 'our', 'methods', 'which', 'depend', 'on', 'the', 'moment', 'conditions', 'and', 'the', 'strength', 'of', 'dependence', 'in', 'the', 'response', 'and', 'covariate', 'processes', 'amongst', 'other', 'factors', 'dependence', 'is', 'quantified', 'by', 'functional', 'dependence', 'measures', 'wu', 'proc', 'natl', 'acad', 'sci', 'usa', '102', '2005', '1415014154', 'and', 'betamixing', 'coefficients', 'and', 'the', 'results', 'rely', 'on', 'the', 'use', 'of', 'nagaev', 'and', 'rosenthal', 'type', 'inequalities', 'for', 'dependent', 'random', 'variables', 'finite', 'sample', 'performance', 'of', 'our', 'methods', 'is', 'shown', 'through', 'extensive', 'simulation', 'studies', 'and', 'we', 'include', 'an', 'application', 'to', 'macroeconomic', 'forecasting']]
[-0.03458029764496084, 0.05308230116934283, -0.06749749444088114, 0.09046833695610985, -0.08335583856647932, -0.14236069467702978, 0.01590201828451092, 0.38662800483013454, -0.24280792082610883, -0.29469678654384457, 0.1581366571374115, -0.3030493213157905, -0.1879103955138769, 0.24764753939142745, -0.07692762541486636, 0.10034178163194539, 0.027411132922249015, -0.018147051000452944, -0.022834900077922562, -0.3121776385318586, 0.27643793804669065, 0.06584624167727797, 0.3263811760998674, 0.027477854595666654, 0.11009428118735454, 0.027546629265538955, -0.11078617629521575, 0.026250107516534626, -0.11621681117643387, 0.09705841821789937, 0.2795958044103157, 0.12283099495199215, 0.34552222996165877, -0.4401957644944272, -0.26267065756623387, 0.08585497248292852, 0.05996620320028773, 0.03841192410886594, -0.00595502629385967, -0.28116878294018344, -0.005456004835861294, -0.1598847475442055, -0.056491488979908785, -0.15840608782968238, 0.07176698594550161, 0.09042405496890607, -0.346852210368716, 0.13550184597506335, 0.056122893579671845, 0.11837602299086651, -0.04714809455725021, -0.1672160625016611, 0.026239404851252115, 0.08907640489173661, 0.10715327324701081, -0.0018331224405157723, 0.10977256497074114, -0.09010800557309841, -0.15132492935854794, 0.3280233706935848, -0.08621968313757526, -0.19477758571309478, 0.2577141517295355, -0.10537468729001519, -0.1881686483791686, 0.043970937468111516, 0.23339570136250634, 0.12729088585750248, -0.16049095471634678, 0.10829581834167536, -0.015315065454495581, 0.14797952748761561, 0.04592708398735053, 0.017244439580673843, 0.09388168636023214, 0.1552238288788909, 0.021900459060960106, 0.058552189298452025, -0.07620361800133986, -0.1035618370496913, -0.24797058694162652, -0.09980248993654785, -0.17534283453500585, -0.0030943157800816393, -0.11009774824334799, -0.18916922099199024, 0.37103024853322975, 0.1820277958749916, 0.17313594003453067, 0.06441200355337443, 0.23806891554574433, 0.13527773333449947, 0.03169272597879171, 0.07515132849006669, 0.14864679550090315, 0.12637879832427165, 0.1263599263234554, -0.16012696919129474, 0.1268295142162395, 0.039404816048121766]
1,802.09117
Testability of high-dimensional linear models with non-sparse structures
Understanding statistical inference under possibly non-sparse high-dimensional models has gained much interest recently. For a given component of the regression coefficient, we show that the difficulty of the problem depends on the sparsity of the corresponding row of the precision matrix of the covariates, not the sparsity of the regression coefficients. We develop new concepts of uniform and essentially uniform non-testability that allow the study of limitations of tests across a broad set of alternatives. Uniform non-testability identifies a collection of alternatives such that the power of any test, against any alternative in the group, is asymptotically at most equal to the nominal size. Implications of the new constructions include new minimax testability results that, in sharp contrast to the current results, do not depend on the sparsity of the regression parameters. We identify new tradeoffs between testability and feature correlation. In particular, we show that, in models with weak feature correlations, minimax lower bound can be attained by a test whose power has the $\sqrt{n}$ rate, regardless of the size of the model sparsity.
math.ST stat.ME stat.ML stat.TH
understanding statistical inference under possibly nonsparse highdimensional models has gained much interest recently for a given component of the regression coefficient we show that the difficulty of the problem depends on the sparsity of the corresponding row of the precision matrix of the covariates not the sparsity of the regression coefficients we develop new concepts of uniform and essentially uniform nontestability that allow the study of limitations of tests across a broad set of alternatives uniform nontestability identifies a collection of alternatives such that the power of any test against any alternative in the group is asymptotically at most equal to the nominal size implications of the new constructions include new minimax testability results that in sharp contrast to the current results do not depend on the sparsity of the regression parameters we identify new tradeoffs between testability and feature correlation in particular we show that in models with weak feature correlations minimax lower bound can be attained by a test whose power has the sqrtn rate regardless of the size of the model sparsity
[['understanding', 'statistical', 'inference', 'under', 'possibly', 'nonsparse', 'highdimensional', 'models', 'has', 'gained', 'much', 'interest', 'recently', 'for', 'a', 'given', 'component', 'of', 'the', 'regression', 'coefficient', 'we', 'show', 'that', 'the', 'difficulty', 'of', 'the', 'problem', 'depends', 'on', 'the', 'sparsity', 'of', 'the', 'corresponding', 'row', 'of', 'the', 'precision', 'matrix', 'of', 'the', 'covariates', 'not', 'the', 'sparsity', 'of', 'the', 'regression', 'coefficients', 'we', 'develop', 'new', 'concepts', 'of', 'uniform', 'and', 'essentially', 'uniform', 'nontestability', 'that', 'allow', 'the', 'study', 'of', 'limitations', 'of', 'tests', 'across', 'a', 'broad', 'set', 'of', 'alternatives', 'uniform', 'nontestability', 'identifies', 'a', 'collection', 'of', 'alternatives', 'such', 'that', 'the', 'power', 'of', 'any', 'test', 'against', 'any', 'alternative', 'in', 'the', 'group', 'is', 'asymptotically', 'at', 'most', 'equal', 'to', 'the', 'nominal', 'size', 'implications', 'of', 'the', 'new', 'constructions', 'include', 'new', 'minimax', 'testability', 'results', 'that', 'in', 'sharp', 'contrast', 'to', 'the', 'current', 'results', 'do', 'not', 'depend', 'on', 'the', 'sparsity', 'of', 'the', 'regression', 'parameters', 'we', 'identify', 'new', 'tradeoffs', 'between', 'testability', 'and', 'feature', 'correlation', 'in', 'particular', 'we', 'show', 'that', 'in', 'models', 'with', 'weak', 'feature', 'correlations', 'minimax', 'lower', 'bound', 'can', 'be', 'attained', 'by', 'a', 'test', 'whose', 'power', 'has', 'the', 'sqrtn', 'rate', 'regardless', 'of', 'the', 'size', 'of', 'the', 'model', 'sparsity']]
[-0.0701527995975422, 0.06785306502200131, -0.0692555852154536, 0.059230742207728324, -0.0775520367947008, -0.13959509081606353, 0.05690898748048182, 0.34570226533072335, -0.27071509374372127, -0.27614368563384883, 0.11427003414769257, -0.23369790680174315, -0.13721144976227412, 0.19883295968640596, -0.09615064325609378, 0.0901753618415179, 0.027163026545728955, 0.05932484186503903, -0.10371142210039709, -0.2899537418410182, 0.32289959170057303, 0.07642388700507581, 0.3203701026684472, 0.03587549369615902, 0.09269671054290873, -0.0006911030398415668, -0.03917243114805647, 0.031125235509659562, -0.13159644025348827, 0.14721548414988708, 0.23696827686179728, 0.1855563195581947, 0.3260904967093042, -0.37779241626816135, -0.20751492710118846, 0.14246026564921652, 0.10168411448065724, 0.06937233381239431, -0.03370670332307262, -0.22666931461276751, 0.0981785439540233, -0.13746122498065233, -0.07895154254244907, -0.0769166049188269, -0.01764130850987775, 0.03910461310696389, -0.3318990234684731, 0.08285386682354978, 0.11636751164815255, 0.03985264141112566, -0.038168003988851396, -0.15692044354043902, 0.03556052272740219, 0.11462059941408889, 0.07611405335167157, -0.033257467675554965, 0.08943180713004299, -0.1559172583158527, -0.1285349955885405, 0.3463638767440404, -0.07254589555286137, -0.220480593065066, 0.2031439302216417, -0.16105336981426394, -0.16125223879303252, 0.09089893884491175, 0.20682292574218342, 0.08503744992294482, -0.11051808883036886, 0.1136369060798149, -0.07977200020636831, 0.1965698446173753, 0.048702239217569256, 0.05902105361489313, 0.1610762372825827, 0.173590344599049, 0.11632628400610494, 0.11283002361455666, -0.09390129136453781, -0.04822887475203191, -0.29989164818610464, -0.12669077115931682, -0.21096462619091783, -0.01532512411724643, -0.17944409649004228, -0.17715377956296186, 0.41631671448903423, 0.19036555738321373, 0.2296942788708423, 0.09499837093371233, 0.2530439007282257, 0.10092555705931902, 0.07193865550415857, 0.08205330635154887, 0.2527561083223139, 0.1167709183120834, -0.00562777748996658, -0.19591833823360502, 0.1404225443303585, 0.026096844363159368]
1,802.09118
Multi-Commodity Flow with In-Network Processing
Modern networks run "middleboxes" that offer services ranging from network address translation and server load balancing to firewalls, encryption, and compression. In an industry trend known as Network Functions Virtualization (NFV), these middleboxes run as virtual machines on any commodity server, and the switches steer traffic through the relevant chain of services. Network administrators must decide how many middleboxes to run, where to place them, and how to direct traffic through them, based on the traffic load and the server and network capacity. Rather than placing specific kinds of middleboxes on each processing node, we argue that server virtualization allows each server node to host all middlebox functions, and simply vary the fraction of resources devoted to each one. This extra flexibility fundamentally changes the optimization problem the network administrators must solve to a new kind of multi-commodity flow problem, where the traffic flows consume bandwidth on the links as well as processing resources on the nodes. We show that allocating resources to maximize the processed flow can be optimized exactly via a linear programming formulation, and to arbitrary accuracy via an efficient combinatorial algorithm. Our experiments with real traffic and topologies show that a joint optimization of node and link resources leads to an efficient use of bandwidth and processing capacity. We also study a class of design problems that decide where to provide node capacity to best process and route a given set of demands, and demonstrate both approximation algorithms and hardness results for these problems.
cs.DS cs.NI
modern networks run middleboxes that offer services ranging from network address translation and server load balancing to firewalls encryption and compression in an industry trend known as network functions virtualization nfv these middleboxes run as virtual machines on any commodity server and the switches steer traffic through the relevant chain of services network administrators must decide how many middleboxes to run where to place them and how to direct traffic through them based on the traffic load and the server and network capacity rather than placing specific kinds of middleboxes on each processing node we argue that server virtualization allows each server node to host all middlebox functions and simply vary the fraction of resources devoted to each one this extra flexibility fundamentally changes the optimization problem the network administrators must solve to a new kind of multicommodity flow problem where the traffic flows consume bandwidth on the links as well as processing resources on the nodes we show that allocating resources to maximize the processed flow can be optimized exactly via a linear programming formulation and to arbitrary accuracy via an efficient combinatorial algorithm our experiments with real traffic and topologies show that a joint optimization of node and link resources leads to an efficient use of bandwidth and processing capacity we also study a class of design problems that decide where to provide node capacity to best process and route a given set of demands and demonstrate both approximation algorithms and hardness results for these problems
[['modern', 'networks', 'run', 'middleboxes', 'that', 'offer', 'services', 'ranging', 'from', 'network', 'address', 'translation', 'and', 'server', 'load', 'balancing', 'to', 'firewalls', 'encryption', 'and', 'compression', 'in', 'an', 'industry', 'trend', 'known', 'as', 'network', 'functions', 'virtualization', 'nfv', 'these', 'middleboxes', 'run', 'as', 'virtual', 'machines', 'on', 'any', 'commodity', 'server', 'and', 'the', 'switches', 'steer', 'traffic', 'through', 'the', 'relevant', 'chain', 'of', 'services', 'network', 'administrators', 'must', 'decide', 'how', 'many', 'middleboxes', 'to', 'run', 'where', 'to', 'place', 'them', 'and', 'how', 'to', 'direct', 'traffic', 'through', 'them', 'based', 'on', 'the', 'traffic', 'load', 'and', 'the', 'server', 'and', 'network', 'capacity', 'rather', 'than', 'placing', 'specific', 'kinds', 'of', 'middleboxes', 'on', 'each', 'processing', 'node', 'we', 'argue', 'that', 'server', 'virtualization', 'allows', 'each', 'server', 'node', 'to', 'host', 'all', 'middlebox', 'functions', 'and', 'simply', 'vary', 'the', 'fraction', 'of', 'resources', 'devoted', 'to', 'each', 'one', 'this', 'extra', 'flexibility', 'fundamentally', 'changes', 'the', 'optimization', 'problem', 'the', 'network', 'administrators', 'must', 'solve', 'to', 'a', 'new', 'kind', 'of', 'multicommodity', 'flow', 'problem', 'where', 'the', 'traffic', 'flows', 'consume', 'bandwidth', 'on', 'the', 'links', 'as', 'well', 'as', 'processing', 'resources', 'on', 'the', 'nodes', 'we', 'show', 'that', 'allocating', 'resources', 'to', 'maximize', 'the', 'processed', 'flow', 'can', 'be', 'optimized', 'exactly', 'via', 'a', 'linear', 'programming', 'formulation', 'and', 'to', 'arbitrary', 'accuracy', 'via', 'an', 'efficient', 'combinatorial', 'algorithm', 'our', 'experiments', 'with', 'real', 'traffic', 'and', 'topologies', 'show', 'that', 'a', 'joint', 'optimization', 'of', 'node', 'and', 'link', 'resources', 'leads', 'to', 'an', 'efficient', 'use', 'of', 'bandwidth', 'and', 'processing', 'capacity', 'we', 'also', 'study', 'a', 'class', 'of', 'design', 'problems', 'that', 'decide', 'where', 'to', 'provide', 'node', 'capacity', 'to', 'best', 'process', 'and', 'route', 'a', 'given', 'set', 'of', 'demands', 'and', 'demonstrate', 'both', 'approximation', 'algorithms', 'and', 'hardness', 'results', 'for', 'these', 'problems']]
[-0.17640469749007495, 0.012165611083776551, -0.0349594910644115, 0.027094295076384726, -0.14263618765999714, -0.24301842815944955, 0.16758281992881693, 0.4034960454455652, -0.3379176607460625, -0.3272457794481588, 0.12405395689054258, -0.25865640113560434, -0.13309136312924355, 0.18690611817310715, -0.1035271532694629, 0.09544954623467469, 0.09213874523758873, 0.03377061598521616, 0.006501989009642961, -0.29691989538485125, 0.27713799448646304, 0.050847940099981406, 0.34420035806514565, 0.09717507663862629, 0.07862697426272432, 0.010260060495291386, -0.00026028682928412193, -0.011716384634529542, -0.073215525994255, 0.1272505651819419, 0.32581209259543326, 0.22369926226993783, 0.3053893021142651, -0.5162084193059033, -0.20407559058343572, 0.11982969255252336, 0.143362112226896, 0.034576537335411675, 0.007548861252050096, -0.24945305733220471, 0.11020123586011675, -0.23265616517023918, -0.030752134270920987, -0.07400986287510962, -0.019245570576223996, 0.056778379057857, -0.2796129987484986, -0.07076752087396604, -0.03448491499734847, 0.0034717176289808366, -0.019632687934180496, -0.05094189718065242, -0.02372605210421757, 0.1899598029398945, 0.02419442989693996, 0.024700048603511778, 0.19594706103652565, -0.13752080264948158, -0.17712578690242803, 0.40442307231827607, 0.048445620109041264, -0.19674645351610268, 0.19084229520916368, 0.025434881404620566, -0.17145787258707587, 0.07772069736740612, 0.27938167717788487, 0.04450868387580305, -0.1837866380960951, -0.002050737965375095, -0.0016665527232802443, 0.18771633426583703, 0.07521151742830331, 0.044366120529781665, 0.16135663191615154, 0.18652512639152607, 0.16740652858859376, 0.16705391731868016, -0.02626333659868725, -0.11501623749087055, -0.21197692931614695, -0.16586053165871906, -0.21519157497048932, 0.01252531025637572, -0.11755216236070415, -0.12570140418228543, 0.36962242832317227, 0.16850403868428174, 0.16982927841731468, 0.133204109144337, 0.38535687162901366, 0.05478949633370869, 0.12166553836681077, 0.20283876857419889, 0.09858369514950027, 0.006166297106603686, 0.1924821149399166, -0.18506399471117485, 0.10023623208079728, 0.0117722088865365]
1,802.09119
Prototyping Virtual Reality Serious Games for Building Earthquake Preparedness: The Auckland City Hospital Case Study
Enhancing evacuee safety is a key factor in reducing the number of injuries and deaths that result from earthquakes. One way this can be achieved is by training occupants. Virtual Reality (VR) and Serious Games (SGs), represent novel techniques that may overcome the limitations of traditional training approaches. VR and SGs have been examined in the fire emergency context, however, their application to earthquake preparedness has not yet been extensively examined. We provide a theoretical discussion of the advantages and limitations of using VR SGs to investigate how building occupants behave during earthquake evacuations and to train building occupants to cope with such emergencies. We explore key design components for developing a VR SG framework: (a) what features constitute an earthquake event, (b) which building types can be selected and represented within the VR environment, (c) how damage to the building can be determined and represented, (d) how non-player characters (NPC) can be designed, and (e) what level of interaction there can be between NPC and the human participants. We illustrate the above by presenting the Auckland City Hospital, New Zealand as a case study, and propose a possible VR SG training tool to enhance earthquake preparedness in public buildings.
cs.AI
enhancing evacuee safety is a key factor in reducing the number of injuries and deaths that result from earthquakes one way this can be achieved is by training occupants virtual reality vr and serious games sgs represent novel techniques that may overcome the limitations of traditional training approaches vr and sgs have been examined in the fire emergency context however their application to earthquake preparedness has not yet been extensively examined we provide a theoretical discussion of the advantages and limitations of using vr sgs to investigate how building occupants behave during earthquake evacuations and to train building occupants to cope with such emergencies we explore key design components for developing a vr sg framework a what features constitute an earthquake event b which building types can be selected and represented within the vr environment c how damage to the building can be determined and represented d how nonplayer characters npc can be designed and e what level of interaction there can be between npc and the human participants we illustrate the above by presenting the auckland city hospital new zealand as a case study and propose a possible vr sg training tool to enhance earthquake preparedness in public buildings
[['enhancing', 'evacuee', 'safety', 'is', 'a', 'key', 'factor', 'in', 'reducing', 'the', 'number', 'of', 'injuries', 'and', 'deaths', 'that', 'result', 'from', 'earthquakes', 'one', 'way', 'this', 'can', 'be', 'achieved', 'is', 'by', 'training', 'occupants', 'virtual', 'reality', 'vr', 'and', 'serious', 'games', 'sgs', 'represent', 'novel', 'techniques', 'that', 'may', 'overcome', 'the', 'limitations', 'of', 'traditional', 'training', 'approaches', 'vr', 'and', 'sgs', 'have', 'been', 'examined', 'in', 'the', 'fire', 'emergency', 'context', 'however', 'their', 'application', 'to', 'earthquake', 'preparedness', 'has', 'not', 'yet', 'been', 'extensively', 'examined', 'we', 'provide', 'a', 'theoretical', 'discussion', 'of', 'the', 'advantages', 'and', 'limitations', 'of', 'using', 'vr', 'sgs', 'to', 'investigate', 'how', 'building', 'occupants', 'behave', 'during', 'earthquake', 'evacuations', 'and', 'to', 'train', 'building', 'occupants', 'to', 'cope', 'with', 'such', 'emergencies', 'we', 'explore', 'key', 'design', 'components', 'for', 'developing', 'a', 'vr', 'sg', 'framework', 'a', 'what', 'features', 'constitute', 'an', 'earthquake', 'event', 'b', 'which', 'building', 'types', 'can', 'be', 'selected', 'and', 'represented', 'within', 'the', 'vr', 'environment', 'c', 'how', 'damage', 'to', 'the', 'building', 'can', 'be', 'determined', 'and', 'represented', 'd', 'how', 'nonplayer', 'characters', 'npc', 'can', 'be', 'designed', 'and', 'e', 'what', 'level', 'of', 'interaction', 'there', 'can', 'be', 'between', 'npc', 'and', 'the', 'human', 'participants', 'we', 'illustrate', 'the', 'above', 'by', 'presenting', 'the', 'auckland', 'city', 'hospital', 'new', 'zealand', 'as', 'a', 'case', 'study', 'and', 'propose', 'a', 'possible', 'vr', 'sg', 'training', 'tool', 'to', 'enhance', 'earthquake', 'preparedness', 'in', 'public', 'buildings']]
[-0.07468322351924143, 0.08997445970278932, -0.08743402278516442, 0.09733406571904198, -0.0895351802976802, -0.15089086535270327, 0.055893252263776956, 0.3943569139763713, -0.23290623708162456, -0.34637570825405417, 0.13044512168329675, -0.2429001895734109, -0.19335706131532787, 0.18695096121635288, -0.16818960690521634, 0.022447782756644302, 0.056237009834731, 0.013564672522625188, 0.020354143648582977, -0.2616646854369901, 0.2571921116998419, 0.034220084911212326, 0.2866784666245803, 0.06902446172083727, 0.05992667579441331, -0.023703239971437143, -0.021966965578030795, 0.03303705810569227, -0.07242999050569779, 0.1276180091011338, 0.3351945766704739, 0.21283608767436818, 0.3434775528125465, -0.4603665617993101, -0.2392884573736228, 0.13119214246282354, 0.14916173255143803, 0.05086676120394259, -0.03525371465599164, -0.32244262569467536, 0.11553148494218476, -0.2389376438211184, -0.14045743823924567, -0.07442331376019866, 0.035615978674031795, 0.038492170456447636, -0.2509897867660038, -0.011994952203240246, 0.027393611410880113, 0.10947590808384121, -0.018996338662691414, -0.09481824757764117, -0.004669054578407668, 0.22397328329505398, 0.059466084002633576, 0.020103598005516688, 0.15265055765223223, -0.13203549931466113, -0.13998982473975047, 0.416812818814069, 0.0014060771139338612, -0.1305051055345393, 0.18960934321017703, -0.05530900616038707, -0.08878761467523873, 0.03723252325609792, 0.2546012648520991, 0.02833551532123238, -0.1895363711565733, -0.0042433247232111174, 0.018182999660639326, 0.12011779937776737, 0.07422512701479718, -0.027259851341950705, 0.19770366523996927, 0.23346612711669879, 0.03071389279091818, 0.0912778392911423, -0.09555565281305461, -0.055394272927951536, -0.242390653192997, -0.15475877771968954, -0.15058105248492212, 0.016831854690171896, -0.04465343398667756, -0.1286979348026216, 0.39684505882672966, 0.21345757569710258, 0.14989513317472303, 0.014085066234110854, 0.27118883245741016, 0.0765079715003958, 0.12824563602305716, 0.0937912288843654, 0.19210940906836185, 0.000774527897592634, 0.132001416827552, -0.16403614149719942, 0.11351960610714741, 0.026518811461282894]
1,802.0912
Exceeding the Nonlinear Shannon-Limit in Coherent Optical Communications by MIMO Machine Learning
The nonlinear Shannon capacity limit has been identified as the fundamental barrier to the maximum rate of transmitted information in optical communications. In long-haul high-bandwidth optical networks, this limit is mainly attributed to deterministic Kerr-induced fiber nonlinearities and from the interaction of amplified spontaneous emission noise from cascaded optical amplifiers with fiber nonlinearity: the stochastic parametric noise amplification. Unlike earlier impractical approaches that compensate solely deterministic nonlinearities, here we demonstrate a novel electronic-based deep neural network with multiple-inputs and outputs (MIMO) that tackles the interplay of deterministic and stochastic nonlinearity manifestation in coherent optical signals. Our demonstration shows that MIMO deep learning can compensate nonlinear inter-carrier crosstalk effects even in the presence of frequency stochastic variations, which has hitherto been considered impossible. Our solution significantly outperforms conventional machine learning and gold-standard nonlinear equalizers without sacrificing computational complexity, leading to record-breaking transmission performance for up to 40 Gbit/sec high-spectral-efficient optical signals.
eess.SP physics.optics
the nonlinear shannon capacity limit has been identified as the fundamental barrier to the maximum rate of transmitted information in optical communications in longhaul highbandwidth optical networks this limit is mainly attributed to deterministic kerrinduced fiber nonlinearities and from the interaction of amplified spontaneous emission noise from cascaded optical amplifiers with fiber nonlinearity the stochastic parametric noise amplification unlike earlier impractical approaches that compensate solely deterministic nonlinearities here we demonstrate a novel electronicbased deep neural network with multipleinputs and outputs mimo that tackles the interplay of deterministic and stochastic nonlinearity manifestation in coherent optical signals our demonstration shows that mimo deep learning can compensate nonlinear intercarrier crosstalk effects even in the presence of frequency stochastic variations which has hitherto been considered impossible our solution significantly outperforms conventional machine learning and goldstandard nonlinear equalizers without sacrificing computational complexity leading to recordbreaking transmission performance for up to 40 gbitsec highspectralefficient optical signals
[['the', 'nonlinear', 'shannon', 'capacity', 'limit', 'has', 'been', 'identified', 'as', 'the', 'fundamental', 'barrier', 'to', 'the', 'maximum', 'rate', 'of', 'transmitted', 'information', 'in', 'optical', 'communications', 'in', 'longhaul', 'highbandwidth', 'optical', 'networks', 'this', 'limit', 'is', 'mainly', 'attributed', 'to', 'deterministic', 'kerrinduced', 'fiber', 'nonlinearities', 'and', 'from', 'the', 'interaction', 'of', 'amplified', 'spontaneous', 'emission', 'noise', 'from', 'cascaded', 'optical', 'amplifiers', 'with', 'fiber', 'nonlinearity', 'the', 'stochastic', 'parametric', 'noise', 'amplification', 'unlike', 'earlier', 'impractical', 'approaches', 'that', 'compensate', 'solely', 'deterministic', 'nonlinearities', 'here', 'we', 'demonstrate', 'a', 'novel', 'electronicbased', 'deep', 'neural', 'network', 'with', 'multipleinputs', 'and', 'outputs', 'mimo', 'that', 'tackles', 'the', 'interplay', 'of', 'deterministic', 'and', 'stochastic', 'nonlinearity', 'manifestation', 'in', 'coherent', 'optical', 'signals', 'our', 'demonstration', 'shows', 'that', 'mimo', 'deep', 'learning', 'can', 'compensate', 'nonlinear', 'intercarrier', 'crosstalk', 'effects', 'even', 'in', 'the', 'presence', 'of', 'frequency', 'stochastic', 'variations', 'which', 'has', 'hitherto', 'been', 'considered', 'impossible', 'our', 'solution', 'significantly', 'outperforms', 'conventional', 'machine', 'learning', 'and', 'goldstandard', 'nonlinear', 'equalizers', 'without', 'sacrificing', 'computational', 'complexity', 'leading', 'to', 'recordbreaking', 'transmission', 'performance', 'for', 'up', 'to', '40', 'gbitsec', 'highspectralefficient', 'optical', 'signals']]
[-0.15366364710309818, 0.060440095783387486, -0.007020893566486602, 0.021859173870620294, -0.10189389550076747, -0.22510971168034105, 0.04787169764529461, 0.41231963701697216, -0.30315552421568615, -0.24100394285837742, 0.08598264264150497, -0.25952902704955555, -0.2335291606786258, 0.2278221626073827, -0.123321190393039, 0.12033602172301176, 0.04227130309477247, -0.04701832438995306, -0.00010632048911616407, -0.21105923834477072, 0.24350152823073487, 0.062359544086329814, 0.39096201310639045, 0.0022264647083608687, 0.1522748807973757, -0.009047762097513958, -0.006539272961703859, -0.05697459534889817, -0.02957113313474307, 0.08074625450614337, 0.3135134854697704, 0.0804870998875452, 0.3138606933927214, -0.4350798958660783, -0.31683432424088587, 0.14144041686715256, 0.17861622486403528, 0.169210193843134, -0.03598012762597284, -0.29390714568639725, 0.030444242373247304, -0.15692484678977445, -0.0102449819733502, -0.0654760470576081, -0.05461676191732073, 0.04459385964956537, -0.28808781086794427, 0.08223827441877408, 0.09505219027522725, 0.05969058601437388, 0.007796389491272134, -0.06317809528067105, 0.01794112683116534, 0.06625070969410543, -0.022824777214712388, -0.008141916205106, 0.1278081052933467, -0.17629820053549042, -0.1531246171955875, 0.3161359141526486, -0.10494784114574007, -0.1565019143839694, 0.16970770339154312, -0.0913173989392817, -0.0652963539610642, 0.22957467803781903, 0.23947491821505734, 0.02862601030603794, -0.16542269514065008, 0.022966084163321333, 0.07662556873558946, 0.24994372745120041, 0.11565982218756266, 0.15611566359340842, 0.12222444077063277, 0.2288073255221133, 0.03564718637514759, 0.15654300954790684, -0.14083621382549708, -0.09091272758716415, -0.18619740809977836, -0.038150722985281736, -0.19557654695126, 0.07279777406035243, -0.0890282742970944, -0.09932800370281895, 0.3419908525334117, 0.18967263622058406, 0.0974715105918664, 0.08270090380510492, 0.41026366534454095, 0.14312672910809116, 0.11824912703092638, 0.062249490925161216, 0.3446252054434169, 0.14802792775161513, 0.142093317086865, -0.26189485260102946, 0.07542626586006451, -0.029025342557705135]
1,802.09121
Limits on representing Boolean functions by linear combinations of simple functions: thresholds, ReLUs, and low-degree polynomials
We consider the problem of representing Boolean functions exactly by "sparse" linear combinations (over $\mathbb{R}$) of functions from some "simple" class ${\cal C}$. In particular, given ${\cal C}$ we are interested in finding low-complexity functions lacking sparse representations. When ${\cal C}$ is the set of PARITY functions or the set of conjunctions, this sort of problem has a well-understood answer, the problem becomes interesting when ${\cal C}$ is "overcomplete" and the set of functions is not linearly independent. We focus on the cases where ${\cal C}$ is the set of linear threshold functions, the set of rectified linear units (ReLUs), and the set of low-degree polynomials over a finite field, all of which are well-studied in different contexts. We provide generic tools for proving lower bounds on representations of this kind. Applying these, we give several new lower bounds for "semi-explicit" Boolean functions. For example, we show there are functions in nondeterministic quasi-polynomial time that require super-polynomial size: $\bullet$ Depth-two neural networks with sign activation function, a special case of depth-two threshold circuit lower bounds. $\bullet$ Depth-two neural networks with ReLU activation function. $\bullet$ $\mathbb{R}$-linear combinations of $O(1)$-degree $\mathbb{F}_p$-polynomials, for every prime $p$ (related to problems regarding Higher-Order "Uncertainty Principles"). We also obtain a function in $E^{NP}$ requiring $2^{\Omega(n)}$ linear combinations. $\bullet$ $\mathbb{R}$-linear combinations of $ACC \circ THR$ circuits of polynomial size (further generalizing the recent lower bounds of Murray and the author). (The above is a shortened abstract. For the full abstract, see the paper.)
cs.CC cs.DM cs.NE
we consider the problem of representing boolean functions exactly by sparse linear combinations over mathbbr of functions from some simple class cal c in particular given cal c we are interested in finding lowcomplexity functions lacking sparse representations when cal c is the set of parity functions or the set of conjunctions this sort of problem has a wellunderstood answer the problem becomes interesting when cal c is overcomplete and the set of functions is not linearly independent we focus on the cases where cal c is the set of linear threshold functions the set of rectified linear units relus and the set of lowdegree polynomials over a finite field all of which are wellstudied in different contexts we provide generic tools for proving lower bounds on representations of this kind applying these we give several new lower bounds for semiexplicit boolean functions for example we show there are functions in nondeterministic quasipolynomial time that require superpolynomial size bullet depthtwo neural networks with sign activation function a special case of depthtwo threshold circuit lower bounds bullet depthtwo neural networks with relu activation function bullet mathbbrlinear combinations of o1degree mathbbf_ppolynomials for every prime p related to problems regarding higherorder uncertainty principles we also obtain a function in enp requiring 2omegan linear combinations bullet mathbbrlinear combinations of acc circ thr circuits of polynomial size further generalizing the recent lower bounds of murray and the author the above is a shortened abstract for the full abstract see the paper
[['we', 'consider', 'the', 'problem', 'of', 'representing', 'boolean', 'functions', 'exactly', 'by', 'sparse', 'linear', 'combinations', 'over', 'mathbbr', 'of', 'functions', 'from', 'some', 'simple', 'class', 'cal', 'c', 'in', 'particular', 'given', 'cal', 'c', 'we', 'are', 'interested', 'in', 'finding', 'lowcomplexity', 'functions', 'lacking', 'sparse', 'representations', 'when', 'cal', 'c', 'is', 'the', 'set', 'of', 'parity', 'functions', 'or', 'the', 'set', 'of', 'conjunctions', 'this', 'sort', 'of', 'problem', 'has', 'a', 'wellunderstood', 'answer', 'the', 'problem', 'becomes', 'interesting', 'when', 'cal', 'c', 'is', 'overcomplete', 'and', 'the', 'set', 'of', 'functions', 'is', 'not', 'linearly', 'independent', 'we', 'focus', 'on', 'the', 'cases', 'where', 'cal', 'c', 'is', 'the', 'set', 'of', 'linear', 'threshold', 'functions', 'the', 'set', 'of', 'rectified', 'linear', 'units', 'relus', 'and', 'the', 'set', 'of', 'lowdegree', 'polynomials', 'over', 'a', 'finite', 'field', 'all', 'of', 'which', 'are', 'wellstudied', 'in', 'different', 'contexts', 'we', 'provide', 'generic', 'tools', 'for', 'proving', 'lower', 'bounds', 'on', 'representations', 'of', 'this', 'kind', 'applying', 'these', 'we', 'give', 'several', 'new', 'lower', 'bounds', 'for', 'semiexplicit', 'boolean', 'functions', 'for', 'example', 'we', 'show', 'there', 'are', 'functions', 'in', 'nondeterministic', 'quasipolynomial', 'time', 'that', 'require', 'superpolynomial', 'size', 'bullet', 'depthtwo', 'neural', 'networks', 'with', 'sign', 'activation', 'function', 'a', 'special', 'case', 'of', 'depthtwo', 'threshold', 'circuit', 'lower', 'bounds', 'bullet', 'depthtwo', 'neural', 'networks', 'with', 'relu', 'activation', 'function', 'bullet', 'mathbbrlinear', 'combinations', 'of', 'o1degree', 'mathbbf_ppolynomials', 'for', 'every', 'prime', 'p', 'related', 'to', 'problems', 'regarding', 'higherorder', 'uncertainty', 'principles', 'we', 'also', 'obtain', 'a', 'function', 'in', 'enp', 'requiring', '2omegan', 'linear', 'combinations', 'bullet', 'mathbbrlinear', 'combinations', 'of', 'acc', 'circ', 'thr', 'circuits', 'of', 'polynomial', 'size', 'further', 'generalizing', 'the', 'recent', 'lower', 'bounds', 'of', 'murray', 'and', 'the', 'author', 'the', 'above', 'is', 'a', 'shortened', 'abstract', 'for', 'the', 'full', 'abstract', 'see', 'the', 'paper']]
[-0.12890936728933308, 0.08890156562012605, 0.002869243976911988, 0.060642011056665605, -0.08330316875191009, -0.1633537662097207, 0.045757723083341736, 0.34820181485570845, -0.3088843803795543, -0.24815295675967927, 0.08970777618128149, -0.258661820147698, -0.17368008583291725, 0.24214134350816002, -0.04834149719681591, 0.12623449557815816, 0.023050813804014175, 0.05846402020354423, -0.0875310563963273, -0.29280596636483813, 0.3107746401448642, -0.023789962289900688, 0.18589903508908437, 0.03389369908407269, 0.08814084435336972, 0.0012445578363067546, 0.0017425420941674288, 0.005010860193034786, -0.13581718838613, 0.10992792629318113, 0.27878889899517667, 0.21062384471012785, 0.28762747671027655, -0.41740509133428605, -0.13965778320562094, 0.1885158660741462, 0.1091824538168902, 0.0734999587002676, 0.012150247857073842, -0.21074305467219778, 0.11988409632887523, -0.1379279531242677, -0.05676714742277581, -0.0501804419833266, 0.08618058933977603, 0.057992767473896506, -0.3109337704553895, 0.031417923472649, 0.11305990446068835, 0.07550612950008592, -0.018642834594786228, -0.203317846344511, 0.03839113034563689, 0.04853912470809787, -0.0492882169156645, 0.060724981199304924, 0.08691729965679859, -0.12842936619360487, -0.1299843767239926, 0.31758087922315126, -0.027991852889097005, -0.23697720634842628, 0.13925783765277078, -0.13458719590350676, -0.19749337963027055, 0.07000071792548415, 0.17966606375593386, 0.13939166249569934, -0.07152261451560886, 0.1595848832161597, -0.13635219433955603, 0.15697119980726054, 0.11838869229684294, 0.06004536954078205, 0.10550443415499491, 0.12214380822270407, 0.10451889526123777, 0.19406211550622324, 0.03928203747386388, -0.03096440212980493, -0.34666532339894623, -0.09413770565784109, -0.14997923210478906, 0.041637447834471486, -0.1332548137945166, -0.19470486152901878, 0.38615354077630965, 0.06779437330475108, 0.20168567563933854, 0.19121046634591338, 0.2302978089046817, 0.18029523294809804, 0.06835773607122438, 0.10485500836559786, 0.1507936737527088, 0.1304409281583503, 0.008994551478803051, -0.15396565368654755, 0.09004140476320228, 0.12217467303051933]
1,802.09122
Wrong Sign Bottom Yukawa in Low Energy Supersymmetry
The study of the Higgs boson properties is one of the most relevant activities in current particle physics. In particular, the Higgs boson couplings to third generation fermions is an important test of the mechanism of mass generation. In spite of their impact on the production and decay properties of the Higgs boson, the values of these couplings are still uncertain and, in models of new physics, they can differ in magnitude as well as in sign with respect to the Standard Model case. In this article, we study the possibility of a wrong sign bottom-quark Yukawa coupling within the framework of the Minimal and Next-to-Minimal Supersymmetric Standard Model. Possible experimental tests are also discussed, including novel decays of the heavy CP-even and CP-odd Higgs fields that may be probed in the near future and that may lead to an explanation of some intriguing di-boson signatures observed at the ATLAS experiment.
hep-ph
the study of the higgs boson properties is one of the most relevant activities in current particle physics in particular the higgs boson couplings to third generation fermions is an important test of the mechanism of mass generation in spite of their impact on the production and decay properties of the higgs boson the values of these couplings are still uncertain and in models of new physics they can differ in magnitude as well as in sign with respect to the standard model case in this article we study the possibility of a wrong sign bottomquark yukawa coupling within the framework of the minimal and nexttominimal supersymmetric standard model possible experimental tests are also discussed including novel decays of the heavy cpeven and cpodd higgs fields that may be probed in the near future and that may lead to an explanation of some intriguing diboson signatures observed at the atlas experiment
[['the', 'study', 'of', 'the', 'higgs', 'boson', 'properties', 'is', 'one', 'of', 'the', 'most', 'relevant', 'activities', 'in', 'current', 'particle', 'physics', 'in', 'particular', 'the', 'higgs', 'boson', 'couplings', 'to', 'third', 'generation', 'fermions', 'is', 'an', 'important', 'test', 'of', 'the', 'mechanism', 'of', 'mass', 'generation', 'in', 'spite', 'of', 'their', 'impact', 'on', 'the', 'production', 'and', 'decay', 'properties', 'of', 'the', 'higgs', 'boson', 'the', 'values', 'of', 'these', 'couplings', 'are', 'still', 'uncertain', 'and', 'in', 'models', 'of', 'new', 'physics', 'they', 'can', 'differ', 'in', 'magnitude', 'as', 'well', 'as', 'in', 'sign', 'with', 'respect', 'to', 'the', 'standard', 'model', 'case', 'in', 'this', 'article', 'we', 'study', 'the', 'possibility', 'of', 'a', 'wrong', 'sign', 'bottomquark', 'yukawa', 'coupling', 'within', 'the', 'framework', 'of', 'the', 'minimal', 'and', 'nexttominimal', 'supersymmetric', 'standard', 'model', 'possible', 'experimental', 'tests', 'are', 'also', 'discussed', 'including', 'novel', 'decays', 'of', 'the', 'heavy', 'cpeven', 'and', 'cpodd', 'higgs', 'fields', 'that', 'may', 'be', 'probed', 'in', 'the', 'near', 'future', 'and', 'that', 'may', 'lead', 'to', 'an', 'explanation', 'of', 'some', 'intriguing', 'diboson', 'signatures', 'observed', 'at', 'the', 'atlas', 'experiment']]
[-0.08218208418477524, 0.21785177081836454, -0.020135118248286527, 0.14465367965884382, -0.07580971744355579, -0.15475988532694068, 0.01035555472615983, 0.31518915543850784, -0.2387971165597698, -0.307566323991794, 0.053607697413605174, -0.28382110904704855, -0.07777166144848363, 0.18967230877737262, 0.011222076441919962, 0.07650791116635892, 0.06367120704928178, 0.032199641261003074, -0.04774514853527202, -0.2604852090319865, 0.295616507887939, 0.051647122839885144, 0.20625570712808444, 0.1120974574398422, 0.01894514483788254, -0.012302226965186118, -0.02450923642123562, -0.06446039661247012, -0.10473507788949353, 0.10405303348073218, 0.17027790687272548, 0.07404548277467835, 0.17462387076572866, -0.35473418697122705, -0.13275304853620118, 0.1713087185230476, 0.15796711010895423, 0.11031014067490912, -0.10085410895889983, -0.30276384176717247, 0.09076712394113165, -0.20012092022286937, -0.12216362133868877, -0.06454902617970099, -0.04735228889282571, -0.07109210280306785, -0.2964190921456312, 0.09337971238893555, -0.023016126109410496, 0.03382373766646727, -0.01846719007408678, -0.14896884217506756, -0.05462581444907909, 0.050752379166714795, 0.18597489054660182, -0.0014202628432717543, 0.14567068861473648, -0.25754354287722203, -0.2090940669252975, 0.4260422082753568, -0.11363086953877921, -0.1669556655002055, 0.2167851028112781, -0.19029299455343296, -0.16350304636956248, 0.06974011785443256, 0.2311033254476967, 0.07435326723517566, -0.17117335613576437, 0.15430542324409074, -0.04141036321298028, 0.12462560630662503, 0.017785841236754463, 0.09590749770698957, 0.29325997919485663, 0.20802556741705153, -0.006746782582031181, 0.07289108799520683, -0.07233686618883138, -0.11338591528169824, -0.42430547075284436, -0.1721001044378326, -0.069352928493542, 0.008922149530544087, -0.05346787874523276, -0.11687636902765525, 0.45210549009606144, 0.1999727989907765, 0.2537684551878086, -0.04662535292256796, 0.2590336457252601, 0.09047317408512513, 0.0954943520698499, -0.018710665546653682, 0.36236385694363415, 0.12585844695321377, 0.09938883841259788, -0.21566156312107843, 0.06168752568249671, 0.04592715529570763]
1,802.09123
Black hole formation from the gravitational collapse of a non-spherical network of structures
We examine the gravitational collapse and black hole formation of multiple non--spherical configurations constructed from Szekeres dust models with positive spatial curvature that smoothly match to a Schwarzschild exterior. These configurations are made of an almost spherical central core region surrounded by a network of "pancake-like" overdensities and voids with spatial positions prescribed through standard initial conditions. We show that a full collapse into a focusing singularity, without shell crossings appearing before the formation of an apparent horizon, is not possible unless the full configuration becomes exactly or almost spherical. Seeking for black hole formation, we demand that shell crossings are covered by the apparent horizon. This requires very special fine-tuned initial conditions that impose very strong and unrealistic constraints on the total black hole mass and full collapse time. As a consequence, non-spherical non-rotating dust sources cannot furnish even minimally realistic toy models of black hole formation at astrophysical scales: demanding realistic collapse time scales yields huge unrealistic black hole masses, while simulations of typical astrophysical black hole masses collapse in unrealistically small times. We note, however, that the resulting time--mass constraint is compatible with early Universe models of primordial black hole formation, suitable in early dust-like environments. Finally, we argue that the shell crossings appearing when non-spherical dust structures collapse are an indicator that such structures do not form galactic mass black holes but virialise into stable stationary objects.
gr-qc astro-ph.GA
we examine the gravitational collapse and black hole formation of multiple nonspherical configurations constructed from szekeres dust models with positive spatial curvature that smoothly match to a schwarzschild exterior these configurations are made of an almost spherical central core region surrounded by a network of pancakelike overdensities and voids with spatial positions prescribed through standard initial conditions we show that a full collapse into a focusing singularity without shell crossings appearing before the formation of an apparent horizon is not possible unless the full configuration becomes exactly or almost spherical seeking for black hole formation we demand that shell crossings are covered by the apparent horizon this requires very special finetuned initial conditions that impose very strong and unrealistic constraints on the total black hole mass and full collapse time as a consequence nonspherical nonrotating dust sources cannot furnish even minimally realistic toy models of black hole formation at astrophysical scales demanding realistic collapse time scales yields huge unrealistic black hole masses while simulations of typical astrophysical black hole masses collapse in unrealistically small times we note however that the resulting timemass constraint is compatible with early universe models of primordial black hole formation suitable in early dustlike environments finally we argue that the shell crossings appearing when nonspherical dust structures collapse are an indicator that such structures do not form galactic mass black holes but virialise into stable stationary objects
[['we', 'examine', 'the', 'gravitational', 'collapse', 'and', 'black', 'hole', 'formation', 'of', 'multiple', 'nonspherical', 'configurations', 'constructed', 'from', 'szekeres', 'dust', 'models', 'with', 'positive', 'spatial', 'curvature', 'that', 'smoothly', 'match', 'to', 'a', 'schwarzschild', 'exterior', 'these', 'configurations', 'are', 'made', 'of', 'an', 'almost', 'spherical', 'central', 'core', 'region', 'surrounded', 'by', 'a', 'network', 'of', 'pancakelike', 'overdensities', 'and', 'voids', 'with', 'spatial', 'positions', 'prescribed', 'through', 'standard', 'initial', 'conditions', 'we', 'show', 'that', 'a', 'full', 'collapse', 'into', 'a', 'focusing', 'singularity', 'without', 'shell', 'crossings', 'appearing', 'before', 'the', 'formation', 'of', 'an', 'apparent', 'horizon', 'is', 'not', 'possible', 'unless', 'the', 'full', 'configuration', 'becomes', 'exactly', 'or', 'almost', 'spherical', 'seeking', 'for', 'black', 'hole', 'formation', 'we', 'demand', 'that', 'shell', 'crossings', 'are', 'covered', 'by', 'the', 'apparent', 'horizon', 'this', 'requires', 'very', 'special', 'finetuned', 'initial', 'conditions', 'that', 'impose', 'very', 'strong', 'and', 'unrealistic', 'constraints', 'on', 'the', 'total', 'black', 'hole', 'mass', 'and', 'full', 'collapse', 'time', 'as', 'a', 'consequence', 'nonspherical', 'nonrotating', 'dust', 'sources', 'can', 'not', 'furnish', 'even', 'minimally', 'realistic', 'toy', 'models', 'of', 'black', 'hole', 'formation', 'at', 'astrophysical', 'scales', 'demanding', 'realistic', 'collapse', 'time', 'scales', 'yields', 'huge', 'unrealistic', 'black', 'hole', 'masses', 'while', 'simulations', 'of', 'typical', 'astrophysical', 'black', 'hole', 'masses', 'collapse', 'in', 'unrealistically', 'small', 'times', 'we', 'note', 'however', 'that', 'the', 'resulting', 'timemass', 'constraint', 'is', 'compatible', 'with', 'early', 'universe', 'models', 'of', 'primordial', 'black', 'hole', 'formation', 'suitable', 'in', 'early', 'dustlike', 'environments', 'finally', 'we', 'argue', 'that', 'the', 'shell', 'crossings', 'appearing', 'when', 'nonspherical', 'dust', 'structures', 'collapse', 'are', 'an', 'indicator', 'that', 'such', 'structures', 'do', 'not', 'form', 'galactic', 'mass', 'black', 'holes', 'but', 'virialise', 'into', 'stable', 'stationary', 'objects']]
[-0.1388990068636851, 0.10831234981455826, -0.05393187785158297, 0.17472084585297046, -0.08633307991468739, -0.1260592111394422, -0.024048968830077358, 0.3660593084684569, -0.13670185950758074, -0.33494524440014517, 0.09916255667551675, -0.22783382421911763, -0.049552744791693824, 0.1462107313433017, -0.02354239732960896, -0.003122208927741911, 0.07833110444697257, -0.01687962572731368, -0.11524198721772769, -0.23455697305962137, 0.397594756390335, 0.11154411565028614, 0.19018985099638952, -0.01617878884907602, 0.06873752802632571, -0.06452078378489201, 0.03005275961053981, 0.07295287670557553, -0.17754421078557026, -0.0036585018325000357, 0.17540141142657753, 0.14461770742321267, 0.21108521865499388, -0.49238034297845196, -0.2550500097588305, 0.11779679688806464, 0.19210210126155414, 0.1719779092626993, -0.12069920585158148, -0.2571910209389347, 0.07053871754984255, -0.21175638611682437, -0.19774889448069002, -0.001259254084021111, 0.08817482090180183, -0.029105964124563566, -0.2263327750792622, 0.15317395776036513, 0.07044283496578793, -0.0921697658920072, -0.12778328063301098, -0.03269377638758725, -0.10266898062838105, 0.06765241284859246, 0.07691694531303496, -0.00874548546467944, 0.2193927849981595, -0.11300464653313257, -0.0283252339259806, 0.4014538645228266, -0.016835059695705788, -0.13166649006428077, 0.2078626724766382, -0.24216630979485454, -0.11242906362205357, 0.1750279498317791, 0.1318513084456498, 0.16463532605010903, -0.11231021914618278, 0.07313406049552096, -0.001657422057461816, 0.2017332254455413, 0.16076014578056186, 0.024780345889155096, 0.43660949479820793, 0.13706010015221773, 0.023591076949151694, 0.10089171093634584, -0.08684318620626899, -0.11033431897408559, -0.305436047665156, -0.05780730630851701, -0.15572944413558115, 0.12322378139538455, -0.18587123693518331, -0.22250300319840147, 0.25164116999624275, 0.06581722798523416, 0.2043560065381487, 0.03167396520155591, 0.25830921725538125, 0.02070947511936034, 0.05825237138398411, 0.14049614111094602, 0.2908607140118942, 0.08585268622909338, 0.09120925130762031, -0.19277559710969921, 0.00739011511473601, 0.015476583975903464]
1,802.09124
Optimal airline de-ice scheduling
We present a decision support framework for optimal flight rescheduling on an airline's day of operations when de-icing becomes necessary due to snow and ice events. Winter weather, especially in areas where such weather is not commonplace, often causes cascading delays and cancellations throughout the system due to the unforeseen need to add de-ice time to each aircraft's turnaround time. Our model optimally reschedules remaining flights of the day to minimize system delays and cancellations. The model is formulated as a mixed integer linear program (MILP). Structural properties of the model allow it to be decomposed into a finite set of linear programs (LP) and a computationally tractable algorithm for its solution is described. Finally, numerical simulations are presented for a case study of Horizon Air, a regional airline based in the Pacific Northwest of the United States.
math.OC
we present a decision support framework for optimal flight rescheduling on an airlines day of operations when deicing becomes necessary due to snow and ice events winter weather especially in areas where such weather is not commonplace often causes cascading delays and cancellations throughout the system due to the unforeseen need to add deice time to each aircrafts turnaround time our model optimally reschedules remaining flights of the day to minimize system delays and cancellations the model is formulated as a mixed integer linear program milp structural properties of the model allow it to be decomposed into a finite set of linear programs lp and a computationally tractable algorithm for its solution is described finally numerical simulations are presented for a case study of horizon air a regional airline based in the pacific northwest of the united states
[['we', 'present', 'a', 'decision', 'support', 'framework', 'for', 'optimal', 'flight', 'rescheduling', 'on', 'an', 'airlines', 'day', 'of', 'operations', 'when', 'deicing', 'becomes', 'necessary', 'due', 'to', 'snow', 'and', 'ice', 'events', 'winter', 'weather', 'especially', 'in', 'areas', 'where', 'such', 'weather', 'is', 'not', 'commonplace', 'often', 'causes', 'cascading', 'delays', 'and', 'cancellations', 'throughout', 'the', 'system', 'due', 'to', 'the', 'unforeseen', 'need', 'to', 'add', 'deice', 'time', 'to', 'each', 'aircrafts', 'turnaround', 'time', 'our', 'model', 'optimally', 'reschedules', 'remaining', 'flights', 'of', 'the', 'day', 'to', 'minimize', 'system', 'delays', 'and', 'cancellations', 'the', 'model', 'is', 'formulated', 'as', 'a', 'mixed', 'integer', 'linear', 'program', 'milp', 'structural', 'properties', 'of', 'the', 'model', 'allow', 'it', 'to', 'be', 'decomposed', 'into', 'a', 'finite', 'set', 'of', 'linear', 'programs', 'lp', 'and', 'a', 'computationally', 'tractable', 'algorithm', 'for', 'its', 'solution', 'is', 'described', 'finally', 'numerical', 'simulations', 'are', 'presented', 'for', 'a', 'case', 'study', 'of', 'horizon', 'air', 'a', 'regional', 'airline', 'based', 'in', 'the', 'pacific', 'northwest', 'of', 'the', 'united', 'states']]
[-0.13132542849647522, 0.1174980896164155, -0.07943124391978104, 0.09575951802051443, -0.06539765836154349, -0.13237523558434017, 0.07827495721705856, 0.35854522963768265, -0.2865182684231414, -0.3108392756663426, 0.20567696434479668, -0.2549003188287581, -0.15515579034431573, 0.18263086277046614, -0.10726563516072929, 0.07851404935014468, 0.07939936113917698, -0.008026329367115658, -0.0009486980886660842, -0.2706130350375698, 0.21524209291912125, 0.09334344220395288, 0.22252180377517683, 0.0404378731113036, 0.09124622039537686, 0.007384176722924857, -0.03830359957051756, 0.022095687299912427, -0.05703475840566476, 0.051815321157010014, 0.3293646859399376, 0.15782716113523357, 0.3057018154348335, -0.4895287058486121, -0.20935951981563494, 0.1200105233396655, 0.0797548861188447, 0.06003186086967696, 0.03286997481235677, -0.2816712624532762, 0.0458039778155567, -0.17867197059638742, -0.11194203145157063, -0.04090275754812207, 0.03626289165300066, -0.03538818641847856, -0.2935793940632189, 0.044021874527280375, 0.00957256446789651, 0.05519150115420403, -0.09738245760141634, -0.09107466201454292, -0.03695435194217049, 0.13954357856253236, 0.06178215522587598, -0.012378204597885054, 0.11564341167975421, -0.08391372037602819, -0.1093960933354989, 0.42348930684264996, -0.005842113028277038, -0.14250970455770293, 0.18352581385648845, -0.10004714884061067, -0.11237788427430782, 0.1414809809134335, 0.251108377023063, 0.1055254216754578, -0.14936464898728843, 0.03708023484291748, -0.024994080814866038, 0.1725266056346034, 0.0504398998654835, -0.02330223215322425, 0.2155398452606895, 0.20095788393625105, 0.15668082293666843, 0.1412142235301367, -0.08386880459423673, -0.13531070455473704, -0.29053796992983916, -0.13920117667230375, -0.1222797502308105, -0.02312635184581354, -0.06787707756849577, -0.16485891000700803, 0.3875886367185272, 0.16212645430801043, 0.13739578240979328, 0.08611065862414828, 0.3027396955974332, 0.10223515460492422, 0.053165956460454425, 0.10895162771530721, 0.16197293848615057, 0.04497972342362423, 0.1389842143649385, -0.2152521661074873, 0.11127170456070316, 0.032583056485117244]
1,802.09125
Gyroaveraging operations using adaptive matrix operators
A new adaptive scheme to be used in Particle-In-Cell codes for carrying out gyroaveraging operations with matrices is presented. This new scheme uses an intermediate velocity grid whose resolution is adapted to the local thermal Larmor radius. The charge density is computed by projecting marker weights in a field-line following manner while preserving the adiabatic magnetic moment $\mu$. These choices permit to improve the accuracy of the gyroaveraging operations performed with matrices even when strong spatial variation of temperature and magnetic field is present. Accuracy of the scheme in different geometries from simple 2d slab geometry to realistic 3d toroidal equilibrium has been studied. A successful implementation in the grokinetic code XGC is presented in the delta-f limit.
physics.plasm-ph
a new adaptive scheme to be used in particleincell codes for carrying out gyroaveraging operations with matrices is presented this new scheme uses an intermediate velocity grid whose resolution is adapted to the local thermal larmor radius the charge density is computed by projecting marker weights in a fieldline following manner while preserving the adiabatic magnetic moment mu these choices permit to improve the accuracy of the gyroaveraging operations performed with matrices even when strong spatial variation of temperature and magnetic field is present accuracy of the scheme in different geometries from simple 2d slab geometry to realistic 3d toroidal equilibrium has been studied a successful implementation in the grokinetic code xgc is presented in the deltaf limit
[['a', 'new', 'adaptive', 'scheme', 'to', 'be', 'used', 'in', 'particleincell', 'codes', 'for', 'carrying', 'out', 'gyroaveraging', 'operations', 'with', 'matrices', 'is', 'presented', 'this', 'new', 'scheme', 'uses', 'an', 'intermediate', 'velocity', 'grid', 'whose', 'resolution', 'is', 'adapted', 'to', 'the', 'local', 'thermal', 'larmor', 'radius', 'the', 'charge', 'density', 'is', 'computed', 'by', 'projecting', 'marker', 'weights', 'in', 'a', 'fieldline', 'following', 'manner', 'while', 'preserving', 'the', 'adiabatic', 'magnetic', 'moment', 'mu', 'these', 'choices', 'permit', 'to', 'improve', 'the', 'accuracy', 'of', 'the', 'gyroaveraging', 'operations', 'performed', 'with', 'matrices', 'even', 'when', 'strong', 'spatial', 'variation', 'of', 'temperature', 'and', 'magnetic', 'field', 'is', 'present', 'accuracy', 'of', 'the', 'scheme', 'in', 'different', 'geometries', 'from', 'simple', '2d', 'slab', 'geometry', 'to', 'realistic', '3d', 'toroidal', 'equilibrium', 'has', 'been', 'studied', 'a', 'successful', 'implementation', 'in', 'the', 'grokinetic', 'code', 'xgc', 'is', 'presented', 'in', 'the', 'deltaf', 'limit']]
[-0.1250542881135861, 0.10080769701455901, -0.061789405620496334, 0.033701885070105825, -0.01066178286945897, -0.15724988372851934, 0.011599823974518524, 0.41490687717330355, -0.2447959220755428, -0.30118236289327516, 0.07340337460406991, -0.17262625557787972, -0.061815806198865175, 0.18772371219529305, -0.05828052676074078, 0.08540530330029814, 0.052123961189424556, 0.0015240730537133742, -0.10478971920534165, -0.2271362349093924, 0.2815308775411566, 0.14370144434787077, 0.2850834538855044, 0.005869813010514039, 0.10169488658244392, -0.0079561597386632, -0.0273711274085458, 0.07178534422238389, -0.11462656985807779, 0.07479758190336348, 0.2124595862114802, 0.06655718593613309, 0.22378575409650162, -0.4437615225043405, -0.22234088212958183, 0.04880548375738977, 0.11970129886096151, 0.13920110088154866, -0.04953659175100319, -0.2402406895918579, 0.10167208633481942, -0.15401331387492345, -0.1327563627052988, -0.11113734642075825, 0.005254329620772202, 0.016942158806567274, -0.3319667465161885, 0.0597258366700583, 0.03433016783373173, 0.09216346933731231, -0.015469096143376725, -0.10307625870838569, -0.017168579739518464, 0.12173736049589934, -0.0042999278340520785, 0.06313131591867141, 0.14121849008771623, -0.06524793837211448, -0.0850531507468108, 0.36691828504012064, -0.03669110592454672, -0.24855450314574007, 0.14831154979966132, -0.14220390370484956, -0.08586311355185021, 0.18267587015951245, 0.14748892155756918, 0.12370324959769717, -0.11352556610968192, 0.10004391546054053, -0.020413002886424034, 0.17815740692332901, 0.05584180482727443, 0.004449946854006627, 0.19477699454151223, 0.16489565924636956, 0.06936054652685235, 0.12167128145490003, -0.12405884949940033, -0.07927084713772839, -0.25242756940585015, -0.11454447643863487, -0.19100234057786392, 0.024176039444965085, -0.10129549413714217, -0.14854893952222734, 0.39294411078352476, 0.15562167329159726, 0.16033908018264278, -0.01142468940113382, 0.34389153441639037, 0.11973650140109761, 0.08526070427013047, 0.10826319631526311, 0.207991493558752, 0.17796368468030965, 0.11186578552186457, -0.24820659492477967, 0.0005287841114954188, 0.11954238838395746]
1,802.09126
Forming Different Planetary Architectures . I . Formation Efficiency of Hot Jupites from High-eccentricity Mechanisms
Exoplanets discovered over the last decades have provided a new sample of giant exoplanets, hot Jupiters. For lack of enough materials in current locations of hot Jupiters, they are perceived to form outside snowline. Then, migrate to the locations observed through interactions with gas disks or high-eccentricity mechanisms. We examined the efficiencies of different high-eccentricity mechanisms to form hot Jupiters in near coplaner multi-planet systems. These mechanisms include planet-planet scattering, Kozai-Lidov mechanism, coplanar high-eccentricity migration, secular chaos, as well as other two new mechanisms we find in this work, which can produce hot Jupiters with high inclinations even retrograde. We find Kozai-Lidov mechanism plays the most important role in producing hot Jupiters among these mechanisms. Secular chaos is not the usual channel for the formation of hot Jupiters due to the lack of angular momentum deficit within 10^7 Tin (periods of the inner orbit). According to comparisons between the observations and simulations, we speculate that there are at least two populations of hot Jupiters. One population migrates into the boundary of tidal effects due to interactions with gas disk, such as ups And b, WASP-47 b and HIP 14810 b. These systems usually have at least two planets with lower eccentricities, and keep dynamical stable in compact orbital configurations. Another population forms through high-eccentricity mechanisms after the excitation of eccentricity due to dynamical instability. This kind of hot Jupiters usually has Jupiterlike companions in distant orbits with moderate or high eccentricities.
astro-ph.EP
exoplanets discovered over the last decades have provided a new sample of giant exoplanets hot jupiters for lack of enough materials in current locations of hot jupiters they are perceived to form outside snowline then migrate to the locations observed through interactions with gas disks or higheccentricity mechanisms we examined the efficiencies of different higheccentricity mechanisms to form hot jupiters in near coplaner multiplanet systems these mechanisms include planetplanet scattering kozailidov mechanism coplanar higheccentricity migration secular chaos as well as other two new mechanisms we find in this work which can produce hot jupiters with high inclinations even retrograde we find kozailidov mechanism plays the most important role in producing hot jupiters among these mechanisms secular chaos is not the usual channel for the formation of hot jupiters due to the lack of angular momentum deficit within 107 tin periods of the inner orbit according to comparisons between the observations and simulations we speculate that there are at least two populations of hot jupiters one population migrates into the boundary of tidal effects due to interactions with gas disk such as ups and b wasp47 b and hip 14810 b these systems usually have at least two planets with lower eccentricities and keep dynamical stable in compact orbital configurations another population forms through higheccentricity mechanisms after the excitation of eccentricity due to dynamical instability this kind of hot jupiters usually has jupiterlike companions in distant orbits with moderate or high eccentricities
[['exoplanets', 'discovered', 'over', 'the', 'last', 'decades', 'have', 'provided', 'a', 'new', 'sample', 'of', 'giant', 'exoplanets', 'hot', 'jupiters', 'for', 'lack', 'of', 'enough', 'materials', 'in', 'current', 'locations', 'of', 'hot', 'jupiters', 'they', 'are', 'perceived', 'to', 'form', 'outside', 'snowline', 'then', 'migrate', 'to', 'the', 'locations', 'observed', 'through', 'interactions', 'with', 'gas', 'disks', 'or', 'higheccentricity', 'mechanisms', 'we', 'examined', 'the', 'efficiencies', 'of', 'different', 'higheccentricity', 'mechanisms', 'to', 'form', 'hot', 'jupiters', 'in', 'near', 'coplaner', 'multiplanet', 'systems', 'these', 'mechanisms', 'include', 'planetplanet', 'scattering', 'kozailidov', 'mechanism', 'coplanar', 'higheccentricity', 'migration', 'secular', 'chaos', 'as', 'well', 'as', 'other', 'two', 'new', 'mechanisms', 'we', 'find', 'in', 'this', 'work', 'which', 'can', 'produce', 'hot', 'jupiters', 'with', 'high', 'inclinations', 'even', 'retrograde', 'we', 'find', 'kozailidov', 'mechanism', 'plays', 'the', 'most', 'important', 'role', 'in', 'producing', 'hot', 'jupiters', 'among', 'these', 'mechanisms', 'secular', 'chaos', 'is', 'not', 'the', 'usual', 'channel', 'for', 'the', 'formation', 'of', 'hot', 'jupiters', 'due', 'to', 'the', 'lack', 'of', 'angular', 'momentum', 'deficit', 'within', '107', 'tin', 'periods', 'of', 'the', 'inner', 'orbit', 'according', 'to', 'comparisons', 'between', 'the', 'observations', 'and', 'simulations', 'we', 'speculate', 'that', 'there', 'are', 'at', 'least', 'two', 'populations', 'of', 'hot', 'jupiters', 'one', 'population', 'migrates', 'into', 'the', 'boundary', 'of', 'tidal', 'effects', 'due', 'to', 'interactions', 'with', 'gas', 'disk', 'such', 'as', 'ups', 'and', 'b', 'wasp47', 'b', 'and', 'hip', '14810', 'b', 'these', 'systems', 'usually', 'have', 'at', 'least', 'two', 'planets', 'with', 'lower', 'eccentricities', 'and', 'keep', 'dynamical', 'stable', 'in', 'compact', 'orbital', 'configurations', 'another', 'population', 'forms', 'through', 'higheccentricity', 'mechanisms', 'after', 'the', 'excitation', 'of', 'eccentricity', 'due', 'to', 'dynamical', 'instability', 'this', 'kind', 'of', 'hot', 'jupiters', 'usually', 'has', 'jupiterlike', 'companions', 'in', 'distant', 'orbits', 'with', 'moderate', 'or', 'high', 'eccentricities']]
[-0.1870465094849351, 0.19952634998674815, -0.06601401782196868, 0.07667109633087724, -0.08714516880184722, -0.091870771877196, 0.0665476611252719, 0.3590944325861832, -0.21040452676679705, -0.3189203695432904, 0.06228664242468464, -0.26825868889051585, -0.10387946654227562, 0.18449414322385566, -0.07082423533526404, 0.012006007581658196, 0.11936494669838188, -0.08289491119940066, 0.015502459036482227, -0.24237586724921129, 0.28963499462552134, 0.05132535617970765, 0.01933404712472111, 0.006545490858601019, 0.011059989338779512, -0.07218427995588475, 0.023452819344432402, -0.09797041239923297, -0.168882992805599, 0.011662327525361131, 0.24139145813145055, 0.08210632706371447, 0.255311946660125, -0.4425062489616721, -0.22862350876481893, 0.06785662630572915, 0.19407060109078883, 0.057605398671876175, -0.05617130825897523, -0.20958775906086277, 0.07913763913384173, -0.23792924521112582, -0.18294012925665204, -0.023745439537257575, 0.09680012843382428, 0.004959870285044114, -0.2758263794069838, 0.11312100788733612, 0.12299130419972547, 0.12355897204737024, -0.11613552820344922, -0.136053268390242, -0.09916896609065588, 0.08535546034933456, 0.09845765158340024, -0.012158657313557341, 0.20218795027467423, -0.05436348323904288, -0.07078977009514346, 0.43190543670983367, -0.06850355867742716, -0.06705232612633456, 0.3470868728281251, -0.26840851349406875, -0.10974324226505511, 0.17263071136433913, 0.21571900342678418, 0.1361898295755964, -0.15409126990125516, -0.06404319601230478, 0.005001029850003154, 0.10548822422060766, 0.12399917647029118, 0.10942795230075716, 0.457275455375202, 0.1225284322174654, 0.04747777646455991, 0.05098595888145307, -0.16474664061388467, -0.12135947799979477, -0.1205905409491, -0.06372286807551669, -0.09845930356726361, 0.015289072372312754, -0.07419807563589226, -0.13818334065338908, 0.29561463004016936, 0.1393021039121474, 0.22745588066366812, -0.04794812129160467, 0.33490748105881113, 0.0583752509279293, 0.1385769846458667, 0.15036857716428736, 0.32601579807233066, 0.14307381716304615, 0.060471770944908104, -0.2699105603484592, 0.1130136534517078, -0.022404854494622366]
1,802.09127
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
Recent advances in deep reinforcement learning have made significant strides in performance on applications such as Go and Atari games. However, developing practical methods to balance exploration and exploitation in complex domains remains largely unsolved. Thompson Sampling and its extension to reinforcement learning provide an elegant approach to exploration that only requires access to posterior samples of the model. At the same time, advances in approximate Bayesian methods have made posterior approximation for flexible neural network models practical. Thus, it is attractive to consider approximate Bayesian neural networks in a Thompson Sampling framework. To understand the impact of using an approximate posterior on Thompson Sampling, we benchmark well-established and recently developed methods for approximate posterior sampling combined with Thompson Sampling over a series of contextual bandit problems. We found that many approaches that have been successful in the supervised learning setting underperformed in the sequential decision-making scenario. In particular, we highlight the challenge of adapting slowly converging uncertainty estimates to the online setting.
stat.ML cs.LG
recent advances in deep reinforcement learning have made significant strides in performance on applications such as go and atari games however developing practical methods to balance exploration and exploitation in complex domains remains largely unsolved thompson sampling and its extension to reinforcement learning provide an elegant approach to exploration that only requires access to posterior samples of the model at the same time advances in approximate bayesian methods have made posterior approximation for flexible neural network models practical thus it is attractive to consider approximate bayesian neural networks in a thompson sampling framework to understand the impact of using an approximate posterior on thompson sampling we benchmark wellestablished and recently developed methods for approximate posterior sampling combined with thompson sampling over a series of contextual bandit problems we found that many approaches that have been successful in the supervised learning setting underperformed in the sequential decisionmaking scenario in particular we highlight the challenge of adapting slowly converging uncertainty estimates to the online setting
[['recent', 'advances', 'in', 'deep', 'reinforcement', 'learning', 'have', 'made', 'significant', 'strides', 'in', 'performance', 'on', 'applications', 'such', 'as', 'go', 'and', 'atari', 'games', 'however', 'developing', 'practical', 'methods', 'to', 'balance', 'exploration', 'and', 'exploitation', 'in', 'complex', 'domains', 'remains', 'largely', 'unsolved', 'thompson', 'sampling', 'and', 'its', 'extension', 'to', 'reinforcement', 'learning', 'provide', 'an', 'elegant', 'approach', 'to', 'exploration', 'that', 'only', 'requires', 'access', 'to', 'posterior', 'samples', 'of', 'the', 'model', 'at', 'the', 'same', 'time', 'advances', 'in', 'approximate', 'bayesian', 'methods', 'have', 'made', 'posterior', 'approximation', 'for', 'flexible', 'neural', 'network', 'models', 'practical', 'thus', 'it', 'is', 'attractive', 'to', 'consider', 'approximate', 'bayesian', 'neural', 'networks', 'in', 'a', 'thompson', 'sampling', 'framework', 'to', 'understand', 'the', 'impact', 'of', 'using', 'an', 'approximate', 'posterior', 'on', 'thompson', 'sampling', 'we', 'benchmark', 'wellestablished', 'and', 'recently', 'developed', 'methods', 'for', 'approximate', 'posterior', 'sampling', 'combined', 'with', 'thompson', 'sampling', 'over', 'a', 'series', 'of', 'contextual', 'bandit', 'problems', 'we', 'found', 'that', 'many', 'approaches', 'that', 'have', 'been', 'successful', 'in', 'the', 'supervised', 'learning', 'setting', 'underperformed', 'in', 'the', 'sequential', 'decisionmaking', 'scenario', 'in', 'particular', 'we', 'highlight', 'the', 'challenge', 'of', 'adapting', 'slowly', 'converging', 'uncertainty', 'estimates', 'to', 'the', 'online', 'setting']]
[0.008273449972089083, -0.010386875975395672, -0.1059798409953782, 0.10662874922604855, -0.13526915773703643, -0.15911482923886985, 0.08946402448063796, 0.5128036738356199, -0.29766831347633843, -0.3318591121058523, 0.08871920107138212, -0.20460743910741586, -0.17768733950183252, 0.21869294593207814, -0.1457383883874178, 0.12062715929811478, 0.09640083329443551, -0.022436148116895014, -0.06108444143069531, -0.28079612690961114, 0.22722302090970833, 0.0744787397824065, 0.3358613588215863, -0.03549951338066371, 0.15329179691116504, 0.01237747106741131, -0.03128877618818607, -0.004835174059741016, -0.1354964763144202, 0.17617752835685901, 0.35502658423816696, 0.19302591208248554, 0.4396584728972678, -0.41010357405807524, -0.27090015209942736, 0.1332167896322129, 0.17335823747083728, 0.11230602186527446, -0.08590345650745636, -0.306954592786318, 0.03561289887446796, -0.19383835247317843, -0.00391908708754127, -0.17158025226618615, -0.020107664504985502, -0.03409155106323377, -0.3005216193765379, 0.0026988390478894023, 0.05546112212158191, 0.04562120175023386, -0.005309396060583599, -0.14478755152092937, 0.1158289630680225, 0.12218276486714925, 0.07561399536264454, 0.05590773920922831, 0.11012944277801602, -0.1883470338363589, -0.2077309670529551, 0.30768673316192774, -0.01805836521089077, -0.17827097442789586, 0.20912026741936163, -0.021951964401434307, -0.22031800165498183, 0.10108776380125135, 0.24847163683934811, 0.1415909736822902, -0.1455905791557754, 0.12500521546926785, -0.028904251165779455, 0.08470904039778958, 0.02273887090750633, -0.03215032414550339, 0.13295692821001873, 0.26601407592516235, 0.08751406701120257, 0.07951569766166157, -0.07872658087500582, -0.19583412721621707, -0.1589360905274109, -0.09274713024268487, -0.19040006936236392, -0.018990557446527334, -0.10132053494703401, -0.1777312623685443, 0.3172043399382497, 0.23911565338244284, 0.17623467574844515, 0.11172829874636937, 0.3483435847550813, 0.05058510456322778, 0.04602715224770406, 0.11374270414327917, 0.2258757001640378, 0.10825272308708243, 0.10165883265821365, -0.13332261439081441, 0.12960088328084127, 0.013997431621641104]
1,802.09128
Averaging Stochastic Gradient Descent on Riemannian Manifolds
We consider the minimization of a function defined on a Riemannian manifold $\mathcal{M}$ accessible only through unbiased estimates of its gradients. We develop a geometric framework to transform a sequence of slowly converging iterates generated from stochastic gradient descent (SGD) on $\mathcal{M}$ to an averaged iterate sequence with a robust and fast $O(1/n)$ convergence rate. We then present an application of our framework to geodesically-strongly-convex (and possibly Euclidean non-convex) problems. Finally, we demonstrate how these ideas apply to the case of streaming $k$-PCA, where we show how to accelerate the slow rate of the randomized power method (without requiring knowledge of the eigengap) into a robust algorithm achieving the optimal rate of convergence.
cs.LG math.OC stat.ML
we consider the minimization of a function defined on a riemannian manifold mathcalm accessible only through unbiased estimates of its gradients we develop a geometric framework to transform a sequence of slowly converging iterates generated from stochastic gradient descent sgd on mathcalm to an averaged iterate sequence with a robust and fast o1n convergence rate we then present an application of our framework to geodesicallystronglyconvex and possibly euclidean nonconvex problems finally we demonstrate how these ideas apply to the case of streaming kpca where we show how to accelerate the slow rate of the randomized power method without requiring knowledge of the eigengap into a robust algorithm achieving the optimal rate of convergence
[['we', 'consider', 'the', 'minimization', 'of', 'a', 'function', 'defined', 'on', 'a', 'riemannian', 'manifold', 'mathcalm', 'accessible', 'only', 'through', 'unbiased', 'estimates', 'of', 'its', 'gradients', 'we', 'develop', 'a', 'geometric', 'framework', 'to', 'transform', 'a', 'sequence', 'of', 'slowly', 'converging', 'iterates', 'generated', 'from', 'stochastic', 'gradient', 'descent', 'sgd', 'on', 'mathcalm', 'to', 'an', 'averaged', 'iterate', 'sequence', 'with', 'a', 'robust', 'and', 'fast', 'o1n', 'convergence', 'rate', 'we', 'then', 'present', 'an', 'application', 'of', 'our', 'framework', 'to', 'geodesicallystronglyconvex', 'and', 'possibly', 'euclidean', 'nonconvex', 'problems', 'finally', 'we', 'demonstrate', 'how', 'these', 'ideas', 'apply', 'to', 'the', 'case', 'of', 'streaming', 'kpca', 'where', 'we', 'show', 'how', 'to', 'accelerate', 'the', 'slow', 'rate', 'of', 'the', 'randomized', 'power', 'method', 'without', 'requiring', 'knowledge', 'of', 'the', 'eigengap', 'into', 'a', 'robust', 'algorithm', 'achieving', 'the', 'optimal', 'rate', 'of', 'convergence']]
[-0.1003260274301283, 0.016618589723293553, -0.11625108001836841, 0.0729975126617189, -0.06861553452160608, -0.11444262167372342, 0.07316950830032251, 0.41502166519473704, -0.3640077269769141, -0.24374643252148026, 0.1285550349712139, -0.21118984319868364, -0.16302598876479482, 0.21748218186881527, -0.11591535315424803, 0.07740604748323676, 0.09350469188731429, 0.03988217987352982, -0.11723563272555891, -0.2876200630105034, 0.29223204522194074, 0.04923511838673481, 0.25691159560353427, -0.014125629826074666, 0.17659704659516656, -0.025136321616758193, -0.008040524071215518, 0.015314179431048356, -0.1304514671693531, 0.16281838210748642, 0.20520046852262958, 0.20860414685116016, 0.372201276602157, -0.4286882202561953, -0.15214486381721923, 0.14775739354081452, 0.18232686086698127, 0.08556751516880468, -0.09611247567434995, -0.24528580073092598, 0.12516147388669197, -0.11999240237803731, -0.10021471351501532, -0.13795993048864016, -0.0646636518150834, 0.045778535397922884, -0.36592191968312754, 0.0754023676106174, 0.10211516481857481, 0.0095041380679634, -0.05866870476997325, -0.0785707828597099, 0.04552202285308989, 0.09756244620906987, 0.0839560490099497, 0.09067118878842198, 0.14847262453726476, -0.06784070739480999, -0.08834931369347032, 0.3022478112585044, -0.1181896089136509, -0.2367675182228725, 0.14398509412421845, -0.0797708413197792, -0.1142362534280567, 0.12157889345378083, 0.24646559796695197, 0.217116395859713, -0.10381928541132115, 0.08031203098341523, -0.011729391216899135, 0.14270397841236054, -0.011188333928917668, -0.02294249937403947, 0.09020716786160067, 0.14724534200338116, 0.20515824534231797, 0.16673235992077803, -0.06447801119065844, -0.11066489394787433, -0.29153011610365603, -0.1356202752223388, -0.19057861365477688, 0.07805437913962773, -0.1494449714744925, -0.1824336584291554, 0.3930285075163868, 0.15125613086690595, 0.24816811602795497, 0.16528667480555928, 0.32763994937496527, 0.10728900373734566, -0.009713808906131558, 0.14909429023308413, 0.18259928043906776, 0.1412969779443561, 0.06600864277321047, -0.2284377639194385, 0.02715531858848408, 0.1267583557304793]
1,802.09129
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning
Supervised object detection and semantic segmentation require object or even pixel level annotations. When there exist image level labels only, it is challenging for weakly supervised algorithms to achieve accurate predictions. The accuracy achieved by top weakly supervised algorithms is still significantly lower than their fully supervised counterparts. In this paper, we propose a novel weakly supervised curriculum learning pipeline for multi-label object recognition, detection and semantic segmentation. In this pipeline, we first obtain intermediate object localization and pixel labeling results for the training images, and then use such results to train task-specific deep networks in a fully supervised manner. The entire process consists of four stages, including object localization in the training images, filtering and fusing object instances, pixel labeling for the training images, and task-specific network training. To obtain clean object instances in the training images, we propose a novel algorithm for filtering, fusing and classifying object instances collected from multiple solution mechanisms. In this algorithm, we incorporate both metric learning and density-based clustering to filter detected object instances. Experiments show that our weakly supervised pipeline achieves state-of-the-art results in multi-label image classification as well as weakly supervised object detection and very competitive results in weakly supervised semantic segmentation on MS-COCO, PASCAL VOC 2007 and PASCAL VOC 2012.
cs.CV cs.AI cs.LG stat.ML
supervised object detection and semantic segmentation require object or even pixel level annotations when there exist image level labels only it is challenging for weakly supervised algorithms to achieve accurate predictions the accuracy achieved by top weakly supervised algorithms is still significantly lower than their fully supervised counterparts in this paper we propose a novel weakly supervised curriculum learning pipeline for multilabel object recognition detection and semantic segmentation in this pipeline we first obtain intermediate object localization and pixel labeling results for the training images and then use such results to train taskspecific deep networks in a fully supervised manner the entire process consists of four stages including object localization in the training images filtering and fusing object instances pixel labeling for the training images and taskspecific network training to obtain clean object instances in the training images we propose a novel algorithm for filtering fusing and classifying object instances collected from multiple solution mechanisms in this algorithm we incorporate both metric learning and densitybased clustering to filter detected object instances experiments show that our weakly supervised pipeline achieves stateoftheart results in multilabel image classification as well as weakly supervised object detection and very competitive results in weakly supervised semantic segmentation on mscoco pascal voc 2007 and pascal voc 2012
[['supervised', 'object', 'detection', 'and', 'semantic', 'segmentation', 'require', 'object', 'or', 'even', 'pixel', 'level', 'annotations', 'when', 'there', 'exist', 'image', 'level', 'labels', 'only', 'it', 'is', 'challenging', 'for', 'weakly', 'supervised', 'algorithms', 'to', 'achieve', 'accurate', 'predictions', 'the', 'accuracy', 'achieved', 'by', 'top', 'weakly', 'supervised', 'algorithms', 'is', 'still', 'significantly', 'lower', 'than', 'their', 'fully', 'supervised', 'counterparts', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'weakly', 'supervised', 'curriculum', 'learning', 'pipeline', 'for', 'multilabel', 'object', 'recognition', 'detection', 'and', 'semantic', 'segmentation', 'in', 'this', 'pipeline', 'we', 'first', 'obtain', 'intermediate', 'object', 'localization', 'and', 'pixel', 'labeling', 'results', 'for', 'the', 'training', 'images', 'and', 'then', 'use', 'such', 'results', 'to', 'train', 'taskspecific', 'deep', 'networks', 'in', 'a', 'fully', 'supervised', 'manner', 'the', 'entire', 'process', 'consists', 'of', 'four', 'stages', 'including', 'object', 'localization', 'in', 'the', 'training', 'images', 'filtering', 'and', 'fusing', 'object', 'instances', 'pixel', 'labeling', 'for', 'the', 'training', 'images', 'and', 'taskspecific', 'network', 'training', 'to', 'obtain', 'clean', 'object', 'instances', 'in', 'the', 'training', 'images', 'we', 'propose', 'a', 'novel', 'algorithm', 'for', 'filtering', 'fusing', 'and', 'classifying', 'object', 'instances', 'collected', 'from', 'multiple', 'solution', 'mechanisms', 'in', 'this', 'algorithm', 'we', 'incorporate', 'both', 'metric', 'learning', 'and', 'densitybased', 'clustering', 'to', 'filter', 'detected', 'object', 'instances', 'experiments', 'show', 'that', 'our', 'weakly', 'supervised', 'pipeline', 'achieves', 'stateoftheart', 'results', 'in', 'multilabel', 'image', 'classification', 'as', 'well', 'as', 'weakly', 'supervised', 'object', 'detection', 'and', 'very', 'competitive', 'results', 'in', 'weakly', 'supervised', 'semantic', 'segmentation', 'on', 'mscoco', 'pascal', 'voc', '2007', 'and', 'pascal', 'voc', '2012']]
[0.017767023955959648, -0.04755178014415183, -0.027501240384853666, 0.06634779399087815, -0.12169187067608749, -0.23705051421365214, 0.026539825684102694, 0.5477954594861894, -0.22484064045406524, -0.3995762758977002, 0.048769426137386336, -0.2729917324547257, -0.14708925498638392, 0.18066747844817915, -0.20477480622274535, 0.10482021508782748, 0.2984818680389296, 0.06661643448418804, -0.06340704692438955, -0.3340179831687627, 0.29535088566508855, 0.012994745234997633, 0.36391887401807166, -0.012427436471694992, 0.1824570541447472, -0.03456690086473134, -0.06706109982000531, -0.02391898657383752, 0.016989548489766006, 0.1731559575859657, 0.4120817851718693, 0.217185344795386, 0.2809700698990907, -0.3243972398518097, -0.19382723270738053, 0.077446191599648, 0.16049736244714863, 0.10234740457630583, -0.056065133155789225, -0.469392078043893, 0.09914395190398431, -0.15667105810716747, 0.1611577764574793, -0.1796879954769143, -0.015163380296767823, -0.07867834795088995, -0.29684998580210264, 0.07976662066122074, 0.14053736737058942, 0.050344353477426225, -0.09891493851540699, -0.10171958047209219, 0.07275818769953081, 0.1675420690246115, -0.03965647881642716, 0.08215716526583058, 0.1684002509030203, -0.3366256964891883, -0.15552154687632408, 0.32310456186532976, -0.05517590739244562, -0.21953921466178838, 0.2740326610571217, -0.0026257228316916596, -0.19347244713322392, 0.12107182703912259, 0.24687541709946734, 0.20391562452451104, -0.16657800604956546, -0.014708194837883291, -0.06777797106298662, 0.21422803840915938, 0.07983450091865268, -0.060324109977643404, 0.1596034344962044, 0.34793639621542144, 0.05534328255785762, 0.1671407327150172, -0.2486575177748732, 0.03101432786068125, -0.19570907420683875, -0.07214564577547468, -0.21668019913846537, -0.07874466967658095, -0.11494876164651942, -0.1815831449570223, 0.3756993937749593, 0.27578225926983924, 0.24141322525905534, 0.15752262479315202, 0.36554660628594104, -0.027893971157858948, 0.1169552084557446, 0.10685565475640553, 0.1908571089701062, -0.04926346279902472, 0.12407646021789073, -0.10614521060266444, 0.04294795804723565, 0.1410331234890258]
1,802.0913
Did You Really Just Have a Heart Attack? Towards Robust Detection of Personal Health Mentions in Social Media
Millions of users share their experiences on social media sites, such as Twitter, which in turn generate valuable data for public health monitoring, digital epidemiology, and other analyses of population health at global scale. The first, critical, task for these applications is classifying whether a personal health event was mentioned, which we call the (PHM) problem. This task is challenging for many reasons, including typically short length of social media posts, inventive spelling and lexicons, and figurative language, including hyperbole using diseases like "heart attack" or "cancer" for emphasis, and not as a health self-report. This problem is even more challenging for rarely reported, or frequent but ambiguously expressed conditions, such as "stroke". To address this problem, we propose a general, robust method for detecting PHMs in social media, which we call WESPAD, that combines lexical, syntactic, word embedding-based, and context-based features. WESPAD is able to generalize from few examples by automatically distorting the word embedding space to most effectively detect the true health mentions. Unlike previously proposed state-of-the-art supervised and deep-learning techniques, WESPAD requires relatively little training data, which makes it possible to adapt, with minimal effort, to each new disease and condition. We evaluate WESPAD on both an established publicly available Flu detection benchmark, and on a new dataset that we have constructed with mentions of multiple health conditions. Our experiments show that WESPAD outperforms the baselines and state-of-the-art methods, especially in cases when the number and proportion of true health mentions in the training data is small.
cs.CL
millions of users share their experiences on social media sites such as twitter which in turn generate valuable data for public health monitoring digital epidemiology and other analyses of population health at global scale the first critical task for these applications is classifying whether a personal health event was mentioned which we call the phm problem this task is challenging for many reasons including typically short length of social media posts inventive spelling and lexicons and figurative language including hyperbole using diseases like heart attack or cancer for emphasis and not as a health selfreport this problem is even more challenging for rarely reported or frequent but ambiguously expressed conditions such as stroke to address this problem we propose a general robust method for detecting phms in social media which we call wespad that combines lexical syntactic word embeddingbased and contextbased features wespad is able to generalize from few examples by automatically distorting the word embedding space to most effectively detect the true health mentions unlike previously proposed stateoftheart supervised and deeplearning techniques wespad requires relatively little training data which makes it possible to adapt with minimal effort to each new disease and condition we evaluate wespad on both an established publicly available flu detection benchmark and on a new dataset that we have constructed with mentions of multiple health conditions our experiments show that wespad outperforms the baselines and stateoftheart methods especially in cases when the number and proportion of true health mentions in the training data is small
[['millions', 'of', 'users', 'share', 'their', 'experiences', 'on', 'social', 'media', 'sites', 'such', 'as', 'twitter', 'which', 'in', 'turn', 'generate', 'valuable', 'data', 'for', 'public', 'health', 'monitoring', 'digital', 'epidemiology', 'and', 'other', 'analyses', 'of', 'population', 'health', 'at', 'global', 'scale', 'the', 'first', 'critical', 'task', 'for', 'these', 'applications', 'is', 'classifying', 'whether', 'a', 'personal', 'health', 'event', 'was', 'mentioned', 'which', 'we', 'call', 'the', 'phm', 'problem', 'this', 'task', 'is', 'challenging', 'for', 'many', 'reasons', 'including', 'typically', 'short', 'length', 'of', 'social', 'media', 'posts', 'inventive', 'spelling', 'and', 'lexicons', 'and', 'figurative', 'language', 'including', 'hyperbole', 'using', 'diseases', 'like', 'heart', 'attack', 'or', 'cancer', 'for', 'emphasis', 'and', 'not', 'as', 'a', 'health', 'selfreport', 'this', 'problem', 'is', 'even', 'more', 'challenging', 'for', 'rarely', 'reported', 'or', 'frequent', 'but', 'ambiguously', 'expressed', 'conditions', 'such', 'as', 'stroke', 'to', 'address', 'this', 'problem', 'we', 'propose', 'a', 'general', 'robust', 'method', 'for', 'detecting', 'phms', 'in', 'social', 'media', 'which', 'we', 'call', 'wespad', 'that', 'combines', 'lexical', 'syntactic', 'word', 'embeddingbased', 'and', 'contextbased', 'features', 'wespad', 'is', 'able', 'to', 'generalize', 'from', 'few', 'examples', 'by', 'automatically', 'distorting', 'the', 'word', 'embedding', 'space', 'to', 'most', 'effectively', 'detect', 'the', 'true', 'health', 'mentions', 'unlike', 'previously', 'proposed', 'stateoftheart', 'supervised', 'and', 'deeplearning', 'techniques', 'wespad', 'requires', 'relatively', 'little', 'training', 'data', 'which', 'makes', 'it', 'possible', 'to', 'adapt', 'with', 'minimal', 'effort', 'to', 'each', 'new', 'disease', 'and', 'condition', 'we', 'evaluate', 'wespad', 'on', 'both', 'an', 'established', 'publicly', 'available', 'flu', 'detection', 'benchmark', 'and', 'on', 'a', 'new', 'dataset', 'that', 'we', 'have', 'constructed', 'with', 'mentions', 'of', 'multiple', 'health', 'conditions', 'our', 'experiments', 'show', 'that', 'wespad', 'outperforms', 'the', 'baselines', 'and', 'stateoftheart', 'methods', 'especially', 'in', 'cases', 'when', 'the', 'number', 'and', 'proportion', 'of', 'true', 'health', 'mentions', 'in', 'the', 'training', 'data', 'is', 'small']]
[-0.044238087953415224, 0.030867856335847255, -0.006382533052681859, 0.14046875691419117, -0.1726612145909628, -0.18925308318524417, 0.06291015985343291, 0.4185064752963951, -0.23782142859380542, -0.32699112637888594, 0.13635660400501934, -0.33318551108484196, -0.195157950790786, 0.24007386220904275, -0.14713777069107117, 0.04489389041029141, 0.127552739452537, 0.09055835003805643, 0.0020779907218569584, -0.3118407604972791, 0.314163999574027, 0.011313368336308792, 0.346104798180212, 0.0695623486942376, 0.09905506225338348, 0.012206204392644296, -0.07338186004713372, -0.01055712935317479, -0.06761967589520362, 0.14439032618586398, 0.3815238330780667, 0.25163379850344786, 0.35467099163112753, -0.3959914672124877, -0.22468519945961823, 0.11576961308538196, 0.11960192903923993, 0.13729695219817256, -0.042413437016035734, -0.35553090721293984, 0.08249663729706862, -0.17571073901244855, -0.0221358160975709, -0.13228258085493222, 0.024150359640215863, -0.014974469889608029, -0.24380232120843523, 0.07478948983356326, 0.01968879136443886, 0.1270072191343998, -0.039215719246915186, -0.1132123173241612, 0.015924033055261494, 0.20180360677927436, 0.10148646734817604, 0.016100795393488014, 0.1266769320081291, -0.17906166273904997, -0.13301448909057131, 0.39850325625386074, -0.012598430431152443, -0.1712568397110096, 0.2213491434343608, -0.03854991640731034, -0.1844065391026572, 0.056699014532970764, 0.22845257548278713, 0.10370423071044095, -0.19423016163654463, -0.026984172818497812, -0.05304017003408697, 0.2018930632088064, 0.08802374945317645, 0.0009798577392425194, 0.13846088660484457, 0.2221536765494066, 0.03915461882444877, 0.0873891703214545, -0.0923981053699051, -0.03937448520399443, -0.18440250714845305, -0.11539187682343714, -0.1558479933034494, 0.005012492657263659, -0.07375760513241403, -0.1806735818645539, 0.37902976167631375, 0.2320182690785891, 0.1351662270779007, 0.058736292550893854, 0.2962642254711813, -0.03647574422091814, 0.11608170861486779, 0.0788952640274607, 0.11755600204152694, -0.05208258873403884, 0.142442716711975, -0.14636333881508948, 0.14603373978051346, 0.019282791598973024]
1,802.09131
Statistical properties of 3D cell geometry from 2D slices
Although cell shape can reflect the mechanical and biochemical properties of the cell and its environment, quantification of 3D cell shapes within 3D tissues remains difficult, typically requiring digital reconstruction from a stack of 2D images. We investigate a simple alternative technique to extract information about the 3D shapes of cells in a tissue; this technique connects the ensemble of 3D shapes in the tissue with the distribution of 2D shapes observed in independent 2D slices. Using cell vertex model geometries, we find that the distribution of 2D shapes allows clear determination of the mean value of a 3D shape index. We analyze the errors that may arise in practice in the estimation of the mean 3D shape index from 2D imagery and find that typically only a few dozen cells in 2D imagery are required to reduce uncertainty below 2\%. This framework could be naturally extended to estimate additional 3D geometric features and quantify their uncertainty in other materials.
q-bio.QM physics.bio-ph
although cell shape can reflect the mechanical and biochemical properties of the cell and its environment quantification of 3d cell shapes within 3d tissues remains difficult typically requiring digital reconstruction from a stack of 2d images we investigate a simple alternative technique to extract information about the 3d shapes of cells in a tissue this technique connects the ensemble of 3d shapes in the tissue with the distribution of 2d shapes observed in independent 2d slices using cell vertex model geometries we find that the distribution of 2d shapes allows clear determination of the mean value of a 3d shape index we analyze the errors that may arise in practice in the estimation of the mean 3d shape index from 2d imagery and find that typically only a few dozen cells in 2d imagery are required to reduce uncertainty below 2 this framework could be naturally extended to estimate additional 3d geometric features and quantify their uncertainty in other materials
[['although', 'cell', 'shape', 'can', 'reflect', 'the', 'mechanical', 'and', 'biochemical', 'properties', 'of', 'the', 'cell', 'and', 'its', 'environment', 'quantification', 'of', '3d', 'cell', 'shapes', 'within', '3d', 'tissues', 'remains', 'difficult', 'typically', 'requiring', 'digital', 'reconstruction', 'from', 'a', 'stack', 'of', '2d', 'images', 'we', 'investigate', 'a', 'simple', 'alternative', 'technique', 'to', 'extract', 'information', 'about', 'the', '3d', 'shapes', 'of', 'cells', 'in', 'a', 'tissue', 'this', 'technique', 'connects', 'the', 'ensemble', 'of', '3d', 'shapes', 'in', 'the', 'tissue', 'with', 'the', 'distribution', 'of', '2d', 'shapes', 'observed', 'in', 'independent', '2d', 'slices', 'using', 'cell', 'vertex', 'model', 'geometries', 'we', 'find', 'that', 'the', 'distribution', 'of', '2d', 'shapes', 'allows', 'clear', 'determination', 'of', 'the', 'mean', 'value', 'of', 'a', '3d', 'shape', 'index', 'we', 'analyze', 'the', 'errors', 'that', 'may', 'arise', 'in', 'practice', 'in', 'the', 'estimation', 'of', 'the', 'mean', '3d', 'shape', 'index', 'from', '2d', 'imagery', 'and', 'find', 'that', 'typically', 'only', 'a', 'few', 'dozen', 'cells', 'in', '2d', 'imagery', 'are', 'required', 'to', 'reduce', 'uncertainty', 'below', '2', 'this', 'framework', 'could', 'be', 'naturally', 'extended', 'to', 'estimate', 'additional', '3d', 'geometric', 'features', 'and', 'quantify', 'their', 'uncertainty', 'in', 'other', 'materials']]
[-0.02281111218908336, 0.053851041110465306, -0.06260047380928882, 0.05900400237296708, -0.04044046394119505, -0.11183242258266546, 0.010408829315565526, 0.4285077278342214, -0.27901077470287416, -0.35953079660612275, 0.0751706326904241, -0.2418939390351625, -0.19784710810527031, 0.17884968877042412, -0.135197484116361, 0.06299936174727919, 0.052810371378291164, -0.012355496559757739, -0.0980469369853381, -0.12685635584348348, 0.25360007449489785, -0.000371581909712404, 0.3243741928556119, -0.025110903388849692, 0.09559487646183698, -0.008030154279549607, -0.04264835316571407, 0.056877961365535155, -0.13140644917943972, 0.18573809474473818, 0.211603530064167, 0.12665801484140501, 0.2067845911718905, -0.47706744231982157, -0.2721436456149604, 0.0878080333059188, 0.18489637101592962, 0.14663825555471705, -0.03394531217054464, -0.2306056541390717, 0.07813366265327204, -0.11092403395596193, -0.120669451620779, -0.042851747399254236, 0.00043129534169565885, 0.002114596308092587, -0.24239176893606781, 0.11415014872618486, 0.021463470890012104, 0.07450411200989038, -0.08295706035096373, -0.08470295002916828, -0.044866115489276125, 0.21977016539603939, -0.023331434129067928, -0.007134979128750274, 0.19079224503657316, -0.20084890674625058, -0.06716006628703326, 0.4193527541239746, 0.027372091154393274, -0.23600364440644625, 0.1765240791020915, -0.18064597774064167, -0.09249090522935148, 0.18310882672085427, 0.2107417324441485, 0.07846600405391654, -0.1404530662111938, 0.02312115476524923, -0.03894720593816601, 0.20697262611356565, 0.04474842955096392, 0.006492312629416119, 0.22731241090223192, 0.1807972983297077, 0.005245245642436202, 0.13594931754232675, -0.18762889467179775, -0.047166528241359626, -0.23285129746072925, -0.158818130922009, -0.1732759516860824, 0.02049642189813312, -0.12590023168850167, -0.21731674635084347, 0.428142490425671, 0.1615964931792405, 0.24352984105578343, 0.021489853545790537, 0.29637160630954895, 0.03161762152740266, 0.10446658265573205, -0.017148250978789293, 0.21264920054818504, 0.08325916253379546, 0.08351714314194396, -0.1778762314323103, 0.05004771532840095, 0.036311011824000164]
1,802.09132
Polynomials of Gaussians and vortex-Gaussian beams as complete, transversely confined bases
A novel type of discrete basis for paraxial beams is proposed, consisting of monomial vortices times polynomials of Gaussians in the radial variable. These bases have the distinctive property that the effective size of their elements is roughly independent of element order, meaning that the optimal scaling for expanding a localized field does not depend significantly on truncation order. This behavior contrasts with that of bases composed of polynomials times Gaussians, such as Hermite-Gauss and Laguerre-Gauss modes, where the scaling changes roughly as the inverse square root of the truncation order.
physics.optics
a novel type of discrete basis for paraxial beams is proposed consisting of monomial vortices times polynomials of gaussians in the radial variable these bases have the distinctive property that the effective size of their elements is roughly independent of element order meaning that the optimal scaling for expanding a localized field does not depend significantly on truncation order this behavior contrasts with that of bases composed of polynomials times gaussians such as hermitegauss and laguerregauss modes where the scaling changes roughly as the inverse square root of the truncation order
[['a', 'novel', 'type', 'of', 'discrete', 'basis', 'for', 'paraxial', 'beams', 'is', 'proposed', 'consisting', 'of', 'monomial', 'vortices', 'times', 'polynomials', 'of', 'gaussians', 'in', 'the', 'radial', 'variable', 'these', 'bases', 'have', 'the', 'distinctive', 'property', 'that', 'the', 'effective', 'size', 'of', 'their', 'elements', 'is', 'roughly', 'independent', 'of', 'element', 'order', 'meaning', 'that', 'the', 'optimal', 'scaling', 'for', 'expanding', 'a', 'localized', 'field', 'does', 'not', 'depend', 'significantly', 'on', 'truncation', 'order', 'this', 'behavior', 'contrasts', 'with', 'that', 'of', 'bases', 'composed', 'of', 'polynomials', 'times', 'gaussians', 'such', 'as', 'hermitegauss', 'and', 'laguerregauss', 'modes', 'where', 'the', 'scaling', 'changes', 'roughly', 'as', 'the', 'inverse', 'square', 'root', 'of', 'the', 'truncation', 'order']]
[-0.1268560636768138, 0.16975462728353974, -0.07270387861017998, 0.0061161775144513, -0.06407517542202885, -0.0788103826599871, -0.016077903158205387, 0.3453932298695321, -0.26883058919274544, -0.2144511300394987, 0.10055633166492763, -0.2537865287286567, -0.09672252451079888, 0.14266257354692852, -0.031192232910953053, 0.0604110585300477, -0.002739644450759822, 0.03995948321707956, -0.11368805576105612, -0.2395165338600566, 0.32874785655096256, 0.04162540909025695, 0.27529734764043445, -0.08014473530648092, 0.12897045563415185, -0.023835351245457326, -0.005583273814888773, 0.006375179750138669, -0.08431604272130414, 0.10918100052047841, 0.2288268912598941, 0.07798053987462081, 0.2408409266435838, -0.40400544295322843, -0.1611125518230128, 0.13420264375303964, 0.23294830598592103, 0.05153274026671859, 0.008652167081331404, -0.19153829296324199, 0.04245286717739693, -0.13638768201837173, -0.21843992497076045, -0.06936127831647684, 0.07113503281584849, 0.10988281421353119, -0.33442151417525917, 0.10575967309529545, 0.11200682769764911, 0.08136421438705708, -0.0069569558887691285, -0.1611488384225375, 0.000276354433211324, 0.05249982082111004, 0.03130845714534459, 0.01719816273160197, 0.08972327689548115, -0.0981526582906084, -0.11093717289111157, 0.39101242251530455, -0.04743352707777336, -0.2298868081972494, 0.1467740104666778, -0.17434373171616263, -0.05869853917181819, 0.14664325023909192, 0.16073247780102295, 0.1058117908292583, -0.04749075388523064, 0.06103257451060607, -0.08951981249009515, 0.21845331806484813, 0.12630540205186214, 0.09499657431944877, 0.16660811133928352, 0.10114687022108299, 0.0494958384533075, 0.08561182612614644, -0.054028934864378486, -0.09410819571956501, -0.34671468776906583, -0.14176307252741285, -0.221799231523259, 0.027818050197291107, -0.16705247147279345, -0.22931020728895787, 0.4499751669201222, 0.10597163096970909, 0.180261915178642, 0.04896193181911668, 0.2320509141945577, 0.13952257647690783, 0.1247020665899042, 0.06385867505405958, 0.1984535831610089, 0.13691694090900186, 0.020195997918822935, -0.2188564481182986, 0.023864916781639003, 0.1153115490349112]
1,802.09133
Uniqueness of completions and related topics
A bounded subset of a normed linear space is said to be (diametrically) complete if it cannot be enlarged without increasing the diameter. A complete super set of a bounded set $K$ having the same diameter as $K$ is called a completion of $K$. In general, a bounded set may have different completions. We study normed linear spaces having the property that there exists a nontrivial segment with a unique completion. It turns out that this property is strictly weaker than the property that each complete set is a ball, and it is strictly stronger than the property that each set of constant width is a ball. Extensions of this property are also discussed.
math.FA math.MG
a bounded subset of a normed linear space is said to be diametrically complete if it cannot be enlarged without increasing the diameter a complete super set of a bounded set k having the same diameter as k is called a completion of k in general a bounded set may have different completions we study normed linear spaces having the property that there exists a nontrivial segment with a unique completion it turns out that this property is strictly weaker than the property that each complete set is a ball and it is strictly stronger than the property that each set of constant width is a ball extensions of this property are also discussed
[['a', 'bounded', 'subset', 'of', 'a', 'normed', 'linear', 'space', 'is', 'said', 'to', 'be', 'diametrically', 'complete', 'if', 'it', 'can', 'not', 'be', 'enlarged', 'without', 'increasing', 'the', 'diameter', 'a', 'complete', 'super', 'set', 'of', 'a', 'bounded', 'set', 'k', 'having', 'the', 'same', 'diameter', 'as', 'k', 'is', 'called', 'a', 'completion', 'of', 'k', 'in', 'general', 'a', 'bounded', 'set', 'may', 'have', 'different', 'completions', 'we', 'study', 'normed', 'linear', 'spaces', 'having', 'the', 'property', 'that', 'there', 'exists', 'a', 'nontrivial', 'segment', 'with', 'a', 'unique', 'completion', 'it', 'turns', 'out', 'that', 'this', 'property', 'is', 'strictly', 'weaker', 'than', 'the', 'property', 'that', 'each', 'complete', 'set', 'is', 'a', 'ball', 'and', 'it', 'is', 'strictly', 'stronger', 'than', 'the', 'property', 'that', 'each', 'set', 'of', 'constant', 'width', 'is', 'a', 'ball', 'extensions', 'of', 'this', 'property', 'are', 'also', 'discussed']]
[-0.14562075112176978, 0.14543246316683034, -0.07942143968589928, 0.04759936656236001, -0.1400042752046948, -0.15147992305295624, 0.014901127973976342, 0.3959209149946337, -0.3054711786058286, -0.15710075335658114, 0.13406179750024383, -0.29710510013948965, -0.10296229434240123, 0.16390468073279962, -0.0703125179461811, -0.00613018552084332, 0.06318125111739273, 0.1376109247257852, -0.09350749222642701, -0.27772242527495583, 0.3129794496718956, -0.02881382938636386, 0.21313671859224206, 0.044039123890030646, 0.10494860822901778, -0.009681816557017357, 0.0538395429495722, 0.16451073765486438, -0.1306597478983863, 0.08732685496544708, 0.2263877992619477, 0.17358057929769807, 0.34825260248845036, -0.3066183320854021, -0.19747391790354057, 0.24698240105872568, 0.09308745859028852, 0.008495220618889384, -0.01212709017664842, -0.22313970921399154, 0.20606084230720348, -0.09397434273977642, -0.1531841672754482, -0.023550520634845546, 0.09180216555706347, -0.054099167014836615, -0.2923864932872517, -0.05591610584271384, 0.14078942119022425, 0.05131061749694788, -0.02593538878161622, -0.08790546676609665, -0.053855782931508576, 0.058957769288478984, -0.03582478735909757, 0.11306138627595552, 0.07562577601360237, -0.034151370892220215, -0.061499612803732895, 0.4028314546074556, -0.05426858881938919, -0.248633244374524, 0.16385762932629366, -0.1763411891201268, -0.10279099989439482, 0.15615178309988392, 0.08122559018109156, 0.13570096145343521, -0.11555419018613579, 0.16683590020933795, -0.19451602393680292, 0.1790008585130715, 0.10029379801176812, 0.07382619865289282, 0.16337085605963417, 0.1602895735560552, 0.18814015338480797, 0.15987156433377253, 0.0405798457077016, -0.035831021057421586, -0.3724027156100973, -0.1447367865551749, -0.17729548333293718, 0.09286724409384592, -0.09572902301151771, -0.208635261339014, 0.338891303802476, 0.03963214563428546, 0.23373193360394393, 0.11167057836023361, 0.23886757968702232, 0.10249275466611953, 0.10747162552509942, 0.09335995469566273, 0.17558148059508075, 0.1250854013973604, -0.010227806193997031, -0.11882472841231072, 0.06747673836172274, 0.07994576309030653]
1,802.09134
Demonstration of Einstein-Podolsky-Rosen Steering with Enhanced Subchannel Discrimination
Einstein-Podolsky-Rosen (EPR) steering describes a quantum nonlocal phenomenon in which one party can nonlocally affect the other's state through local measurements. It reveals an additional concept of quantum nonlocality, which stands between quantum entanglement and Bell nonlocality. Recently, a quantum information task named as subchannel discrimination (SD) provides a necessary and sufficient characterization of EPR steering. The success probability of SD using steerable states is higher than using any unsteerable states, even when they are entangled. However, the detailed construction of such subchannels and the experimental realization of the corresponding task are still technologically challenging. In this work, we designed a feasible collection of subchannels for a quantum channel and experimentally demonstrated the corresponding SD task where the probabilities of correct discrimination are clearly enhanced by exploiting steerable states. Our results provide a concrete example to operationally demonstrate EPR steering and shine a new light on the potential application of EPR steering.
quant-ph physics.optics
einsteinpodolskyrosen epr steering describes a quantum nonlocal phenomenon in which one party can nonlocally affect the others state through local measurements it reveals an additional concept of quantum nonlocality which stands between quantum entanglement and bell nonlocality recently a quantum information task named as subchannel discrimination sd provides a necessary and sufficient characterization of epr steering the success probability of sd using steerable states is higher than using any unsteerable states even when they are entangled however the detailed construction of such subchannels and the experimental realization of the corresponding task are still technologically challenging in this work we designed a feasible collection of subchannels for a quantum channel and experimentally demonstrated the corresponding sd task where the probabilities of correct discrimination are clearly enhanced by exploiting steerable states our results provide a concrete example to operationally demonstrate epr steering and shine a new light on the potential application of epr steering
[['einsteinpodolskyrosen', 'epr', 'steering', 'describes', 'a', 'quantum', 'nonlocal', 'phenomenon', 'in', 'which', 'one', 'party', 'can', 'nonlocally', 'affect', 'the', 'others', 'state', 'through', 'local', 'measurements', 'it', 'reveals', 'an', 'additional', 'concept', 'of', 'quantum', 'nonlocality', 'which', 'stands', 'between', 'quantum', 'entanglement', 'and', 'bell', 'nonlocality', 'recently', 'a', 'quantum', 'information', 'task', 'named', 'as', 'subchannel', 'discrimination', 'sd', 'provides', 'a', 'necessary', 'and', 'sufficient', 'characterization', 'of', 'epr', 'steering', 'the', 'success', 'probability', 'of', 'sd', 'using', 'steerable', 'states', 'is', 'higher', 'than', 'using', 'any', 'unsteerable', 'states', 'even', 'when', 'they', 'are', 'entangled', 'however', 'the', 'detailed', 'construction', 'of', 'such', 'subchannels', 'and', 'the', 'experimental', 'realization', 'of', 'the', 'corresponding', 'task', 'are', 'still', 'technologically', 'challenging', 'in', 'this', 'work', 'we', 'designed', 'a', 'feasible', 'collection', 'of', 'subchannels', 'for', 'a', 'quantum', 'channel', 'and', 'experimentally', 'demonstrated', 'the', 'corresponding', 'sd', 'task', 'where', 'the', 'probabilities', 'of', 'correct', 'discrimination', 'are', 'clearly', 'enhanced', 'by', 'exploiting', 'steerable', 'states', 'our', 'results', 'provide', 'a', 'concrete', 'example', 'to', 'operationally', 'demonstrate', 'epr', 'steering', 'and', 'shine', 'a', 'new', 'light', 'on', 'the', 'potential', 'application', 'of', 'epr', 'steering']]
[-0.12529478177250558, 0.14343278390429318, -0.09088066127151251, 0.09142453377870352, -0.06205091003549138, -0.2893371924445474, 0.06834194493651587, 0.3694503000251165, -0.20590066950664646, -0.2717594172572717, 0.035938485236041935, -0.2658549388135342, -0.14777255584302015, 0.20546929840929806, -0.0660559105668462, 0.12676618895248362, 0.07655386896371247, 0.049625715916542835, -0.054719275345345715, -0.2186936497271649, 0.29239862772565656, 0.04434535118592688, 0.34218828162595044, 0.09898441200608718, 0.12656134424890442, 0.05365507325194286, 0.029911035780586598, -0.011741488896261313, -0.06218568858457729, 0.12203716718527415, 0.29374686285767604, 0.1942786163999699, 0.27455164156057627, -0.3854276864960986, -0.19210077884685903, 0.11353676841214397, 0.08994419468064352, 0.17496963778333002, -0.04693153726724344, -0.39553117136912125, 0.004998956445457512, -0.1666345363942367, -0.07148076038452257, -0.122768288019487, -0.01388480242856435, -0.0679539352031976, -0.27839269463315997, 0.0927141402805175, 0.07674448664061186, 0.04772833072408838, 0.0175236371869687, -0.03646597653431328, 0.02936510483911996, 0.12235135069108526, -0.08563747754822926, -0.029548053480347766, 0.10989908907887232, -0.10921672862854107, -0.1983699251033709, 0.34270863916332783, 0.02319476726006542, -0.22141481600699894, 0.15601549826303535, -0.11623909853331402, -0.08502079734247864, 0.05415723385215786, 0.10840589928710342, 0.09404084857976015, -0.14592003498402942, -0.03198887836257008, -0.07200426905489478, 0.2019374479499866, 0.08507741614257132, 0.17825169839871755, 0.19278220712103097, 0.12846523817279376, 0.09233443926457671, 0.19206909069601497, -0.0711367292357241, -0.12626643227964737, -0.3344226956894425, -0.23249836730036277, -0.26688624222419766, 0.08120178313019048, -0.021225752458600543, -0.06649607987339168, 0.4110293629775314, 0.10317532125995249, 0.13707376317133343, -0.028455057880292817, 0.2813149566247471, 0.06381802854019425, 0.034048533832997475, 0.05649939576343106, 0.2856562375458644, 0.15326965005461765, 0.06406583491786334, -0.23285168409500712, 0.10625400727516726, -0.05197868227735039]
1,802.09135
Complete confined bases for beam propagation in Cartesian coordinates
Complete bases that are useful for beam propagation problems and that present the distinct property of being spatially confined at the initial plane are proposed. These bases are constructed in terms of polynomials of Gaussians, in contrast with standard alternatives such as the Hermite-Gaussian basis that are given by a Gaussian times a polynomial. The property of spatial confinement implies that, for all basis elements, the spatial extent at the initial plane is roughly the same. This property leads to an optimal scaling parameter that is independent of truncation order for the fitting of a confined initial field. Given their form as combinations of Gaussians, the paraxial propagation of these basis elements can be modeled analytically.
physics.optics
complete bases that are useful for beam propagation problems and that present the distinct property of being spatially confined at the initial plane are proposed these bases are constructed in terms of polynomials of gaussians in contrast with standard alternatives such as the hermitegaussian basis that are given by a gaussian times a polynomial the property of spatial confinement implies that for all basis elements the spatial extent at the initial plane is roughly the same this property leads to an optimal scaling parameter that is independent of truncation order for the fitting of a confined initial field given their form as combinations of gaussians the paraxial propagation of these basis elements can be modeled analytically
[['complete', 'bases', 'that', 'are', 'useful', 'for', 'beam', 'propagation', 'problems', 'and', 'that', 'present', 'the', 'distinct', 'property', 'of', 'being', 'spatially', 'confined', 'at', 'the', 'initial', 'plane', 'are', 'proposed', 'these', 'bases', 'are', 'constructed', 'in', 'terms', 'of', 'polynomials', 'of', 'gaussians', 'in', 'contrast', 'with', 'standard', 'alternatives', 'such', 'as', 'the', 'hermitegaussian', 'basis', 'that', 'are', 'given', 'by', 'a', 'gaussian', 'times', 'a', 'polynomial', 'the', 'property', 'of', 'spatial', 'confinement', 'implies', 'that', 'for', 'all', 'basis', 'elements', 'the', 'spatial', 'extent', 'at', 'the', 'initial', 'plane', 'is', 'roughly', 'the', 'same', 'this', 'property', 'leads', 'to', 'an', 'optimal', 'scaling', 'parameter', 'that', 'is', 'independent', 'of', 'truncation', 'order', 'for', 'the', 'fitting', 'of', 'a', 'confined', 'initial', 'field', 'given', 'their', 'form', 'as', 'combinations', 'of', 'gaussians', 'the', 'paraxial', 'propagation', 'of', 'these', 'basis', 'elements', 'can', 'be', 'modeled', 'analytically']]
[-0.11359350987035653, 0.15187676348595514, -0.0742361606018425, 0.03187505450553325, -0.027595052644128686, -0.08520169861229329, -0.03754977068305818, 0.4067101814254219, -0.28501416478659314, -0.23608763848736497, 0.0968608915472628, -0.21987243014656746, -0.09159928007484895, 0.17288010944772897, 0.004000707200310868, 0.0795423492421958, 0.03993676089609427, 0.01420424392864365, -0.09118855691410536, -0.2423845192674419, 0.3381016008427431, 0.037748861206888126, 0.2658117666182205, -0.03945645102267635, 0.1054746170753035, -0.006257960416280247, 0.0060870325035246985, 0.03775334506343793, -0.08561197728886327, 0.1193269705038582, 0.23776284785005905, 0.13438411494198904, 0.24327506450133335, -0.3960998839024326, -0.20711547472706898, 0.12150256745196109, 0.1917762099885671, 0.09460286252654222, -0.015956508156297535, -0.22516162417716637, 0.07117721320386848, -0.10479091727656537, -0.21001402309951211, -0.06745793625455478, 0.022719186551041964, 0.0917837462400022, -0.32986514489487584, 0.09066662732672331, 0.06923328260118383, 0.05861729614793901, -0.0232063381659702, -0.13867232519009248, -0.01846267327923199, 0.10434320308910362, 0.00021957795662932894, 0.03843845508527011, 0.07299532283675568, -0.09260104786391885, -0.09460140334277671, 0.40201897211051707, -0.025871556040485678, -0.264022140426497, 0.15344232339652833, -0.1555747704822289, -0.05703489487219987, 0.13707623223107757, 0.15547464082242343, 0.09278820549812296, -0.1264900650331301, 0.0783799366723417, -0.08834105933181427, 0.15175356371990598, 0.1325936003202765, 0.07996145663542095, 0.19655136850758873, 0.09692147674424381, 0.052193926671391416, 0.11940451635043779, -0.03783314809171033, -0.09371436929635318, -0.35690936291237074, -0.12480353532310832, -0.19749882719620002, 0.002120320885923916, -0.14666991508232152, -0.1928685485417473, 0.4042917791300389, 0.11602378035654667, 0.20523790468799014, 0.03938203149250355, 0.24573300652013258, 0.15099922719146608, 0.06095801153950843, 0.06412531158902907, 0.22549171296975992, 0.13590796369103844, 0.010133091954450155, -0.15920827424219922, 0.06990564780727286, 0.05925275643902092]
1,802.09136
III-V Tri-Gate Quantum Well MOSFET: Quantum Ballistic Simulation Study for 10nm Technology and Beyond
In this work, quantum ballistic simulation study of a III-V tri-gate MOSFET has been presented. At the same time, effects of device parameter variation on ballistic, subthrshold and short channel performance is observed and presented. The ballistic simulation result has also been used to observe the electrostatic performance and Capacitance-Voltage characteristics of the device. With constant urge to keep in pace with Moore's law as well as aggressive scaling and device operation reaching near ballistic limit, a full quantum transport study at 10nm gate length is necessary. Our simulation reveals an increase in device drain current with increasing channel cross-section. However short channel performance and subthreshold performance get degraded with channel cross-section increment. Increasing device cross-section lowers threshold voltage of the device. The effect of gate oxide thickness on ballistic device performance is also observed. Increase in top gate oxide thickness affects device performance only upto a certain value. The thickness of the top gate oxide however shows no apparent effect on device threshold voltage. The ballistic simulation study has been further used to extract ballistic injection velocity of the carrier and ballistic carrier mobility in the channel. The effect of device dimension and gate oxide thickness on ballistic velocity and effective carrier mobility is also presented.
physics.comp-ph physics.app-ph
in this work quantum ballistic simulation study of a iiiv trigate mosfet has been presented at the same time effects of device parameter variation on ballistic subthrshold and short channel performance is observed and presented the ballistic simulation result has also been used to observe the electrostatic performance and capacitancevoltage characteristics of the device with constant urge to keep in pace with moores law as well as aggressive scaling and device operation reaching near ballistic limit a full quantum transport study at 10nm gate length is necessary our simulation reveals an increase in device drain current with increasing channel crosssection however short channel performance and subthreshold performance get degraded with channel crosssection increment increasing device crosssection lowers threshold voltage of the device the effect of gate oxide thickness on ballistic device performance is also observed increase in top gate oxide thickness affects device performance only upto a certain value the thickness of the top gate oxide however shows no apparent effect on device threshold voltage the ballistic simulation study has been further used to extract ballistic injection velocity of the carrier and ballistic carrier mobility in the channel the effect of device dimension and gate oxide thickness on ballistic velocity and effective carrier mobility is also presented
[['in', 'this', 'work', 'quantum', 'ballistic', 'simulation', 'study', 'of', 'a', 'iiiv', 'trigate', 'mosfet', 'has', 'been', 'presented', 'at', 'the', 'same', 'time', 'effects', 'of', 'device', 'parameter', 'variation', 'on', 'ballistic', 'subthrshold', 'and', 'short', 'channel', 'performance', 'is', 'observed', 'and', 'presented', 'the', 'ballistic', 'simulation', 'result', 'has', 'also', 'been', 'used', 'to', 'observe', 'the', 'electrostatic', 'performance', 'and', 'capacitancevoltage', 'characteristics', 'of', 'the', 'device', 'with', 'constant', 'urge', 'to', 'keep', 'in', 'pace', 'with', 'moores', 'law', 'as', 'well', 'as', 'aggressive', 'scaling', 'and', 'device', 'operation', 'reaching', 'near', 'ballistic', 'limit', 'a', 'full', 'quantum', 'transport', 'study', 'at', '10nm', 'gate', 'length', 'is', 'necessary', 'our', 'simulation', 'reveals', 'an', 'increase', 'in', 'device', 'drain', 'current', 'with', 'increasing', 'channel', 'crosssection', 'however', 'short', 'channel', 'performance', 'and', 'subthreshold', 'performance', 'get', 'degraded', 'with', 'channel', 'crosssection', 'increment', 'increasing', 'device', 'crosssection', 'lowers', 'threshold', 'voltage', 'of', 'the', 'device', 'the', 'effect', 'of', 'gate', 'oxide', 'thickness', 'on', 'ballistic', 'device', 'performance', 'is', 'also', 'observed', 'increase', 'in', 'top', 'gate', 'oxide', 'thickness', 'affects', 'device', 'performance', 'only', 'upto', 'a', 'certain', 'value', 'the', 'thickness', 'of', 'the', 'top', 'gate', 'oxide', 'however', 'shows', 'no', 'apparent', 'effect', 'on', 'device', 'threshold', 'voltage', 'the', 'ballistic', 'simulation', 'study', 'has', 'been', 'further', 'used', 'to', 'extract', 'ballistic', 'injection', 'velocity', 'of', 'the', 'carrier', 'and', 'ballistic', 'carrier', 'mobility', 'in', 'the', 'channel', 'the', 'effect', 'of', 'device', 'dimension', 'and', 'gate', 'oxide', 'thickness', 'on', 'ballistic', 'velocity', 'and', 'effective', 'carrier', 'mobility', 'is', 'also', 'presented']]
[-0.1689232410546573, 0.10691264433198827, -0.0513399197783285, -0.04747879665256794, -0.011152832765466742, -0.2394223954298, 0.10512482148292249, 0.4255456326493216, -0.24177814736844772, -0.3272448340340436, 0.021808599327573355, -0.2833565428030216, -0.10214532911099349, 0.28848535867715347, -0.06604092654283837, 0.10749917011029873, 0.031880443312173476, -0.018469991854129775, -0.04473583618386929, -0.22015722506923727, 0.1833718383076682, 0.11133115227985223, 0.38316324890310904, 0.16286759690191704, 0.074546216286321, -0.01601245694169865, 0.06418994558721926, 0.017993386466399704, -0.14271177307847271, -0.037288427592517395, 0.23034978266613268, -0.09738055879964484, 0.20913293958614462, -0.4520209863854265, -0.21614312472624944, -0.044087255305217274, 0.15759413898244357, 0.11210267400274107, -0.09069207329099582, -0.24465959894389494, 0.12708939080922277, -0.21345851434512264, -0.09091286292046453, 0.03922233938519816, 0.05535832228979946, -0.006027423521250631, -0.2149841004363216, 0.0991922222355887, 0.026642169990436653, 0.05411570080221423, 0.013089106213476608, -0.1290679849925546, -0.030659636369571815, 0.13733517451102176, 0.025395584418167114, 0.0036637516764616504, 0.2996546781725856, -0.11960188463924779, -0.12124213832995664, 0.2722539077987623, -0.048932561645221, -0.13794319886596673, 0.14319539691764607, -0.19674295854293605, 0.055450061649237804, 0.14434905883119198, 0.18282777086822588, 0.03530359234807372, -0.15783178879318813, 0.0839677267522524, 0.03805294298584962, 0.21070330461839812, 0.0844780381461515, 0.11568658415497127, 0.17057114295001385, 0.2830402491415299, 0.07824663657387629, 0.13199923892993734, -0.157374007691792, -0.04600586210989543, -0.24114688728185532, -0.18454707670025527, -0.18675906142334056, 0.11106197728924634, -0.0825672867008286, -0.1727084754881431, 0.40662551393678176, 0.20487322359915497, 0.16408333668679687, 0.02291418569732132, 0.3419913858338033, 0.14361097303262088, 0.09188252938933923, 0.028513470628452532, 0.2280638991059392, 0.15725050646714522, 0.16252862983066768, -0.28231768316173367, 0.15229248915667853, -0.05290835944243969]
1,802.09137
Conformality of quasiconformal mappings at a point, revisited
We present a new and simple proof of Teichm\"uller-Wittich-Belinskii's and Gutlyanskii-Martio's theorems on the conformality of quasiconformal mappings at a given point. Known proofs gave separate estimates for the radial and angular variations, but our proof unifies them using Gr\"otzsch-type inequality for the variation of cross-ratio of four points on the Riemann sphere. We also give a sufficient condition for $C^{1+\alpha}$-conformality
math.CV
we present a new and simple proof of teichmullerwittichbelinskiis and gutlyanskiimartios theorems on the conformality of quasiconformal mappings at a given point known proofs gave separate estimates for the radial and angular variations but our proof unifies them using grotzschtype inequality for the variation of crossratio of four points on the riemann sphere we also give a sufficient condition for c1alphaconformality
[['we', 'present', 'a', 'new', 'and', 'simple', 'proof', 'of', 'teichmullerwittichbelinskiis', 'and', 'gutlyanskiimartios', 'theorems', 'on', 'the', 'conformality', 'of', 'quasiconformal', 'mappings', 'at', 'a', 'given', 'point', 'known', 'proofs', 'gave', 'separate', 'estimates', 'for', 'the', 'radial', 'and', 'angular', 'variations', 'but', 'our', 'proof', 'unifies', 'them', 'using', 'grotzschtype', 'inequality', 'for', 'the', 'variation', 'of', 'crossratio', 'of', 'four', 'points', 'on', 'the', 'riemann', 'sphere', 'we', 'also', 'give', 'a', 'sufficient', 'condition', 'for', 'c1alphaconformality']]
[-0.1143165339803601, 0.004760437530645153, -0.1489462432647614, 0.09111905914911053, -0.09193791625531096, -0.139184424269683, 0.08592511352821532, 0.2983998334721515, -0.20880140929499216, -0.26606843855820206, 0.14901595025143602, -0.24630101845321947, -0.12536356166789406, 0.264709349999433, -0.12181243916417946, 0.043390626675988496, 0.04019396009511853, 0.005750821462195171, -0.12086367736603215, -0.2454266135433787, 0.3723411090190016, -0.044432457303628325, 0.19521389471922526, 0.16593683515103502, 0.17900260099977777, 0.028899115640996842, -0.08758092298695262, -0.02782236106628389, -0.2294665857120172, 0.15459977489030152, 0.16984717465790086, 0.12287099331029151, 0.19786443515566357, -0.3801470501511766, -0.15398509994051174, 0.08146599549677615, 0.09417526903480553, 0.06366964867501929, -0.06884968259960021, -0.2633757686340495, 0.0633028986978165, -0.024282507271620266, -0.1894136505332171, -0.10634958819208438, 0.009827807512983941, 0.02623092490983637, -0.28221572978062587, 0.07094264079830936, 0.1669975352195794, 0.1339290006445688, -0.07686973051494804, -0.12884426541757166, 0.020537463478384574, 0.08543322032742333, 0.04769939348395718, 0.03740633197798671, 0.06799603392484418, -0.03125521272682307, -0.0918224640844161, 0.33560241628111454, -0.02558523223719053, -0.2257367961492651, 0.1929697017103695, -0.11412825643722165, -0.19447475661964794, 0.059187584385079775, 0.1304196015882649, 0.15394475289800189, -0.11654486809448715, 0.09261519445224844, -0.09512890342688352, 0.10627082768233347, 0.14937193606767737, 0.037030126441989025, 0.1668218252853605, 0.060900199276052024, 0.15490534560950964, 0.16469008099745241, -0.07305805452562165, -0.05677370138858494, -0.4270358633642134, -0.175239627037132, -0.17904477891626588, 0.05678745187163402, -0.16635401156376597, -0.19603745214510382, 0.42163214734510374, 0.06265380600336612, 0.18512400533807905, 0.17794393055271684, 0.2500290187369836, 0.08963167155263618, 0.04759470902775463, 0.0691270382029184, 0.22716846619324202, 0.16669311126073202, 0.08511106138068594, -0.10314469497748896, -0.00643617471908791, 0.2069894930739936]
1,802.09138
The Role of the Communal Entropy and Free Volume for the Viscosity Divergence near the Glass Transition: A New Conceptual Approach
The conventional approach to study glasses either requires considering the rapid drop in the excess entropy {\Delta}S_ex or the free volume V_f. As the two quantities are not directly related to each other, the viscosity in the two approaches do not diverge at the same temperature, which casts doubt on the physical significance of the divergence and of the ideal glass transition (IG). By invoking a recently developed nonequilibrium thermodynamics, we identify the instantaneous temperature, pressure, entropy, etc. and discover the way they relax. We show that by replacing {\Delta}S_ex by a properly defined communal entropy S^comm (not to be confused with the configurational entropy) and V_f vanish simultaneously at IG, where the glass is jammed with no free volume and communal entropy. By exploiting the fact that there are no thermodynamic singularities in the entropy of the supercooled liquid at IG, we show that various currently existing phenomenologies become unified.
cond-mat.stat-mech
the conventional approach to study glasses either requires considering the rapid drop in the excess entropy deltas_ex or the free volume v_f as the two quantities are not directly related to each other the viscosity in the two approaches do not diverge at the same temperature which casts doubt on the physical significance of the divergence and of the ideal glass transition ig by invoking a recently developed nonequilibrium thermodynamics we identify the instantaneous temperature pressure entropy etc and discover the way they relax we show that by replacing deltas_ex by a properly defined communal entropy scomm not to be confused with the configurational entropy and v_f vanish simultaneously at ig where the glass is jammed with no free volume and communal entropy by exploiting the fact that there are no thermodynamic singularities in the entropy of the supercooled liquid at ig we show that various currently existing phenomenologies become unified
[['the', 'conventional', 'approach', 'to', 'study', 'glasses', 'either', 'requires', 'considering', 'the', 'rapid', 'drop', 'in', 'the', 'excess', 'entropy', 'deltas_ex', 'or', 'the', 'free', 'volume', 'v_f', 'as', 'the', 'two', 'quantities', 'are', 'not', 'directly', 'related', 'to', 'each', 'other', 'the', 'viscosity', 'in', 'the', 'two', 'approaches', 'do', 'not', 'diverge', 'at', 'the', 'same', 'temperature', 'which', 'casts', 'doubt', 'on', 'the', 'physical', 'significance', 'of', 'the', 'divergence', 'and', 'of', 'the', 'ideal', 'glass', 'transition', 'ig', 'by', 'invoking', 'a', 'recently', 'developed', 'nonequilibrium', 'thermodynamics', 'we', 'identify', 'the', 'instantaneous', 'temperature', 'pressure', 'entropy', 'etc', 'and', 'discover', 'the', 'way', 'they', 'relax', 'we', 'show', 'that', 'by', 'replacing', 'deltas_ex', 'by', 'a', 'properly', 'defined', 'communal', 'entropy', 'scomm', 'not', 'to', 'be', 'confused', 'with', 'the', 'configurational', 'entropy', 'and', 'v_f', 'vanish', 'simultaneously', 'at', 'ig', 'where', 'the', 'glass', 'is', 'jammed', 'with', 'no', 'free', 'volume', 'and', 'communal', 'entropy', 'by', 'exploiting', 'the', 'fact', 'that', 'there', 'are', 'no', 'thermodynamic', 'singularities', 'in', 'the', 'entropy', 'of', 'the', 'supercooled', 'liquid', 'at', 'ig', 'we', 'show', 'that', 'various', 'currently', 'existing', 'phenomenologies', 'become', 'unified']]
[-0.07909526766240094, 0.20998316140518197, -0.12181364176354396, 0.06159156451483157, -0.033035053006323006, -0.14295051253803476, 0.05738878709490638, 0.32054844080483086, -0.27263485438291085, -0.2557645370504139, 0.0958730862452334, -0.32428390571746873, -0.09884726508784838, 0.13298831711841017, -0.05807381045274638, 0.05280659540959105, -0.023511954668179357, 0.07328447943389718, -0.07716563257083574, -0.21705341213886198, 0.32671831011444935, 0.02269645409683722, 0.3146481602893186, 0.11417087244115316, 0.07276102254242711, -0.007540597322371763, 0.011747936888069316, 0.11529133692179253, -0.1788483781549223, 0.052665307321837426, 0.24796210148850004, 0.09471933671109681, 0.22799623126440957, -0.42784617524719926, -0.2754017048188158, 0.1400813461592849, 0.08520304601375214, 0.06859203940493407, -0.008650195131210509, -0.2186712819541729, 0.05724020319915301, -0.1750652550096699, -0.12722945894347504, -0.09285385438517944, -0.023308888796679174, -0.007672134383520225, -0.1778085716194599, 0.13122897804085468, 0.07797016376610594, 0.05972460102969529, -0.03989374967342293, -0.09914890014428042, -0.06458563126727461, 0.09044608442471488, 0.07232387739704053, 0.03248802136403282, 0.18154597647230117, -0.13902507041977416, -0.0779712803117503, 0.3507456771802862, -0.0612579498289002, -0.18646671644072174, 0.2480909836170188, -0.1709029375374116, -0.12046695598621375, 0.13704568121701832, 0.05441943523662819, 0.07754041135588007, -0.15164575564700203, 0.0582423265110953, 0.016337625204107246, 0.1583878359304288, 0.0704705480586838, 0.03045805687921726, 0.24501183739787824, 0.10326217015500407, 0.031076858204795752, 0.14045623246607106, -0.05609583825256827, -0.1229465008442718, -0.2974391062240544, -0.19451396978724547, -0.2360302162123844, 0.03334700401958528, -0.06431808602497473, -0.1500469704891706, 0.30895801958930047, 0.14734526329069725, 0.2156724893610698, 0.03467970216926817, 0.2771704193807169, 0.11990870068375198, 0.09922645750417802, 0.11053422857013002, 0.2692662550362985, 0.07109951782763961, 0.09272827146058851, -0.25422991749223295, 0.0960116646255719, 0.06851379828593643]
1,802.09139
Drumhead surface states and their signatures in quasiparticle scattering interference
We consider a two-orbital tight-binding model defined on a layered three-dimensional hexagonal lattice to investigate the properties of topological nodal lines and their associated drumhead surface states. We examine these surface states in centrosymmetric systems, where the bulk nodal lines are of Dirac type (i.e., four-fold degenerate), as well as in non-centrosymmetric systems with strong Rashba and/or Dresselhaus spin-orbit coupling, where the bulk nodal lines are of Weyl type (i.e., two-fold degenerate). We find that in non-centrosymmetric systems the nodal lines and their corresponding drumhead surface states are fully spin polarized due to spin-orbit coupling. We show that unique signatures of the topologically nontrivial drumhead surface states can be measured by means of quasiparticle scattering interference, which we compute for both Dirac and Weyl nodal line semimetals. At the end, we analyze the possible crystal structures with a symmetry that supports flat surface states which are effectively ringlike.
cond-mat.str-el cond-mat.mtrl-sci
we consider a twoorbital tightbinding model defined on a layered threedimensional hexagonal lattice to investigate the properties of topological nodal lines and their associated drumhead surface states we examine these surface states in centrosymmetric systems where the bulk nodal lines are of dirac type ie fourfold degenerate as well as in noncentrosymmetric systems with strong rashba andor dresselhaus spinorbit coupling where the bulk nodal lines are of weyl type ie twofold degenerate we find that in noncentrosymmetric systems the nodal lines and their corresponding drumhead surface states are fully spin polarized due to spinorbit coupling we show that unique signatures of the topologically nontrivial drumhead surface states can be measured by means of quasiparticle scattering interference which we compute for both dirac and weyl nodal line semimetals at the end we analyze the possible crystal structures with a symmetry that supports flat surface states which are effectively ringlike
[['we', 'consider', 'a', 'twoorbital', 'tightbinding', 'model', 'defined', 'on', 'a', 'layered', 'threedimensional', 'hexagonal', 'lattice', 'to', 'investigate', 'the', 'properties', 'of', 'topological', 'nodal', 'lines', 'and', 'their', 'associated', 'drumhead', 'surface', 'states', 'we', 'examine', 'these', 'surface', 'states', 'in', 'centrosymmetric', 'systems', 'where', 'the', 'bulk', 'nodal', 'lines', 'are', 'of', 'dirac', 'type', 'ie', 'fourfold', 'degenerate', 'as', 'well', 'as', 'in', 'noncentrosymmetric', 'systems', 'with', 'strong', 'rashba', 'andor', 'dresselhaus', 'spinorbit', 'coupling', 'where', 'the', 'bulk', 'nodal', 'lines', 'are', 'of', 'weyl', 'type', 'ie', 'twofold', 'degenerate', 'we', 'find', 'that', 'in', 'noncentrosymmetric', 'systems', 'the', 'nodal', 'lines', 'and', 'their', 'corresponding', 'drumhead', 'surface', 'states', 'are', 'fully', 'spin', 'polarized', 'due', 'to', 'spinorbit', 'coupling', 'we', 'show', 'that', 'unique', 'signatures', 'of', 'the', 'topologically', 'nontrivial', 'drumhead', 'surface', 'states', 'can', 'be', 'measured', 'by', 'means', 'of', 'quasiparticle', 'scattering', 'interference', 'which', 'we', 'compute', 'for', 'both', 'dirac', 'and', 'weyl', 'nodal', 'line', 'semimetals', 'at', 'the', 'end', 'we', 'analyze', 'the', 'possible', 'crystal', 'structures', 'with', 'a', 'symmetry', 'that', 'supports', 'flat', 'surface', 'states', 'which', 'are', 'effectively', 'ringlike']]
[-0.26914633832171064, 0.1821492894551075, 0.027407893895272265, 0.0386317566578352, -0.09165147465741816, -0.21064902058915813, 0.06897869663678009, 0.40334341464315643, -0.2683796813849964, -0.24187651311749014, -0.018849158048790227, -0.3250433117075748, -0.169398026292313, 0.13721169022736265, 0.04186371322941488, 0.01825886985249314, -0.04032916629158363, -0.07393377747172741, -0.16046638643515385, -0.19584254288378902, 0.41296997536099644, -0.06288716966613524, 0.3229620294028742, 0.07291897482276466, -0.021166787995654787, -0.03529440151288401, 0.13599947962211445, 0.040440518626112594, -0.13646467854389788, 0.10305848418116707, 0.24249008725982513, -0.1259317073052296, 0.097966306540813, -0.45375710388494506, -0.2219658846387992, 0.011507806264342287, 0.14060062359439562, 0.17437259655766743, -0.043317502909623135, -0.3320203088381252, 0.06099186859225754, -0.13530515614783745, -0.1820457733104106, -0.10186811801002084, -0.04581025961434116, -0.01711700766070469, -0.1597662447602488, 0.06678528254348282, 0.0423733378466332, 0.09531018583377748, -0.08732804186277192, -0.08370136851728013, -0.21828088010944477, 0.039367930973074526, 0.02360298071918707, -0.037374291364481116, 0.05643359604181495, -0.09799412122575214, -0.14714119510687385, 0.4291247379135441, -0.09755759684973069, -0.15153350915784972, 0.18448233303953768, -0.16197214392800438, -0.08789475438361233, 0.1532009897558522, 0.17487196636825134, 0.1047437149068542, -0.06896143583572986, 0.12710806480774064, -0.07364079069874778, 0.09050041486232265, 0.02148503247598136, 0.12754499844615222, 0.3241055436759583, 0.0837028661948893, 0.08215177017956267, 0.10793503100757261, -0.1652532375965903, -0.04867148073429456, -0.26959406653721185, -0.20214196556952554, -0.23640287399443016, 0.06266580471561316, 0.011534794282016338, -0.24776149432275546, 0.443059950107331, 0.040091918605203565, 0.21292876500976146, -0.05724417174398597, 0.17463331776545257, 0.11429993984151028, 0.07358108386963706, 0.07139907896399146, 0.2425285818596446, 0.16227801245278553, -0.0022771406283199386, -0.3028303870893511, -0.003996552757893664, 0.03141018182567849]
1,802.0914
Simulation of Thin-TFETs Using Transition Metal Dichalcogenides: Effect of Material Parameters, Gate Dielectric on Electrostatic Device Performance
In recent years, a lot of scientific research effort has been put forth for the investigation of Transition Metal Dichalcogenides (TMDC) and other Two Dimensional (2D) materials like Graphene, Boron Nitride. Theoretical investigation on the physical aspects of these materials has revealed a whole new range of exciting applications due to wide tunability in electronic and optoelectronic properties. Besides theoretical exploration, these materials have been successfully implemented in electronic and optoelectronic devices with promising results. In this work, we have investigated the effect of monolayer TMDC materials and monolayer TMDC alloys on the performance of a promising electronic device that can achieve steep switching characteristics- thin Tunneling Filed Effect Transistor or thin-TFET, using self-consistent determination of conduction, valance band levels in the device and a simplified model of interlayer tunneling current that treats scattering semi-classically and incorporates the energy broadening effect using a Gaussian approximation. We have also explored the effect of gate dielectric material variation, interlayer material variation on the performance of the device.
physics.comp-ph physics.app-ph
in recent years a lot of scientific research effort has been put forth for the investigation of transition metal dichalcogenides tmdc and other two dimensional 2d materials like graphene boron nitride theoretical investigation on the physical aspects of these materials has revealed a whole new range of exciting applications due to wide tunability in electronic and optoelectronic properties besides theoretical exploration these materials have been successfully implemented in electronic and optoelectronic devices with promising results in this work we have investigated the effect of monolayer tmdc materials and monolayer tmdc alloys on the performance of a promising electronic device that can achieve steep switching characteristics thin tunneling filed effect transistor or thintfet using selfconsistent determination of conduction valance band levels in the device and a simplified model of interlayer tunneling current that treats scattering semiclassically and incorporates the energy broadening effect using a gaussian approximation we have also explored the effect of gate dielectric material variation interlayer material variation on the performance of the device
[['in', 'recent', 'years', 'a', 'lot', 'of', 'scientific', 'research', 'effort', 'has', 'been', 'put', 'forth', 'for', 'the', 'investigation', 'of', 'transition', 'metal', 'dichalcogenides', 'tmdc', 'and', 'other', 'two', 'dimensional', '2d', 'materials', 'like', 'graphene', 'boron', 'nitride', 'theoretical', 'investigation', 'on', 'the', 'physical', 'aspects', 'of', 'these', 'materials', 'has', 'revealed', 'a', 'whole', 'new', 'range', 'of', 'exciting', 'applications', 'due', 'to', 'wide', 'tunability', 'in', 'electronic', 'and', 'optoelectronic', 'properties', 'besides', 'theoretical', 'exploration', 'these', 'materials', 'have', 'been', 'successfully', 'implemented', 'in', 'electronic', 'and', 'optoelectronic', 'devices', 'with', 'promising', 'results', 'in', 'this', 'work', 'we', 'have', 'investigated', 'the', 'effect', 'of', 'monolayer', 'tmdc', 'materials', 'and', 'monolayer', 'tmdc', 'alloys', 'on', 'the', 'performance', 'of', 'a', 'promising', 'electronic', 'device', 'that', 'can', 'achieve', 'steep', 'switching', 'characteristics', 'thin', 'tunneling', 'filed', 'effect', 'transistor', 'or', 'thintfet', 'using', 'selfconsistent', 'determination', 'of', 'conduction', 'valance', 'band', 'levels', 'in', 'the', 'device', 'and', 'a', 'simplified', 'model', 'of', 'interlayer', 'tunneling', 'current', 'that', 'treats', 'scattering', 'semiclassically', 'and', 'incorporates', 'the', 'energy', 'broadening', 'effect', 'using', 'a', 'gaussian', 'approximation', 'we', 'have', 'also', 'explored', 'the', 'effect', 'of', 'gate', 'dielectric', 'material', 'variation', 'interlayer', 'material', 'variation', 'on', 'the', 'performance', 'of', 'the', 'device']]
[-0.12977754273875194, 0.09192570819321907, -0.03892031178075933, -0.032187149771065876, -0.06262994405785294, -0.18681473066240098, 0.11212403033436699, 0.4749081580589215, -0.21959664199331944, -0.3216915312321913, -0.02748112076060903, -0.30682874913468505, -0.2054289538258066, 0.250516620018717, 0.013623325760956064, 0.0948838258105697, 0.016129929798118996, -0.1456404036475402, -0.0854444339866115, -0.18588629656640643, 0.2413412007587877, 0.04650837065595569, 0.37552827204380074, 0.15583518991021045, 0.04596477426080541, -0.02815116929087901, 0.10230053907090968, 0.020436755430207332, -0.15590871455779326, 0.09993962132809402, 0.2613190909424289, -0.10735443393050721, 0.2957203645259142, -0.49415080452507193, -0.3041742464538071, -0.027066377258266914, 0.13439442410105557, 0.13503795990889722, -0.16164841494649987, -0.2679071548931075, 0.03813528720233025, -0.18726520835224425, -0.055392480480650465, -0.10299808043549119, 0.022705884040756658, -0.0006983691487799992, -0.171257213665751, 0.007700185287059426, 0.011488504829167417, 0.06292509399636677, -0.08837180896353498, -0.18540584390249215, -0.042920743256355774, 0.07668482298454778, 0.045919838613322515, -0.013275447767933435, 0.21178227324659626, -0.12162577060785913, -0.1299705142620951, 0.39235167674946064, -0.031048085041005504, -0.09448986885448298, 0.1699907710295961, -0.16310552511589996, -0.08277806618222684, 0.11623140190248236, 0.18249666051318247, 0.08268216844140129, -0.1658320391042666, 0.11458399004345252, 0.011132514753350706, 0.12737276372923093, 0.04666713849274498, 0.17200279208746824, 0.2619171250047106, 0.2765434319209872, -0.017546458803399494, 0.13321680108078218, -0.1034044545863501, -0.02021454818426388, -0.14486178251717127, -0.2099478540857407, -0.2165641342811851, 0.09178833627904004, -0.05767954942350502, -0.22062101561971234, 0.4746321706609292, 0.16536328549934268, 0.11328088054433465, -0.10204090127918983, 0.28993510753198554, 0.0954893043434078, 0.11089391941204667, -0.032071489226919686, 0.30690302623887405, 0.17666538481911023, 0.14855485208143804, -0.2038063565748885, 0.10641466139914524, -0.040336539534231025]
1,802.09141
Trilayer TMDC Heterostructures for MOSFETs and Nanobiosensors
Two dimensional materials such as Transition Metal Dichalcogenides (TMDC) and their bi-layer/tri-layer heterostructures have become the focus of intense research and investigation in recent years due to their promising applications in electronics and optoelectronics. In this work, we have explored device level performance of trilayer TMDC heterostructure (MoS2/MX2/MoS2; M=Mo or, W and X=S or, Se) Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) in the quantum ballistic regime. Our simulation shows that device 'on' current can be improved by inserting a WS2 monolayer between two MoS2 monolayers. Application of biaxial tensile strain reveals a reduction in drain current which can be attributed to the lowering of carrier effective mass with increased tensile strain. In addition, it is found that gate underlap geometry improves electrostatic device performance by improving sub-threshold swing. However, increase in channel resistance reduces drain current. Besides exploring the prospect of these materials in device performance, novel trilayer TMDC heterostructure double gate Field Effect Transistors (FETs) are proposed for sensing Nano biomolecules as well as for pH sensing. Bottom gate operation ensures these FETs operating beyond Nernst limit of 59 mV/pH. Simulation results found in this work reveal that scaling of bottom gate oxide results in better sensitivity while top oxide scaling exhibits an opposite trend. It is also found that, for identical operating conditions, proposed TMDC FET pH sensors show super-Nernst sensitivity indicating these materials as potential candidates in implementing such sensor. Besides pH sensing, all these materials show high sensitivity in the sub-threshold region as a channel material in nanobiosensor while MoS2/WS2/MoS2 FET shows the least sensitivity among them.
physics.comp-ph physics.app-ph
two dimensional materials such as transition metal dichalcogenides tmdc and their bilayertrilayer heterostructures have become the focus of intense research and investigation in recent years due to their promising applications in electronics and optoelectronics in this work we have explored device level performance of trilayer tmdc heterostructure mos2mx2mos2 mmo or w and xs or se metal oxide semiconductor field effect transistors mosfets in the quantum ballistic regime our simulation shows that device on current can be improved by inserting a ws2 monolayer between two mos2 monolayers application of biaxial tensile strain reveals a reduction in drain current which can be attributed to the lowering of carrier effective mass with increased tensile strain in addition it is found that gate underlap geometry improves electrostatic device performance by improving subthreshold swing however increase in channel resistance reduces drain current besides exploring the prospect of these materials in device performance novel trilayer tmdc heterostructure double gate field effect transistors fets are proposed for sensing nano biomolecules as well as for ph sensing bottom gate operation ensures these fets operating beyond nernst limit of 59 mvph simulation results found in this work reveal that scaling of bottom gate oxide results in better sensitivity while top oxide scaling exhibits an opposite trend it is also found that for identical operating conditions proposed tmdc fet ph sensors show supernernst sensitivity indicating these materials as potential candidates in implementing such sensor besides ph sensing all these materials show high sensitivity in the subthreshold region as a channel material in nanobiosensor while mos2ws2mos2 fet shows the least sensitivity among them
[['two', 'dimensional', 'materials', 'such', 'as', 'transition', 'metal', 'dichalcogenides', 'tmdc', 'and', 'their', 'bilayertrilayer', 'heterostructures', 'have', 'become', 'the', 'focus', 'of', 'intense', 'research', 'and', 'investigation', 'in', 'recent', 'years', 'due', 'to', 'their', 'promising', 'applications', 'in', 'electronics', 'and', 'optoelectronics', 'in', 'this', 'work', 'we', 'have', 'explored', 'device', 'level', 'performance', 'of', 'trilayer', 'tmdc', 'heterostructure', 'mos2mx2mos2', 'mmo', 'or', 'w', 'and', 'xs', 'or', 'se', 'metal', 'oxide', 'semiconductor', 'field', 'effect', 'transistors', 'mosfets', 'in', 'the', 'quantum', 'ballistic', 'regime', 'our', 'simulation', 'shows', 'that', 'device', 'on', 'current', 'can', 'be', 'improved', 'by', 'inserting', 'a', 'ws2', 'monolayer', 'between', 'two', 'mos2', 'monolayers', 'application', 'of', 'biaxial', 'tensile', 'strain', 'reveals', 'a', 'reduction', 'in', 'drain', 'current', 'which', 'can', 'be', 'attributed', 'to', 'the', 'lowering', 'of', 'carrier', 'effective', 'mass', 'with', 'increased', 'tensile', 'strain', 'in', 'addition', 'it', 'is', 'found', 'that', 'gate', 'underlap', 'geometry', 'improves', 'electrostatic', 'device', 'performance', 'by', 'improving', 'subthreshold', 'swing', 'however', 'increase', 'in', 'channel', 'resistance', 'reduces', 'drain', 'current', 'besides', 'exploring', 'the', 'prospect', 'of', 'these', 'materials', 'in', 'device', 'performance', 'novel', 'trilayer', 'tmdc', 'heterostructure', 'double', 'gate', 'field', 'effect', 'transistors', 'fets', 'are', 'proposed', 'for', 'sensing', 'nano', 'biomolecules', 'as', 'well', 'as', 'for', 'ph', 'sensing', 'bottom', 'gate', 'operation', 'ensures', 'these', 'fets', 'operating', 'beyond', 'nernst', 'limit', 'of', '59', 'mvph', 'simulation', 'results', 'found', 'in', 'this', 'work', 'reveal', 'that', 'scaling', 'of', 'bottom', 'gate', 'oxide', 'results', 'in', 'better', 'sensitivity', 'while', 'top', 'oxide', 'scaling', 'exhibits', 'an', 'opposite', 'trend', 'it', 'is', 'also', 'found', 'that', 'for', 'identical', 'operating', 'conditions', 'proposed', 'tmdc', 'fet', 'ph', 'sensors', 'show', 'supernernst', 'sensitivity', 'indicating', 'these', 'materials', 'as', 'potential', 'candidates', 'in', 'implementing', 'such', 'sensor', 'besides', 'ph', 'sensing', 'all', 'these', 'materials', 'show', 'high', 'sensitivity', 'in', 'the', 'subthreshold', 'region', 'as', 'a', 'channel', 'material', 'in', 'nanobiosensor', 'while', 'mos2ws2mos2', 'fet', 'shows', 'the', 'least', 'sensitivity', 'among', 'them']]
[-0.15308835169865817, 0.11527480059823376, 0.012394041671280482, -0.05179683626164654, 0.021865175823074613, -0.2697538811327211, 0.10822820170446797, 0.4632468706821705, -0.210813418741865, -0.33693929293640534, -0.006939174124137174, -0.29418893143274755, -0.21136503764644785, 0.28642652822250514, -0.04701107589615051, 0.07546013237027697, 0.007384377912538805, -0.11941758281453838, -0.07471732807872716, -0.21230399218629192, 0.16711185576372542, 0.06550304128837144, 0.40193788235097433, 0.1261802238011516, 0.023976637631683617, -0.04251686827813874, 0.12675898964697307, 0.00802880215148131, -0.0895654159359356, 0.04019173425748627, 0.3118375305496084, -0.12350015163190606, 0.23972765509898292, -0.4648541926420763, -0.2337333647698496, -0.039502123890123364, 0.15424191376894655, 0.11342585837611091, -0.15155782650383695, -0.266215161369868, 0.12635203742949191, -0.1878845677350092, -0.040987726036989844, -0.05164279276572796, -0.0033338816729085448, 0.0002793686671088659, -0.21244896702297383, 0.04972904268133295, 0.035484430943742075, 0.0592645687893098, -0.05478619148254452, -0.20190532023245975, -0.07258779104618994, 0.06055798539855741, 0.04174619916372557, 0.03348222975932737, 0.30948703072950706, -0.17244430292071616, -0.13053450076127887, 0.3265603222034135, -0.03496337412629103, -0.10284207747390046, 0.16913026165940923, -0.17224135853768896, -0.030286806131994654, 0.1135840958684625, 0.14254255158296072, 0.05129633190168082, -0.16894759371418275, 0.09165958133471999, 0.05676214164709528, 0.16334275831107425, 0.10775323850716385, 0.13956635638118484, 0.2511350737447858, 0.27791605727695645, 0.06781688038473624, 0.1271670452768503, -0.09078457253426042, 0.02052373917008093, -0.16955369902601422, -0.23634615358391184, -0.17781802893899626, 0.12280450843079666, -0.08210959648077246, -0.1831958128785527, 0.4008692588310602, 0.1843120377795507, 0.12522808697738852, -0.04082270739049571, 0.2810132975036697, 0.09464163497377318, 0.11867908164028569, -0.019656722062057996, 0.28912884620913526, 0.15937105593877995, 0.14189414314694646, -0.22010359710963198, 0.09362628815069347, -0.07697461174111525]
1,802.09142
Electronic Properties of MoS2/MX2/MoS2 Trilayer Heterostructures: A First Principle Study
In this work, we have presented a first principle simulation study on the electronic properties of MoS2/MX2/MoS2 (M=Mo or W; X=S or Se) trilayer heterostrcuture. We have investigated the effect of stacking configuration, bi-axial compressive and tensile strain on the electronic properties of the trilayer heterostructures. In our study, it is found that, under relaxed condition all the trilayer heterostructures at different stacking configurations show semiconducting nature. The nature of the bandgap however depends on the inserted TMDC monolayer between the top and bottom MoS2 layers and their stacking configurations. Like bilayer heterostructures, trilayer structures also show semiconducting to metal transition under the application of tensile strain. With increased tensile strain the conduction band minima shifts to K point in the brillouin zone and lowering of electron effective mass at conduction band minima is observed. The study on the projected density of states reveal that, the conduction band minima is mostly contributed by the MoS2 layers and states at the valance band maxima are contributed by the middle TMDC monolayer.
physics.comp-ph cond-mat.mtrl-sci
in this work we have presented a first principle simulation study on the electronic properties of mos2mx2mos2 mmo or w xs or se trilayer heterostrcuture we have investigated the effect of stacking configuration biaxial compressive and tensile strain on the electronic properties of the trilayer heterostructures in our study it is found that under relaxed condition all the trilayer heterostructures at different stacking configurations show semiconducting nature the nature of the bandgap however depends on the inserted tmdc monolayer between the top and bottom mos2 layers and their stacking configurations like bilayer heterostructures trilayer structures also show semiconducting to metal transition under the application of tensile strain with increased tensile strain the conduction band minima shifts to k point in the brillouin zone and lowering of electron effective mass at conduction band minima is observed the study on the projected density of states reveal that the conduction band minima is mostly contributed by the mos2 layers and states at the valance band maxima are contributed by the middle tmdc monolayer
[['in', 'this', 'work', 'we', 'have', 'presented', 'a', 'first', 'principle', 'simulation', 'study', 'on', 'the', 'electronic', 'properties', 'of', 'mos2mx2mos2', 'mmo', 'or', 'w', 'xs', 'or', 'se', 'trilayer', 'heterostrcuture', 'we', 'have', 'investigated', 'the', 'effect', 'of', 'stacking', 'configuration', 'biaxial', 'compressive', 'and', 'tensile', 'strain', 'on', 'the', 'electronic', 'properties', 'of', 'the', 'trilayer', 'heterostructures', 'in', 'our', 'study', 'it', 'is', 'found', 'that', 'under', 'relaxed', 'condition', 'all', 'the', 'trilayer', 'heterostructures', 'at', 'different', 'stacking', 'configurations', 'show', 'semiconducting', 'nature', 'the', 'nature', 'of', 'the', 'bandgap', 'however', 'depends', 'on', 'the', 'inserted', 'tmdc', 'monolayer', 'between', 'the', 'top', 'and', 'bottom', 'mos2', 'layers', 'and', 'their', 'stacking', 'configurations', 'like', 'bilayer', 'heterostructures', 'trilayer', 'structures', 'also', 'show', 'semiconducting', 'to', 'metal', 'transition', 'under', 'the', 'application', 'of', 'tensile', 'strain', 'with', 'increased', 'tensile', 'strain', 'the', 'conduction', 'band', 'minima', 'shifts', 'to', 'k', 'point', 'in', 'the', 'brillouin', 'zone', 'and', 'lowering', 'of', 'electron', 'effective', 'mass', 'at', 'conduction', 'band', 'minima', 'is', 'observed', 'the', 'study', 'on', 'the', 'projected', 'density', 'of', 'states', 'reveal', 'that', 'the', 'conduction', 'band', 'minima', 'is', 'mostly', 'contributed', 'by', 'the', 'mos2', 'layers', 'and', 'states', 'at', 'the', 'valance', 'band', 'maxima', 'are', 'contributed', 'by', 'the', 'middle', 'tmdc', 'monolayer']]
[-0.1743091045645997, 0.131035283119196, 0.003801664110228774, -0.0227986286502398, 0.03297174783490066, -0.1320756618709614, 0.14410735808355857, 0.46419798924970174, -0.2934283141013501, -0.29830100057768594, -0.036355622301925905, -0.32346725519303055, -0.18350384254188698, 0.1489835292172973, 0.07720714675573011, 0.002701602238673894, 0.036414966181231044, -0.14598237494577743, -0.1416594003925898, -0.21742631472976168, 0.2951329082771692, 0.028760174217279114, 0.38481359495337875, 0.10536382720636625, -0.03418956603300536, 0.014951940900313534, 0.1638374773569272, -0.007883759792007151, -0.17606667178517368, 0.07026882038848098, 0.2202203772363386, -0.19835321376503348, 0.2358273835492409, -0.4665426451025442, -0.18239723634178517, -0.04300823847768784, 0.0964405918036521, 0.09761473010197126, -0.049818546613789205, -0.26827487331770716, 0.13368017537452812, -0.0987345836114227, -0.035290997752565, -0.037927764980676806, -0.035649176207481925, -0.020823012307768556, -0.18122203103294374, 0.10655562450500881, 0.02753657442683886, 0.08089880467395276, -0.13133254230100042, -0.19362980927828521, -0.213926987280415, 0.023646196150886162, 0.08835250433878086, 0.0018865302854031878, 0.2460840123960571, -0.10043741685443647, -0.09196956123715998, 0.395239762257829, -0.004158699154643165, -0.07125979753410709, 0.16889720682298676, -0.17095893068818396, -0.059294551732905564, 0.1415091602469883, 0.1318612514033226, 0.0801942922892825, -0.09002902435964816, 0.09999862497144411, 0.006541500992690479, 0.15118886320384003, 0.1090730580451366, 0.08687077450477296, 0.273603503261083, 0.1850252035541676, 0.08310309573633796, 0.1318732782522039, -0.14748132062682306, 0.04161731980275363, -0.17202732703160672, -0.20773511298466474, -0.2413142926573831, 0.06506201076055211, -0.06239485313484953, -0.2320760919627944, 0.4714495061031942, 0.10301658774482175, 0.15234979235156926, -0.05322485942798223, 0.20329564269022307, 0.1110653862297546, 0.09893137195363774, 0.03208282596287539, 0.3257035713731533, 0.17253189652858833, 0.10580454120922479, -0.23518797251606538, 0.07595396180875555, -0.0307279569207735]
1,802.09143
Multicopter attitude control for recovery from large disturbances
We present a novel, high-performance attitude control law for multicopters, with a view to recovery from large disturbances. The controller is compared to three well-established alternatives from the literature. All controllers considered are identical to first order, but differ in their computation of the attitude error. We show that the popular use of the skew-symmetric part of the rotation matrix is problematic from a safety perspective, and specifically that the closed loop system may linger at large attitude errors for an arbitrary duration (leading to potential failures of practical systems). The novel proposed controller prioritizes the error in the vehicle thrust direction, and is shown to outperform a similar, existing controller from the literature. Stability follows via a Lyapunov function, and the controller is validated in experiments. This novel controller is especially attractive in safety-critical situations, where a multicopter may be required to recover from large initial disturbances.
cs.RO
we present a novel highperformance attitude control law for multicopters with a view to recovery from large disturbances the controller is compared to three wellestablished alternatives from the literature all controllers considered are identical to first order but differ in their computation of the attitude error we show that the popular use of the skewsymmetric part of the rotation matrix is problematic from a safety perspective and specifically that the closed loop system may linger at large attitude errors for an arbitrary duration leading to potential failures of practical systems the novel proposed controller prioritizes the error in the vehicle thrust direction and is shown to outperform a similar existing controller from the literature stability follows via a lyapunov function and the controller is validated in experiments this novel controller is especially attractive in safetycritical situations where a multicopter may be required to recover from large initial disturbances
[['we', 'present', 'a', 'novel', 'highperformance', 'attitude', 'control', 'law', 'for', 'multicopters', 'with', 'a', 'view', 'to', 'recovery', 'from', 'large', 'disturbances', 'the', 'controller', 'is', 'compared', 'to', 'three', 'wellestablished', 'alternatives', 'from', 'the', 'literature', 'all', 'controllers', 'considered', 'are', 'identical', 'to', 'first', 'order', 'but', 'differ', 'in', 'their', 'computation', 'of', 'the', 'attitude', 'error', 'we', 'show', 'that', 'the', 'popular', 'use', 'of', 'the', 'skewsymmetric', 'part', 'of', 'the', 'rotation', 'matrix', 'is', 'problematic', 'from', 'a', 'safety', 'perspective', 'and', 'specifically', 'that', 'the', 'closed', 'loop', 'system', 'may', 'linger', 'at', 'large', 'attitude', 'errors', 'for', 'an', 'arbitrary', 'duration', 'leading', 'to', 'potential', 'failures', 'of', 'practical', 'systems', 'the', 'novel', 'proposed', 'controller', 'prioritizes', 'the', 'error', 'in', 'the', 'vehicle', 'thrust', 'direction', 'and', 'is', 'shown', 'to', 'outperform', 'a', 'similar', 'existing', 'controller', 'from', 'the', 'literature', 'stability', 'follows', 'via', 'a', 'lyapunov', 'function', 'and', 'the', 'controller', 'is', 'validated', 'in', 'experiments', 'this', 'novel', 'controller', 'is', 'especially', 'attractive', 'in', 'safetycritical', 'situations', 'where', 'a', 'multicopter', 'may', 'be', 'required', 'to', 'recover', 'from', 'large', 'initial', 'disturbances']]
[-0.1527755443923918, 0.03379540819121364, -0.08779243578799258, 0.035393773486862914, -0.08133943961159251, -0.17941803706658854, 0.01697197012647332, 0.3546938720108891, -0.27753796741819464, -0.28979107536174153, 0.15500409763724846, -0.24080064649869865, -0.17037522192490664, 0.2366226116900106, -0.1726990926291438, 0.1307839464358482, 0.06006526096088409, 0.04427493965674846, -0.0483615934849572, -0.19493681139539223, 0.284792687759634, 0.044776497146026606, 0.27295048475089306, -0.024633185063312586, 0.1216608586251528, -0.028495912375620793, 0.015660263789106614, 0.03474048941358421, -0.06193685531980009, 0.09953233112684905, 0.27251410089760414, 0.12618208790160212, 0.3222156120841769, -0.41107261562216524, -0.17214616096729562, 0.10103808439689109, 0.12834625854786183, 0.13932429673150182, -0.06217032203110992, -0.2989000879240701, 0.12418673440776262, -0.21025347806563652, -0.10425231082233556, -0.07026429867806114, 0.012012772443012108, 0.04251220735180116, -0.31569824892574466, 0.029316074741891008, 0.015168847312255623, 0.04230041750329169, -0.07667020581602874, -0.11289109859373295, 0.006514683551457082, 0.19462504602553374, 0.0639766879691239, 0.026704505894559662, 0.17098028329201043, -0.09336269469939587, -0.12848076880421816, 0.3840341999170345, -0.007834710846214581, -0.2137546275767523, 0.17239847681422188, -0.09095706718240713, -0.11317367680886811, 0.13451960894933626, 0.22181405333921667, 0.08771315493961722, -0.16432990765944752, 0.0328680935392087, 0.02102742744436664, 0.1823361653392518, -0.0004968463641440345, -0.011714573505938658, 0.16279984674907313, 0.17853484545658166, 0.13422515276014, 0.1325211411560697, -0.05590285906077337, -0.1341335598058445, -0.29830223422598195, -0.10839300622181916, -0.15211347135089062, -0.020003264209859678, -0.06250250058980561, -0.12978369634456122, 0.37527418935772133, 0.20279263702340777, 0.1518415681895095, 0.1043835951257623, 0.38014908540188463, 0.10183642958872952, 0.08381819541131877, 0.10289602609967964, 0.2840418269365359, 0.07668007162361834, 0.11759671209556227, -0.22412082671842262, 0.11625503507644139, 0.005362964946323553]
1,802.09144
Invariant-based inverse engineering for fluctuation transfer between membranes in an optomechanical cavity system
In this paper, by invariant-based inverse engineering, we design classical driving fields to transfer quantum fluctuations between two suspended membranes in an optomechanical cavity system. The transfer can be quickly attained through a non-adiabatic evolution path determined by a so-called dynamical invariant. Such an evolution path allows one to optimize the occupancies of the unstable "intermediate" states thus the influence of cavity decays can be suppressed. Numerical simulation demonstrates that a perfect fluctuation transfer between two membranes can be rapidly achieved in one step, and the transfer is robust to both the amplitude noises and cavity decays.
quant-ph
in this paper by invariantbased inverse engineering we design classical driving fields to transfer quantum fluctuations between two suspended membranes in an optomechanical cavity system the transfer can be quickly attained through a nonadiabatic evolution path determined by a socalled dynamical invariant such an evolution path allows one to optimize the occupancies of the unstable intermediate states thus the influence of cavity decays can be suppressed numerical simulation demonstrates that a perfect fluctuation transfer between two membranes can be rapidly achieved in one step and the transfer is robust to both the amplitude noises and cavity decays
[['in', 'this', 'paper', 'by', 'invariantbased', 'inverse', 'engineering', 'we', 'design', 'classical', 'driving', 'fields', 'to', 'transfer', 'quantum', 'fluctuations', 'between', 'two', 'suspended', 'membranes', 'in', 'an', 'optomechanical', 'cavity', 'system', 'the', 'transfer', 'can', 'be', 'quickly', 'attained', 'through', 'a', 'nonadiabatic', 'evolution', 'path', 'determined', 'by', 'a', 'socalled', 'dynamical', 'invariant', 'such', 'an', 'evolution', 'path', 'allows', 'one', 'to', 'optimize', 'the', 'occupancies', 'of', 'the', 'unstable', 'intermediate', 'states', 'thus', 'the', 'influence', 'of', 'cavity', 'decays', 'can', 'be', 'suppressed', 'numerical', 'simulation', 'demonstrates', 'that', 'a', 'perfect', 'fluctuation', 'transfer', 'between', 'two', 'membranes', 'can', 'be', 'rapidly', 'achieved', 'in', 'one', 'step', 'and', 'the', 'transfer', 'is', 'robust', 'to', 'both', 'the', 'amplitude', 'noises', 'and', 'cavity', 'decays']]
[-0.16308955419040524, 0.2335546317815747, -0.11025680130174786, 0.04034686014152218, -0.009373045670463867, -0.16122605311852334, 0.01242102365748784, 0.3809909358543834, -0.3561544455587864, -0.2707523944566852, 0.04844678303025202, -0.24516121903209367, -0.13715605841008657, 0.2153436924071656, -0.009826484217894138, 0.08047628309577703, 0.07768938172435791, -0.04788748871717487, -0.04216135406660242, -0.15522289739744066, 0.29438969350333527, 0.06141081735006889, 0.2889444696592148, 0.029532024483244445, 0.06329588161435784, -0.014053722373065874, 0.05411047915227173, 0.005068924354830968, -0.1098991603589498, 0.08953508652792283, 0.24396506671976184, 0.04061367847121407, 0.2774732558383155, -0.43431928072163123, -0.21673928514199772, 0.09350829316091906, 0.2187773785313841, 0.16580733925718621, -0.0482180382226493, -0.25876746347807733, 0.0492360719681247, -0.17665755276126577, -0.08688801204420857, -0.07722262464962977, -0.009112560982364662, -0.02484657310103018, -0.30255409449185294, 0.04450190394214287, 0.04012258445871658, 0.011518450468279345, -0.026296876669146083, -0.016942888420296006, -0.02218823233312092, 0.16915785433417282, -0.002507763062651778, 0.009385499666377748, 0.21445402728163243, -0.12880286199674396, -0.12853014566359522, 0.3345048691040462, -0.09683054598581199, -0.2155489696669224, 0.17838998446024992, -0.09887318140299049, -0.01642607326724941, 0.14241940220913937, 0.14244477464289396, 0.0923627505232532, -0.16615311724623455, 0.0216456764874519, 0.0747858220039262, 0.19287858993899962, 0.07341160600976154, 0.02630718287138134, 0.24077204748770323, 0.17795608922378303, 0.04799991789437139, 0.20426076791398035, -0.04633221293549946, -0.13538750653519996, -0.27022716303154365, -0.16211600541185164, -0.18326217413294255, 0.10000497482467405, -0.06642443552516046, -0.1256555084057498, 0.37018994490625623, 0.1340614017645214, 0.18216700514912912, -0.01483093188192273, 0.3112623410433838, 0.15073194999017359, 0.04807483744759535, 0.057836073647570055, 0.30949038791364614, 0.15880320882232687, 0.08971886404492345, -0.3270216618242107, 0.01128873084767808, 0.00018090207475362366]
1,802.09145
Transverse momentum spectra and nuclear modification factors of charged particles in pp, p-Pb and Pb-Pb collisions at the LHC
We report the measured transverse momentum ($p_{\rm T}$) spectra of primary charged particles from pp, p-Pb and Pb-Pb collisions at a center-of-mass energy $\sqrt{s_{\rm NN}} = 5.02$ TeV in the kinematic range of $0.15<p_{\rm T}<50$ GeV/$c$ and $|\eta|< 0.8$. A significant improvement of systematic uncertainties motivated the reanalysis of data in pp and Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV, as well as in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV, which is also presented. Spectra from Pb-Pb collisions are presented in nine centrality intervals and are compared to a reference spectrum from pp collisions scaled by the number of binary nucleon-nucleon collisions. For central collisions, the $p_{\rm T}$ spectra are suppressed by more than a factor of 7 around 6-7 GeV/$c$ with a significant reduction in suppression towards higher momenta up to 30 GeV/$c$. The nuclear modification factor $R_{\rm pPb}$, constructed from the pp and p-Pb spectra measured at the same collision energy, is consistent with unity above 8 GeV/$c$. While the spectra in both pp and Pb-Pb collisions are substantially harder at $\sqrt{s_{\rm NN}} = 5.02$ TeV compared to 2.76 TeV, the nuclear modification factors show no significant collision energy dependence. The obtained results should provide further constraints on the parton energy loss calculations to determine the transport properties of the hot and dense QCD matter.
nucl-ex hep-ex
we report the measured transverse momentum p_rm t spectra of primary charged particles from pp ppb and pbpb collisions at a centerofmass energy sqrts_rm nn 502 tev in the kinematic range of 015p_rm t50 gevc and eta 08 a significant improvement of systematic uncertainties motivated the reanalysis of data in pp and pbpb collisions at sqrts_rm nn 276 tev as well as in ppb collisions at sqrts_rm nn 502 tev which is also presented spectra from pbpb collisions are presented in nine centrality intervals and are compared to a reference spectrum from pp collisions scaled by the number of binary nucleonnucleon collisions for central collisions the p_rm t spectra are suppressed by more than a factor of 7 around 67 gevc with a significant reduction in suppression towards higher momenta up to 30 gevc the nuclear modification factor r_rm ppb constructed from the pp and ppb spectra measured at the same collision energy is consistent with unity above 8 gevc while the spectra in both pp and pbpb collisions are substantially harder at sqrts_rm nn 502 tev compared to 276 tev the nuclear modification factors show no significant collision energy dependence the obtained results should provide further constraints on the parton energy loss calculations to determine the transport properties of the hot and dense qcd matter
[['we', 'report', 'the', 'measured', 'transverse', 'momentum', 'p_rm', 't', 'spectra', 'of', 'primary', 'charged', 'particles', 'from', 'pp', 'ppb', 'and', 'pbpb', 'collisions', 'at', 'a', 'centerofmass', 'energy', 'sqrts_rm', 'nn', '502', 'tev', 'in', 'the', 'kinematic', 'range', 'of', '015p_rm', 't50', 'gevc', 'and', 'eta', '08', 'a', 'significant', 'improvement', 'of', 'systematic', 'uncertainties', 'motivated', 'the', 'reanalysis', 'of', 'data', 'in', 'pp', 'and', 'pbpb', 'collisions', 'at', 'sqrts_rm', 'nn', '276', 'tev', 'as', 'well', 'as', 'in', 'ppb', 'collisions', 'at', 'sqrts_rm', 'nn', '502', 'tev', 'which', 'is', 'also', 'presented', 'spectra', 'from', 'pbpb', 'collisions', 'are', 'presented', 'in', 'nine', 'centrality', 'intervals', 'and', 'are', 'compared', 'to', 'a', 'reference', 'spectrum', 'from', 'pp', 'collisions', 'scaled', 'by', 'the', 'number', 'of', 'binary', 'nucleonnucleon', 'collisions', 'for', 'central', 'collisions', 'the', 'p_rm', 't', 'spectra', 'are', 'suppressed', 'by', 'more', 'than', 'a', 'factor', 'of', '7', 'around', '67', 'gevc', 'with', 'a', 'significant', 'reduction', 'in', 'suppression', 'towards', 'higher', 'momenta', 'up', 'to', '30', 'gevc', 'the', 'nuclear', 'modification', 'factor', 'r_rm', 'ppb', 'constructed', 'from', 'the', 'pp', 'and', 'ppb', 'spectra', 'measured', 'at', 'the', 'same', 'collision', 'energy', 'is', 'consistent', 'with', 'unity', 'above', '8', 'gevc', 'while', 'the', 'spectra', 'in', 'both', 'pp', 'and', 'pbpb', 'collisions', 'are', 'substantially', 'harder', 'at', 'sqrts_rm', 'nn', '502', 'tev', 'compared', 'to', '276', 'tev', 'the', 'nuclear', 'modification', 'factors', 'show', 'no', 'significant', 'collision', 'energy', 'dependence', 'the', 'obtained', 'results', 'should', 'provide', 'further', 'constraints', 'on', 'the', 'parton', 'energy', 'loss', 'calculations', 'to', 'determine', 'the', 'transport', 'properties', 'of', 'the', 'hot', 'and', 'dense', 'qcd', 'matter']]
[-0.05602646901119173, 0.22606690394416176, -0.16794956558064936, 0.13460625440024565, 0.09065347338522163, -0.08727239113499376, -0.12771445445401627, 0.3575706887091251, -0.16399090475385525, -0.3803287120708437, -0.1397950070450962, -0.4641654720094434, 0.1956923802823035, 0.15489521875429932, 0.0937463971056163, 0.10881055532566582, 0.19375389478389277, 0.006496603420802987, -0.0658601462383996, -0.18817104961015974, 0.2383692454012042, 0.2170120123051607, 0.16610564158677502, 0.20517626701836922, 0.03432635172470731, 0.09492276464718291, -0.010622465025840534, -0.005721089481893513, -0.14670873285676525, 0.03674389674065255, 0.36236739715699245, -0.04550797260944145, 0.12098322538292484, -0.2925681385332374, -0.08868613589934453, 0.13319798178660372, 0.14877024658899582, 0.041366725691693355, -0.08031287431131878, -0.24846876479299412, 0.197407946600126, -0.3084678007095742, -0.11526214043530032, 0.0062641158152406135, 0.039516119780105156, 0.05552731795830402, -0.2765681973887021, 0.21507856434227843, -0.025944206276714493, 0.1727346255596179, -0.05970739121807532, -0.2789945825826618, -0.12850626514194086, -0.07679240040791531, 0.06155753135896736, 0.17474823104674686, 0.2088367569786324, -0.10224837589258742, -0.18747358566960665, 0.42780475841869636, 0.06487176823072703, -0.0458613889231519, 0.20682638024057573, -0.21244679165236582, -0.14055076821306203, 0.214049485066897, 0.3278187442375821, 0.0543649069947639, -0.25086583711500104, 0.004910359480601511, 0.03923744453371641, 0.24086591406483893, 0.15185647305204636, 0.0794764363715701, 0.0738784300823075, 0.18024476843398857, -0.03639761477070688, 0.048210282003748474, -0.1565592243148583, -0.06799808886393698, -0.4333024127629836, 0.0011129690899030753, -0.10112298183850255, 0.07051398913177696, -0.14221636919878453, 0.09965461943540033, 0.3227565101718668, 0.07291315401858743, 0.3913908430754586, -0.007394114318972074, 0.262031504431636, 0.08564708101308767, 0.06219570219939299, 0.18092461272694724, 0.3149972652059255, 0.1560435136521442, 0.29348607530657855, -0.23498513008477553, -0.033633127183377465, 0.030007076867925073]
1,802.09146
Iron-based trinuclear metal-organic nanostructures on a surface with local charge accumulation
Coordination chemistry relies on harnessing active metal sites within organic matrices. Polynuclear complexes - consisting of organic ligands binding to clusters of several metal atoms are of particular interest, owing to their electronic/magnetic properties and potential for functional reactivity pathways. However, their synthesis remains challenging; only a limited number of geometries and configurations have been achieved. Here, we synthesise - via supramolecular chemistry on a noble metal surface - one-dimensional metal-organic nanostructures composed of terpyridine (tpy)-based molecules coordinated with well-defined polynuclear iron clusters. By a combination of low-temperature scanning probe microscopy techniques and density functional theory, we demonstrate that the coordination motif consists of coplanar tpy's linked via a linear tri-iron node in a mixed (positive) valence, metal-metal bond configuration. This unusual linkage is stabilized by a local accumulation of electrons at the interface between cations, ligand and surface. The latter, enabled by the bottom-up on-surface synthesis, hints at a chemically active metal centre, and opens the door to the engineering of nanomaterials with novel catalytic and magnetic functionalities.
cond-mat.mes-hall cond-mat.mtrl-sci physics.chem-ph
coordination chemistry relies on harnessing active metal sites within organic matrices polynuclear complexes consisting of organic ligands binding to clusters of several metal atoms are of particular interest owing to their electronicmagnetic properties and potential for functional reactivity pathways however their synthesis remains challenging only a limited number of geometries and configurations have been achieved here we synthesise via supramolecular chemistry on a noble metal surface onedimensional metalorganic nanostructures composed of terpyridine tpybased molecules coordinated with welldefined polynuclear iron clusters by a combination of lowtemperature scanning probe microscopy techniques and density functional theory we demonstrate that the coordination motif consists of coplanar tpys linked via a linear triiron node in a mixed positive valence metalmetal bond configuration this unusual linkage is stabilized by a local accumulation of electrons at the interface between cations ligand and surface the latter enabled by the bottomup onsurface synthesis hints at a chemically active metal centre and opens the door to the engineering of nanomaterials with novel catalytic and magnetic functionalities
[['coordination', 'chemistry', 'relies', 'on', 'harnessing', 'active', 'metal', 'sites', 'within', 'organic', 'matrices', 'polynuclear', 'complexes', 'consisting', 'of', 'organic', 'ligands', 'binding', 'to', 'clusters', 'of', 'several', 'metal', 'atoms', 'are', 'of', 'particular', 'interest', 'owing', 'to', 'their', 'electronicmagnetic', 'properties', 'and', 'potential', 'for', 'functional', 'reactivity', 'pathways', 'however', 'their', 'synthesis', 'remains', 'challenging', 'only', 'a', 'limited', 'number', 'of', 'geometries', 'and', 'configurations', 'have', 'been', 'achieved', 'here', 'we', 'synthesise', 'via', 'supramolecular', 'chemistry', 'on', 'a', 'noble', 'metal', 'surface', 'onedimensional', 'metalorganic', 'nanostructures', 'composed', 'of', 'terpyridine', 'tpybased', 'molecules', 'coordinated', 'with', 'welldefined', 'polynuclear', 'iron', 'clusters', 'by', 'a', 'combination', 'of', 'lowtemperature', 'scanning', 'probe', 'microscopy', 'techniques', 'and', 'density', 'functional', 'theory', 'we', 'demonstrate', 'that', 'the', 'coordination', 'motif', 'consists', 'of', 'coplanar', 'tpys', 'linked', 'via', 'a', 'linear', 'triiron', 'node', 'in', 'a', 'mixed', 'positive', 'valence', 'metalmetal', 'bond', 'configuration', 'this', 'unusual', 'linkage', 'is', 'stabilized', 'by', 'a', 'local', 'accumulation', 'of', 'electrons', 'at', 'the', 'interface', 'between', 'cations', 'ligand', 'and', 'surface', 'the', 'latter', 'enabled', 'by', 'the', 'bottomup', 'onsurface', 'synthesis', 'hints', 'at', 'a', 'chemically', 'active', 'metal', 'centre', 'and', 'opens', 'the', 'door', 'to', 'the', 'engineering', 'of', 'nanomaterials', 'with', 'novel', 'catalytic', 'and', 'magnetic', 'functionalities']]
[-0.11178995790052873, 0.17258496572223544, 0.011385546265844187, -0.01690374681743239, -0.004503584783981366, -0.16949636209470453, 0.13398244863046058, 0.42371946506907854, -0.261188355814437, -0.31013745391895664, -0.02857541388109258, -0.28607249220738906, -0.16399051108900342, 0.14224000288847766, 0.026950191042208874, -0.01033516178490377, -0.00021184119824434351, -0.11597168911819809, -0.04703497619116736, -0.16545321130582297, 0.25311356798482865, 0.05169061938246449, 0.29643504632396933, 0.10185552772671624, 0.06821765320552685, -0.022584574157086434, 0.07459032949791547, 0.019137856427671535, -0.13291169089241778, 0.22417936375372874, 0.2790404291812079, -0.023026876840054805, 0.2391508212313056, -0.5295865743369595, -0.26341238127452854, 0.007778529409159181, 0.1393996598556112, 0.15030434523691977, -0.17166173819772487, -0.24802066692282543, 0.043605903017140374, -0.12092014976371468, -0.12940969048753564, -0.0735731440556287, -0.015172882502658601, 0.06850049091557303, -0.2112690639493564, 0.05273939227932447, -0.009927774522384983, 0.11775228796873, -0.08952794144318604, -0.1345309263746614, -0.0948988442634878, 0.0850311051604218, -0.041223175922248716, -0.018992805275694677, 0.25778891999514464, -0.09840187304681795, -0.1052364036869372, 0.3867391978413369, -0.009034690271457372, -0.10384538280777633, 0.27594589945100295, -0.11551757341399332, -0.1452823769304033, 0.19056126140229449, 0.12889767107318092, 0.1654565571343092, -0.17852754945198268, 0.0987788583616229, 0.01898015088164619, 0.19276894750255674, 0.08109831649444403, 0.048556160778121485, 0.2975053421244528, 0.24187102665170523, 0.04965467921292489, 0.15332440787317814, -0.07868230579695179, -0.08083308077320182, -0.11868109281297681, -0.21796713131794168, -0.19896267217932487, 0.034249152676802286, -0.05606002155266434, -0.20517886580293712, 0.36403453889434323, 0.03198103169607787, 0.14790779704148052, -0.08322132734240438, 0.21642126284676827, -0.029023762862340895, 0.09914084769031205, -0.04593581946543846, 0.18649610874537334, 0.18301814157612897, 0.0609000540360597, -0.27322659015789785, 0.14770969958044589, 0.03815750441688222]
1,802.09147
A stochastic asymptotic-preserving scheme for the bipolar semiconductor Boltzmann-Poisson system with random inputs and diffusive scalings
In this paper, we study the bipolar Boltzmann-Poisson model, both for the deterministic system and the system with uncertainties, with asymptotic behavior leading to the drift diffusion-Poisson system as the Knudsen number goes to zero. The random inputs can arise from collision kernels, doping profile and initial data. We adopt a generalized polynomial chaos approach based stochastic Galerkin (gPC-SG) method. Sensitivity analysis is conducted using hypocoercivity theory for both the analytical solution and the gPC solution for a simpler model that ignores the electric field, and it gives their convergence toward the global Maxwellian exponentially in time. A formal proof of the stochastic asymptotic-preserving (s-AP) property and a uniform spectral convergence with error exponentially decaying in time in the random space of the scheme is given. Numerical experiments are conducted to validate the accuracy, efficiency and asymptotic properties of the proposed method.
math.NA
in this paper we study the bipolar boltzmannpoisson model both for the deterministic system and the system with uncertainties with asymptotic behavior leading to the drift diffusionpoisson system as the knudsen number goes to zero the random inputs can arise from collision kernels doping profile and initial data we adopt a generalized polynomial chaos approach based stochastic galerkin gpcsg method sensitivity analysis is conducted using hypocoercivity theory for both the analytical solution and the gpc solution for a simpler model that ignores the electric field and it gives their convergence toward the global maxwellian exponentially in time a formal proof of the stochastic asymptoticpreserving sap property and a uniform spectral convergence with error exponentially decaying in time in the random space of the scheme is given numerical experiments are conducted to validate the accuracy efficiency and asymptotic properties of the proposed method
[['in', 'this', 'paper', 'we', 'study', 'the', 'bipolar', 'boltzmannpoisson', 'model', 'both', 'for', 'the', 'deterministic', 'system', 'and', 'the', 'system', 'with', 'uncertainties', 'with', 'asymptotic', 'behavior', 'leading', 'to', 'the', 'drift', 'diffusionpoisson', 'system', 'as', 'the', 'knudsen', 'number', 'goes', 'to', 'zero', 'the', 'random', 'inputs', 'can', 'arise', 'from', 'collision', 'kernels', 'doping', 'profile', 'and', 'initial', 'data', 'we', 'adopt', 'a', 'generalized', 'polynomial', 'chaos', 'approach', 'based', 'stochastic', 'galerkin', 'gpcsg', 'method', 'sensitivity', 'analysis', 'is', 'conducted', 'using', 'hypocoercivity', 'theory', 'for', 'both', 'the', 'analytical', 'solution', 'and', 'the', 'gpc', 'solution', 'for', 'a', 'simpler', 'model', 'that', 'ignores', 'the', 'electric', 'field', 'and', 'it', 'gives', 'their', 'convergence', 'toward', 'the', 'global', 'maxwellian', 'exponentially', 'in', 'time', 'a', 'formal', 'proof', 'of', 'the', 'stochastic', 'asymptoticpreserving', 'sap', 'property', 'and', 'a', 'uniform', 'spectral', 'convergence', 'with', 'error', 'exponentially', 'decaying', 'in', 'time', 'in', 'the', 'random', 'space', 'of', 'the', 'scheme', 'is', 'given', 'numerical', 'experiments', 'are', 'conducted', 'to', 'validate', 'the', 'accuracy', 'efficiency', 'and', 'asymptotic', 'properties', 'of', 'the', 'proposed', 'method']]
[-0.11383579637696768, 0.019094711338031166, -0.14418206325606675, 0.05339980123528273, -0.03937497256812474, -0.12148022494470397, 0.05744651017102895, 0.3339977431976309, -0.27877382504760373, -0.26534562413778867, 0.1140505360928199, -0.2554478258528608, -0.1189610489915746, 0.1861047300853575, -0.025687210631708726, 0.13390421196950456, 0.07124559372557816, 0.010588526298087222, -0.058868057537883364, -0.23051613653144726, 0.2824801445364001, 0.07969250592010109, 0.2932900505960698, 0.006583797438268332, 0.12260333631527841, -0.04568611977932354, -0.024078855713736927, 0.03880159646179362, -0.11306514900619641, 0.08024197744687768, 0.19032890965719543, 0.10909090197730995, 0.3156600125424617, -0.41545888019976673, -0.1928955493693022, 0.07869747571039495, 0.1683472379780348, 0.12043828208078729, -0.046451908280203576, -0.2816340357646452, 0.09527900497468704, -0.18546661865362463, -0.17399067692838424, -0.10480936492317693, -0.02462835853889664, 0.08739055099761682, -0.33317381431553383, 0.10560947766771923, 0.08046878739227112, 0.04775126797315526, -0.06343633704818785, -0.09299366707923486, 0.025679381656937686, 0.0747574364423012, 0.07876016148894444, 0.014147029342526134, 0.09542819072248031, -0.071548724902054, -0.09429026965517551, 0.34246570954482397, -0.10509696851999677, -0.2432587228464425, 0.18809525504648844, -0.13130303896990017, -0.07946186604519896, 0.16640450168361373, 0.2039120500966748, 0.12883841979659183, -0.12063011558766061, 0.10649647188277135, -0.018574734409967212, 0.1463714964846347, 0.026582446052933917, 0.01672077465947744, 0.09035288929569384, 0.20326562064653592, 0.08499395782920591, 0.13596370951635828, -0.09077729656673135, -0.15731959352732128, -0.30715903293024355, -0.13624443088043878, -0.18278179390369154, 0.01684852666138995, -0.15397596780928216, -0.189156220974863, 0.40110031117986805, 0.19226914018405772, 0.1629650379252019, 0.1209236502231277, 0.31365359524357406, 0.16684359636947063, -0.032860460910774394, 0.0916223831867786, 0.20472848587107997, 0.155901110318245, 0.1565433697022022, -0.24412721474588922, 0.07063561861224948, 0.1280316361870141]
1,802.09148
Modeling Interdependent and Periodic Real-World Action Sequences
Mobile health applications, including those that track activities such as exercise, sleep, and diet, are becoming widely used. Accurately predicting human actions is essential for targeted recommendations that could improve our health and for personalization of these applications. However, making such predictions is extremely difficult due to the complexities of human behavior, which consists of a large number of potential actions that vary over time, depend on each other, and are periodic. Previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating, commuting or exercising. In this work, we develop a novel statistical model for Time-varying, Interdependent, and Periodic Action Sequences. Our approach is based on personalized, multivariate temporal point processes that model time-varying action propensities through a mixture of Gaussian intensities. Our model captures short-term and long-term periodic interdependencies between actions through Hawkes process-based self-excitations. We evaluate our approach on two activity logging datasets comprising 12 million actions taken by 20 thousand users over 17 months. We demonstrate that our approach allows us to make successful predictions of future user actions and their timing. Specifically, our model improves predictions of actions, and their timing, over existing methods across multiple datasets by up to 156%, and up to 37%, respectively. Performance improvements are particularly large for relatively rare and periodic actions such as walking and biking, improving over baselines by up to 256%. This demonstrates that explicit modeling of dependencies and periodicities in real-world behavior enables successful predictions of future actions, with implications for modeling human behavior, app personalization, and targeting of health interventions.
cs.SI
mobile health applications including those that track activities such as exercise sleep and diet are becoming widely used accurately predicting human actions is essential for targeted recommendations that could improve our health and for personalization of these applications however making such predictions is extremely difficult due to the complexities of human behavior which consists of a large number of potential actions that vary over time depend on each other and are periodic previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating commuting or exercising in this work we develop a novel statistical model for timevarying interdependent and periodic action sequences our approach is based on personalized multivariate temporal point processes that model timevarying action propensities through a mixture of gaussian intensities our model captures shortterm and longterm periodic interdependencies between actions through hawkes processbased selfexcitations we evaluate our approach on two activity logging datasets comprising 12 million actions taken by 20 thousand users over 17 months we demonstrate that our approach allows us to make successful predictions of future user actions and their timing specifically our model improves predictions of actions and their timing over existing methods across multiple datasets by up to 156 and up to 37 respectively performance improvements are particularly large for relatively rare and periodic actions such as walking and biking improving over baselines by up to 256 this demonstrates that explicit modeling of dependencies and periodicities in realworld behavior enables successful predictions of future actions with implications for modeling human behavior app personalization and targeting of health interventions
[['mobile', 'health', 'applications', 'including', 'those', 'that', 'track', 'activities', 'such', 'as', 'exercise', 'sleep', 'and', 'diet', 'are', 'becoming', 'widely', 'used', 'accurately', 'predicting', 'human', 'actions', 'is', 'essential', 'for', 'targeted', 'recommendations', 'that', 'could', 'improve', 'our', 'health', 'and', 'for', 'personalization', 'of', 'these', 'applications', 'however', 'making', 'such', 'predictions', 'is', 'extremely', 'difficult', 'due', 'to', 'the', 'complexities', 'of', 'human', 'behavior', 'which', 'consists', 'of', 'a', 'large', 'number', 'of', 'potential', 'actions', 'that', 'vary', 'over', 'time', 'depend', 'on', 'each', 'other', 'and', 'are', 'periodic', 'previous', 'work', 'has', 'not', 'jointly', 'modeled', 'these', 'dynamics', 'and', 'has', 'largely', 'focused', 'on', 'item', 'consumption', 'patterns', 'instead', 'of', 'broader', 'types', 'of', 'behaviors', 'such', 'as', 'eating', 'commuting', 'or', 'exercising', 'in', 'this', 'work', 'we', 'develop', 'a', 'novel', 'statistical', 'model', 'for', 'timevarying', 'interdependent', 'and', 'periodic', 'action', 'sequences', 'our', 'approach', 'is', 'based', 'on', 'personalized', 'multivariate', 'temporal', 'point', 'processes', 'that', 'model', 'timevarying', 'action', 'propensities', 'through', 'a', 'mixture', 'of', 'gaussian', 'intensities', 'our', 'model', 'captures', 'shortterm', 'and', 'longterm', 'periodic', 'interdependencies', 'between', 'actions', 'through', 'hawkes', 'processbased', 'selfexcitations', 'we', 'evaluate', 'our', 'approach', 'on', 'two', 'activity', 'logging', 'datasets', 'comprising', '12', 'million', 'actions', 'taken', 'by', '20', 'thousand', 'users', 'over', '17', 'months', 'we', 'demonstrate', 'that', 'our', 'approach', 'allows', 'us', 'to', 'make', 'successful', 'predictions', 'of', 'future', 'user', 'actions', 'and', 'their', 'timing', 'specifically', 'our', 'model', 'improves', 'predictions', 'of', 'actions', 'and', 'their', 'timing', 'over', 'existing', 'methods', 'across', 'multiple', 'datasets', 'by', 'up', 'to', '156', 'and', 'up', 'to', '37', 'respectively', 'performance', 'improvements', 'are', 'particularly', 'large', 'for', 'relatively', 'rare', 'and', 'periodic', 'actions', 'such', 'as', 'walking', 'and', 'biking', 'improving', 'over', 'baselines', 'by', 'up', 'to', '256', 'this', 'demonstrates', 'that', 'explicit', 'modeling', 'of', 'dependencies', 'and', 'periodicities', 'in', 'realworld', 'behavior', 'enables', 'successful', 'predictions', 'of', 'future', 'actions', 'with', 'implications', 'for', 'modeling', 'human', 'behavior', 'app', 'personalization', 'and', 'targeting', 'of', 'health', 'interventions']]
[-0.06715998900341871, 0.08575826597142854, -0.045371479299197444, 0.05517326609914386, -0.10464554593495246, -0.1699888905781363, 0.0928600188735664, 0.44443067478766635, -0.21590483451171763, -0.36377670586112637, 0.11667949342785532, -0.30492128460124396, -0.19387410308404673, 0.2420684087356038, -0.10724239328219347, 0.07793670123679314, 0.09353674896132659, 0.04091666704443381, -0.00038061910804097, -0.28510523934886833, 0.2643261868749926, 0.045451806927683636, 0.2974349534827104, 0.0389272074333267, 0.0862413309862031, 0.04121483280410323, -0.08610791954952084, -0.013713258243888728, -0.044407161904588856, 0.13946426225089426, 0.29824327406258, 0.1698615049121036, 0.325132420112782, -0.4274270885281696, -0.2574245637780535, 0.08839922914813175, 0.118409707025041, 0.04991910454294551, -0.0015524148944515124, -0.3289891226849616, 0.0911835014959971, -0.20811222464110313, -0.06687532184878364, -0.14796530840585684, 0.042030838591832, 0.03763528459978206, -0.2866655840528017, 0.0408877127181822, 0.013551842687137203, 0.10876993622818489, -0.08571641481157441, -0.09694258071162473, 0.01717568884965088, 0.2501727519930452, 0.09291894740942838, -0.024868913842782156, 0.17258558799026172, -0.1189472020536984, -0.16725657720713, 0.3722104786533807, -0.04925880759499216, -0.16524441674379492, 0.24581179295496236, -0.07806972485431926, -0.15733858291233488, 0.11456561849431705, 0.25134642152185205, 0.11538613003282461, -0.16983853127293067, -0.011507996944615047, 0.006690301226952405, 0.18186149021505063, 0.03955207400392296, 0.018516952023796263, 0.2095853998299702, 0.22855078390931516, 0.03613459785449764, 0.06012470075411465, -0.0720707909169315, -0.12332483960155731, -0.20260304465860393, -0.07780804821731412, -0.07550730773442384, 0.035742681727229025, -0.10749966101850159, -0.13742318649399668, 0.42629064755330087, 0.23360163854511537, 0.17570197432338427, 0.10263258011769695, 0.29156397915195065, 0.015506375004162095, 0.06570406852910336, 0.04858628582337927, 0.13896548941317918, -0.004659584613079066, 0.1117351937156393, -0.18302290003013505, 0.1259593614863593, -0.025901278377503657]
1,802.09149
Dynamic and static analyses of glass-like properties of three-dimensional tissues
The mechanical properties of cells, which influence the properties of the tissue they belong to, are controlled by various mechanisms. Bi et al. theoretically demonstrated that density-independent rigidity transition occurs in two-dimensional confluent tissues that consist of mechanically uniform cells. They also analyzed the dynamical behavior of tissues near the critical point, which is geometrically controlled by `shape parameter'. To investigate whether the behavior of three-dimensional tissues is similar to that of two-dimensional ones, we extend the model proposed by Bi et al. to a three-dimensional one both dynamically and statically. The model reveals that the two mechanical states exist with a phase transition and has some similarities with those of glassy materials. Scaling analysis is applied to the static model focused in the rearrangement viewpoint. The results suggest that the upper critical dimension is also the same as the jamming transition.
cond-mat.soft
the mechanical properties of cells which influence the properties of the tissue they belong to are controlled by various mechanisms bi et al theoretically demonstrated that densityindependent rigidity transition occurs in twodimensional confluent tissues that consist of mechanically uniform cells they also analyzed the dynamical behavior of tissues near the critical point which is geometrically controlled by shape parameter to investigate whether the behavior of threedimensional tissues is similar to that of twodimensional ones we extend the model proposed by bi et al to a threedimensional one both dynamically and statically the model reveals that the two mechanical states exist with a phase transition and has some similarities with those of glassy materials scaling analysis is applied to the static model focused in the rearrangement viewpoint the results suggest that the upper critical dimension is also the same as the jamming transition
[['the', 'mechanical', 'properties', 'of', 'cells', 'which', 'influence', 'the', 'properties', 'of', 'the', 'tissue', 'they', 'belong', 'to', 'are', 'controlled', 'by', 'various', 'mechanisms', 'bi', 'et', 'al', 'theoretically', 'demonstrated', 'that', 'densityindependent', 'rigidity', 'transition', 'occurs', 'in', 'twodimensional', 'confluent', 'tissues', 'that', 'consist', 'of', 'mechanically', 'uniform', 'cells', 'they', 'also', 'analyzed', 'the', 'dynamical', 'behavior', 'of', 'tissues', 'near', 'the', 'critical', 'point', 'which', 'is', 'geometrically', 'controlled', 'by', 'shape', 'parameter', 'to', 'investigate', 'whether', 'the', 'behavior', 'of', 'threedimensional', 'tissues', 'is', 'similar', 'to', 'that', 'of', 'twodimensional', 'ones', 'we', 'extend', 'the', 'model', 'proposed', 'by', 'bi', 'et', 'al', 'to', 'a', 'threedimensional', 'one', 'both', 'dynamically', 'and', 'statically', 'the', 'model', 'reveals', 'that', 'the', 'two', 'mechanical', 'states', 'exist', 'with', 'a', 'phase', 'transition', 'and', 'has', 'some', 'similarities', 'with', 'those', 'of', 'glassy', 'materials', 'scaling', 'analysis', 'is', 'applied', 'to', 'the', 'static', 'model', 'focused', 'in', 'the', 'rearrangement', 'viewpoint', 'the', 'results', 'suggest', 'that', 'the', 'upper', 'critical', 'dimension', 'is', 'also', 'the', 'same', 'as', 'the', 'jamming', 'transition']]
[-0.0933967525611671, 0.18111084810536826, -0.07850644424964319, 0.012645399581614725, -0.02535520143426535, -0.13332417462772073, 0.057491935501006286, 0.36230076485457763, -0.2692946411774192, -0.26144787021355154, 0.0604406968496976, -0.29210790597610703, -0.24945613986838766, 0.16219662694739256, -0.034143938355042903, 0.0690883849747479, -0.038595492725299906, -0.018971207512306496, -0.04452986091467172, -0.20128316491265114, 0.31505936935452195, 0.03507563213384907, 0.33679767927600884, 0.007163330778138528, 0.025975188237129593, -0.03709714044160931, 0.07817694191611044, 0.07348966809697974, -0.17070913038666, 0.0699631422212918, 0.2137997259220279, 0.0477019345705909, 0.22851686339340055, -0.4416765815801394, -0.28036315367609577, 0.07347010671731714, 0.12302428662521162, 0.08536618479534092, -0.0510719375304458, -0.2577042455070088, 0.09534696303103053, -0.10869844615747201, -0.14422299799142063, -0.08414245669034795, 0.023404772194187667, 0.04610872990451753, -0.21562595864836598, 0.09545490026603531, 0.10446412952081464, 0.04428772600576721, -0.10161232335729078, -0.07050654617085739, -0.06645950887591617, 0.14556756251225983, 0.03397411817084657, -0.01650910572358735, 0.17219295936741563, -0.14335631413227864, -0.10470615045338029, 0.383819925123301, 0.01819374262679919, -0.1834987694968168, 0.24348985115197344, -0.15788735456036693, -0.09874904474151701, 0.14604928934107153, 0.13999019600910095, 0.10276580178244434, -0.15565108816782144, 0.05757455046298507, -0.03893192339537691, 0.16871932538535322, 0.05026545144394565, 0.008450599318422692, 0.1757320362458032, 0.1690529731535156, -0.010135281116137622, 0.17306271283461017, -0.057876635267412366, -0.12180397779972647, -0.23172711432111306, -0.14270632578925768, -0.17254197912972788, 0.008161023250144814, -0.07894951906559405, -0.19735711057995065, 0.38739841130339137, 0.14046970232796502, 0.23060620800201767, -0.005591650350537056, 0.21054599352482653, 0.07296591685530664, 0.054884040465867014, 0.033392899312262594, 0.31041211025354054, 0.11197797080967575, 0.08973653347749577, -0.2372039751371887, 0.0777132833922941, 0.07300139276120601]
1,802.0915
Global stability of traveling waves with oscillations for Nicholson's blowflies equation
For Nicholson's blowflies equation, a kind of reaction-diffusion equations with time-delay, when the ratio of birth rate coefficient and death rate coefficient satisfies $\frac{p}{\delta}>e$, the large time-delay $r>0$ usually causes the traveling waves to be oscillatory. In this paper, we are interested in the global stability of these oscillatory traveling waves, in particular, the challenging case of the critical traveling waves with oscillations. We prove that, the critical oscillatory traveling waves are globally stable with the algebraic convergence rate $t^{-1/2}$, and the non-critical traveling waves are globally stable with the exponential convergence rate $t^{-1/2}e^{-\mu t}$ for a positive constant $\mu$, where the initial perturbations around the oscillatory traveling wave in a weighted Sobolev can be arbitrarily large. The approach adopted is the technical weighted energy method with some new development in establishing the boundedness estimate of the oscillating solutions, which, with the help of optimal decay estimates by deriving the fundamental solutions for the linearized equations, can allow us to prove the global stability and to obtain the optimal convergence rates.
math.AP
for nicholsons blowflies equation a kind of reactiondiffusion equations with timedelay when the ratio of birth rate coefficient and death rate coefficient satisfies fracpdeltae the large timedelay r0 usually causes the traveling waves to be oscillatory in this paper we are interested in the global stability of these oscillatory traveling waves in particular the challenging case of the critical traveling waves with oscillations we prove that the critical oscillatory traveling waves are globally stable with the algebraic convergence rate t12 and the noncritical traveling waves are globally stable with the exponential convergence rate t12emu t for a positive constant mu where the initial perturbations around the oscillatory traveling wave in a weighted sobolev can be arbitrarily large the approach adopted is the technical weighted energy method with some new development in establishing the boundedness estimate of the oscillating solutions which with the help of optimal decay estimates by deriving the fundamental solutions for the linearized equations can allow us to prove the global stability and to obtain the optimal convergence rates
[['for', 'nicholsons', 'blowflies', 'equation', 'a', 'kind', 'of', 'reactiondiffusion', 'equations', 'with', 'timedelay', 'when', 'the', 'ratio', 'of', 'birth', 'rate', 'coefficient', 'and', 'death', 'rate', 'coefficient', 'satisfies', 'fracpdeltae', 'the', 'large', 'timedelay', 'r0', 'usually', 'causes', 'the', 'traveling', 'waves', 'to', 'be', 'oscillatory', 'in', 'this', 'paper', 'we', 'are', 'interested', 'in', 'the', 'global', 'stability', 'of', 'these', 'oscillatory', 'traveling', 'waves', 'in', 'particular', 'the', 'challenging', 'case', 'of', 'the', 'critical', 'traveling', 'waves', 'with', 'oscillations', 'we', 'prove', 'that', 'the', 'critical', 'oscillatory', 'traveling', 'waves', 'are', 'globally', 'stable', 'with', 'the', 'algebraic', 'convergence', 'rate', 't12', 'and', 'the', 'noncritical', 'traveling', 'waves', 'are', 'globally', 'stable', 'with', 'the', 'exponential', 'convergence', 'rate', 't12emu', 't', 'for', 'a', 'positive', 'constant', 'mu', 'where', 'the', 'initial', 'perturbations', 'around', 'the', 'oscillatory', 'traveling', 'wave', 'in', 'a', 'weighted', 'sobolev', 'can', 'be', 'arbitrarily', 'large', 'the', 'approach', 'adopted', 'is', 'the', 'technical', 'weighted', 'energy', 'method', 'with', 'some', 'new', 'development', 'in', 'establishing', 'the', 'boundedness', 'estimate', 'of', 'the', 'oscillating', 'solutions', 'which', 'with', 'the', 'help', 'of', 'optimal', 'decay', 'estimates', 'by', 'deriving', 'the', 'fundamental', 'solutions', 'for', 'the', 'linearized', 'equations', 'can', 'allow', 'us', 'to', 'prove', 'the', 'global', 'stability', 'and', 'to', 'obtain', 'the', 'optimal', 'convergence', 'rates']]
[-0.2066616793727976, 0.13969146293869034, -0.06541472017318499, 0.0744105664057073, -0.07237082359948631, -0.13236432880460774, 0.008609322385349966, 0.2624162962293726, -0.31761091477485626, -0.21169456913405973, 0.17131834923077552, -0.26353414081720383, -0.15089391988251613, 0.20473853153446633, -0.005304603994832259, 0.12291357255700601, 0.0696960892548961, 0.06190428926234723, -0.04178336286537085, -0.21024593926646565, 0.3210523087564393, 0.028283885702182203, 0.2691700760703589, 0.012548243059341371, 0.08730650482115132, -0.056106877803923726, 0.02257485629318381, -0.006647741471654212, -0.1987893968422676, 0.08748749792355405, 0.24049246836391336, 0.08900873224972886, 0.2999641047267122, -0.4219770170197155, -0.20174701050193924, 0.15269216891796983, 0.18326584630805623, 0.14013010956768562, -0.04455670070236538, -0.293776259895348, 0.08613431226867169, -0.07501864691744366, -0.22386849152210814, -0.047174094219350385, 0.029328736798981063, 0.16327845689857148, -0.31453530066068003, 0.1637402567654275, 0.044735442317978165, -0.014135643082103256, -0.13040369712698036, -0.03657816607813687, -0.00809747192556777, 0.09073530084308176, 0.11988722464378328, 0.021230596765881328, 0.048924809090308184, -0.11895687093465043, -0.04461503720473079, 0.32326856592240244, -0.1434424600202987, -0.23915474833755274, 0.16605339650017864, -0.17536076447876864, -0.06959022916357457, 0.16555583442026783, 0.20150295746948063, 0.1489944552600428, -0.11560618755527835, 0.055911874427865174, -0.00454537864330503, 0.13663062868783107, 0.15027923843707647, 0.022522194162231578, 0.1498808508364142, 0.1391730085373498, 0.15887771678135107, 0.1170452055314655, -0.04447892721888427, -0.11132854229037667, -0.3059544893940525, -0.11164075543156125, -0.0828946633588181, 0.08798873199302545, -0.14646387193050614, -0.1904205903259365, 0.4045097295238951, 0.09858449051961214, 0.1493465145443671, 0.1010437676656892, 0.2235817679330795, 0.19805571547924325, -0.019427378057121965, 0.12293278258623654, 0.29330197875281194, 0.13394168211207808, 0.14667795139183043, -0.2588853079208432, 0.08384086972670134, 0.11323282359300192]
1,802.09151
Parallel paths across the Pacific: a speculative explanation for the dilep in Marshallese navigation
Traditional techniques used by navigators in the Marshall Islands include the use of wave patterns as influenced by reflection and refraction around islands. The dilep is one such pattern, apparently providing signals to guide a navigator directly between two distant islands; so far there is no agreed causal explanation for such a phenomenon. We propose a mechanism; this generates a number of qualitative and quantitative predictions that may in principle be tested against satellite photo evidence, hydrodynamic simulations, experiments by small boat navigators in the right conditions, and ethnographic reports.
physics.pop-ph
traditional techniques used by navigators in the marshall islands include the use of wave patterns as influenced by reflection and refraction around islands the dilep is one such pattern apparently providing signals to guide a navigator directly between two distant islands so far there is no agreed causal explanation for such a phenomenon we propose a mechanism this generates a number of qualitative and quantitative predictions that may in principle be tested against satellite photo evidence hydrodynamic simulations experiments by small boat navigators in the right conditions and ethnographic reports
[['traditional', 'techniques', 'used', 'by', 'navigators', 'in', 'the', 'marshall', 'islands', 'include', 'the', 'use', 'of', 'wave', 'patterns', 'as', 'influenced', 'by', 'reflection', 'and', 'refraction', 'around', 'islands', 'the', 'dilep', 'is', 'one', 'such', 'pattern', 'apparently', 'providing', 'signals', 'to', 'guide', 'a', 'navigator', 'directly', 'between', 'two', 'distant', 'islands', 'so', 'far', 'there', 'is', 'no', 'agreed', 'causal', 'explanation', 'for', 'such', 'a', 'phenomenon', 'we', 'propose', 'a', 'mechanism', 'this', 'generates', 'a', 'number', 'of', 'qualitative', 'and', 'quantitative', 'predictions', 'that', 'may', 'in', 'principle', 'be', 'tested', 'against', 'satellite', 'photo', 'evidence', 'hydrodynamic', 'simulations', 'experiments', 'by', 'small', 'boat', 'navigators', 'in', 'the', 'right', 'conditions', 'and', 'ethnographic', 'reports']]
[-0.12537772857238738, 0.125309225402019, -0.1143218551479866, 0.1237958086447874, -0.09793051189659269, -0.1309383482635649, 0.06589134436707651, 0.3749672993912958, -0.21223551406409968, -0.34070158062837597, 0.0851829092010458, -0.3086304886873518, -0.19374502707649482, 0.23631119167463582, -0.0482136853787462, 0.027545546895688337, 0.06368893209133256, -0.02177251413140153, 0.031190042093584544, -0.1455887533473165, 0.2688312221454519, 0.08767720681956571, 0.2974108030203353, 0.03835856371161559, 0.06916781327572097, 0.007840117654145768, -0.05569245774047763, 0.05845680438947414, -0.11995069031498011, 0.03788000850132509, 0.26458609259028115, 0.145399882269793, 0.2765856366185995, -0.5005840835360329, -0.2167321481229214, 0.0485256967459167, 0.11302766343447893, 0.12308913370950168, -0.11998436630970348, -0.3090815453507592, 0.07038129240358143, -0.12888630302727558, -0.14940551321971848, -0.031890090000344797, -0.00480420615921697, -0.00402939419675451, -0.25394167189141004, 0.05918118547323798, 0.05103716682747341, 0.09861599768543344, -0.0108264874237893, -0.05881864207880467, -0.01088844296218974, 0.1368951771599293, 0.05849508861121669, 0.009487225862450144, 0.12125449212728424, -0.09590126509684023, -0.1503425223983071, 0.3799890899674946, -0.05027380197444994, -0.16971934044761766, 0.2159568418623105, -0.13266672826047693, -0.08032779680209214, 0.11335701122879982, 0.10181526748170511, 0.0846569233919295, -0.132963921644547, -0.024565311025153178, -0.08042288680146893, 0.17915797839202824, 0.10267861456128904, -0.011857835493531874, 0.26540376548393724, 0.1725632009106908, 0.03083178869793924, 0.09654656307068078, -0.08453213406747646, -0.056937641296745015, -0.2229457511206869, -0.11191044159997464, -0.1360189719805808, -0.005502593859878442, -0.03129537091698377, -0.14711226732470095, 0.35534715401322653, 0.16990630740294588, 0.213943085518111, -0.03946865419072382, 0.28817380870577325, 0.04676138036596599, 0.09025937230901772, 0.022252620114118195, 0.24824761464966857, 0.050729857692285704, 0.12771146131281771, -0.15836694804046386, 0.14335304130329174, 0.028819258170453516]
1,802.09152
Non-static effects in ordered and disordered quantum spin systems I: theoretical formulation, energy gap and non-extensive terms of ground-state energy of the ferromagnetic Ising model in a transverse field
In the path integral formulation of the partition function of quantum spin models, most current treatments employ the so-called static approximation to simplify the process of summing over all possible paths. Although sufficient for studying the thermodynamic aspects of the system, static approximation ignores the contributions made by time-dependent, or non-static, fluctuations in the paths of the path integral. This non-static component is very small relative to the static part, and its careful treatment is necessary for the calculation of small non-extensive quantities such as the energy gap within the path integral framework. We propose a formalism for incorporating non-static effects into the path integral calculation of a class of spin models whose partition functions are reducible to the trace of a single spin (often known as the effective Hamiltonian). We first show that the time-dependent behavior of the single spin trace is governed by the Pauli equation. Time-dependent perturbation theory is used to obtain a perturbative expansion of the solution of the Pauli equation, and then for the single spin trace. This gives us a perturbative expansion of the path integral which can be integrated systematically using standard techniques. In this paper, we develop the theoretical framework outlined above in detail and apply it to a simple ordered spin model, the infinite-range ferromagnetic Ising model in a transverse field. We calculated two non-extensive quantites with this non-static approach: the $N^0$ and $N^{-1}$ terms of the ground-state energy ($N$=number of spins) and the energy gap between the ground and first-excited states. We checked our results by comparing with those of Holstein-Primakoff transform and numerical diagonalization of the Hamiltonian. The application of the method to quantum spin-glasses is briefly discussed.
cond-mat.stat-mech
in the path integral formulation of the partition function of quantum spin models most current treatments employ the socalled static approximation to simplify the process of summing over all possible paths although sufficient for studying the thermodynamic aspects of the system static approximation ignores the contributions made by timedependent or nonstatic fluctuations in the paths of the path integral this nonstatic component is very small relative to the static part and its careful treatment is necessary for the calculation of small nonextensive quantities such as the energy gap within the path integral framework we propose a formalism for incorporating nonstatic effects into the path integral calculation of a class of spin models whose partition functions are reducible to the trace of a single spin often known as the effective hamiltonian we first show that the timedependent behavior of the single spin trace is governed by the pauli equation timedependent perturbation theory is used to obtain a perturbative expansion of the solution of the pauli equation and then for the single spin trace this gives us a perturbative expansion of the path integral which can be integrated systematically using standard techniques in this paper we develop the theoretical framework outlined above in detail and apply it to a simple ordered spin model the infiniterange ferromagnetic ising model in a transverse field we calculated two nonextensive quantites with this nonstatic approach the n0 and n1 terms of the groundstate energy nnumber of spins and the energy gap between the ground and firstexcited states we checked our results by comparing with those of holsteinprimakoff transform and numerical diagonalization of the hamiltonian the application of the method to quantum spinglasses is briefly discussed
[['in', 'the', 'path', 'integral', 'formulation', 'of', 'the', 'partition', 'function', 'of', 'quantum', 'spin', 'models', 'most', 'current', 'treatments', 'employ', 'the', 'socalled', 'static', 'approximation', 'to', 'simplify', 'the', 'process', 'of', 'summing', 'over', 'all', 'possible', 'paths', 'although', 'sufficient', 'for', 'studying', 'the', 'thermodynamic', 'aspects', 'of', 'the', 'system', 'static', 'approximation', 'ignores', 'the', 'contributions', 'made', 'by', 'timedependent', 'or', 'nonstatic', 'fluctuations', 'in', 'the', 'paths', 'of', 'the', 'path', 'integral', 'this', 'nonstatic', 'component', 'is', 'very', 'small', 'relative', 'to', 'the', 'static', 'part', 'and', 'its', 'careful', 'treatment', 'is', 'necessary', 'for', 'the', 'calculation', 'of', 'small', 'nonextensive', 'quantities', 'such', 'as', 'the', 'energy', 'gap', 'within', 'the', 'path', 'integral', 'framework', 'we', 'propose', 'a', 'formalism', 'for', 'incorporating', 'nonstatic', 'effects', 'into', 'the', 'path', 'integral', 'calculation', 'of', 'a', 'class', 'of', 'spin', 'models', 'whose', 'partition', 'functions', 'are', 'reducible', 'to', 'the', 'trace', 'of', 'a', 'single', 'spin', 'often', 'known', 'as', 'the', 'effective', 'hamiltonian', 'we', 'first', 'show', 'that', 'the', 'timedependent', 'behavior', 'of', 'the', 'single', 'spin', 'trace', 'is', 'governed', 'by', 'the', 'pauli', 'equation', 'timedependent', 'perturbation', 'theory', 'is', 'used', 'to', 'obtain', 'a', 'perturbative', 'expansion', 'of', 'the', 'solution', 'of', 'the', 'pauli', 'equation', 'and', 'then', 'for', 'the', 'single', 'spin', 'trace', 'this', 'gives', 'us', 'a', 'perturbative', 'expansion', 'of', 'the', 'path', 'integral', 'which', 'can', 'be', 'integrated', 'systematically', 'using', 'standard', 'techniques', 'in', 'this', 'paper', 'we', 'develop', 'the', 'theoretical', 'framework', 'outlined', 'above', 'in', 'detail', 'and', 'apply', 'it', 'to', 'a', 'simple', 'ordered', 'spin', 'model', 'the', 'infiniterange', 'ferromagnetic', 'ising', 'model', 'in', 'a', 'transverse', 'field', 'we', 'calculated', 'two', 'nonextensive', 'quantites', 'with', 'this', 'nonstatic', 'approach', 'the', 'n0', 'and', 'n1', 'terms', 'of', 'the', 'groundstate', 'energy', 'nnumber', 'of', 'spins', 'and', 'the', 'energy', 'gap', 'between', 'the', 'ground', 'and', 'firstexcited', 'states', 'we', 'checked', 'our', 'results', 'by', 'comparing', 'with', 'those', 'of', 'holsteinprimakoff', 'transform', 'and', 'numerical', 'diagonalization', 'of', 'the', 'hamiltonian', 'the', 'application', 'of', 'the', 'method', 'to', 'quantum', 'spinglasses', 'is', 'briefly', 'discussed']]
[-0.12024891765047145, 0.1255088770181261, -0.0947385155095128, 0.08058414240533701, -0.03919936609905093, -0.08514874519806982, 0.03404358206825885, 0.33402365250980287, -0.259501325823183, -0.2667736886319534, 0.045695745677012935, -0.2635869449371719, -0.12757452218175788, 0.15892933570532844, 0.02570545773929833, 0.06031046155944473, 0.03439873548334725, 0.04646804840237196, -0.1138839857144979, -0.1963913046861715, 0.325641650203315, 0.026912514201288637, 0.24841205820718307, 0.06901388057744577, 0.10155107861670155, 0.07414696042135518, 0.006469743677638605, 0.04658103375584029, -0.1503170793301538, 0.11434133031958794, 0.22450922358828354, 0.06033084524034332, 0.22803421400814555, -0.4299384163939611, -0.2102681045557329, 0.06359608710942102, 0.1297900404690975, 0.15311847386779898, -0.0006772009338716239, -0.26988776523192615, 0.0439968925707149, -0.2105755167896442, -0.16892846248289536, -0.11177528483708019, -0.007784503479955524, -0.008078266465101779, -0.2573621521010101, 0.10022446412647787, 0.06132499854707624, -0.0020739262578107656, -0.0914869561973345, -0.1076648676960719, 0.011366833718226535, 0.11317849847134269, 0.04156222301574948, 0.03982082377630203, 0.09481966481827814, -0.12966270998661075, -0.12284026410193667, 0.3696492058775758, -0.05078054283909152, -0.22499672241202692, 0.1269640474510129, -0.12726105075649996, -0.10887757220929722, 0.11587179698947964, 0.09653529583219451, 0.15435431884799075, -0.1875416170428073, 0.12507457207612138, 0.0013217331823228615, 0.11113321187899292, 0.00790596491904215, 0.025779145057930688, 0.19001463325955512, 0.1272640017405366, 0.029054236479811237, 0.1756428821236863, -0.0708037087899102, -0.17672984083254042, -0.3351073917702481, -0.16169692937018548, -0.20530261641984143, 0.07636487646625914, -0.09945619084642186, -0.19910936933978857, 0.4117953723970814, 0.16069162900536238, 0.14902910858010507, 0.044784738136852645, 0.2956701648091116, 0.18106801008098797, 0.046474066956843314, 0.0520440754776914, 0.22252784492022368, 0.17324487975211048, 0.06898512614275058, -0.26642900318079243, 0.00017137448620518477, 0.09280738388989321]
1,802.09153
PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence
This work explores the binarization of the deconvolution-based generator in a GAN for memory saving and speedup of image construction. Our study suggests that different from convolutional neural networks (including the discriminator) where all layers can be binarized, only some of the layers in the generator can be binarized without significant performance loss. Supported by theoretical analysis and verified by experiments, a direct metric based on the dimension of deconvolution operations is established, which can be used to quickly decide which layers in the generator can be binarized. Our results also indicate that both the generator and the discriminator should be binarized simultaneously for balanced competition and better performance. Experimental results based on CelebA suggest that directly applying state-of-the-art binarization techniques to all the layers of the generator will lead to 2.83$\times$ performance loss measured by sliced Wasserstein distance compared with the original generator, while applying them to selected layers only can yield up to 25.81$\times$ saving in memory consumption, and 1.96$\times$ and 1.32$\times$ speedup in inference and training respectively with little performance loss.
cs.CV
this work explores the binarization of the deconvolutionbased generator in a gan for memory saving and speedup of image construction our study suggests that different from convolutional neural networks including the discriminator where all layers can be binarized only some of the layers in the generator can be binarized without significant performance loss supported by theoretical analysis and verified by experiments a direct metric based on the dimension of deconvolution operations is established which can be used to quickly decide which layers in the generator can be binarized our results also indicate that both the generator and the discriminator should be binarized simultaneously for balanced competition and better performance experimental results based on celeba suggest that directly applying stateoftheart binarization techniques to all the layers of the generator will lead to 283times performance loss measured by sliced wasserstein distance compared with the original generator while applying them to selected layers only can yield up to 2581times saving in memory consumption and 196times and 132times speedup in inference and training respectively with little performance loss
[['this', 'work', 'explores', 'the', 'binarization', 'of', 'the', 'deconvolutionbased', 'generator', 'in', 'a', 'gan', 'for', 'memory', 'saving', 'and', 'speedup', 'of', 'image', 'construction', 'our', 'study', 'suggests', 'that', 'different', 'from', 'convolutional', 'neural', 'networks', 'including', 'the', 'discriminator', 'where', 'all', 'layers', 'can', 'be', 'binarized', 'only', 'some', 'of', 'the', 'layers', 'in', 'the', 'generator', 'can', 'be', 'binarized', 'without', 'significant', 'performance', 'loss', 'supported', 'by', 'theoretical', 'analysis', 'and', 'verified', 'by', 'experiments', 'a', 'direct', 'metric', 'based', 'on', 'the', 'dimension', 'of', 'deconvolution', 'operations', 'is', 'established', 'which', 'can', 'be', 'used', 'to', 'quickly', 'decide', 'which', 'layers', 'in', 'the', 'generator', 'can', 'be', 'binarized', 'our', 'results', 'also', 'indicate', 'that', 'both', 'the', 'generator', 'and', 'the', 'discriminator', 'should', 'be', 'binarized', 'simultaneously', 'for', 'balanced', 'competition', 'and', 'better', 'performance', 'experimental', 'results', 'based', 'on', 'celeba', 'suggest', 'that', 'directly', 'applying', 'stateoftheart', 'binarization', 'techniques', 'to', 'all', 'the', 'layers', 'of', 'the', 'generator', 'will', 'lead', 'to', '283times', 'performance', 'loss', 'measured', 'by', 'sliced', 'wasserstein', 'distance', 'compared', 'with', 'the', 'original', 'generator', 'while', 'applying', 'them', 'to', 'selected', 'layers', 'only', 'can', 'yield', 'up', 'to', '2581times', 'saving', 'in', 'memory', 'consumption', 'and', '196times', 'and', '132times', 'speedup', 'in', 'inference', 'and', 'training', 'respectively', 'with', 'little', 'performance', 'loss']]
[-0.022390112954829084, 0.014771975203803932, -0.05380621877068665, 0.049662969592544765, -0.06702828803780483, -0.15608103744337085, 0.03381067505977743, 0.4589681261987017, -0.2810779027831441, -0.3496023092353553, 0.09357380930113753, -0.2618427066491884, -0.16774079095768302, 0.23587933819392445, -0.12825478931714657, 0.09113570752591767, 0.17485168506527504, 0.018779285469947504, -0.10178068978303488, -0.32767760410716984, 0.27987638765493983, 0.1175419732448999, 0.3400037483481026, 0.03729424026947229, 0.10424964083630962, -0.06214628222382121, -0.007228979067495692, 0.017656871670454044, -0.019809993173835503, 0.14862842138377372, 0.2448855296174903, 0.13513606730222222, 0.2535580311008669, -0.45698041197631445, -0.22806996218598044, 0.06477295061878381, 0.11066512500987066, 0.07228701658702145, -0.043344443992096165, -0.30378832131057804, 0.15184844294610592, -0.16774229511716648, 0.058390356946126584, -0.138532714949402, -0.0676991945590105, 0.03155258143755024, -0.32385154094340074, 0.020371796388814922, 0.10156742465132249, 0.007710776660776539, -0.007174805291432735, -0.13860295686260823, -0.047438628868096404, 0.14708766985374191, 0.02340168935486404, 0.07422210625577065, 0.12238863369787646, -0.1301994077215919, -0.1633630749573441, 0.3109517049708823, -0.08609965674399414, -0.21666580548646794, 0.17533672753481838, -0.05103302345888918, -0.06588416667219404, 0.09702620370999764, 0.22496493394372233, 0.07633951429702472, -0.13998140725552252, -0.010565132144716029, 0.017321276926430085, 0.20936288327599564, 0.08022075121247411, 0.013563487044268708, 0.11968661872506664, 0.22279875330138157, 0.03013076680598029, 0.1765336134928491, -0.11100557585514412, -0.07218415748698322, -0.239298046533868, -0.15769760631864252, -0.21494399295025096, 0.020159674394461844, -0.12208504891368542, -0.09171583120471509, 0.41197065823324763, 0.2057402312744692, 0.2448141325676367, 0.09025139761176396, 0.333149048581458, 0.0724730658571628, 0.18095433744513403, 0.12467952206327815, 0.23215329163038576, 0.04310088101311516, 0.05935365038008936, -0.1849519518283686, 0.09722775073275405, 0.04954998965282538]
1,802.09154
A novel demonstration of the renormalization group invariance of the fixed-order predictions using the principle of maximum conformality and the $C$-scheme coupling
As a basic requirement of the renormalization group invariance, any physical observable must be independent of the choice of both the renormalization scheme and the initial renormalization scale. In this paper, we show that by using the newly suggested $C$-scheme coupling, one can obtain a demonstration that the {\it Principle of Maximum Conformality} prediction is scheme-independent to all-orders for any renormalization schemes, thus satisfying all of the conditions of the renormalization group invariance. We illustrate these features for the non-singlet Adler function and for $\tau $ decay to $\nu +$ hadrons at the four-loop level.
hep-ph
as a basic requirement of the renormalization group invariance any physical observable must be independent of the choice of both the renormalization scheme and the initial renormalization scale in this paper we show that by using the newly suggested cscheme coupling one can obtain a demonstration that the it principle of maximum conformality prediction is schemeindependent to allorders for any renormalization schemes thus satisfying all of the conditions of the renormalization group invariance we illustrate these features for the nonsinglet adler function and for tau decay to nu hadrons at the fourloop level
[['as', 'a', 'basic', 'requirement', 'of', 'the', 'renormalization', 'group', 'invariance', 'any', 'physical', 'observable', 'must', 'be', 'independent', 'of', 'the', 'choice', 'of', 'both', 'the', 'renormalization', 'scheme', 'and', 'the', 'initial', 'renormalization', 'scale', 'in', 'this', 'paper', 'we', 'show', 'that', 'by', 'using', 'the', 'newly', 'suggested', 'cscheme', 'coupling', 'one', 'can', 'obtain', 'a', 'demonstration', 'that', 'the', 'it', 'principle', 'of', 'maximum', 'conformality', 'prediction', 'is', 'schemeindependent', 'to', 'allorders', 'for', 'any', 'renormalization', 'schemes', 'thus', 'satisfying', 'all', 'of', 'the', 'conditions', 'of', 'the', 'renormalization', 'group', 'invariance', 'we', 'illustrate', 'these', 'features', 'for', 'the', 'nonsinglet', 'adler', 'function', 'and', 'for', 'tau', 'decay', 'to', 'nu', 'hadrons', 'at', 'the', 'fourloop', 'level']]
[-0.13693662913095567, 0.1555715355551451, -0.16404805070800726, 0.08209276009070617, -0.07263269538049816, -0.10892140761428383, 0.058814703367940924, 0.3291085628412103, -0.2549368214783489, -0.2609191985941061, 0.09226462956122373, -0.22089769057328662, -0.10294381518077145, 0.15268196217635627, 0.030190457650009665, 0.11340133856821766, 0.024977711064400533, 0.0378052752705351, -0.12533849719110676, -0.2168789618618546, 0.3787536762394412, 0.043725310336618174, 0.27889120162174263, 0.13716718677022327, 0.10491434872771303, 0.008097450213847302, -0.039637467669953984, -0.015420359549342944, -0.11522344083813775, 0.05943082540511324, 0.21992762553785997, 0.06450318742187641, 0.23448477947824103, -0.3184295612517544, -0.19512422955394673, 0.06072421076517272, 0.13635035488449077, 0.12405633434286512, -0.011109027821290236, -0.28072754734305927, 0.1293770916639797, -0.18210318040413162, -0.16979238785983575, -0.13928695080140907, -0.033369080468972204, -0.047394993434590034, -0.3300335655810051, 0.06097047022914374, -0.037160090721582856, 0.028371474144840113, -0.004913633781915871, -0.08548424208676943, -0.017102116879115822, 0.13968184861725055, 0.12373297807500167, 0.03954848432969753, 0.10410212239460839, -0.1446240713534456, -0.11470858534918196, 0.423693724016669, -0.0826090582075619, -0.1948147052398292, 0.12755234904026472, -0.15445119157178147, -0.20939652066958206, 0.07185485017215533, 0.09173682139265121, 0.09008231488311844, -0.16778612284550584, 0.13266382349895373, -0.06254370792415895, 0.13716377028494434, 0.0525336749163226, 0.05296364209804964, 0.09408835844407158, 0.10691699646763823, 0.05092856424650358, 0.04258071654100692, -0.022154473264010682, -0.044676783321906, -0.4599378617300141, -0.17088539053195267, -0.16925738107598318, 0.0908218614396549, -0.1493588992934649, -0.11744052258830878, 0.4124553793709477, 0.15851910851435155, 0.19137210661285026, 0.09184503162740379, 0.2661924073372477, 0.1644082709894045, 0.1277624580668666, 0.07764485058304603, 0.22621844179667933, 0.12147368827674498, 0.008545192028646188, -0.30749356685586837, 0.02215517277739221, 0.16790389280606022]
1,802.09155
Generalised teleparallel quintom dark energy non-minimally coupled with the scalar torsion and a boundary term
Within this work, we propose a new generalised quintom dark energy model in the teleparallel alternative of general relativity theory, by considering a non-minimal coupling between the scalar fields of a quintom model with the scalar torsion component $T$ and the boundary term $B$. In the teleparallel alternative of general relativity theory, the boundary term represents the divergence of the torsion vector, $B=2\nabla_{\mu}T^{\mu}$, and is related to the Ricci scalar $R$ and the torsion scalar $T$, by the fundamental relation: $R=-T+B$. We have investigated the dynamical properties of the present quintom scenario in the teleparallel alternative of general relativity theory by performing a dynamical system analysis in the case of decomposable exponential potentials. The study analysed the structure of the phase space, revealing the fundamental dynamical effects of the scalar torsion and boundary couplings in the case of a more general quintom scenario. Additionally, a numerical approach to the model is presented to analyse the cosmological evolution of the system.
gr-qc astro-ph.CO
within this work we propose a new generalised quintom dark energy model in the teleparallel alternative of general relativity theory by considering a nonminimal coupling between the scalar fields of a quintom model with the scalar torsion component t and the boundary term b in the teleparallel alternative of general relativity theory the boundary term represents the divergence of the torsion vector b2nabla_mutmu and is related to the ricci scalar r and the torsion scalar t by the fundamental relation rtb we have investigated the dynamical properties of the present quintom scenario in the teleparallel alternative of general relativity theory by performing a dynamical system analysis in the case of decomposable exponential potentials the study analysed the structure of the phase space revealing the fundamental dynamical effects of the scalar torsion and boundary couplings in the case of a more general quintom scenario additionally a numerical approach to the model is presented to analyse the cosmological evolution of the system
[['within', 'this', 'work', 'we', 'propose', 'a', 'new', 'generalised', 'quintom', 'dark', 'energy', 'model', 'in', 'the', 'teleparallel', 'alternative', 'of', 'general', 'relativity', 'theory', 'by', 'considering', 'a', 'nonminimal', 'coupling', 'between', 'the', 'scalar', 'fields', 'of', 'a', 'quintom', 'model', 'with', 'the', 'scalar', 'torsion', 'component', 't', 'and', 'the', 'boundary', 'term', 'b', 'in', 'the', 'teleparallel', 'alternative', 'of', 'general', 'relativity', 'theory', 'the', 'boundary', 'term', 'represents', 'the', 'divergence', 'of', 'the', 'torsion', 'vector', 'b2nabla_mutmu', 'and', 'is', 'related', 'to', 'the', 'ricci', 'scalar', 'r', 'and', 'the', 'torsion', 'scalar', 't', 'by', 'the', 'fundamental', 'relation', 'rtb', 'we', 'have', 'investigated', 'the', 'dynamical', 'properties', 'of', 'the', 'present', 'quintom', 'scenario', 'in', 'the', 'teleparallel', 'alternative', 'of', 'general', 'relativity', 'theory', 'by', 'performing', 'a', 'dynamical', 'system', 'analysis', 'in', 'the', 'case', 'of', 'decomposable', 'exponential', 'potentials', 'the', 'study', 'analysed', 'the', 'structure', 'of', 'the', 'phase', 'space', 'revealing', 'the', 'fundamental', 'dynamical', 'effects', 'of', 'the', 'scalar', 'torsion', 'and', 'boundary', 'couplings', 'in', 'the', 'case', 'of', 'a', 'more', 'general', 'quintom', 'scenario', 'additionally', 'a', 'numerical', 'approach', 'to', 'the', 'model', 'is', 'presented', 'to', 'analyse', 'the', 'cosmological', 'evolution', 'of', 'the', 'system']]
[-0.215134880234109, 0.10757323130237637, -0.11950530793692452, 0.10499368191885879, -0.12331318439682945, -0.18162647626522813, -0.047385993667558066, 0.2616136486787582, -0.24713142860273365, -0.2768126930925064, 0.013660951332713011, -0.21979473939281888, -0.1694616679858882, 0.09584688784816535, -0.0028109829829190856, 0.027064018597593532, -0.0066874006704892965, 0.08018302795535419, -0.0650249162768887, -0.23146010448544985, 0.3933810760994675, 0.07393437169957906, 0.21110394264687785, 0.011763589663314634, 0.08500138550880365, -0.018046599750232418, -0.021082726150052623, 0.01589095290091791, -0.1835111656342633, 0.09744643754602293, 0.1660238319542259, 0.08823218969046139, 0.23453215582703707, -0.37991858867462724, -0.2998792574275285, 0.11940625024726614, 0.07198851578868926, 0.10304461628838908, -0.049984889450297484, -0.29017520864435936, 0.04497673854057212, -0.20925530293607153, -0.14498975297283323, -0.04954055064008571, -0.00625921361206565, -0.07901999360328774, -0.24672902535421598, 0.13550375307386275, 0.030648729223503323, 0.028844034738722258, -0.11752386781590758, -0.04605018462971202, -0.017372544571117032, 0.007192819920601323, 0.13673220166310784, 0.021559054452518468, 0.08257535704178735, -0.16395968043216272, -0.08634322247744422, 0.4178233647486195, -0.1521277390747855, -0.24274119750625686, 0.13125251534147536, -0.11890305889246519, -0.13742226718459277, 0.012468011878081598, 0.1346732130390592, 0.1733178395195864, -0.1654252045078465, 0.21776126130862394, -0.011936779876850778, 0.10200723426241894, 0.04196043404081138, -0.013047105284931604, 0.24665734570007772, 0.14009025221457705, 0.016738975430780557, 0.14711316359462218, -0.00471276802563807, -0.16182431986089796, -0.4150462925201282, -0.19135567778139376, -0.10702173124154797, 0.05555976758842007, -0.16365426719094103, -0.16362821428338065, 0.43902542019204704, 0.09833332187845371, 0.12437793200806482, 0.05187201370717957, 0.2780741143389605, 0.09041181802022039, 0.026362723428246682, 0.03662063495662551, 0.2923112402262632, 0.20404370426404056, 0.12974684198125033, -0.2513210846635047, -0.04787057100620586, 0.0726946120877983]
1,802.09156
Twisted states in low-dimensional hypercubic lattices
Twisted states with non-zero winding numbers composed of sinusoidally coupled identical oscillators have been observed in a ring. The phase of each oscillator in these states constantly shifts, following its preceding neighbor in a clockwise direction, and the summation of such phase shifts around the ring over $2\pi$ characterizes the winding number of each state. In this work, we consider finite-sized $d$-dimensional hypercubic lattices, namely square ($d=2$) and cubic ($d=3$) lattices with periodic boundary conditions. For identical oscillators, we observe new states in which the oscillators belonging to each line (plane) for $d=2$ ($d=3$) are phase synchronized with non-zero winding numbers along the perpendicular direction. These states can be reduced into twisted states in a ring with the same winding number if we regard each subset of phase-synchronized oscillators as one single oscillator. For nonidentical oscillators with heterogeneous natural frequencies, we observe similar patterns with slightly heterogeneous phases in each line $(d=2)$ and plane $(d=3)$. We show that these states generally appear for random configurations when the global coupling strength is larger than the critical values for the states.
nlin.AO
twisted states with nonzero winding numbers composed of sinusoidally coupled identical oscillators have been observed in a ring the phase of each oscillator in these states constantly shifts following its preceding neighbor in a clockwise direction and the summation of such phase shifts around the ring over 2pi characterizes the winding number of each state in this work we consider finitesized ddimensional hypercubic lattices namely square d2 and cubic d3 lattices with periodic boundary conditions for identical oscillators we observe new states in which the oscillators belonging to each line plane for d2 d3 are phase synchronized with nonzero winding numbers along the perpendicular direction these states can be reduced into twisted states in a ring with the same winding number if we regard each subset of phasesynchronized oscillators as one single oscillator for nonidentical oscillators with heterogeneous natural frequencies we observe similar patterns with slightly heterogeneous phases in each line d2 and plane d3 we show that these states generally appear for random configurations when the global coupling strength is larger than the critical values for the states
[['twisted', 'states', 'with', 'nonzero', 'winding', 'numbers', 'composed', 'of', 'sinusoidally', 'coupled', 'identical', 'oscillators', 'have', 'been', 'observed', 'in', 'a', 'ring', 'the', 'phase', 'of', 'each', 'oscillator', 'in', 'these', 'states', 'constantly', 'shifts', 'following', 'its', 'preceding', 'neighbor', 'in', 'a', 'clockwise', 'direction', 'and', 'the', 'summation', 'of', 'such', 'phase', 'shifts', 'around', 'the', 'ring', 'over', '2pi', 'characterizes', 'the', 'winding', 'number', 'of', 'each', 'state', 'in', 'this', 'work', 'we', 'consider', 'finitesized', 'ddimensional', 'hypercubic', 'lattices', 'namely', 'square', 'd2', 'and', 'cubic', 'd3', 'lattices', 'with', 'periodic', 'boundary', 'conditions', 'for', 'identical', 'oscillators', 'we', 'observe', 'new', 'states', 'in', 'which', 'the', 'oscillators', 'belonging', 'to', 'each', 'line', 'plane', 'for', 'd2', 'd3', 'are', 'phase', 'synchronized', 'with', 'nonzero', 'winding', 'numbers', 'along', 'the', 'perpendicular', 'direction', 'these', 'states', 'can', 'be', 'reduced', 'into', 'twisted', 'states', 'in', 'a', 'ring', 'with', 'the', 'same', 'winding', 'number', 'if', 'we', 'regard', 'each', 'subset', 'of', 'phasesynchronized', 'oscillators', 'as', 'one', 'single', 'oscillator', 'for', 'nonidentical', 'oscillators', 'with', 'heterogeneous', 'natural', 'frequencies', 'we', 'observe', 'similar', 'patterns', 'with', 'slightly', 'heterogeneous', 'phases', 'in', 'each', 'line', 'd2', 'and', 'plane', 'd3', 'we', 'show', 'that', 'these', 'states', 'generally', 'appear', 'for', 'random', 'configurations', 'when', 'the', 'global', 'coupling', 'strength', 'is', 'larger', 'than', 'the', 'critical', 'values', 'for', 'the', 'states']]
[-0.24357075232221595, 0.27752758810223815, 0.01182696137020583, -0.03337904063701193, 0.0002267755861992443, -0.21407731895610774, 0.020953940936525525, 0.3909049286850463, -0.21809593986917558, -0.21256120396809206, 0.04487447470345914, -0.28201983471572734, -0.1340187444174714, 0.1342458487202169, -0.005348935673877014, 0.009209923786075406, 0.032318281605527556, 0.08007911135385323, -0.0490499544776872, -0.2256903816651886, 0.30487393689804904, -0.0715334202896533, 0.284563890383865, -0.06170142667144329, 0.03567383734264812, -0.004641366868888616, 0.0866505055787177, 0.04042097702934589, -0.12536826628207798, 0.0502164446005426, 0.19898087040562829, -0.035444880171039, 0.18819580107469466, -0.43802919909982374, -0.1773025051966393, 0.14458062815838935, 0.1844869467284135, 0.14161367995297672, 0.02445634999657154, -0.2862467679075439, 0.03453762848359434, -0.12764789135450258, -0.19492799804322214, -0.035651667540445506, 0.07525333135737387, 0.0714648067066706, -0.2491454793525308, 0.04238306177655162, 0.024538992822180663, 0.08893426873476645, -0.057032219899750665, -0.11043966399745068, -0.07178424408544874, 0.12386135775521112, -0.022759841915672676, 0.02409308814240734, 0.07600631237071653, -0.08931491196977609, -0.12664826263481097, 0.35810976853274207, -0.06657458975930326, -0.23042976873401325, 0.1699494835972661, -0.19853242057352521, -0.1434991133513772, 0.1504126830018703, 0.11146050906355114, 0.09696638776905127, -0.041628929668424165, 0.041658567193461137, -0.051358664107207186, 0.1747399902481107, 0.1312598179708438, 0.04840653342215667, 0.2429160515471445, 0.07348059191025128, 0.10473486729009811, 0.2146038189784015, -0.07224366182946554, -0.15933515371718346, -0.2797387653764067, -0.11584160791309395, -0.19610847966282435, 0.04879366791827927, -0.11248306540992467, -0.16760762453120848, 0.42154807516233217, 0.07443074084357905, 0.2416524543744309, 0.008243256396166564, 0.22637216704923596, 0.11853596857324888, 0.06857746143112552, 0.075423828079027, 0.20618899362343857, 0.14719793180591692, 0.06922472764376301, -0.21420723101639255, -0.03967100622778883, 0.07485888513356613]
1,802.09157
Wigner-Type Theorem on transition probability preserving maps in semifinite factors
The Wigner's theorem, which is one of the cornerstones of the mathematical formulation of quantum mechanics, asserts that every symmetry of quantum system is unitary or anti-unitary. This classical result was first given by Wigner in 1931. Thereafter it has been proved and generalized in various ways by many authors. Recently, G. P. Geh\'{e}r extended Wigner's and Moln\'{a}r's theorems and characterized the transformations on the Grassmann space of all rank-$n$ projections which preserve the transition probability. The aim of this paper is to provide a new approach to describe the general form of the transition probability preserving (not necessarily bijective) maps between Grassmann spaces. As a byproduct, we are able to generalize the results of Moln\'{a}r and G. P. Geh\'{e}r.
math.OA
the wigners theorem which is one of the cornerstones of the mathematical formulation of quantum mechanics asserts that every symmetry of quantum system is unitary or antiunitary this classical result was first given by wigner in 1931 thereafter it has been proved and generalized in various ways by many authors recently g p geher extended wigners and molnars theorems and characterized the transformations on the grassmann space of all rankn projections which preserve the transition probability the aim of this paper is to provide a new approach to describe the general form of the transition probability preserving not necessarily bijective maps between grassmann spaces as a byproduct we are able to generalize the results of molnar and g p geher
[['the', 'wigners', 'theorem', 'which', 'is', 'one', 'of', 'the', 'cornerstones', 'of', 'the', 'mathematical', 'formulation', 'of', 'quantum', 'mechanics', 'asserts', 'that', 'every', 'symmetry', 'of', 'quantum', 'system', 'is', 'unitary', 'or', 'antiunitary', 'this', 'classical', 'result', 'was', 'first', 'given', 'by', 'wigner', 'in', '1931', 'thereafter', 'it', 'has', 'been', 'proved', 'and', 'generalized', 'in', 'various', 'ways', 'by', 'many', 'authors', 'recently', 'g', 'p', 'geher', 'extended', 'wigners', 'and', 'molnars', 'theorems', 'and', 'characterized', 'the', 'transformations', 'on', 'the', 'grassmann', 'space', 'of', 'all', 'rankn', 'projections', 'which', 'preserve', 'the', 'transition', 'probability', 'the', 'aim', 'of', 'this', 'paper', 'is', 'to', 'provide', 'a', 'new', 'approach', 'to', 'describe', 'the', 'general', 'form', 'of', 'the', 'transition', 'probability', 'preserving', 'not', 'necessarily', 'bijective', 'maps', 'between', 'grassmann', 'spaces', 'as', 'a', 'byproduct', 'we', 'are', 'able', 'to', 'generalize', 'the', 'results', 'of', 'molnar', 'and', 'g', 'p', 'geher']]
[-0.08537285981389384, 0.12137752854808544, -0.13944464413604388, 0.056303222843174204, -0.05380424750716581, -0.13478522361256182, 0.02231887397065293, 0.31034114400390533, -0.2616293950006366, -0.258911394343401, 0.06649394356936682, -0.248121350518583, -0.20803159096006615, 0.1605120056599844, -0.1338474430454274, 0.06911948294534037, 0.0005579793990667289, 0.07938624681385893, -0.11678210277847635, -0.26639382108987775, 0.34642495738225987, -0.0034545069085046027, 0.25778221019233266, 0.03987117483629845, 0.11727513574102583, 0.03949174604495056, -0.028365695903388163, -0.018589319290913408, -0.12004673731892884, 0.10669232728347804, 0.2644618956488557, 0.14793166611925698, 0.25355371039671204, -0.3672013249808515, -0.18599178503500297, 0.14357389516662805, 0.09919329498079606, 0.08942122346682785, -0.007993918381786595, -0.3293621766846627, 0.07395519718217353, -0.16178395153256134, -0.15222235911448176, -0.08811818475854429, 0.05462152994393061, -0.0339339634073743, -0.21299534067123507, 0.049894998808546615, 0.1749277738854289, 0.05602035119663924, -0.010957542426573734, -0.07509473902755417, -0.02467362230430202, 0.11486259066538575, 0.005162708959930266, 0.06391621202540894, 0.047790542158084766, -0.03169427071309959, -0.1482290336008494, 0.40553381415084006, 0.0033608323896866447, -0.20109978209172066, 0.14385359345857676, -0.1540400768145143, -0.19928749833876888, 0.08408537343154118, 0.08277799872836719, 0.12096006924984977, -0.12175047103276787, 0.1550994229367158, -0.11837611513522764, 0.08753376704019805, 0.1040736508652723, 0.02259424717000608, 0.14279822545940987, 0.06382188253725568, 0.07861056735612995, 0.13047734705614858, 0.008534006636667375, -0.10267506857780972, -0.3312488953893383, -0.1979446657690763, -0.21714778940950055, 0.09681969015715973, -0.04408053609804483, -0.1309553012251854, 0.3689896037666282, 0.08919310537700463, 0.17732035839774957, 0.062470293081908795, 0.20894316890044137, 0.13074928227094157, 0.03522290200926363, 0.054086602258030324, 0.1828243088326417, 0.24242452374504259, 0.04835018748805548, -0.12994581015082077, 0.019227214766821512, 0.1614464615820907]
1,802.09158
Surrogate Scoring Rules
Strictly proper scoring rules (SPSR) are incentive compatible for eliciting information about random variables from strategic agents when the principal can reward agents after the realization of the random variables. They also quantify the quality of elicited information, with more accurate predictions receiving higher scores in expectation. In this paper, we extend such scoring rules to settings where a principal elicits private probabilistic beliefs but only has access to agents' reports. We name our solution \emph{Surrogate Scoring Rules} (SSR). SSR build on a bias correction step and an error rate estimation procedure for a reference answer defined using agents' reports. We show that, with a single bit of information about the prior distribution of the random variables, SSR in a multi-task setting recover SPSR in expectation, as if having access to the ground truth. Therefore, a salient feature of SSR is that they quantify the quality of information despite the lack of ground truth, just as SPSR do for the setting \emph{with} ground truth. As a by-product, SSR induce \emph{dominant truthfulness} in reporting. Our method is verified both theoretically and empirically using data collected from real human forecasters.
cs.GT cs.AI
strictly proper scoring rules spsr are incentive compatible for eliciting information about random variables from strategic agents when the principal can reward agents after the realization of the random variables they also quantify the quality of elicited information with more accurate predictions receiving higher scores in expectation in this paper we extend such scoring rules to settings where a principal elicits private probabilistic beliefs but only has access to agents reports we name our solution emphsurrogate scoring rules ssr ssr build on a bias correction step and an error rate estimation procedure for a reference answer defined using agents reports we show that with a single bit of information about the prior distribution of the random variables ssr in a multitask setting recover spsr in expectation as if having access to the ground truth therefore a salient feature of ssr is that they quantify the quality of information despite the lack of ground truth just as spsr do for the setting emphwith ground truth as a byproduct ssr induce emphdominant truthfulness in reporting our method is verified both theoretically and empirically using data collected from real human forecasters
[['strictly', 'proper', 'scoring', 'rules', 'spsr', 'are', 'incentive', 'compatible', 'for', 'eliciting', 'information', 'about', 'random', 'variables', 'from', 'strategic', 'agents', 'when', 'the', 'principal', 'can', 'reward', 'agents', 'after', 'the', 'realization', 'of', 'the', 'random', 'variables', 'they', 'also', 'quantify', 'the', 'quality', 'of', 'elicited', 'information', 'with', 'more', 'accurate', 'predictions', 'receiving', 'higher', 'scores', 'in', 'expectation', 'in', 'this', 'paper', 'we', 'extend', 'such', 'scoring', 'rules', 'to', 'settings', 'where', 'a', 'principal', 'elicits', 'private', 'probabilistic', 'beliefs', 'but', 'only', 'has', 'access', 'to', 'agents', 'reports', 'we', 'name', 'our', 'solution', 'emphsurrogate', 'scoring', 'rules', 'ssr', 'ssr', 'build', 'on', 'a', 'bias', 'correction', 'step', 'and', 'an', 'error', 'rate', 'estimation', 'procedure', 'for', 'a', 'reference', 'answer', 'defined', 'using', 'agents', 'reports', 'we', 'show', 'that', 'with', 'a', 'single', 'bit', 'of', 'information', 'about', 'the', 'prior', 'distribution', 'of', 'the', 'random', 'variables', 'ssr', 'in', 'a', 'multitask', 'setting', 'recover', 'spsr', 'in', 'expectation', 'as', 'if', 'having', 'access', 'to', 'the', 'ground', 'truth', 'therefore', 'a', 'salient', 'feature', 'of', 'ssr', 'is', 'that', 'they', 'quantify', 'the', 'quality', 'of', 'information', 'despite', 'the', 'lack', 'of', 'ground', 'truth', 'just', 'as', 'spsr', 'do', 'for', 'the', 'setting', 'emphwith', 'ground', 'truth', 'as', 'a', 'byproduct', 'ssr', 'induce', 'emphdominant', 'truthfulness', 'in', 'reporting', 'our', 'method', 'is', 'verified', 'both', 'theoretically', 'and', 'empirically', 'using', 'data', 'collected', 'from', 'real', 'human', 'forecasters']]
[-0.06786741111715454, 0.032098946585373135, -0.08850048781843275, 0.08564653207537948, -0.13187142515364753, -0.1666820762711527, 0.16451085448798333, 0.4414394948711639, -0.24815800683998493, -0.29677384245579924, 0.08847420669588892, -0.2700036805716433, -0.1445168760449936, 0.12813458385719587, -0.15250725912741356, 0.05996561015240087, 0.08694415204026686, 0.11098886814759544, -0.025892402972995995, -0.28589516788000063, 0.2857181107204768, 0.052145176975216756, 0.31343645598458986, -0.03083853575811591, 0.13184674583708428, 0.058663018225562025, -0.03729146202370244, 0.025900976754905235, -0.0809076402755861, 0.12972340193046358, 0.3163472950253235, 0.2220182071805441, 0.3637999332039267, -0.38207122226375884, -0.16098200028101284, 0.1289422156023843, 0.08792764276656653, 0.1258748069140179, 0.010633995326130114, -0.32377945077956044, 0.06719728319164646, -0.16300677719916548, -0.03533536535237105, -0.13081349770072848, -0.032043141688430504, 0.004196129520692843, -0.3648628251187714, 0.051245384980888126, 0.06123526822975887, 0.08457764892548483, -0.0749296506538847, -0.13947574405239954, -0.008603667692651832, 0.17481283903868633, 0.051926704898031396, 0.018804417178911025, 0.14913964151312167, -0.16769566517623682, -0.19575163990419397, 0.3538840219919239, -0.01451744614369286, -0.21904611120861706, 0.10837092813134434, -0.10049613259897958, -0.12944052834689657, 0.10842928696944508, 0.16490692507615815, 0.08794426819640061, -0.16478894945518527, -0.013300534941741736, -0.08018966200160643, 0.21120362051872796, 0.05930202976069463, 0.04811179000096926, 0.16985347846232515, 0.14821915749976192, 0.07197577748272407, 0.09041461365307452, -0.032746770936164564, -0.11533668148268755, -0.26992581784412245, -0.13574667128141887, -0.21551529373422826, 0.049777000569735316, -0.08574495825310043, -0.1598725822480065, 0.33416021253753414, 0.21399890226862764, 0.19103702652735652, 0.12440436584774846, 0.329033572326905, 0.053475046246838305, 0.04013518172176054, 0.06605956267117352, 0.19564434069976142, 0.03845489328171337, 0.06864211017075646, -0.1326101813915997, 0.19675841600251115, -0.00271446390768453]
1,802.09159
Antifragility for Intelligent Autonomous Systems
Antifragile systems grow measurably better in the presence of hazards. This is in contrast to fragile systems which break down in the presence of hazards, robust systems that tolerate hazards up to a certain degree, and resilient systems that -- like self-healing systems -- revert to their earlier expected behavior after a period of convalescence. The notion of antifragility was introduced by Taleb for economics systems, but its applicability has been illustrated in biological and engineering domains as well. In this paper, we propose an architecture that imparts antifragility to intelligent autonomous systems, specifically those that are goal-driven and based on AI-planning. We argue that this architecture allows the system to self-improve by uncovering new capabilities obtained either through the hazards themselves (opportunistic) or through deliberation (strategic). An AI planning-based case study of an autonomous wheeled robot is presented. We show that with the proposed architecture, the robot develops antifragile behaviour with respect to an oil spill hazard.
cs.AI
antifragile systems grow measurably better in the presence of hazards this is in contrast to fragile systems which break down in the presence of hazards robust systems that tolerate hazards up to a certain degree and resilient systems that like selfhealing systems revert to their earlier expected behavior after a period of convalescence the notion of antifragility was introduced by taleb for economics systems but its applicability has been illustrated in biological and engineering domains as well in this paper we propose an architecture that imparts antifragility to intelligent autonomous systems specifically those that are goaldriven and based on aiplanning we argue that this architecture allows the system to selfimprove by uncovering new capabilities obtained either through the hazards themselves opportunistic or through deliberation strategic an ai planningbased case study of an autonomous wheeled robot is presented we show that with the proposed architecture the robot develops antifragile behaviour with respect to an oil spill hazard
[['antifragile', 'systems', 'grow', 'measurably', 'better', 'in', 'the', 'presence', 'of', 'hazards', 'this', 'is', 'in', 'contrast', 'to', 'fragile', 'systems', 'which', 'break', 'down', 'in', 'the', 'presence', 'of', 'hazards', 'robust', 'systems', 'that', 'tolerate', 'hazards', 'up', 'to', 'a', 'certain', 'degree', 'and', 'resilient', 'systems', 'that', 'like', 'selfhealing', 'systems', 'revert', 'to', 'their', 'earlier', 'expected', 'behavior', 'after', 'a', 'period', 'of', 'convalescence', 'the', 'notion', 'of', 'antifragility', 'was', 'introduced', 'by', 'taleb', 'for', 'economics', 'systems', 'but', 'its', 'applicability', 'has', 'been', 'illustrated', 'in', 'biological', 'and', 'engineering', 'domains', 'as', 'well', 'in', 'this', 'paper', 'we', 'propose', 'an', 'architecture', 'that', 'imparts', 'antifragility', 'to', 'intelligent', 'autonomous', 'systems', 'specifically', 'those', 'that', 'are', 'goaldriven', 'and', 'based', 'on', 'aiplanning', 'we', 'argue', 'that', 'this', 'architecture', 'allows', 'the', 'system', 'to', 'selfimprove', 'by', 'uncovering', 'new', 'capabilities', 'obtained', 'either', 'through', 'the', 'hazards', 'themselves', 'opportunistic', 'or', 'through', 'deliberation', 'strategic', 'an', 'ai', 'planningbased', 'case', 'study', 'of', 'an', 'autonomous', 'wheeled', 'robot', 'is', 'presented', 'we', 'show', 'that', 'with', 'the', 'proposed', 'architecture', 'the', 'robot', 'develops', 'antifragile', 'behaviour', 'with', 'respect', 'to', 'an', 'oil', 'spill', 'hazard']]
[-0.14115531612701665, 0.08867689985033524, -0.07811373709277673, 0.025027715170895075, -0.06375555311898132, -0.15666601950508335, 0.01437435716212207, 0.3780958329194358, -0.2555558314462277, -0.2984688498866714, 0.12185851424288416, -0.25622223653422754, -0.25092880306432824, 0.1866877852325243, -0.1745086207369028, 0.05622651081573061, 0.022356387050882852, 0.009014249469347105, 0.005537434854520509, -0.25850313916415363, 0.30350936411021207, 0.08186243765370606, 0.28292842951524616, 0.010318241012585046, 0.0876432687146952, 0.0199579830703253, 0.05028165985626779, 0.006116851700119093, -0.059746813018373125, 0.12666736373847182, 0.2699360939214466, 0.150481059214451, 0.31799680400978436, -0.4388673108724224, -0.23304151465463174, 0.11131565084729295, 0.12506129966093252, 0.05883049413292705, -0.019871591058916522, -0.31775475802450354, 0.0893383340293227, -0.24134627257274577, -0.16140123763932035, -0.10743903807007599, 0.023679066225644443, 0.029629146966738504, -0.23922164211512315, 0.009877711786229357, 0.09344588286718111, 0.0954394837593442, -0.04428386869999072, -0.05931255918271332, 0.004030906471314949, 0.12165895825276127, 0.06059921716563645, -0.006054965009634661, 0.1697890759844865, -0.13311151761180637, -0.15411301444408593, 0.38718322189766674, -0.003902923656694059, -0.17581716569007508, 0.2597306881858907, -0.06086212443792588, -0.130693548531332, 0.09190923790447414, 0.22304409699720124, 0.07374212111485517, -0.18507518645908153, 0.01304573513145631, 0.02555807045201299, 0.17030009351876357, 0.013431860946644968, -0.008911621448426665, 0.1851599836229141, 0.22347488895348913, 0.11386470104773323, 0.1450172149789423, -0.02824219475672641, -0.11800590725524908, -0.20087820573939713, -0.15167583211917768, -0.11252639038025632, 0.003926218890996239, -0.002244323842524545, -0.1489146788613629, 0.3418571582946975, 0.22517526612992023, 0.16229503121916447, 0.08469824149354978, 0.3062129767155033, 0.07739667976562345, 0.08964645720773766, 0.06502106474476636, 0.21332716882567515, 0.01807180091182326, 0.15329604970545255, -0.20660356545893402, 0.13034949198292642, -0.031146838163424815]