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1,802.0636 | Anomaly Detection using One-Class Neural Networks | We propose a one-class neural network (OC-NN) model to detect anomalies in
complex data sets. OC-NN combines the ability of deep networks to extract a
progressively rich representation of data with the one-class objective of
creating a tight envelope around normal data. The OC-NN approach breaks new
ground for the following crucial reason: data representation in the hidden
layer is driven by the OC-NN objective and is thus customized for anomaly
detection. This is a departure from other approaches which use a hybrid
approach of learning deep features using an autoencoder and then feeding the
features into a separate anomaly detection method like one-class SVM (OC-SVM).
The hybrid OC-SVM approach is sub-optimal because it is unable to influence
representational learning in the hidden layers. A comprehensive set of
experiments demonstrate that on complex data sets (like CIFAR and GTSRB), OC-NN
performs on par with state-of-the-art methods and outperformed conventional
shallow methods in some scenarios.
| cs.LG cs.NE stat.ML | we propose a oneclass neural network ocnn model to detect anomalies in complex data sets ocnn combines the ability of deep networks to extract a progressively rich representation of data with the oneclass objective of creating a tight envelope around normal data the ocnn approach breaks new ground for the following crucial reason data representation in the hidden layer is driven by the ocnn objective and is thus customized for anomaly detection this is a departure from other approaches which use a hybrid approach of learning deep features using an autoencoder and then feeding the features into a separate anomaly detection method like oneclass svm ocsvm the hybrid ocsvm approach is suboptimal because it is unable to influence representational learning in the hidden layers a comprehensive set of experiments demonstrate that on complex data sets like cifar and gtsrb ocnn performs on par with stateoftheart methods and outperformed conventional shallow methods in some scenarios | [['we', 'propose', 'a', 'oneclass', 'neural', 'network', 'ocnn', 'model', 'to', 'detect', 'anomalies', 'in', 'complex', 'data', 'sets', 'ocnn', 'combines', 'the', 'ability', 'of', 'deep', 'networks', 'to', 'extract', 'a', 'progressively', 'rich', 'representation', 'of', 'data', 'with', 'the', 'oneclass', 'objective', 'of', 'creating', 'a', 'tight', 'envelope', 'around', 'normal', 'data', 'the', 'ocnn', 'approach', 'breaks', 'new', 'ground', 'for', 'the', 'following', 'crucial', 'reason', 'data', 'representation', 'in', 'the', 'hidden', 'layer', 'is', 'driven', 'by', 'the', 'ocnn', 'objective', 'and', 'is', 'thus', 'customized', 'for', 'anomaly', 'detection', 'this', 'is', 'a', 'departure', 'from', 'other', 'approaches', 'which', 'use', 'a', 'hybrid', 'approach', 'of', 'learning', 'deep', 'features', 'using', 'an', 'autoencoder', 'and', 'then', 'feeding', 'the', 'features', 'into', 'a', 'separate', 'anomaly', 'detection', 'method', 'like', 'oneclass', 'svm', 'ocsvm', 'the', 'hybrid', 'ocsvm', 'approach', 'is', 'suboptimal', 'because', 'it', 'is', 'unable', 'to', 'influence', 'representational', 'learning', 'in', 'the', 'hidden', 'layers', 'a', 'comprehensive', 'set', 'of', 'experiments', 'demonstrate', 'that', 'on', 'complex', 'data', 'sets', 'like', 'cifar', 'and', 'gtsrb', 'ocnn', 'performs', 'on', 'par', 'with', 'stateoftheart', 'methods', 'and', 'outperformed', 'conventional', 'shallow', 'methods', 'in', 'some', 'scenarios']] | [-0.029434442797005963, -0.019769788141322304, -0.10406230695397509, 0.0815283161631102, -0.14268990568877138, -0.19249215837289857, 0.06299442225801093, 0.4007190616753001, -0.2758577674470068, -0.2984567617320202, 0.06894704069059293, -0.31354171617029164, -0.21382729263141653, 0.17678236462895505, -0.07750232652881993, 0.07549360118407224, 0.11691227448838097, 0.058539104012941774, -0.08110247554435915, -0.2364884344195681, 0.33260947327861295, 0.034426653995813634, 0.3881824962528689, -0.014120326247429113, 0.13233652399390233, -0.03993357726759821, -0.012781132789715738, -0.013871987592942964, 0.0033175990802546593, 0.1794945668767799, 0.2740071201016643, 0.21989463984001695, 0.30672373251941104, -0.4154641879480574, -0.2532814834387852, 0.08651491737162526, 0.12760810937744554, 0.08669467551509741, -0.02834853481096155, -0.3293256839471204, 0.0905385168493036, -0.14654770233916337, -0.013874229522990425, -0.1863138188846869, -0.06948500665663682, -0.038368703590331045, -0.30301590826605784, 0.042730472245640666, 0.07896917080922451, 0.04178669674823956, -0.07982518387559269, -0.11058584393558467, 0.024229563090817204, 0.09109088330372393, -0.004584239701311068, 0.0862923746024464, 0.11706280924569568, -0.1822037993062457, -0.1350646128533287, 0.34945010270487953, -0.12197354027711145, -0.19927859811570386, 0.2437545446158907, 0.008591740751977672, -0.1772761232697393, 0.11160100695326344, 0.23935499764047563, 0.1199273180871198, -0.14954051437981233, -0.0027468756140608874, -0.047176468075712685, 0.17497716099326197, -0.006858819347274091, -0.0337109383673395, 0.20061569615394215, 0.3017192303698945, 0.01833828862200116, 0.13008017480175324, -0.18312906601780712, -0.06837289543465602, -0.18669030011946022, -0.10277616072373537, -0.1916053186839011, -0.06535271587539707, -0.08159560650283193, -0.16090909883609744, 0.39785905245185244, 0.2096101119479334, 0.23446489930418984, 0.09348466030288753, 0.37316290257716334, 0.011815783610909894, 0.16451493943980955, 0.10286253894446418, 0.1943668922654719, 0.04793307995166654, 0.10238769293049133, -0.15646791811760322, 0.06886011906808799, 0.041918605070881694] |
1,802.06361 | On Finding Dense Common Subgraphs | We study the recently introduced problem of finding dense common subgraphs:
Given a sequence of graphs that share the same vertex set, the goal is to find
a subset of vertices $S$ that maximizes some aggregate measure of the density
of the subgraphs induced by $S$ in each of the given graphs. Different choices
for the aggregation function give rise to variants of the problem that were
studied recently. We settle many of the questions left open by previous works,
showing NP-hardness, hardness of approximation, non-trivial approximation
algorithms, and an integrality gap for a natural relaxation.
| cs.DS cs.CC | we study the recently introduced problem of finding dense common subgraphs given a sequence of graphs that share the same vertex set the goal is to find a subset of vertices s that maximizes some aggregate measure of the density of the subgraphs induced by s in each of the given graphs different choices for the aggregation function give rise to variants of the problem that were studied recently we settle many of the questions left open by previous works showing nphardness hardness of approximation nontrivial approximation algorithms and an integrality gap for a natural relaxation | [['we', 'study', 'the', 'recently', 'introduced', 'problem', 'of', 'finding', 'dense', 'common', 'subgraphs', 'given', 'a', 'sequence', 'of', 'graphs', 'that', 'share', 'the', 'same', 'vertex', 'set', 'the', 'goal', 'is', 'to', 'find', 'a', 'subset', 'of', 'vertices', 's', 'that', 'maximizes', 'some', 'aggregate', 'measure', 'of', 'the', 'density', 'of', 'the', 'subgraphs', 'induced', 'by', 's', 'in', 'each', 'of', 'the', 'given', 'graphs', 'different', 'choices', 'for', 'the', 'aggregation', 'function', 'give', 'rise', 'to', 'variants', 'of', 'the', 'problem', 'that', 'were', 'studied', 'recently', 'we', 'settle', 'many', 'of', 'the', 'questions', 'left', 'open', 'by', 'previous', 'works', 'showing', 'nphardness', 'hardness', 'of', 'approximation', 'nontrivial', 'approximation', 'algorithms', 'and', 'an', 'integrality', 'gap', 'for', 'a', 'natural', 'relaxation']] | [-0.15334806082925448, 0.061115833807131516, -0.049894011909297355, 0.06081166925165841, -0.06686173828590351, -0.09486150986534388, 0.0870774840307907, 0.36880437556343776, -0.3196555249839245, -0.32966739099356346, 0.05340501324462821, -0.28139045246643946, -0.15213819195438796, 0.11624889478359061, -0.08627264402457513, 0.07371918660768036, 0.0857795455813175, 0.045733134543600805, -0.030987879472377244, -0.3102371353888884, 0.3277639177686069, 4.2170907060305275e-05, 0.21452039444314627, 0.08792616175681663, 0.08402986024157144, 0.010356801891854653, -0.02175033078189396, 0.07691610047186259, -0.18793888070278322, 0.1266287116862562, 0.24542057062111175, 0.1873988816223573, 0.31732735596597195, -0.4009944961289875, -0.19220335872281188, 0.155724588020045, 0.10106454644483165, 0.06832744064740837, -0.028940868154071115, -0.21713733390788548, 0.14356252226571087, -0.09258895462820267, -0.08629832530762845, -0.015279686951544136, 0.09898299735505134, 0.03655845978209982, -0.2633384575674427, -0.0031516252590032914, 0.11875345595278002, -0.010771533755663162, -0.035527986367621146, -0.17105588989215903, 0.04041503468033625, 0.13716830123060694, 0.034213231932274844, 0.06072132829164426, 0.0531127397310532, -0.13703624487970956, -0.17937311795928204, 0.3578540452872403, -0.012910130967308456, -0.139861407209537, 0.15425629163898216, -0.10570566012756899, -0.1756361917796312, 0.11953152871137718, 0.11404023426196848, 0.15142611318151467, -0.14413785163196735, 0.12122864196559628, -0.1496735619887962, 0.09954821613670599, 0.137080200802302, 0.04257073963041572, 0.1356061788101215, 0.15376193311143047, 0.14669777871980236, 0.19677580782930212, 0.026463093930942705, -0.04980158586113248, -0.2475225615586775, -0.09821842865979609, -0.20688601699657738, 0.028988629800248116, -0.11051286622614498, -0.193458950156734, 0.44620116307244945, 0.11660074873361737, 0.2563005141467632, 0.07127677160315216, 0.21683969248988433, 0.09603897257951151, 0.026711403194591792, 0.13139852607370509, 0.1485748201706277, 0.14328228993690573, -0.014213030469060564, -0.21329711519744401, 0.08443297414729993, 0.10866319552345279] |
1,802.06362 | Experimental demonstration of three-dimensional broadband underwater
acoustic carpet cloak | We present the design, architecture and detailed performance of a
three-dimensional (3D) underwater acoustic carpet cloak (UACC). The proposed
system of the 3D UACC is an octahedral pyramid which is composed of periodical
steel strips. This underwater acoustic device, placed over the target to hide,
is able to manipulate the scattered wavefront to mimic a reflecting plane. The
effectiveness of the prototype is experimentally demonstrated in an anechoic
tank. The measured acoustic pressure distributions show that the 3D UACC can
work in all directions in a wide frequency range. This experimental
verification of 3D device paves the way for guidelines on future practical
applications.
| physics.app-ph | we present the design architecture and detailed performance of a threedimensional 3d underwater acoustic carpet cloak uacc the proposed system of the 3d uacc is an octahedral pyramid which is composed of periodical steel strips this underwater acoustic device placed over the target to hide is able to manipulate the scattered wavefront to mimic a reflecting plane the effectiveness of the prototype is experimentally demonstrated in an anechoic tank the measured acoustic pressure distributions show that the 3d uacc can work in all directions in a wide frequency range this experimental verification of 3d device paves the way for guidelines on future practical applications | [['we', 'present', 'the', 'design', 'architecture', 'and', 'detailed', 'performance', 'of', 'a', 'threedimensional', '3d', 'underwater', 'acoustic', 'carpet', 'cloak', 'uacc', 'the', 'proposed', 'system', 'of', 'the', '3d', 'uacc', 'is', 'an', 'octahedral', 'pyramid', 'which', 'is', 'composed', 'of', 'periodical', 'steel', 'strips', 'this', 'underwater', 'acoustic', 'device', 'placed', 'over', 'the', 'target', 'to', 'hide', 'is', 'able', 'to', 'manipulate', 'the', 'scattered', 'wavefront', 'to', 'mimic', 'a', 'reflecting', 'plane', 'the', 'effectiveness', 'of', 'the', 'prototype', 'is', 'experimentally', 'demonstrated', 'in', 'an', 'anechoic', 'tank', 'the', 'measured', 'acoustic', 'pressure', 'distributions', 'show', 'that', 'the', '3d', 'uacc', 'can', 'work', 'in', 'all', 'directions', 'in', 'a', 'wide', 'frequency', 'range', 'this', 'experimental', 'verification', 'of', '3d', 'device', 'paves', 'the', 'way', 'for', 'guidelines', 'on', 'future', 'practical', 'applications']] | [-0.13066445132622342, 0.0799179181857863, -0.016487059622214965, -0.0604200552266915, -0.108927176920518, -0.09463933327396472, -0.036401416862365574, 0.45133011755891717, -0.23444726817363587, -0.304386587065752, 0.05816699774564208, -0.25842337466649323, -0.16642799949309287, 0.2718399551500065, -0.08387086021516901, 0.129192312552522, 0.05643497972386495, -0.018988170976696823, -0.04327809425796239, -0.1552335015999583, 0.23792795308579046, 0.07626289104183133, 0.3897019692365295, 0.03322725991109529, 0.11816067099033926, -0.002955245433930451, 0.03685984017283772, 0.0011125421901502146, -0.09862210507771334, 0.10337759193946393, 0.2748407716638982, 0.07646549803366025, 0.19844478556814676, -0.43964136209195626, -0.2550840216706722, 0.025598922199256215, 0.15147724672435567, 0.11158819982329778, -0.11332713291966894, -0.33496963256038725, 0.10062343701261292, -0.13753055016814658, -0.16199839471552807, -0.03538086680838695, -0.004998166176777046, -0.014529572732639141, -0.24302461497091615, -0.04056347160635946, 0.05167554196304991, 0.06148941192077473, -0.0891310959839477, -0.07212584054146785, 0.006508379444802323, 0.15152993788293456, -0.0703999840367872, 0.013852357540879613, 0.14600510499440134, -0.09753030546842358, -0.07464979413019207, 0.42102676235999054, 0.004402194496763583, -0.21700143688268816, 0.15843638113270012, -0.12523653620155528, 0.015583896581889488, 0.1255880439936076, 0.25454544082570535, 0.07825539510947867, -0.15559083631244272, 0.017522574229447994, -0.07264907755262147, 0.19438618165888608, 0.09280516506987624, -0.015287185674354147, 0.2306833039060271, 0.28686970185663085, 0.06265334201116975, 0.20175774016556366, -0.18264326618653007, 0.012865463159799289, -0.28952618725284435, -0.17193298978516117, -0.19353449508959714, -0.030715936293395665, -0.04201743439219941, -0.17979139453158355, 0.42922172165260863, 0.22125476896718071, 0.1570300801854151, -0.015505724066035608, 0.3686679953377909, 0.00432531370405251, 0.08275261290299778, 0.024534801240616407, 0.2524932097428693, 0.06041822057718841, 0.14533304098809963, -0.21023704627385506, 0.022529819653405305, -0.010967288300609933] |
1,802.06363 | Generalized Bessel multipliers in Hilbert spaces | The notation of generalized Bessel multipliers is obtained by a bounded
operator on $\ell^2$ which is inserted between the analysis and synthesis
operators. We show that various properties of generalized multipliers are
closely related to their parameters, in particular it will be shown that the
membership of generalized Bessel multiplier in the certain operator classes
requires that its symbol belongs in the same classes, in special sense. Also,
we give some examples to illustrate our results. As we shall see, generalized
multipliers associated with Riesz bases are well-behaved, more precisely in
this case multipliers can be easily composed and inverted. Special attention is
devoted to the study of invertible generalized multipliers. Sufficient and/or
necessary conditions for invertibility are determined. Finally, the behavior of
these operators under perturbations is discussed.
| math.FA | the notation of generalized bessel multipliers is obtained by a bounded operator on ell2 which is inserted between the analysis and synthesis operators we show that various properties of generalized multipliers are closely related to their parameters in particular it will be shown that the membership of generalized bessel multiplier in the certain operator classes requires that its symbol belongs in the same classes in special sense also we give some examples to illustrate our results as we shall see generalized multipliers associated with riesz bases are wellbehaved more precisely in this case multipliers can be easily composed and inverted special attention is devoted to the study of invertible generalized multipliers sufficient andor necessary conditions for invertibility are determined finally the behavior of these operators under perturbations is discussed | [['the', 'notation', 'of', 'generalized', 'bessel', 'multipliers', 'is', 'obtained', 'by', 'a', 'bounded', 'operator', 'on', 'ell2', 'which', 'is', 'inserted', 'between', 'the', 'analysis', 'and', 'synthesis', 'operators', 'we', 'show', 'that', 'various', 'properties', 'of', 'generalized', 'multipliers', 'are', 'closely', 'related', 'to', 'their', 'parameters', 'in', 'particular', 'it', 'will', 'be', 'shown', 'that', 'the', 'membership', 'of', 'generalized', 'bessel', 'multiplier', 'in', 'the', 'certain', 'operator', 'classes', 'requires', 'that', 'its', 'symbol', 'belongs', 'in', 'the', 'same', 'classes', 'in', 'special', 'sense', 'also', 'we', 'give', 'some', 'examples', 'to', 'illustrate', 'our', 'results', 'as', 'we', 'shall', 'see', 'generalized', 'multipliers', 'associated', 'with', 'riesz', 'bases', 'are', 'wellbehaved', 'more', 'precisely', 'in', 'this', 'case', 'multipliers', 'can', 'be', 'easily', 'composed', 'and', 'inverted', 'special', 'attention', 'is', 'devoted', 'to', 'the', 'study', 'of', 'invertible', 'generalized', 'multipliers', 'sufficient', 'andor', 'necessary', 'conditions', 'for', 'invertibility', 'are', 'determined', 'finally', 'the', 'behavior', 'of', 'these', 'operators', 'under', 'perturbations', 'is', 'discussed']] | [-0.09875477872276317, 0.11992317782859355, -0.039466793422272266, 0.11430070976196073, -0.12038684847345937, -0.12856455990510393, -0.04433945545298589, 0.39626677885882616, -0.3024603324227555, -0.19015978325822558, 0.15710290758455417, -0.23475463645417213, -0.2011648524920781, 0.22999038675785527, -0.11810243767036428, 0.05085963762298501, 0.050004241096447834, 0.07386819185515822, -0.16478571672418493, -0.26178351441730363, 0.3648332467089703, 0.01931965752421741, 0.21928046680734198, 0.029363382424953458, 0.03741799431759142, -0.019733856273309668, -0.037941379860664405, -0.018161647487431765, -0.13581424959759947, 0.11322348862669843, 0.2574338444093262, 0.11159707788493513, 0.2597746847363463, -0.40453633450173826, -0.14007208395619378, 0.15404749163534753, 0.13716607457279523, -0.017164968880969137, -0.05954672399036994, -0.2840995278711207, 0.122814978699402, -0.1447850197856856, -0.1649739002310779, -0.12357299224033143, -0.011705889460421347, 0.11384136653180386, -0.30684885285910246, 0.02818308435466191, 0.1209568780550892, 0.008306985699333424, -0.09891939365175055, -0.12222311627516855, -0.00020150354316154884, 0.0681035587268109, 0.021255704942484233, -0.05077788453592464, 0.06343819160924055, -0.025065513235668458, -0.07934109725928035, 0.36240630212795827, -0.0247332973702623, -0.3306366247781498, 0.14769066315028787, -0.15469456150858887, -0.1504768598283273, 0.038741743137930024, 0.10296761623562076, 0.15973804679937487, -0.1554176269185751, 0.1223705529421207, -0.08892680743940232, 0.09799018429678887, 0.11649193023800734, 0.054915845357134306, 0.10978839664842731, 0.05611348758422762, 0.12409005397497568, 0.2080500041923843, 0.0039820769136634385, -0.078830132968435, -0.3537041268260904, -0.16264085424432256, -0.15562855155936392, 0.016964885811393632, -0.056931101265607055, -0.1465587954281905, 0.44530565339292205, 0.1439071543633851, 0.1684069872956521, 0.04433707903272855, 0.19873050308620283, 0.1850922389561491, 0.09332953451757225, 0.04274134527776362, 0.19300533305287773, 0.18815483939256375, 0.07726031111177895, -0.15960828646252206, 0.03024293313727014, 0.15491426325899046] |
1,802.06364 | The variation of invariant graphs in forced systems | In skew-product systems with contractive factors, all orbits asymptotically
approach the graph of the so-called sync function; hence, the corresponding
regularity properties primarily matter. In the literature, sync function
Lipschitz continuity and differentiability have been proved to hold depending
on the derivative of the base reciprocal, if not on its Lyapunov exponent.
However, forcing topological features can also impact the sync function
regularity. Here, we estimate the total variation of sync functions generated
by one-dimensional Markov maps. A sharp condition for bounded variation is
obtained depending on parameters, that involves the Markov map topological
entropy. The results are illustrated with examples.
| math.DS nlin.CD | in skewproduct systems with contractive factors all orbits asymptotically approach the graph of the socalled sync function hence the corresponding regularity properties primarily matter in the literature sync function lipschitz continuity and differentiability have been proved to hold depending on the derivative of the base reciprocal if not on its lyapunov exponent however forcing topological features can also impact the sync function regularity here we estimate the total variation of sync functions generated by onedimensional markov maps a sharp condition for bounded variation is obtained depending on parameters that involves the markov map topological entropy the results are illustrated with examples | [['in', 'skewproduct', 'systems', 'with', 'contractive', 'factors', 'all', 'orbits', 'asymptotically', 'approach', 'the', 'graph', 'of', 'the', 'socalled', 'sync', 'function', 'hence', 'the', 'corresponding', 'regularity', 'properties', 'primarily', 'matter', 'in', 'the', 'literature', 'sync', 'function', 'lipschitz', 'continuity', 'and', 'differentiability', 'have', 'been', 'proved', 'to', 'hold', 'depending', 'on', 'the', 'derivative', 'of', 'the', 'base', 'reciprocal', 'if', 'not', 'on', 'its', 'lyapunov', 'exponent', 'however', 'forcing', 'topological', 'features', 'can', 'also', 'impact', 'the', 'sync', 'function', 'regularity', 'here', 'we', 'estimate', 'the', 'total', 'variation', 'of', 'sync', 'functions', 'generated', 'by', 'onedimensional', 'markov', 'maps', 'a', 'sharp', 'condition', 'for', 'bounded', 'variation', 'is', 'obtained', 'depending', 'on', 'parameters', 'that', 'involves', 'the', 'markov', 'map', 'topological', 'entropy', 'the', 'results', 'are', 'illustrated', 'with', 'examples']] | [-0.15062412387912744, 0.11449804084057376, -0.08524129641505124, 0.08745998197746933, -0.09736195086596054, -0.104768046952489, 0.03336038106838057, 0.3576774466598388, -0.31676183993199675, -0.22227719384660521, 0.1411239796520976, -0.2899196915568249, -0.1683522947760769, 0.1988848938265502, -0.09163167382507484, 0.1307789895661627, 0.024512640873689463, 0.06892705794151799, -0.11602177015173774, -0.2645391966011675, 0.36775491637463614, 0.0040839160838634665, 0.24745728066974865, 0.04687526717431622, 0.12532267965708332, -0.033446115644482695, -0.02808312529993087, 0.004435845734009815, -0.2108474375411671, 0.06840753478763423, 0.17165491062373217, 0.08060524177202714, 0.2716370620764792, -0.36815130137054636, -0.23976534752101444, 0.1645568710300002, 0.08653186274793848, 0.0037165152757327154, -0.01266602270816923, -0.29986305147556974, 0.11294573044754785, -0.10541738809021835, -0.11874028527187092, -0.06386522685020866, 0.036617692417031764, 0.10926652208113545, -0.28738029930500847, 0.07618357531356366, 0.09265395833898595, 0.09606794704507926, -0.10105835810179205, -0.0744152275296758, -0.10822676829440464, 0.10830920935599225, 0.06903872608280934, 0.034755664104180836, 0.14842466778112667, -0.07816620750610928, -0.09410973170329587, 0.29615333295510254, -0.08269999707624832, -0.2869486841603671, 0.16867253574194607, -0.16859879827421934, -0.1348554342293577, 0.1113025308503632, 0.1271722346802454, 0.11259658812628229, -0.13074148095000793, 0.14006663767544847, -0.05037740099538892, 0.18707479836879123, 0.10364063926465293, 0.06504587965122986, 0.0981448779601862, 0.09351959215052942, 0.16104161024951183, 0.16096822951348627, 0.0007535410148211488, -0.11997788774292215, -0.3102168383003019, -0.10161313280868943, -0.21858148399560648, 0.04059532050537245, -0.11585974421263973, -0.18741614420409544, 0.40239322611412015, 0.12309625045405609, 0.19455038289548737, 0.11100495467192982, 0.24641050202864231, 0.18537253058414058, 0.03635485532536808, 0.10026086190494128, 0.20704470287160118, 0.13618582876233182, 0.09015998818524329, -0.1776125629185837, 0.14021961244588516, 0.1599742429067858] |
1,802.06365 | Orbitally limited pair-density wave phase of multilayer superconductors | We investigate the magnetic field dependence of an ideal superconducting
vortex lattice in the parity-mixed pair-density wave phase of multilayer
superconductors within a circular cell Ginzburg-Landau approach. In multilayer
systems, due to local inversion symmetry breaking, a Rashba spin-orbit coupling
is induced at the outer layers. This combined with a perpendicular paramagnetic
(Pauli) limiting magnetic field stabilizes a staggered layer dependent
pair-density wave phase in the superconducting singlet channel. The high-field
pair-density wave phase is separated from the low-field BCS phase by a
first-order phase transition. The motivating guiding question in this paper is:
what is the minimal necessary Maki parameter $\alpha_M$ for the appearance of
the pair-density wave phase of a superconducting trilayer system? To address
this problem we generalize the circular cell method for the regular flux-line
lattice of a type-II superconductor to include paramagnetic depairing effects.
Then, we apply the model to the trilayer system, where each of the layers are
characterized by Ginzburg-Landau parameter $\kappa_0$, and a Maki parameter
$\alpha_M$. We find that when the spin-orbit Rashba interaction compares to the
superconducting condensation energy, the orbitally limited pair-density wave
phase stabilizes for Maki parameters $\alpha_M> 10$.
| cond-mat.supr-con | we investigate the magnetic field dependence of an ideal superconducting vortex lattice in the paritymixed pairdensity wave phase of multilayer superconductors within a circular cell ginzburglandau approach in multilayer systems due to local inversion symmetry breaking a rashba spinorbit coupling is induced at the outer layers this combined with a perpendicular paramagnetic pauli limiting magnetic field stabilizes a staggered layer dependent pairdensity wave phase in the superconducting singlet channel the highfield pairdensity wave phase is separated from the lowfield bcs phase by a firstorder phase transition the motivating guiding question in this paper is what is the minimal necessary maki parameter alpha_m for the appearance of the pairdensity wave phase of a superconducting trilayer system to address this problem we generalize the circular cell method for the regular fluxline lattice of a typeii superconductor to include paramagnetic depairing effects then we apply the model to the trilayer system where each of the layers are characterized by ginzburglandau parameter kappa_0 and a maki parameter alpha_m we find that when the spinorbit rashba interaction compares to the superconducting condensation energy the orbitally limited pairdensity wave phase stabilizes for maki parameters alpha_m 10 | [['we', 'investigate', 'the', 'magnetic', 'field', 'dependence', 'of', 'an', 'ideal', 'superconducting', 'vortex', 'lattice', 'in', 'the', 'paritymixed', 'pairdensity', 'wave', 'phase', 'of', 'multilayer', 'superconductors', 'within', 'a', 'circular', 'cell', 'ginzburglandau', 'approach', 'in', 'multilayer', 'systems', 'due', 'to', 'local', 'inversion', 'symmetry', 'breaking', 'a', 'rashba', 'spinorbit', 'coupling', 'is', 'induced', 'at', 'the', 'outer', 'layers', 'this', 'combined', 'with', 'a', 'perpendicular', 'paramagnetic', 'pauli', 'limiting', 'magnetic', 'field', 'stabilizes', 'a', 'staggered', 'layer', 'dependent', 'pairdensity', 'wave', 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1,802.06366 | On the c-concavity with respect to the quadratic cost on a manifold | Pushing a little forward an approach proposed by Villani, we are going to
prove that in the Riemannian setting the condition $\nabla^2 f< g$ implies that
$f$ is $c$-concave with respect to the quadratic cost as soon as it has a
sufficiently small $C^1$-norm. From this, we deduce a sufficient condition for
the optimality of transport maps.
| math.OC math.DG | pushing a little forward an approach proposed by villani we are going to prove that in the riemannian setting the condition nabla2 f g implies that f is cconcave with respect to the quadratic cost as soon as it has a sufficiently small c1norm from this we deduce a sufficient condition for the optimality of transport maps | [['pushing', 'a', 'little', 'forward', 'an', 'approach', 'proposed', 'by', 'villani', 'we', 'are', 'going', 'to', 'prove', 'that', 'in', 'the', 'riemannian', 'setting', 'the', 'condition', 'nabla2', 'f', 'g', 'implies', 'that', 'f', 'is', 'cconcave', 'with', 'respect', 'to', 'the', 'quadratic', 'cost', 'as', 'soon', 'as', 'it', 'has', 'a', 'sufficiently', 'small', 'c1norm', 'from', 'this', 'we', 'deduce', 'a', 'sufficient', 'condition', 'for', 'the', 'optimality', 'of', 'transport', 'maps']] | [-0.1442271657828574, 0.0723392219705212, -0.1058953325596771, 0.07326463698908421, -0.0778831769047039, -0.15918056571224173, 0.033003480140385885, 0.347843026476247, -0.31242760909455164, -0.2523334539031826, 0.1287540584848362, -0.2518848011137119, -0.15046742037936514, 0.20029583248210006, -0.12629414108648365, 0.05128093782280173, 0.07270565569134695, 0.07874410912128431, -0.06513919769141856, -0.24080964511501537, 0.31273659871866194, 0.04921460053550878, 0.19249226691733515, 0.10619478041605492, 0.14521910714185132, -0.030017443225785558, 0.06778468796567592, 0.03139296217289354, -0.17755361983316625, 0.06418594468518027, 0.2290778234933636, 0.11324294700170867, 0.3543334411058043, -0.3787799373136035, -0.18472259700398094, 0.16105547379369714, 0.0836758537708582, 0.059689044004439244, -0.050484217011606755, -0.252511347510985, 0.14776985959490826, -0.11326839452210281, -0.1652430768008344, -0.09128264966836598, 0.03215230197279847, 0.006416686852129975, -0.33870555899089333, 0.02116825231184651, 0.1396938551749502, 0.02641028508410922, -0.03749551071918437, -0.08309017586023922, -0.06513875345366874, 0.08784821901852931, 0.06513616385720004, 0.1265808276033827, 0.055089194261069806, -0.0936362631411092, -0.029170136616033102, 0.3699483451533264, -0.12440843499332134, -0.23813271652241902, 0.14942424316645234, -0.1430003101455181, -0.13307800702750683, 0.10233925613907299, 0.11463722491836441, 0.1403741078018876, -0.1212624137156776, 0.17355057750163333, -0.10112180890116308, 0.08610329584085516, 0.090586936858017, -0.009408033369774265, 0.08200778788055427, 0.10598052091414242, 0.22482174190892174, 0.17735135897029458, -0.03098858004835035, -0.010141532169654965, -0.34321461897343397, -0.1707192361354828, -0.1888531820649015, 0.1150935860579401, -0.07942618377273902, -0.1066668752381312, 0.2905881319560909, 0.10233511599445981, 0.23304160918840872, 0.13644447498622217, 0.2553653589483084, 0.1631183011995745, 0.06929684339723151, 0.11453704583358817, 0.20629119300948723, 0.17787344636079588, 0.08753728553918856, -0.14987685625653416, 0.05890398017696238, 0.09815114807237738] |
1,802.06367 | Efficient Sparse-Winograd Convolutional Neural Networks | Convolutional Neural Networks (CNNs) are computationally intensive, which
limits their application on mobile devices. Their energy is dominated by the
number of multiplies needed to perform the convolutions. Winograd's minimal
filtering algorithm (Lavin, 2015) and network pruning (Han et al., 2015) can
reduce the operation count, but these two methods cannot be directly combined
$-$ applying the Winograd transform fills in the sparsity in both the weights
and the activations. We propose two modifications to Winograd-based CNNs to
enable these methods to exploit sparsity. First, we move the ReLU operation
into the Winograd domain to increase the sparsity of the transformed
activations. Second, we prune the weights in the Winograd domain to exploit
static weight sparsity. For models on CIFAR-10, CIFAR-100 and ImageNet
datasets, our method reduces the number of multiplications by $10.4\times$,
$6.8\times$ and $10.8\times$ respectively with loss of accuracy less than
$0.1\%$, outperforming previous baselines by $2.0\times$-$3.0\times$. We also
show that moving ReLU to the Winograd domain allows more aggressive pruning.
| cs.CV cs.LG cs.NE | convolutional neural networks cnns are computationally intensive which limits their application on mobile devices their energy is dominated by the number of multiplies needed to perform the convolutions winograds minimal filtering algorithm lavin 2015 and network pruning han et al 2015 can reduce the operation count but these two methods cannot be directly combined applying the winograd transform fills in the sparsity in both the weights and the activations we propose two modifications to winogradbased cnns to enable these methods to exploit sparsity first we move the relu operation into the winograd domain to increase the sparsity of the transformed activations second we prune the weights in the winograd domain to exploit static weight sparsity for models on cifar10 cifar100 and imagenet datasets our method reduces the number of multiplications by 104times 68times and 108times respectively with loss of accuracy less than 01 outperforming previous baselines by 20times30times we also show that moving relu to the winograd domain allows more aggressive pruning | [['convolutional', 'neural', 'networks', 'cnns', 'are', 'computationally', 'intensive', 'which', 'limits', 'their', 'application', 'on', 'mobile', 'devices', 'their', 'energy', 'is', 'dominated', 'by', 'the', 'number', 'of', 'multiplies', 'needed', 'to', 'perform', 'the', 'convolutions', 'winograds', 'minimal', 'filtering', 'algorithm', 'lavin', '2015', 'and', 'network', 'pruning', 'han', 'et', 'al', '2015', 'can', 'reduce', 'the', 'operation', 'count', 'but', 'these', 'two', 'methods', 'can', 'not', 'be', 'directly', 'combined', 'applying', 'the', 'winograd', 'transform', 'fills', 'in', 'the', 'sparsity', 'in', 'both', 'the', 'weights', 'and', 'the', 'activations', 'we', 'propose', 'two', 'modifications', 'to', 'winogradbased', 'cnns', 'to', 'enable', 'these', 'methods', 'to', 'exploit', 'sparsity', 'first', 'we', 'move', 'the', 'relu', 'operation', 'into', 'the', 'winograd', 'domain', 'to', 'increase', 'the', 'sparsity', 'of', 'the', 'transformed', 'activations', 'second', 'we', 'prune', 'the', 'weights', 'in', 'the', 'winograd', 'domain', 'to', 'exploit', 'static', 'weight', 'sparsity', 'for', 'models', 'on', 'cifar10', 'cifar100', 'and', 'imagenet', 'datasets', 'our', 'method', 'reduces', 'the', 'number', 'of', 'multiplications', 'by', '104times', '68times', 'and', '108times', 'respectively', 'with', 'loss', 'of', 'accuracy', 'less', 'than', '01', 'outperforming', 'previous', 'baselines', 'by', '20times30times', 'we', 'also', 'show', 'that', 'moving', 'relu', 'to', 'the', 'winograd', 'domain', 'allows', 'more', 'aggressive', 'pruning']] | [-0.05088024093321401, 0.033669003379185616, -0.018622360953697993, 0.03891590068119713, -0.13803223727575545, -0.15847684172386267, 0.0749819084667709, 0.4649617877296822, -0.3050398426364709, -0.34515277659461935, 0.08223534673972219, -0.2598556540453398, -0.19954023943370525, 0.16997489653258296, -0.15116575817173383, 0.11410280404342983, 0.12292020447528774, -0.010662874034108044, -0.10473692084885196, -0.3657751219968001, 0.24606682924530324, 0.069311145353336, 0.30519141091924135, -0.0030895872378382105, 0.07744199291432464, -0.032924641868240144, -0.0501592416014616, -0.05716709548141807, -0.030780178191861116, 0.1870608104937622, 0.23319905426503038, 0.15865720771604552, 0.32400896591456524, -0.46224849811702406, -0.20352835658023943, 0.10991416722916816, 0.13584844410747476, 0.07184066074329601, 0.047758307925454026, -0.31545649512975515, 0.13388192861830764, -0.15351540928284796, 0.057382922460059285, -0.1792280559908341, -0.04215378314256668, 0.01674171089877099, -0.30181965243903064, 0.06715116502095524, 0.09296079588861428, -0.028032340847377508, -0.01480260610285013, -0.15937960101291537, -0.0023564427795251773, 0.11858271026351261, -0.008430998299399731, 0.05358704524817613, 0.12397293612117873, -0.1736394971163955, -0.13681999631460356, 0.29019547667377776, -0.030364579865697964, -0.24245479697677888, 0.19183377639109375, -0.0429604415453783, -0.1354681461985053, 0.10551811578835847, 0.23183862523833998, 0.09958162848140646, -0.08407934875236298, 0.058187980042278487, -0.005270438549934693, 0.1819861105133621, 0.15365460443269438, -0.004999968290999649, 0.08535526157649667, 0.21885736243881332, 0.07480996108830631, 0.1411267286891399, -0.1549851200104041, -0.028654883421830094, -0.1890258732524191, -0.0815922467172755, -0.22004735987610038, -0.03774855279650337, -0.1263918228511136, -0.10299984616250878, 0.4082430589990983, 0.22009542347781313, 0.24015926713791658, 0.158022206365248, 0.31976666574442536, 0.06414527046924703, 0.1906247831143017, 0.14995921903096562, 0.19526782090945533, 0.06809022449653994, 0.12392341669900753, -0.18722080754327775, 0.029578103457830858, 0.08356047818530937] |
1,802.06368 | Node Centralities and Classification Performance for Characterizing Node
Embedding Algorithms | Embedding graph nodes into a vector space can allow the use of machine
learning to e.g. predict node classes, but the study of node embedding
algorithms is immature compared to the natural language processing field
because of a diverse nature of graphs. We examine the performance of node
embedding algorithms with respect to graph centrality measures that
characterize diverse graphs, through systematic experiments with four node
embedding algorithms, four or five graph centralities, and six datasets.
Experimental results give insights into the properties of node embedding
algorithms, which can be a basis for further research on this topic.
| cs.LG cs.SI stat.ML | embedding graph nodes into a vector space can allow the use of machine learning to eg predict node classes but the study of node embedding algorithms is immature compared to the natural language processing field because of a diverse nature of graphs we examine the performance of node embedding algorithms with respect to graph centrality measures that characterize diverse graphs through systematic experiments with four node embedding algorithms four or five graph centralities and six datasets experimental results give insights into the properties of node embedding algorithms which can be a basis for further research on this topic | [['embedding', 'graph', 'nodes', 'into', 'a', 'vector', 'space', 'can', 'allow', 'the', 'use', 'of', 'machine', 'learning', 'to', 'eg', 'predict', 'node', 'classes', 'but', 'the', 'study', 'of', 'node', 'embedding', 'algorithms', 'is', 'immature', 'compared', 'to', 'the', 'natural', 'language', 'processing', 'field', 'because', 'of', 'a', 'diverse', 'nature', 'of', 'graphs', 'we', 'examine', 'the', 'performance', 'of', 'node', 'embedding', 'algorithms', 'with', 'respect', 'to', 'graph', 'centrality', 'measures', 'that', 'characterize', 'diverse', 'graphs', 'through', 'systematic', 'experiments', 'with', 'four', 'node', 'embedding', 'algorithms', 'four', 'or', 'five', 'graph', 'centralities', 'and', 'six', 'datasets', 'experimental', 'results', 'give', 'insights', 'into', 'the', 'properties', 'of', 'node', 'embedding', 'algorithms', 'which', 'can', 'be', 'a', 'basis', 'for', 'further', 'research', 'on', 'this', 'topic']] | [-0.09139364899126623, 0.021497235723714134, -0.08651483648608686, 0.05076391080736506, -0.14431438081403625, -0.17934034157031198, 0.062383242493153225, 0.4468485278514575, -0.2830934975942483, -0.3428589048188379, 0.07184191653980132, -0.3133776412079377, -0.16637662033388886, 0.16401937413647086, -0.06009717667665409, 0.043373952315626095, 0.17505799703376027, 0.11672005915244547, -0.03793845221053391, -0.27155556273616954, 0.32252080388823334, 0.0031448944224690906, 0.3118933542935672, 0.05114053068825101, 0.08971855018706042, -0.017155882783652265, -0.05226733085309745, 0.09152584089582777, -0.11242198560433522, 0.17399718610531822, 0.3129968856727438, 0.24668408500277722, 0.28167811087427697, -0.40412105283490857, -0.23976295535946834, 0.1627963252688701, 0.1414557408714579, 0.09251563808401424, 0.008012232103394535, -0.3056470075270579, 0.1032264803593256, -0.13723078175276823, 0.016437643112576738, -0.13482798775658011, 0.007702936286496341, 0.025421178355641966, -0.24172173368112584, -0.05986371056927482, 0.05869883800172532, 0.060735459591509125, -0.017824640656745404, -0.13300213470641636, -0.0004209318882500639, 0.1442865395790194, 0.012938517451105754, 0.056521407497229476, 0.14785143072545834, -0.13033646546133168, -0.2563608216801278, 0.40682402686501035, 0.011845443594953691, -0.2082674488153817, 0.189382008609495, -0.045610742650603, -0.2165700656228832, 0.07379625199305616, 0.2837930970447499, 0.06775390764232725, -0.16460310777991402, 0.0437368864605764, -0.0251569899882437, 0.13098277257308744, 0.055353773993021826, 0.05583541406489605, 0.14736387507315268, 0.21429170782164653, 0.08102056781324196, 0.16896804633944731, -0.05555195550253729, -0.07895351864625605, -0.18764558739542048, -0.13848299805873207, -0.18579573626154844, -0.011045075190367595, -0.20831626111968796, -0.16303594044542738, 0.5056751295496539, 0.1579883552099369, 0.23937824048215942, 0.06961817533010617, 0.27505270520947417, -0.00034876869117118876, 0.08599082082129862, 0.13892286981703067, 0.12293916932136124, 0.09788595944433948, 0.05489907581929346, -0.10636865984344361, 0.08103785523550813, 0.08076573943016024] |
1,802.06369 | Linear-Time Algorithm for Long LCF with $k$ Mismatches | In the Longest Common Factor with $k$ Mismatches (LCF$_k$) problem, we are
given two strings $X$ and $Y$ of total length $n$, and we are asked to find a
pair of maximal-length factors, one of $X$ and the other of $Y$, such that
their Hamming distance is at most $k$. Thankachan et al. show that this problem
can be solved in $\mathcal{O}(n \log^k n)$ time and $\mathcal{O}(n)$ space for
constant $k$. We consider the LCF$_k$($\ell$) problem in which we assume that
the sought factors have length at least $\ell$, and the LCF$_k$($\ell$) problem
for $\ell=\Omega(\log^{2k+2} n)$, which we call the Long LCF$_k$ problem. We
use difference covers to reduce the Long LCF$_k$ problem to a task involving
$m=\mathcal{O}(n/\log^{k+1}n)$ synchronized factors. The latter can be solved
in $\mathcal{O}(m \log^{k+1}m)$ time, which results in a linear-time algorithm
for Long LCF$_k$. In general, our solution to LCF$_k$($\ell$) for arbitrary
$\ell$ takes $\mathcal{O}(n + n \log^{k+1} n/\sqrt{\ell})$ time.
| cs.DS | in the longest common factor with k mismatches lcf_k problem we are given two strings x and y of total length n and we are asked to find a pair of maximallength factors one of x and the other of y such that their hamming distance is at most k thankachan et al show that this problem can be solved in mathcalon logk n time and mathcalon space for constant k we consider the lcf_kell problem in which we assume that the sought factors have length at least ell and the lcf_kell problem for ellomegalog2k2 n which we call the long lcf_k problem we use difference covers to reduce the long lcf_k problem to a task involving mmathcalonlogk1n synchronized factors the latter can be solved in mathcalom logk1m time which results in a lineartime algorithm for long lcf_k in general our solution to lcf_kell for arbitrary ell takes mathcalon n logk1 nsqrtell time | [['in', 'the', 'longest', 'common', 'factor', 'with', 'k', 'mismatches', 'lcf_k', 'problem', 'we', 'are', 'given', 'two', 'strings', 'x', 'and', 'y', 'of', 'total', 'length', 'n', 'and', 'we', 'are', 'asked', 'to', 'find', 'a', 'pair', 'of', 'maximallength', 'factors', 'one', 'of', 'x', 'and', 'the', 'other', 'of', 'y', 'such', 'that', 'their', 'hamming', 'distance', 'is', 'at', 'most', 'k', 'thankachan', 'et', 'al', 'show', 'that', 'this', 'problem', 'can', 'be', 'solved', 'in', 'mathcalon', 'logk', 'n', 'time', 'and', 'mathcalon', 'space', 'for', 'constant', 'k', 'we', 'consider', 'the', 'lcf_kell', 'problem', 'in', 'which', 'we', 'assume', 'that', 'the', 'sought', 'factors', 'have', 'length', 'at', 'least', 'ell', 'and', 'the', 'lcf_kell', 'problem', 'for', 'ellomegalog2k2', 'n', 'which', 'we', 'call', 'the', 'long', 'lcf_k', 'problem', 'we', 'use', 'difference', 'covers', 'to', 'reduce', 'the', 'long', 'lcf_k', 'problem', 'to', 'a', 'task', 'involving', 'mmathcalonlogk1n', 'synchronized', 'factors', 'the', 'latter', 'can', 'be', 'solved', 'in', 'mathcalom', 'logk1m', 'time', 'which', 'results', 'in', 'a', 'lineartime', 'algorithm', 'for', 'long', 'lcf_k', 'in', 'general', 'our', 'solution', 'to', 'lcf_kell', 'for', 'arbitrary', 'ell', 'takes', 'mathcalon', 'n', 'logk1', 'nsqrtell', 'time']] | [-0.17379220231908232, 0.12535686950735137, -0.027423512184201446, 0.04739285255335782, -0.030966030719230743, -0.16298788480384097, 0.06188264302590428, 0.3968764764754331, -0.32233650517117307, -0.3260979880515027, 0.066767935567553, -0.2756107559823112, -0.09530345924148394, 0.1612058101885327, -0.038869211096188995, 0.05371897432662878, 0.03488287117574619, 0.0786397787232003, -0.05915841960494904, -0.3206633154624971, 0.24646683990291945, -0.011915948484348108, 0.17027104778011162, 0.025722296595930644, 0.10790795691579275, 0.0194316298624322, -0.0013099203288095863, 0.04350574152948405, -0.1294540877266901, 0.0577601656837593, 0.30688041609660915, 0.15111504212557658, 0.27681884455354244, -0.4098450342473918, -0.16687377903942172, 0.16398053404186175, 0.15794991006698358, 0.08747889856051985, 0.05281979183679166, -0.1794076038728634, 0.13621323538963262, -0.07567307554553773, -0.08018606399466628, -0.004346970529359294, 0.11891986839218091, -0.0407260047903361, -0.3071922167421204, 0.046376283731062784, 0.060134769522597734, -0.02949857579588839, 0.0006582383098310395, -0.15984136937106386, 0.08125294333846908, 0.1305321424606269, 0.03849689143929911, 0.09627316922127996, 0.007375729544573042, -0.06694398537654532, -0.1020349161061522, 0.3703912537391872, -0.08748986312225684, -0.1876966596313127, 0.11282989803433724, -0.11705561336257482, -0.1616861397840644, 0.12269944551541176, 0.18440046805684288, 0.19249424779124252, -0.07425525665705009, 0.14449878332120597, -0.09416989839878188, 0.1947458339663707, 0.12516103069974135, 0.03192896344451782, 0.10272892380822195, 0.1373045710840403, 0.08175729447816282, 0.11419607228511779, -0.05191681587475365, -0.03191178088428848, -0.2711966902030351, -0.16763658376812476, -0.18173900794569556, 0.057061256834446156, -0.1090594393751155, -0.11356928481477989, 0.31455605520152374, 0.1149589423702596, 0.2506930971594307, 0.10750020993474795, 0.23392165486688074, 0.10459704444367336, 0.023483174489428327, 0.1575981846604694, 0.11803797925886227, 0.051249229451258704, 0.037200377303596634, -0.23308834256939207, 0.043236094660903904, 0.10598695997710098] |
1,802.0637 | Hamiltonian Zoo for systems with one degree of freedom | We present alternative explicit forms of the standard Hamiltonian for systems
with one degree of freedom. This new class of infinite Hamiltonians is called
Newton-equivalent Hamiltonian zoo, producing the same equation of motion. These
Hamiltonians are directly solved from the Hamilton's equations and come with
extra-parameters, which are interpreted as scaling factors for the time
evolution on phase space. Moreover, each Hamiltonian in the zoo can be used as
a generating function for a Hamiltonian hierarchy.
| math-ph math.MP | we present alternative explicit forms of the standard hamiltonian for systems with one degree of freedom this new class of infinite hamiltonians is called newtonequivalent hamiltonian zoo producing the same equation of motion these hamiltonians are directly solved from the hamiltons equations and come with extraparameters which are interpreted as scaling factors for the time evolution on phase space moreover each hamiltonian in the zoo can be used as a generating function for a hamiltonian hierarchy | [['we', 'present', 'alternative', 'explicit', 'forms', 'of', 'the', 'standard', 'hamiltonian', 'for', 'systems', 'with', 'one', 'degree', 'of', 'freedom', 'this', 'new', 'class', 'of', 'infinite', 'hamiltonians', 'is', 'called', 'newtonequivalent', 'hamiltonian', 'zoo', 'producing', 'the', 'same', 'equation', 'of', 'motion', 'these', 'hamiltonians', 'are', 'directly', 'solved', 'from', 'the', 'hamiltons', 'equations', 'and', 'come', 'with', 'extraparameters', 'which', 'are', 'interpreted', 'as', 'scaling', 'factors', 'for', 'the', 'time', 'evolution', 'on', 'phase', 'space', 'moreover', 'each', 'hamiltonian', 'in', 'the', 'zoo', 'can', 'be', 'used', 'as', 'a', 'generating', 'function', 'for', 'a', 'hamiltonian', 'hierarchy']] | [-0.14155982645555726, 0.14559589793301514, -0.09646712198249392, 0.08542574397162409, -0.09559557260316168, -0.12081427898610363, -0.04255767399445176, 0.30233247059623936, -0.29737876259998697, -0.3285859680256328, 0.0885417247143876, -0.2502894910002077, -0.15169859151481777, 0.20241063360024142, 0.011158186980095264, 0.061873545769501374, 0.0680499189357097, 0.030091866020213912, -0.10591727358012183, -0.2176424164476024, 0.34784065074023063, -0.01668819581233972, 0.1727364326424494, -0.05177758782283982, 0.15173489989310102, 0.00604622985387372, 0.06757386008629927, 0.015023081418287286, -0.10620904627029558, 0.1124743043596076, 0.23299624379315237, 0.12254487236684843, 0.2052817334848884, -0.4062245179886451, -0.21714274303333178, 0.0913371272460633, 0.16375428437872008, 0.1614480896874935, -0.03592640239072058, -0.29087734049991576, -0.004587902700075427, -0.18807936675639703, -0.20504101140525294, -0.1162913856474129, -0.004212334613642983, 0.03373097560865603, -0.24011817943254435, 0.0895433301496244, 0.05032230147185761, 0.04549999864822304, -0.0781361931255339, -0.12309207737043097, -0.04002596579517263, 0.13504390210869746, -0.004350163652939168, 0.017633587984066154, 0.044977039998598596, -0.09855207392782275, -0.1291295457757204, 0.42484484086870344, -0.055050875752459504, -0.2615758203775496, 0.1585471944229023, -0.0623151117029625, -0.15557201936010373, 0.1003359899749174, 0.16191589341001786, 0.12784129524653828, -0.19330695048729712, 0.10920806461237245, -0.026748175984500227, 0.12361804545523498, 0.012526053859776742, 0.042905261928870064, 0.16549364036905603, 0.10635591239819454, 0.07032166216270747, 0.14433802121690148, 0.011022720035996187, -0.16399066195496032, -0.34003563819302096, -0.16888981632183533, -0.21224766605961565, 0.09292608930263668, -0.09667147830662765, -0.16103670499728037, 0.44937529880632143, 0.10602636883708623, 0.19172250205097166, 0.0828276699821062, 0.22017738804523204, 0.2098463179285613, 0.1166291507904896, 0.0585526633139297, 0.19565450921151284, 0.07720801170433185, 0.03233505422375291, -0.2021614065853174, 0.03301797235837659, 0.1513920987616419] |
1,802.06371 | Inductive Framework for Multi-Aspect Streaming Tensor Completion with
Side Information | Low rank tensor completion is a well studied problem and has applications in
various fields. However, in many real world applications the data is dynamic,
i.e., new data arrives at different time intervals. As a result, the tensors
used to represent the data grow in size. Besides the tensors, in many real
world scenarios, side information is also available in the form of matrices
which also grow in size with time. The problem of predicting missing values in
the dynamically growing tensor is called dynamic tensor completion. Most of the
previous work in dynamic tensor completion make an assumption that the tensor
grows only in one mode. To the best of our Knowledge, there is no previous work
which incorporates side information with dynamic tensor completion. We bridge
this gap in this paper by proposing a dynamic tensor completion framework
called Side Information infused Incremental Tensor Analysis (SIITA), which
incorporates side information and works for general incremental tensors. We
also show how non-negative constraints can be incorporated with SIITA, which is
essential for mining interpretable latent clusters. We carry out extensive
experiments on multiple real world datasets to demonstrate the effectiveness of
SIITA in various different settings.
| cs.LG | low rank tensor completion is a well studied problem and has applications in various fields however in many real world applications the data is dynamic ie new data arrives at different time intervals as a result the tensors used to represent the data grow in size besides the tensors in many real world scenarios side information is also available in the form of matrices which also grow in size with time the problem of predicting missing values in the dynamically growing tensor is called dynamic tensor completion most of the previous work in dynamic tensor completion make an assumption that the tensor grows only in one mode to the best of our knowledge there is no previous work which incorporates side information with dynamic tensor completion we bridge this gap in this paper by proposing a dynamic tensor completion framework called side information infused incremental tensor analysis siita which incorporates side information and works for general incremental tensors we also show how nonnegative constraints can be incorporated with siita which is essential for mining interpretable latent clusters we carry out extensive experiments on multiple real world datasets to demonstrate the effectiveness of siita in various different settings | [['low', 'rank', 'tensor', 'completion', 'is', 'a', 'well', 'studied', 'problem', 'and', 'has', 'applications', 'in', 'various', 'fields', 'however', 'in', 'many', 'real', 'world', 'applications', 'the', 'data', 'is', 'dynamic', 'ie', 'new', 'data', 'arrives', 'at', 'different', 'time', 'intervals', 'as', 'a', 'result', 'the', 'tensors', 'used', 'to', 'represent', 'the', 'data', 'grow', 'in', 'size', 'besides', 'the', 'tensors', 'in', 'many', 'real', 'world', 'scenarios', 'side', 'information', 'is', 'also', 'available', 'in', 'the', 'form', 'of', 'matrices', 'which', 'also', 'grow', 'in', 'size', 'with', 'time', 'the', 'problem', 'of', 'predicting', 'missing', 'values', 'in', 'the', 'dynamically', 'growing', 'tensor', 'is', 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1,802.06372 | Strong convergence rates of semi-discrete splitting approximations for
stochastic Allen--Cahn equation | This article analyzes an explicit temporal splitting numerical scheme for the
stochastic Allen-Cahn equation driven by additive noise, in a bounded spatial
domain with smooth boundary in dimension $d\le 3$. The splitting strategy is
combined with an exponential Euler scheme of an auxiliary problem.
When $d=1$ and the driving noise is a space-time white noise, we first show
some a priori estimates of this splitting scheme. Using the monotonicity of the
drift nonlinearity, we then prove that under very mild assumptions on the
initial data, this scheme achieves the optimal strong convergence rate
$\OO(\delta t^{\frac 14})$. When $d\le 3$ and the driving noise possesses some
regularity in space, we study exponential integrability properties of the exact
and numerical solutions. Finally, in dimension $d=1$, these properties are used
to prove that the splitting scheme has a strong convergence rate $\OO(\delta
t)$.
| math.PR | this article analyzes an explicit temporal splitting numerical scheme for the stochastic allencahn equation driven by additive noise in a bounded spatial domain with smooth boundary in dimension dle 3 the splitting strategy is combined with an exponential euler scheme of an auxiliary problem when d1 and the driving noise is a spacetime white noise we first show some a priori estimates of this splitting scheme using the monotonicity of the drift nonlinearity we then prove that under very mild assumptions on the initial data this scheme achieves the optimal strong convergence rate oodelta tfrac 14 when dle 3 and the driving noise possesses some regularity in space we study exponential integrability properties of the exact and numerical solutions finally in dimension d1 these properties are used to prove that the splitting scheme has a strong convergence rate oodelta t | [['this', 'article', 'analyzes', 'an', 'explicit', 'temporal', 'splitting', 'numerical', 'scheme', 'for', 'the', 'stochastic', 'allencahn', 'equation', 'driven', 'by', 'additive', 'noise', 'in', 'a', 'bounded', 'spatial', 'domain', 'with', 'smooth', 'boundary', 'in', 'dimension', 'dle', '3', 'the', 'splitting', 'strategy', 'is', 'combined', 'with', 'an', 'exponential', 'euler', 'scheme', 'of', 'an', 'auxiliary', 'problem', 'when', 'd1', 'and', 'the', 'driving', 'noise', 'is', 'a', 'spacetime', 'white', 'noise', 'we', 'first', 'show', 'some', 'a', 'priori', 'estimates', 'of', 'this', 'splitting', 'scheme', 'using', 'the', 'monotonicity', 'of', 'the', 'drift', 'nonlinearity', 'we', 'then', 'prove', 'that', 'under', 'very', 'mild', 'assumptions', 'on', 'the', 'initial', 'data', 'this', 'scheme', 'achieves', 'the', 'optimal', 'strong', 'convergence', 'rate', 'oodelta', 'tfrac', '14', 'when', 'dle', '3', 'and', 'the', 'driving', 'noise', 'possesses', 'some', 'regularity', 'in', 'space', 'we', 'study', 'exponential', 'integrability', 'properties', 'of', 'the', 'exact', 'and', 'numerical', 'solutions', 'finally', 'in', 'dimension', 'd1', 'these', 'properties', 'are', 'used', 'to', 'prove', 'that', 'the', 'splitting', 'scheme', 'has', 'a', 'strong', 'convergence', 'rate', 'oodelta', 't']] | [-0.17827779284772882, 0.048312241798144445, -0.08752981163865037, 0.08311173964571883, -0.0350576558055869, -0.16905492577242895, 0.030517539927277012, 0.38014070236164593, -0.2893634869825041, -0.2247810193904392, 0.15131749811015374, -0.2130174469827013, -0.15538587117486674, 0.18128490130808475, -0.10162379252690606, 0.06706728707818463, 0.05015229663231235, 0.010227929550624602, -0.0796700332455499, -0.2929916344076881, 0.36517579239064263, -0.0019208599165405917, 0.2633771236607994, 0.02588484884852179, 0.1699588517599361, -0.052355205130668866, 0.002593519341578518, -0.014221327247956862, -0.18059813982920564, 0.0841171738322136, 0.1687173476709269, 0.059347025649385876, 0.3238316754797015, -0.36696851806904096, -0.21692559789812219, 0.10946152289229297, 0.13123693779778187, 0.12608008978861399, -0.07403631432258619, -0.2672742328039654, 0.13783040503714827, -0.1122773898144563, -0.17471634011810133, -0.0778708617604486, 0.004255143507127313, 0.06565594454329676, -0.36496606454982056, 0.09247789221167889, 0.14631832147732485, 0.059899744118793286, -0.08009955346030925, -0.09044609830100629, 0.016014263138471953, 0.0607407976593991, 0.05512201775580752, 0.01573418040398805, 0.04446542458490644, -0.10923385760996598, -0.0877727234585926, 0.28629035820916254, -0.13176215196617178, -0.2804891496156072, 0.16143546630695893, -0.1331590018538839, -0.12636779284145197, 0.16376283096041586, 0.13647515180966127, 0.12386880265008929, -0.12737362031201474, 0.15644049241445432, -0.02025472222864493, 0.20205453995183326, 0.10031287223303123, 0.050150898636143276, 0.014237043724489817, 0.153173799832365, 0.17753511220824136, 0.13400356351580148, -0.09554946961124307, -0.08637875488510463, -0.35366640156269935, -0.11482054234964881, -0.1675131453970528, 0.10641098766169255, -0.1620594924135493, -0.12261219849418578, 0.33002012373456807, 0.12981603998501878, 0.16285823294859164, 0.08079602175891615, 0.30136701228448015, 0.17542531967595004, -0.06363250775957831, 0.12440128202338795, 0.1736434233949378, 0.1338479454996928, 0.09771312665965314, -0.2557614174236179, 0.03248597767231041, 0.11368919995078139] |
1,802.06373 | Estimation of the linear fractional stable motion | In this paper we investigate the parametric inference for the linear
fractional stable motion in high and low frequency setting. The symmetric
linear fractional stable motion is a three-parameter family, which constitutes
a natural non-Gaussian analogue of the scaled fractional Brownian motion. It is
fully characterised by the scaling parameter $\sigma>0$, the self-similarity
parameter $H \in (0,1)$ and the stability index $\alpha \in (0,2)$ of the
driving stable motion. The parametric estimation of the model is inspired by
the limit theory for stationary increments L\'evy moving average processes that
has been recently studied in \cite{BLP}. More specifically, we combine
(negative) power variation statistics and empirical characteristic functions to
obtain consistent estimates of $(\sigma, \alpha, H)$. We present the law of
large numbers and some fully feasible weak limit theorems.
| stat.ME | in this paper we investigate the parametric inference for the linear fractional stable motion in high and low frequency setting the symmetric linear fractional stable motion is a threeparameter family which constitutes a natural nongaussian analogue of the scaled fractional brownian motion it is fully characterised by the scaling parameter sigma0 the selfsimilarity parameter h in 01 and the stability index alpha in 02 of the driving stable motion the parametric estimation of the model is inspired by the limit theory for stationary increments levy moving average processes that has been recently studied in citeblp more specifically we combine negative power variation statistics and empirical characteristic functions to obtain consistent estimates of sigma alpha h we present the law of large numbers and some fully feasible weak limit theorems | [['in', 'this', 'paper', 'we', 'investigate', 'the', 'parametric', 'inference', 'for', 'the', 'linear', 'fractional', 'stable', 'motion', 'in', 'high', 'and', 'low', 'frequency', 'setting', 'the', 'symmetric', 'linear', 'fractional', 'stable', 'motion', 'is', 'a', 'threeparameter', 'family', 'which', 'constitutes', 'a', 'natural', 'nongaussian', 'analogue', 'of', 'the', 'scaled', 'fractional', 'brownian', 'motion', 'it', 'is', 'fully', 'characterised', 'by', 'the', 'scaling', 'parameter', 'sigma0', 'the', 'selfsimilarity', 'parameter', 'h', 'in', '01', 'and', 'the', 'stability', 'index', 'alpha', 'in', '02', 'of', 'the', 'driving', 'stable', 'motion', 'the', 'parametric', 'estimation', 'of', 'the', 'model', 'is', 'inspired', 'by', 'the', 'limit', 'theory', 'for', 'stationary', 'increments', 'levy', 'moving', 'average', 'processes', 'that', 'has', 'been', 'recently', 'studied', 'in', 'citeblp', 'more', 'specifically', 'we', 'combine', 'negative', 'power', 'variation', 'statistics', 'and', 'empirical', 'characteristic', 'functions', 'to', 'obtain', 'consistent', 'estimates', 'of', 'sigma', 'alpha', 'h', 'we', 'present', 'the', 'law', 'of', 'large', 'numbers', 'and', 'some', 'fully', 'feasible', 'weak', 'limit', 'theorems']] | [-0.11593009952684952, 0.15351297536108177, -0.09389245346392272, 0.08121935816325276, -0.05427266302831413, -0.1251135958955274, 0.02613133384033972, 0.3494362585624913, -0.29030249900824856, -0.2607816389281652, 0.102214767634905, -0.23753595240123104, -0.12008243474883784, 0.18218546735261043, -0.07578401983118965, 0.12374918327986961, -0.028971495557925664, 0.012381033828205545, -0.016720746516170948, -0.14307634555007098, 0.27573924015814555, 0.02108144781232113, 0.2715681043409859, -0.06463877487476566, 0.1291379741523997, -0.01990820419450756, -0.05956933318066149, 0.04650279315774242, -0.20457685659454228, 0.11939476662882953, 0.1773299745973418, 0.013908915339925443, 0.3010442886588862, -0.3222293840517523, -0.22253180853658705, 0.14615443133516237, 0.12075563900907582, 0.04609372661161615, -0.03619501849482276, -0.2698438609804725, 0.09687332464636711, -0.16638954802328954, -0.18215203448926331, -0.08236925964592956, 0.1138088478546706, 0.0393265159054863, -0.3072732653381536, 0.16633441442172625, 0.12220053369310335, 0.036816728657868225, -0.05621875205633842, -0.09957398627011571, -0.003406407737202244, 0.06954707839395269, 0.028505038689218054, -0.026640898115147138, 0.10272833040653495, -0.139039112638784, -0.10303193057279714, 0.3353051937597229, -0.12687963783901068, -0.23690030786383431, 0.133205961479689, -0.21161112833215157, -0.16712359492885298, 0.1451463073863124, 0.16269213947521166, 0.1523668626044241, -0.14035230349782069, 0.14597436219651172, -0.029201418183220085, 0.1557055210314502, 0.0787442355431267, 0.002508073961507762, 0.147221438564884, 0.16004444789723493, 0.10189229457319016, 0.14459526168502634, -0.10964290989841174, -0.14680822180889663, -0.31572018309816485, -0.12097347900999011, -0.15700714981358033, 0.060113422534413985, -0.13664841015770435, -0.1711040329264506, 0.34551017789999605, 0.11032190441983403, 0.1965799184035859, 0.09160921056991356, 0.23514753684867173, 0.24305234399798792, -0.02841770703162183, 0.0468720592034515, 0.22625407785130847, 0.1694888950260065, 0.08895972698519472, -0.17918015613759053, 0.044907253148267046, 0.05041288157917734] |
1,802.06374 | Quantum metamaterials: entanglement of spin and orbital angular momentum
of a single photon | Metamaterials have been a major research area for more than two decades now,
involving artificial structures with predesigned electromagnetic properties
constructed from deep subwavelength building blocks. They have been used to
demonstrate a wealth of fascinating phenomena ranging from negative refractive
index and epsilon-near-zero to cloaking, emulations of general relativity
effects, and super-resolution imaging, to name a few. In the past few years,
metamaterials have been suggested as a new platform for quantum optics, and
several pioneering experiments have already been carried out with single
photons. Here, we employ a dielectric metasurface to generate entanglement
between spin and orbital angular momentum of single photons. We demonstrate
experimentally the generation of the four Bell states by utilizing the
geometric phase arising from the photonic spin-orbit interaction. These are the
first experiments with entangled states with metasurfaces, and as such they are
paving the way to the new area of quantum metamaterials.
| quant-ph physics.optics | metamaterials have been a major research area for more than two decades now involving artificial structures with predesigned electromagnetic properties constructed from deep subwavelength building blocks they have been used to demonstrate a wealth of fascinating phenomena ranging from negative refractive index and epsilonnearzero to cloaking emulations of general relativity effects and superresolution imaging to name a few in the past few years metamaterials have been suggested as a new platform for quantum optics and several pioneering experiments have already been carried out with single photons here we employ a dielectric metasurface to generate entanglement between spin and orbital angular momentum of single photons we demonstrate experimentally the generation of the four bell states by utilizing the geometric phase arising from the photonic spinorbit interaction these are the first experiments with entangled states with metasurfaces and as such they are paving the way to the new area of quantum metamaterials | [['metamaterials', 'have', 'been', 'a', 'major', 'research', 'area', 'for', 'more', 'than', 'two', 'decades', 'now', 'involving', 'artificial', 'structures', 'with', 'predesigned', 'electromagnetic', 'properties', 'constructed', 'from', 'deep', 'subwavelength', 'building', 'blocks', 'they', 'have', 'been', 'used', 'to', 'demonstrate', 'a', 'wealth', 'of', 'fascinating', 'phenomena', 'ranging', 'from', 'negative', 'refractive', 'index', 'and', 'epsilonnearzero', 'to', 'cloaking', 'emulations', 'of', 'general', 'relativity', 'effects', 'and', 'superresolution', 'imaging', 'to', 'name', 'a', 'few', 'in', 'the', 'past', 'few', 'years', 'metamaterials', 'have', 'been', 'suggested', 'as', 'a', 'new', 'platform', 'for', 'quantum', 'optics', 'and', 'several', 'pioneering', 'experiments', 'have', 'already', 'been', 'carried', 'out', 'with', 'single', 'photons', 'here', 'we', 'employ', 'a', 'dielectric', 'metasurface', 'to', 'generate', 'entanglement', 'between', 'spin', 'and', 'orbital', 'angular', 'momentum', 'of', 'single', 'photons', 'we', 'demonstrate', 'experimentally', 'the', 'generation', 'of', 'the', 'four', 'bell', 'states', 'by', 'utilizing', 'the', 'geometric', 'phase', 'arising', 'from', 'the', 'photonic', 'spinorbit', 'interaction', 'these', 'are', 'the', 'first', 'experiments', 'with', 'entangled', 'states', 'with', 'metasurfaces', 'and', 'as', 'such', 'they', 'are', 'paving', 'the', 'way', 'to', 'the', 'new', 'area', 'of', 'quantum', 'metamaterials']] | [-0.1058371989079751, 0.17586387191899122, -0.07745615549385548, -0.013115248593191306, -0.1045470295722286, -0.16948944464636345, -0.024085098545377454, 0.46902893027911585, -0.24101101247724727, -0.3523763555660844, 0.06910455927640821, -0.31497736408064764, -0.19166966423702736, 0.2751039052630464, 0.00659585136299332, 0.16429433258250356, -0.002104375345321993, -0.07219307864705722, -0.043004439142532644, -0.18628204746792715, 0.28153569483508667, 0.03364481743716169, 0.285346307028085, 0.04925382647275304, 0.12005001935797432, -0.02619058691392032, 0.015124207066061596, 0.01262211499735713, -0.07485341388596377, 0.14914659884680684, 0.27365947657303574, 0.04990875439771723, 0.2877880144416607, -0.4775520221640666, -0.28688705451165636, 0.05308523187413812, 0.13822282386633258, 0.17599836298575003, -0.1270539470409858, -0.31500285018235447, 0.0015288884239271284, -0.17075125223957002, -0.10550221375189722, -0.12166606245174383, 0.003940249482790629, -0.009992204170363644, -0.16942422589287162, -0.009843694310014446, 0.0021001538230727116, 0.07563900436429928, 0.0027178914891555907, -0.11177535690212001, 0.02340077403622369, 0.11625808241854732, 0.008835232829054197, -0.03830070525407791, 0.10056862360293356, -0.13335343948526618, -0.19440414163400419, 0.3823380625868837, 0.0026396773139276773, -0.14343542365667722, 0.18980585373627643, -0.15239468166294198, -0.0710577115851144, 0.12315733659081161, 0.2045469635228316, 0.1253593480742226, -0.14835742477017144, 0.01893874033470638, -0.05596608672911922, 0.15710117949793737, 0.12717999797003965, 0.14610742914684427, 0.29752281264712416, 0.17731120423413813, 0.010541025043154757, 0.1455652267485857, -0.10372143484652042, -0.06552793441961209, -0.21818123629316688, -0.15978875182258587, -0.21684737944354612, 0.07029461352465054, -0.03462197221214107, -0.1402642468580355, 0.39313547905534507, 0.1299849248273919, 0.14579370741421976, -0.033131966219904524, 0.2705421385044853, 0.05335702600423246, 0.1656134328059852, 0.02219598640066882, 0.36240472381313643, 0.16242994903431585, 0.1390148572406421, -0.1431741195222518, -0.01587835708943506, -0.029781349180266262] |
1,802.06375 | Efficient Gradual Typing | Gradual typing combines static and dynamic typing in the same program. One
would hope that the performance in a gradually typed language would range
between that of a dynamically typed language and a statically typed language.
Existing implementations of gradually typed languages have not achieved this
goal due to overheads associated with runtime casts. Takikawa et al. (2016)
report up to 100$\times$ slowdowns for partially typed programs. In this paper
we present a compiler, named Grift, for evaluating implementation techniques
for gradual typing. We take a straightforward but surprisingly unexplored
implementation approach for gradual typing, that is, ahead-of-time compilation
to native assembly code with carefully chosen runtime representations and
space-efficient coercions.
Our experiments show that this approach achieves performance on par with
OCaml on statically typed programs and performance between that of Gambit and
Racket on untyped programs. On partially typed code, the geometric mean ranges
from 0.42$\times$ to 2.36$\times$ that of (untyped) Racket across the
benchmarks. We implement casts using the coercions of Siek, Thiemann, and
Wadler (2015). This technique eliminates all catastrophic slowdowns without
introducing significant overhead. Across the benchmarks, coercions range from
15% slower (fft) to almost 2$\times$ faster (matmult) than regular casts. We
also implement the monotonic references of Siek et al. (2015). Monotonic
references eliminate all overhead in statically typed code, and for partially
typed code, they are faster than proxied references, sometimes up to
1.48$\times$.
| cs.PL | gradual typing combines static and dynamic typing in the same program one would hope that the performance in a gradually typed language would range between that of a dynamically typed language and a statically typed language existing implementations of gradually typed languages have not achieved this goal due to overheads associated with runtime casts takikawa et al 2016 report up to 100times slowdowns for partially typed programs in this paper we present a compiler named grift for evaluating implementation techniques for gradual typing we take a straightforward but surprisingly unexplored implementation approach for gradual typing that is aheadoftime compilation to native assembly code with carefully chosen runtime representations and spaceefficient coercions our experiments show that this approach achieves performance on par with ocaml on statically typed programs and performance between that of gambit and racket on untyped programs on partially typed code the geometric mean ranges from 042times to 236times that of untyped racket across the benchmarks we implement casts using the coercions of siek thiemann and wadler 2015 this technique eliminates all catastrophic slowdowns without introducing significant overhead across the benchmarks coercions range from 15 slower fft to almost 2times faster matmult than regular casts we also implement the monotonic references of siek et al 2015 monotonic references eliminate all overhead in statically typed code and for partially typed code they are faster than proxied references sometimes up to 148times | [['gradual', 'typing', 'combines', 'static', 'and', 'dynamic', 'typing', 'in', 'the', 'same', 'program', 'one', 'would', 'hope', 'that', 'the', 'performance', 'in', 'a', 'gradually', 'typed', 'language', 'would', 'range', 'between', 'that', 'of', 'a', 'dynamically', 'typed', 'language', 'and', 'a', 'statically', 'typed', 'language', 'existing', 'implementations', 'of', 'gradually', 'typed', 'languages', 'have', 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0.029181314869007716] |
1,802.06376 | On the entropy norm on the group of diffeomorphisms of closed oriented
surface | We prove that the entropy norm on the group of diffeomorphisms of a closed
orientable surface of positive genus is unbounded.
| math.GT math.DS math.GR | we prove that the entropy norm on the group of diffeomorphisms of a closed orientable surface of positive genus is unbounded | [['we', 'prove', 'that', 'the', 'entropy', 'norm', 'on', 'the', 'group', 'of', 'diffeomorphisms', 'of', 'a', 'closed', 'orientable', 'surface', 'of', 'positive', 'genus', 'is', 'unbounded']] | [-0.28340629062482287, 0.1680966934100503, -0.10938043733975585, 0.0993740335384029, -0.05850109910326345, -0.14092305805977612, -0.013779837948580584, 0.29986756046613056, -0.2689369973682222, -0.16975756335471356, 0.08274009688535616, -0.33158501849642824, -0.1288793708552562, 0.21659342891403607, -0.20686604636943057, 0.025906212627887726, 0.08544525796813625, 0.19400967196339652, -0.12204054134365704, -0.26740746581483454, 0.4645330565316336, -0.14327053796677364, 0.16478057808819271, 0.20019579403811977, 0.18419977809701646, -0.10556110912667853, 0.052401870311725704, 0.05686705266790731, -0.15999301652863368, 0.17527594541509947, 0.2614837283534663, 0.06080134453562399, 0.20963171771949246, -0.4238362483502853, -0.2559308851403849, 0.213569241975035, 0.07191265942085356, -0.04167671896339882, -0.05663546440302439, -0.2780369441246703, 0.10818953160196543, -0.08751895074688253, -0.20602603633666322, -0.0302824451188956, 0.08932261976102988, -0.05037466764804863, -0.1802710576781205, 0.049862442227701344, 0.17049138496319452, 0.1660641659317272, -0.1255953371347416, -0.06818344262206838, -0.15376820743438743, 0.10427909679267378, 0.05688108524884142, 0.10643550404901839, 0.11260752399851169, -0.005087785511499359, -0.04688792445120357, 0.2468329133199794, -0.15701909057263816, -0.3141716369205997, 0.07677738129028253, -0.21085498442075082, -0.16714119574143774, 0.13290664591338663, 0.1653685597259374, 0.2270143379767736, 0.011439593774931771, 0.27049184120481923, -0.1577835888380096, 0.10909007276807513, 0.05908931969177155, -0.06843471329747922, 0.09871828547191053, 0.05320667471027091, 0.24252765084661188, 0.1929287730405728, -0.007275695435791498, -0.006254771214333319, -0.392891349537032, -0.2835425749487643, -0.17506989162592662, 0.20445601185340256, -0.14255518985113927, -0.2622016810235523, 0.4177869643483843, -0.04770722948679967, 0.10987742493549983, 0.22217503283172846, 0.23978945275857336, 0.05925333854697999, 0.04265204448962495, 0.1651816382072866, 0.0659608163294338, 0.21946785448207742, -0.15524012486760816, -0.23231244595011785, 0.015428421154086078, 0.2756609215977646] |
1,802.06377 | On the structure of affine flat group schemes over discrete valuation
rings, II | In the 1st part of this work [DHdS18], we studied affine group schemes over a
discrete valuation ring (DVR) by means of Neron blowups. We also showed how to
apply these findings to throw light on the group schemes coming from Tannakian
categories of D-modules. In the present work, we follow up this theme. We show
that a certain class of affine group schemes of "infinite type", Neron blowups
of formal subgroups, are quite typical. We also explain how these group schemes
appear naturally in Tannakian categories of D-modules. To conclude, we isolate
a Tannakian property of affine group schemes, named prudence, which allows one
to verify if the underlying ring of functions is a free module over the base
ring. This is then successfully applied to obtain a general result on the
structure of differential Galois groups over complete DVRs.
| math.AG | in the 1st part of this work dhds18 we studied affine group schemes over a discrete valuation ring dvr by means of neron blowups we also showed how to apply these findings to throw light on the group schemes coming from tannakian categories of dmodules in the present work we follow up this theme we show that a certain class of affine group schemes of infinite type neron blowups of formal subgroups are quite typical we also explain how these group schemes appear naturally in tannakian categories of dmodules to conclude we isolate a tannakian property of affine group schemes named prudence which allows one to verify if the underlying ring of functions is a free module over the base ring this is then successfully applied to obtain a general result on the structure of differential galois groups over complete dvrs | [['in', 'the', '1st', 'part', 'of', 'this', 'work', 'dhds18', 'we', 'studied', 'affine', 'group', 'schemes', 'over', 'a', 'discrete', 'valuation', 'ring', 'dvr', 'by', 'means', 'of', 'neron', 'blowups', 'we', 'also', 'showed', 'how', 'to', 'apply', 'these', 'findings', 'to', 'throw', 'light', 'on', 'the', 'group', 'schemes', 'coming', 'from', 'tannakian', 'categories', 'of', 'dmodules', 'in', 'the', 'present', 'work', 'we', 'follow', 'up', 'this', 'theme', 'we', 'show', 'that', 'a', 'certain', 'class', 'of', 'affine', 'group', 'schemes', 'of', 'infinite', 'type', 'neron', 'blowups', 'of', 'formal', 'subgroups', 'are', 'quite', 'typical', 'we', 'also', 'explain', 'how', 'these', 'group', 'schemes', 'appear', 'naturally', 'in', 'tannakian', 'categories', 'of', 'dmodules', 'to', 'conclude', 'we', 'isolate', 'a', 'tannakian', 'property', 'of', 'affine', 'group', 'schemes', 'named', 'prudence', 'which', 'allows', 'one', 'to', 'verify', 'if', 'the', 'underlying', 'ring', 'of', 'functions', 'is', 'a', 'free', 'module', 'over', 'the', 'base', 'ring', 'this', 'is', 'then', 'successfully', 'applied', 'to', 'obtain', 'a', 'general', 'result', 'on', 'the', 'structure', 'of', 'differential', 'galois', 'groups', 'over', 'complete', 'dvrs']] | [-0.14836060029857825, -0.008757677720859646, -0.17710367214001183, 0.06972701207851059, -0.12624340380009796, -0.12397732751643552, 0.031555814966226794, 0.38848519727887054, -0.36718272965268367, -0.19097491389340057, 0.07642891825027098, -0.1669058638442948, -0.15092372138419055, 0.23056177775641637, -0.19414249644614756, -0.053994017925911714, 0.012410651849183654, 0.08130265821902348, -0.08007584820069107, -0.3364144287853768, 0.4370157015543165, -0.035481652690629875, 0.2694578116925965, 0.015453688976205221, 0.10435665905034901, 0.010902918253227005, -0.07878399918720658, -0.0045882725422935824, -0.12978659696803205, 0.14382002707155023, 0.34181482498367716, 0.05782600403098123, 0.22636510882959035, -0.3906637640936034, -0.16580199872675752, 0.1716484677038222, 0.12440321864227631, 0.09233359624881164, -0.019791635932467345, -0.2683651422150433, 0.12415302585411285, -0.24540901825364148, -0.14988483219474022, -0.08061966111417859, 0.015529449014658374, 0.048044582426830726, -0.21692236585284783, -0.04606077531061601, 0.052626843045332605, 0.13352773085768735, -0.03935152199327214, -0.04816077459794802, 0.0035804305317079913, 0.07167258001198726, 0.008679702023177275, -0.02811568517770086, 0.1371670430492876, -0.06102154114716021, -0.1389712430578324, 0.40330908726235587, -0.08295874377446515, -0.1762427134173257, 0.13972825537369188, -0.16573039838778122, -0.18928103305266372, 0.1362609339678394, 0.12413816139742266, 0.16170219956631107, -0.030025514072622172, 0.13505144436411293, -0.14417164121488377, 0.10912242532441659, 0.05443342986317085, 0.003444360285149222, 0.09909449803152322, 0.08369496196641453, 0.059709079065318554, 0.11225321933494083, 0.011012719174946792, -0.06560041306739939, -0.34980112249696893, -0.1867897065755512, -0.03695699188059994, 0.1065985519572028, -0.036722452312408546, -0.13477898838630478, 0.43755568164799896, 0.12734469913411886, 0.17578692567933882, 0.10229063692718877, 0.2172972027511735, 0.02210657966456243, 0.08765845875854471, 0.03433751870345857, 0.13066265297987098, 0.22387242499971763, -0.02171299575877908, -0.13441563427747627, -0.030427245922536324, 0.17626029483840933] |
1,802.06378 | Neutral gas properties of Lyman continuum emitting galaxies: column
densities and covering fractions from UV absorption lines | The processes allowing the escape of ionizing photons from galaxies into the
intergalactic medium are poorly known. To understand how Lyman continuum (LyC)
photons escape galaxies, we constrain the HI covering fractions and column
densities using ultraviolet HI and metal absorption lines of 18 star-forming
galaxies which have Lyman series observations. Nine of these galaxies are
confirmed LyC emitters. We fit the stellar continuum, dust attenuation, metal,
and HI properties to consistently determine the UV attenuation, as well as the
column densities and covering factors of neutral hydrogen and metals. We use
synthetic interstellar absorption lines to explore the systematics of our
measurements. Then we apply our method to the observed UV spectra of
low-redshift and z-2 galaxies. The observed HI lines are found to be saturated
in all galaxies. An indirect approach using OI column densities and the
observed O/H abundances yields HI column densities of 18.6 to 20 cm-2. These
columns are too high to allow the escape of ionizing photons. We find that the
known LyC leakers have HI covering fractions less than unity. Ionizing photons
escape through optically thin holes/channels in a clumpy interstellar medium.
Our simulations confirm that the HI covering fractions are accurately
recovered. The SiII and HI covering fractions scale linearly, in agreement with
observations from stacked Lyman break galaxy spectra at z-3. Thus, with an
empirical correction, the SiII absorption lines can also be used to determine
the HI coverage. Finally, we show that a consistent fitting of dust
attenuation, continuum and absorption lines is required to properly infer the
covering fraction of neutral gas and subsequently to infer the escape fraction
of ionizing radiation. These measurements can estimate the LyC escape fraction,
as we demonstrate in a companion paper.
| astro-ph.GA | the processes allowing the escape of ionizing photons from galaxies into the intergalactic medium are poorly known to understand how lyman continuum lyc photons escape galaxies we constrain the hi covering fractions and column densities using ultraviolet hi and metal absorption lines of 18 starforming galaxies which have lyman series observations nine of these galaxies are confirmed lyc emitters we fit the stellar continuum dust attenuation metal and hi properties to consistently determine the uv attenuation as well as the column densities and covering factors of neutral hydrogen and metals we use synthetic interstellar absorption lines to explore the systematics of our measurements then we apply our method to the observed uv spectra of lowredshift and z2 galaxies the observed hi lines are found to be saturated in all galaxies an indirect approach using oi column densities and the observed oh abundances yields hi column densities of 186 to 20 cm2 these columns are too high to allow the escape of ionizing photons we find that the known lyc leakers have hi covering fractions less than unity ionizing photons escape through optically thin holeschannels in a clumpy interstellar medium our simulations confirm that the hi covering fractions are accurately recovered the siii and hi covering fractions scale linearly in agreement with observations from stacked lyman break galaxy spectra at z3 thus with an empirical correction the siii absorption lines can also be used to determine the hi coverage finally we show that a consistent fitting of dust attenuation continuum and absorption lines is required to properly infer the covering fraction of neutral gas and subsequently to infer the escape fraction of ionizing radiation these measurements can estimate the lyc escape fraction as we demonstrate in a companion paper | [['the', 'processes', 'allowing', 'the', 'escape', 'of', 'ionizing', 'photons', 'from', 'galaxies', 'into', 'the', 'intergalactic', 'medium', 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1,802.06379 | Long-Term Oscillations of Sunspots and a Special Class of Artifacts in
SOHO(MDI) and SDO(HMI) Data | A specific type of artifacts, that originate due to displacement of the image
of a moving object along the digital (pixel) matrix of receiver are analyzed in
detail. The criteria of appearance and the influence of these artifacts on the
study of long-term oscillations of sunspots are deduced. The obtained criteria
suggest us methods for reduction or even elimination of these artifacts. It is
shown that the use of integral parameters can be very effective against the
artifact distortions. The simultaneous observations of sunspot magnetic field
and ultraviolet intensity of the umbra have given the same periods for the
long-term oscillations. In this way the real physical nature of the oscillatory
process, which is independent of the artifacts have been confirmed again. A
number of examples considered here confirm the dependence between the periods
of main mode of the sunspot magnetic field long-term oscillations and its
strength. The dependence was derived earlier from both the observations and the
theoretical model of the shallow sunspot. The anti-phase behavior of time
variations of sunspot umbra area and magnetic field of the sunspot demonstrates
that the umbra of sunspot moves in long-term oscillations as a whole: all its
points oscillate with the same phase.
| astro-ph.SR | a specific type of artifacts that originate due to displacement of the image of a moving object along the digital pixel matrix of receiver are analyzed in detail the criteria of appearance and the influence of these artifacts on the study of longterm oscillations of sunspots are deduced the obtained criteria suggest us methods for reduction or even elimination of these artifacts it is shown that the use of integral parameters can be very effective against the artifact distortions the simultaneous observations of sunspot magnetic field and ultraviolet intensity of the umbra have given the same periods for the longterm oscillations in this way the real physical nature of the oscillatory process which is independent of the artifacts have been confirmed again a number of examples considered here confirm the dependence between the periods of main mode of the sunspot magnetic field longterm oscillations and its strength the dependence was derived earlier from both the observations and the theoretical model of the shallow sunspot the antiphase behavior of time variations of sunspot umbra area and magnetic field of the sunspot demonstrates that the umbra of sunspot moves in longterm oscillations as a whole all its points oscillate with the same phase | [['a', 'specific', 'type', 'of', 'artifacts', 'that', 'originate', 'due', 'to', 'displacement', 'of', 'the', 'image', 'of', 'a', 'moving', 'object', 'along', 'the', 'digital', 'pixel', 'matrix', 'of', 'receiver', 'are', 'analyzed', 'in', 'detail', 'the', 'criteria', 'of', 'appearance', 'and', 'the', 'influence', 'of', 'these', 'artifacts', 'on', 'the', 'study', 'of', 'longterm', 'oscillations', 'of', 'sunspots', 'are', 'deduced', 'the', 'obtained', 'criteria', 'suggest', 'us', 'methods', 'for', 'reduction', 'or', 'even', 'elimination', 'of', 'these', 'artifacts', 'it', 'is', 'shown', 'that', 'the', 'use', 'of', 'integral', 'parameters', 'can', 'be', 'very', 'effective', 'against', 'the', 'artifact', 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1,802.0638 | A new discontinuous Galerkin spectral element method for elastic waves
with physically motivated numerical fluxes | The discontinuous Galerkin (DG) method is an established method for computing
approximate solutions of partial differential equations in many applications.
Unlike continuous finite elements, in DG methods, numerical fluxes are used to
enforce inter-element conditions, and internal and external physical boundary
conditions. However, for certain problems such as elastic wave propagation in
complex media, where several wave types and wave speeds are simultaneously
present, a standard numerical flux may not be compatible with the physical
boundary conditions. If surface or interface waves are present, this
incompatibility may lead to numerical instabilities. We present a stable and
arbitrary order accurate DG method for elastic waves with a physically
motivated numerical flux. Our numerical flux is compatible with all well-posed,
internal and external, boundary conditions, including linear and nonlinear
frictional constitutive equations for modelling spontaneously propagating shear
ruptures in elastic solids and dynamic earthquake rupture processes. We present
numerical experiments in one and two space dimensions verifying high order
accuracy and asymptotic numerical stability, and demonstrating potentials for
modelling complex nonlinear frictional problems in elastic solids.
| math.NA cs.NA | the discontinuous galerkin dg method is an established method for computing approximate solutions of partial differential equations in many applications unlike continuous finite elements in dg methods numerical fluxes are used to enforce interelement conditions and internal and external physical boundary conditions however for certain problems such as elastic wave propagation in complex media where several wave types and wave speeds are simultaneously present a standard numerical flux may not be compatible with the physical boundary conditions if surface or interface waves are present this incompatibility may lead to numerical instabilities we present a stable and arbitrary order accurate dg method for elastic waves with a physically motivated numerical flux our numerical flux is compatible with all wellposed internal and external boundary conditions including linear and nonlinear frictional constitutive equations for modelling spontaneously propagating shear ruptures in elastic solids and dynamic earthquake rupture processes we present numerical experiments in one and two space dimensions verifying high order accuracy and asymptotic numerical stability and demonstrating potentials for modelling complex nonlinear frictional problems in elastic solids | [['the', 'discontinuous', 'galerkin', 'dg', 'method', 'is', 'an', 'established', 'method', 'for', 'computing', 'approximate', 'solutions', 'of', 'partial', 'differential', 'equations', 'in', 'many', 'applications', 'unlike', 'continuous', 'finite', 'elements', 'in', 'dg', 'methods', 'numerical', 'fluxes', 'are', 'used', 'to', 'enforce', 'interelement', 'conditions', 'and', 'internal', 'and', 'external', 'physical', 'boundary', 'conditions', 'however', 'for', 'certain', 'problems', 'such', 'as', 'elastic', 'wave', 'propagation', 'in', 'complex', 'media', 'where', 'several', 'wave', 'types', 'and', 'wave', 'speeds', 'are', 'simultaneously', 'present', 'a', 'standard', 'numerical', 'flux', 'may', 'not', 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1,802.06381 | Smooth maps compatible with simplicial structures and inverse images | As a higher dimensional version of the theory of Morse functions, there have
been various studies of smooth manifolds using generic smooth maps. As
fundamental results, in these studies, they have found that inverse images of
such maps often restrict the types of the source manifolds. For example, if a
generic map such that the inverse image of a regular value is not
null-cobordant, then the homology group of its {\it Reeb} space, which is
defined as the space of all the connected components of inverse images of the
map and a fundamental tool in the theory of generic smooth maps, is known to be
non-trivial. In this paper, we show similar results in new appropriate
situations. These works are regarded as extensions of works by Hiratuka and
Saeki in 2013--4.
| math.AT | as a higher dimensional version of the theory of morse functions there have been various studies of smooth manifolds using generic smooth maps as fundamental results in these studies they have found that inverse images of such maps often restrict the types of the source manifolds for example if a generic map such that the inverse image of a regular value is not nullcobordant then the homology group of its it reeb space which is defined as the space of all the connected components of inverse images of the map and a fundamental tool in the theory of generic smooth maps is known to be nontrivial in this paper we show similar results in new appropriate situations these works are regarded as extensions of works by hiratuka and saeki in 20134 | [['as', 'a', 'higher', 'dimensional', 'version', 'of', 'the', 'theory', 'of', 'morse', 'functions', 'there', 'have', 'been', 'various', 'studies', 'of', 'smooth', 'manifolds', 'using', 'generic', 'smooth', 'maps', 'as', 'fundamental', 'results', 'in', 'these', 'studies', 'they', 'have', 'found', 'that', 'inverse', 'images', 'of', 'such', 'maps', 'often', 'restrict', 'the', 'types', 'of', 'the', 'source', 'manifolds', 'for', 'example', 'if', 'a', 'generic', 'map', 'such', 'that', 'the', 'inverse', 'image', 'of', 'a', 'regular', 'value', 'is', 'not', 'nullcobordant', 'then', 'the', 'homology', 'group', 'of', 'its', 'it', 'reeb', 'space', 'which', 'is', 'defined', 'as', 'the', 'space', 'of', 'all', 'the', 'connected', 'components', 'of', 'inverse', 'images', 'of', 'the', 'map', 'and', 'a', 'fundamental', 'tool', 'in', 'the', 'theory', 'of', 'generic', 'smooth', 'maps', 'is', 'known', 'to', 'be', 'nontrivial', 'in', 'this', 'paper', 'we', 'show', 'similar', 'results', 'in', 'new', 'appropriate', 'situations', 'these', 'works', 'are', 'regarded', 'as', 'extensions', 'of', 'works', 'by', 'hiratuka', 'and', 'saeki', 'in', '20134']] | [-0.09810723292712982, 0.06037787841991163, -0.08853925234423234, 0.09814614286252225, -0.04608883090818731, -0.11396860142524999, -0.04521904532672264, 0.37515604943753433, -0.28354231600578017, -0.2529073494629791, 0.1652553211996117, -0.24347342741675676, -0.22873946751396243, 0.2515874806218422, -0.10839999904856086, 0.05003990365075879, 0.038048149172503216, 0.07244772232280901, -0.07866840768524876, -0.22750635023784035, 0.3979040331637057, -0.011763749851916845, 0.22868615404451983, 0.05133096039510117, 0.10780983463359567, -0.02111150800393751, -0.04101742996941679, 0.07154850482609337, -0.11777687261223596, 0.12552690816541703, 0.2904766000001333, 0.11665654184404188, 0.22002474564987307, -0.37252492854514946, -0.24977124544003834, 0.1629544720134268, 0.12611943512904242, 0.05936629993464941, -0.039564439525397926, -0.27241862366119257, 0.12192570246541157, -0.12358896807731631, -0.11967354637140838, -0.09233387592606819, 0.03779689514776692, 0.04951439099475885, -0.22300535723244627, 0.015874336815725726, 0.1080833727422242, 0.07655021607732544, -0.07408232057126812, -0.07388180149719119, -0.050735374075324774, 0.16559669878871108, 0.0465243345968282, 0.08123025111137674, 0.0953258769443402, -0.13655414528895143, -0.12166861057496414, 0.38702983600087465, -0.07842559633919825, -0.24384574016126304, 0.20434561440577872, -0.11078741300063065, -0.18435931595113988, 0.0993140471740984, 0.1336907209020305, 0.1614801459444257, -0.09604541892185807, 0.13621493957560651, -0.12228089968602245, 0.10308170559672782, 0.05745831330020267, 0.0005300394044472621, 0.16617083549857714, 0.11934331943495916, 0.09097696815817752, 0.13148783864722086, -0.03937115949363663, -0.051131943702841035, -0.30307672685370424, -0.17631655774580746, -0.17229364698018448, 0.058748524243912054, -0.09188089745562487, -0.19313742231147793, 0.4000653451308608, 0.08848546464488698, 0.22549408618002556, 0.03510941921178108, 0.2751638256604425, 0.11168274965513354, 0.09520152097639556, 0.035202540926491985, 0.19149039150394787, 0.13426946860451539, 0.02861283144985254, -0.09028909494204876, -0.00908256179223267, 0.0926772995851934] |
1,802.06382 | Space-efficient Feature Maps for String Alignment Kernels | String kernels are attractive data analysis tools for analyzing string data.
Among them, alignment kernels are known for their high prediction accuracies in
string classifications when tested in combination with SVM in various
applications. However, alignment kernels have a crucial drawback in that they
scale poorly due to their quadratic computation complexity in the number of
input strings, which limits large-scale applications in practice. We address
this need by presenting the first approximation for string alignment kernels,
which we call space-efficient feature maps for edit distance with moves
(SFMEDM), by leveraging a metric embedding named edit sensitive parsing (ESP)
and feature maps (FMs) of random Fourier features (RFFs) for large-scale string
analyses. The original FMs for RFFs consume a huge amount of memory
proportional to the dimension d of input vectors and the dimension D of output
vectors, which prohibits its large-scale applications. We present novel
space-efficient feature maps (SFMs) of RFFs for a space reduction from O(dD) of
the original FMs to O(d) of SFMs with a theoretical guarantee with respect to
concentration bounds. We experimentally test SFMEDM on its ability to learn SVM
for large-scale string classifications with various massive string data, and we
demonstrate the superior performance of SFMEDM with respect to prediction
accuracy, scalability and computation efficiency.
| cs.LG cs.AI stat.ML | string kernels are attractive data analysis tools for analyzing string data among them alignment kernels are known for their high prediction accuracies in string classifications when tested in combination with svm in various applications however alignment kernels have a crucial drawback in that they scale poorly due to their quadratic computation complexity in the number of input strings which limits largescale applications in practice we address this need by presenting the first approximation for string alignment kernels which we call spaceefficient feature maps for edit distance with moves sfmedm by leveraging a metric embedding named edit sensitive parsing esp and feature maps fms of random fourier features rffs for largescale string analyses the original fms for rffs consume a huge amount of memory proportional to the dimension d of input vectors and the dimension d of output vectors which prohibits its largescale applications we present novel spaceefficient feature maps sfms of rffs for a space reduction from odd of the original fms to od of sfms with a theoretical guarantee with respect to concentration bounds we experimentally test sfmedm on its ability to learn svm for largescale string classifications with various massive string data and we demonstrate the superior performance of sfmedm with respect to prediction accuracy scalability and computation efficiency | [['string', 'kernels', 'are', 'attractive', 'data', 'analysis', 'tools', 'for', 'analyzing', 'string', 'data', 'among', 'them', 'alignment', 'kernels', 'are', 'known', 'for', 'their', 'high', 'prediction', 'accuracies', 'in', 'string', 'classifications', 'when', 'tested', 'in', 'combination', 'with', 'svm', 'in', 'various', 'applications', 'however', 'alignment', 'kernels', 'have', 'a', 'crucial', 'drawback', 'in', 'that', 'they', 'scale', 'poorly', 'due', 'to', 'their', 'quadratic', 'computation', 'complexity', 'in', 'the', 'number', 'of', 'input', 'strings', 'which', 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1,802.06383 | Efficient Gaussian Process Classification Using Polya-Gamma Data
Augmentation | We propose a scalable stochastic variational approach to GP classification
building on Polya-Gamma data augmentation and inducing points. Unlike former
approaches, we obtain closed-form updates based on natural gradients that lead
to efficient optimization. We evaluate the algorithm on real-world datasets
containing up to 11 million data points and demonstrate that it is up to two
orders of magnitude faster than the state-of-the-art while being competitive in
terms of prediction performance.
| stat.ML cs.LG | we propose a scalable stochastic variational approach to gp classification building on polyagamma data augmentation and inducing points unlike former approaches we obtain closedform updates based on natural gradients that lead to efficient optimization we evaluate the algorithm on realworld datasets containing up to 11 million data points and demonstrate that it is up to two orders of magnitude faster than the stateoftheart while being competitive in terms of prediction performance | [['we', 'propose', 'a', 'scalable', 'stochastic', 'variational', 'approach', 'to', 'gp', 'classification', 'building', 'on', 'polyagamma', 'data', 'augmentation', 'and', 'inducing', 'points', 'unlike', 'former', 'approaches', 'we', 'obtain', 'closedform', 'updates', 'based', 'on', 'natural', 'gradients', 'that', 'lead', 'to', 'efficient', 'optimization', 'we', 'evaluate', 'the', 'algorithm', 'on', 'realworld', 'datasets', 'containing', 'up', 'to', '11', 'million', 'data', 'points', 'and', 'demonstrate', 'that', 'it', 'is', 'up', 'to', 'two', 'orders', 'of', 'magnitude', 'faster', 'than', 'the', 'stateoftheart', 'while', 'being', 'competitive', 'in', 'terms', 'of', 'prediction', 'performance']] | [-0.05104938377691826, -0.058047694823061914, -0.03924709943477327, 0.03652937680279548, -0.09847689771198366, -0.14439571388459332, 0.08283522868738838, 0.43964378798091913, -0.21993264453616782, -0.36851802066912953, 0.10498530588040626, -0.30194715769882774, -0.15034519030276397, 0.2632074732313746, -0.08444317678173244, 0.05080470774637561, 0.13218512191948756, 0.028280266809841276, -0.12691018286712047, -0.34893432343509834, 0.2572930780613244, 0.0015352978436669834, 0.35474957704124316, -0.009117021179482552, 0.1657011175272383, -0.06109183668863999, -0.03113758162362501, 0.0009738237262559189, -0.08799582521015496, 0.20587133782797715, 0.24246357294770193, 0.15574061223568106, 0.27590154166477665, -0.411719906196313, -0.18044856505494722, 0.12568357256306728, 0.1508424132795919, 0.11297639231808307, -0.00305113392967311, -0.2790758209434194, 0.12420989950449848, -0.13616729233558225, -0.01469891701995487, -0.22336347588226463, -0.03265737095506678, -0.02625734359107938, -0.33402184798369106, 0.09579776720681661, 0.03242680957724511, 0.022569144761163583, -0.024825101800289164, -0.17753749799219445, 0.05927929360727766, 0.05418739905974395, 0.046558371610598455, 0.06809163380178138, 0.12915880725600978, -0.11096946316888855, -0.19890814633305434, 0.3611957432020088, -0.10839875690203692, -0.19687673164872635, 0.23938293233317073, -0.021737377828275655, -0.13046901861966495, 0.1450381384454143, 0.2564246756562465, 0.16375383349056816, -0.1484089673260673, 0.007853454265835315, -0.0016126806493586218, 0.14725249344122293, 0.06526871417767145, -0.03457318460339234, 0.08516008163553099, 0.2611021843909378, 0.1495374672436221, 0.1362490978249362, -0.09284688138507936, -0.16135826291070438, -0.1870650324026044, -0.11930464340609984, -0.16217025191011564, 0.007332733192835265, -0.14258869628472792, -0.16357642884405565, 0.3929368239814337, 0.283426666743791, 0.21793248417826605, 0.10691771114533635, 0.3744185618190488, 0.06509721649705734, 0.1049077207170112, 0.15076155734943672, 0.16708283281137407, 0.002438255782488366, 0.0415763294842409, -0.1655933725365608, 0.046961950764558474, 0.05121753730771827] |
1,802.06384 | Spurious Valleys in Two-layer Neural Network Optimization Landscapes | Neural networks provide a rich class of high-dimensional, non-convex
optimization problems. Despite their non-convexity, gradient-descent methods
often successfully optimize these models. This has motivated a recent spur in
research attempting to characterize properties of their loss surface that may
explain such success.
In this paper, we address this phenomenon by studying a key topological
property of the loss: the presence or absence of spurious valleys, defined as
connected components of sub-level sets that do not include a global minimum.
Focusing on a class of two-layer neural networks defined by smooth (but
generally non-linear) activation functions, we identify a notion of intrinsic
dimension and show that it provides necessary and sufficient conditions for the
absence of spurious valleys. More concretely, finite intrinsic dimension
guarantees that for sufficiently overparametrised models no spurious valleys
exist, independently of the data distribution. Conversely, infinite intrinsic
dimension implies that spurious valleys do exist for certain data
distributions, independently of model overparametrisation. Besides these
positive and negative results, we show that, although spurious valleys may
exist in general, they are confined to low risk levels and avoided with high
probability on overparametrised models.
| math.OC cs.LG stat.ML | neural networks provide a rich class of highdimensional nonconvex optimization problems despite their nonconvexity gradientdescent methods often successfully optimize these models this has motivated a recent spur in research attempting to characterize properties of their loss surface that may explain such success in this paper we address this phenomenon by studying a key topological property of the loss the presence or absence of spurious valleys defined as connected components of sublevel sets that do not include a global minimum focusing on a class of twolayer neural networks defined by smooth but generally nonlinear activation functions we identify a notion of intrinsic dimension and show that it provides necessary and sufficient conditions for the absence of spurious valleys more concretely finite intrinsic dimension guarantees that for sufficiently overparametrised models no spurious valleys exist independently of the data distribution conversely infinite intrinsic dimension implies that spurious valleys do exist for certain data distributions independently of model overparametrisation besides these positive and negative results we show that although spurious valleys may exist in general they are confined to low risk levels and avoided with high probability on overparametrised models | [['neural', 'networks', 'provide', 'a', 'rich', 'class', 'of', 'highdimensional', 'nonconvex', 'optimization', 'problems', 'despite', 'their', 'nonconvexity', 'gradientdescent', 'methods', 'often', 'successfully', 'optimize', 'these', 'models', 'this', 'has', 'motivated', 'a', 'recent', 'spur', 'in', 'research', 'attempting', 'to', 'characterize', 'properties', 'of', 'their', 'loss', 'surface', 'that', 'may', 'explain', 'such', 'success', 'in', 'this', 'paper', 'we', 'address', 'this', 'phenomenon', 'by', 'studying', 'a', 'key', 'topological', 'property', 'of', 'the', 'loss', 'the', 'presence', 'or', 'absence', 'of', 'spurious', 'valleys', 'defined', 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1,802.06385 | Connection between diphoton and triboson channels in new physics
searches | Diphoton channel provides a clean signature in searches for new physics. In
this paper, we discuss a connection between the diphoton channel
($\gamma\gamma$) and triboson channels ($Z\gamma\gamma$, $ZZ\gamma$,
$WW\gamma$) imposed by the $SU(2)_{L}\times U(1)_{Y}$ symmetry of the Standard
Model (SM) in certain classes of models. To illustrate this idea we choose a
simple model that has all these channels. In this model, the same physics can
give rise to $\gamma+$MET instead of $\gamma\gamma$ and 2 bosons plus missing
energy instead of 3-boson channels. We analyze existing constraints and
previous searches and show that channels $WW\gamma$ and especially
$Z\gamma+$MET have a potential to discover new physics at the LHC.
| hep-ph hep-ex | diphoton channel provides a clean signature in searches for new physics in this paper we discuss a connection between the diphoton channel gammagamma and triboson channels zgammagamma zzgamma wwgamma imposed by the su2_ltimes u1_y symmetry of the standard model sm in certain classes of models to illustrate this idea we choose a simple model that has all these channels in this model the same physics can give rise to gammamet instead of gammagamma and 2 bosons plus missing energy instead of 3boson channels we analyze existing constraints and previous searches and show that channels wwgamma and especially zgammamet have a potential to discover new physics at the lhc | [['diphoton', 'channel', 'provides', 'a', 'clean', 'signature', 'in', 'searches', 'for', 'new', 'physics', 'in', 'this', 'paper', 'we', 'discuss', 'a', 'connection', 'between', 'the', 'diphoton', 'channel', 'gammagamma', 'and', 'triboson', 'channels', 'zgammagamma', 'zzgamma', 'wwgamma', 'imposed', 'by', 'the', 'su2_ltimes', 'u1_y', 'symmetry', 'of', 'the', 'standard', 'model', 'sm', 'in', 'certain', 'classes', 'of', 'models', 'to', 'illustrate', 'this', 'idea', 'we', 'choose', 'a', 'simple', 'model', 'that', 'has', 'all', 'these', 'channels', 'in', 'this', 'model', 'the', 'same', 'physics', 'can', 'give', 'rise', 'to', 'gammamet', 'instead', 'of', 'gammagamma', 'and', '2', 'bosons', 'plus', 'missing', 'energy', 'instead', 'of', '3boson', 'channels', 'we', 'analyze', 'existing', 'constraints', 'and', 'previous', 'searches', 'and', 'show', 'that', 'channels', 'wwgamma', 'and', 'especially', 'zgammamet', 'have', 'a', 'potential', 'to', 'discover', 'new', 'physics', 'at', 'the', 'lhc']] | [-0.11806909259231317, 0.17638909904552358, -0.07861781811252946, 0.14534837741160855, -0.09117708870298451, -0.25048397750194584, 0.04713424305941555, 0.3216793228472982, -0.250801008975222, -0.30310181285299004, 0.021861376178761324, -0.2696737960424452, -0.09935029557506952, 0.11995918701314146, 0.013045582618741763, 0.04560321300689663, 0.06275626989524989, -0.0007685549911998567, -0.05654298948079702, -0.24705319684885796, 0.26634728884590525, 0.0645537336489984, 0.22068697124542225, 0.11770005448765698, 0.06118985769294557, 0.047545176130231646, -0.05925101713482512, -0.12336543441883155, -0.15735462963916472, 0.08543128668374958, 0.19676977211233213, 0.08641045852786018, 0.12245483477378176, -0.3711353141104891, -0.17924724603958783, 0.17771725022189674, 0.15207193736873922, 0.12006736620595412, -0.08461077003074544, -0.33114038985666067, 0.11087200022524311, -0.24002446987710538, -0.042481595311324956, -0.04735510616696307, -0.058593205659694614, -0.10996930322476796, -0.33506549291667487, 0.05381392868058313, 0.01546764269116379, 0.016808588996008483, 0.004915633487204711, -0.16072769638239628, -0.011442756395609606, 0.030458469919505574, 0.113514201149034, -0.002233652247204667, 0.10504712837282568, -0.2241246352970068, -0.2269157477033635, 0.36372150017746857, -0.08162898123929543, -0.19515453640903746, 0.24595266863637205, -0.15220820292653073, -0.19067120159895803, 0.10577189820995998, 0.2682532797124059, -0.000249385576517809, -0.22511674285023694, 0.19159029013244436, -0.0551913484221413, 0.12018888963475113, -0.006675312144770509, 0.11149850846933466, 0.2049503147247292, 0.18416034936727513, 0.022380748109537222, 0.09761674060885395, -0.11096515473909677, -0.03718049540406182, -0.4264654590969994, -0.14517398623838312, -0.05258006199950441, 0.031701315487069746, -0.016315685371574504, -0.05614868362345511, 0.41746148561083135, 0.18160843909052865, 0.27779558732928267, 0.035943693679846116, 0.28593793349074464, 0.08083298773105656, 0.08034156528079793, 0.031598526234960275, 0.303611166251912, 0.1296244991167138, 0.09686769695863837, -0.15556262953295594, 0.018344457154827458, 0.04321645359020858] |
1,802.06386 | How local in time is the no-arbitrage property under capital gains taxes
? | In frictionless financial markets, no-arbitrage is a local property in time.
This means that a discrete time model is arbitrage-free if and only if there
does not exist a one-period-arbitrage. With capital gains taxes, this
equivalence fails. For a model with a linear tax and one non-shortable risky
stock, we introduce the concept of robust local no-arbitrage (RLNA) as the
weakest local condition which guarantees dynamic no-arbitrage. Under a sharp
dichotomy condition, we prove (RLNA). Since no-one-period-arbitrage is
necessary for no-arbitrage, the latter is sandwiched between two local
conditions, which allows us to estimate its non-locality.
Furthermore, we construct a stock price process such that two long positions
in the same stock hedge each other. This puzzling phenomenon that cannot occur
in arbitrage-free frictionless markets (or markets with proportional
transaction costs) is used to show that no-arbitrage alone does not imply the
existence of an equivalent separating measure if the probability space is
infinite.
Finally, we show that the model with a linear tax on capital gains can be
written as a model with proportional transaction costs by introducing several
fictitious securities.
| q-fin.PM math.PR q-fin.MF | in frictionless financial markets noarbitrage is a local property in time this means that a discrete time model is arbitragefree if and only if there does not exist a oneperiodarbitrage with capital gains taxes this equivalence fails for a model with a linear tax and one nonshortable risky stock we introduce the concept of robust local noarbitrage rlna as the weakest local condition which guarantees dynamic noarbitrage under a sharp dichotomy condition we prove rlna since nooneperiodarbitrage is necessary for noarbitrage the latter is sandwiched between two local conditions which allows us to estimate its nonlocality furthermore we construct a stock price process such that two long positions in the same stock hedge each other this puzzling phenomenon that cannot occur in arbitragefree frictionless markets or markets with proportional transaction costs is used to show that noarbitrage alone does not imply the existence of an equivalent separating measure if the probability space is infinite finally we show that the model with a linear tax on capital gains can be written as a model with proportional transaction costs by introducing several fictitious securities | [['in', 'frictionless', 'financial', 'markets', 'noarbitrage', 'is', 'a', 'local', 'property', 'in', 'time', 'this', 'means', 'that', 'a', 'discrete', 'time', 'model', 'is', 'arbitragefree', 'if', 'and', 'only', 'if', 'there', 'does', 'not', 'exist', 'a', 'oneperiodarbitrage', 'with', 'capital', 'gains', 'taxes', 'this', 'equivalence', 'fails', 'for', 'a', 'model', 'with', 'a', 'linear', 'tax', 'and', 'one', 'nonshortable', 'risky', 'stock', 'we', 'introduce', 'the', 'concept', 'of', 'robust', 'local', 'noarbitrage', 'rlna', 'as', 'the', 'weakest', 'local', 'condition', 'which', 'guarantees', 'dynamic', 'noarbitrage', 'under', 'a', 'sharp', 'dichotomy', 'condition', 'we', 'prove', 'rlna', 'since', 'nooneperiodarbitrage', 'is', 'necessary', 'for', 'noarbitrage', 'the', 'latter', 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1,802.06387 | Quantifying tolerance of a nonlocal multi-qudit state to any local noise | We present a general approach for quantifying tolerance of a nonlocal
N-partite state to any local noise under different classes of quantum
correlation scenarios with arbitrary numbers of settings and outcomes at each
site. This allows us to derive new precise bounds in d and N on noise
tolerances for: (i) an arbitrary nonlocal N-qudit state; (ii) the N-qudit
Greenberger-Horne-Zeilinger (GHZ) state; (iii) the N-qubit W state and the
N-qubit Dicke states, and to analyse asymptotics of these precise bounds for
large N and d.
| quant-ph math-ph math.MP | we present a general approach for quantifying tolerance of a nonlocal npartite state to any local noise under different classes of quantum correlation scenarios with arbitrary numbers of settings and outcomes at each site this allows us to derive new precise bounds in d and n on noise tolerances for i an arbitrary nonlocal nqudit state ii the nqudit greenbergerhornezeilinger ghz state iii the nqubit w state and the nqubit dicke states and to analyse asymptotics of these precise bounds for large n and d | [['we', 'present', 'a', 'general', 'approach', 'for', 'quantifying', 'tolerance', 'of', 'a', 'nonlocal', 'npartite', 'state', 'to', 'any', 'local', 'noise', 'under', 'different', 'classes', 'of', 'quantum', 'correlation', 'scenarios', 'with', 'arbitrary', 'numbers', 'of', 'settings', 'and', 'outcomes', 'at', 'each', 'site', 'this', 'allows', 'us', 'to', 'derive', 'new', 'precise', 'bounds', 'in', 'd', 'and', 'n', 'on', 'noise', 'tolerances', 'for', 'i', 'an', 'arbitrary', 'nonlocal', 'nqudit', 'state', 'ii', 'the', 'nqudit', 'greenbergerhornezeilinger', 'ghz', 'state', 'iii', 'the', 'nqubit', 'w', 'state', 'and', 'the', 'nqubit', 'dicke', 'states', 'and', 'to', 'analyse', 'asymptotics', 'of', 'these', 'precise', 'bounds', 'for', 'large', 'n', 'and', 'd']] | [-0.14330450455274651, 0.16258809442292926, -0.034894129924257014, 0.05952066162135452, 0.013317694361595547, -0.2788806805277572, 0.10239216108422945, 0.3046087637324544, -0.17940594712546204, -0.31767051568364396, 0.0532526958062697, -0.22041661800998127, -0.029664130203480667, 0.14883750492213843, -0.030888527544105752, 0.10801760781939854, 0.055960624522584324, 0.025064214154639664, -0.08587249321863055, -0.24677359562586335, 0.3577797718346119, -0.011554312811452238, 0.2733628752915298, -0.0026178578606477995, 0.10383924084770328, 0.025551865025259118, 0.016546728330499985, -0.005174060899983434, -0.15885148462565507, 0.10703466956654345, 0.2738982822848758, 0.1648347203838913, 0.22632048119078665, -0.39405304097077426, -0.13387944225276657, 0.1610851491417955, 0.04542368907919701, 0.21817092023351614, 0.06374387564822374, -0.38533884396447854, 0.022383224076646217, -0.18188261212233234, -0.14066717234604498, -0.10164211454856045, 0.10391505387995173, -0.04519001708968597, -0.37653051782399416, 0.08742060678846696, 0.05585960467236445, 0.01593258324873579, -0.025553125590222943, -0.13580846315496328, 0.04740051926004098, 0.13212489404660813, -0.13555088275495697, -0.04739121092373834, 0.07323201919412788, -0.11728699151700472, -0.1715657046496156, 0.2962271913064315, -0.06962810698896646, -0.2291806114864919, 0.1889794823987519, -0.16096468980369322, -0.16433139265487517, 0.047533653084846104, 0.17201828252085868, 0.09774752442779787, -0.10373553600819672, 0.09078569760861094, -0.014414992358754663, 0.19048287604442415, 0.05154048285501845, 0.17442174759652357, 0.09087502491824767, 0.027871545152190855, 0.13805968577370925, 0.20677629082518464, -0.08880435241221943, -0.06950658342855819, -0.3743434688185944, -0.19698857387856525, -0.18733592846102137, 0.13340368175550418, -0.13761834714695237, -0.11977890599245096, 0.4048823903150418, 0.09591107392026221, 0.15337511271457463, 0.07663020844406941, 0.20719245782888987, 0.0760464980650474, -0.05324382188675158, 0.11002023053245948, 0.16772631178883946, 0.17767247734591365, 0.038635094896616304, -0.25765523336389484, 0.09032126372296582, 0.0074212663587840165] |
1,802.06388 | On energy stable discontinuous Galerkin spectral element approximations
of the perfectly matched layer for the wave equation | We develop a provably energy stable discontinuous Galerkin spectral element
method (DGSEM) approximation of the perfectly matched layer (PML) for the three
and two space dimensional (3D and 2D) linear acoustic wave equations, in first
order form, subject to well-posed linear boundary conditions. First, using the
well-known complex coordinate stretching, we derive an efficient un-split modal
PML for the 3D acoustic wave equation. Second, we prove asymptotic stability of
the continuous PML by deriving energy estimates in the Laplace space, for the
3D PML in a heterogeneous acoustic medium, assuming piece-wise constant PML
damping. Third, we develop a DGSEM for the wave equation using physically
motivated numerical flux, with penalty weights, which are compatible with all
well-posed, internal and external, boundary conditions. When the PML damping
vanishes, by construction, our choice of penalty parameters yield an upwind
scheme and a discrete energy estimate analogous to the continuous energy
estimate. Fourth, to ensure numerical stability when PML damping is present, it
is necessary to systematically extend the numerical numerical fluxes, and the
inter-element and boundary procedures, to the PML auxiliary differential
equations. This is critical for deriving discrete energy estimates analogous to
the continuous energy estimates. Finally, we propose a procedure to compute PML
damping coefficients such that the PML error converges to zero, at the optimal
convergence rate of the underlying numerical method. Numerical experiments are
presented in 2D and 3D corroborating the theoretical results.
| math.NA | we develop a provably energy stable discontinuous galerkin spectral element method dgsem approximation of the perfectly matched layer pml for the three and two space dimensional 3d and 2d linear acoustic wave equations in first order form subject to wellposed linear boundary conditions first using the wellknown complex coordinate stretching we derive an efficient unsplit modal pml for the 3d acoustic wave equation second we prove asymptotic stability of the continuous pml by deriving energy estimates in the laplace space for the 3d pml in a heterogeneous acoustic medium assuming piecewise constant pml damping third we develop a dgsem for the wave equation using physically motivated numerical flux with penalty weights which are compatible with all wellposed internal and external boundary conditions when the pml damping vanishes by construction our choice of penalty parameters yield an upwind scheme and a discrete energy estimate analogous to the continuous energy estimate fourth to ensure numerical stability when pml damping is present it is necessary to systematically extend the numerical numerical fluxes and the interelement and boundary procedures to the pml auxiliary differential equations this is critical for deriving discrete energy estimates analogous to the continuous energy estimates finally we propose a procedure to compute pml damping coefficients such that the pml error converges to zero at the optimal convergence rate of the underlying numerical method numerical experiments are presented in 2d and 3d corroborating the theoretical results | [['we', 'develop', 'a', 'provably', 'energy', 'stable', 'discontinuous', 'galerkin', 'spectral', 'element', 'method', 'dgsem', 'approximation', 'of', 'the', 'perfectly', 'matched', 'layer', 'pml', 'for', 'the', 'three', 'and', 'two', 'space', 'dimensional', '3d', 'and', '2d', 'linear', 'acoustic', 'wave', 'equations', 'in', 'first', 'order', 'form', 'subject', 'to', 'wellposed', 'linear', 'boundary', 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1,802.06389 | Malliavin calculus for the stochastic Cahn-Hilliard / Allen Cahn
equation with unbounded noise diffusion | The stochastic partial differential equation analyzed in this work, is
motivated by a simplified mesoscopic physical model for phase separation. It
describes pattern formation due to adsorption and desorption mechanisms
involved in surface processes, in the presence of a stochastic driving force.
This equation is a combination of Cahn-Hilliard and Allen-Cahn type operators
with a multiplicative, white, space-time noise of unbounded diffusion. We apply
Malliavin calculus, in order to investigate the existence of a density for the
stochastic solution $u$. In dimension one, according to the regularity result
in \cite{AKM}, $u$ admits continuous paths a.s. Using this property, and
inspired by a method proposed in \cite{CW1}, we construct a modified
approximating sequence for $u$, which properly treats the new second order
Allen-Cahn operator. Under a localization argument, we prove that the Malliavin
derivative of $u$ exists locally, and that the law of $u$ is absolutely
continuous, establishing thus that a density exists.
| math.PR | the stochastic partial differential equation analyzed in this work is motivated by a simplified mesoscopic physical model for phase separation it describes pattern formation due to adsorption and desorption mechanisms involved in surface processes in the presence of a stochastic driving force this equation is a combination of cahnhilliard and allencahn type operators with a multiplicative white spacetime noise of unbounded diffusion we apply malliavin calculus in order to investigate the existence of a density for the stochastic solution u in dimension one according to the regularity result in citeakm u admits continuous paths as using this property and inspired by a method proposed in citecw1 we construct a modified approximating sequence for u which properly treats the new second order allencahn operator under a localization argument we prove that the malliavin derivative of u exists locally and that the law of u is absolutely continuous establishing thus that a density exists | [['the', 'stochastic', 'partial', 'differential', 'equation', 'analyzed', 'in', 'this', 'work', 'is', 'motivated', 'by', 'a', 'simplified', 'mesoscopic', 'physical', 'model', 'for', 'phase', 'separation', 'it', 'describes', 'pattern', 'formation', 'due', 'to', 'adsorption', 'and', 'desorption', 'mechanisms', 'involved', 'in', 'surface', 'processes', 'in', 'the', 'presence', 'of', 'a', 'stochastic', 'driving', 'force', 'this', 'equation', 'is', 'a', 'combination', 'of', 'cahnhilliard', 'and', 'allencahn', 'type', 'operators', 'with', 'a', 'multiplicative', 'white', 'spacetime', 'noise', 'of', 'unbounded', 'diffusion', 'we', 'apply', 'malliavin', 'calculus', 'in', 'order', 'to', 'investigate', 'the', 'existence', 'of', 'a', 'density', 'for', 'the', 'stochastic', 'solution', 'u', 'in', 'dimension', 'one', 'according', 'to', 'the', 'regularity', 'result', 'in', 'citeakm', 'u', 'admits', 'continuous', 'paths', 'as', 'using', 'this', 'property', 'and', 'inspired', 'by', 'a', 'method', 'proposed', 'in', 'citecw1', 'we', 'construct', 'a', 'modified', 'approximating', 'sequence', 'for', 'u', 'which', 'properly', 'treats', 'the', 'new', 'second', 'order', 'allencahn', 'operator', 'under', 'a', 'localization', 'argument', 'we', 'prove', 'that', 'the', 'malliavin', 'derivative', 'of', 'u', 'exists', 'locally', 'and', 'that', 'the', 'law', 'of', 'u', 'is', 'absolutely', 'continuous', 'establishing', 'thus', 'that', 'a', 'density', 'exists']] | [-0.13827983270875727, 0.07942183349213705, -0.09411133327043388, 0.06527433804828452, -0.06720731828503607, -0.12882934601064647, 0.046782614306287704, 0.30770223534092406, -0.3312622841959511, -0.21811699757771874, 0.0819714223566644, -0.25976507320679376, -0.18350995893880034, 0.12615886745536514, -0.09261650557549583, 0.04057194792822817, 0.013969574783564798, 0.006524553068756243, -0.04285197717211647, -0.1821001286013977, 0.3645376343155663, -0.05003561945755454, 0.1998751327235079, 0.040096932739583736, 0.1517570153393764, 0.001846678875732106, -0.027613097166531528, 0.0028189950053937062, -0.16671929398272303, 0.09739981584454462, 0.21708771408017452, 0.02760318291700439, 0.32258759569438383, -0.4089295012839385, -0.27062011106766215, 0.11967905513350142, 0.09407541350656597, 0.07801859268520817, -0.06975384241444928, -0.2745866168302712, 0.08317389312070726, -0.14319068863324896, -0.19341612525210278, -0.06514668810976953, 0.049366353109358684, 0.057465242888063, -0.3277181471938526, 0.12398721228372182, 0.11988542547267522, -0.005288246133987675, -0.09865616077236486, -0.0483205474200751, -0.03046234284484426, 0.04435106928981471, 0.01866793404996321, 0.05824676300984937, 0.07854370408019187, -0.08679452884035642, -0.0878723405096495, 0.3454675266695739, -0.14760601570650886, -0.26720166426315434, 0.1571635017109825, -0.1343226838295675, -0.13024697103075042, 0.12112627079192037, 0.12378830786806759, 0.1481078772180477, -0.19898464704943908, 0.1646889479790771, -0.0038284566453873916, 0.15722133081239828, 0.09440806333518384, -0.007957452790972017, 0.08791342120777988, 0.19554292173155688, 0.14930557241256268, 0.1221520606218683, -0.042318470822338826, -0.1396293988195402, -0.340238092053953, -0.15558824294696974, -0.1704441788560088, 0.08786634102291027, -0.08808908691542648, -0.2033082798033928, 0.36152073056652945, 0.1416770080397436, 0.17118102902336824, 0.04580899487813898, 0.25131429015930173, 0.19754410020017146, -0.014740829485536412, 0.055833518505096436, 0.14695550528021886, 0.17588447684588662, 0.12496962413709882, -0.2236745616173239, 0.0820431732125457, 0.17872700758204357] |
1,802.0639 | Current-density implementation for calculating flexoelectric
coefficients | The flexoelectric effect refers to polarization induced in an insulator when
a strain gradient is applied. We have developed a first-principles methodology
based on density-functional perturbation theory to calculate the elements of
the bulk, clamped-ion flexoelectric tensor. In order to determine the
transverse and shear components directly from a unit cell calculation, we
calculate the current density induced by the adiabatic atomic displacements of
a long-wavelength acoustic phonon. Previous implementations based on the
charge-density response required supercells to capture these components. Our
density-functional-theory implementation requires the development of an
expression for the current density that is valid for the case of nonlocal
pseudopotentials, and long-wavelength phonon perturbations. We benchmark our
methodology on simple systems of isolated noble gas atoms, and apply it to
calculate the clamped-ion flexoelectric constants for a variety of
technologically important cubic oxides. We also discuss some technical issues
that are associated with the definition of current density in a nonlocal
pseudopotential context, and their relevance to the calculation of macroscopic
response properties of crystals.
| cond-mat.mtrl-sci cond-mat.mes-hall | the flexoelectric effect refers to polarization induced in an insulator when a strain gradient is applied we have developed a firstprinciples methodology based on densityfunctional perturbation theory to calculate the elements of the bulk clampedion flexoelectric tensor in order to determine the transverse and shear components directly from a unit cell calculation we calculate the current density induced by the adiabatic atomic displacements of a longwavelength acoustic phonon previous implementations based on the chargedensity response required supercells to capture these components our densityfunctionaltheory implementation requires the development of an expression for the current density that is valid for the case of nonlocal pseudopotentials and longwavelength phonon perturbations we benchmark our methodology on simple systems of isolated noble gas atoms and apply it to calculate the clampedion flexoelectric constants for a variety of technologically important cubic oxides we also discuss some technical issues that are associated with the definition of current density in a nonlocal pseudopotential context and their relevance to the calculation of macroscopic response properties of crystals | [['the', 'flexoelectric', 'effect', 'refers', 'to', 'polarization', 'induced', 'in', 'an', 'insulator', 'when', 'a', 'strain', 'gradient', 'is', 'applied', 'we', 'have', 'developed', 'a', 'firstprinciples', 'methodology', 'based', 'on', 'densityfunctional', 'perturbation', 'theory', 'to', 'calculate', 'the', 'elements', 'of', 'the', 'bulk', 'clampedion', 'flexoelectric', 'tensor', 'in', 'order', 'to', 'determine', 'the', 'transverse', 'and', 'shear', 'components', 'directly', 'from', 'a', 'unit', 'cell', 'calculation', 'we', 'calculate', 'the', 'current', 'density', 'induced', 'by', 'the', 'adiabatic', 'atomic', 'displacements', 'of', 'a', 'longwavelength', 'acoustic', 'phonon', 'previous', 'implementations', 'based', 'on', 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1,802.06391 | Orbits in elementary, power-law galaxy bars: 1. Occurence and role of
single loops | Orbits in galaxy bars are generally complex, but simple closed loop orbits
play an important role in our conceptual understanding of bars. Such orbits are
found in some well-studied potentials, provide a simple model of the bar in
themselves, and may generate complex orbit families. The precessing, power
ellipse (p-ellipse) orbit approximation provides accurate analytic orbit orbits
in symmetric galaxy potentials. It remains useful for finding and fitting
simple loop orbits in the frame of a rotating bar with bar-like and symmetric
power-law potentials. Second order perturbation theory yields two or fewer
simple loop solutions in these potentials. Numerical integrations in the
parameter space neighborhood of perturbation solutions reveal zero or one ac-
tual loops in a range of such potentials with rising rotation curves. These
loops are embedded in a small parameter region of similar, but librating
orbits, which have a subharmonic frequency superimposed on the basic loop.
These loops and their librat- ing companions support annular bars. Solid bars
can be produced in more complex potentials, as shown by an example with
power-law indices varying with radius. The power-law potentials can be viewed
as the elementary constituents of more complex potentials. Numerical
integrations also reveal interesting classes of orbits with multiple loops. In
two-dimensional, self-gravitating bars, with power-law potentials, single loop
orbits are very rare. This result suggests that gas bars or oval distortions
are unlikely to be long-lived, and that complex orbits or three-dimensional
structure must support self-gravitating stellar bars.
| astro-ph.GA | orbits in galaxy bars are generally complex but simple closed loop orbits play an important role in our conceptual understanding of bars such orbits are found in some wellstudied potentials provide a simple model of the bar in themselves and may generate complex orbit families the precessing power ellipse pellipse orbit approximation provides accurate analytic orbit orbits in symmetric galaxy potentials it remains useful for finding and fitting simple loop orbits in the frame of a rotating bar with barlike and symmetric powerlaw potentials second order perturbation theory yields two or fewer simple loop solutions in these potentials numerical integrations in the parameter space neighborhood of perturbation solutions reveal zero or one ac tual loops in a range of such potentials with rising rotation curves these loops are embedded in a small parameter region of similar but librating orbits which have a subharmonic frequency superimposed on the basic loop these loops and their librat ing companions support annular bars solid bars can be produced in more complex potentials as shown by an example with powerlaw indices varying with radius the powerlaw potentials can be viewed as the elementary constituents of more complex potentials numerical integrations also reveal interesting classes of orbits with multiple loops in twodimensional selfgravitating bars with powerlaw potentials single loop orbits are very rare this result suggests that gas bars or oval distortions are unlikely to be longlived and that complex orbits or threedimensional structure must support selfgravitating stellar bars | [['orbits', 'in', 'galaxy', 'bars', 'are', 'generally', 'complex', 'but', 'simple', 'closed', 'loop', 'orbits', 'play', 'an', 'important', 'role', 'in', 'our', 'conceptual', 'understanding', 'of', 'bars', 'such', 'orbits', 'are', 'found', 'in', 'some', 'wellstudied', 'potentials', 'provide', 'a', 'simple', 'model', 'of', 'the', 'bar', 'in', 'themselves', 'and', 'may', 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1,802.06392 | Center-of-Mass-Based Grasp Pose Adaptation Using 3D Range and
Force/Torque Sensing | Lifting objects, whose mass may produce high wrist torques that exceed the
hardware strength limits, could lead to unstable grasps or serious robot
damage. This work introduces a new Center-of-Mass (CoM)-based grasp pose
adaptation method, for picking up objects using a combination of exteroceptive
3D perception and proprioceptive force/torque sensor feedback. The method works
in two iterative stages to provide reliable and wrist torque efficient grasps.
Initially, a geometric object CoM is estimated from the input range data. In
the first stage, a set of hand-size handle grasps are localized on the object
and the closest to its CoM is selected for grasping. In the second stage, the
object is lifted using a single arm, while the force and torque readings from
the sensor on the wrist are monitored. Based on these readings, a displacement
to the new CoM estimation is calculated. The object is released and the process
is repeated until the wrist torque effort is minimized. The advantage of our
method is the blending of both exteroceptive (3D range) and proprioceptive
(force/torque) sensing for finding the grasp location that minimizes the wrist
effort, potentially improving the reliability of the grasping and the
subsequent manipulation task. We experimentally validate the proposed method by
executing a number of tests on a set of objects that include handles, using the
humanoid robot WALK-MAN.
| cs.RO | lifting objects whose mass may produce high wrist torques that exceed the hardware strength limits could lead to unstable grasps or serious robot damage this work introduces a new centerofmass combased grasp pose adaptation method for picking up objects using a combination of exteroceptive 3d perception and proprioceptive forcetorque sensor feedback the method works in two iterative stages to provide reliable and wrist torque efficient grasps initially a geometric object com is estimated from the input range data in the first stage a set of handsize handle grasps are localized on the object and the closest to its com is selected for grasping in the second stage the object is lifted using a single arm while the force and torque readings from the sensor on the wrist are monitored based on these readings a displacement to the new com estimation is calculated the object is released and the process is repeated until the wrist torque effort is minimized the advantage of our method is the blending of both exteroceptive 3d range and proprioceptive forcetorque sensing for finding the grasp location that minimizes the wrist effort potentially improving the reliability of the grasping and the subsequent manipulation task we experimentally validate the proposed method by executing a number of tests on a set of objects that include handles using the humanoid robot walkman | [['lifting', 'objects', 'whose', 'mass', 'may', 'produce', 'high', 'wrist', 'torques', 'that', 'exceed', 'the', 'hardware', 'strength', 'limits', 'could', 'lead', 'to', 'unstable', 'grasps', 'or', 'serious', 'robot', 'damage', 'this', 'work', 'introduces', 'a', 'new', 'centerofmass', 'combased', 'grasp', 'pose', 'adaptation', 'method', 'for', 'picking', 'up', 'objects', 'using', 'a', 'combination', 'of', 'exteroceptive', '3d', 'perception', 'and', 'proprioceptive', 'forcetorque', 'sensor', 'feedback', 'the', 'method', 'works', 'in', 'two', 'iterative', 'stages', 'to', 'provide', 'reliable', 'and', 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1,802.06393 | Primordial black holes and uncertainties in the choice of the window
function | Primordial black holes (PBHs) can be produced by the perturbations that exit
the horizon during inflationary phase. While inflation models predict the power
spectrum of the perturbations in Fourier space, the PBH abundance depends on
the probability distribution function (PDF) of density perturbations in real
space. In order to estimate the PBH abundance in a given inflation model, we
must relate the power spectrum in Fourier space to the PDF in real space by
coarse-graining the perturbations with a window function. However, there are
uncertainties on what window function should be used, which could change the
relation between the PBH abundance and the power spectrum. This is particularly
important in considering PBHs with mass $30 M_\odot$ that account for the LIGO
events because the required power spectrum is severely constrained by the
observations. In this paper, we investigate how large influence the
uncertainties on the choice of a window function have over the power spectrum
required for LIGO PBHs. As a result, it is found that the uncertainties
significantly affect the prediction for the stochastic gravitational waves
(GWs) induced by the second order effect of the perturbations. In particular,
the pulsar timing array constraints on the produced GWs could disappear for the
real-space top-hat window function.
| astro-ph.CO hep-ph | primordial black holes pbhs can be produced by the perturbations that exit the horizon during inflationary phase while inflation models predict the power spectrum of the perturbations in fourier space the pbh abundance depends on the probability distribution function pdf of density perturbations in real space in order to estimate the pbh abundance in a given inflation model we must relate the power spectrum in fourier space to the pdf in real space by coarsegraining the perturbations with a window function however there are uncertainties on what window function should be used which could change the relation between the pbh abundance and the power spectrum this is particularly important in considering pbhs with mass 30 m_odot that account for the ligo events because the required power spectrum is severely constrained by the observations in this paper we investigate how large influence the uncertainties on the choice of a window function have over the power spectrum required for ligo pbhs as a result it is found that the uncertainties significantly affect the prediction for the stochastic gravitational waves gws induced by the second order effect of the perturbations in particular the pulsar timing array constraints on the produced gws could disappear for the realspace tophat window function | [['primordial', 'black', 'holes', 'pbhs', 'can', 'be', 'produced', 'by', 'the', 'perturbations', 'that', 'exit', 'the', 'horizon', 'during', 'inflationary', 'phase', 'while', 'inflation', 'models', 'predict', 'the', 'power', 'spectrum', 'of', 'the', 'perturbations', 'in', 'fourier', 'space', 'the', 'pbh', 'abundance', 'depends', 'on', 'the', 'probability', 'distribution', 'function', 'pdf', 'of', 'density', 'perturbations', 'in', 'real', 'space', 'in', 'order', 'to', 'estimate', 'the', 'pbh', 'abundance', 'in', 'a', 'given', 'inflation', 'model', 'we', 'must', 'relate', 'the', 'power', 'spectrum', 'in', 'fourier', 'space', 'to', 'the', 'pdf', 'in', 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1,802.06394 | Training Big Random Forests with Little Resources | Without access to large compute clusters, building random forests on large
datasets is still a challenging problem. This is, in particular, the case if
fully-grown trees are desired. We propose a simple yet effective framework that
allows to efficiently construct ensembles of huge trees for hundreds of
millions or even billions of training instances using a cheap desktop computer
with commodity hardware. The basic idea is to consider a multi-level
construction scheme, which builds top trees for small random subsets of the
available data and which subsequently distributes all training instances to the
top trees' leaves for further processing. While being conceptually simple, the
overall efficiency crucially depends on the particular implementation of the
different phases. The practical merits of our approach are demonstrated using
dense datasets with hundreds of millions of training instances.
| cs.LG stat.ML | without access to large compute clusters building random forests on large datasets is still a challenging problem this is in particular the case if fullygrown trees are desired we propose a simple yet effective framework that allows to efficiently construct ensembles of huge trees for hundreds of millions or even billions of training instances using a cheap desktop computer with commodity hardware the basic idea is to consider a multilevel construction scheme which builds top trees for small random subsets of the available data and which subsequently distributes all training instances to the top trees leaves for further processing while being conceptually simple the overall efficiency crucially depends on the particular implementation of the different phases the practical merits of our approach are demonstrated using dense datasets with hundreds of millions of training instances | [['without', 'access', 'to', 'large', 'compute', 'clusters', 'building', 'random', 'forests', 'on', 'large', 'datasets', 'is', 'still', 'a', 'challenging', 'problem', 'this', 'is', 'in', 'particular', 'the', 'case', 'if', 'fullygrown', 'trees', 'are', 'desired', 'we', 'propose', 'a', 'simple', 'yet', 'effective', 'framework', 'that', 'allows', 'to', 'efficiently', 'construct', 'ensembles', 'of', 'huge', 'trees', 'for', 'hundreds', 'of', 'millions', 'or', 'even', 'billions', 'of', 'training', 'instances', 'using', 'a', 'cheap', 'desktop', 'computer', 'with', 'commodity', 'hardware', 'the', 'basic', 'idea', 'is', 'to', 'consider', 'a', 'multilevel', 'construction', 'scheme', 'which', 'builds', 'top', 'trees', 'for', 'small', 'random', 'subsets', 'of', 'the', 'available', 'data', 'and', 'which', 'subsequently', 'distributes', 'all', 'training', 'instances', 'to', 'the', 'top', 'trees', 'leaves', 'for', 'further', 'processing', 'while', 'being', 'conceptually', 'simple', 'the', 'overall', 'efficiency', 'crucially', 'depends', 'on', 'the', 'particular', 'implementation', 'of', 'the', 'different', 'phases', 'the', 'practical', 'merits', 'of', 'our', 'approach', 'are', 'demonstrated', 'using', 'dense', 'datasets', 'with', 'hundreds', 'of', 'millions', 'of', 'training', 'instances']] | [-0.10271035896306087, 0.10050490284968812, -0.01930097860802329, 0.03874645263649859, -0.12555947495253295, -0.15769411993556118, 0.09159257118345092, 0.3888004962494947, -0.27780034209608584, -0.36461347873721806, 0.11645236178178732, -0.2542875461803121, -0.1182202171075641, 0.2503459816010795, -0.07823220377129719, 0.06478683108505898, 0.1742497408811591, 0.029826040866371608, -0.03529804198183399, -0.34870233939596473, 0.2999248277059847, 0.04338903048712956, 0.31825277690348547, 0.026590219845897274, 0.13347090186666755, -0.008208300311427346, -0.023414612159962746, -0.007732325982778592, -0.008735717175612874, 0.16793329454083136, 0.25089650872492586, 0.18780918700158372, 0.32431971898680567, -0.4434527705626604, -0.1726778890599262, 0.1347588647009903, 0.13462748470422076, 0.15274470542378976, -0.04939224889424903, -0.23357467571644575, 0.13932471030349738, -0.15963830784859515, -0.052784506207037916, -0.13989602198782272, 0.015706114625012067, 0.01369378705206152, -0.27017052415618326, -0.00018153787451390092, -0.00031285373059878675, 0.022775231617243777, 0.04948707813129207, -0.11810449315795213, 0.02838017346330435, 0.1551035699991271, -0.03185785059638573, -0.015633052960738428, 0.13981437399857363, -0.10317487737927165, -0.13048690084115902, 0.4062851205506691, -0.0064690910258743545, -0.19782900552552446, 0.23686121046347053, -0.06450082119075053, -0.17556563997291086, 0.1123090733570936, 0.22688904437551596, 0.16357903744451197, -0.1775849722404579, 0.07189394526062813, -0.06558898572076491, 0.17473662494510217, 0.05640834052451795, -0.012553985958876914, 0.184862493103216, 0.2569063658391903, 0.05374042382568849, 0.18386233798263216, -0.06959132652176558, -0.10309140603023029, -0.20922340113841192, -0.08684965277014517, -0.22268310289819465, -0.007193929644448585, -0.1599425696311615, -0.23151147566714736, 0.3843722305124872, 0.21151281637052088, 0.23310064726082005, 0.1262695834240211, 0.35818899113376784, -0.00348342162700496, 0.12645883826342852, 0.13434637129951016, 0.10608609425450179, 0.04909771944123103, 0.0672110692454376, -0.11101967661424463, 0.07121199520157748, 0.02652826926432886] |
1,802.06395 | A quasilinear approach to fully nonlinear parabolic (S)PDEs on
$\mathbb{R}^d$ | We study the Cauchy problem for fully nonlinear (stochastic) parabolic
partial differential equations. We provide both in deterministic and stochastic
case the existence of a maximal defined solution for the problem and we provide
suitable blow-up criterion. The key idea is the use of the paradifferential
operator calculus in order to reduce the fully nonlinear problem into an
abstract quasilinear (stochastic) parabolic equation. This allows us to use
some recent results on abstract quasilinear (stochastic) evolution equations in
Banach spaces. To do so, we analyse the properties of the paradifferential
operator, in light of known results on the boundedness of the
$\mathcal{H}^{\infty}$-calculus for pseudodifferential operator. Finally, we
extend the theory just developed to cover high order fully nonlinear parabolic
(S)PDEs.
| math.AP | we study the cauchy problem for fully nonlinear stochastic parabolic partial differential equations we provide both in deterministic and stochastic case the existence of a maximal defined solution for the problem and we provide suitable blowup criterion the key idea is the use of the paradifferential operator calculus in order to reduce the fully nonlinear problem into an abstract quasilinear stochastic parabolic equation this allows us to use some recent results on abstract quasilinear stochastic evolution equations in banach spaces to do so we analyse the properties of the paradifferential operator in light of known results on the boundedness of the mathcalhinftycalculus for pseudodifferential operator finally we extend the theory just developed to cover high order fully nonlinear parabolic spdes | [['we', 'study', 'the', 'cauchy', 'problem', 'for', 'fully', 'nonlinear', 'stochastic', 'parabolic', 'partial', 'differential', 'equations', 'we', 'provide', 'both', 'in', 'deterministic', 'and', 'stochastic', 'case', 'the', 'existence', 'of', 'a', 'maximal', 'defined', 'solution', 'for', 'the', 'problem', 'and', 'we', 'provide', 'suitable', 'blowup', 'criterion', 'the', 'key', 'idea', 'is', 'the', 'use', 'of', 'the', 'paradifferential', 'operator', 'calculus', 'in', 'order', 'to', 'reduce', 'the', 'fully', 'nonlinear', 'problem', 'into', 'an', 'abstract', 'quasilinear', 'stochastic', 'parabolic', 'equation', 'this', 'allows', 'us', 'to', 'use', 'some', 'recent', 'results', 'on', 'abstract', 'quasilinear', 'stochastic', 'evolution', 'equations', 'in', 'banach', 'spaces', 'to', 'do', 'so', 'we', 'analyse', 'the', 'properties', 'of', 'the', 'paradifferential', 'operator', 'in', 'light', 'of', 'known', 'results', 'on', 'the', 'boundedness', 'of', 'the', 'mathcalhinftycalculus', 'for', 'pseudodifferential', 'operator', 'finally', 'we', 'extend', 'the', 'theory', 'just', 'developed', 'to', 'cover', 'high', 'order', 'fully', 'nonlinear', 'parabolic', 'spdes']] | [-0.08806040125588575, -0.002043149254435169, -0.07054951251969517, 0.11331352781465588, -0.17211408759467303, -0.08715669509256259, -0.029773340088043672, 0.29257195175935824, -0.3656712183728814, -0.2057496146298945, 0.15205826702682923, -0.27461440180013597, -0.16552102173057695, 0.19784801503507576, -0.1155730651555738, 0.15395855138388773, 0.03657389780661712, -0.0025895929657660114, -0.0962889603843602, -0.23533360556078453, 0.4111172074335627, -0.050727973032432296, 0.19072864605889966, 0.02331496209371835, 0.14731624503225854, 0.02731271554560711, -0.059944319581457725, -0.0013303201276964197, -0.19508151704794727, 0.12550237211107743, 0.2797833024058491, 0.07661507746670396, 0.33346999847951037, -0.48096341982794305, -0.20185015409563978, 0.10917525597324129, 0.11756655447243247, 0.11580454126621285, -0.02835196215698185, -0.2931999386113603, 0.08735236309003085, -0.13041451210156083, -0.19980433285527396, -0.09447701168828644, -0.044378220138605685, 0.04615617647262601, -0.2802017237331408, 0.0678054551477544, 0.12806173337739893, 0.0063771154130032905, -0.14938676343930032, -0.03784135111879247, 0.005665700228807206, 0.05368172235321254, -0.02433505992521532, -0.04685230010266726, 0.003661104377048711, -0.061054086753089605, -0.11472326868679375, 0.32762621257764596, -0.1177976929548701, -0.2880572463851422, 0.12689816858425426, -0.1525665887631476, -0.13991316674121965, 0.09542944390171518, 0.22592720993173618, 0.20189715029361346, -0.1588833424068677, 0.1495195807336131, -0.06656393468147144, 0.13380325688049197, 0.02693639947877576, 0.014835654594935476, 0.035107612749561666, 0.17617421770313133, 0.16055503926666764, 0.11751607552481194, 0.0221582528630582, -0.15585164209041977, -0.3522917642568549, -0.16022409541377178, -0.05573334925187131, 0.08392183796192208, -0.09114892625851402, -0.19830948657666644, 0.39588650981895623, 0.1779970682381342, 0.14709616918116808, 0.08981946510806059, 0.23055803978350015, 0.23577239922403048, -0.0014369405495623748, 0.048142872444441306, 0.19863202403770022, 0.2257210931488468, 0.18060094774118624, -0.23005809360571827, 0.017991405776895893, 0.19663245205107766] |
1,802.06396 | Can quantum mechanics be considered consistent? a discussion of
Frauchinger and Renner's argument | We discuss the argument proposed in Ref.~\cite{Frauchiger-Renner}, and show
that it does not particularly illustrate any inconsistency in quantum
mechanics, but rather the well known difficulty often described as the
\textquotedblleft shifty split\textquotedblright: the exact point at which the
von Neumann reduction postulate should be applied is ill defined. This is the
origin of the famous Schr\"{o}dinger's cat or Wigner's friend paradoxes.
We investigate the argument of Ref.~\cite{Frauchiger-Renner} and show that it
combines statements obtained by different agents assuming very different
positions of the shifty split, and therefore applying the reduction postulate
in different ways. This results in the introduction of several different state
vectors, while such descriptions are considered as incompatible in standard
quantum mechanics. To our knowledge, no interpretation of quantum mechanics
includes this possibility; the argument thus refers to a new form of quantum
mechanics that should be specified more precisely.
| quant-ph | we discuss the argument proposed in refcitefrauchigerrenner and show that it does not particularly illustrate any inconsistency in quantum mechanics but rather the well known difficulty often described as the textquotedblleft shifty splittextquotedblright the exact point at which the von neumann reduction postulate should be applied is ill defined this is the origin of the famous schrodingers cat or wigners friend paradoxes we investigate the argument of refcitefrauchigerrenner and show that it combines statements obtained by different agents assuming very different positions of the shifty split and therefore applying the reduction postulate in different ways this results in the introduction of several different state vectors while such descriptions are considered as incompatible in standard quantum mechanics to our knowledge no interpretation of quantum mechanics includes this possibility the argument thus refers to a new form of quantum mechanics that should be specified more precisely | [['we', 'discuss', 'the', 'argument', 'proposed', 'in', 'refcitefrauchigerrenner', 'and', 'show', 'that', 'it', 'does', 'not', 'particularly', 'illustrate', 'any', 'inconsistency', 'in', 'quantum', 'mechanics', 'but', 'rather', 'the', 'well', 'known', 'difficulty', 'often', 'described', 'as', 'the', 'textquotedblleft', 'shifty', 'splittextquotedblright', 'the', 'exact', 'point', 'at', 'which', 'the', 'von', 'neumann', 'reduction', 'postulate', 'should', 'be', 'applied', 'is', 'ill', 'defined', 'this', 'is', 'the', 'origin', 'of', 'the', 'famous', 'schrodingers', 'cat', 'or', 'wigners', 'friend', 'paradoxes', 'we', 'investigate', 'the', 'argument', 'of', 'refcitefrauchigerrenner', 'and', 'show', 'that', 'it', 'combines', 'statements', 'obtained', 'by', 'different', 'agents', 'assuming', 'very', 'different', 'positions', 'of', 'the', 'shifty', 'split', 'and', 'therefore', 'applying', 'the', 'reduction', 'postulate', 'in', 'different', 'ways', 'this', 'results', 'in', 'the', 'introduction', 'of', 'several', 'different', 'state', 'vectors', 'while', 'such', 'descriptions', 'are', 'considered', 'as', 'incompatible', 'in', 'standard', 'quantum', 'mechanics', 'to', 'our', 'knowledge', 'no', 'interpretation', 'of', 'quantum', 'mechanics', 'includes', 'this', 'possibility', 'the', 'argument', 'thus', 'refers', 'to', 'a', 'new', 'form', 'of', 'quantum', 'mechanics', 'that', 'should', 'be', 'specified', 'more', 'precisely']] | [-0.06257236301519162, 0.11167263999541706, -0.13407117389811282, 0.12963367848415985, -0.08426722070426805, -0.1801487993822988, 0.02867661084953352, 0.3028963075154824, -0.2666242993866087, -0.2999740598181672, 0.06996358362611066, -0.2429461900428836, -0.1679085643635072, 0.17809733601967334, -0.12873739284522673, 0.030704826324623315, 0.06100851031026889, 0.07344372800703272, -0.06692009122632708, -0.2120537420153512, 0.3263682184628614, 0.029195050350621553, 0.28562753134141244, 0.04022665656376498, 0.09998773047634472, 0.030729697961096012, -0.031022601394339443, 0.0525837492144911, -0.07655022198788232, 0.09187620360708089, 0.27117677128061335, 0.1709089231981189, 0.30339219554571817, -0.44140610471367836, -0.21353018555810002, 0.08988247857287077, 0.11125243615345858, 0.1557817932685626, 0.005159475570953293, -0.3117536162389508, 0.05063544589273156, -0.16347152402076262, -0.1731696653325137, -0.06893584811201332, -0.0048192103842524345, -0.043324904551429025, -0.16930833817888977, 0.08523055498574114, 0.13385829838993463, 0.03586433241341976, -0.03695568997608597, -0.10559163584063451, 0.03790411739841315, 0.101911680728316, 0.0332818798405442, -0.011008452676923563, 0.10855344215619332, -0.0983458794108493, -0.15814537274261528, 0.41891353000748033, 0.018053808989307137, -0.2224693587908508, 0.19882208111544028, -0.1206509988451152, -0.14534988945369867, 0.023807233186266947, 0.03560226130487516, 0.08449677656014971, -0.1399206009013116, 0.05766572561392648, -0.04429795944746187, 0.1479396952205942, 0.09044119858196177, 0.045167824024737464, 0.2002072614478938, 0.07202803536734366, 0.022148029340417884, 0.1055598816081406, 0.0006002035414707577, -0.17229483856040165, -0.3546001694317088, -0.18193978448571796, -0.2260996528062309, 0.1062076738755861, -0.047179803248607974, -0.1415534792798208, 0.32204560416664746, 0.17336605207875688, 0.19452487541270172, 0.020462529661946317, 0.25959753315790113, 0.1395079323717274, 0.057038232351815106, 0.03162884783884841, 0.25754010567692576, 0.10881588299402055, 0.08877342557600627, -0.1878626000529142, 0.07771562748582017, 0.04257880766208924] |
1,802.06397 | Semiclassical approach to finite temperature quantum annealing with
trapped ions | Recently it has been demonstrated that an ensemble of trapped ions may serve
as a quantum annealer for the number-partitioning problem [Nature Comm. DOI:
10.1038/ncomms11524]. This hard computational problem may be addressed
employing a tunable spin glass architecture. Following the proposal of the
trapped ions annealer, we study here its robustness against thermal effects,
that is, we investigate the role played by thermal phonons. For the efficient
description of the system, we use a semiclassical approach, and benchmark it
against the exact quantum evolution. The aim is to understand better and
characterize how the quantum device approaches a solution of, an otherwise,
difficult to solve NP-hard problem.
| quant-ph cond-mat.quant-gas | recently it has been demonstrated that an ensemble of trapped ions may serve as a quantum annealer for the numberpartitioning problem nature comm doi 101038ncomms11524 this hard computational problem may be addressed employing a tunable spin glass architecture following the proposal of the trapped ions annealer we study here its robustness against thermal effects that is we investigate the role played by thermal phonons for the efficient description of the system we use a semiclassical approach and benchmark it against the exact quantum evolution the aim is to understand better and characterize how the quantum device approaches a solution of an otherwise difficult to solve nphard problem | [['recently', 'it', 'has', 'been', 'demonstrated', 'that', 'an', 'ensemble', 'of', 'trapped', 'ions', 'may', 'serve', 'as', 'a', 'quantum', 'annealer', 'for', 'the', 'numberpartitioning', 'problem', 'nature', 'comm', 'doi', '101038ncomms11524', 'this', 'hard', 'computational', 'problem', 'may', 'be', 'addressed', 'employing', 'a', 'tunable', 'spin', 'glass', 'architecture', 'following', 'the', 'proposal', 'of', 'the', 'trapped', 'ions', 'annealer', 'we', 'study', 'here', 'its', 'robustness', 'against', 'thermal', 'effects', 'that', 'is', 'we', 'investigate', 'the', 'role', 'played', 'by', 'thermal', 'phonons', 'for', 'the', 'efficient', 'description', 'of', 'the', 'system', 'we', 'use', 'a', 'semiclassical', 'approach', 'and', 'benchmark', 'it', 'against', 'the', 'exact', 'quantum', 'evolution', 'the', 'aim', 'is', 'to', 'understand', 'better', 'and', 'characterize', 'how', 'the', 'quantum', 'device', 'approaches', 'a', 'solution', 'of', 'an', 'otherwise', 'difficult', 'to', 'solve', 'nphard', 'problem']] | [-0.08805376187499081, 0.0842433529354388, -0.10303643531432109, 0.07622830320615322, -0.03352914258305516, -0.18468658308986396, 0.037030554272323137, 0.3920996604930787, -0.2561114413974186, -0.3039496638767776, 0.07051441584314619, -0.2669655050018004, -0.17083713465503284, 0.1979172869186316, -0.05600649959939931, 0.10494625295146502, 0.06688693625231584, -0.033762301285085936, -0.024631564500963404, -0.24326739266869568, 0.2569092352697182, 0.12978571609571754, 0.2958870257007047, 0.09362294628018779, 0.09105522471613117, -0.005299667288948383, 0.05843130459875933, 0.0414014910491893, -0.1354786437643703, 0.08901387362275273, 0.26108367879475863, 0.08786190931596571, 0.31033584434716477, -0.4620495525144395, -0.22886178282399972, 0.11122941744425112, 0.1552941568073861, 0.18463747347483322, -0.04247987341313135, -0.2577265617038522, 0.06273152932435984, -0.1842512309285147, -0.1527453196368047, -0.12622056403862578, 0.017862745250264805, -0.08481660780075582, -0.22522996030304404, 0.02726314396020912, 0.09275028916253221, 0.000989196307602383, -0.04839615067799709, -0.05501738998573273, 0.06625097336336261, 0.11002846291022642, -0.026505794844845134, 0.035542147213016594, 0.13343289557933097, -0.12195352320781067, -0.172498061348285, 0.3995511586201333, -0.015328931866124981, -0.19840211148451392, 0.1969433042664258, -0.013777678987632195, -0.10302520781600227, 0.0797475966713613, 0.14745666917546518, 0.1411622909296836, -0.16235581333527252, 0.0801692606315815, -0.028731326426246335, 0.16823524718305893, 0.019053563404650916, 0.0590081957479318, 0.2234372095027495, 0.2108331907806652, 0.04099488391407898, 0.2039425546026212, -0.06886482277907253, -0.13680184538964005, -0.20084935161506845, -0.17639109059791303, -0.2349636320734308, 0.0731743483405028, -0.011196823306991496, -0.14154159809861863, 0.37801489922484116, 0.22101617195321957, 0.13247743742096993, -0.05060638848337389, 0.29393338236425604, 0.11909132372654442, -0.006780261708800459, 0.07143727587535978, 0.2505928492794434, 0.15932004041082803, 0.0988336266195845, -0.3217210002687006, 0.04896937516251845, 0.038325554504990575] |
1,802.06398 | HybridSVD: When Collaborative Information is Not Enough | We propose a new hybrid algorithm that allows incorporating both user and
item side information within the standard collaborative filtering technique.
One of its key features is that it naturally extends a simple PureSVD approach
and inherits its unique advantages, such as highly efficient Lanczos-based
optimization procedure, simplified hyper-parameter tuning and a quick
folding-in computation for generating recommendations instantly even in highly
dynamic online environments. The algorithm utilizes a generalized formulation
of the singular value decomposition, which adds flexibility to the solution and
allows imposing the desired structure on its latent space. Conveniently, the
resulting model also admits an efficient and straightforward solution for the
cold start scenario. We evaluate our approach on a diverse set of datasets and
show its superiority over similar classes of hybrid models.
| cs.LG cs.IR stat.ML | we propose a new hybrid algorithm that allows incorporating both user and item side information within the standard collaborative filtering technique one of its key features is that it naturally extends a simple puresvd approach and inherits its unique advantages such as highly efficient lanczosbased optimization procedure simplified hyperparameter tuning and a quick foldingin computation for generating recommendations instantly even in highly dynamic online environments the algorithm utilizes a generalized formulation of the singular value decomposition which adds flexibility to the solution and allows imposing the desired structure on its latent space conveniently the resulting model also admits an efficient and straightforward solution for the cold start scenario we evaluate our approach on a diverse set of datasets and show its superiority over similar classes of hybrid models | [['we', 'propose', 'a', 'new', 'hybrid', 'algorithm', 'that', 'allows', 'incorporating', 'both', 'user', 'and', 'item', 'side', 'information', 'within', 'the', 'standard', 'collaborative', 'filtering', 'technique', 'one', 'of', 'its', 'key', 'features', 'is', 'that', 'it', 'naturally', 'extends', 'a', 'simple', 'puresvd', 'approach', 'and', 'inherits', 'its', 'unique', 'advantages', 'such', 'as', 'highly', 'efficient', 'lanczosbased', 'optimization', 'procedure', 'simplified', 'hyperparameter', 'tuning', 'and', 'a', 'quick', 'foldingin', 'computation', 'for', 'generating', 'recommendations', 'instantly', 'even', 'in', 'highly', 'dynamic', 'online', 'environments', 'the', 'algorithm', 'utilizes', 'a', 'generalized', 'formulation', 'of', 'the', 'singular', 'value', 'decomposition', 'which', 'adds', 'flexibility', 'to', 'the', 'solution', 'and', 'allows', 'imposing', 'the', 'desired', 'structure', 'on', 'its', 'latent', 'space', 'conveniently', 'the', 'resulting', 'model', 'also', 'admits', 'an', 'efficient', 'and', 'straightforward', 'solution', 'for', 'the', 'cold', 'start', 'scenario', 'we', 'evaluate', 'our', 'approach', 'on', 'a', 'diverse', 'set', 'of', 'datasets', 'and', 'show', 'its', 'superiority', 'over', 'similar', 'classes', 'of', 'hybrid', 'models']] | [-0.07235967371525476, -0.014088062515725142, -0.12505348077684175, 0.046684479002124135, -0.16563637093713623, -0.18339402615310973, 0.07423524736077525, 0.40349072303251887, -0.2948613119588117, -0.3048254134992021, 0.09170082043752359, -0.20698211313379034, -0.2031421173014678, 0.20431712716344919, -0.07291920700095034, 0.0492165356181431, 0.10565659069652611, 0.01204400216738577, -0.08203544111529482, -0.21713492399612733, 0.2711457369478012, 0.06720980357476947, 0.3215540023156791, 0.02135121047786015, 0.17701528938050615, 0.04083471777391878, -0.030521964057697915, 0.021555069328087484, -0.06755740433129631, 0.1616094265045831, 0.2256943382848533, 0.213203847008117, 0.32808228966496245, -0.37541776617035794, -0.21264174881071085, 0.0656434360134881, 0.13137143935455242, 0.10538549560453703, -0.06682760924923059, -0.26744131681334693, 0.08397145085564262, -0.21518275009839272, -0.08878850752080325, -0.17679113263420732, -0.05646620683546644, -0.037386432366474764, -0.33853249141839115, 0.02713695000579719, 0.05482484910316998, -0.050013651545668836, -0.04656521504239208, -0.11172864134277916, 0.024389580932620447, 0.09365295708812482, -0.012087271788004728, 0.010171823122618662, 0.13308760278232512, -0.12408818283751089, -0.12640725795972685, 0.3943369234129932, -0.060035545318896766, -0.21891316461858423, 0.2038137469389767, 0.0033571652857062872, -0.12891687151568476, 0.1390486991222133, 0.17774654481036123, 0.16124572286207695, -0.14385187358175244, 0.09580322600504587, -0.05928548180963844, 0.1568517487430654, 0.004356949308203184, 0.022889498755830573, 0.1709566072695452, 0.23034870336414315, 0.10677295127243269, 0.14509914538211888, -0.052384500555490376, -0.1262507613573689, -0.24677594337117625, -0.14858261690551444, -0.15386085941281635, -0.04276804777691723, -0.16687360310902477, -0.18284221948852064, 0.4560443034097261, 0.20118273014486476, 0.17998684163774215, 0.07233503541010577, 0.3562488983734511, 0.08012051799153141, 0.060744239061477856, 0.0952168681724288, 0.13117474944374408, 0.052764479756660876, 0.09637387750535709, -0.18639746898588783, 0.08338187278059195, 0.05314796572383784] |
1,802.06399 | Visual-Only Recognition of Normal, Whispered and Silent Speech | Silent speech interfaces have been recently proposed as a way to enable
communication when the acoustic signal is not available. This introduces the
need to build visual speech recognition systems for silent and whispered
speech. However, almost all the recently proposed systems have been trained on
vocalised data only. This is in contrast with evidence in the literature which
suggests that lip movements change depending on the speech mode. In this work,
we introduce a new audiovisual database which is publicly available and
contains normal, whispered and silent speech. To the best of our knowledge,
this is the first study which investigates the differences between the three
speech modes using the visual modality only. We show that an absolute decrease
in classification rate of up to 3.7% is observed when training and testing on
normal and whispered, respectively, and vice versa. An even higher decrease of
up to 8.5% is reported when the models are tested on silent speech. This
reveals that there are indeed visual differences between the 3 speech modes and
the common assumption that vocalized training data can be used directly to
train a silent speech recognition system may not be true.
| cs.CV | silent speech interfaces have been recently proposed as a way to enable communication when the acoustic signal is not available this introduces the need to build visual speech recognition systems for silent and whispered speech however almost all the recently proposed systems have been trained on vocalised data only this is in contrast with evidence in the literature which suggests that lip movements change depending on the speech mode in this work we introduce a new audiovisual database which is publicly available and contains normal whispered and silent speech to the best of our knowledge this is the first study which investigates the differences between the three speech modes using the visual modality only we show that an absolute decrease in classification rate of up to 37 is observed when training and testing on normal and whispered respectively and vice versa an even higher decrease of up to 85 is reported when the models are tested on silent speech this reveals that there are indeed visual differences between the 3 speech modes and the common assumption that vocalized training data can be used directly to train a silent speech recognition system may not be true | [['silent', 'speech', 'interfaces', 'have', 'been', 'recently', 'proposed', 'as', 'a', 'way', 'to', 'enable', 'communication', 'when', 'the', 'acoustic', 'signal', 'is', 'not', 'available', 'this', 'introduces', 'the', 'need', 'to', 'build', 'visual', 'speech', 'recognition', 'systems', 'for', 'silent', 'and', 'whispered', 'speech', 'however', 'almost', 'all', 'the', 'recently', 'proposed', 'systems', 'have', 'been', 'trained', 'on', 'vocalised', 'data', 'only', 'this', 'is', 'in', 'contrast', 'with', 'evidence', 'in', 'the', 'literature', 'which', 'suggests', 'that', 'lip', 'movements', 'change', 'depending', 'on', 'the', 'speech', 'mode', 'in', 'this', 'work', 'we', 'introduce', 'a', 'new', 'audiovisual', 'database', 'which', 'is', 'publicly', 'available', 'and', 'contains', 'normal', 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1,802.064 | Elementary Quotient Completions, Church's Thesis, and Partioned
Assemblies | Hyland's effective topos offers an important realizability model for
constructive mathematics in the form of a category whose internal logic
validates Church's Thesis. It also contains a boolean full sub-quasitopos of
"assemblies" where only a restricted form of Church's Thesis survives. In the
present paper we compare the effective topos and the quasitopos of assemblies
each as the elementary quotient completions of a Lawvere doctrine based on the
partitioned assemblies. In that way we can explain why the two forms of
Church's Thesis each category satisfies differ by the way each is inherited
from specific properties of the doctrine which determines the elementary
quotient completion.
| math.LO | hylands effective topos offers an important realizability model for constructive mathematics in the form of a category whose internal logic validates churchs thesis it also contains a boolean full subquasitopos of assemblies where only a restricted form of churchs thesis survives in the present paper we compare the effective topos and the quasitopos of assemblies each as the elementary quotient completions of a lawvere doctrine based on the partitioned assemblies in that way we can explain why the two forms of churchs thesis each category satisfies differ by the way each is inherited from specific properties of the doctrine which determines the elementary quotient completion | [['hylands', 'effective', 'topos', 'offers', 'an', 'important', 'realizability', 'model', 'for', 'constructive', 'mathematics', 'in', 'the', 'form', 'of', 'a', 'category', 'whose', 'internal', 'logic', 'validates', 'churchs', 'thesis', 'it', 'also', 'contains', 'a', 'boolean', 'full', 'subquasitopos', 'of', 'assemblies', 'where', 'only', 'a', 'restricted', 'form', 'of', 'churchs', 'thesis', 'survives', 'in', 'the', 'present', 'paper', 'we', 'compare', 'the', 'effective', 'topos', 'and', 'the', 'quasitopos', 'of', 'assemblies', 'each', 'as', 'the', 'elementary', 'quotient', 'completions', 'of', 'a', 'lawvere', 'doctrine', 'based', 'on', 'the', 'partitioned', 'assemblies', 'in', 'that', 'way', 'we', 'can', 'explain', 'why', 'the', 'two', 'forms', 'of', 'churchs', 'thesis', 'each', 'category', 'satisfies', 'differ', 'by', 'the', 'way', 'each', 'is', 'inherited', 'from', 'specific', 'properties', 'of', 'the', 'doctrine', 'which', 'determines', 'the', 'elementary', 'quotient', 'completion']] | [-0.10223212684146486, 0.0714582330979633, -0.14233943839924626, 0.1107326474616107, -0.10862741498903443, -0.12267273544477156, 0.01335716844858745, 0.28186352757620625, -0.32696200124561214, -0.2399461360182613, 0.03189396206401467, -0.20798669859337118, -0.16355549762710536, 0.1257884268662355, -0.1516001694746172, -0.08560593775473535, 0.013125157048657106, 0.10054469600212403, -0.028057984499565255, -0.23964572867575604, 0.3771538288386252, -0.004240871380226543, 0.259228921844624, 0.0016593084616873127, 0.14005506654771474, 0.049373854013258375, 0.009956412460619153, 0.043225198258789115, -0.1293928692380527, 0.16023845244042326, 0.2810002179623832, 0.18367634942450634, 0.26645566468673326, -0.4419449308994584, -0.09600974853114727, 0.08548044771976912, 0.1386875564393659, 0.0725233413697704, 0.010029053918865079, -0.24387553164090675, 0.06764605126451127, -0.18675318584204292, -0.07174982911405656, -0.043505589603647914, 0.051754206051835075, 0.0023030935329958224, -0.18124648823868483, -0.03994825681701723, 0.13911995783340758, 0.08704064384353562, -0.08536366986831687, -0.10442352433500883, -0.028858757443511143, 0.09331556140498903, -0.060249703784603086, 0.008753976266374454, 0.1338923368916417, -0.12341968208532378, -0.11481534947457615, 0.4304624916896081, -0.0376786820214385, -0.15804924675299284, 0.15853144260472618, -0.08254276846016112, -0.1884342020852133, 0.07252381527303861, 0.04389828848294341, 0.12475068793775371, -0.12413100089627103, 0.19300126207739454, -0.12370653491906033, 0.1570790484950591, 0.09810898102855739, 0.0727196563474046, 0.19546379761763652, 0.21235327110984004, -0.018593778936729696, 0.17524940064714217, 0.06922220974453151, -0.09622564426480004, -0.404458101803007, -0.18623037022413114, -0.10609118695943974, 0.07446503740412971, -0.023847458633239373, -0.18688154423860118, 0.39958369421611467, 0.1587297034008001, 0.15077076146217921, 0.10909450239649651, 0.2636302546553242, 0.049654200246620275, 0.08390030393806788, 0.005194104151227153, 0.1694619407913146, 0.17684134302096657, 0.014042196504306048, -0.13031164127348277, 0.06996984129476075, 0.16347758699647294] |
1,802.06401 | An Overview of Physical Layer Security with Finite-Alphabet Signaling | Providing secure communications over the physical layer with the objective of
achieving perfect secrecy without requiring a secret key has been receiving
growing attention within the past decade. The vast majority of the existing
studies in the area of physical layer security focus exclusively on the
scenarios where the channel inputs are Gaussian distributed. However, in
practice, the signals employed for transmission are drawn from discrete signal
constellations such as phase shift keying and quadrature amplitude modulation.
Hence, understanding the impact of the finite-alphabet input constraints and
designing secure transmission schemes under this assumption is a mandatory step
towards a practical implementation of physical layer security. With this
motivation, this article reviews recent developments on physical layer security
with finite-alphabet inputs. We explore transmit signal design algorithms for
single-antenna as well as multi-antenna wiretap channels under different
assumptions on the channel state information at the transmitter. Moreover, we
present a review of the recent results on secure transmission with discrete
signaling for various scenarios including multi-carrier transmission systems,
broadcast channels with confidential messages, cognitive multiple access and
relay networks. Throughout the article, we stress the important behavioral
differences of discrete versus Gaussian inputs in the context of the physical
layer security. We also present an overview of practical code construction over
Gaussian and fading wiretap channels, and we discuss some open problems and
directions for future research.
| cs.IT math.IT | providing secure communications over the physical layer with the objective of achieving perfect secrecy without requiring a secret key has been receiving growing attention within the past decade the vast majority of the existing studies in the area of physical layer security focus exclusively on the scenarios where the channel inputs are gaussian distributed however in practice the signals employed for transmission are drawn from discrete signal constellations such as phase shift keying and quadrature amplitude modulation hence understanding the impact of the finitealphabet input constraints and designing secure transmission schemes under this assumption is a mandatory step towards a practical implementation of physical layer security with this motivation this article reviews recent developments on physical layer security with finitealphabet inputs we explore transmit signal design algorithms for singleantenna as well as multiantenna wiretap channels under different assumptions on the channel state information at the transmitter moreover we present a review of the recent results on secure transmission with discrete signaling for various scenarios including multicarrier transmission systems broadcast channels with confidential messages cognitive multiple access and relay networks throughout the article we stress the important behavioral differences of discrete versus gaussian inputs in the context of the physical layer security we also present an overview of practical code construction over gaussian and fading wiretap channels and we discuss some open problems and directions for future research | [['providing', 'secure', 'communications', 'over', 'the', 'physical', 'layer', 'with', 'the', 'objective', 'of', 'achieving', 'perfect', 'secrecy', 'without', 'requiring', 'a', 'secret', 'key', 'has', 'been', 'receiving', 'growing', 'attention', 'within', 'the', 'past', 'decade', 'the', 'vast', 'majority', 'of', 'the', 'existing', 'studies', 'in', 'the', 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1,802.06402 | Towards Ultra-High Performance and Energy Efficiency of Deep Learning
Systems: An Algorithm-Hardware Co-Optimization Framework | Hardware accelerations of deep learning systems have been extensively
investigated in industry and academia. The aim of this paper is to achieve
ultra-high energy efficiency and performance for hardware implementations of
deep neural networks (DNNs). An algorithm-hardware co-optimization framework is
developed, which is applicable to different DNN types, sizes, and application
scenarios. The algorithm part adopts the general block-circulant matrices to
achieve a fine-grained tradeoff between accuracy and compression ratio. It
applies to both fully-connected and convolutional layers and contains a
mathematically rigorous proof of the effectiveness of the method. The proposed
algorithm reduces computational complexity per layer from O($n^2$) to O($n\log
n$) and storage complexity from O($n^2$) to O($n$), both for training and
inference. The hardware part consists of highly efficient Field Programmable
Gate Array (FPGA)-based implementations using effective reconfiguration, batch
processing, deep pipelining, resource re-using, and hierarchical control.
Experimental results demonstrate that the proposed framework achieves at least
152X speedup and 71X energy efficiency gain compared with IBM TrueNorth
processor under the same test accuracy. It achieves at least 31X energy
efficiency gain compared with the reference FPGA-based work.
| cs.LG stat.ML | hardware accelerations of deep learning systems have been extensively investigated in industry and academia the aim of this paper is to achieve ultrahigh energy efficiency and performance for hardware implementations of deep neural networks dnns an algorithmhardware cooptimization framework is developed which is applicable to different dnn types sizes and application scenarios the algorithm part adopts the general blockcirculant matrices to achieve a finegrained tradeoff between accuracy and compression ratio it applies to both fullyconnected and convolutional layers and contains a mathematically rigorous proof of the effectiveness of the method the proposed algorithm reduces computational complexity per layer from on2 to onlog n and storage complexity from on2 to on both for training and inference the hardware part consists of highly efficient field programmable gate array fpgabased implementations using effective reconfiguration batch processing deep pipelining resource reusing and hierarchical control experimental results demonstrate that the proposed framework achieves at least 152x speedup and 71x energy efficiency gain compared with ibm truenorth processor under the same test accuracy it achieves at least 31x energy efficiency gain compared with the reference fpgabased work | [['hardware', 'accelerations', 'of', 'deep', 'learning', 'systems', 'have', 'been', 'extensively', 'investigated', 'in', 'industry', 'and', 'academia', 'the', 'aim', 'of', 'this', 'paper', 'is', 'to', 'achieve', 'ultrahigh', 'energy', 'efficiency', 'and', 'performance', 'for', 'hardware', 'implementations', 'of', 'deep', 'neural', 'networks', 'dnns', 'an', 'algorithmhardware', 'cooptimization', 'framework', 'is', 'developed', 'which', 'is', 'applicable', 'to', 'different', 'dnn', 'types', 'sizes', 'and', 'application', 'scenarios', 'the', 'algorithm', 'part', 'adopts', 'the', 'general', 'blockcirculant', 'matrices', 'to', 'achieve', 'a', 'finegrained', 'tradeoff', 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1,802.06403 | RadialGAN: Leveraging multiple datasets to improve target-specific
predictive models using Generative Adversarial Networks | Training complex machine learning models for prediction often requires a
large amount of data that is not always readily available. Leveraging these
external datasets from related but different sources is therefore an important
task if good predictive models are to be built for deployment in settings where
data can be rare. In this paper we propose a novel approach to the problem in
which we use multiple GAN architectures to learn to translate from one dataset
to another, thereby allowing us to effectively enlarge the target dataset, and
therefore learn better predictive models than if we simply used the target
dataset. We show the utility of such an approach, demonstrating that our method
improves the prediction performance on the target domain over using just the
target dataset and also show that our framework outperforms several other
benchmarks on a collection of real-world medical datasets.
| cs.LG stat.ML | training complex machine learning models for prediction often requires a large amount of data that is not always readily available leveraging these external datasets from related but different sources is therefore an important task if good predictive models are to be built for deployment in settings where data can be rare in this paper we propose a novel approach to the problem in which we use multiple gan architectures to learn to translate from one dataset to another thereby allowing us to effectively enlarge the target dataset and therefore learn better predictive models than if we simply used the target dataset we show the utility of such an approach demonstrating that our method improves the prediction performance on the target domain over using just the target dataset and also show that our framework outperforms several other benchmarks on a collection of realworld medical datasets | [['training', 'complex', 'machine', 'learning', 'models', 'for', 'prediction', 'often', 'requires', 'a', 'large', 'amount', 'of', 'data', 'that', 'is', 'not', 'always', 'readily', 'available', 'leveraging', 'these', 'external', 'datasets', 'from', 'related', 'but', 'different', 'sources', 'is', 'therefore', 'an', 'important', 'task', 'if', 'good', 'predictive', 'models', 'are', 'to', 'be', 'built', 'for', 'deployment', 'in', 'settings', 'where', 'data', 'can', 'be', 'rare', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'approach', 'to', 'the', 'problem', 'in', 'which', 'we', 'use', 'multiple', 'gan', 'architectures', 'to', 'learn', 'to', 'translate', 'from', 'one', 'dataset', 'to', 'another', 'thereby', 'allowing', 'us', 'to', 'effectively', 'enlarge', 'the', 'target', 'dataset', 'and', 'therefore', 'learn', 'better', 'predictive', 'models', 'than', 'if', 'we', 'simply', 'used', 'the', 'target', 'dataset', 'we', 'show', 'the', 'utility', 'of', 'such', 'an', 'approach', 'demonstrating', 'that', 'our', 'method', 'improves', 'the', 'prediction', 'performance', 'on', 'the', 'target', 'domain', 'over', 'using', 'just', 'the', 'target', 'dataset', 'and', 'also', 'show', 'that', 'our', 'framework', 'outperforms', 'several', 'other', 'benchmarks', 'on', 'a', 'collection', 'of', 'realworld', 'medical', 'datasets']] | [0.01820663794286601, -0.010293224365442357, -0.07942860552510764, 0.06545503992836327, -0.1337022715565076, -0.16518079829337592, 0.048677504979827466, 0.4480398245569732, -0.2748482956602756, -0.3720236484530485, 0.08674533373353673, -0.27514836888035965, -0.14701470896963859, 0.28637117959765923, -0.14524891073556823, 0.043328547947263964, 0.1510505414981809, 0.05957234737029972, -0.041388807316252496, -0.30724300091646406, 0.32210549065429306, 0.03762134517051487, 0.35090708802454174, 0.050734169490169734, 0.10597258993948344, -0.04957246303092688, 0.005733679550758097, 0.010437707423180755, -0.03241184895235468, 0.18710911931298646, 0.3149455342614955, 0.23214385761982864, 0.3013491747228222, -0.4047450185753405, -0.2371998298395839, 0.1328146850121104, 0.14512975079641263, 0.13366592304636368, -0.022082772201328125, -0.32016445079352707, 0.09301197751645102, -0.17131929935809845, -0.013653527424644886, -0.17519724235818204, -0.044988399491153866, -0.02906141667578292, -0.3354539375868626, 0.02896413933497873, 0.03958140320092854, 0.020664907641831733, -0.05492705959477462, -0.10815026578105365, 0.02501772607340374, 0.18204578462528945, 0.047996428937444255, 0.05733912565240947, 0.11974294048074323, -0.15931506857062536, -0.12520594524297243, 0.37619281897787005, -0.06029474994738848, -0.24061859030775345, 0.22629314754481633, -0.07283737043487942, -0.156015288747666, 0.08880846904099195, 0.25342744984664023, 0.14638777689671972, -0.17436533383119646, -0.00206046981960147, -0.06311050178353778, 0.2177074116641759, -0.0019248861644882709, -0.02446297585265711, 0.17033711431011195, 0.26900176335281384, 0.04012990332234444, 0.1403776862025552, -0.11491371107856846, -0.06427983490801933, -0.2291390181995262, -0.0953757871078172, -0.19809951981167412, -0.011323853626385648, -0.08424657633663123, -0.12854812705477847, 0.38252265677308767, 0.2879937675283549, 0.20659835897903475, 0.08373887425033091, 0.33454830805567326, -0.0043188874664742295, 0.13223746677006906, 0.10594548447948506, 0.15870272544755912, -0.04629675767177509, 0.0801612896894868, -0.15126769681390012, 0.07434257776185405, -0.04261871863855049] |
1,802.06404 | Using 3D Hahn Moments as A Computational Representation of ATS Drugs
Molecular Structure | The campaign against drug abuse is fought by all countries, most notably on
ATS drugs. The technical limitations of the current test kits to detect new
brand of ATS drugs present a challenge to law enforcement authorities and
forensic laboratories. Meanwhile, new molecular imaging devices which allowed
mankind to characterize the physical 3D molecular structure have been recently
introduced, and it can be used to remedy the limitations of existing drug test
kits. Thus, a new type of 3D molecular structure representation technique
should be developed to cater the 3D molecular structure acquired physically
using these molecular imaging devices. One of the applications of image
processing methods to represent a 3D image is 3D moments, and this study
formulates a new 3D moments technique, namely 3D Hahn moments, to represent the
3D molecular structure of ATS drugs. The performance of the proposed technique
was analysed using drug chemical structures obtained from UNODC for the ATS
drugs, while non-ATS drugs are obtained randomly from ChemSpider database. The
evaluation shows the technique is qualified to be further explored in the
future works to be fully compatible with ATS drug identification domain.
| cs.CV | the campaign against drug abuse is fought by all countries most notably on ats drugs the technical limitations of the current test kits to detect new brand of ats drugs present a challenge to law enforcement authorities and forensic laboratories meanwhile new molecular imaging devices which allowed mankind to characterize the physical 3d molecular structure have been recently introduced and it can be used to remedy the limitations of existing drug test kits thus a new type of 3d molecular structure representation technique should be developed to cater the 3d molecular structure acquired physically using these molecular imaging devices one of the applications of image processing methods to represent a 3d image is 3d moments and this study formulates a new 3d moments technique namely 3d hahn moments to represent the 3d molecular structure of ats drugs the performance of the proposed technique was analysed using drug chemical structures obtained from unodc for the ats drugs while nonats drugs are obtained randomly from chemspider database the evaluation shows the technique is qualified to be further explored in the future works to be fully compatible with ats drug identification domain | [['the', 'campaign', 'against', 'drug', 'abuse', 'is', 'fought', 'by', 'all', 'countries', 'most', 'notably', 'on', 'ats', 'drugs', 'the', 'technical', 'limitations', 'of', 'the', 'current', 'test', 'kits', 'to', 'detect', 'new', 'brand', 'of', 'ats', 'drugs', 'present', 'a', 'challenge', 'to', 'law', 'enforcement', 'authorities', 'and', 'forensic', 'laboratories', 'meanwhile', 'new', 'molecular', 'imaging', 'devices', 'which', 'allowed', 'mankind', 'to', 'characterize', 'the', 'physical', '3d', 'molecular', 'structure', 'have', 'been', 'recently', 'introduced', 'and', 'it', 'can', 'be', 'used', 'to', 'remedy', 'the', 'limitations', 'of', 'existing', 'drug', 'test', 'kits', 'thus', 'a', 'new', 'type', 'of', '3d', 'molecular', 'structure', 'representation', 'technique', 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1,802.06405 | Sums, products and ratios along the edges of a graph | In their seminal paper Erd\H{o}s and Szemer\'edi formulated conjectures on
the size of sumset and product set of integers. The strongest form of their
conjecture is about sums and products along the edges of a graph. In this paper
we show that this strong form of the Erd\H{o}s-Szemer\'edi conjecture does not
hold. We give upper and lower bounds on the cardinalities of sumsets, product
sets and ratio sets along the edges of graphs.
| math.CO math.NT | in their seminal paper erdhos and szemeredi formulated conjectures on the size of sumset and product set of integers the strongest form of their conjecture is about sums and products along the edges of a graph in this paper we show that this strong form of the erdhosszemeredi conjecture does not hold we give upper and lower bounds on the cardinalities of sumsets product sets and ratio sets along the edges of graphs | [['in', 'their', 'seminal', 'paper', 'erdhos', 'and', 'szemeredi', 'formulated', 'conjectures', 'on', 'the', 'size', 'of', 'sumset', 'and', 'product', 'set', 'of', 'integers', 'the', 'strongest', 'form', 'of', 'their', 'conjecture', 'is', 'about', 'sums', 'and', 'products', 'along', 'the', 'edges', 'of', 'a', 'graph', 'in', 'this', 'paper', 'we', 'show', 'that', 'this', 'strong', 'form', 'of', 'the', 'erdhosszemeredi', 'conjecture', 'does', 'not', 'hold', 'we', 'give', 'upper', 'and', 'lower', 'bounds', 'on', 'the', 'cardinalities', 'of', 'sumsets', 'product', 'sets', 'and', 'ratio', 'sets', 'along', 'the', 'edges', 'of', 'graphs']] | [-0.20122776407595366, 0.06670806901401853, -0.04293191485897931, 0.05151742428050007, -0.047514720730585595, -0.04799399383952969, 0.1049572663439106, 0.3153521551380623, -0.2648721812420512, -0.2976825629705436, 0.09260241922361087, -0.3057259377666226, -0.12262226489997685, 0.17093453756597352, -0.12812214916291303, 0.00890481088801657, 0.10090928654224701, 0.05271813503071053, -0.006877431645989418, -0.36519174468392596, 0.34810480425351187, -0.04156583958394723, 0.22987280280826844, 0.1865615254676301, -0.002295981276116959, 0.03319583334385941, -0.027280995762613537, 0.02649119748950821, -0.21024641753479356, 0.1768530843498772, 0.18364843797602065, 0.19607937084638502, 0.25789599209921815, -0.424185705128802, -0.07471511704362419, 0.1914150753147798, 0.1324915124060768, 0.027332032992415232, 0.027224130746717118, -0.2362098994071608, 0.11524252577569999, -0.09109095218655182, -0.09503974627116568, -0.00653316303832482, 0.09250867790351175, 0.03291462139826115, -0.256738455232539, 0.04100504920703091, 0.1628022228099712, 0.06952591985105282, -0.0443178498352023, -0.2186394755230987, 0.01656198189976587, 0.09121914590670638, 0.034840561433580435, -0.002040565587988455, 0.0025027540132837142, -0.087682289802565, -0.15890871146566246, 0.32338930337294325, -0.04321809177612248, -0.14396578647604544, 0.14519235708396755, -0.18405896681679845, -0.19263870659450147, 0.05591534861452775, 0.164122824276453, 0.15433640827820316, -0.030279384849414434, 0.14028199555030194, -0.20337074693955787, 0.09640934568357794, 0.206569748854086, 0.07641516810232034, 0.1489790870157415, 0.038140281320434725, 0.11388550030246172, 0.17537559073877662, 0.02171537102110786, -0.005121040961717906, -0.2970296713485293, -0.17129989941795803, -0.22169174885294363, 0.0989413234608149, -0.15447889705254753, -0.23621708678866238, 0.3626129688848167, 0.12294052395816535, 0.21006504099254739, 0.1638730311995908, 0.2243906400638492, 0.0947082811340208, 0.028094918435209826, 0.12888549966737628, 0.1348803617978749, 0.24796009574034442, -0.026049271162140043, -0.0950101880956288, 0.09995367350248135, 0.1750516209955493] |
1,802.06406 | Predicting B Cell Receptor Substitution Profiles Using Public Repertoire
Data | B cells develop high affinity receptors during the course of affinity
maturation, a cyclic process of mutation and selection. At the end of affinity
maturation, a number of cells sharing the same ancestor (i.e. in the same
"clonal family") are released from the germinal center, their amino acid
frequency profile reflects the allowed and disallowed substitutions at each
position. These clonal-family-specific frequency profiles, called "substitution
profiles", are useful for studying the course of affinity maturation as well as
for antibody engineering purposes. However, most often only a single sequence
is recovered from each clonal family in a sequencing experiment, making it
impossible to construct a clonal-family-specific substitution profile. Given
the public release of many high-quality large B cell receptor datasets, one may
ask whether it is possible to use such data in a prediction model for
clonal-family-specific substitution profiles. In this paper, we present the
method "Substitution Profiles Using Related Families" (SPURF), a penalized
tensor regression framework that integrates information from a rich assemblage
of datasets to predict the clonal-family-specific substitution profile for any
single input sequence. Using this framework, we show that substitution profiles
from similar clonal families can be leveraged together with simulated
substitution profiles and germline gene sequence information to improve
prediction. We fit this model on a large public dataset and validate the
robustness of our approach on an external dataset. Furthermore, we provide a
command-line tool in an open-source software package
(https://github.com/krdav/SPURF) implementing these ideas and providing easy
prediction using our pre-fit models.
| q-bio.BM q-bio.GN | b cells develop high affinity receptors during the course of affinity maturation a cyclic process of mutation and selection at the end of affinity maturation a number of cells sharing the same ancestor ie in the same clonal family are released from the germinal center their amino acid frequency profile reflects the allowed and disallowed substitutions at each position these clonalfamilyspecific frequency profiles called substitution profiles are useful for studying the course of affinity maturation as well as for antibody engineering purposes however most often only a single sequence is recovered from each clonal family in a sequencing experiment making it impossible to construct a clonalfamilyspecific substitution profile given the public release of many highquality large b cell receptor datasets one may ask whether it is possible to use such data in a prediction model for clonalfamilyspecific substitution profiles in this paper we present the method substitution profiles using related families spurf a penalized tensor regression framework that integrates information from a rich assemblage of datasets to predict the clonalfamilyspecific substitution profile for any single input sequence using this framework we show that substitution profiles from similar clonal families can be leveraged together with simulated substitution profiles and germline gene sequence information to improve prediction we fit this model on a large public dataset and validate the robustness of our approach on an external dataset furthermore we provide a commandline tool in an opensource software package httpsgithubcomkrdavspurf implementing these ideas and providing easy prediction using our prefit models | [['b', 'cells', 'develop', 'high', 'affinity', 'receptors', 'during', 'the', 'course', 'of', 'affinity', 'maturation', 'a', 'cyclic', 'process', 'of', 'mutation', 'and', 'selection', 'at', 'the', 'end', 'of', 'affinity', 'maturation', 'a', 'number', 'of', 'cells', 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1,802.06407 | Systematic elimination of Stokes divergences emanating from complex
phase space caustics | Stokes phenomenon refers to the fact that the asymptotic expansion of complex
functions can differ in different regions of the complex plane, and that beyond
the so-called Stokes lines has an unphysical divergence. An important special
case is when the Stokes lines emanate from phase space caustics of a complex
trajectory manifold. In this case, symmetry determines that to second order
there is a double coverage of the space, one portion of which is unphysical.
Building on the seminal but laconic findings of Adachi, we show that the
deviation from second order can be used to rigorously determine the Stokes
lines and therefore the region of the space that should be removed. The method
has applications to wavepacket reconstruction from complex valued classical
trajectories. With a rigorous method in hand for removing unphysical
divergences, we demonstrate excellent wavepacket reconstruction for the Morse,
Quartic, Coulomb and Eckart systems.
| quant-ph | stokes phenomenon refers to the fact that the asymptotic expansion of complex functions can differ in different regions of the complex plane and that beyond the socalled stokes lines has an unphysical divergence an important special case is when the stokes lines emanate from phase space caustics of a complex trajectory manifold in this case symmetry determines that to second order there is a double coverage of the space one portion of which is unphysical building on the seminal but laconic findings of adachi we show that the deviation from second order can be used to rigorously determine the stokes lines and therefore the region of the space that should be removed the method has applications to wavepacket reconstruction from complex valued classical trajectories with a rigorous method in hand for removing unphysical divergences we demonstrate excellent wavepacket reconstruction for the morse quartic coulomb and eckart systems | [['stokes', 'phenomenon', 'refers', 'to', 'the', 'fact', 'that', 'the', 'asymptotic', 'expansion', 'of', 'complex', 'functions', 'can', 'differ', 'in', 'different', 'regions', 'of', 'the', 'complex', 'plane', 'and', 'that', 'beyond', 'the', 'socalled', 'stokes', 'lines', 'has', 'an', 'unphysical', 'divergence', 'an', 'important', 'special', 'case', 'is', 'when', 'the', 'stokes', 'lines', 'emanate', 'from', 'phase', 'space', 'caustics', 'of', 'a', 'complex', 'trajectory', 'manifold', 'in', 'this', 'case', 'symmetry', 'determines', 'that', 'to', 'second', 'order', 'there', 'is', 'a', 'double', 'coverage', 'of', 'the', 'space', 'one', 'portion', 'of', 'which', 'is', 'unphysical', 'building', 'on', 'the', 'seminal', 'but', 'laconic', 'findings', 'of', 'adachi', 'we', 'show', 'that', 'the', 'deviation', 'from', 'second', 'order', 'can', 'be', 'used', 'to', 'rigorously', 'determine', 'the', 'stokes', 'lines', 'and', 'therefore', 'the', 'region', 'of', 'the', 'space', 'that', 'should', 'be', 'removed', 'the', 'method', 'has', 'applications', 'to', 'wavepacket', 'reconstruction', 'from', 'complex', 'valued', 'classical', 'trajectories', 'with', 'a', 'rigorous', 'method', 'in', 'hand', 'for', 'removing', 'unphysical', 'divergences', 'we', 'demonstrate', 'excellent', 'wavepacket', 'reconstruction', 'for', 'the', 'morse', 'quartic', 'coulomb', 'and', 'eckart', 'systems']] | [-0.10369577069234635, 0.08156080056971009, -0.10136238005341722, 0.06971540535977554, -0.08771034476163538, -0.09768420461324506, 0.011903356228555952, 0.33681467063978415, -0.2599011780694127, -0.2446988571409871, 0.07076755975734214, -0.2719955382168572, -0.18158062533507136, 0.2042560501049469, -0.08746737699348284, 0.022493780251643083, 0.05044714083616324, 0.021465790331312993, -0.07328906390328138, -0.19699797876888797, 0.35490024836138395, 0.013123892520302527, 0.24352924855185204, 0.03808127747861301, 0.08763786222069797, 0.017597119719879765, 0.011236184808824743, 0.027309690163586427, -0.09821041420362074, 0.1018057107912744, 0.22759811132734475, 0.0945450906217301, 0.24201459955854887, -0.382007137599851, -0.2542690444788357, 0.1256759404109753, 0.20081825959211103, 0.133217303000777, -0.0019006373932534436, -0.27189039362619827, 0.04899345171720195, -0.08879120538619403, -0.17760137575013296, -0.08477451023804088, 0.013660354552423062, -0.0011587237244706323, -0.2668480317101998, 0.05533431702908002, 0.05296753741940167, 0.039035442687545704, -0.02320617882195911, -0.07692400066714201, -0.04257284382636957, 0.1351351427814375, 0.0498888779183704, 0.047698559331371876, 0.09953252242349063, -0.11426431115647005, -0.07028135828211346, 0.40508982525872334, -0.058022718572494934, -0.20874909541700717, 0.16459163022385973, -0.18390059215808605, -0.11185639128279017, 0.20495727654866444, 0.13134651925085353, 0.1309082905324746, -0.09152955523120686, 0.11172178535774464, -0.03793409591553365, 0.14469340063479483, 0.10244458254908217, -0.01644465871959874, 0.16719610009621194, 0.06257855705758493, 0.09084347460963794, 0.1262364606923411, -0.10848521102112116, -0.14211362912034503, -0.34530589080789464, -0.15863639104724894, -0.1950807184983539, 0.024386766114823367, -0.09430275554263878, -0.18933329741996366, 0.3869737353055899, 0.1331727493781641, 0.1948459654203838, -0.009064090819110726, 0.2923674117409478, 0.1515854845919526, 0.059663615664657284, 0.04927517312458482, 0.26657270989222387, 0.1131072489253315, 0.09762111290668447, -0.2061635972571648, 0.024562422360363257, 0.09348168427466738] |
1,802.06408 | A study of the HI and optical properties of Low Surface Brightness
galaxies: spirals, dwarfs and irregulars | We present a study of the HI and optical properties of nearby ($z$ $\le$ 0.1)
Low Surface Brightness galaxies (LSBGs). We started with a literature sample of
$\sim$900 LSBGs and divided them into three morphological classes: spirals,
irregulars and dwarfs. Of these, we could use $\sim$490 LSBGs to study their HI
and stellar masses, colours and colour magnitude diagrams, and local
environment, compare them with normal, High Surface Brightness (HSB) galaxies
and determine the differences between the three morphological classes. We found
that LSB and HSB galaxies span a similar range in HI and stellar masses, and
have a similar $M_{\rm HI}$/$M_{\star}$--$M_{\star}$ relationship. Among the
LSBGs, as expected, the spirals have the highest average HI and stellar masses,
both of about 10$^{9.8}$ $M_\odot$. The LSGBs' ($g$--$r$) integrated colour is
nearly constant as function of HI mass for all classes. In the colour magnitude
diagram, the spirals are spread over the red and blue regions whereas the
irregulars and dwarfs are confined to the blue region. The spirals also exhibit
a steeper slope in the $M_{\rm HI}$/$M_{\star}$--$M_{\star}$ plane. Within
their local environment we confirmed that LSBGs are more isolated than HSB
galaxies, and LSB spirals more isolated than irregulars and dwarfs.
Kolmogorov-Smirnov statistical tests on the HI mass, stellar mass and number of
neighbours indicates that the spirals are a statistically different population
from the dwarfs and irregulars. This suggests that the spirals may have
different formation and HI evolution than the dwarfs and irregulars.
| astro-ph.GA | we present a study of the hi and optical properties of nearby z le 01 low surface brightness galaxies lsbgs we started with a literature sample of sim900 lsbgs and divided them into three morphological classes spirals irregulars and dwarfs of these we could use sim490 lsbgs to study their hi and stellar masses colours and colour magnitude diagrams and local environment compare them with normal high surface brightness hsb galaxies and determine the differences between the three morphological classes we found that lsb and hsb galaxies span a similar range in hi and stellar masses and have a similar m_rm him_starm_star relationship among the lsbgs as expected the spirals have the highest average hi and stellar masses both of about 1098 m_odot the lsgbs gr integrated colour is nearly constant as function of hi mass for all classes in the colour magnitude diagram the spirals are spread over the red and blue regions whereas the irregulars and dwarfs are confined to the blue region the spirals also exhibit a steeper slope in the m_rm him_starm_star plane within their local environment we confirmed that lsbgs are more isolated than hsb galaxies and lsb spirals more isolated than irregulars and dwarfs kolmogorovsmirnov statistical tests on the hi mass stellar mass and number of neighbours indicates that the spirals are a statistically different population from the dwarfs and irregulars this suggests that the spirals may have different formation and hi evolution than the dwarfs and irregulars | [['we', 'present', 'a', 'study', 'of', 'the', 'hi', 'and', 'optical', 'properties', 'of', 'nearby', 'z', 'le', '01', 'low', 'surface', 'brightness', 'galaxies', 'lsbgs', 'we', 'started', 'with', 'a', 'literature', 'sample', 'of', 'sim900', 'lsbgs', 'and', 'divided', 'them', 'into', 'three', 'morphological', 'classes', 'spirals', 'irregulars', 'and', 'dwarfs', 'of', 'these', 'we', 'could', 'use', 'sim490', 'lsbgs', 'to', 'study', 'their', 'hi', 'and', 'stellar', 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1,802.06409 | The many-faceted light curves of young disk-bearing stars in Upper Sco
and $\rho$ Oph observed by $K2$ Campaign 2 | The $K2$ Mission has photometrically monitored thousands of stars at high
precision and cadence in a series of $\sim$80-day campaigns focused on sections
of the ecliptic plane. During its second campaign, $K2$ targeted over 1000
young stellar objects (YSOs) in the $\sim$1-3 Myr $\rho$ Ophiuchus and 5-10 Myr
Upper Scorpius regions. From this set, we have carefully vetted photometry from
{\em WISE} and {\em Spitzer} to identify those YSOs with infrared excess
indicative of primordial circumstellar disks. We present here the resulting
comprehensive sample of 288 young disk-bearing stars from B through M spectral
types and analysis of their associated $K2$ light curves. Using statistics of
periodicity and symmetry, we categorize each light curves into eight different
variability classes, notably including "dippers" (fading events), "bursters"
(brightening events), stochastic, and quasi-periodic types. Nearly all (96\%)
of disk-bearing YSOs are identified as variable at 30-minute cadence with the
sub-1\% precision of {\em K2}. Combining our variability classifications with
(circum)stellar properties, we find that the bursters, stochastic sources, and
the largest amplitude quasi-periodic stars have larger infrared colors, and
hence stronger circumstellar disks. They also tend to have larger H$\alpha$
equivalent widths, indicative of higher accretion rates. The dippers, on the
other hand, cluster toward moderate infrared colors and low H$\alpha$. Using
resolved disk observations, we further find that the latter favor high
inclinations, apart from a few notable exceptions with close to face-on disks.
These observations support the idea that YSO time domain properties are
dependent on several factors including accretion rate and view angle.
| astro-ph.SR | the k2 mission has photometrically monitored thousands of stars at high precision and cadence in a series of sim80day campaigns focused on sections of the ecliptic plane during its second campaign k2 targeted over 1000 young stellar objects ysos in the sim13 myr rho ophiuchus and 510 myr upper scorpius regions from this set we have carefully vetted photometry from em wise and em spitzer to identify those ysos with infrared excess indicative of primordial circumstellar disks we present here the resulting comprehensive sample of 288 young diskbearing stars from b through m spectral types and analysis of their associated k2 light curves using statistics of periodicity and symmetry we categorize each light curves into eight different variability classes notably including dippers fading events bursters brightening events stochastic and quasiperiodic types nearly all 96 of diskbearing ysos are identified as variable at 30minute cadence with the sub1 precision of em k2 combining our variability classifications with circumstellar properties we find that the bursters stochastic sources and the largest amplitude quasiperiodic stars have larger infrared colors and hence stronger circumstellar disks they also tend to have larger halpha equivalent widths indicative of higher accretion rates the dippers on the other hand cluster toward moderate infrared colors and low halpha using resolved disk observations we further find that the latter favor high inclinations apart from a few notable exceptions with close to faceon disks these observations support the idea that yso time domain properties are dependent on several factors including accretion rate and view angle | [['the', 'k2', 'mission', 'has', 'photometrically', 'monitored', 'thousands', 'of', 'stars', 'at', 'high', 'precision', 'and', 'cadence', 'in', 'a', 'series', 'of', 'sim80day', 'campaigns', 'focused', 'on', 'sections', 'of', 'the', 'ecliptic', 'plane', 'during', 'its', 'second', 'campaign', 'k2', 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1,802.0641 | Emergence of oscillatory behaviors for excitable systems with noise and
mean-field interaction, a slow-fast dynamics approach | We consider the long-time dynamics of a general class of nonlinear
Fokker-Planck equations, describing the large population behavior of mean-field
interacting units. The main motivation of this work concerns the case where the
individual dynamics is excitable, i.e. when each isolated dynamics rests in a
stable state, whereas a sufficiently strong perturbation induces a large
excursion in the phase space. We address the question of the emergence of
oscillatory behaviors induced by noise and interaction in such systems. We
tackle this problem by considering this model as a slow-fast system (the mean
value of the process giving the slow dynamics) in the regime of small
individual dynamics and by proving the existence of a positively stable
invariant manifold, whose slow dynamics is at first order the dynamics of a
single individual averaged with a Gaussian kernel. We consider applications of
this result to Stuart-Landau, FitzHugh-Nagumo and Cucker-Smale oscillators.
| math.AP math-ph math.DS math.MP math.PR nlin.AO | we consider the longtime dynamics of a general class of nonlinear fokkerplanck equations describing the large population behavior of meanfield interacting units the main motivation of this work concerns the case where the individual dynamics is excitable ie when each isolated dynamics rests in a stable state whereas a sufficiently strong perturbation induces a large excursion in the phase space we address the question of the emergence of oscillatory behaviors induced by noise and interaction in such systems we tackle this problem by considering this model as a slowfast system the mean value of the process giving the slow dynamics in the regime of small individual dynamics and by proving the existence of a positively stable invariant manifold whose slow dynamics is at first order the dynamics of a single individual averaged with a gaussian kernel we consider applications of this result to stuartlandau fitzhughnagumo and cuckersmale oscillators | [['we', 'consider', 'the', 'longtime', 'dynamics', 'of', 'a', 'general', 'class', 'of', 'nonlinear', 'fokkerplanck', 'equations', 'describing', 'the', 'large', 'population', 'behavior', 'of', 'meanfield', 'interacting', 'units', 'the', 'main', 'motivation', 'of', 'this', 'work', 'concerns', 'the', 'case', 'where', 'the', 'individual', 'dynamics', 'is', 'excitable', 'ie', 'when', 'each', 'isolated', 'dynamics', 'rests', 'in', 'a', 'stable', 'state', 'whereas', 'a', 'sufficiently', 'strong', 'perturbation', 'induces', 'a', 'large', 'excursion', 'in', 'the', 'phase', 'space', 'we', 'address', 'the', 'question', 'of', 'the', 'emergence', 'of', 'oscillatory', 'behaviors', 'induced', 'by', 'noise', 'and', 'interaction', 'in', 'such', 'systems', 'we', 'tackle', 'this', 'problem', 'by', 'considering', 'this', 'model', 'as', 'a', 'slowfast', 'system', 'the', 'mean', 'value', 'of', 'the', 'process', 'giving', 'the', 'slow', 'dynamics', 'in', 'the', 'regime', 'of', 'small', 'individual', 'dynamics', 'and', 'by', 'proving', 'the', 'existence', 'of', 'a', 'positively', 'stable', 'invariant', 'manifold', 'whose', 'slow', 'dynamics', 'is', 'at', 'first', 'order', 'the', 'dynamics', 'of', 'a', 'single', 'individual', 'averaged', 'with', 'a', 'gaussian', 'kernel', 'we', 'consider', 'applications', 'of', 'this', 'result', 'to', 'stuartlandau', 'fitzhughnagumo', 'and', 'cuckersmale', 'oscillators']] | [-0.19693949855423556, 0.16071072250692728, -0.06398321292520426, 0.04941412614471119, 0.004672014151347449, -0.1252727026144999, 0.010203696522276496, 0.27992198256892936, -0.3099428922743411, -0.25806070411124743, 0.08226797476920576, -0.24819040497941142, -0.20768310852125413, 0.1237312826576542, -0.02722484362547638, 0.035843692889839816, 0.0678826341990734, 0.043405079341027886, -0.003395242034457624, -0.19008021113443868, 0.3635877175075694, 0.014595850886827385, 0.2508932651096099, -0.03291099478342772, 0.1462574968794109, 0.007352748588419746, 0.04228867823572678, 0.032067523523339234, -0.11759372451814597, 0.10068546574660325, 0.2019684501940139, 0.046276840601569495, 0.3448770116775523, -0.4222536968772073, -0.231934738053226, 0.12111329309472411, 0.14818921450028397, 0.15338059324720824, -0.01948041935227937, -0.2932958352502209, 0.03251256947279782, -0.13379390189240095, -0.20261364095416423, -0.04635704266272385, 0.03537592282864844, 0.06965891129456812, -0.25953509001615077, 0.10842843755223863, 0.11695761209970491, 0.05338476393965696, -0.06524460877895959, -0.003255233047467128, 0.010280489400847236, 0.13407012319127004, 0.03766686412269042, -0.034159314548093324, 0.11899754654842655, -0.15401764893337982, -0.07361818043942991, 0.37033347466746597, -0.13624941628045603, -0.2121302364519923, 0.19114590510474266, -0.1654617544924337, -0.14008179047094607, 0.13944205836191573, 0.18724604485229263, 0.16160862158820335, -0.16456184086181, 0.1013125611608376, -0.02219835966762558, 0.14814882496736842, 0.0005554767778596362, 0.011224096381763072, 0.17795247036485454, 0.25271987017067904, 0.06356358002695078, 0.1658282137084186, -0.04236987205473958, -0.2017088854792402, -0.2821913264263925, -0.09390179196536239, -0.14617939847458555, 0.11600220205444792, -0.06895389319745575, -0.19275102962588742, 0.43190492861400787, 0.11984507505769364, 0.23028560745454318, 0.05328245604775746, 0.26632779533974826, 0.1517965612088242, -0.033295356558409296, 0.054868913598585166, 0.21022829045289876, 0.14231282746658433, 0.09534094184385361, -0.26804172768685464, 0.057021001196541896, 0.06246351563321376] |
1,802.06411 | Magnetoelectric effect and orbital magnetization in skyrmion crystals:
Detection and characterization of skyrmions | Skyrmions are small magnetic quasiparticles, which are uniquely characterized
by their topological charge and their helicity. In this Rapid Communication, we
show via calculations how both properties can be determined without relying on
real-space imaging. The orbital magnetization and topological Hall conductivity
measure the arising magnetization due to the circulation of electrons in the
bulk and the occurrence of topologically protected edge channels due to the
emergent field of a skyrmion crystal. Both observables quantify the topological
Hall effect and distinguish skyrmions from antiskyrmions by sign. Additionally,
we predict a magnetoelectric effect in skyrmion crystals, which is the
generation of a magnetization (polarization) by application of an electric
(magnetic) field. This effect is quantified by spin toroidization and
magnetoelectric polarizability. The dependence of the transverse
magnetoelectric effect on the skyrmion helicity fits that of the classical
toroidal moment of the spin texture and allows to differentiate skyrmion
helicities: it is largest for Bloch skyrmions and zero for Neel skyrmions. We
predict distinct features of the four observables that can be used to detect
and characterize skyrmions in experiments.
| cond-mat.str-el | skyrmions are small magnetic quasiparticles which are uniquely characterized by their topological charge and their helicity in this rapid communication we show via calculations how both properties can be determined without relying on realspace imaging the orbital magnetization and topological hall conductivity measure the arising magnetization due to the circulation of electrons in the bulk and the occurrence of topologically protected edge channels due to the emergent field of a skyrmion crystal both observables quantify the topological hall effect and distinguish skyrmions from antiskyrmions by sign additionally we predict a magnetoelectric effect in skyrmion crystals which is the generation of a magnetization polarization by application of an electric magnetic field this effect is quantified by spin toroidization and magnetoelectric polarizability the dependence of the transverse magnetoelectric effect on the skyrmion helicity fits that of the classical toroidal moment of the spin texture and allows to differentiate skyrmion helicities it is largest for bloch skyrmions and zero for neel skyrmions we predict distinct features of the four observables that can be used to detect and characterize skyrmions in experiments | [['skyrmions', 'are', 'small', 'magnetic', 'quasiparticles', 'which', 'are', 'uniquely', 'characterized', 'by', 'their', 'topological', 'charge', 'and', 'their', 'helicity', 'in', 'this', 'rapid', 'communication', 'we', 'show', 'via', 'calculations', 'how', 'both', 'properties', 'can', 'be', 'determined', 'without', 'relying', 'on', 'realspace', 'imaging', 'the', 'orbital', 'magnetization', 'and', 'topological', 'hall', 'conductivity', 'measure', 'the', 'arising', 'magnetization', 'due', 'to', 'the', 'circulation', 'of', 'electrons', 'in', 'the', 'bulk', 'and', 'the', 'occurrence', 'of', 'topologically', 'protected', 'edge', 'channels', 'due', 'to', 'the', 'emergent', 'field', 'of', 'a', 'skyrmion', 'crystal', 'both', 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1,802.06412 | Improved TDNNs using Deep Kernels and Frequency Dependent Grid-RNNs | Time delay neural networks (TDNNs) are an effective acoustic model for large
vocabulary speech recognition. The strength of the model can be attributed to
its ability to effectively model long temporal contexts. However, current TDNN
models are relatively shallow, which limits the modelling capability. This
paper proposes a method of increasing the network depth by deepening the kernel
used in the TDNN temporal convolutions. The best performing kernel consists of
three fully connected layers with a residual (ResNet) connection from the
output of the first to the output of the third. The addition of
spectro-temporal processing as the input to the TDNN in the form of a
convolutional neural network (CNN) and a newly designed Grid-RNN was
investigated. The Grid-RNN strongly outperforms a CNN if different sets of
parameters for different frequency bands are used and can be further enhanced
by using a bi-directional Grid-RNN. Experiments using the multi-genre broadcast
(MGB3) English data (275h) show that deep kernel TDNNs reduces the word error
rate (WER) by 6% relative and when combined with the frequency dependent
Grid-RNN gives a relative WER reduction of 9%.
| cs.CL cs.AI cs.SD eess.AS stat.ML | time delay neural networks tdnns are an effective acoustic model for large vocabulary speech recognition the strength of the model can be attributed to its ability to effectively model long temporal contexts however current tdnn models are relatively shallow which limits the modelling capability this paper proposes a method of increasing the network depth by deepening the kernel used in the tdnn temporal convolutions the best performing kernel consists of three fully connected layers with a residual resnet connection from the output of the first to the output of the third the addition of spectrotemporal processing as the input to the tdnn in the form of a convolutional neural network cnn and a newly designed gridrnn was investigated the gridrnn strongly outperforms a cnn if different sets of parameters for different frequency bands are used and can be further enhanced by using a bidirectional gridrnn experiments using the multigenre broadcast mgb3 english data 275h show that deep kernel tdnns reduces the word error rate wer by 6 relative and when combined with the frequency dependent gridrnn gives a relative wer reduction of 9 | [['time', 'delay', 'neural', 'networks', 'tdnns', 'are', 'an', 'effective', 'acoustic', 'model', 'for', 'large', 'vocabulary', 'speech', 'recognition', 'the', 'strength', 'of', 'the', 'model', 'can', 'be', 'attributed', 'to', 'its', 'ability', 'to', 'effectively', 'model', 'long', 'temporal', 'contexts', 'however', 'current', 'tdnn', 'models', 'are', 'relatively', 'shallow', 'which', 'limits', 'the', 'modelling', 'capability', 'this', 'paper', 'proposes', 'a', 'method', 'of', 'increasing', 'the', 'network', 'depth', 'by', 'deepening', 'the', 'kernel', 'used', 'in', 'the', 'tdnn', 'temporal', 'convolutions', 'the', 'best', 'performing', 'kernel', 'consists', 'of', 'three', 'fully', 'connected', 'layers', 'with', 'a', 'residual', 'resnet', 'connection', 'from', 'the', 'output', 'of', 'the', 'first', 'to', 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1,802.06413 | New spinor classes on the Graf-Clifford algebra | Pinor and spinor fields are sections of the subbundles whose fibers are the
representation spaces of the Clifford algebra of the forms, equipped with the
Graf product. In this context, pinors and spinors are here considered and the
geometric generalized Fierz identities provide the necessary framework to
derive and construct new spinor classes on the space of smooth sections of the
exterior bundle, endowed with the Graf product, for prominent specific
signatures, whose applications are discussed.
| math-ph math.MP | pinor and spinor fields are sections of the subbundles whose fibers are the representation spaces of the clifford algebra of the forms equipped with the graf product in this context pinors and spinors are here considered and the geometric generalized fierz identities provide the necessary framework to derive and construct new spinor classes on the space of smooth sections of the exterior bundle endowed with the graf product for prominent specific signatures whose applications are discussed | [['pinor', 'and', 'spinor', 'fields', 'are', 'sections', 'of', 'the', 'subbundles', 'whose', 'fibers', 'are', 'the', 'representation', 'spaces', 'of', 'the', 'clifford', 'algebra', 'of', 'the', 'forms', 'equipped', 'with', 'the', 'graf', 'product', 'in', 'this', 'context', 'pinors', 'and', 'spinors', 'are', 'here', 'considered', 'and', 'the', 'geometric', 'generalized', 'fierz', 'identities', 'provide', 'the', 'necessary', 'framework', 'to', 'derive', 'and', 'construct', 'new', 'spinor', 'classes', 'on', 'the', 'space', 'of', 'smooth', 'sections', 'of', 'the', 'exterior', 'bundle', 'endowed', 'with', 'the', 'graf', 'product', 'for', 'prominent', 'specific', 'signatures', 'whose', 'applications', 'are', 'discussed']] | [-0.1571313050808385, 0.10404535128097785, -0.02569430257886109, 0.07529418098611611, -0.113461264617447, -0.11315062397012585, -0.09756953646673967, 0.3507819428402734, -0.24630205676045366, -0.22141375010342976, 0.11449305544527688, -0.22209889950279735, -0.16823359451403744, 0.20115842627618755, -0.07302059178657241, -0.012280700630263278, 0.009102372109497847, 0.10805315516719068, -0.14437475609348008, -0.2590842957648228, 0.4879616281311763, -0.021860045082193164, 0.2498166083394991, 0.025978189563734065, 0.15317689329630843, 0.01578870011297496, -0.05544415780490166, -0.06217572126747415, -0.1466193945931369, 0.20212110606524603, 0.24793294331941165, 0.09267063594521269, 0.12675303780767871, -0.42001609179485394, -0.13353943754918873, 0.1348670612297658, 0.08284232325508799, -0.01938310737329486, -0.002169454220596603, -0.34137702926895336, 0.02644764109343094, -0.1562984591889146, -0.1415153132800601, -0.16636307271638592, 0.013224789793112953, 0.02819006724626218, -0.23012290526745155, -0.003270312132755, 0.04786755610104209, 0.08310693389687099, -0.11001357378891523, -0.12330844640535743, -0.07253501865105998, 0.05963870435708055, -0.013527686704611895, -0.009428276426134337, 0.09208101235134036, -0.0789057182754684, -0.1562891796991033, 0.37807412239673893, -0.027034245909721664, -0.3013366482857811, 0.12840515429056004, -0.12075098376034905, -0.1376589962134236, 0.08146947998504497, 0.15271116141229868, 0.13908997410908341, -0.08256744654653103, 0.14262396715716213, -0.06246116176541699, -0.0068690381380484295, 0.0942282039108441, 0.06843838740238234, 0.17538860736806927, 0.07605367041143932, 0.023331074780894835, 0.12315692854003589, -0.008428831404001502, -0.11372478330419031, -0.4158847341804128, -0.26232899350457284, -0.06070226444372613, 0.06965896851187081, -0.07927114774984627, -0.17750054253510347, 0.38960420383802175, 0.013931304197812048, 0.18977981023980597, 0.05004874190107282, 0.2187380480831244, 0.11113973852786187, 0.1131681913362914, 0.03451167447737565, 0.17969802666553542, 0.2722638991024149, 0.04976797470896456, -0.10735609725509819, -0.05423592165492377, 0.13235478343650406] |
1,802.06414 | Magnetoanisotropic spin-triplet Andreev reflection in ferromagnet-Ising
superconductor junctions | We theoretically study the electronic transport through a ferromagnet-Ising
superconductor junction. A tight-binding Hamiltonian describing the Ising
superconductor is presented. Then by combing the non-equilibrium Green's
function method, the expressions of Andreev reflection coefficient and
conductance are obtained. A strong magnetoanisotropic spin-triplet Andreev
reflection is shown, and the magnetoanisotropic period is $\pi$ instead of
$2\pi$ as in the conventional magnetoanisotropic system. We demonstrate a
significant increase of the spin-triplet Andreev reflection for the single-band
Ising superconductor. Furthermore, the dependence of the Andreev reflection on
the incident energy and incident angle are also investigated. A complete
Andreev reflection can occur when the incident energy is equal to the
superconductor gap, regardless of the Fermi energy (spin polarization) of the
ferromagnet. For the suitable oblique incidence, the spin-triplet Andreev
reflection can be strongly enhanced. In addition, the conductance
spectroscopies of both zero bias and finite bias are studied, and the influence
of gate voltage, exchange energy, and spin-orbit coupling on the conductance
spectroscopy are discussed in detail. The conductance reveals a strong
magnetoanisotropy with period $\pi$ as the Andreev reflection coefficient. When
the magnetization direction is parallel to the junction plane, a large
conductance peak always emerges at the superconductor gap. This work offers a
comprehensive and systematic study of the spin-triplet Andreev reflection, and
has underlying application of $\pi$-periodic spin valve in spintronics.
| cond-mat.supr-con | we theoretically study the electronic transport through a ferromagnetising superconductor junction a tightbinding hamiltonian describing the ising superconductor is presented then by combing the nonequilibrium greens function method the expressions of andreev reflection coefficient and conductance are obtained a strong magnetoanisotropic spintriplet andreev reflection is shown and the magnetoanisotropic period is pi instead of 2pi as in the conventional magnetoanisotropic system we demonstrate a significant increase of the spintriplet andreev reflection for the singleband ising superconductor furthermore the dependence of the andreev reflection on the incident energy and incident angle are also investigated a complete andreev reflection can occur when the incident energy is equal to the superconductor gap regardless of the fermi energy spin polarization of the ferromagnet for the suitable oblique incidence the spintriplet andreev reflection can be strongly enhanced in addition the conductance spectroscopies of both zero bias and finite bias are studied and the influence of gate voltage exchange energy and spinorbit coupling on the conductance spectroscopy are discussed in detail the conductance reveals a strong magnetoanisotropy with period pi as the andreev reflection coefficient when the magnetization direction is parallel to the junction plane a large conductance peak always emerges at the superconductor gap this work offers a comprehensive and systematic study of the spintriplet andreev reflection and has underlying application of piperiodic spin valve in spintronics | [['we', 'theoretically', 'study', 'the', 'electronic', 'transport', 'through', 'a', 'ferromagnetising', 'superconductor', 'junction', 'a', 'tightbinding', 'hamiltonian', 'describing', 'the', 'ising', 'superconductor', 'is', 'presented', 'then', 'by', 'combing', 'the', 'nonequilibrium', 'greens', 'function', 'method', 'the', 'expressions', 'of', 'andreev', 'reflection', 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1,802.06415 | Solving Large-Scale Minimum-Weight Triangulation Instances to Provable
Optimality | We consider practical methods for the problem of finding a minimum-weight
triangulation (MWT) of a planar point set, a classic problem of computational
geometry with many applications. While Mulzer and Rote proved in 2006 that
computing an MWT is NP-hard, Beirouti and Snoeyink showed in 1998 that
computing provably optimal solutions for MWT instances of up to 80,000
uniformly distributed points is possible, making use of clever heuristics that
are based on geometric insights. We show that these techniques can be refined
and extended to instances of much bigger size and different type, based on an
array of modifications and parallelizations in combination with more efficient
geometric encodings and data structures. As a result, we are able to solve MWT
instances with up to 30,000,000 uniformly distributed points in less than 4
minutes to provable optimality. Moreover, we can compute optimal solutions for
a vast array of other benchmark instances that are not uniformly distributed,
including normally distributed instances (up to 30,000,000 points), all point
sets in the TSPLIB (up to 85,900 points), and VLSI instances with up to 744,710
points. This demonstrates that from a practical point of view, MWT instances
can be handled quite well, despite their theoretical difficulty.
| cs.CG | we consider practical methods for the problem of finding a minimumweight triangulation mwt of a planar point set a classic problem of computational geometry with many applications while mulzer and rote proved in 2006 that computing an mwt is nphard beirouti and snoeyink showed in 1998 that computing provably optimal solutions for mwt instances of up to 80000 uniformly distributed points is possible making use of clever heuristics that are based on geometric insights we show that these techniques can be refined and extended to instances of much bigger size and different type based on an array of modifications and parallelizations in combination with more efficient geometric encodings and data structures as a result we are able to solve mwt instances with up to 30000000 uniformly distributed points in less than 4 minutes to provable optimality moreover we can compute optimal solutions for a vast array of other benchmark instances that are not uniformly distributed including normally distributed instances up to 30000000 points all point sets in the tsplib up to 85900 points and vlsi instances with up to 744710 points this demonstrates that from a practical point of view mwt instances can be handled quite well despite their theoretical difficulty | [['we', 'consider', 'practical', 'methods', 'for', 'the', 'problem', 'of', 'finding', 'a', 'minimumweight', 'triangulation', 'mwt', 'of', 'a', 'planar', 'point', 'set', 'a', 'classic', 'problem', 'of', 'computational', 'geometry', 'with', 'many', 'applications', 'while', 'mulzer', 'and', 'rote', 'proved', 'in', '2006', 'that', 'computing', 'an', 'mwt', 'is', 'nphard', 'beirouti', 'and', 'snoeyink', 'showed', 'in', '1998', 'that', 'computing', 'provably', 'optimal', 'solutions', 'for', 'mwt', 'instances', 'of', 'up', 'to', '80000', 'uniformly', 'distributed', 'points', 'is', 'possible', 'making', 'use', 'of', 'clever', 'heuristics', 'that', 'are', 'based', 'on', 'geometric', 'insights', 'we', 'show', 'that', 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1,802.06416 | Sim-to-Real Optimization of Complex Real World Mobile Network with
Imperfect Information via Deep Reinforcement Learning from Self-play | Mobile network that millions of people use every day is one of the most
complex systems in the world. Optimization of mobile network to meet exploding
customer demand and reduce capital/operation expenditures poses great
challenges. Despite recent progress, application of deep reinforcement learning
(DRL) to complex real world problem still remains unsolved, given data
scarcity, partial observability, risk and complex rules/dynamics in real world,
as well as the huge reality gap between simulation and real world. To bridge
the reality gap, we introduce a Sim-to-Real framework to directly transfer
learning from simulation to real world via graph convolutional neural network
(CNN) - by abstracting partially observable mobile network into graph, then
distilling domain-variant irregular graph into domain-invariant tensor in
locally Euclidean space as input to CNN -, domain randomization and multi-task
learning. We use a novel self-play mechanism to encourage competition among DRL
agents for best record on multiple tasks via simulated annealing, just like
athletes compete for world record in decathlon. We also propose a decentralized
multi-agent, competitive and cooperative DRL method to coordinate the actions
of multi-cells to maximize global reward and minimize negative impact to
neighbor cells. Using 6 field trials on commercial mobile networks, we
demonstrate for the first time that a DRL agent can successfully transfer
learning from simulation to complex real world problem with imperfect
information, complex rules/dynamics, huge state/action space, and multi-agent
interactions, without any training in the real world.
| cs.AI cs.LG stat.ML | mobile network that millions of people use every day is one of the most complex systems in the world optimization of mobile network to meet exploding customer demand and reduce capitaloperation expenditures poses great challenges despite recent progress application of deep reinforcement learning drl to complex real world problem still remains unsolved given data scarcity partial observability risk and complex rulesdynamics in real world as well as the huge reality gap between simulation and real world to bridge the reality gap we introduce a simtoreal framework to directly transfer learning from simulation to real world via graph convolutional neural network cnn by abstracting partially observable mobile network into graph then distilling domainvariant irregular graph into domaininvariant tensor in locally euclidean space as input to cnn domain randomization and multitask learning we use a novel selfplay mechanism to encourage competition among drl agents for best record on multiple tasks via simulated annealing just like athletes compete for world record in decathlon we also propose a decentralized multiagent competitive and cooperative drl method to coordinate the actions of multicells to maximize global reward and minimize negative impact to neighbor cells using 6 field trials on commercial mobile networks we demonstrate for the first time that a drl agent can successfully transfer learning from simulation to complex real world problem with imperfect information complex rulesdynamics huge stateaction space and multiagent interactions without any training in the real world | [['mobile', 'network', 'that', 'millions', 'of', 'people', 'use', 'every', 'day', 'is', 'one', 'of', 'the', 'most', 'complex', 'systems', 'in', 'the', 'world', 'optimization', 'of', 'mobile', 'network', 'to', 'meet', 'exploding', 'customer', 'demand', 'and', 'reduce', 'capitaloperation', 'expenditures', 'poses', 'great', 'challenges', 'despite', 'recent', 'progress', 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1,802.06417 | Superthermal photon bunching in terms of simple probability
distributions | We analyze the second-order photon autocorrelation function $g^{(2)}$ with
respect to the photon probability distribution and discuss the generic features
of a distribution that result in superthermal photon bunching ($g^{(2)}>2$).
Superthermal photon bunching has been reported for a number of optical
microcavity systems that exhibit processes like superradiance or mode
competition. We show that a superthermal photon number distribution cannot be
constructed from the principle of maximum entropy, if only the intensity and
the second-order autocorrelation are given. However, for bimodal systems an
unbiased superthermal distribution can be constructed from second-order
correlations and the intensities alone. Our findings suggest modeling
superthermal single-mode distributions by a mixture of a thermal and a lasing
like state and thus reveal a generic mechanism in the photon probability
distribution responsible for creating superthermal photon bunching. We relate
our general considerations to a physical system, a (single-emitter) bimodal
laser, and show that its statistics can be approximated and understood within
our proposed model. Furthermore the excellent agreement of the statistics of
the bimodal laser and our model reveal that the bimodal laser is an ideal
source of bunched photons, in the sense that it can generate statistics that
contain no other features but the superthermal bunching.
| physics.optics quant-ph | we analyze the secondorder photon autocorrelation function g2 with respect to the photon probability distribution and discuss the generic features of a distribution that result in superthermal photon bunching g22 superthermal photon bunching has been reported for a number of optical microcavity systems that exhibit processes like superradiance or mode competition we show that a superthermal photon number distribution cannot be constructed from the principle of maximum entropy if only the intensity and the secondorder autocorrelation are given however for bimodal systems an unbiased superthermal distribution can be constructed from secondorder correlations and the intensities alone our findings suggest modeling superthermal singlemode distributions by a mixture of a thermal and a lasing like state and thus reveal a generic mechanism in the photon probability distribution responsible for creating superthermal photon bunching we relate our general considerations to a physical system a singleemitter bimodal laser and show that its statistics can be approximated and understood within our proposed model furthermore the excellent agreement of the statistics of the bimodal laser and our model reveal that the bimodal laser is an ideal source of bunched photons in the sense that it can generate statistics that contain no other features but the superthermal bunching | [['we', 'analyze', 'the', 'secondorder', 'photon', 'autocorrelation', 'function', 'g2', 'with', 'respect', 'to', 'the', 'photon', 'probability', 'distribution', 'and', 'discuss', 'the', 'generic', 'features', 'of', 'a', 'distribution', 'that', 'result', 'in', 'superthermal', 'photon', 'bunching', 'g22', 'superthermal', 'photon', 'bunching', 'has', 'been', 'reported', 'for', 'a', 'number', 'of', 'optical', 'microcavity', 'systems', 'that', 'exhibit', 'processes', 'like', 'superradiance', 'or', 'mode', 'competition', 'we', 'show', 'that', 'a', 'superthermal', 'photon', 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1,802.06418 | Hot electron cooling in Dirac semimetal Cd$_3$As$_2$ due to polar
optical phonons | A theory of hot electron cooling power due to polar optical phonons $P_{\rm
op}$ is developed in three-dimensional Dirac semimetal($3$DDS) Cd$_3$As$_2$
taking account of hot phonon effect. Hot phonon distribution $N_q$ and $P_{\rm
op}$ are investigated as a function of electron temperature $T_e$, electron
density $n_e$, and phonon relaxation time $\tau_p$. It is found that $P_{\rm
op}$ increases rapidly (slowly) with $T_e$ at lower (higher) temperature
regime. Whereas, $P_{\rm op}$ is weakly deceasing with increasing $n_e$. The
results are compared with those for three-dimensional electron gas ($3$DEG) in
Cd$_3$As$_2$ semiconductor. Hot phonon effect is found to reduce $P_{\rm op}$
considerably and it is stronger in 3DDS Cd$_3$As$_2$ than in Cd$_3$As$_2$
semiconductor. $P_{\rm op}$ is also compared with the hot electron cooling
power due to acoustic phonons $P_{\rm ac}$. We find that a crossover takes
place from $P_{\rm ac}$ dominated cooling at low $T_e$ to $P_{\rm op}$
dominated cooling at higher $T_e$. The temperature at which this crossover
occurs shifts towards higher values with the increase of $n_e$. Also, hot
electron energy relaxation time $\tau_e$ is discussed and estimated.
| cond-mat.mes-hall | a theory of hot electron cooling power due to polar optical phonons p_rm op is developed in threedimensional dirac semimetal3dds cd_3as_2 taking account of hot phonon effect hot phonon distribution n_q and p_rm op are investigated as a function of electron temperature t_e electron density n_e and phonon relaxation time tau_p it is found that p_rm op increases rapidly slowly with t_e at lower higher temperature regime whereas p_rm op is weakly deceasing with increasing n_e the results are compared with those for threedimensional electron gas 3deg in cd_3as_2 semiconductor hot phonon effect is found to reduce p_rm op considerably and it is stronger in 3dds cd_3as_2 than in cd_3as_2 semiconductor p_rm op is also compared with the hot electron cooling power due to acoustic phonons p_rm ac we find that a crossover takes place from p_rm ac dominated cooling at low t_e to p_rm op dominated cooling at higher t_e the temperature at which this crossover occurs shifts towards higher values with the increase of n_e also hot electron energy relaxation time tau_e is discussed and estimated | [['a', 'theory', 'of', 'hot', 'electron', 'cooling', 'power', 'due', 'to', 'polar', 'optical', 'phonons', 'p_rm', 'op', 'is', 'developed', 'in', 'threedimensional', 'dirac', 'semimetal3dds', 'cd_3as_2', 'taking', 'account', 'of', 'hot', 'phonon', 'effect', 'hot', 'phonon', 'distribution', 'n_q', 'and', 'p_rm', 'op', 'are', 'investigated', 'as', 'a', 'function', 'of', 'electron', 'temperature', 't_e', 'electron', 'density', 'n_e', 'and', 'phonon', 'relaxation', 'time', 'tau_p', 'it', 'is', 'found', 'that', 'p_rm', 'op', 'increases', 'rapidly', 'slowly', 'with', 't_e', 'at', 'lower', 'higher', 'temperature', 'regime', 'whereas', 'p_rm', 'op', 'is', 'weakly', 'deceasing', 'with', 'increasing', 'n_e', 'the', 'results', 'are', 'compared', 'with', 'those', 'for', 'threedimensional', 'electron', 'gas', '3deg', 'in', 'cd_3as_2', 'semiconductor', 'hot', 'phonon', 'effect', 'is', 'found', 'to', 'reduce', 'p_rm', 'op', 'considerably', 'and', 'it', 'is', 'stronger', 'in', '3dds', 'cd_3as_2', 'than', 'in', 'cd_3as_2', 'semiconductor', 'p_rm', 'op', 'is', 'also', 'compared', 'with', 'the', 'hot', 'electron', 'cooling', 'power', 'due', 'to', 'acoustic', 'phonons', 'p_rm', 'ac', 'we', 'find', 'that', 'a', 'crossover', 'takes', 'place', 'from', 'p_rm', 'ac', 'dominated', 'cooling', 'at', 'low', 't_e', 'to', 'p_rm', 'op', 'dominated', 'cooling', 'at', 'higher', 't_e', 'the', 'temperature', 'at', 'which', 'this', 'crossover', 'occurs', 'shifts', 'towards', 'higher', 'values', 'with', 'the', 'increase', 'of', 'n_e', 'also', 'hot', 'electron', 'energy', 'relaxation', 'time', 'tau_e', 'is', 'discussed', 'and', 'estimated']] | [-0.11411050265814993, 0.3381530779323922, -0.029755191536175764, 0.03994296801366462, 0.005436045407391662, -0.19048087213410658, 0.054605594985001844, 0.371031222642738, -0.20352098709289831, -0.28553361678496003, -0.05136462919869122, -0.37907567944388243, 0.05566156935475936, 0.2552189588790167, 0.054218874118832486, -0.023385712020254603, -0.07397173910893881, -0.01817268038443713, -0.13486256753094494, -0.17857975567775694, 0.19968959523248486, 0.11404143253193152, 0.286545847407648, 0.1352692704425532, -0.0014029834525321019, -0.01996994623782071, 0.06456955994045446, 0.029674316302010662, -0.15973112447524976, -0.09045735683122819, 0.2783066152637316, -0.0919973070399878, 0.18820947384334763, -0.3693642432759093, -0.24418308403850955, 0.014404112126530063, 0.17888342202852733, 0.05840700359112816, -0.035239159916686316, -0.14429951072353023, 0.02550628276499496, -0.21836705483358607, -0.10397796071695418, -0.03170567467300729, 0.09875417635670271, -0.021294911339117043, -0.2608676186275922, 0.20414183450438114, 0.03703500064412682, 0.08312787512708879, -0.10343218172982399, -0.16138636072388512, -0.10650117839792404, -0.04031717589664781, 0.06402121073254173, 0.12761176146291706, 0.1956510134821821, -0.038438879542809445, 0.020929511451289396, 0.3937893052987585, -0.07763291626220466, -0.005673290590162982, 0.1641303907645951, -0.24242880278457465, -0.04769477214143659, 0.26651475446256384, 0.1291054222965613, 0.0937810185793999, -0.07554537571294614, 0.03179909000507244, 0.03749797510350949, 0.17885190355908973, 0.06902499198490246, 0.08647492022481112, 0.19428043388920327, 0.1581416897666217, 0.04029941999760922, 0.0889024196248184, -0.15052832633690824, -0.03247182826188774, -0.17000715898625043, -0.10937469273763285, -0.17696696270881643, 0.08900545496726409, -0.05845130510351737, -0.08145848888406446, 0.35320570205063134, 0.11648685438492314, 0.2225134894422147, 0.015202718724057459, 0.3432658308778297, 0.26723279769000574, 0.05241682367473417, 0.18764523531982294, 0.22072540472833102, 0.19192963309945876, 0.19288549479295564, -0.347766043046828, 0.04654268100487322, 0.010212103349410674] |
1,802.06419 | Maximizing the number of edges in three-dimensional colored
triangulations whose building blocks are balls | Colored triangulations offer a generalization of combinatorial maps to higher
dimensions. Just like maps are gluings of polygons, colored triangulations are
built as gluings of special, higher-dimensional building blocks, such as
octahedra, which we call colored building blocks and known in the dual as
bubbles. A colored building block is determined by its boundary triangulation,
which in the case of polygons is simply characterized by its length. In three
dimensions, colored building blocks are labeled by some 2D triangulations and
those homeomorphic to the 3-ball are labeled by the subset of planar ones.
Similarly to Euler's formula in 2D which provides an upper bound to the number
of vertices at fixed number of polygons with given lengths, we look in three
dimensions for an upper bound on the number of edges at fixed number of given
colored building blocks. In this article we solve this problem when all colored
building blocks, except possibly one, are homeomorphic to the 3-ball. To do
this, we find a characterization of the way a colored building block
homeomorphic to the ball has to be glued to other blocks of arbitrary topology
in a colored triangulation which maximizes the number of edges. This local
characterization can be extended to the whole triangulation as long as there is
at most one colored building block which is not a 3-ball. The triangulations
obtained this way are in bijection with trees. The number of edges is given as
an independent sum over the building blocks of such a triangulation. In the
case of all colored building blocks being homeomorphic to the 3-ball, we show
that these triangulations are homeomorphic to the 3-sphere. Those results were
only known for the octahedron and for melonic building blocks before. This
article is self-contained and can be used as an introduction to colored
triangulations and their bubbles from a purely combinatorial point of view.
| math.CO gr-qc math-ph math.MP | colored triangulations offer a generalization of combinatorial maps to higher dimensions just like maps are gluings of polygons colored triangulations are built as gluings of special higherdimensional building blocks such as octahedra which we call colored building blocks and known in the dual as bubbles a colored building block is determined by its boundary triangulation which in the case of polygons is simply characterized by its length in three dimensions colored building blocks are labeled by some 2d triangulations and those homeomorphic to the 3ball are labeled by the subset of planar ones similarly to eulers formula in 2d which provides an upper bound to the number of vertices at fixed number of polygons with given lengths we look in three dimensions for an upper bound on the number of edges at fixed number of given colored building blocks in this article we solve this problem when all colored building blocks except possibly one are homeomorphic to the 3ball to do this we find a characterization of the way a colored building block homeomorphic to the ball has to be glued to other blocks of arbitrary topology in a colored triangulation which maximizes the number of edges this local characterization can be extended to the whole triangulation as long as there is at most one colored building block which is not a 3ball the triangulations obtained this way are in bijection with trees the number of edges is given as an independent sum over the building blocks of such a triangulation in the case of all colored building blocks being homeomorphic to the 3ball we show that these triangulations are homeomorphic to the 3sphere those results were only known for the octahedron and for melonic building blocks before this article is selfcontained and can be used as an introduction to colored triangulations and their bubbles from a purely combinatorial point of view | [['colored', 'triangulations', 'offer', 'a', 'generalization', 'of', 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1,802.0642 | Spectral stability of nonlinear gravity waves in the atmosphere | We apply spectral stability theory to investigate nonlinear gravity waves in
the atmosphere. These waves are determined by modulation equations that result
from Wentzel-Kramers-Brillouin theory. First, we establish that plane waves,
which represent exact solutions to the inviscid Boussinesq equations, are
spectrally stable with respect to their nonlinear modulation equations under
the same conditions as what is known as modulational stability from weakly
nonlinear theory. In contrast to Boussinesq, the pseudo-incompressible regime
does account for the altitudinal varying background density. Second, we show
for the first time that upward-traveling wave fronts solving the inviscid
modulation equations, that compare to pseudo-incompressible theory, are
unconditionally unstable. Both inviscid regimes turn out to be ill-posed as the
spectra allow for arbitrarily large instability growth rates. Third, a
regularization is found by including dissipative effects. The corresponding
traveling wave solutions have localized amplitude and blow up unconditionally
by embedded eigenvalue instabilities but the instability growth rate is bounded
from above. Additionally, all three types of nonlinear modulation equations are
solved numerically to further investigate and illustrate the nature of the
analytic stability results.
| physics.flu-dyn | we apply spectral stability theory to investigate nonlinear gravity waves in the atmosphere these waves are determined by modulation equations that result from wentzelkramersbrillouin theory first we establish that plane waves which represent exact solutions to the inviscid boussinesq equations are spectrally stable with respect to their nonlinear modulation equations under the same conditions as what is known as modulational stability from weakly nonlinear theory in contrast to boussinesq the pseudoincompressible regime does account for the altitudinal varying background density second we show for the first time that upwardtraveling wave fronts solving the inviscid modulation equations that compare to pseudoincompressible theory are unconditionally unstable both inviscid regimes turn out to be illposed as the spectra allow for arbitrarily large instability growth rates third a regularization is found by including dissipative effects the corresponding traveling wave solutions have localized amplitude and blow up unconditionally by embedded eigenvalue instabilities but the instability growth rate is bounded from above additionally all three types of nonlinear modulation equations are solved numerically to further investigate and illustrate the nature of the analytic stability results | [['we', 'apply', 'spectral', 'stability', 'theory', 'to', 'investigate', 'nonlinear', 'gravity', 'waves', 'in', 'the', 'atmosphere', 'these', 'waves', 'are', 'determined', 'by', 'modulation', 'equations', 'that', 'result', 'from', 'wentzelkramersbrillouin', 'theory', 'first', 'we', 'establish', 'that', 'plane', 'waves', 'which', 'represent', 'exact', 'solutions', 'to', 'the', 'inviscid', 'boussinesq', 'equations', 'are', 'spectrally', 'stable', 'with', 'respect', 'to', 'their', 'nonlinear', 'modulation', 'equations', 'under', 'the', 'same', 'conditions', 'as', 'what', 'is', 'known', 'as', 'modulational', 'stability', 'from', 'weakly', 'nonlinear', 'theory', 'in', 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1,802.06421 | Measuring Accessibility using Gravity and Radiation Models | Since the presentation of the Radiation Model, much work has been done to
compare its findings with those obtained from Gravitational Models. These
comparisons always aim at measuring the accuracy with which the models
reproduce the mobility described by origin-destination matrices. This has been
done at different spatial scales using different datasets, and several versions
of the models have been proposed to adjust to various spatial systems. However
the models, to our knowledge, have never been compared with respect to policy
testing scenarios. For this reason, here we use the models to analyze the
impact of the introduction of a new transportation network, a Bus Rapid
Transport system, in the city of Teresina in Brazil. We do this by measuring
the estimated variation in the trip distribution, and formulate an
accessibility to employment indicator for the different zones of the city. By
comparing the results obtained with the two approaches, we are able, not only
to better assess the goodness of fit and the impact of this intervention, but
also to understand reasons for the systematic similarities and differences in
their predictions.
| physics.soc-ph | since the presentation of the radiation model much work has been done to compare its findings with those obtained from gravitational models these comparisons always aim at measuring the accuracy with which the models reproduce the mobility described by origindestination matrices this has been done at different spatial scales using different datasets and several versions of the models have been proposed to adjust to various spatial systems however the models to our knowledge have never been compared with respect to policy testing scenarios for this reason here we use the models to analyze the impact of the introduction of a new transportation network a bus rapid transport system in the city of teresina in brazil we do this by measuring the estimated variation in the trip distribution and formulate an accessibility to employment indicator for the different zones of the city by comparing the results obtained with the two approaches we are able not only to better assess the goodness of fit and the impact of this intervention but also to understand reasons for the systematic similarities and differences in their predictions | [['since', 'the', 'presentation', 'of', 'the', 'radiation', 'model', 'much', 'work', 'has', 'been', 'done', 'to', 'compare', 'its', 'findings', 'with', 'those', 'obtained', 'from', 'gravitational', 'models', 'these', 'comparisons', 'always', 'aim', 'at', 'measuring', 'the', 'accuracy', 'with', 'which', 'the', 'models', 'reproduce', 'the', 'mobility', 'described', 'by', 'origindestination', 'matrices', 'this', 'has', 'been', 'done', 'at', 'different', 'spatial', 'scales', 'using', 'different', 'datasets', 'and', 'several', 'versions', 'of', 'the', 'models', 'have', 'been', 'proposed', 'to', 'adjust', 'to', 'various', 'spatial', 'systems', 'however', 'the', 'models', 'to', 'our', 'knowledge', 'have', 'never', 'been', 'compared', 'with', 'respect', 'to', 'policy', 'testing', 'scenarios', 'for', 'this', 'reason', 'here', 'we', 'use', 'the', 'models', 'to', 'analyze', 'the', 'impact', 'of', 'the', 'introduction', 'of', 'a', 'new', 'transportation', 'network', 'a', 'bus', 'rapid', 'transport', 'system', 'in', 'the', 'city', 'of', 'teresina', 'in', 'brazil', 'we', 'do', 'this', 'by', 'measuring', 'the', 'estimated', 'variation', 'in', 'the', 'trip', 'distribution', 'and', 'formulate', 'an', 'accessibility', 'to', 'employment', 'indicator', 'for', 'the', 'different', 'zones', 'of', 'the', 'city', 'by', 'comparing', 'the', 'results', 'obtained', 'with', 'the', 'two', 'approaches', 'we', 'are', 'able', 'not', 'only', 'to', 'better', 'assess', 'the', 'goodness', 'of', 'fit', 'and', 'the', 'impact', 'of', 'this', 'intervention', 'but', 'also', 'to', 'understand', 'reasons', 'for', 'the', 'systematic', 'similarities', 'and', 'differences', 'in', 'their', 'predictions']] | [-0.029073757996772368, 0.036846236158011206, -0.10367265186987776, 0.0942752592957666, -0.027858511403264757, -0.11789334078643533, 0.042596482547020635, 0.401737774912659, -0.22698565067990956, -0.37136292605929705, 0.11417922398939893, -0.2828754734824211, -0.12003876720491613, 0.1948756998972787, -0.07944390957001905, 0.0663585241743137, 0.04603691670711754, 0.02160229483871458, -0.07431215306651362, -0.2581822003304794, 0.3195532805489592, 0.10131334617234848, 0.31537039994097504, 0.05614505572378306, 0.07712245641150177, -0.06094832051910707, -0.08097020710833906, 0.04416258804415203, -0.1317532866825324, 0.14192499430562006, 0.22248674224413245, 0.1345375283320244, 0.2759151800293784, -0.4410450152476519, -0.26009670233878807, 0.1170689714763787, 0.1331946920337881, 0.10836629826295413, -0.008739066749517884, -0.28425247260261305, 0.08615509166449144, -0.2024121218578355, -0.11486770958480173, -0.06629128273813188, 0.006129857401288943, 0.028973224568013514, -0.22950383920984044, 0.01285666681794599, -0.0026470013580269574, 0.0754655186879289, -0.06134692036038013, -0.12135980572379117, -0.003919028326513976, 0.20864350260981457, 0.10041334780733209, -0.008060536289443546, 0.08777243944492129, -0.11751473745207677, -0.13787249578111574, 0.3905020733852742, -0.046918733790259584, -0.20641401262975745, 0.23450569247374137, -0.14354570510987583, -0.13211175685784476, 0.05969420352859683, 0.20206238364914011, 0.07269346350133457, -0.1855655694123131, -0.0011876887945025433, -0.0012537598692251174, 0.13724809433770938, 0.042976008926245556, -0.0024153851847375295, 0.19007921165359612, 0.18401922622067823, 0.0002567728001171548, 0.10110550940947514, -0.0935013048422847, -0.11038128242092156, -0.22578325890807321, -0.118353555138475, -0.15669962702812987, -0.02409304476924207, -0.06556157360994386, -0.09555002879248468, 0.43406770232221037, 0.2350263724499768, 0.204758084744462, 0.06598645620477689, 0.2961414321814535, 0.09067756035725344, 0.09662639161215539, 0.05480659654935133, 0.26326713051379386, 0.07105342435485874, 0.134688646398814, -0.2143753028441946, 0.13107185982533046, -0.012257272811956738] |
1,802.06422 | Stochastic stability of invariant measures: The 2D Euler equation | In finite-dimensional dynamical systems, stochastic stability provides the
selection of physical relevant measures from the myriad invariant measures of
conservative systems. That this might also apply to infinite-dimensional
systems is the inspiration for this work. As an example the 2D Euler equation
is studied. Among other results this study suggests that the coherent
structures observed in 2D hydrodynamics are associated to configurations that
maximize stochastically stable measures uniquely determined by the boundary
conditions in mode space.
| math.DS physics.flu-dyn | in finitedimensional dynamical systems stochastic stability provides the selection of physical relevant measures from the myriad invariant measures of conservative systems that this might also apply to infinitedimensional systems is the inspiration for this work as an example the 2d euler equation is studied among other results this study suggests that the coherent structures observed in 2d hydrodynamics are associated to configurations that maximize stochastically stable measures uniquely determined by the boundary conditions in mode space | [['in', 'finitedimensional', 'dynamical', 'systems', 'stochastic', 'stability', 'provides', 'the', 'selection', 'of', 'physical', 'relevant', 'measures', 'from', 'the', 'myriad', 'invariant', 'measures', 'of', 'conservative', 'systems', 'that', 'this', 'might', 'also', 'apply', 'to', 'infinitedimensional', 'systems', 'is', 'the', 'inspiration', 'for', 'this', 'work', 'as', 'an', 'example', 'the', '2d', 'euler', 'equation', 'is', 'studied', 'among', 'other', 'results', 'this', 'study', 'suggests', 'that', 'the', 'coherent', 'structures', 'observed', 'in', '2d', 'hydrodynamics', 'are', 'associated', 'to', 'configurations', 'that', 'maximize', 'stochastically', 'stable', 'measures', 'uniquely', 'determined', 'by', 'the', 'boundary', 'conditions', 'in', 'mode', 'space']] | [-0.14852333904587126, 0.1235929818528683, -0.09605703906058088, 0.10165637549423416, -0.04432334140323004, -0.12135710739561259, -0.016144303310858577, 0.33143752705501883, -0.3076937028978902, -0.2288346507549776, 0.1048979440927628, -0.22646034895871325, -0.20315713594103918, 0.2338533228214242, -0.08672895143421269, 0.07474065838553208, 0.0639345504383336, 0.012717777593551497, -0.07081535240439207, -0.20000727979564353, 0.38896292668620225, 0.04489300934303748, 0.28910387124817233, -0.02052152737681019, 0.10397775279125199, -0.027803451208838897, -0.02200421565947564, 0.038573862758455923, -0.18006548355170757, 0.08540758863704181, 0.26171256383072194, 0.08955909349146839, 0.2604005524496499, -0.35754279189399985, -0.2741911580393973, 0.10309581512487248, 0.1331630124355127, 0.09965621160441324, -0.02147461331792568, -0.2912650805113739, 0.09287182573768261, -0.11394745816735515, -0.16432363281982312, -0.10146621104918029, 0.03303433117750836, 0.03470606253923554, -0.24039759604554428, 0.057146929507373566, 0.07482053412815348, 0.03620359388572213, -0.1412929407884612, -0.07135192349577617, -0.06627240679900799, 0.12289553547376081, 0.02056023774447998, -0.007016798619205426, 0.12398776566413672, -0.10383106766599476, -0.15929883910882237, 0.4150985333284265, -0.03323073848610205, -0.2711168915078528, 0.24897138831989937, -0.12599559812684005, -0.17135228608783923, 0.1477470367987591, 0.1901200230870592, 0.11779027280863374, -0.20831285861296286, 0.06155505831549434, -0.07379706034063067, 0.11513430012488052, 0.0012792172094218824, 0.06750972147442792, 0.1931651977601608, 0.14316305644369046, 0.09052632831184096, 0.1575896614728998, 0.0028170256555313244, -0.16558871141291762, -0.26618858662090805, -0.15181429839791044, -0.154511585783774, 0.05389381065891173, -0.05290232835594859, -0.15238348001271093, 0.35532365175037595, 0.1777813816198001, 0.17053859679665612, 0.016474984708781306, 0.2703598496062975, 0.13828710397233648, 0.019009652259563536, 0.02655393904761264, 0.2318691809196025, 0.13091549028161498, 0.0742713337163686, -0.21795267338778726, 0.04165485699808127, 0.07962340789871585] |
1,802.06423 | Experimental investigation of dynamical structures formation due to
flowing complex plasma past an obstacle | We report the experimental observation of dynamical behavior of flowing
complex plasma past a spherical obstacle. The experiment has been carried out
in a $\Pi$-shaped DC glow discharge experimental device using kaolin particles
as the dust component in a background of Argon plasma. A stationary dust cloud
is formed by maintaining the pumping speed and gas flow rate. A spherical
obstacle vertically mounted on the cathode tray acts as an obstacle to the flow
of dust particles. The controlled dust flow is generated by reducing the mass
flow of the neutrals through a mass flow controller. The flowing dust particles
are repelled by the electrostatic field of the negatively charged sphere and a
microparticle free region (dust void) is formed surrounding the obstacle. The
far particles are attracted towards the floating obstacle and reflected back
when they have arrived at a minimum distance, causing a ring shaped structure
around the obstacle. We characterize the shape of this structure over a range
of dust flow speeds and obstacle biases. For a supersonic flow of dust fluid
around a negatively biased obstacle, a bow shock is formed on the upstream side
of the sphere, while the generation of wave structures is observed on the
downstream side for a particular range of flow velocities. Reynolds numbers in
this case is estimated as $R_e \gtrsim 50$. This wave structure reminds of the
beginning of the formation of a Von-K\'arm\'an vortex street. A physical
picture for the observed structure based on ion-drag, neutral streaming and
electric forces is discussed.
| physics.plasm-ph | we report the experimental observation of dynamical behavior of flowing complex plasma past a spherical obstacle the experiment has been carried out in a pishaped dc glow discharge experimental device using kaolin particles as the dust component in a background of argon plasma a stationary dust cloud is formed by maintaining the pumping speed and gas flow rate a spherical obstacle vertically mounted on the cathode tray acts as an obstacle to the flow of dust particles the controlled dust flow is generated by reducing the mass flow of the neutrals through a mass flow controller the flowing dust particles are repelled by the electrostatic field of the negatively charged sphere and a microparticle free region dust void is formed surrounding the obstacle the far particles are attracted towards the floating obstacle and reflected back when they have arrived at a minimum distance causing a ring shaped structure around the obstacle we characterize the shape of this structure over a range of dust flow speeds and obstacle biases for a supersonic flow of dust fluid around a negatively biased obstacle a bow shock is formed on the upstream side of the sphere while the generation of wave structures is observed on the downstream side for a particular range of flow velocities reynolds numbers in this case is estimated as r_e gtrsim 50 this wave structure reminds of the beginning of the formation of a vonkarman vortex street a physical picture for the observed structure based on iondrag neutral streaming and electric forces is discussed | [['we', 'report', 'the', 'experimental', 'observation', 'of', 'dynamical', 'behavior', 'of', 'flowing', 'complex', 'plasma', 'past', 'a', 'spherical', 'obstacle', 'the', 'experiment', 'has', 'been', 'carried', 'out', 'in', 'a', 'pishaped', 'dc', 'glow', 'discharge', 'experimental', 'device', 'using', 'kaolin', 'particles', 'as', 'the', 'dust', 'component', 'in', 'a', 'background', 'of', 'argon', 'plasma', 'a', 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1,802.06424 | End-to-end Audiovisual Speech Recognition | Several end-to-end deep learning approaches have been recently presented
which extract either audio or visual features from the input images or audio
signals and perform speech recognition. However, research on end-to-end
audiovisual models is very limited. In this work, we present an end-to-end
audiovisual model based on residual networks and Bidirectional Gated Recurrent
Units (BGRUs). To the best of our knowledge, this is the first audiovisual
fusion model which simultaneously learns to extract features directly from the
image pixels and audio waveforms and performs within-context word recognition
on a large publicly available dataset (LRW). The model consists of two streams,
one for each modality, which extract features directly from mouth regions and
raw waveforms. The temporal dynamics in each stream/modality are modeled by a
2-layer BGRU and the fusion of multiple streams/modalities takes place via
another 2-layer BGRU. A slight improvement in the classification rate over an
end-to-end audio-only and MFCC-based model is reported in clean audio
conditions and low levels of noise. In presence of high levels of noise, the
end-to-end audiovisual model significantly outperforms both audio-only models.
| cs.CV | several endtoend deep learning approaches have been recently presented which extract either audio or visual features from the input images or audio signals and perform speech recognition however research on endtoend audiovisual models is very limited in this work we present an endtoend audiovisual model based on residual networks and bidirectional gated recurrent units bgrus to the best of our knowledge this is the first audiovisual fusion model which simultaneously learns to extract features directly from the image pixels and audio waveforms and performs withincontext word recognition on a large publicly available dataset lrw the model consists of two streams one for each modality which extract features directly from mouth regions and raw waveforms the temporal dynamics in each streammodality are modeled by a 2layer bgru and the fusion of multiple streamsmodalities takes place via another 2layer bgru a slight improvement in the classification rate over an endtoend audioonly and mfccbased model is reported in clean audio conditions and low levels of noise in presence of high levels of noise the endtoend audiovisual model significantly outperforms both audioonly models | [['several', 'endtoend', 'deep', 'learning', 'approaches', 'have', 'been', 'recently', 'presented', 'which', 'extract', 'either', 'audio', 'or', 'visual', 'features', 'from', 'the', 'input', 'images', 'or', 'audio', 'signals', 'and', 'perform', 'speech', 'recognition', 'however', 'research', 'on', 'endtoend', 'audiovisual', 'models', 'is', 'very', 'limited', 'in', 'this', 'work', 'we', 'present', 'an', 'endtoend', 'audiovisual', 'model', 'based', 'on', 'residual', 'networks', 'and', 'bidirectional', 'gated', 'recurrent', 'units', 'bgrus', 'to', 'the', 'best', 'of', 'our', 'knowledge', 'this', 'is', 'the', 'first', 'audiovisual', 'fusion', 'model', 'which', 'simultaneously', 'learns', 'to', 'extract', 'features', 'directly', 'from', 'the', 'image', 'pixels', 'and', 'audio', 'waveforms', 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1,802.06425 | Parabolic orbits of $2$-nilpotent elements for classical groups | We consider the conjugation-action of the Borel subgroup of the symplectic or
the orthogonal group on the variety of nilpotent complex elements of nilpotency
degree $2$ in its Lie algebra. We translate the setup to a
representation-theoretic context in the language of a symmetric quiver algebra.
This makes it possible to provide a parametrization of the orbits via a
combinatorial tool that we call symplectic/orthogonal oriented link patterns.
We deduce information about numerology. We then generalize these
classifications to standard parabolic subgroups for all classical groups.
Finally, our results are restricted to the nilradical.
| math.RT math.CO | we consider the conjugationaction of the borel subgroup of the symplectic or the orthogonal group on the variety of nilpotent complex elements of nilpotency degree 2 in its lie algebra we translate the setup to a representationtheoretic context in the language of a symmetric quiver algebra this makes it possible to provide a parametrization of the orbits via a combinatorial tool that we call symplecticorthogonal oriented link patterns we deduce information about numerology we then generalize these classifications to standard parabolic subgroups for all classical groups finally our results are restricted to the nilradical | [['we', 'consider', 'the', 'conjugationaction', 'of', 'the', 'borel', 'subgroup', 'of', 'the', 'symplectic', 'or', 'the', 'orthogonal', 'group', 'on', 'the', 'variety', 'of', 'nilpotent', 'complex', 'elements', 'of', 'nilpotency', 'degree', '2', 'in', 'its', 'lie', 'algebra', 'we', 'translate', 'the', 'setup', 'to', 'a', 'representationtheoretic', 'context', 'in', 'the', 'language', 'of', 'a', 'symmetric', 'quiver', 'algebra', 'this', 'makes', 'it', 'possible', 'to', 'provide', 'a', 'parametrization', 'of', 'the', 'orbits', 'via', 'a', 'combinatorial', 'tool', 'that', 'we', 'call', 'symplecticorthogonal', 'oriented', 'link', 'patterns', 'we', 'deduce', 'information', 'about', 'numerology', 'we', 'then', 'generalize', 'these', 'classifications', 'to', 'standard', 'parabolic', 'subgroups', 'for', 'all', 'classical', 'groups', 'finally', 'our', 'results', 'are', 'restricted', 'to', 'the', 'nilradical']] | [-0.15689748240278123, 0.04044712513209658, -0.10128570726498011, 0.0727344731678889, -0.1818353344260299, -0.11528309252846272, 0.038603759962109296, 0.38367805287162676, -0.3492970887690465, -0.2179594367663277, 0.11655470038432271, -0.2171640507629181, -0.14312696665218297, 0.19381237407759863, -0.15761867007290192, -0.04497399172520245, 0.053888035799436115, 0.12751050465498764, -0.10552067391782134, -0.24962313822222912, 0.39722002741504225, -0.04489409836892167, 0.21959822203102025, -0.004705596574027329, 0.10054218373261392, 0.034078205782087874, -0.03764785437824878, -0.039390737336981015, -0.1523766935375882, 0.16708457324792572, 0.2765965436763586, 0.11354960853907656, 0.1646487445897482, -0.3681593836939081, -0.12010838955819131, 0.18556072468809942, 0.13596511600994843, 0.07750480107844193, -0.04396985382358098, -0.2745724730788076, 0.12159406631303198, -0.2166720681832769, -0.1784324165473276, -0.06730266534624264, 0.0421749944303264, -0.017237504805497666, -0.224641213266605, -0.007342010444188689, 0.09469791992686372, 0.12187651702341565, -0.045170937254876295, -0.09355875091739321, -0.027182133935213564, 0.11605239785623123, -0.0256959009987421, -0.013469584832374166, 0.10623743984243891, -0.07211085580081303, -0.16969295893795788, 0.42276696747842624, -0.01130544422058131, -0.2535542749002219, 0.17864656686148744, -0.17758326816491465, -0.21446049898525976, 0.07370523430724094, 0.13089500127875425, 0.12054789975344976, -0.05313525127960329, 0.154340270203241, -0.15130550351905378, 0.05683419082506976, 0.05145256614134191, -0.0011904228310239441, 0.14193055345094763, 0.10518020456111891, 0.0523523487784761, 0.13745385511689126, 0.03576037334278226, -0.022475859809770904, -0.3226034492353334, -0.20264086295711867, -0.06402519173508986, 0.0970474081469992, -0.12991730363028955, -0.1539834381621133, 0.453436155506271, 0.130109591877083, 0.152742676471578, 0.12876784717267814, 0.20997958162680586, 0.049057956741617476, 0.09408396086655557, 0.0460460951543745, 0.1380598721740906, 0.2319435843543962, -0.05137489882961629, -0.1522198155512439, -0.0540725745909669, 0.1553472629673977] |
1,802.06426 | Estimating scale-invariant future in continuous time | Natural learners must compute an estimate of future outcomes that follow from
a stimulus in continuous time. Widely used reinforcement learning algorithms
discretize continuous time and estimate either transition functions from one
step to the next (model-based algorithms) or a scalar value of
exponentially-discounted future reward using the Bellman equation (model-free
algorithms). An important drawback of model-based algorithms is that
computational cost grows linearly with the amount of time to be simulated. On
the other hand, an important drawback of model-free algorithms is the need to
select a time-scale required for exponential discounting. We present a
computational mechanism, developed based on work in psychology and
neuroscience, for computing a scale-invariant timeline of future outcomes. This
mechanism efficiently computes an estimate of inputs as a function of future
time on a logarithmically-compressed scale, and can be used to generate a
scale-invariant power-law-discounted estimate of expected future reward. The
representation of future time retains information about what will happen when.
The entire timeline can be constructed in a single parallel operation which
generates concrete behavioral and neural predictions. This computational
mechanism could be incorporated into future reinforcement learning algorithms.
| cs.AI q-bio.NC | natural learners must compute an estimate of future outcomes that follow from a stimulus in continuous time widely used reinforcement learning algorithms discretize continuous time and estimate either transition functions from one step to the next modelbased algorithms or a scalar value of exponentiallydiscounted future reward using the bellman equation modelfree algorithms an important drawback of modelbased algorithms is that computational cost grows linearly with the amount of time to be simulated on the other hand an important drawback of modelfree algorithms is the need to select a timescale required for exponential discounting we present a computational mechanism developed based on work in psychology and neuroscience for computing a scaleinvariant timeline of future outcomes this mechanism efficiently computes an estimate of inputs as a function of future time on a logarithmicallycompressed scale and can be used to generate a scaleinvariant powerlawdiscounted estimate of expected future reward the representation of future time retains information about what will happen when the entire timeline can be constructed in a single parallel operation which generates concrete behavioral and neural predictions this computational mechanism could be incorporated into future reinforcement learning algorithms | [['natural', 'learners', 'must', 'compute', 'an', 'estimate', 'of', 'future', 'outcomes', 'that', 'follow', 'from', 'a', 'stimulus', 'in', 'continuous', 'time', 'widely', 'used', 'reinforcement', 'learning', 'algorithms', 'discretize', 'continuous', 'time', 'and', 'estimate', 'either', 'transition', 'functions', 'from', 'one', 'step', 'to', 'the', 'next', 'modelbased', 'algorithms', 'or', 'a', 'scalar', 'value', 'of', 'exponentiallydiscounted', 'future', 'reward', 'using', 'the', 'bellman', 'equation', 'modelfree', 'algorithms', 'an', 'important', 'drawback', 'of', 'modelbased', 'algorithms', 'is', 'that', 'computational', 'cost', 'grows', 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1,802.06427 | Iwasawa Main Conjecture for $p$-adic families of elliptic modular
cuspforms | In this article, we discuss Iwasawa Main Conjecture for $p$-adic families of
elliptic modular cuspforms. After the overview on the situation of the ordinary
case of Hida family, we will introduce a Coleman map for Coleman family for the
non-ordinary case (Coleman family) which was obtained as a joint work with
Filippo Nuccio [NO16] and we give some results on Iwasawa Theory for Coleman
families as applications of . First, we give a construction of a two-variable
$p$-adic $L$-function for a Coleman family thanks to the ingredients given in
[NO16] (Theorem 5.1). Combining this result and Coleman map obtained in [NO16],
we also construct Beilinson-Kato Euler systems over a Coleman family (Thorem
5.3). Finally we formulate Iwasawa Main conjecture for a Coleman family and
prove the half of Iwasawa Main Conjecture (Theorem 5.6).
| math.NT | in this article we discuss iwasawa main conjecture for padic families of elliptic modular cuspforms after the overview on the situation of the ordinary case of hida family we will introduce a coleman map for coleman family for the nonordinary case coleman family which was obtained as a joint work with filippo nuccio no16 and we give some results on iwasawa theory for coleman families as applications of first we give a construction of a twovariable padic lfunction for a coleman family thanks to the ingredients given in no16 theorem 51 combining this result and coleman map obtained in no16 we also construct beilinsonkato euler systems over a coleman family thorem 53 finally we formulate iwasawa main conjecture for a coleman family and prove the half of iwasawa main conjecture theorem 56 | [['in', 'this', 'article', 'we', 'discuss', 'iwasawa', 'main', 'conjecture', 'for', 'padic', 'families', 'of', 'elliptic', 'modular', 'cuspforms', 'after', 'the', 'overview', 'on', 'the', 'situation', 'of', 'the', 'ordinary', 'case', 'of', 'hida', 'family', 'we', 'will', 'introduce', 'a', 'coleman', 'map', 'for', 'coleman', 'family', 'for', 'the', 'nonordinary', 'case', 'coleman', 'family', 'which', 'was', 'obtained', 'as', 'a', 'joint', 'work', 'with', 'filippo', 'nuccio', 'no16', 'and', 'we', 'give', 'some', 'results', 'on', 'iwasawa', 'theory', 'for', 'coleman', 'families', 'as', 'applications', 'of', 'first', 'we', 'give', 'a', 'construction', 'of', 'a', 'twovariable', 'padic', 'lfunction', 'for', 'a', 'coleman', 'family', 'thanks', 'to', 'the', 'ingredients', 'given', 'in', 'no16', 'theorem', '51', 'combining', 'this', 'result', 'and', 'coleman', 'map', 'obtained', 'in', 'no16', 'we', 'also', 'construct', 'beilinsonkato', 'euler', 'systems', 'over', 'a', 'coleman', 'family', 'thorem', '53', 'finally', 'we', 'formulate', 'iwasawa', 'main', 'conjecture', 'for', 'a', 'coleman', 'family', 'and', 'prove', 'the', 'half', 'of', 'iwasawa', 'main', 'conjecture', 'theorem', '56']] | [-0.19315585279695063, -0.000651052845499784, -0.18325334390134815, 0.09422518911181402, -0.08993993368255727, -0.11854397827930009, -0.0026283269678775705, 0.203006018735184, -0.22888564954703775, -0.26851448852689724, 0.07795122035206757, -0.20876963201284637, -0.1932046652010834, 0.2884464540042495, -0.18392532471858875, 0.042240441286268124, 0.038433803515579866, 0.02523263481993029, -0.04877644061032711, -0.339507476591953, 0.41313534975407346, -0.02219560762284366, 0.16451991114850717, 0.05388851088777412, 0.08190510233238567, 0.06691781245527491, -0.03052854754087579, -0.1347100714591282, -0.1968118821533809, 0.17023581041037353, 0.31324740338587126, 0.04463297761052506, 0.2554318820453384, -0.31850643666418454, -0.12901985455097326, 0.16666697109302947, 0.07359561304213437, 0.08165486342582909, -0.05302413002026218, -0.24765699335821825, 0.09601647595213797, -0.2360500651624992, -0.2653773379394827, -0.11045437524244474, 0.04539141290686058, 0.013905669662049253, -0.23997379417214826, 0.005653967033806861, 0.12147979874817924, 0.14327491491407385, -0.08877173092976952, -0.171852171831615, 0.03563543015252088, -0.009749381902506788, 0.030253234386927525, 0.059787303578990106, 0.026389411986514014, -0.04088745644060141, -0.13056990530569362, 0.2930679484777053, -0.10585645988507139, -0.1136416386784488, 0.06724865936837693, -0.12189615084896334, -0.2741377682901407, 0.07193878301568614, 0.09887149570979008, 0.15085071525785304, -0.048753085055651554, 0.16695841069676282, -0.15340488044303338, 0.030385449923262114, 0.17853697660940748, -0.06674022701007264, 0.14180814340365838, 0.033467093109373604, 0.0325077525091194, 0.16909778338878323, -0.01951061083245596, -0.07362103766098775, -0.36655002621976474, -0.25093922506194055, -0.09072483240676518, 0.142262868922673, -0.036259108254679775, -0.16008668542192636, 0.4448916220198606, 0.10320682249223913, 0.14885753566640933, 0.1994302846208741, 0.17796771269858608, 0.08236367226478765, 0.009237633852771562, 0.022808140398355072, 0.1267916519820907, 0.20650757211509324, 0.022718910944562774, -0.0819484033490325, -0.0895655463486981, 0.2603207874673468] |
1,802.06428 | Improving Mild Cognitive Impairment Prediction via Reinforcement
Learning and Dialogue Simulation | Mild cognitive impairment (MCI) is a prodromal phase in the progression from
normal aging to dementia, especially Alzheimers disease. Even though there is
mild cognitive decline in MCI patients, they have normal overall cognition and
thus is challenging to distinguish from normal aging. Using transcribed data
obtained from recorded conversational interactions between participants and
trained interviewers, and applying supervised learning models to these data, a
recent clinical trial has shown a promising result in differentiating MCI from
normal aging. However, the substantial amount of interactions with medical
staff can still incur significant medical care expenses in practice. In this
paper, we propose a novel reinforcement learning (RL) framework to train an
efficient dialogue agent on existing transcripts from clinical trials.
Specifically, the agent is trained to sketch disease-specific lexical
probability distribution, and thus to converse in a way that maximizes the
diagnosis accuracy and minimizes the number of conversation turns. We evaluate
the performance of the proposed reinforcement learning framework on the MCI
diagnosis from a real clinical trial. The results show that while using only a
few turns of conversation, our framework can significantly outperform
state-of-the-art supervised learning approaches.
| cs.LG cs.CL stat.ML | mild cognitive impairment mci is a prodromal phase in the progression from normal aging to dementia especially alzheimers disease even though there is mild cognitive decline in mci patients they have normal overall cognition and thus is challenging to distinguish from normal aging using transcribed data obtained from recorded conversational interactions between participants and trained interviewers and applying supervised learning models to these data a recent clinical trial has shown a promising result in differentiating mci from normal aging however the substantial amount of interactions with medical staff can still incur significant medical care expenses in practice in this paper we propose a novel reinforcement learning rl framework to train an efficient dialogue agent on existing transcripts from clinical trials specifically the agent is trained to sketch diseasespecific lexical probability distribution and thus to converse in a way that maximizes the diagnosis accuracy and minimizes the number of conversation turns we evaluate the performance of the proposed reinforcement learning framework on the mci diagnosis from a real clinical trial the results show that while using only a few turns of conversation our framework can significantly outperform stateoftheart supervised learning approaches | [['mild', 'cognitive', 'impairment', 'mci', 'is', 'a', 'prodromal', 'phase', 'in', 'the', 'progression', 'from', 'normal', 'aging', 'to', 'dementia', 'especially', 'alzheimers', 'disease', 'even', 'though', 'there', 'is', 'mild', 'cognitive', 'decline', 'in', 'mci', 'patients', 'they', 'have', 'normal', 'overall', 'cognition', 'and', 'thus', 'is', 'challenging', 'to', 'distinguish', 'from', 'normal', 'aging', 'using', 'transcribed', 'data', 'obtained', 'from', 'recorded', 'conversational', 'interactions', 'between', 'participants', 'and', 'trained', 'interviewers', 'and', 'applying', 'supervised', 'learning', 'models', 'to', 'these', 'data', 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1,802.06429 | Cech cohomology and the Capitulation kernel | We discuss the capitulation kernel associated to a degree n covering using
Cech cohomology and the Kummer sequence. The main result is a five-term exact
sequence that relates the capitulation kernel to the Cech cohomology of the
n-th roots of unity and a certain subquotient of the group of units modulo n-th
powers.
| math.NT math.AG | we discuss the capitulation kernel associated to a degree n covering using cech cohomology and the kummer sequence the main result is a fiveterm exact sequence that relates the capitulation kernel to the cech cohomology of the nth roots of unity and a certain subquotient of the group of units modulo nth powers | [['we', 'discuss', 'the', 'capitulation', 'kernel', 'associated', 'to', 'a', 'degree', 'n', 'covering', 'using', 'cech', 'cohomology', 'and', 'the', 'kummer', 'sequence', 'the', 'main', 'result', 'is', 'a', 'fiveterm', 'exact', 'sequence', 'that', 'relates', 'the', 'capitulation', 'kernel', 'to', 'the', 'cech', 'cohomology', 'of', 'the', 'nth', 'roots', 'of', 'unity', 'and', 'a', 'certain', 'subquotient', 'of', 'the', 'group', 'of', 'units', 'modulo', 'nth', 'powers']] | [-0.23903135452770963, 0.03547060941258129, -0.09170161837817363, 0.06821314728036874, -0.0910257778025039, -0.05586886687977415, -0.004780340575138634, 0.26555759781303834, -0.40852348003887906, -0.18126697237339784, 0.08033947093974587, -0.23799445775319944, -0.17980144770359094, 0.17320179418256543, -0.12371350353899992, 0.008540781570668772, 0.004518008070453158, 0.18537602960219923, -0.07709581617986397, -0.2710085557597988, 0.4358732308840977, 0.001230141042538409, 0.17716014258704096, 0.0013342664559494774, 0.15921779504080988, -0.039410826425015366, -0.015374693773546309, -0.11233675476374491, -0.13243286892893077, 0.17448522995735677, 0.29133815832769955, 0.056884152656596784, 0.23571451612800923, -0.32498013674509973, -0.028926854267856985, 0.2405333109375722, 0.12171628143427507, -0.04002902704238329, 0.054830149959944154, -0.21376993026549243, 0.15483753497378444, -0.19865386850746428, -0.17794377926104474, -0.042723408671763705, 0.042200479709174274, 0.11059808158227857, -0.2449929554296552, -0.0025408389046788216, 0.07970323912658782, 0.12324947324353007, -0.0424943440154476, -0.15095234745761976, -0.01433986302394912, 0.10899237697100583, -0.015291040820368338, 0.04219929622661955, 0.10022527247421303, -0.12297514200491726, -0.11597818385739371, 0.39908187451579097, -0.05993199408194929, -0.15200621761241048, 0.07007315522938404, -0.22948802176441224, -0.19664570534566664, 0.14900357861352978, 0.026895953588328272, 0.16667573463681312, 0.05531455920833462, 0.18665569626840428, -0.09583541873912767, 0.11970090085886559, 0.1245424811781015, -0.04366938122284581, 0.11017605980401332, 0.05041052468718504, 0.037379089962550495, 0.20477920714414344, -0.013783026593166211, -0.03465498765965678, -0.37471110936043395, -0.2725249550037332, -0.20400880336902052, 0.1603635355197596, -0.19412192347281576, -0.1644627529741177, 0.46067176017699374, 0.10720853122689251, 0.18873985661720893, 0.20455786872233422, 0.22023573411817504, 0.12809176265068775, 0.09168914665099022, -0.006788362941871077, -0.011962129506018927, 0.28476682305336, -0.05424810383679732, -0.20135586015563808, -0.03519010591267977, 0.31867337957868036] |
1,802.0643 | DARTS: Deceiving Autonomous Cars with Toxic Signs | Sign recognition is an integral part of autonomous cars. Any
misclassification of traffic signs can potentially lead to a multitude of
disastrous consequences, ranging from a life-threatening accident to even a
large-scale interruption of transportation services relying on autonomous cars.
In this paper, we propose and examine security attacks against sign recognition
systems for Deceiving Autonomous caRs with Toxic Signs (we call the proposed
attacks DARTS). In particular, we introduce two novel methods to create these
toxic signs. First, we propose Out-of-Distribution attacks, which expand the
scope of adversarial examples by enabling the adversary to generate these
starting from an arbitrary point in the image space compared to prior attacks
which are restricted to existing training/test data (In-Distribution). Second,
we present the Lenticular Printing attack, which relies on an optical
phenomenon to deceive the traffic sign recognition system. We extensively
evaluate the effectiveness of the proposed attacks in both virtual and
real-world settings and consider both white-box and black-box threat models.
Our results demonstrate that the proposed attacks are successful under both
settings and threat models. We further show that Out-of-Distribution attacks
can outperform In-Distribution attacks on classifiers defended using the
adversarial training defense, exposing a new attack vector for these defenses.
| cs.CR cs.CV | sign recognition is an integral part of autonomous cars any misclassification of traffic signs can potentially lead to a multitude of disastrous consequences ranging from a lifethreatening accident to even a largescale interruption of transportation services relying on autonomous cars in this paper we propose and examine security attacks against sign recognition systems for deceiving autonomous cars with toxic signs we call the proposed attacks darts in particular we introduce two novel methods to create these toxic signs first we propose outofdistribution attacks which expand the scope of adversarial examples by enabling the adversary to generate these starting from an arbitrary point in the image space compared to prior attacks which are restricted to existing trainingtest data indistribution second we present the lenticular printing attack which relies on an optical phenomenon to deceive the traffic sign recognition system we extensively evaluate the effectiveness of the proposed attacks in both virtual and realworld settings and consider both whitebox and blackbox threat models our results demonstrate that the proposed attacks are successful under both settings and threat models we further show that outofdistribution attacks can outperform indistribution attacks on classifiers defended using the adversarial training defense exposing a new attack vector for these defenses | [['sign', 'recognition', 'is', 'an', 'integral', 'part', 'of', 'autonomous', 'cars', 'any', 'misclassification', 'of', 'traffic', 'signs', 'can', 'potentially', 'lead', 'to', 'a', 'multitude', 'of', 'disastrous', 'consequences', 'ranging', 'from', 'a', 'lifethreatening', 'accident', 'to', 'even', 'a', 'largescale', 'interruption', 'of', 'transportation', 'services', 'relying', 'on', 'autonomous', 'cars', 'in', 'this', 'paper', 'we', 'propose', 'and', 'examine', 'security', 'attacks', 'against', 'sign', 'recognition', 'systems', 'for', 'deceiving', 'autonomous', 'cars', 'with', 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1,802.06431 | String Model with Mesons and Baryons in Modified Measure Theory | We consider string meson and string baryon models in the framework of the
modified measure theory, the theory that does not use the determinant of the
metric to construct the invariant volume element. As the outcome of this
theory, the string tension is not placed ad hoc but is derived. When the
charges are presented, the tension undergoes alterations. In the string meson
model there are one string and two opposite charges at the endpoints. In the
string baryon model there are two strings, two pairs of opposite charges at the
endpoints and one additional charge at the intersection point, the point where
these two strings are connected. The application of the modified measure theory
is justified because the Neumann boundary conditions are obtained dynamically
at every point where the charge is located and Dirichlet boundary conditions
arise naturally at the intersection point. In particular, the Neumann boundary
conditions that are obtained at the intersection point differ from that
considered before by 't Hooft in [hep-th/0408148] and are stronger, which
appears to solve the nonlocality problem that was encountered in the standard
measure approach. The solutions of the equations of motion are presented.
Assuming that each endpoint is the dynamical massless particle, the Regge
trajectory with the slope parameter that depends on three different tensions is
obtained.
| hep-th | we consider string meson and string baryon models in the framework of the modified measure theory the theory that does not use the determinant of the metric to construct the invariant volume element as the outcome of this theory the string tension is not placed ad hoc but is derived when the charges are presented the tension undergoes alterations in the string meson model there are one string and two opposite charges at the endpoints in the string baryon model there are two strings two pairs of opposite charges at the endpoints and one additional charge at the intersection point the point where these two strings are connected the application of the modified measure theory is justified because the neumann boundary conditions are obtained dynamically at every point where the charge is located and dirichlet boundary conditions arise naturally at the intersection point in particular the neumann boundary conditions that are obtained at the intersection point differ from that considered before by t hooft in hepth0408148 and are stronger which appears to solve the nonlocality problem that was encountered in the standard measure approach the solutions of the equations of motion are presented assuming that each endpoint is the dynamical massless particle the regge trajectory with the slope parameter that depends on three different tensions is obtained | [['we', 'consider', 'string', 'meson', 'and', 'string', 'baryon', 'models', 'in', 'the', 'framework', 'of', 'the', 'modified', 'measure', 'theory', 'the', 'theory', 'that', 'does', 'not', 'use', 'the', 'determinant', 'of', 'the', 'metric', 'to', 'construct', 'the', 'invariant', 'volume', 'element', 'as', 'the', 'outcome', 'of', 'this', 'theory', 'the', 'string', 'tension', 'is', 'not', 'placed', 'ad', 'hoc', 'but', 'is', 'derived', 'when', 'the', 'charges', 'are', 'presented', 'the', 'tension', 'undergoes', 'alterations', 'in', 'the', 'string', 'meson', 'model', 'there', 'are', 'one', 'string', 'and', 'two', 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1,802.06432 | Music Genre Classification using Masked Conditional Neural Networks | The ConditionaL Neural Networks (CLNN) and the Masked ConditionaL Neural
Networks (MCLNN) exploit the nature of multi-dimensional temporal signals. The
CLNN captures the conditional temporal influence between the frames in a window
and the mask in the MCLNN enforces a systematic sparseness that follows a
filterbank-like pattern over the network links. The mask induces the network to
learn about time-frequency representations in bands, allowing the network to
sustain frequency shifts. Additionally, the mask in the MCLNN automates the
exploration of a range of feature combinations, usually done through an
exhaustive manual search. We have evaluated the MCLNN performance using the
Ballroom and Homburg datasets of music genres. MCLNN has achieved accuracies
that are competitive to state-of-the-art handcrafted attempts in addition to
models based on Convolutional Neural Networks.
| cs.LG stat.ML | the conditional neural networks clnn and the masked conditional neural networks mclnn exploit the nature of multidimensional temporal signals the clnn captures the conditional temporal influence between the frames in a window and the mask in the mclnn enforces a systematic sparseness that follows a filterbanklike pattern over the network links the mask induces the network to learn about timefrequency representations in bands allowing the network to sustain frequency shifts additionally the mask in the mclnn automates the exploration of a range of feature combinations usually done through an exhaustive manual search we have evaluated the mclnn performance using the ballroom and homburg datasets of music genres mclnn has achieved accuracies that are competitive to stateoftheart handcrafted attempts in addition to models based on convolutional neural networks | [['the', 'conditional', 'neural', 'networks', 'clnn', 'and', 'the', 'masked', 'conditional', 'neural', 'networks', 'mclnn', 'exploit', 'the', 'nature', 'of', 'multidimensional', 'temporal', 'signals', 'the', 'clnn', 'captures', 'the', 'conditional', 'temporal', 'influence', 'between', 'the', 'frames', 'in', 'a', 'window', 'and', 'the', 'mask', 'in', 'the', 'mclnn', 'enforces', 'a', 'systematic', 'sparseness', 'that', 'follows', 'a', 'filterbanklike', 'pattern', 'over', 'the', 'network', 'links', 'the', 'mask', 'induces', 'the', 'network', 'to', 'learn', 'about', 'timefrequency', 'representations', 'in', 'bands', 'allowing', 'the', 'network', 'to', 'sustain', 'frequency', 'shifts', 'additionally', 'the', 'mask', 'in', 'the', 'mclnn', 'automates', 'the', 'exploration', 'of', 'a', 'range', 'of', 'feature', 'combinations', 'usually', 'done', 'through', 'an', 'exhaustive', 'manual', 'search', 'we', 'have', 'evaluated', 'the', 'mclnn', 'performance', 'using', 'the', 'ballroom', 'and', 'homburg', 'datasets', 'of', 'music', 'genres', 'mclnn', 'has', 'achieved', 'accuracies', 'that', 'are', 'competitive', 'to', 'stateoftheart', 'handcrafted', 'attempts', 'in', 'addition', 'to', 'models', 'based', 'on', 'convolutional', 'neural', 'networks']] | [-0.095111622859443, 0.00758462602335919, -0.07482703651730267, 0.07571918710267969, -0.09634047211147845, -0.10926821849138904, 0.055573632197809364, 0.48565958050035296, -0.29231720827224233, -0.2931626871198652, 0.042550122065077876, -0.25083530724551234, -0.2198661132383027, 0.1547462460621896, -0.10145962918694648, 0.08595456283480402, 0.10324389011033677, 0.029088648985923518, -0.08791761499086866, -0.24614696784706283, 0.28927206012627316, 0.08947872332045956, 0.38924141064108836, -0.019211921499051626, 0.1601677260228566, -0.011780146008638281, -0.08306659406442786, -0.025390856033597614, -0.023191373305933898, 0.16085326093219457, 0.2730745731344844, 0.1853308431685917, 0.3028756100850712, -0.40699734775319935, -0.28339630750650985, 0.125124784755624, 0.11288173453760378, 0.08718959327765448, 0.04957732425111952, -0.39538384002027294, 0.08436753920885542, -0.14962104811806173, 0.09214291266638726, -0.12180077735545292, -0.04085673523248203, 0.01559203713097506, -0.30345274080034523, 0.03958117694313091, 0.11296704584743739, 0.0786062033019132, -0.019638647064788357, -0.09192743463559992, -0.021391021712343136, 0.18408227451736964, -0.0065633789331297435, 0.05672421675759353, 0.11463366175026056, -0.198678198736161, -0.14325497066971685, 0.31932657894988853, -0.09143980077305247, -0.19949225173331797, 0.14582806124374093, -0.035813306992326585, -0.12795434913982356, 0.11859696898757228, 0.25261778658669853, 0.07153235861499395, -0.15280598626630973, 0.0020018101375113935, -0.02354390567375554, 0.24721975294625506, 0.09249815991192702, 0.052518331612061174, 0.1998813731821313, 0.2708723017325004, 0.01620283392664518, 0.14436911809256314, -0.19335132715706196, -0.05968528359182297, -0.16898824506400464, -0.03679373756139761, -0.17934075096023402, -0.0785458325851886, -0.12103929784158633, -0.14551156582017447, 0.4677038640375175, 0.2114742196771124, 0.2165439548266549, 0.12628672439752828, 0.31283633527715526, 0.01992065683265941, 0.17324100322430097, 0.05662338284864312, 0.2042028061188166, 0.05316653973903389, 0.1550201058123512, -0.1533872736174436, 0.11472404388792162, 0.05497539614785522] |
1,802.06433 | Interpolating by functions from model subspaces in $H^1$ | Given an interpolating Blaschke product $B$ with zeros $\{a_j\}$, we seek to
characterize the sequences of values $\{w_j\}$ for which the interpolation
problem $$f(a_j)=w_j\qquad (j=1,2,\dots)$$ can be solved with a function $f$
from the model subspace $H^1\cap B\overline{H^1_0}$ of the Hardy space $H^1$.
| math.CV math.CA math.FA | given an interpolating blaschke product b with zeros a_j we seek to characterize the sequences of values w_j for which the interpolation problem fa_jw_jqquad j12dots can be solved with a function f from the model subspace h1cap boverlineh1_0 of the hardy space h1 | [['given', 'an', 'interpolating', 'blaschke', 'product', 'b', 'with', 'zeros', 'a_j', 'we', 'seek', 'to', 'characterize', 'the', 'sequences', 'of', 'values', 'w_j', 'for', 'which', 'the', 'interpolation', 'problem', 'fa_jw_jqquad', 'j12dots', 'can', 'be', 'solved', 'with', 'a', 'function', 'f', 'from', 'the', 'model', 'subspace', 'h1cap', 'boverlineh1_0', 'of', 'the', 'hardy', 'space', 'h1']] | [-0.1446044005271865, 0.05145348818928696, -0.0562523564823517, 0.048443376211585794, -0.043191880691887403, -0.10452996766785295, 0.016699590061495944, 0.3488687050369818, -0.38908518423757904, -0.20590224071610264, 0.11160909787683589, -0.2662585504671059, -0.08435404362020696, 0.1424861987768786, -0.04949862067019794, 0.09044540251879214, 0.0503352977698896, 0.044465079222147055, -0.14755442043448366, -0.25487521347567077, 0.3751833921116663, -0.039755259345217446, 0.10950918577429725, -0.03518121162565743, 0.06114035245121979, 0.006225336729208144, 0.004070476719700709, -0.07008638127391771, -0.22505241786356925, 0.1209886026563032, 0.2574534636081719, 0.15851948889562997, 0.3056208930182748, -0.34217995271177554, -0.11292831686030073, 0.2853266380318418, 0.17297916838944685, -0.06889455896382016, 0.011461846348715991, -0.2882725939881511, 0.054722630305261144, -0.10608551596722952, -0.11858573256105912, -0.08915316954073382, 0.03212537509729949, 0.0547362188695044, -0.43871087090271277, 0.06442397922595464, -0.006273160159031338, 0.012357348757909566, -0.1094308391940303, -0.17863910811067354, -0.01571048564482026, 0.08499088596052877, -0.0034328651211292644, 0.18453196184028212, 0.030547701932558017, -0.051504187109857436, -0.0747148779834189, 0.3386679060938882, -0.07069712173102832, -0.31255646755282834, 0.06710388216121894, -0.1984382640661263, -0.07743995610579121, 0.06068882986721469, 0.10959582401030674, 0.14326330099826987, -0.08763818729032831, 0.18958501317879048, -0.12984756375776557, 0.1283194446345655, 0.11023977648739408, -0.009455968966571296, 0.11083864386011733, 0.023896837243583144, 0.11381477879632901, 0.13160225542023687, -0.0032117160079041043, -0.005003225603481618, -0.3292797795474166, -0.15548733508259785, -0.23507429986465267, 0.07380674833931573, -0.1417657056846088, -0.1841231452346575, 0.35799674170727774, 0.05228273155985445, 0.2731191796142744, 0.08526582818580564, 0.17858709735659564, 0.1416582203038582, 0.06280465224877045, 0.08214916272952062, 0.10043749837886269, 0.147026750242065, 0.030597622108804744, -0.15974115486620222, 0.025231332904318483, 0.21460932052535256] |
1,802.06434 | Random time-changes and asymptotic results for a class of
continuous-time Markov chains on integers with alternating rates | We consider continuous-time Markov chains on integers which allow transitions
to adjacent states only, with alternating rates. We give explicit formulas for
probability generating functions, and also for means, variances and state
probabilities of the random variables of the process. Moreover we study
independent random time-changes with the inverse of the stable subordinator,
the stable subordinator and the tempered stable subodinator. We also present
some asymptotic results in the fashion of large deviations. These results give
some generalizations of those presented in Di Crescenzo A., Macci C.,
Martinucci B. (2014).
| math.PR | we consider continuoustime markov chains on integers which allow transitions to adjacent states only with alternating rates we give explicit formulas for probability generating functions and also for means variances and state probabilities of the random variables of the process moreover we study independent random timechanges with the inverse of the stable subordinator the stable subordinator and the tempered stable subodinator we also present some asymptotic results in the fashion of large deviations these results give some generalizations of those presented in di crescenzo a macci c martinucci b 2014 | [['we', 'consider', 'continuoustime', 'markov', 'chains', 'on', 'integers', 'which', 'allow', 'transitions', 'to', 'adjacent', 'states', 'only', 'with', 'alternating', 'rates', 'we', 'give', 'explicit', 'formulas', 'for', 'probability', 'generating', 'functions', 'and', 'also', 'for', 'means', 'variances', 'and', 'state', 'probabilities', 'of', 'the', 'random', 'variables', 'of', 'the', 'process', 'moreover', 'we', 'study', 'independent', 'random', 'timechanges', 'with', 'the', 'inverse', 'of', 'the', 'stable', 'subordinator', 'the', 'stable', 'subordinator', 'and', 'the', 'tempered', 'stable', 'subodinator', 'we', 'also', 'present', 'some', 'asymptotic', 'results', 'in', 'the', 'fashion', 'of', 'large', 'deviations', 'these', 'results', 'give', 'some', 'generalizations', 'of', 'those', 'presented', 'in', 'di', 'crescenzo', 'a', 'macci', 'c', 'martinucci', 'b', '2014']] | [-0.11337895766436387, 0.18458342932122337, -0.06920389876573939, 0.078253476513489, -0.025053553873228586, -0.1442541818250902, 0.10645681734736585, 0.39589405023831536, -0.2622755408731543, -0.18914973413021388, 0.11280072807196782, -0.2480450584500266, -0.13752871870317243, 0.17723960313014686, -0.04830534565073983, 0.0828038263663819, 0.05651074703994461, 0.03200654053415002, -0.03367113746935502, -0.25843223413209093, 0.29281728668138385, 0.009086507330225273, 0.21366869528587398, -0.025570164101240647, 0.11224858483976939, 0.02608331105015664, -0.04424056205475195, -0.03302440481175753, -0.20987225353548472, 0.09985994721897772, 0.2441241491681219, 0.07516324410897307, 0.21996742076325146, -0.4002274777846072, -0.12012000132182782, 0.1695700070175173, 0.09942855743627826, 0.0847034196194727, -0.0524926485496425, -0.31923371375887655, 0.08994705012777228, -0.16286029313182968, -0.12776055567453362, -0.10835869793399153, 0.06596816799984398, 0.1071988413115667, -0.3371333333039233, 0.08254969826785699, 0.11833857353088785, 0.0383107980702665, -0.043569377697580916, -0.18788021813485434, 0.016657083517533134, 0.0793654418666847, 0.05005000937771084, -0.08481040361220948, 0.07639381532366811, -0.05428890550551428, -0.16546627528309313, 0.2654199599796398, -0.07089884789986006, -0.22452268510427198, 0.17815092500876, -0.16701465854632921, -0.1863640509545803, 0.10849173653828488, 0.14175083875042302, 0.16927746143615383, -0.11046254794663665, 0.098949917119171, -0.04330641027031974, 0.08433383828113702, 0.07355760769728063, 0.025776360448534517, 0.1257279568288306, 0.054027979717251255, 0.08106109591740691, 0.18529157432071355, -0.043831776978384536, -0.14938017882576043, -0.32925876475531946, -0.18481470582297665, -0.12806584381244399, 0.07497313162788156, -0.12805029007276145, -0.1981759468379261, 0.38596315477678383, 0.14063387777423486, 0.2289769963562404, 0.13910855994353452, 0.18141837644560094, 0.15906641959339718, -0.08264842935353624, 0.07155824521958659, 0.11602071909543486, 0.17946259963156824, 0.05302252752219581, -0.14594685937150975, 0.1031096280309033, 0.10504893291826276] |
1,802.06435 | Topological Methods in the Quest for Periodic Orbits | These are lecture notes on Floer and Rabinowitz-Floer homology written for a
graduate course at UNICAMP August-December 2016 and a mini-course held at IMPA
in August 2017.
| math.SG math-ph math.DG math.DS math.GT math.MP | these are lecture notes on floer and rabinowitzfloer homology written for a graduate course at unicamp augustdecember 2016 and a minicourse held at impa in august 2017 | [['these', 'are', 'lecture', 'notes', 'on', 'floer', 'and', 'rabinowitzfloer', 'homology', 'written', 'for', 'a', 'graduate', 'course', 'at', 'unicamp', 'augustdecember', '2016', 'and', 'a', 'minicourse', 'held', 'at', 'impa', 'in', 'august', '2017']] | [-0.0972043197877981, 0.1285603372035203, -0.18079421665795423, 0.052517585180423876, -0.05262737569433672, -0.16648570199807486, -0.057059481739997864, 0.2648084144349451, -0.12274697575614685, -0.43794979651769, 0.2005398265318945, -0.33935483931391325, -0.14351219626971418, 0.16689326020854492, -0.23845113931154763, -0.10975189365584541, 0.14781736199640566, -0.0073128508886805286, -0.06083583010843507, -0.47401300962600446, 0.2396958766966472, 0.12670932144478517, 0.17150901230397048, 0.12889040696124235, 0.18170026299992093, 0.026671734121110704, -0.10491470734726775, -0.12861128054835178, -0.17862590247144303, 0.0765617897009684, 0.48935263990252104, -0.03059120498666609, 0.27665982864521166, -0.46237829327583313, 0.09056932592971458, -0.09490094195051049, -0.08703339064528269, 0.005273662322131848, 0.029914015330615693, -0.3918456796694685, -0.03011289466586378, -0.16765024685473354, -0.026878565480863606, 0.10490271559468022, 0.11498805333825725, -0.015722221781120257, -0.05589157173892966, -0.014795495800811935, 0.0117654179662673, 0.3539361148658726, 0.0015973730952720398, -0.22672588171230423, -0.0009701936160800633, 0.11943650921737706, -0.0904278691202678, 0.1498547581334909, 0.11325096263101807, -0.032958630196474215, -0.17402044769928413, 0.3120256834835918, -0.04499079859643071, 0.007613311487215536, 0.14678397098625148, -0.11996842675876838, -0.35827659220538205, 0.10928037597073449, 0.3051829476047445, 0.10565775460391133, -0.1127655462672313, 0.15037248034840794, 0.028884641258628108, 0.12922794944434254, 0.2004745145742264, -0.16299860276005887, 0.3203307078392417, -0.010785156343546178, -0.10346094539595975, -0.03489969656975181, 0.01665494712587032, -0.08509987468520801, -0.4359149756254973, -0.19388973550802027, -0.15679410638080704, 0.09019971956257467, 0.16266011565824523, -0.0729330695208369, 0.38481623375857316, 0.03479606809991377, 0.01901149309102308, 0.04869616124778986, 0.051664335342744984, 0.04184668172254331, -0.10241278536893704, 0.16993629901359478, 0.1212739225614954, 0.07497373388873206, 0.31175682743735333, 0.07165587320923805, -0.058913366248210274, 0.33952641814809154] |
1,802.06436 | Multicritical edge statistics for the momenta of fermions in
non-harmonic traps | We compute the joint statistics of the momenta $p_i$ of $N$ non-interacting
fermions in a trap, near the Fermi edge, with a particular focus on the largest
one $p_{\max}$. For a $1d$ harmonic trap, momenta and positions play a
symmetric role and hence, the joint statistics of momenta is identical to that
of the positions. In particular, $p_{\max}$, as $x_{\max}$, is distributed
according to the Tracy-Widom distribution. Here we show that novel "momentum
edge statistics" emerge when the curvature of the potential vanishes, i.e. for
"flat traps" near their minimum, with $V(x) \sim x^{2n}$ and $n>1$. These are
based on generalisations of the Airy kernel that we obtain explicitly. The
fluctuations of $p_{\max}$ are governed by new universal distributions
determined from the $n$-th member of the second Painlev\'e hierarchy of
non-linear differential equations, with connections to multicritical random
matrix models. Finite temperature extensions and possible experimental
signatures in cold atoms are discussed.
| cond-mat.stat-mech cond-mat.quant-gas math-ph math.MP math.PR | we compute the joint statistics of the momenta p_i of n noninteracting fermions in a trap near the fermi edge with a particular focus on the largest one p_max for a 1d harmonic trap momenta and positions play a symmetric role and hence the joint statistics of momenta is identical to that of the positions in particular p_max as x_max is distributed according to the tracywidom distribution here we show that novel momentum edge statistics emerge when the curvature of the potential vanishes ie for flat traps near their minimum with vx sim x2n and n1 these are based on generalisations of the airy kernel that we obtain explicitly the fluctuations of p_max are governed by new universal distributions determined from the nth member of the second painleve hierarchy of nonlinear differential equations with connections to multicritical random matrix models finite temperature extensions and possible experimental signatures in cold atoms are discussed | [['we', 'compute', 'the', 'joint', 'statistics', 'of', 'the', 'momenta', 'p_i', 'of', 'n', 'noninteracting', 'fermions', 'in', 'a', 'trap', 'near', 'the', 'fermi', 'edge', 'with', 'a', 'particular', 'focus', 'on', 'the', 'largest', 'one', 'p_max', 'for', 'a', '1d', 'harmonic', 'trap', 'momenta', 'and', 'positions', 'play', 'a', 'symmetric', 'role', 'and', 'hence', 'the', 'joint', 'statistics', 'of', 'momenta', 'is', 'identical', 'to', 'that', 'of', 'the', 'positions', 'in', 'particular', 'p_max', 'as', 'x_max', 'is', 'distributed', 'according', 'to', 'the', 'tracywidom', 'distribution', 'here', 'we', 'show', 'that', 'novel', 'momentum', 'edge', 'statistics', 'emerge', 'when', 'the', 'curvature', 'of', 'the', 'potential', 'vanishes', 'ie', 'for', 'flat', 'traps', 'near', 'their', 'minimum', 'with', 'vx', 'sim', 'x2n', 'and', 'n1', 'these', 'are', 'based', 'on', 'generalisations', 'of', 'the', 'airy', 'kernel', 'that', 'we', 'obtain', 'explicitly', 'the', 'fluctuations', 'of', 'p_max', 'are', 'governed', 'by', 'new', 'universal', 'distributions', 'determined', 'from', 'the', 'nth', 'member', 'of', 'the', 'second', 'painleve', 'hierarchy', 'of', 'nonlinear', 'differential', 'equations', 'with', 'connections', 'to', 'multicritical', 'random', 'matrix', 'models', 'finite', 'temperature', 'extensions', 'and', 'possible', 'experimental', 'signatures', 'in', 'cold', 'atoms', 'are', 'discussed']] | [-0.14092686494481504, 0.19608366004142322, -0.06416206143330783, 0.04446433115088822, -0.01938094468909855, -0.168234505476185, 0.011781318338379558, 0.33832648508465163, -0.2451527418299137, -0.2453646648048705, 0.038245129170000405, -0.3378090202551041, -0.11254311941631481, 0.14534769887043358, 0.0008684965348373609, 0.06773960507770856, -0.0032347728778595887, 0.061407830318019385, -0.08484645893814129, -0.22127962823172934, 0.35310532345120965, 0.04785915975164818, 0.25278240066989766, 0.026740545606021203, 0.09971419936291089, 0.012715229293558207, 0.009112425283283779, -0.012972184661808378, -0.14711961991341874, 0.08149700122349283, 0.206697081759007, 0.018021982230589186, 0.2250604361776679, -0.38232950822719813, -0.13584723545385427, 0.128751575903918, 0.16061096507627026, 0.07398996315283798, -0.015298317016506763, -0.24797257372349696, 0.03665000214363987, -0.13569972708845804, -0.19830132257706473, -0.05077035539924461, 0.05158012384613118, 0.0968817615373011, -0.25289880260702613, 0.11729341842951008, 0.06494600357683866, 0.025643586141277888, -0.04442711009974837, -0.15653747542589708, -0.05403148006390486, 0.08861676724355723, 0.008953424775666607, -0.019053370296636497, 0.10926116828341037, -0.1328770335852536, -0.09374315479477732, 0.38861111473096044, -0.06386640312848613, -0.20301355913914831, 0.11043033813965801, -0.19435488012325214, -0.1268662334432041, 0.12031133947158723, 0.16444148865718344, 0.10233380597109269, -0.1031904220631795, 0.10820943139103627, -0.04429016206229694, 0.10144626651813987, 0.09249602451822475, 0.044250167492703586, 0.24180390441937274, 0.0875988428949648, 0.06984924494731547, 0.13297789780067673, -0.11366168419236171, -0.13947832259681922, -0.3428599937990504, -0.13516898941567265, -0.25268818430700585, 0.028764970511953213, -0.09626377539940509, -0.17511445103139667, 0.39877638179122615, 0.12762979247858502, 0.25270922281963165, 0.06619967476734401, 0.21303841926304526, 0.16246268589977836, 0.03168753400524637, 0.09268223943945486, 0.19138448001314445, 0.1530589916464554, 0.06972239211226176, -0.24182710983490993, -0.016431785053818634, 0.07516322866630569] |
1,802.06437 | What We Read, What We Search: Media Attention and Public Attention Among
193 Countries | We investigate the alignment of international attention of news media
organizations within 193 countries with the expressed international interests
of the public within those same countries from March 7, 2016 to April 14, 2017.
We collect fourteen months of longitudinal data of online news from Unfiltered
News and web search volume data from Google Trends and build a multiplex
network of media attention and public attention in order to study its
structural and dynamic properties. Structurally, the media attention and the
public attention are both similar and different depending on the resolution of
the analysis. For example, we find that 63.2% of the country-specific media and
the public pay attention to different countries, but local attention flow
patterns, which are measured by network motifs, are very similar. We also show
that there are strong regional similarities with both media and public
attention that is only disrupted by significantly major worldwide incidents
(e.g., Brexit). Using Granger causality, we show that there are a substantial
number of countries where media attention and public attention are dissimilar
by topical interest. Our findings show that the media and public attention
toward specific countries are often at odds, indicating that the public within
these countries may be ignoring their country-specific news outlets and seeking
other online sources to address their media needs and desires.
| cs.SI physics.soc-ph | we investigate the alignment of international attention of news media organizations within 193 countries with the expressed international interests of the public within those same countries from march 7 2016 to april 14 2017 we collect fourteen months of longitudinal data of online news from unfiltered news and web search volume data from google trends and build a multiplex network of media attention and public attention in order to study its structural and dynamic properties structurally the media attention and the public attention are both similar and different depending on the resolution of the analysis for example we find that 632 of the countryspecific media and the public pay attention to different countries but local attention flow patterns which are measured by network motifs are very similar we also show that there are strong regional similarities with both media and public attention that is only disrupted by significantly major worldwide incidents eg brexit using granger causality we show that there are a substantial number of countries where media attention and public attention are dissimilar by topical interest our findings show that the media and public attention toward specific countries are often at odds indicating that the public within these countries may be ignoring their countryspecific news outlets and seeking other online sources to address their media needs and desires | [['we', 'investigate', 'the', 'alignment', 'of', 'international', 'attention', 'of', 'news', 'media', 'organizations', 'within', '193', 'countries', 'with', 'the', 'expressed', 'international', 'interests', 'of', 'the', 'public', 'within', 'those', 'same', 'countries', 'from', 'march', '7', '2016', 'to', 'april', '14', '2017', 'we', 'collect', 'fourteen', 'months', 'of', 'longitudinal', 'data', 'of', 'online', 'news', 'from', 'unfiltered', 'news', 'and', 'web', 'search', 'volume', 'data', 'from', 'google', 'trends', 'and', 'build', 'a', 'multiplex', 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1,802.06438 | Theory of nonlinear microwave absorption by interacting two-level
systems | The microwave absorption and noise caused by quantum two-level systems (TLS)
dramatically suppress the coherence in Josephson junction qubits that are
promising candidates for a quantum information applications. Microwave
absorption by TLSs is not clearly understood yet because of the complexity of
their interactions leading to the spectral diffusion. Here, the theory of the
non-linear absorption in the presence of spectral diffusion is developed using
the generalized master equation formalism. The theory predicts that the linear
absorption regime holds while a TLS Rabi frequency is smaller than their phase
decoherence rate. At higher external fields, a novel non-linear absorption
regime is found with the loss tangent inversely proportional to the intensity
of the field. The theory can be generalized to acoustic absorption and lower
dimensions realized in superconducting qubits.
| cond-mat.mes-hall quant-ph | the microwave absorption and noise caused by quantum twolevel systems tls dramatically suppress the coherence in josephson junction qubits that are promising candidates for a quantum information applications microwave absorption by tlss is not clearly understood yet because of the complexity of their interactions leading to the spectral diffusion here the theory of the nonlinear absorption in the presence of spectral diffusion is developed using the generalized master equation formalism the theory predicts that the linear absorption regime holds while a tls rabi frequency is smaller than their phase decoherence rate at higher external fields a novel nonlinear absorption regime is found with the loss tangent inversely proportional to the intensity of the field the theory can be generalized to acoustic absorption and lower dimensions realized in superconducting qubits | [['the', 'microwave', 'absorption', 'and', 'noise', 'caused', 'by', 'quantum', 'twolevel', 'systems', 'tls', 'dramatically', 'suppress', 'the', 'coherence', 'in', 'josephson', 'junction', 'qubits', 'that', 'are', 'promising', 'candidates', 'for', 'a', 'quantum', 'information', 'applications', 'microwave', 'absorption', 'by', 'tlss', 'is', 'not', 'clearly', 'understood', 'yet', 'because', 'of', 'the', 'complexity', 'of', 'their', 'interactions', 'leading', 'to', 'the', 'spectral', 'diffusion', 'here', 'the', 'theory', 'of', 'the', 'nonlinear', 'absorption', 'in', 'the', 'presence', 'of', 'spectral', 'diffusion', 'is', 'developed', 'using', 'the', 'generalized', 'master', 'equation', 'formalism', 'the', 'theory', 'predicts', 'that', 'the', 'linear', 'absorption', 'regime', 'holds', 'while', 'a', 'tls', 'rabi', 'frequency', 'is', 'smaller', 'than', 'their', 'phase', 'decoherence', 'rate', 'at', 'higher', 'external', 'fields', 'a', 'novel', 'nonlinear', 'absorption', 'regime', 'is', 'found', 'with', 'the', 'loss', 'tangent', 'inversely', 'proportional', 'to', 'the', 'intensity', 'of', 'the', 'field', 'the', 'theory', 'can', 'be', 'generalized', 'to', 'acoustic', 'absorption', 'and', 'lower', 'dimensions', 'realized', 'in', 'superconducting', 'qubits']] | [-0.15633478006997772, 0.18473635090681068, -0.004535167974820577, 0.051230229099385814, -0.03536983491318633, -0.19356553448912825, 0.018624643389994727, 0.35260824486613274, -0.2616054011118967, -0.2690644865068643, 0.021786562045278072, -0.29803699197864897, -0.14320191133103166, 0.21133885943726094, -0.010561410471248303, 0.0420580512894563, -0.03444588562480874, -0.001494415638636249, -0.021255280040096233, -0.21385854991629374, 0.29777675063544234, 0.07418684395708779, 0.3339366590524771, 0.05816754116857237, 0.07881008861803038, -0.02846522648753815, 0.06121782195400591, 0.015676993473303005, -0.07662554556026048, 0.08731999166910862, 0.2680242080223393, 0.013507276787891868, 0.24349452534603866, -0.4195879500561444, -0.26815574114344465, 0.06660320223652029, 0.1707224858755087, 0.1746356733442941, -0.004759825033301762, -0.2862865784198277, 0.007719792559194242, -0.12651324244721454, -0.13821299080267663, -0.045374212652993524, -0.010891460700776399, -0.011109048244814106, -0.2245141384191811, 0.1251496067992592, 0.05958013196724878, 0.02113809673361076, -0.012754919711327138, -0.01994971619050791, -0.009006841176788705, 0.041935621976921, -0.02222106336478808, -0.014595514055984023, 0.18039085412426858, -0.12874420895782668, -0.12059768420001564, 0.35775101438251344, -0.13405619981545727, -0.13674394230452158, 0.16208598874653726, -0.15047579294778118, -0.04072371685819686, 0.18470818020923194, 0.1191835440090648, 0.08275903065376662, -0.1736089324302495, 0.08407653604594399, 0.056771775924189145, 0.22439637224283793, 0.07761463064830317, 0.15237617685798874, 0.21059960390751561, 0.1407168684671669, 0.039985173735623214, 0.13319409570689206, -0.1031265723439612, -0.08317541032885165, -0.25397070552143014, -0.10074501188701247, -0.22367976517091656, 0.09083789900360835, -0.08293957264652628, -0.1576707272162271, 0.39033467917840264, 0.16506412785406432, 0.14506767336784523, -0.002939493216704144, 0.3240374381646745, 0.2464564388704508, 0.08424638713847181, 0.036226322376277556, 0.3058057871264543, 0.22422726189197842, 0.09900276442491558, -0.3253350164885669, 0.06005416545193902, -0.008793259963624237] |
1,802.06439 | Local Optimality and Generalization Guarantees for the Langevin
Algorithm via Empirical Metastability | We study the detailed path-wise behavior of the discrete-time Langevin
algorithm for non-convex Empirical Risk Minimization (ERM) through the lens of
metastability, adopting some techniques from Berglund and Gentz (2003.
For a particular local optimum of the empirical risk, with an arbitrary
initialization, we show that, with high probability, at least one of the
following two events will occur: (1) the Langevin trajectory ends up somewhere
outside the $\varepsilon$-neighborhood of this particular optimum within a
short recurrence time; (2) it enters this $\varepsilon$-neighborhood by the
recurrence time and stays there until a potentially exponentially long escape
time. We call this phenomenon empirical metastability.
This two-timescale characterization aligns nicely with the existing
literature in the following two senses. First, the effective recurrence time
(i.e., number of iterations multiplied by stepsize) is dimension-independent,
and resembles the convergence time of continuous-time deterministic Gradient
Descent (GD). However unlike GD, the Langevin algorithm does not require strong
conditions on local initialization, and has the possibility of eventually
visiting all optima. Second, the scaling of the escape time is consistent with
the Eyring-Kramers law, which states that the Langevin scheme will eventually
visit all local minima, but it will take an exponentially long time to transit
among them. We apply this path-wise concentration result in the context of
statistical learning to examine local notions of generalization and optimality.
| cs.LG math.OC math.PR stat.ML | we study the detailed pathwise behavior of the discretetime langevin algorithm for nonconvex empirical risk minimization erm through the lens of metastability adopting some techniques from berglund and gentz 2003 for a particular local optimum of the empirical risk with an arbitrary initialization we show that with high probability at least one of the following two events will occur 1 the langevin trajectory ends up somewhere outside the varepsilonneighborhood of this particular optimum within a short recurrence time 2 it enters this varepsilonneighborhood by the recurrence time and stays there until a potentially exponentially long escape time we call this phenomenon empirical metastability this twotimescale characterization aligns nicely with the existing literature in the following two senses first the effective recurrence time ie number of iterations multiplied by stepsize is dimensionindependent and resembles the convergence time of continuoustime deterministic gradient descent gd however unlike gd the langevin algorithm does not require strong conditions on local initialization and has the possibility of eventually visiting all optima second the scaling of the escape time is consistent with the eyringkramers law which states that the langevin scheme will eventually visit all local minima but it will take an exponentially long time to transit among them we apply this pathwise concentration result in the context of statistical learning to examine local notions of generalization and optimality | [['we', 'study', 'the', 'detailed', 'pathwise', 'behavior', 'of', 'the', 'discretetime', 'langevin', 'algorithm', 'for', 'nonconvex', 'empirical', 'risk', 'minimization', 'erm', 'through', 'the', 'lens', 'of', 'metastability', 'adopting', 'some', 'techniques', 'from', 'berglund', 'and', 'gentz', '2003', 'for', 'a', 'particular', 'local', 'optimum', 'of', 'the', 'empirical', 'risk', 'with', 'an', 'arbitrary', 'initialization', 'we', 'show', 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1,802.0644 | Capacitated Dynamic Programming: Faster Knapsack and Graph Algorithms | One of the most fundamental problems in Computer Science is the Knapsack
problem. Given a set of n items with different weights and values, it asks to
pick the most valuable subset whose total weight is below a capacity threshold
T. Despite its wide applicability in various areas in Computer Science,
Operations Research, and Finance, the best known running time for the problem
is O(Tn). The main result of our work is an improved algorithm running in time
O(TD), where D is the number of distinct weights. Previously, faster runtimes
for Knapsack were only possible when both weights and values are bounded by M
and V respectively, running in time O(nMV) [Pisinger'99]. In comparison, our
algorithm implies a bound of O(nM^2) without any dependence on V, or O(nV^2)
without any dependence on M. Additionally, for the unbounded Knapsack problem,
we provide an algorithm running in time O(M^2) or O(V^2). Both our algorithms
match recent conditional lower bounds shown for the Knapsack problem [Cygan et
al'17, K\"unnemann et al'17].
We also initiate a systematic study of general capacitated dynamic
programming, of which Knapsack is a core problem. This problem asks to compute
the maximum weight path of length k in an edge- or node-weighted directed
acyclic graph. In a graph with m edges, these problems are solvable by dynamic
programming in time O(km), and we explore under which conditions the dependence
on k can be eliminated. We identify large classes of graphs where this is
possible and apply our results to obtain linear time algorithms for the problem
of k-sparse Delta-separated sequences. The main technical innovation behind our
results is identifying and exploiting concavity that appears in relaxations and
subproblems of the tasks we consider.
| cs.DS | one of the most fundamental problems in computer science is the knapsack problem given a set of n items with different weights and values it asks to pick the most valuable subset whose total weight is below a capacity threshold t despite its wide applicability in various areas in computer science operations research and finance the best known running time for the problem is otn the main result of our work is an improved algorithm running in time otd where d is the number of distinct weights previously faster runtimes for knapsack were only possible when both weights and values are bounded by m and v respectively running in time onmv pisinger99 in comparison our algorithm implies a bound of onm2 without any dependence on v or onv2 without any dependence on m additionally for the unbounded knapsack problem we provide an algorithm running in time om2 or ov2 both our algorithms match recent conditional lower bounds shown for the knapsack problem cygan et al17 kunnemann et al17 we also initiate a systematic study of general capacitated dynamic programming of which knapsack is a core problem this problem asks to compute the maximum weight path of length k in an edge or nodeweighted directed acyclic graph in a graph with m edges these problems are solvable by dynamic programming in time okm and we explore under which conditions the dependence on k can be eliminated we identify large classes of graphs where this is possible and apply our results to obtain linear time algorithms for the problem of ksparse deltaseparated sequences the main technical innovation behind our results is identifying and exploiting concavity that appears in relaxations and subproblems of the tasks we consider | [['one', 'of', 'the', 'most', 'fundamental', 'problems', 'in', 'computer', 'science', 'is', 'the', 'knapsack', 'problem', 'given', 'a', 'set', 'of', 'n', 'items', 'with', 'different', 'weights', 'and', 'values', 'it', 'asks', 'to', 'pick', 'the', 'most', 'valuable', 'subset', 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1,802.06441 | Deep neural decoders for near term fault-tolerant experiments | Finding efficient decoders for quantum error correcting codes adapted to
realistic experimental noise in fault-tolerant devices represents a significant
challenge. In this paper we introduce several decoding algorithms complemented
by deep neural decoders and apply them to analyze several fault-tolerant error
correction protocols such as the surface code as well as Steane and Knill error
correction. Our methods require no knowledge of the underlying noise model
afflicting the quantum device making them appealing for real-world experiments.
Our analysis is based on a full circuit-level noise model. It considers both
distance-three and five codes, and is performed near the codes pseudo-threshold
regime. Training deep neural decoders in low noise rate regimes appears to be a
challenging machine learning endeavour. We provide a detailed description of
our neural network architectures and training methodology. We then discuss both
the advantages and limitations of deep neural decoders. Lastly, we provide a
rigorous analysis of the decoding runtime of trained deep neural decoders and
compare our methods with anticipated gate times in future quantum devices.
Given the broad applications of our decoding schemes, we believe that the
methods presented in this paper could have practical applications for near term
fault-tolerant experiments.
| quant-ph stat.ML | finding efficient decoders for quantum error correcting codes adapted to realistic experimental noise in faulttolerant devices represents a significant challenge in this paper we introduce several decoding algorithms complemented by deep neural decoders and apply them to analyze several faulttolerant error correction protocols such as the surface code as well as steane and knill error correction our methods require no knowledge of the underlying noise model afflicting the quantum device making them appealing for realworld experiments our analysis is based on a full circuitlevel noise model it considers both distancethree and five codes and is performed near the codes pseudothreshold regime training deep neural decoders in low noise rate regimes appears to be a challenging machine learning endeavour we provide a detailed description of our neural network architectures and training methodology we then discuss both the advantages and limitations of deep neural decoders lastly we provide a rigorous analysis of the decoding runtime of trained deep neural decoders and compare our methods with anticipated gate times in future quantum devices given the broad applications of our decoding schemes we believe that the methods presented in this paper could have practical applications for near term faulttolerant experiments | [['finding', 'efficient', 'decoders', 'for', 'quantum', 'error', 'correcting', 'codes', 'adapted', 'to', 'realistic', 'experimental', 'noise', 'in', 'faulttolerant', 'devices', 'represents', 'a', 'significant', 'challenge', 'in', 'this', 'paper', 'we', 'introduce', 'several', 'decoding', 'algorithms', 'complemented', 'by', 'deep', 'neural', 'decoders', 'and', 'apply', 'them', 'to', 'analyze', 'several', 'faulttolerant', 'error', 'correction', 'protocols', 'such', 'as', 'the', 'surface', 'code', 'as', 'well', 'as', 'steane', 'and', 'knill', 'error', 'correction', 'our', 'methods', 'require', 'no', 'knowledge', 'of', 'the', 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1,802.06442 | Tame and Wild Symmetric Special Multiserial Algebras | We provide a complete classification of all tame and wild symmetric special
multiserial algebras in terms of the underlying Brauer configuration. Our
classification contains the symmetric special multiserial algebras of finite
representation type.
| math.RT | we provide a complete classification of all tame and wild symmetric special multiserial algebras in terms of the underlying brauer configuration our classification contains the symmetric special multiserial algebras of finite representation type | [['we', 'provide', 'a', 'complete', 'classification', 'of', 'all', 'tame', 'and', 'wild', 'symmetric', 'special', 'multiserial', 'algebras', 'in', 'terms', 'of', 'the', 'underlying', 'brauer', 'configuration', 'our', 'classification', 'contains', 'the', 'symmetric', 'special', 'multiserial', 'algebras', 'of', 'finite', 'representation', 'type']] | [-0.14981194207388343, -0.007892408544042459, -0.015834171212080753, 0.0860781367077972, -0.1615551646770627, -0.18208425897032474, -0.0827707350747942, 0.3472141755998812, -0.271334270819683, -0.11927014036160527, 0.1302677453883613, -0.1712452238284503, -0.1853624882289406, 0.1457767684972196, -0.2075712684485497, -0.1520301288727558, 0.10509621622887524, 0.19254016836092694, -0.17828703522117753, -0.36810891636802506, 0.4229091274918932, -0.06420989849632888, 0.28942889573447633, 0.0016055380304654439, 0.08694633351864689, 0.14693637147094263, -0.04748188038215493, -0.01348010856996883, -0.14255544828307448, 0.09907631161904921, 0.38661711516253877, 0.09148551681728075, 0.18388345687664254, -0.29837194062543637, -0.09018229509732037, 0.25646516624273674, 0.14823597122096654, 0.10174671010198919, -0.07331943797004042, -0.2923002608797767, 0.09007543228058652, -0.28800901488372777, -0.16818120835744071, -0.07235282351911972, 0.0700827134829579, 0.021229295285813736, -0.2169195662506602, 0.038403066750051396, 0.17254406394380511, 0.19469054571042457, -0.133450791500791, -0.13764043537561188, -0.12474599522256265, 0.14392657390315877, -0.13387496966981527, -0.046739719875128656, 0.022215247619897127, -0.12023505017383616, -0.17613914744420486, 0.3801000252591841, 0.04972501350284526, -0.24535913265902887, 0.13895046050575646, -0.16935144562387106, -0.21535277417437595, 0.12202605811850817, 0.09301681105386127, 0.1858190835425348, -0.014128716239197687, 0.21365166672639493, -0.1820423835606286, -0.032489978546050916, 0.08775409855738733, 0.0011309594953094017, 0.09917542967719561, 0.13456612548819094, -0.007233892426346288, 0.19799887304278938, 0.037966693130632244, -0.05181664379426476, -0.4332075489289833, -0.1377292356143395, -0.04418430026183187, 0.12240819175812331, -0.16707130362038064, -0.28834549473090604, 0.5018464055928317, 0.033736887529040825, 0.09096250189186046, 0.10609176543287256, 0.1584772062064572, 0.014970547283265852, 0.12830324229699644, 0.029052837878804316, 0.07674317606583689, 0.2811597043535475, -0.038812354037707504, -0.10973703333487113, -0.03053276169565365, 0.2389466856521639] |
1,802.06443 | Lifting Private Information Retrieval from Two to any Number of Messages | We study private information retrieval (PIR) on coded data with possibly
colluding servers. Devising PIR schemes with optimal download rate in the case
of collusion and coded data is still open in general. We provide a lifting
operation that can transform what we call one-shot PIR schemes for two messages
into schemes for any number of messages. We apply this lifting operation on
existing PIR schemes and describe two immediate implications. First, we obtain
novel PIR schemes with improved download rate in the case of MDS coded data and
server collusion. Second, we provide a simplified description of existing
optimal PIR schemes on replicated data as lifted secret sharing based PIR.
| cs.IT math.IT | we study private information retrieval pir on coded data with possibly colluding servers devising pir schemes with optimal download rate in the case of collusion and coded data is still open in general we provide a lifting operation that can transform what we call oneshot pir schemes for two messages into schemes for any number of messages we apply this lifting operation on existing pir schemes and describe two immediate implications first we obtain novel pir schemes with improved download rate in the case of mds coded data and server collusion second we provide a simplified description of existing optimal pir schemes on replicated data as lifted secret sharing based pir | [['we', 'study', 'private', 'information', 'retrieval', 'pir', 'on', 'coded', 'data', 'with', 'possibly', 'colluding', 'servers', 'devising', 'pir', 'schemes', 'with', 'optimal', 'download', 'rate', 'in', 'the', 'case', 'of', 'collusion', 'and', 'coded', 'data', 'is', 'still', 'open', 'in', 'general', 'we', 'provide', 'a', 'lifting', 'operation', 'that', 'can', 'transform', 'what', 'we', 'call', 'oneshot', 'pir', 'schemes', 'for', 'two', 'messages', 'into', 'schemes', 'for', 'any', 'number', 'of', 'messages', 'we', 'apply', 'this', 'lifting', 'operation', 'on', 'existing', 'pir', 'schemes', 'and', 'describe', 'two', 'immediate', 'implications', 'first', 'we', 'obtain', 'novel', 'pir', 'schemes', 'with', 'improved', 'download', 'rate', 'in', 'the', 'case', 'of', 'mds', 'coded', 'data', 'and', 'server', 'collusion', 'second', 'we', 'provide', 'a', 'simplified', 'description', 'of', 'existing', 'optimal', 'pir', 'schemes', 'on', 'replicated', 'data', 'as', 'lifted', 'secret', 'sharing', 'based', 'pir']] | [-0.2619828150213302, -0.026229375847489446, -0.029020253292008025, 0.07339939956662354, -0.08244636636080539, -0.3411799036385911, 0.1866637063338547, 0.367685962678143, -0.3102543482112254, -0.23389239274049262, 0.19783762327357624, -0.2775526817023821, -0.06281515313228508, 0.20487276957210926, -0.21579477104131836, 0.07773462753440882, 0.011512034312561826, 0.03665996654649257, -0.057165148900821805, -0.416219623675486, 0.3367444282431189, 0.0859286821623509, 0.3257333186312436, 0.027164247809900895, 0.053177437078006366, 0.07094160624074976, -0.09008317830057831, -0.06849789429405653, -0.2022912942132255, 0.11046894501552808, 0.3811449933176239, 0.28050153148318596, 0.1788260805177259, -0.38269211279714965, -0.20851976539402664, 0.10711979442947284, 0.13103982928704033, 0.2060087605354351, -0.12502382722418956, -0.23669501481712, 0.09104087561691969, -0.2709872749978089, 0.05410155594382469, -0.08650358911469444, -0.06448855660520159, 0.019990470023355907, -0.3625329830515962, -0.03488436699551237, -0.006115176782079108, 0.054814014611094516, -0.05059846319040066, -0.060321100768297574, 0.08902460179786693, 0.15610288565156158, -0.01861725953042608, 0.002298053506098956, 0.07591237487304989, -0.05919556125688056, -0.17274006052773344, 0.38566204779655544, -0.06197444153823764, -0.17521959890166786, 0.08831219260396252, -0.01847782045569237, -0.1446422876513286, 0.1233348665289111, 0.2396538740124654, 0.1337564518415109, -0.14801589625694597, 0.015476070988927506, -0.11354776401374791, 0.23212113476731722, 0.09068067629217498, 0.19288338816762474, 0.06775514351472527, 0.14553290294265156, 0.13130384080556665, 0.21013241991199352, -0.04898873561162602, -0.14254558406904475, -0.22210259615498185, -0.16908878587324777, -0.18109210362020242, 0.0012049584876041154, -0.1315813943538406, -0.0242122738194224, 0.3017716941734155, 0.18914985766651127, 0.10737354681000684, 0.10181630406474175, 0.4269167855298063, -0.029710563991495686, 0.07101897355840281, 0.24652087679636236, 0.09090612865648828, 0.022826903004635562, 0.10452296524014962, -0.17118405761131136, 0.09134358701690494, 0.08682772786532705] |
1,802.06444 | Efficient Collaborative Multi-Agent Deep Reinforcement Learning for
Large-Scale Fleet Management | Large-scale online ride-sharing platforms have substantially transformed our
lives by reallocating transportation resources to alleviate traffic congestion
and promote transportation efficiency. An efficient fleet management strategy
not only can significantly improve the utilization of transportation resources
but also increase the revenue and customer satisfaction. It is a challenging
task to design an effective fleet management strategy that can adapt to an
environment involving complex dynamics between demand and supply. Existing
studies usually work on a simplified problem setting that can hardly capture
the complicated stochastic demand-supply variations in high-dimensional space.
In this paper we propose to tackle the large-scale fleet management problem
using reinforcement learning, and propose a contextual multi-agent
reinforcement learning framework including three concrete algorithms to achieve
coordination among a large number of agents adaptive to different contexts. We
show significant improvements of the proposed framework over state-of-the-art
approaches through extensive empirical studies.
| cs.MA cs.AI | largescale online ridesharing platforms have substantially transformed our lives by reallocating transportation resources to alleviate traffic congestion and promote transportation efficiency an efficient fleet management strategy not only can significantly improve the utilization of transportation resources but also increase the revenue and customer satisfaction it is a challenging task to design an effective fleet management strategy that can adapt to an environment involving complex dynamics between demand and supply existing studies usually work on a simplified problem setting that can hardly capture the complicated stochastic demandsupply variations in highdimensional space in this paper we propose to tackle the largescale fleet management problem using reinforcement learning and propose a contextual multiagent reinforcement learning framework including three concrete algorithms to achieve coordination among a large number of agents adaptive to different contexts we show significant improvements of the proposed framework over stateoftheart approaches through extensive empirical studies | [['largescale', 'online', 'ridesharing', 'platforms', 'have', 'substantially', 'transformed', 'our', 'lives', 'by', 'reallocating', 'transportation', 'resources', 'to', 'alleviate', 'traffic', 'congestion', 'and', 'promote', 'transportation', 'efficiency', 'an', 'efficient', 'fleet', 'management', 'strategy', 'not', 'only', 'can', 'significantly', 'improve', 'the', 'utilization', 'of', 'transportation', 'resources', 'but', 'also', 'increase', 'the', 'revenue', 'and', 'customer', 'satisfaction', 'it', 'is', 'a', 'challenging', 'task', 'to', 'design', 'an', 'effective', 'fleet', 'management', 'strategy', 'that', 'can', 'adapt', 'to', 'an', 'environment', 'involving', 'complex', 'dynamics', 'between', 'demand', 'and', 'supply', 'existing', 'studies', 'usually', 'work', 'on', 'a', 'simplified', 'problem', 'setting', 'that', 'can', 'hardly', 'capture', 'the', 'complicated', 'stochastic', 'demandsupply', 'variations', 'in', 'highdimensional', 'space', 'in', 'this', 'paper', 'we', 'propose', 'to', 'tackle', 'the', 'largescale', 'fleet', 'management', 'problem', 'using', 'reinforcement', 'learning', 'and', 'propose', 'a', 'contextual', 'multiagent', 'reinforcement', 'learning', 'framework', 'including', 'three', 'concrete', 'algorithms', 'to', 'achieve', 'coordination', 'among', 'a', 'large', 'number', 'of', 'agents', 'adaptive', 'to', 'different', 'contexts', 'we', 'show', 'significant', 'improvements', 'of', 'the', 'proposed', 'framework', 'over', 'stateoftheart', 'approaches', 'through', 'extensive', 'empirical', 'studies']] | [-0.1066558069388928, 0.027388599050403892, -0.03964552185337605, 0.06697650106447138, -0.14209404437770617, -0.1584328322960385, 0.08713573442916546, 0.4482081123081775, -0.3052312619823577, -0.3918747920446612, 0.09162716405177168, -0.2343817742822435, -0.18939329015797582, 0.20233026108351246, -0.20803807003359343, 0.07105973591819277, 0.11752095117297923, -0.01984270951020178, -0.005957166645033606, -0.29904684224085687, 0.26461397932103736, 0.07115749203567875, 0.38952136603665766, 0.0731322219145709, 0.08840250257595346, 0.007386182153854391, -0.014526346277702471, 0.03271159932703775, -0.07825425432980912, 0.20867152483973267, 0.3824575577878618, 0.23382791913724665, 0.40387923410483473, -0.4584241883893465, -0.2679454244881997, 0.15746478009166132, 0.16799645492594273, 0.04331113394221355, -0.038260993491537096, -0.2811929367996495, 0.035221772473947754, -0.2621354911604832, -0.0457877232147188, -0.15036693189357375, -0.04283138853979522, -0.002158538152560078, -0.30523139529636706, -0.032707796990469995, -0.0006028627302369167, 0.04165744967076221, -0.05578668667324658, -0.0775028825914166, 0.05686834628918561, 0.16091828572339026, 0.07250950519188211, -0.018210666695738148, 0.17808654288408057, -0.15613445291648909, -0.1901360815246429, 0.39612738399541586, 0.004205413634792484, -0.2119674033774384, 0.18968037568546575, 0.023593426987143427, -0.1715528689389085, 0.09458071498826531, 0.3265197400774421, 0.1087854617403756, -0.2131913915019611, 0.007284028490941072, -0.030821340492573276, 0.18887689498188936, -0.00011976138078447046, -0.005846448377545538, 0.13459071799920036, 0.28412810472835753, 0.2002462399850503, 0.10870368371974548, -0.01646645578619992, -0.17560190909766946, -0.1378800259774615, -0.11581568764362099, -0.14037417067367391, 0.0034687076166376534, -0.10193983079375828, -0.09254128194157163, 0.3235681393793945, 0.2208212864585221, 0.127966447482849, 0.0912255544119097, 0.3985425001074528, 0.06868491520029332, 0.06917077059504287, 0.14567410627596786, 0.1457629354172868, -0.05759905619578885, 0.20866931048302173, -0.25326715553628987, 0.11472867493164436, -0.021630191189590198] |
1,802.06445 | Dancing twins: stellar hierarchies that formed sequentially? | This paper attracts attention to the class of resolved triple stars with
moderate ratios of inner and outer periods (possibly in a mean motion
resonance) and nearly circular, mutually aligned orbits. Moreover, stars in the
inner pair are twins with almost identical masses, while the mass sum of the
inner pair is comparable to the mass of the outer component. Such systems could
be formed either sequentially (inside-out) by disk fragmentation with
subsequent accretion and migration or by a cascade hierarchical fragmentation
of a rotating cloud. Orbits of the outer and inner subsystems are computed or
updated in four such hierarchies: LHS 1070 (GJ 2005, periods 77.6 and 17.25
years), HIP 9497 (80 and 14.4 years), HIP 25240 (1200 and 47.0 years), and HIP
78842 (131 and 10.5 years).
| astro-ph.SR | this paper attracts attention to the class of resolved triple stars with moderate ratios of inner and outer periods possibly in a mean motion resonance and nearly circular mutually aligned orbits moreover stars in the inner pair are twins with almost identical masses while the mass sum of the inner pair is comparable to the mass of the outer component such systems could be formed either sequentially insideout by disk fragmentation with subsequent accretion and migration or by a cascade hierarchical fragmentation of a rotating cloud orbits of the outer and inner subsystems are computed or updated in four such hierarchies lhs 1070 gj 2005 periods 776 and 1725 years hip 9497 80 and 144 years hip 25240 1200 and 470 years and hip 78842 131 and 105 years | [['this', 'paper', 'attracts', 'attention', 'to', 'the', 'class', 'of', 'resolved', 'triple', 'stars', 'with', 'moderate', 'ratios', 'of', 'inner', 'and', 'outer', 'periods', 'possibly', 'in', 'a', 'mean', 'motion', 'resonance', 'and', 'nearly', 'circular', 'mutually', 'aligned', 'orbits', 'moreover', 'stars', 'in', 'the', 'inner', 'pair', 'are', 'twins', 'with', 'almost', 'identical', 'masses', 'while', 'the', 'mass', 'sum', 'of', 'the', 'inner', 'pair', 'is', 'comparable', 'to', 'the', 'mass', 'of', 'the', 'outer', 'component', 'such', 'systems', 'could', 'be', 'formed', 'either', 'sequentially', 'insideout', 'by', 'disk', 'fragmentation', 'with', 'subsequent', 'accretion', 'and', 'migration', 'or', 'by', 'a', 'cascade', 'hierarchical', 'fragmentation', 'of', 'a', 'rotating', 'cloud', 'orbits', 'of', 'the', 'outer', 'and', 'inner', 'subsystems', 'are', 'computed', 'or', 'updated', 'in', 'four', 'such', 'hierarchies', 'lhs', '1070', 'gj', '2005', 'periods', '776', 'and', '1725', 'years', 'hip', '9497', '80', 'and', '144', 'years', 'hip', '25240', '1200', 'and', '470', 'years', 'and', 'hip', '78842', '131', 'and', '105', 'years']] | [-0.1405820591323899, 0.20058354377328586, -0.010398923357083338, 0.009761436866215013, -0.056861617112913584, -0.0823911504900655, 0.03388830640730925, 0.39089461350740173, -0.20206053536311966, -0.3817497567222344, 0.10591730782963835, -0.28740662364444997, 0.000242591391896873, 0.1700454954608842, -0.06366097159669037, 0.04219117594926845, 0.1690359819454955, -0.01235888733191225, -0.07212325127788005, -0.24007850814625387, 0.2779822329675236, 0.01713042899917657, 0.09216913707072179, -0.07122759835695569, 0.04061436656803832, -0.025468585187730593, -0.022289430904092165, -0.06389879149304131, -0.12582523785678185, 0.09832605413769878, 0.1751121989869344, 0.08541101685681153, 0.21121631675641836, -0.33811856088811515, -0.123606578448758, 0.04080914759891122, 0.19669169016314422, -0.04811932887757329, -0.03593644787242094, -0.23458709033191438, 0.10309123644957274, -0.2629824962730952, -0.15148199035412097, 0.05999629505667982, 0.12908497311387535, -0.037873435816379246, -0.289548398303528, 0.13766623671738593, 0.07889782812989016, 0.09863045535922989, -0.11492697327529762, -0.1618087945091648, -0.10143552057437716, 0.07963479735602544, 0.03912458348630627, 0.05345031051111855, 0.18535411407516567, -0.025705066471045295, -0.07345615049978117, 0.371715390864085, -0.08418719269569934, -0.04778708325420308, 0.2730486297239293, -0.1911718888986511, -0.09338846642846667, 0.1673389718424177, 0.17345172115858262, 0.16438329282884054, -0.1768836034461856, -0.04633831438529635, -0.036607746496855276, 0.1552369198706881, 0.16689546864597113, 0.016050154984906667, 0.3855218890262401, 0.11358789341729575, 0.033847831966956766, 0.046222304961072117, -0.2038411228682875, -0.1302170032235669, -0.15213882218401029, -0.11565176100565458, -0.04952698556145316, 0.030036612422990164, -0.07771371077921692, -0.10567000384376508, 0.3374753523119322, 2.1535851882667994e-05, 0.2874499283562319, 0.015405268427607874, 0.29287333894011336, 0.04033447875949283, 0.13355062811774768, 0.16337298856329496, 0.33113471558867535, 0.19370365387019445, 0.07347750027781337, -0.19028200739701315, 0.03928829936354648, -0.008714881193948778] |
1,802.06446 | Fast 5DOF Needle Tracking in iOCT | Purpose. Intraoperative Optical Coherence Tomography (iOCT) is an
increasingly available imaging technique for ophthalmic microsurgery that
provides high-resolution cross-sectional information of the surgical scene. We
propose to build on its desirable qualities and present a method for tracking
the orientation and location of a surgical needle. Thereby, we enable direct
analysis of instrument-tissue interaction directly in OCT space without complex
multimodal calibration that would be required with traditional instrument
tracking methods. Method. The intersection of the needle with the iOCT scan is
detected by a peculiar multi-step ellipse fitting that takes advantage of the
directionality of the modality. The geometric modelling allows us to use the
ellipse parameters and provide them into a latency aware estimator to infer the
5DOF pose during needle movement. Results. Experiments on phantom data and
ex-vivo porcine eyes indicate that the algorithm retains angular precision
especially during lateral needle movement and provides a more robust and
consistent estimation than baseline methods. Conclusion. Using solely
crosssectional iOCT information, we are able to successfully and robustly
estimate a 5DOF pose of the instrument in less than 5.5 ms on a CPU.
| cs.CV | purpose intraoperative optical coherence tomography ioct is an increasingly available imaging technique for ophthalmic microsurgery that provides highresolution crosssectional information of the surgical scene we propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle thereby we enable direct analysis of instrumenttissue interaction directly in oct space without complex multimodal calibration that would be required with traditional instrument tracking methods method the intersection of the needle with the ioct scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality the geometric modelling allows us to use the ellipse parameters and provide them into a latency aware estimator to infer the 5dof pose during needle movement results experiments on phantom data and exvivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods conclusion using solely crosssectional ioct information we are able to successfully and robustly estimate a 5dof pose of the instrument in less than 55 ms on a cpu | [['purpose', 'intraoperative', 'optical', 'coherence', 'tomography', 'ioct', 'is', 'an', 'increasingly', 'available', 'imaging', 'technique', 'for', 'ophthalmic', 'microsurgery', 'that', 'provides', 'highresolution', 'crosssectional', 'information', 'of', 'the', 'surgical', 'scene', 'we', 'propose', 'to', 'build', 'on', 'its', 'desirable', 'qualities', 'and', 'present', 'a', 'method', 'for', 'tracking', 'the', 'orientation', 'and', 'location', 'of', 'a', 'surgical', 'needle', 'thereby', 'we', 'enable', 'direct', 'analysis', 'of', 'instrumenttissue', 'interaction', 'directly', 'in', 'oct', 'space', 'without', 'complex', 'multimodal', 'calibration', 'that', 'would', 'be', 'required', 'with', 'traditional', 'instrument', 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1,802.06447 | Eigenvalue bounds for Stark operators with complex potentials | We consider the 3-dimensional Stark operator perturbed by a complex-valued
potential. We obtain an estimate for the number of eigenvalues of this operator
as well as for the sum of imaginary parts of eigenvalues situated in the upper
half-plane.
| math.SP | we consider the 3dimensional stark operator perturbed by a complexvalued potential we obtain an estimate for the number of eigenvalues of this operator as well as for the sum of imaginary parts of eigenvalues situated in the upper halfplane | [['we', 'consider', 'the', '3dimensional', 'stark', 'operator', 'perturbed', 'by', 'a', 'complexvalued', 'potential', 'we', 'obtain', 'an', 'estimate', 'for', 'the', 'number', 'of', 'eigenvalues', 'of', 'this', 'operator', 'as', 'well', 'as', 'for', 'the', 'sum', 'of', 'imaginary', 'parts', 'of', 'eigenvalues', 'situated', 'in', 'the', 'upper', 'halfplane']] | [-0.1454436944749875, 0.06357707965929503, 0.005171034306001205, 0.03237469139425323, -0.03954043062642599, -0.04756832140712784, 0.012700024801187025, 0.2969457636324641, -0.24851708916517404, -0.24462997555159605, 0.12447531390875483, -0.31465003276482606, -0.16396881226384535, 0.18185058355522463, -0.02158477138250302, 0.06721635721623898, 0.023320096330000803, 0.144620850825539, -0.045010011619291246, -0.1427092003958443, 0.3867727466500722, -0.00704154372215271, 0.12311146841742672, 0.07823357425439052, 0.06320141076755065, 0.05311128499511725, 0.02293123758565157, -0.06422514769320305, -0.09845559850621682, 0.11783796644363648, 0.21912013844419748, 0.04113678672374823, 0.2705555477967629, -0.41917867860637414, -0.14904911496127263, 0.19160754448519304, 0.2153247553282059, 0.012989199505402492, -0.024572971957520798, -0.3025596485688136, 0.03270659939003869, -0.11640926546011215, -0.2307942961103832, -0.02989763016693103, 0.04838540400259006, 0.016143521771599084, -0.31779347164317584, 0.10326277978049639, 0.06099864905282187, 0.058388385126958244, -0.13565032293375295, -0.18471589034948593, 0.014615124873578167, 0.1566294029307289, 0.0076604936695777075, -0.029201119947127808, 0.06738888861563726, -0.08955288743480849, -0.0694521061765651, 0.35183951191795176, -0.12152720791980243, -0.25321114903841263, 0.058056640152174696, -0.17466886960065517, -0.04205012711463496, 0.035731380280011736, 0.19670602841637072, 0.16281333532279882, -0.10388703687259784, 0.17441076150116247, -0.07862936126259275, 0.07068621699149027, 0.08390177745754138, 0.021236144555493806, 0.15159336104989052, 0.06431129018370157, 0.16421882380755284, 0.23905825051359642, -0.03142721312216077, -0.07129814533086923, -0.36325342322771365, -0.18544869249065718, -0.27666466377484494, 0.0735622310342315, -0.1110126031562686, -0.27101548699041206, 0.4205221807918487, 0.09018004160278882, 0.3166265659726774, 0.09622305244780503, 0.3042184448777101, 0.253234486734399, 0.038180773838972434, 0.053178921389656186, 0.21749128255611047, 0.1974861626692403, 0.06309830621840098, -0.20039476812458956, -0.0484936006892568, 0.1498086186698996] |
1,802.06448 | Particle resuspension from complex surfaces: current knowledge and
limitations | This review explores particle resuspension from surfaces due to fluid flows.
The objective of this review is to provide a general framework and terminology
for particle resuspension while highlighting the future developments needed to
deepen our understanding of these phenomena. For that purpose, the manuscript
is organized with respect to three mechanisms identified in particle
resuspension, namely: the incipient motion of particles (i.e. how particles are
set in motion), their migration on the surface (i.e. rolling or sliding motion)
and their re-entrainment in the flow (i.e. their motion in the near-wall region
after detachment). Recent measurements and simulations of particle resuspension
are used to underline our current understanding of each mechanism for particle
resuspension. These selected examples also highlight the limitations in the
present knowledge of particle resuspension, while providing insights into
future developments that need to be addressed. In particular, the paper
addresses the issue of adhesion forces between complex surfaces - where more
detailed characterizations of adhesion force distributions are needed - and the
issue of particle sliding/rolling motion on the surface - which can lead to
particles halting/being trapped in regions with high adhesion forces.
| physics.flu-dyn cond-mat.soft | this review explores particle resuspension from surfaces due to fluid flows the objective of this review is to provide a general framework and terminology for particle resuspension while highlighting the future developments needed to deepen our understanding of these phenomena for that purpose the manuscript is organized with respect to three mechanisms identified in particle resuspension namely the incipient motion of particles ie how particles are set in motion their migration on the surface ie rolling or sliding motion and their reentrainment in the flow ie their motion in the nearwall region after detachment recent measurements and simulations of particle resuspension are used to underline our current understanding of each mechanism for particle resuspension these selected examples also highlight the limitations in the present knowledge of particle resuspension while providing insights into future developments that need to be addressed in particular the paper addresses the issue of adhesion forces between complex surfaces where more detailed characterizations of adhesion force distributions are needed and the issue of particle slidingrolling motion on the surface which can lead to particles haltingbeing trapped in regions with high adhesion forces | [['this', 'review', 'explores', 'particle', 'resuspension', 'from', 'surfaces', 'due', 'to', 'fluid', 'flows', 'the', 'objective', 'of', 'this', 'review', 'is', 'to', 'provide', 'a', 'general', 'framework', 'and', 'terminology', 'for', 'particle', 'resuspension', 'while', 'highlighting', 'the', 'future', 'developments', 'needed', 'to', 'deepen', 'our', 'understanding', 'of', 'these', 'phenomena', 'for', 'that', 'purpose', 'the', 'manuscript', 'is', 'organized', 'with', 'respect', 'to', 'three', 'mechanisms', 'identified', 'in', 'particle', 'resuspension', 'namely', 'the', 'incipient', 'motion', 'of', 'particles', 'ie', 'how', 'particles', 'are', 'set', 'in', 'motion', 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1,802.06449 | Toric topology of the complex Grassmann manifolds | The family of the complex Grassmann manifolds $G_{n,k}$ with a canonical
action of the torus $T^n=\mathbb{T}^{n}$ and the analogue of the moment map
$\mu : G_{n,k}\to \Delta _{n,k}$ for the hypersimplex $\Delta _{n,k}$, is well
known. In this paper we study the structure of the orbit space $G_{n,k}/T^n$ by
developing the methods of toric geometry and toric topology. We use a
subdivision of $G_{n,k}$ into the strata $W_{\sigma}$ and determine all regular
and singular points of the moment map $\mu$, introduce the notion of the
admissible polytopes $P_\sigma$ such that $\mu (W_{\sigma}) =
\stackrel{\circ}{P_{\sigma}}$ and the notion of the spaces of parameters
$F_{\sigma}$, which together describe $W_{\sigma}/T^{n}$ as the product
$\stackrel{\circ}{P_{\sigma}} \times F_{\sigma}$. To find the appropriate
topology for the set $\cup _{\sigma} \stackrel{\circ}{P_{\sigma}} \times
F_{\sigma}$ we introduce the notions of the universal space of parameters
$\tilde{\mathcal{F}}$ and the virtual spaces of parameters
$\tilde{F}_{\sigma}\subset \tilde{\mathcal{F}}$ such that there exist the
projections $\tilde{F}_{\sigma}\to F_{\sigma}$. Hence, we propose a method for
the description of the orbit space $G_{n,k}/T^n$. Earlier we proved that the
orbit space $G_{4,2}/T^4$, defined by the canonical $T^4$-action of complexity
$1$, is homeomorphic to $\partial \Delta _{4,2}\ast \mathbb{C} P^1$. We prove
here that the orbit space $G_{5,2}/T^5$, defined by the canonical $T^5$-action
of complexity $2$, is homotopy equivalent to the space obtained by attaching
the disc $D^8$ to the space $\Sigma ^{4}\mathbb{R} P^2$ by the generator of the
group $\pi _{7}(\Sigma ^{4}\mathbb{R} P^2)=\mathbb{Z} _{4}$. In particular,
$(G_{5,2}/G_{4,2})/T^5$ is homotopy equivalent to $\partial \Delta _{5,2}\ast
\mathbb{C} P^2$. The methods and the results of this paper are fundaments for
our theory of $(2l,q)$-manifolds.
| math.AT | the family of the complex grassmann manifolds g_nk with a canonical action of the torus tnmathbbtn and the analogue of the moment map mu g_nkto delta _nk for the hypersimplex delta _nk is well known in this paper we study the structure of the orbit space g_nktn by developing the methods of toric geometry and toric topology we use a subdivision of g_nk into the strata w_sigma and determine all regular and singular points of the moment map mu introduce the notion of the admissible polytopes p_sigma such that mu w_sigma stackrelcircp_sigma and the notion of the spaces of parameters f_sigma which together describe w_sigmatn as the product stackrelcircp_sigma times f_sigma to find the appropriate topology for the set cup _sigma stackrelcircp_sigma times f_sigma we introduce the notions of the universal space of parameters tildemathcalf and the virtual spaces of parameters tildef_sigmasubset tildemathcalf such that there exist the projections tildef_sigmato f_sigma hence we propose a method for the description of the orbit space g_nktn earlier we proved that the orbit space g_42t4 defined by the canonical t4action of complexity 1 is homeomorphic to partial delta _42ast mathbbc p1 we prove here that the orbit space g_52t5 defined by the canonical t5action of complexity 2 is homotopy equivalent to the space obtained by attaching the disc d8 to the space sigma 4mathbbr p2 by the generator of the group pi _7sigma 4mathbbr p2mathbbz _4 in particular g_52g_42t5 is homotopy equivalent to partial delta _52ast mathbbc p2 the methods and the results of this paper are fundaments for our theory of 2lqmanifolds | [['the', 'family', 'of', 'the', 'complex', 'grassmann', 'manifolds', 'g_nk', 'with', 'a', 'canonical', 'action', 'of', 'the', 'torus', 'tnmathbbtn', 'and', 'the', 'analogue', 'of', 'the', 'moment', 'map', 'mu', 'g_nkto', 'delta', '_nk', 'for', 'the', 'hypersimplex', 'delta', '_nk', 'is', 'well', 'known', 'in', 'this', 'paper', 'we', 'study', 'the', 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1,802.0645 | Reducing Initial Cell-search Latency in mmWave Networks | Millimeter-wave (mmWave) networks rely on directional transmissions, in both
control plane and data plane, to overcome severe path-loss. Nevertheless, the
use of narrow beams complicates the initial cell-search procedure where we lack
sufficient information for beamforming. In this paper, we investigate the
feasibility of random beamforming for cell-search. We develop a stochastic
geometry framework to analyze the performance in terms of failure probability
and expected latency of cell-search. Meanwhile, we compare our results with the
naive, but heavily used, exhaustive search scheme. Numerical results show that,
for a given discovery failure probability, random beamforming can substantially
reduce the latency of exhaustive search, especially in dense networks. Our work
demonstrates that developing complex cell-discovery algorithms may be
unnecessary in dense mmWave networks and thus shed new lights on mmWave system
design.
| cs.IT cs.NI math.IT | millimeterwave mmwave networks rely on directional transmissions in both control plane and data plane to overcome severe pathloss nevertheless the use of narrow beams complicates the initial cellsearch procedure where we lack sufficient information for beamforming in this paper we investigate the feasibility of random beamforming for cellsearch we develop a stochastic geometry framework to analyze the performance in terms of failure probability and expected latency of cellsearch meanwhile we compare our results with the naive but heavily used exhaustive search scheme numerical results show that for a given discovery failure probability random beamforming can substantially reduce the latency of exhaustive search especially in dense networks our work demonstrates that developing complex celldiscovery algorithms may be unnecessary in dense mmwave networks and thus shed new lights on mmwave system design | [['millimeterwave', 'mmwave', 'networks', 'rely', 'on', 'directional', 'transmissions', 'in', 'both', 'control', 'plane', 'and', 'data', 'plane', 'to', 'overcome', 'severe', 'pathloss', 'nevertheless', 'the', 'use', 'of', 'narrow', 'beams', 'complicates', 'the', 'initial', 'cellsearch', 'procedure', 'where', 'we', 'lack', 'sufficient', 'information', 'for', 'beamforming', 'in', 'this', 'paper', 'we', 'investigate', 'the', 'feasibility', 'of', 'random', 'beamforming', 'for', 'cellsearch', 'we', 'develop', 'a', 'stochastic', 'geometry', 'framework', 'to', 'analyze', 'the', 'performance', 'in', 'terms', 'of', 'failure', 'probability', 'and', 'expected', 'latency', 'of', 'cellsearch', 'meanwhile', 'we', 'compare', 'our', 'results', 'with', 'the', 'naive', 'but', 'heavily', 'used', 'exhaustive', 'search', 'scheme', 'numerical', 'results', 'show', 'that', 'for', 'a', 'given', 'discovery', 'failure', 'probability', 'random', 'beamforming', 'can', 'substantially', 'reduce', 'the', 'latency', 'of', 'exhaustive', 'search', 'especially', 'in', 'dense', 'networks', 'our', 'work', 'demonstrates', 'that', 'developing', 'complex', 'celldiscovery', 'algorithms', 'may', 'be', 'unnecessary', 'in', 'dense', 'mmwave', 'networks', 'and', 'thus', 'shed', 'new', 'lights', 'on', 'mmwave', 'system', 'design']] | [-0.20695125833406408, 0.016970097592692506, -0.026904808624481507, 0.045345387615573905, -0.10873924158044275, -0.1584357280110897, 0.1245944217802206, 0.4148027055081009, -0.21468032478325993, -0.25760646491102124, 0.11280082299305458, -0.19169053685844176, -0.24317334159169085, 0.18827255817072452, -0.1203637477732444, 0.10358197308441465, 0.1083942438338616, -0.05563247457413768, -0.057988497955623525, -0.24944829662843038, 0.28119612542926803, 0.11096737409270434, 0.373793118517817, 0.04743530104918651, 0.04392089762918059, 0.028644178241361364, -0.0781491119071639, -0.02043222240713793, -0.09285974359311716, 0.13119046211553118, 0.3080471610549346, 0.20150280939487292, 0.27249536863997464, -0.4621028884119073, -0.26291442528193776, 0.12374532564593725, 0.1867487829234072, 0.08982795291686749, -0.06922956854790853, -0.28899672466452964, 0.14104340908789012, -0.16762002518350014, -0.08964732352146958, -0.06723772752452498, -0.08655056462428251, 0.07167445635062086, -0.3077632573527075, 0.016089345655194664, 0.017350107187751766, 0.019894971136841202, -0.011412498669323418, -0.11174832987183951, 0.05371631348375664, 0.09138605890564563, 0.0165727901526965, 0.011694863296922499, 0.07839339252474696, -0.1321838544776284, -0.1238131349863008, 0.3884125353349734, 0.006952853494345448, -0.24287051686388983, 0.18656271453874634, -0.10238536713327202, -0.1505250594860246, 0.16339515085294193, 0.3119753733522786, 0.08030429824666921, -0.1637022212574569, 0.016693780933734203, 0.009806288621034618, 0.15713662289212957, 0.05599389819955352, 0.10085602578988602, 0.14960732560987447, 0.21880238808604868, 0.13463498633571488, 0.12351274460666026, -0.13773978410952892, -0.08392099635278474, -0.22046262775944878, -0.12235610270439538, -0.1980387256101727, 0.01893385097947578, -0.10186479429774395, -0.10581747478581677, 0.3527640229373457, 0.2391336036046476, 0.1647966506298949, 0.12290409347403419, 0.36611367207626966, 0.07710069574031242, 0.023193325049626505, 0.10290846196833507, 0.2288053645012366, 0.07557674114368568, 0.13873311833211388, -0.19551538596247403, 0.07113279596462037, -0.029608233732553994] |
1,802.06451 | D-Sempre: Learning Deep Semantic-Preserving Embeddings for User
interests-Social Contents Modeling | Exponential growth of social media consumption demands effective user
interests-social contents modeling for more personalized recommendation and
social media summarization. However, due to the heterogeneous nature of social
contents, traditional approaches lack the ability of capturing the hidden
semantic correlations across these multi-modal data, which leads to semantic
gaps between social content understanding and user interests. To effectively
bridge the semantic gaps, we propose a novel deep learning framework for user
interests-social contents modeling. We first mine and parse data, i.e. textual
content, visual content, social context and social relation, from heterogeneous
social media feeds. Then, we design a two-branch network to map the social
contents and users into a same latent space. Particularly, the network is
trained by a large margin objective that combines a cross-instance distance
constraint with a within-instance semantic-preserving constraint in an end-to-
end manner. At last, a Deep Semantic-Preserving Embedding (D-Sempre) is
learned, and the ranking results can be given by calculating distances between
social contents and users. To demonstrate the effectiveness of D-Sempre in user
interests-social contents modeling, we construct a Twitter dataset and conduct
extensive experiments on it. As a result, D-Sempre effectively integrates the
multi-modal data from heterogeneous social media feeds and captures the hidden
semantic correlations between users' interests and social contents.
| cs.SI | exponential growth of social media consumption demands effective user interestssocial contents modeling for more personalized recommendation and social media summarization however due to the heterogeneous nature of social contents traditional approaches lack the ability of capturing the hidden semantic correlations across these multimodal data which leads to semantic gaps between social content understanding and user interests to effectively bridge the semantic gaps we propose a novel deep learning framework for user interestssocial contents modeling we first mine and parse data ie textual content visual content social context and social relation from heterogeneous social media feeds then we design a twobranch network to map the social contents and users into a same latent space particularly the network is trained by a large margin objective that combines a crossinstance distance constraint with a withininstance semanticpreserving constraint in an endto end manner at last a deep semanticpreserving embedding dsempre is learned and the ranking results can be given by calculating distances between social contents and users to demonstrate the effectiveness of dsempre in user interestssocial contents modeling we construct a twitter dataset and conduct extensive experiments on it as a result dsempre effectively integrates the multimodal data from heterogeneous social media feeds and captures the hidden semantic correlations between users interests and social contents | [['exponential', 'growth', 'of', 'social', 'media', 'consumption', 'demands', 'effective', 'user', 'interestssocial', 'contents', 'modeling', 'for', 'more', 'personalized', 'recommendation', 'and', 'social', 'media', 'summarization', 'however', 'due', 'to', 'the', 'heterogeneous', 'nature', 'of', 'social', 'contents', 'traditional', 'approaches', 'lack', 'the', 'ability', 'of', 'capturing', 'the', 'hidden', 'semantic', 'correlations', 'across', 'these', 'multimodal', 'data', 'which', 'leads', 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1,802.06452 | Direct linearisation of the discrete-time two-dimensional Toda lattices | The discrete-time two-dimensional Toda lattice of $A_\infty$-type is studied
within the direct linearisation framework, which allows us to deal with several
nonlinear equations in this class simultaneously and to construct more general
solutions of these equations. The periodic reductions of this model are also
considered, giving rise to the discrete-time two-dimensional Toda lattices of
$A_{r-1}^{(1)}$-type for $r\geq 2$ (which amount to the negative flows of
members in the discrete Gel'fand--Dikii hierarchy) and their integrability
properties.
| nlin.SI math-ph math.MP | the discretetime twodimensional toda lattice of a_inftytype is studied within the direct linearisation framework which allows us to deal with several nonlinear equations in this class simultaneously and to construct more general solutions of these equations the periodic reductions of this model are also considered giving rise to the discretetime twodimensional toda lattices of a_r11type for rgeq 2 which amount to the negative flows of members in the discrete gelfanddikii hierarchy and their integrability properties | [['the', 'discretetime', 'twodimensional', 'toda', 'lattice', 'of', 'a_inftytype', 'is', 'studied', 'within', 'the', 'direct', 'linearisation', 'framework', 'which', 'allows', 'us', 'to', 'deal', 'with', 'several', 'nonlinear', 'equations', 'in', 'this', 'class', 'simultaneously', 'and', 'to', 'construct', 'more', 'general', 'solutions', 'of', 'these', 'equations', 'the', 'periodic', 'reductions', 'of', 'this', 'model', 'are', 'also', 'considered', 'giving', 'rise', 'to', 'the', 'discretetime', 'twodimensional', 'toda', 'lattices', 'of', 'a_r11type', 'for', 'rgeq', '2', 'which', 'amount', 'to', 'the', 'negative', 'flows', 'of', 'members', 'in', 'the', 'discrete', 'gelfanddikii', 'hierarchy', 'and', 'their', 'integrability', 'properties']] | [-0.12268884427612647, 0.08306224032531719, -0.03033555977398882, 0.06664260567039663, -0.10538123903569539, -0.17489384307299513, -0.02171043850830756, 0.3210089118094058, -0.33083673903869615, -0.24811024491901737, 0.13078781732710432, -0.22613839118295456, -0.14745785367700295, 0.17548895088288732, -0.03387660544831306, 0.09660135603484672, 0.017027898188176994, -0.002708519992223513, -0.11111504624194994, -0.3057534613243833, 0.30208946964577643, -0.00541014681771599, 0.23439577813386112, 0.0004973201760770502, 0.1127116110402386, -0.018436686160999374, -0.009768061006341028, 0.0026842024479363418, -0.17557822380134697, 0.15414829342626035, 0.23797311664030357, 0.015846610742595954, 0.23697438518944625, -0.41406898943052906, -0.2257460790333917, 0.1160778832697385, 0.12928332195843797, 0.1497737717015568, -0.0018356050582165277, -0.29810455428889476, 0.09100668531892872, -0.15993228779926366, -0.19792141117205894, -0.06472631517445317, 0.016609125443407008, 0.049462252183238395, -0.26854989337860735, 0.08645549892547, 0.09335665081980059, 0.03182468166876886, -0.10235606844464594, -0.04277059635795603, -0.04594828257009991, 0.08779197205109773, 0.02223017646433987, -0.04619677889639059, -0.030540559642218256, -0.1140131809012461, -0.12192207103834261, 0.4240938952016468, -0.02889057808882884, -0.28531034531172467, 0.21164398106771545, -0.11145670969995695, -0.16304208853634428, 0.157324288839575, 0.2113758867191201, 0.09487627887141865, -0.17350974020774704, 0.0919400942873688, -0.10603023750229261, 0.10794584440520487, 0.049802356887281546, 0.02461987838064119, 0.17852048015668737, 0.11806778312736266, 0.10199521973452254, 0.15818483984991405, 0.008030956785660237, -0.2075515875743853, -0.2853700621808703, -0.13332870705179065, -0.06701864407876053, 0.10300666341759465, -0.07884373226772516, -0.20828098646440618, 0.4263918056479982, 0.12947338792504082, 0.15361796486871065, 0.10030243376181838, 0.15268037925675712, 0.16284700749895056, 0.06256773609139428, 0.035398389952181766, 0.16332778044837853, 0.2067605202130319, 0.11079262173105334, -0.22577281639521085, -0.06355174467898905, 0.15675976702540712] |
1,802.06453 | Rescaling nonsmooth optimization using BFGS and Shor updates | The BFGS quasi-Newton methodology, popular for smooth minimization, has also
proved surprisingly effective in nonsmooth optimization. Through a variety of
simple examples and computational experiments, we explore how the BFGS matrix
update improves the local metric associated with a convex function even in the
absence of smoothness and without using a line search. We compare the behavior
of the BFGS and Shor r-algorithm updates.
| math.OC | the bfgs quasinewton methodology popular for smooth minimization has also proved surprisingly effective in nonsmooth optimization through a variety of simple examples and computational experiments we explore how the bfgs matrix update improves the local metric associated with a convex function even in the absence of smoothness and without using a line search we compare the behavior of the bfgs and shor ralgorithm updates | [['the', 'bfgs', 'quasinewton', 'methodology', 'popular', 'for', 'smooth', 'minimization', 'has', 'also', 'proved', 'surprisingly', 'effective', 'in', 'nonsmooth', 'optimization', 'through', 'a', 'variety', 'of', 'simple', 'examples', 'and', 'computational', 'experiments', 'we', 'explore', 'how', 'the', 'bfgs', 'matrix', 'update', 'improves', 'the', 'local', 'metric', 'associated', 'with', 'a', 'convex', 'function', 'even', 'in', 'the', 'absence', 'of', 'smoothness', 'and', 'without', 'using', 'a', 'line', 'search', 'we', 'compare', 'the', 'behavior', 'of', 'the', 'bfgs', 'and', 'shor', 'ralgorithm', 'updates']] | [-0.06797985173761845, -0.028645387603088268, -0.08844648005943449, 0.08322843059986121, -0.11093580379845604, -0.19552044985106304, 0.07589742369831555, 0.41676493018629057, -0.2917720621954354, -0.2974430960566101, 0.1337430790576729, -0.22920305777104602, -0.22323573694106133, 0.18172014947788465, -0.10228840968320294, 0.09924541798139376, 0.08245686054347999, -0.002443539703057872, -0.18446394851771258, -0.30188815062496044, 0.27626047283411026, 0.04916137788030836, 0.2190109138923978, 0.047512780054516736, 0.13035218076159558, 0.04348301167585074, -0.039429938139778284, 0.05152971822295397, -0.07490267575393239, 0.11675425373860412, 0.2166564639561647, 0.20233952665021496, 0.34372392184441053, -0.42001617782645756, -0.1930176177106443, 0.16102942482509192, 0.12572316067027195, 0.08242522339735713, -0.0995568588767792, -0.2447064800690564, 0.1053963295287556, -0.1367092142029414, -0.08517134331521534, -0.1779028761961926, -0.05213367995170374, 0.07628655143540412, -0.2920823783007643, 0.05097914338278185, 0.03856752850558786, 0.047719340727088, -0.05501983897568333, -0.14272378885468084, 0.032690719169165404, -0.0003580569200927303, 0.03319313147267888, 0.05657769993154539, 0.1557047719076749, -0.1137258859558238, -0.12994636795557443, 0.33772538756094284, -0.11198023125706684, -0.26156985466664157, 0.1759719598358349, -0.022064931768303115, -0.11547037693376225, 0.12081624151370118, 0.1861487879373488, 0.1939321199491147, -0.11051800486350817, 0.16722808295716754, -0.04264253824727521, 0.10361926246153576, 0.03390472495765795, -0.04237854761433684, 0.025357666769109312, 0.16169642728738606, 0.15393016103004653, 0.17858600036965477, -0.0512874419884091, -0.13665285218684448, -0.2694650718291837, -0.1498304112622189, -0.21432268414794217, -0.01312422700640228, -0.17810039819400234, -0.15601774382715425, 0.4186348124067225, 0.11385753400446404, 0.20575743832344573, 0.12801490948786812, 0.3278782735209143, 0.08441047417739081, 0.032714667094368786, 0.13286417153560454, 0.1846191766006606, 0.1110492502302227, 0.11711213228455375, -0.27708834648087977, 0.10640518335507267, 0.1247014779715784] |
1,802.06454 | DA-GAN: Instance-level Image Translation by Deep Attention Generative
Adversarial Networks (with Supplementary Materials) | Unsupervised image translation, which aims in translating two independent
sets of images, is challenging in discovering the correct correspondences
without paired data. Existing works build upon Generative Adversarial Network
(GAN) such that the distribution of the translated images are indistinguishable
from the distribution of the target set. However, such set-level constraints
cannot learn the instance-level correspondences (e.g. aligned semantic parts in
object configuration task). This limitation often results in false positives
(e.g. geometric or semantic artifacts), and further leads to mode collapse
problem. To address the above issues, we propose a novel framework for
instance-level image translation by Deep Attention GAN (DA-GAN). Such a design
enables DA-GAN to decompose the task of translating samples from two sets into
translating instances in a highly-structured latent space. Specifically, we
jointly learn a deep attention encoder, and the instancelevel correspondences
could be consequently discovered through attending on the learned instance
pairs. Therefore, the constraints could be exploited on both set-level and
instance-level. Comparisons against several state-ofthe- arts demonstrate the
superiority of our approach, and the broad application capability, e.g, pose
morphing, data augmentation, etc., pushes the margin of domain translation
problem.
| cs.CV | unsupervised image translation which aims in translating two independent sets of images is challenging in discovering the correct correspondences without paired data existing works build upon generative adversarial network gan such that the distribution of the translated images are indistinguishable from the distribution of the target set however such setlevel constraints cannot learn the instancelevel correspondences eg aligned semantic parts in object configuration task this limitation often results in false positives eg geometric or semantic artifacts and further leads to mode collapse problem to address the above issues we propose a novel framework for instancelevel image translation by deep attention gan dagan such a design enables dagan to decompose the task of translating samples from two sets into translating instances in a highlystructured latent space specifically we jointly learn a deep attention encoder and the instancelevel correspondences could be consequently discovered through attending on the learned instance pairs therefore the constraints could be exploited on both setlevel and instancelevel comparisons against several stateofthe arts demonstrate the superiority of our approach and the broad application capability eg pose morphing data augmentation etc pushes the margin of domain translation problem | [['unsupervised', 'image', 'translation', 'which', 'aims', 'in', 'translating', 'two', 'independent', 'sets', 'of', 'images', 'is', 'challenging', 'in', 'discovering', 'the', 'correct', 'correspondences', 'without', 'paired', 'data', 'existing', 'works', 'build', 'upon', 'generative', 'adversarial', 'network', 'gan', 'such', 'that', 'the', 'distribution', 'of', 'the', 'translated', 'images', 'are', 'indistinguishable', 'from', 'the', 'distribution', 'of', 'the', 'target', 'set', 'however', 'such', 'setlevel', 'constraints', 'can', 'not', 'learn', 'the', 'instancelevel', 'correspondences', 'eg', 'aligned', 'semantic', 'parts', 'in', 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1,802.06455 | Bayesian Uncertainty Estimation for Batch Normalized Deep Networks | We show that training a deep network using batch normalization is equivalent
to approximate inference in Bayesian models. We further demonstrate that this
finding allows us to make meaningful estimates of the model uncertainty using
conventional architectures, without modifications to the network or the
training procedure. Our approach is thoroughly validated by measuring the
quality of uncertainty in a series of empirical experiments on different tasks.
It outperforms baselines with strong statistical significance, and displays
competitive performance with recent Bayesian approaches.
| stat.ML | we show that training a deep network using batch normalization is equivalent to approximate inference in bayesian models we further demonstrate that this finding allows us to make meaningful estimates of the model uncertainty using conventional architectures without modifications to the network or the training procedure our approach is thoroughly validated by measuring the quality of uncertainty in a series of empirical experiments on different tasks it outperforms baselines with strong statistical significance and displays competitive performance with recent bayesian approaches | [['we', 'show', 'that', 'training', 'a', 'deep', 'network', 'using', 'batch', 'normalization', 'is', 'equivalent', 'to', 'approximate', 'inference', 'in', 'bayesian', 'models', 'we', 'further', 'demonstrate', 'that', 'this', 'finding', 'allows', 'us', 'to', 'make', 'meaningful', 'estimates', 'of', 'the', 'model', 'uncertainty', 'using', 'conventional', 'architectures', 'without', 'modifications', 'to', 'the', 'network', 'or', 'the', 'training', 'procedure', 'our', 'approach', 'is', 'thoroughly', 'validated', 'by', 'measuring', 'the', 'quality', 'of', 'uncertainty', 'in', 'a', 'series', 'of', 'empirical', 'experiments', 'on', 'different', 'tasks', 'it', 'outperforms', 'baselines', 'with', 'strong', 'statistical', 'significance', 'and', 'displays', 'competitive', 'performance', 'with', 'recent', 'bayesian', 'approaches']] | [-0.02334703872969121, -0.0684532521761103, -0.11355102829919714, 0.07957004915698673, -0.10573458886003972, -0.16514773095417537, 0.09702890081170165, 0.4845896387173806, -0.23831163112212111, -0.3591052143903518, 0.044819904413695134, -0.24459110693391672, -0.16742761610478255, 0.2270667394220737, -0.09752920762647266, 0.13281410656593465, 0.18125201055757056, 0.0034219314585681314, -0.12699106529952936, -0.2907229517414062, 0.28526985499272006, 0.0841895306542556, 0.3812408663539423, 0.007069812317229348, 0.12961758305836055, -0.044552816014828876, -0.04120090956092571, 0.05187895942628844, -0.07672638952660943, 0.19123474119323086, 0.23780054545784002, 0.216356730243812, 0.32683874714981626, -0.3907958594852208, -0.24670684684274924, 0.10452496440920198, 0.11796586246540149, 0.11306115643431743, 0.023143914434771387, -0.3184567297561623, 0.07421594915910118, -0.1756597178539744, 0.009671878474936993, -0.1889026003694277, -0.05848001010922922, -0.005566320370560811, -0.3459455272251809, 0.10713160556833042, 0.042150388971936924, 0.04542861792638346, -0.00732089526862205, -0.14066732613323832, 0.05513473998835701, 0.1203668716745911, 0.06758817080494568, 0.012729439102573159, 0.1165880119703986, -0.13282361848820232, -0.16603884798831042, 0.32697534863549615, -0.10094207194116381, -0.21126461863793708, 0.19086074630189456, -0.03356700227883311, -0.18742591950950432, 0.07922218038045147, 0.1907273867615947, 0.07931043883716618, -0.15756907522172472, 0.025584730433938267, -0.02493538732646194, 0.20170439849895092, 0.006221307910127956, -0.051019617459840245, 0.14831107852831024, 0.3077971259660927, 0.014378134000264569, 0.15160676787526886, -0.1336692733672896, -0.09862176505963743, -0.2233082893545981, -0.08821584793658536, -0.16258368521560856, -0.012908619061762031, -0.12673044492139188, -0.12475270234669249, 0.37595998950555554, 0.29286003470374844, 0.19679509000392792, 0.15214674265043418, 0.36829230690627923, 0.056113314373637146, 0.10203232834069634, 0.07691606849627454, 0.2626242561058866, 0.04787672234319702, 0.06101398359133321, -0.1769873096814586, 0.10203992194110918, -0.0027631663567857976] |
1,802.06456 | Optimal allocation of attentional resource to multiple items with
unequal relevance | In natural perception, different items (objects) in a scene are rarely
equally relevant to the observer. The brain improves performance by directing
attention to the most relevant items, for example the ones most likely to be
probed. For a general set of probing probabilities, it is not known how
attentional resources should be allocated to maximize performance. Here, we
investigate the optimal strategy for allocating a fixed resource budget E among
N items when on each trial, only one item gets probed. We develop an efficient
algorithm that, for any concave utility function, reduces the N-dimensional
problem to a set of N one-dimensional problems that the brain could plausibly
solve. We find that the intuitive strategy of allocating resource in proportion
to the probing probabilities is in general not optimal. In particular, in some
tasks, if resource is low, the optimal strategy involves allocating zero
resource to items with a nonzero probability of being probed. Our work opens
the door to normatively guided studies of attentional allocation.
| q-bio.NC | in natural perception different items objects in a scene are rarely equally relevant to the observer the brain improves performance by directing attention to the most relevant items for example the ones most likely to be probed for a general set of probing probabilities it is not known how attentional resources should be allocated to maximize performance here we investigate the optimal strategy for allocating a fixed resource budget e among n items when on each trial only one item gets probed we develop an efficient algorithm that for any concave utility function reduces the ndimensional problem to a set of n onedimensional problems that the brain could plausibly solve we find that the intuitive strategy of allocating resource in proportion to the probing probabilities is in general not optimal in particular in some tasks if resource is low the optimal strategy involves allocating zero resource to items with a nonzero probability of being probed our work opens the door to normatively guided studies of attentional allocation | [['in', 'natural', 'perception', 'different', 'items', 'objects', 'in', 'a', 'scene', 'are', 'rarely', 'equally', 'relevant', 'to', 'the', 'observer', 'the', 'brain', 'improves', 'performance', 'by', 'directing', 'attention', 'to', 'the', 'most', 'relevant', 'items', 'for', 'example', 'the', 'ones', 'most', 'likely', 'to', 'be', 'probed', 'for', 'a', 'general', 'set', 'of', 'probing', 'probabilities', 'it', 'is', 'not', 'known', 'how', 'attentional', 'resources', 'should', 'be', 'allocated', 'to', 'maximize', 'performance', 'here', 'we', 'investigate', 'the', 'optimal', 'strategy', 'for', 'allocating', 'a', 'fixed', 'resource', 'budget', 'e', 'among', 'n', 'items', 'when', 'on', 'each', 'trial', 'only', 'one', 'item', 'gets', 'probed', 'we', 'develop', 'an', 'efficient', 'algorithm', 'that', 'for', 'any', 'concave', 'utility', 'function', 'reduces', 'the', 'ndimensional', 'problem', 'to', 'a', 'set', 'of', 'n', 'onedimensional', 'problems', 'that', 'the', 'brain', 'could', 'plausibly', 'solve', 'we', 'find', 'that', 'the', 'intuitive', 'strategy', 'of', 'allocating', 'resource', 'in', 'proportion', 'to', 'the', 'probing', 'probabilities', 'is', 'in', 'general', 'not', 'optimal', 'in', 'particular', 'in', 'some', 'tasks', 'if', 'resource', 'is', 'low', 'the', 'optimal', 'strategy', 'involves', 'allocating', 'zero', 'resource', 'to', 'items', 'with', 'a', 'nonzero', 'probability', 'of', 'being', 'probed', 'our', 'work', 'opens', 'the', 'door', 'to', 'normatively', 'guided', 'studies', 'of', 'attentional', 'allocation']] | [-0.09516723674839128, 0.10674924339095625, -0.04212280301499866, 0.08971701857904363, -0.15212225019206813, -0.21951076072016118, 0.12490074378842611, 0.4193723128465824, -0.2745256073212441, -0.30392715250682867, 0.049030281198431475, -0.25673317521305833, -0.13694051664579146, 0.17955430526660007, -0.12908922767679312, 0.04223666017077596, 0.039337482771133546, 0.05534186368127783, 0.027242300810270056, -0.31477873223348557, 0.28301074928018505, 0.0824737864376386, 0.29088988267359306, 0.024552866847192992, 0.06952154239037348, 0.006807879850123368, -0.025124744534796427, 0.0328511194978467, -0.10549635490646389, 0.1311467877794113, 0.3891376442203443, 0.21004754990132937, 0.384115213054249, -0.38869441422204415, -0.19486163461770484, 0.15423124931086257, 0.15214735819138364, 0.09038541216157868, -0.021840674761532175, -0.22911507397064726, 0.10358643201686506, -0.14511450683463833, -0.06621163803247546, -0.04874143235400754, 0.03130681281295901, -0.030382684808402897, -0.3305636713459731, -0.004539113186444797, -0.0035486681342214166, -0.02404745539906853, -0.08679109322141387, -0.10984956960941102, 0.025175029577821226, 0.1748628169153524, 0.040222248398492526, 0.021500251175066133, 0.16977679941100543, -0.14841780656792536, -0.14025275281234506, 0.41661960695741956, 0.012861162633216846, -0.24764085008935657, 0.14250214929374572, -0.1246919693191073, -0.14751353992210578, 0.11308383542352808, 0.17643665601806102, 0.1377122974508403, -0.16430943204038762, 0.02701253920091556, -0.07984464380365217, 0.1586310742916135, 0.054741467561148956, 0.07321764529378762, 0.20215751858383507, 0.212311923049368, 0.13495289875629418, 0.15621283457302182, -0.020983989555444456, -0.07415623281675274, -0.2366831117477979, -0.14705792895356518, -0.21926867675585504, 0.028596007180975994, -0.07163318900759527, -0.0791983102458044, 0.3746542480389426, 0.1691797383709582, 0.20075148498516776, 0.09724324987922421, 0.30275878755788427, 0.09366634392411682, 0.05464959708300369, 0.10957170820454816, 0.15989054118030047, -0.018391541261114402, 0.05264892969364133, -0.21514795580878854, 0.10815922748353221, 0.017985064631138376] |
1,802.06457 | Circles and crossing planar compact convex sets | Let $K_0$ be a compact convex subset of the plane $\mathbb R^2$, and assume
that whenever $K_1\subseteq \mathbb R^2$ is congruent to $K_0$, then $K_0$ and
$K_1$ are not crossing in a natural sense due to L. Fejes-T\'oth. A theorem of
L. Fejes-T\'oth from 1967 states that the assumption above holds for $K_0$ if
and only if $K_0$ is a disk. In a paper appeared in 2017, the present author
introduced a new concept of crossing, and proved that L. Fejes-T\'oth's theorem
remains true if the old concept is replaced by the new one. Our purpose is to
describe the hierarchy among several variants of the new concepts and the old
concept of crossing. In particular, we prove that each variant of the new
concept of crossing is more restrictive then the old one. Therefore, L.
Fejes-T\'oth's theorem from 1967 becomes an immediate consequence of the 2017
characterization of circles but not conversely. Finally, a mini-survey shows
that this purely geometric paper has precursor in combinatorics and, mainly, in
lattice theory.
| math.MG math.CO | let k_0 be a compact convex subset of the plane mathbb r2 and assume that whenever k_1subseteq mathbb r2 is congruent to k_0 then k_0 and k_1 are not crossing in a natural sense due to l fejestoth a theorem of l fejestoth from 1967 states that the assumption above holds for k_0 if and only if k_0 is a disk in a paper appeared in 2017 the present author introduced a new concept of crossing and proved that l fejestoths theorem remains true if the old concept is replaced by the new one our purpose is to describe the hierarchy among several variants of the new concepts and the old concept of crossing in particular we prove that each variant of the new concept of crossing is more restrictive then the old one therefore l fejestoths theorem from 1967 becomes an immediate consequence of the 2017 characterization of circles but not conversely finally a minisurvey shows that this purely geometric paper has precursor in combinatorics and mainly in lattice theory | [['let', 'k_0', 'be', 'a', 'compact', 'convex', 'subset', 'of', 'the', 'plane', 'mathbb', 'r2', 'and', 'assume', 'that', 'whenever', 'k_1subseteq', 'mathbb', 'r2', 'is', 'congruent', 'to', 'k_0', 'then', 'k_0', 'and', 'k_1', 'are', 'not', 'crossing', 'in', 'a', 'natural', 'sense', 'due', 'to', 'l', 'fejestoth', 'a', 'theorem', 'of', 'l', 'fejestoth', 'from', '1967', 'states', 'that', 'the', 'assumption', 'above', 'holds', 'for', 'k_0', 'if', 'and', 'only', 'if', 'k_0', 'is', 'a', 'disk', 'in', 'a', 'paper', 'appeared', 'in', '2017', 'the', 'present', 'author', 'introduced', 'a', 'new', 'concept', 'of', 'crossing', 'and', 'proved', 'that', 'l', 'fejestoths', 'theorem', 'remains', 'true', 'if', 'the', 'old', 'concept', 'is', 'replaced', 'by', 'the', 'new', 'one', 'our', 'purpose', 'is', 'to', 'describe', 'the', 'hierarchy', 'among', 'several', 'variants', 'of', 'the', 'new', 'concepts', 'and', 'the', 'old', 'concept', 'of', 'crossing', 'in', 'particular', 'we', 'prove', 'that', 'each', 'variant', 'of', 'the', 'new', 'concept', 'of', 'crossing', 'is', 'more', 'restrictive', 'then', 'the', 'old', 'one', 'therefore', 'l', 'fejestoths', 'theorem', 'from', '1967', 'becomes', 'an', 'immediate', 'consequence', 'of', 'the', '2017', 'characterization', 'of', 'circles', 'but', 'not', 'conversely', 'finally', 'a', 'minisurvey', 'shows', 'that', 'this', 'purely', 'geometric', 'paper', 'has', 'precursor', 'in', 'combinatorics', 'and', 'mainly', 'in', 'lattice', 'theory']] | [-0.1265698769949542, 0.10249565836924236, -0.1144244611599433, 0.05986062718070382, -0.1070662801479094, -0.13324396413910758, 0.04029813581408062, 0.2957593774500154, -0.309534582984496, -0.2411514415499374, 0.10461667791345107, -0.24175555425070602, -0.16180095201380243, 0.19187866353458097, -0.14106685896514304, -0.06141337047512891, 0.03366833852229298, 0.08917983885325448, -0.04581090320072539, -0.24911115259846903, 0.3242300860997091, -0.02927260587168251, 0.18189160059586432, 0.08464057823524607, 0.07724118327237005, 0.02056642355309171, -0.0066857374433053314, 0.021986550986270843, -0.1800744336552814, 0.11708466449549929, 0.2245748487890825, 0.13735150652055866, 0.3017821059997618, -0.35313131164803485, -0.15150947167989992, 0.15598140906586627, 0.13364885127193918, 0.04056911937583833, -0.007067514501237201, -0.2456354034248982, 0.15218197939278194, -0.12932768647046483, -0.17278898270117374, -0.005451054215850033, 0.11160273287864127, -0.02114954718647624, -0.25101332348280936, 0.06382301588647464, 0.16457151128640454, 0.06467143568270922, -0.010237580766631345, -0.11820296511004443, -0.018020343782170812, 0.03770912856072981, 0.02438776263796322, 0.08754183161871497, 0.04885681204431685, -0.06675624157875203, -0.08682431557598749, 0.3836887291351543, -0.04054484899140641, -0.16000922953092753, 0.15506562595007686, -0.1529453818633954, -0.17367308690645264, 0.09528626532971683, 0.08471862057543542, 0.13011051471945803, -0.1005957858339393, 0.17127219627999848, -0.1343367405830932, 0.14764424139005544, 0.11302632866248202, 0.0036861664841513664, 0.16589581319985128, 0.08563176060464651, 0.10911211385612084, 0.11834123832264573, -0.0394516382311311, -0.041985277610020875, -0.3518744659549474, -0.15652566754910818, -0.2009793193039578, 0.0884978754527539, -0.025021112614384295, -0.139325830049416, 0.3326785772399613, 0.08779559359533062, 0.19810980455137062, 0.06460087836620855, 0.24350111065680416, 0.06858862225812193, 0.03656729792393523, 0.11058799210748464, 0.18637455359222532, 0.16816997612528944, 0.03455920174673817, -0.10556211252283504, 0.007620812269732268, 0.11310805191737792] |
1,802.06458 | A Generative Modeling Approach to Limited Channel ECG Classification | Processing temporal sequences is central to a variety of applications in
health care, and in particular multi-channel Electrocardiogram (ECG) is a
highly prevalent diagnostic modality that relies on robust sequence modeling.
While Recurrent Neural Networks (RNNs) have led to significant advances in
automated diagnosis with time-series data, they perform poorly when models are
trained using a limited set of channels. A crucial limitation of existing
solutions is that they rely solely on discriminative models, which tend to
generalize poorly in such scenarios. In order to combat this limitation, we
develop a generative modeling approach to limited channel ECG classification.
This approach first uses a Seq2Seq model to implicitly generate the missing
channel information, and then uses the latent representation to perform the
actual supervisory task. This decoupling enables the use of unsupervised data
and also provides highly robust metric spaces for subsequent discriminative
learning. Our experiments with the Physionet dataset clearly evidence the
effectiveness of our approach over standard RNNs in disease prediction.
| stat.ML cs.LG | processing temporal sequences is central to a variety of applications in health care and in particular multichannel electrocardiogram ecg is a highly prevalent diagnostic modality that relies on robust sequence modeling while recurrent neural networks rnns have led to significant advances in automated diagnosis with timeseries data they perform poorly when models are trained using a limited set of channels a crucial limitation of existing solutions is that they rely solely on discriminative models which tend to generalize poorly in such scenarios in order to combat this limitation we develop a generative modeling approach to limited channel ecg classification this approach first uses a seq2seq model to implicitly generate the missing channel information and then uses the latent representation to perform the actual supervisory task this decoupling enables the use of unsupervised data and also provides highly robust metric spaces for subsequent discriminative learning our experiments with the physionet dataset clearly evidence the effectiveness of our approach over standard rnns in disease prediction | [['processing', 'temporal', 'sequences', 'is', 'central', 'to', 'a', 'variety', 'of', 'applications', 'in', 'health', 'care', 'and', 'in', 'particular', 'multichannel', 'electrocardiogram', 'ecg', 'is', 'a', 'highly', 'prevalent', 'diagnostic', 'modality', 'that', 'relies', 'on', 'robust', 'sequence', 'modeling', 'while', 'recurrent', 'neural', 'networks', 'rnns', 'have', 'led', 'to', 'significant', 'advances', 'in', 'automated', 'diagnosis', 'with', 'timeseries', 'data', 'they', 'perform', 'poorly', 'when', 'models', 'are', 'trained', 'using', 'a', 'limited', 'set', 'of', 'channels', 'a', 'crucial', 'limitation', 'of', 'existing', 'solutions', 'is', 'that', 'they', 'rely', 'solely', 'on', 'discriminative', 'models', 'which', 'tend', 'to', 'generalize', 'poorly', 'in', 'such', 'scenarios', 'in', 'order', 'to', 'combat', 'this', 'limitation', 'we', 'develop', 'a', 'generative', 'modeling', 'approach', 'to', 'limited', 'channel', 'ecg', 'classification', 'this', 'approach', 'first', 'uses', 'a', 'seq2seq', 'model', 'to', 'implicitly', 'generate', 'the', 'missing', 'channel', 'information', 'and', 'then', 'uses', 'the', 'latent', 'representation', 'to', 'perform', 'the', 'actual', 'supervisory', 'task', 'this', 'decoupling', 'enables', 'the', 'use', 'of', 'unsupervised', 'data', 'and', 'also', 'provides', 'highly', 'robust', 'metric', 'spaces', 'for', 'subsequent', 'discriminative', 'learning', 'our', 'experiments', 'with', 'the', 'physionet', 'dataset', 'clearly', 'evidence', 'the', 'effectiveness', 'of', 'our', 'approach', 'over', 'standard', 'rnns', 'in', 'disease', 'prediction']] | [-0.037861574492617255, -0.012505438187348148, -0.0867292909251606, 0.09865100172982534, -0.13840569296503222, -0.19368895366959318, 0.03793502240256046, 0.43694788594644496, -0.25649936253810585, -0.2975708749202406, 0.1156331690591103, -0.2627878524991541, -0.2152673582734963, 0.2216897802584536, -0.17919878074556497, 0.10491387067902605, 0.16349421759233154, 0.052560071432334515, -0.011284746558182627, -0.24872032599970043, 0.2915772907235917, 0.035995961069786475, 0.3718721966939104, -0.0026534975983453857, 0.10807941531893894, 0.004465650467122076, -0.07156191616279124, -0.06171472952272629, -0.029129517520795737, 0.1878576086351271, 0.3551747096262596, 0.1984212775621849, 0.3438527119957322, -0.4350534510661982, -0.2866863638871104, 0.13268527009472983, 0.1558695474919503, 0.12184626479173205, -0.026452593586801843, -0.3256042254803005, 0.11068532017396729, -0.17093671486567294, 0.04027411590210316, -0.1694727418201467, -0.03144947721400052, -0.03748064992543698, -0.317452745288939, 0.07550609364882083, 0.06908015619129217, 0.06986800727485878, -0.05513469260214525, -0.06667254039406365, 0.03206250321461413, 0.16992024211387974, 0.04221874435269417, 0.06561047055449999, 0.114667839542077, -0.16296312437168511, -0.1362066937987607, 0.3355615379437347, -0.05276867716238931, -0.23173552377012335, 0.22772671178946033, -0.03156268718492446, -0.18448103240411157, 0.09307080520991168, 0.24899141177566483, 0.12500761974705782, -0.19570183905566102, -0.003494917341876501, 0.00011241756539586132, 0.21059615231559045, -0.01207641493157695, 0.011480692282684741, 0.18180836737120204, 0.2919144870261976, -0.01661137129934333, 0.10667583423786642, -0.14012187901895745, -0.06213245975772102, -0.1934101352021041, -0.06217563080892789, -0.16902719608342354, 0.0005191703101311542, -0.08122126784925907, -0.16879125995178668, 0.4077323921641872, 0.270076526757444, 0.19304600452855686, 0.08642404053454499, 0.3730343313419197, 0.011969752661955966, 0.12671177203344192, 0.05642517244099051, 0.15870066013678544, 0.06765381651848378, 0.1449464773846736, -0.14914420438341888, 0.11862974092964243, 0.014067706350591376] |
1,802.06459 | Structured Label Inference for Visual Understanding | Visual data such as images and videos contain a rich source of structured
semantic labels as well as a wide range of interacting components. Visual
content could be assigned with fine-grained labels describing major components,
coarse-grained labels depicting high level abstractions, or a set of labels
revealing attributes. Such categorization over different, interacting layers of
labels evinces the potential for a graph-based encoding of label information.
In this paper, we exploit this rich structure for performing graph-based
inference in label space for a number of tasks: multi-label image and video
classification and action detection in untrimmed videos. We consider the use of
the Bidirectional Inference Neural Network (BINN) and Structured Inference
Neural Network (SINN) for performing graph-based inference in label space and
propose a Long Short-Term Memory (LSTM) based extension for exploiting activity
progression on untrimmed videos. The methods were evaluated on (i) the Animal
with Attributes (AwA), Scene Understanding (SUN) and NUS-WIDE datasets for
multi-label image classification, (ii) the first two releases of the YouTube-8M
large scale dataset for multi-label video classification, and (iii) the
THUMOS'14 and MultiTHUMOS video datasets for action detection. Our results
demonstrate the effectiveness of structured label inference in these
challenging tasks, achieving significant improvements against baselines.
| cs.CV | visual data such as images and videos contain a rich source of structured semantic labels as well as a wide range of interacting components visual content could be assigned with finegrained labels describing major components coarsegrained labels depicting high level abstractions or a set of labels revealing attributes such categorization over different interacting layers of labels evinces the potential for a graphbased encoding of label information in this paper we exploit this rich structure for performing graphbased inference in label space for a number of tasks multilabel image and video classification and action detection in untrimmed videos we consider the use of the bidirectional inference neural network binn and structured inference neural network sinn for performing graphbased inference in label space and propose a long shortterm memory lstm based extension for exploiting activity progression on untrimmed videos the methods were evaluated on i the animal with attributes awa scene understanding sun and nuswide datasets for multilabel image classification ii the first two releases of the youtube8m large scale dataset for multilabel video classification and iii the thumos14 and multithumos video datasets for action detection our results demonstrate the effectiveness of structured label inference in these challenging tasks achieving significant improvements against baselines | [['visual', 'data', 'such', 'as', 'images', 'and', 'videos', 'contain', 'a', 'rich', 'source', 'of', 'structured', 'semantic', 'labels', 'as', 'well', 'as', 'a', 'wide', 'range', 'of', 'interacting', 'components', 'visual', 'content', 'could', 'be', 'assigned', 'with', 'finegrained', 'labels', 'describing', 'major', 'components', 'coarsegrained', 'labels', 'depicting', 'high', 'level', 'abstractions', 'or', 'a', 'set', 'of', 'labels', 'revealing', 'attributes', 'such', 'categorization', 'over', 'different', 'interacting', 'layers', 'of', 'labels', 'evinces', 'the', 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