id
float64
706
1.8k
title
stringlengths
1
343
abstract
stringlengths
6
6.09k
categories
stringlengths
5
125
processed_abstract
stringlengths
2
5.96k
tokenized_abstract
stringlengths
8
8.74k
centroid
stringlengths
2.1k
2.17k
1,802.0216
Quantum Spectral Curve of $\gamma$-twisted ${\cal N}=4$ SYM theory and fishnet CFT
We review the quantum spectral curve (QSC) formalism for anomalous dimensions of planar ${\cal\ N}=4$ SYM, including its $\gamma$-deformation. Leaving aside its derivation, we concentrate on formulation of the "final product" in its most general form: a minimal set of assumptions about the algebraic structure and the analyticity of the $Q$-system -- the full system of Baxter $Q$-functions of the underlying integrable model. The algebraic structure of the $Q$-system is entirely based on (super)symmetry of the model and is efficiently described by Wronskian formulas for $Q$-functions organized into the Hasse diagram. When supplemented with analyticity conditions on $Q$-functions, it fixes completely the set of physical solutions for spectrum of an integrable model. First we demonstrate the spectral equations on the example of $gl(N)$ and $gl(K|M)$ Heisenberg (super)spin chains. Supersymmetry $gl(K|M)$ occurs as a "rotation" of the Hasse diagram for a $gl(K+M)$ system. This picture helps us to construct the QSC formalism for spectrum of AdS$_5$/CFT$_4$-duality, with more complicated analyticity constraints on $Q$-functions which involve an infinitely branching Riemann surface and a set of Riemann-Hilbert conditions. As an example of application of QSC, we consider a special double scaling limit of $\gamma$-twisted ${\cal\ N}=4$ SYM, combining weak coupling and strong imaginary twist. This leads to a new type of non-unitary CFT dominated by particular integrable, and often computable, 4D fishnet Feynman graphs. For the simplest of such models -- the bi-scalar theory -- the QSC degenerates into the $Q$-system for integrable non-compact Heisenberg spin chain with conformal, $SU(2,2)$ symmetry. We apply the QSC for derivation of Baxter equation and the quantization condition for particular, "wheel" fishnet graphs, and review numerical and analytic results for them.
hep-th
we review the quantum spectral curve qsc formalism for anomalous dimensions of planar cal n4 sym including its gammadeformation leaving aside its derivation we concentrate on formulation of the final product in its most general form a minimal set of assumptions about the algebraic structure and the analyticity of the qsystem the full system of baxter qfunctions of the underlying integrable model the algebraic structure of the qsystem is entirely based on supersymmetry of the model and is efficiently described by wronskian formulas for qfunctions organized into the hasse diagram when supplemented with analyticity conditions on qfunctions it fixes completely the set of physical solutions for spectrum of an integrable model first we demonstrate the spectral equations on the example of gln and glkm heisenberg superspin chains supersymmetry glkm occurs as a rotation of the hasse diagram for a glkm system this picture helps us to construct the qsc formalism for spectrum of ads_5cft_4duality with more complicated analyticity constraints on qfunctions which involve an infinitely branching riemann surface and a set of riemannhilbert conditions as an example of application of qsc we consider a special double scaling limit of gammatwisted cal n4 sym combining weak coupling and strong imaginary twist this leads to a new type of nonunitary cft dominated by particular integrable and often computable 4d fishnet feynman graphs for the simplest of such models the biscalar theory the qsc degenerates into the qsystem for integrable noncompact heisenberg spin chain with conformal su22 symmetry we apply the qsc for derivation of baxter equation and the quantization condition for particular wheel fishnet graphs and review numerical and analytic results for them
[['we', 'review', 'the', 'quantum', 'spectral', 'curve', 'qsc', 'formalism', 'for', 'anomalous', 'dimensions', 'of', 'planar', 'cal', 'n4', 'sym', 'including', 'its', 'gammadeformation', 'leaving', 'aside', 'its', 'derivation', 'we', 'concentrate', 'on', 'formulation', 'of', 'the', 'final', 'product', 'in', 'its', 'most', 'general', 'form', 'a', 'minimal', 'set', 'of', 'assumptions', 'about', 'the', 'algebraic', 'structure', 'and', 'the', 'analyticity', 'of', 'the', 'qsystem', 'the', 'full', 'system', 'of', 'baxter', 'qfunctions', 'of', 'the', 'underlying', 'integrable', 'model', 'the', 'algebraic', 'structure', 'of', 'the', 'qsystem', 'is', 'entirely', 'based', 'on', 'supersymmetry', 'of', 'the', 'model', 'and', 'is', 'efficiently', 'described', 'by', 'wronskian', 'formulas', 'for', 'qfunctions', 'organized', 'into', 'the', 'hasse', 'diagram', 'when', 'supplemented', 'with', 'analyticity', 'conditions', 'on', 'qfunctions', 'it', 'fixes', 'completely', 'the', 'set', 'of', 'physical', 'solutions', 'for', 'spectrum', 'of', 'an', 'integrable', 'model', 'first', 'we', 'demonstrate', 'the', 'spectral', 'equations', 'on', 'the', 'example', 'of', 'gln', 'and', 'glkm', 'heisenberg', 'superspin', 'chains', 'supersymmetry', 'glkm', 'occurs', 'as', 'a', 'rotation', 'of', 'the', 'hasse', 'diagram', 'for', 'a', 'glkm', 'system', 'this', 'picture', 'helps', 'us', 'to', 'construct', 'the', 'qsc', 'formalism', 'for', 'spectrum', 'of', 'ads_5cft_4duality', 'with', 'more', 'complicated', 'analyticity', 'constraints', 'on', 'qfunctions', 'which', 'involve', 'an', 'infinitely', 'branching', 'riemann', 'surface', 'and', 'a', 'set', 'of', 'riemannhilbert', 'conditions', 'as', 'an', 'example', 'of', 'application', 'of', 'qsc', 'we', 'consider', 'a', 'special', 'double', 'scaling', 'limit', 'of', 'gammatwisted', 'cal', 'n4', 'sym', 'combining', 'weak', 'coupling', 'and', 'strong', 'imaginary', 'twist', 'this', 'leads', 'to', 'a', 'new', 'type', 'of', 'nonunitary', 'cft', 'dominated', 'by', 'particular', 'integrable', 'and', 'often', 'computable', '4d', 'fishnet', 'feynman', 'graphs', 'for', 'the', 'simplest', 'of', 'such', 'models', 'the', 'biscalar', 'theory', 'the', 'qsc', 'degenerates', 'into', 'the', 'qsystem', 'for', 'integrable', 'noncompact', 'heisenberg', 'spin', 'chain', 'with', 'conformal', 'su22', 'symmetry', 'we', 'apply', 'the', 'qsc', 'for', 'derivation', 'of', 'baxter', 'equation', 'and', 'the', 'quantization', 'condition', 'for', 'particular', 'wheel', 'fishnet', 'graphs', 'and', 'review', 'numerical', 'and', 'analytic', 'results', 'for', 'them']]
[-0.1476994685973127, 0.10227039581379224, -0.08064425487202782, 0.09330099162956079, -0.133186236301575, -0.15873996509342558, -0.004266093645451797, 0.2867821397880713, -0.2330940438283573, -0.21570797860105004, 0.11026802070706186, -0.2521116780332738, -0.18173074939771108, 0.18411647172524007, -0.023481548983168236, 0.06810945634777589, 0.04329267524579471, 0.059465414844453335, -0.13361409284105455, -0.21106199563041123, 0.36487615714712, -0.03790167455121668, 0.2281531234694369, 0.041879087537785784, 0.12491296118263293, 0.07228177428866427, 0.036157589072913485, -0.03602728397688932, -0.1657412419233609, 0.11765271169909587, 0.2192573872068924, 0.08613884812910799, 0.10013045281930655, -0.4242495929201444, -0.14798463068005663, 0.07428124087552229, 0.17207868173028584, 0.1145540398213564, 0.03352840979410016, -0.29044470102698716, 0.023200797991120015, -0.18093162658451883, -0.21763808367842877, -0.09788707922799168, 0.014599033835757938, -0.06098953156249115, -0.25740154983553415, 0.04732677414840846, 0.10371948939196214, 0.07292535619603263, -0.0487322763308098, -0.08926576104950747, -0.0613238228286651, 0.07255930515422261, 0.0147458118153736, -0.008583266653672412, 0.05735161969507182, -0.1621580547998073, -0.11426956005972763, 0.3657707020933567, -0.010240938666242141, -0.22588718137574484, 0.11444978527843314, -0.13758197177796522, -0.2055338600822897, 0.09935600814383684, 0.09140416882690731, 0.12667757566259416, -0.12402251059932125, 0.22439904772588676, -0.07163806263426388, 0.09882287456895467, 0.07294488697726693, 0.016792762812649555, 0.1708318981281654, 0.12701144197382275, 0.03424602862516487, 0.18083615319337695, 0.02133165327476389, -0.14911851937434187, -0.38934125162454114, -0.1535762776480826, -0.14599698659429258, 0.12609572553903692, -0.15835540709899593, -0.22693271965685266, 0.4044842249998409, 0.10323830349592147, 0.16521953300969605, 0.09272014120533303, 0.19427226182176835, 0.16595490156921894, 0.06354268559306446, 0.026237209622437755, 0.1638426199193216, 0.2299312289873207, 0.05482529660781708, -0.24113769645250782, -0.058898259375106406, 0.19393683276311666]
1,802.02161
Dynamical synchronization transition in interacting electron systems
Synchronization is a ubiquitous phenomenon in nature and we propose its new perspective in ultrafast dynamics in interacting electron systems. In particular, using graphene irradiated by an intense bi-circular pulse laser as a prototypical and experimental viable example, we theoretically investigate how to selectively generate a coherent oscillation of electronic order such as charge density waves (CDW). The key is to use tailored fields that match the crystalline symmetry broken by the target order. After the pump, a macroscopic number of electrons start oscillating and coherence is built up through a transition. The resulting physics is detectable as a coherent light emission at the synchronization frequency and may be used as a purely electronic way of realizing Floquet states respecting exotic space time crystalline symmetries. In the process, we also explore possible flipping of existing static CDW orders and generation of higher harmonics. The general framework for the coherent electronic order is found to be analogous with the celebrated Kuramoto model, describing the classical synchronization of coupled pendulums.
cond-mat.str-el cond-mat.mes-hall
synchronization is a ubiquitous phenomenon in nature and we propose its new perspective in ultrafast dynamics in interacting electron systems in particular using graphene irradiated by an intense bicircular pulse laser as a prototypical and experimental viable example we theoretically investigate how to selectively generate a coherent oscillation of electronic order such as charge density waves cdw the key is to use tailored fields that match the crystalline symmetry broken by the target order after the pump a macroscopic number of electrons start oscillating and coherence is built up through a transition the resulting physics is detectable as a coherent light emission at the synchronization frequency and may be used as a purely electronic way of realizing floquet states respecting exotic space time crystalline symmetries in the process we also explore possible flipping of existing static cdw orders and generation of higher harmonics the general framework for the coherent electronic order is found to be analogous with the celebrated kuramoto model describing the classical synchronization of coupled pendulums
[['synchronization', 'is', 'a', 'ubiquitous', 'phenomenon', 'in', 'nature', 'and', 'we', 'propose', 'its', 'new', 'perspective', 'in', 'ultrafast', 'dynamics', 'in', 'interacting', 'electron', 'systems', 'in', 'particular', 'using', 'graphene', 'irradiated', 'by', 'an', 'intense', 'bicircular', 'pulse', 'laser', 'as', 'a', 'prototypical', 'and', 'experimental', 'viable', 'example', 'we', 'theoretically', 'investigate', 'how', 'to', 'selectively', 'generate', 'a', 'coherent', 'oscillation', 'of', 'electronic', 'order', 'such', 'as', 'charge', 'density', 'waves', 'cdw', 'the', 'key', 'is', 'to', 'use', 'tailored', 'fields', 'that', 'match', 'the', 'crystalline', 'symmetry', 'broken', 'by', 'the', 'target', 'order', 'after', 'the', 'pump', 'a', 'macroscopic', 'number', 'of', 'electrons', 'start', 'oscillating', 'and', 'coherence', 'is', 'built', 'up', 'through', 'a', 'transition', 'the', 'resulting', 'physics', 'is', 'detectable', 'as', 'a', 'coherent', 'light', 'emission', 'at', 'the', 'synchronization', 'frequency', 'and', 'may', 'be', 'used', 'as', 'a', 'purely', 'electronic', 'way', 'of', 'realizing', 'floquet', 'states', 'respecting', 'exotic', 'space', 'time', 'crystalline', 'symmetries', 'in', 'the', 'process', 'we', 'also', 'explore', 'possible', 'flipping', 'of', 'existing', 'static', 'cdw', 'orders', 'and', 'generation', 'of', 'higher', 'harmonics', 'the', 'general', 'framework', 'for', 'the', 'coherent', 'electronic', 'order', 'is', 'found', 'to', 'be', 'analogous', 'with', 'the', 'celebrated', 'kuramoto', 'model', 'describing', 'the', 'classical', 'synchronization', 'of', 'coupled', 'pendulums']]
[-0.1592402644330702, 0.23441367195023521, -0.06568218106847434, 0.07656915988910182, -0.05721809762638129, -0.13264320992277048, 0.044132941280536, 0.3798102629426423, -0.2740543860154936, -0.28395887623108657, 0.04911654344011497, -0.251397344788226, -0.1562605339762134, 0.1811096167782255, 0.011098517365531907, 0.046545255726544256, -0.03377317131976486, -0.0001851572222741587, -0.043840997779278995, -0.15912767382715606, 0.28905038479881895, 0.04138010003676061, 0.30579260493479005, 0.00516657542210028, 0.0887288873720016, -0.0030703012349217068, 0.07165854331383127, -0.025912443367338882, -0.10297438595604208, 0.0997412033566867, 0.263178733594638, 0.009111793182368967, 0.2229689456372788, -0.4884451832511418, -0.2367137206297013, 0.0655930654403554, 0.1416878382329915, 0.1773414512309024, -0.09683992381351778, -0.29346060193243567, 0.02154339104197875, -0.1713202497062628, -0.16047107819966705, -0.12473756467391338, -0.0036906883261898266, 0.026983148531663965, -0.2367647563036631, 0.07077204752723835, 0.051772515541718654, 0.034698250489219346, -0.04104907291323235, 0.006021942873173559, -0.04395140511041973, 0.08106974520099659, 0.01274739632676106, 0.049839456050124555, 0.13830789916773073, -0.12015504713712116, -0.16007727702526608, 0.42686465475708246, -0.07826649607089903, -0.11448298922455467, 0.17927065692354172, -0.1345376540294161, -0.07682319532198432, 0.14029806422574134, 0.1524895875717491, 0.10943177013680161, -0.12073452482512775, 0.03282354755286915, -0.012297985784936741, 0.1832884316806615, 0.08826255004498221, 0.11374855275962978, 0.25967275400901035, 0.21602870541669073, 0.0544130186847594, 0.16785641494408038, -0.0790419432104543, -0.08509920814131397, -0.27202796551587416, -0.12629862473113462, -0.18767324461424278, 0.07034749011342813, -0.019906324794127222, -0.12453104432539217, 0.465844261074727, 0.15361989659036876, 0.14019577847682826, -0.06183822071068876, 0.2873108089884876, 0.13372230578845898, 0.031157189944115954, 0.011858462155075921, 0.24211978860936748, 0.15321154215087604, 0.09135326631422643, -0.2462343636185064, 0.034861107844681966, 0.013930755643828195]
1,802.02162
LeMMINGs. I. The eMERLIN legacy survey of nearby galaxies. 1.5-GHz parsec-scale radio structures and cores
We present the first data release of high-resolution ($\leq0.2$ arcsec) 1.5-GHz radio images of 103 nearby galaxies from the Palomar sample, observed with the eMERLIN array, as part of the LeMMINGs survey. This sample includes galaxies which are active (LINER and Seyfert) and quiescent (HII galaxies and Absorption line galaxies, ALG), which are reclassified based upon revised emission-line diagrams. We detect radio emission $\gtrsim$ 0.2 mJy for 47/103 galaxies (22/34 for LINERS, 4/4 for Seyferts, 16/51 for HII galaxies and 5/14 for ALGs) with radio sizes typically of $\lesssim$100 pc. We identify the radio core position within the radio structures for 41 sources. Half of the sample shows jetted morphologies. The remaining half shows single radio cores or complex morphologies. LINERs show radio structures more core-brightened than Seyferts. Radio luminosities of the sample range from 10$^{32}$ to 10$^{40}$ erg s$^{-1}$: LINERs and HII galaxies show the highest and the lowest radio powers respectively, while ALGs and Seyferts have intermediate luminosities. We find that radio core luminosities correlate with black hole (BH) mass down to $\sim$10$^{7}$ M$_{\odot}$, but a break emerges at lower masses. Using [O III] line luminosity as a proxy for the accretion luminosity, active nuclei and jetted HII galaxies follow an optical fundamental plane of BH activity, suggesting a common disc-jet relationship. In conclusion, LINER nuclei are the scaled-down version of FR I radio galaxies; Seyferts show less collimated jets; HII galaxies may host weak active BHs and/or nuclear star-forming cores; and recurrent BH activity may account for ALG properties.
astro-ph.GA astro-ph.HE
we present the first data release of highresolution leq02 arcsec 15ghz radio images of 103 nearby galaxies from the palomar sample observed with the emerlin array as part of the lemmings survey this sample includes galaxies which are active liner and seyfert and quiescent hii galaxies and absorption line galaxies alg which are reclassified based upon revised emissionline diagrams we detect radio emission gtrsim 02 mjy for 47103 galaxies 2234 for liners 44 for seyferts 1651 for hii galaxies and 514 for algs with radio sizes typically of lesssim100 pc we identify the radio core position within the radio structures for 41 sources half of the sample shows jetted morphologies the remaining half shows single radio cores or complex morphologies liners show radio structures more corebrightened than seyferts radio luminosities of the sample range from 1032 to 1040 erg s1 liners and hii galaxies show the highest and the lowest radio powers respectively while algs and seyferts have intermediate luminosities we find that radio core luminosities correlate with black hole bh mass down to sim107 m_odot but a break emerges at lower masses using o iii line luminosity as a proxy for the accretion luminosity active nuclei and jetted hii galaxies follow an optical fundamental plane of bh activity suggesting a common discjet relationship in conclusion liner nuclei are the scaleddown version of fr i radio galaxies seyferts show less collimated jets hii galaxies may host weak active bhs andor nuclear starforming cores and recurrent bh activity may account for alg properties
[['we', 'present', 'the', 'first', 'data', 'release', 'of', 'highresolution', 'leq02', 'arcsec', '15ghz', 'radio', 'images', 'of', '103', 'nearby', 'galaxies', 'from', 'the', 'palomar', 'sample', 'observed', 'with', 'the', 'emerlin', 'array', 'as', 'part', 'of', 'the', 'lemmings', 'survey', 'this', 'sample', 'includes', 'galaxies', 'which', 'are', 'active', 'liner', 'and', 'seyfert', 'and', 'quiescent', 'hii', 'galaxies', 'and', 'absorption', 'line', 'galaxies', 'alg', 'which', 'are', 'reclassified', 'based', 'upon', 'revised', 'emissionline', 'diagrams', 'we', 'detect', 'radio', 'emission', 'gtrsim', '02', 'mjy', 'for', '47103', 'galaxies', '2234', 'for', 'liners', '44', 'for', 'seyferts', '1651', 'for', 'hii', 'galaxies', 'and', '514', 'for', 'algs', 'with', 'radio', 'sizes', 'typically', 'of', 'lesssim100', 'pc', 'we', 'identify', 'the', 'radio', 'core', 'position', 'within', 'the', 'radio', 'structures', 'for', '41', 'sources', 'half', 'of', 'the', 'sample', 'shows', 'jetted', 'morphologies', 'the', 'remaining', 'half', 'shows', 'single', 'radio', 'cores', 'or', 'complex', 'morphologies', 'liners', 'show', 'radio', 'structures', 'more', 'corebrightened', 'than', 'seyferts', 'radio', 'luminosities', 'of', 'the', 'sample', 'range', 'from', '1032', 'to', '1040', 'erg', 's1', 'liners', 'and', 'hii', 'galaxies', 'show', 'the', 'highest', 'and', 'the', 'lowest', 'radio', 'powers', 'respectively', 'while', 'algs', 'and', 'seyferts', 'have', 'intermediate', 'luminosities', 'we', 'find', 'that', 'radio', 'core', 'luminosities', 'correlate', 'with', 'black', 'hole', 'bh', 'mass', 'down', 'to', 'sim107', 'm_odot', 'but', 'a', 'break', 'emerges', 'at', 'lower', 'masses', 'using', 'o', 'iii', 'line', 'luminosity', 'as', 'a', 'proxy', 'for', 'the', 'accretion', 'luminosity', 'active', 'nuclei', 'and', 'jetted', 'hii', 'galaxies', 'follow', 'an', 'optical', 'fundamental', 'plane', 'of', 'bh', 'activity', 'suggesting', 'a', 'common', 'discjet', 'relationship', 'in', 'conclusion', 'liner', 'nuclei', 'are', 'the', 'scaleddown', 'version', 'of', 'fr', 'i', 'radio', 'galaxies', 'seyferts', 'show', 'less', 'collimated', 'jets', 'hii', 'galaxies', 'may', 'host', 'weak', 'active', 'bhs', 'andor', 'nuclear', 'starforming', 'cores', 'and', 'recurrent', 'bh', 'activity', 'may', 'account', 'for', 'alg', 'properties']]
[-0.03064130939578172, 0.06606139880046248, 0.03242452384904027, 0.1690012063193135, -0.11740289210528135, -0.0807263290155679, 0.07038362754229456, 0.5317153759524226, -0.0023126537278294564, -0.3556704539768398, 0.04667816568963463, -0.3123393050406594, 0.05839491519890726, 0.1942252101865597, 0.009498889054171742, -0.11047805291274562, -0.012919143496081233, -0.20168474804237485, -0.039934704929590226, -0.2176538057839498, 0.2751143043935299, 0.07039005808904766, 0.18315596666373313, -0.10546591007290408, 0.06147943887161091, -0.16742941019684077, -0.08987275576218963, -0.05682950866408646, -0.10740924796243781, -0.007972345056012273, 0.3091808081455529, 0.15093402624689042, 0.19483351256808965, -0.3182487622195622, -0.1738979141358286, 0.06453695510979741, 0.25569556578807534, -0.020356838753446935, -0.050188959147140846, -0.2888200185522437, 0.10522580208815634, -0.24653819323144854, -0.17597818736173212, 0.16546257835626602, 0.08698809792334214, 0.060748746080091225, -0.16922500707767904, 0.20508503745496273, -0.007016242666635662, 0.10502321303635835, -0.15348627210687846, -0.09640792939253151, -0.06518438972439616, 0.039650137417018415, -0.023445531361270696, 0.07059582670871169, 0.2876780878873542, -0.14151018144283445, -0.05470407550781965, 0.39017666729539635, 0.05517548290285049, 0.1287092804722488, 0.256857572930865, -0.25022061019577085, -0.2245962044354528, 0.18264360893750564, 0.1673412140663713, 0.1243261460987851, -0.11612723527289927, -0.05628825147659518, -0.02496076924027875, 0.2848058532550931, -0.012637916323728859, 0.13324645431153476, 0.3288021609671414, 0.05373168141022325, 0.03855116633046418, 0.12152619013935327, -0.26646965673519296, 0.045389349342207425, -0.23148472042754292, -0.0511061468978296, -0.09244799493765458, 0.1796031248215586, -0.17496883675217395, -0.07840794425574131, 0.3140265619521961, 0.00561321118613705, 0.2350878225112101, 0.10173655845597386, 0.27829346353188156, 0.04505891608353704, 0.16021116639114916, 0.2081477900892496, 0.35409872146509586, 0.1893446255857125, 0.09426006408501417, -0.2113751893346198, -0.016855971339158712, 0.017860653647221624]
1,802.02163
How to Make Causal Inferences Using Texts
New text as data techniques offer a great promise: the ability to inductively discover measures that are useful for testing social science theories of interest from large collections of text. We introduce a conceptual framework for making causal inferences with discovered measures as a treatment or outcome. Our framework enables researchers to discover high-dimensional textual interventions and estimate the ways that observed treatments affect text-based outcomes. We argue that nearly all text-based causal inferences depend upon a latent representation of the text and we provide a framework to learn the latent representation. But estimating this latent representation, we show, creates new risks: we may introduce an identification problem or overfit. To address these risks we describe a split-sample framework and apply it to estimate causal effects from an experiment on immigration attitudes and a study on bureaucratic response. Our work provides a rigorous foundation for text-based causal inferences.
stat.ML cs.CL stat.ME
new text as data techniques offer a great promise the ability to inductively discover measures that are useful for testing social science theories of interest from large collections of text we introduce a conceptual framework for making causal inferences with discovered measures as a treatment or outcome our framework enables researchers to discover highdimensional textual interventions and estimate the ways that observed treatments affect textbased outcomes we argue that nearly all textbased causal inferences depend upon a latent representation of the text and we provide a framework to learn the latent representation but estimating this latent representation we show creates new risks we may introduce an identification problem or overfit to address these risks we describe a splitsample framework and apply it to estimate causal effects from an experiment on immigration attitudes and a study on bureaucratic response our work provides a rigorous foundation for textbased causal inferences
[['new', 'text', 'as', 'data', 'techniques', 'offer', 'a', 'great', 'promise', 'the', 'ability', 'to', 'inductively', 'discover', 'measures', 'that', 'are', 'useful', 'for', 'testing', 'social', 'science', 'theories', 'of', 'interest', 'from', 'large', 'collections', 'of', 'text', 'we', 'introduce', 'a', 'conceptual', 'framework', 'for', 'making', 'causal', 'inferences', 'with', 'discovered', 'measures', 'as', 'a', 'treatment', 'or', 'outcome', 'our', 'framework', 'enables', 'researchers', 'to', 'discover', 'highdimensional', 'textual', 'interventions', 'and', 'estimate', 'the', 'ways', 'that', 'observed', 'treatments', 'affect', 'textbased', 'outcomes', 'we', 'argue', 'that', 'nearly', 'all', 'textbased', 'causal', 'inferences', 'depend', 'upon', 'a', 'latent', 'representation', 'of', 'the', 'text', 'and', 'we', 'provide', 'a', 'framework', 'to', 'learn', 'the', 'latent', 'representation', 'but', 'estimating', 'this', 'latent', 'representation', 'we', 'show', 'creates', 'new', 'risks', 'we', 'may', 'introduce', 'an', 'identification', 'problem', 'or', 'overfit', 'to', 'address', 'these', 'risks', 'we', 'describe', 'a', 'splitsample', 'framework', 'and', 'apply', 'it', 'to', 'estimate', 'causal', 'effects', 'from', 'an', 'experiment', 'on', 'immigration', 'attitudes', 'and', 'a', 'study', 'on', 'bureaucratic', 'response', 'our', 'work', 'provides', 'a', 'rigorous', 'foundation', 'for', 'textbased', 'causal', 'inferences']]
[-0.021335816311310173, 0.05523957243536102, -0.12435238245509665, 0.14337282296430595, -0.21249437783026714, -0.14746722198292814, 0.10639271518920322, 0.3919669560886718, -0.2572555584499512, -0.31275880051701255, 0.06641965643801676, -0.28415749088949144, -0.20314845150868358, 0.19188577145325472, -0.12960541472342368, 0.02957409304311826, 0.1036943232552526, 0.025891161868482438, -0.031686449917410875, -0.2405182981228053, 0.3248807053314522, 0.029809006829620212, 0.3357795718931467, 0.025151958459409308, 0.11560029165293845, 0.03876830861161186, -0.10687413090223295, 0.02513797290472163, -0.14652743552746747, 0.19784110568297045, 0.3702701371339326, 0.2718529727725262, 0.3815756166539457, -0.40947045444202534, -0.2595417104611123, 0.08733569208306034, 0.09112209509240111, 0.1501050413321905, -0.0337612818552156, -0.3470850969236848, 0.021757046106850374, -0.18492260619972808, -0.058089669803283304, -0.20255509738863847, -0.031923964075316245, -0.05721958238270442, -0.30261551917253715, 0.038662441045744345, 0.08375826974775377, 0.08310995908214937, -0.053677933243405376, -0.08949394956407314, 0.07995939283392618, 0.17563393851348855, 0.07012531389734028, 0.01977598704743778, 0.11390040908008814, -0.13649006743720304, -0.16966381737005873, 0.35401968547218554, -0.01464376801536796, -0.22889982700989758, 0.20373024810986542, -0.06446299881428934, -0.19436566528275837, 0.033041514374466764, 0.27132279380866503, 0.09029537332684708, -0.20752929144765478, 0.005190265509677497, -0.04703137504268828, 0.1749791372504488, 0.011406350484419917, 0.01673073771510374, 0.23210139779650882, 0.20436808481384572, 0.032409117230673544, 0.09767596573392684, -0.06961126286360259, -0.05510216255395396, -0.24986608064657934, -0.16586271759021926, -0.10880983209731435, 0.03009553039540864, -0.10306604189217733, -0.19878959874876198, 0.36148247639554226, 0.276287280543034, 0.18089434204975496, 0.09237411938374862, 0.25017692723840074, 0.022724188593644147, 0.05426236248033977, 0.06532951497875557, 0.1345302387696417, 0.06875619246007723, 0.08094648489291226, -0.13007343046027361, 0.17904621393363168, -0.0009833953431429895]
1,802.02164
The First Hours of the GW170817 Kilonova and the Importance of Early Optical and Ultraviolet Observations for Constraining Emission Models
The kilonova associated with GW170817 displayed early blue emission which has been interpreted as a signature of either radioactive decay in low-opacity ejecta, relativistic boosting of radioactive decay in high-velocity ejecta, the cooling of material heated by a wind or by a "cocoon" surrounding a jet, or a combination thereof. Distinguishing between these mechanisms is important for constraining the ejecta components and their parameters, which tie directly into the physics we can learn from these events. I compile published ultraviolet, optical, and infrared light curves of the GW170817 kilonova and examine whether the combined data set can be used to distinguish between early-emission models. The combined optical data show an early rise consistent with radioactive decay of low opacity ejecta as the main emission source, but the subsequent decline is fit well by all models. A lack of constraints on the ultraviolet flux during the first few hours after discovery allows for both radioactive decay and other cooling mechanisms to explain the early bolometric light curve. This analysis demonstrates that early (few hours after merger) high-cadence optical and ultraviolet observations will be critical for determining the source of blue emission in future kilonovae.
astro-ph.HE gr-qc
the kilonova associated with gw170817 displayed early blue emission which has been interpreted as a signature of either radioactive decay in lowopacity ejecta relativistic boosting of radioactive decay in highvelocity ejecta the cooling of material heated by a wind or by a cocoon surrounding a jet or a combination thereof distinguishing between these mechanisms is important for constraining the ejecta components and their parameters which tie directly into the physics we can learn from these events i compile published ultraviolet optical and infrared light curves of the gw170817 kilonova and examine whether the combined data set can be used to distinguish between earlyemission models the combined optical data show an early rise consistent with radioactive decay of low opacity ejecta as the main emission source but the subsequent decline is fit well by all models a lack of constraints on the ultraviolet flux during the first few hours after discovery allows for both radioactive decay and other cooling mechanisms to explain the early bolometric light curve this analysis demonstrates that early few hours after merger highcadence optical and ultraviolet observations will be critical for determining the source of blue emission in future kilonovae
[['the', 'kilonova', 'associated', 'with', 'gw170817', 'displayed', 'early', 'blue', 'emission', 'which', 'has', 'been', 'interpreted', 'as', 'a', 'signature', 'of', 'either', 'radioactive', 'decay', 'in', 'lowopacity', 'ejecta', 'relativistic', 'boosting', 'of', 'radioactive', 'decay', 'in', 'highvelocity', 'ejecta', 'the', 'cooling', 'of', 'material', 'heated', 'by', 'a', 'wind', 'or', 'by', 'a', 'cocoon', 'surrounding', 'a', 'jet', 'or', 'a', 'combination', 'thereof', 'distinguishing', 'between', 'these', 'mechanisms', 'is', 'important', 'for', 'constraining', 'the', 'ejecta', 'components', 'and', 'their', 'parameters', 'which', 'tie', 'directly', 'into', 'the', 'physics', 'we', 'can', 'learn', 'from', 'these', 'events', 'i', 'compile', 'published', 'ultraviolet', 'optical', 'and', 'infrared', 'light', 'curves', 'of', 'the', 'gw170817', 'kilonova', 'and', 'examine', 'whether', 'the', 'combined', 'data', 'set', 'can', 'be', 'used', 'to', 'distinguish', 'between', 'earlyemission', 'models', 'the', 'combined', 'optical', 'data', 'show', 'an', 'early', 'rise', 'consistent', 'with', 'radioactive', 'decay', 'of', 'low', 'opacity', 'ejecta', 'as', 'the', 'main', 'emission', 'source', 'but', 'the', 'subsequent', 'decline', 'is', 'fit', 'well', 'by', 'all', 'models', 'a', 'lack', 'of', 'constraints', 'on', 'the', 'ultraviolet', 'flux', 'during', 'the', 'first', 'few', 'hours', 'after', 'discovery', 'allows', 'for', 'both', 'radioactive', 'decay', 'and', 'other', 'cooling', 'mechanisms', 'to', 'explain', 'the', 'early', 'bolometric', 'light', 'curve', 'this', 'analysis', 'demonstrates', 'that', 'early', 'few', 'hours', 'after', 'merger', 'highcadence', 'optical', 'and', 'ultraviolet', 'observations', 'will', 'be', 'critical', 'for', 'determining', 'the', 'source', 'of', 'blue', 'emission', 'in', 'future', 'kilonovae']]
[-0.016202038958302484, 0.14400289267185448, -0.09940864472931328, 0.12437043852029699, -0.11841861547873123, -0.13987239280929012, 0.03684781505338227, 0.44201515420960885, -0.23391120241528066, -0.3172902152703803, 0.10847867451290465, -0.29976526284137134, -0.007459014843334444, 0.23633534564699707, -0.01945992772622655, -0.012983358038278917, 0.11249724645023207, -0.06556861056985024, -0.05787231334034004, -0.19658463842157894, 0.26820247764529387, 0.10433204642807443, 0.17416516605590004, 0.030886829897402397, 0.04974506118621017, -0.07188071996400443, -0.09341004812934746, -0.08218075402328395, -0.0587524552308499, 0.05146967015313445, 0.17977039172838735, 0.19031886820766886, 0.18445862206317543, -0.44052894282503985, -0.2776413804870875, 0.1198071054580699, 0.1708450382866431, 0.04663774154444885, -0.07458507390144102, -0.26891030643794994, 0.005306626472095862, -0.20509239487485806, -0.14597200523955203, 0.02446429132396588, 0.03590797534949767, 0.04257964669219897, -0.22606710711382524, 0.06911948297541433, -0.0026951849346611803, 0.05606946855368733, -0.0912207076850488, -0.0620366081057, -0.048415199329610914, 0.052509972692253847, 0.10729603705173456, 0.0409216757689137, 0.15887014832090549, -0.15280722319948836, -0.05193347009480931, 0.4054763912281487, -0.09926793655661943, 0.06601052788028028, 0.19638197485619457, -0.14723872981994646, -0.13042154180705742, 0.22936753807395385, 0.16529446277369667, 0.08521129592554644, -0.1800098507325553, -0.05346065825642654, 0.040065847938725106, 0.17399945149857862, 0.04022881111207729, 0.08749057661528543, 0.3404947047044213, 0.15565965802428158, -0.06566625216665518, 0.11457233740990584, -0.1820394614360339, 0.027889273114851676, -0.3127850330298922, -0.10434752282647726, -0.10106028052481027, 0.10999322630777897, -0.10307729797652125, -0.12307387991169587, 0.3843225610083512, 0.08654076452269995, 0.21565380180618376, -0.026121990975904435, 0.30690919761400437, 0.07642182493456555, 0.07012840017826723, 0.09487219240448515, 0.35172940038804273, 0.126461587925102, 0.11142757536678498, -0.2504455724883883, 0.12898937227146234, 0.02146965358527571]
1,802.02165
A general framework to test gravity using galaxy clusters I: Modelling the dynamical mass of haloes in $ f(R) $ gravity
We propose a new framework for testing gravity using cluster observations, which aims to provide an unbiased constraint on modified gravity models from Sunyaev Zel'dovich (SZ) and X-ray cluster counts and the cluster gas fraction, among other possible observables. Focusing on a popular $ f(R) $ model of gravity, we propose a novel procedure to recalibrate mass scaling relations from $ \Lambda $CDM to $ f(R) $ gravity for SZ and X-ray cluster observables. We find that the complicated modified gravity effects can be simply modelled as a dependence on a combination of the background scalar field and redshift, $ f_R(z)/(1+z) $, regardless of the $ f(R) $ model parameter. By employing a large suite of N-body simulations, we demonstrate that a theoretically derived tanh fitting formula is in excellent agreement with the dynamical mass enhancement of dark matter haloes for a large range of background field parameters and redshifts. Our framework is sufficiently flexible to allow for tests of other models and inclusion of further observables. The one-parameter description of the dynamical mass enhancement can have important implications on the theoretical modelling of observables and on practical tests of gravity.
astro-ph.CO
we propose a new framework for testing gravity using cluster observations which aims to provide an unbiased constraint on modified gravity models from sunyaev zeldovich sz and xray cluster counts and the cluster gas fraction among other possible observables focusing on a popular fr model of gravity we propose a novel procedure to recalibrate mass scaling relations from lambda cdm to fr gravity for sz and xray cluster observables we find that the complicated modified gravity effects can be simply modelled as a dependence on a combination of the background scalar field and redshift f_rz1z regardless of the fr model parameter by employing a large suite of nbody simulations we demonstrate that a theoretically derived tanh fitting formula is in excellent agreement with the dynamical mass enhancement of dark matter haloes for a large range of background field parameters and redshifts our framework is sufficiently flexible to allow for tests of other models and inclusion of further observables the oneparameter description of the dynamical mass enhancement can have important implications on the theoretical modelling of observables and on practical tests of gravity
[['we', 'propose', 'a', 'new', 'framework', 'for', 'testing', 'gravity', 'using', 'cluster', 'observations', 'which', 'aims', 'to', 'provide', 'an', 'unbiased', 'constraint', 'on', 'modified', 'gravity', 'models', 'from', 'sunyaev', 'zeldovich', 'sz', 'and', 'xray', 'cluster', 'counts', 'and', 'the', 'cluster', 'gas', 'fraction', 'among', 'other', 'possible', 'observables', 'focusing', 'on', 'a', 'popular', 'fr', 'model', 'of', 'gravity', 'we', 'propose', 'a', 'novel', 'procedure', 'to', 'recalibrate', 'mass', 'scaling', 'relations', 'from', 'lambda', 'cdm', 'to', 'fr', 'gravity', 'for', 'sz', 'and', 'xray', 'cluster', 'observables', 'we', 'find', 'that', 'the', 'complicated', 'modified', 'gravity', 'effects', 'can', 'be', 'simply', 'modelled', 'as', 'a', 'dependence', 'on', 'a', 'combination', 'of', 'the', 'background', 'scalar', 'field', 'and', 'redshift', 'f_rz1z', 'regardless', 'of', 'the', 'fr', 'model', 'parameter', 'by', 'employing', 'a', 'large', 'suite', 'of', 'nbody', 'simulations', 'we', 'demonstrate', 'that', 'a', 'theoretically', 'derived', 'tanh', 'fitting', 'formula', 'is', 'in', 'excellent', 'agreement', 'with', 'the', 'dynamical', 'mass', 'enhancement', 'of', 'dark', 'matter', 'haloes', 'for', 'a', 'large', 'range', 'of', 'background', 'field', 'parameters', 'and', 'redshifts', 'our', 'framework', 'is', 'sufficiently', 'flexible', 'to', 'allow', 'for', 'tests', 'of', 'other', 'models', 'and', 'inclusion', 'of', 'further', 'observables', 'the', 'oneparameter', 'description', 'of', 'the', 'dynamical', 'mass', 'enhancement', 'can', 'have', 'important', 'implications', 'on', 'the', 'theoretical', 'modelling', 'of', 'observables', 'and', 'on', 'practical', 'tests', 'of', 'gravity']]
[-0.07907314554888509, 0.06327773226003448, -0.13783872273148587, 0.1272849730429502, -0.11409632540539483, -0.12416791652318976, 0.013464681006638715, 0.338103399905299, -0.17546223534415192, -0.3611180724689315, 0.028321222242003934, -0.24479487708651393, -0.09297574671803464, 0.22874964047892235, 0.008740520225683463, 0.054111011719938304, 0.031219154375075307, -0.03312895218285382, -0.0716075625997236, -0.21798918954513513, 0.3349515858687749, 0.1277418904423261, 0.22178580887739172, -0.012856000257419288, 0.11594025782715961, -0.03360090120849894, -0.06673189746061577, 0.09311216472498866, -0.20022079558730788, 0.0490509774127476, 0.1799580162719168, 0.13543846359918954, 0.21144508809309184, -0.3762051712217334, -0.2554136280945466, 0.08274553659325723, 0.1392201704554548, 0.13098506318168582, -0.09210226903039222, -0.26428074040836064, 0.050870965204062715, -0.22014751409319389, -0.11509970076142897, -0.07976361957008214, -0.00023919207723142362, 0.003285461187733142, -0.29094826597051476, 0.15539696197365077, -0.03057516503529829, 0.000897525063618112, -0.06321555876445786, -0.10775544753462817, -0.002555820010396657, 0.052624227625101765, 0.0393114317573854, 0.03394281999748303, 0.17034424625553232, -0.17061683625620866, -0.07481922471744024, 0.424282051015707, -0.1155658186090472, -0.1510769244262856, 0.19366941735719573, -0.13900049599800876, -0.2021712251007557, 0.024222321214041165, 0.18419607471962823, 0.08833533498453419, -0.16203931681052858, 0.11264175214986086, -0.01950339145909542, 0.20823691846566142, 0.021092199499188866, 0.023024356223857328, 0.3175127212966674, 0.13970380947534097, -0.0002977184022555529, 0.10516462390161845, -0.13135115914329762, -0.04378899266635896, -0.3021995020742163, -0.09282896025054857, -0.12520646680022965, 0.031936721755346044, -0.17631292389134956, -0.15429083723060333, 0.34966223627246545, 0.16972496153179617, 0.17219798671189715, 0.11042114496887122, 0.30326168157818895, 0.10261863647787754, 0.07630494830214023, 0.023069500753357595, 0.28090380476427507, 0.1742863552451895, 0.012616365571063815, -0.2509587424812396, -0.01155135217534368, 0.03004175341991677]
1,802.02166
Galaxy pairs in the SDSS - XIII. The connection between enhanced star formation and molecular gas properties in galaxy mergers
We investigate the connection between star formation and molecular gas properties in galaxy mergers at low redshift (z$\leq$0.06). The study we present is based on IRAM 30-m CO(1-0) observations of 11 galaxies with a close companion selected from the Sloan Digital Sky Survey (SDSS). The pairs have mass ratios $\leq$4, projected separations r$_{\mathrm{p}} \leq$30 kpc and velocity separations $\Delta$V$\leq$300 km s$^{-1}$, and have been selected to exhibit enhanced specific star formation rates (sSFR). We calculate molecular gas (H$_{2}$) masses, assigning to each galaxy a physically motivated conversion factor $\alpha_{\mathrm{CO}}$, and we derive molecular gas fractions and depletion times. We compare these quantities with those of isolated galaxies from the extended CO Legacy Data base for the GALEX Arecibo SDSS Survey sample (xCOLDGASS, Saintonge et al. 2017) with gas quantities computed in an identical way. Ours is the first study which directly compares the gas properties of galaxy pairs and those of a control sample of normal galaxies with rigorous control procedures and for which SFR and H$_{2}$ masses have been estimated using the same method. We find that the galaxy pairs have shorter depletion times and an average molecular gas fraction enhancement of 0.4 dex compared to the mass matched control sample drawn from xCOLDGASS. However, the gas masses (and fractions) in galaxy pairs and their depletion times are consistent with those of non-mergers whose SFRs are similarly elevated. We conclude that both external interactions and internal processes may lead to molecular gas enhancement and decreased depletion times.
astro-ph.GA
we investigate the connection between star formation and molecular gas properties in galaxy mergers at low redshift zleq006 the study we present is based on iram 30m co10 observations of 11 galaxies with a close companion selected from the sloan digital sky survey sdss the pairs have mass ratios leq4 projected separations r_mathrmp leq30 kpc and velocity separations deltavleq300 km s1 and have been selected to exhibit enhanced specific star formation rates ssfr we calculate molecular gas h_2 masses assigning to each galaxy a physically motivated conversion factor alpha_mathrmco and we derive molecular gas fractions and depletion times we compare these quantities with those of isolated galaxies from the extended co legacy data base for the galex arecibo sdss survey sample xcoldgass saintonge et al 2017 with gas quantities computed in an identical way ours is the first study which directly compares the gas properties of galaxy pairs and those of a control sample of normal galaxies with rigorous control procedures and for which sfr and h_2 masses have been estimated using the same method we find that the galaxy pairs have shorter depletion times and an average molecular gas fraction enhancement of 04 dex compared to the mass matched control sample drawn from xcoldgass however the gas masses and fractions in galaxy pairs and their depletion times are consistent with those of nonmergers whose sfrs are similarly elevated we conclude that both external interactions and internal processes may lead to molecular gas enhancement and decreased depletion times
[['we', 'investigate', 'the', 'connection', 'between', 'star', 'formation', 'and', 'molecular', 'gas', 'properties', 'in', 'galaxy', 'mergers', 'at', 'low', 'redshift', 'zleq006', 'the', 'study', 'we', 'present', 'is', 'based', 'on', 'iram', '30m', 'co10', 'observations', 'of', '11', 'galaxies', 'with', 'a', 'close', 'companion', 'selected', 'from', 'the', 'sloan', 'digital', 'sky', 'survey', 'sdss', 'the', 'pairs', 'have', 'mass', 'ratios', 'leq4', 'projected', 'separations', 'r_mathrmp', 'leq30', 'kpc', 'and', 'velocity', 'separations', 'deltavleq300', 'km', 's1', 'and', 'have', 'been', 'selected', 'to', 'exhibit', 'enhanced', 'specific', 'star', 'formation', 'rates', 'ssfr', 'we', 'calculate', 'molecular', 'gas', 'h_2', 'masses', 'assigning', 'to', 'each', 'galaxy', 'a', 'physically', 'motivated', 'conversion', 'factor', 'alpha_mathrmco', 'and', 'we', 'derive', 'molecular', 'gas', 'fractions', 'and', 'depletion', 'times', 'we', 'compare', 'these', 'quantities', 'with', 'those', 'of', 'isolated', 'galaxies', 'from', 'the', 'extended', 'co', 'legacy', 'data', 'base', 'for', 'the', 'galex', 'arecibo', 'sdss', 'survey', 'sample', 'xcoldgass', 'saintonge', 'et', 'al', '2017', 'with', 'gas', 'quantities', 'computed', 'in', 'an', 'identical', 'way', 'ours', 'is', 'the', 'first', 'study', 'which', 'directly', 'compares', 'the', 'gas', 'properties', 'of', 'galaxy', 'pairs', 'and', 'those', 'of', 'a', 'control', 'sample', 'of', 'normal', 'galaxies', 'with', 'rigorous', 'control', 'procedures', 'and', 'for', 'which', 'sfr', 'and', 'h_2', 'masses', 'have', 'been', 'estimated', 'using', 'the', 'same', 'method', 'we', 'find', 'that', 'the', 'galaxy', 'pairs', 'have', 'shorter', 'depletion', 'times', 'and', 'an', 'average', 'molecular', 'gas', 'fraction', 'enhancement', 'of', '04', 'dex', 'compared', 'to', 'the', 'mass', 'matched', 'control', 'sample', 'drawn', 'from', 'xcoldgass', 'however', 'the', 'gas', 'masses', 'and', 'fractions', 'in', 'galaxy', 'pairs', 'and', 'their', 'depletion', 'times', 'are', 'consistent', 'with', 'those', 'of', 'nonmergers', 'whose', 'sfrs', 'are', 'similarly', 'elevated', 'we', 'conclude', 'that', 'both', 'external', 'interactions', 'and', 'internal', 'processes', 'may', 'lead', 'to', 'molecular', 'gas', 'enhancement', 'and', 'decreased', 'depletion', 'times']]
[-0.062328075218769444, 0.07325047359108607, -0.02689465078924794, 0.07061996148734395, -0.039233374099894865, -0.03334075711938694, 0.05585935216257157, 0.45740726882967436, -0.12230324382901406, -0.34815141321025755, 0.03850664510037137, -0.31084875393957817, 0.003841661678535151, 0.18827717795435323, 0.007461861670860415, -0.02602901268144878, 0.024907920011817457, -0.13334993735231734, -0.09503360723624142, -0.30519853385908857, 0.27831429117953277, 0.06037682512537442, 0.20493030622064945, -0.04195095184680703, 0.07472564507546019, -0.13900194936187615, -0.10664744800293949, -0.044718619573999335, -0.2207854969272847, 0.037202263328557215, 0.2357543648475467, 0.10068468372874084, 0.2026858616135478, -0.35211020722986347, -0.1538979876422373, 0.08523176649610278, 0.20375676918487398, 0.08681824259841317, -0.08142368850986179, -0.2844136948266101, 0.06619874182647792, -0.2110877160094065, -0.1493043823995524, 0.058791331463941825, 0.04610273259271925, 0.08826349691464853, -0.22481763177290712, 0.19680373259693568, -0.037413911173434414, 0.10677793576600558, -0.09685905509218266, -0.13174422110484552, -0.09882374108125122, 0.0860324751972815, -0.02738233543970764, 0.09843534529649886, 0.254374104144158, -0.12190832605550962, -0.012108547176107948, 0.3911069761003548, -0.06810702268635939, -0.00923663855304198, 0.2742149086004131, -0.2010094975106947, -0.16073972375588222, 0.15361023975206622, 0.1771066747888455, 0.09244807119243643, -0.18935336552774956, -0.018762298236977608, -0.039778017779091686, 0.22260147318677065, 0.06873649360282431, 0.08983369086278122, 0.3130928599773887, 0.07812479088718163, 0.03015516115996389, 0.07771728735286819, -0.20683266674149245, -0.059777719928037924, -0.172431847402527, -0.10221742862527002, -0.12398382270835157, 0.10152257366561994, -0.09229724124617014, -0.042447165186146135, 0.2680076607043085, 0.11417321777772474, 0.28992971409411156, 0.10520324580957768, 0.3038616432777679, 0.08972487556259436, 0.12047443471929449, 0.0937741094495461, 0.26265848940813247, 0.1848251788719814, 0.037029841013632166, -0.25887461441929294, 0.04120922663513525, 0.013532986758092854]
1,802.02167
Valley Stoner Instability of the Composite Fermi Sea
We study two-component electrons in the lowest Landau level at total filling factor $\nu _T=1/2$ with anisotropic mass tensors and principal axes rotated by $\pi/2$ as realized in Aluminum Arsenide (AlAs) quantum wells. Combining exact diagonalization and the density matrix renormalization group we demonstrate that the system undergoes a quantum phase transition from a gapless state in which both flavors are equally populated to another gapless state in which all the electrons spontaneously polarize into a single flavor beyond a critical mass anisotropy of {\bf $m_x/m_y \sim 7$}. We propose that this phase transition is a form of itinerant Stoner transition between a two-component and a single-component composite fermi sea states and describe a set of trial wavefunctions which successfully capture the quantum numbers and shell filling effects in finite size systems as well as providing a physical picture for the energetics of these states. Our estimates indicate that the composite Fermi sea of AlAs is the analog of an itinerant Stoner magnet with a finite spontaneous valley polarization. We pinpoint experimental evidence indicating the presence of Stoner magnetism in the Jain states surrounding $\nu=1/2$.
cond-mat.str-el
we study twocomponent electrons in the lowest landau level at total filling factor nu _t12 with anisotropic mass tensors and principal axes rotated by pi2 as realized in aluminum arsenide alas quantum wells combining exact diagonalization and the density matrix renormalization group we demonstrate that the system undergoes a quantum phase transition from a gapless state in which both flavors are equally populated to another gapless state in which all the electrons spontaneously polarize into a single flavor beyond a critical mass anisotropy of bf m_xm_y sim 7 we propose that this phase transition is a form of itinerant stoner transition between a twocomponent and a singlecomponent composite fermi sea states and describe a set of trial wavefunctions which successfully capture the quantum numbers and shell filling effects in finite size systems as well as providing a physical picture for the energetics of these states our estimates indicate that the composite fermi sea of alas is the analog of an itinerant stoner magnet with a finite spontaneous valley polarization we pinpoint experimental evidence indicating the presence of stoner magnetism in the jain states surrounding nu12
[['we', 'study', 'twocomponent', 'electrons', 'in', 'the', 'lowest', 'landau', 'level', 'at', 'total', 'filling', 'factor', 'nu', '_t12', 'with', 'anisotropic', 'mass', 'tensors', 'and', 'principal', 'axes', 'rotated', 'by', 'pi2', 'as', 'realized', 'in', 'aluminum', 'arsenide', 'alas', 'quantum', 'wells', 'combining', 'exact', 'diagonalization', 'and', 'the', 'density', 'matrix', 'renormalization', 'group', 'we', 'demonstrate', 'that', 'the', 'system', 'undergoes', 'a', 'quantum', 'phase', 'transition', 'from', 'a', 'gapless', 'state', 'in', 'which', 'both', 'flavors', 'are', 'equally', 'populated', 'to', 'another', 'gapless', 'state', 'in', 'which', 'all', 'the', 'electrons', 'spontaneously', 'polarize', 'into', 'a', 'single', 'flavor', 'beyond', 'a', 'critical', 'mass', 'anisotropy', 'of', 'bf', 'm_xm_y', 'sim', '7', 'we', 'propose', 'that', 'this', 'phase', 'transition', 'is', 'a', 'form', 'of', 'itinerant', 'stoner', 'transition', 'between', 'a', 'twocomponent', 'and', 'a', 'singlecomponent', 'composite', 'fermi', 'sea', 'states', 'and', 'describe', 'a', 'set', 'of', 'trial', 'wavefunctions', 'which', 'successfully', 'capture', 'the', 'quantum', 'numbers', 'and', 'shell', 'filling', 'effects', 'in', 'finite', 'size', 'systems', 'as', 'well', 'as', 'providing', 'a', 'physical', 'picture', 'for', 'the', 'energetics', 'of', 'these', 'states', 'our', 'estimates', 'indicate', 'that', 'the', 'composite', 'fermi', 'sea', 'of', 'alas', 'is', 'the', 'analog', 'of', 'an', 'itinerant', 'stoner', 'magnet', 'with', 'a', 'finite', 'spontaneous', 'valley', 'polarization', 'we', 'pinpoint', 'experimental', 'evidence', 'indicating', 'the', 'presence', 'of', 'stoner', 'magnetism', 'in', 'the', 'jain', 'states', 'surrounding', 'nu12']]
[-0.17224931755639694, 0.26813016242783266, -0.04060702598919464, 0.08175384996486726, 0.014897438330555578, -0.15817318062308122, 0.11531707635731436, 0.3180324611869013, -0.20193999448953115, -0.29379715718855354, 0.003304071652287941, -0.3148258152903746, -0.10061666369438171, 0.1077881544074246, 0.06960238193657817, 0.005321551056113094, -0.03065980827238451, -0.05240316662314834, -0.14550965751202413, -0.1676065354208138, 0.2857361516558424, 0.0054896427546222894, 0.29921803696323995, 0.06340464734682388, 0.04687820342255493, -0.0021865913910875424, 0.1429253795902933, -0.009776537161403963, -0.08856350021956726, 0.025987522416234362, 0.25689746678361425, -0.060695412673774866, 0.20609649935700555, -0.41181257377257163, -0.17798233775386546, 0.01212233639291852, 0.1618704451323973, 0.13644515668388718, -0.06675519317302489, -0.31942139273514447, -0.003988042357377708, -0.19681990414898357, -0.18150681929926024, -0.08668851585452617, -0.034867072207144585, -0.0658758088209889, -0.2393394626079775, 0.14490025403970125, 0.04302302213529955, 0.05294918742172582, -0.083926335761688, -0.14021271043241976, -0.08014026255746697, 0.06782026669015581, 0.01761482009612297, 0.06297859533024956, 0.13964214851781118, -0.13788781204493716, -0.12415825622092994, 0.38950462659324886, -0.04395758309376264, -0.14799414086661747, 0.15887151527947382, -0.19856447828098442, -0.09422653332433623, 0.17395719213780705, 0.12565708337870488, 0.031500077333159585, -0.09153754025717954, 0.07723778877223832, -0.07447160803016943, 0.1989817354251104, 0.0012484547763091066, 0.0607349282179949, 0.2916302729661212, 0.16351268619030673, 0.025276907765225547, 0.14958407227759776, -0.1166702041439788, -0.11652623469759103, -0.28354313023611094, -0.1826156793021769, -0.24428928392855753, 0.09547352230520514, -0.04120170931626332, -0.19995777297046277, 0.4209098100760931, 0.09587752478641366, 0.2014839724465476, -0.03388653640602412, 0.22231776496324607, 0.10619612981170813, 0.04277856137638952, 0.0943905673237801, 0.23186541772599373, 0.1520461046058462, 0.03562493241422445, -0.27758713060883683, -0.017419297886827615, 0.055514022909135194]
1,802.02168
Signals of the electroweak phase transition at colliders and gravitational wave observatories
If the electroweak phase transition (EWPT) is of strongly first order due to higher dimensional operators, the scale of new physics generating them is at the TeV scale or below. In this case the effective-field theory (EFT) neglecting operators of dimension higher than six may overlook terms that are relevant for the EWPT analysis. In this article we study the EWPT in the EFT to dimension eight. We estimate the reach of the future gravitational wave observatory LISA for probing the region in which the EWPT is strongly first order and compare it with the capabilities of the Higgs measurements via double-Higgs production at current and future colliders. We also match different UV models to the previously mentioned dimension-eight EFT and demonstrate that, from the top-down point of view, the double-Higgs production is not the best signal to explore these scenarios.
hep-ph
if the electroweak phase transition ewpt is of strongly first order due to higher dimensional operators the scale of new physics generating them is at the tev scale or below in this case the effectivefield theory eft neglecting operators of dimension higher than six may overlook terms that are relevant for the ewpt analysis in this article we study the ewpt in the eft to dimension eight we estimate the reach of the future gravitational wave observatory lisa for probing the region in which the ewpt is strongly first order and compare it with the capabilities of the higgs measurements via doublehiggs production at current and future colliders we also match different uv models to the previously mentioned dimensioneight eft and demonstrate that from the topdown point of view the doublehiggs production is not the best signal to explore these scenarios
[['if', 'the', 'electroweak', 'phase', 'transition', 'ewpt', 'is', 'of', 'strongly', 'first', 'order', 'due', 'to', 'higher', 'dimensional', 'operators', 'the', 'scale', 'of', 'new', 'physics', 'generating', 'them', 'is', 'at', 'the', 'tev', 'scale', 'or', 'below', 'in', 'this', 'case', 'the', 'effectivefield', 'theory', 'eft', 'neglecting', 'operators', 'of', 'dimension', 'higher', 'than', 'six', 'may', 'overlook', 'terms', 'that', 'are', 'relevant', 'for', 'the', 'ewpt', 'analysis', 'in', 'this', 'article', 'we', 'study', 'the', 'ewpt', 'in', 'the', 'eft', 'to', 'dimension', 'eight', 'we', 'estimate', 'the', 'reach', 'of', 'the', 'future', 'gravitational', 'wave', 'observatory', 'lisa', 'for', 'probing', 'the', 'region', 'in', 'which', 'the', 'ewpt', 'is', 'strongly', 'first', 'order', 'and', 'compare', 'it', 'with', 'the', 'capabilities', 'of', 'the', 'higgs', 'measurements', 'via', 'doublehiggs', 'production', 'at', 'current', 'and', 'future', 'colliders', 'we', 'also', 'match', 'different', 'uv', 'models', 'to', 'the', 'previously', 'mentioned', 'dimensioneight', 'eft', 'and', 'demonstrate', 'that', 'from', 'the', 'topdown', 'point', 'of', 'view', 'the', 'doublehiggs', 'production', 'is', 'not', 'the', 'best', 'signal', 'to', 'explore', 'these', 'scenarios']]
[-0.08195022984361607, 0.17647249815021213, -0.031304550405050105, 0.12171801969785481, -0.0720984606990419, -0.08356126135954937, 0.006798769732943822, 0.31895474459421125, -0.2209405467832289, -0.2892616330877158, 0.0923272039120396, -0.2953707735642051, -0.09903928070826165, 0.1707562031141806, 0.0629133482821573, 0.03213769769137527, 0.0011597210475316284, 0.04541971610449519, -0.07489285960212244, -0.2577415081434586, 0.339109724466788, 0.09953697534700763, 0.22035548796362064, 0.08934790843846739, 0.037704727893153614, -0.024459067599993226, -0.02694790030529075, -0.03321530548063047, -0.12339135490249305, 0.1102762874554354, 0.25947430912283576, 0.09425605277709187, 0.17691634086799538, -0.388175585472309, -0.20299834738227915, 0.13588960127779515, 0.1324335322451137, 0.13587679969169966, 0.000994313386077365, -0.3068919825476614, 0.10201227220009801, -0.1832651408613785, -0.12215886792788903, -0.08063779086706803, -0.044968839282341674, -0.06640359167016197, -0.2906344816293435, 0.047209762566655225, -0.011346514373092998, 0.02130652013967963, -0.039662376634036815, -0.09699197343062668, -0.024654340794878014, 0.06238715217864894, 0.08477062095577519, 0.054853566190729855, 0.13626408984501523, -0.18653949570466627, -0.14983989288435973, 0.4027903810050999, -0.08118557280760526, -0.10753467251796024, 0.20231544674235455, -0.2541846756935648, -0.17394466456422147, 0.11319551378874941, 0.18972998129448304, 0.11245123862044502, -0.1518163191260281, 0.12722874598136727, 0.03374653963666452, 0.1661283036585359, 0.061589702058926964, 0.06261993518696952, 0.22860872575762212, 0.19062036897405876, 0.06941122072253456, 0.07228307892297599, -0.08247000675550199, -0.09203093047980351, -0.4139227661310781, -0.10559914825180321, -0.10114085923299088, -0.014873026522183593, -0.08763825926066506, -0.0841981127811926, 0.4069846946224306, 0.2522898204645294, 0.19481249293642686, 0.022281751820176894, 0.3163823549270775, 0.1328128822022349, 0.07615148174041446, 0.01128088177267647, 0.3437342662232142, 0.07999310734952596, 0.1060710175273319, -0.20313378106901778, 0.017679652487297696, 0.09355960943214331]
1,802.02169
The New Numerical Galaxy Catalogue (\nu^2 GC): Properties of Active Galactic Nuclei and Their Host Galaxies
We present the latest results of a semi-analytic model of galaxy formation, "New Numerical Galaxy Catalogue", which is combined with large cosmological N-body simulations. This model can reproduce statistical properties of galaxies at z < 6.0. We focus on the properties of active galactic nuclei (AGNs) and supermassive black holes, especially on the accretion timescale onto black holes. We find that the number density of AGNs at z < 1.5 and at hard X-ray luminosity 10^{ 44 }< erg/s is underestimated compared with recent observational estimates when we assume the exponentially decreasing accretion rate and the accretion timescale which is proportional to the dynamical time of the host halo or the bulge, as is often assumed in semi-analytic models. We show that to solve this discrepancy, the accretion timescale of such less luminous AGNs instead should be a function of the black hole mass and the accreted gas mass. This timescale can be obtained from a phenomenological modelling of the gas angular momentum loss in the circumnuclear torus and/or the accretion disc. Such models predict a longer accretion timescale for less luminous AGNs at z < 1.0 than bright QSOs whose accretion timescale would be 10^{ 7-8 } yr. With this newly introduced accretion timescale, our model can explain the observed luminosity functions of AGNs at z < 6.0.
astro-ph.GA
we present the latest results of a semianalytic model of galaxy formation new numerical galaxy catalogue which is combined with large cosmological nbody simulations this model can reproduce statistical properties of galaxies at z 60 we focus on the properties of active galactic nuclei agns and supermassive black holes especially on the accretion timescale onto black holes we find that the number density of agns at z 15 and at hard xray luminosity 10 44 ergs is underestimated compared with recent observational estimates when we assume the exponentially decreasing accretion rate and the accretion timescale which is proportional to the dynamical time of the host halo or the bulge as is often assumed in semianalytic models we show that to solve this discrepancy the accretion timescale of such less luminous agns instead should be a function of the black hole mass and the accreted gas mass this timescale can be obtained from a phenomenological modelling of the gas angular momentum loss in the circumnuclear torus andor the accretion disc such models predict a longer accretion timescale for less luminous agns at z 10 than bright qsos whose accretion timescale would be 10 78 yr with this newly introduced accretion timescale our model can explain the observed luminosity functions of agns at z 60
[['we', 'present', 'the', 'latest', 'results', 'of', 'a', 'semianalytic', 'model', 'of', 'galaxy', 'formation', 'new', 'numerical', 'galaxy', 'catalogue', 'which', 'is', 'combined', 'with', 'large', 'cosmological', 'nbody', 'simulations', 'this', 'model', 'can', 'reproduce', 'statistical', 'properties', 'of', 'galaxies', 'at', 'z', '60', 'we', 'focus', 'on', 'the', 'properties', 'of', 'active', 'galactic', 'nuclei', 'agns', 'and', 'supermassive', 'black', 'holes', 'especially', 'on', 'the', 'accretion', 'timescale', 'onto', 'black', 'holes', 'we', 'find', 'that', 'the', 'number', 'density', 'of', 'agns', 'at', 'z', '15', 'and', 'at', 'hard', 'xray', 'luminosity', '10', '44', 'ergs', 'is', 'underestimated', 'compared', 'with', 'recent', 'observational', 'estimates', 'when', 'we', 'assume', 'the', 'exponentially', 'decreasing', 'accretion', 'rate', 'and', 'the', 'accretion', 'timescale', 'which', 'is', 'proportional', 'to', 'the', 'dynamical', 'time', 'of', 'the', 'host', 'halo', 'or', 'the', 'bulge', 'as', 'is', 'often', 'assumed', 'in', 'semianalytic', 'models', 'we', 'show', 'that', 'to', 'solve', 'this', 'discrepancy', 'the', 'accretion', 'timescale', 'of', 'such', 'less', 'luminous', 'agns', 'instead', 'should', 'be', 'a', 'function', 'of', 'the', 'black', 'hole', 'mass', 'and', 'the', 'accreted', 'gas', 'mass', 'this', 'timescale', 'can', 'be', 'obtained', 'from', 'a', 'phenomenological', 'modelling', 'of', 'the', 'gas', 'angular', 'momentum', 'loss', 'in', 'the', 'circumnuclear', 'torus', 'andor', 'the', 'accretion', 'disc', 'such', 'models', 'predict', 'a', 'longer', 'accretion', 'timescale', 'for', 'less', 'luminous', 'agns', 'at', 'z', '10', 'than', 'bright', 'qsos', 'whose', 'accretion', 'timescale', 'would', 'be', '10', '78', 'yr', 'with', 'this', 'newly', 'introduced', 'accretion', 'timescale', 'our', 'model', 'can', 'explain', 'the', 'observed', 'luminosity', 'functions', 'of', 'agns', 'at', 'z', '60']]
[-0.048570276391605015, 0.11861763944840627, -0.053487772255383884, 0.16068311357442203, -0.09429901726478317, -0.07230497591313359, 0.028536543391640582, 0.41443376406642474, -0.15633902387877166, -0.3542557693274578, 0.07308126793094329, -0.30207952618939987, 0.03436262052770056, 0.21422663755889654, -0.012381715052640897, -0.00790542519668843, 0.017503467210275535, -0.1069680716789944, -0.07828660842966935, -0.29840005363639394, 0.29957686623934426, 0.11039850692715093, 0.10735217018841062, -0.05313127984603246, 0.0733538475871401, -0.11104678454870856, -0.07171715483585364, -0.05066135513460692, -0.19640401214998743, -0.002963840358064208, 0.22917146814764755, 0.11380104483389449, 0.2528476903101368, -0.385027507153895, -0.22526413754028807, 0.07896244082328789, 0.21297948009076534, 0.059271237730953684, -0.08026664790767354, -0.18384143691335067, 0.07107356644755868, -0.2726002669157548, -0.1483408605392657, 0.07302839122493991, 0.059598644010442806, 0.025230569192186487, -0.21884307670603756, 0.19681011076509392, 0.04336428703309011, 0.014028563684490925, -0.12151489775636597, -0.03926216874396245, -0.09586273156381933, -0.026598777367155168, 0.10612001171512661, 0.11238829739951471, 0.2676949785664861, -0.1258767021430805, -0.046863809352557004, 0.3834686614354382, -0.03996269924145579, -0.02609085811065956, 0.23901365504560756, -0.26319682637465674, -0.15380812304951424, 0.1555053560990193, 0.20088571363168073, 0.1532396198635125, -0.12262629671384385, -0.0036592014700156843, -0.04411593998482827, 0.27327673468616365, -0.011888671911238505, 0.050152252568287266, 0.3826260805532266, 0.1482987709058134, -0.004156485981495937, 0.0700004329820745, -0.18608296574902297, -0.03266182802224033, -0.22275788807681818, -0.05147275463033013, -0.14232546615987107, 0.1748222079119282, -0.18237670667293512, -0.08011497485674393, 0.31812240218551296, 0.0931821628429975, 0.2794035767782217, 0.0919839165470248, 0.2980817591673719, 0.10825411582960279, 0.10513310187890855, 0.15645501674852497, 0.3433839902238037, 0.1357784697779415, 0.06940670655012796, -0.24860524794222358, 0.06269978764827665, 0.04321401576651479]
1,802.0217
Certifying the building blocks of quantum computers from Bell's theorem
The power of quantum computers relies on the capability of their components to maintain faithfully and process accurately quantum information. Since this property eludes classical certification methods, fundamentally new protocols are required to guarantee that elementary components are suitable for quantum computation. These protocols must be device-independent, that is, they cannot rely on a particular physical description of the actual implementation if one is to qualify a block for all possible usages. Bell's theorem has been proposed to certify, in a device-independent way, blocks either producing or measuring quantum states. In this manuscript, we provide the missing piece: a method based on Bell's theorem to certify coherent operations such as storage, processing and transfer of quantum information. This completes the set of tools needed to certify all building blocks of a quantum computer. Our method is robust to experimental imperfections, and so can be readily used to certify that today's quantum devices are qualified for usage in future quantum computers.
quant-ph
the power of quantum computers relies on the capability of their components to maintain faithfully and process accurately quantum information since this property eludes classical certification methods fundamentally new protocols are required to guarantee that elementary components are suitable for quantum computation these protocols must be deviceindependent that is they cannot rely on a particular physical description of the actual implementation if one is to qualify a block for all possible usages bells theorem has been proposed to certify in a deviceindependent way blocks either producing or measuring quantum states in this manuscript we provide the missing piece a method based on bells theorem to certify coherent operations such as storage processing and transfer of quantum information this completes the set of tools needed to certify all building blocks of a quantum computer our method is robust to experimental imperfections and so can be readily used to certify that todays quantum devices are qualified for usage in future quantum computers
[['the', 'power', 'of', 'quantum', 'computers', 'relies', 'on', 'the', 'capability', 'of', 'their', 'components', 'to', 'maintain', 'faithfully', 'and', 'process', 'accurately', 'quantum', 'information', 'since', 'this', 'property', 'eludes', 'classical', 'certification', 'methods', 'fundamentally', 'new', 'protocols', 'are', 'required', 'to', 'guarantee', 'that', 'elementary', 'components', 'are', 'suitable', 'for', 'quantum', 'computation', 'these', 'protocols', 'must', 'be', 'deviceindependent', 'that', 'is', 'they', 'can', 'not', 'rely', 'on', 'a', 'particular', 'physical', 'description', 'of', 'the', 'actual', 'implementation', 'if', 'one', 'is', 'to', 'qualify', 'a', 'block', 'for', 'all', 'possible', 'usages', 'bells', 'theorem', 'has', 'been', 'proposed', 'to', 'certify', 'in', 'a', 'deviceindependent', 'way', 'blocks', 'either', 'producing', 'or', 'measuring', 'quantum', 'states', 'in', 'this', 'manuscript', 'we', 'provide', 'the', 'missing', 'piece', 'a', 'method', 'based', 'on', 'bells', 'theorem', 'to', 'certify', 'coherent', 'operations', 'such', 'as', 'storage', 'processing', 'and', 'transfer', 'of', 'quantum', 'information', 'this', 'completes', 'the', 'set', 'of', 'tools', 'needed', 'to', 'certify', 'all', 'building', 'blocks', 'of', 'a', 'quantum', 'computer', 'our', 'method', 'is', 'robust', 'to', 'experimental', 'imperfections', 'and', 'so', 'can', 'be', 'readily', 'used', 'to', 'certify', 'that', 'todays', 'quantum', 'devices', 'are', 'qualified', 'for', 'usage', 'in', 'future', 'quantum', 'computers']]
[-0.10347543373235403, 0.09086035027006722, -0.13266365219092702, 0.07704480359898976, -0.1005008613577934, -0.217939605765762, 0.04269809771896056, 0.3432780731909023, -0.2744624171411815, -0.2997785999312395, 0.12910707843394498, -0.22864477599606567, -0.11460268831130707, 0.29131050974633893, -0.1310973597561394, 0.15469988600946732, 0.06820111084868263, 0.01880862245857513, -0.012248195150667536, -0.2995342490789683, 0.2579505791944041, 0.03632503990604548, 0.3035617968391465, 0.07571909070356246, 0.06949553770007369, 0.009049911221188511, -0.004457110472555671, -0.03242473576473859, -0.06087127021890421, 0.17014292079011, 0.33696768636473956, 0.20744099001608418, 0.2736783454842541, -0.47534691196467194, -0.17588052624165548, 0.1354321099308707, 0.11513823991289264, 0.19851127132680846, -0.025883758853490448, -0.2808149195397678, 0.13799039126404197, -0.1667994027067936, -0.1167098943689825, -0.16469562046738886, -0.017228915431299566, -0.030203770996528382, -0.24462786891283642, 0.01888540980799459, 0.08078357879859135, 0.020829215234359554, 0.06923964153279287, -0.025157501984688437, 0.060557910381463464, 0.18510752091016505, -0.0870262286294995, -0.02495536857620113, 0.17737725865159484, -0.08991645793112353, -0.20969852267241001, 0.39423644057943585, 0.04586233201824268, -0.21393093994893828, 0.1930575852328622, -0.06197829077292164, -0.15073941793489437, 0.030401327230776688, 0.13338163086742463, 0.07675910975367571, -0.153777194805935, 0.06139406300061643, -0.006932551538722115, 0.2032678895767327, 0.02628990907441848, 0.1672523555588787, 0.2276967367177586, 0.11032110972544004, 0.06859478118071283, 0.0987036789388552, -0.003817098546391411, -0.13222948032299706, -0.31548536934178345, -0.2522582222001847, -0.2675758025606064, 0.09006950684820565, -0.02456671745570229, -0.1647916995249226, 0.36405809577670156, 0.19921588135980103, 0.126311047407596, 0.017302691410093204, 0.3711421384493479, 0.06489439499327661, 0.10905910724548404, 0.09635849109046762, 0.23176602187121045, 0.12546368658554202, 0.075580083004413, -0.14598621714640386, 0.1278978896830578, 0.0319598220217892]
1,802.02171
Model-independent determinations of the electron EDM and the role of diamagnetic atoms
We perform model-independent analyses extracting limits for the electric dipole moment of the electron and the P,T-odd scalar-pseudoscalar (S-PS) nucleon-electron coupling from the most recent measurements with atoms and molecules. The analysis using paramagnetic systems, only, is improved substantially by the inclusion of the recent measurement on HfF+ ions, but complicated by the fact that the corresponding constraints are largely aligned, owing to a general relation between the coefficients for the two contributions. Since this same relation does not hold in diamagnetic systems, it is possible to find atoms that provide essentially orthogonal constraints to those from para\-magnetic ones. However, the coefficients are suppressed in closed-shell systems and enhancements of P,T-odd effects are only prevalent in the presence of hyperfine interactions. We formulate the hyperfine-induced time-reversal-symmetry breaking S-PS nucleon-electron interaction in general atoms in a mixed perturbative and variational approach, based on electronic Dirac-wavefunctions including the effects of electron correlations. The method is applied to the Hg atom, yielding the first direct calculation of the coefficient of the S-PS nucleon-electron coupling in a diamagnetic system. This results in additionally improved model-independent limits for both the electron EDM and the nucleon-electron coupling from the global fit. Finally we employ this fit to provide indirect limits for several paramagnetic systems under investigation.
hep-ph physics.atom-ph
we perform modelindependent analyses extracting limits for the electric dipole moment of the electron and the ptodd scalarpseudoscalar sps nucleonelectron coupling from the most recent measurements with atoms and molecules the analysis using paramagnetic systems only is improved substantially by the inclusion of the recent measurement on hff ions but complicated by the fact that the corresponding constraints are largely aligned owing to a general relation between the coefficients for the two contributions since this same relation does not hold in diamagnetic systems it is possible to find atoms that provide essentially orthogonal constraints to those from paramagnetic ones however the coefficients are suppressed in closedshell systems and enhancements of ptodd effects are only prevalent in the presence of hyperfine interactions we formulate the hyperfineinduced timereversalsymmetry breaking sps nucleonelectron interaction in general atoms in a mixed perturbative and variational approach based on electronic diracwavefunctions including the effects of electron correlations the method is applied to the hg atom yielding the first direct calculation of the coefficient of the sps nucleonelectron coupling in a diamagnetic system this results in additionally improved modelindependent limits for both the electron edm and the nucleonelectron coupling from the global fit finally we employ this fit to provide indirect limits for several paramagnetic systems under investigation
[['we', 'perform', 'modelindependent', 'analyses', 'extracting', 'limits', 'for', 'the', 'electric', 'dipole', 'moment', 'of', 'the', 'electron', 'and', 'the', 'ptodd', 'scalarpseudoscalar', 'sps', 'nucleonelectron', 'coupling', 'from', 'the', 'most', 'recent', 'measurements', 'with', 'atoms', 'and', 'molecules', 'the', 'analysis', 'using', 'paramagnetic', 'systems', 'only', 'is', 'improved', 'substantially', 'by', 'the', 'inclusion', 'of', 'the', 'recent', 'measurement', 'on', 'hff', 'ions', 'but', 'complicated', 'by', 'the', 'fact', 'that', 'the', 'corresponding', 'constraints', 'are', 'largely', 'aligned', 'owing', 'to', 'a', 'general', 'relation', 'between', 'the', 'coefficients', 'for', 'the', 'two', 'contributions', 'since', 'this', 'same', 'relation', 'does', 'not', 'hold', 'in', 'diamagnetic', 'systems', 'it', 'is', 'possible', 'to', 'find', 'atoms', 'that', 'provide', 'essentially', 'orthogonal', 'constraints', 'to', 'those', 'from', 'paramagnetic', 'ones', 'however', 'the', 'coefficients', 'are', 'suppressed', 'in', 'closedshell', 'systems', 'and', 'enhancements', 'of', 'ptodd', 'effects', 'are', 'only', 'prevalent', 'in', 'the', 'presence', 'of', 'hyperfine', 'interactions', 'we', 'formulate', 'the', 'hyperfineinduced', 'timereversalsymmetry', 'breaking', 'sps', 'nucleonelectron', 'interaction', 'in', 'general', 'atoms', 'in', 'a', 'mixed', 'perturbative', 'and', 'variational', 'approach', 'based', 'on', 'electronic', 'diracwavefunctions', 'including', 'the', 'effects', 'of', 'electron', 'correlations', 'the', 'method', 'is', 'applied', 'to', 'the', 'hg', 'atom', 'yielding', 'the', 'first', 'direct', 'calculation', 'of', 'the', 'coefficient', 'of', 'the', 'sps', 'nucleonelectron', 'coupling', 'in', 'a', 'diamagnetic', 'system', 'this', 'results', 'in', 'additionally', 'improved', 'modelindependent', 'limits', 'for', 'both', 'the', 'electron', 'edm', 'and', 'the', 'nucleonelectron', 'coupling', 'from', 'the', 'global', 'fit', 'finally', 'we', 'employ', 'this', 'fit', 'to', 'provide', 'indirect', 'limits', 'for', 'several', 'paramagnetic', 'systems', 'under', 'investigation']]
[-0.10075085633434355, 0.14887101678166575, -0.03585157726705297, 0.07523141442642114, -0.0320808309348719, -0.1220206996564125, 0.06547568246647582, 0.3421700450114942, -0.2214899063138202, -0.289267561068696, 0.020906585211304136, -0.31151946127619684, -0.06519650936607967, 0.19376869580338588, 0.07135707842137076, 0.010274732096619797, 0.0393326007248611, -0.017889852609661402, -0.10395100051130537, -0.19875870313123314, 0.3003725864251621, 0.046680151841393784, 0.2869097603569654, 0.13479887151897943, 0.04549940309874963, 0.03174737593132343, 0.01958444841767541, 0.011690976796114737, -0.10045589520920427, 0.15072164112595066, 0.21501004399701676, 0.0257189456467031, 0.15668123397913775, -0.4449375857861989, -0.15493750914432217, 0.06866946805526979, 0.12333268261153661, 0.1731741094034896, -0.05446412829731248, -0.29072024822948084, 0.006272996383670129, -0.1596372112738744, -0.08549633080309088, -0.11513288875230762, -0.0132770375771956, 0.02074096731687829, -0.3348091410464077, 0.11068985957884048, 0.053474945620005356, 0.0556497937696025, -0.08581899014707102, -0.1511252747049876, 0.02548491903614146, 0.08201848225373971, 0.06827985423251666, 0.023291442357226494, 0.13899987409532996, -0.11451444581360445, -0.10107705033602613, 0.41313734628331433, -0.08792010090970011, -0.1577810229316942, 0.1855622458599762, -0.1838470381480178, -0.16126399177113218, 0.1220844488704586, 0.16200581529961997, 0.09791925618367639, -0.17538409099499716, 0.1052982639707959, -0.016713481262754026, 0.16438557154111313, 0.0272162871203568, 0.07179099818052162, 0.18587904214930306, 0.1235361018521114, 0.05024834596841601, 0.09239321725964368, -0.07742500892571846, -0.07914184957200163, -0.25861717445963023, -0.09611999415725683, -0.16016898064040824, 0.013907558970450219, -0.037702572200089164, -0.10710715515701698, 0.3520377662487364, 0.16955911921800682, 0.17622008260548935, -0.022494085371476468, 0.3199584489870977, 0.11993527794802677, 0.0814306482006506, 0.0038481712782461393, 0.35309723024056006, 0.17260841462698778, 0.07532171216240803, -0.2880640826388552, 0.08160673614934479, 0.026445199224126466]
1,802.02172
Augmented Artificial Intelligence: a Conceptual Framework
All artificial Intelligence (AI) systems make errors. These errors are unexpected, and differ often from the typical human mistakes ("non-human" errors). The AI errors should be corrected without damage of existing skills and, hopefully, avoiding direct human expertise. This paper presents an initial summary report of project taking new and systematic approach to improving the intellectual effectiveness of the individual AI by communities of AIs. We combine some ideas of learning in heterogeneous multiagent systems with new and original mathematical approaches for non-iterative corrections of errors of legacy AI systems. The mathematical foundations of AI non-destructive correction are presented and a series of new stochastic separation theorems is proven. These theorems provide a new instrument for the development, analysis, and assessment of machine learning methods and algorithms in high dimension. They demonstrate that in high dimensions and even for exponentially large samples, linear classifiers in their classical Fisher's form are powerful enough to separate errors from correct responses with high probability and to provide efficient solution to the non-destructive corrector problem. In particular, we prove some hypotheses formulated in our paper `Stochastic Separation Theorems' (Neural Networks, 94, 255--259, 2017), and answer one general problem published by Donoho and Tanner in 2009.
cs.AI
all artificial intelligence ai systems make errors these errors are unexpected and differ often from the typical human mistakes nonhuman errors the ai errors should be corrected without damage of existing skills and hopefully avoiding direct human expertise this paper presents an initial summary report of project taking new and systematic approach to improving the intellectual effectiveness of the individual ai by communities of ais we combine some ideas of learning in heterogeneous multiagent systems with new and original mathematical approaches for noniterative corrections of errors of legacy ai systems the mathematical foundations of ai nondestructive correction are presented and a series of new stochastic separation theorems is proven these theorems provide a new instrument for the development analysis and assessment of machine learning methods and algorithms in high dimension they demonstrate that in high dimensions and even for exponentially large samples linear classifiers in their classical fishers form are powerful enough to separate errors from correct responses with high probability and to provide efficient solution to the nondestructive corrector problem in particular we prove some hypotheses formulated in our paper stochastic separation theorems neural networks 94 255259 2017 and answer one general problem published by donoho and tanner in 2009
[['all', 'artificial', 'intelligence', 'ai', 'systems', 'make', 'errors', 'these', 'errors', 'are', 'unexpected', 'and', 'differ', 'often', 'from', 'the', 'typical', 'human', 'mistakes', 'nonhuman', 'errors', 'the', 'ai', 'errors', 'should', 'be', 'corrected', 'without', 'damage', 'of', 'existing', 'skills', 'and', 'hopefully', 'avoiding', 'direct', 'human', 'expertise', 'this', 'paper', 'presents', 'an', 'initial', 'summary', 'report', 'of', 'project', 'taking', 'new', 'and', 'systematic', 'approach', 'to', 'improving', 'the', 'intellectual', 'effectiveness', 'of', 'the', 'individual', 'ai', 'by', 'communities', 'of', 'ais', 'we', 'combine', 'some', 'ideas', 'of', 'learning', 'in', 'heterogeneous', 'multiagent', 'systems', 'with', 'new', 'and', 'original', 'mathematical', 'approaches', 'for', 'noniterative', 'corrections', 'of', 'errors', 'of', 'legacy', 'ai', 'systems', 'the', 'mathematical', 'foundations', 'of', 'ai', 'nondestructive', 'correction', 'are', 'presented', 'and', 'a', 'series', 'of', 'new', 'stochastic', 'separation', 'theorems', 'is', 'proven', 'these', 'theorems', 'provide', 'a', 'new', 'instrument', 'for', 'the', 'development', 'analysis', 'and', 'assessment', 'of', 'machine', 'learning', 'methods', 'and', 'algorithms', 'in', 'high', 'dimension', 'they', 'demonstrate', 'that', 'in', 'high', 'dimensions', 'and', 'even', 'for', 'exponentially', 'large', 'samples', 'linear', 'classifiers', 'in', 'their', 'classical', 'fishers', 'form', 'are', 'powerful', 'enough', 'to', 'separate', 'errors', 'from', 'correct', 'responses', 'with', 'high', 'probability', 'and', 'to', 'provide', 'efficient', 'solution', 'to', 'the', 'nondestructive', 'corrector', 'problem', 'in', 'particular', 'we', 'prove', 'some', 'hypotheses', 'formulated', 'in', 'our', 'paper', 'stochastic', 'separation', 'theorems', 'neural', 'networks', '94', '255259', '2017', 'and', 'answer', 'one', 'general', 'problem', 'published', 'by', 'donoho', 'and', 'tanner', 'in', '2009']]
[-0.06522202539257706, 0.04025073964447074, -0.07961091629229486, 0.10128511114744469, -0.09924142212606966, -0.17916056805835978, 0.056288840719498696, 0.35528622919344344, -0.25161721964366734, -0.35470518182497474, 0.10556535728275776, -0.263876164695248, -0.191214813341212, 0.2129154196148738, -0.17856526762712746, 0.1239873110537883, 0.12080209648585878, -0.03093184264114825, -0.033971731835626996, -0.29809922747372186, 0.27756618222396356, 0.047969082437921313, 0.2872245660191402, 0.01043984796386212, 0.08751106790266931, 0.002445547871757299, -0.07938492597313598, 0.014684386071749031, -0.09560408453999117, 0.18665578913060016, 0.3441895036282949, 0.20629301555454732, 0.37011717457324267, -0.442836003722623, -0.17753163389861584, 0.06581330713583157, 0.13235132080240875, 0.1520228643110022, -0.028935313493711874, -0.3224566199164838, 0.08399610465392471, -0.1504103989514988, -0.092027819941286, -0.14149783357512205, 0.022216537368949504, 0.029769495564105453, -0.26136741948546843, 0.04904779691016301, 0.10299295792647171, 0.13261810443829744, -0.03189276709919795, -0.17638459901500028, 0.09665388825698756, 0.1609413043729728, 0.038447998354563424, 0.016318272842327133, 0.1252945985092083, -0.1401860767288599, -0.17142195861204526, 0.3408273075777106, 0.004530639424920082, -0.17152803400706035, 0.20035042309056736, -0.06018054653366562, -0.18688744761166162, 0.10548622339731083, 0.22733847049996256, 0.08124805761734023, -0.1820053251227364, 0.05012673144839937, 0.057497564039658756, 0.16143451187293978, 0.04333855436590966, 0.023774217845930253, 0.17729230852797628, 0.16981245138653323, 0.05030365152517333, 0.0820817353198072, -0.04425720511004329, -0.07404548956081271, -0.2532439330872148, -0.13420256211888046, -0.12729585530410986, 0.022263301233178937, -0.07881374343785864, -0.16577239139936864, 0.33623737495276146, 0.2165976822664379, 0.11670740851783194, 0.09432349088718184, 0.31604773307939465, 0.0610878224222688, 0.03147391109581804, 0.05799095070804469, 0.2403821626669378, 0.09118877800763585, 0.13890323668078053, -0.15876987474039198, 0.0781561875261832, 0.03130397247383371]
1,802.02173
Coercivity, hypocoercivity, exponential time decay and simulations for discrete Fokker-Planck equations
In this article, we propose and study several discrete versions of homogeneous and inhomogeneous one-dimensional Fokker-Planck equations. In particular, for these discretizations of velocity and space, we prove the exponential convergence to the equilibrium of the solutions, for time-continuous equations as well as for time-discrete equations. Our method uses new types of discrete Poincar\'e inequalities for a "two-direction" discretization of the derivative in velocity. For the inhomogeneous problem, we adapt hypocoercive methods to the discrete cases.
math.NA
in this article we propose and study several discrete versions of homogeneous and inhomogeneous onedimensional fokkerplanck equations in particular for these discretizations of velocity and space we prove the exponential convergence to the equilibrium of the solutions for timecontinuous equations as well as for timediscrete equations our method uses new types of discrete poincare inequalities for a twodirection discretization of the derivative in velocity for the inhomogeneous problem we adapt hypocoercive methods to the discrete cases
[['in', 'this', 'article', 'we', 'propose', 'and', 'study', 'several', 'discrete', 'versions', 'of', 'homogeneous', 'and', 'inhomogeneous', 'onedimensional', 'fokkerplanck', 'equations', 'in', 'particular', 'for', 'these', 'discretizations', 'of', 'velocity', 'and', 'space', 'we', 'prove', 'the', 'exponential', 'convergence', 'to', 'the', 'equilibrium', 'of', 'the', 'solutions', 'for', 'timecontinuous', 'equations', 'as', 'well', 'as', 'for', 'timediscrete', 'equations', 'our', 'method', 'uses', 'new', 'types', 'of', 'discrete', 'poincare', 'inequalities', 'for', 'a', 'twodirection', 'discretization', 'of', 'the', 'derivative', 'in', 'velocity', 'for', 'the', 'inhomogeneous', 'problem', 'we', 'adapt', 'hypocoercive', 'methods', 'to', 'the', 'discrete', 'cases']]
[-0.05795271967929837, 0.044380815984607726, -0.10739303292786262, 0.08000710942800843, -0.06285689349629377, -0.10412673125852291, -0.01868890967575441, 0.3336896828228706, -0.31145125574211735, -0.2327184086714528, 0.14322452856944629, -0.21269601486672304, -0.12848277291969248, 0.199007545683631, -0.06776879633482742, 0.1452332268848917, 0.024500354720083505, -0.02592919742394435, -0.12778901491975903, -0.2312695391010493, 0.3519563951259969, -0.06439166712133508, 0.237344260027289, -0.006257176619807356, 0.17703441417114318, -0.006174976998744042, -0.05009706819270689, 0.02225265190394279, -0.1949510454096047, 0.11564127507613432, 0.2269651684419889, 0.04618905132673191, 0.30278713469344537, -0.4187903701768894, -0.22974214169784987, 0.11486390822469011, 0.17608580947470678, 0.14660415478589894, -0.02433781475625246, -0.3187548961416867, 0.04479280475674099, -0.13997953365507879, -0.22920679059614868, -0.11835193962446953, 0.00015567621755364694, 0.1373503290478287, -0.30296368442328747, 0.1658041683871201, 0.08259585604920223, 0.03763516412245257, -0.157409980188516, -0.05595024786644468, 0.013677919669517953, 0.05171014497816367, 0.03631435330699835, -0.07737230461421668, -0.007862139456464272, -0.0795224173527554, -0.12190017796513673, 0.3898788238875568, -0.12263429867054679, -0.3163884637485209, 0.1819658386643584, -0.08517294108720594, -0.1827203161940959, 0.06597404457187095, 0.22855966375822104, 0.1837078114897993, -0.14097041995754758, 0.10812721703290376, -0.048480829211736194, 0.07351726883873773, 0.06141470158227572, 0.015855889252730106, 0.04639100440238651, 0.11733937996292584, 0.1453545947090453, 0.15569633015088344, -0.04528795626155395, -0.18672170564164653, -0.35715727331606967, -0.20957812212566895, -0.13709164787034847, 0.046475427311011834, -0.12884086719656662, -0.2176204601602972, 0.3874145483438808, 0.1486061521511721, 0.11449276669392068, 0.12241376002662276, 0.26118731577145426, 0.19646198115476995, -0.03498931111473786, 0.08738017124979754, 0.1553998097140146, 0.18670573644340038, 0.16472181063574298, -0.21966924007344796, -4.270168535999561e-05, 0.19705165912225647]
1,802.02174
A fluid-kinetic framework for self-consistent runaway-electron simulations
The problem of self-consistently coupling kinetic runaway-electron physics to the macroscopic evolution of the plasma is addressed by dividing the electron population into a bulk and a tail. A probabilistic closure is adopted to determine the coupling between the bulk and the tail populations, preserving them both as genuine, non-negative distribution functions. Macroscopic one-fluid equations and the kinetic equation for the runaway-electron population are then derived, now displaying sink and source terms due to transfer of electrons between the bulk and the tail.
physics.plasm-ph
the problem of selfconsistently coupling kinetic runawayelectron physics to the macroscopic evolution of the plasma is addressed by dividing the electron population into a bulk and a tail a probabilistic closure is adopted to determine the coupling between the bulk and the tail populations preserving them both as genuine nonnegative distribution functions macroscopic onefluid equations and the kinetic equation for the runawayelectron population are then derived now displaying sink and source terms due to transfer of electrons between the bulk and the tail
[['the', 'problem', 'of', 'selfconsistently', 'coupling', 'kinetic', 'runawayelectron', 'physics', 'to', 'the', 'macroscopic', 'evolution', 'of', 'the', 'plasma', 'is', 'addressed', 'by', 'dividing', 'the', 'electron', 'population', 'into', 'a', 'bulk', 'and', 'a', 'tail', 'a', 'probabilistic', 'closure', 'is', 'adopted', 'to', 'determine', 'the', 'coupling', 'between', 'the', 'bulk', 'and', 'the', 'tail', 'populations', 'preserving', 'them', 'both', 'as', 'genuine', 'nonnegative', 'distribution', 'functions', 'macroscopic', 'onefluid', 'equations', 'and', 'the', 'kinetic', 'equation', 'for', 'the', 'runawayelectron', 'population', 'are', 'then', 'derived', 'now', 'displaying', 'sink', 'and', 'source', 'terms', 'due', 'to', 'transfer', 'of', 'electrons', 'between', 'the', 'bulk', 'and', 'the', 'tail']]
[-0.08049230787241046, 0.14960121821208172, -0.09830178605415017, 0.12285849219468613, -0.046198041105351174, -0.10897839590570474, 0.005345053982034505, 0.2931656189801463, -0.31227444493806505, -0.33009405064968816, 0.02640376145760697, -0.2817272353603179, -0.022901936734364515, 0.1403394762471498, 0.04808720965387232, 0.036164378068488406, -0.019062089618766702, -0.026319057759211725, -0.05157060745026333, -0.1439045437678964, 0.33761298714811544, 0.05711329417550061, 0.25867351223097507, 0.06804376547729754, 0.14754869558859662, -0.04070283745763352, -0.005654692526413016, 0.010040914334065044, -0.12565061230130398, 0.09026772403915648, 0.17931575826313123, 0.059834210087085164, 0.25292360055518437, -0.4426602166067495, -0.2454791275156011, 0.05305064161005149, 0.16259442568835186, 0.09240215614224863, -0.036533294122172405, -0.24537110209734325, 0.007220489848180708, -0.19656064897685885, -0.13774877084778195, -0.008973958419568568, 0.04691654231107558, 0.04012813780411898, -0.27188881620181254, 0.12417674091285522, 0.03817948173866215, -0.011986169638673225, -0.09247645660000572, -0.08750206652849195, -0.08415675409564591, 0.15259133223780846, 0.06550251743307405, -0.006606565858517964, 0.13589966557471148, -0.15613613200811557, -0.02295570809910276, 0.3923981469797801, -0.051314928243497766, -0.18999758636556477, 0.20611491336778973, -0.16588986730651864, -0.05507132371730474, 0.14878584792366228, 0.12989058821316224, 0.08097261208928673, -0.2180152667282396, 0.07614858449276829, -0.004862675011292638, 0.1278218299778829, 0.018897571909544338, 0.04541354222470019, 0.23885207968281516, 0.1319582747430148, 0.0023033070568758323, 0.13332443267628774, -0.08773650633520447, -0.11551537184628198, -0.2847842605537679, -0.13630712315081114, -0.1905552599893277, 0.06323547416131, -0.09267439032222442, -0.1857073844735881, 0.39930344013923624, 0.09647965213530753, 0.1472712244434529, 0.0608460116705083, 0.26526868145868004, 0.17596042191985636, 0.01691928321596639, 0.10329298477013965, 0.23370072962393626, 0.21255791442558528, 0.08603159187877753, -0.3069393421882337, 0.09648954874768584, 0.06817287636965692]
1,802.02175
Black Holes and Complexity Classes
It is not known what the limitations are on using quantum computation to speed up classical computation. An example would be the power to speed up PSPACE-complete computations. It is also not known what the limitations are on the duration of time over which classical general relativity can describe the interior geometry of black holes. What is known is that these two questions are closely connected: the longer GR can describe black holes, the more limited are quantum computers. This conclusion, formulated as a theorem, is a result of unpublished work done by Scott Aaronson and myself which I explain here.
hep-th quant-ph
it is not known what the limitations are on using quantum computation to speed up classical computation an example would be the power to speed up pspacecomplete computations it is also not known what the limitations are on the duration of time over which classical general relativity can describe the interior geometry of black holes what is known is that these two questions are closely connected the longer gr can describe black holes the more limited are quantum computers this conclusion formulated as a theorem is a result of unpublished work done by scott aaronson and myself which i explain here
[['it', 'is', 'not', 'known', 'what', 'the', 'limitations', 'are', 'on', 'using', 'quantum', 'computation', 'to', 'speed', 'up', 'classical', 'computation', 'an', 'example', 'would', 'be', 'the', 'power', 'to', 'speed', 'up', 'pspacecomplete', 'computations', 'it', 'is', 'also', 'not', 'known', 'what', 'the', 'limitations', 'are', 'on', 'the', 'duration', 'of', 'time', 'over', 'which', 'classical', 'general', 'relativity', 'can', 'describe', 'the', 'interior', 'geometry', 'of', 'black', 'holes', 'what', 'is', 'known', 'is', 'that', 'these', 'two', 'questions', 'are', 'closely', 'connected', 'the', 'longer', 'gr', 'can', 'describe', 'black', 'holes', 'the', 'more', 'limited', 'are', 'quantum', 'computers', 'this', 'conclusion', 'formulated', 'as', 'a', 'theorem', 'is', 'a', 'result', 'of', 'unpublished', 'work', 'done', 'by', 'scott', 'aaronson', 'and', 'myself', 'which', 'i', 'explain', 'here']]
[-0.09380015132471568, 0.1321740183429758, -0.08296757155558496, 0.14551583437783883, -0.13295441034185415, -0.1760594182195935, 0.02296094249214719, 0.3507391725722147, -0.2813682041020308, -0.33135614439033634, 0.14721199061657017, -0.23599035956776968, -0.15236784501167216, 0.26670737358013, -0.15651691834486117, 0.02968413397522256, 0.033933938065967936, 0.052784306928515434, -0.048908779607384954, -0.3372748001377181, 0.28020839099219014, 0.08117213826580434, 0.2123248429443355, 0.04576505949527099, 0.01536659289630923, -0.06126604303440983, -0.009233464035067227, 0.045915395422552775, -0.12553301059658523, 0.08864159346788679, 0.2621738065361497, 0.17914494065715386, 0.25928041696695997, -0.4223244655139671, -0.21552533032095963, 0.06602702650246164, 0.11896559369051829, 0.1551555873904525, 0.007387984972095606, -0.24469932248022888, 0.11483519148925264, -0.16820279645300149, -0.13929017327984075, -0.06787680229633161, 0.04985476612104195, -0.030350640872585596, -0.1452126218061341, 0.03800174545716854, 0.12984969559134824, -0.030171637976597443, 0.014959780665317385, -0.05474116388791342, 0.04921009898702107, 0.11441294206675179, 0.040821394864582146, 0.04833426283174517, 0.11993662163841141, -0.0905554093406674, -0.1755171413763915, 0.3979960064044093, 0.02198362401179453, -0.19539408511159442, 0.18951304824930607, -0.15441608177682403, -0.09875430461793842, 0.07524736590065652, 0.08573479473182821, 0.1691504205936695, -0.1490689972784407, 0.11448830544042612, -0.07602017296427437, 0.17491967070820086, 0.11236396987489101, 0.036186402657249074, 0.2413388383805309, 0.10814480771688689, 0.0229133609958952, 0.09329909028019756, 0.0006793851060516174, -0.13186065428936394, -0.30549814543308745, -0.13999584151229055, -0.21089485823637852, 0.12806715128861487, -0.03500693763988346, -0.12338797315162155, 0.3148178103631178, 0.1513137574674156, 0.1332337889373118, 0.062307339754084694, 0.30456475089086593, 0.12082883294113902, 0.06123106901782869, 0.11223394120812859, 0.2797849151757684, 0.13250566003982459, 0.09887155478631174, -0.16631969902203372, 0.06354119442403316, 0.06711035248095004]
1,802.02176
Quasitoric stably normally split manifolds
A smooth stably complex manifold is called a totally tangentially/normally split manifold (TTS/TNS-manifold, for short, resp.) if the respective complex tangential/normal vector bundle is stably isomorphic to a Whitney sum of complex linear bundles, resp. In this paper we construct manifolds $M$ s.t. any complex vector bundle over $M$ is stably equivalent to a Whitney sum of complex linear bundles. A quasitoric manifold shares this property iff it is a TNS-manifold. We establish a new criterion of the TNS-property for a quasitoric manifold $M$ via non-semidefiniteness of certain higher-degree forms in the respective cohomology ring of $M$. In the family of quasitoric manifolds, this generalises the theorem of J. Lannes about the signature of a simply connected stably complex TNS $4$-manifold. We apply our criterion to show the flag property of the moment polytope for a nonsingular toric projective TNS-manifold of complex dimension $3$.
math.KT math.AT
a smooth stably complex manifold is called a totally tangentiallynormally split manifold ttstnsmanifold for short resp if the respective complex tangentialnormal vector bundle is stably isomorphic to a whitney sum of complex linear bundles resp in this paper we construct manifolds m st any complex vector bundle over m is stably equivalent to a whitney sum of complex linear bundles a quasitoric manifold shares this property iff it is a tnsmanifold we establish a new criterion of the tnsproperty for a quasitoric manifold m via nonsemidefiniteness of certain higherdegree forms in the respective cohomology ring of m in the family of quasitoric manifolds this generalises the theorem of j lannes about the signature of a simply connected stably complex tns 4manifold we apply our criterion to show the flag property of the moment polytope for a nonsingular toric projective tnsmanifold of complex dimension 3
[['a', 'smooth', 'stably', 'complex', 'manifold', 'is', 'called', 'a', 'totally', 'tangentiallynormally', 'split', 'manifold', 'ttstnsmanifold', 'for', 'short', 'resp', 'if', 'the', 'respective', 'complex', 'tangentialnormal', 'vector', 'bundle', 'is', 'stably', 'isomorphic', 'to', 'a', 'whitney', 'sum', 'of', 'complex', 'linear', 'bundles', 'resp', 'in', 'this', 'paper', 'we', 'construct', 'manifolds', 'm', 'st', 'any', 'complex', 'vector', 'bundle', 'over', 'm', 'is', 'stably', 'equivalent', 'to', 'a', 'whitney', 'sum', 'of', 'complex', 'linear', 'bundles', 'a', 'quasitoric', 'manifold', 'shares', 'this', 'property', 'iff', 'it', 'is', 'a', 'tnsmanifold', 'we', 'establish', 'a', 'new', 'criterion', 'of', 'the', 'tnsproperty', 'for', 'a', 'quasitoric', 'manifold', 'm', 'via', 'nonsemidefiniteness', 'of', 'certain', 'higherdegree', 'forms', 'in', 'the', 'respective', 'cohomology', 'ring', 'of', 'm', 'in', 'the', 'family', 'of', 'quasitoric', 'manifolds', 'this', 'generalises', 'the', 'theorem', 'of', 'j', 'lannes', 'about', 'the', 'signature', 'of', 'a', 'simply', 'connected', 'stably', 'complex', 'tns', '4manifold', 'we', 'apply', 'our', 'criterion', 'to', 'show', 'the', 'flag', 'property', 'of', 'the', 'moment', 'polytope', 'for', 'a', 'nonsingular', 'toric', 'projective', 'tnsmanifold', 'of', 'complex', 'dimension', '3']]
[-0.25841390306850637, 0.04963582746232486, -0.07760112486562154, 0.07464406212722122, -0.13767471378261265, -0.1801696795304, -0.038108682515266196, 0.3432059631594559, -0.3302348326130288, -0.16880953195674794, 0.10365375205891438, -0.19256913232324768, -0.1989725797036051, 0.14748378705749982, -0.15210117137290702, -0.053547496421357796, 0.07452050280369764, 0.12624378836489397, -0.10812582833909967, -0.29959330410207113, 0.472214063371185, -0.05844545555742879, 0.20105241538797858, 0.055509849947734474, 0.19156819799000205, 0.018035130756295346, 0.03144129146787807, 0.026731892305351522, -0.13958207155530253, 0.13654519021545067, 0.320873606841277, 0.09450275030320197, 0.18527313436119797, -0.33663561103022555, -0.15943782707254817, 0.25462236510161446, 0.09757975231937684, -0.05115468430937859, 0.05967624034107166, -0.23923775858252588, 0.14739179603048486, -0.11874030115096455, -0.170099965487029, -0.10492493614238299, 0.059586088594565864, -0.019023969055690468, -0.25344877808361593, -0.04558702591929014, 0.15781140020185144, 0.11217554447489253, -0.052517854261898644, -0.052355526575995404, -0.11110785413349904, 0.02129118647647301, -0.06804997081711997, 0.081404397797764, 0.08536161249163594, -0.009381722952885023, -0.09464154551383516, 0.35946434480775435, -0.08464722632749999, -0.30039844907527913, 0.10744917829160708, -0.13205382055229078, -0.14060575889940136, 0.20729306419753898, 0.09449793859282984, 0.23091246681219904, 0.001883386257002606, 0.1757097296267204, -0.15709614394110266, 0.06263067233665119, 0.07497309819271747, -0.06872843623324468, 0.14821558871245297, 0.1213200573272405, 0.13505621736101894, 0.09734038549754088, 0.017252586010408445, -0.07120597111333134, -0.3299509693127479, -0.28523351019588267, -0.13815133074420866, 0.24302867640924714, -0.10658759376489604, -0.17694885168822794, 0.39477725291665455, -0.04985919280358366, 0.2503859529638813, 0.1432772996176007, 0.2576380699165981, -0.03176606140850642, 0.04822918605382289, 0.08632193174192777, 0.12278684693300267, 0.2837860422875107, -0.021184318227333146, -0.07030526707186806, -0.07858728111660393, 0.18104590690375244]
1,802.02177
Physical and numerical stability and instability of AGN bubbles in a hot intracluster medium
While feedback from Active Galactic Nuclei (AGN) is an important heating source in the centre of galaxy clusters, it is still unclear how the feedback energy is injected into the intracluster medium (ICM) and what role different numerical approaches play. Here, we compare four hydrodynamical schemes in idealized simulations of a rising bubble inflated by AGN feedback in a hot stratified ICM: (traditional) smoothed particle hydrodynamics (TSPH), a pressure flavour of SPH (PSPH), a meshless finite mass (MFM) scheme, as well as an Eulerian code with adaptive mesh refinement. In the absence of magnetic fields, the bubble is Kelvin-Helmholtz unstable on short enough time scales to dissolve it fully in the ICM, which is captured by MFM and RAMSES simulations, while in the TSPH simulation the bubble survives. When the ICM is turbulent, mixing of the bubble with the ICM is accelerated. This occurs if the numerical scheme can capture the instabilities well. The differences in the evolution of the bubble has a surprisingly small influence on the thermal structure of the ICM. However, in the simulations with MFM and RAMSES the bubble disruption leads to turbulent stirring of the ICM which is suppressed in SPH. In the latter the thermal energy remains trapped in the bubble and is transported to large radii. We discuss if the choice of hydrodynamical schemes can lead to systematic differences in the outcomes of cosmological simulations.
astro-ph.GA astro-ph.CO
while feedback from active galactic nuclei agn is an important heating source in the centre of galaxy clusters it is still unclear how the feedback energy is injected into the intracluster medium icm and what role different numerical approaches play here we compare four hydrodynamical schemes in idealized simulations of a rising bubble inflated by agn feedback in a hot stratified icm traditional smoothed particle hydrodynamics tsph a pressure flavour of sph psph a meshless finite mass mfm scheme as well as an eulerian code with adaptive mesh refinement in the absence of magnetic fields the bubble is kelvinhelmholtz unstable on short enough time scales to dissolve it fully in the icm which is captured by mfm and ramses simulations while in the tsph simulation the bubble survives when the icm is turbulent mixing of the bubble with the icm is accelerated this occurs if the numerical scheme can capture the instabilities well the differences in the evolution of the bubble has a surprisingly small influence on the thermal structure of the icm however in the simulations with mfm and ramses the bubble disruption leads to turbulent stirring of the icm which is suppressed in sph in the latter the thermal energy remains trapped in the bubble and is transported to large radii we discuss if the choice of hydrodynamical schemes can lead to systematic differences in the outcomes of cosmological simulations
[['while', 'feedback', 'from', 'active', 'galactic', 'nuclei', 'agn', 'is', 'an', 'important', 'heating', 'source', 'in', 'the', 'centre', 'of', 'galaxy', 'clusters', 'it', 'is', 'still', 'unclear', 'how', 'the', 'feedback', 'energy', 'is', 'injected', 'into', 'the', 'intracluster', 'medium', 'icm', 'and', 'what', 'role', 'different', 'numerical', 'approaches', 'play', 'here', 'we', 'compare', 'four', 'hydrodynamical', 'schemes', 'in', 'idealized', 'simulations', 'of', 'a', 'rising', 'bubble', 'inflated', 'by', 'agn', 'feedback', 'in', 'a', 'hot', 'stratified', 'icm', 'traditional', 'smoothed', 'particle', 'hydrodynamics', 'tsph', 'a', 'pressure', 'flavour', 'of', 'sph', 'psph', 'a', 'meshless', 'finite', 'mass', 'mfm', 'scheme', 'as', 'well', 'as', 'an', 'eulerian', 'code', 'with', 'adaptive', 'mesh', 'refinement', 'in', 'the', 'absence', 'of', 'magnetic', 'fields', 'the', 'bubble', 'is', 'kelvinhelmholtz', 'unstable', 'on', 'short', 'enough', 'time', 'scales', 'to', 'dissolve', 'it', 'fully', 'in', 'the', 'icm', 'which', 'is', 'captured', 'by', 'mfm', 'and', 'ramses', 'simulations', 'while', 'in', 'the', 'tsph', 'simulation', 'the', 'bubble', 'survives', 'when', 'the', 'icm', 'is', 'turbulent', 'mixing', 'of', 'the', 'bubble', 'with', 'the', 'icm', 'is', 'accelerated', 'this', 'occurs', 'if', 'the', 'numerical', 'scheme', 'can', 'capture', 'the', 'instabilities', 'well', 'the', 'differences', 'in', 'the', 'evolution', 'of', 'the', 'bubble', 'has', 'a', 'surprisingly', 'small', 'influence', 'on', 'the', 'thermal', 'structure', 'of', 'the', 'icm', 'however', 'in', 'the', 'simulations', 'with', 'mfm', 'and', 'ramses', 'the', 'bubble', 'disruption', 'leads', 'to', 'turbulent', 'stirring', 'of', 'the', 'icm', 'which', 'is', 'suppressed', 'in', 'sph', 'in', 'the', 'latter', 'the', 'thermal', 'energy', 'remains', 'trapped', 'in', 'the', 'bubble', 'and', 'is', 'transported', 'to', 'large', 'radii', 'we', 'discuss', 'if', 'the', 'choice', 'of', 'hydrodynamical', 'schemes', 'can', 'lead', 'to', 'systematic', 'differences', 'in', 'the', 'outcomes', 'of', 'cosmological', 'simulations']]
[-0.08975553962442538, 0.18148656985532674, -0.12195599041069331, 0.10915043692954857, -0.05185380277892008, -0.0515510072607709, -0.011636749385228462, 0.37573743789942693, -0.2713146806249152, -0.30317724884345965, 0.07099964584264418, -0.2530803613182481, -0.013854278451965555, 0.17757222014125032, 0.0015163368965580087, -0.009560361917576064, 0.060269062931689876, -0.06407200054002359, -0.02251752591084527, -0.26206650775553575, 0.31320464746247084, 0.17269159516360125, 0.21346716257014675, 0.037735872197410335, 0.0829763889150775, -0.1171057429873263, -0.09016565249261001, 0.07268878654323761, -0.16352617278462275, -0.030211945977973064, 0.1836371903996105, 0.057780739853320565, 0.30340440463294965, -0.4783578110858798, -0.27481762206424837, 0.04673679976865811, 0.21005447848355802, 0.13028543999155417, -0.11080448337509195, -0.18487598728995933, 0.06980182896418821, -0.2135463647939184, -0.1325374146538746, 0.014989083986121999, -0.025592359461133248, 0.03073761090996097, -0.2539646826352944, 0.17744356546773696, 0.043264414729935155, 0.027774620137136916, -0.07161420008734516, -0.016139780977012023, -0.05149386998483628, 0.095627985926109, 0.04524392698443515, 0.048038053868905355, 0.23614500504513475, -0.16797395741425292, -0.0259847947821507, 0.4544104471883696, -0.02061388289515415, -0.1391753196878278, 0.2376342503313461, -0.17783149965512363, -0.0889075486156482, 0.15562756244148856, 0.17251928618744664, 0.08864704172896302, -0.08215761549686051, 0.03575795245984488, -0.07208513171164035, 0.16914003277804865, 0.03102304125002221, -0.028794817979708214, 0.24186375746098548, 0.1781178001365017, 0.028914928032368746, 0.1322532590539397, -0.13915762283090177, -0.1113840978147219, -0.2745256933525367, -0.1061910588496729, -0.14115778546699365, 0.0240715535237383, -0.12394767586602425, -0.17514818019800535, 0.3153155248643484, 0.15125438318911777, 0.13415607059091006, -0.04410445559668638, 0.3717882687954799, 0.03454920225776732, 0.07745221568595456, 0.15008275772687857, 0.2786236610385063, 0.1716570859339655, 0.11541323550450414, -0.31619688561388654, 0.06041595793288687, 0.07567285476049976]
1,802.02178
LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks
Application-specific integrated circuit (ASIC) implementations for Deep Neural Networks (DNNs) have been adopted in many systems because of their higher classification speed. However, although they may be characterized by better accuracy, larger DNNs require significant energy and area, thereby limiting their wide adoption. The energy consumption of DNNs is driven by both memory accesses and computation. Binarized Neural Networks (BNNs), as a trade-off between accuracy and energy consumption, can achieve great energy reduction, and have good accuracy for large DNNs due to its regularization effect. However, BNNs show poor accuracy when a smaller DNN configuration is adopted. In this paper, we propose a new DNN model, LightNN, which replaces the multiplications to one shift or a constrained number of shifts and adds. For a fixed DNN configuration, LightNNs have better accuracy at a slight energy increase than BNNs, yet are more energy efficient with only slightly less accuracy than conventional DNNs. Therefore, LightNNs provide more options for hardware designers to make trade-offs between accuracy and energy. Moreover, for large DNN configurations, LightNNs have a regularization effect, making them better in accuracy than conventional DNNs. These conclusions are verified by experiment using the MNIST and CIFAR-10 datasets for different DNN configurations.
cs.NE
applicationspecific integrated circuit asic implementations for deep neural networks dnns have been adopted in many systems because of their higher classification speed however although they may be characterized by better accuracy larger dnns require significant energy and area thereby limiting their wide adoption the energy consumption of dnns is driven by both memory accesses and computation binarized neural networks bnns as a tradeoff between accuracy and energy consumption can achieve great energy reduction and have good accuracy for large dnns due to its regularization effect however bnns show poor accuracy when a smaller dnn configuration is adopted in this paper we propose a new dnn model lightnn which replaces the multiplications to one shift or a constrained number of shifts and adds for a fixed dnn configuration lightnns have better accuracy at a slight energy increase than bnns yet are more energy efficient with only slightly less accuracy than conventional dnns therefore lightnns provide more options for hardware designers to make tradeoffs between accuracy and energy moreover for large dnn configurations lightnns have a regularization effect making them better in accuracy than conventional dnns these conclusions are verified by experiment using the mnist and cifar10 datasets for different dnn configurations
[['applicationspecific', 'integrated', 'circuit', 'asic', 'implementations', 'for', 'deep', 'neural', 'networks', 'dnns', 'have', 'been', 'adopted', 'in', 'many', 'systems', 'because', 'of', 'their', 'higher', 'classification', 'speed', 'however', 'although', 'they', 'may', 'be', 'characterized', 'by', 'better', 'accuracy', 'larger', 'dnns', 'require', 'significant', 'energy', 'and', 'area', 'thereby', 'limiting', 'their', 'wide', 'adoption', 'the', 'energy', 'consumption', 'of', 'dnns', 'is', 'driven', 'by', 'both', 'memory', 'accesses', 'and', 'computation', 'binarized', 'neural', 'networks', 'bnns', 'as', 'a', 'tradeoff', 'between', 'accuracy', 'and', 'energy', 'consumption', 'can', 'achieve', 'great', 'energy', 'reduction', 'and', 'have', 'good', 'accuracy', 'for', 'large', 'dnns', 'due', 'to', 'its', 'regularization', 'effect', 'however', 'bnns', 'show', 'poor', 'accuracy', 'when', 'a', 'smaller', 'dnn', 'configuration', 'is', 'adopted', 'in', 'this', 'paper', 'we', 'propose', 'a', 'new', 'dnn', 'model', 'lightnn', 'which', 'replaces', 'the', 'multiplications', 'to', 'one', 'shift', 'or', 'a', 'constrained', 'number', 'of', 'shifts', 'and', 'adds', 'for', 'a', 'fixed', 'dnn', 'configuration', 'lightnns', 'have', 'better', 'accuracy', 'at', 'a', 'slight', 'energy', 'increase', 'than', 'bnns', 'yet', 'are', 'more', 'energy', 'efficient', 'with', 'only', 'slightly', 'less', 'accuracy', 'than', 'conventional', 'dnns', 'therefore', 'lightnns', 'provide', 'more', 'options', 'for', 'hardware', 'designers', 'to', 'make', 'tradeoffs', 'between', 'accuracy', 'and', 'energy', 'moreover', 'for', 'large', 'dnn', 'configurations', 'lightnns', 'have', 'a', 'regularization', 'effect', 'making', 'them', 'better', 'in', 'accuracy', 'than', 'conventional', 'dnns', 'these', 'conclusions', 'are', 'verified', 'by', 'experiment', 'using', 'the', 'mnist', 'and', 'cifar10', 'datasets', 'for', 'different', 'dnn', 'configurations']]
[-0.0766534605402799, 0.015918701176938773, -0.025219851095070266, 0.11179021831681418, -0.07993290181992453, -0.2265078305084277, 0.07022035711306854, 0.46894750711344296, -0.20036354271142776, -0.41864450462162495, 0.07427983048685531, -0.24560857247842016, -0.1355734820250684, 0.2510130764406418, -0.12980472480152247, 0.12653490088513852, 0.16049886586603207, 0.002358448208601041, -0.1129276055138296, -0.30848095620673466, 0.2397675299268197, 0.151549153955245, 0.3360292445973554, 0.04416495486017522, 0.09133707594135823, -0.10318778398278258, 0.049254838184186786, -0.0062767276189397625, -0.00913733151746006, 0.16536797827633856, 0.2868868674750641, 0.1160654896867623, 0.3377433482220574, -0.46459081198027985, -0.2375756991113391, 0.15137930972208843, 0.16106725620321144, 0.08322930884503364, -0.015538862733382161, -0.25692321627339976, 0.13666944871726797, -0.21646515571807123, -0.010957847992847464, -0.1822530041845403, 0.007749078287532431, 0.029631344627252025, -0.2379762013700215, 0.049336789859149924, 0.055658622252305584, 0.0781864126601336, 0.010640982879517627, -0.18769297070904217, -0.010861798982842634, 0.09921899597331924, 0.009215579444809288, 0.0598961770050134, 0.13714766388188054, -0.2015190204177239, -0.099687710744282, 0.3333744998827071, -0.012542665142717482, -0.23610311032895318, 0.1932585654176547, -0.0025181407436503838, -0.09895239704424262, 0.137047236195611, 0.22864603637027361, 0.04304617905905049, -0.12810884433338973, 0.008087355143041935, 0.0802759768993561, 0.21518081141139694, 0.09996988820894878, 0.0705521989791612, 0.161069642934052, 0.28858454048109417, 0.056351543094988576, 0.11492467889194868, -0.09119961776869516, -0.079670154197076, -0.14202109860939596, -0.08816328887060172, -0.1649596522288425, 0.02233057143049661, -0.14461896981964714, -0.08760527919172942, 0.3678638882813367, 0.19426491217811748, 0.1962724408022498, 0.14855079351393177, 0.3612133636696255, 0.09143499254036096, 0.18044304733524968, 0.135215766608584, 0.26035992049813345, 0.02037740295785643, 0.14103870648872013, -0.15209980936014286, 0.08383110020749608, -0.0316348988808523]
1,802.02179
A Systematic Analysis for State-of-the-Art 3D Lung Nodule Proposals Generation
Lung nodule proposals generation is the primary step of lung nodule detection and has received much attention in recent years . In this paper, we first construct a model of 3-dimension Convolutional Neural Network (3D CNN) to generate lung nodule proposals, which can achieve the state-of-the-art performance. Then, we analyze a series of key problems concerning the training performance and efficiency. Firstly, we train the 3D CNN model with data in different resolutions and find out that models trained by high resolution input data achieve better lung nodule proposals generation performances especially for nodules in too small sizes, while consumes much more memory at the same time. Then, we analyze the memory consumptions on different platforms and the experimental results indicate that CPU architecture can provide us with larger memory and enables us to explore more possibilities of 3D applications. We implement the 3D CNN model on CPU platform and propose an Intel Extended-Caffe framework which supports many highly-efficient 3D computations, which is opened source at https://github.com/extendedcaffe/extended-caffe.
cs.CV
lung nodule proposals generation is the primary step of lung nodule detection and has received much attention in recent years in this paper we first construct a model of 3dimension convolutional neural network 3d cnn to generate lung nodule proposals which can achieve the stateoftheart performance then we analyze a series of key problems concerning the training performance and efficiency firstly we train the 3d cnn model with data in different resolutions and find out that models trained by high resolution input data achieve better lung nodule proposals generation performances especially for nodules in too small sizes while consumes much more memory at the same time then we analyze the memory consumptions on different platforms and the experimental results indicate that cpu architecture can provide us with larger memory and enables us to explore more possibilities of 3d applications we implement the 3d cnn model on cpu platform and propose an intel extendedcaffe framework which supports many highlyefficient 3d computations which is opened source at httpsgithubcomextendedcaffeextendedcaffe
[['lung', 'nodule', 'proposals', 'generation', 'is', 'the', 'primary', 'step', 'of', 'lung', 'nodule', 'detection', 'and', 'has', 'received', 'much', 'attention', 'in', 'recent', 'years', 'in', 'this', 'paper', 'we', 'first', 'construct', 'a', 'model', 'of', '3dimension', 'convolutional', 'neural', 'network', '3d', 'cnn', 'to', 'generate', 'lung', 'nodule', 'proposals', 'which', 'can', 'achieve', 'the', 'stateoftheart', 'performance', 'then', 'we', 'analyze', 'a', 'series', 'of', 'key', 'problems', 'concerning', 'the', 'training', 'performance', 'and', 'efficiency', 'firstly', 'we', 'train', 'the', '3d', 'cnn', 'model', 'with', 'data', 'in', 'different', 'resolutions', 'and', 'find', 'out', 'that', 'models', 'trained', 'by', 'high', 'resolution', 'input', 'data', 'achieve', 'better', 'lung', 'nodule', 'proposals', 'generation', 'performances', 'especially', 'for', 'nodules', 'in', 'too', 'small', 'sizes', 'while', 'consumes', 'much', 'more', 'memory', 'at', 'the', 'same', 'time', 'then', 'we', 'analyze', 'the', 'memory', 'consumptions', 'on', 'different', 'platforms', 'and', 'the', 'experimental', 'results', 'indicate', 'that', 'cpu', 'architecture', 'can', 'provide', 'us', 'with', 'larger', 'memory', 'and', 'enables', 'us', 'to', 'explore', 'more', 'possibilities', 'of', '3d', 'applications', 'we', 'implement', 'the', '3d', 'cnn', 'model', 'on', 'cpu', 'platform', 'and', 'propose', 'an', 'intel', 'extendedcaffe', 'framework', 'which', 'supports', 'many', 'highlyefficient', '3d', 'computations', 'which', 'is', 'opened', 'source', 'at', 'httpsgithubcomextendedcaffeextendedcaffe']]
[-0.025752087357942377, 0.0031645922338988963, -0.022423949609397024, 0.034503652416765916, -0.0753480126646847, -0.21984071129501412, 0.00229452047624807, 0.4502080288920097, -0.19848342445145203, -0.3525730215649052, 0.07887719936737018, -0.25445788629671057, -0.1553807330116198, 0.23301298077439708, -0.12830421615607765, 0.12685366187857963, 0.1718596994859825, 0.01836676713488797, -0.06058666188974024, -0.30977496703541496, 0.2500650747693371, 0.09191198551618471, 0.3751111592779436, 0.03444215301111931, 0.12788193949594776, -0.10227179826129364, -0.02742259415354943, -0.035829293701326384, -0.08051656901017584, 0.19561105455760275, 0.27668068453445677, 0.17231973753418636, 0.3216011702315882, -0.49317491690560084, -0.2420146560364562, 0.07010479087986779, 0.1376892732152511, 0.12424262848089268, -0.02947907288017166, -0.3040789370254682, 0.11407603129812675, -0.2033683665653282, 0.002467679913069133, -0.157300683782612, -0.0035310339767531287, -0.05127504489685568, -0.29567275620519934, 0.03080492379234695, 0.010286309253765134, 0.016718850720946383, -0.062150157749562, -0.09034740414879308, 0.005922255861550206, 0.17382104914044824, -0.007273154802488734, 0.059230780453284886, 0.1116734902003905, -0.20468684717432153, -0.15556977273578323, 0.3688696473851096, -0.018443547240344853, -0.17853848886585272, 0.19391633004160236, -0.07746511940253763, -0.14624001599689265, 0.10744071425195705, 0.26922642042088074, 0.11371665177071785, -0.12684310386638817, -0.0276187379871461, -0.005306340277013256, 0.20659150433919687, 0.05976848411317006, 0.006570514121870851, 0.17819460242398924, 0.3141247871127434, 0.001976019776321198, 0.1821111041964486, -0.21926268934635673, -0.044671709217676304, -0.19306488927431043, -0.15784005273315238, -0.16863076704009095, -0.016036474756419478, -0.08611683223752174, -0.12062133300805283, 0.44551897989358846, 0.26604262234574955, 0.19119325447855973, 0.12064315977565968, 0.35332405978314035, -0.003919102353748025, 0.1700028626009731, 0.09883555820745575, 0.16620038442665758, -0.020875266324388, 0.1458802128327079, -0.17410763449364955, 0.05236196882877976, 0.04994077664546572]
1,802.0218
Interstellar communication. IX. Message decontamination is impossible
A complex message from space may require the use of computers to display, analyze and understand. Such a message cannot be decontaminated with certainty, and technical risks remain which can pose an existential threat. Complex messages would need to be destroyed in the risk averse case.
astro-ph.IM physics.pop-ph
a complex message from space may require the use of computers to display analyze and understand such a message cannot be decontaminated with certainty and technical risks remain which can pose an existential threat complex messages would need to be destroyed in the risk averse case
[['a', 'complex', 'message', 'from', 'space', 'may', 'require', 'the', 'use', 'of', 'computers', 'to', 'display', 'analyze', 'and', 'understand', 'such', 'a', 'message', 'can', 'not', 'be', 'decontaminated', 'with', 'certainty', 'and', 'technical', 'risks', 'remain', 'which', 'can', 'pose', 'an', 'existential', 'threat', 'complex', 'messages', 'would', 'need', 'to', 'be', 'destroyed', 'in', 'the', 'risk', 'averse', 'case']]
[-0.12508032887064396, 0.060415020780055784, -0.09500883422554174, 0.13923034777349613, -0.1701211192981994, -0.23613578142558642, 0.08610026749405772, 0.40018715955158496, -0.3266356457829812, -0.32141179270408254, 0.16620036643345226, -0.2797608020259662, -0.1413554398025921, 0.16008583176881075, -0.24992834713509396, -0.00014919942205256605, 0.025431387661460865, 0.07355164149974255, 0.001696181052582378, -0.2999354970264942, 0.30057397245013334, 0.00793226788494181, 0.1624699997557129, 0.06139476617124486, 0.006023070319218838, -0.025954945904618883, 0.011204620793541061, 0.009452507424321858, -0.014600786420100547, 0.09140898703419148, 0.3830603690857583, 0.24562726605762827, 0.3332098432757119, -0.49574956963671013, -0.1961297510548475, 0.18975754513187296, 0.19204644139539054, 0.1219856866927659, 0.014711252354243969, -0.3485598772952452, 0.04698545245473531, -0.20340456938410692, -0.12072562537294754, -0.13834790373468733, -0.08201084091783838, -0.0026434923106051504, -0.2723906902705339, -0.0036760645304271516, 0.00320000711709578, 0.05834634199817764, 0.021968596649574155, -0.03159545381811071, -0.004823976335056285, 0.21430413327873388, 0.05050612835490957, 0.02582137538318304, 0.17198405296918243, -0.13080290093908997, -0.13712614513141044, 0.39754530309917446, 0.01648075987604704, -0.21126995977271903, 0.19236814968555452, -0.08160731067603573, -0.1228353329736026, 0.18234682788557194, 0.2207552433172439, 0.026118491994256667, -0.1741535628927832, 0.015843423120578393, 0.027882414731256504, 0.2566429777665341, 0.0627349783725878, 0.05728643295414587, 0.23606859056397955, 0.07932799864322582, 0.07739173347487095, 0.08396630432516178, -0.05655019978021688, -0.10057997386506264, -0.2203090232103429, -0.19401857294538555, -0.12522908260530613, 0.09452169216665231, -0.06539992720540118, -0.1609886795123841, 0.2965330389486824, 0.2011826682087787, 0.15729697131888665, 0.07705821366633903, 0.29388971326555663, 0.06350136126213252, 0.09625965610463569, 0.12995453277959468, 0.19640156672276715, -0.005813231275595249, 0.05638183554153929, -0.11045906919133948, 0.2704838578232584, -0.06781685948768194]
1,802.02181
Applications of a Graph Theoretic Based Clustering Framework in Computer Vision and Pattern Recognition
Recently, several clustering algorithms have been used to solve variety of problems from different discipline. This dissertation aims to address different challenging tasks in computer vision and pattern recognition by casting the problems as a clustering problem. We proposed novel approaches to solve multi-target tracking, visual geo-localization and outlier detection problems using a unified underlining clustering framework, i.e., dominant set clustering and its extensions, and presented a superior result over several state-of-the-art approaches.
cs.CV
recently several clustering algorithms have been used to solve variety of problems from different discipline this dissertation aims to address different challenging tasks in computer vision and pattern recognition by casting the problems as a clustering problem we proposed novel approaches to solve multitarget tracking visual geolocalization and outlier detection problems using a unified underlining clustering framework ie dominant set clustering and its extensions and presented a superior result over several stateoftheart approaches
[['recently', 'several', 'clustering', 'algorithms', 'have', 'been', 'used', 'to', 'solve', 'variety', 'of', 'problems', 'from', 'different', 'discipline', 'this', 'dissertation', 'aims', 'to', 'address', 'different', 'challenging', 'tasks', 'in', 'computer', 'vision', 'and', 'pattern', 'recognition', 'by', 'casting', 'the', 'problems', 'as', 'a', 'clustering', 'problem', 'we', 'proposed', 'novel', 'approaches', 'to', 'solve', 'multitarget', 'tracking', 'visual', 'geolocalization', 'and', 'outlier', 'detection', 'problems', 'using', 'a', 'unified', 'underlining', 'clustering', 'framework', 'ie', 'dominant', 'set', 'clustering', 'and', 'its', 'extensions', 'and', 'presented', 'a', 'superior', 'result', 'over', 'several', 'stateoftheart', 'approaches']]
[-0.018796093340912094, -0.1098939170550606, -0.10343541595319362, 0.0694578494924465, -0.12483645554580917, -0.19264064252070368, -0.03338079608670653, 0.4064003697609248, -0.31473506061513334, -0.39979905264901816, 0.11420229118642691, -0.23704096646851872, -0.20629964031483214, 0.22144491697521243, -0.15810180820798986, 0.19862104607793846, 0.12160202128531998, -0.004800394636719194, -0.084844611521351, -0.28420373688975015, 0.25875907713764235, 0.008361733888518321, 0.37303648900865793, 0.06033688146391348, 0.15175769867196884, -0.022309703943766142, -0.07099571522350794, 0.08611601496064296, -0.06609549276747625, 0.1621515609065632, 0.3982096884801525, 0.2564749598394671, 0.3836659694677346, -0.36103146472205855, -0.27341132090835235, 0.12677620890333433, 0.22287118728336405, 0.10270381661463682, -0.08332258885828396, -0.33872917110789313, 0.12120098736111636, -0.18242697780058809, 0.03531417094987549, -0.10140640772113653, -0.007352404275666667, -0.04040829790118214, -0.2223860571951899, 0.04855688333460321, 0.04756457140439586, 0.054965168607663616, -0.07099970205757154, -0.15566486420671213, 0.18479792391307243, 0.1444410136518107, 0.06274932666286213, 0.029436390681115733, 0.13454971893065393, -0.1933647710032608, -0.2577025809465614, 0.42966853572081215, 0.006800860326022726, -0.18859742932685025, 0.2817593418980298, 0.06503507880851218, -0.24065159434095434, 0.08473643664372703, 0.2622650095759189, 0.19189140668189894, -0.1919843723410613, 0.04298827212546276, -0.03926069604564611, 0.11319454820597008, 0.058007817256124056, -0.045190654146446754, 0.18629406974331975, 0.27123062860552377, 0.08656107330988225, 0.12516449669962876, -0.10242473489719711, -0.07367814302265849, -0.13661573862988655, -0.04038158160545034, -0.14857063448209673, -0.10456860977646014, -0.05924223649733355, -0.13076070482421615, 0.43698281496252916, 0.2499224904937389, 0.19482876752401154, 0.049626468412884296, 0.3754962013192373, 0.033350747904926856, 0.06682070890881682, 0.051948810047278665, 0.1484767304915195, 0.08548353144529033, 0.12320300165327802, -0.19337964056327633, 0.03169372255837366, 0.07234548247891338]
1,802.02182
2D-Densely Connected Convolution Neural Networks for automatic Liver and Tumor Segmentation
In this paper we propose a fully automatic 2-stage cascaded approach for segmentation of liver and its tumors in CT (Computed Tomography) images using densely connected fully convolutional neural network (DenseNet). We independently train liver and tumor segmentation models and cascade them for a combined segmentation of the liver and its tumor. The first stage involves segmentation of liver and the second stage uses the first stage's segmentation results for localization of liver and henceforth tumor segmentations inside liver region. The liver model was trained on the down-sampled axial slices $(256 \times 256)$, whereas for the tumor model no down-sampling of slices was done, but instead it was trained on the CT axial slices windowed at three different Hounsfield (HU) levels. On the test set our model achieved a global dice score of 0.923 and 0.625 on liver and tumor respectively. The computed tumor burden had an rmse of 0.044.
cs.CV
in this paper we propose a fully automatic 2stage cascaded approach for segmentation of liver and its tumors in ct computed tomography images using densely connected fully convolutional neural network densenet we independently train liver and tumor segmentation models and cascade them for a combined segmentation of the liver and its tumor the first stage involves segmentation of liver and the second stage uses the first stages segmentation results for localization of liver and henceforth tumor segmentations inside liver region the liver model was trained on the downsampled axial slices 256 times 256 whereas for the tumor model no downsampling of slices was done but instead it was trained on the ct axial slices windowed at three different hounsfield hu levels on the test set our model achieved a global dice score of 0923 and 0625 on liver and tumor respectively the computed tumor burden had an rmse of 0044
[['in', 'this', 'paper', 'we', 'propose', 'a', 'fully', 'automatic', '2stage', 'cascaded', 'approach', 'for', 'segmentation', 'of', 'liver', 'and', 'its', 'tumors', 'in', 'ct', 'computed', 'tomography', 'images', 'using', 'densely', 'connected', 'fully', 'convolutional', 'neural', 'network', 'densenet', 'we', 'independently', 'train', 'liver', 'and', 'tumor', 'segmentation', 'models', 'and', 'cascade', 'them', 'for', 'a', 'combined', 'segmentation', 'of', 'the', 'liver', 'and', 'its', 'tumor', 'the', 'first', 'stage', 'involves', 'segmentation', 'of', 'liver', 'and', 'the', 'second', 'stage', 'uses', 'the', 'first', 'stages', 'segmentation', 'results', 'for', 'localization', 'of', 'liver', 'and', 'henceforth', 'tumor', 'segmentations', 'inside', 'liver', 'region', 'the', 'liver', 'model', 'was', 'trained', 'on', 'the', 'downsampled', 'axial', 'slices', '256', 'times', '256', 'whereas', 'for', 'the', 'tumor', 'model', 'no', 'downsampling', 'of', 'slices', 'was', 'done', 'but', 'instead', 'it', 'was', 'trained', 'on', 'the', 'ct', 'axial', 'slices', 'windowed', 'at', 'three', 'different', 'hounsfield', 'hu', 'levels', 'on', 'the', 'test', 'set', 'our', 'model', 'achieved', 'a', 'global', 'dice', 'score', 'of', '0923', 'and', '0625', 'on', 'liver', 'and', 'tumor', 'respectively', 'the', 'computed', 'tumor', 'burden', 'had', 'an', 'rmse', 'of', '0044']]
[0.039843839346431195, 0.015491777187465534, 0.01300327513832599, 0.03196915301727131, 0.03411464850418269, -0.16097583066982527, 0.024791560884720336, 0.44162172977502145, -0.1524335099508365, -0.25970872475455203, 0.13670543041235456, -0.2726338379830122, -0.14473584862736363, 0.16250752845235789, -0.16503133438702208, 0.08351997351506725, 0.16521339789343378, 0.0446535085234791, -0.00533006366652747, -0.30108240387547996, 0.21448323543338726, 0.004901191128107408, 0.3615602000088741, 0.0036957093855986994, 0.2067371612538894, -0.050976683602202685, -0.04404341032107671, -0.030473815699030335, -0.09900129018661877, 0.1621216606069356, 0.26212387695086364, 0.17297667058805624, 0.31639261577278377, -0.42812642963603137, -0.21259522962073485, 0.06698550680846287, 0.1745569164166227, 0.05838180174430212, 0.042584424152349434, -0.3461779993710419, 0.14070701961095133, -0.1207219875146014, 0.062111122765927576, -0.04696762474874656, -0.021413296019503227, -0.09469531811773776, -0.32002580545221765, 0.205846568212534, 0.010492094965302385, 0.09172289254143834, -0.18102036397283275, -0.10462389811097333, -0.03134127355258291, 0.21966334476446112, -0.03603131170927858, 0.15459744653354088, 0.1720656639469477, -0.21691496400317797, -0.11458726472609367, 0.2871339696800957, 0.0376678890370143, -0.1913398650661111, 0.1373067128409942, -0.07414758125009636, -0.09719979031787564, 0.1718514408171177, 0.20294146694631005, 0.1476623373447607, -0.163104632422328, -0.09397841771754126, 0.0026468722708523273, 0.21072683083824814, 0.11224622150301002, -0.18044218074142312, 0.1305929637812854, 0.315160373179242, -0.08177868426505787, 0.16919559039951612, -0.2874839427809153, 0.03854094217065722, -0.23890937347275515, -0.16618957212194801, -0.16628702072426677, -0.05317843687565376, -0.13255121969540293, -0.20108276351355017, 0.4547985376169284, 0.12281053033967813, 0.18233632144207756, 0.14214297700983783, 0.3315484695121025, -0.044480373946231944, 0.13085742957890034, 2.856540804107984e-05, 0.1712485871533863, 0.033327052616514266, 0.11122872503784796, -0.2038661963393679, 0.0810537373709182, 0.1612751578624981]
1,802.02183
Enhanced Image Classification With Data Augmentation Using Position Coordinates
In this paper we propose the use of image pixel position coordinate system to improve image classification accuracy in various applications. Specifically, we hypothesize that the use of pixel coordinates will lead to (a) Resolution invariant performance. Here, by resolution we mean the spacing between the pixels rather than the size of the image matrix. (b) Overall improvement in classification accuracy in comparison with network models trained without local pixel coordinates. This is due to position coordinates enabling the network to learn relationship between parts of objects, mimicking the human vision system. We demonstrate our hypothesis using empirical results and intuitive explanations of the feature maps learnt by deep neural networks. Specifically, our approach showed improvements in MNIST digit classification and beats state of the results on the SVHN database. We also show that the performance of our networks is unaffected despite training the same using blurred images of the MNIST database and predicting on the high resolution database.
cs.CV
in this paper we propose the use of image pixel position coordinate system to improve image classification accuracy in various applications specifically we hypothesize that the use of pixel coordinates will lead to a resolution invariant performance here by resolution we mean the spacing between the pixels rather than the size of the image matrix b overall improvement in classification accuracy in comparison with network models trained without local pixel coordinates this is due to position coordinates enabling the network to learn relationship between parts of objects mimicking the human vision system we demonstrate our hypothesis using empirical results and intuitive explanations of the feature maps learnt by deep neural networks specifically our approach showed improvements in mnist digit classification and beats state of the results on the svhn database we also show that the performance of our networks is unaffected despite training the same using blurred images of the mnist database and predicting on the high resolution database
[['in', 'this', 'paper', 'we', 'propose', 'the', 'use', 'of', 'image', 'pixel', 'position', 'coordinate', 'system', 'to', 'improve', 'image', 'classification', 'accuracy', 'in', 'various', 'applications', 'specifically', 'we', 'hypothesize', 'that', 'the', 'use', 'of', 'pixel', 'coordinates', 'will', 'lead', 'to', 'a', 'resolution', 'invariant', 'performance', 'here', 'by', 'resolution', 'we', 'mean', 'the', 'spacing', 'between', 'the', 'pixels', 'rather', 'than', 'the', 'size', 'of', 'the', 'image', 'matrix', 'b', 'overall', 'improvement', 'in', 'classification', 'accuracy', 'in', 'comparison', 'with', 'network', 'models', 'trained', 'without', 'local', 'pixel', 'coordinates', 'this', 'is', 'due', 'to', 'position', 'coordinates', 'enabling', 'the', 'network', 'to', 'learn', 'relationship', 'between', 'parts', 'of', 'objects', 'mimicking', 'the', 'human', 'vision', 'system', 'we', 'demonstrate', 'our', 'hypothesis', 'using', 'empirical', 'results', 'and', 'intuitive', 'explanations', 'of', 'the', 'feature', 'maps', 'learnt', 'by', 'deep', 'neural', 'networks', 'specifically', 'our', 'approach', 'showed', 'improvements', 'in', 'mnist', 'digit', 'classification', 'and', 'beats', 'state', 'of', 'the', 'results', 'on', 'the', 'svhn', 'database', 'we', 'also', 'show', 'that', 'the', 'performance', 'of', 'our', 'networks', 'is', 'unaffected', 'despite', 'training', 'the', 'same', 'using', 'blurred', 'images', 'of', 'the', 'mnist', 'database', 'and', 'predicting', 'on', 'the', 'high', 'resolution', 'database']]
[-0.045720493762150594, -0.04787002528619326, -0.06841617142752328, 0.040251754707533796, -0.037890798549911696, -0.10989271162616664, 0.04412750215430703, 0.4717417727663832, -0.2432423103483593, -0.36640496876489065, 0.060789491904389883, -0.2813216947874277, -0.186079612561156, 0.17841089735211768, -0.17537699795456943, 0.07010977834744274, 0.1674771161571309, 0.05369662547355178, -0.116493166087535, -0.3033174429646746, 0.3032705799029238, 0.08211856928003114, 0.3416265296726341, -0.0009955057834784657, 0.14497507146542082, -0.03284317671882176, -0.044485779177491205, -0.0076051011444333025, -0.03660905746929421, 0.18044553447292191, 0.2462647541307556, 0.162900322345349, 0.2543799006790157, -0.3960181536598119, -0.18389154527828377, 0.08283166475623331, 0.13245206835105688, 0.09644450710606088, -0.01673168783023391, -0.35138175568145075, 0.10135352339759562, -0.1337330617426467, -0.020753919861554726, -0.12760657575069312, -0.001210840081403606, -0.0017451696045134427, -0.256173658916879, 0.07085592002456323, 0.0917727776917295, 0.11091725060821704, -0.0785390318872161, -0.11189612424009884, 0.013888789529021853, 0.18672106051583243, -0.005615770269138446, 0.057880069287318106, 0.15261377474738272, -0.21214352451915028, -0.12860783056096825, 0.357112415779218, -0.07409617481301115, -0.2223011027309903, 0.18790963590847995, -0.11179732721088068, -0.1144211573772273, 0.0892004117489728, 0.22742065852917964, 0.0833271578153443, -0.11231473256956856, 0.007289426400159257, -0.05952658552278138, 0.23837995817943378, 0.09180085663647104, -0.002267376238585643, 0.17212074723331924, 0.2595168143487389, 0.015822925804030594, 0.15751128145581428, -0.21244768593050306, -0.03640120826462436, -0.23171109176656735, -0.10594759481986868, -0.2039916323023444, -0.016079923668847005, -0.1282358985397351, -0.10321711187674473, 0.4257089477032423, 0.26611613949069624, 0.25275901259280414, 0.11564416683325837, 0.33561074129253066, 0.006077333358585038, 0.11892890608788954, 0.053859774329342275, 0.20860727187597528, 0.022520230301075948, 0.11823806038958097, -0.19004318706175816, 0.05545378647123774, 0.049834374108486484]
1,802.02184
Wormholes in conformal gravity
We present a new class of solutions for static spherically symmetric wormhole spacetimes in conformal gravity and outline a detailed method for their construction. As an explicit example, we construct a class of traversable and non-traversable wormholes that are locally conformal to Schwarzschild-(anti) de Sitter spacetimes. These wormhole spacetimes are exact vacuum solutions in, but not being limited to, Weyl gravity and conformal scalar-tensor theories. Importantly, the method implies that every conformal theory of gravity with static spherically symmetric solutions will trivially contain wormholes without the need for exotic matter. Applying those results on gravitational theories that possess conformal symmetry in the ultraviolet regime, the central singularities of black holes can be replaced with wormhole throats. We speculate on possible phenomenological consequences. We also discuss the inclusion of matter fields and give explicit examples of charged wormholes in Weyl gravity and conformal scalar-tensor gravity.
gr-qc hep-th
we present a new class of solutions for static spherically symmetric wormhole spacetimes in conformal gravity and outline a detailed method for their construction as an explicit example we construct a class of traversable and nontraversable wormholes that are locally conformal to schwarzschildanti de sitter spacetimes these wormhole spacetimes are exact vacuum solutions in but not being limited to weyl gravity and conformal scalartensor theories importantly the method implies that every conformal theory of gravity with static spherically symmetric solutions will trivially contain wormholes without the need for exotic matter applying those results on gravitational theories that possess conformal symmetry in the ultraviolet regime the central singularities of black holes can be replaced with wormhole throats we speculate on possible phenomenological consequences we also discuss the inclusion of matter fields and give explicit examples of charged wormholes in weyl gravity and conformal scalartensor gravity
[['we', 'present', 'a', 'new', 'class', 'of', 'solutions', 'for', 'static', 'spherically', 'symmetric', 'wormhole', 'spacetimes', 'in', 'conformal', 'gravity', 'and', 'outline', 'a', 'detailed', 'method', 'for', 'their', 'construction', 'as', 'an', 'explicit', 'example', 'we', 'construct', 'a', 'class', 'of', 'traversable', 'and', 'nontraversable', 'wormholes', 'that', 'are', 'locally', 'conformal', 'to', 'schwarzschildanti', 'de', 'sitter', 'spacetimes', 'these', 'wormhole', 'spacetimes', 'are', 'exact', 'vacuum', 'solutions', 'in', 'but', 'not', 'being', 'limited', 'to', 'weyl', 'gravity', 'and', 'conformal', 'scalartensor', 'theories', 'importantly', 'the', 'method', 'implies', 'that', 'every', 'conformal', 'theory', 'of', 'gravity', 'with', 'static', 'spherically', 'symmetric', 'solutions', 'will', 'trivially', 'contain', 'wormholes', 'without', 'the', 'need', 'for', 'exotic', 'matter', 'applying', 'those', 'results', 'on', 'gravitational', 'theories', 'that', 'possess', 'conformal', 'symmetry', 'in', 'the', 'ultraviolet', 'regime', 'the', 'central', 'singularities', 'of', 'black', 'holes', 'can', 'be', 'replaced', 'with', 'wormhole', 'throats', 'we', 'speculate', 'on', 'possible', 'phenomenological', 'consequences', 'we', 'also', 'discuss', 'the', 'inclusion', 'of', 'matter', 'fields', 'and', 'give', 'explicit', 'examples', 'of', 'charged', 'wormholes', 'in', 'weyl', 'gravity', 'and', 'conformal', 'scalartensor', 'gravity']]
[-0.1859174026920098, 0.1179868958175171, -0.11354963273818915, 0.14785643933767764, -0.17589908461862555, -0.22259704805845912, -0.09763088864161142, 0.32783580718872446, -0.08753221556091578, -0.2527382630958325, 0.08270805676309262, -0.2708677792624157, -0.15123082828682122, 0.1389028242815079, -0.07294487016042694, 0.035369919761756644, -0.06251919682189408, 0.02915489096388531, -0.13900176648369073, -0.23437467822966734, 0.4581171831927754, 0.038035027967352, 0.22909212974223514, 0.011978688404067524, 0.08275832116406592, -0.05989811223116703, 0.023097837773497706, 0.09215615898655313, -0.20724830019667528, 0.03406872164749883, 0.23288996744344737, 0.13022504744003527, 0.14822313348445781, -0.4503741924569719, -0.26346752533390827, 0.11031092521605185, 0.1541724754012345, 0.23947516491170973, -0.1453475823040612, -0.35447720050190884, 0.09645936565518948, -0.21941944384808368, -0.2189820521032541, -0.11744947369313902, 0.025570411322405562, -0.07326010385683428, -0.16826056635990325, 0.0890330956169944, 0.03504108890208752, -0.0462199496994597, -0.13254623704738655, -0.005686557125752895, -0.03676320297139076, 0.016161566205684923, 0.14703825529431924, -0.012300300900177617, 0.16093676899173362, -0.14532012997854812, -0.12788910440091664, 0.374287616493853, -0.07349232974876133, -0.27570526361361974, 0.14043876382816556, -0.1850506716226745, -0.154878149900469, 0.06753240131527288, 0.0948701626584807, 0.24286488912508097, -0.12325620259960285, 0.2315904038999482, -0.007892019692614364, 0.0838927859788075, 0.16261320019839332, 0.07719528081927113, 0.3922319014479096, 0.014715929806698114, 0.039810256246710196, 0.1393397902502329, 0.06254821615422973, -0.0896507801541399, -0.47146212856750935, -0.17112277985446175, -0.10308092374503354, 0.10888413638501031, -0.20044572784243225, -0.23323987921079, 0.3169579235012255, 0.09290932573902763, 0.03844488644002316, 0.07182075263214453, 0.15608688445973307, -0.005251917218427277, 0.049227520614901245, 0.13815118558704853, 0.3177964899223298, 0.13065962561975336, 0.10148166198794367, -0.176774562705153, -0.13923865829646173, 0.1246029886387987]
1,802.02185
Smile detection in the wild based on transfer learning
Smile detection from unconstrained facial images is a specialized and challenging problem. As one of the most informative expressions, smiles convey basic underlying emotions, such as happiness and satisfaction, which lead to multiple applications, e.g., human behavior analysis and interactive controlling. Compared to the size of databases for face recognition, far less labeled data is available for training smile detection systems. To leverage the large amount of labeled data from face recognition datasets and to alleviate overfitting on smile detection, an efficient transfer learning-based smile detection approach is proposed in this paper. Unlike previous works which use either hand-engineered features or train deep convolutional networks from scratch, a well-trained deep face recognition model is explored and fine-tuned for smile detection in the wild. Three different models are built as a result of fine-tuning the face recognition model with different inputs, including aligned, unaligned and grayscale images generated from the GENKI-4K dataset. Experiments show that the proposed approach achieves improved state-of-the-art performance. Robustness of the model to noise and blur artifacts is also evaluated in this paper.
cs.CV
smile detection from unconstrained facial images is a specialized and challenging problem as one of the most informative expressions smiles convey basic underlying emotions such as happiness and satisfaction which lead to multiple applications eg human behavior analysis and interactive controlling compared to the size of databases for face recognition far less labeled data is available for training smile detection systems to leverage the large amount of labeled data from face recognition datasets and to alleviate overfitting on smile detection an efficient transfer learningbased smile detection approach is proposed in this paper unlike previous works which use either handengineered features or train deep convolutional networks from scratch a welltrained deep face recognition model is explored and finetuned for smile detection in the wild three different models are built as a result of finetuning the face recognition model with different inputs including aligned unaligned and grayscale images generated from the genki4k dataset experiments show that the proposed approach achieves improved stateoftheart performance robustness of the model to noise and blur artifacts is also evaluated in this paper
[['smile', 'detection', 'from', 'unconstrained', 'facial', 'images', 'is', 'a', 'specialized', 'and', 'challenging', 'problem', 'as', 'one', 'of', 'the', 'most', 'informative', 'expressions', 'smiles', 'convey', 'basic', 'underlying', 'emotions', 'such', 'as', 'happiness', 'and', 'satisfaction', 'which', 'lead', 'to', 'multiple', 'applications', 'eg', 'human', 'behavior', 'analysis', 'and', 'interactive', 'controlling', 'compared', 'to', 'the', 'size', 'of', 'databases', 'for', 'face', 'recognition', 'far', 'less', 'labeled', 'data', 'is', 'available', 'for', 'training', 'smile', 'detection', 'systems', 'to', 'leverage', 'the', 'large', 'amount', 'of', 'labeled', 'data', 'from', 'face', 'recognition', 'datasets', 'and', 'to', 'alleviate', 'overfitting', 'on', 'smile', 'detection', 'an', 'efficient', 'transfer', 'learningbased', 'smile', 'detection', 'approach', 'is', 'proposed', 'in', 'this', 'paper', 'unlike', 'previous', 'works', 'which', 'use', 'either', 'handengineered', 'features', 'or', 'train', 'deep', 'convolutional', 'networks', 'from', 'scratch', 'a', 'welltrained', 'deep', 'face', 'recognition', 'model', 'is', 'explored', 'and', 'finetuned', 'for', 'smile', 'detection', 'in', 'the', 'wild', 'three', 'different', 'models', 'are', 'built', 'as', 'a', 'result', 'of', 'finetuning', 'the', 'face', 'recognition', 'model', 'with', 'different', 'inputs', 'including', 'aligned', 'unaligned', 'and', 'grayscale', 'images', 'generated', 'from', 'the', 'genki4k', 'dataset', 'experiments', 'show', 'that', 'the', 'proposed', 'approach', 'achieves', 'improved', 'stateoftheart', 'performance', 'robustness', 'of', 'the', 'model', 'to', 'noise', 'and', 'blur', 'artifacts', 'is', 'also', 'evaluated', 'in', 'this', 'paper']]
[0.0025484401559723274, -0.04323518987138024, -0.016099172426121574, 0.09540033807379326, -0.11687108500993677, -0.2316156826939966, -0.03467510436395449, 0.45513503557869367, -0.2572033618716523, -0.34957735032907555, 0.12516398886551283, -0.31932821320635935, -0.20427523585435536, 0.21147336742175477, -0.19488238024026422, 0.0758540607915659, 0.17783865377905644, 0.06352684526837298, -0.022435209625899524, -0.27471210428713155, 0.2803608728918646, 0.02327413075171145, 0.36324492538863395, 0.03956847880301731, 0.12283578984040235, -0.06185285556529249, -0.03335711526418371, -0.022640328535011838, -0.012579171870643871, 0.19526989196892827, 0.3110496212977159, 0.22046635362452693, 0.25968563961330804, -0.3979338343760797, -0.23303857598786376, 0.09021777551089015, 0.1404532125953951, 0.14170337401322156, -0.0606757569612403, -0.394261786433469, 0.07346339885145425, -0.1812475413163858, 0.03738898813192334, -0.14356020403227635, -0.006472287743485399, -0.06115736869962088, -0.3111100984258311, 0.06715218166404936, 0.08560142652763586, 0.10457046257331967, -0.03831643110806388, -0.13025878333220525, 0.03341859077768666, 0.21568826476245054, 0.07497107764639492, 0.039324765897222926, 0.1575748571274536, -0.27951480405937346, -0.14730529370451612, 0.38400729455053806, -0.06892344932071864, -0.21613499499857425, 0.22354424451610871, -0.01485693412600085, -0.14082692083237427, 0.13998819715742555, 0.2505729290071343, 0.12701115058601967, -0.15844844740948508, -0.026040780634419728, -0.053958878719380925, 0.19063943647380385, 0.09436969609798065, -0.0298472396922963, 0.17715126780926116, 0.2658935084805957, -0.012813067939132452, 0.1449288690143398, -0.1900779148004949, -0.038993304480931586, -0.1634308275118071, -0.03934784288385085, -0.20764149035992366, -0.04668787691941751, -0.09468493238033261, -0.1513111744501761, 0.39675858359517796, 0.29158156797422896, 0.21773331055816794, 0.13592130592358964, 0.40161432144897324, 0.003459399399081511, 0.13921477363844004, 0.033435463379802445, 0.15296640737780504, -0.08344263396092824, 0.11583185058120372, -0.16464597391762903, 0.12516037216418358, 0.03392330103819924]
1,802.02186
FastNet
Inception and the Resnet family of Convolutional Neural Network archi-tectures have broken records in the past few years, but recent state of the art models have also incurred very high computational cost in terms of training, inference and model size. Making the deployment of these models on Edge devices, impractical. In light of this, we present a new novel architecture that is designed for high computational efficiency on both GPUs and CPUs, and is highly suited for deployment on Mobile Applications, Smart Cameras, Iot devices and controllers as well as low cost drones. Our architecture boasts competitive accuracies on standard Datasets even out-performing the original Resnet. We present below the motivation for this research, the architecture of the network, single test accuracies on CIFAR 10 and CIFAR 100 , a detailed comparison with other well-known architectures and link to an implementation in Keras.
cs.CV cs.AI cs.LG
inception and the resnet family of convolutional neural network architectures have broken records in the past few years but recent state of the art models have also incurred very high computational cost in terms of training inference and model size making the deployment of these models on edge devices impractical in light of this we present a new novel architecture that is designed for high computational efficiency on both gpus and cpus and is highly suited for deployment on mobile applications smart cameras iot devices and controllers as well as low cost drones our architecture boasts competitive accuracies on standard datasets even outperforming the original resnet we present below the motivation for this research the architecture of the network single test accuracies on cifar 10 and cifar 100 a detailed comparison with other wellknown architectures and link to an implementation in keras
[['inception', 'and', 'the', 'resnet', 'family', 'of', 'convolutional', 'neural', 'network', 'architectures', 'have', 'broken', 'records', 'in', 'the', 'past', 'few', 'years', 'but', 'recent', 'state', 'of', 'the', 'art', 'models', 'have', 'also', 'incurred', 'very', 'high', 'computational', 'cost', 'in', 'terms', 'of', 'training', 'inference', 'and', 'model', 'size', 'making', 'the', 'deployment', 'of', 'these', 'models', 'on', 'edge', 'devices', 'impractical', 'in', 'light', 'of', 'this', 'we', 'present', 'a', 'new', 'novel', 'architecture', 'that', 'is', 'designed', 'for', 'high', 'computational', 'efficiency', 'on', 'both', 'gpus', 'and', 'cpus', 'and', 'is', 'highly', 'suited', 'for', 'deployment', 'on', 'mobile', 'applications', 'smart', 'cameras', 'iot', 'devices', 'and', 'controllers', 'as', 'well', 'as', 'low', 'cost', 'drones', 'our', 'architecture', 'boasts', 'competitive', 'accuracies', 'on', 'standard', 'datasets', 'even', 'outperforming', 'the', 'original', 'resnet', 'we', 'present', 'below', 'the', 'motivation', 'for', 'this', 'research', 'the', 'architecture', 'of', 'the', 'network', 'single', 'test', 'accuracies', 'on', 'cifar', '10', 'and', 'cifar', '100', 'a', 'detailed', 'comparison', 'with', 'other', 'wellknown', 'architectures', 'and', 'link', 'to', 'an', 'implementation', 'in', 'keras']]
[-0.11458971589134717, -0.004725394359667635, 0.014744139479761812, 0.02732772829378365, -0.07184792412149811, -0.21097630112182716, 0.04210332290492427, 0.4546538064597358, -0.2226010486483574, -0.39256687293117737, 0.12283234713061279, -0.26179667092485903, -0.165144000090921, 0.2545802113288541, -0.1462795883269561, 0.1122589036100872, 0.17006545151177216, 0.004436881379814635, -0.08693899196313537, -0.32361476169899106, 0.22444350194369614, 0.09655656734510967, 0.3744061000409051, 0.05091733319199526, 0.11424261840424356, -0.07705706980163035, 0.0460782107396189, -0.05007265903823025, -0.020179317600323744, 0.17086459726462483, 0.2589511200382385, 0.1784851613985768, 0.3147244811136748, -0.4643551251182044, -0.20969426431561963, 0.04439520381364814, 0.1293447778599573, 0.05812426356192511, -0.048164617061175564, -0.3074714511085275, 0.09310609117251965, -0.2361731325640199, -0.006567760721352411, -0.13517507659943617, -0.006044550146251707, 0.021089180296206596, -0.21631051386824587, 0.02274717545832842, -0.005590057070203073, 0.08301719628695832, -0.024715868921165066, -0.18320519167562604, 0.02583878033820697, 0.1358181681569246, -0.017632943044357578, 0.025971913329837188, 0.1453577984176891, -0.2223764226909622, -0.16490877102437415, 0.3680498790218082, -0.050021076037115614, -0.15861817247326104, 0.23939557817869517, -0.0049009801898623855, -0.17794357006385608, 0.056686151175904025, 0.2715165640004504, 0.11192402275095523, -0.12987587091342453, 0.03347407214316494, 0.01026250462008404, 0.16784076379533386, 0.026695086174762586, 0.06061014251678552, 0.17200082911729392, 0.3585310010514124, 0.05266290380739161, 0.11163182761954656, -0.14619822878042946, -0.0854018998109329, -0.2013161111136072, -0.11512213813068843, -0.20965123316273093, -0.0041685975697809755, -0.11383902935672331, -0.13100396201644146, 0.4053116971036603, 0.22540002580548466, 0.1637182878428729, 0.15566887878353747, 0.40243697468138917, -0.014276577485233389, 0.17678992597601034, 0.13399819948736735, 0.2031685207826151, 0.013585638449179717, 0.19233908362909627, -0.12704165461538752, 0.05536304658662502, -0.025930229042169742]
1,802.02187
A High-Performance HOG Extractor on FPGA
Pedestrian detection is one of the key problems in emerging self-driving car industry. And HOG algorithm has proven to provide good accuracy for pedestrian detection. There are plenty of research works have been done in accelerating HOG algorithm on FPGA because of its low-power and high-throughput characteristics. In this paper, we present a high-performance HOG architecture for pedestrian detection on a low-cost FPGA platform. It achieves a maximum throughput of 526 FPS with 640x480 input images, which is 3.25 times faster than the state of the art design. The accelerator is integrated with SVM-based prediction in realizing a pedestrian detection system. And the power consumption of the whole system is comparable with the best existing implementations.
cs.CV
pedestrian detection is one of the key problems in emerging selfdriving car industry and hog algorithm has proven to provide good accuracy for pedestrian detection there are plenty of research works have been done in accelerating hog algorithm on fpga because of its lowpower and highthroughput characteristics in this paper we present a highperformance hog architecture for pedestrian detection on a lowcost fpga platform it achieves a maximum throughput of 526 fps with 640x480 input images which is 325 times faster than the state of the art design the accelerator is integrated with svmbased prediction in realizing a pedestrian detection system and the power consumption of the whole system is comparable with the best existing implementations
[['pedestrian', 'detection', 'is', 'one', 'of', 'the', 'key', 'problems', 'in', 'emerging', 'selfdriving', 'car', 'industry', 'and', 'hog', 'algorithm', 'has', 'proven', 'to', 'provide', 'good', 'accuracy', 'for', 'pedestrian', 'detection', 'there', 'are', 'plenty', 'of', 'research', 'works', 'have', 'been', 'done', 'in', 'accelerating', 'hog', 'algorithm', 'on', 'fpga', 'because', 'of', 'its', 'lowpower', 'and', 'highthroughput', 'characteristics', 'in', 'this', 'paper', 'we', 'present', 'a', 'highperformance', 'hog', 'architecture', 'for', 'pedestrian', 'detection', 'on', 'a', 'lowcost', 'fpga', 'platform', 'it', 'achieves', 'a', 'maximum', 'throughput', 'of', '526', 'fps', 'with', '640x480', 'input', 'images', 'which', 'is', '325', 'times', 'faster', 'than', 'the', 'state', 'of', 'the', 'art', 'design', 'the', 'accelerator', 'is', 'integrated', 'with', 'svmbased', 'prediction', 'in', 'realizing', 'a', 'pedestrian', 'detection', 'system', 'and', 'the', 'power', 'consumption', 'of', 'the', 'whole', 'system', 'is', 'comparable', 'with', 'the', 'best', 'existing', 'implementations']]
[-0.12390468544366866, -0.023301539529147076, -0.05887501304246614, -0.036849095427395034, -0.06594488870930569, -0.20798563548155, -0.019283344159264054, 0.46194442249192247, -0.16271687943713162, -0.35078269008803986, 0.10933089687424744, -0.26493173596802455, -0.13982594687519756, 0.29658499581273645, -0.13646187031930634, 0.129262948881911, 0.14091802811539123, 0.05850181500813803, -0.029485614272838072, -0.25817500989370307, 0.1517638752180762, 0.10060503853260186, 0.3944554057570399, 0.046735333218560396, 0.16315746859743677, -0.08564715523369096, -0.00185443378246293, -0.03501511953273338, -0.023207695664966416, 0.18508088456643423, 0.3166586081657944, 0.1854767334338374, 0.2921288417138416, -0.4044706456298972, -0.20463500830248513, 0.0689118640248439, 0.1343093601663613, 0.06203676015038268, -0.08696957737215441, -0.3235951926446809, 0.14180148056700623, -0.2040925483090867, -0.038867005355784606, -0.06331231666664625, 0.03580238624849228, 0.020194879893598885, -0.22348994350036736, 0.014682836124095423, 0.001320400872420327, 0.08775162864637015, -0.022418150374192168, -0.1408203455904531, 0.07279487925677977, 0.12589661049624457, -0.015006921808074775, 0.10396922041625908, 0.1631927244798762, -0.1900551658191975, -0.16701508652025449, 0.3998497253091171, -0.043022174093744855, -0.1528057872201316, 0.19931543017095277, -0.02328643906090794, -0.12341607887055002, 0.13244015876813953, 0.2265553208166364, 0.09290257190627142, -0.13837204343269996, 0.0008801967071184631, -0.029771542529864557, 0.18396351268065386, 0.041605653355684905, 0.026632550951286124, 0.19226436959258442, 0.3576089622902459, 0.09863762441291955, 0.1117506448323999, -0.15575365964644428, -0.06095861211611793, -0.20109059458803225, -0.17790087047113298, -0.17131595282638767, -0.02663281643642755, -0.06927595561300505, -0.11854791731156152, 0.41516725812107325, 0.22471048536806784, 0.14575795993080426, 0.0741559019691616, 0.427826981911243, 0.06526991578043792, 0.12479752053081154, 0.15077404104622788, 0.2128162249192146, -0.011624149432213142, 0.17683521183338097, -0.17848422792178162, 0.09058888889206894, 0.0432075448748194]
1,802.02188
Uptake and outcome of manuscripts in Nature journals by review model and author characteristics
Double-blind peer review has been proposed as a possible solution to avoid implicit referee bias in academic publishing. The aims of this study are to analyse the demographics of corresponding authors choosing double blind peer review, and to identify differences in the editorial outcome of manuscripts depending on their review model. Data includes 128,454 manuscripts received between March 2015 and February 2017 by 25 Nature-branded journals. Author uptake for double-blind was 12%. We found a small but significant association between journal tier and review type. We found no statistically significant difference in the distribution of peer review model between males and females. We found that corresponding authors from the less prestigious institutions are more likely to choose double-blind review. In the ten countries with the highest number of submissions, we found a small but significant association between country and review type. The outcome at both first decision and post review is significantly more negative (i.e. a higher likelihood for rejection) for double than single-blind papers. Authors choose double-blind review more frequently when they submit to more prestigious journals, they are affiliated with less prestigious institutions or they are from specific countries; the double-blind option is also linked to less successful editorial outcomes.
cs.DL cs.CY
doubleblind peer review has been proposed as a possible solution to avoid implicit referee bias in academic publishing the aims of this study are to analyse the demographics of corresponding authors choosing double blind peer review and to identify differences in the editorial outcome of manuscripts depending on their review model data includes 128454 manuscripts received between march 2015 and february 2017 by 25 naturebranded journals author uptake for doubleblind was 12 we found a small but significant association between journal tier and review type we found no statistically significant difference in the distribution of peer review model between males and females we found that corresponding authors from the less prestigious institutions are more likely to choose doubleblind review in the ten countries with the highest number of submissions we found a small but significant association between country and review type the outcome at both first decision and post review is significantly more negative ie a higher likelihood for rejection for double than singleblind papers authors choose doubleblind review more frequently when they submit to more prestigious journals they are affiliated with less prestigious institutions or they are from specific countries the doubleblind option is also linked to less successful editorial outcomes
[['doubleblind', 'peer', 'review', 'has', 'been', 'proposed', 'as', 'a', 'possible', 'solution', 'to', 'avoid', 'implicit', 'referee', 'bias', 'in', 'academic', 'publishing', 'the', 'aims', 'of', 'this', 'study', 'are', 'to', 'analyse', 'the', 'demographics', 'of', 'corresponding', 'authors', 'choosing', 'double', 'blind', 'peer', 'review', 'and', 'to', 'identify', 'differences', 'in', 'the', 'editorial', 'outcome', 'of', 'manuscripts', 'depending', 'on', 'their', 'review', 'model', 'data', 'includes', '128454', 'manuscripts', 'received', 'between', 'march', '2015', 'and', 'february', '2017', 'by', '25', 'naturebranded', 'journals', 'author', 'uptake', 'for', 'doubleblind', 'was', '12', 'we', 'found', 'a', 'small', 'but', 'significant', 'association', 'between', 'journal', 'tier', 'and', 'review', 'type', 'we', 'found', 'no', 'statistically', 'significant', 'difference', 'in', 'the', 'distribution', 'of', 'peer', 'review', 'model', 'between', 'males', 'and', 'females', 'we', 'found', 'that', 'corresponding', 'authors', 'from', 'the', 'less', 'prestigious', 'institutions', 'are', 'more', 'likely', 'to', 'choose', 'doubleblind', 'review', 'in', 'the', 'ten', 'countries', 'with', 'the', 'highest', 'number', 'of', 'submissions', 'we', 'found', 'a', 'small', 'but', 'significant', 'association', 'between', 'country', 'and', 'review', 'type', 'the', 'outcome', 'at', 'both', 'first', 'decision', 'and', 'post', 'review', 'is', 'significantly', 'more', 'negative', 'ie', 'a', 'higher', 'likelihood', 'for', 'rejection', 'for', 'double', 'than', 'singleblind', 'papers', 'authors', 'choose', 'doubleblind', 'review', 'more', 'frequently', 'when', 'they', 'submit', 'to', 'more', 'prestigious', 'journals', 'they', 'are', 'affiliated', 'with', 'less', 'prestigious', 'institutions', 'or', 'they', 'are', 'from', 'specific', 'countries', 'the', 'doubleblind', 'option', 'is', 'also', 'linked', 'to', 'less', 'successful', 'editorial', 'outcomes']]
[-0.05652366393158445, 0.069474686193862, -0.04072401107288897, 0.11496859281614888, -0.1478700406779535, -0.16659721068805083, 0.1397085418831557, 0.4072562315128744, -0.13401868626708166, -0.37910126708447933, 0.07231187974932254, -0.3731278747878969, -0.13254584248701576, 0.15954038272961044, -0.13764155118202326, -0.07421978087630123, 0.09222538643050938, 0.049033555905334654, -0.019174638953700196, -0.3786954819317907, 0.28675553065026177, 0.11377960490179248, 0.3042125790799037, 0.018244601692422292, 0.0032752329763025044, -0.05083776023820974, -0.20602537368889898, -0.011193552101030946, -0.1412929368971163, 0.1093316381960176, 0.32610922584775837, 0.16732930403319188, 0.40946690960787235, -0.39933647096157077, -0.10178746302146464, 0.07965096222935245, 0.08388155651278793, 0.07856349023990333, -0.027520442688983168, -0.27095010566525163, 0.05195661009289324, -0.25860276181425434, -0.03302736497571459, -0.021220251803752036, 0.10401895891875029, 0.00592310365056619, -0.1804810819355771, 0.08722251087296172, -0.021801888304762543, 0.13883186115883292, -0.00819075712468475, -0.2195075950375758, -0.010275197093142197, 0.16565105714442324, 0.12435730402357877, 0.022043252857984044, 0.1124233973538503, -0.14087343714782036, -0.1458804459683597, 0.3606240248866379, 0.014113238904028548, -0.12310455583501607, 0.19864359117578714, -0.15474275117740036, -0.1779450934525812, 0.06558391663827934, 0.2172847649315372, 0.05662676844513044, -0.2036812957647635, -0.04224236837995704, -0.016107975363265723, 0.19034934459836222, 0.12654082710389047, -0.032222743908059785, 0.17213917501969264, 0.12103127622161992, 0.02615806020097807, 0.06434778030961752, -0.03299345627776347, -0.10932871442084434, -0.2528253107704222, -0.13995991489151494, -0.08581853929557838, 0.032659584268694745, -0.005671721512480871, -0.12327570176683367, 0.3840303659439087, 0.16159116519185773, 0.09119132466614246, -0.01048994596581906, 0.20633077308302744, 0.02390470386540983, 0.04687307543703355, 0.0936827936861664, 0.2304703133297153, 0.041173723163083195, 0.19411141298711299, -0.09201933977194131, 0.15620655640028416, -0.0035655631532426923]
1,802.02189
Mars Thermospheric Variability Revealed by MAVEN EUVM Solar Occultations: Structure at Aphelion and Perihelion, and Response to EUV Forcing
The Mars thermosphere holds clues to the evolution of the Martian climate, and has practical implications for spacecraft visiting Mars, which often use it for aerobraking upon arrival, or for landers, which must pass through it. Nevertheless, it has been sparsely characterized, even when past accelerometer measurements and remote observations are taken into account. The Mars Atmosphere and Volatile EvolutioN (MAVEN) orbiter, which includes a number of instruments designed to characterize the thermosphere, has greatly expanded the available thermospheric observations. This paper presents new and unanticipated measurements of density and temperature profiles (120-200 km) derived from solar occultations using the MAVEN Extreme Ultraviolet (EUV) Monitor. These new measurements complement and expand MAVEN's intended thermospheric measurement capacity. In particular, because the local-time is inherently fixed to the terminator, solar occultations are ideally suited for characterizing long-term and latitudinal variability. Occultation measurements are made during approximately half of all orbits, resulting in thousands of new thermospheric profiles. The density retrieval method is presented in detail, including an uncertainty analysis. Altitude-latitude maps of thermospheric density and temperature at perihelion and aphelion are presented, revealing structures that have not been previously observed. Tracers of atmospheric dynamics are also observed, including a high altitude polar warming feature at intermediate latitudes, and an apparent thermostatic response to solar EUV heating during a solar rotation, which shows heating at high altitudes that is accompanied by cooling at lower altitudes.
astro-ph.EP
the mars thermosphere holds clues to the evolution of the martian climate and has practical implications for spacecraft visiting mars which often use it for aerobraking upon arrival or for landers which must pass through it nevertheless it has been sparsely characterized even when past accelerometer measurements and remote observations are taken into account the mars atmosphere and volatile evolution maven orbiter which includes a number of instruments designed to characterize the thermosphere has greatly expanded the available thermospheric observations this paper presents new and unanticipated measurements of density and temperature profiles 120200 km derived from solar occultations using the maven extreme ultraviolet euv monitor these new measurements complement and expand mavens intended thermospheric measurement capacity in particular because the localtime is inherently fixed to the terminator solar occultations are ideally suited for characterizing longterm and latitudinal variability occultation measurements are made during approximately half of all orbits resulting in thousands of new thermospheric profiles the density retrieval method is presented in detail including an uncertainty analysis altitudelatitude maps of thermospheric density and temperature at perihelion and aphelion are presented revealing structures that have not been previously observed tracers of atmospheric dynamics are also observed including a high altitude polar warming feature at intermediate latitudes and an apparent thermostatic response to solar euv heating during a solar rotation which shows heating at high altitudes that is accompanied by cooling at lower altitudes
[['the', 'mars', 'thermosphere', 'holds', 'clues', 'to', 'the', 'evolution', 'of', 'the', 'martian', 'climate', 'and', 'has', 'practical', 'implications', 'for', 'spacecraft', 'visiting', 'mars', 'which', 'often', 'use', 'it', 'for', 'aerobraking', 'upon', 'arrival', 'or', 'for', 'landers', 'which', 'must', 'pass', 'through', 'it', 'nevertheless', 'it', 'has', 'been', 'sparsely', 'characterized', 'even', 'when', 'past', 'accelerometer', 'measurements', 'and', 'remote', 'observations', 'are', 'taken', 'into', 'account', 'the', 'mars', 'atmosphere', 'and', 'volatile', 'evolution', 'maven', 'orbiter', 'which', 'includes', 'a', 'number', 'of', 'instruments', 'designed', 'to', 'characterize', 'the', 'thermosphere', 'has', 'greatly', 'expanded', 'the', 'available', 'thermospheric', 'observations', 'this', 'paper', 'presents', 'new', 'and', 'unanticipated', 'measurements', 'of', 'density', 'and', 'temperature', 'profiles', '120200', 'km', 'derived', 'from', 'solar', 'occultations', 'using', 'the', 'maven', 'extreme', 'ultraviolet', 'euv', 'monitor', 'these', 'new', 'measurements', 'complement', 'and', 'expand', 'mavens', 'intended', 'thermospheric', 'measurement', 'capacity', 'in', 'particular', 'because', 'the', 'localtime', 'is', 'inherently', 'fixed', 'to', 'the', 'terminator', 'solar', 'occultations', 'are', 'ideally', 'suited', 'for', 'characterizing', 'longterm', 'and', 'latitudinal', 'variability', 'occultation', 'measurements', 'are', 'made', 'during', 'approximately', 'half', 'of', 'all', 'orbits', 'resulting', 'in', 'thousands', 'of', 'new', 'thermospheric', 'profiles', 'the', 'density', 'retrieval', 'method', 'is', 'presented', 'in', 'detail', 'including', 'an', 'uncertainty', 'analysis', 'altitudelatitude', 'maps', 'of', 'thermospheric', 'density', 'and', 'temperature', 'at', 'perihelion', 'and', 'aphelion', 'are', 'presented', 'revealing', 'structures', 'that', 'have', 'not', 'been', 'previously', 'observed', 'tracers', 'of', 'atmospheric', 'dynamics', 'are', 'also', 'observed', 'including', 'a', 'high', 'altitude', 'polar', 'warming', 'feature', 'at', 'intermediate', 'latitudes', 'and', 'an', 'apparent', 'thermostatic', 'response', 'to', 'solar', 'euv', 'heating', 'during', 'a', 'solar', 'rotation', 'which', 'shows', 'heating', 'at', 'high', 'altitudes', 'that', 'is', 'accompanied', 'by', 'cooling', 'at', 'lower', 'altitudes']]
[-0.07565044637860346, 0.21273347365135314, -0.058966096689753035, 0.06356245117862463, -0.05682003862590104, -0.07418147527373788, 0.010026342032799954, 0.3876044055336694, -0.20916100114935257, -0.38763487149895937, 0.1492973094057545, -0.2783916205159601, -0.10962110003783253, 0.24615942261471788, -0.08258579599491336, 0.04229048265985687, 0.09083446784911518, -0.029656844876865904, -0.031027055717698346, -0.21273610561937012, 0.19275694094463497, 0.17245800264910877, 0.17836020170024744, 0.038490648113988675, 0.10263143901778549, -0.06954207589845746, -0.06330953991416384, -0.011763517727479012, -0.1318325412977541, 0.06036623448463822, 0.2641905937877406, 0.1581099673864644, 0.1949906922517377, -0.46310161829419566, -0.2860020002348424, 0.020139317718546903, 0.1051145479912265, 0.013062948414140888, -0.03999856609867461, -0.2546810390746319, -0.008784397217249008, -0.14627866950008625, -0.1423934883674966, -0.021221195423174976, 0.05522232212981754, 0.0023008555280077353, -0.2737210577276225, 0.03971675962294971, -0.004766677106983894, 0.1804757893714531, -0.1301529906940822, -0.11639239279177498, -0.08297139922312151, 0.15456473162633125, 0.06721789906262993, -0.005143519885646049, 0.18066121030112794, -0.050356188852323645, -0.0012769176759512017, 0.37648560349796817, -0.07636888741245984, -0.016910318488953635, 0.22551052037038302, -0.24173467648991695, -0.15054580070928, 0.21181345032834398, 0.1778166801316394, 0.06949672554905542, -0.16953798954298754, -0.001493812369166367, -0.001562470488001086, 0.16061617223558164, 0.11497482972366638, 0.027453038662778248, 0.31114657611275714, 0.1337809235249695, 0.08630333841791614, 0.06592361990100983, -0.2255209687782713, -0.060875787960340905, -0.208073575534192, -0.10214698104097981, -0.11897523815742604, 0.007325144975383361, -0.054300897235327536, -0.1179958954867049, 0.36854781007206294, 0.1977539377301327, 0.15702609049274766, -0.007375249240890537, 0.3515999338940897, 0.08021557221511837, 0.065495400791661, 0.13868644169180475, 0.31109234233582883, 0.10556102211826089, 0.1738150984767759, -0.21529638166069626, 0.16416925776202493, 0.018911875804820864]
1,802.0219
Velocimetry of cold atoms by matterwave interferometry
We present an elegant application of matterwave interferometry to the velocimetry of cold atoms whereby, in analogy to Fourier transform spectroscopy, the 1-D velocity distribution is manifest in the frequency domain of the interferometer output. By using stimulated Raman transitions between hyperfine ground states to perform a three-pulse interferometer sequence, we have measured the velocity distributions of clouds of freely-expanding $^{85}$Rb atoms with temperatures of 33 $\mu$K and 17 $\mu$K. Quadrature measurement of the interferometer output as a function of the temporal asymmetry yields velocity distributions with excellent fidelity. Our technique, which is particularly suited to ultracold samples, compares favourably with conventional Doppler and time-of-flight techniques, and reveals artefacts in standard Raman Doppler methods. The technique is related to, and provides a conceptual foundation of, interferometric matterwave accelerometry, gravimetry and rotation sensing.
physics.atom-ph quant-ph
we present an elegant application of matterwave interferometry to the velocimetry of cold atoms whereby in analogy to fourier transform spectroscopy the 1d velocity distribution is manifest in the frequency domain of the interferometer output by using stimulated raman transitions between hyperfine ground states to perform a threepulse interferometer sequence we have measured the velocity distributions of clouds of freelyexpanding 85rb atoms with temperatures of 33 muk and 17 muk quadrature measurement of the interferometer output as a function of the temporal asymmetry yields velocity distributions with excellent fidelity our technique which is particularly suited to ultracold samples compares favourably with conventional doppler and timeofflight techniques and reveals artefacts in standard raman doppler methods the technique is related to and provides a conceptual foundation of interferometric matterwave accelerometry gravimetry and rotation sensing
[['we', 'present', 'an', 'elegant', 'application', 'of', 'matterwave', 'interferometry', 'to', 'the', 'velocimetry', 'of', 'cold', 'atoms', 'whereby', 'in', 'analogy', 'to', 'fourier', 'transform', 'spectroscopy', 'the', '1d', 'velocity', 'distribution', 'is', 'manifest', 'in', 'the', 'frequency', 'domain', 'of', 'the', 'interferometer', 'output', 'by', 'using', 'stimulated', 'raman', 'transitions', 'between', 'hyperfine', 'ground', 'states', 'to', 'perform', 'a', 'threepulse', 'interferometer', 'sequence', 'we', 'have', 'measured', 'the', 'velocity', 'distributions', 'of', 'clouds', 'of', 'freelyexpanding', '85rb', 'atoms', 'with', 'temperatures', 'of', '33', 'muk', 'and', '17', 'muk', 'quadrature', 'measurement', 'of', 'the', 'interferometer', 'output', 'as', 'a', 'function', 'of', 'the', 'temporal', 'asymmetry', 'yields', 'velocity', 'distributions', 'with', 'excellent', 'fidelity', 'our', 'technique', 'which', 'is', 'particularly', 'suited', 'to', 'ultracold', 'samples', 'compares', 'favourably', 'with', 'conventional', 'doppler', 'and', 'timeofflight', 'techniques', 'and', 'reveals', 'artefacts', 'in', 'standard', 'raman', 'doppler', 'methods', 'the', 'technique', 'is', 'related', 'to', 'and', 'provides', 'a', 'conceptual', 'foundation', 'of', 'interferometric', 'matterwave', 'accelerometry', 'gravimetry', 'and', 'rotation', 'sensing']]
[-0.07842394278497633, 0.16964295936607718, -0.13465940970292484, 0.00507860310167554, -0.014363679593908742, -0.13221763407063641, 0.06021166054393468, 0.458149890810477, -0.221439432437447, -0.29428693393922667, -0.004882937917224781, -0.26639451994207886, -0.061656600809797193, 0.24447542086074298, -0.02117300279099833, 0.12455626615679427, 0.0684362738957685, -0.04691183309390026, -0.06476302855387048, -0.13202999862418932, 0.24647436661391772, 0.09970814376455647, 0.3108405393449533, -0.030458474457687276, 0.12779135863776458, -0.012271046829868503, -0.03720552522590327, -0.05525737168323813, -0.08534479671101453, 0.10167844061321706, 0.26680318563717953, 0.08851328590941249, 0.20724474159633796, -0.39263946420484874, -0.18776657806257857, 0.0593914895875831, 0.1661208869349635, 0.16475689177186173, -0.032169867685297504, -0.36657561097914976, -0.07233814790026483, -0.12344558036332301, -0.13675879365870391, -0.12544190169622502, 0.01751914792200268, 0.055226163949224756, -0.28216367464329145, 0.11746039377723003, -0.029109932813849864, 0.1358455972125133, -0.045861565758417724, -0.08995950378117744, 0.06888491315520227, 0.052838090704895105, -0.06777297756740484, 0.06486633205151354, 0.1553464678405417, -0.07917372374372049, -0.10951446221830945, 0.40319442149308143, -0.15080476473601515, -0.09322014804506167, 0.1841242777211874, -0.17791706312158512, -0.05798844882343529, 0.13814831902378832, 0.10629940257499446, 0.10206082726962808, -0.08165897372104651, -0.02832091510847959, -0.01049012712125356, 0.2243370523034228, 0.1492199589794671, 0.11784105933849898, 0.20192849576988287, 0.16209587561245303, 0.03722470636994606, 0.17372228064006334, -0.2601547520568023, -0.05339788674962509, -0.2146274131779192, -0.15063582755321864, -0.20378547893470209, 0.010657739095305178, -0.03581078381885715, -0.10391541543261458, 0.33547775539089786, 0.15752560387464296, 0.19685755167720895, -0.03316853997195281, 0.41945528154346073, 0.1127305461312503, 0.04983076317038274, -0.04086401663583026, 0.23922052473680003, 0.2580689548260786, 0.1286085414432102, -0.2881159129945886, -0.025958280442423667, 0.0012858637386340308]
1,802.02191
Cellular Cohomology in Homotopy Type Theory
We present a development of cellular cohomology in homotopy type theory. Cohomology associates to each space a sequence of abelian groups capturing part of its structure, and has the advantage over homotopy groups in that these abelian groups of many common spaces are easier to compute. Cellular cohomology is a special kind of cohomology designed for cell complexes: these are built in stages by attaching spheres of progressively higher dimension, and cellular cohomology defines the groups out of the combinatorial description of how spheres are attached. Our main result is that for finite cell complexes, a wide class of cohomology theories (including the ones defined through Eilenberg-MacLane spaces) can be calculated via cellular cohomology. This result was formalized in the Agda proof assistant.
cs.LO math.AT
we present a development of cellular cohomology in homotopy type theory cohomology associates to each space a sequence of abelian groups capturing part of its structure and has the advantage over homotopy groups in that these abelian groups of many common spaces are easier to compute cellular cohomology is a special kind of cohomology designed for cell complexes these are built in stages by attaching spheres of progressively higher dimension and cellular cohomology defines the groups out of the combinatorial description of how spheres are attached our main result is that for finite cell complexes a wide class of cohomology theories including the ones defined through eilenbergmaclane spaces can be calculated via cellular cohomology this result was formalized in the agda proof assistant
[['we', 'present', 'a', 'development', 'of', 'cellular', 'cohomology', 'in', 'homotopy', 'type', 'theory', 'cohomology', 'associates', 'to', 'each', 'space', 'a', 'sequence', 'of', 'abelian', 'groups', 'capturing', 'part', 'of', 'its', 'structure', 'and', 'has', 'the', 'advantage', 'over', 'homotopy', 'groups', 'in', 'that', 'these', 'abelian', 'groups', 'of', 'many', 'common', 'spaces', 'are', 'easier', 'to', 'compute', 'cellular', 'cohomology', 'is', 'a', 'special', 'kind', 'of', 'cohomology', 'designed', 'for', 'cell', 'complexes', 'these', 'are', 'built', 'in', 'stages', 'by', 'attaching', 'spheres', 'of', 'progressively', 'higher', 'dimension', 'and', 'cellular', 'cohomology', 'defines', 'the', 'groups', 'out', 'of', 'the', 'combinatorial', 'description', 'of', 'how', 'spheres', 'are', 'attached', 'our', 'main', 'result', 'is', 'that', 'for', 'finite', 'cell', 'complexes', 'a', 'wide', 'class', 'of', 'cohomology', 'theories', 'including', 'the', 'ones', 'defined', 'through', 'eilenbergmaclane', 'spaces', 'can', 'be', 'calculated', 'via', 'cellular', 'cohomology', 'this', 'result', 'was', 'formalized', 'in', 'the', 'agda', 'proof', 'assistant']]
[-0.17610178049464476, 0.08322631041102899, -0.09888806793747879, 0.07951818643293034, -0.07275955071218493, -0.12348125116687601, -0.01380261773341979, 0.354665511310464, -0.33381325340776785, -0.22900041436579655, 0.09083160210771835, -0.173856704724892, -0.17767157815623938, 0.18768112145636867, -0.15927614233214257, -0.08101733036413107, 0.028977961679806978, 0.0828009719612092, -0.00834998132643712, -0.29085698008927235, 0.42395584337125586, -0.02403977904771644, 0.2537937737797028, 0.021067057910367726, 0.06412622501422477, -0.003698933210859938, -0.051095908784072816, 0.003759090913359333, -0.11615507113541443, 0.19043161425686525, 0.39618440196523824, 0.05064131459410537, 0.22708067334469076, -0.39944115121720164, -0.17103538495617185, 0.14763071759636098, 0.15079208005719433, 0.03659516501778025, -0.018299303115989134, -0.27367865166255856, 0.1385791858504867, -0.2182762220500007, -0.12729486407015503, -0.10212601916637362, 0.029617908199666053, 0.055232483772485234, -0.16750945061742425, -0.059769119232574976, 0.04116348670492691, 0.13724905790049372, -0.11011400195387594, -0.06860537958384408, -0.07435965335670465, 0.1700387367726932, -0.04777758756493468, -0.004588810531081768, 0.16886139459287128, -0.08305704291357197, -0.17119962383606813, 0.4228239691649692, -0.01280870969308828, -0.19866471124313226, 0.1952587637039492, -0.13987441258353553, -0.22365389008271863, 0.17892917189311722, 0.05008317992219898, 0.16875193634153746, -0.039009736995193806, 0.15550407969744923, -0.07048675754841993, 0.07841787062494493, 0.10051524529718166, 0.0057185112112542475, 0.1542996297802443, 0.17343626987204197, 0.05041405180756881, 0.1476778748693187, 0.02803479498858011, -0.11701563515083303, -0.3110566498726849, -0.23464137555016734, -0.13227147822518173, 0.10389251374011117, -0.08089705815939119, -0.16966476411713907, 0.39964536993529615, 0.0416816866850647, 0.1255264958609047, 0.1561574763277682, 0.23471094234808673, 0.01468736015551731, 0.13622890235250437, -0.04107825752590003, 0.1071387754613155, 0.22352631281061872, 0.03896815667394549, -0.07789340977201133, -0.008293410626853384, 0.27664534817260455]
1,802.02192
Counting rational points and lower bounds for Galois orbits
In this article we present a new method to obtain polynomial lower bounds for Galois orbits of torsion points of one dimensional group varieties.
math.NT
in this article we present a new method to obtain polynomial lower bounds for galois orbits of torsion points of one dimensional group varieties
[['in', 'this', 'article', 'we', 'present', 'a', 'new', 'method', 'to', 'obtain', 'polynomial', 'lower', 'bounds', 'for', 'galois', 'orbits', 'of', 'torsion', 'points', 'of', 'one', 'dimensional', 'group', 'varieties']]
[-0.22383288689889014, 0.018761874681028228, -0.16006387425780608, 0.043804857001911536, -0.14125965923691788, -0.1326516911503859, 0.05642930491012521, 0.2638297102724512, -0.29506255600911874, -0.25355604413198307, 0.05679880680690985, -0.17776246873351434, -0.15316738866386004, 0.28483751346357167, -0.1826746177781994, 0.0021788201217229166, 0.03648830569970111, 0.10965855542356924, -0.1297207596944645, -0.4040154848092546, 0.40990350892146427, -0.032685610271679856, 0.14723717797702798, 0.019092786669110257, 0.12003934464883059, -0.05393377245248606, 0.012288692407310009, -0.055738184096602104, -0.23115227522794157, 0.2118391237066438, 0.3511573633489509, 0.01581044673609237, 0.19654105132212862, -0.3756389770035942, -0.11754882795503363, 0.2429527104832232, 0.1581324898482611, 0.12891813724612197, -0.0753758056089282, -0.25473686963475, 0.09941621962934732, -0.17720020903895298, -0.2109449009100596, -0.10834251716732979, 0.03517902485327795, -0.02495723815324406, -0.23237116638726243, 0.027046712474354234, 0.06383148066621895, 0.226492892135866, -0.058839518033588924, -0.1479015223449096, 0.06715927358406286, 0.05011424769569809, 0.03462378967863818, 0.0029920982973029218, 0.019807831597669672, -0.06766536726505971, -0.14489874329107502, 0.3751824312688162, -0.0942868417672192, -0.19570254806118706, 0.14529595302883536, -0.20254230309122553, -0.23798899841494858, 0.1350332936272025, 0.24331316930086663, 0.20904843276366591, -0.05770134677489599, 0.15353043047556034, -0.15451834560371935, 0.05720232962630689, 0.09194124210625887, -0.014584079151973128, 0.09822436598672842, 0.0948541663819924, 0.18645590039280555, 0.14372387062758207, -0.013301325166442743, 0.027843256675017376, -0.34717000151673955, -0.2287734441148738, -0.09268105371544759, 0.03459928665931026, -0.12182367517380044, -0.18913243970503876, 0.4309187987819314, 0.1444268689447199, 0.17819125608851513, 0.16596168749189624, 0.26894732580209774, 0.08081528746212523, 0.0033353347486505904, 0.09694827972756077, 0.15843218724088123, 0.21217396203428507, -0.07243137457408011, -0.10118634020909667, -0.10234610526822507, 0.28834433005734655]
1,802.02193
Asymptotic Analysis of Normalized SNR-Based Scheduling in Uplink Cellular Networks with Truncated Channel Inversion Power Control
This paper provides the signal-to-interference-plus-noise ratio (SINR) complimentary cumulative distribution function (CCDF) and average data rate of the normalized SNR-based scheduling in an uplink cellular network using stochastic geometry. The uplink analysis is essentially different from the downlink analysis in that the per-user transmit power control is performed and that the interferers are composed of at most one transmitting user in each cell other than the target cell. In addition, as the effect of multi-user diversity varies from cell to cell depending on the number of users involved in the scheduling, the distribution of the number of users is required to obtain the averaged performance of the scheduling. This paper derives the SINR CCDF relative to the typical scheduled user by focusing on two incompatible cases, where the scheduler selects a user from all the users in the corresponding Voronoi cell or does not select users near cell edges. In each case, the SINR CCDF is marginalized over the distribution of the number of users involved in the scheduling, which is asymptotically correct if the BS density is sufficiently large or small. Through the simulations, the accuracies of the analytical results are validated for both cases, and the scheduling gains are evaluated to confirm the multi-user diversity gain.
cs.IT math.IT
this paper provides the signaltointerferenceplusnoise ratio sinr complimentary cumulative distribution function ccdf and average data rate of the normalized snrbased scheduling in an uplink cellular network using stochastic geometry the uplink analysis is essentially different from the downlink analysis in that the peruser transmit power control is performed and that the interferers are composed of at most one transmitting user in each cell other than the target cell in addition as the effect of multiuser diversity varies from cell to cell depending on the number of users involved in the scheduling the distribution of the number of users is required to obtain the averaged performance of the scheduling this paper derives the sinr ccdf relative to the typical scheduled user by focusing on two incompatible cases where the scheduler selects a user from all the users in the corresponding voronoi cell or does not select users near cell edges in each case the sinr ccdf is marginalized over the distribution of the number of users involved in the scheduling which is asymptotically correct if the bs density is sufficiently large or small through the simulations the accuracies of the analytical results are validated for both cases and the scheduling gains are evaluated to confirm the multiuser diversity gain
[['this', 'paper', 'provides', 'the', 'signaltointerferenceplusnoise', 'ratio', 'sinr', 'complimentary', 'cumulative', 'distribution', 'function', 'ccdf', 'and', 'average', 'data', 'rate', 'of', 'the', 'normalized', 'snrbased', 'scheduling', 'in', 'an', 'uplink', 'cellular', 'network', 'using', 'stochastic', 'geometry', 'the', 'uplink', 'analysis', 'is', 'essentially', 'different', 'from', 'the', 'downlink', 'analysis', 'in', 'that', 'the', 'peruser', 'transmit', 'power', 'control', 'is', 'performed', 'and', 'that', 'the', 'interferers', 'are', 'composed', 'of', 'at', 'most', 'one', 'transmitting', 'user', 'in', 'each', 'cell', 'other', 'than', 'the', 'target', 'cell', 'in', 'addition', 'as', 'the', 'effect', 'of', 'multiuser', 'diversity', 'varies', 'from', 'cell', 'to', 'cell', 'depending', 'on', 'the', 'number', 'of', 'users', 'involved', 'in', 'the', 'scheduling', 'the', 'distribution', 'of', 'the', 'number', 'of', 'users', 'is', 'required', 'to', 'obtain', 'the', 'averaged', 'performance', 'of', 'the', 'scheduling', 'this', 'paper', 'derives', 'the', 'sinr', 'ccdf', 'relative', 'to', 'the', 'typical', 'scheduled', 'user', 'by', 'focusing', 'on', 'two', 'incompatible', 'cases', 'where', 'the', 'scheduler', 'selects', 'a', 'user', 'from', 'all', 'the', 'users', 'in', 'the', 'corresponding', 'voronoi', 'cell', 'or', 'does', 'not', 'select', 'users', 'near', 'cell', 'edges', 'in', 'each', 'case', 'the', 'sinr', 'ccdf', 'is', 'marginalized', 'over', 'the', 'distribution', 'of', 'the', 'number', 'of', 'users', 'involved', 'in', 'the', 'scheduling', 'which', 'is', 'asymptotically', 'correct', 'if', 'the', 'bs', 'density', 'is', 'sufficiently', 'large', 'or', 'small', 'through', 'the', 'simulations', 'the', 'accuracies', 'of', 'the', 'analytical', 'results', 'are', 'validated', 'for', 'both', 'cases', 'and', 'the', 'scheduling', 'gains', 'are', 'evaluated', 'to', 'confirm', 'the', 'multiuser', 'diversity', 'gain']]
[-0.19956655379904148, 0.02214940450308999, -0.01256701535665063, 0.0171879318547256, -0.05727584380432605, -0.1731474025582429, 0.1342130744496199, 0.35435497711072317, -0.22304840887227328, -0.2949620873506109, 0.04495642863184912, -0.28113297602305043, -0.14452548414164296, 0.13678972476806778, -0.11072254813580702, 0.021627468897070054, 0.03472688588170478, 0.10506492578245413, 0.0005059044521588546, -0.2944094407766198, 0.2786527530955097, 0.11660090083471285, 0.3669642994332557, -0.007058595208666072, 0.06191275975624404, 0.0294390510694379, -0.049558434422718935, -0.00987856719762721, -0.09463394170464969, 0.07050142472368091, 0.2972027827266944, 0.21612372130039148, 0.2842898814235993, -0.40794402805533114, -0.20241131463710468, 0.09095568885543169, 0.188758340622651, 0.005875839168416301, -0.005827994325395243, -0.21981194937633028, 0.1469601180707776, -0.18382733624625522, -0.02016286872766124, 0.05575626545760315, -0.06420728053993886, 0.10908545116231275, -0.36491381950327195, 0.025953382561475828, -0.043501848839451455, 0.03230272367811547, -0.06210490321189774, -0.15532509286780483, -0.023137258170978524, 0.2240664625340007, 0.08019506477509052, -0.04149129723933024, 0.14774902966634657, -0.12508236718601368, -0.06440815949231539, 0.402272901215698, 0.012039843499713663, -0.2604740182421385, 0.13536004511899172, -0.15444576437808932, -0.07718874709882165, 0.1877286970725086, 0.23891323290836924, 0.07951407211993892, -0.17779343476733908, 0.015696964646709742, -0.048349882467076756, 0.16954770281825823, 0.10623913809943658, 0.06280540247994046, 0.15032587603939015, 0.19680572830111487, 0.13080147722212132, 0.11844567682559361, -0.14311132116171604, -0.12516193608574283, -0.25284955008268856, -0.11019424501752767, -0.2365130542893894, 0.006174256154316446, -0.13885287399149931, -0.08148930368882318, 0.39635709840177485, 0.11995145941126303, 0.15717943340692167, 0.15250253714811363, 0.37754093340257755, 0.13656604039435757, 0.03240425277237172, 0.11215332915778092, 0.18285295476317304, 0.0691329316536072, 0.13549740083768624, -0.25583667897892437, 0.0962451620255776, -0.014010086231372463]
1,802.02194
On the length and depth of finite groups (with an appendix by D.R. Heath-Brown)
An unrefinable chain of a finite group $G$ is a chain of subgroups $G = G_0 > G_1 > \cdots > G_t = 1$, where each $G_i$ is a maximal subgroup of $G_{i-1}$. The length (respectively, depth) of $G$ is the maximal (respectively, minimal) length of such a chain. We studied the depth of finite simple groups in a previous paper, which included a classification of the simple groups of depth $3$. Here we go much further by determining the finite groups of depth $3$ and $4$. We also obtain several new results on the lengths of finite groups. For example, we classify the simple groups of length at most $9$, which extends earlier work of Janko and Harada from the 1960s, and we use this to describe the structure of arbitrary finite groups of small length. We also present a number-theoretic result of Heath-Brown, which implies that there are infinitely many non-abelian simple groups of length at most $9$. Finally we study the chain difference of $G$ (namely the length minus the depth). We obtain results on groups with chain difference $1$ and $2$, including a complete classification of the simple groups with chain difference $2$, extending earlier work of Brewster et al. We also derive a best possible lower bound on the chain ratio (the length divided by the depth) of simple groups, which yields an explicit linear bound on the length of $G/R(G)$ in terms of the chain difference of $G$, where $R(G)$ is the soluble radical of $G$.
math.GR
an unrefinable chain of a finite group g is a chain of subgroups g g_0 g_1 cdots g_t 1 where each g_i is a maximal subgroup of g_i1 the length respectively depth of g is the maximal respectively minimal length of such a chain we studied the depth of finite simple groups in a previous paper which included a classification of the simple groups of depth 3 here we go much further by determining the finite groups of depth 3 and 4 we also obtain several new results on the lengths of finite groups for example we classify the simple groups of length at most 9 which extends earlier work of janko and harada from the 1960s and we use this to describe the structure of arbitrary finite groups of small length we also present a numbertheoretic result of heathbrown which implies that there are infinitely many nonabelian simple groups of length at most 9 finally we study the chain difference of g namely the length minus the depth we obtain results on groups with chain difference 1 and 2 including a complete classification of the simple groups with chain difference 2 extending earlier work of brewster et al we also derive a best possible lower bound on the chain ratio the length divided by the depth of simple groups which yields an explicit linear bound on the length of grg in terms of the chain difference of g where rg is the soluble radical of g
[['an', 'unrefinable', 'chain', 'of', 'a', 'finite', 'group', 'g', 'is', 'a', 'chain', 'of', 'subgroups', 'g', 'g_0', 'g_1', 'cdots', 'g_t', '1', 'where', 'each', 'g_i', 'is', 'a', 'maximal', 'subgroup', 'of', 'g_i1', 'the', 'length', 'respectively', 'depth', 'of', 'g', 'is', 'the', 'maximal', 'respectively', 'minimal', 'length', 'of', 'such', 'a', 'chain', 'we', 'studied', 'the', 'depth', 'of', 'finite', 'simple', 'groups', 'in', 'a', 'previous', 'paper', 'which', 'included', 'a', 'classification', 'of', 'the', 'simple', 'groups', 'of', 'depth', '3', 'here', 'we', 'go', 'much', 'further', 'by', 'determining', 'the', 'finite', 'groups', 'of', 'depth', '3', 'and', '4', 'we', 'also', 'obtain', 'several', 'new', 'results', 'on', 'the', 'lengths', 'of', 'finite', 'groups', 'for', 'example', 'we', 'classify', 'the', 'simple', 'groups', 'of', 'length', 'at', 'most', '9', 'which', 'extends', 'earlier', 'work', 'of', 'janko', 'and', 'harada', 'from', 'the', '1960s', 'and', 'we', 'use', 'this', 'to', 'describe', 'the', 'structure', 'of', 'arbitrary', 'finite', 'groups', 'of', 'small', 'length', 'we', 'also', 'present', 'a', 'numbertheoretic', 'result', 'of', 'heathbrown', 'which', 'implies', 'that', 'there', 'are', 'infinitely', 'many', 'nonabelian', 'simple', 'groups', 'of', 'length', 'at', 'most', '9', 'finally', 'we', 'study', 'the', 'chain', 'difference', 'of', 'g', 'namely', 'the', 'length', 'minus', 'the', 'depth', 'we', 'obtain', 'results', 'on', 'groups', 'with', 'chain', 'difference', '1', 'and', '2', 'including', 'a', 'complete', 'classification', 'of', 'the', 'simple', 'groups', 'with', 'chain', 'difference', '2', 'extending', 'earlier', 'work', 'of', 'brewster', 'et', 'al', 'we', 'also', 'derive', 'a', 'best', 'possible', 'lower', 'bound', 'on', 'the', 'chain', 'ratio', 'the', 'length', 'divided', 'by', 'the', 'depth', 'of', 'simple', 'groups', 'which', 'yields', 'an', 'explicit', 'linear', 'bound', 'on', 'the', 'length', 'of', 'grg', 'in', 'terms', 'of', 'the', 'chain', 'difference', 'of', 'g', 'where', 'rg', 'is', 'the', 'soluble', 'radical', 'of', 'g']]
[-0.15961762058816337, 0.1544062773168496, -0.05530352593750244, 0.017660527301552566, -0.05733425863207835, -0.09830248606983226, 0.04424032284397451, 0.3868811063860592, -0.2677929491513533, -0.2673964234943754, 0.10192047221009216, -0.26502804836137633, -0.10419442146160614, 0.21740759493074255, -0.04621144276591176, -0.04906175553945726, 0.02237977248839862, 0.12229834482835432, -0.06611987171239345, -0.2845231654185628, 0.31196468270870176, -0.003393870842480949, 0.2248361707214447, 0.06405049372931729, 0.09418109220524247, 0.03625084276533561, -0.037070957579469, 0.02776921140067732, -0.2082330700066207, 0.13670555860000222, 0.2160019403689273, 0.04845740213172005, 0.2200541218473135, -0.35312447351543047, -0.18822985838887543, 0.15300299960795624, 0.13846219399555582, 0.08734062923540772, -0.010234154945593855, -0.21867047172220733, 0.13257432226393268, -0.1938735333371244, -0.12360412073566725, 0.03375119184660405, 0.10123607786259188, 0.009516087112767312, -0.2160844020349886, 0.06102635731427131, 0.11191674194634263, 0.11946916967057265, 0.011750962038482972, -0.16311996227398, 0.008897239409258913, 0.154804883858468, -0.002499326245354013, 0.014685925242381721, 0.053643710481432766, -0.0863332576929075, -0.11051022619959193, 0.3540857213093081, -0.08614019499815952, -0.13940238428060794, 0.17899113666899652, -0.12824049734732942, -0.16561484768862275, 0.10965724587760986, 0.11241605293820141, 0.16303428286485758, -0.0695878099426269, 0.12760279425382162, -0.12996892249475606, 0.1561105012656133, 0.08085671816160714, -0.030114205086581136, 0.08974452012101648, 0.15209832721906394, 0.10300300639053912, 0.14845954134272268, -0.02879917429975019, 0.02024600696068932, -0.3471268068750197, -0.17103007553297997, -0.15163020335509242, 0.07623229528728284, -0.12034493605469576, -0.14947776690310222, 0.4191545440178168, 0.0942762178446457, 0.21590768798197402, 0.12565873278802644, 0.21569106787790052, 0.07935036710550186, 0.06166957092297269, 0.08302941964939237, 0.11293203408192647, 0.18267716403941242, -0.09844672136943833, -0.20833022002251403, -0.02273448297613949, 0.13030614605859706]
1,802.02195
Granger-causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks
Knowledge of the importance of input features towards decisions made by machine-learning models is essential to increase our understanding of both the models and the underlying data. Here, we present a new approach to estimating feature importance with neural networks based on the idea of distributing the features of interest among experts in an attentive mixture of experts (AME). AMEs use attentive gating networks trained with a Granger-causal objective to learn to jointly produce accurate predictions as well as estimates of feature importance in a single model. Our experiments show (i) that the feature importance estimates provided by AMEs compare favourably to those provided by state-of-the-art methods, (ii) that AMEs are significantly faster at estimating feature importance than existing methods, and (iii) that the associations discovered by AMEs are consistent with those reported by domain experts.
cs.LG cs.AI cs.NE
knowledge of the importance of input features towards decisions made by machinelearning models is essential to increase our understanding of both the models and the underlying data here we present a new approach to estimating feature importance with neural networks based on the idea of distributing the features of interest among experts in an attentive mixture of experts ame ames use attentive gating networks trained with a grangercausal objective to learn to jointly produce accurate predictions as well as estimates of feature importance in a single model our experiments show i that the feature importance estimates provided by ames compare favourably to those provided by stateoftheart methods ii that ames are significantly faster at estimating feature importance than existing methods and iii that the associations discovered by ames are consistent with those reported by domain experts
[['knowledge', 'of', 'the', 'importance', 'of', 'input', 'features', 'towards', 'decisions', 'made', 'by', 'machinelearning', 'models', 'is', 'essential', 'to', 'increase', 'our', 'understanding', 'of', 'both', 'the', 'models', 'and', 'the', 'underlying', 'data', 'here', 'we', 'present', 'a', 'new', 'approach', 'to', 'estimating', 'feature', 'importance', 'with', 'neural', 'networks', 'based', 'on', 'the', 'idea', 'of', 'distributing', 'the', 'features', 'of', 'interest', 'among', 'experts', 'in', 'an', 'attentive', 'mixture', 'of', 'experts', 'ame', 'ames', 'use', 'attentive', 'gating', 'networks', 'trained', 'with', 'a', 'grangercausal', 'objective', 'to', 'learn', 'to', 'jointly', 'produce', 'accurate', 'predictions', 'as', 'well', 'as', 'estimates', 'of', 'feature', 'importance', 'in', 'a', 'single', 'model', 'our', 'experiments', 'show', 'i', 'that', 'the', 'feature', 'importance', 'estimates', 'provided', 'by', 'ames', 'compare', 'favourably', 'to', 'those', 'provided', 'by', 'stateoftheart', 'methods', 'ii', 'that', 'ames', 'are', 'significantly', 'faster', 'at', 'estimating', 'feature', 'importance', 'than', 'existing', 'methods', 'and', 'iii', 'that', 'the', 'associations', 'discovered', 'by', 'ames', 'are', 'consistent', 'with', 'those', 'reported', 'by', 'domain', 'experts']]
[0.021816725452320978, 0.019153927419585458, -0.0544321440765998, 0.060877308133914246, -0.10378643516314161, -0.15943316324025064, 0.05204628943294451, 0.4433706047232537, -0.21556690628366434, -0.3431537141338648, 0.06564987375681727, -0.304810608172214, -0.180710842476829, 0.20204295132562572, -0.06858349447297234, 0.060487252108834905, 0.10334990221856381, 0.008168697524952757, -0.01503670132232775, -0.2522458822795135, 0.32319634856471297, 0.11101995668072692, 0.3462399149977821, -0.019320340043016, 0.09284845013719271, -0.04824563916704124, -0.11207289007656715, -0.0023831816335373067, -0.07177644195663187, 0.24107166342711187, 0.328915536659438, 0.18091615602059072, 0.3300280310213566, -0.4068154183401288, -0.2724943453632638, 0.05396885357057566, 0.12131386365988017, 0.08256409308010274, -0.05381431084328249, -0.33269697972847256, 0.0723111519268166, -0.1533065274467363, -0.06350825084304876, -0.1266744352726485, -0.009900554117527516, 0.04119540139457539, -0.2838312187026638, 0.027681246425559306, 0.07534858850532841, 0.04744247677188147, -0.06608108048128676, -0.1751457319341545, -0.014115497646237011, 0.15532513409305146, 0.03983649163873291, 0.061507459110169506, 0.1293988005593693, -0.2002506689476671, -0.15807246279163176, 0.33600183023030267, -0.0980085681851907, -0.18060200188183978, 0.22378562416997738, -0.04579310758152347, -0.12233744337059119, 0.10331585336312213, 0.17482964884873262, 0.1007483998512137, -0.1559130872688804, -0.02797131438017138, 0.0007652265057378612, 0.166792187918498, -0.02826629257384304, 0.003221211342058857, 0.20654315058131675, 0.2188647444401046, -0.013847271692665183, 0.11417495285379975, -0.12431513084447943, -0.08715849731336622, -0.21827619537875495, -0.07667600711615438, -0.2171014894881998, -0.06094767372055417, -0.07051964793743751, -0.09309000541725254, 0.3926112892188351, 0.2614592395188725, 0.24382807236414758, 0.08714869357508552, 0.3300597651190508, 0.008426635704167625, 0.12827452250605667, 0.08059701391304021, 0.22514477245482234, 0.045617062843281445, 0.07284982598331921, -0.17515770534929984, 0.1515667329829953, 0.040265114147640654]
1,802.02196
On the asymptotic of exit problems for controlled Markov diffusion processes with random jumps and vanishing diffusion terms
In this paper, we study the asymptotic of exit problem for controlled Markov diffusion processes with random jumps and vanishing diffusion terms, where the random jumps are introduced in order to modify the evolution of the controlled diffusions by switching from one mode of dynamics to another. That is, depending on the state-position and state-transition information, the dynamics of the controlled diffusions randomly switches between the different drift and diffusion terms. Here, we specifically investigate the asymptotic exit problem concerning such controlled Markov diffusion processes in two steps: (i) First, for each controlled diffusion model, we look for an admissible Markov control process that minimizes the principal eigenvalue for the corresponding infinitesimal generator with zero Dirichlet boundary conditions -- where such an admissible control process also forces the controlled diffusion process to remain in a given bounded open domain for a longer duration. (ii) Then, using large deviations theory, we determine the exit place and the type of distribution at the exit time for the controlled Markov diffusion processes coupled with random jumps and vanishing diffusion terms. Moreover, the asymptotic results at the exit time also allow us to determine the limiting behavior of the Dirichlet problem for the corresponding system of elliptic partial differential equations containing a small vanishing parameter.
math.DS math.PR
in this paper we study the asymptotic of exit problem for controlled markov diffusion processes with random jumps and vanishing diffusion terms where the random jumps are introduced in order to modify the evolution of the controlled diffusions by switching from one mode of dynamics to another that is depending on the stateposition and statetransition information the dynamics of the controlled diffusions randomly switches between the different drift and diffusion terms here we specifically investigate the asymptotic exit problem concerning such controlled markov diffusion processes in two steps i first for each controlled diffusion model we look for an admissible markov control process that minimizes the principal eigenvalue for the corresponding infinitesimal generator with zero dirichlet boundary conditions where such an admissible control process also forces the controlled diffusion process to remain in a given bounded open domain for a longer duration ii then using large deviations theory we determine the exit place and the type of distribution at the exit time for the controlled markov diffusion processes coupled with random jumps and vanishing diffusion terms moreover the asymptotic results at the exit time also allow us to determine the limiting behavior of the dirichlet problem for the corresponding system of elliptic partial differential equations containing a small vanishing parameter
[['in', 'this', 'paper', 'we', 'study', 'the', 'asymptotic', 'of', 'exit', 'problem', 'for', 'controlled', 'markov', 'diffusion', 'processes', 'with', 'random', 'jumps', 'and', 'vanishing', 'diffusion', 'terms', 'where', 'the', 'random', 'jumps', 'are', 'introduced', 'in', 'order', 'to', 'modify', 'the', 'evolution', 'of', 'the', 'controlled', 'diffusions', 'by', 'switching', 'from', 'one', 'mode', 'of', 'dynamics', 'to', 'another', 'that', 'is', 'depending', 'on', 'the', 'stateposition', 'and', 'statetransition', 'information', 'the', 'dynamics', 'of', 'the', 'controlled', 'diffusions', 'randomly', 'switches', 'between', 'the', 'different', 'drift', 'and', 'diffusion', 'terms', 'here', 'we', 'specifically', 'investigate', 'the', 'asymptotic', 'exit', 'problem', 'concerning', 'such', 'controlled', 'markov', 'diffusion', 'processes', 'in', 'two', 'steps', 'i', 'first', 'for', 'each', 'controlled', 'diffusion', 'model', 'we', 'look', 'for', 'an', 'admissible', 'markov', 'control', 'process', 'that', 'minimizes', 'the', 'principal', 'eigenvalue', 'for', 'the', 'corresponding', 'infinitesimal', 'generator', 'with', 'zero', 'dirichlet', 'boundary', 'conditions', 'where', 'such', 'an', 'admissible', 'control', 'process', 'also', 'forces', 'the', 'controlled', 'diffusion', 'process', 'to', 'remain', 'in', 'a', 'given', 'bounded', 'open', 'domain', 'for', 'a', 'longer', 'duration', 'ii', 'then', 'using', 'large', 'deviations', 'theory', 'we', 'determine', 'the', 'exit', 'place', 'and', 'the', 'type', 'of', 'distribution', 'at', 'the', 'exit', 'time', 'for', 'the', 'controlled', 'markov', 'diffusion', 'processes', 'coupled', 'with', 'random', 'jumps', 'and', 'vanishing', 'diffusion', 'terms', 'moreover', 'the', 'asymptotic', 'results', 'at', 'the', 'exit', 'time', 'also', 'allow', 'us', 'to', 'determine', 'the', 'limiting', 'behavior', 'of', 'the', 'dirichlet', 'problem', 'for', 'the', 'corresponding', 'system', 'of', 'elliptic', 'partial', 'differential', 'equations', 'containing', 'a', 'small', 'vanishing', 'parameter']]
[-0.10357765461491983, 0.17744127332367132, -0.050857510970254836, 0.03428520595987625, -0.07164385384527976, -0.13617235545345258, 0.03829534546333994, 0.33857689389254914, -0.37301755203691683, -0.2186448343664087, 0.1548193798614354, -0.25022329150757006, -0.1056512871720387, 0.15057130023707863, -0.023267704088900363, 0.07096978406974395, 0.02955126689644486, 0.0514969802082797, -0.014979884039574976, -0.19557295231656593, 0.34049648292915247, 0.01412365087374831, 0.24701021755399388, 0.016971922836057023, 0.1672134032410583, 0.019553173567072608, -0.02260246488954159, -0.009725761229426345, -0.19606638219438408, 0.06824395169657722, 0.20845058021073243, 0.012893640549862357, 0.28820250006214354, -0.4509804332673407, -0.18780665511140626, 0.1457377058101827, 0.14609946667787096, 0.10378728960039156, -0.004859208402281814, -0.29350749712936475, 0.0689620881354766, -0.10649140948612404, -0.15295140145114805, -0.0057011158550915675, 0.016685950788156836, 0.062436513011187814, -0.33692236896827105, 0.07068896157478771, 0.07329611411166675, 0.03914759333610855, -0.06928225819179655, -0.06621530031257322, 0.004785755942196866, 0.17056825767721287, 0.05069059887402424, -0.06551420628639054, 0.12497614643148829, -0.10381415809067991, -0.13085183280862145, 0.30333775932049495, -0.11462101783619026, -0.26222210045030525, 0.15107791542418694, -0.1674184480806786, -0.11889026299092259, 0.13943071749493588, 0.19708269740049347, 0.1546379993282566, -0.1783113898698276, 0.0926477622057525, 0.03771778758510537, 0.08801430802620751, 0.07897799318816745, -0.02087861227688188, 0.11627091852609407, 0.1556480303941446, 0.12294493726918108, 0.145080998057553, -0.0696613333370697, -0.19859825198774775, -0.36292304846337825, -0.16126814641004972, -0.17500951144280041, 0.08234514200026125, -0.13971209339275298, -0.20167672806575396, 0.3721767090033722, 0.155677300670661, 0.22356467386908188, 0.08795356841392495, 0.21343955329761943, 0.19875842468750676, -0.03806451502652687, 0.06738209411274623, 0.14306041294414745, 0.1255435383707089, 0.11847332732431128, -0.26409920295321665, 0.14149766340272493, 0.05640716707292425]
1,802.02197
Via Method for Lithography Free Contact and Preservation of 2D Materials
Atomically thin 2D materials span the common components of electronic circuits as metals, semi-conductors, and insulators, and can manifest correlated phases such as superconductivity, charge density waves, and magnetism. An ongoing challenge in the field is to incorporate these 2D materials into multi-layer hetero-structures with robust electrical contacts while preventing disorder and degradation. In particular, preserving and studying air-sensitive 2D materials has presented a significant challenge since they readily oxidize under atmospheric conditions. We report a new technique for contacting 2D materials, in which metal via contacts are integrated into flakes of insulating hexagonal boron nitride, and then placed onto the desired conducting 2D layer, avoiding direct lithographic patterning onto the 2D conductor. The metal contacts are planar with the bottom surface of the boron nitride and form robust contacts to multiple 2D materials. These structures protect air-sensitive 2D materials for months with no degradation in performance. This via contact technique will provide the capability to produce atomic printed circuit boards that can form the basis of more complex multi-layer heterostructures.
cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.supr-con
atomically thin 2d materials span the common components of electronic circuits as metals semiconductors and insulators and can manifest correlated phases such as superconductivity charge density waves and magnetism an ongoing challenge in the field is to incorporate these 2d materials into multilayer heterostructures with robust electrical contacts while preventing disorder and degradation in particular preserving and studying airsensitive 2d materials has presented a significant challenge since they readily oxidize under atmospheric conditions we report a new technique for contacting 2d materials in which metal via contacts are integrated into flakes of insulating hexagonal boron nitride and then placed onto the desired conducting 2d layer avoiding direct lithographic patterning onto the 2d conductor the metal contacts are planar with the bottom surface of the boron nitride and form robust contacts to multiple 2d materials these structures protect airsensitive 2d materials for months with no degradation in performance this via contact technique will provide the capability to produce atomic printed circuit boards that can form the basis of more complex multilayer heterostructures
[['atomically', 'thin', '2d', 'materials', 'span', 'the', 'common', 'components', 'of', 'electronic', 'circuits', 'as', 'metals', 'semiconductors', 'and', 'insulators', 'and', 'can', 'manifest', 'correlated', 'phases', 'such', 'as', 'superconductivity', 'charge', 'density', 'waves', 'and', 'magnetism', 'an', 'ongoing', 'challenge', 'in', 'the', 'field', 'is', 'to', 'incorporate', 'these', '2d', 'materials', 'into', 'multilayer', 'heterostructures', 'with', 'robust', 'electrical', 'contacts', 'while', 'preventing', 'disorder', 'and', 'degradation', 'in', 'particular', 'preserving', 'and', 'studying', 'airsensitive', '2d', 'materials', 'has', 'presented', 'a', 'significant', 'challenge', 'since', 'they', 'readily', 'oxidize', 'under', 'atmospheric', 'conditions', 'we', 'report', 'a', 'new', 'technique', 'for', 'contacting', '2d', 'materials', 'in', 'which', 'metal', 'via', 'contacts', 'are', 'integrated', 'into', 'flakes', 'of', 'insulating', 'hexagonal', 'boron', 'nitride', 'and', 'then', 'placed', 'onto', 'the', 'desired', 'conducting', '2d', 'layer', 'avoiding', 'direct', 'lithographic', 'patterning', 'onto', 'the', '2d', 'conductor', 'the', 'metal', 'contacts', 'are', 'planar', 'with', 'the', 'bottom', 'surface', 'of', 'the', 'boron', 'nitride', 'and', 'form', 'robust', 'contacts', 'to', 'multiple', '2d', 'materials', 'these', 'structures', 'protect', 'airsensitive', '2d', 'materials', 'for', 'months', 'with', 'no', 'degradation', 'in', 'performance', 'this', 'via', 'contact', 'technique', 'will', 'provide', 'the', 'capability', 'to', 'produce', 'atomic', 'printed', 'circuit', 'boards', 'that', 'can', 'form', 'the', 'basis', 'of', 'more', 'complex', 'multilayer', 'heterostructures']]
[-0.12892633494825717, 0.14213923529161165, 0.01437337179729519, -0.05028700232179018, -0.025529848875978974, -0.2255995666270542, 0.05879693204531588, 0.4584430587526999, -0.2668188027220598, -0.29866631292569185, 0.03876796816829701, -0.3475888233592023, -0.2001973181766899, 0.21689387593875853, 0.0037230684541775818, 0.09895233394120607, 0.021837591204509052, -0.1891647352963313, -0.10925938618949435, -0.2054976521172882, 0.2593810008811541, 0.005241420715012484, 0.36005077339512737, 0.07415785938222233, 0.030307847853989628, -0.026908536885925625, 0.11725465557946448, 0.019585302969636887, -0.12443860797831899, 0.1068519380022581, 0.2882404751879604, -0.13371178997974648, 0.19950453136443047, -0.5991857371739607, -0.24469896856891482, -0.009158488531863828, 0.11409832249063323, 0.14154657417137656, -0.14781058063549848, -0.27959718014936, 0.08829402879911219, -0.09967603953691384, -0.07618250703025195, -0.08424345748662426, -0.033809259541370845, -0.026238073132270456, -0.20884203522810604, 0.02438367133666026, 0.0523082275319387, 0.06254046093277656, -0.06298175931646767, -0.13110218813631966, -0.12274377647180067, 0.1270781034407647, -0.032861910470385565, -0.0023832577988723218, 0.21761174064826722, -0.15212598214966208, -0.07828046855576641, 0.4149283652550579, -0.009583953491613617, -0.14431363495872818, 0.2182243291876818, -0.1282966953324602, -0.031600893818234145, 0.16064884620636963, 0.18086268337258296, 0.04902588605488602, -0.1825945042206481, 0.03059845972480797, -0.0030915452288572637, 0.16700675492569783, 0.0670271355451809, 0.08726105202542214, 0.3137058937031645, 0.25143731668542485, 0.04313082293547215, 0.13823072060844616, -0.08446899047992819, 0.04710741357453037, -0.15128988383524392, -0.26413188937082016, -0.2111681818333046, 0.06470890655263997, -0.05731168299719721, -0.28320773612511785, 0.4005420933564722, 0.12672764797795738, 0.13498658476920242, -0.0801500676244726, 0.27093114470518387, 0.027928553060056607, 0.13474278868181488, -0.024217532558246838, 0.22645836493152885, 0.1454120784251112, 0.08606279220124666, -0.1405186014350678, 0.10465108179514519, -0.005421220968962151]
1,802.02198
Electron Physics in 3D Two-Fluid Ten-Moment Modeling of Ganymede's Magnetosphere
We studied the role of electron physics in 3D two-fluid 10-moment simulation of the Ganymede's magnetosphere. The model captures non-ideal physics like the Hall effect, the electron inertia, and anisotropic, non-gyrotropic pressure effects. A series of analyses were carried out: 1) The resulting magnetic field topology and electron and ion convection patterns were investigated. The magnetic fields were shown to agree reasonably well with in-situ measurements by the Galileo satellite. 2) The physics of collisionless magnetic reconnection were carefully examined in terms of the current sheet formation and decomposition of generalized Ohm's law. The importance of pressure anisotropy and non-gyrotropy in supporting the reconnection electric field is confirmed. 3) We compared surface "brightness" morphology, represented by surface electron and ion pressure contours, with oxygen emission observed by the Hubble Space Telescope (HST). The correlation between the observed emission morphology and spatial variability in electron/ion pressure was demonstrated. Potential extension to multi-ion species in the context of Ganymede and other magnetospheric systems is also discussed.
physics.space-ph
we studied the role of electron physics in 3d twofluid 10moment simulation of the ganymedes magnetosphere the model captures nonideal physics like the hall effect the electron inertia and anisotropic nongyrotropic pressure effects a series of analyses were carried out 1 the resulting magnetic field topology and electron and ion convection patterns were investigated the magnetic fields were shown to agree reasonably well with insitu measurements by the galileo satellite 2 the physics of collisionless magnetic reconnection were carefully examined in terms of the current sheet formation and decomposition of generalized ohms law the importance of pressure anisotropy and nongyrotropy in supporting the reconnection electric field is confirmed 3 we compared surface brightness morphology represented by surface electron and ion pressure contours with oxygen emission observed by the hubble space telescope hst the correlation between the observed emission morphology and spatial variability in electronion pressure was demonstrated potential extension to multiion species in the context of ganymede and other magnetospheric systems is also discussed
[['we', 'studied', 'the', 'role', 'of', 'electron', 'physics', 'in', '3d', 'twofluid', '10moment', 'simulation', 'of', 'the', 'ganymedes', 'magnetosphere', 'the', 'model', 'captures', 'nonideal', 'physics', 'like', 'the', 'hall', 'effect', 'the', 'electron', 'inertia', 'and', 'anisotropic', 'nongyrotropic', 'pressure', 'effects', 'a', 'series', 'of', 'analyses', 'were', 'carried', 'out', '1', 'the', 'resulting', 'magnetic', 'field', 'topology', 'and', 'electron', 'and', 'ion', 'convection', 'patterns', 'were', 'investigated', 'the', 'magnetic', 'fields', 'were', 'shown', 'to', 'agree', 'reasonably', 'well', 'with', 'insitu', 'measurements', 'by', 'the', 'galileo', 'satellite', '2', 'the', 'physics', 'of', 'collisionless', 'magnetic', 'reconnection', 'were', 'carefully', 'examined', 'in', 'terms', 'of', 'the', 'current', 'sheet', 'formation', 'and', 'decomposition', 'of', 'generalized', 'ohms', 'law', 'the', 'importance', 'of', 'pressure', 'anisotropy', 'and', 'nongyrotropy', 'in', 'supporting', 'the', 'reconnection', 'electric', 'field', 'is', 'confirmed', '3', 'we', 'compared', 'surface', 'brightness', 'morphology', 'represented', 'by', 'surface', 'electron', 'and', 'ion', 'pressure', 'contours', 'with', 'oxygen', 'emission', 'observed', 'by', 'the', 'hubble', 'space', 'telescope', 'hst', 'the', 'correlation', 'between', 'the', 'observed', 'emission', 'morphology', 'and', 'spatial', 'variability', 'in', 'electronion', 'pressure', 'was', 'demonstrated', 'potential', 'extension', 'to', 'multiion', 'species', 'in', 'the', 'context', 'of', 'ganymede', 'and', 'other', 'magnetospheric', 'systems', 'is', 'also', 'discussed']]
[-0.11683964511456263, 0.19030881521473753, -0.04096339406195756, 0.10845577627670293, -0.03300201129338636, -0.07303033956814921, -0.04055496664411139, 0.36761070416513375, -0.22154585470263732, -0.3650068877969028, 0.028474132292591627, -0.25611111271853854, -0.07895199980348258, 0.21260037630790754, 0.03822299410736688, 0.03214685088655309, 0.002682914845247912, -0.07434458763156904, -0.03149459611980025, -0.1984458990514324, 0.27395801436121964, 0.14994097525671282, 0.2808880857078404, 0.0626102446961052, 0.07367676616896217, -0.052487256550570814, -0.05526609016048563, 0.096290603852916, -0.1434543398691614, 0.012476111577664753, 0.18901035015857437, 0.011914144980681425, 0.17523149229733773, -0.4867422129538637, -0.2750592337319309, -0.05041352351673129, 0.13299076478337732, 0.041658685001737736, -0.06689307162262749, -0.2705784690560682, -0.022101884807187427, -0.15916972856957284, -0.16085652987474133, -0.021631157619129048, 0.017517678655766335, 0.047660963771660333, -0.2624934794659522, 0.13010121484854253, 0.034203916363611184, 0.1413968709388339, -0.15693831406022626, -0.09915362723262572, -0.08648221964150009, 0.05300339083357646, 0.07108067578803634, 0.050656583716683995, 0.2316288991388297, -0.12212530258196838, -0.07456009120896186, 0.3838868949039862, -0.05191028504291686, -0.101960997074479, 0.1848370385024038, -0.2850427064567623, -0.07986774656455964, 0.1599737848978626, 0.1238452232976603, 0.04400991635893439, -0.12468835357974124, 0.07463466278390914, -0.018757073674350977, 0.1075801198868448, 0.0843023065273173, -0.015871144643780297, 0.2809498574153134, 0.15285579032028979, -0.036840183927291416, 0.10633274352887118, -0.2243264962481789, -0.03801792754050594, -0.2366797525191498, -0.14576992168937378, -0.1461243713487553, 0.01586744125517903, -0.04683468630537391, -0.13515787377790975, 0.37103653267287173, 0.12566775426434681, 0.12501897041901675, -0.09192017358358631, 0.2961342769061647, 0.08557298458067746, 0.042754616523047954, 0.09173863631298357, 0.2871883195660236, 0.21197090306597557, 0.15706624359278598, -0.3044713805954926, 0.07150080195974513, 0.042320826038343425]
1,802.02199
Building a linear equation of state for trapped gravitons from finite size effects and the Schwarzschild black hole case
In this paper we continue the investigations present in \cite{1} and \cite{2} concerning the spectrum of trapped gravitons in a spherical box, and in particular inside a Schwarzschild black hole (BH). We explore the possibility that, due to finite size effects, the frequency of the radiation made of trapped gravitons can be modified in such a way that a linear equation of state $PV=\gamma U$ for the pressure $P$ and the internal energy $U$ arises. Firstly, we study the case with $U\sim R$, where only fluids with $\gamma >-\frac{1}{3}$ are possible. If corrections $\sim 1/R$ are added to $U$, for $\gamma\in[0,\frac{1}{3}]$ we found no limitation on the allowed value for the areal radius of the trapped sphere $R$. Moreover, for $\gamma>\frac{1}{3}$ we have a minimum allowed value for $R$ of the order of the Planck length $L_P$. Conversely, a fluid with $P<0$ can be obtained but with a maximum allowed value for $R$. With the added term looking like $\sim 1/R$ to the BH internal energy $U$, the well known logarithmic corrections to the BH entropy naturally emerge for any linear equation of state. The results of this paper suggest that finite size effects could modify the structure of graviton's radiation inside, showing a possible mechanism to transform radiation into dark energy.
hep-th astro-ph.CO gr-qc
in this paper we continue the investigations present in cite1 and cite2 concerning the spectrum of trapped gravitons in a spherical box and in particular inside a schwarzschild black hole bh we explore the possibility that due to finite size effects the frequency of the radiation made of trapped gravitons can be modified in such a way that a linear equation of state pvgamma u for the pressure p and the internal energy u arises firstly we study the case with usim r where only fluids with gamma frac13 are possible if corrections sim 1r are added to u for gammain0frac13 we found no limitation on the allowed value for the areal radius of the trapped sphere r moreover for gammafrac13 we have a minimum allowed value for r of the order of the planck length l_p conversely a fluid with p0 can be obtained but with a maximum allowed value for r with the added term looking like sim 1r to the bh internal energy u the well known logarithmic corrections to the bh entropy naturally emerge for any linear equation of state the results of this paper suggest that finite size effects could modify the structure of gravitons radiation inside showing a possible mechanism to transform radiation into dark energy
[['in', 'this', 'paper', 'we', 'continue', 'the', 'investigations', 'present', 'in', 'cite1', 'and', 'cite2', 'concerning', 'the', 'spectrum', 'of', 'trapped', 'gravitons', 'in', 'a', 'spherical', 'box', 'and', 'in', 'particular', 'inside', 'a', 'schwarzschild', 'black', 'hole', 'bh', 'we', 'explore', 'the', 'possibility', 'that', 'due', 'to', 'finite', 'size', 'effects', 'the', 'frequency', 'of', 'the', 'radiation', 'made', 'of', 'trapped', 'gravitons', 'can', 'be', 'modified', 'in', 'such', 'a', 'way', 'that', 'a', 'linear', 'equation', 'of', 'state', 'pvgamma', 'u', 'for', 'the', 'pressure', 'p', 'and', 'the', 'internal', 'energy', 'u', 'arises', 'firstly', 'we', 'study', 'the', 'case', 'with', 'usim', 'r', 'where', 'only', 'fluids', 'with', 'gamma', 'frac13', 'are', 'possible', 'if', 'corrections', 'sim', '1r', 'are', 'added', 'to', 'u', 'for', 'gammain0frac13', 'we', 'found', 'no', 'limitation', 'on', 'the', 'allowed', 'value', 'for', 'the', 'areal', 'radius', 'of', 'the', 'trapped', 'sphere', 'r', 'moreover', 'for', 'gammafrac13', 'we', 'have', 'a', 'minimum', 'allowed', 'value', 'for', 'r', 'of', 'the', 'order', 'of', 'the', 'planck', 'length', 'l_p', 'conversely', 'a', 'fluid', 'with', 'p0', 'can', 'be', 'obtained', 'but', 'with', 'a', 'maximum', 'allowed', 'value', 'for', 'r', 'with', 'the', 'added', 'term', 'looking', 'like', 'sim', '1r', 'to', 'the', 'bh', 'internal', 'energy', 'u', 'the', 'well', 'known', 'logarithmic', 'corrections', 'to', 'the', 'bh', 'entropy', 'naturally', 'emerge', 'for', 'any', 'linear', 'equation', 'of', 'state', 'the', 'results', 'of', 'this', 'paper', 'suggest', 'that', 'finite', 'size', 'effects', 'could', 'modify', 'the', 'structure', 'of', 'gravitons', 'radiation', 'inside', 'showing', 'a', 'possible', 'mechanism', 'to', 'transform', 'radiation', 'into', 'dark', 'energy']]
[-0.12931673854264167, 0.15907086515754604, -0.07012333068773863, 0.06659683062579108, -0.06639644431237701, -0.12899227891591908, 0.04170103915524223, 0.3060198475530986, -0.25767929978116133, -0.2799784702083996, 0.0689740002408187, -0.30402385902426177, -0.04909350492202779, 0.16990182747502933, -0.01946853724409688, 0.023439792051697463, 0.01800871776131708, 0.0778278643942135, -0.06069987606085641, -0.21081445060233678, 0.3227242195987673, 0.07173531892058845, 0.16967963362246324, 0.07299707288983051, 0.07335755798261631, -0.005626811182491802, 0.015308036529080292, 0.0688865053440716, -0.21149365830122527, 0.06552982780625713, 0.18833989317364028, 0.06468394800405682, 0.26129317426670823, -0.4110107386371112, -0.2214758356712295, 0.14685962710175307, 0.152331665319248, 0.10371976644112661, -0.04081608991541913, -0.23554106081198706, 0.08838333887840136, -0.19552878370958618, -0.17762820639660912, -0.016215854549432914, 0.0772391414519346, -0.00798147348753894, -0.2783487435916559, 0.09934457396624975, 0.08288838088336405, -0.05374172520929609, -0.0782754732759304, -0.10279875098054773, -0.03359810913785954, 0.05436349031348316, 0.07167047540251718, 0.04661485452637183, 0.11550581612307846, -0.13026455168959877, -0.038984476869400035, 0.38470135954694384, -0.0985196948170653, -0.18068389339221008, 0.1395897771873507, -0.20267360929497763, -0.07205284550634511, 0.10156082918975529, 0.14068776744770992, 0.11698673440156834, -0.09185807646834848, 0.15829433593147046, -0.008056423610686793, 0.18881257891913422, 0.10039818560945217, 0.05135566325475012, 0.23439555155986733, 0.09400637652479897, 0.04031947428142233, 0.1531566472626046, -0.10212613369391688, -0.04364687851217963, -0.34625606570820633, -0.14623846781092503, -0.1665801981299153, 0.0905725778131768, -0.1063768538938413, -0.146974915687583, 0.3362649966824497, 0.12385766091422316, 0.20402686956949068, 0.03340800528517038, 0.2426127935336395, 0.11486912643287385, 0.06571770258221116, 0.11416971568702208, 0.26193718081919487, 0.10208108652946785, 0.08289677873188374, -0.24028747626602578, -0.0237592654539446, 0.052406222722158904]
1,802.022
On the polynomial Szemer\'edi theorem in finite fields
Let $P_1,\dots,P_m\in\mathbb{Z}[y]$ be any linearly independent polynomials with zero constant term. We show that there exists a $\gamma>0$ such that any subset of $\mathbb{F}_q$ of size at least $q^{1-\gamma}$ contains a nontrivial polynomial progression $x,x+P_1(y),\dots,x+P_m(y)$, provided the characteristic of $\mathbb{F}_q$ is large enough.
math.NT math.CO
let p_1dotsp_minmathbbzy be any linearly independent polynomials with zero constant term we show that there exists a gamma0 such that any subset of mathbbf_q of size at least q1gamma contains a nontrivial polynomial progression xxp_1ydotsxp_my provided the characteristic of mathbbf_q is large enough
[['let', 'p_1dotsp_minmathbbzy', 'be', 'any', 'linearly', 'independent', 'polynomials', 'with', 'zero', 'constant', 'term', 'we', 'show', 'that', 'there', 'exists', 'a', 'gamma0', 'such', 'that', 'any', 'subset', 'of', 'mathbbf_q', 'of', 'size', 'at', 'least', 'q1gamma', 'contains', 'a', 'nontrivial', 'polynomial', 'progression', 'xxp_1ydotsxp_my', 'provided', 'the', 'characteristic', 'of', 'mathbbf_q', 'is', 'large', 'enough']]
[-0.2841032958123833, 0.1911455074834521, -0.08642432020278648, -0.04115135618194472, -0.0626071777776815, -0.23607319323346018, -0.032135722250677644, 0.30018063860479743, -0.3375630176626146, -0.16470132259419187, 0.054309570777695625, -0.30840127421543, -0.1029490935150534, 0.20362307506147773, -0.035879658337216826, -0.05655850162729621, 0.039906368975061925, 0.1537445338908583, -0.04703444830374792, -0.32580152521841227, 0.3155665906291688, -0.08784031267277896, 0.1293462301371619, 0.0629389368928969, 0.19494736085180192, -0.039639806712511924, 0.047236757789505646, 0.07467403748887591, -0.1415332686756301, -0.03594071859261021, 0.33780096684349703, 0.15136763283062465, 0.3438733226619661, -0.3385216927621514, -0.1838365672621876, 0.3193308792077005, 0.19343001034576446, 0.0332954894984141, -0.03282299917191267, -0.11086745537468232, 0.22855999004095792, -0.12002575991209596, -0.1991282262839377, -0.04815173360984772, 0.12812442407011987, 0.05181907089427114, -0.35603074851096606, -0.019454249646514654, 0.07259166114963592, 0.1619970441912301, 0.005484071018872783, -0.20010123755782844, 0.02757213943405077, 0.0869470419595018, 0.0229941641620826, 0.17785731953626965, -0.02586136608151719, -0.06570241145600449, -0.05447209667181596, 0.34000143778976055, -0.14237825740128757, -0.23540096941869706, 0.10071742339059711, -0.20571397244930267, -0.11420513150515035, 0.18066270416602492, 0.09311272308696061, 0.1147287089843303, 0.03824367462657392, 0.2185264489147812, -0.16844461071304978, 0.2736473864642903, 0.08004961486440151, 0.005771364620886743, 0.1518553464440629, 0.023830492049455643, 0.1108180965995416, 0.1234236712771235, 0.013044929201714694, 0.033267488435376434, -0.47208351297304035, -0.08512372218538075, -0.24869520985521376, 0.17866247163619847, -0.21885775174014271, -0.24212459241971374, 0.3388517108745873, 0.07206979656475596, 0.17112384907668457, 0.12893043062649667, 0.2094528115907451, 0.12480317717418074, 0.11925942707457579, 0.18427321206545458, 0.03297764165326953, 0.1009698445443064, -0.07792173456400633, -0.19246870202478022, 0.0977958532399498, 0.053795274475123736]
1,802.02201
Surface Tension Prediction for Pure Fluids
In this paper we propose an analytic expression for surface tension of organic compounds. This new expression, originally derived from the statistical-mechanics is shown to represent the experimental surface tension data of 94 different organic compounds within 1.05 AAD%. We also propose another simpler expression. When this generalized expression is used surface tensions for all the 94 compounds can be predicted within 2.57 AAD% for all temperatures investigated.
physics.chem-ph cond-mat.soft physics.flu-dyn
in this paper we propose an analytic expression for surface tension of organic compounds this new expression originally derived from the statisticalmechanics is shown to represent the experimental surface tension data of 94 different organic compounds within 105 aad we also propose another simpler expression when this generalized expression is used surface tensions for all the 94 compounds can be predicted within 257 aad for all temperatures investigated
[['in', 'this', 'paper', 'we', 'propose', 'an', 'analytic', 'expression', 'for', 'surface', 'tension', 'of', 'organic', 'compounds', 'this', 'new', 'expression', 'originally', 'derived', 'from', 'the', 'statisticalmechanics', 'is', 'shown', 'to', 'represent', 'the', 'experimental', 'surface', 'tension', 'data', 'of', '94', 'different', 'organic', 'compounds', 'within', '105', 'aad', 'we', 'also', 'propose', 'another', 'simpler', 'expression', 'when', 'this', 'generalized', 'expression', 'is', 'used', 'surface', 'tensions', 'for', 'all', 'the', '94', 'compounds', 'can', 'be', 'predicted', 'within', '257', 'aad', 'for', 'all', 'temperatures', 'investigated']]
[-0.08985757544766837, 0.11838691010031172, -0.026724328697823426, 0.10701376864830416, -0.027245701715240583, -0.14324775373782306, 0.09181634853902164, 0.33324537437190027, -0.19770797624197953, -0.33147625490913496, 0.02259013375014012, -0.25977695132057893, -0.21711782546823516, 0.23155453932635925, -0.07190300989896059, 0.01129869297694634, -0.0008096678066067398, -0.006940791216466631, -0.0868955253459075, -0.20911569035995534, 0.23242403670926304, 0.027666438937611768, 0.31904580915237174, 0.11923734722522032, 0.06740018900189385, -0.08864466615212972, 0.03661927196662873, 0.02724455757004976, -0.21493285382166505, 0.14824860602589873, 0.3112187833278714, 0.07865153039422106, 0.13111554077990792, -0.4170945951276842, -0.24454926188542125, 0.05370701730306096, 0.15120480056537097, 0.1625378853367532, -0.05751314606758944, -0.23120464483166442, 0.07944538689437597, -0.18926021240322904, -0.08162745040403131, -0.07400858832304091, 0.04725579268244259, -0.05236782121937722, -0.25432063351549644, 0.1356634032798705, -0.052291572956806594, 0.08774879971957382, -0.17854616953991354, -0.21428647716803587, 0.0036525058779208097, 0.08697046668770353, 0.03962650247986483, 0.05807881892028758, 0.10358825015068493, -0.03522054862354279, -0.030396408394581693, 0.3710813888293855, -0.09597972151138545, -0.18111993051955805, 0.1699175119831446, -0.13491523116553092, -0.13891689208171823, 0.16552058321095126, 0.11876418892129817, 0.1192207360325162, -0.2742391628025336, 0.04128298852318788, -0.053780287805506415, 0.15249587849179722, 0.08414773394435864, -0.02942090654088294, 0.21765116046128027, 0.16186077548670308, -0.04513589884428417, 0.16213841934736326, -0.12768876396448298, -0.00901294157237691, -0.23722624565776, -0.20175470617901095, -0.1469999397163252, 0.02545265224762261, -0.0702762835083858, -0.1435115778598736, 0.35833581449354396, 0.15819308851325117, 0.18305581504725577, 0.051619017524096894, 0.24625599998569883, 0.09633943739840213, 0.05388507948202245, 0.04424118595745634, 0.21479099153486245, 0.09521355774417958, 0.036699709537274694, -0.1823590357260614, 0.11658273675643346, 0.04051472476053545]
1,802.02202
Object Detection on Dynamic Occupancy Grid Maps Using Deep Learning and Automatic Label Generation
We tackle the problem of object detection and pose estimation in a shared space downtown environment. For perception multiple laser scanners with 360{\deg} coverage were fused in a dynamic occupancy grid map (DOGMa). A single-stage deep convolutional neural network is trained to provide object hypotheses comprising of shape, position, orientation and an existence score from a single input DOGMa. Furthermore, an algorithm for offline object extraction was developed to automatically label several hours of training data. The algorithm is based on a two-pass trajectory extraction, forward and backward in time. Typical for engineered algorithms, the automatic label generation suffers from misdetections, which makes hard negative mining impractical. Therefore, we propose a loss function counteracting the high imbalance between mostly static background and extremely rare dynamic grid cells. Experiments indicate, that the trained network has good generalization capabilities since it detects objects occasionally lost by the label algorithm. Evaluation reaches an average precision (AP) of 75.9%
cs.CV cs.RO
we tackle the problem of object detection and pose estimation in a shared space downtown environment for perception multiple laser scanners with 360deg coverage were fused in a dynamic occupancy grid map dogma a singlestage deep convolutional neural network is trained to provide object hypotheses comprising of shape position orientation and an existence score from a single input dogma furthermore an algorithm for offline object extraction was developed to automatically label several hours of training data the algorithm is based on a twopass trajectory extraction forward and backward in time typical for engineered algorithms the automatic label generation suffers from misdetections which makes hard negative mining impractical therefore we propose a loss function counteracting the high imbalance between mostly static background and extremely rare dynamic grid cells experiments indicate that the trained network has good generalization capabilities since it detects objects occasionally lost by the label algorithm evaluation reaches an average precision ap of 759
[['we', 'tackle', 'the', 'problem', 'of', 'object', 'detection', 'and', 'pose', 'estimation', 'in', 'a', 'shared', 'space', 'downtown', 'environment', 'for', 'perception', 'multiple', 'laser', 'scanners', 'with', '360deg', 'coverage', 'were', 'fused', 'in', 'a', 'dynamic', 'occupancy', 'grid', 'map', 'dogma', 'a', 'singlestage', 'deep', 'convolutional', 'neural', 'network', 'is', 'trained', 'to', 'provide', 'object', 'hypotheses', 'comprising', 'of', 'shape', 'position', 'orientation', 'and', 'an', 'existence', 'score', 'from', 'a', 'single', 'input', 'dogma', 'furthermore', 'an', 'algorithm', 'for', 'offline', 'object', 'extraction', 'was', 'developed', 'to', 'automatically', 'label', 'several', 'hours', 'of', 'training', 'data', 'the', 'algorithm', 'is', 'based', 'on', 'a', 'twopass', 'trajectory', 'extraction', 'forward', 'and', 'backward', 'in', 'time', 'typical', 'for', 'engineered', 'algorithms', 'the', 'automatic', 'label', 'generation', 'suffers', 'from', 'misdetections', 'which', 'makes', 'hard', 'negative', 'mining', 'impractical', 'therefore', 'we', 'propose', 'a', 'loss', 'function', 'counteracting', 'the', 'high', 'imbalance', 'between', 'mostly', 'static', 'background', 'and', 'extremely', 'rare', 'dynamic', 'grid', 'cells', 'experiments', 'indicate', 'that', 'the', 'trained', 'network', 'has', 'good', 'generalization', 'capabilities', 'since', 'it', 'detects', 'objects', 'occasionally', 'lost', 'by', 'the', 'label', 'algorithm', 'evaluation', 'reaches', 'an', 'average', 'precision', 'ap', 'of', '759']]
[-0.07535151445096538, 0.026437975045184664, -0.06010931866063226, 0.06231698907851692, -0.1022954724819189, -0.20545704330828402, 0.07082757347774121, 0.47729835799865183, -0.26300561854375465, -0.36297878684295765, 0.07875201270780376, -0.2591870290617789, -0.13591033633077337, 0.16667208600744243, -0.15540236898307358, 0.09274338944364459, 0.16483288280545705, 0.03851117734335393, -0.03361235174816102, -0.21698325013801936, 0.2483750999815041, 0.08175062981054877, 0.3508314428009814, -0.005722749515646888, 0.1898749079082101, 0.031134838388571815, -0.04732462551760217, -0.018469057747560944, -0.006297452379470586, 0.13314035146031528, 0.2751805842583699, 0.20147045625433807, 0.32213494801413145, -0.3896415152797295, -0.19969558046770192, 0.07923154114865728, 0.13104202678997912, 0.10155825460134374, -0.05537456294837138, -0.3339311070740223, 0.10097017921056718, -0.15893827757888263, -0.0022950999498847994, -0.08191226522340589, 0.0065030117278858535, -0.025637377894693805, -0.297309110077819, 0.03426460590544007, 0.03099809173164108, 0.062467960442975916, -0.07403927231507916, -0.08159547216529327, 0.022348652115362064, 0.17631544307354957, -0.0028473889425156577, 0.08581480041536833, 0.1667321898429955, -0.19818567967703266, -0.14115109926450156, 0.34019793481115373, -0.0335942427049421, -0.2013604971294802, 0.18009340044321312, -0.038680739504108656, -0.13295171415853885, 0.18460888281434534, 0.2372198471679322, 0.13897519391030072, -0.15236792184051967, -0.0215587830846949, -0.02416274294617676, 0.22645343238367668, 0.07698477888029188, -0.03364882602266246, 0.2001724492112595, 0.26359140657249, 0.067734699894584, 0.1658332563095516, -0.2115091030020267, -0.05130802650275009, -0.19310749299831748, -0.08594739271718407, -0.1948658735634038, -0.016604005099244177, -0.10655575279980117, -0.18432565370739828, 0.36096214002238647, 0.1959117985330522, 0.21247223489661982, 0.08198420189906873, 0.3658815612115206, 0.03133622932458116, 0.09483042895313232, 0.08899943451397122, 0.17925955671967278, 0.003639044719297559, 0.15451369707269835, -0.1649173161052468, 0.12577035196666275, 0.07366698830568742]
1,802.02203
Automatic construction of Chinese herbal prescription from tongue image via CNNs and auxiliary latent therapy topics
The tongue image provides important physical information of humans. It is of great importance for diagnoses and treatments in clinical medicine. Herbal prescriptions are simple, noninvasive and have low side effects. Thus, they are widely applied in China. Studies on the automatic construction technology of herbal prescriptions based on tongue images have great significance for deep learning to explore the relevance of tongue images for herbal prescriptions, it can be applied to healthcare services in mobile medical systems. In order to adapt to the tongue image in a variety of photographic environments and construct herbal prescriptions, a neural network framework for prescription construction is designed. It includes single/double convolution channels and fully connected layers. Furthermore, it proposes the auxiliary therapy topic loss mechanism to model the therapy of Chinese doctors and alleviate the interference of sparse output labels on the diversity of results. The experiment use the real world tongue images and the corresponding prescriptions and the results can generate prescriptions that are close to the real samples, which verifies the feasibility of the proposed method for the automatic construction of herbal prescriptions from tongue images. Also, it provides a reference for automatic herbal prescription construction from more physical information.
cs.CV cs.LG cs.NE
the tongue image provides important physical information of humans it is of great importance for diagnoses and treatments in clinical medicine herbal prescriptions are simple noninvasive and have low side effects thus they are widely applied in china studies on the automatic construction technology of herbal prescriptions based on tongue images have great significance for deep learning to explore the relevance of tongue images for herbal prescriptions it can be applied to healthcare services in mobile medical systems in order to adapt to the tongue image in a variety of photographic environments and construct herbal prescriptions a neural network framework for prescription construction is designed it includes singledouble convolution channels and fully connected layers furthermore it proposes the auxiliary therapy topic loss mechanism to model the therapy of chinese doctors and alleviate the interference of sparse output labels on the diversity of results the experiment use the real world tongue images and the corresponding prescriptions and the results can generate prescriptions that are close to the real samples which verifies the feasibility of the proposed method for the automatic construction of herbal prescriptions from tongue images also it provides a reference for automatic herbal prescription construction from more physical information
[['the', 'tongue', 'image', 'provides', 'important', 'physical', 'information', 'of', 'humans', 'it', 'is', 'of', 'great', 'importance', 'for', 'diagnoses', 'and', 'treatments', 'in', 'clinical', 'medicine', 'herbal', 'prescriptions', 'are', 'simple', 'noninvasive', 'and', 'have', 'low', 'side', 'effects', 'thus', 'they', 'are', 'widely', 'applied', 'in', 'china', 'studies', 'on', 'the', 'automatic', 'construction', 'technology', 'of', 'herbal', 'prescriptions', 'based', 'on', 'tongue', 'images', 'have', 'great', 'significance', 'for', 'deep', 'learning', 'to', 'explore', 'the', 'relevance', 'of', 'tongue', 'images', 'for', 'herbal', 'prescriptions', 'it', 'can', 'be', 'applied', 'to', 'healthcare', 'services', 'in', 'mobile', 'medical', 'systems', 'in', 'order', 'to', 'adapt', 'to', 'the', 'tongue', 'image', 'in', 'a', 'variety', 'of', 'photographic', 'environments', 'and', 'construct', 'herbal', 'prescriptions', 'a', 'neural', 'network', 'framework', 'for', 'prescription', 'construction', 'is', 'designed', 'it', 'includes', 'singledouble', 'convolution', 'channels', 'and', 'fully', 'connected', 'layers', 'furthermore', 'it', 'proposes', 'the', 'auxiliary', 'therapy', 'topic', 'loss', 'mechanism', 'to', 'model', 'the', 'therapy', 'of', 'chinese', 'doctors', 'and', 'alleviate', 'the', 'interference', 'of', 'sparse', 'output', 'labels', 'on', 'the', 'diversity', 'of', 'results', 'the', 'experiment', 'use', 'the', 'real', 'world', 'tongue', 'images', 'and', 'the', 'corresponding', 'prescriptions', 'and', 'the', 'results', 'can', 'generate', 'prescriptions', 'that', 'are', 'close', 'to', 'the', 'real', 'samples', 'which', 'verifies', 'the', 'feasibility', 'of', 'the', 'proposed', 'method', 'for', 'the', 'automatic', 'construction', 'of', 'herbal', 'prescriptions', 'from', 'tongue', 'images', 'also', 'it', 'provides', 'a', 'reference', 'for', 'automatic', 'herbal', 'prescription', 'construction', 'from', 'more', 'physical', 'information']]
[-0.010995475552626886, 0.01629998990625609, -0.07679477955331095, 0.11109615685069002, -0.10938518039765768, -0.15246876762481407, 0.021629755011526867, 0.40820390414446595, -0.19262695136712865, -0.30530086340964774, 0.09666131018253508, -0.25783765364438294, -0.21253226313740015, 0.2655725675227586, -0.16280828478280454, 0.06601294098421931, 0.10802313399733976, 0.01378132552956231, 0.006608698178897612, -0.23782875503879042, 0.29648346328642217, 0.04178353769108071, 0.38299833178520204, 0.05756228836427908, 0.12326346994843335, -0.006107649279292673, -0.07897456771170255, -0.05521284545597155, -0.09080097956251848, 0.13994170870166273, 0.32820808914955707, 0.22532700539100914, 0.28476413622964175, -0.43771093532908706, -0.25389280393195807, 0.04491214329842478, 0.1025075605744496, 0.12349422931147273, -0.062457304989002295, -0.3001048678578809, 0.06451526653487236, -0.19948157176026143, -0.05523021811619401, -0.11500365777639672, 0.005880780720617622, -0.02401055912981974, -0.30747666880022734, 0.04786001548738568, 0.004688544917444233, 0.0815072511008475, -0.0949417540547438, -0.0928721293027047, -0.0025557627150556072, 0.23146411816123874, 0.02251930812082719, 0.06015958349104039, 0.17170593702467157, -0.2032675771563663, -0.10797649655491114, 0.3758797805639915, 0.026948195977020077, -0.219052062908886, 0.23825491901603527, -0.09216115749557502, -0.09518690513563342, 0.09134307258878835, 0.21761807009577752, 0.09777972923824564, -0.19022581489989535, 0.005945354310533731, 0.012224980280734599, 0.11782366389408708, 0.05835657091112807, -0.03613868539861869, 0.19742307997774333, 0.182922988939099, -0.043999876728921666, 0.10920419266622047, -0.12745926692834472, -0.0558387242333265, -0.2055204809899442, -0.13251433681638447, -0.13910208727698772, -0.010075408658012748, -0.0828852239385742, -0.15340371750411577, 0.38456769422860815, 0.24751736366655677, 0.14000158234848642, 0.00414331189065706, 0.36661134371184745, 0.011831311597488821, 0.16348835706710815, -0.009908470001537353, 0.16892873735458125, 0.06913310738746077, 0.14241881714668125, -0.16873527952702716, 0.0980269841523841, 0.07340718485880643]
1,802.02204
SocialML: machine learning for social media video creators
In the recent years, social media have become one of the main places where creative content is being published and consumed by billions of users. Contrary to traditional media, social media allow the publishers to receive almost instantaneous feedback regarding their creative work at an unprecedented scale. This is a perfect use case for machine learning methods that can use these massive amounts of data to provide content creators with inspirational ideas and constructive criticism of their work. In this work, we present a comprehensive overview of machine learning-empowered tools we developed for video creators at Group Nine Media - one of the major social media companies that creates short-form videos with over three billion views per month. Our main contribution is a set of tools that allow the creators to leverage massive amounts of data to improve their creation process, evaluate their videos before the publication and improve content quality. These applications include an interactive conversational bot that allows access to material archives, a Web-based application for automatic selection of optimal video thumbnail, as well as deep learning methods for optimizing headline and predicting video popularity. Our A/B tests show that deployment of our tools leads to significant increase of average video view count by 12.9%. Our additional contribution is a set of considerations collected during the deployment of those tools that can hel
cs.CV
in the recent years social media have become one of the main places where creative content is being published and consumed by billions of users contrary to traditional media social media allow the publishers to receive almost instantaneous feedback regarding their creative work at an unprecedented scale this is a perfect use case for machine learning methods that can use these massive amounts of data to provide content creators with inspirational ideas and constructive criticism of their work in this work we present a comprehensive overview of machine learningempowered tools we developed for video creators at group nine media one of the major social media companies that creates shortform videos with over three billion views per month our main contribution is a set of tools that allow the creators to leverage massive amounts of data to improve their creation process evaluate their videos before the publication and improve content quality these applications include an interactive conversational bot that allows access to material archives a webbased application for automatic selection of optimal video thumbnail as well as deep learning methods for optimizing headline and predicting video popularity our ab tests show that deployment of our tools leads to significant increase of average video view count by 129 our additional contribution is a set of considerations collected during the deployment of those tools that can hel
[['in', 'the', 'recent', 'years', 'social', 'media', 'have', 'become', 'one', 'of', 'the', 'main', 'places', 'where', 'creative', 'content', 'is', 'being', 'published', 'and', 'consumed', 'by', 'billions', 'of', 'users', 'contrary', 'to', 'traditional', 'media', 'social', 'media', 'allow', 'the', 'publishers', 'to', 'receive', 'almost', 'instantaneous', 'feedback', 'regarding', 'their', 'creative', 'work', 'at', 'an', 'unprecedented', 'scale', 'this', 'is', 'a', 'perfect', 'use', 'case', 'for', 'machine', 'learning', 'methods', 'that', 'can', 'use', 'these', 'massive', 'amounts', 'of', 'data', 'to', 'provide', 'content', 'creators', 'with', 'inspirational', 'ideas', 'and', 'constructive', 'criticism', 'of', 'their', 'work', 'in', 'this', 'work', 'we', 'present', 'a', 'comprehensive', 'overview', 'of', 'machine', 'learningempowered', 'tools', 'we', 'developed', 'for', 'video', 'creators', 'at', 'group', 'nine', 'media', 'one', 'of', 'the', 'major', 'social', 'media', 'companies', 'that', 'creates', 'shortform', 'videos', 'with', 'over', 'three', 'billion', 'views', 'per', 'month', 'our', 'main', 'contribution', 'is', 'a', 'set', 'of', 'tools', 'that', 'allow', 'the', 'creators', 'to', 'leverage', 'massive', 'amounts', 'of', 'data', 'to', 'improve', 'their', 'creation', 'process', 'evaluate', 'their', 'videos', 'before', 'the', 'publication', 'and', 'improve', 'content', 'quality', 'these', 'applications', 'include', 'an', 'interactive', 'conversational', 'bot', 'that', 'allows', 'access', 'to', 'material', 'archives', 'a', 'webbased', 'application', 'for', 'automatic', 'selection', 'of', 'optimal', 'video', 'thumbnail', 'as', 'well', 'as', 'deep', 'learning', 'methods', 'for', 'optimizing', 'headline', 'and', 'predicting', 'video', 'popularity', 'our', 'ab', 'tests', 'show', 'that', 'deployment', 'of', 'our', 'tools', 'leads', 'to', 'significant', 'increase', 'of', 'average', 'video', 'view', 'count', 'by', '129', 'our', 'additional', 'contribution', 'is', 'a', 'set', 'of', 'considerations', 'collected', 'during', 'the', 'deployment', 'of', 'those', 'tools', 'that', 'can', 'hel']]
[-0.06363734354227447, 0.03144294928747329, -0.07427290938335217, 0.0459619343530214, -0.15247748626579818, -0.10900448158596363, 0.07703407305123644, 0.4128740188151999, -0.2286797734624769, -0.365174652206724, 0.08590495188495002, -0.3429583533273017, -0.14461800873367275, 0.20315894150830838, -0.11651048027062497, 0.010986224620816018, 0.1023887423600066, 0.04245999508556668, 0.010965490684481213, -0.3680698192164703, 0.31820131199133705, 0.06358070703181062, 0.35063250729137607, 0.055909450042725545, 0.0767856644823596, 0.016357035401189542, -0.14345394136543874, -0.04831786707384019, -0.07743364926410637, 0.20656421954426163, 0.3417525386830349, 0.24190942564511447, 0.37526659983222793, -0.4349821331376218, -0.21316227330220655, 0.054580885964160476, 0.15801921740775685, 0.10429037702499551, -0.09261822583302104, -0.28771737077265075, 0.10458676494614141, -0.23505931412250392, -0.06951810933144204, -0.08659696218196403, 0.03246504499789979, 0.011610739903929166, -0.24888947246504337, 0.007750468645996577, 0.019978467282638655, 0.10533796904051067, -0.025406593320350425, -0.09370263177283408, 0.03535319314361237, 0.22755264610285983, 0.08259241005200621, 0.035278633229576487, 0.16866248112376528, -0.16825898777300805, -0.15906316501969647, 0.40305174635347363, -0.03267093170397693, -0.11703151928870667, 0.2286253340073523, -0.02800030616893028, -0.13812175503359783, 0.11944025386575893, 0.26958041188240284, 0.07929565289137142, -0.19200181215166243, -0.015553277898412782, -0.03759627833319285, 0.19270224119651427, 0.06757642269073051, 0.03977711274468177, 0.20597106905449433, 0.19188235171824158, 0.03411272487753476, 0.08068374079347258, -0.013987217453462928, -0.059728494110295856, -0.19851889432462208, -0.1625757641221643, -0.1501975511200726, 0.03764474611925671, -0.09074687357598314, -0.122144843130101, 0.3563619231713326, 0.21534387391862447, 0.13063767209916372, 0.059756487307259853, 0.3268741940611748, -0.006768338868134517, 0.08720676214517734, 0.08091825402588186, 0.16898261971725778, -0.0006593245075339026, 0.23533251633525162, -0.10633409263424141, 0.07554782971566451, -0.008114057993975722]
1,802.02205
Using electropolymerization based doping for electro-addressable functionalization of a multi-electrode array probe for nucleic acid detection
Here, we report a facile method for electro-addressable functionalization of a probe comprising of closely spaced three individually addressable carbon fiber electrodes for detection of nucleic acids. First, a multi electrode array probe comprising three adjacent carbon fiber electrodes was fabricated through pulling a three-barrel glass capillary with a single carbon fiber in each barrel using a micropuller. Second, electropolymerization based doping was used for electro-addressable functionalization of the multi-electrode array probe. To demonstrate that the current strategy works, anti-miR-34a was electrografted on only one of three electrodes by electropolymerization of pyrrole on the specific electrode. A second electrode was coated only with polypyrrole (PPy) and the third was left unmodified. Electrochemical impedance spectroscopy (EIS) was used for analysis and the results clearly showed charge transfer resistance of the PPy + anti-miR-34a modified electrode increased significantly after hybridization, while charge transfer resistance of the other two electrodes remained almost constant. The results demonstrate that the present strategy has great potential for constructing multiplex nucleic acid micro/nano biosensors for local and in situ detection of multiple nucleic acid molecules such as miRNAs at a time.
physics.ins-det physics.app-ph physics.bio-ph physics.chem-ph
here we report a facile method for electroaddressable functionalization of a probe comprising of closely spaced three individually addressable carbon fiber electrodes for detection of nucleic acids first a multi electrode array probe comprising three adjacent carbon fiber electrodes was fabricated through pulling a threebarrel glass capillary with a single carbon fiber in each barrel using a micropuller second electropolymerization based doping was used for electroaddressable functionalization of the multielectrode array probe to demonstrate that the current strategy works antimir34a was electrografted on only one of three electrodes by electropolymerization of pyrrole on the specific electrode a second electrode was coated only with polypyrrole ppy and the third was left unmodified electrochemical impedance spectroscopy eis was used for analysis and the results clearly showed charge transfer resistance of the ppy antimir34a modified electrode increased significantly after hybridization while charge transfer resistance of the other two electrodes remained almost constant the results demonstrate that the present strategy has great potential for constructing multiplex nucleic acid micronano biosensors for local and in situ detection of multiple nucleic acid molecules such as mirnas at a time
[['here', 'we', 'report', 'a', 'facile', 'method', 'for', 'electroaddressable', 'functionalization', 'of', 'a', 'probe', 'comprising', 'of', 'closely', 'spaced', 'three', 'individually', 'addressable', 'carbon', 'fiber', 'electrodes', 'for', 'detection', 'of', 'nucleic', 'acids', 'first', 'a', 'multi', 'electrode', 'array', 'probe', 'comprising', 'three', 'adjacent', 'carbon', 'fiber', 'electrodes', 'was', 'fabricated', 'through', 'pulling', 'a', 'threebarrel', 'glass', 'capillary', 'with', 'a', 'single', 'carbon', 'fiber', 'in', 'each', 'barrel', 'using', 'a', 'micropuller', 'second', 'electropolymerization', 'based', 'doping', 'was', 'used', 'for', 'electroaddressable', 'functionalization', 'of', 'the', 'multielectrode', 'array', 'probe', 'to', 'demonstrate', 'that', 'the', 'current', 'strategy', 'works', 'antimir34a', 'was', 'electrografted', 'on', 'only', 'one', 'of', 'three', 'electrodes', 'by', 'electropolymerization', 'of', 'pyrrole', 'on', 'the', 'specific', 'electrode', 'a', 'second', 'electrode', 'was', 'coated', 'only', 'with', 'polypyrrole', 'ppy', 'and', 'the', 'third', 'was', 'left', 'unmodified', 'electrochemical', 'impedance', 'spectroscopy', 'eis', 'was', 'used', 'for', 'analysis', 'and', 'the', 'results', 'clearly', 'showed', 'charge', 'transfer', 'resistance', 'of', 'the', 'ppy', 'antimir34a', 'modified', 'electrode', 'increased', 'significantly', 'after', 'hybridization', 'while', 'charge', 'transfer', 'resistance', 'of', 'the', 'other', 'two', 'electrodes', 'remained', 'almost', 'constant', 'the', 'results', 'demonstrate', 'that', 'the', 'present', 'strategy', 'has', 'great', 'potential', 'for', 'constructing', 'multiplex', 'nucleic', 'acid', 'micronano', 'biosensors', 'for', 'local', 'and', 'in', 'situ', 'detection', 'of', 'multiple', 'nucleic', 'acid', 'molecules', 'such', 'as', 'mirnas', 'at', 'a', 'time']]
[-0.1002275045472991, 0.10821323255632623, -0.0021537195965389733, -0.08430407605853608, 0.021519868555267087, -0.2597653567685153, 0.06411406882398296, 0.4505569575862451, -0.19367615364237942, -0.2951152911581713, 0.03408710673639606, -0.30662353126469744, -0.13874928959624164, 0.19639594709521838, -0.014330095122039149, 0.022218576590107245, 0.06312511159657416, -0.04851345996046968, -0.011075375032801689, -0.19027912979204717, 0.20832377860312012, 0.06812633067602292, 0.32400010549727914, 0.10623876659453592, 0.13030289084417745, -0.017257340415860446, 0.026074452431533824, 0.00442260456144471, -0.11766560619674817, 0.13824886611705137, 0.26420380756264256, -0.046026479903957807, 0.244832554186525, -0.493222236080328, -0.21521600894100795, -0.004146710576605983, 0.12137375031174584, 0.13317238773213996, -0.10495583092878488, -0.22613995208997617, 0.08484437584014483, -0.1263367289158685, -0.08237639674123122, -0.011086087493987923, -0.01770124447912994, 0.06836009808962858, -0.2272144717022787, 0.03884804583239285, -0.005263372880687133, 0.08285211427772249, -0.07600077444856818, -0.14185946802767416, -0.07192686963720586, 0.1233782789508537, -0.024215806007057174, 0.0011368454910222101, 0.28851026238143357, -0.05495103062342175, -0.08706366475036537, 0.2953246174782345, -0.0839117313735187, -0.1304873052034633, 0.17778665414847306, -0.1235356231548146, -0.08052149990478276, 0.15455480936560145, 0.07232049321332439, 0.15446076763857325, -0.2342970494699495, -0.016084584288777973, 0.010860742415058088, 0.22404320242904677, 0.1983143221851523, -0.02152248603207144, 0.23573032142171127, 0.28917912846571364, 0.0240541004803328, 0.1720522992310924, -0.16866062211391347, 0.015272673323290126, -0.16608163520769184, -0.2501268348410535, -0.18813843044600534, 0.05453563741982428, -0.0459141056963662, -0.18923611612990499, 0.4190701559947973, 0.04093607241132056, 0.12256663932136937, -0.04027324855732414, 0.2972245682771741, -0.0421022932403668, 0.13232015766632024, -0.07093496032096235, 0.2396322257356422, 0.1574375379145336, 0.1273096037607915, -0.2493211120417982, 0.10330361524393084, 0.018725944656497715]
1,802.02206
Recovering decimation-based cryptographic sequences by means of linear CAs
The sequences produced by the cryptographic sequence generator known as the shrinking generator can be modelled as the output sequences of linear elementary cellular automata. These sequences are composed of interleaved m-sequences produced by linear structures based on feedback shifts. This profitable characteristic can be used in the cryptanalysis of this generator. In this work we propose an algorithm that takes advantage of the inherent linearity of these cellular automata and the interleaved m-sequences. Although irregularly decimated generators have been conceived and designed as non-linear sequence generators, in practice they can be easily analysed in terms of simple linear structures.
cs.CR
the sequences produced by the cryptographic sequence generator known as the shrinking generator can be modelled as the output sequences of linear elementary cellular automata these sequences are composed of interleaved msequences produced by linear structures based on feedback shifts this profitable characteristic can be used in the cryptanalysis of this generator in this work we propose an algorithm that takes advantage of the inherent linearity of these cellular automata and the interleaved msequences although irregularly decimated generators have been conceived and designed as nonlinear sequence generators in practice they can be easily analysed in terms of simple linear structures
[['the', 'sequences', 'produced', 'by', 'the', 'cryptographic', 'sequence', 'generator', 'known', 'as', 'the', 'shrinking', 'generator', 'can', 'be', 'modelled', 'as', 'the', 'output', 'sequences', 'of', 'linear', 'elementary', 'cellular', 'automata', 'these', 'sequences', 'are', 'composed', 'of', 'interleaved', 'msequences', 'produced', 'by', 'linear', 'structures', 'based', 'on', 'feedback', 'shifts', 'this', 'profitable', 'characteristic', 'can', 'be', 'used', 'in', 'the', 'cryptanalysis', 'of', 'this', 'generator', 'in', 'this', 'work', 'we', 'propose', 'an', 'algorithm', 'that', 'takes', 'advantage', 'of', 'the', 'inherent', 'linearity', 'of', 'these', 'cellular', 'automata', 'and', 'the', 'interleaved', 'msequences', 'although', 'irregularly', 'decimated', 'generators', 'have', 'been', 'conceived', 'and', 'designed', 'as', 'nonlinear', 'sequence', 'generators', 'in', 'practice', 'they', 'can', 'be', 'easily', 'analysed', 'in', 'terms', 'of', 'simple', 'linear', 'structures']]
[-0.11367490033851936, 0.13963507352062152, -0.05959966555790743, 0.11220123007311486, -0.0380272589949891, -0.14507887384388596, -0.04162451925454661, 0.4326310644298792, -0.35075918161775915, -0.2547561845742166, 0.1372032284643501, -0.19016989319585265, -0.18483941567421425, 0.21297915627481415, -0.12192451704759151, 0.09302410729462281, 0.06422470423392951, 0.02368467067135498, -0.027011816513258964, -0.2688951553404331, 0.26258918080711735, 0.0927266846038401, 0.26370549350976946, -0.1219850920618046, 0.10777279256843031, 0.00572212107013911, -0.042667653439566494, 0.02600550196249969, -0.03935867541389598, 0.11316417218651623, 0.31497155866585674, 0.14857315426925197, 0.23502434418536722, -0.45803765242220834, -0.18323576926253737, 0.13532625503023155, 0.18595780266914516, 0.09860667745582759, -0.06286307588801719, -0.26089461935684083, 0.12966983600868842, -0.19597771792206914, -0.04158379163593054, -0.06916556487791241, -0.03902070831041783, 0.13051677610224943, -0.2569271833728999, -0.019764709938317537, 0.13698322643642313, 0.07625291028060019, 0.024285610662773252, -0.10568994922563434, -0.008094639545306563, 0.14671274012420327, -0.030878755655139686, -0.03445617378456518, 0.10198151756078006, -0.0005628219828940927, -0.19815982861444353, 0.35787360288901254, -0.048175443949876356, -0.2243440332286991, 0.16380875478149393, -0.05118234182242304, -0.1191659068944864, 0.14276896530762315, 0.2105983408819884, 0.09189979034475983, -0.16879689968191086, 0.06195960243581794, -0.0480835049925372, 0.20569093859288842, 0.1103747344436124, 0.06760099614024512, 0.18365513978525996, 0.1603165570204146, -0.015700629685889, 0.1778728314547334, -0.012487872866622639, -0.08484363337396644, -0.2623620856739581, -0.10535335123713593, -0.1828606094326824, 0.04240155878243968, -0.04266617318586213, -0.18605474738404154, 0.3820705920970067, 0.09323388057295233, 0.16714462796226143, 0.06527015022002161, 0.2858608840405941, 0.151627682155231, 0.1500418252532836, 0.042633748105727134, 0.14060640855226667, 0.10535873252432794, 0.08026107205543667, -0.16388929212465883, 0.12747777736745775, 0.11684600395616145]
1,802.02207
Automated dataset generation for image recognition using the example of taxonomy
This master thesis addresses the subject of automatically generating a dataset for image recognition, which takes a lot of time when being done manually. As the thesis was written with motivation from the context of the biodiversity workgroup at the City University of Applied Sciences Bremen, the classification of taxonomic entries was chosen as an exemplary use case. In order to automate the dataset creation, a prototype was conceptualized and implemented after working out knowledge basics and analyzing requirements for it. It makes use of an pre-trained abstract artificial intelligence which is able to sort out images that do not contain the desired content. Subsequent to the implementation and the automated dataset creation resulting from it, an evaluation was performed. Other, manually collected datasets were compared to the one the prototype produced in means of specifications and accuracy. The results were more than satisfactory and showed that automatically generating a dataset for image recognition is not only possible, but also might be a decent alternative to spending time and money in doing this task manually. At the very end of this work, an idea of how to use the principle of employing abstract artificial intelligences for step-by-step classification of deeper taxonomic layers in a productive system is presented and discussed.
cs.CV cs.LG
this master thesis addresses the subject of automatically generating a dataset for image recognition which takes a lot of time when being done manually as the thesis was written with motivation from the context of the biodiversity workgroup at the city university of applied sciences bremen the classification of taxonomic entries was chosen as an exemplary use case in order to automate the dataset creation a prototype was conceptualized and implemented after working out knowledge basics and analyzing requirements for it it makes use of an pretrained abstract artificial intelligence which is able to sort out images that do not contain the desired content subsequent to the implementation and the automated dataset creation resulting from it an evaluation was performed other manually collected datasets were compared to the one the prototype produced in means of specifications and accuracy the results were more than satisfactory and showed that automatically generating a dataset for image recognition is not only possible but also might be a decent alternative to spending time and money in doing this task manually at the very end of this work an idea of how to use the principle of employing abstract artificial intelligences for stepbystep classification of deeper taxonomic layers in a productive system is presented and discussed
[['this', 'master', 'thesis', 'addresses', 'the', 'subject', 'of', 'automatically', 'generating', 'a', 'dataset', 'for', 'image', 'recognition', 'which', 'takes', 'a', 'lot', 'of', 'time', 'when', 'being', 'done', 'manually', 'as', 'the', 'thesis', 'was', 'written', 'with', 'motivation', 'from', 'the', 'context', 'of', 'the', 'biodiversity', 'workgroup', 'at', 'the', 'city', 'university', 'of', 'applied', 'sciences', 'bremen', 'the', 'classification', 'of', 'taxonomic', 'entries', 'was', 'chosen', 'as', 'an', 'exemplary', 'use', 'case', 'in', 'order', 'to', 'automate', 'the', 'dataset', 'creation', 'a', 'prototype', 'was', 'conceptualized', 'and', 'implemented', 'after', 'working', 'out', 'knowledge', 'basics', 'and', 'analyzing', 'requirements', 'for', 'it', 'it', 'makes', 'use', 'of', 'an', 'pretrained', 'abstract', 'artificial', 'intelligence', 'which', 'is', 'able', 'to', 'sort', 'out', 'images', 'that', 'do', 'not', 'contain', 'the', 'desired', 'content', 'subsequent', 'to', 'the', 'implementation', 'and', 'the', 'automated', 'dataset', 'creation', 'resulting', 'from', 'it', 'an', 'evaluation', 'was', 'performed', 'other', 'manually', 'collected', 'datasets', 'were', 'compared', 'to', 'the', 'one', 'the', 'prototype', 'produced', 'in', 'means', 'of', 'specifications', 'and', 'accuracy', 'the', 'results', 'were', 'more', 'than', 'satisfactory', 'and', 'showed', 'that', 'automatically', 'generating', 'a', 'dataset', 'for', 'image', 'recognition', 'is', 'not', 'only', 'possible', 'but', 'also', 'might', 'be', 'a', 'decent', 'alternative', 'to', 'spending', 'time', 'and', 'money', 'in', 'doing', 'this', 'task', 'manually', 'at', 'the', 'very', 'end', 'of', 'this', 'work', 'an', 'idea', 'of', 'how', 'to', 'use', 'the', 'principle', 'of', 'employing', 'abstract', 'artificial', 'intelligences', 'for', 'stepbystep', 'classification', 'of', 'deeper', 'taxonomic', 'layers', 'in', 'a', 'productive', 'system', 'is', 'presented', 'and', 'discussed']]
[-0.030522418951399493, 0.02760247734979549, -0.09426152163761713, 0.07108484978033673, -0.12135927014252437, -0.12953882658454988, 0.05092441986330197, 0.38784845728604567, -0.2178157535935974, -0.38399853288595165, 0.117201047251001, -0.25552520054015554, -0.12874837964773178, 0.22399732981464782, -0.13012902541086077, 0.047082751390657256, 0.11408291522723933, 0.07122305436392448, -0.014284789531042666, -0.31341212139065777, 0.2887715257438166, 0.10099407962434703, 0.3086544979984562, 0.015851145976090004, 0.11199682057846248, -0.03261679957345006, -0.06438732847843008, -0.011914726965395467, -0.0378410226641184, 0.12610272565812228, 0.31864222255535424, 0.19551080173502366, 0.30728731551872834, -0.4241695554394807, -0.1544771235613596, 0.07258137621517692, 0.12863563808080342, 0.11105796441919492, -0.04232292863730219, -0.3278895709275578, 0.0729778657866908, -0.16848062298349326, -0.085659821900273, -0.09949846139733425, 0.02344485682621044, -0.05184800861170515, -0.2432444367840487, -0.013741464466216885, 0.055667400368873216, 0.12278984602917695, -0.0356292250022913, -0.10613050696029816, -0.009111923777631351, 0.19215184423055257, 0.030237542513004017, 0.044834936288229765, 0.13093299778133985, -0.13602194106760657, -0.10847715971148794, 0.4003786655497693, -0.018656711780169557, -0.17037818824451062, 0.19418535022996367, -0.03544827450865081, -0.16698138988133343, 0.10993792001335394, 0.17722403680728305, 0.10847104965221314, -0.2238351515708408, 0.009037842546379016, -0.025555356214976028, 0.21508758584802437, 0.08668508635656465, -0.05735053034233195, 0.18476045238563701, 0.23621660247445106, -0.01025575365361181, 0.15712130605548044, -0.07724902673757501, -0.06343644189764745, -0.26077190210954065, -0.1674270941875875, -0.19223300063361723, 0.019124131301179573, 0.005142211846361447, -0.12298231500954855, 0.4073697192017876, 0.214568086025039, 0.14060341172762925, 0.04619671169050326, 0.28926450587099506, 0.03869548878477266, 0.12955898401504826, 0.03848584240518643, 0.17607281628574822, -0.007687034384746637, 0.1803605945448258, -0.1400779586307527, 0.08505532927589403, 0.041121960870389426]
1,802.02208
Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural Network
Automated pavement crack detection is a challenging task that has been researched for decades due to the complicated pavement conditions in real world. In this paper, a supervised method based on deep learning is proposed, which has the capability of dealing with different pavement conditions. Specifically, a convolutional neural network (CNN) is used to learn the structure of the cracks from raw images, without any preprocessing. Small patches are extracted from crack images as inputs to generate a large training database, a CNN is trained and crack detection is modeled as a multi-label classification problem. Typically, crack pixels are much fewer than non-crack pixels. To deal with the problem with severely imbalanced data, a strategy with modifying the ratio of positive to negative samples is proposed. The method is tested on two public databases and compared with five existing methods. Experimental results show that it outperforms the other methods.
cs.CV
automated pavement crack detection is a challenging task that has been researched for decades due to the complicated pavement conditions in real world in this paper a supervised method based on deep learning is proposed which has the capability of dealing with different pavement conditions specifically a convolutional neural network cnn is used to learn the structure of the cracks from raw images without any preprocessing small patches are extracted from crack images as inputs to generate a large training database a cnn is trained and crack detection is modeled as a multilabel classification problem typically crack pixels are much fewer than noncrack pixels to deal with the problem with severely imbalanced data a strategy with modifying the ratio of positive to negative samples is proposed the method is tested on two public databases and compared with five existing methods experimental results show that it outperforms the other methods
[['automated', 'pavement', 'crack', 'detection', 'is', 'a', 'challenging', 'task', 'that', 'has', 'been', 'researched', 'for', 'decades', 'due', 'to', 'the', 'complicated', 'pavement', 'conditions', 'in', 'real', 'world', 'in', 'this', 'paper', 'a', 'supervised', 'method', 'based', 'on', 'deep', 'learning', 'is', 'proposed', 'which', 'has', 'the', 'capability', 'of', 'dealing', 'with', 'different', 'pavement', 'conditions', 'specifically', 'a', 'convolutional', 'neural', 'network', 'cnn', 'is', 'used', 'to', 'learn', 'the', 'structure', 'of', 'the', 'cracks', 'from', 'raw', 'images', 'without', 'any', 'preprocessing', 'small', 'patches', 'are', 'extracted', 'from', 'crack', 'images', 'as', 'inputs', 'to', 'generate', 'a', 'large', 'training', 'database', 'a', 'cnn', 'is', 'trained', 'and', 'crack', 'detection', 'is', 'modeled', 'as', 'a', 'multilabel', 'classification', 'problem', 'typically', 'crack', 'pixels', 'are', 'much', 'fewer', 'than', 'noncrack', 'pixels', 'to', 'deal', 'with', 'the', 'problem', 'with', 'severely', 'imbalanced', 'data', 'a', 'strategy', 'with', 'modifying', 'the', 'ratio', 'of', 'positive', 'to', 'negative', 'samples', 'is', 'proposed', 'the', 'method', 'is', 'tested', 'on', 'two', 'public', 'databases', 'and', 'compared', 'with', 'five', 'existing', 'methods', 'experimental', 'results', 'show', 'that', 'it', 'outperforms', 'the', 'other', 'methods']]
[-0.029017655175758172, 0.004045658656773535, -0.05710349306055169, 0.04090413301899979, -0.1258172157969376, -0.20803460594883338, -0.03351108052428006, 0.45748300367110484, -0.24408465842212979, -0.33536648700592686, 0.11910141876590363, -0.29349379462340996, -0.17855903911058213, 0.21637660400262354, -0.1417387868403583, 0.11158617152722326, 0.1691586488757182, 0.047226237199218896, -0.05831222087333633, -0.3085410955859147, 0.3079374700948294, 0.023060734288387844, 0.3780810444368399, 0.00997352518921567, 0.12995039212684198, -0.06873768352670595, -0.04133360233390704, 0.04858510157744702, -0.02638782455884408, 0.14722038226082568, 0.32496795444308807, 0.15214648176255208, 0.3114812950795592, -0.4180291610316852, -0.2567306113495441, 0.11078646225300995, 0.11353537292893019, 0.14712652362288428, -0.016843032063538762, -0.3376890705077204, 0.1312607313172791, -0.1188582006458042, 0.013224534665209215, -0.08477458586865985, -0.011732934629607544, -0.03528571954804057, -0.2958997084505107, 0.05129731748869794, 0.01862650225882897, 0.07765740036612025, -0.051168551079368824, -0.11107794736587517, 0.013872942517549303, 0.14503709713273957, 0.05681286027145295, 0.06491292698381192, 0.14182829615310766, -0.19830935296399607, -0.10802308248624999, 0.3919754116481321, -0.025363021648691093, -0.22098196124834185, 0.2149685584370525, -0.015653721774248657, -0.10978256453558602, 0.17214659533645907, 0.23015422013437226, 0.1294158973630417, -0.1595268939701192, -0.015161407879409002, -0.060574857991604086, 0.19400050764827914, 0.08357237217156531, -0.08556619079506679, 0.1381510878304284, 0.29657172189940495, 0.02994595198401225, 0.15475449407657269, -0.17608504731686334, -0.033605914975900354, -0.17805627402393273, -0.07293664593708928, -0.23538723156859823, -0.03750811684624972, -0.09172625370253651, -0.18325210296569747, 0.37552600583640505, 0.2070262490840931, 0.2234551035736159, 0.09296200622102825, 0.373890247422497, 0.022804912543113065, 0.18243467839233377, 0.06635628755454515, 0.18586163921439014, 0.022736367785271158, 0.13189475590951513, -0.1438697499657251, 0.1338428867700812, 0.03147042202574478]
1,802.02209
IONet: Learning to Cure the Curse of Drift in Inertial Odometry
Inertial sensors play a pivotal role in indoor localization, which in turn lays the foundation for pervasive personal applications. However, low-cost inertial sensors, as commonly found in smartphones, are plagued by bias and noise, which leads to unbounded growth in error when accelerations are double integrated to obtain displacement. Small errors in state estimation propagate to make odometry virtually unusable in a matter of seconds. We propose to break the cycle of continuous integration, and instead segment inertial data into independent windows. The challenge becomes estimating the latent states of each window, such as velocity and orientation, as these are not directly observable from sensor data. We demonstrate how to formulate this as an optimization problem, and show how deep recurrent neural networks can yield highly accurate trajectories, outperforming state-of-the-art shallow techniques, on a wide range of tests and attachments. In particular, we demonstrate that IONet can generalize to estimate odometry for non-periodic motion, such as a shopping trolley or baby-stroller, an extremely challenging task for existing techniques.
cs.RO cs.AI cs.CV
inertial sensors play a pivotal role in indoor localization which in turn lays the foundation for pervasive personal applications however lowcost inertial sensors as commonly found in smartphones are plagued by bias and noise which leads to unbounded growth in error when accelerations are double integrated to obtain displacement small errors in state estimation propagate to make odometry virtually unusable in a matter of seconds we propose to break the cycle of continuous integration and instead segment inertial data into independent windows the challenge becomes estimating the latent states of each window such as velocity and orientation as these are not directly observable from sensor data we demonstrate how to formulate this as an optimization problem and show how deep recurrent neural networks can yield highly accurate trajectories outperforming stateoftheart shallow techniques on a wide range of tests and attachments in particular we demonstrate that ionet can generalize to estimate odometry for nonperiodic motion such as a shopping trolley or babystroller an extremely challenging task for existing techniques
[['inertial', 'sensors', 'play', 'a', 'pivotal', 'role', 'in', 'indoor', 'localization', 'which', 'in', 'turn', 'lays', 'the', 'foundation', 'for', 'pervasive', 'personal', 'applications', 'however', 'lowcost', 'inertial', 'sensors', 'as', 'commonly', 'found', 'in', 'smartphones', 'are', 'plagued', 'by', 'bias', 'and', 'noise', 'which', 'leads', 'to', 'unbounded', 'growth', 'in', 'error', 'when', 'accelerations', 'are', 'double', 'integrated', 'to', 'obtain', 'displacement', 'small', 'errors', 'in', 'state', 'estimation', 'propagate', 'to', 'make', 'odometry', 'virtually', 'unusable', 'in', 'a', 'matter', 'of', 'seconds', 'we', 'propose', 'to', 'break', 'the', 'cycle', 'of', 'continuous', 'integration', 'and', 'instead', 'segment', 'inertial', 'data', 'into', 'independent', 'windows', 'the', 'challenge', 'becomes', 'estimating', 'the', 'latent', 'states', 'of', 'each', 'window', 'such', 'as', 'velocity', 'and', 'orientation', 'as', 'these', 'are', 'not', 'directly', 'observable', 'from', 'sensor', 'data', 'we', 'demonstrate', 'how', 'to', 'formulate', 'this', 'as', 'an', 'optimization', 'problem', 'and', 'show', 'how', 'deep', 'recurrent', 'neural', 'networks', 'can', 'yield', 'highly', 'accurate', 'trajectories', 'outperforming', 'stateoftheart', 'shallow', 'techniques', 'on', 'a', 'wide', 'range', 'of', 'tests', 'and', 'attachments', 'in', 'particular', 'we', 'demonstrate', 'that', 'ionet', 'can', 'generalize', 'to', 'estimate', 'odometry', 'for', 'nonperiodic', 'motion', 'such', 'as', 'a', 'shopping', 'trolley', 'or', 'babystroller', 'an', 'extremely', 'challenging', 'task', 'for', 'existing', 'techniques']]
[-0.09651215481627957, 0.10445273404044003, -0.04620347337808505, 0.054875734549700225, -0.08176200879535761, -0.16642112569064352, -0.0029252402614858225, 0.4423699257979506, -0.29644650309514925, -0.3304600132831249, 0.12436458334419315, -0.23571888984781297, -0.15205603790874817, 0.25333020814655194, -0.1581844706200512, 0.09886774912768279, 0.12373814730994763, 0.03390090352384351, -0.03502896173256842, -0.19126476553066757, 0.2413289751170248, 0.03457243976597702, 0.31445609788825535, 0.03018385811473232, 0.11611454321368855, 0.024216215105177498, -0.022019778712125248, 0.01931941822866898, -0.0570544359691568, 0.12430718441385809, 0.33649974901380625, 0.11419879839118642, 0.31309187153623586, -0.4414140762388145, -0.24118873470670443, 0.09737019948184446, 0.19258223980502506, 0.11637121233500046, -0.052820523244929106, -0.3288698482652565, 0.08396842149899801, -0.16171022548048522, -0.06221206405716219, -0.12558267108888466, 0.04263434757433652, 0.027784330969892374, -0.2830422708500985, 0.08785923783168062, 0.017867039806344152, 0.043433548759526, -0.05589181121792195, -0.0779548988436315, 0.03660677348162575, 0.2096399679362384, 0.03731885435429951, 0.01588877306897642, 0.19862993105022933, -0.15316361323397337, -0.10865327979070527, 0.3949861718925187, -0.051758563465435975, -0.2075460557208722, 0.1851868528468781, -0.04515912069613675, -0.12687147052464895, 0.1065252548173429, 0.2425671102400555, 0.1009343761350421, -0.15004317121201893, 0.007273555934886414, 0.023326007677354366, 0.17136134074843792, 0.05395744130553969, 0.05677678175999906, 0.21745328072329467, 0.1931005468597658, 0.12447775514229728, 0.0922527783802789, -0.13942963764960709, -0.07083859686537769, -0.24249091823178578, -0.1277162077371557, -0.15362650241649498, 0.02886036548268047, -0.05651904771015741, -0.20918807244638027, 0.3270940750399717, 0.23879784171284368, 0.21755792819950953, 0.0578924998520391, 0.33938829245113106, 0.05052597045334595, 0.08787972931483626, 0.06283072620337123, 0.23566075589322677, 0.03878184422115649, 0.11518166502741312, -0.14469849966264453, 0.0735141365208203, 0.019245622498656523]
1,802.0221
Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli
Quantitative modeling of human brain activity based on language representations has been actively studied in systems neuroscience. However, previous studies examined word-level representation, and little is known about whether we could recover structured sentences from brain activity. This study attempts to generate natural language descriptions of semantic contents from human brain activity evoked by visual stimuli. To effectively use a small amount of available brain activity data, our proposed method employs a pre-trained image-captioning network model using a deep learning framework. To apply brain activity to the image-captioning network, we train regression models that learn the relationship between brain activity and deep-layer image features. The results demonstrate that the proposed model can decode brain activity and generate descriptions using natural language sentences. We also conducted several experiments with data from different subsets of brain regions known to process visual stimuli. The results suggest that semantic information for sentence generations is widespread across the entire cortex.
cs.CV
quantitative modeling of human brain activity based on language representations has been actively studied in systems neuroscience however previous studies examined wordlevel representation and little is known about whether we could recover structured sentences from brain activity this study attempts to generate natural language descriptions of semantic contents from human brain activity evoked by visual stimuli to effectively use a small amount of available brain activity data our proposed method employs a pretrained imagecaptioning network model using a deep learning framework to apply brain activity to the imagecaptioning network we train regression models that learn the relationship between brain activity and deeplayer image features the results demonstrate that the proposed model can decode brain activity and generate descriptions using natural language sentences we also conducted several experiments with data from different subsets of brain regions known to process visual stimuli the results suggest that semantic information for sentence generations is widespread across the entire cortex
[['quantitative', 'modeling', 'of', 'human', 'brain', 'activity', 'based', 'on', 'language', 'representations', 'has', 'been', 'actively', 'studied', 'in', 'systems', 'neuroscience', 'however', 'previous', 'studies', 'examined', 'wordlevel', 'representation', 'and', 'little', 'is', 'known', 'about', 'whether', 'we', 'could', 'recover', 'structured', 'sentences', 'from', 'brain', 'activity', 'this', 'study', 'attempts', 'to', 'generate', 'natural', 'language', 'descriptions', 'of', 'semantic', 'contents', 'from', 'human', 'brain', 'activity', 'evoked', 'by', 'visual', 'stimuli', 'to', 'effectively', 'use', 'a', 'small', 'amount', 'of', 'available', 'brain', 'activity', 'data', 'our', 'proposed', 'method', 'employs', 'a', 'pretrained', 'imagecaptioning', 'network', 'model', 'using', 'a', 'deep', 'learning', 'framework', 'to', 'apply', 'brain', 'activity', 'to', 'the', 'imagecaptioning', 'network', 'we', 'train', 'regression', 'models', 'that', 'learn', 'the', 'relationship', 'between', 'brain', 'activity', 'and', 'deeplayer', 'image', 'features', 'the', 'results', 'demonstrate', 'that', 'the', 'proposed', 'model', 'can', 'decode', 'brain', 'activity', 'and', 'generate', 'descriptions', 'using', 'natural', 'language', 'sentences', 'we', 'also', 'conducted', 'several', 'experiments', 'with', 'data', 'from', 'different', 'subsets', 'of', 'brain', 'regions', 'known', 'to', 'process', 'visual', 'stimuli', 'the', 'results', 'suggest', 'that', 'semantic', 'information', 'for', 'sentence', 'generations', 'is', 'widespread', 'across', 'the', 'entire', 'cortex']]
[0.014085065932463734, 0.0189638567622751, -0.06625378961494613, 0.1344910428946253, -0.16621475743069763, -0.13791789980905672, 0.02728397643884584, 0.4800184744019662, -0.2696226728178801, -0.3317196685971031, 0.022477268474927592, -0.2805934727492352, -0.30485033205439965, 0.17467269295405957, -0.14269991601186413, 0.04646386799192236, 0.12503211137673428, 0.1165913553848382, 0.01652382539374934, -0.23072834944562806, 0.27175287496478806, 0.019196373601106084, 0.34934878172052486, -0.011052770934052646, 0.12894230968499135, -0.08405309325880221, -0.06377836884630303, -0.054173387534495805, -0.06820544907442977, 0.2061301352005572, 0.40736356405046065, 0.2828998270399508, 0.31474808477496186, -0.5018157162733616, -0.31198239150351936, 0.05607693592657245, 0.11551203924050975, 0.09313761824441533, -0.0469560474525356, -0.38439824481404594, 0.09980087881539798, -0.13883012954986865, 0.0808990762553989, -0.14006574207676514, 0.021818884936792234, -0.04499560882968287, -0.2639839354451866, 0.059516568505768516, 0.06853516510417385, 0.1585587332201671, -0.09035505766289369, -0.03816967026721085, -0.017702141288487662, 0.24995393299407537, 0.05491411244447884, 0.09951764400222249, 0.21184529690672793, -0.19382509629827954, -0.16156759943452573, 0.28348085700023556, -0.01776673785530992, -0.19181361534302274, 0.26792666885190675, -0.09304252657738905, -0.15799753171722256, 0.06772161362572543, 0.23152495205041862, 0.05366661392392651, -0.2076327133112617, -0.03324047856205593, -0.0679411755649433, 0.2820054379344407, 0.05770789838936781, -0.025411138641497782, 0.2030029418547788, 0.25755810807308843, -0.09590943840542628, 0.1525666129872984, -0.11335567209358897, -0.047354639928427436, -0.16930421164349443, -0.03434263797657144, -0.16187835553090177, -0.05468087948167757, -0.07724598285623811, -0.08266435804027658, 0.4505662437768713, 0.2330929143324254, 0.2100147156315225, 0.11941051572662659, 0.30088276009886494, -0.03722118164127272, 0.15182331912670163, 0.052602010259344696, 0.12014686227625897, 0.0695133053802795, 0.13940759181615806, -0.16262093778031186, 0.13182745140736862, 0.04498926581394288]
1,802.02211
Resonant behavior of the generalized Langevin system with tempered Mittag-Leffler memory kernel
The generalized Langevin equation describes anomalous dynamics. Noise is not only the origin of uncertainty but also plays a positive role in helping to detect signal with information, termed stochastic resonance (SR). This paper analyzes the anomalous resonant behaviors of the generalized Langevin system with a multiplicative dichotomous noise and an internal tempered Mittag-Leffler noise. For the system with fluctuating harmonic potential, we obtain the exact expressions of several SR, such as, the first moment, the amplitude and the autocorrelation function for the output signal as well as the signal-noise ratio. We analyze the influence of the tempering parameter and memory exponent on the bona fide SR and the general SR. Moreover, it is detected that the critical memory exponent changes regularly with the increase of tempering parameter. Almost all the theoretical results are validated by numerical simulations.
cond-mat.stat-mech
the generalized langevin equation describes anomalous dynamics noise is not only the origin of uncertainty but also plays a positive role in helping to detect signal with information termed stochastic resonance sr this paper analyzes the anomalous resonant behaviors of the generalized langevin system with a multiplicative dichotomous noise and an internal tempered mittagleffler noise for the system with fluctuating harmonic potential we obtain the exact expressions of several sr such as the first moment the amplitude and the autocorrelation function for the output signal as well as the signalnoise ratio we analyze the influence of the tempering parameter and memory exponent on the bona fide sr and the general sr moreover it is detected that the critical memory exponent changes regularly with the increase of tempering parameter almost all the theoretical results are validated by numerical simulations
[['the', 'generalized', 'langevin', 'equation', 'describes', 'anomalous', 'dynamics', 'noise', 'is', 'not', 'only', 'the', 'origin', 'of', 'uncertainty', 'but', 'also', 'plays', 'a', 'positive', 'role', 'in', 'helping', 'to', 'detect', 'signal', 'with', 'information', 'termed', 'stochastic', 'resonance', 'sr', 'this', 'paper', 'analyzes', 'the', 'anomalous', 'resonant', 'behaviors', 'of', 'the', 'generalized', 'langevin', 'system', 'with', 'a', 'multiplicative', 'dichotomous', 'noise', 'and', 'an', 'internal', 'tempered', 'mittagleffler', 'noise', 'for', 'the', 'system', 'with', 'fluctuating', 'harmonic', 'potential', 'we', 'obtain', 'the', 'exact', 'expressions', 'of', 'several', 'sr', 'such', 'as', 'the', 'first', 'moment', 'the', 'amplitude', 'and', 'the', 'autocorrelation', 'function', 'for', 'the', 'output', 'signal', 'as', 'well', 'as', 'the', 'signalnoise', 'ratio', 'we', 'analyze', 'the', 'influence', 'of', 'the', 'tempering', 'parameter', 'and', 'memory', 'exponent', 'on', 'the', 'bona', 'fide', 'sr', 'and', 'the', 'general', 'sr', 'moreover', 'it', 'is', 'detected', 'that', 'the', 'critical', 'memory', 'exponent', 'changes', 'regularly', 'with', 'the', 'increase', 'of', 'tempering', 'parameter', 'almost', 'all', 'the', 'theoretical', 'results', 'are', 'validated', 'by', 'numerical', 'simulations']]
[-0.12893756914000615, 0.11692414591453744, -0.06462546523139083, 0.08872723090546746, -0.045512704166037074, -0.14157809721697392, 0.0474859919998815, 0.3327369379888599, -0.27983935596083925, -0.28942324707041617, 0.07587630681244764, -0.2919595409825822, -0.20828364353856424, 0.17683603736720438, -0.032335640670245754, 0.06582605038040681, 0.0037825002446365747, 0.06331498537927974, -0.03480173921907671, -0.213640539812437, 0.2879588575223866, 0.11383698662520265, 0.2587412537035087, -0.008413805987388976, 0.13090718261209194, -0.014980078500229865, -0.0341565550500662, -0.0019148297547160284, -0.11723473270456822, 0.03371803077454282, 0.1922250206420279, 0.06460345052250162, 0.24480821382240864, -0.3536619584487778, -0.22335211198399033, 0.12186828392652282, 0.15104643130937315, 0.0823134517810051, -0.042505395150763674, -0.30127764292115317, 0.05728163425405712, -0.14527633366431447, -0.14313953837879217, -0.1132746815033581, 0.030649762541609074, 0.08295116228037987, -0.292260511484726, 0.13091632334892536, 0.10666276445102783, 0.05096335096311742, -0.06499544415999191, -0.14369835170066875, 0.021456867825928264, 0.11421817882354304, 0.060951705416327044, 0.005464635082466555, 0.15939273154767958, -0.11387941003540882, -0.09908472979356926, 0.3367172260338481, -0.1137077695760957, -0.22017747302121227, 0.1391974425321256, -0.17470630533669307, -0.12466370977420846, 0.1330002642395245, 0.14556983790859795, 0.07285916535318762, -0.17220760173285785, 0.06126778843252501, 0.04202595493921578, 0.18767577592971857, 0.027253598850422903, 0.053820979874665456, 0.13700383410289668, 0.15753832169929924, 0.037526045257792524, 0.1646489247534613, -0.13985022135476238, -0.13869609858459403, -0.29266199998328113, -0.1606351262678905, -0.17882362111350117, 0.04552415774578812, -0.12671218265102757, -0.17400211278025224, 0.385184560895668, 0.16085091490379494, 0.17472486160830528, 0.06604609810544745, 0.2905452319933776, 0.19282415912543976, -0.006207921980893699, 0.03463063969452312, 0.2103510079500468, 0.150778780505736, 0.12003339794329435, -0.28604877892665675, 0.09687377598564363, 0.01149208119570993]
1,802.02212
Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach
Analysis of histopathology slides is a critical step for many diagnoses, and in particular in oncology where it defines the gold standard. In the case of digital histopathological analysis, highly trained pathologists must review vast whole-slide-images of extreme digital resolution ($100,000^2$ pixels) across multiple zoom levels in order to locate abnormal regions of cells, or in some cases single cells, out of millions. The application of deep learning to this problem is hampered not only by small sample sizes, as typical datasets contain only a few hundred samples, but also by the generation of ground-truth localized annotations for training interpretable classification and segmentation models. We propose a method for disease localization in the context of weakly supervised learning, where only image-level labels are available during training. Even without pixel-level annotations, we are able to demonstrate performance comparable with models trained with strong annotations on the Camelyon-16 lymph node metastases detection challenge. We accomplish this through the use of pre-trained deep convolutional networks, feature embedding, as well as learning via top instances and negative evidence, a multiple instance learning technique from the field of semantic segmentation and object detection.
cs.CV cs.LG stat.ML
analysis of histopathology slides is a critical step for many diagnoses and in particular in oncology where it defines the gold standard in the case of digital histopathological analysis highly trained pathologists must review vast wholeslideimages of extreme digital resolution 1000002 pixels across multiple zoom levels in order to locate abnormal regions of cells or in some cases single cells out of millions the application of deep learning to this problem is hampered not only by small sample sizes as typical datasets contain only a few hundred samples but also by the generation of groundtruth localized annotations for training interpretable classification and segmentation models we propose a method for disease localization in the context of weakly supervised learning where only imagelevel labels are available during training even without pixellevel annotations we are able to demonstrate performance comparable with models trained with strong annotations on the camelyon16 lymph node metastases detection challenge we accomplish this through the use of pretrained deep convolutional networks feature embedding as well as learning via top instances and negative evidence a multiple instance learning technique from the field of semantic segmentation and object detection
[['analysis', 'of', 'histopathology', 'slides', 'is', 'a', 'critical', 'step', 'for', 'many', 'diagnoses', 'and', 'in', 'particular', 'in', 'oncology', 'where', 'it', 'defines', 'the', 'gold', 'standard', 'in', 'the', 'case', 'of', 'digital', 'histopathological', 'analysis', 'highly', 'trained', 'pathologists', 'must', 'review', 'vast', 'wholeslideimages', 'of', 'extreme', 'digital', 'resolution', '1000002', 'pixels', 'across', 'multiple', 'zoom', 'levels', 'in', 'order', 'to', 'locate', 'abnormal', 'regions', 'of', 'cells', 'or', 'in', 'some', 'cases', 'single', 'cells', 'out', 'of', 'millions', 'the', 'application', 'of', 'deep', 'learning', 'to', 'this', 'problem', 'is', 'hampered', 'not', 'only', 'by', 'small', 'sample', 'sizes', 'as', 'typical', 'datasets', 'contain', 'only', 'a', 'few', 'hundred', 'samples', 'but', 'also', 'by', 'the', 'generation', 'of', 'groundtruth', 'localized', 'annotations', 'for', 'training', 'interpretable', 'classification', 'and', 'segmentation', 'models', 'we', 'propose', 'a', 'method', 'for', 'disease', 'localization', 'in', 'the', 'context', 'of', 'weakly', 'supervised', 'learning', 'where', 'only', 'imagelevel', 'labels', 'are', 'available', 'during', 'training', 'even', 'without', 'pixellevel', 'annotations', 'we', 'are', 'able', 'to', 'demonstrate', 'performance', 'comparable', 'with', 'models', 'trained', 'with', 'strong', 'annotations', 'on', 'the', 'camelyon16', 'lymph', 'node', 'metastases', 'detection', 'challenge', 'we', 'accomplish', 'this', 'through', 'the', 'use', 'of', 'pretrained', 'deep', 'convolutional', 'networks', 'feature', 'embedding', 'as', 'well', 'as', 'learning', 'via', 'top', 'instances', 'and', 'negative', 'evidence', 'a', 'multiple', 'instance', 'learning', 'technique', 'from', 'the', 'field', 'of', 'semantic', 'segmentation', 'and', 'object', 'detection']]
[-0.01292854829400938, 0.01702574714367348, 0.02081127288020266, 0.06827815152612084, -0.09165683638314487, -0.18780139046570948, 0.05169148490543888, 0.4522644224882086, -0.23586232732650975, -0.3680947315278313, 0.09816147311795903, -0.295052829560303, -0.15949441665866143, 0.1982079313752512, -0.13332077050181004, 0.05224330571820579, 0.18184588085647213, 0.07673067983330017, -0.011538984325353897, -0.28575418891024684, 0.292625890098392, -0.0015584261695508876, 0.3353220217120183, 0.0033519125884018276, 0.12886820184830475, -0.039615056139507124, -0.04808538763218068, 0.0026236999366285813, -0.027336394401318492, 0.15721574285185286, 0.35938354947289575, 0.18012238677430858, 0.3630514012859954, -0.41473110226934784, -0.22848930727672934, 0.11313035047703213, 0.18175210043542608, 0.13069179458241667, -0.045242940324799266, -0.35748907837951654, 0.11108403441856705, -0.136790125090028, 0.03770686090693519, -0.12842024060126433, -0.03861180800751793, -0.027250894007989034, -0.2673291577935664, 0.08517339170183762, 0.047394570333430024, 0.11090167851552808, -0.05822555997824517, -0.06906152332341799, -0.0012403468899328703, 0.19721319391867848, 0.02126261706699327, 0.03719324634350356, 0.1553727313312852, -0.27238197451186996, -0.09136732386660472, 0.3317548442852664, -0.02852658541767948, -0.18552158053673964, 0.22947644786433546, -0.07754090580318163, -0.15188090058584366, 0.13890157461226468, 0.2218165987181247, 0.16796270171580938, -0.16399969118841304, -0.0165597405966862, -0.029182680987662846, 0.2091678034686934, 0.07979102095749269, -0.036211921608135585, 0.19966917051257746, 0.28308206095525457, -0.00922378658984227, 0.13951870828856944, -0.20306141296982444, -0.016747824198025608, -0.2403544326098786, -0.10598128994110652, -0.20177376927477458, -0.013245521001790035, -0.10309976223895016, -0.20093946700655324, 0.37628871271817355, 0.21422436140397544, 0.22743354453855463, 0.0753360466131257, 0.33420633712923653, -0.04482752617426036, 0.17148522407777847, 0.04148640320573743, 0.16596881766263422, -0.01024451327021359, 0.11197139489494505, -0.11295334219066326, 0.10119375875607754, 0.0581417908123444]
1,802.02213
A Multiresolution Convolutional Neural Network with Partial Label Training for Annotating Reflectance Confocal Microscopy Images of Skin
We describe a new multiresolution "nested encoder-decoder" convolutional network architecture and use it to annotate morphological patterns in reflectance confocal microscopy (RCM) images of human skin for aiding cancer diagnosis. Skin cancers are the most common types of cancers, melanoma being the deadliest among them. RCM is an effective, non-invasive pre-screening tool for skin cancer diagnosis, with the required cellular resolution. However, images are complex, low-contrast, and highly variable, so that clinicians require months to years of expert-level training to be able to make accurate assessments. In this paper, we address classifying 4 key clinically important structural/textural patterns in RCM images. The occurrence and morphology of these patterns are used by clinicians for diagnosis of melanomas. The large size of RCM images, the large variance of pattern size, the large-scale range over which patterns appear, the class imbalance in collected images, and the lack of fully-labeled images all make this a challenging problem to address, even with automated machine learning tools. We designed a novel nested U-net architecture to cope with these challenges, and a selective loss function to handle partial labeling. Trained and tested on 56 melanoma-suspicious, partially labeled, 12k x 12k pixel images, our network automatically annotated diagnostic patterns with high sensitivity and specificity, providing consistent labels for unlabeled sections of the test images. Providing such annotation will aid clinicians in achieving diagnostic accuracy, and perhaps more important, dramatically facilitate clinical training, thus enabling much more rapid adoption of RCM into widespread clinical use process. In addition, our adaptation of U-net architecture provides an intrinsically multiresolution deep network that may be useful in other challenging biomedical image analysis applications.
cs.CV
we describe a new multiresolution nested encoderdecoder convolutional network architecture and use it to annotate morphological patterns in reflectance confocal microscopy rcm images of human skin for aiding cancer diagnosis skin cancers are the most common types of cancers melanoma being the deadliest among them rcm is an effective noninvasive prescreening tool for skin cancer diagnosis with the required cellular resolution however images are complex lowcontrast and highly variable so that clinicians require months to years of expertlevel training to be able to make accurate assessments in this paper we address classifying 4 key clinically important structuraltextural patterns in rcm images the occurrence and morphology of these patterns are used by clinicians for diagnosis of melanomas the large size of rcm images the large variance of pattern size the largescale range over which patterns appear the class imbalance in collected images and the lack of fullylabeled images all make this a challenging problem to address even with automated machine learning tools we designed a novel nested unet architecture to cope with these challenges and a selective loss function to handle partial labeling trained and tested on 56 melanomasuspicious partially labeled 12k x 12k pixel images our network automatically annotated diagnostic patterns with high sensitivity and specificity providing consistent labels for unlabeled sections of the test images providing such annotation will aid clinicians in achieving diagnostic accuracy and perhaps more important dramatically facilitate clinical training thus enabling much more rapid adoption of rcm into widespread clinical use process in addition our adaptation of unet architecture provides an intrinsically multiresolution deep network that may be useful in other challenging biomedical image analysis applications
[['we', 'describe', 'a', 'new', 'multiresolution', 'nested', 'encoderdecoder', 'convolutional', 'network', 'architecture', 'and', 'use', 'it', 'to', 'annotate', 'morphological', 'patterns', 'in', 'reflectance', 'confocal', 'microscopy', 'rcm', 'images', 'of', 'human', 'skin', 'for', 'aiding', 'cancer', 'diagnosis', 'skin', 'cancers', 'are', 'the', 'most', 'common', 'types', 'of', 'cancers', 'melanoma', 'being', 'the', 'deadliest', 'among', 'them', 'rcm', 'is', 'an', 'effective', 'noninvasive', 'prescreening', 'tool', 'for', 'skin', 'cancer', 'diagnosis', 'with', 'the', 'required', 'cellular', 'resolution', 'however', 'images', 'are', 'complex', 'lowcontrast', 'and', 'highly', 'variable', 'so', 'that', 'clinicians', 'require', 'months', 'to', 'years', 'of', 'expertlevel', 'training', 'to', 'be', 'able', 'to', 'make', 'accurate', 'assessments', 'in', 'this', 'paper', 'we', 'address', 'classifying', '4', 'key', 'clinically', 'important', 'structuraltextural', 'patterns', 'in', 'rcm', 'images', 'the', 'occurrence', 'and', 'morphology', 'of', 'these', 'patterns', 'are', 'used', 'by', 'clinicians', 'for', 'diagnosis', 'of', 'melanomas', 'the', 'large', 'size', 'of', 'rcm', 'images', 'the', 'large', 'variance', 'of', 'pattern', 'size', 'the', 'largescale', 'range', 'over', 'which', 'patterns', 'appear', 'the', 'class', 'imbalance', 'in', 'collected', 'images', 'and', 'the', 'lack', 'of', 'fullylabeled', 'images', 'all', 'make', 'this', 'a', 'challenging', 'problem', 'to', 'address', 'even', 'with', 'automated', 'machine', 'learning', 'tools', 'we', 'designed', 'a', 'novel', 'nested', 'unet', 'architecture', 'to', 'cope', 'with', 'these', 'challenges', 'and', 'a', 'selective', 'loss', 'function', 'to', 'handle', 'partial', 'labeling', 'trained', 'and', 'tested', 'on', '56', 'melanomasuspicious', 'partially', 'labeled', '12k', 'x', '12k', 'pixel', 'images', 'our', 'network', 'automatically', 'annotated', 'diagnostic', 'patterns', 'with', 'high', 'sensitivity', 'and', 'specificity', 'providing', 'consistent', 'labels', 'for', 'unlabeled', 'sections', 'of', 'the', 'test', 'images', 'providing', 'such', 'annotation', 'will', 'aid', 'clinicians', 'in', 'achieving', 'diagnostic', 'accuracy', 'and', 'perhaps', 'more', 'important', 'dramatically', 'facilitate', 'clinical', 'training', 'thus', 'enabling', 'much', 'more', 'rapid', 'adoption', 'of', 'rcm', 'into', 'widespread', 'clinical', 'use', 'process', 'in', 'addition', 'our', 'adaptation', 'of', 'unet', 'architecture', 'provides', 'an', 'intrinsically', 'multiresolution', 'deep', 'network', 'that', 'may', 'be', 'useful', 'in', 'other', 'challenging', 'biomedical', 'image', 'analysis', 'applications']]
[-0.009746303749841995, 0.03229483450275195, -0.009245759928702866, 0.10479011443394179, -0.11725590015037962, -0.18534538066741701, 0.015614432690199465, 0.4515644645692303, -0.2343865445598425, -0.3361256072595439, 0.09256329049259342, -0.2640786304791652, -0.1820366866899599, 0.20395000142453854, -0.17289440859226876, 0.09421161223388169, 0.15095589768992335, -0.008897571672155734, 0.0028378593083644168, -0.28247719228901247, 0.2576251651201965, 0.054429288002204486, 0.363546738618739, 0.011670576218951867, 0.0867967556713696, -0.020536866189641914, -0.07963512656490966, -0.01799282715110572, -0.04781843078991123, 0.19678023624619934, 0.41809764508760383, 0.23374659233799266, 0.3188355837110776, -0.4504436208701218, -0.2286618324896826, 0.09011834073590191, 0.16125212908379705, 0.0894771109566224, -0.034849151901984725, -0.32954127011391365, 0.10070752632738433, -0.13221213172820007, -0.04504110738133049, -0.15149895058205648, 0.009958562475791872, -0.04907446668559485, -0.30161029100483006, 0.07906638886673518, 0.00825294651537718, 0.16468099114869386, -0.060875816809075806, -0.09072985633217547, 0.027469903041979084, 0.2009668406601095, 0.008443360024657218, 0.07250740388442925, 0.14577718777473855, -0.21514273435137057, -0.09157184682454096, 0.338590692752993, 0.054922595030721624, -0.17670446353337857, 0.23355574586401004, -0.07014181473912139, -0.14194389356501041, 0.16263152360846894, 0.21895508412410225, 0.11078305801612127, -0.1934593573176271, -0.08588433790810018, 0.02855374470533159, 0.2217308268557756, 0.08730338847690494, -0.019676183311488966, 0.17739379771926256, 0.2836781574056577, 0.004101501937244143, 0.13030519041766803, -0.18805962096266604, 0.036801365073242304, -0.1811716988379591, -0.1428655308456966, -0.10566658248603829, -0.014370335846339599, -0.11439963929507913, -0.18862509119608284, 0.37886260561368057, 0.23020696287003578, 0.18705353761251087, 0.043375664204964935, 0.3149797765842767, -0.03579442589162921, 0.18128109791274546, -0.01213433856030296, 0.12761235163334175, 0.033942609921973683, 0.13182380222793336, -0.16654500096420097, 0.12535510643374098, 0.012008433989301102]
1,802.02214
Electromagnetically driven convection suitable for mass transfer enhancement in liquid metal batteries
Liquid metal batteries (LMBs) were recently proposed as cheap large scale energy storage. Such devices are urgently required for balancing highly fluctuating renewable energy sources. During discharge, intermetallic phases tend to form in the cathode of LMBs. These do not only limit the up-scalability, but also the efficiency of the cells. Generating a mild fluid flow in the fully liquid cell will smoothen concentration gradients and minimise the formation of intermetallics. In this context we study electro-vortex flow numerically. We simulate a recent LMB related experiment and discuss how the feeding lines to the cell can be optimised to enhance mass transfer. The Lorentz forces have to overcome the stable thermal stratification in the cathode of the cell; we show that thermal effects may reduce electro-vortex flow velocities considerable. Finally, we study the influence of the Earth magnetic field on the flow.
physics.app-ph physics.flu-dyn
liquid metal batteries lmbs were recently proposed as cheap large scale energy storage such devices are urgently required for balancing highly fluctuating renewable energy sources during discharge intermetallic phases tend to form in the cathode of lmbs these do not only limit the upscalability but also the efficiency of the cells generating a mild fluid flow in the fully liquid cell will smoothen concentration gradients and minimise the formation of intermetallics in this context we study electrovortex flow numerically we simulate a recent lmb related experiment and discuss how the feeding lines to the cell can be optimised to enhance mass transfer the lorentz forces have to overcome the stable thermal stratification in the cathode of the cell we show that thermal effects may reduce electrovortex flow velocities considerable finally we study the influence of the earth magnetic field on the flow
[['liquid', 'metal', 'batteries', 'lmbs', 'were', 'recently', 'proposed', 'as', 'cheap', 'large', 'scale', 'energy', 'storage', 'such', 'devices', 'are', 'urgently', 'required', 'for', 'balancing', 'highly', 'fluctuating', 'renewable', 'energy', 'sources', 'during', 'discharge', 'intermetallic', 'phases', 'tend', 'to', 'form', 'in', 'the', 'cathode', 'of', 'lmbs', 'these', 'do', 'not', 'only', 'limit', 'the', 'upscalability', 'but', 'also', 'the', 'efficiency', 'of', 'the', 'cells', 'generating', 'a', 'mild', 'fluid', 'flow', 'in', 'the', 'fully', 'liquid', 'cell', 'will', 'smoothen', 'concentration', 'gradients', 'and', 'minimise', 'the', 'formation', 'of', 'intermetallics', 'in', 'this', 'context', 'we', 'study', 'electrovortex', 'flow', 'numerically', 'we', 'simulate', 'a', 'recent', 'lmb', 'related', 'experiment', 'and', 'discuss', 'how', 'the', 'feeding', 'lines', 'to', 'the', 'cell', 'can', 'be', 'optimised', 'to', 'enhance', 'mass', 'transfer', 'the', 'lorentz', 'forces', 'have', 'to', 'overcome', 'the', 'stable', 'thermal', 'stratification', 'in', 'the', 'cathode', 'of', 'the', 'cell', 'we', 'show', 'that', 'thermal', 'effects', 'may', 'reduce', 'electrovortex', 'flow', 'velocities', 'considerable', 'finally', 'we', 'study', 'the', 'influence', 'of', 'the', 'earth', 'magnetic', 'field', 'on', 'the', 'flow']]
[-0.11522440379219044, 0.19782643371038663, -0.03294618545152562, 0.04220725730320596, -0.031183105493357902, -0.10007805328875204, 0.052075563116707434, 0.3837002163726679, -0.2647719294304999, -0.3057378263304561, 0.0860174240201751, -0.26837137684514617, -0.09987994964057448, 0.17753838922936652, -0.1037212412683031, 0.03470108075014932, 0.029147788974076088, -0.04151521826779444, -0.03009391476360845, -0.2094012685972725, 0.24555967926231384, 0.110832344071651, 0.33367226605342937, 0.10117172759721502, 0.06732211190826771, -0.11289839582799763, 0.009242069622186917, 0.06335442770324962, -0.1423246922862694, 0.07809214256490699, 0.23383530705485125, 0.02981204380491145, 0.23952534937129263, -0.5348535566262795, -0.26749916133736457, 0.10481862911567565, 0.12659971865589245, 0.10331839232780958, -0.10734886767401715, -0.18214035745132978, 0.08626782929059118, -0.19557599517070806, -0.12191024300481215, -0.1006114304288697, -0.019231195116422177, 0.08172760590456728, -0.2205134327293859, 0.05430653619126607, 0.016607758175896506, 0.02212638132975922, -0.10547324950435005, -0.09466835405041372, -0.06525851063336849, 0.116573906054353, 0.055087526391168505, -0.0256270578747589, 0.2243922336263136, -0.14382276217564677, -0.02649749175999576, 0.3941951571425921, -0.03184436112322556, -0.1636865230483777, 0.20084940444540336, -0.16541936571070756, -0.0850581255984086, 0.14794822447133107, 0.23305503451462153, 0.10840323538906604, -0.16386296970992756, 0.0014507652343985376, 0.0008040452080870598, 0.13754970183871476, 0.06868301353312399, 0.0018167601370344488, 0.23146633006317516, 0.18253888828601217, 0.05263143575555173, 0.12234180389934639, -0.13842381230755513, -0.0756587569313255, -0.23275788579403398, -0.20513922863469367, -0.140413600971109, 0.04415547361191195, -0.051710865527357, -0.15721182212599186, 0.35537941966855136, 0.16873960656730433, 0.14115201269971653, -0.041650831560000885, 0.2879675596585156, 0.0814347759235165, 0.09946278903082433, 0.06930473702631786, 0.26801013081780517, 0.12320333872233111, 0.17469499949169096, -0.3002077269164557, 0.08172839669273792, 0.03860086090469234]
1,802.02215
Lieb polariton topological insulators
We predict that the interplay between the spin-orbit coupling, stemming from the TE-TM energy splitting, and the Zeeman effect in semiconductor microcavities supporting exci- ton-polariton quasi-particles results in the appearance of unidirectional linear topological edge states when the top microcavity mirror is patterned to form a truncated dislocated Lieb lattice of cylindrical pillars. Periodic nonlinear edge states are found to emerge from the linear ones. They are strongly localized across the interface and they are remarkably robust in comparison to their counterparts in hexagonal lattices. Such robustness makes possible the existence of nested unidirectional dark solitons that move steadily along the lattice edge.
cond-mat.mes-hall nlin.PS physics.optics
we predict that the interplay between the spinorbit coupling stemming from the tetm energy splitting and the zeeman effect in semiconductor microcavities supporting exci tonpolariton quasiparticles results in the appearance of unidirectional linear topological edge states when the top microcavity mirror is patterned to form a truncated dislocated lieb lattice of cylindrical pillars periodic nonlinear edge states are found to emerge from the linear ones they are strongly localized across the interface and they are remarkably robust in comparison to their counterparts in hexagonal lattices such robustness makes possible the existence of nested unidirectional dark solitons that move steadily along the lattice edge
[['we', 'predict', 'that', 'the', 'interplay', 'between', 'the', 'spinorbit', 'coupling', 'stemming', 'from', 'the', 'tetm', 'energy', 'splitting', 'and', 'the', 'zeeman', 'effect', 'in', 'semiconductor', 'microcavities', 'supporting', 'exci', 'tonpolariton', 'quasiparticles', 'results', 'in', 'the', 'appearance', 'of', 'unidirectional', 'linear', 'topological', 'edge', 'states', 'when', 'the', 'top', 'microcavity', 'mirror', 'is', 'patterned', 'to', 'form', 'a', 'truncated', 'dislocated', 'lieb', 'lattice', 'of', 'cylindrical', 'pillars', 'periodic', 'nonlinear', 'edge', 'states', 'are', 'found', 'to', 'emerge', 'from', 'the', 'linear', 'ones', 'they', 'are', 'strongly', 'localized', 'across', 'the', 'interface', 'and', 'they', 'are', 'remarkably', 'robust', 'in', 'comparison', 'to', 'their', 'counterparts', 'in', 'hexagonal', 'lattices', 'such', 'robustness', 'makes', 'possible', 'the', 'existence', 'of', 'nested', 'unidirectional', 'dark', 'solitons', 'that', 'move', 'steadily', 'along', 'the', 'lattice', 'edge']]
[-0.2090086452286307, 0.22946919507219218, -0.04891376573038328, 0.05796137769756766, -0.08659693890926885, -0.17632887645295875, 0.030184019760995665, 0.45191289997641365, -0.2962314923038231, -0.25801798363453615, 0.031960951776115916, -0.3152513552740143, -0.15419244457620615, 0.13804167990490576, 0.02230428533363795, 0.04177050855850764, 0.031826146155842304, -0.0735752689013002, -0.04661406697899414, -0.1844885262418721, 0.29914983102650033, -0.017667713159622223, 0.35707243781664644, 0.06822820714510539, -0.013164618387521592, -0.007598967014643017, 0.0736801062080571, 0.009268968991533505, -0.10340969910455397, 0.11897809201207779, 0.22622076560761414, -0.10883388177171582, 0.1990788332985568, -0.49914208070977645, -0.16211288252516703, 0.008046606409491277, 0.13951619351556635, 0.18587437953672134, -0.06957347684895948, -0.32205226275996834, 0.05718801462881304, -0.11648410977481856, -0.14840468905373094, -0.0391649140465055, -0.01676684345162072, 0.02839180065647644, -0.19436321970915385, 0.05932664087637985, 0.10144154391452379, 0.02280271478800797, -0.06486524711363018, -0.08419299951192978, -0.14943128845234419, 0.0626125019035124, 0.01345270206266101, -0.01445032284576811, 0.120128114931468, -0.1634456847392607, -0.15252310960489673, 0.38520205565089105, -0.08800727079563099, -0.17207896312032187, 0.23252073947258076, -0.1330639581908198, -0.0038157517875672554, 0.15372267789116092, 0.17058269821527397, 0.03442043911976119, -0.05094496077842504, 0.0663395908435204, -0.07192190088715185, 0.13206265380094742, 0.10564520228288922, 0.12090247331099246, 0.2854289851680982, 0.13173632007879754, 0.10450749348748621, 0.1690503722205119, -0.07663782668646936, -0.15641903493601336, -0.23502350512917117, -0.10945844380915457, -0.208603844512254, 0.022130678572198925, -0.039026089514521245, -0.21806589785538724, 0.40368131516893924, 0.06257268245555643, 0.1931111793919448, -0.03201960138868148, 0.21003079749917722, 0.09814295890129299, 0.09317340310343414, 0.06225222579372462, 0.29776651028991113, 0.16971104173503324, 0.05409592141251208, -0.27293608867216346, -0.02816425582083563, 0.010623499020641925]
1,802.02216
The Heart of an Image: Quantum Superposition and Entanglement in Visual Perception
We analyse the way in which the principle that 'the whole is greater than the sum of its parts' manifests itself with phenomena of visual perception. For this investigation we use insights and techniques coming from quantum cognition, and more specifically we are inspired by the correspondence of this principle with the phenomenon of the conjunction effect in human cognition. We identify entities of meaning within artefacts of visual perception and rely on how such entities are modelled for corpuses of texts such as the webpages of the World-Wide Web for our study of how they appear in phenomena of visual perception. We identify concretely the conjunction effect in visual artefacts and analyse its structure in the example of a photograph. We also analyse quantum entanglement between different aspects of meaning in artefacts of visual perception. We confirm its presence by showing that well elected experiments on images retrieved accordingly by Google Images give rise to probabilities and expectation values violating the Clauser Horne Shimony Holt version of Bell's inequalities. We point out how this approach can lead to a mathematical description of the meaning content of a visual artefact such as a photograph.
cs.CV quant-ph
we analyse the way in which the principle that the whole is greater than the sum of its parts manifests itself with phenomena of visual perception for this investigation we use insights and techniques coming from quantum cognition and more specifically we are inspired by the correspondence of this principle with the phenomenon of the conjunction effect in human cognition we identify entities of meaning within artefacts of visual perception and rely on how such entities are modelled for corpuses of texts such as the webpages of the worldwide web for our study of how they appear in phenomena of visual perception we identify concretely the conjunction effect in visual artefacts and analyse its structure in the example of a photograph we also analyse quantum entanglement between different aspects of meaning in artefacts of visual perception we confirm its presence by showing that well elected experiments on images retrieved accordingly by google images give rise to probabilities and expectation values violating the clauser horne shimony holt version of bells inequalities we point out how this approach can lead to a mathematical description of the meaning content of a visual artefact such as a photograph
[['we', 'analyse', 'the', 'way', 'in', 'which', 'the', 'principle', 'that', 'the', 'whole', 'is', 'greater', 'than', 'the', 'sum', 'of', 'its', 'parts', 'manifests', 'itself', 'with', 'phenomena', 'of', 'visual', 'perception', 'for', 'this', 'investigation', 'we', 'use', 'insights', 'and', 'techniques', 'coming', 'from', 'quantum', 'cognition', 'and', 'more', 'specifically', 'we', 'are', 'inspired', 'by', 'the', 'correspondence', 'of', 'this', 'principle', 'with', 'the', 'phenomenon', 'of', 'the', 'conjunction', 'effect', 'in', 'human', 'cognition', 'we', 'identify', 'entities', 'of', 'meaning', 'within', 'artefacts', 'of', 'visual', 'perception', 'and', 'rely', 'on', 'how', 'such', 'entities', 'are', 'modelled', 'for', 'corpuses', 'of', 'texts', 'such', 'as', 'the', 'webpages', 'of', 'the', 'worldwide', 'web', 'for', 'our', 'study', 'of', 'how', 'they', 'appear', 'in', 'phenomena', 'of', 'visual', 'perception', 'we', 'identify', 'concretely', 'the', 'conjunction', 'effect', 'in', 'visual', 'artefacts', 'and', 'analyse', 'its', 'structure', 'in', 'the', 'example', 'of', 'a', 'photograph', 'we', 'also', 'analyse', 'quantum', 'entanglement', 'between', 'different', 'aspects', 'of', 'meaning', 'in', 'artefacts', 'of', 'visual', 'perception', 'we', 'confirm', 'its', 'presence', 'by', 'showing', 'that', 'well', 'elected', 'experiments', 'on', 'images', 'retrieved', 'accordingly', 'by', 'google', 'images', 'give', 'rise', 'to', 'probabilities', 'and', 'expectation', 'values', 'violating', 'the', 'clauser', 'horne', 'shimony', 'holt', 'version', 'of', 'bells', 'inequalities', 'we', 'point', 'out', 'how', 'this', 'approach', 'can', 'lead', 'to', 'a', 'mathematical', 'description', 'of', 'the', 'meaning', 'content', 'of', 'a', 'visual', 'artefact', 'such', 'as', 'a', 'photograph']]
[-0.06418420202110789, 0.07017394538714368, -0.11644340201596652, 0.10507168491027731, -0.10528361264462631, -0.09837201948892133, 0.0788997946398275, 0.3648417584991716, -0.2480022254785206, -0.33765072396658746, 0.07969623664033974, -0.29848483393866493, -0.24071156770559796, 0.18781046969240012, -0.146166765744337, -0.008354088789816423, 0.04247843056494735, 0.06469025603764374, -0.04794782598817375, -0.21647950015918918, 0.3201202922188629, 0.032143762287925016, 0.2728202689940724, 0.06772581320352007, 0.0972248430972314, 0.005928115357558445, -0.07668390712393544, 0.027943541696079113, -0.09418901515749256, 0.1568407237820193, 0.28125162237112594, 0.22185394046684132, 0.2711594103530683, -0.4254472299440543, -0.18251815994423767, 0.07109040735870331, 0.11558376927139986, 0.11384052087699265, -0.029035285334045802, -0.37814309889661896, 0.04661580130275454, -0.1512947084355773, -0.0822793705072062, -0.08936699591673065, 0.011270172688773996, -0.03080229341297305, -0.2029785791321384, 0.07296576387157121, 0.07575233628764537, 0.1199622191254712, -0.02578157885960236, -0.053484177833768666, 0.01628711696152489, 0.19275692236830586, 0.04989680883921107, -0.03059112909399981, 0.15162552863637888, -0.18294439357033326, -0.1731103617012664, 0.4300682431269322, -0.02618063040494441, -0.20380129094363716, 0.2028366820490679, -0.11255631986861453, -0.13546469715212653, 0.031054206199694387, 0.17102420896522164, 0.07012992032045096, -0.14174916792076475, 0.02705520403315793, -0.06938877878422589, 0.16927109423802192, 0.08507746059601147, 0.09291959693295325, 0.23158854064915674, 0.1473865239477726, -0.019416676128532775, 0.15916381127767495, -0.06119676180347109, -0.08463443516388766, -0.28752645975958135, -0.16628056727397764, -0.1544199658416154, 0.048465730756828466, -0.08537055044211435, -0.13579454915309996, 0.37431951930035945, 0.22530435975977056, 0.19907634932855048, 0.022877454201417218, 0.2804350815101325, 0.053293717381203566, 0.07952547650160172, 0.012122859640680637, 0.21289429330139795, 0.0491024568885776, 0.14337236030728162, -0.18878536444390193, 0.08472553508496632, 0.06491017727944616]
1,802.02217
Bright single InAsP quantum dots at telecom wavelengths in position-controlled InP nanowires: the role of the photonic waveguide
We report on the site-selected growth of bright single InAsP quantum dots embedded within InP photonic nanowire waveguides emitting at telecom wavelengths. We demonstrate a dramatic dependence of the emission rate on both the emission wavelength and the nanowire diameter. With an appropriately designed waveguide, tailored to the emission wavelength of the dot, an increase in count rate by nearly two orders of magnitude (0.4kcps to 35kcps) is obtained for quantum dots emitting in the telecom O-band. Using emission-wavelength-optimised waveguides, we demonstrate bright, narrow linewidth emission from single InAsP quantum dots with an unprecedented tuning range from 880nm to 1550nm. These results pave the way towards efficient single photon sources at telecom wavelengths using deterministically grown InAsP/InP nanowire quantum dots.
cond-mat.mes-hall physics.optics
we report on the siteselected growth of bright single inasp quantum dots embedded within inp photonic nanowire waveguides emitting at telecom wavelengths we demonstrate a dramatic dependence of the emission rate on both the emission wavelength and the nanowire diameter with an appropriately designed waveguide tailored to the emission wavelength of the dot an increase in count rate by nearly two orders of magnitude 04kcps to 35kcps is obtained for quantum dots emitting in the telecom oband using emissionwavelengthoptimised waveguides we demonstrate bright narrow linewidth emission from single inasp quantum dots with an unprecedented tuning range from 880nm to 1550nm these results pave the way towards efficient single photon sources at telecom wavelengths using deterministically grown inaspinp nanowire quantum dots
[['we', 'report', 'on', 'the', 'siteselected', 'growth', 'of', 'bright', 'single', 'inasp', 'quantum', 'dots', 'embedded', 'within', 'inp', 'photonic', 'nanowire', 'waveguides', 'emitting', 'at', 'telecom', 'wavelengths', 'we', 'demonstrate', 'a', 'dramatic', 'dependence', 'of', 'the', 'emission', 'rate', 'on', 'both', 'the', 'emission', 'wavelength', 'and', 'the', 'nanowire', 'diameter', 'with', 'an', 'appropriately', 'designed', 'waveguide', 'tailored', 'to', 'the', 'emission', 'wavelength', 'of', 'the', 'dot', 'an', 'increase', 'in', 'count', 'rate', 'by', 'nearly', 'two', 'orders', 'of', 'magnitude', '04kcps', 'to', '35kcps', 'is', 'obtained', 'for', 'quantum', 'dots', 'emitting', 'in', 'the', 'telecom', 'oband', 'using', 'emissionwavelengthoptimised', 'waveguides', 'we', 'demonstrate', 'bright', 'narrow', 'linewidth', 'emission', 'from', 'single', 'inasp', 'quantum', 'dots', 'with', 'an', 'unprecedented', 'tuning', 'range', 'from', '880nm', 'to', '1550nm', 'these', 'results', 'pave', 'the', 'way', 'towards', 'efficient', 'single', 'photon', 'sources', 'at', 'telecom', 'wavelengths', 'using', 'deterministically', 'grown', 'inaspinp', 'nanowire', 'quantum', 'dots']]
[-0.1041797323027979, 0.1783540753131092, 0.005359043038032692, -0.07887492847833621, 0.043426664048356226, -0.2164442895887548, 0.0338426908991974, 0.5846678505065562, -0.2092879166453274, -0.30496422214240865, -0.002475730398396865, -0.33820862105469507, 0.01972256598046756, 0.30074810265194113, 0.024996477916406076, 0.07833827084235462, 0.009965364339536634, -0.1371894744545992, 0.03430250430768677, -0.141755428347849, 0.22919440282316045, 0.04688726931987009, 0.3464939027205752, 0.07054985022766451, 0.08520818957336375, -0.006888360828803531, 0.12178509732194502, -0.10859622899442911, -0.14868145005713249, 0.11623815823635407, 0.25575207238454883, -0.06236359500326216, 0.22777903135584923, -0.4354569035750846, -0.1749582406502731, 0.014371967633608086, 0.21762719167524885, 0.10988053358119816, -0.07768927184074058, -0.3305149863088696, 0.03862606049796309, -0.09850721252311406, -0.11451139725074333, 0.08784545439391814, -0.053437986820615055, -0.011000503494368128, -0.18329085849209464, -0.008389711917923957, -0.03848129924756057, 0.024337196618254328, 0.052504311263529134, -0.005003578097816428, -0.011879133429390313, 0.041479679470849705, -0.12683239026227966, -0.006815617500627735, 0.24649281590647096, -0.08942939956713072, -0.19918504124507308, 0.3161816756594284, -0.11448664997768557, -0.02078805178211167, 0.09976407348836676, -0.22262869964369797, -0.01586326571374104, 0.1939201603627539, 0.14328858040369533, 0.1406744410412322, -0.09199608132395701, 0.01369375160620307, 0.05902053346327538, 0.3023056899165285, 0.14226812285828758, 0.2389722024813166, 0.2982671337426993, 0.1927061654900297, 0.010180620518753883, 0.1951135062183061, -0.18270421106817908, -0.06775202142106819, -0.2556529662668191, -0.15926143072208326, -0.21410400430061693, 0.1499617027183031, -0.13534364150824518, -0.16200864617261185, 0.39752058280182295, 0.12025271537553134, 0.15270475011543724, 4.2872479313920286e-05, 0.27880327496677637, 0.1479270884622659, 0.13844473444021724, 0.044808458384319114, 0.3056610883695298, 0.15252234470621073, 0.06419346147971548, -0.2456572718500834, -0.054473532118898785, -0.12430522207106495]
1,802.02218
On the Preliminary Investigation of Selfish Mining Strategy with Multiple Selfish Miners
Eyal and Sirer's selfish mining strategy has demonstrated that Bitcoin system is not secure even if 50% of total mining power is held by altruistic miners. Since then, researchers have been investigating either to improve the efficiency of selfish mining, or how to defend against it, typically in a single selfish miner setting. Yet there is no research on a selfish mining strategies concurrently used by multiple miners in the system. The effectiveness of such selfish mining strategies and their required mining power under such multiple selfish miners setting remains unknown. In this paper, a preliminary investigation and our findings of selfish mining strategy used by multiple miners are reported. In addition, the conventional model of Bitcoin system is slightly redesigned to tackle its shortcoming: namely, a concurrency of individual mining processes. Although a theoretical analysis of selfish mining strategy under this setting is yet to be established, the current findings based on simulations is promising and of great interest. In particular, our work shows that a lower bound of power threshold required for selfish mining strategy decreases in proportion to a number of selfish miners. Moreover, there exist Nash equilibria where all selfish miners in the system do not change to an honest mining strategy and simultaneously earn their unfair amount of mining reward given that they equally possess sufficiently large mining power. Lastly, our new model yields a power threshold for mounting selfish mining strategy slightly greater than one from the conventional model.
cs.MA cs.CR cs.GT
eyal and sirers selfish mining strategy has demonstrated that bitcoin system is not secure even if 50 of total mining power is held by altruistic miners since then researchers have been investigating either to improve the efficiency of selfish mining or how to defend against it typically in a single selfish miner setting yet there is no research on a selfish mining strategies concurrently used by multiple miners in the system the effectiveness of such selfish mining strategies and their required mining power under such multiple selfish miners setting remains unknown in this paper a preliminary investigation and our findings of selfish mining strategy used by multiple miners are reported in addition the conventional model of bitcoin system is slightly redesigned to tackle its shortcoming namely a concurrency of individual mining processes although a theoretical analysis of selfish mining strategy under this setting is yet to be established the current findings based on simulations is promising and of great interest in particular our work shows that a lower bound of power threshold required for selfish mining strategy decreases in proportion to a number of selfish miners moreover there exist nash equilibria where all selfish miners in the system do not change to an honest mining strategy and simultaneously earn their unfair amount of mining reward given that they equally possess sufficiently large mining power lastly our new model yields a power threshold for mounting selfish mining strategy slightly greater than one from the conventional model
[['eyal', 'and', 'sirers', 'selfish', 'mining', 'strategy', 'has', 'demonstrated', 'that', 'bitcoin', 'system', 'is', 'not', 'secure', 'even', 'if', '50', 'of', 'total', 'mining', 'power', 'is', 'held', 'by', 'altruistic', 'miners', 'since', 'then', 'researchers', 'have', 'been', 'investigating', 'either', 'to', 'improve', 'the', 'efficiency', 'of', 'selfish', 'mining', 'or', 'how', 'to', 'defend', 'against', 'it', 'typically', 'in', 'a', 'single', 'selfish', 'miner', 'setting', 'yet', 'there', 'is', 'no', 'research', 'on', 'a', 'selfish', 'mining', 'strategies', 'concurrently', 'used', 'by', 'multiple', 'miners', 'in', 'the', 'system', 'the', 'effectiveness', 'of', 'such', 'selfish', 'mining', 'strategies', 'and', 'their', 'required', 'mining', 'power', 'under', 'such', 'multiple', 'selfish', 'miners', 'setting', 'remains', 'unknown', 'in', 'this', 'paper', 'a', 'preliminary', 'investigation', 'and', 'our', 'findings', 'of', 'selfish', 'mining', 'strategy', 'used', 'by', 'multiple', 'miners', 'are', 'reported', 'in', 'addition', 'the', 'conventional', 'model', 'of', 'bitcoin', 'system', 'is', 'slightly', 'redesigned', 'to', 'tackle', 'its', 'shortcoming', 'namely', 'a', 'concurrency', 'of', 'individual', 'mining', 'processes', 'although', 'a', 'theoretical', 'analysis', 'of', 'selfish', 'mining', 'strategy', 'under', 'this', 'setting', 'is', 'yet', 'to', 'be', 'established', 'the', 'current', 'findings', 'based', 'on', 'simulations', 'is', 'promising', 'and', 'of', 'great', 'interest', 'in', 'particular', 'our', 'work', 'shows', 'that', 'a', 'lower', 'bound', 'of', 'power', 'threshold', 'required', 'for', 'selfish', 'mining', 'strategy', 'decreases', 'in', 'proportion', 'to', 'a', 'number', 'of', 'selfish', 'miners', 'moreover', 'there', 'exist', 'nash', 'equilibria', 'where', 'all', 'selfish', 'miners', 'in', 'the', 'system', 'do', 'not', 'change', 'to', 'an', 'honest', 'mining', 'strategy', 'and', 'simultaneously', 'earn', 'their', 'unfair', 'amount', 'of', 'mining', 'reward', 'given', 'that', 'they', 'equally', 'possess', 'sufficiently', 'large', 'mining', 'power', 'lastly', 'our', 'new', 'model', 'yields', 'a', 'power', 'threshold', 'for', 'mounting', 'selfish', 'mining', 'strategy', 'slightly', 'greater', 'than', 'one', 'from', 'the', 'conventional', 'model']]
[-0.13749144743576797, 0.040890119953273456, -0.11119759410467683, 0.05789614184735799, -0.1364531392535689, -0.23096507616170056, 0.17522909903414166, 0.3732309183599998, -0.2856032362093731, -0.32851540198055457, 0.0956254522031059, -0.3003735210822553, -0.17433652151233459, 0.14884222537820815, -0.16405210178535506, 0.02969096164024264, 0.04625823583016742, 0.05887930719752093, 0.11893781341982967, -0.35953419764279104, 0.2982893070491145, 0.07257054913028771, 0.3651750026166211, 0.027674277894179887, 0.028068077452100663, -0.0015505146995490912, -0.044444206248664735, 0.02620144564544364, -0.08716957791448851, 0.1120515151310484, 0.3537560761431042, 0.2188968638157738, 0.3989555904375655, -0.41710022602382363, -0.16189198928257945, 0.21275769870215078, 0.16980538960280164, 0.0879632884560495, -0.08007685266226074, -0.21952942893365207, 0.17264800404616612, -0.2508369235378899, -0.07019988394114283, -0.11713599293131609, -0.010104796517526313, 0.015931981404867897, -0.2784828906783796, -0.018341870145986275, 0.06528491993548767, 0.0847457253887337, -0.019264072775175528, -0.12597458484411544, -0.006994608520739237, 0.13503383623616655, 0.09854445350974114, -0.0359805884020289, 0.15955408964382142, -0.14128844703699708, -0.20860076048506462, 0.38767273012852793, 0.024427022238212106, -0.1448874031668719, 0.1756791852614177, -0.02773435396446409, -0.17516385056030917, 0.1177107898936588, 0.1869694252308382, 0.12192230937356244, -0.17712648169574688, -0.004900449304603876, -0.05247610312107266, 0.19977007370171307, 0.0668515077324071, -0.005707147748361589, 0.18904111880015545, 0.22008909017455822, 0.15517215369630377, 0.054838598790407485, -0.0015028818239628964, -0.15998637532929377, -0.1799128694771029, -0.07157445868919128, -0.17724724602933062, 0.026917435527821925, -0.0728023180126911, -0.10813284673899108, 0.32369108386527823, 0.16876711035337374, 0.11534200412392312, 0.03819557813148261, 0.35575910647000586, 0.04980251786289547, 0.06507868895364204, 0.11130599436369173, 0.19977374075702867, -0.019029326220660718, 0.1680220925268166, -0.1935612464292754, 0.17885242705328427, -0.05914825716683147]
1,802.02219
Practical Transfer Learning for Bayesian Optimization
When hyperparameter optimization of a machine learning algorithm is repeated for multiple datasets it is possible to transfer knowledge to an optimization run on a new dataset. We develop a new hyperparameter-free ensemble model for Bayesian optimization that is a generalization of two existing transfer learning extensions to Bayesian optimization and establish a worst-case bound compared to vanilla Bayesian optimization. Using a large collection of hyperparameter optimization benchmark problems, we demonstrate that our contributions substantially reduce optimization time compared to standard Gaussian process-based Bayesian optimization and improve over the current state-of-the-art for transfer hyperparameter optimization.
stat.ML cs.AI
when hyperparameter optimization of a machine learning algorithm is repeated for multiple datasets it is possible to transfer knowledge to an optimization run on a new dataset we develop a new hyperparameterfree ensemble model for bayesian optimization that is a generalization of two existing transfer learning extensions to bayesian optimization and establish a worstcase bound compared to vanilla bayesian optimization using a large collection of hyperparameter optimization benchmark problems we demonstrate that our contributions substantially reduce optimization time compared to standard gaussian processbased bayesian optimization and improve over the current stateoftheart for transfer hyperparameter optimization
[['when', 'hyperparameter', 'optimization', 'of', 'a', 'machine', 'learning', 'algorithm', 'is', 'repeated', 'for', 'multiple', 'datasets', 'it', 'is', 'possible', 'to', 'transfer', 'knowledge', 'to', 'an', 'optimization', 'run', 'on', 'a', 'new', 'dataset', 'we', 'develop', 'a', 'new', 'hyperparameterfree', 'ensemble', 'model', 'for', 'bayesian', 'optimization', 'that', 'is', 'a', 'generalization', 'of', 'two', 'existing', 'transfer', 'learning', 'extensions', 'to', 'bayesian', 'optimization', 'and', 'establish', 'a', 'worstcase', 'bound', 'compared', 'to', 'vanilla', 'bayesian', 'optimization', 'using', 'a', 'large', 'collection', 'of', 'hyperparameter', 'optimization', 'benchmark', 'problems', 'we', 'demonstrate', 'that', 'our', 'contributions', 'substantially', 'reduce', 'optimization', 'time', 'compared', 'to', 'standard', 'gaussian', 'processbased', 'bayesian', 'optimization', 'and', 'improve', 'over', 'the', 'current', 'stateoftheart', 'for', 'transfer', 'hyperparameter', 'optimization']]
[-0.0015323946571075603, -0.08823533515847215, -0.09181793472533556, 0.10430933489880868, -0.14253686839518578, -0.2181953577520816, 0.08090455625206232, 0.43978182163677715, -0.3319034292411647, -0.38736045472323893, 0.11425141794607044, -0.21806420192220494, -0.1448719577177575, 0.2291607203819838, -0.11945193458936716, 0.13308720914156813, 0.17954653127020911, -0.05527618250956661, -0.12042896839312131, -0.3121143023826574, 0.24178868679966975, 0.06518200232990479, 0.31704633900601614, -0.027292284619455275, 0.12626279343630334, 0.03185309089328113, 0.027086039166897537, 0.0009112071160129027, -0.09138526097751884, 0.19012404910876954, 0.3144752856625832, 0.26617014274295225, 0.39232395693267647, -0.33815582502437264, -0.2504425922114598, 0.15487020881356378, 0.17546968318914113, 0.09299942627687031, -0.04506234750274177, -0.2281640228080122, 0.04196897261089792, -0.19822388346503048, 0.08129244877123519, -0.18225554086660084, -0.07437103469978626, -0.029547636078572588, -0.42429503033819954, 0.003149584445514177, 0.022300909361556955, 0.012771491618906637, -0.04659285673283433, -0.2063997312007766, 0.09472611283050164, 0.054124573818224136, 0.053841137533125125, 0.05552936293870995, 0.17034605613076373, -0.1305173861009902, -0.24202551924084362, 0.30835572159604024, -0.08242403975148735, -0.24761772273892635, 0.1647939600540619, 0.07089508815153846, -0.15865285627936063, 0.12876071463290015, 0.2849118801912195, 0.17477369796711412, -0.16348065521987767, 0.05800548926069352, -0.04305940432179915, 0.17073441267405687, -0.01522455420345068, -0.10481925050875074, 0.1043894507015418, 0.30033600227172047, 0.16359746205179315, 0.1645974163578725, -0.09855584683337885, -0.20041950615674356, -0.2187068675454755, -0.11722011210727751, -0.1996228289055197, 0.002650066935702374, -0.13826427083725942, -0.17654954437166454, 0.3890362683879702, 0.24566813339234184, 0.17295060094543976, 0.17237648831582383, 0.3645392628092515, 0.05595240716111699, 0.06105063277247705, 0.11406227903636662, 0.2125250704292404, 0.06192989472888018, 0.09879548067202497, -0.19713762542110327, 0.04372086542119321, -0.007847164713434484]
1,802.0222
Epitaxial Growth of Single-Orientation High-Quality MoS$_2$ Monolayers
We present a study on the growth and characterization of high-quality single-layer MoS$_2$ with a single orientation, i.e. without the presence of mirror domains. This single orientation of the MoS$_2$ layer is established by means of x-ray photoelectron diffraction. The high quality is evidenced by combining scanning tunneling microscopy with x-ray photoelectron spectroscopy measurements. Spin- and angle-resolved photoemission experiments performed on the sample revealed complete spin-polarization of the valence band states near the K and -K points of the Brillouin zone. These findings open up the possibility to exploit the spin and valley degrees of freedom for encoding and processing information in devices that are based on epitaxially grown materials.
cond-mat.mtrl-sci
we present a study on the growth and characterization of highquality singlelayer mos_2 with a single orientation ie without the presence of mirror domains this single orientation of the mos_2 layer is established by means of xray photoelectron diffraction the high quality is evidenced by combining scanning tunneling microscopy with xray photoelectron spectroscopy measurements spin and angleresolved photoemission experiments performed on the sample revealed complete spinpolarization of the valence band states near the k and k points of the brillouin zone these findings open up the possibility to exploit the spin and valley degrees of freedom for encoding and processing information in devices that are based on epitaxially grown materials
[['we', 'present', 'a', 'study', 'on', 'the', 'growth', 'and', 'characterization', 'of', 'highquality', 'singlelayer', 'mos_2', 'with', 'a', 'single', 'orientation', 'ie', 'without', 'the', 'presence', 'of', 'mirror', 'domains', 'this', 'single', 'orientation', 'of', 'the', 'mos_2', 'layer', 'is', 'established', 'by', 'means', 'of', 'xray', 'photoelectron', 'diffraction', 'the', 'high', 'quality', 'is', 'evidenced', 'by', 'combining', 'scanning', 'tunneling', 'microscopy', 'with', 'xray', 'photoelectron', 'spectroscopy', 'measurements', 'spin', 'and', 'angleresolved', 'photoemission', 'experiments', 'performed', 'on', 'the', 'sample', 'revealed', 'complete', 'spinpolarization', 'of', 'the', 'valence', 'band', 'states', 'near', 'the', 'k', 'and', 'k', 'points', 'of', 'the', 'brillouin', 'zone', 'these', 'findings', 'open', 'up', 'the', 'possibility', 'to', 'exploit', 'the', 'spin', 'and', 'valley', 'degrees', 'of', 'freedom', 'for', 'encoding', 'and', 'processing', 'information', 'in', 'devices', 'that', 'are', 'based', 'on', 'epitaxially', 'grown', 'materials']]
[-0.146689707039993, 0.1383589786985381, -0.05219102842119438, -0.057338498773010955, -0.03546144386584109, -0.11313001070679589, 0.16296670556184836, 0.46369334204884416, -0.28336545521901413, -0.3449503352780911, 0.01937490233368325, -0.37486419180746783, -0.10418887638740919, 0.22388280311768705, 0.04253590626070614, 0.08033853063190526, 0.02599873301488432, -0.11365073457021604, -0.10602526978631928, -0.20819010245825417, 0.30366259697951714, 0.05634575310925191, 0.33812247932126577, 0.09690944419073111, 0.0864371906415644, 0.10016486659984697, 0.04602112968198278, 0.007745441857894713, -0.15678447342976473, 0.1362468632377303, 0.24496611871079288, -0.05970916530032727, 0.19403962594541638, -0.4693223819810638, -0.24384234878657893, -0.08194964937019077, 0.12226077576845207, 0.0899459791507318, -0.11444649656451392, -0.2847396238199012, 0.07548218024047938, -0.03904721102338623, -0.11055083545546619, -0.12079664781604978, -0.09039016170003875, -0.03594841897297143, -0.19459717638409613, 0.05857597616374154, -0.0013396472289142283, 0.13600912935693155, -0.09282736882570052, -0.06789529337971048, -0.11711116439493542, 0.06299564617643641, 0.0072246871253644875, 0.03449577236738564, 0.16713561770844865, -0.11486067350064828, -0.1845530972773717, 0.3235387555535205, -0.03013287931469015, -0.06785301490771499, 0.1344588545108722, -0.25094221061815253, -0.07269090268210593, 0.15254994348030199, 0.09875527415424586, 0.19481120328630575, -0.1206774649252607, 0.07087732927016491, -0.03510818833654577, 0.2283196372350424, 0.12709776926150715, 0.12901721212758938, 0.25287602945146237, 0.2020482233661989, 0.029305138464339756, 0.13894790251823988, -0.2171019121856344, 0.03945034421049058, -0.18005249621346592, -0.1744621675588529, -0.25006470144938, 0.09440921254625374, -0.04377112997608492, -0.14071167509748855, 0.4001663956960494, 0.06688373854108663, 0.1939334618308666, -0.058248996472155506, 0.2992924646220424, 0.0649037668724883, 0.08128179008649154, 0.0014793343672698195, 0.22605504127727313, 0.1626732413233681, 0.09324372945438054, -0.29234582831744443, 0.08003355564380234, -0.04634585830129006]
1,802.02221
Inequalities for integrals of the modified Struve function of the first kind
Simple inequalities for some integrals involving the modified Struve function of the first kind $\mathbf{L}_{\nu}(x)$ are established. In most cases, these inequalities have best possible constant. We also deduce a tight double inequality, involving the modified Struve function $\mathbf{L}_{\nu}(x)$, for a generalized hypergeometric function.
math.CA
simple inequalities for some integrals involving the modified struve function of the first kind mathbfl_nux are established in most cases these inequalities have best possible constant we also deduce a tight double inequality involving the modified struve function mathbfl_nux for a generalized hypergeometric function
[['simple', 'inequalities', 'for', 'some', 'integrals', 'involving', 'the', 'modified', 'struve', 'function', 'of', 'the', 'first', 'kind', 'mathbfl_nux', 'are', 'established', 'in', 'most', 'cases', 'these', 'inequalities', 'have', 'best', 'possible', 'constant', 'we', 'also', 'deduce', 'a', 'tight', 'double', 'inequality', 'involving', 'the', 'modified', 'struve', 'function', 'mathbfl_nux', 'for', 'a', 'generalized', 'hypergeometric', 'function']]
[-0.11433328736827454, 0.01772057927552272, -0.0699066876603121, 0.21750304983420807, -0.1365626649507745, -0.20682571493935856, 0.024019693236120722, 0.27094182617623697, -0.2719555269868579, -0.2509307384660298, 0.07310708946368488, -0.25541792380284856, -0.2305220073004338, 0.3243136245080016, -0.024240142073143612, 0.11187983644247818, -0.004467287122017958, 0.017681568416512826, -0.14106216216697992, -0.30221835523843765, 0.34326396767177025, -0.03698590712420727, 0.1290151180318472, 0.07256890925584064, 0.08312191873450171, 0.03806522895518521, -0.00527003746141087, -0.06939712226287818, -0.25075308881192043, 0.08260777012699029, 0.19489075037100437, 0.1323889014522799, 0.28054892077026045, -0.36657644622027874, -0.14738468220457435, 0.11849387853660366, 0.09614892865912142, -0.025336926633661442, -0.051834815206265455, -0.22384104259650817, -0.05466698772877201, -0.16440195763822307, -0.2350972160188989, -0.0972189954482019, -0.01803181152155792, 0.17473807067356326, -0.313396984287961, 0.15875125161454146, 0.003484182610091838, -0.03312096433100206, -0.04581182693999091, -0.22732614116235214, 0.10131551413161849, 0.04485843996305696, 0.0023449497212740507, 0.009109203026375988, 0.03274552838411182, -0.0585749234623191, -0.10043491414663466, 0.27472281394611026, -0.08172056264381601, -0.2755546965583397, 0.056415631118315185, -0.1721996301361783, -0.27740064028396527, 0.0035463488364422865, 0.08622226023792544, 0.20177971156822008, -0.1997071999040517, 0.0728638339152729, -0.09156723553314805, 0.05301968708888374, 0.2106667552672496, 0.05666217135942795, 0.06073125959797339, -0.011612775820222769, 0.039354722219286487, 0.21974621186117557, 1.1267902498895472e-05, -0.11675495593094225, -0.40110565247860824, -0.23244093866510826, -0.210132214080328, 0.051861001453785735, -0.1858589635442265, -0.18419314313425936, 0.3425333147699183, -0.06028771921145645, 0.09371501448648897, 0.1273886896034872, 0.1774703155864369, 0.2503611837429079, 0.11361519793916325, -0.022138573017648676, 0.2680058438596792, 0.18731888912258332, 0.09619663010182028, -0.11138133370232853, 0.0791684296511283, 0.21068533207289875]
1,802.02222
Fragile aspects of topological transition in lossy and parity-time symmetric quantum walks
Quantum walks often provide telling insights about the structure of the system on which they are performed. In PT-symmetric and lossy dimer lattices, the topological properties of the band structure manifest themselves in the quantization of the mean displacement of such a walker. We investigate the fragile aspects of a topological transition in these two dimer models. We find that the transition is sensitive to the initial state of the walker on the Bloch sphere, and the resultant mean displacement has a robust topological component and a quasiclassical component. In PT symmetric dimer lattices, we also show that the transition is smeared by nonlinear effects that become important in the PT-symmetry broken region. By carrying out consistency checks via analytical calculations, tight-binding results, and beam-propagation-method simulations, we show that our predictions are easily testable in today's experimental systems.
quant-ph cond-mat.other physics.optics
quantum walks often provide telling insights about the structure of the system on which they are performed in ptsymmetric and lossy dimer lattices the topological properties of the band structure manifest themselves in the quantization of the mean displacement of such a walker we investigate the fragile aspects of a topological transition in these two dimer models we find that the transition is sensitive to the initial state of the walker on the bloch sphere and the resultant mean displacement has a robust topological component and a quasiclassical component in pt symmetric dimer lattices we also show that the transition is smeared by nonlinear effects that become important in the ptsymmetry broken region by carrying out consistency checks via analytical calculations tightbinding results and beampropagationmethod simulations we show that our predictions are easily testable in todays experimental systems
[['quantum', 'walks', 'often', 'provide', 'telling', 'insights', 'about', 'the', 'structure', 'of', 'the', 'system', 'on', 'which', 'they', 'are', 'performed', 'in', 'ptsymmetric', 'and', 'lossy', 'dimer', 'lattices', 'the', 'topological', 'properties', 'of', 'the', 'band', 'structure', 'manifest', 'themselves', 'in', 'the', 'quantization', 'of', 'the', 'mean', 'displacement', 'of', 'such', 'a', 'walker', 'we', 'investigate', 'the', 'fragile', 'aspects', 'of', 'a', 'topological', 'transition', 'in', 'these', 'two', 'dimer', 'models', 'we', 'find', 'that', 'the', 'transition', 'is', 'sensitive', 'to', 'the', 'initial', 'state', 'of', 'the', 'walker', 'on', 'the', 'bloch', 'sphere', 'and', 'the', 'resultant', 'mean', 'displacement', 'has', 'a', 'robust', 'topological', 'component', 'and', 'a', 'quasiclassical', 'component', 'in', 'pt', 'symmetric', 'dimer', 'lattices', 'we', 'also', 'show', 'that', 'the', 'transition', 'is', 'smeared', 'by', 'nonlinear', 'effects', 'that', 'become', 'important', 'in', 'the', 'ptsymmetry', 'broken', 'region', 'by', 'carrying', 'out', 'consistency', 'checks', 'via', 'analytical', 'calculations', 'tightbinding', 'results', 'and', 'beampropagationmethod', 'simulations', 'we', 'show', 'that', 'our', 'predictions', 'are', 'easily', 'testable', 'in', 'todays', 'experimental', 'systems']]
[-0.15153478783806854, 0.1639263564448831, -0.1068416931870373, 0.07790830011146456, -0.032317059073787534, -0.14459517778978295, 0.0344779850731529, 0.4184025138562178, -0.2309766343529642, -0.23170430017431287, 0.10292219717130337, -0.27969374569527206, -0.20308833478535288, 0.1307710200517581, 0.02627472313487202, 0.05731877400437846, 0.04370837204538993, 0.01802598008988799, -0.09461562512323506, -0.21800052695125885, 0.2942402126372921, 0.03474353716358624, 0.29988234327004776, 0.06076507024079507, 0.03422418291286232, 0.0010258186817590665, 0.04830270509718217, 0.03576425330570634, -0.15180040936153144, 0.09023821393340609, 0.20051797992077908, 0.01334685168099882, 0.19311759003308893, -0.4582658538282135, -0.2347760856126938, 0.03475949172114097, 0.13316165362178845, 0.14819415690237997, -0.04436677767908758, -0.3338486155916522, 0.05979468007605985, -0.13464256425993176, -0.12522773758719002, -0.1137401752206191, 0.002103826452563279, -0.004161621579886788, -0.227311898113813, 0.0740896055734475, 0.08188140037279222, 0.056383304618650376, -0.032546790289509034, -0.07402017541539033, -0.0734752112061438, 0.11090495914006673, -0.0038686089700319037, -0.02408204311301021, 0.12800406616004387, -0.14096897661713134, -0.12624529678456103, 0.406003912108658, -0.03453261587245349, -0.19145962832509167, 0.1745477012565944, -0.15708870471992198, -0.1228465579558898, 0.11510390745829382, 0.132366874520361, 0.07400371554396014, -0.08078575065702771, 0.06945971672654315, -0.04537376144520231, 0.16889433947096097, 0.007549272313115806, 0.06204118049723932, 0.2554301213282738, 0.13353755404615272, 0.04396856120293858, 0.1648748211756376, -0.06357508953184868, -0.18248851016762047, -0.3079256859257899, -0.13980705799181423, -0.21403376033434468, 0.06702972263315299, -0.08303643039378412, -0.18709948518904893, 0.41330091010806336, 0.1557407606066796, 0.2047704688620067, 0.009211351842633074, 0.23529000907633318, 0.11344117799138202, 0.047217787475406746, 0.046505897122360494, 0.2752259898910394, 0.14245022291633688, 0.059643604928614015, -0.24115765480202261, 0.025834617584801014, 0.03288571197322033]
1,802.02223
Seeded Ising Model and Statistical Natures of Human Iris Templates
We propose a variant of Ising model, called the Seeded Ising Model, to model probabilistic nature of human iris templates. This model is an Ising model in which the values at certain lattice points are held fixed throughout Ising model evolution. Using this we show how to reconstruct the full iris template from partial information, and we show that about 1/6 of the given template is needed to recover almost all information content of the original one in the sense that the resulting Hamming distance is well within the range to assert correctly the identity of the subject. This leads us to propose the concept of effective statistical degree of freedom of iris templates and show it is about 1/6 of the total number of bits. In particular, for a template of $2048$ bits, its effective statistical degree of freedom is about $342$ bits, which coincides very well with the degree of freedom computed by the completely different method proposed by Daugman.
stat.AP cs.CV cs.HC physics.data-an q-bio.OT
we propose a variant of ising model called the seeded ising model to model probabilistic nature of human iris templates this model is an ising model in which the values at certain lattice points are held fixed throughout ising model evolution using this we show how to reconstruct the full iris template from partial information and we show that about 16 of the given template is needed to recover almost all information content of the original one in the sense that the resulting hamming distance is well within the range to assert correctly the identity of the subject this leads us to propose the concept of effective statistical degree of freedom of iris templates and show it is about 16 of the total number of bits in particular for a template of 2048 bits its effective statistical degree of freedom is about 342 bits which coincides very well with the degree of freedom computed by the completely different method proposed by daugman
[['we', 'propose', 'a', 'variant', 'of', 'ising', 'model', 'called', 'the', 'seeded', 'ising', 'model', 'to', 'model', 'probabilistic', 'nature', 'of', 'human', 'iris', 'templates', 'this', 'model', 'is', 'an', 'ising', 'model', 'in', 'which', 'the', 'values', 'at', 'certain', 'lattice', 'points', 'are', 'held', 'fixed', 'throughout', 'ising', 'model', 'evolution', 'using', 'this', 'we', 'show', 'how', 'to', 'reconstruct', 'the', 'full', 'iris', 'template', 'from', 'partial', 'information', 'and', 'we', 'show', 'that', 'about', '16', 'of', 'the', 'given', 'template', 'is', 'needed', 'to', 'recover', 'almost', 'all', 'information', 'content', 'of', 'the', 'original', 'one', 'in', 'the', 'sense', 'that', 'the', 'resulting', 'hamming', 'distance', 'is', 'well', 'within', 'the', 'range', 'to', 'assert', 'correctly', 'the', 'identity', 'of', 'the', 'subject', 'this', 'leads', 'us', 'to', 'propose', 'the', 'concept', 'of', 'effective', 'statistical', 'degree', 'of', 'freedom', 'of', 'iris', 'templates', 'and', 'show', 'it', 'is', 'about', '16', 'of', 'the', 'total', 'number', 'of', 'bits', 'in', 'particular', 'for', 'a', 'template', 'of', '2048', 'bits', 'its', 'effective', 'statistical', 'degree', 'of', 'freedom', 'is', 'about', '342', 'bits', 'which', 'coincides', 'very', 'well', 'with', 'the', 'degree', 'of', 'freedom', 'computed', 'by', 'the', 'completely', 'different', 'method', 'proposed', 'by', 'daugman']]
[-0.07964320021486025, 0.07971269910787535, -0.06440635365261524, 0.04265622564492299, -0.03584062867297756, -0.14539020660011398, 0.04621861733274856, 0.3459244677279558, -0.28061659820665275, -0.37372897644699726, 0.07570613983710998, -0.2725778145451145, -0.14221586166294636, 0.1254284185282656, -0.06668072874675056, 0.046674474552550416, 0.020095233701997332, 0.07982343159986797, -0.03658449793245965, -0.267196913048579, 0.2777851726773574, 0.07805428007778561, 0.26032248518377954, 0.013830706228525091, 0.13664900427281765, 0.035727921376050804, -0.004541972761306866, -0.011736429348174069, -0.12591232633677005, 0.1417123189204614, 0.2063861355562062, 0.15959810970902996, 0.22753129733933342, -0.3607040554842693, -0.2132393513866528, 0.0814473614639913, 0.1115322313106182, 0.1423031843747415, 0.022537220045234316, -0.23510807169023556, 0.12364756463693431, -0.15266944506062974, -0.12852781931409774, -0.036830028956669765, -0.01305740956435509, -0.007855071962155678, -0.27478907749999637, 0.05932928011774224, 0.07520009867737737, 0.07603042645316663, -0.028018386882908045, -0.09609734933581893, -0.04348529993131021, 0.1590051917232757, 0.007560050433334883, 0.06479725111304656, 0.08031611435437276, -0.12196200253531038, -0.10546548149252402, 0.37853598855090914, -0.03455709592715182, -0.18909383938866264, 0.15438943294187388, -0.1318299151111946, -0.1049753644929072, 0.11423588963800374, 0.1511887441918162, 0.1166526996128169, -0.1521337164377644, 0.07643006140305833, -0.055104867468967485, 0.25286091857354076, 0.024636230102372297, 0.04300736361700627, 0.20275600049874665, 0.12583010131026112, 0.02794265710564767, 0.20226953365483585, -0.10738316844907347, -0.1287858257282893, -0.29331376357004046, -0.12858118224072695, -0.21104149711763853, 0.036482300965782304, -0.13713015836769898, -0.15823320655819076, 0.4384021328785169, 0.22006209074436214, 0.22121137005250388, 0.06039094234052126, 0.25629198568424694, 0.05923659584260787, 0.08243638918451954, 0.08632706788678964, 0.19954186318805844, 0.10816509939764661, 0.05431364439097291, -0.1779339385483368, 0.05974823791522211, 0.07398752074395479]
1,802.02224
Magnetic oscillations Excited by Concurrent Spin Injection from a Tunneling Current and a Spin Hall Current
In this paper, a 3-terminal spin-transfer torque nano-oscillator (STNO) is studied using the concurrent spin injection of a spin-polarized tunneling current and a spin Hall current exciting the free layer into dynamic regimes beyond what is achieved by each individual mechanism. The pure spin injection is capable of inducing oscillations in the absence of charge currents effectively reducing the critical tunneling current to zero. This reduction of the critical charge currents can improve the endurance of both STNOs and non-volatile magnetic memories (MRAM) devices. It is shown that the system response can be described in terms of an injected spin current density $J_s$ which results from the contribution of both spin injection mechanisms, with the tunneling current polarization $p$ and the spin Hall angle $\theta$ acting as key parameters determining the efficiency of each injection mechanism. The experimental data exhibits an excellent agreement with this model which can be used to quantitatively predict the critical points ($J_s = -2.26\pm 0.09 \times 10^9 \hbar/e$ A/m$^2$) and the oscillation amplitude as a function of the input currents. In addition, the fitting of the data also allows an independent confirmation of the values estimated for the spin Hall angle and tunneling current polarization as well as the extraction of the damping $\alpha = 0.01$ and non-linear damping $Q = 3.8\pm 0.3$ parameters.
cond-mat.mes-hall
in this paper a 3terminal spintransfer torque nanooscillator stno is studied using the concurrent spin injection of a spinpolarized tunneling current and a spin hall current exciting the free layer into dynamic regimes beyond what is achieved by each individual mechanism the pure spin injection is capable of inducing oscillations in the absence of charge currents effectively reducing the critical tunneling current to zero this reduction of the critical charge currents can improve the endurance of both stnos and nonvolatile magnetic memories mram devices it is shown that the system response can be described in terms of an injected spin current density j_s which results from the contribution of both spin injection mechanisms with the tunneling current polarization p and the spin hall angle theta acting as key parameters determining the efficiency of each injection mechanism the experimental data exhibits an excellent agreement with this model which can be used to quantitatively predict the critical points j_s 226pm 009 times 109 hbare am2 and the oscillation amplitude as a function of the input currents in addition the fitting of the data also allows an independent confirmation of the values estimated for the spin hall angle and tunneling current polarization as well as the extraction of the damping alpha 001 and nonlinear damping q 38pm 03 parameters
[['in', 'this', 'paper', 'a', '3terminal', 'spintransfer', 'torque', 'nanooscillator', 'stno', 'is', 'studied', 'using', 'the', 'concurrent', 'spin', 'injection', 'of', 'a', 'spinpolarized', 'tunneling', 'current', 'and', 'a', 'spin', 'hall', 'current', 'exciting', 'the', 'free', 'layer', 'into', 'dynamic', 'regimes', 'beyond', 'what', 'is', 'achieved', 'by', 'each', 'individual', 'mechanism', 'the', 'pure', 'spin', 'injection', 'is', 'capable', 'of', 'inducing', 'oscillations', 'in', 'the', 'absence', 'of', 'charge', 'currents', 'effectively', 'reducing', 'the', 'critical', 'tunneling', 'current', 'to', 'zero', 'this', 'reduction', 'of', 'the', 'critical', 'charge', 'currents', 'can', 'improve', 'the', 'endurance', 'of', 'both', 'stnos', 'and', 'nonvolatile', 'magnetic', 'memories', 'mram', 'devices', 'it', 'is', 'shown', 'that', 'the', 'system', 'response', 'can', 'be', 'described', 'in', 'terms', 'of', 'an', 'injected', 'spin', 'current', 'density', 'j_s', 'which', 'results', 'from', 'the', 'contribution', 'of', 'both', 'spin', 'injection', 'mechanisms', 'with', 'the', 'tunneling', 'current', 'polarization', 'p', 'and', 'the', 'spin', 'hall', 'angle', 'theta', 'acting', 'as', 'key', 'parameters', 'determining', 'the', 'efficiency', 'of', 'each', 'injection', 'mechanism', 'the', 'experimental', 'data', 'exhibits', 'an', 'excellent', 'agreement', 'with', 'this', 'model', 'which', 'can', 'be', 'used', 'to', 'quantitatively', 'predict', 'the', 'critical', 'points', 'j_s', '226pm', '009', 'times', '109', 'hbare', 'am2', 'and', 'the', 'oscillation', 'amplitude', 'as', 'a', 'function', 'of', 'the', 'input', 'currents', 'in', 'addition', 'the', 'fitting', 'of', 'the', 'data', 'also', 'allows', 'an', 'independent', 'confirmation', 'of', 'the', 'values', 'estimated', 'for', 'the', 'spin', 'hall', 'angle', 'and', 'tunneling', 'current', 'polarization', 'as', 'well', 'as', 'the', 'extraction', 'of', 'the', 'damping', 'alpha', '001', 'and', 'nonlinear', 'damping', 'q', '38pm', '03', 'parameters']]
[-0.19281635243001632, 0.20431851306029997, -0.0057861552519593825, 0.007151483065925192, -0.02350354335855606, -0.13529245523346026, 0.05384376906237543, 0.30865971746659554, -0.29007080778219674, -0.3237641001943239, 0.04965896909287589, -0.2637420232549207, -0.08755203518843235, 0.2441967312766369, 0.018214195987296313, 0.03538094801174444, -0.031810653922679365, -0.014362065807028219, -0.05709168253531463, -0.17156970895242032, 0.23995925703973964, 0.06659321633795666, 0.334553405131365, 0.07226254738823966, 0.10728140125852512, 0.024529524462644097, 0.0580585123039782, 0.012044140393304271, -0.1337093074575573, 0.03269122771074086, 0.22224714070623525, -0.030804794529475932, 0.16606797924005362, -0.44282626587637636, -0.18486824919724143, 0.031884656014830565, 0.14288705395707904, 0.1397259105576289, -0.043630755630993216, -0.24599548615948405, 0.04486218148701673, -0.20304074984606962, -0.10824261144186684, -0.08129565973527902, 0.03744640765105223, 0.009158419178755477, -0.3072842314059651, 0.09959874838512109, 0.0831287114702295, 0.020735477825063606, -0.07195823538492076, -0.13462425953556978, -0.08242584307634726, 0.11094825926431737, 0.05134630029246774, 0.10089713531914492, 0.21228695381432772, -0.16513923198352892, -0.17305816651733463, 0.2961470341244929, -0.08426891663111746, -0.17842108364471473, 0.11099624645593034, -0.19188709846416185, -0.012656781052477485, 0.10967084207507068, 0.10028381724841892, 0.0826564485783862, -0.14047487623296503, 0.04242924227285182, 0.019563036407127456, 0.16190248340758126, 0.037902770855269115, 0.0487170522531351, 0.2844224458213809, 0.19797782061491595, 0.04682736245178899, 0.0998674810024758, -0.1630197300326599, -0.025169002041112373, -0.259196502637378, -0.13405494503819027, -0.18595627414950625, 0.12175400877414748, -0.08723361042699083, -0.11981963943730671, 0.4423499520781428, 0.20256865459905807, 0.19994500349600647, -0.021052305065745184, 0.3557478832297547, 0.1817878008841775, 0.07962061832550653, 0.040297164848117635, 0.247600517841056, 0.17067674043220143, 0.12910076265418252, -0.3223498668012664, 0.11153420187359632, -0.04020822281126193]
1,802.02225
Stratifications of affine Deligne-Lusztig varieties
Affine Deligne-Lusztig varieties are analogues of Deligne-Lusztig varieties in the context of affine flag varieties and affine Grassmannians. They are closely related to moduli spaces of $p$-divisible groups in positive characteristic, and thus to arithmetic properties of Shimura varieties. We compare stratifications of affine Deligne-Lusztig varieties attached to a basic element $b$. In particular, we show that the stratification defined by Chen and Viehmann using the relative position to elements of the group $J_b$, the $\sigma$-centralizer of $b$, coincides with the Bruhat-Tits stratification in all cases of Coxeter type, as defined by X. He and the author.
math.AG math.GR
affine delignelusztig varieties are analogues of delignelusztig varieties in the context of affine flag varieties and affine grassmannians they are closely related to moduli spaces of pdivisible groups in positive characteristic and thus to arithmetic properties of shimura varieties we compare stratifications of affine delignelusztig varieties attached to a basic element b in particular we show that the stratification defined by chen and viehmann using the relative position to elements of the group j_b the sigmacentralizer of b coincides with the bruhattits stratification in all cases of coxeter type as defined by x he and the author
[['affine', 'delignelusztig', 'varieties', 'are', 'analogues', 'of', 'delignelusztig', 'varieties', 'in', 'the', 'context', 'of', 'affine', 'flag', 'varieties', 'and', 'affine', 'grassmannians', 'they', 'are', 'closely', 'related', 'to', 'moduli', 'spaces', 'of', 'pdivisible', 'groups', 'in', 'positive', 'characteristic', 'and', 'thus', 'to', 'arithmetic', 'properties', 'of', 'shimura', 'varieties', 'we', 'compare', 'stratifications', 'of', 'affine', 'delignelusztig', 'varieties', 'attached', 'to', 'a', 'basic', 'element', 'b', 'in', 'particular', 'we', 'show', 'that', 'the', 'stratification', 'defined', 'by', 'chen', 'and', 'viehmann', 'using', 'the', 'relative', 'position', 'to', 'elements', 'of', 'the', 'group', 'j_b', 'the', 'sigmacentralizer', 'of', 'b', 'coincides', 'with', 'the', 'bruhattits', 'stratification', 'in', 'all', 'cases', 'of', 'coxeter', 'type', 'as', 'defined', 'by', 'x', 'he', 'and', 'the', 'author']]
[-0.17050743980386565, 0.05258723047639554, -0.07989988422787064, 0.056559522961227536, -0.09690144068736117, -0.12872259348417478, -0.013449980217653016, 0.3123561694131543, -0.3839739063453938, -0.16715396716608666, 0.0848407711503872, -0.21438160282559693, -0.15858086746205421, 0.22365115230786614, -0.27782561564041924, -0.0430676426331047, -0.02288719585825068, 0.05941915714841647, -0.11520848055927975, -0.40122577535415377, 0.5010684217559174, -0.04526211180685399, 0.2502194822494251, -0.015060890989843756, 0.08515263740749408, -0.007104487228692354, -0.03636846249961915, -0.009410374435162794, -0.11301246956562257, 0.17377523153603155, 0.3907663546342519, 0.05392124345235061, 0.13132404434145428, -0.3492590857349569, -0.11988206519163214, 0.2105682946955009, 0.11865861226882164, -0.0036969452039556927, 0.04860565814306028, -0.2634370482022253, 0.050207530099820964, -0.15018540285382187, -0.2123077270031596, -0.03410975791242284, 0.0920646344020497, 0.12586030886935382, -0.19201590616527633, -0.03305900932173245, 0.0750626631953158, 0.22778457657356435, -0.09729265475956102, -0.16343851584436683, -0.11924979217777339, 0.06909350448889502, -0.030546473106369376, 0.02755011784392991, 0.12520173885665523, -0.08634489411876227, -0.1323204233776778, 0.4158329126657918, -0.0644185365284405, -0.2009669195394963, 0.14114984432186853, -0.20582139212153075, -0.15960082466093203, 0.11686249107879121, 0.10639124244335108, 0.12774886322949897, 0.07605737026703234, 0.17748580596283622, -0.1270521064992257, -0.05709685144635538, 0.12694153568008915, -0.03788882261627199, 0.11834742097804944, 0.02192589791714757, -0.004976182483612017, 0.09120149561204016, 0.006793719929798196, -0.020614806823990268, -0.36699420353397727, -0.23638540273047207, -0.005615974321699468, 0.1303955637170778, -0.10226510627338332, -0.17063560345801912, 0.35937997539682937, 0.047850249238157026, 0.19303384719144864, 0.11157717082339029, 0.1632309623528272, -0.02087307812689687, 0.043766141089387624, 0.01914751982743231, 0.10919493097268666, 0.3531976267646921, -0.09016601057373919, -0.16663680922647472, 0.013145886701143658, 0.2678426433558343]
1,802.02226
Generative Adversarial Networks using Adaptive Convolution
Most existing GANs architectures that generate images use transposed convolution or resize-convolution as their upsampling algorithm from lower to higher resolution feature maps in the generator. We argue that this kind of fixed operation is problematic for GANs to model objects that have very different visual appearances. We propose a novel adaptive convolution method that learns the upsampling algorithm based on the local context at each location to address this problem. We modify a baseline GANs architecture by replacing normal convolutions with adaptive convolutions in the generator. Experiments on CIFAR-10 dataset show that our modified models improve the baseline model by a large margin. Furthermore, our models achieve state-of-the-art performance on CIFAR-10 and STL-10 datasets in the unsupervised setting.
cs.CV stat.ML
most existing gans architectures that generate images use transposed convolution or resizeconvolution as their upsampling algorithm from lower to higher resolution feature maps in the generator we argue that this kind of fixed operation is problematic for gans to model objects that have very different visual appearances we propose a novel adaptive convolution method that learns the upsampling algorithm based on the local context at each location to address this problem we modify a baseline gans architecture by replacing normal convolutions with adaptive convolutions in the generator experiments on cifar10 dataset show that our modified models improve the baseline model by a large margin furthermore our models achieve stateoftheart performance on cifar10 and stl10 datasets in the unsupervised setting
[['most', 'existing', 'gans', 'architectures', 'that', 'generate', 'images', 'use', 'transposed', 'convolution', 'or', 'resizeconvolution', 'as', 'their', 'upsampling', 'algorithm', 'from', 'lower', 'to', 'higher', 'resolution', 'feature', 'maps', 'in', 'the', 'generator', 'we', 'argue', 'that', 'this', 'kind', 'of', 'fixed', 'operation', 'is', 'problematic', 'for', 'gans', 'to', 'model', 'objects', 'that', 'have', 'very', 'different', 'visual', 'appearances', 'we', 'propose', 'a', 'novel', 'adaptive', 'convolution', 'method', 'that', 'learns', 'the', 'upsampling', 'algorithm', 'based', 'on', 'the', 'local', 'context', 'at', 'each', 'location', 'to', 'address', 'this', 'problem', 'we', 'modify', 'a', 'baseline', 'gans', 'architecture', 'by', 'replacing', 'normal', 'convolutions', 'with', 'adaptive', 'convolutions', 'in', 'the', 'generator', 'experiments', 'on', 'cifar10', 'dataset', 'show', 'that', 'our', 'modified', 'models', 'improve', 'the', 'baseline', 'model', 'by', 'a', 'large', 'margin', 'furthermore', 'our', 'models', 'achieve', 'stateoftheart', 'performance', 'on', 'cifar10', 'and', 'stl10', 'datasets', 'in', 'the', 'unsupervised', 'setting']]
[0.013825157921666564, -0.02091059681438541, -0.08592671306282913, 0.09125656282856777, -0.08595536129699105, -0.18139434981917552, 0.0009512168047476118, 0.49753194392295713, -0.2739520361222785, -0.3169928522685827, 0.07057350815246198, -0.24899596466793347, -0.21942837710957974, 0.19735016743455208, -0.18126364793407462, 0.07010334729852344, 0.18799270372206378, 0.003014435664103445, -0.12009222261505044, -0.3010819720595649, 0.32233175615409104, 0.07298195258698474, 0.3688460022637273, -0.03537724464263577, 0.1733652813107533, -0.08228464758465603, -0.007035532321039019, -0.031080286381608348, -0.025584417538901384, 0.17789631736784448, 0.25020859398667245, 0.169256288072852, 0.31121261893392743, -0.41203642038281185, -0.22977408851196957, 0.08057675557704326, 0.09843203100233765, 0.08246432704235905, -0.05184462503628742, -0.33743592397451905, 0.12737237965792686, -0.1950531537502499, 0.0402732267581179, -0.16505283781848215, -0.06958515286520597, 0.0005518481627667038, -0.3311165550021234, 0.047898490040097386, 0.10274320784872358, 0.02626093972663758, -0.045389447193513864, -0.12236418886015475, 0.04859779470489692, 0.12436056889443642, -0.028556679229457246, 0.06118407617796654, 0.1155992060575646, -0.20101079190597806, -0.16386663156040646, 0.3069208464979873, -0.11579637902678322, -0.23502507523862423, 0.18961643632225125, -0.04211817097739648, -0.17008069944094426, 0.07492593839227901, 0.2561849817649414, 0.16261186467688846, -0.10092019382864237, 0.014418667542917844, -0.083130585005057, 0.17632620964274284, 0.08002715505525407, 0.001735686273235133, 0.13384235941980555, 0.2610301641289587, 0.05305583566087851, 0.16027720230710457, -0.17570302039345378, -0.0352081179192637, -0.2166622271129893, -0.05180178836019615, -0.20640146254040934, -0.03868892076188477, -0.13145381330413314, -0.1272384738312813, 0.4034000114474635, 0.30642669464429934, 0.2494898595199999, 0.1592863186152052, 0.3679907035114149, 0.01729089167793834, 0.1760895243999785, 0.08898181233444583, 0.15523880134904916, -0.022787538029537615, 0.10547025741267381, -0.16429481197294574, 0.06720282112532375, 0.11756686541109772]
1,802.02227
On Decision Support for Remote Industrial Facilities using the Collaborative Engineering Framework
Means to support collaboration for remote industrial facilities such as mining are an important topic, especially in Australia, where major mining sites can be more than a thousand kilometers from population centres. Software-based collaboration and maintenance solutions can help to reduce costs associated with these remote facilities. In this paper, we report on our collaborative engineering project providing a decision support solution tailored for Australian needs. We present two application examples: one related to incident handling in industrial automation, the other one in the area of smart energy systems.
cs.SE
means to support collaboration for remote industrial facilities such as mining are an important topic especially in australia where major mining sites can be more than a thousand kilometers from population centres softwarebased collaboration and maintenance solutions can help to reduce costs associated with these remote facilities in this paper we report on our collaborative engineering project providing a decision support solution tailored for australian needs we present two application examples one related to incident handling in industrial automation the other one in the area of smart energy systems
[['means', 'to', 'support', 'collaboration', 'for', 'remote', 'industrial', 'facilities', 'such', 'as', 'mining', 'are', 'an', 'important', 'topic', 'especially', 'in', 'australia', 'where', 'major', 'mining', 'sites', 'can', 'be', 'more', 'than', 'a', 'thousand', 'kilometers', 'from', 'population', 'centres', 'softwarebased', 'collaboration', 'and', 'maintenance', 'solutions', 'can', 'help', 'to', 'reduce', 'costs', 'associated', 'with', 'these', 'remote', 'facilities', 'in', 'this', 'paper', 'we', 'report', 'on', 'our', 'collaborative', 'engineering', 'project', 'providing', 'a', 'decision', 'support', 'solution', 'tailored', 'for', 'australian', 'needs', 'we', 'present', 'two', 'application', 'examples', 'one', 'related', 'to', 'incident', 'handling', 'in', 'industrial', 'automation', 'the', 'other', 'one', 'in', 'the', 'area', 'of', 'smart', 'energy', 'systems']]
[-0.10012880830765242, 0.08789068706359143, -0.004110583360568526, 0.04674531113267405, -0.13838383793736692, -0.12304904546295659, 0.050282466726304355, 0.4213627025987325, -0.2203522515535522, -0.3595148647633078, 0.20285452228939432, -0.33481997653339685, -0.11336815355180795, 0.2690988185925388, -0.09213742302479537, 0.05995805061349038, 0.10780825655321392, -0.007885896961801173, 0.04383463442869735, -0.24569274064446434, 0.2828132316281789, 0.09402317718048109, 0.3183435746939497, 0.07457343289063553, 0.013223695788490638, 0.004236973039910532, -0.08365909514027868, -0.02352417280290569, -0.028571071260179697, 0.19626459518164327, 0.433148145178605, 0.20203745524723377, 0.3627983490842279, -0.47555534292556595, -0.17698320531903694, 0.11309602119426211, 0.14775778410244692, 0.05401601934847369, -0.11911172894816557, -0.28539946985828657, 0.052925961123507344, -0.26400350533907163, -0.1932106496288122, -0.06627998538603064, -0.0210078960295055, 0.028755884983817512, -0.23127085371780093, -0.03354116707119379, -0.07687257391432029, 0.10223736948846432, -0.06145808652692129, -0.14129032838168773, 0.049581512725085354, 0.19399733430172286, 0.02602142704587974, 0.037931784309886314, 0.15891135722304578, -0.12830945012013145, -0.17177742537048257, 0.3908420761816957, 0.03749033075340715, -0.12932732368536878, 0.23342200758045517, -0.07494888992802229, -0.21053398683081181, 0.039327284919616005, 0.26820540222538153, 0.08308866374414373, -0.19377224266612797, -0.004046292322180286, 0.04451088136417812, 0.17671204062722876, 0.07916404811790988, -0.007316654506191778, 0.2480269698556931, 0.2562189380104622, 0.1617083322901666, 0.153172848201383, -0.05077396541260957, -0.10357446736248022, -0.2203146172713572, -0.16408238393578972, -0.1260793155289433, 0.026165284697761696, -0.04657428299212237, -0.08907005097717047, 0.3592970643945959, 0.18993528261309844, 0.09556279890827855, -0.05085847847650267, 0.3255021075372783, 0.0241490536568205, 0.14299460679549053, 0.07453906271878756, 0.16052070077969116, -0.011448614806815815, 0.18748778914718817, -0.12631294069278023, 0.08992789666367214, -0.021477968766866775]
1,802.02228
Growing low-dimensional supramolecular crystals directly from 3D particles
We show that one-dimensional (1D) nanostructures and two-dimensional (2D) supramolecular crystals of organic semiconductors can be grown on substrates under ambient conditions directly from three-dimensional (3D) organic crystals. The approach does not require dissolving, melting or evaporating of the source crystals and is based on the Organic Solid-Solid Wetting Deposition (OSWD). We exemplify our approach by the pigment quinacridone (QAC). Scanning Tunnelling Microscopy (STM) investigations show that the structures of the resulting 2D crystals are similar to the chain arrangement of the alpha and beta QAC polymorphs and are independent of the 3D source crystal polymorph (gamma). Furthermore, distinct 1D chains can be produced systematically.
cond-mat.mtrl-sci physics.atm-clus
we show that onedimensional 1d nanostructures and twodimensional 2d supramolecular crystals of organic semiconductors can be grown on substrates under ambient conditions directly from threedimensional 3d organic crystals the approach does not require dissolving melting or evaporating of the source crystals and is based on the organic solidsolid wetting deposition oswd we exemplify our approach by the pigment quinacridone qac scanning tunnelling microscopy stm investigations show that the structures of the resulting 2d crystals are similar to the chain arrangement of the alpha and beta qac polymorphs and are independent of the 3d source crystal polymorph gamma furthermore distinct 1d chains can be produced systematically
[['we', 'show', 'that', 'onedimensional', '1d', 'nanostructures', 'and', 'twodimensional', '2d', 'supramolecular', 'crystals', 'of', 'organic', 'semiconductors', 'can', 'be', 'grown', 'on', 'substrates', 'under', 'ambient', 'conditions', 'directly', 'from', 'threedimensional', '3d', 'organic', 'crystals', 'the', 'approach', 'does', 'not', 'require', 'dissolving', 'melting', 'or', 'evaporating', 'of', 'the', 'source', 'crystals', 'and', 'is', 'based', 'on', 'the', 'organic', 'solidsolid', 'wetting', 'deposition', 'oswd', 'we', 'exemplify', 'our', 'approach', 'by', 'the', 'pigment', 'quinacridone', 'qac', 'scanning', 'tunnelling', 'microscopy', 'stm', 'investigations', 'show', 'that', 'the', 'structures', 'of', 'the', 'resulting', '2d', 'crystals', 'are', 'similar', 'to', 'the', 'chain', 'arrangement', 'of', 'the', 'alpha', 'and', 'beta', 'qac', 'polymorphs', 'and', 'are', 'independent', 'of', 'the', '3d', 'source', 'crystal', 'polymorph', 'gamma', 'furthermore', 'distinct', '1d', 'chains', 'can', 'be', 'produced', 'systematically']]
[-0.06918538368504065, 0.2050218215534607, -0.07269101113063069, -0.03610177470993502, -0.014832208821854483, -0.1908995521013052, 0.0378995060762883, 0.4833539638247413, -0.2611880006555181, -0.26821668761280865, 0.0332784952255539, -0.3023161953136038, -0.1631688681731108, 0.22001278933916743, 0.03502311993641062, 0.07829867160091034, 0.02254252076202717, -0.12859210282420883, -0.10207574032560493, -0.203120065969415, 0.26730884043410275, 0.03717969186478653, 0.3505676923445068, 0.07688824591045537, 0.04608062027210298, -0.028141795917270847, 0.12498782557220413, 0.03173235271466323, -0.23138156088694253, 0.10202848643113892, 0.21786954831511068, -0.08592265148714572, 0.09546981427746896, -0.5245018355870763, -0.3224229542896725, 0.003261230796432266, 0.14436208038219214, 0.13634121666948956, -0.10546056090522772, -0.27098937176812726, 0.06727267374159195, -0.06304593543217589, -0.07194660372960453, -0.094324961264367, -0.10852182207879825, 0.052582425919424094, -0.20046710171468127, 0.06636289420902568, 0.0513785384408458, 0.07542954433637743, -0.11158668141937457, -0.09949081554749192, -0.10170781434862874, 0.049712091082116015, -0.015471676447375033, -0.017684897009390764, 0.2539259570901497, -0.0945256997186404, -0.08545945479104725, 0.4310593214244224, -0.002106725014387988, -0.1371742186244004, 0.2240795681562024, -0.17132675663406888, -0.08647810240598539, 0.21330284832331997, 0.09481274664274399, 0.16740912461290675, -0.13658466326216093, 0.07524892259523487, -0.047326085256197706, 0.2403192128871384, 0.12152427146569468, 0.003123008075188129, 0.23779131173908424, 0.20976894193266232, -0.03301977956345162, 0.155297258956125, -0.13469957889397988, -0.028050366412991516, -0.15695111928149486, -0.2768201691170151, -0.23130032919848767, 0.0718283546438425, -0.06595470507734437, -0.2358793722165641, 0.3517009273704249, 0.09829192511741579, 0.1134580128844111, -0.07579099453197649, 0.20488924045681556, 0.018645081209027782, 0.0650232242903887, -0.07103332256575903, 0.17003131597840154, 0.09823642973564208, 0.0670292793164173, -0.24231476561488727, 0.07920598666309021, 0.044567345802743845]
1,802.02229
Axiomatic Foundations and Algorithms for Deciding Semantic Equivalences of SQL Queries
Deciding the equivalence of SQL queries is a fundamental problem in data management. As prior work has mainly focused on studying the theoretical limitations of the problem, very few implementations for checking such equivalences exist. In this paper, we present a new formalism and implementation for reasoning about the equivalences of SQL queries. Our formalism, U-semiring, extends SQL's semiring semantics with unbounded summation and duplicate elimination. U-semiring is defined using only very few axioms and can thus be easily implemented using proof assistants such as Coq for automated query reasoning. Yet, they are sufficient enough to enable us reason about sophisticated SQL queries that are evaluated over bags and sets, along with various integrity constraints. To evaluate the effectiveness of U-semiring, we have used it to formally verify 39 query rewrite rules from both classical data management research papers and real-world SQL engines, where many of them have never been proven correct before.
cs.DB cs.PL
deciding the equivalence of sql queries is a fundamental problem in data management as prior work has mainly focused on studying the theoretical limitations of the problem very few implementations for checking such equivalences exist in this paper we present a new formalism and implementation for reasoning about the equivalences of sql queries our formalism usemiring extends sqls semiring semantics with unbounded summation and duplicate elimination usemiring is defined using only very few axioms and can thus be easily implemented using proof assistants such as coq for automated query reasoning yet they are sufficient enough to enable us reason about sophisticated sql queries that are evaluated over bags and sets along with various integrity constraints to evaluate the effectiveness of usemiring we have used it to formally verify 39 query rewrite rules from both classical data management research papers and realworld sql engines where many of them have never been proven correct before
[['deciding', 'the', 'equivalence', 'of', 'sql', 'queries', 'is', 'a', 'fundamental', 'problem', 'in', 'data', 'management', 'as', 'prior', 'work', 'has', 'mainly', 'focused', 'on', 'studying', 'the', 'theoretical', 'limitations', 'of', 'the', 'problem', 'very', 'few', 'implementations', 'for', 'checking', 'such', 'equivalences', 'exist', 'in', 'this', 'paper', 'we', 'present', 'a', 'new', 'formalism', 'and', 'implementation', 'for', 'reasoning', 'about', 'the', 'equivalences', 'of', 'sql', 'queries', 'our', 'formalism', 'usemiring', 'extends', 'sqls', 'semiring', 'semantics', 'with', 'unbounded', 'summation', 'and', 'duplicate', 'elimination', 'usemiring', 'is', 'defined', 'using', 'only', 'very', 'few', 'axioms', 'and', 'can', 'thus', 'be', 'easily', 'implemented', 'using', 'proof', 'assistants', 'such', 'as', 'coq', 'for', 'automated', 'query', 'reasoning', 'yet', 'they', 'are', 'sufficient', 'enough', 'to', 'enable', 'us', 'reason', 'about', 'sophisticated', 'sql', 'queries', 'that', 'are', 'evaluated', 'over', 'bags', 'and', 'sets', 'along', 'with', 'various', 'integrity', 'constraints', 'to', 'evaluate', 'the', 'effectiveness', 'of', 'usemiring', 'we', 'have', 'used', 'it', 'to', 'formally', 'verify', '39', 'query', 'rewrite', 'rules', 'from', 'both', 'classical', 'data', 'management', 'research', 'papers', 'and', 'realworld', 'sql', 'engines', 'where', 'many', 'of', 'them', 'have', 'never', 'been', 'proven', 'correct', 'before']]
[-0.07977306403621447, -0.007998423596077105, -0.08187760525912631, 0.1339498467650569, -0.1689970837023377, -0.1844710518052083, 0.10556290377756228, 0.39029726105113666, -0.2793388615481805, -0.36448736206683163, 0.13864411488768882, -0.26427882611508074, -0.058088887397662485, 0.2565579981074419, -0.1073512706077761, 0.1181317962389561, 0.0811294308601836, 0.027518598420630678, -0.028901260917027802, -0.2900550776447346, 0.28392067612103167, 0.00815672588951618, 0.2556589873434574, 0.09975756167622855, 0.04783727529114782, 0.029046385521617007, -0.05195417394861579, 0.02872812288989818, -0.06479774767349762, 0.11581530635780807, 0.38027394695353567, 0.28408187508942206, 0.3045904215340034, -0.4486185756871124, -0.13607122246906453, 0.06908882030718078, 0.16596092380053712, 0.11566367527177814, -0.00468445300912862, -0.3196259966984489, 0.12593712428207296, -0.212413042587429, -0.02859919973849958, -0.16582150125778675, 0.040499350896068646, 0.006736253341051196, -0.1996314735714882, -0.07194642839782865, 0.12333289652627595, 0.12269027791673841, -0.008532960001330555, -0.06815837994613533, 0.03569073597459257, 0.11568916145882575, 0.02135402582938862, 0.005278202577256689, 0.14159833771949695, -0.06948757201719084, -0.18166961654825928, 0.38517998753030314, -0.003311215650314599, -0.1815999869525043, 0.18283401299389748, -0.025148870406696708, -0.2071195085825143, 0.09053985991293041, 0.12018074361254381, 0.1387673727620174, -0.2108060481373732, 0.11912415368487035, -0.055307380319420806, 0.19455615083193956, 0.1374456136140461, 0.05200746718769759, 0.1856929014948215, 0.18148100819876967, 0.0042342962662908525, 0.13013680207807862, 0.02486540191160862, -0.10526116295973313, -0.2588317411178662, -0.12865037305149885, -0.12499652452024272, -0.00844354173655506, -0.07616937044181243, -0.17276860562950566, 0.319125888404266, 0.2728425229840997, 0.13860273972367473, 0.11259670062538456, 0.3389950774950919, 0.06779216572960375, 0.12162951161031874, 0.0729739427660878, 0.15820548082610555, 0.09358699239327822, 0.13503040338895325, -0.07659875034633111, 0.1333427456895413, 0.041824878528227215]
1,802.0223
Dissipation-consistent modelling and classification of extended plasticity formulations
A unified classification framework for models of extended plasticity is presented. The models include well known micromorphic and strain gradient plasticity formulations. A unified treatment is possible due to the representation of strain gradient plasticity as an Eringen-type micromorphic continua. The classification is based on the form of the energetic and dissipative model structures and exploits the framework of dissipation-consistent modelling to elucidate the flow relation and yield condition. Models are identified as either serial or parallel. This designation is also applicable to familiar models of classical plasticity. Particular attention is paid to the rate-dependent problem arising from the choice of a smooth dissipation potential. The inability to locally determine the region of admissible stresses for the non-smooth (rate-independent) parallel models of plasticity is made clear.
cond-mat.soft physics.comp-ph
a unified classification framework for models of extended plasticity is presented the models include well known micromorphic and strain gradient plasticity formulations a unified treatment is possible due to the representation of strain gradient plasticity as an eringentype micromorphic continua the classification is based on the form of the energetic and dissipative model structures and exploits the framework of dissipationconsistent modelling to elucidate the flow relation and yield condition models are identified as either serial or parallel this designation is also applicable to familiar models of classical plasticity particular attention is paid to the ratedependent problem arising from the choice of a smooth dissipation potential the inability to locally determine the region of admissible stresses for the nonsmooth rateindependent parallel models of plasticity is made clear
[['a', 'unified', 'classification', 'framework', 'for', 'models', 'of', 'extended', 'plasticity', 'is', 'presented', 'the', 'models', 'include', 'well', 'known', 'micromorphic', 'and', 'strain', 'gradient', 'plasticity', 'formulations', 'a', 'unified', 'treatment', 'is', 'possible', 'due', 'to', 'the', 'representation', 'of', 'strain', 'gradient', 'plasticity', 'as', 'an', 'eringentype', 'micromorphic', 'continua', 'the', 'classification', 'is', 'based', 'on', 'the', 'form', 'of', 'the', 'energetic', 'and', 'dissipative', 'model', 'structures', 'and', 'exploits', 'the', 'framework', 'of', 'dissipationconsistent', 'modelling', 'to', 'elucidate', 'the', 'flow', 'relation', 'and', 'yield', 'condition', 'models', 'are', 'identified', 'as', 'either', 'serial', 'or', 'parallel', 'this', 'designation', 'is', 'also', 'applicable', 'to', 'familiar', 'models', 'of', 'classical', 'plasticity', 'particular', 'attention', 'is', 'paid', 'to', 'the', 'ratedependent', 'problem', 'arising', 'from', 'the', 'choice', 'of', 'a', 'smooth', 'dissipation', 'potential', 'the', 'inability', 'to', 'locally', 'determine', 'the', 'region', 'of', 'admissible', 'stresses', 'for', 'the', 'nonsmooth', 'rateindependent', 'parallel', 'models', 'of', 'plasticity', 'is', 'made', 'clear']]
[-0.07857209532108579, 0.05068918972592069, -0.08800940814938757, 0.07949889494921081, -0.12535704803022166, -0.1585415093746457, -0.006977352621634641, 0.376291474687957, -0.3147801894695975, -0.2530148659021624, 0.10018085806739456, -0.19281719700102845, -0.19218075803608722, 0.16586133153102692, -0.09711474485365831, 0.042587022034211025, 0.01849481273975764, 0.0036721513456394596, -0.040033682024635885, -0.19353147300200596, 0.2833941812559421, 0.0732160275651803, 0.34356510958393977, 0.048711869478856605, 0.10488885457650007, -0.0270633757820413, -0.04023477782855832, 0.058906012650338874, -0.11814535110850909, 0.1289098960344657, 0.22687085347925243, 0.05921179584355184, 0.27063003318195816, -0.4510740338404092, -0.3129943827122089, 0.08759805671363738, 0.063807891880823, 0.12327309799072664, 0.008167067173710693, -0.2125028259263584, 0.040255700399528346, -0.14334541060886677, -0.10042664380894313, -0.10920847796519557, -0.0051749395075133976, 0.03814265899540436, -0.2823566276234605, 0.13797319746334968, 0.11983680052235873, 0.03674484755573494, -0.1508555357915259, -0.08126374224441187, -0.050444672302898744, 0.0579321124880094, 0.06221187167196354, 0.03926844421714064, 0.14135310351247748, -0.16389620330958296, -0.1118378697165979, 0.4282353620135015, 0.006956648196078717, -0.22209482793245586, 0.2368968419388928, -0.010542583925979994, -0.10324310159851466, 0.10855934614946525, 0.19915270168454416, 0.11284161318889668, -0.17005793463378663, 0.06610491569717264, 0.03430481260734415, 0.13544732650306315, 0.0005566551567866436, -0.03734569529431962, 0.19973322409655778, 0.22265455437516193, 0.010881632566452026, 0.14742702951714878, -0.054374240862671286, -0.14601023370567184, -0.34147922096834066, -0.10971466261957351, -0.1309150185251999, 0.027179736587699625, -0.08033257551564489, -0.22380842760415567, 0.3576370838470006, 0.0999354917322278, 0.16599750019339543, 0.09467856709717683, 0.2413462967641892, 0.1005225978367361, 0.11306978719339016, 0.0501255463403199, 0.2546421124284426, 0.21975596639658174, 0.08178249816410244, -0.21638319265630637, 0.10205063849289511, 0.06342127290554345]
1,802.02231
Why Is There Something, Rather Than Nothing?
It seems natural to ask why the universe exists at all. Modern physics suggests that the universe can exist all by itself as a self-contained system, without anything external to create or sustain it. But there might not be an absolute answer to why it exists. I argue that any attempt to account for the existence of something rather than nothing must ultimately bottom out in a set of brute facts; the universe simply is, without ultimate cause or explanation.
physics.hist-ph gr-qc
it seems natural to ask why the universe exists at all modern physics suggests that the universe can exist all by itself as a selfcontained system without anything external to create or sustain it but there might not be an absolute answer to why it exists i argue that any attempt to account for the existence of something rather than nothing must ultimately bottom out in a set of brute facts the universe simply is without ultimate cause or explanation
[['it', 'seems', 'natural', 'to', 'ask', 'why', 'the', 'universe', 'exists', 'at', 'all', 'modern', 'physics', 'suggests', 'that', 'the', 'universe', 'can', 'exist', 'all', 'by', 'itself', 'as', 'a', 'selfcontained', 'system', 'without', 'anything', 'external', 'to', 'create', 'or', 'sustain', 'it', 'but', 'there', 'might', 'not', 'be', 'an', 'absolute', 'answer', 'to', 'why', 'it', 'exists', 'i', 'argue', 'that', 'any', 'attempt', 'to', 'account', 'for', 'the', 'existence', 'of', 'something', 'rather', 'than', 'nothing', 'must', 'ultimately', 'bottom', 'out', 'in', 'a', 'set', 'of', 'brute', 'facts', 'the', 'universe', 'simply', 'is', 'without', 'ultimate', 'cause', 'or', 'explanation']]
[-0.08908303869829978, 0.14669757439278328, -0.1471989365410991, 0.18724472565372707, -0.17579746540868654, -0.19283886057564814, 0.08143382369307801, 0.34437940616626295, -0.26252492400817573, -0.33973676085006443, 0.10501395294995745, -0.24863008284009994, -0.11756350233918056, 0.19386682146578096, -0.07337802448892035, -0.11280685034580529, 0.035481269854062705, 0.08769239843531977, 0.0017175113112898543, -0.2595763209334109, 0.2936328369192779, 0.03612116272233834, 0.22239337229402736, 0.06302886733901687, 0.08351019550573255, -0.06729627618042286, 0.009942770597990602, 0.021848710579797627, -0.08693577348694817, 0.015722686299704948, 0.2648068144742865, 0.20638868752866985, 0.3169809938874096, -0.4805608227616176, -0.21168156792409717, 0.21759778117120732, 0.16802707001334055, 0.1420374004985206, -0.02702049172949046, -0.17510574301268206, 0.12985082347295246, -0.11962330664973705, -0.19998374932911248, -0.11849802351207472, 0.0667406752530951, -0.13212534923222846, -0.18531473859329708, 0.027329387022473384, 0.14094072983571096, 0.004466716982835806, -0.024758987137465736, -0.06724468702595914, 0.023036856003454887, 0.11240648179373239, 0.05875783501004435, 0.08785203314218962, 0.13285322396841365, -0.12632520119659602, -0.08749216271680779, 0.44610439161770044, -0.03617064649388339, -0.1908577838621568, 0.21598044398997446, -0.1702433481317712, -0.09899837370612659, 0.12717446433089208, 0.039266392053104934, 0.014597766264341772, -0.1562298429082148, 0.03787952240818413, -0.05840442042099312, 0.2339977943105623, 0.07703737486153842, 0.02780690211802721, 0.3298723947722465, 0.09218682473292575, 0.0824189149774611, 0.01773294885424548, 0.07639525269623845, -0.07023438956239261, -0.34548533651977775, -0.1581831494346261, -0.15902882316440808, 0.16117600130401116, 0.006936347655573627, -0.18054735591867938, 0.2580500958370976, 0.20632137567736208, 0.21296602393267677, -0.021943044115323572, 0.2979618420096813, 0.05487421523739613, 0.1158868295897264, 0.10961185623891652, 0.26450607493752615, 0.012878647368052044, 0.09821161478175781, -0.12291069987622905, 0.14951735424110665, 0.011636953975539654]
1,802.02232
Feature Based Framework to Detect Diseases, Tumor, and Bleeding in Wireless Capsule Endoscopy
Studying animal locomotion improves our understanding of motor control and aids in the treatment of motor impairment. Mice are a premier model of human disease and are the model system of choice for much of basic neuroscience. High frame rates (250 Hz) are needed to quantify the kinematics of these running rodents. Manual tracking, especially for multiple markers, becomes time-consuming and impossible. Therefore, an automated method is necessary. We propose a method to track the paws of the animal in the following manner: first, segmenting all the possible paws based on color; second, classifying the segmented objects using a support vector machine (SVM) and neural network (NN); third, classifying the objects using the kinematic features of the running animal, coupled with texture features from earlier frames; and finally, detecting and handling collisions to assure the correctness of labelled paws. The proposed method is validated in sixty 1,000 frame video sequences (4 seconds) captured by four cameras from five mice. The total sensitivity for tracking of the front and hind paw is 99.70% using the SVM classifier and 99.76% using the NN classifier. In addition, we show the feasibility of 3D reconstruction using the four camera system.
cs.CV
studying animal locomotion improves our understanding of motor control and aids in the treatment of motor impairment mice are a premier model of human disease and are the model system of choice for much of basic neuroscience high frame rates 250 hz are needed to quantify the kinematics of these running rodents manual tracking especially for multiple markers becomes timeconsuming and impossible therefore an automated method is necessary we propose a method to track the paws of the animal in the following manner first segmenting all the possible paws based on color second classifying the segmented objects using a support vector machine svm and neural network nn third classifying the objects using the kinematic features of the running animal coupled with texture features from earlier frames and finally detecting and handling collisions to assure the correctness of labelled paws the proposed method is validated in sixty 1000 frame video sequences 4 seconds captured by four cameras from five mice the total sensitivity for tracking of the front and hind paw is 9970 using the svm classifier and 9976 using the nn classifier in addition we show the feasibility of 3d reconstruction using the four camera system
[['studying', 'animal', 'locomotion', 'improves', 'our', 'understanding', 'of', 'motor', 'control', 'and', 'aids', 'in', 'the', 'treatment', 'of', 'motor', 'impairment', 'mice', 'are', 'a', 'premier', 'model', 'of', 'human', 'disease', 'and', 'are', 'the', 'model', 'system', 'of', 'choice', 'for', 'much', 'of', 'basic', 'neuroscience', 'high', 'frame', 'rates', '250', 'hz', 'are', 'needed', 'to', 'quantify', 'the', 'kinematics', 'of', 'these', 'running', 'rodents', 'manual', 'tracking', 'especially', 'for', 'multiple', 'markers', 'becomes', 'timeconsuming', 'and', 'impossible', 'therefore', 'an', 'automated', 'method', 'is', 'necessary', 'we', 'propose', 'a', 'method', 'to', 'track', 'the', 'paws', 'of', 'the', 'animal', 'in', 'the', 'following', 'manner', 'first', 'segmenting', 'all', 'the', 'possible', 'paws', 'based', 'on', 'color', 'second', 'classifying', 'the', 'segmented', 'objects', 'using', 'a', 'support', 'vector', 'machine', 'svm', 'and', 'neural', 'network', 'nn', 'third', 'classifying', 'the', 'objects', 'using', 'the', 'kinematic', 'features', 'of', 'the', 'running', 'animal', 'coupled', 'with', 'texture', 'features', 'from', 'earlier', 'frames', 'and', 'finally', 'detecting', 'and', 'handling', 'collisions', 'to', 'assure', 'the', 'correctness', 'of', 'labelled', 'paws', 'the', 'proposed', 'method', 'is', 'validated', 'in', 'sixty', '1000', 'frame', 'video', 'sequences', '4', 'seconds', 'captured', 'by', 'four', 'cameras', 'from', 'five', 'mice', 'the', 'total', 'sensitivity', 'for', 'tracking', 'of', 'the', 'front', 'and', 'hind', 'paw', 'is', '9970', 'using', 'the', 'svm', 'classifier', 'and', '9976', 'using', 'the', 'nn', 'classifier', 'in', 'addition', 'we', 'show', 'the', 'feasibility', 'of', '3d', 'reconstruction', 'using', 'the', 'four', 'camera', 'system']]
[-0.06502431296050931, 0.04999283634026189, -0.05334481713511289, 0.040517344654728775, -0.06177367539001772, -0.15155307351587674, 0.012622292081897076, 0.4071638513643008, -0.20789484124879193, -0.34754049921981417, 0.08683565528734993, -0.2735990322027833, -0.1649731644608367, 0.19965046092387265, -0.10408920266617758, 0.09713760800659657, 0.12089314440217538, 0.06404110649242424, 0.013902250464516095, -0.24785637385331286, 0.25187620066631683, 0.05411691483683311, 0.2977970916580839, -0.03567266416353866, 0.15326458918623245, 0.026120326846826056, -0.09077394737530714, -0.012491828009175757, -0.04165308320035155, 0.16477977979035738, 0.2798156088850915, 0.20204430874198293, 0.27821198019843835, -0.42295726088281627, -0.18386554875148411, 0.08359493943504416, 0.14146588251997644, 0.10850885845526742, -0.010534930479330703, -0.3367244068831683, 0.10937650303881712, -0.142748148775158, -0.07283390961088933, -0.09425081389192014, -0.0019225002851528234, 0.016057985693884967, -0.2518363962606646, 0.0592783050539975, 0.007169149073664672, 0.13970971205749383, -0.11369783366099, -0.09066564786152388, 0.0001645941643987615, 0.20195050693015593, 0.016259455737413074, 0.06600391229566856, 0.18452629777961052, -0.1780823368501539, -0.11555652637034655, 0.38010260263242973, -0.009937791701537581, -0.17935257248150616, 0.21983123016304887, -0.09007577711525254, -0.12438820513825004, 0.13950842352679524, 0.1979467934319893, 0.1339843054761728, -0.18165324087439774, -0.03528845330927139, 0.001774175197351724, 0.19132862381446056, 0.07630151367674654, -0.048975934885824336, 0.16171272278357393, 0.2691263476816507, -0.012988431379199028, 0.10685452460908355, -0.18830367820874716, -0.03149780777211373, -0.26145179454529754, -0.1331734996289015, -0.1275857555351626, -0.06590687332985302, -0.09316196574244458, -0.10099622928716528, 0.4190615584548467, 0.19664068838815765, 0.18735954960664877, 0.09635700544294638, 0.33963294629103097, 0.004736766052575639, 0.0845349910436198, 0.04076252676164493, 0.206577016112323, 0.0460689922730522, 0.11165006721201233, -0.22235063434450122, 0.0690138628348135, 0.07407878476003997]
1,802.02233
Cyberhubs: Virtual Research Environments for Astronomy
Collaborations in astronomy and astrophysics are faced with numerous cyber infrastructure challenges, such as large data sets, the need to combine heterogeneous data sets, and the challenge to effectively collaborate on those large, heterogeneous data sets with significant processing requirements and complex science software tools. The cyberhubs system is an easy-to-deploy package for small to medium-sized collaborations based on the Jupyter and Docker technology, that allows web-browser enabled, remote, interactive analytic access to shared data. It offers an initial step to address these challenges. The features and deployment steps of the system are described, as well as the requirements collection through an account of the different approaches to data structuring, handling and available analytic tools for the NuGrid and PPMstar collaborations. NuGrid is an international collaboration that creates stellar evolution and explosion physics and nucleosynthesis simulation data. The PPMstar collaboration performs large-scale 3D stellar hydrodynamics simulation of interior convection in the late phases of stellar evolution. Examples of science that is presently performed on cyberhubs, in the areas 3D stellar hydrodynamic simulations, stellar evolution and nucleosynthesis and Galactic chemical evolution, are presented.
astro-ph.IM
collaborations in astronomy and astrophysics are faced with numerous cyber infrastructure challenges such as large data sets the need to combine heterogeneous data sets and the challenge to effectively collaborate on those large heterogeneous data sets with significant processing requirements and complex science software tools the cyberhubs system is an easytodeploy package for small to mediumsized collaborations based on the jupyter and docker technology that allows webbrowser enabled remote interactive analytic access to shared data it offers an initial step to address these challenges the features and deployment steps of the system are described as well as the requirements collection through an account of the different approaches to data structuring handling and available analytic tools for the nugrid and ppmstar collaborations nugrid is an international collaboration that creates stellar evolution and explosion physics and nucleosynthesis simulation data the ppmstar collaboration performs largescale 3d stellar hydrodynamics simulation of interior convection in the late phases of stellar evolution examples of science that is presently performed on cyberhubs in the areas 3d stellar hydrodynamic simulations stellar evolution and nucleosynthesis and galactic chemical evolution are presented
[['collaborations', 'in', 'astronomy', 'and', 'astrophysics', 'are', 'faced', 'with', 'numerous', 'cyber', 'infrastructure', 'challenges', 'such', 'as', 'large', 'data', 'sets', 'the', 'need', 'to', 'combine', 'heterogeneous', 'data', 'sets', 'and', 'the', 'challenge', 'to', 'effectively', 'collaborate', 'on', 'those', 'large', 'heterogeneous', 'data', 'sets', 'with', 'significant', 'processing', 'requirements', 'and', 'complex', 'science', 'software', 'tools', 'the', 'cyberhubs', 'system', 'is', 'an', 'easytodeploy', 'package', 'for', 'small', 'to', 'mediumsized', 'collaborations', 'based', 'on', 'the', 'jupyter', 'and', 'docker', 'technology', 'that', 'allows', 'webbrowser', 'enabled', 'remote', 'interactive', 'analytic', 'access', 'to', 'shared', 'data', 'it', 'offers', 'an', 'initial', 'step', 'to', 'address', 'these', 'challenges', 'the', 'features', 'and', 'deployment', 'steps', 'of', 'the', 'system', 'are', 'described', 'as', 'well', 'as', 'the', 'requirements', 'collection', 'through', 'an', 'account', 'of', 'the', 'different', 'approaches', 'to', 'data', 'structuring', 'handling', 'and', 'available', 'analytic', 'tools', 'for', 'the', 'nugrid', 'and', 'ppmstar', 'collaborations', 'nugrid', 'is', 'an', 'international', 'collaboration', 'that', 'creates', 'stellar', 'evolution', 'and', 'explosion', 'physics', 'and', 'nucleosynthesis', 'simulation', 'data', 'the', 'ppmstar', 'collaboration', 'performs', 'largescale', '3d', 'stellar', 'hydrodynamics', 'simulation', 'of', 'interior', 'convection', 'in', 'the', 'late', 'phases', 'of', 'stellar', 'evolution', 'examples', 'of', 'science', 'that', 'is', 'presently', 'performed', 'on', 'cyberhubs', 'in', 'the', 'areas', '3d', 'stellar', 'hydrodynamic', 'simulations', 'stellar', 'evolution', 'and', 'nucleosynthesis', 'and', 'galactic', 'chemical', 'evolution', 'are', 'presented']]
[-0.08070753756491991, 0.07699780100910777, -0.053465183008085476, 0.08627975879046082, -0.12084867360509849, -0.09209419145991796, -0.018654629289894628, 0.36180567020927085, -0.24611766018977996, -0.4090113762813212, 0.12320676397694422, -0.3123741775246375, -0.08123304931841938, 0.24402612680046076, -0.04263698493308398, 0.10762541046761123, 0.16937091206775956, -0.09973360090307222, 0.0007289525375209665, -0.253979903980671, 0.32932922499335443, 0.11954519333019643, 0.2787355712583561, 0.030713111570293314, 0.043196431924902905, -0.051347081988966196, -0.1212607013987733, -0.045395963532285075, -0.11317300727898144, 0.11470158905669879, 0.3338774417139841, 0.262253696004745, 0.276062382045045, -0.4900636621175355, -0.20843365712593612, 0.027594748641144525, 0.1507859107805416, 0.08095240658881624, -0.1176467977740195, -0.29230212615907525, 0.029295913915652155, -0.21049520886618267, -0.13415873726683386, -0.08156232701698213, 0.01765218640290452, 0.033114978235235876, -0.2745823793667839, -0.017529312356406552, -0.052755652426537965, 0.10199135258464205, -0.055539628153659, -0.1011229730093475, -0.04205955279431191, 0.20983613005988405, 0.0020574588590861415, 0.031186667509021215, 0.14143839247100934, -0.13627261575311422, -0.10495169385430518, 0.4085359787176039, 0.01661893969082556, -0.11210044724814426, 0.258679869962762, -0.10405688726592069, -0.17992761055415685, 0.05818496205519592, 0.22930379834005168, 0.029285567175607416, -0.1964219742090954, 0.08762152725213444, 0.05908406296420549, 0.1676241904510227, -0.007717366973879967, -0.016570644618634636, 0.23658202992480123, 0.24813354823194192, 0.015609220271992885, 0.04769502206067188, -0.09343970748805179, -0.11752608742857917, -0.240321483604971, -0.09701741183846352, -0.15442564815879287, -0.016987780041029948, -0.08720617189003073, -0.1564422531231317, 0.3298322859402024, 0.15984561156907925, 0.13000551197322063, -0.0055762744362183505, 0.37448558220744466, -0.023268203498936896, 0.10148370398203267, 0.11052731142164825, 0.1684941811215007, 0.07020380878834095, 0.19381891085021982, -0.19737724300730303, 0.05461977828644593, -0.022030216427205988]
1,802.02234
Monodromy and Log Geometry
A now classical construction due to Kato and Nakayama attaches a topological space (the "Betti realization") to a log scheme over $\mathbf{C}$. We show that in the case of a log smooth degeneration over the standard log disc, this construction allows one to recover the topology of the germ of the family from the log special fiber alone. We go on to give combinatorial formulas for the monodromy and the $d^2$ differentials acting on the nearby cycle complex in terms of the log structures. We also provide variants of these results for the Kummer etale topology. In the case of curves, these data are essentially equivalent to those encoded by the dual graph of a semistable degeneration, including the monodromy pairing and the Picard-Lefschetz formula.
math.AG
a now classical construction due to kato and nakayama attaches a topological space the betti realization to a log scheme over mathbfc we show that in the case of a log smooth degeneration over the standard log disc this construction allows one to recover the topology of the germ of the family from the log special fiber alone we go on to give combinatorial formulas for the monodromy and the d2 differentials acting on the nearby cycle complex in terms of the log structures we also provide variants of these results for the kummer etale topology in the case of curves these data are essentially equivalent to those encoded by the dual graph of a semistable degeneration including the monodromy pairing and the picardlefschetz formula
[['a', 'now', 'classical', 'construction', 'due', 'to', 'kato', 'and', 'nakayama', 'attaches', 'a', 'topological', 'space', 'the', 'betti', 'realization', 'to', 'a', 'log', 'scheme', 'over', 'mathbfc', 'we', 'show', 'that', 'in', 'the', 'case', 'of', 'a', 'log', 'smooth', 'degeneration', 'over', 'the', 'standard', 'log', 'disc', 'this', 'construction', 'allows', 'one', 'to', 'recover', 'the', 'topology', 'of', 'the', 'germ', 'of', 'the', 'family', 'from', 'the', 'log', 'special', 'fiber', 'alone', 'we', 'go', 'on', 'to', 'give', 'combinatorial', 'formulas', 'for', 'the', 'monodromy', 'and', 'the', 'd2', 'differentials', 'acting', 'on', 'the', 'nearby', 'cycle', 'complex', 'in', 'terms', 'of', 'the', 'log', 'structures', 'we', 'also', 'provide', 'variants', 'of', 'these', 'results', 'for', 'the', 'kummer', 'etale', 'topology', 'in', 'the', 'case', 'of', 'curves', 'these', 'data', 'are', 'essentially', 'equivalent', 'to', 'those', 'encoded', 'by', 'the', 'dual', 'graph', 'of', 'a', 'semistable', 'degeneration', 'including', 'the', 'monodromy', 'pairing', 'and', 'the', 'picardlefschetz', 'formula']]
[-0.15938858823478222, 0.017940432760864496, -0.09361270665749907, 0.08848862734995783, -0.09308373367786407, -0.11226028053089976, 0.04430896577984095, 0.30249771401286124, -0.3106269259825349, -0.24113458240404725, 0.09755600985698402, -0.2359641896748217, -0.18193008200079203, 0.24826509898900986, -0.16354847982840146, -0.00790985380858183, 0.009295752285048366, 0.06762244782713242, -0.08637792515283217, -0.31365280247689226, 0.3938960862569511, -0.018081676468253136, 0.2215866556223482, 0.01429158566147089, 0.08105357790086419, 0.019235400575911627, -0.011465519905090331, -0.05454090420925058, -0.16932954783953028, 0.16238412926904858, 0.2781301600933075, 0.07074716958776116, 0.13777286618947981, -0.39383457419276235, -0.15971936545474455, 0.1623934573084116, 0.10072419692575932, 0.0668067457228899, 0.0126545245712623, -0.22587455683574081, 0.09607737420126795, -0.14162500139698386, -0.16428874272294341, -0.0859056110791862, 0.018296274326741694, 0.03087362801283598, -0.21010157809406518, -0.030848424209514634, 0.07899238388985395, 0.08472904415801168, -0.046758958030957726, -0.06810027392208576, -0.0752564043328166, 0.07905893831327558, 0.00016050928086042403, 0.05480101154744625, 0.08658327177539468, -0.11451168850250543, -0.0878427558168769, 0.3604996491312049, -0.08710315341874957, -0.17113018761575222, 0.13575767484307288, -0.12978565740212797, -0.15070981750637294, 0.12961879352945835, 0.09283026465028524, 0.17837671820819379, -0.007160512521862983, 0.16751247488567605, -0.06829564644396305, 0.09259181720018386, 0.1064678746946156, 0.01317815283499658, 0.11615134262293578, 0.08386760437488557, 0.06633235600776971, 0.1287557668192312, -0.057949302140623334, -0.10209342659451068, -0.36813454096019266, -0.2090518395495601, -0.12084126301296055, 0.13952731032669544, -0.13347186852397863, -0.19861842091009022, 0.43491410556723714, 0.06444414488365874, 0.2618402153737843, 0.12232067653536796, 0.2600668556294404, 0.07008537500351668, 0.0643639158802107, 0.0437531338147819, 0.1409560011252761, 0.18624414500035347, -0.0008748827241361141, -0.18192518383264542, 0.014898024787195027, 0.19698719046264887]
1,802.02235
The Effect of Alternating Magnetic Field on Acceleration of Charged Particles
The self-consistent problem of the wave and particle spectrum is formulated and solved for acceleration of particles in a homogeneous magnetic field that varies periodically with time. It follows from the obtained solutions that when account is taken of the synchrotron radiation, the diffusion coefficient Do of ultrarelativistic electrons does not differ from the Fermi value. An expression is obtained for the minimum concentration of the accelerated particles, at which the cyclotron instability ensures the scattering necessary for effective acceleration.
physics.acc-ph
the selfconsistent problem of the wave and particle spectrum is formulated and solved for acceleration of particles in a homogeneous magnetic field that varies periodically with time it follows from the obtained solutions that when account is taken of the synchrotron radiation the diffusion coefficient do of ultrarelativistic electrons does not differ from the fermi value an expression is obtained for the minimum concentration of the accelerated particles at which the cyclotron instability ensures the scattering necessary for effective acceleration
[['the', 'selfconsistent', 'problem', 'of', 'the', 'wave', 'and', 'particle', 'spectrum', 'is', 'formulated', 'and', 'solved', 'for', 'acceleration', 'of', 'particles', 'in', 'a', 'homogeneous', 'magnetic', 'field', 'that', 'varies', 'periodically', 'with', 'time', 'it', 'follows', 'from', 'the', 'obtained', 'solutions', 'that', 'when', 'account', 'is', 'taken', 'of', 'the', 'synchrotron', 'radiation', 'the', 'diffusion', 'coefficient', 'do', 'of', 'ultrarelativistic', 'electrons', 'does', 'not', 'differ', 'from', 'the', 'fermi', 'value', 'an', 'expression', 'is', 'obtained', 'for', 'the', 'minimum', 'concentration', 'of', 'the', 'accelerated', 'particles', 'at', 'which', 'the', 'cyclotron', 'instability', 'ensures', 'the', 'scattering', 'necessary', 'for', 'effective', 'acceleration']]
[-0.1202829253335949, 0.20382556900894996, -0.0810452149307821, 0.08412921393319266, -0.03664226939436048, -0.1113842889375519, -0.03224312849633861, 0.32682083859981503, -0.2857007915619761, -0.294219259545207, 0.021433953240921254, -0.275119135226123, -0.021854015812277795, 0.21724528130898763, 0.03381754154106602, 0.0014206390595063567, 0.043376207863911984, 0.05432383297011256, -0.017678199271904303, -0.16777825664030388, 0.3037616502318997, 0.12386189057142474, 0.26626733313314616, 0.07819220524397678, 0.14165811913553625, 0.04482512577087618, 0.022604868991766124, 0.06096311159199104, -0.11178805477193236, 0.030206750227080192, 0.16889469309244304, 0.0641636016080156, 0.20720533281564713, -0.45560135446867206, -0.24672842279542237, 0.06653095266083256, 0.19480425440706312, 0.10844442889065249, -0.07320055084855995, -0.2171934727288317, 0.008277288434328511, -0.11017876720579807, -0.18217029044171795, 0.03534741425537504, 0.008852875437878539, 0.024358791322447358, -0.3195258358144201, 0.13097130625210412, 0.05150835937820375, -0.010491179977543652, -0.16836504149541726, -0.08348639570758679, 0.004714321665233001, 0.09230401449785859, 0.09994175809260923, 0.04113671436352888, 0.16115656918700552, -0.1340849474654533, -0.04622629332588986, 0.4346272485796362, -0.07889406663016416, -0.15539542336482554, 0.14275383300846442, -0.18312672957545145, -0.06165878124302253, 0.240581101574935, 0.12049959936994128, 0.10372144432622007, -0.14846472401204663, 0.09847245145210763, -0.014917991217043892, 0.14052398563653695, 0.0778833094984293, -0.03861274921800941, 0.2090969586162828, 0.10152839624497574, 0.04634637311974075, 0.0860565118433442, -0.09762003652285785, -0.06767260301858187, -0.31131700152764097, -0.13655704401317054, -0.24498697406961584, 0.05432745445650653, -0.08297557525183948, -0.1641100710767205, 0.3829144204966724, 0.13278798158280553, 0.1397989374003373, 0.02489975893549854, 0.2603857337788213, 0.2189816402620636, 0.040420323092257605, 0.13997229738160968, 0.3060389312828192, 0.10180471101775765, 0.1482303034281358, -0.29240294543560597, 0.04218680444755592, 0.05820995109388605]
1,802.02236
Designing scattering-free isotropic index profiles using phase-amplitude equations
The Helmholtz equation can be written as coupled equations for the amplitude and phase. By considering spatial phase distributions corresponding to reflectionless wave propagation in the plane and solving for the amplitude in terms of this phase, we designed two-dimensional graded-index media which do not scatter light. We give two illustrative examples, the first of which is a periodic grating for which diffraction is completely suppressed at a single frequency at normal incidence to the periodicity. The second example is a medium which behaves as a 'beam shifter' at a single frequency; acting to laterally shift a plane wave, or sufficiently wide beam, without reflection.
physics.optics
the helmholtz equation can be written as coupled equations for the amplitude and phase by considering spatial phase distributions corresponding to reflectionless wave propagation in the plane and solving for the amplitude in terms of this phase we designed twodimensional gradedindex media which do not scatter light we give two illustrative examples the first of which is a periodic grating for which diffraction is completely suppressed at a single frequency at normal incidence to the periodicity the second example is a medium which behaves as a beam shifter at a single frequency acting to laterally shift a plane wave or sufficiently wide beam without reflection
[['the', 'helmholtz', 'equation', 'can', 'be', 'written', 'as', 'coupled', 'equations', 'for', 'the', 'amplitude', 'and', 'phase', 'by', 'considering', 'spatial', 'phase', 'distributions', 'corresponding', 'to', 'reflectionless', 'wave', 'propagation', 'in', 'the', 'plane', 'and', 'solving', 'for', 'the', 'amplitude', 'in', 'terms', 'of', 'this', 'phase', 'we', 'designed', 'twodimensional', 'gradedindex', 'media', 'which', 'do', 'not', 'scatter', 'light', 'we', 'give', 'two', 'illustrative', 'examples', 'the', 'first', 'of', 'which', 'is', 'a', 'periodic', 'grating', 'for', 'which', 'diffraction', 'is', 'completely', 'suppressed', 'at', 'a', 'single', 'frequency', 'at', 'normal', 'incidence', 'to', 'the', 'periodicity', 'the', 'second', 'example', 'is', 'a', 'medium', 'which', 'behaves', 'as', 'a', 'beam', 'shifter', 'at', 'a', 'single', 'frequency', 'acting', 'to', 'laterally', 'shift', 'a', 'plane', 'wave', 'or', 'sufficiently', 'wide', 'beam', 'without', 'reflection']]
[-0.17095259909429367, 0.1991990496215987, -0.07058141897654249, 0.011569424404851383, -0.11427645487710833, -0.1319805530831218, 0.018764982046559454, 0.4255902604953874, -0.2842083445439736, -0.2568668470230131, 0.10824636509863748, -0.27141159812786747, -0.12610861772804388, 0.2230530960917739, 0.029355207378310818, 0.04831941277952865, -0.0037490570163797765, 0.013149007933125609, -0.08861759148892902, -0.14678421448140094, 0.3118639964344246, 0.01569741556332225, 0.2765878174720066, 0.0023242283169002762, 0.11685161787040886, 0.05827383790608673, 0.0587082649625483, 0.01335571151492851, -0.07554845035608326, 0.013748544977889174, 0.2532041866731431, 0.0032919174492625253, 0.20090554487403658, -0.3944606763798566, -0.25422220477124763, 0.07374706848391464, 0.17985185698683684, 0.13832443061595162, -0.067665381485685, -0.271378440197025, 0.009208676644733974, -0.10725475523975633, -0.2163463472654777, 0.009127362830830472, -0.01674930698105267, 0.038846115581691265, -0.283485437157963, 0.07255079567964588, 0.04042673824532401, 0.016340197099461443, -0.013357101198995398, -0.03407156668780815, -0.03359411093184636, 0.05450221326956082, -0.03720056423473926, 0.03498360302986666, 0.06992125548948977, -0.08776668521708676, -0.037354802899062636, 0.4207911623020967, -0.07820145764964677, -0.22417893384893736, 0.11297461880104882, -0.18136810732733769, -0.0029634531676059677, 0.1997136613176692, 0.20688459893599861, 0.09988432824611664, -0.13534838169414018, 0.009299316584310007, -0.017978321104255016, 0.21949930608804738, 0.18141656704246997, 0.022154696471989154, 0.2039130936598494, 0.1550909147509152, 0.05227821673588118, 0.15734318288907942, -0.10211288399462189, -0.041333335744483134, -0.3220548898070341, -0.11247019918103303, -0.16233158003583195, 0.030634247692207628, -0.041628591316874096, -0.20872839891484807, 0.41360727208001274, 0.061587565292471225, 0.16286700958652156, -0.00804167560612162, 0.3225508848604347, 0.20185855033452668, 0.054542174859948105, 0.022819463221267575, 0.22911388878710567, 0.14146086257838067, 0.1545943116680497, -0.2028029467602859, -0.007830094931913273, 0.031865990692971365]
1,802.02237
Weighted Delta-Tracking in Scattering Media
In this work, we expand the weighted delta-tracking routine to include a treatment for scattering. The weighted delta-tracking routine adds survival biasing to normal delta-tracking, improving problem figure of merit. In the original formulation of this method, only absorption events were considered. We have expanded the method to include scattering and investigated the method's effectiveness with two test cases: a pressurized water reactor pin cell and a fast reactor pin cell. We compare the figure of merit for calculating infinite flux and total cross-section while incrementally changing the amount of weighted delta-tracking used. We find that this new WDT routine has strong potential to improve the efficiency of fast reactor calculations, and may be useful for light water reactor calculations.
physics.comp-ph physics.ins-det stat.AP
in this work we expand the weighted deltatracking routine to include a treatment for scattering the weighted deltatracking routine adds survival biasing to normal deltatracking improving problem figure of merit in the original formulation of this method only absorption events were considered we have expanded the method to include scattering and investigated the methods effectiveness with two test cases a pressurized water reactor pin cell and a fast reactor pin cell we compare the figure of merit for calculating infinite flux and total crosssection while incrementally changing the amount of weighted deltatracking used we find that this new wdt routine has strong potential to improve the efficiency of fast reactor calculations and may be useful for light water reactor calculations
[['in', 'this', 'work', 'we', 'expand', 'the', 'weighted', 'deltatracking', 'routine', 'to', 'include', 'a', 'treatment', 'for', 'scattering', 'the', 'weighted', 'deltatracking', 'routine', 'adds', 'survival', 'biasing', 'to', 'normal', 'deltatracking', 'improving', 'problem', 'figure', 'of', 'merit', 'in', 'the', 'original', 'formulation', 'of', 'this', 'method', 'only', 'absorption', 'events', 'were', 'considered', 'we', 'have', 'expanded', 'the', 'method', 'to', 'include', 'scattering', 'and', 'investigated', 'the', 'methods', 'effectiveness', 'with', 'two', 'test', 'cases', 'a', 'pressurized', 'water', 'reactor', 'pin', 'cell', 'and', 'a', 'fast', 'reactor', 'pin', 'cell', 'we', 'compare', 'the', 'figure', 'of', 'merit', 'for', 'calculating', 'infinite', 'flux', 'and', 'total', 'crosssection', 'while', 'incrementally', 'changing', 'the', 'amount', 'of', 'weighted', 'deltatracking', 'used', 'we', 'find', 'that', 'this', 'new', 'wdt', 'routine', 'has', 'strong', 'potential', 'to', 'improve', 'the', 'efficiency', 'of', 'fast', 'reactor', 'calculations', 'and', 'may', 'be', 'useful', 'for', 'light', 'water', 'reactor', 'calculations']]
[-0.027756238003106167, 0.08422098727120707, -0.04495535128129025, 0.05355196131567937, -0.060454662344030415, -0.11567092523813093, 0.10063030036593167, 0.3767659469662855, -0.23319067992269993, -0.30427890752907844, 0.06683731066877954, -0.28847475938964634, -0.10853932244547954, 0.24453437199117617, -0.059246184684646624, 0.09774871900832902, 0.086076833641467, -0.025394191903372606, -0.07963921874955607, -0.26024350588559175, 0.224291227303911, 0.09632537268140974, 0.26881496670345467, 0.12063795223366469, 0.07338873892246435, 0.017645569056427727, -0.06315909157274291, 0.01511352367147083, -0.1208556653740743, 0.11299670904312127, 0.2372757701164422, 0.12687789931660517, 0.23118617316164697, -0.42694631094733876, -0.23959606552962215, 0.12839673173148186, 0.11237343424775949, 0.08659201548240768, -0.04740539503109176, -0.21441799526607308, 0.07703844100469723, -0.20427290508523582, -0.16087404285402349, -0.09636848099956599, -0.028924853746624044, 0.025448921997546375, -0.28199433932701745, 0.07237770019176727, -0.006058208784573556, 0.003864370180599508, -0.07282391416374594, -0.18784937356443454, 0.035841585711265604, 0.1209793848800473, 0.038776624877937135, -0.008070760716994604, 0.16505657037560012, -0.08438730277703144, -0.0599206390499603, 0.3576792585042616, -0.05348536456003785, -0.18329940003653367, 0.09650538978166878, -0.12115225453162566, -0.12890972961904482, 0.15401202479454998, 0.1915968524175696, 0.11638507773265398, -0.1600133396452293, 0.0004243391080914686, -0.014302908297395334, 0.12576524274190887, 0.1027813055086881, -0.030037527170497923, 0.16135658204633122, 0.217585489541428, 0.07687471747340169, 0.13627706531648678, -0.15973181334945064, -0.020507649650486806, -0.2521231570125868, -0.1734490028291475, -0.1264006964551906, 0.03096790291989843, -0.06007475689548301, -0.16926794301640863, 0.39363718684762716, 0.15498460734282465, 0.1323531223577447, 0.01767752522137016, 0.3028118608597045, 0.0989746654444995, 0.08129049758960415, 0.0077429091441445054, 0.2525630692873771, 0.12998398679725748, 0.1172526734667675, -0.25378381487874624, 0.07093475350411609, 0.05142297841181668]
1,802.02238
Semiclassical Self Consistent Treatment of the Emergence of Seeds of Cosmic Structure. The second order construction
In this work we extend the results of [1] where, Semiclassical Selfconsistent Configurations (SSC) formalism was introduced. The scheme combines quantum field theory on a background space-time, semiclassical treatment of gravitation and spontaneous collapse theories. The approach is applied to the context of early universe cosmology using a formal description of the transition from an initial inflationary stage characterized by a spatially homogeneous and isotropic (H&I) universe, to another where inhomogeneities are present in association with quantum fluctuations of the field driving inflation. In that work two constructions are produced. One of them describes a universe that is completely spatially (H&I), and the other is characterized by a slight excitation of the particular inhomogeneous and anisotropic perturbation. Finally, a characterization of their gluing to each other is provided as representing the transition as a result from a spontaneous collapse of the state of the quantum field, following the hypothesis originally introduced in [2]. Specifically, in [1] this construction is carried out by using cosmological perturbation theory and working up to linear order in the perturbation. However, given the nonlinear nature of gravitation, we should in principle explore the application of the formalism in a nonlinear regime. To this end and as a first step, we study in this work the transition from a spatially (H&I), from a SSC-I to one SSC-II that is not spatially (H&I), working this time up to second order in perturbation theory. We find that the self consistent construction now requires consideration of the so called tensor modes, as well as a nontrivial mixing of modes that made the analysis much more difficult and which could not a priori be warranted to work out in detail. The present work shows that this is indeed the case.
gr-qc
in this work we extend the results of 1 where semiclassical selfconsistent configurations ssc formalism was introduced the scheme combines quantum field theory on a background spacetime semiclassical treatment of gravitation and spontaneous collapse theories the approach is applied to the context of early universe cosmology using a formal description of the transition from an initial inflationary stage characterized by a spatially homogeneous and isotropic hi universe to another where inhomogeneities are present in association with quantum fluctuations of the field driving inflation in that work two constructions are produced one of them describes a universe that is completely spatially hi and the other is characterized by a slight excitation of the particular inhomogeneous and anisotropic perturbation finally a characterization of their gluing to each other is provided as representing the transition as a result from a spontaneous collapse of the state of the quantum field following the hypothesis originally introduced in 2 specifically in 1 this construction is carried out by using cosmological perturbation theory and working up to linear order in the perturbation however given the nonlinear nature of gravitation we should in principle explore the application of the formalism in a nonlinear regime to this end and as a first step we study in this work the transition from a spatially hi from a ssci to one sscii that is not spatially hi working this time up to second order in perturbation theory we find that the self consistent construction now requires consideration of the so called tensor modes as well as a nontrivial mixing of modes that made the analysis much more difficult and which could not a priori be warranted to work out in detail the present work shows that this is indeed the case
[['in', 'this', 'work', 'we', 'extend', 'the', 'results', 'of', '1', 'where', 'semiclassical', 'selfconsistent', 'configurations', 'ssc', 'formalism', 'was', 'introduced', 'the', 'scheme', 'combines', 'quantum', 'field', 'theory', 'on', 'a', 'background', 'spacetime', 'semiclassical', 'treatment', 'of', 'gravitation', 'and', 'spontaneous', 'collapse', 'theories', 'the', 'approach', 'is', 'applied', 'to', 'the', 'context', 'of', 'early', 'universe', 'cosmology', 'using', 'a', 'formal', 'description', 'of', 'the', 'transition', 'from', 'an', 'initial', 'inflationary', 'stage', 'characterized', 'by', 'a', 'spatially', 'homogeneous', 'and', 'isotropic', 'hi', 'universe', 'to', 'another', 'where', 'inhomogeneities', 'are', 'present', 'in', 'association', 'with', 'quantum', 'fluctuations', 'of', 'the', 'field', 'driving', 'inflation', 'in', 'that', 'work', 'two', 'constructions', 'are', 'produced', 'one', 'of', 'them', 'describes', 'a', 'universe', 'that', 'is', 'completely', 'spatially', 'hi', 'and', 'the', 'other', 'is', 'characterized', 'by', 'a', 'slight', 'excitation', 'of', 'the', 'particular', 'inhomogeneous', 'and', 'anisotropic', 'perturbation', 'finally', 'a', 'characterization', 'of', 'their', 'gluing', 'to', 'each', 'other', 'is', 'provided', 'as', 'representing', 'the', 'transition', 'as', 'a', 'result', 'from', 'a', 'spontaneous', 'collapse', 'of', 'the', 'state', 'of', 'the', 'quantum', 'field', 'following', 'the', 'hypothesis', 'originally', 'introduced', 'in', '2', 'specifically', 'in', '1', 'this', 'construction', 'is', 'carried', 'out', 'by', 'using', 'cosmological', 'perturbation', 'theory', 'and', 'working', 'up', 'to', 'linear', 'order', 'in', 'the', 'perturbation', 'however', 'given', 'the', 'nonlinear', 'nature', 'of', 'gravitation', 'we', 'should', 'in', 'principle', 'explore', 'the', 'application', 'of', 'the', 'formalism', 'in', 'a', 'nonlinear', 'regime', 'to', 'this', 'end', 'and', 'as', 'a', 'first', 'step', 'we', 'study', 'in', 'this', 'work', 'the', 'transition', 'from', 'a', 'spatially', 'hi', 'from', 'a', 'ssci', 'to', 'one', 'sscii', 'that', 'is', 'not', 'spatially', 'hi', 'working', 'this', 'time', 'up', 'to', 'second', 'order', 'in', 'perturbation', 'theory', 'we', 'find', 'that', 'the', 'self', 'consistent', 'construction', 'now', 'requires', 'consideration', 'of', 'the', 'so', 'called', 'tensor', 'modes', 'as', 'well', 'as', 'a', 'nontrivial', 'mixing', 'of', 'modes', 'that', 'made', 'the', 'analysis', 'much', 'more', 'difficult', 'and', 'which', 'could', 'not', 'a', 'priori', 'be', 'warranted', 'to', 'work', 'out', 'in', 'detail', 'the', 'present', 'work', 'shows', 'that', 'this', 'is', 'indeed', 'the', 'case']]
[-0.10577952463436022, 0.12976640203503842, -0.11461222285781841, 0.05281873532872209, -0.05725089921599905, -0.09879195668724942, 0.008780499119843296, 0.333899504975593, -0.2293540802381443, -0.2687008169022063, 0.09065072337418446, -0.22365058833968046, -0.15979005175458982, 0.149117200102844, -0.018351116177390707, 0.009256311697131312, -0.0033933618182483997, 0.019855635706335306, -0.045611127976982316, -0.22966548700891048, 0.3630712841730887, 0.08539916202627368, 0.24184719373546154, 0.012187939421612138, 0.0742691659358907, -0.04096190743535035, -0.04788859681368106, 0.057143462625264506, -0.12754316005937774, 0.10076830165773296, 0.23622120449409714, 0.10123302469958123, 0.2728675772938684, -0.41675147324620027, -0.23909707069795766, 0.0709771061465982, 0.1402109880101058, 0.1797114719139657, -0.0463356717145147, -0.2809415191313684, 0.060172287302549324, -0.18030585424336493, -0.14429327689439936, -0.05946986624098119, -0.00098359076810556, -0.03970606891546321, -0.2603682833441749, 0.08103960012988055, 0.07584687949978597, 0.01919465641745698, -0.05861838015197586, -0.01718723937421135, 0.014291105742379379, 0.08033773275277542, 0.053062620275060944, 0.057305011031408004, 0.105779082867217, -0.1215340630066739, -0.09062988683138248, 0.4087331946810327, -0.10588467109059774, -0.15583242166619812, 0.16793488223624503, -0.1504524638554062, -0.15382143712939314, 0.09684324962454348, 0.12046489981607338, 0.12965073985785608, -0.15463019716698406, 0.09441185772767818, -0.00506438197290918, 0.16561154658812707, 0.06561825953578661, 0.006303290940843729, 0.22615082969866487, 0.14894671037359725, 0.038746576912533554, 0.1340676972756942, -0.05192477496151142, -0.12411218005712676, -0.3505887860064894, -0.13854366393156523, -0.18673324801275912, 0.0825146455399307, -0.047224877568199077, -0.1717933756951887, 0.39740117958059384, 0.15387431114177288, 0.19229190376571906, 0.022462779467330864, 0.28936810087602727, 0.10318702431097562, 0.03576357133531859, 0.04809489346207619, 0.27617500300090564, 0.1564841732881467, 0.10571609072670804, -0.17889963018888796, 0.004897702923592399, 0.04243337902059991]
1,802.02239
Spectrophotometric Redshifts In The Faint Infrared Grism Survey: Finding Overdensities Of Faint Galaxies
We improve the accuracy of photometric redshifts by including low-resolution spectral data from the G102 grism on the Hubble Space Telescope, which assists in redshift determination by further constraining the shape of the broadband Spectral Energy Disribution (SED) and identifying spectral features. The photometry used in the redshift fits includes near-IR photometry from FIGS+CANDELS, as well as optical data from ground-based surveys and HST ACS, and mid-IR data from Spitzer. We calculated the redshifts through the comparison of measured photometry with template galaxy models, using the EAZY photometric redshift code. For objects with F105W $< 26.5$ AB mag with a redshift range of $0 < z < 6$, we find a typical error of $\Delta z = 0.03 * (1+z)$ for the purely photometric redshifts; with the addition of FIGS spectra, these become $\Delta z = 0.02 * (1+z)$, an improvement of 50\%. Addition of grism data also reduces the outlier rate from 8\% to 7\% across all fields. With the more-accurate spectrophotometric redshifts (SPZs), we searched the FIGS fields for galaxy overdensities. We identified 24 overdensities across the 4 fields. The strongest overdensity, matching a spectroscopically identified cluster at $z=0.85$, has 28 potential member galaxies, of which 8 have previous spectroscopic confirmation, and features a corresponding X-ray signal. Another corresponding to a cluster at $z=1.84$ has 22 members, 18 of which are spectroscopically confirmed. Additionally, we find 4 overdensities that are detected at an equal or higher significance in at least one metric to the two confirmed clusters.
astro-ph.GA
we improve the accuracy of photometric redshifts by including lowresolution spectral data from the g102 grism on the hubble space telescope which assists in redshift determination by further constraining the shape of the broadband spectral energy disribution sed and identifying spectral features the photometry used in the redshift fits includes nearir photometry from figscandels as well as optical data from groundbased surveys and hst acs and midir data from spitzer we calculated the redshifts through the comparison of measured photometry with template galaxy models using the eazy photometric redshift code for objects with f105w 265 ab mag with a redshift range of 0 z 6 we find a typical error of delta z 003 1z for the purely photometric redshifts with the addition of figs spectra these become delta z 002 1z an improvement of 50 addition of grism data also reduces the outlier rate from 8 to 7 across all fields with the moreaccurate spectrophotometric redshifts spzs we searched the figs fields for galaxy overdensities we identified 24 overdensities across the 4 fields the strongest overdensity matching a spectroscopically identified cluster at z085 has 28 potential member galaxies of which 8 have previous spectroscopic confirmation and features a corresponding xray signal another corresponding to a cluster at z184 has 22 members 18 of which are spectroscopically confirmed additionally we find 4 overdensities that are detected at an equal or higher significance in at least one metric to the two confirmed clusters
[['we', 'improve', 'the', 'accuracy', 'of', 'photometric', 'redshifts', 'by', 'including', 'lowresolution', 'spectral', 'data', 'from', 'the', 'g102', 'grism', 'on', 'the', 'hubble', 'space', 'telescope', 'which', 'assists', 'in', 'redshift', 'determination', 'by', 'further', 'constraining', 'the', 'shape', 'of', 'the', 'broadband', 'spectral', 'energy', 'disribution', 'sed', 'and', 'identifying', 'spectral', 'features', 'the', 'photometry', 'used', 'in', 'the', 'redshift', 'fits', 'includes', 'nearir', 'photometry', 'from', 'figscandels', 'as', 'well', 'as', 'optical', 'data', 'from', 'groundbased', 'surveys', 'and', 'hst', 'acs', 'and', 'midir', 'data', 'from', 'spitzer', 'we', 'calculated', 'the', 'redshifts', 'through', 'the', 'comparison', 'of', 'measured', 'photometry', 'with', 'template', 'galaxy', 'models', 'using', 'the', 'eazy', 'photometric', 'redshift', 'code', 'for', 'objects', 'with', 'f105w', '265', 'ab', 'mag', 'with', 'a', 'redshift', 'range', 'of', '0', 'z', '6', 'we', 'find', 'a', 'typical', 'error', 'of', 'delta', 'z', '003', '1z', 'for', 'the', 'purely', 'photometric', 'redshifts', 'with', 'the', 'addition', 'of', 'figs', 'spectra', 'these', 'become', 'delta', 'z', '002', '1z', 'an', 'improvement', 'of', '50', 'addition', 'of', 'grism', 'data', 'also', 'reduces', 'the', 'outlier', 'rate', 'from', '8', 'to', '7', 'across', 'all', 'fields', 'with', 'the', 'moreaccurate', 'spectrophotometric', 'redshifts', 'spzs', 'we', 'searched', 'the', 'figs', 'fields', 'for', 'galaxy', 'overdensities', 'we', 'identified', '24', 'overdensities', 'across', 'the', '4', 'fields', 'the', 'strongest', 'overdensity', 'matching', 'a', 'spectroscopically', 'identified', 'cluster', 'at', 'z085', 'has', '28', 'potential', 'member', 'galaxies', 'of', 'which', '8', 'have', 'previous', 'spectroscopic', 'confirmation', 'and', 'features', 'a', 'corresponding', 'xray', 'signal', 'another', 'corresponding', 'to', 'a', 'cluster', 'at', 'z184', 'has', '22', 'members', '18', 'of', 'which', 'are', 'spectroscopically', 'confirmed', 'additionally', 'we', 'find', '4', 'overdensities', 'that', 'are', 'detected', 'at', 'an', 'equal', 'or', 'higher', 'significance', 'in', 'at', 'least', 'one', 'metric', 'to', 'the', 'two', 'confirmed', 'clusters']]
[-0.01400438420858015, 0.057369509830355776, -0.0819391505010113, 0.062401742063963615, -0.08071663814201607, -0.07851762503890336, 0.0784538404276485, 0.45680298180389806, -0.14186663180002707, -0.39092838895671506, 0.06806811338100786, -0.35427533223160673, -0.0065819316537769025, 0.2216534833687929, 0.018838413111804866, 0.014101241951996163, 0.0702826436452505, -0.09138587155935018, -0.04576791637208305, -0.3257517250525734, 0.2621150153274296, 0.05806541508611511, 0.16637453678388836, -0.088660377866252, 0.08473096738037254, -0.04351800518719863, -0.16282441944447384, -0.02308903280618706, -0.2014075064585124, 0.01720038609811058, 0.2613293349019971, 0.12885146889788637, 0.22563414863788156, -0.2094106725299684, -0.1947721368026677, 0.07177239473705657, 0.20738986298880158, 0.048640589856350905, -0.02865940029488313, -0.30282457175071764, 0.08922367890271507, -0.14847254009913466, -0.14108323256539948, 0.04979432440272869, 0.005694853576260204, 0.030905044445877567, -0.22077824814761637, 0.16816377161208154, -0.0760912145155349, 0.18067521370649964, -0.15760896369000943, -0.15091865041543642, -0.10318549087676102, 0.09013794533890758, -0.05205902464672172, 0.12345506792825435, 0.0822773224012848, -0.16206497286775096, -0.046894222463700265, 0.3911343794394316, -0.08563959028277382, 0.03889296802559069, 0.18063750359309963, -0.17831394522039498, -0.18413760364564338, 0.16257925271623994, 0.1419028203930518, 0.07760912568519722, -0.18239248927854815, 0.04902460368667111, 0.057537922348060155, 0.266750198205886, 0.055414843629309984, 0.09744111099879614, 0.2522853531800367, 0.0642553738850568, 0.028685043549298177, 0.06503040759243119, -0.3214843478944043, 0.0731747947230215, -0.25939828820307465, -0.08879811926979665, -0.15242058938386763, 0.08503252323990797, -0.19356381778087772, -0.09540102690333079, 0.38048524248703314, 0.12114965614760999, 0.22525203591819165, 0.11137028372168596, 0.27974026737746416, 0.05818889062155132, 0.16321657800718264, 0.06597435137769599, 0.33518905727145804, 0.1221684139816701, 0.06227954703445757, -0.14885847707486421, -0.029042972942438572, -0.01465804992094949]
1,802.0224
A machine learning approach to reconstruction of heart surface potentials from body surface potentials
Invasive cardiac catheterisation is a common procedure that is carried out before surgical intervention. Yet, invasive cardiac diagnostics are full of risks, especially for young children. Decades of research has been conducted on the so called inverse problem of electrocardiography, which can be used to reconstruct Heart Surface Potentials (HSPs) from Body Surface Potentials (BSPs), for non-invasive diagnostics. State of the art solutions to the inverse problem are unsatisfactory, since the inverse problem is known to be ill-posed. In this paper we propose a novel approach to reconstructing HSPs from BSPs using a Time-Delay Artificial Neural Network (TDANN). We first design the TDANN architecture, and then develop an iterative search space algorithm to find the parameters of the TDANN, which results in the best overall HSP prediction. We use real-world recorded BSPs and HSPs from individuals suffering from serious cardiac conditions to validate our TDANN. The results are encouraging, in that coefficients obtained by correlating the predicted HSP with the recorded patient' HSP approach ideal values.
cs.LG cs.CV
invasive cardiac catheterisation is a common procedure that is carried out before surgical intervention yet invasive cardiac diagnostics are full of risks especially for young children decades of research has been conducted on the so called inverse problem of electrocardiography which can be used to reconstruct heart surface potentials hsps from body surface potentials bsps for noninvasive diagnostics state of the art solutions to the inverse problem are unsatisfactory since the inverse problem is known to be illposed in this paper we propose a novel approach to reconstructing hsps from bsps using a timedelay artificial neural network tdann we first design the tdann architecture and then develop an iterative search space algorithm to find the parameters of the tdann which results in the best overall hsp prediction we use realworld recorded bsps and hsps from individuals suffering from serious cardiac conditions to validate our tdann the results are encouraging in that coefficients obtained by correlating the predicted hsp with the recorded patient hsp approach ideal values
[['invasive', 'cardiac', 'catheterisation', 'is', 'a', 'common', 'procedure', 'that', 'is', 'carried', 'out', 'before', 'surgical', 'intervention', 'yet', 'invasive', 'cardiac', 'diagnostics', 'are', 'full', 'of', 'risks', 'especially', 'for', 'young', 'children', 'decades', 'of', 'research', 'has', 'been', 'conducted', 'on', 'the', 'so', 'called', 'inverse', 'problem', 'of', 'electrocardiography', 'which', 'can', 'be', 'used', 'to', 'reconstruct', 'heart', 'surface', 'potentials', 'hsps', 'from', 'body', 'surface', 'potentials', 'bsps', 'for', 'noninvasive', 'diagnostics', 'state', 'of', 'the', 'art', 'solutions', 'to', 'the', 'inverse', 'problem', 'are', 'unsatisfactory', 'since', 'the', 'inverse', 'problem', 'is', 'known', 'to', 'be', 'illposed', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'approach', 'to', 'reconstructing', 'hsps', 'from', 'bsps', 'using', 'a', 'timedelay', 'artificial', 'neural', 'network', 'tdann', 'we', 'first', 'design', 'the', 'tdann', 'architecture', 'and', 'then', 'develop', 'an', 'iterative', 'search', 'space', 'algorithm', 'to', 'find', 'the', 'parameters', 'of', 'the', 'tdann', 'which', 'results', 'in', 'the', 'best', 'overall', 'hsp', 'prediction', 'we', 'use', 'realworld', 'recorded', 'bsps', 'and', 'hsps', 'from', 'individuals', 'suffering', 'from', 'serious', 'cardiac', 'conditions', 'to', 'validate', 'our', 'tdann', 'the', 'results', 'are', 'encouraging', 'in', 'that', 'coefficients', 'obtained', 'by', 'correlating', 'the', 'predicted', 'hsp', 'with', 'the', 'recorded', 'patient', 'hsp', 'approach', 'ideal', 'values']]
[-0.013895537406879377, 0.03987932210047912, -0.07998679162715618, 0.06734321897159364, -0.10753472795126488, -0.17393110675950457, 0.021388420969085116, 0.4164793843021953, -0.23041269896798824, -0.2992433421930904, 0.13822312965492595, -0.25765633999919857, -0.21037958713293256, 0.24987488432299257, -0.12174241159515209, 0.10012406650700968, 0.12472409337579486, 0.016240599755960775, -0.02808067910317107, -0.23408485590255854, 0.26765950892614315, 0.046060050975149834, 0.29700673187533055, 0.013493669292249953, 0.11468513201044155, -0.01119378973247416, -0.035988816776851486, -0.0013206009761814635, -0.0801660179239256, 0.1402298067815613, 0.3250317294192669, 0.16970581056603443, 0.2970246804361961, -0.4186406575524843, -0.2304078493805894, 0.12838914844625438, 0.13228008532980792, 0.10931774850967003, -0.04767925946213058, -0.32029623435024757, 0.09996994550294995, -0.13176651370812612, -0.0999087119695565, -0.06411120431856757, -0.025717267951737326, -0.02619648980452253, -0.2971874294151743, 0.10441371598365122, -0.04083066596193744, 0.09105186474071927, -0.11074604987200484, -0.11439927931908653, 0.0281192657189915, 0.15598755658895944, 0.05141692830695692, 0.038926432864370204, 0.14089590505449975, -0.15454092684218726, -0.1405033739466018, 0.3324647034933589, 0.01555137263880257, -0.1559947943497247, 0.19593037711316158, -0.06717355942342386, -0.1258871111042618, 0.13248453198382296, 0.1911406427346933, 0.13060827785682114, -0.20881540319007114, 0.007604631194872894, -0.01469849865232785, 0.1630172377609345, 0.03553166967698833, -0.06853015250414161, 0.15252122572477322, 0.19697302314368673, 0.008889571769185454, 0.14236555094914846, -0.12426551667754594, -0.017383547258529676, -0.22225880467456327, -0.10748272068259945, -0.15778736974511026, 0.0278451265683061, -0.02748224898139772, -0.14555439847473794, 0.4105385703017868, 0.19425367448108652, 0.14838140545670975, 0.042877469614361334, 0.3122901115370129, 0.0653573476621062, 0.06926666263838759, 0.05651549363778119, 0.23239031131659826, 0.05856507698898709, 0.08904801583806816, -0.21383308990106706, 0.09364516001351807, 0.04102111649394445]
1,802.02241
Seismic-Net: A Deep Densely Connected Neural Network to Detect Seismic Events
One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the large subsurface uncertainty and complex governing physics. Traditional leakage detection and monitoring techniques rely on geophysical observations including seismic. However, the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation, therefore yielding in-accurate estimates of leakage rates and locations. In this work, we develop a novel machine-learning detection package, named "Seismic-Net", which is based on the deep densely connected neural network. To validate the performance of our proposed leakage detection method, we employ our method to a natural analog site at Chimay\'o, New Mexico. The seismic events in the data sets are generated because of the eruptions of geysers, which is due to the leakage of $\mathrm{CO}_\mathrm{2}$. In particular, we demonstrate the efficacy of our Seismic-Net by formulating our detection problem as an event detection problem with time series data. A fixed-length window is slid throughout the time series data and we build a deep densely connected network to classify each window to determine if a geyser event is included. Through our numerical tests, we show that our model achieves precision/recall as high as 0.889/0.923. Therefore, our Seismic-Net has a great potential for detection of $\mathrm{CO}_\mathrm{2}$ leakage.
eess.SP cs.CV cs.LG
one of the risks of largescale geologic carbon sequestration is the potential migration of fluids out of the storage formations accurate and fast detection of this fluids migration is not only important but also challenging due to the large subsurface uncertainty and complex governing physics traditional leakage detection and monitoring techniques rely on geophysical observations including seismic however the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation therefore yielding inaccurate estimates of leakage rates and locations in this work we develop a novel machinelearning detection package named seismicnet which is based on the deep densely connected neural network to validate the performance of our proposed leakage detection method we employ our method to a natural analog site at chimayo new mexico the seismic events in the data sets are generated because of the eruptions of geysers which is due to the leakage of mathrmco_mathrm2 in particular we demonstrate the efficacy of our seismicnet by formulating our detection problem as an event detection problem with time series data a fixedlength window is slid throughout the time series data and we build a deep densely connected network to classify each window to determine if a geyser event is included through our numerical tests we show that our model achieves precisionrecall as high as 08890923 therefore our seismicnet has a great potential for detection of mathrmco_mathrm2 leakage
[['one', 'of', 'the', 'risks', 'of', 'largescale', 'geologic', 'carbon', 'sequestration', 'is', 'the', 'potential', 'migration', 'of', 'fluids', 'out', 'of', 'the', 'storage', 'formations', 'accurate', 'and', 'fast', 'detection', 'of', 'this', 'fluids', 'migration', 'is', 'not', 'only', 'important', 'but', 'also', 'challenging', 'due', 'to', 'the', 'large', 'subsurface', 'uncertainty', 'and', 'complex', 'governing', 'physics', 'traditional', 'leakage', 'detection', 'and', 'monitoring', 'techniques', 'rely', 'on', 'geophysical', 'observations', 'including', 'seismic', 'however', 'the', 'resulting', 'accuracy', 'of', 'these', 'methods', 'is', 'limited', 'because', 'of', 'indirect', 'information', 'they', 'provide', 'requiring', 'expert', 'interpretation', 'therefore', 'yielding', 'inaccurate', 'estimates', 'of', 'leakage', 'rates', 'and', 'locations', 'in', 'this', 'work', 'we', 'develop', 'a', 'novel', 'machinelearning', 'detection', 'package', 'named', 'seismicnet', 'which', 'is', 'based', 'on', 'the', 'deep', 'densely', 'connected', 'neural', 'network', 'to', 'validate', 'the', 'performance', 'of', 'our', 'proposed', 'leakage', 'detection', 'method', 'we', 'employ', 'our', 'method', 'to', 'a', 'natural', 'analog', 'site', 'at', 'chimayo', 'new', 'mexico', 'the', 'seismic', 'events', 'in', 'the', 'data', 'sets', 'are', 'generated', 'because', 'of', 'the', 'eruptions', 'of', 'geysers', 'which', 'is', 'due', 'to', 'the', 'leakage', 'of', 'mathrmco_mathrm2', 'in', 'particular', 'we', 'demonstrate', 'the', 'efficacy', 'of', 'our', 'seismicnet', 'by', 'formulating', 'our', 'detection', 'problem', 'as', 'an', 'event', 'detection', 'problem', 'with', 'time', 'series', 'data', 'a', 'fixedlength', 'window', 'is', 'slid', 'throughout', 'the', 'time', 'series', 'data', 'and', 'we', 'build', 'a', 'deep', 'densely', 'connected', 'network', 'to', 'classify', 'each', 'window', 'to', 'determine', 'if', 'a', 'geyser', 'event', 'is', 'included', 'through', 'our', 'numerical', 'tests', 'we', 'show', 'that', 'our', 'model', 'achieves', 'precisionrecall', 'as', 'high', 'as', '08890923', 'therefore', 'our', 'seismicnet', 'has', 'a', 'great', 'potential', 'for', 'detection', 'of', 'mathrmco_mathrm2', 'leakage']]
[-0.08116846748019095, 0.019119303475969917, -0.05316370304289944, 0.04936116520905655, -0.08094536882964078, -0.10238488500513006, 0.056501347485831695, 0.36531785256208915, -0.25634114164450583, -0.3312861543422434, 0.15985596943197347, -0.27084600780922063, -0.16756173319248646, 0.22813332495749356, -0.09659989286018045, 0.0484393334808645, 0.11914883576345776, 0.025747335208666698, -0.019478851761002596, -0.24546461544671552, 0.25879473358151717, 0.10345615623692427, 0.316417001185759, 0.08018499585619122, 0.11435982151918947, -0.02868489850222607, -0.07387097061125628, -0.010822115356731637, -0.08464192449878681, 0.15473904695541582, 0.28729303367231696, 0.18137879587307557, 0.28115942864270327, -0.4363516807278389, -0.26553120311112716, 0.0939397371043206, 0.13230010123669145, 0.10301803555130232, -0.06975745121394937, -0.3025444958107791, 0.07747286264253617, -0.1683167343634475, -0.0541111730534906, -0.10192692669589999, 0.013859687538474406, 0.012486619445425867, -0.28138502863064213, 0.08506482283356538, 0.033437348169013205, 0.05004403017575673, -0.04773953972331232, -0.07099074344538774, 0.008536295288522205, 0.1512685480686885, 0.03381188903637067, 0.004665395507911677, 0.1433937444347529, -0.13583025133662058, -0.09723996151679833, 0.3701226084335838, -0.05100104614189548, -0.16238361784551097, 0.22299451545379206, -0.0837397817869491, -0.14088316297101414, 0.13782219313750893, 0.22209204062119967, 0.12906112938658784, -0.15975559295641192, -0.002570257370264204, -0.01523879727985906, 0.16393424745285556, 0.0235867083114531, -0.0017382881518355326, 0.21975505396646136, 0.2609387330972312, 0.06567372222381987, 0.11167341080216463, -0.18694548793989765, -0.04982521664963937, -0.26165478555648997, -0.13634527380533032, -0.18070833676233233, 0.0022089678760063465, -0.050846992558817555, -0.17506005049666815, 0.39354445679489064, 0.21069502580620905, 0.17483202796204733, 0.041202091151366436, 0.35043606102433905, 0.06350839222381055, 0.09379017499291845, 0.0760468013585635, 0.23152073100464532, 0.0627206471481099, 0.0898593426684608, -0.19955087348506295, 0.10429246236647789, 0.009832240687070512]
1,802.02242
Full-pulse Tomographic Reconstruction with Deep Neural Networks
Plasma tomography consists in reconstructing the 2D radiation profile in a poloidal cross-section of a fusion device, based on line-integrated measurements along several lines of sight. The reconstruction process is computationally intensive and, in practice, only a few reconstructions are usually computed per pulse. In this work, we trained a deep neural network based on a large collection of sample tomograms that have been produced at JET over several years. Once trained, the network is able to reproduce those results with high accuracy. More importantly, it can compute all the tomographic reconstructions for a given pulse in just a few seconds. This makes it possible to visualize several phenomena -- such as plasma heating, disruptions and impurity transport -- over the course of a discharge.
physics.comp-ph stat.ML
plasma tomography consists in reconstructing the 2d radiation profile in a poloidal crosssection of a fusion device based on lineintegrated measurements along several lines of sight the reconstruction process is computationally intensive and in practice only a few reconstructions are usually computed per pulse in this work we trained a deep neural network based on a large collection of sample tomograms that have been produced at jet over several years once trained the network is able to reproduce those results with high accuracy more importantly it can compute all the tomographic reconstructions for a given pulse in just a few seconds this makes it possible to visualize several phenomena such as plasma heating disruptions and impurity transport over the course of a discharge
[['plasma', 'tomography', 'consists', 'in', 'reconstructing', 'the', '2d', 'radiation', 'profile', 'in', 'a', 'poloidal', 'crosssection', 'of', 'a', 'fusion', 'device', 'based', 'on', 'lineintegrated', 'measurements', 'along', 'several', 'lines', 'of', 'sight', 'the', 'reconstruction', 'process', 'is', 'computationally', 'intensive', 'and', 'in', 'practice', 'only', 'a', 'few', 'reconstructions', 'are', 'usually', 'computed', 'per', 'pulse', 'in', 'this', 'work', 'we', 'trained', 'a', 'deep', 'neural', 'network', 'based', 'on', 'a', 'large', 'collection', 'of', 'sample', 'tomograms', 'that', 'have', 'been', 'produced', 'at', 'jet', 'over', 'several', 'years', 'once', 'trained', 'the', 'network', 'is', 'able', 'to', 'reproduce', 'those', 'results', 'with', 'high', 'accuracy', 'more', 'importantly', 'it', 'can', 'compute', 'all', 'the', 'tomographic', 'reconstructions', 'for', 'a', 'given', 'pulse', 'in', 'just', 'a', 'few', 'seconds', 'this', 'makes', 'it', 'possible', 'to', 'visualize', 'several', 'phenomena', 'such', 'as', 'plasma', 'heating', 'disruptions', 'and', 'impurity', 'transport', 'over', 'the', 'course', 'of', 'a', 'discharge']]
[-0.0641002188298503, 0.08385539374776124, -0.053350143647578556, 0.06046490730371194, -0.042575828013638774, -0.12672371111764777, -0.005955638159520742, 0.4644028278961172, -0.22715899203638962, -0.34344574024643354, 0.09347932189002603, -0.27863772394044733, -0.08250150903360208, 0.2711439166006034, -0.05538025724406286, 0.08181360151194703, 0.13076610555985896, 0.02017009268870683, -0.08311869512355652, -0.2520437642517386, 0.23401290498583055, 0.07539328385870411, 0.2742366823405633, 0.028331848050702393, 0.11601557876399862, -0.021426781035232836, -0.02744026768316583, 0.03795136490692877, -0.05564072205808356, 0.09796103757874268, 0.25020292198391464, 0.133065097020727, 0.27535472075810763, -0.46313931250809154, -0.2765729301949827, 0.04827880876222095, 0.16143559996508122, 0.1314451359704561, -0.04788483395792517, -0.22123300385987008, 0.06395339380525719, -0.17291329823040624, -0.029662443305994195, -0.06535056510625968, 0.021451950099743235, 0.0030557370282770172, -0.255993721771955, 0.05484687663781328, -0.017643068343064013, 0.06335340943982506, -0.03131787979793621, -0.05201604520538595, -0.024071583581134315, 0.0916614495974973, 0.012120732530048571, 0.06926776426920016, 0.19984911938341773, -0.15151778581680928, -0.07620602389570416, 0.36954082339638616, -0.05702585889768552, -0.1509316052495676, 0.17966677746319068, -0.15874255911212384, -0.14318745540894143, 0.2174070624680054, 0.1952885554278103, 0.15010929896734745, -0.1710330053323471, -0.04917682757756362, -0.057083117800227144, 0.1603560874492263, 0.08631761986156547, -0.006105003203170722, 0.2155962941763029, 0.20851892390386845, 0.017132247871969167, 0.11924710912143478, -0.18629310226703927, -0.03262625223572737, -0.2699846229989203, -0.10375255157005012, -0.1943165654386583, 0.04921706211923554, -0.03701099732533907, -0.1651109743643764, 0.4519268801450972, 0.182359295473169, 0.23286276305760673, 0.00914724727683678, 0.3468770968417327, 0.0691746275595624, 0.10372866071737939, 0.08799511624303291, 0.22887344050365008, 0.13561277143748068, 0.1369913814653741, -0.15129353216758407, 0.08734159030747123, 0.0017570956189912267]
1,802.02243
Topological phase transition measured in a dissipative metamaterial
We construct a metamaterial from radio-frequency harmonic oscillators, and find two topologically distinct phases resulting from dissipation engineered into the system. These phases are distinguished by a quantized value of bulk energy transport. The impulse response of our circuit is measured and used to reconstruct the band structure and winding number of circuit eigenfunctions around a dark mode. Our results demonstrate that dissipation can lead to topological transport in a much wider class of physical systems than considered before.
cond-mat.mes-hall physics.class-ph quant-ph
we construct a metamaterial from radiofrequency harmonic oscillators and find two topologically distinct phases resulting from dissipation engineered into the system these phases are distinguished by a quantized value of bulk energy transport the impulse response of our circuit is measured and used to reconstruct the band structure and winding number of circuit eigenfunctions around a dark mode our results demonstrate that dissipation can lead to topological transport in a much wider class of physical systems than considered before
[['we', 'construct', 'a', 'metamaterial', 'from', 'radiofrequency', 'harmonic', 'oscillators', 'and', 'find', 'two', 'topologically', 'distinct', 'phases', 'resulting', 'from', 'dissipation', 'engineered', 'into', 'the', 'system', 'these', 'phases', 'are', 'distinguished', 'by', 'a', 'quantized', 'value', 'of', 'bulk', 'energy', 'transport', 'the', 'impulse', 'response', 'of', 'our', 'circuit', 'is', 'measured', 'and', 'used', 'to', 'reconstruct', 'the', 'band', 'structure', 'and', 'winding', 'number', 'of', 'circuit', 'eigenfunctions', 'around', 'a', 'dark', 'mode', 'our', 'results', 'demonstrate', 'that', 'dissipation', 'can', 'lead', 'to', 'topological', 'transport', 'in', 'a', 'much', 'wider', 'class', 'of', 'physical', 'systems', 'than', 'considered', 'before']]
[-0.1865214831608383, 0.1833261457932052, -0.06741777960140305, 0.0041183292706603114, -0.03385688397514669, -0.1476957795056927, 0.026872502787250886, 0.35594788198418253, -0.27029919176350664, -0.3154724910855293, 0.03590704623427053, -0.26073226926824716, -0.16163091470275215, 0.24733076725579514, -5.328908704126937e-05, 0.05542036827323558, 0.0227740769144855, -0.004032788093826628, -0.04834240911634568, -0.14690845782420586, 0.2943253449128964, -0.02565266082322673, 0.28385811129325556, -0.0157176114536256, 0.06196227928334729, -0.0814769114515025, 0.05290175184513195, 0.04886996163691901, -0.1284572825494666, 0.08349632327975351, 0.23867797056401643, -0.0011830264879272709, 0.20220776610194316, -0.4747448941999221, -0.26143411482696105, 0.07600242497776694, 0.14284991521883425, 0.12626554668421233, -0.03646029979933666, -0.28515544844956336, 0.052067891417566355, -0.17676215597923514, -0.09855109515092984, -0.09632720020776496, -0.02209235506155823, -0.011118953010138077, -0.23401496434492897, 0.051446683501494644, 0.027624983891632548, 0.014920863741419361, -0.07691735559131337, -0.09803745874846236, -0.09725163654200261, 0.09012309735923817, -0.01229225916351793, -0.02100226098282522, 0.1679480448424156, -0.11578757708444248, -0.11667276430827907, 0.3820043235392416, -0.05068988512845598, -0.18207779310973762, 0.18865641524803034, -0.15998695566815535, -0.029212022960610404, 0.17912982352950338, 0.16847409139375522, 0.051655883423371025, -0.13013626392849698, 0.0005665289428191188, 0.005741013152100429, 0.18347208989383298, 0.04174201951444715, 0.10900575273281222, 0.277461383444599, 0.13537670617268857, 0.05722857735273015, 0.18832506673392851, -0.05758592510548762, -0.06450476737905152, -0.2806740859169749, -0.14658569915903896, -0.2338871732365216, 0.08128756229305946, -0.03586868701824665, -0.17752223841468745, 0.49262483007734337, 0.13943419405082358, 0.1830636720066961, 0.024764841101191277, 0.2584119657573255, 0.14690609565417317, 0.08313580963147592, 0.07601432037197903, 0.28030193170320383, 0.14777438992434005, 0.08605701340910613, -0.26171489704482825, -0.020688076064438572, 0.031583913749296075]
1,802.02244
De Finetti's theorem: rate of convergence in Kolmogorov distance
This paper provides a quantitative version of de Finetti law of large numbers. Given an infinite sequence $\{X_n\}_{n \geq 1}$ of exchangeable Bernoulli variables, it is well-known that $\frac{1}{n} \sum_{i = 1}^n X_i \stackrel{a.s.}{\longrightarrow} Y$, for a suitable random variable $Y$ taking values in $[0,1]$. Here, we consider the rate of convergence in law of $\frac{1}{n} \sum_{i = 1}^n X_i$ towards $Y$, with respect to the Kolmogorov distance. After showing that any rate of the type of $1/n^{\alpha}$ can be obtained for any $\alpha \in (0,1]$, we find a sufficient condition on the probability distribution of $Y$ for the achievement of the optimal rate of convergence, that is $1/n$. Our main result improve on existing literature: in particular, with respect to \cite{MPS}, we study a stronger metric while, with respect to \cite{Mna}, we weaken the regularity hypothesis on the probability distribution of $Y$.
math.PR
this paper provides a quantitative version of de finetti law of large numbers given an infinite sequence x_n_n geq 1 of exchangeable bernoulli variables it is wellknown that frac1n sum_i 1n x_i stackrelaslongrightarrow y for a suitable random variable y taking values in 01 here we consider the rate of convergence in law of frac1n sum_i 1n x_i towards y with respect to the kolmogorov distance after showing that any rate of the type of 1nalpha can be obtained for any alpha in 01 we find a sufficient condition on the probability distribution of y for the achievement of the optimal rate of convergence that is 1n our main result improve on existing literature in particular with respect to citemps we study a stronger metric while with respect to citemna we weaken the regularity hypothesis on the probability distribution of y
[['this', 'paper', 'provides', 'a', 'quantitative', 'version', 'of', 'de', 'finetti', 'law', 'of', 'large', 'numbers', 'given', 'an', 'infinite', 'sequence', 'x_n_n', 'geq', '1', 'of', 'exchangeable', 'bernoulli', 'variables', 'it', 'is', 'wellknown', 'that', 'frac1n', 'sum_i', '1n', 'x_i', 'stackrelaslongrightarrow', 'y', 'for', 'a', 'suitable', 'random', 'variable', 'y', 'taking', 'values', 'in', '01', 'here', 'we', 'consider', 'the', 'rate', 'of', 'convergence', 'in', 'law', 'of', 'frac1n', 'sum_i', '1n', 'x_i', 'towards', 'y', 'with', 'respect', 'to', 'the', 'kolmogorov', 'distance', 'after', 'showing', 'that', 'any', 'rate', 'of', 'the', 'type', 'of', '1nalpha', 'can', 'be', 'obtained', 'for', 'any', 'alpha', 'in', '01', 'we', 'find', 'a', 'sufficient', 'condition', 'on', 'the', 'probability', 'distribution', 'of', 'y', 'for', 'the', 'achievement', 'of', 'the', 'optimal', 'rate', 'of', 'convergence', 'that', 'is', '1n', 'our', 'main', 'result', 'improve', 'on', 'existing', 'literature', 'in', 'particular', 'with', 'respect', 'to', 'citemps', 'we', 'study', 'a', 'stronger', 'metric', 'while', 'with', 'respect', 'to', 'citemna', 'we', 'weaken', 'the', 'regularity', 'hypothesis', 'on', 'the', 'probability', 'distribution', 'of', 'y']]
[-0.1393087643225664, 0.1022119676379826, -0.07199109526540058, 0.05866827486180768, 0.007284817022635885, -0.1356569653093491, 0.08525935162965587, 0.3520716388804325, -0.26525897755409067, -0.21490299523145, 0.06476212761945267, -0.2972769591167731, -0.07133718234135945, 0.16029519514194218, -0.1340370050701086, 0.03688711973687084, 0.0064495547364155454, 0.08926703855125369, -0.056711499957178814, -0.27669564470061625, 0.3267878229405893, 0.03192076151110772, 0.2457999983917166, -0.023930285382421985, 0.12479998257375606, 0.013362273354542212, -0.008629253618351684, 0.0017684614825723827, -0.2058118044835177, 0.08561044255359287, 0.18926250445993914, 0.13909751588168243, 0.32786228140627127, -0.33593470363816974, -0.14832660318959667, 0.17823530273697386, 0.15042550677047245, 0.002530639680723349, -0.0146911172592756, -0.22971553565002978, 0.1577443223449982, -0.14040262656762142, -0.16114245169539598, -0.022545414366017, 0.0650709313272998, 0.11245041945400863, -0.37962713233023154, 0.09211010652580771, 0.14463945297335368, 0.010513028690078552, -0.014377864013574477, -0.16442342575949928, 0.012930143113329035, 0.1065834276513129, 0.08161309125168464, 0.12051479249139843, 0.03751643052311155, -0.07633849582803584, -0.07947166278566895, 0.32894765308963647, -0.10643674865149069, -0.20984412732439628, 0.09700897359626665, -0.214275478358394, -0.19552915257847178, 0.09168779653281081, 0.12187813535675177, 0.13665160769143267, -0.08887394112906, 0.14697800888140025, -0.05149404674538992, 0.1709750679159618, 0.07752964572063174, 0.04889419659688745, 0.09911287102453492, 0.09800939256008175, 0.1327595262673508, 0.10754244949962215, -0.052661212291096104, -0.07084585917924625, -0.35542705223433324, -0.18940537282522174, -0.2087180361074085, 0.1562795233440356, -0.1736814274918288, -0.1390481178810739, 0.2859897925450966, 0.15442283712732402, 0.23055229428965782, 0.14864869355021612, 0.19980067768525603, 0.1397173355111643, -0.061941040845155934, 0.037456439620734236, 0.1323623687663264, 0.13767788859516167, 0.06347477142327884, -0.15418497262104158, 0.11570748783634517, 0.1185551981974825]
1,802.02245
Structure-stiffness relation of live mouse brain tissue determined by depth-controlled indentation mapping
The mechanical properties of brain tissue play a pivotal role in neurodevelopment and neurological disorders. Yet, at present, there is no consensus on how the different structural parts of the tissue contribute to its stiffness variations. Here, we have gathered depth-controlled indentation viscoelasticity maps of the hippocampus of isolated horizontal live mouse brain sections. Our results confirm the highly viscoelestic nature of the material and clearly show that the mechanical properties correlate with the different morphological layers of the samples investigated. Interestingly, the relative cell nuclei area seems to negatively correlate with the stiffness observed.
physics.bio-ph
the mechanical properties of brain tissue play a pivotal role in neurodevelopment and neurological disorders yet at present there is no consensus on how the different structural parts of the tissue contribute to its stiffness variations here we have gathered depthcontrolled indentation viscoelasticity maps of the hippocampus of isolated horizontal live mouse brain sections our results confirm the highly viscoelestic nature of the material and clearly show that the mechanical properties correlate with the different morphological layers of the samples investigated interestingly the relative cell nuclei area seems to negatively correlate with the stiffness observed
[['the', 'mechanical', 'properties', 'of', 'brain', 'tissue', 'play', 'a', 'pivotal', 'role', 'in', 'neurodevelopment', 'and', 'neurological', 'disorders', 'yet', 'at', 'present', 'there', 'is', 'no', 'consensus', 'on', 'how', 'the', 'different', 'structural', 'parts', 'of', 'the', 'tissue', 'contribute', 'to', 'its', 'stiffness', 'variations', 'here', 'we', 'have', 'gathered', 'depthcontrolled', 'indentation', 'viscoelasticity', 'maps', 'of', 'the', 'hippocampus', 'of', 'isolated', 'horizontal', 'live', 'mouse', 'brain', 'sections', 'our', 'results', 'confirm', 'the', 'highly', 'viscoelestic', 'nature', 'of', 'the', 'material', 'and', 'clearly', 'show', 'that', 'the', 'mechanical', 'properties', 'correlate', 'with', 'the', 'different', 'morphological', 'layers', 'of', 'the', 'samples', 'investigated', 'interestingly', 'the', 'relative', 'cell', 'nuclei', 'area', 'seems', 'to', 'negatively', 'correlate', 'with', 'the', 'stiffness', 'observed']]
[-0.06975915024621769, 0.12470209515068997, -0.06534818429598942, 0.02542700651820075, -0.01802884528730461, -0.09504321011457037, 0.009238770480535211, 0.43890743250859543, -0.23466583781261394, -0.2852831927956047, 0.05958501147874136, -0.29207710190577074, -0.2360619184265546, 0.1535851988406416, -0.08005038856409807, 0.0024294013428709845, 0.06453370588256958, 0.030173794510080777, 0.0005250502838455933, -0.19664861550777557, 0.290824215755144, 0.03993473447453072, 0.32588468206442023, 0.053503499299466135, 0.08355433548097202, -0.04076410656140998, -0.025170419315629182, 0.03957006722680006, -0.14472567517735482, 0.13127511972066094, 0.274552830534571, 0.07293943406399736, 0.25690174381932285, -0.48706277113090807, -0.2389982292834828, 0.07954935262356191, 0.13152869556599514, 0.04153397919094943, -0.03519756977193731, -0.2519280439084198, 0.08272849909213194, -0.05763136613321431, -0.10737093809516506, -0.0648997020115085, 0.03333415922292687, 0.02662212576499169, -0.13844002189828045, 0.1575924765412755, 0.048753801433934874, 0.142685368019924, -0.12791434894043438, -0.10640005734154677, -0.08484649221521821, 0.22432147588164725, 0.0794949051540127, 0.009916968192865557, 0.28132869856570786, -0.17282440460366297, -0.07521969646195624, 0.3275137965349441, 0.06973504426671152, -0.15705953597771052, 0.240889121282925, -0.16382884404106818, -0.12808544461199262, 0.13276853734389582, 0.1666849026595183, 0.05239373100723358, -0.13073044603175304, -0.03022665835476104, -0.0011709888881825386, 0.22305682984656316, 0.0647920362274856, 0.018774955314237306, 0.17726042625454672, 0.2106385462362557, -0.03535821043856521, 0.13509352194353383, -0.12581482407527955, -0.011303968388250376, -0.2423855000859166, -0.14773641406816054, -0.1008492059748065, 0.0025838318028848896, -0.10778932311996926, -0.20145496242045563, 0.4163979174262111, 0.09974648219909757, 0.2133969414677035, 0.016862974479853948, 0.20823279607600156, -0.013965064321614882, 0.11865230464435955, -0.01813695263712013, 0.30295824325405696, 0.15672035475677631, 0.14340154295836754, -0.30555802887365063, 0.17111943862301873, -0.042992449033648725]
1,802.02246
Approximation Methods for Bilevel Programming
In this paper, we study a class of bilevel programming problem where the inner objective function is strongly convex. More specifically, under some mile assumptions on the partial derivatives of both inner and outer objective functions, we present an approximation algorithm for solving this class of problem and provide its finite-time convergence analysis under different convexity assumption on the outer objective function. We also present an accelerated variant of this method which improves the rate of convergence under convexity assumption. Furthermore, we generalize our results under stochastic setting where only noisy information of both objective functions is available. To the best of our knowledge, this is the first time that such (stochastic) approximation algorithms with established iteration complexity (sample complexity) are provided for bilevel programming.
math.OC
in this paper we study a class of bilevel programming problem where the inner objective function is strongly convex more specifically under some mile assumptions on the partial derivatives of both inner and outer objective functions we present an approximation algorithm for solving this class of problem and provide its finitetime convergence analysis under different convexity assumption on the outer objective function we also present an accelerated variant of this method which improves the rate of convergence under convexity assumption furthermore we generalize our results under stochastic setting where only noisy information of both objective functions is available to the best of our knowledge this is the first time that such stochastic approximation algorithms with established iteration complexity sample complexity are provided for bilevel programming
[['in', 'this', 'paper', 'we', 'study', 'a', 'class', 'of', 'bilevel', 'programming', 'problem', 'where', 'the', 'inner', 'objective', 'function', 'is', 'strongly', 'convex', 'more', 'specifically', 'under', 'some', 'mile', 'assumptions', 'on', 'the', 'partial', 'derivatives', 'of', 'both', 'inner', 'and', 'outer', 'objective', 'functions', 'we', 'present', 'an', 'approximation', 'algorithm', 'for', 'solving', 'this', 'class', 'of', 'problem', 'and', 'provide', 'its', 'finitetime', 'convergence', 'analysis', 'under', 'different', 'convexity', 'assumption', 'on', 'the', 'outer', 'objective', 'function', 'we', 'also', 'present', 'an', 'accelerated', 'variant', 'of', 'this', 'method', 'which', 'improves', 'the', 'rate', 'of', 'convergence', 'under', 'convexity', 'assumption', 'furthermore', 'we', 'generalize', 'our', 'results', 'under', 'stochastic', 'setting', 'where', 'only', 'noisy', 'information', 'of', 'both', 'objective', 'functions', 'is', 'available', 'to', 'the', 'best', 'of', 'our', 'knowledge', 'this', 'is', 'the', 'first', 'time', 'that', 'such', 'stochastic', 'approximation', 'algorithms', 'with', 'established', 'iteration', 'complexity', 'sample', 'complexity', 'are', 'provided', 'for', 'bilevel', 'programming']]
[-0.09608500008564443, -0.055915378177305686, -0.09434660800918937, 0.0764962747497484, -0.10340646091848611, -0.1034096070304513, 0.05358235061261803, 0.38939329438656567, -0.3242177769690752, -0.2786965411826968, 0.14377235919144005, -0.20694096346199511, -0.1992771461457014, 0.19276886376738547, -0.1022221752833575, 0.10633394785923883, 0.05849464100599289, -0.00028938257112167776, -0.10543517045956105, -0.32064613865315916, 0.3412409265190363, 0.030115060716867446, 0.22324064561165868, 0.0499758032746613, 0.10793181414529682, 0.017444268852472307, 0.027102119635790588, 0.025850967638194562, -0.1559668500482221, 0.13754055822081865, 0.25206475950032475, 0.22067463585734368, 0.3888120007291436, -0.4186542862278293, -0.15558800625242292, 0.11379568804055452, 0.09284015816031024, 0.05070824574958533, -0.06388667851744685, -0.22426822021603585, 0.0983648662418127, -0.09957116904109717, -0.07403172674402594, -0.04895041462779045, -0.07866644526273012, 0.029186876541003586, -0.3474276591539383, 0.055494309140136464, 0.10138725758064539, 0.043438818225637076, -0.11860731627605856, -0.12833164826780558, 0.08421303023770452, 0.05098912449926138, 0.0832198081407696, 0.04485963653866202, 0.11635950263217092, -0.0750096965059638, -0.08697589923534542, 0.32587258095294236, -0.05709233262948692, -0.2728875006418675, 0.1809722638297826, -0.10626951722800732, -0.19155970926955343, 0.11184421507269145, 0.21888031996809879, 0.21669061579555274, -0.17612057936191558, 0.1131589367100969, -0.09497051880508661, 0.1584883960261941, 0.04582755343988538, 0.037878555335104466, 0.05790351451560855, 0.18917685259506106, 0.19279005246609449, 0.2082123528588563, -0.02342525327578187, -0.13706431549042464, -0.3322221769019961, -0.12812967525795102, -0.19167557648383082, -0.016085389940999447, -0.12596869954001158, -0.15598254127055405, 0.37999891874194147, 0.14488910452276468, 0.13898104225471616, 0.18429688481334597, 0.34732403191924094, 0.1389876158181578, -0.01971120888367295, 0.14755929930880665, 0.2042534538276959, 0.09439042055234313, 0.07790448647737504, -0.22709865479916333, 0.149271733622998, 0.09132367846369743]
1,802.02247
Automatic differentiation of ODE integration
We discuss the calculation of the derivatives of ODE systems with the automatic differentiation tool ADiMat. Using the well-known Lotka-Volterra equations and the ode23 ODE solver as examples we show the analytic derivatives and detail how to differentiate a top-level function that calls ode23 somewhere with ADiMat. This involves the manual construction of substitution function to propagate the derivatives in forward and reverse mode. We also show how to use the reverse mode code to evaluate the Hessian in forward-over-reverse mode.
cs.MS
we discuss the calculation of the derivatives of ode systems with the automatic differentiation tool adimat using the wellknown lotkavolterra equations and the ode23 ode solver as examples we show the analytic derivatives and detail how to differentiate a toplevel function that calls ode23 somewhere with adimat this involves the manual construction of substitution function to propagate the derivatives in forward and reverse mode we also show how to use the reverse mode code to evaluate the hessian in forwardoverreverse mode
[['we', 'discuss', 'the', 'calculation', 'of', 'the', 'derivatives', 'of', 'ode', 'systems', 'with', 'the', 'automatic', 'differentiation', 'tool', 'adimat', 'using', 'the', 'wellknown', 'lotkavolterra', 'equations', 'and', 'the', 'ode23', 'ode', 'solver', 'as', 'examples', 'we', 'show', 'the', 'analytic', 'derivatives', 'and', 'detail', 'how', 'to', 'differentiate', 'a', 'toplevel', 'function', 'that', 'calls', 'ode23', 'somewhere', 'with', 'adimat', 'this', 'involves', 'the', 'manual', 'construction', 'of', 'substitution', 'function', 'to', 'propagate', 'the', 'derivatives', 'in', 'forward', 'and', 'reverse', 'mode', 'we', 'also', 'show', 'how', 'to', 'use', 'the', 'reverse', 'mode', 'code', 'to', 'evaluate', 'the', 'hessian', 'in', 'forwardoverreverse', 'mode']]
[-0.07384215780582867, 0.005030973826682097, -0.07245668933702339, 0.10605447420599184, -0.12798834386232652, -0.09324499898694309, 0.06701677681044921, 0.35057417903781724, -0.31607069388816234, -0.2500317240820119, 0.12762028884792112, -0.2731455707077035, -0.19679889945607437, 0.17235725245585568, -0.01762283774472675, 0.0306563407709626, 0.06283907314125252, 0.004439797693569409, -0.08505353215456891, -0.21653322697813182, 0.3338034045882523, 0.014728825772181153, 0.24012708700090452, 0.04265724802634826, 0.13978313055428626, 0.0017912672881625201, -0.030225671950335566, -0.0636460201778008, -0.13687029726679611, 0.1049020210905981, 0.25853180401885, 0.15677388392597144, 0.27994169134303537, -0.4521994695533067, -0.16894045207108752, 0.055342623706612935, 0.14718625875876137, 0.12299036224813838, -0.028753719323216693, -0.23188296960372673, 0.05691988046869243, -0.17105242117050742, -0.1770472472509075, -0.11984142536101372, -0.03662184400692288, 0.058740276982701435, -0.2619943539703902, 0.046831619646629984, 0.04391529222362136, 0.04949517027278872, -0.036526693325293694, -0.07377131120148606, -0.064278683755363, 0.10559013803293438, 0.08580322931581912, 0.012990120302052483, 0.10070382345829305, -0.09447923533556796, -0.1262367532410855, 0.3526195884853798, -0.11248735927878634, -0.2840346831240152, 0.19750326590024328, -0.13526632472272276, -0.1150744729169865, 0.06759144658663947, 0.1644108053266169, 0.12197934469747308, -0.12829743222774645, 0.06180366200753365, 0.06892996837728117, 0.18592061721229633, 0.0760512807602553, -0.04884658854969434, 0.08824493429672561, 0.12011456825329285, 0.03731468163651267, 0.19774651080737576, -0.034617181965395025, -0.10979836913266856, -0.32976266810835925, -0.23655885236535382, -0.10430902722146129, -0.016012889467866012, -0.07900271976407232, -0.20520709398643752, 0.42680117938863604, 0.19641967742752872, 0.12401465977248001, 0.0766937198595291, 0.32412460566449325, 0.18670846073195876, 0.08221162326241795, 0.05590848912681012, 0.2089670588948617, 0.097160592221802, 0.12349650538281391, -0.24109132993065654, 0.06128529704935653, 0.13355972505738273]
1,802.02248
Tautological classes and smooth bundles over BSU(2)
For a Lie group G and a smooth manifold W, we study the difference between smooth actions of G on W and bundles over the classifying space of G with fiber W and structure group Diff(W). In particular, we exhibit smooth manifold bundles over BSU(2) that are not induced by an action. The main tool for reaching this goal is a technical result that gives a constraint for the values of tautological classes pulled back to the cohomology of BSU(2) along a map induced by an action.
math.AT math.GT
for a lie group g and a smooth manifold w we study the difference between smooth actions of g on w and bundles over the classifying space of g with fiber w and structure group diffw in particular we exhibit smooth manifold bundles over bsu2 that are not induced by an action the main tool for reaching this goal is a technical result that gives a constraint for the values of tautological classes pulled back to the cohomology of bsu2 along a map induced by an action
[['for', 'a', 'lie', 'group', 'g', 'and', 'a', 'smooth', 'manifold', 'w', 'we', 'study', 'the', 'difference', 'between', 'smooth', 'actions', 'of', 'g', 'on', 'w', 'and', 'bundles', 'over', 'the', 'classifying', 'space', 'of', 'g', 'with', 'fiber', 'w', 'and', 'structure', 'group', 'diffw', 'in', 'particular', 'we', 'exhibit', 'smooth', 'manifold', 'bundles', 'over', 'bsu2', 'that', 'are', 'not', 'induced', 'by', 'an', 'action', 'the', 'main', 'tool', 'for', 'reaching', 'this', 'goal', 'is', 'a', 'technical', 'result', 'that', 'gives', 'a', 'constraint', 'for', 'the', 'values', 'of', 'tautological', 'classes', 'pulled', 'back', 'to', 'the', 'cohomology', 'of', 'bsu2', 'along', 'a', 'map', 'induced', 'by', 'an', 'action']]
[-0.19730585596935693, 0.08497335118150913, -0.09471899472436933, -0.018597088407638462, -0.10110175756867541, -0.101042294847714, 0.03350012617315664, 0.4245356094135448, -0.3037576710068902, -0.25570645555853844, 0.07432329829451953, -0.21337534313436685, -0.15452390560490448, 0.24059150056090467, -0.11997913152282667, -0.06955408881710122, 0.07405331613885802, 0.10197547328831671, -0.09633599570952356, -0.24026204223019007, 0.43691934515223946, -0.03845122178236759, 0.22142447531223297, 0.02270237046705429, 0.15368548991851683, 0.009109721275393006, -0.0012419608280842388, 0.010344620154788826, -0.11181902530759459, 0.13949920479641403, 0.2603160899652298, 0.04457287810374658, 0.2467693403217032, -0.32473472055307656, -0.17598385399554012, 0.17785474332590956, 0.05678253158856573, 0.005131967398229726, -0.010409246909507919, -0.30235246057773746, 0.13321281603515842, -0.13476045121341337, -0.11722890641756875, -0.03891095853692224, 0.09953472767631676, -0.018859399636925827, -0.2228696507565558, -0.054233467839874844, 0.08611564956562118, 0.08483856784309758, -0.061929591544592474, -0.051474930723955814, -0.09608435048180264, 0.14061969798599738, 0.021789591767565283, 0.12465687308644573, 0.11903058380689906, -0.13138169223215257, -0.08783486646838314, 0.3950725625767264, -0.15717080896070532, -0.21450552240360615, 0.12596033404169735, -0.13028153102455098, -0.13528504946572317, 0.16337269054032688, 0.13454633686951425, 0.1612142941719571, -0.012986274745429021, 0.13850397546031123, -0.08115765433975083, 0.07340551786622855, 0.049991087354503055, -0.03840734898437594, 0.14808714867374578, 0.14472401350585007, 0.13298710668459535, 0.0888664600287759, -0.015363977369202603, -0.006335707657515656, -0.38449281826615334, -0.20765273993141775, -0.1090480116694126, 0.15013416234128377, -0.07270673307712694, -0.1262159500823378, 0.4126040299130647, 0.01894352150821062, 0.26993324960646936, 0.10146776197997984, 0.2076214123950448, 0.03901710001708463, 0.05582552462772921, 0.05483048711903393, 0.1411891436031045, 0.2207138783861558, -0.06164348392671537, -0.16479836519385233, -0.0216815686503122, 0.1539334427067187]
1,802.02249
Dirac neutrino mixings from hidden $\mu-\tau$ symmetry
We explore masses and mixings for Dirac neutrinos in models where lepton number is conserved, under the guidance of a hidden, but broken, $\mu-\tau$ exchange symmetry, that makes itself evident in the squared hermitian mass matrix. We study the parameter space in the most general theory as allowed by current neutrino oscillation experiment data. By using a general parameterization of the mass matrix which contains only observable parameters we stablish that the amount of breaking of the symmetry is in the range of the atmospheric mass scale, without regard to the neutrino hierarchy, the absolute neutrino mass and the Dirac CP phase. An estimate of the invisible branching ratio for a Higgs boson decaying into Dirac neutrinos, $H\rightarrow\nu\overline{\nu}$ , is given and compared to recent measurements in this context.
hep-ph
we explore masses and mixings for dirac neutrinos in models where lepton number is conserved under the guidance of a hidden but broken mutau exchange symmetry that makes itself evident in the squared hermitian mass matrix we study the parameter space in the most general theory as allowed by current neutrino oscillation experiment data by using a general parameterization of the mass matrix which contains only observable parameters we stablish that the amount of breaking of the symmetry is in the range of the atmospheric mass scale without regard to the neutrino hierarchy the absolute neutrino mass and the dirac cp phase an estimate of the invisible branching ratio for a higgs boson decaying into dirac neutrinos hrightarrownuoverlinenu is given and compared to recent measurements in this context
[['we', 'explore', 'masses', 'and', 'mixings', 'for', 'dirac', 'neutrinos', 'in', 'models', 'where', 'lepton', 'number', 'is', 'conserved', 'under', 'the', 'guidance', 'of', 'a', 'hidden', 'but', 'broken', 'mutau', 'exchange', 'symmetry', 'that', 'makes', 'itself', 'evident', 'in', 'the', 'squared', 'hermitian', 'mass', 'matrix', 'we', 'study', 'the', 'parameter', 'space', 'in', 'the', 'most', 'general', 'theory', 'as', 'allowed', 'by', 'current', 'neutrino', 'oscillation', 'experiment', 'data', 'by', 'using', 'a', 'general', 'parameterization', 'of', 'the', 'mass', 'matrix', 'which', 'contains', 'only', 'observable', 'parameters', 'we', 'stablish', 'that', 'the', 'amount', 'of', 'breaking', 'of', 'the', 'symmetry', 'is', 'in', 'the', 'range', 'of', 'the', 'atmospheric', 'mass', 'scale', 'without', 'regard', 'to', 'the', 'neutrino', 'hierarchy', 'the', 'absolute', 'neutrino', 'mass', 'and', 'the', 'dirac', 'cp', 'phase', 'an', 'estimate', 'of', 'the', 'invisible', 'branching', 'ratio', 'for', 'a', 'higgs', 'boson', 'decaying', 'into', 'dirac', 'neutrinos', 'hrightarrownuoverlinenu', 'is', 'given', 'and', 'compared', 'to', 'recent', 'measurements', 'in', 'this', 'context']]
[-0.12207489309595956, 0.2657544258236014, 0.00395483860570028, 0.1512160226061031, -0.100369737025233, -0.12191411420724935, 0.06182611302754981, 0.30900034970625884, -0.22512842698011723, -0.3233825715596047, 0.0655351232574138, -0.26867715131095427, -0.06332016588504037, 0.1265869431388308, 0.02213656416118849, 0.06475134209022072, 0.04295101492687708, 0.0368433129042387, -0.13230369205029285, -0.18713109349413942, 0.3433626282146186, 0.056097534650159396, 0.22523260541905568, 0.04332473439917951, 0.0892671914734533, -0.01297756210042853, -0.035222298832331585, -0.08219915932419299, -0.09768775662860565, 0.030500455089390102, 0.16513972862855203, 0.10759164699844605, 0.11594033110740147, -0.35366506594431213, -0.16260703097970233, 0.18920978224711624, 0.1465626822373881, 0.09320685753917805, -0.1080248781267231, -0.3159165232786982, 0.04833764253609528, -0.18673228667902314, -0.13019977314177694, -0.04729994300818877, -0.024869049972612557, -0.11584498224537966, -0.3380303761855824, 0.1125036872681377, -0.045375786685040144, -0.002258810218364939, -0.025994915550017334, -0.14582538274831805, -0.06632971340849057, 0.05753411270135383, 0.17139198307835268, -0.02593938401060575, 0.10235649764567144, -0.16914935732296096, -0.06484581682259055, 0.44739437323268944, -0.0857506679997992, -0.1946761512608216, 0.0993159988081068, -0.1721601694250318, -0.14313616719478228, 0.11816650951706519, 0.18631917413500115, 0.0454277450138131, -0.17947929791050163, 0.15623100142143154, -0.11984126021953549, 0.1789079115022062, 0.02703488738125733, 0.024122255155816674, 0.2554503512664104, 0.19427501885532072, 0.10354518096923358, -0.0008895280734291227, -0.08889271647808707, -0.07322612854168112, -0.36467686374708425, -0.1551279377074927, -0.16152230322848654, 0.06923084587636073, -0.08818996693367435, -0.10883540470945084, 0.4474566680907206, 0.1499894455251262, 0.2533913472242008, 0.027420226210456956, 0.2723412200273198, 0.10698871987534496, 0.09944712397033774, 0.01829918279994543, 0.2997482825312617, 0.1766199707466097, 0.11429052269379572, -0.2544171656225258, 0.01669368775484453, 0.07456094853022671]
1,802.0225
Atmospheric reconnaissance of the habitable-zone Earth-sized planets orbiting TRAPPIST-1
Seven temperate Earth-sized exoplanets readily amenable for atmospheric studies transit the nearby ultracool dwarf star TRAPPIST-1 (refs 1,2). Their atmospheric regime is unknown and could range from extended primordial hydrogen-dominated to depleted atmospheres (refs 3-6). Hydrogen in particular is a powerful greenhouse gas that may prevent the habitability of inner planets while enabling the habitability of outer ones (refs 6-8). An atmosphere largely dominated by hydrogen, if cloud-free, should yield prominent spectroscopic signatures in the near-infrared detectable during transits. Observations of the innermost planets have ruled out such signatures (ref 9). However, the outermost planets are more likely to have sustained such a Neptune-like atmosphere (refs 10,11). Here, we report observations for the four planets within or near the system's habitable zone, the circumstellar region where liquid water could exist on a planetary surface (refs 12-14). These planets do not exhibit prominent spectroscopic signatures at near-infrared wavelengths either, which rules out cloud-free hydrogen-dominated atmospheres for TRAPPIST-1 d, e and f, with significance of 8, 6 and 4 sigma, respectively. Such an atmosphere is instead not excluded for planet g. As high-altitude clouds and hazes are not expected in hydrogen-dominated atmospheres around planets with such insolation (refs 15,16), these observations further support their terrestrial and potentially habitable nature.
astro-ph.EP
seven temperate earthsized exoplanets readily amenable for atmospheric studies transit the nearby ultracool dwarf star trappist1 refs 12 their atmospheric regime is unknown and could range from extended primordial hydrogendominated to depleted atmospheres refs 36 hydrogen in particular is a powerful greenhouse gas that may prevent the habitability of inner planets while enabling the habitability of outer ones refs 68 an atmosphere largely dominated by hydrogen if cloudfree should yield prominent spectroscopic signatures in the nearinfrared detectable during transits observations of the innermost planets have ruled out such signatures ref 9 however the outermost planets are more likely to have sustained such a neptunelike atmosphere refs 1011 here we report observations for the four planets within or near the systems habitable zone the circumstellar region where liquid water could exist on a planetary surface refs 1214 these planets do not exhibit prominent spectroscopic signatures at nearinfrared wavelengths either which rules out cloudfree hydrogendominated atmospheres for trappist1 d e and f with significance of 8 6 and 4 sigma respectively such an atmosphere is instead not excluded for planet g as highaltitude clouds and hazes are not expected in hydrogendominated atmospheres around planets with such insolation refs 1516 these observations further support their terrestrial and potentially habitable nature
[['seven', 'temperate', 'earthsized', 'exoplanets', 'readily', 'amenable', 'for', 'atmospheric', 'studies', 'transit', 'the', 'nearby', 'ultracool', 'dwarf', 'star', 'trappist1', 'refs', '12', 'their', 'atmospheric', 'regime', 'is', 'unknown', 'and', 'could', 'range', 'from', 'extended', 'primordial', 'hydrogendominated', 'to', 'depleted', 'atmospheres', 'refs', '36', 'hydrogen', 'in', 'particular', 'is', 'a', 'powerful', 'greenhouse', 'gas', 'that', 'may', 'prevent', 'the', 'habitability', 'of', 'inner', 'planets', 'while', 'enabling', 'the', 'habitability', 'of', 'outer', 'ones', 'refs', '68', 'an', 'atmosphere', 'largely', 'dominated', 'by', 'hydrogen', 'if', 'cloudfree', 'should', 'yield', 'prominent', 'spectroscopic', 'signatures', 'in', 'the', 'nearinfrared', 'detectable', 'during', 'transits', 'observations', 'of', 'the', 'innermost', 'planets', 'have', 'ruled', 'out', 'such', 'signatures', 'ref', '9', 'however', 'the', 'outermost', 'planets', 'are', 'more', 'likely', 'to', 'have', 'sustained', 'such', 'a', 'neptunelike', 'atmosphere', 'refs', '1011', 'here', 'we', 'report', 'observations', 'for', 'the', 'four', 'planets', 'within', 'or', 'near', 'the', 'systems', 'habitable', 'zone', 'the', 'circumstellar', 'region', 'where', 'liquid', 'water', 'could', 'exist', 'on', 'a', 'planetary', 'surface', 'refs', '1214', 'these', 'planets', 'do', 'not', 'exhibit', 'prominent', 'spectroscopic', 'signatures', 'at', 'nearinfrared', 'wavelengths', 'either', 'which', 'rules', 'out', 'cloudfree', 'hydrogendominated', 'atmospheres', 'for', 'trappist1', 'd', 'e', 'and', 'f', 'with', 'significance', 'of', '8', '6', 'and', '4', 'sigma', 'respectively', 'such', 'an', 'atmosphere', 'is', 'instead', 'not', 'excluded', 'for', 'planet', 'g', 'as', 'highaltitude', 'clouds', 'and', 'hazes', 'are', 'not', 'expected', 'in', 'hydrogendominated', 'atmospheres', 'around', 'planets', 'with', 'such', 'insolation', 'refs', '1516', 'these', 'observations', 'further', 'support', 'their', 'terrestrial', 'and', 'potentially', 'habitable', 'nature']]
[-0.0918464521888153, 0.22242485552225913, -0.00047069032348080536, 0.08469022723906876, -0.11209268865944899, -0.0852824284353154, 0.13033554417301635, 0.3439411037069507, -0.11001054292425495, -0.3595009783197392, 0.12293746568552771, -0.29692265547919966, -0.09870500536972954, 0.21370073384099195, -0.078052603723037, 0.017848077768365434, 0.14096533596529154, -0.10760324981832958, 0.012065852894661453, -0.29530994201771876, 0.23353448127742837, 0.10409708432054623, -0.05774706189806353, 0.025229715315560678, -0.0782751766424896, -0.15011584676930384, -0.03738340682008164, -0.12055583047154157, -0.20929042732299913, -0.02107602660206781, 0.30351669632420303, 0.09608969243990194, 0.17309268647669881, -0.4290320727083346, -0.31352102290389045, 0.09014946756877285, 0.18527307280885946, -0.023768452616466956, -0.01148922333094811, -0.2531026977064889, 0.061443197531940566, -0.190520151918709, -0.19580623289966137, 0.01294206672658523, 0.10256158798744065, -0.07806049760502475, -0.25905599002726376, 0.05077113891650297, 0.07020137120985341, 0.21219765100175975, -0.1503782989749694, -0.22228478492296116, -0.12101961931681647, 0.04514467846017313, -0.06261274968622621, -0.011637661642066522, 0.23039983851826135, -0.05780660673067118, 0.01798915625707323, 0.41886315272518115, -0.15035982148616084, 0.0032991707046034833, 0.33447516566943286, -0.2448607419475751, -0.14767039236770088, 0.21059908844746542, 0.1195827202246061, 0.13892653440732672, -0.18184232083261734, 0.008266232706716618, -0.046048043313597055, 0.1860172679098908, 0.12967729209562323, 0.06141154574014354, 0.4856697288757991, 0.11559601464637236, 0.07372475947041947, -0.033022528514266014, -0.2683629401664785, -0.022414050820836987, -0.15622065716607558, -0.13416792465326632, -0.1077094623989961, 0.05037003737481498, -0.04624659074030328, -0.1067426447921932, 0.3053100243039825, 0.15381358695977956, 0.11289809549754319, -0.02153818411325163, 0.27700582693965325, 0.040648579403447606, 0.09907229036360035, 0.13514311454069894, 0.37147444168753596, 0.12446639358947854, 0.08352798866760436, -0.2012055792206345, 0.09905570567527039, -0.049467038353235834]
1,802.02251
An Imputation-Consistency Algorithm for High-Dimensional Missing Data Problems and Beyond
Missing data are frequently encountered in high-dimensional problems, but they are usually difficult to deal with using standard algorithms, such as the expectation-maximization (EM) algorithm and its variants. To tackle this difficulty, some problem-specific algorithms have been developed in the literature, but there still lacks a general algorithm. This work is to fill the gap: we propose a general algorithm for high-dimensional missing data problems. The proposed algorithm works by iterating between an imputation step and a consistency step. At the imputation step, the missing data are imputed conditional on the observed data and the current estimate of parameters; and at the consistency step, a consistent estimate is found for the minimizer of a Kullback-Leibler divergence defined on the pseudo-complete data. For high dimensional problems, the consistent estimate can be found under sparsity constraints. The consistency of the averaged estimate for the true parameter can be established under quite general conditions. The proposed algorithm is illustrated using high-dimensional Gaussian graphical models, high-dimensional variable selection, and a random coefficient model.
stat.ME
missing data are frequently encountered in highdimensional problems but they are usually difficult to deal with using standard algorithms such as the expectationmaximization em algorithm and its variants to tackle this difficulty some problemspecific algorithms have been developed in the literature but there still lacks a general algorithm this work is to fill the gap we propose a general algorithm for highdimensional missing data problems the proposed algorithm works by iterating between an imputation step and a consistency step at the imputation step the missing data are imputed conditional on the observed data and the current estimate of parameters and at the consistency step a consistent estimate is found for the minimizer of a kullbackleibler divergence defined on the pseudocomplete data for high dimensional problems the consistent estimate can be found under sparsity constraints the consistency of the averaged estimate for the true parameter can be established under quite general conditions the proposed algorithm is illustrated using highdimensional gaussian graphical models highdimensional variable selection and a random coefficient model
[['missing', 'data', 'are', 'frequently', 'encountered', 'in', 'highdimensional', 'problems', 'but', 'they', 'are', 'usually', 'difficult', 'to', 'deal', 'with', 'using', 'standard', 'algorithms', 'such', 'as', 'the', 'expectationmaximization', 'em', 'algorithm', 'and', 'its', 'variants', 'to', 'tackle', 'this', 'difficulty', 'some', 'problemspecific', 'algorithms', 'have', 'been', 'developed', 'in', 'the', 'literature', 'but', 'there', 'still', 'lacks', 'a', 'general', 'algorithm', 'this', 'work', 'is', 'to', 'fill', 'the', 'gap', 'we', 'propose', 'a', 'general', 'algorithm', 'for', 'highdimensional', 'missing', 'data', 'problems', 'the', 'proposed', 'algorithm', 'works', 'by', 'iterating', 'between', 'an', 'imputation', 'step', 'and', 'a', 'consistency', 'step', 'at', 'the', 'imputation', 'step', 'the', 'missing', 'data', 'are', 'imputed', 'conditional', 'on', 'the', 'observed', 'data', 'and', 'the', 'current', 'estimate', 'of', 'parameters', 'and', 'at', 'the', 'consistency', 'step', 'a', 'consistent', 'estimate', 'is', 'found', 'for', 'the', 'minimizer', 'of', 'a', 'kullbackleibler', 'divergence', 'defined', 'on', 'the', 'pseudocomplete', 'data', 'for', 'high', 'dimensional', 'problems', 'the', 'consistent', 'estimate', 'can', 'be', 'found', 'under', 'sparsity', 'constraints', 'the', 'consistency', 'of', 'the', 'averaged', 'estimate', 'for', 'the', 'true', 'parameter', 'can', 'be', 'established', 'under', 'quite', 'general', 'conditions', 'the', 'proposed', 'algorithm', 'is', 'illustrated', 'using', 'highdimensional', 'gaussian', 'graphical', 'models', 'highdimensional', 'variable', 'selection', 'and', 'a', 'random', 'coefficient', 'model']]
[-0.04015009616047055, 0.0067278012354238725, -0.08960922351217873, 0.16500024675250252, -0.10038656975597232, -0.17657218203558364, 0.04624412908396196, 0.40552347166729824, -0.27954216765716583, -0.34009086358959656, 0.1610849084501665, -0.2235392321738237, -0.12923181917479573, 0.18060676018164182, -0.12402538040797004, 0.15062663567749995, 0.10927358082941889, 0.01954374151093708, -0.06499837102559727, -0.2862385322029392, 0.29152795198717196, 0.05751277936810982, 0.30300077615400023, -0.026372353463860538, 0.13652859679132234, -0.008895846776708606, -0.05272392203776343, 0.05057859046029903, -0.1106223516787092, 0.13351670396133114, 0.28373547367172725, 0.15610107585893102, 0.3439241431243274, -0.38689055026181796, -0.22455673912052243, 0.13806829386435093, 0.13982012896477022, 0.11655083830035957, -0.029866411777523656, -0.27110993227965774, 0.07722096297324502, -0.09914993035064461, -0.07289025354077153, -0.11684907359137599, -0.0480252215527885, -0.024717524187595007, -0.37231580599577035, 0.12333444690808565, 0.03195206536440223, 0.04178854821449412, -0.04278534688013939, -0.15050503155119563, 0.03816521795843506, 0.08448936427122958, 0.08911927414772522, 0.049259526583011304, 0.07141666537305962, -0.10868174605227632, -0.1289389287551222, 0.35421501618388684, -0.007315876444668642, -0.24019602387921796, 0.16527788360725112, -0.05867043217100824, -0.19400963448528533, 0.09744252686366617, 0.18332259340621976, 0.11214035569546035, -0.18754704242261747, 0.09513164803190323, -0.041744907874436604, 0.11830371798714623, 0.01361646001307582, -0.022857286605271622, 0.12477672055718445, 0.16865702015015163, 0.07703821927758067, 0.12126385122870229, -0.11737453629792158, -0.08605235904577144, -0.27300358922886, -0.09739570543163045, -0.25312582589685917, -0.06872303580721131, -0.128068021678354, -0.1690054629600906, 0.3576533781888429, 0.19365842942352174, 0.24535177502409733, 0.085248618867592, 0.32769241290433065, 0.1437107505868577, 0.059493336289527916, 0.10426012992892149, 0.2010132640988602, 0.11199119549738021, 0.08627684131663825, -0.15833786726995772, 0.16801107306188592, 0.019487941159500873]
1,802.02252
Constraining Type Ia Supernova Progenitor Scenarios with Extremely Late-time Photometry of Supernova SN 2013aa
We present Hubble Space Telescope observations and photometric measurements of the Type Ia supernova (SN Ia) SN 2013aa 1500 days after explosion. At this epoch, the luminosity is primarily dictated by the amounts of radioactive ${}^{57}\textrm{Co}$ and ${}^{55}\textrm{Fe}$, while at earlier epochs, the luminosity depends on the amount of radioactive ${}^{56}\textrm{Co}$. The ratio of odd-numbered to even-numbered isotopes depends significantly on the density of the progenitor white dwarf during the SN explosion, which, in turn, depends on the details of the progenitor system at the time of ignition. From a comprehensive analysis of the entire light curve of SN 2013aa, we measure a $M({}^{57}\textrm{Co})/M({}^{56}\textrm{Co})$ ratio of $0.02^{+0.01}_{-0.02}$, which indicates a relatively low central density for the progenitor white dwarf at the time of explosion, consistent with double-degenerate progenitor channels. We estimate $M({}^{56}\textrm{Ni}) = 0.732 \pm 0.151\:\mathrm{M_{\odot}}$, and place an upper limit on the abundance of ${}^{55}\textrm{Fe}$. A recent study reported a possible correlation between $M({}^{57}\textrm{Co})/M({}^{56}\textrm{Co})$ and stretch for four SNe Ia. SN 2013aa, however, does not fit this trend, indicating either SN 2013aa is an extreme outlier or the correlation does not hold up with a larger sample. The $M({}^{57}\textrm{Co})/M({}^{56}\textrm{Co})$ measured for the expanded sample of SNe Ia with photometry at extremely late times has a much larger range than that of explosion models, perhaps limiting conclusions about SN Ia progenitors drawn from extremely late-time photometry.
astro-ph.HE
we present hubble space telescope observations and photometric measurements of the type ia supernova sn ia sn 2013aa 1500 days after explosion at this epoch the luminosity is primarily dictated by the amounts of radioactive 57textrmco and 55textrmfe while at earlier epochs the luminosity depends on the amount of radioactive 56textrmco the ratio of oddnumbered to evennumbered isotopes depends significantly on the density of the progenitor white dwarf during the sn explosion which in turn depends on the details of the progenitor system at the time of ignition from a comprehensive analysis of the entire light curve of sn 2013aa we measure a m57textrmcom56textrmco ratio of 002001_002 which indicates a relatively low central density for the progenitor white dwarf at the time of explosion consistent with doubledegenerate progenitor channels we estimate m56textrmni 0732 pm 0151mathrmm_odot and place an upper limit on the abundance of 55textrmfe a recent study reported a possible correlation between m57textrmcom56textrmco and stretch for four sne ia sn 2013aa however does not fit this trend indicating either sn 2013aa is an extreme outlier or the correlation does not hold up with a larger sample the m57textrmcom56textrmco measured for the expanded sample of sne ia with photometry at extremely late times has a much larger range than that of explosion models perhaps limiting conclusions about sn ia progenitors drawn from extremely latetime photometry
[['we', 'present', 'hubble', 'space', 'telescope', 'observations', 'and', 'photometric', 'measurements', 'of', 'the', 'type', 'ia', 'supernova', 'sn', 'ia', 'sn', '2013aa', '1500', 'days', 'after', 'explosion', 'at', 'this', 'epoch', 'the', 'luminosity', 'is', 'primarily', 'dictated', 'by', 'the', 'amounts', 'of', 'radioactive', '57textrmco', 'and', '55textrmfe', 'while', 'at', 'earlier', 'epochs', 'the', 'luminosity', 'depends', 'on', 'the', 'amount', 'of', 'radioactive', '56textrmco', 'the', 'ratio', 'of', 'oddnumbered', 'to', 'evennumbered', 'isotopes', 'depends', 'significantly', 'on', 'the', 'density', 'of', 'the', 'progenitor', 'white', 'dwarf', 'during', 'the', 'sn', 'explosion', 'which', 'in', 'turn', 'depends', 'on', 'the', 'details', 'of', 'the', 'progenitor', 'system', 'at', 'the', 'time', 'of', 'ignition', 'from', 'a', 'comprehensive', 'analysis', 'of', 'the', 'entire', 'light', 'curve', 'of', 'sn', '2013aa', 'we', 'measure', 'a', 'm57textrmcom56textrmco', 'ratio', 'of', '002001_002', 'which', 'indicates', 'a', 'relatively', 'low', 'central', 'density', 'for', 'the', 'progenitor', 'white', 'dwarf', 'at', 'the', 'time', 'of', 'explosion', 'consistent', 'with', 'doubledegenerate', 'progenitor', 'channels', 'we', 'estimate', 'm56textrmni', '0732', 'pm', '0151mathrmm_odot', 'and', 'place', 'an', 'upper', 'limit', 'on', 'the', 'abundance', 'of', '55textrmfe', 'a', 'recent', 'study', 'reported', 'a', 'possible', 'correlation', 'between', 'm57textrmcom56textrmco', 'and', 'stretch', 'for', 'four', 'sne', 'ia', 'sn', '2013aa', 'however', 'does', 'not', 'fit', 'this', 'trend', 'indicating', 'either', 'sn', '2013aa', 'is', 'an', 'extreme', 'outlier', 'or', 'the', 'correlation', 'does', 'not', 'hold', 'up', 'with', 'a', 'larger', 'sample', 'the', 'm57textrmcom56textrmco', 'measured', 'for', 'the', 'expanded', 'sample', 'of', 'sne', 'ia', 'with', 'photometry', 'at', 'extremely', 'late', 'times', 'has', 'a', 'much', 'larger', 'range', 'than', 'that', 'of', 'explosion', 'models', 'perhaps', 'limiting', 'conclusions', 'about', 'sn', 'ia', 'progenitors', 'drawn', 'from', 'extremely', 'latetime', 'photometry']]
[-0.03845360509649671, 0.08616229667610792, -0.06841303157265546, 0.0832157996055935, -0.09208204094993395, -0.11909867210314745, 0.11885384628693402, 0.3857501425028462, -0.12761507038915648, -0.30138427475595486, 0.07676958469428344, -0.3209939101772861, 0.01021275641647629, 0.2198675246914601, -0.05372455136619782, -0.0731063071401243, 0.1526736364904962, -0.03842339220343568, -0.15397573172231205, -0.330107491647124, 0.29151968548016693, 0.10764595287944909, 0.22703141187650894, -0.054438265969703366, 0.07668101085417203, -0.08818245648487616, -0.07159412739405391, -0.09034861747398139, -0.16209214228999597, 0.010048296359162608, 0.16978618036797058, 0.1671195895658857, 0.18160000720292058, -0.360596038255541, -0.2462390484929153, 0.15115892413764373, 0.21954246282838114, 0.06373087504511238, -0.03734080691035803, -0.24060707391931788, 0.05964339591579836, -0.18669994016297572, -0.13222931140239155, 0.14234657320081803, 0.06811344208667541, 0.03833144240748346, -0.24045846786044556, 0.14470841467739382, 0.014000884958953007, 0.07711056882497927, -0.09565342971392898, -0.12270251842463441, -0.04367637661405318, -0.010808988088750443, 0.05708536279490303, 0.03875183858887352, 0.07077744033042375, -0.11565554935544935, 0.07727923951274075, 0.4063630344804351, -0.06402599277038078, 0.06975683908153393, 0.19838115663204658, -0.18175683603109366, -0.13257009060113528, 0.17032638570900424, 0.15276160876457837, 0.08348063105789927, -0.15493157997923912, -0.014679072648922297, 0.02817847240404354, 0.1923160191642445, 0.03312586818676476, 0.07993177218307819, 0.27999243698159765, 0.1799331470312542, 0.02930923635375028, 0.021973898625236278, -0.22161781849524373, 0.018930248672371183, -0.2762919896700924, -0.09537396449894739, -0.19277390979397016, 0.19046817182783793, -0.18190641013489942, -0.13409158869669452, 0.3507949942103459, 0.06731640879457834, 0.23835433018500618, 0.02825248714028046, 0.23519402184446744, 0.06594531585402581, 0.10315315605198896, 0.08336201902807887, 0.3214997551831152, 0.15555832757071994, 0.13229205216592982, -0.25031585045107596, 0.14925445575713514, 0.009604284948874435]
1,802.02253
Reconfigurable topological phases in next-nearest-neighbor coupled resonator lattices
We present a reconfigurable topological photonic system consisting of a 2D lattice of coupled ring resonators, with two sublattices of site rings coupled by link rings, which can be accurately described by a tight-binding model. Unlike previous coupled-ring topological models, the design is translationally invariant, similar to the Haldane model, and the nontrivial topology is a result of next-nearest couplings with non-zero staggered phases. The system exhibits a topological phase transition between trivial and spin Chern insulator phases when the sublattices are frequency detuned. Such topological phase transitions can be easily induced by thermal or electro-optic modulators, or nonlinear cross phase modulation. We use this lattice to design reconfigurable topological waveguides, with potential applications in on-chip photon routing and switching.
physics.optics cond-mat.mes-hall quant-ph
we present a reconfigurable topological photonic system consisting of a 2d lattice of coupled ring resonators with two sublattices of site rings coupled by link rings which can be accurately described by a tightbinding model unlike previous coupledring topological models the design is translationally invariant similar to the haldane model and the nontrivial topology is a result of nextnearest couplings with nonzero staggered phases the system exhibits a topological phase transition between trivial and spin chern insulator phases when the sublattices are frequency detuned such topological phase transitions can be easily induced by thermal or electrooptic modulators or nonlinear cross phase modulation we use this lattice to design reconfigurable topological waveguides with potential applications in onchip photon routing and switching
[['we', 'present', 'a', 'reconfigurable', 'topological', 'photonic', 'system', 'consisting', 'of', 'a', '2d', 'lattice', 'of', 'coupled', 'ring', 'resonators', 'with', 'two', 'sublattices', 'of', 'site', 'rings', 'coupled', 'by', 'link', 'rings', 'which', 'can', 'be', 'accurately', 'described', 'by', 'a', 'tightbinding', 'model', 'unlike', 'previous', 'coupledring', 'topological', 'models', 'the', 'design', 'is', 'translationally', 'invariant', 'similar', 'to', 'the', 'haldane', 'model', 'and', 'the', 'nontrivial', 'topology', 'is', 'a', 'result', 'of', 'nextnearest', 'couplings', 'with', 'nonzero', 'staggered', 'phases', 'the', 'system', 'exhibits', 'a', 'topological', 'phase', 'transition', 'between', 'trivial', 'and', 'spin', 'chern', 'insulator', 'phases', 'when', 'the', 'sublattices', 'are', 'frequency', 'detuned', 'such', 'topological', 'phase', 'transitions', 'can', 'be', 'easily', 'induced', 'by', 'thermal', 'or', 'electrooptic', 'modulators', 'or', 'nonlinear', 'cross', 'phase', 'modulation', 'we', 'use', 'this', 'lattice', 'to', 'design', 'reconfigurable', 'topological', 'waveguides', 'with', 'potential', 'applications', 'in', 'onchip', 'photon', 'routing', 'and', 'switching']]
[-0.2744664116956604, 0.261646607198054, -0.021050284919328987, -0.04850435538003997, -0.06724811484261105, -0.2775285739723283, 0.05158503446727991, 0.4621963229806473, -0.25654384853163115, -0.241058917894649, 0.032061821908185566, -0.2868566559317211, -0.20125638045137748, 0.13387712298814827, 0.022942156059434636, 0.05868537228088826, -0.026442473214895776, -0.08251298919397716, -0.09411768230687206, -0.18652005451731385, 0.27161982473917307, -0.043756550449567534, 0.3081315767252818, 0.022242882962261016, 0.0330370098517354, -0.02685930348622302, 0.12561066271931243, 0.012573025527914675, -0.13662513663681844, 0.07105158184034129, 0.25148448251557054, -0.11888334608908432, 0.09962493970524519, -0.43878264429513364, -0.22441468487377278, 0.06730901004630141, 0.10540153940867943, 0.14054042751571008, -0.044868197235822055, -0.3476805643644184, 0.03808652620452146, -0.21677413148184618, -0.0937872914907833, -0.1289237236759315, -0.021338471102838714, 0.010196943526777129, -0.23297748280262265, 0.023350662792411943, 0.059132839925587176, 0.07740454708303636, -0.014001676948585859, -0.03644504146844459, -0.09560291450858736, 0.03635809916231665, -0.06603651842936718, 0.03028502662588532, 0.11588175921933726, -0.09247248714285282, -0.2122852055549932, 0.4085351064025114, -0.06921807202743366, -0.17031688977925416, 0.1577826677200695, -0.09749934048959404, -0.04509046482659566, 0.14571836560498924, 0.1268092841026373, 0.06218875466535489, -0.09499577693798832, 0.08088907043232514, 0.006781797813406835, 0.2149347274234363, 0.023146990250097588, 0.10384456561102222, 0.31465931637988737, 0.19377152780264925, 0.096249725145996, 0.21483571822172962, -0.04420590084434176, -0.10246573659048105, -0.23198860810759167, -0.1599326958724608, -0.2505318300294069, 0.05823312940774485, -0.07920603079607341, -0.1955253920207421, 0.4702783409661303, 0.11639121434612511, 0.15448149462463334, -0.05434971202533537, 0.30375333320116626, 0.13138306361312668, 0.09408063982458165, -0.0024579693640892704, 0.2114179525213937, 0.17227666599404376, 0.07601990250404925, -0.23502005018332664, -0.024886089268450935, 0.08157995773750978]
1,802.02254
Trajectory-driven Influential Billboard Placement
In this paper we propose and study the problem of trajectory-driven influential billboard placement: given a set of billboards $U$ (each with a location and a cost), a database of trajectories $\mathcal{T}$ and a budget $L$, find a set of billboards within the budget to influence the largest number of trajectories. One core challenge is to identify and reduce the overlap of the influence from different billboards to the same trajectories, while keeping the budget constraint into consideration. We show that this problem is NP-hard and present an enumeration based algorithm with $(1-1/e)$ approximation ratio. However, the enumeration should be very costly when $|U|$ is large. By exploiting the locality property of billboards' influence, we propose a partition-based framework PartSel. PartSel partitions $U$ into a set of small clusters, computes the locally influential billboards for each cluster, and merges them to generate the global solution. Since the local solutions can be obtained much more efficient than the global one, PartSel should reduce the computation cost greatly; meanwhile it achieves a non-trivial approximation ratio guarantee. Then we propose a LazyProbe method to further prune billboards with low marginal influence, while achieving the same approximation ratio as PartSel. Experiments on real datasets verify the efficiency and effectiveness of our methods.
cs.SI cs.DB
in this paper we propose and study the problem of trajectorydriven influential billboard placement given a set of billboards u each with a location and a cost a database of trajectories mathcalt and a budget l find a set of billboards within the budget to influence the largest number of trajectories one core challenge is to identify and reduce the overlap of the influence from different billboards to the same trajectories while keeping the budget constraint into consideration we show that this problem is nphard and present an enumeration based algorithm with 11e approximation ratio however the enumeration should be very costly when u is large by exploiting the locality property of billboards influence we propose a partitionbased framework partsel partsel partitions u into a set of small clusters computes the locally influential billboards for each cluster and merges them to generate the global solution since the local solutions can be obtained much more efficient than the global one partsel should reduce the computation cost greatly meanwhile it achieves a nontrivial approximation ratio guarantee then we propose a lazyprobe method to further prune billboards with low marginal influence while achieving the same approximation ratio as partsel experiments on real datasets verify the efficiency and effectiveness of our methods
[['in', 'this', 'paper', 'we', 'propose', 'and', 'study', 'the', 'problem', 'of', 'trajectorydriven', 'influential', 'billboard', 'placement', 'given', 'a', 'set', 'of', 'billboards', 'u', 'each', 'with', 'a', 'location', 'and', 'a', 'cost', 'a', 'database', 'of', 'trajectories', 'mathcalt', 'and', 'a', 'budget', 'l', 'find', 'a', 'set', 'of', 'billboards', 'within', 'the', 'budget', 'to', 'influence', 'the', 'largest', 'number', 'of', 'trajectories', 'one', 'core', 'challenge', 'is', 'to', 'identify', 'and', 'reduce', 'the', 'overlap', 'of', 'the', 'influence', 'from', 'different', 'billboards', 'to', 'the', 'same', 'trajectories', 'while', 'keeping', 'the', 'budget', 'constraint', 'into', 'consideration', 'we', 'show', 'that', 'this', 'problem', 'is', 'nphard', 'and', 'present', 'an', 'enumeration', 'based', 'algorithm', 'with', '11e', 'approximation', 'ratio', 'however', 'the', 'enumeration', 'should', 'be', 'very', 'costly', 'when', 'u', 'is', 'large', 'by', 'exploiting', 'the', 'locality', 'property', 'of', 'billboards', 'influence', 'we', 'propose', 'a', 'partitionbased', 'framework', 'partsel', 'partsel', 'partitions', 'u', 'into', 'a', 'set', 'of', 'small', 'clusters', 'computes', 'the', 'locally', 'influential', 'billboards', 'for', 'each', 'cluster', 'and', 'merges', 'them', 'to', 'generate', 'the', 'global', 'solution', 'since', 'the', 'local', 'solutions', 'can', 'be', 'obtained', 'much', 'more', 'efficient', 'than', 'the', 'global', 'one', 'partsel', 'should', 'reduce', 'the', 'computation', 'cost', 'greatly', 'meanwhile', 'it', 'achieves', 'a', 'nontrivial', 'approximation', 'ratio', 'guarantee', 'then', 'we', 'propose', 'a', 'lazyprobe', 'method', 'to', 'further', 'prune', 'billboards', 'with', 'low', 'marginal', 'influence', 'while', 'achieving', 'the', 'same', 'approximation', 'ratio', 'as', 'partsel', 'experiments', 'on', 'real', 'datasets', 'verify', 'the', 'efficiency', 'and', 'effectiveness', 'of', 'our', 'methods']]
[-0.12648346335615837, 0.02618534236676478, -0.0702336465892409, 0.05473766965142822, -0.08361801560470852, -0.12349451515480007, 0.1266904878469627, 0.3411415946303677, -0.2742763145112442, -0.34659429998091845, 0.08846708752742734, -0.2714913061951927, -0.12425626104797047, 0.13558607267948247, -0.05223664051716926, 0.04065015371777264, 0.10352865822197309, 0.04467912566920435, -0.05475612073736627, -0.28703849194842634, 0.2766209611555028, 0.06691493007164558, 0.3007891773770663, 0.04382199048995972, 0.11035464646733248, -0.0031238469697571205, -0.0161571838978895, 0.07387462760817974, -0.08757462287910121, 0.13180388788521985, 0.22859711841300348, 0.18189651354270292, 0.3438483766433828, -0.39832249868381997, -0.1466062271332332, 0.13403778584918133, 0.14201331074864973, 0.08698964310710791, -0.024289465121468824, -0.2480756509913475, 0.1416060380248841, -0.14713155916774445, -0.0732634588849993, -0.07259585316184437, 0.01878333966885196, 0.010279198748780667, -0.3021117237688142, 0.019674625830923758, 0.010690308720194419, -0.026959819330390798, -0.0539871568597166, -0.1266826920559431, 0.00045053201085589465, 0.14423006107915956, 0.030500840642789007, 0.05529296675751221, 0.1038587213789443, -0.12009672149512872, -0.06856278097483068, 0.41848381453202765, -0.021644169500098197, -0.2259002374281691, 0.14673926485973654, -0.09738479088087684, -0.13742383261373972, 0.1285108575457255, 0.1916340881499724, 0.1418474152666128, -0.13339777551152013, 0.06651011143414896, -0.05653117992886957, 0.17409898767482887, 0.055247728905281124, 0.026664109292521495, 0.15735253752254455, 0.18919000472224687, 0.14467543183862078, 0.170535863272041, -0.08255281417986075, -0.07207010015031522, -0.24255774919965387, -0.12804820165105923, -0.1700904858993701, 0.008423993596807122, -0.11059216499839766, -0.15220871231025898, 0.3785436733408822, 0.17110977233704, 0.22830797059380098, 0.1116509007875473, 0.3076020739836962, 0.10094121142901713, 0.06365840759318213, 0.1351969743201744, 0.18482602490293024, 0.03429272603435731, 0.04227321538017403, -0.23049326206091791, 0.10211759605625807, 0.09371642073677419]
1,802.02255
Model Selection Using Cosmic Chronometers with Gaussian Processes
The use of Gaussian Processes with a measurement of the cosmic expansion rate based solely on the observation of cosmic chronometers provides a completely cosmology-independent reconstruction of the Hubble constant H(z) suitable for testing different models. The corresponding dispersion sigma_H is smaller than ~9% over the entire redshift range (0 < z < 2) of the observations, rivaling many kinds of cosmological measurements available today. We use the reconstructed H(z) function to test six different cosmologies, and show that it favours the R_h=ct universe, which has only one free parameter (i.e., H_0) over other models, including Planck LCDM. The parameters of the standard model may be re-optimized to improve the fits to the reconstructed H(z) function, but the results have smaller p-values than one finds with R_h=ct.
astro-ph.CO astro-ph.GA gr-qc hep-ph
the use of gaussian processes with a measurement of the cosmic expansion rate based solely on the observation of cosmic chronometers provides a completely cosmologyindependent reconstruction of the hubble constant hz suitable for testing different models the corresponding dispersion sigma_h is smaller than 9 over the entire redshift range 0 z 2 of the observations rivaling many kinds of cosmological measurements available today we use the reconstructed hz function to test six different cosmologies and show that it favours the r_hct universe which has only one free parameter ie h_0 over other models including planck lcdm the parameters of the standard model may be reoptimized to improve the fits to the reconstructed hz function but the results have smaller pvalues than one finds with r_hct
[['the', 'use', 'of', 'gaussian', 'processes', 'with', 'a', 'measurement', 'of', 'the', 'cosmic', 'expansion', 'rate', 'based', 'solely', 'on', 'the', 'observation', 'of', 'cosmic', 'chronometers', 'provides', 'a', 'completely', 'cosmologyindependent', 'reconstruction', 'of', 'the', 'hubble', 'constant', 'hz', 'suitable', 'for', 'testing', 'different', 'models', 'the', 'corresponding', 'dispersion', 'sigma_h', 'is', 'smaller', 'than', '9', 'over', 'the', 'entire', 'redshift', 'range', '0', 'z', '2', 'of', 'the', 'observations', 'rivaling', 'many', 'kinds', 'of', 'cosmological', 'measurements', 'available', 'today', 'we', 'use', 'the', 'reconstructed', 'hz', 'function', 'to', 'test', 'six', 'different', 'cosmologies', 'and', 'show', 'that', 'it', 'favours', 'the', 'r_hct', 'universe', 'which', 'has', 'only', 'one', 'free', 'parameter', 'ie', 'h_0', 'over', 'other', 'models', 'including', 'planck', 'lcdm', 'the', 'parameters', 'of', 'the', 'standard', 'model', 'may', 'be', 'reoptimized', 'to', 'improve', 'the', 'fits', 'to', 'the', 'reconstructed', 'hz', 'function', 'but', 'the', 'results', 'have', 'smaller', 'pvalues', 'than', 'one', 'finds', 'with', 'r_hct']]
[-0.07038399105332792, 0.11015017265733332, -0.07602118625678123, 0.07152813976723701, -0.10516086979582906, -0.12575021159648894, 0.00795733404159546, 0.32859097877144816, -0.23338704720884562, -0.3360176482796669, 0.08759860970266163, -0.27879900827258824, 0.016906195476651193, 0.26081873000226913, 0.045372376658953724, 0.01780471220612526, 0.06398919171001761, 0.021324829652905466, -0.09581971475749743, -0.31507306575123223, 0.2788798306202516, 0.11713791655004024, 0.2651995865255594, -0.07887465679325396, 0.10052343587949872, -0.04793232177756727, -0.09866857255250215, -0.022033413641154766, -0.22500527143693763, 0.0675828177537769, 0.19534125344344647, 0.19087882520537824, 0.2231026426181197, -0.32279244416207076, -0.26629617363773284, 0.15879004748165607, 0.15101490576565266, 0.08797164667304605, 0.02304683696012944, -0.25702157559155603, 0.08065774676203728, -0.160732067306526, -0.08316090486198664, 0.004961061488837004, -0.03429306720942259, -0.03750747755728662, -0.26479133872687816, 0.19975354773178697, -0.05773612003400922, 0.008009197261184453, -0.10617717503197491, -0.13961037031561135, -0.01433745750784874, 0.0751308826059103, 0.07095306160766632, 0.07333280235156417, 0.14229782454669476, -0.11861450611054897, -0.08349507584562525, 0.38984355436637996, -0.12288170611229725, -0.13322016536444425, 0.1801813103687018, -0.20799592775991185, -0.11431879694387316, 0.08671099028922617, 0.10183448543399573, 0.06844087194278836, -0.13314192628860474, 0.12190507181687281, 0.027725715465843678, 0.22091713237017394, 0.08338152465596795, -0.004187288209795952, 0.22404556265845896, 0.12813252931833266, 0.042740430967416615, 0.02430274197878316, -0.12759153372235596, -0.02649962685024366, -0.3045276307463646, -0.10249081538105384, -0.17306036007031797, 0.06332072692364454, -0.20387463506299536, -0.17921609512344003, 0.39410867684707046, 0.168582594034262, 0.23306272875890136, 0.09657637317571789, 0.3044222183227539, 0.05910629895236343, 0.10313590841862606, 0.04137249086238444, 0.2950975302048027, 0.07514790431037545, 0.03261226728744805, -0.1387397102061659, 0.0690283816382289, -0.03387853990867734]
1,802.02256
Magnetohydrodynamic Turbulence in the Plasmoid-Mediated Regime
Magnetohydrodynamic turbulence and magnetic reconnection are ubiquitous in astrophysical environments. In most situations, these processes do not occur in isolation, but interact with each other. This renders a comprehensive theory of these processes highly challenging. Here, we propose a theory of magnetohydrodynamic turbulence driven at large scale that self-consistently accounts for the mutual interplay with magnetic reconnection occurring at smaller scales. Magnetic reconnection produces plasmoids that grow from turbulence-generated noise and eventually disrupt the sheet-like structures in which they are born. The disruption of these structures leads to a modification of the turbulent energy cascade, which, in turn, exerts a feedback effect on the plasmoid formation via the turbulence-generated noise. The energy spectrum in this plasmoid-mediated range steepens relative to the standard inertial range and does not follow a simple power law. As a result of the complex interplay between turbulence and reconnection, we also find that the length scale which marks the beginning of the plasmoid-mediated range and the dissipation length scale do not obey true power laws. The transitional magnetic Reynolds number above which the plasmoid formation becomes statistically significant enough to affect the turbulent cascade is fairly modest, implying that plasmoids are expected to modify the turbulent path to dissipation in many astrophysical systems.
physics.plasm-ph astro-ph.HE astro-ph.SR physics.flu-dyn physics.space-ph
magnetohydrodynamic turbulence and magnetic reconnection are ubiquitous in astrophysical environments in most situations these processes do not occur in isolation but interact with each other this renders a comprehensive theory of these processes highly challenging here we propose a theory of magnetohydrodynamic turbulence driven at large scale that selfconsistently accounts for the mutual interplay with magnetic reconnection occurring at smaller scales magnetic reconnection produces plasmoids that grow from turbulencegenerated noise and eventually disrupt the sheetlike structures in which they are born the disruption of these structures leads to a modification of the turbulent energy cascade which in turn exerts a feedback effect on the plasmoid formation via the turbulencegenerated noise the energy spectrum in this plasmoidmediated range steepens relative to the standard inertial range and does not follow a simple power law as a result of the complex interplay between turbulence and reconnection we also find that the length scale which marks the beginning of the plasmoidmediated range and the dissipation length scale do not obey true power laws the transitional magnetic reynolds number above which the plasmoid formation becomes statistically significant enough to affect the turbulent cascade is fairly modest implying that plasmoids are expected to modify the turbulent path to dissipation in many astrophysical systems
[['magnetohydrodynamic', 'turbulence', 'and', 'magnetic', 'reconnection', 'are', 'ubiquitous', 'in', 'astrophysical', 'environments', 'in', 'most', 'situations', 'these', 'processes', 'do', 'not', 'occur', 'in', 'isolation', 'but', 'interact', 'with', 'each', 'other', 'this', 'renders', 'a', 'comprehensive', 'theory', 'of', 'these', 'processes', 'highly', 'challenging', 'here', 'we', 'propose', 'a', 'theory', 'of', 'magnetohydrodynamic', 'turbulence', 'driven', 'at', 'large', 'scale', 'that', 'selfconsistently', 'accounts', 'for', 'the', 'mutual', 'interplay', 'with', 'magnetic', 'reconnection', 'occurring', 'at', 'smaller', 'scales', 'magnetic', 'reconnection', 'produces', 'plasmoids', 'that', 'grow', 'from', 'turbulencegenerated', 'noise', 'and', 'eventually', 'disrupt', 'the', 'sheetlike', 'structures', 'in', 'which', 'they', 'are', 'born', 'the', 'disruption', 'of', 'these', 'structures', 'leads', 'to', 'a', 'modification', 'of', 'the', 'turbulent', 'energy', 'cascade', 'which', 'in', 'turn', 'exerts', 'a', 'feedback', 'effect', 'on', 'the', 'plasmoid', 'formation', 'via', 'the', 'turbulencegenerated', 'noise', 'the', 'energy', 'spectrum', 'in', 'this', 'plasmoidmediated', 'range', 'steepens', 'relative', 'to', 'the', 'standard', 'inertial', 'range', 'and', 'does', 'not', 'follow', 'a', 'simple', 'power', 'law', 'as', 'a', 'result', 'of', 'the', 'complex', 'interplay', 'between', 'turbulence', 'and', 'reconnection', 'we', 'also', 'find', 'that', 'the', 'length', 'scale', 'which', 'marks', 'the', 'beginning', 'of', 'the', 'plasmoidmediated', 'range', 'and', 'the', 'dissipation', 'length', 'scale', 'do', 'not', 'obey', 'true', 'power', 'laws', 'the', 'transitional', 'magnetic', 'reynolds', 'number', 'above', 'which', 'the', 'plasmoid', 'formation', 'becomes', 'statistically', 'significant', 'enough', 'to', 'affect', 'the', 'turbulent', 'cascade', 'is', 'fairly', 'modest', 'implying', 'that', 'plasmoids', 'are', 'expected', 'to', 'modify', 'the', 'turbulent', 'path', 'to', 'dissipation', 'in', 'many', 'astrophysical', 'systems']]
[-0.17219782982736934, 0.25310903952281544, -0.05197763160896906, 0.1287702123340948, -0.08172063504296224, -0.06777459616403901, -0.019876911813856646, 0.3328587853840152, -0.2988626744068376, -0.3307839504669191, 0.01752938431235489, -0.21428768602334827, -0.10141915823827871, 0.22972366281623102, 0.007047505943545541, -0.03173392438745927, 0.04920123105729224, -0.02404603149386456, 0.014483999514081717, -0.15387685092813944, 0.31464873932263754, 0.13985077455045952, 0.26336850915869003, 0.034772252427764994, 0.04883116043222267, -0.11087734680307876, -0.006299067051307374, 0.04948710305177593, -0.1401183409089108, 0.0115474049769036, 0.20016973542953856, 0.04083196286804938, 0.27473839146764456, -0.4896027684247724, -0.25560317210652606, 0.062488743041052626, 0.19948312778819965, 0.09619059194450758, -0.036422840895464166, -0.18740197459397756, 0.08396766479532032, -0.18623898012095674, -0.07821042163540488, -0.024373035854322538, 0.030677908928030066, 0.04722564395698377, -0.2916905895271451, 0.1465898350505147, 0.09991892547688165, 0.03674771650221901, -0.07356455467038468, -0.0001712589674282837, -0.04872054527659905, 0.10730969742084472, 0.08873576189814235, 0.024103239075177245, 0.22351294285100368, -0.17287866170698066, -0.06632000386966887, 0.3993226046435499, 0.00878879780192738, -0.14043648018454458, 0.2569298024271313, -0.2299037983659025, -0.1356515846061093, 0.20792051080326382, 0.18820331565057746, 0.06406263803804078, -0.0765016170111451, 0.008561815966116399, -0.029892093771933647, 0.1507193596813162, 0.05137998401356078, 0.03312935588818385, 0.26433528995171335, 0.15024333375906526, 0.0452338966182748, 0.07749265684562866, -0.12500266033305746, -0.1263433049628646, -0.30016338096364686, -0.08482533522571127, -0.13866690970824555, 0.09226518547057527, -0.0749829420163988, -0.21224825897766952, 0.33189471745818566, 0.20348462998048192, 0.1992302328204187, 0.031134138747617817, 0.2746514906287913, 0.12915270609988105, 0.09631730376063409, 0.15274566939496548, 0.2717043825083273, 0.14473911482224394, 0.16616185928879368, -0.2226740183007278, 0.07604167839750683, 0.01571021134996616]
1,802.02257
Synthesis and/or grafting of noble metal nanoparticles by microplasma and by atmospheric plasma torch
Plasmas at atmospheric pressure are presented as a simple, fast, and versatile tool for the synthesis or/and the grafting of noble metallic NPs (Au, Pt) on substrates. In this study, noble metal NPs are generated either by the reduction of a gold salt in an aqueous medium by microplasma or either by the decomposition of a platinum or gold organometallic in the post-discharge of an atmospheric plasma torch. The latter can also be used for the grafting of NPs from a commercial colloidal solution
physics.app-ph physics.plasm-ph
plasmas at atmospheric pressure are presented as a simple fast and versatile tool for the synthesis orand the grafting of noble metallic nps au pt on substrates in this study noble metal nps are generated either by the reduction of a gold salt in an aqueous medium by microplasma or either by the decomposition of a platinum or gold organometallic in the postdischarge of an atmospheric plasma torch the latter can also be used for the grafting of nps from a commercial colloidal solution
[['plasmas', 'at', 'atmospheric', 'pressure', 'are', 'presented', 'as', 'a', 'simple', 'fast', 'and', 'versatile', 'tool', 'for', 'the', 'synthesis', 'orand', 'the', 'grafting', 'of', 'noble', 'metallic', 'nps', 'au', 'pt', 'on', 'substrates', 'in', 'this', 'study', 'noble', 'metal', 'nps', 'are', 'generated', 'either', 'by', 'the', 'reduction', 'of', 'a', 'gold', 'salt', 'in', 'an', 'aqueous', 'medium', 'by', 'microplasma', 'or', 'either', 'by', 'the', 'decomposition', 'of', 'a', 'platinum', 'or', 'gold', 'organometallic', 'in', 'the', 'postdischarge', 'of', 'an', 'atmospheric', 'plasma', 'torch', 'the', 'latter', 'can', 'also', 'be', 'used', 'for', 'the', 'grafting', 'of', 'nps', 'from', 'a', 'commercial', 'colloidal', 'solution']]
[-0.00048312179223146466, 0.21726587861866437, -0.04269081115212646, -0.02913481242527875, 0.05049622826377994, -0.12833581141950118, 0.012129786033169478, 0.4532068070201647, -0.25537007364133996, -0.29415295530287994, 0.07792928806156851, -0.3054268025249864, -0.09092179146440078, 0.21726281374936834, 7.547343903709025e-06, 0.017307028709096596, 0.00856121357563617, -0.09397663005317251, -0.03303550040748503, -0.1409923388800096, 0.21912166906432026, 0.08655762303360029, 0.23947603756650573, 0.09740980460663282, 0.05616593274420926, -0.04047447828842061, 0.07243896521616816, 0.05009353944305552, -0.11580716129832408, 0.10036585207230278, 0.266562403235141, -0.01514956249489582, 0.21272880246397108, -0.5133897125543583, -0.24137825107997438, -0.01296594298799478, 0.11583540127390907, 0.08848313534898418, -0.17799368511658117, -0.24594614286685273, 0.0592258144946148, -0.16366696172571255, -0.12288982247091121, 0.009675207610208807, -0.04429368686950987, 0.08848120189768019, -0.26082505004264284, 0.008829250019473312, 0.07059819969747748, 0.1397929811584098, -0.04569367177984012, -0.15340276824177376, -0.05879198187973261, 0.048267294747001005, 0.013053042855712451, -0.005682763241652754, 0.2785266219372196, -0.11397154519190303, -0.014903250252938875, 0.3990838220342994, -0.12778287731288446, -0.14200080951004998, 0.2562068547787411, -0.10746111077189978, -0.012408655696725916, 0.2183022342422711, 0.17063841606224223, 0.17876584654940025, -0.2212395602837205, 0.061629551467679754, -0.017990867197070094, 0.1886972796083206, 0.15638277080974408, -0.0752510695407788, 0.2433477883958923, 0.24158040794455224, 0.026683044568233612, 0.18030911030863145, -0.09340378492128193, 0.06081049864934314, -0.1578664469443971, -0.26901107839131283, -0.20730364959066114, 0.03307495779535245, -0.1035225888590503, -0.2563460347287002, 0.32912691092739504, 0.016340996487997472, 0.10674505307161737, -0.09319116610069093, 0.2942593415687692, -0.0021600806656005304, 0.049361180771874, -0.024974867501961335, 0.22129838674196176, 0.1363715088116892, 0.12655809280529087, -0.23233850144814433, 0.13001310189775678, 0.04757320879781175]
1,802.02258
A computational framework for microstructural modelling of polycrystalline materials with damage and failure
In the present thesis, a computational framework for the analysis of the deformation and damage phenomena occurring at the micro-scale of polycrystalline materials is presented. Micro-mechanics studies are commonly performed using the Finite Element Method (FEM) for its versatility and robustness. However, finite element formulations usually lead to an extremely high number of degrees of freedom of the considered micro-structures, thus making alternative formulations of great engineering interest. Among the others, the Boundary Element Method (BEM) represents a viable alternative to FEM approaches as it allows to express the problem in terms of boundary values only, thus reducing the total number of degrees of freedom. The computational framework developed in this thesis is based on a non-linear multi-domain BEM approach for generally anisotropic materials and is devoted to the analysis of three-dimensional polycrystalline microstructures. Different theoretical and numerical aspects of the polycrystalline problem using the boundary element method are investigated: first, being the formulation based on a integral representation of the governing equations, a novel and more compact expression of the integration kernels capable of representing the multi-field behaviour of generally anisotropic materials is presented; second, the sources of the high computational cost of polycrystalline analyses are identified and suitably treated by means of different strategies including an ad-hoc grain boundary meshing technique developed to tackle the large statistical variability of polycrystalline micro-morphologies; third, non-linear deformation and failure mechanisms such as inter-granular and trans-granular cracking and generally anisotropic crystal plasticity are studied and the numerical results presented throughout the thesis demonstrate the potential of the developed framework.
cs.CE physics.comp-ph
in the present thesis a computational framework for the analysis of the deformation and damage phenomena occurring at the microscale of polycrystalline materials is presented micromechanics studies are commonly performed using the finite element method fem for its versatility and robustness however finite element formulations usually lead to an extremely high number of degrees of freedom of the considered microstructures thus making alternative formulations of great engineering interest among the others the boundary element method bem represents a viable alternative to fem approaches as it allows to express the problem in terms of boundary values only thus reducing the total number of degrees of freedom the computational framework developed in this thesis is based on a nonlinear multidomain bem approach for generally anisotropic materials and is devoted to the analysis of threedimensional polycrystalline microstructures different theoretical and numerical aspects of the polycrystalline problem using the boundary element method are investigated first being the formulation based on a integral representation of the governing equations a novel and more compact expression of the integration kernels capable of representing the multifield behaviour of generally anisotropic materials is presented second the sources of the high computational cost of polycrystalline analyses are identified and suitably treated by means of different strategies including an adhoc grain boundary meshing technique developed to tackle the large statistical variability of polycrystalline micromorphologies third nonlinear deformation and failure mechanisms such as intergranular and transgranular cracking and generally anisotropic crystal plasticity are studied and the numerical results presented throughout the thesis demonstrate the potential of the developed framework
[['in', 'the', 'present', 'thesis', 'a', 'computational', 'framework', 'for', 'the', 'analysis', 'of', 'the', 'deformation', 'and', 'damage', 'phenomena', 'occurring', 'at', 'the', 'microscale', 'of', 'polycrystalline', 'materials', 'is', 'presented', 'micromechanics', 'studies', 'are', 'commonly', 'performed', 'using', 'the', 'finite', 'element', 'method', 'fem', 'for', 'its', 'versatility', 'and', 'robustness', 'however', 'finite', 'element', 'formulations', 'usually', 'lead', 'to', 'an', 'extremely', 'high', 'number', 'of', 'degrees', 'of', 'freedom', 'of', 'the', 'considered', 'microstructures', 'thus', 'making', 'alternative', 'formulations', 'of', 'great', 'engineering', 'interest', 'among', 'the', 'others', 'the', 'boundary', 'element', 'method', 'bem', 'represents', 'a', 'viable', 'alternative', 'to', 'fem', 'approaches', 'as', 'it', 'allows', 'to', 'express', 'the', 'problem', 'in', 'terms', 'of', 'boundary', 'values', 'only', 'thus', 'reducing', 'the', 'total', 'number', 'of', 'degrees', 'of', 'freedom', 'the', 'computational', 'framework', 'developed', 'in', 'this', 'thesis', 'is', 'based', 'on', 'a', 'nonlinear', 'multidomain', 'bem', 'approach', 'for', 'generally', 'anisotropic', 'materials', 'and', 'is', 'devoted', 'to', 'the', 'analysis', 'of', 'threedimensional', 'polycrystalline', 'microstructures', 'different', 'theoretical', 'and', 'numerical', 'aspects', 'of', 'the', 'polycrystalline', 'problem', 'using', 'the', 'boundary', 'element', 'method', 'are', 'investigated', 'first', 'being', 'the', 'formulation', 'based', 'on', 'a', 'integral', 'representation', 'of', 'the', 'governing', 'equations', 'a', 'novel', 'and', 'more', 'compact', 'expression', 'of', 'the', 'integration', 'kernels', 'capable', 'of', 'representing', 'the', 'multifield', 'behaviour', 'of', 'generally', 'anisotropic', 'materials', 'is', 'presented', 'second', 'the', 'sources', 'of', 'the', 'high', 'computational', 'cost', 'of', 'polycrystalline', 'analyses', 'are', 'identified', 'and', 'suitably', 'treated', 'by', 'means', 'of', 'different', 'strategies', 'including', 'an', 'adhoc', 'grain', 'boundary', 'meshing', 'technique', 'developed', 'to', 'tackle', 'the', 'large', 'statistical', 'variability', 'of', 'polycrystalline', 'micromorphologies', 'third', 'nonlinear', 'deformation', 'and', 'failure', 'mechanisms', 'such', 'as', 'intergranular', 'and', 'transgranular', 'cracking', 'and', 'generally', 'anisotropic', 'crystal', 'plasticity', 'are', 'studied', 'and', 'the', 'numerical', 'results', 'presented', 'throughout', 'the', 'thesis', 'demonstrate', 'the', 'potential', 'of', 'the', 'developed', 'framework']]
[-0.08141155588634774, 0.07899422197135664, -0.08036700273623865, 0.004627768439149804, -0.08479888554938952, -0.10183793140095077, 0.004769571527049266, 0.3550092803379812, -0.2522209278286027, -0.30536005228350405, 0.10849081013498107, -0.23864413064535483, -0.1621897616314527, 0.20963738538193866, -0.05645228623143339, 0.11448459120521193, 0.04869299991287335, -0.047524830340989865, -0.0617896354435743, -0.21536753907139428, 0.2972482584041245, 0.05647470056283055, 0.33756957949753996, 0.05169854829728138, 0.11845168790023308, -0.019257703856965236, -0.05747548680142245, 0.06479937445146788, -0.1297624779454054, 0.16312059173628768, 0.28028258934864425, 0.034838947667594766, 0.2890214300277876, -0.4646183488002862, -0.2750762772739108, 0.039239379153514164, 0.10310429927994846, 0.09899504409685278, -0.041669337961423025, -0.23164238304889295, 0.09608946003208985, -0.13960221847810317, -0.15806833763235772, -0.09350687743017261, -0.012248721355717862, 0.00403976326697375, -0.25060447138810105, 0.06957177155163663, 0.03826114564708405, 0.09243916321065626, -0.08337399824699787, -0.14864652252708765, 0.004995024326490238, 0.08145623483324016, 0.05885401257455669, -0.040266026931931265, 0.11496993940454558, -0.12189529571969615, -0.08845194307286874, 0.4220573375132517, 0.014406155095457507, -0.23117609039036324, 0.20269409473871747, -0.08011719761634595, -0.1058385785399878, 0.15003765288565774, 0.1746239479068663, 0.1740878712716949, -0.17891767798209912, 0.07413495041646456, 0.04218692137328617, 0.14078121570719304, 0.03094958595102071, 0.014086691928241635, 0.1465546742638253, 0.2352714697663032, 0.005985644023894565, 0.14885128727200936, -0.06468504444637801, -0.09709526114056644, -0.30679809910361655, -0.1840452602732512, -0.19865703557752568, -0.027045609344895638, -0.1169913110051084, -0.2144004817125733, 0.38212693189416314, 0.14319878768674243, 0.11047591517672117, -0.0015201293510926916, 0.28547958402123186, 0.09063346940274641, 0.06391918739336688, 0.024583401022937323, 0.21930817679822212, 0.1674659473110296, 0.11039524535681267, -0.24210837603106938, 0.07965813640112174, 0.07611697510765225]
1,802.02259
Single and multiple pin(s)-to-liquid discharges: connecting self-organization patterns and ROS production in liquids for plasma agronomy application
Pin-to-liquid discharges are investigated for the activation of liquids dedicated to agriculture applications. They are characterized through their electrical and optical properties, with a particular attention paid to their filaments and self-organized patterns occurring at the liquid interface. We show how modulating their interaction with ambient air can promote the production of reactive species in liquids such as H2O2, NO2- and NO3-. The effects of the resulting plasma activated media are reported on lentils seeds.
physics.plasm-ph
pintoliquid discharges are investigated for the activation of liquids dedicated to agriculture applications they are characterized through their electrical and optical properties with a particular attention paid to their filaments and selforganized patterns occurring at the liquid interface we show how modulating their interaction with ambient air can promote the production of reactive species in liquids such as h2o2 no2 and no3 the effects of the resulting plasma activated media are reported on lentils seeds
[['pintoliquid', 'discharges', 'are', 'investigated', 'for', 'the', 'activation', 'of', 'liquids', 'dedicated', 'to', 'agriculture', 'applications', 'they', 'are', 'characterized', 'through', 'their', 'electrical', 'and', 'optical', 'properties', 'with', 'a', 'particular', 'attention', 'paid', 'to', 'their', 'filaments', 'and', 'selforganized', 'patterns', 'occurring', 'at', 'the', 'liquid', 'interface', 'we', 'show', 'how', 'modulating', 'their', 'interaction', 'with', 'ambient', 'air', 'can', 'promote', 'the', 'production', 'of', 'reactive', 'species', 'in', 'liquids', 'such', 'as', 'h2o2', 'no2', 'and', 'no3', 'the', 'effects', 'of', 'the', 'resulting', 'plasma', 'activated', 'media', 'are', 'reported', 'on', 'lentils', 'seeds']]
[-0.11320147525544304, 0.2584537211428019, -0.0191508865147527, 0.028507304547757312, 0.005448935024843023, -0.11901157084424552, 0.0407582350748566, 0.4518913213868399, -0.24198635136456909, -0.30334165983053074, 0.1037691519642878, -0.3218545533615995, -0.1603602044224563, 0.17050747847266345, 0.013300210306722973, 0.036884501589009085, -0.02183435539513625, -0.027570470607512304, 0.0190113590120942, -0.19898288123108246, 0.2249271366784563, 0.09320010745746864, 0.31462466371925296, 0.1340649490169174, 0.0769770483335329, -0.06328066019970621, -0.014451096547811569, 0.012904832768883254, -0.12476619388778361, 0.10081617386281691, 0.28665353714038516, 0.009317014193338519, 0.2167948582335501, -0.5447027397316855, -0.28570391406380646, 0.05819651499591969, 0.10765396879759391, 0.07118367520160973, -0.09669683275373049, -0.27084648001913886, 0.03392048761550639, -0.15758545556407724, -0.09289669017685023, -0.05574600413643025, 0.010390064213424921, 0.11323535701573033, -0.19881776945564794, 0.07603315340757773, 0.02635802500377837, 0.10506277630653081, -0.06610289471840637, -0.10245896596461535, -0.12199617810924915, 0.14503131194883404, 0.06518464033315713, -0.06083004520199186, 0.2919379114865552, -0.18240872332574548, -0.07656683964101044, 0.421221362426877, -0.023400583789004264, -0.13196126107642478, 0.29605719434550487, -0.1354214509609281, -0.09938752919913747, 0.16229804533193945, 0.2073844070451938, 0.0889705367184974, -0.12486494698158994, -0.03952648908739935, 0.03401401880625132, 0.10379723969821793, 0.10830880414593864, 0.03428879738911181, 0.21458391759645296, 0.18930518745469885, -0.01588135546174001, 0.16039055633685878, -0.0714771254837664, -0.038418969381726474, -0.16719687402223213, -0.1631892615161534, -0.09865584998467081, 0.01078204731960353, -0.00886980952585676, -0.14195939839771962, 0.36445007346117414, 0.0967783316493198, 0.15101637863050643, -0.060063662485697784, 0.20443925920974565, 0.05317015243486527, 0.0466671182185638, 0.0270530403893743, 0.23186492615983495, 0.12193569892927347, 0.18802114820258842, -0.23750580731791923, 0.15377013311671042, 0.0009272123712140161]