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 |
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1,802.0786 | Neural Predictive Coding using Convolutional Neural Networks towards
Unsupervised Learning of Speaker Characteristics | Learning speaker-specific features is vital in many applications like speaker
recognition, diarization and speech recognition. This paper provides a novel
approach, we term Neural Predictive Coding (NPC), to learn speaker-specific
characteristics in a completely unsupervised manner from large amounts of
unlabeled training data that even contain many non-speech events and
multi-speaker audio streams. The NPC framework exploits the proposed short-term
active-speaker stationarity hypothesis which assumes two temporally-close short
speech segments belong to the same speaker, and thus a common representation
that can encode the commonalities of both the segments, should capture the
vocal characteristics of that speaker. We train a convolutional deep siamese
network to produce "speaker embeddings" by learning to separate `same' vs
`different' speaker pairs which are generated from an unlabeled data of audio
streams. Two sets of experiments are done in different scenarios to evaluate
the strength of NPC embeddings and compare with state-of-the-art in-domain
supervised methods. First, two speaker identification experiments with
different context lengths are performed in a scenario with comparatively
limited within-speaker channel variability. NPC embeddings are found to perform
the best at short duration experiment, and they provide complementary
information to i-vectors for full utterance experiments. Second, a large scale
speaker verification task having a wide range of within-speaker channel
variability is adopted as an upper-bound experiment where comparisons are drawn
with in-domain supervised methods.
| cs.SD cs.CL eess.AS | learning speakerspecific features is vital in many applications like speaker recognition diarization and speech recognition this paper provides a novel approach we term neural predictive coding npc to learn speakerspecific characteristics in a completely unsupervised manner from large amounts of unlabeled training data that even contain many nonspeech events and multispeaker audio streams the npc framework exploits the proposed shortterm activespeaker stationarity hypothesis which assumes two temporallyclose short speech segments belong to the same speaker and thus a common representation that can encode the commonalities of both the segments should capture the vocal characteristics of that speaker we train a convolutional deep siamese network to produce speaker embeddings by learning to separate same vs different speaker pairs which are generated from an unlabeled data of audio streams two sets of experiments are done in different scenarios to evaluate the strength of npc embeddings and compare with stateoftheart indomain supervised methods first two speaker identification experiments with different context lengths are performed in a scenario with comparatively limited withinspeaker channel variability npc embeddings are found to perform the best at short duration experiment and they provide complementary information to ivectors for full utterance experiments second a large scale speaker verification task having a wide range of withinspeaker channel variability is adopted as an upperbound experiment where comparisons are drawn with indomain supervised methods | [['learning', 'speakerspecific', 'features', 'is', 'vital', 'in', 'many', 'applications', 'like', 'speaker', 'recognition', 'diarization', 'and', 'speech', 'recognition', 'this', 'paper', 'provides', 'a', 'novel', 'approach', 'we', 'term', 'neural', 'predictive', 'coding', 'npc', 'to', 'learn', 'speakerspecific', 'characteristics', 'in', 'a', 'completely', 'unsupervised', 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1,802.07861 | Statistical complexity without explicit reference to underlying
probabilities | We show that extremely simple systems of a not too large number of particles
can be simultane- ously thermally stable and complex. To such an end, we extend
the statistical complexity's notion to simple configurations of non-interacting
particles, without appeal to probabilities, and discuss configurational
properties.
| cond-mat.stat-mech | we show that extremely simple systems of a not too large number of particles can be simultane ously thermally stable and complex to such an end we extend the statistical complexitys notion to simple configurations of noninteracting particles without appeal to probabilities and discuss configurational properties | [['we', 'show', 'that', 'extremely', 'simple', 'systems', 'of', 'a', 'not', 'too', 'large', 'number', 'of', 'particles', 'can', 'be', 'simultane', 'ously', 'thermally', 'stable', 'and', 'complex', 'to', 'such', 'an', 'end', 'we', 'extend', 'the', 'statistical', 'complexitys', 'notion', 'to', 'simple', 'configurations', 'of', 'noninteracting', 'particles', 'without', 'appeal', 'to', 'probabilities', 'and', 'discuss', 'configurational', 'properties']] | [-0.10578530680631167, 0.21710817954463774, -0.10747873622660889, 0.10302284576565675, -0.08466225081761165, -0.116288527795721, 0.06410493605527216, 0.37557892760504846, -0.2602936262467309, -0.28199989571357553, 0.041260119902132, -0.23835208744782468, -0.133120558730772, 0.16134830758623456, -0.1158876180264127, 0.01642743529468451, 0.05261512723265459, 0.0129896380290713, -0.02730249677804987, -0.20449487533440572, 0.2654624271975911, 0.05350586830678841, 0.21640194608303515, 0.05337562936398646, 0.07076792914987258, 0.010446832333084034, 0.05715421904080912, 0.08808907581007351, -0.12664150546444705, 0.08100150651096003, 0.21737489529439938, 0.09378211171892674, 0.22468599450329077, -0.45328029131759767, -0.1869348464128764, 0.205762587047344, 0.16479733717911269, 0.15503682447192463, -0.030966036791062874, -0.24623988491847462, 0.12338477688962998, -0.204392704019404, -0.19499148604581537, -0.16534035358294522, 0.011072669810939418, 0.04035524718220467, -0.21851488795009968, 0.024047302770549835, 0.07921048229479272, 0.027584340909252995, -0.02342067224621449, -0.052154287341577205, -0.02183391838638193, 0.06176170453672176, 0.02566022814615913, -0.09379508562952928, 0.15982721189198934, -0.13323782740727716, -0.09015001988281375, 0.38100220352087333, -0.03448246557103551, -0.22739016404881587, 0.29220177699766203, -0.11664071186121715, -0.15216960336851038, 0.14890066535293084, 0.15610117313411573, 0.1532880232223998, -0.16089250689939313, 0.0523832841224604, -0.005472034479126982, 0.1772182809755854, 0.02804890495684484, 0.04377726190116094, 0.23926086853379788, 0.11346878467694572, 0.049246654491466674, 0.1502243464675975, -0.04287711184714799, -0.10884477275059275, -0.24104796244722346, -0.18645796963297154, -0.20209592763010575, 0.07438448689524944, -0.07217771843336421, -0.19736464422844027, 0.3094035991690243, 0.17435183161464723, 0.25713013841912313, 0.08696593710160612, 0.24513636480854906, 0.07604843375030094, 0.009574832394719124, 0.06052826013436298, 0.2164995629016472, 0.12696520405133133, 0.026128606060924736, -0.16081332829375955, 0.0200329947832, 0.023719967909805153] |
1,802.07862 | Multimodal Named Entity Recognition for Short Social Media Posts | We introduce a new task called Multimodal Named Entity Recognition (MNER) for
noisy user-generated data such as tweets or Snapchat captions, which comprise
short text with accompanying images. These social media posts often come in
inconsistent or incomplete syntax and lexical notations with very limited
surrounding textual contexts, bringing significant challenges for NER. To this
end, we create a new dataset for MNER called SnapCaptions (Snapchat
image-caption pairs submitted to public and crowd-sourced stories with fully
annotated named entities). We then build upon the state-of-the-art Bi-LSTM
word/character based NER models with 1) a deep image network which incorporates
relevant visual context to augment textual information, and 2) a generic
modality-attention module which learns to attenuate irrelevant modalities while
amplifying the most informative ones to extract contexts from, adaptive to each
sample and token. The proposed MNER model with modality attention significantly
outperforms the state-of-the-art text-only NER models by successfully
leveraging provided visual contexts, opening up potential applications of MNER
on myriads of social media platforms.
| cs.CL | we introduce a new task called multimodal named entity recognition mner for noisy usergenerated data such as tweets or snapchat captions which comprise short text with accompanying images these social media posts often come in inconsistent or incomplete syntax and lexical notations with very limited surrounding textual contexts bringing significant challenges for ner to this end we create a new dataset for mner called snapcaptions snapchat imagecaption pairs submitted to public and crowdsourced stories with fully annotated named entities we then build upon the stateoftheart bilstm wordcharacter based ner models with 1 a deep image network which incorporates relevant visual context to augment textual information and 2 a generic modalityattention module which learns to attenuate irrelevant modalities while amplifying the most informative ones to extract contexts from adaptive to each sample and token the proposed mner model with modality attention significantly outperforms the stateoftheart textonly ner models by successfully leveraging provided visual contexts opening up potential applications of mner on myriads of social media platforms | [['we', 'introduce', 'a', 'new', 'task', 'called', 'multimodal', 'named', 'entity', 'recognition', 'mner', 'for', 'noisy', 'usergenerated', 'data', 'such', 'as', 'tweets', 'or', 'snapchat', 'captions', 'which', 'comprise', 'short', 'text', 'with', 'accompanying', 'images', 'these', 'social', 'media', 'posts', 'often', 'come', 'in', 'inconsistent', 'or', 'incomplete', 'syntax', 'and', 'lexical', 'notations', 'with', 'very', 'limited', 'surrounding', 'textual', 'contexts', 'bringing', 'significant', 'challenges', 'for', 'ner', 'to', 'this', 'end', 'we', 'create', 'a', 'new', 'dataset', 'for', 'mner', 'called', 'snapcaptions', 'snapchat', 'imagecaption', 'pairs', 'submitted', 'to', 'public', 'and', 'crowdsourced', 'stories', 'with', 'fully', 'annotated', 'named', 'entities', 'we', 'then', 'build', 'upon', 'the', 'stateoftheart', 'bilstm', 'wordcharacter', 'based', 'ner', 'models', 'with', '1', 'a', 'deep', 'image', 'network', 'which', 'incorporates', 'relevant', 'visual', 'context', 'to', 'augment', 'textual', 'information', 'and', '2', 'a', 'generic', 'modalityattention', 'module', 'which', 'learns', 'to', 'attenuate', 'irrelevant', 'modalities', 'while', 'amplifying', 'the', 'most', 'informative', 'ones', 'to', 'extract', 'contexts', 'from', 'adaptive', 'to', 'each', 'sample', 'and', 'token', 'the', 'proposed', 'mner', 'model', 'with', 'modality', 'attention', 'significantly', 'outperforms', 'the', 'stateoftheart', 'textonly', 'ner', 'models', 'by', 'successfully', 'leveraging', 'provided', 'visual', 'contexts', 'opening', 'up', 'potential', 'applications', 'of', 'mner', 'on', 'myriads', 'of', 'social', 'media', 'platforms']] | [-0.011606709581679819, 0.012150014597819718, -0.010759356071704005, 0.09601849063508144, -0.23261411304077123, -0.22417112945241888, 0.037463259934647684, 0.43838571583955016, -0.2801952375980391, -0.3339748785211819, 0.029506332697375376, -0.3680745120405968, -0.16178314940592536, 0.16054441062790667, -0.1446500834323283, 0.026047673059250313, 0.1433234834940704, 0.08164453700447649, 0.004294232582456313, -0.27062728683956316, 0.3193597865570908, 0.022880915256518516, 0.3486436422845703, 0.004823151586628719, 0.1787296857626286, -0.022083190415465942, -0.11478399995505878, -0.026194247900668325, -0.04775640577580666, 0.21681370648721154, 0.3923733529649147, 0.24331480282375967, 0.32677308908532277, -0.3985292033970044, -0.22527858424086147, 0.03375753371828476, 0.12939203860226767, 0.12207818947581751, -0.04449952070164191, -0.43185330723680876, 0.07726659011838535, -0.21839757119105455, 0.07481308169577248, -0.14730402393883632, 0.013139534879481546, -0.0035899200257445267, -0.2711327963457243, 0.043165934980601256, 0.08161933664653873, 0.09880764631017402, -0.032469973954417815, -0.0937323225290726, 0.027745083828622397, 0.17905753832081892, 0.029934987875038725, 0.06508379333803967, 0.14079052204569012, -0.22461687296448973, -0.15878576653341026, 0.38982426996794217, -0.05631657951065779, -0.17896364346300853, 0.23070735337092696, 0.024481735177955197, -0.16399979987610247, 0.06995198658547519, 0.24223317646105813, 0.07212811331707482, -0.19124468268278094, -0.05548388030568561, -0.05518439296987251, 0.2561561735146936, 0.0898062832927777, 0.03152705909844282, 0.20254672823862696, 0.24702169108518793, -0.05488010670166988, 0.1273704789338942, -0.0812504266894371, -0.04353929193550435, -0.14975398708637688, -0.07421961441733217, -0.13284076390033758, -0.044115050584420654, -0.08881063449326503, -0.16428415645756672, 0.3688980662806725, 0.26546636426627085, 0.19238430784123897, 0.07713580252802674, 0.30978920938092874, -0.07986890083318862, 0.1601086346853233, 0.09530177502428679, 0.07161004937031061, -0.061959528231131274, 0.20148138381523634, -0.07941231612070389, 0.08957149302358368, 0.05813448103658992] |
1,802.07863 | Efficient Enumeration of Dominating Sets for Sparse Graphs | A dominating set $D$ of a graph $G$ is a set of vertices such that any vertex
in $G$ is in $D$ or its neighbor is in $D$. Enumeration of minimal dominating
sets in a graph is one of central problems in enumeration study since
enumeration of minimal dominating sets corresponds to enumeration of minimal
hypergraph transversal. However, enumeration of dominating sets including
non-minimal ones has not been received much attention. In this paper, we
address enumeration problems for dominating sets from sparse graphs which are
degenerate graphs and graphs with large girth, and we propose two algorithms
for solving the problems. The first algorithm enumerates all the dominating
sets for a $k$-degenerate graph in $O(k)$ time per solution using $O(n + m)$
space, where $n$ and $m$ are respectively the number of vertices and edges in
an input graph. That is, the algorithm is optimal for graphs with constant
degeneracy such as trees, planar graphs, $H$-minor free graphs with some fixed
$H$. The second algorithm enumerates all the dominating sets in constant time
per solution for input graphs with girth at least nine.
| cs.DS | a dominating set d of a graph g is a set of vertices such that any vertex in g is in d or its neighbor is in d enumeration of minimal dominating sets in a graph is one of central problems in enumeration study since enumeration of minimal dominating sets corresponds to enumeration of minimal hypergraph transversal however enumeration of dominating sets including nonminimal ones has not been received much attention in this paper we address enumeration problems for dominating sets from sparse graphs which are degenerate graphs and graphs with large girth and we propose two algorithms for solving the problems the first algorithm enumerates all the dominating sets for a kdegenerate graph in ok time per solution using on m space where n and m are respectively the number of vertices and edges in an input graph that is the algorithm is optimal for graphs with constant degeneracy such as trees planar graphs hminor free graphs with some fixed h the second algorithm enumerates all the dominating sets in constant time per solution for input graphs with girth at least nine | [['a', 'dominating', 'set', 'd', 'of', 'a', 'graph', 'g', 'is', 'a', 'set', 'of', 'vertices', 'such', 'that', 'any', 'vertex', 'in', 'g', 'is', 'in', 'd', 'or', 'its', 'neighbor', 'is', 'in', 'd', 'enumeration', 'of', 'minimal', 'dominating', 'sets', 'in', 'a', 'graph', 'is', 'one', 'of', 'central', 'problems', 'in', 'enumeration', 'study', 'since', 'enumeration', 'of', 'minimal', 'dominating', 'sets', 'corresponds', 'to', 'enumeration', 'of', 'minimal', 'hypergraph', 'transversal', 'however', 'enumeration', 'of', 'dominating', 'sets', 'including', 'nonminimal', 'ones', 'has', 'not', 'been', 'received', 'much', 'attention', 'in', 'this', 'paper', 'we', 'address', 'enumeration', 'problems', 'for', 'dominating', 'sets', 'from', 'sparse', 'graphs', 'which', 'are', 'degenerate', 'graphs', 'and', 'graphs', 'with', 'large', 'girth', 'and', 'we', 'propose', 'two', 'algorithms', 'for', 'solving', 'the', 'problems', 'the', 'first', 'algorithm', 'enumerates', 'all', 'the', 'dominating', 'sets', 'for', 'a', 'kdegenerate', 'graph', 'in', 'ok', 'time', 'per', 'solution', 'using', 'on', 'm', 'space', 'where', 'n', 'and', 'm', 'are', 'respectively', 'the', 'number', 'of', 'vertices', 'and', 'edges', 'in', 'an', 'input', 'graph', 'that', 'is', 'the', 'algorithm', 'is', 'optimal', 'for', 'graphs', 'with', 'constant', 'degeneracy', 'such', 'as', 'trees', 'planar', 'graphs', 'hminor', 'free', 'graphs', 'with', 'some', 'fixed', 'h', 'the', 'second', 'algorithm', 'enumerates', 'all', 'the', 'dominating', 'sets', 'in', 'constant', 'time', 'per', 'solution', 'for', 'input', 'graphs', 'with', 'girth', 'at', 'least', 'nine']] | [-0.1892201495076952, 0.11616890500193078, 0.025855901040381095, 0.039019812018702145, -0.10982923627871756, -0.14822089890415063, 0.050156012965656326, 0.3903596791326796, -0.266058554730373, -0.3505560101004816, 0.11251594013944166, -0.35251569072588707, -0.1104740013884981, 0.135371302365188, -0.07968652556787749, 0.06306889632817286, 0.14343680577769957, 0.09951607332325699, 0.034102269532311644, -0.3011501725964106, 0.306089317466799, -0.05295985482144551, 0.15359734368887146, 0.053560023267290306, 0.08882817217337141, 0.01629499612818854, -0.0130647924713424, 0.10222551442636305, -0.14868997603877832, 0.08984993035584445, 0.2821892868801239, 0.1906792236774488, 0.26072456465799954, -0.37543796623746556, -0.15021257305834596, 0.24841517433676807, 0.10717001413834877, 0.0896109662958945, 0.026470994248876827, -0.14427468139433958, 0.1398556145834304, -0.06699979287964072, -0.03619460457722183, 0.007450003314335815, 0.14188047633837156, -0.005785151592791691, -0.2905441463894409, -0.026633278847178393, 0.07574586774085144, 0.033381709790803855, 0.052867564847921864, -0.19646347538043893, -0.023555993944752576, 0.07554853753227476, -0.05391300628165323, 0.08496125665355901, -0.016856433653216707, -0.1162056181455143, -0.22600152443768712, 0.39583807818265887, -0.00676967861141012, -0.16761469585653088, 0.11799637289066377, -0.12798033647819376, -0.20623363748630458, 0.15479562097722716, 0.17534918211848358, 0.19049617692146226, -0.12139822477016782, 0.18722901323459065, -0.1200438568201883, 0.10628520248233865, 0.14495540457609735, 0.011309959801025893, 0.10310371891885507, 0.19100414966411197, 0.21131366133547383, 0.1914551728608626, 0.011315215637276325, 7.080939175978384e-05, -0.291931699152242, -0.06401102335441633, -0.2666516635831588, 0.02915629843776967, -0.2139141301168358, -0.25042042448605245, 0.42035087856306325, 0.09233039345012092, 0.21199258592468304, 0.12087706963549485, 0.23151365150519407, 0.040355623614003557, 0.06088430101377635, 0.2153891197331326, 0.08842300836590393, 0.1506932337407043, -0.06275118720244433, -0.16019643017722554, 0.060926029104943, 0.16569925480537484] |
1,802.07864 | A tight-binding model for the band dispersion in rhombohedral
topological insulators over the whole Brilluoin zone | We put forward a tight-binding model for rhombohedral topological insulators
materials with the space group $D^{5}_{3d}(R\bar{3}m)$. The model describes the
bulk band structure of these materials over the whole Brillouin zone. Within
this framework, we also describe the topological nature of surface states,
characterized by a Dirac cone-like dispersion and the emergence of surface
projected bulk states near to the Dirac-point in energy. We find that the
breaking of the $R_{3}$ symmetry as one moves away from the $\Gamma$ point has
an important role in the hybridization of the $p_x$, $p_y$, and $p_z$ atomic
orbitals. In our tight-binding model, the latter leads to a band mixing matrix
element ruled by a single parameter. We show that our model gives a good
description of the strategies/mechanisms proposed in the literature to
eliminate and/or energy shift the bulk states away from the Dirac point, such
as stacking faults and the introduction of an external applied electric field.
| cond-mat.mes-hall | we put forward a tightbinding model for rhombohedral topological insulators materials with the space group d5_3drbar3m the model describes the bulk band structure of these materials over the whole brillouin zone within this framework we also describe the topological nature of surface states characterized by a dirac conelike dispersion and the emergence of surface projected bulk states near to the diracpoint in energy we find that the breaking of the r_3 symmetry as one moves away from the gamma point has an important role in the hybridization of the p_x p_y and p_z atomic orbitals in our tightbinding model the latter leads to a band mixing matrix element ruled by a single parameter we show that our model gives a good description of the strategiesmechanisms proposed in the literature to eliminate andor energy shift the bulk states away from the dirac point such as stacking faults and the introduction of an external applied electric field | [['we', 'put', 'forward', 'a', 'tightbinding', 'model', 'for', 'rhombohedral', 'topological', 'insulators', 'materials', 'with', 'the', 'space', 'group', 'd5_3drbar3m', 'the', 'model', 'describes', 'the', 'bulk', 'band', 'structure', 'of', 'these', 'materials', 'over', 'the', 'whole', 'brillouin', 'zone', 'within', 'this', 'framework', 'we', 'also', 'describe', 'the', 'topological', 'nature', 'of', 'surface', 'states', 'characterized', 'by', 'a', 'dirac', 'conelike', 'dispersion', 'and', 'the', 'emergence', 'of', 'surface', 'projected', 'bulk', 'states', 'near', 'to', 'the', 'diracpoint', 'in', 'energy', 'we', 'find', 'that', 'the', 'breaking', 'of', 'the', 'r_3', 'symmetry', 'as', 'one', 'moves', 'away', 'from', 'the', 'gamma', 'point', 'has', 'an', 'important', 'role', 'in', 'the', 'hybridization', 'of', 'the', 'p_x', 'p_y', 'and', 'p_z', 'atomic', 'orbitals', 'in', 'our', 'tightbinding', 'model', 'the', 'latter', 'leads', 'to', 'a', 'band', 'mixing', 'matrix', 'element', 'ruled', 'by', 'a', 'single', 'parameter', 'we', 'show', 'that', 'our', 'model', 'gives', 'a', 'good', 'description', 'of', 'the', 'strategiesmechanisms', 'proposed', 'in', 'the', 'literature', 'to', 'eliminate', 'andor', 'energy', 'shift', 'the', 'bulk', 'states', 'away', 'from', 'the', 'dirac', 'point', 'such', 'as', 'stacking', 'faults', 'and', 'the', 'introduction', 'of', 'an', 'external', 'applied', 'electric', 'field']] | [-0.1574783209297392, 0.14699747106170713, -0.0655763437910602, 0.033904162045336916, -0.03569085791317466, -0.10233282023626897, 0.1171632532564485, 0.3583381961958081, -0.30508878716614607, -0.2766399098913264, -0.006621922905027282, -0.29087532871080185, -0.1468072382199085, 0.12582686662771345, 0.019584115873109185, -0.005801479545196677, -0.009132447485124168, -0.028799388341581314, -0.12427320387944871, -0.1427381990851798, 0.32935429941497596, 0.03463878525798422, 0.30194583943028463, 0.05258188178318437, 0.0273267392927379, 0.02580137684137798, 0.08006017124949912, 0.009933150461471633, -0.13210482747962446, 0.1091451128336808, 0.2342016109496696, -0.05355133215160249, 0.19714984387993276, -0.4405662884899214, -0.2436993708742746, 0.02399683199226369, 0.11818354255808944, 0.1425320025407131, -0.06461182953120252, -0.3076222739151977, 0.04128141026773484, -0.16230829768613272, -0.17197955914109556, -0.06527296191209234, -0.02032396320810578, -0.059541287250646384, -0.2018786342529233, 0.06551968001778043, 0.05332454338401946, 0.05731398701740831, -0.10160534627970728, -0.12648945124028554, -0.14973074204008419, 0.08150822229476438, 0.07021099395876494, 0.05206285286816507, 0.11440674845034902, -0.11020053652102992, -0.08636223441415947, 0.43209463098007284, -0.047985052452513985, -0.16924395599079872, 0.15272371366230492, -0.13755712635112086, -0.0894653438879603, 0.16009751104086248, 0.12869729480273973, 0.06149744610393457, -0.085132481959828, 0.14192021608822888, -0.05583310786640771, 0.1395337575901257, 0.0034837152114978024, 0.03889368349698439, 0.25043324820599916, 0.15432852965393834, 0.09360058047181738, 0.11789947717977091, -0.15515913132249431, -0.06953385858218265, -0.33017713412812916, -0.19058560927130672, -0.22646884128810485, 0.027378070283851592, -0.05861500255868913, -0.20564924761186143, 0.467666931292103, 0.12991792320279905, 0.2115259037164399, -0.044333607865363556, 0.20794637944074532, 0.12628409747046485, 0.08288745245906932, 0.0661433299735578, 0.26449439460959506, 0.12347873687147608, 0.05637573227027638, -0.23476395172560038, 0.009784955971149934, 0.05886299647634326] |
1,802.07865 | On the Super Mumford Form in the Presence of Ramond and Neveu-Schwarz
Punctures | We generalize the result of Voronov (1988) to give an expression for the
super Mumford form $\mu$ on the moduli spaces of super Riemann surfaces with
Ramond and Neveu-Schwarz punctures in the limit where the number of punctures
is large compared to the genus. In the case of Neveu-Schwarz punctures we
consider the super Mumford form over the component of the moduli space
corresponding to an odd spin structure. The super Mumford form $\mu$ can be
used to create a measure whose integral computes scattering amplitudes of
superstring theory. We express $\mu$ in terms of local bases of $H^0(\Sigma,
\omega^j)$ for $\omega$ the Berezinian line bundle of a family of super Riemann
surfaces.
| math-ph hep-th math.AG math.MP math.QA | we generalize the result of voronov 1988 to give an expression for the super mumford form mu on the moduli spaces of super riemann surfaces with ramond and neveuschwarz punctures in the limit where the number of punctures is large compared to the genus in the case of neveuschwarz punctures we consider the super mumford form over the component of the moduli space corresponding to an odd spin structure the super mumford form mu can be used to create a measure whose integral computes scattering amplitudes of superstring theory we express mu in terms of local bases of h0sigma omegaj for omega the berezinian line bundle of a family of super riemann surfaces | [['we', 'generalize', 'the', 'result', 'of', 'voronov', '1988', 'to', 'give', 'an', 'expression', 'for', 'the', 'super', 'mumford', 'form', 'mu', 'on', 'the', 'moduli', 'spaces', 'of', 'super', 'riemann', 'surfaces', 'with', 'ramond', 'and', 'neveuschwarz', 'punctures', 'in', 'the', 'limit', 'where', 'the', 'number', 'of', 'punctures', 'is', 'large', 'compared', 'to', 'the', 'genus', 'in', 'the', 'case', 'of', 'neveuschwarz', 'punctures', 'we', 'consider', 'the', 'super', 'mumford', 'form', 'over', 'the', 'component', 'of', 'the', 'moduli', 'space', 'corresponding', 'to', 'an', 'odd', 'spin', 'structure', 'the', 'super', 'mumford', 'form', 'mu', 'can', 'be', 'used', 'to', 'create', 'a', 'measure', 'whose', 'integral', 'computes', 'scattering', 'amplitudes', 'of', 'superstring', 'theory', 'we', 'express', 'mu', 'in', 'terms', 'of', 'local', 'bases', 'of', 'h0sigma', 'omegaj', 'for', 'omega', 'the', 'berezinian', 'line', 'bundle', 'of', 'a', 'family', 'of', 'super', 'riemann', 'surfaces']] | [-0.1851413149727575, 0.11268770532089027, -0.07395913836288466, 0.0825343811770186, -0.0744663476860816, -0.08641858033037611, 0.0006520922553525972, 0.26964977584845784, -0.24496564466971904, -0.23525080475623586, 0.07508528710422979, -0.2586148874418411, -0.16118779931483523, 0.18525835961398635, -0.1195381077746528, -0.011712224571965635, 0.0059435872057552585, 0.11299494505510665, -0.10670538957180854, -0.2920747378136314, 0.40712114523713744, -0.03095128002626422, 0.2238770984279524, 0.03565029798898779, 0.08293036423648507, 0.03540416324228447, 0.0007732513726555876, -0.051146128905332135, -0.1233965896036742, 0.18701545411853918, 0.2799654422394399, 0.06804751271764482, 0.08630319747317117, -0.4465496952346127, -0.16061955160278427, 0.1591196383357913, 0.11945541967621207, 0.0029242343734949827, 0.07917769472052376, -0.23060384202524023, 0.055410147796335095, -0.138770608181533, -0.23344861514799828, -0.062151738334380625, 0.07924103753508202, -0.03503042640347433, -0.23428887662937217, -0.008308943805916767, 0.023015873847595816, 0.07726777339952864, -0.08866840820077673, -0.11395388876969394, -0.0735733861303223, 0.06445285989320837, 0.05029323757896366, 0.10207673932641878, 0.06540109210098828, -0.1574652825906274, -0.11118950326428083, 0.3217991908890586, -0.11684524609258265, -0.24675041545456874, 0.12611448187713645, -0.16841858895869727, -0.14417360524281062, 0.14965143796455646, 0.1274507276622379, 0.2048969178078031, -0.03605131126460037, 0.22435502912256716, -0.08528665388335607, 0.06360997439229063, 0.17577332180891453, -0.022942951339895705, 0.1993305962449605, 0.10337760405465295, 0.05409820349970167, 0.14718277993441525, -0.08784881248928807, -0.053842056590968114, -0.3890983671216028, -0.2368930909017633, -0.1168061093277564, 0.14515408781257325, -0.13426291337015886, -0.20432612368936784, 0.3614805703296692, 0.013126367179211229, 0.20490174592539137, 0.1281432922852608, 0.15255543098984553, 0.11573055006530401, 0.06716629799276623, 0.05981514670721871, 0.14335076172470249, 0.2325352211482823, -2.2464341392541038e-05, -0.20302622016502678, -0.08889648164456178, 0.2058201554588907] |
1,802.07866 | Multi-Sensor Integration for Indoor 3D Reconstruction | Outdoor maps and navigation information delivered by modern services and
technologies like Google Maps and Garmin navigators have revolutionized the
lifestyle of many people. Motivated by the desire for similar navigation
systems for indoor usage from consumers, advertisers, emergency
rescuers/responders, etc., many indoor environments such as shopping malls,
museums, casinos, airports, transit stations, offices, and schools need to be
mapped. Typically, the environment is first reconstructed by capturing many
point clouds from various stations and defining their spatial relationships.
Currently, there is a lack of an accurate, rigorous, and speedy method for
relating point clouds in indoor, urban, satellite-denied environments. This
thesis presents a novel and automatic way for fusing calibrated point clouds
obtained using a terrestrial laser scanner and the Microsoft Kinect by
integrating them with a low-cost inertial measurement unit. The developed
system, titled the Scannect, is the first joint static-kinematic indoor 3D
mapper.
| cs.CV cs.RO | outdoor maps and navigation information delivered by modern services and technologies like google maps and garmin navigators have revolutionized the lifestyle of many people motivated by the desire for similar navigation systems for indoor usage from consumers advertisers emergency rescuersresponders etc many indoor environments such as shopping malls museums casinos airports transit stations offices and schools need to be mapped typically the environment is first reconstructed by capturing many point clouds from various stations and defining their spatial relationships currently there is a lack of an accurate rigorous and speedy method for relating point clouds in indoor urban satellitedenied environments this thesis presents a novel and automatic way for fusing calibrated point clouds obtained using a terrestrial laser scanner and the microsoft kinect by integrating them with a lowcost inertial measurement unit the developed system titled the scannect is the first joint statickinematic indoor 3d mapper | [['outdoor', 'maps', 'and', 'navigation', 'information', 'delivered', 'by', 'modern', 'services', 'and', 'technologies', 'like', 'google', 'maps', 'and', 'garmin', 'navigators', 'have', 'revolutionized', 'the', 'lifestyle', 'of', 'many', 'people', 'motivated', 'by', 'the', 'desire', 'for', 'similar', 'navigation', 'systems', 'for', 'indoor', 'usage', 'from', 'consumers', 'advertisers', 'emergency', 'rescuersresponders', 'etc', 'many', 'indoor', 'environments', 'such', 'as', 'shopping', 'malls', 'museums', 'casinos', 'airports', 'transit', 'stations', 'offices', 'and', 'schools', 'need', 'to', 'be', 'mapped', 'typically', 'the', 'environment', 'is', 'first', 'reconstructed', 'by', 'capturing', 'many', 'point', 'clouds', 'from', 'various', 'stations', 'and', 'defining', 'their', 'spatial', 'relationships', 'currently', 'there', 'is', 'a', 'lack', 'of', 'an', 'accurate', 'rigorous', 'and', 'speedy', 'method', 'for', 'relating', 'point', 'clouds', 'in', 'indoor', 'urban', 'satellitedenied', 'environments', 'this', 'thesis', 'presents', 'a', 'novel', 'and', 'automatic', 'way', 'for', 'fusing', 'calibrated', 'point', 'clouds', 'obtained', 'using', 'a', 'terrestrial', 'laser', 'scanner', 'and', 'the', 'microsoft', 'kinect', 'by', 'integrating', 'them', 'with', 'a', 'lowcost', 'inertial', 'measurement', 'unit', 'the', 'developed', 'system', 'titled', 'the', 'scannect', 'is', 'the', 'first', 'joint', 'statickinematic', 'indoor', '3d', 'mapper']] | [-0.113958864984378, 0.06115131867767892, -0.03681698898681518, 0.05288723357510425, -0.06187764858551533, -0.14009415433073127, 0.06629449393539558, 0.4237868496992389, -0.2065542336605804, -0.3571217868109824, 0.11283956102380843, -0.3261837772762691, -0.18372355560234316, 0.24563845758601813, -0.17782077042904065, 0.08500784646242555, 0.0806256009857695, -0.017283917920381933, 0.024339817084362204, -0.19432976223613646, 0.2653881095244851, 0.06342502130838243, 0.31834740443548687, 0.011160521505689117, 0.14761369660210594, 0.014027034456478465, -0.08993909527378774, -0.03664927961121143, -0.039073460853435625, 0.17537257118924507, 0.3764387685985921, 0.21392506233032818, 0.27906619623290296, -0.44900926171710165, -0.23750811959551255, 0.0853012710265343, 0.14193325933818313, 0.006009370314849305, -0.08936901094103364, -0.44269159514929207, 0.04625117891258232, -0.23084439532864104, -0.09360741647485067, -0.056670758355094095, 0.02359447201622099, 0.060698224267673115, -0.2391623184543995, -0.04663617409680459, -0.06652772023250729, 0.19122757703643029, -0.06555097282316509, -0.05660728019790094, 0.01296835300073185, 0.3091690915072678, -0.013766946279260159, 0.024184104477376744, 0.22675423046678933, -0.15678291491062288, -0.07938977455536664, 0.4464883750016001, 0.02213423440403397, -0.12411317869473222, 0.23256894202925868, -0.05243393648284632, -0.12107963446842533, 0.08685220732406096, 0.21629742577567068, 0.08067794234170513, -0.25518700203687794, 0.01698214614527746, -0.024685047852190237, 0.12447083375701995, 0.11639219654632181, 0.006429631377793323, 0.2605518956904785, 0.21198992388204893, 0.13296393803558576, 0.041008391229822756, -0.11084793035525495, -0.06929646047409362, -0.1478312915989565, -0.14442001302916357, -0.171641397378473, 0.006497095116007496, -0.07902141051239032, -0.09983494605632945, 0.3246444422935306, 0.2242030549800994, 0.1209888013742182, 0.021622430212618653, 0.41385988922606054, -0.01323454782553673, 0.07191553052586937, 0.09439773215833579, 0.1180494020547075, -0.0554312621210505, 0.24922839559706478, -0.08847508844624365, 0.07819110458441289, 0.034104933468690535] |
1,802.07867 | Interlayer Couplings Mediated by Antiferromagnetic Magnons | Collinear antiferromagnets (AFs) support two degenerate magnon excitations
carrying opposite spin polarizations, by which magnons can function as
electrons in various spin-related phenomena. In an insulating
ferromagnet(F)/AF/F trilayer, we explore the magnon-mediated interlayer
coupling by calculating the magnon thermal energy in the AF as a function of
the orientations of the Fs. The effect manifests as an interlayer exchange
interaction and a perpendicular magnetic anisotropy; they both depend on
temperature and the AF thickness. In particular, the exchange interaction turns
out to be antiferromagnetic at low temperatures and ferromagnetic at high
temperatures, whose magnitude can be $10-100$ $\mu$eV for nanoscale
separations, allowing experimental verification.
| cond-mat.mes-hall cond-mat.mtrl-sci quant-ph | collinear antiferromagnets afs support two degenerate magnon excitations carrying opposite spin polarizations by which magnons can function as electrons in various spinrelated phenomena in an insulating ferromagnetfaff trilayer we explore the magnonmediated interlayer coupling by calculating the magnon thermal energy in the af as a function of the orientations of the fs the effect manifests as an interlayer exchange interaction and a perpendicular magnetic anisotropy they both depend on temperature and the af thickness in particular the exchange interaction turns out to be antiferromagnetic at low temperatures and ferromagnetic at high temperatures whose magnitude can be 10100 muev for nanoscale separations allowing experimental verification | [['collinear', 'antiferromagnets', 'afs', 'support', 'two', 'degenerate', 'magnon', 'excitations', 'carrying', 'opposite', 'spin', 'polarizations', 'by', 'which', 'magnons', 'can', 'function', 'as', 'electrons', 'in', 'various', 'spinrelated', 'phenomena', 'in', 'an', 'insulating', 'ferromagnetfaff', 'trilayer', 'we', 'explore', 'the', 'magnonmediated', 'interlayer', 'coupling', 'by', 'calculating', 'the', 'magnon', 'thermal', 'energy', 'in', 'the', 'af', 'as', 'a', 'function', 'of', 'the', 'orientations', 'of', 'the', 'fs', 'the', 'effect', 'manifests', 'as', 'an', 'interlayer', 'exchange', 'interaction', 'and', 'a', 'perpendicular', 'magnetic', 'anisotropy', 'they', 'both', 'depend', 'on', 'temperature', 'and', 'the', 'af', 'thickness', 'in', 'particular', 'the', 'exchange', 'interaction', 'turns', 'out', 'to', 'be', 'antiferromagnetic', 'at', 'low', 'temperatures', 'and', 'ferromagnetic', 'at', 'high', 'temperatures', 'whose', 'magnitude', 'can', 'be', '10100', 'muev', 'for', 'nanoscale', 'separations', 'allowing', 'experimental', 'verification']] | [-0.24102082004933392, 0.29354432623328197, -0.018526210011100594, 0.06057585991842184, -0.06460438211882505, -0.1285426338085706, 0.033002877502828765, 0.4076859076661103, -0.2804714266427802, -0.29592310293640905, -0.023863112436408557, -0.31790850224714834, -0.036290362992694655, 0.2002667345884211, 0.14657367373482116, -0.0726558743315993, -0.0707367817482468, -0.03822136047924643, -0.10305817789303193, -0.1696160863542441, 0.25449128318758846, 0.008164558665334129, 0.32826535969755605, 0.1626216742815902, 0.055130899897369655, 0.03554083533738785, 0.18907393135347414, 0.015181738729543478, -0.14024613943240308, -0.015242413373537433, 0.30037027630091473, -0.20711605230490993, 0.1843265854850755, -0.4422686607802956, -0.14995264532315788, 0.006822424422617825, 0.1858177638015918, 0.15723193146048783, 0.006750383802002422, -0.2613203357543471, 0.020587894981907842, -0.18235570619569966, -0.10436367294219892, -0.11688616044945943, -0.035948582273880834, 0.008635411798519996, -0.25831508074968473, 0.10778061381893829, 0.08690848228187092, 0.11503431786900585, -0.08621065525193382, -0.14130593969224436, -0.14248287645326838, 0.06936849905087532, 0.09202142362934944, 0.06851861365501163, 0.15858993373666574, -0.12413139491188295, -0.14921062193286505, 0.3162472496731478, -0.06599749438012543, -0.1270310309471436, 0.176372978974188, -0.1688734252928096, -0.026148314949450562, 0.16093179997219478, 0.11946232467991508, 0.08974059207536714, -0.12891120278023327, 0.07173193682937937, 0.055347485924410876, 0.1511614401983007, 0.07426218566421455, 0.12256240712826873, 0.34730554917302814, 0.16653068762869366, 0.03641404349340501, 0.1597992648049574, -0.136041699164972, -0.056135696820119055, -0.20377438513754084, -0.1257140535219274, -0.2517976073132267, 0.0769620714076225, -0.13363225753060248, -0.1652183624852485, 0.3908786251327222, 0.17985857080089526, 0.18927627762110488, -0.09557458286250499, 0.28116879087321245, 0.12646535990954133, 0.08507125330546382, 0.038311510504287265, 0.30189940845819857, 0.19480992083491994, 0.1120636700042207, -0.30566227003633617, 0.0626514554475841, -0.024295525923732995] |
1,802.07868 | Magnetic-field enhanced high-thermoelectric performance in topological
Dirac semimetal Cd$_3$As$_2$ crystal | Thermoelectric materials can be used to convert heat to electric power
through the Seebeck effect. We study magneto-thermoelectric figure of merit
(ZT) in three-dimensional Dirac semimetal Cd$_3$As$_2$ crystal. It is found
that enhancement of power factor and reduction of thermal conductivity can be
realized at the same time through magnetic field although magnetoresistivity is
greatly increased. ZT can be highly enhanced from 0.17 to 1.1 by more than six
times around 350 K under a perpendicular magnetic field of 7 Tesla. The huge
enhancement of ZT by magnetic field arises from the linear Dirac band with
large Fermi velocity and the large electric thermal conductivity in
Cd$_3$As$_2$. Our work paves a new way to greatly enhance the thermoelectric
performance in the quantum topological materials.
| cond-mat.mtrl-sci cond-mat.str-el | thermoelectric materials can be used to convert heat to electric power through the seebeck effect we study magnetothermoelectric figure of merit zt in threedimensional dirac semimetal cd_3as_2 crystal it is found that enhancement of power factor and reduction of thermal conductivity can be realized at the same time through magnetic field although magnetoresistivity is greatly increased zt can be highly enhanced from 017 to 11 by more than six times around 350 k under a perpendicular magnetic field of 7 tesla the huge enhancement of zt by magnetic field arises from the linear dirac band with large fermi velocity and the large electric thermal conductivity in cd_3as_2 our work paves a new way to greatly enhance the thermoelectric performance in the quantum topological materials | [['thermoelectric', 'materials', 'can', 'be', 'used', 'to', 'convert', 'heat', 'to', 'electric', 'power', 'through', 'the', 'seebeck', 'effect', 'we', 'study', 'magnetothermoelectric', 'figure', 'of', 'merit', 'zt', 'in', 'threedimensional', 'dirac', 'semimetal', 'cd_3as_2', 'crystal', 'it', 'is', 'found', 'that', 'enhancement', 'of', 'power', 'factor', 'and', 'reduction', 'of', 'thermal', 'conductivity', 'can', 'be', 'realized', 'at', 'the', 'same', 'time', 'through', 'magnetic', 'field', 'although', 'magnetoresistivity', 'is', 'greatly', 'increased', 'zt', 'can', 'be', 'highly', 'enhanced', 'from', '017', 'to', '11', 'by', 'more', 'than', 'six', 'times', 'around', '350', 'k', 'under', 'a', 'perpendicular', 'magnetic', 'field', 'of', '7', 'tesla', 'the', 'huge', 'enhancement', 'of', 'zt', 'by', 'magnetic', 'field', 'arises', 'from', 'the', 'linear', 'dirac', 'band', 'with', 'large', 'fermi', 'velocity', 'and', 'the', 'large', 'electric', 'thermal', 'conductivity', 'in', 'cd_3as_2', 'our', 'work', 'paves', 'a', 'new', 'way', 'to', 'greatly', 'enhance', 'the', 'thermoelectric', 'performance', 'in', 'the', 'quantum', 'topological', 'materials']] | [-0.16034881973304907, 0.19704985541982517, -0.02468340480775242, -0.06776485226920716, -0.09476959075958978, -0.13232353620696813, 0.06938862512939639, 0.3716965815007326, -0.29983176265077127, -0.357832012683033, -0.023958906271277117, -0.30577314416727713, -0.12053171986894261, 0.3133069168806316, 0.013204175513237715, 0.029136069485121558, -0.03267799487953345, -0.04461867634146925, -0.09509942571880416, -0.2539721050697769, 0.21068837462488801, 0.08509009058358177, 0.34950422633799816, 0.10384325508634755, 0.010569686920667488, -0.04966776787947428, 0.12137459356481192, 0.11821494569190807, -0.08599027894999908, 0.04447291150779253, 0.2693285963107501, -0.1308407523169843, 0.18409071275363525, -0.3994028887921764, -0.19896814649954678, 0.031998533729253514, 0.13894942298816937, 0.08460323952773076, -0.05923679975791357, -0.23195961037849738, 0.11879565439284628, -0.15065476297205616, -0.09752857258107754, -0.12080197145170983, -0.0280597586956461, -0.06996374475889869, -0.22894530736225388, 0.11947676526840716, 0.010203709270084096, 0.10079758849385526, -0.04764372616210171, -0.1822419366404985, -0.04856288060921455, 0.009552125653792773, 0.06648690374042358, 0.06741087618866004, 0.23251213588481467, -0.16075275867478922, -0.10593168282761209, 0.42125704142475323, -0.1254120443018403, -0.10075251960886582, 0.08868176555035696, -0.23280172261800017, -0.028738441792572098, 0.2347209969546736, 0.15996884305974574, 0.05354057426654523, -0.1664935903879063, 0.0806546876866055, 0.02061512650764217, 0.14861660075539182, 0.055422667331332644, 0.05461928203341461, 0.2758663881423643, 0.16158285841623682, 0.06119470518540531, 0.17748624686951628, -0.13035023458031636, 0.05582412360649135, -0.16787723663653578, -0.25157005842324465, -0.22418808931815287, 0.17212709366914727, -0.13468809343941113, -0.11889654848228899, 0.4298735631380095, 0.21543990831536752, 0.15644820598554948, -0.09152074547995243, 0.23585311721469607, 0.1919221729162194, 0.1374543598823009, 0.07755681815286798, 0.2771920275483881, 0.16546931062569661, 0.18777057374527137, -0.294979844756815, 0.00734448054760334, -0.030482282775694564] |
1,802.07869 | End-to-end learning of keypoint detector and descriptor for pose
invariant 3D matching | Finding correspondences between images or 3D scans is at the heart of many
computer vision and image retrieval applications and is often enabled by
matching local keypoint descriptors. Various learning approaches have been
applied in the past to different stages of the matching pipeline, considering
detector, descriptor, or metric learning objectives. These objectives were
typically addressed separately and most previous work has focused on image
data. This paper proposes an end-to-end learning framework for keypoint
detection and its representation (descriptor) for 3D depth maps or 3D scans,
where the two can be jointly optimized towards task-specific objectives without
a need for separate annotations. We employ a Siamese architecture augmented by
a sampling layer and a novel score loss function which in turn affects the
selection of region proposals. The positive and negative examples are obtained
automatically by sampling corresponding region proposals based on their
consistency with known 3D pose labels. Matching experiments with depth data on
multiple benchmark datasets demonstrate the efficacy of the proposed approach,
showing significant improvements over state-of-the-art methods.
| cs.CV | finding correspondences between images or 3d scans is at the heart of many computer vision and image retrieval applications and is often enabled by matching local keypoint descriptors various learning approaches have been applied in the past to different stages of the matching pipeline considering detector descriptor or metric learning objectives these objectives were typically addressed separately and most previous work has focused on image data this paper proposes an endtoend learning framework for keypoint detection and its representation descriptor for 3d depth maps or 3d scans where the two can be jointly optimized towards taskspecific objectives without a need for separate annotations we employ a siamese architecture augmented by a sampling layer and a novel score loss function which in turn affects the selection of region proposals the positive and negative examples are obtained automatically by sampling corresponding region proposals based on their consistency with known 3d pose labels matching experiments with depth data on multiple benchmark datasets demonstrate the efficacy of the proposed approach showing significant improvements over stateoftheart methods | [['finding', 'correspondences', 'between', 'images', 'or', '3d', 'scans', 'is', 'at', 'the', 'heart', 'of', 'many', 'computer', 'vision', 'and', 'image', 'retrieval', 'applications', 'and', 'is', 'often', 'enabled', 'by', 'matching', 'local', 'keypoint', 'descriptors', 'various', 'learning', 'approaches', 'have', 'been', 'applied', 'in', 'the', 'past', 'to', 'different', 'stages', 'of', 'the', 'matching', 'pipeline', 'considering', 'detector', 'descriptor', 'or', 'metric', 'learning', 'objectives', 'these', 'objectives', 'were', 'typically', 'addressed', 'separately', 'and', 'most', 'previous', 'work', 'has', 'focused', 'on', 'image', 'data', 'this', 'paper', 'proposes', 'an', 'endtoend', 'learning', 'framework', 'for', 'keypoint', 'detection', 'and', 'its', 'representation', 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1,802.0787 | Progenitor Mass Distribution for Core-Collapse Supernova Remnants in M31
and M33 | Using the star formation histories (SFHs) near 94 supernova remnants (SNRs),
we infer the progenitor mass distribution for core-collapse supernovae. We use
Bayesian inference and model each SFH with multiple bursts of star formation
(SF), one of which is assumed to be associated with the SNR. Assuming
single-star evolution, the minimum mass of CCSNe is $7.33^{+0.02}_{-0.16}$
$\text{M}_\odot$, the slope of the progenitor mass distribution is $\alpha =
-2.96^{+0.45}_{-0.25}$, and the maximum mass is greater than
$\text{M}_\textrm{max} > 59$ $\text{M}_\odot$ with a 68% confidence. While
these results are consistent with previous inferences, they also provide
tighter constraints. The progenitor distribution is somewhat steeper than a
Salpeter initial mass function ($\alpha$ = -2.35). This suggests that either
SNR catalogs are biased against the youngest SF regions, or the most massive
stars do not explode as easily as lower mass stars. If SNR catalogs are biased,
it will most likely affect the slope but not the minimum mass. The
uncertainties are dominated by three primary sources of uncertainty, the SFH
resolution, the number of SF bursts, and the uncertainty on SF rate in each age
bin. We address the first two of these uncertainties, with an emphasis on
multiple bursts. The third will be addressed in future work.
| astro-ph.SR astro-ph.GA | using the star formation histories sfhs near 94 supernova remnants snrs we infer the progenitor mass distribution for corecollapse supernovae we use bayesian inference and model each sfh with multiple bursts of star formation sf one of which is assumed to be associated with the snr assuming singlestar evolution the minimum mass of ccsne is 733002_016 textm_odot the slope of the progenitor mass distribution is alpha 296045_025 and the maximum mass is greater than textm_textrmmax 59 textm_odot with a 68 confidence while these results are consistent with previous inferences they also provide tighter constraints the progenitor distribution is somewhat steeper than a salpeter initial mass function alpha 235 this suggests that either snr catalogs are biased against the youngest sf regions or the most massive stars do not explode as easily as lower mass stars if snr catalogs are biased it will most likely affect the slope but not the minimum mass the uncertainties are dominated by three primary sources of uncertainty the sfh resolution the number of sf bursts and the uncertainty on sf rate in each age bin we address the first two of these uncertainties with an emphasis on multiple bursts the third will be addressed in future work | [['using', 'the', 'star', 'formation', 'histories', 'sfhs', 'near', '94', 'supernova', 'remnants', 'snrs', 'we', 'infer', 'the', 'progenitor', 'mass', 'distribution', 'for', 'corecollapse', 'supernovae', 'we', 'use', 'bayesian', 'inference', 'and', 'model', 'each', 'sfh', 'with', 'multiple', 'bursts', 'of', 'star', 'formation', 'sf', 'one', 'of', 'which', 'is', 'assumed', 'to', 'be', 'associated', 'with', 'the', 'snr', 'assuming', 'singlestar', 'evolution', 'the', 'minimum', 'mass', 'of', 'ccsne', 'is', '733002_016', 'textm_odot', 'the', 'slope', 'of', 'the', 'progenitor', 'mass', 'distribution', 'is', 'alpha', '296045_025', 'and', 'the', 'maximum', 'mass', 'is', 'greater', 'than', 'textm_textrmmax', '59', 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1,802.07871 | Atomistic mechanism of graphene growth on SiC substrate: Large-scale
molecular dynamics simulation based on a new charge-transfer bond-order type
potential | Thermal decomposition of silicon carbide is a promising approach for the
fabrication of graphene. However, the atomistic growth mechanism of graphene
remains unclear. This paper describes the development of a new charge-transfer
interatomic potential. Carbon bonds with a wide variety of characteristics can
be reproduced by the proposed vectorized bond-order term. Large-scale thermal
decomposition simulation enables us to observe the continuous growth process of
the multi-ring carbon structure. The annealing simulation reveals the atomistic
process by which the multi-ring carbon structure is transformed to flat
graphene involving only 6-membered rings. Also, it is found that the surface
atoms of the silicon carbide substrate enhance the homogeneous graphene
formation.
| cond-mat.mtrl-sci | thermal decomposition of silicon carbide is a promising approach for the fabrication of graphene however the atomistic growth mechanism of graphene remains unclear this paper describes the development of a new chargetransfer interatomic potential carbon bonds with a wide variety of characteristics can be reproduced by the proposed vectorized bondorder term largescale thermal decomposition simulation enables us to observe the continuous growth process of the multiring carbon structure the annealing simulation reveals the atomistic process by which the multiring carbon structure is transformed to flat graphene involving only 6membered rings also it is found that the surface atoms of the silicon carbide substrate enhance the homogeneous graphene formation | [['thermal', 'decomposition', 'of', 'silicon', 'carbide', 'is', 'a', 'promising', 'approach', 'for', 'the', 'fabrication', 'of', 'graphene', 'however', 'the', 'atomistic', 'growth', 'mechanism', 'of', 'graphene', 'remains', 'unclear', 'this', 'paper', 'describes', 'the', 'development', 'of', 'a', 'new', 'chargetransfer', 'interatomic', 'potential', 'carbon', 'bonds', 'with', 'a', 'wide', 'variety', 'of', 'characteristics', 'can', 'be', 'reproduced', 'by', 'the', 'proposed', 'vectorized', 'bondorder', 'term', 'largescale', 'thermal', 'decomposition', 'simulation', 'enables', 'us', 'to', 'observe', 'the', 'continuous', 'growth', 'process', 'of', 'the', 'multiring', 'carbon', 'structure', 'the', 'annealing', 'simulation', 'reveals', 'the', 'atomistic', 'process', 'by', 'which', 'the', 'multiring', 'carbon', 'structure', 'is', 'transformed', 'to', 'flat', 'graphene', 'involving', 'only', '6membered', 'rings', 'also', 'it', 'is', 'found', 'that', 'the', 'surface', 'atoms', 'of', 'the', 'silicon', 'carbide', 'substrate', 'enhance', 'the', 'homogeneous', 'graphene', 'formation']] | [-0.10750085575057676, 0.1029400844471874, -0.07545380567252222, -0.03769553231470329, -0.017398595189054806, -0.1517082466442069, 0.03373164850334568, 0.43210948195687876, -0.3177078239085084, -0.25654858721665935, 0.024479721974650467, -0.23601387599127419, -0.1748136594650094, 0.16937124978371518, 0.026717961869306035, 0.019658507486046466, 0.09258306526182289, -0.14723799717440098, -0.033323062141857075, -0.2287397286078582, 0.24794862890202138, 0.10944337366769712, 0.360188603616768, 0.11440612151097783, 0.049008985645034246, -0.027107792268334714, 0.047901223267049146, -0.034523784148472327, -0.16016148752351, 0.15964515532228957, 0.20344486580816684, -0.04833793853133641, 0.23176883509451593, -0.4895964755538713, -0.24004995460725492, 0.019438493393223594, 0.13733143228347655, 0.15796681847401756, -0.09920619943403397, -0.20014342649287922, 0.0752899238443071, -0.1581817951174108, -0.12764690409379978, -0.06253000221180695, 0.00011778131765485914, -0.020280631914458894, -0.2145732971462335, 0.05657163097849763, 0.03458381468145591, 0.004602593214561542, -0.10043296153243217, -0.11028358269983006, -0.11452280701066936, 0.03439945347727863, -0.03454042985632205, -0.003650667008952479, 0.264433821145859, -0.07554966007699948, -0.08485182587551039, 0.42562352817643573, -0.049867419808395895, -0.1125826751727059, 0.21293068050268898, -0.13121113322106087, -0.06882798347484183, 0.1858561389337949, 0.09147841739037109, 0.09711055873237827, -0.1990881187386414, 0.09018567518365604, 0.0043522462731710185, 0.15963122287885873, 0.07822555939115032, 0.031853475732970295, 0.24581133905384275, 0.2947937040762217, 0.02141368864061035, 0.1676610750566599, -0.09500344787051694, -0.07891040209128901, -0.19137965667027015, -0.2269156041201549, -0.21011007738437643, 0.10128270282358345, -0.1054479198280239, -0.27678138609216724, 0.3963292730472016, 0.09512809488525684, 0.12192434392852226, -0.05106726780219038, 0.2519982211567737, 0.060686595996634826, 0.1113769917326324, -0.034604976975565985, 0.22157448452586928, 0.17369320597585844, 0.0983839017442531, -0.26062325278676496, 0.11495152214990446, -0.01593090697726304] |
1,802.07872 | Surfing its own wave: hydroelasticity of a particle near a membrane | We show using theory and experiments that a small particle moving along an
elastic membrane through a viscous fluid is repelled from the membrane due to
hydro-elastic forces. The viscous stress field produces an elastic disturbance
leading to particle-wave coupling. We derive an analytic expression for the
particle trajectory in the lubrication limit, bypassing the construction of the
detailed velocity and pressure fields. The normal force is quadratic in the
parallel speed, and is a function of the tension and bending resistance of the
membrane. Experimentally, we measure the normal displacement of spheres
sedimenting along an elastic membrane and find quantitative agreement with the
theoretical predictions with no fitting parameters. We experimentally
demonstrate the effect to be strong enough for particle separation and sorting.
We discuss the significance of these results for bio-membranes and propose our
model for membrane elasticity measurements.
| cond-mat.soft physics.bio-ph physics.flu-dyn | we show using theory and experiments that a small particle moving along an elastic membrane through a viscous fluid is repelled from the membrane due to hydroelastic forces the viscous stress field produces an elastic disturbance leading to particlewave coupling we derive an analytic expression for the particle trajectory in the lubrication limit bypassing the construction of the detailed velocity and pressure fields the normal force is quadratic in the parallel speed and is a function of the tension and bending resistance of the membrane experimentally we measure the normal displacement of spheres sedimenting along an elastic membrane and find quantitative agreement with the theoretical predictions with no fitting parameters we experimentally demonstrate the effect to be strong enough for particle separation and sorting we discuss the significance of these results for biomembranes and propose our model for membrane elasticity measurements | [['we', 'show', 'using', 'theory', 'and', 'experiments', 'that', 'a', 'small', 'particle', 'moving', 'along', 'an', 'elastic', 'membrane', 'through', 'a', 'viscous', 'fluid', 'is', 'repelled', 'from', 'the', 'membrane', 'due', 'to', 'hydroelastic', 'forces', 'the', 'viscous', 'stress', 'field', 'produces', 'an', 'elastic', 'disturbance', 'leading', 'to', 'particlewave', 'coupling', 'we', 'derive', 'an', 'analytic', 'expression', 'for', 'the', 'particle', 'trajectory', 'in', 'the', 'lubrication', 'limit', 'bypassing', 'the', 'construction', 'of', 'the', 'detailed', 'velocity', 'and', 'pressure', 'fields', 'the', 'normal', 'force', 'is', 'quadratic', 'in', 'the', 'parallel', 'speed', 'and', 'is', 'a', 'function', 'of', 'the', 'tension', 'and', 'bending', 'resistance', 'of', 'the', 'membrane', 'experimentally', 'we', 'measure', 'the', 'normal', 'displacement', 'of', 'spheres', 'sedimenting', 'along', 'an', 'elastic', 'membrane', 'and', 'find', 'quantitative', 'agreement', 'with', 'the', 'theoretical', 'predictions', 'with', 'no', 'fitting', 'parameters', 'we', 'experimentally', 'demonstrate', 'the', 'effect', 'to', 'be', 'strong', 'enough', 'for', 'particle', 'separation', 'and', 'sorting', 'we', 'discuss', 'the', 'significance', 'of', 'these', 'results', 'for', 'biomembranes', 'and', 'propose', 'our', 'model', 'for', 'membrane', 'elasticity', 'measurements']] | [-0.12876511139940497, 0.15635675563789073, -0.1055929736359745, 0.00040107353752254384, -0.048461302594737486, -0.10357928457868068, -0.0034072883693412183, 0.36858842963128224, -0.28817297557058436, -0.26862262195498016, 0.019180507125029115, -0.27715758228317855, -0.16286991406166068, 0.18866105959750712, -0.03284852381742804, 0.0667372488132711, 0.046108313370496035, 0.014192090482048109, -0.00984285127021478, -0.12079756898336536, 0.24707666337275416, 0.0679746272508055, 0.2948143629898839, 0.11490837483277135, 0.13275314199388133, 0.018982425787823, 0.007653520660514527, 0.08980880611648796, -0.20823064477023784, 0.08741804644306923, 0.15972556283281364, -0.01045323161289413, 0.20415057898466046, -0.5000697494689244, -0.20172097330317662, 0.048609912184113306, 0.10832286766418157, 0.17157376975115018, -0.07048140252537444, -0.23534459662326473, 0.034906830477647165, -0.12872062857322236, -0.1591109631596305, -0.07404389817280867, 0.040973606807549634, 0.030782616056554708, -0.2659739432592236, 0.15160155193450867, 0.030806276201706458, 0.06381787409087815, -0.1365446132766281, -0.06986897560298866, -0.012259390238170506, 0.09218102413500455, 0.12207207369786549, 0.029779221027006284, 0.22057437044461026, -0.16259263165737667, -0.05658155353079345, 0.37982165228232, -0.082672106892247, -0.24914245869541632, 0.2080878993052104, -0.10425664616190558, -0.02770766314343675, 0.1456929155268726, 0.16487954323120574, 0.06592792422793052, -0.14050659104679705, 0.04377439849001045, -0.009002037878075601, 0.17187733152478352, 0.09097956061356616, -0.0841132724597899, 0.21320840564444132, 0.18169159126461398, 0.03729038506891605, 0.16127713273712005, -0.1410799637498377, -0.09497055705266853, -0.3449355011264272, -0.18958608909358984, -0.14397657642814707, 0.0102518359620243, -0.14664276145947255, -0.20531152524978769, 0.3282315075522989, 0.11350606580707409, 0.19496887847649078, 0.10288422316946882, 0.3064151815987516, 0.09981966324163773, 0.0413212481108395, 0.045863065469006065, 0.33854294053761036, 0.17012157591872235, 0.07589187939050245, -0.2734300960136036, 0.033072182489228795, 0.02499629564398358] |
1,802.07873 | Charge Transfer Database for Bio-molecule Tight Binding Model Derived
from Thousands of Proteins | The anisotropic feature of charge transfer reactions in realistic proteins
cannot be ignored, due to the highly complex chemical structure of
bio-molecules. In this work, we have performed the first large-scale
quantitative assessment of charge transfer preference in protein complexes by
calculating the charge transfer couplings in all 20*20 possible amino acid side
chain combinations, which are extracted from available high-quality structures
of thousands of protein complexes. The charge transfer database quantitatively
shows distinct features of charge transfer couplings among millions of amino
acid side-chains combinations. The knowledge graph of charge transfer couplings
reveals that only one average or representative structure cannot be regarded as
the typical charge transfer preference in realistic proteins. This data driven
model provides us an alternative route to comprehensively understand the
pairwise charge transfer coupling parameters based structural similarity,
without any require of the knowledge of chemical intuition about the chemical
interactions.
| physics.chem-ph cond-mat.soft | the anisotropic feature of charge transfer reactions in realistic proteins cannot be ignored due to the highly complex chemical structure of biomolecules in this work we have performed the first largescale quantitative assessment of charge transfer preference in protein complexes by calculating the charge transfer couplings in all 2020 possible amino acid side chain combinations which are extracted from available highquality structures of thousands of protein complexes the charge transfer database quantitatively shows distinct features of charge transfer couplings among millions of amino acid sidechains combinations the knowledge graph of charge transfer couplings reveals that only one average or representative structure cannot be regarded as the typical charge transfer preference in realistic proteins this data driven model provides us an alternative route to comprehensively understand the pairwise charge transfer coupling parameters based structural similarity without any require of the knowledge of chemical intuition about the chemical interactions | [['the', 'anisotropic', 'feature', 'of', 'charge', 'transfer', 'reactions', 'in', 'realistic', 'proteins', 'can', 'not', 'be', 'ignored', 'due', 'to', 'the', 'highly', 'complex', 'chemical', 'structure', 'of', 'biomolecules', 'in', 'this', 'work', 'we', 'have', 'performed', 'the', 'first', 'largescale', 'quantitative', 'assessment', 'of', 'charge', 'transfer', 'preference', 'in', 'protein', 'complexes', 'by', 'calculating', 'the', 'charge', 'transfer', 'couplings', 'in', 'all', '2020', 'possible', 'amino', 'acid', 'side', 'chain', 'combinations', 'which', 'are', 'extracted', 'from', 'available', 'highquality', 'structures', 'of', 'thousands', 'of', 'protein', 'complexes', 'the', 'charge', 'transfer', 'database', 'quantitatively', 'shows', 'distinct', 'features', 'of', 'charge', 'transfer', 'couplings', 'among', 'millions', 'of', 'amino', 'acid', 'sidechains', 'combinations', 'the', 'knowledge', 'graph', 'of', 'charge', 'transfer', 'couplings', 'reveals', 'that', 'only', 'one', 'average', 'or', 'representative', 'structure', 'can', 'not', 'be', 'regarded', 'as', 'the', 'typical', 'charge', 'transfer', 'preference', 'in', 'realistic', 'proteins', 'this', 'data', 'driven', 'model', 'provides', 'us', 'an', 'alternative', 'route', 'to', 'comprehensively', 'understand', 'the', 'pairwise', 'charge', 'transfer', 'coupling', 'parameters', 'based', 'structural', 'similarity', 'without', 'any', 'require', 'of', 'the', 'knowledge', 'of', 'chemical', 'intuition', 'about', 'the', 'chemical', 'interactions']] | [-0.12044082400420268, 0.10166010361615234, -0.01543510946540487, 0.07706598317931912, -0.060499353656207754, -0.13264172192937976, 0.053439835070838666, 0.4089313537732467, -0.2922063617492032, -0.34943955452900205, -0.0317879489305798, -0.30184219923025096, -0.13753911146062783, 0.11238085809507525, 0.04410219863807195, -0.010070652215766576, 0.08684128615380134, 0.020689104180533015, -0.03010546729857752, -0.16170695030240612, 0.2990630610202183, 0.06978327986603015, 0.2776460443067071, 0.10772464638138378, 0.04837939017624188, -0.014900175548289846, -0.021524473124702504, -0.03243427690518583, -0.1235308285223749, 0.1846178373784427, 0.29209681365313944, 0.08775775710233306, 0.1925371822888569, -0.4746187316791323, -0.2701584840780937, 0.10266681771800422, 0.13965350557423364, 0.18276988782048, -0.08142648044748595, -0.22240807127907572, 0.06595577220369955, -0.18057872346233603, -0.048658317673776375, -0.12606454685161628, -0.007841348185535245, 0.05742181378147946, -0.263751623849697, 0.1041867357300557, 0.03432248098050688, 0.10015192231625919, -0.08727164449945292, -0.15611118157456735, -0.11039546036455256, 0.23819210727374077, 0.025313441290820155, -0.010957656828249061, 0.23167332102882132, -0.11650357602614185, -0.10771518675711994, 0.3753815942362651, -0.030878610394882575, -0.22506974708138897, 0.19057971686624842, -0.09817292482510909, -0.13241279163966643, 0.1762537844182186, 0.11480836116477547, 0.1591393076095905, -0.23474833283076477, 0.026726976537064417, 0.023506461898952523, 0.23560534964234336, 0.07412896248794805, 0.031438150499391075, 0.25470698818301896, 0.18759465584181398, 0.0026378133006068885, 0.09044631952404251, -0.051845198415919835, -0.12385647359886988, -0.18610792354549338, -0.14905663029034466, -0.20004307292011136, 0.09712826200286645, -0.11145917074004776, -0.152495658275165, 0.4029339701874844, 0.16878051029564956, 0.21439093485124558, -0.05051354937577283, 0.24912323596365374, -0.035253250187781686, 0.13926362286434327, -0.029358454489292914, 0.18809976368429976, 0.09663770242669188, 0.10602927241386884, -0.24555706302322847, 0.14552514426778976, 0.012275698460363502] |
1,802.07874 | Regularity of biased 1D random walks in random environment | We study the asymptotic properties of nearest-neighbor random walks in 1d
random environment under the influence of an external field of intensity
$\lambda\in\mathbb{R}$. For ergodic shift-invariant environments, we show that
the limiting velocity $v(\lambda)$ is always increasing and that it is
everywhere analytic except at most in two points $\lambda_-$ and $\lambda_+$.
When $\lambda_-$ and $\lambda_+$ are distinct, $v(\lambda)$ might fail to be
continuous. We refine the assumptions in \cite{Z} for having a recentered CLT
with diffusivity $\sigma^2(\lambda)$ and give explicit conditions for
$\sigma^2(\lambda)$ to be analytic. For the random conductance model we show
that, in contrast with the deterministic case, $\sigma^2(\lambda)$ is not
monotone on the positive (resp.~negative) half-line and that it is not
differentiable at $\lambda=0$. For this model we also prove the Einstein
Relation, both in discrete and continuous time, extending the result of
\cite{LD16}.
| math.PR | we study the asymptotic properties of nearestneighbor random walks in 1d random environment under the influence of an external field of intensity lambdainmathbbr for ergodic shiftinvariant environments we show that the limiting velocity vlambda is always increasing and that it is everywhere analytic except at most in two points lambda_ and lambda_ when lambda_ and lambda_ are distinct vlambda might fail to be continuous we refine the assumptions in citez for having a recentered clt with diffusivity sigma2lambda and give explicit conditions for sigma2lambda to be analytic for the random conductance model we show that in contrast with the deterministic case sigma2lambda is not monotone on the positive respnegative halfline and that it is not differentiable at lambda0 for this model we also prove the einstein relation both in discrete and continuous time extending the result of citeld16 | [['we', 'study', 'the', 'asymptotic', 'properties', 'of', 'nearestneighbor', 'random', 'walks', 'in', '1d', 'random', 'environment', 'under', 'the', 'influence', 'of', 'an', 'external', 'field', 'of', 'intensity', 'lambdainmathbbr', 'for', 'ergodic', 'shiftinvariant', 'environments', 'we', 'show', 'that', 'the', 'limiting', 'velocity', 'vlambda', 'is', 'always', 'increasing', 'and', 'that', 'it', 'is', 'everywhere', 'analytic', 'except', 'at', 'most', 'in', 'two', 'points', 'lambda_', 'and', 'lambda_', 'when', 'lambda_', 'and', 'lambda_', 'are', 'distinct', 'vlambda', 'might', 'fail', 'to', 'be', 'continuous', 'we', 'refine', 'the', 'assumptions', 'in', 'citez', 'for', 'having', 'a', 'recentered', 'clt', 'with', 'diffusivity', 'sigma2lambda', 'and', 'give', 'explicit', 'conditions', 'for', 'sigma2lambda', 'to', 'be', 'analytic', 'for', 'the', 'random', 'conductance', 'model', 'we', 'show', 'that', 'in', 'contrast', 'with', 'the', 'deterministic', 'case', 'sigma2lambda', 'is', 'not', 'monotone', 'on', 'the', 'positive', 'respnegative', 'halfline', 'and', 'that', 'it', 'is', 'not', 'differentiable', 'at', 'lambda0', 'for', 'this', 'model', 'we', 'also', 'prove', 'the', 'einstein', 'relation', 'both', 'in', 'discrete', 'and', 'continuous', 'time', 'extending', 'the', 'result', 'of', 'citeld16']] | [-0.12039639500503921, 0.13966303382178868, -0.07678726872922305, 0.061681615522555897, -0.035088081084027445, -0.1696040552581989, -0.0018054322503945406, 0.42274291514802503, -0.25175458068620443, -0.17611684820012136, 0.10541178872517776, -0.27107617404630324, -0.14194838245919741, 0.2063857550452025, -0.05985661068082075, 0.033976133131492295, 0.011434704321265384, 0.07145510236595702, -0.04566433306043858, -0.2449436162800446, 0.31718420056516633, -0.028047081918510443, 0.21122337783933343, 0.0679972813848187, 0.08251612754333217, 0.007826901263529983, 0.021546698005883682, 0.023876094723270985, -0.16572591325251884, 0.023273123948670486, 0.214760394381729, 0.05363074435359415, 0.2504518214649151, -0.36993158518966723, -0.18719763764666447, 0.1884374260005322, 0.12974358332918629, 0.06700173919842414, -0.005026371164764415, -0.26126138369984214, 0.12577944192847046, -0.09850162325892597, -0.1541680920182604, -0.0471423757947324, 0.06182206757383777, 0.06793990209938355, -0.3342476323219564, 0.11734351042383316, 0.11211806117995259, 0.03955651331788806, -0.08386747836416095, -0.10298996677225017, -0.02252568894319291, 0.11093745440153083, 0.054476176393697694, 0.04998381968385622, 0.08291505726725411, -0.09194764302297057, -0.042623174859566945, 0.3385077734676409, -0.1066399035283693, -0.2549248076427509, 0.1902134335571592, -0.19547408046748707, -0.16181806564289966, 0.09189431714099448, 0.1113782705142512, 0.10187083900125478, -0.11537637582670654, 0.1473904224292389, -0.07595556683030308, 0.12200937130461063, 0.08471398312694338, 0.023728041240246966, 0.13279689618331544, 0.08303061360664502, 0.1451180706362185, 0.11267891486161663, -0.0299273839670658, -0.110261638477609, -0.31765957392224875, -0.15321272504447467, -0.1955431140051908, 0.0912017041908471, -0.133779062091087, -0.19322890758870498, 0.3325606409343891, 0.17302558684776373, 0.2213232203742818, 0.1537353993489352, 0.23041121063151343, 0.1731798525844865, -0.027053115656599402, 0.1191915258874788, 0.17613764102776153, 0.12155103336964898, 0.06290988464196048, -0.1794113084427355, 0.0644173573476591, 0.0730784265050555] |
1,802.07875 | The stationary distribution of a sample from the Wright-Fisher diffusion
model with general small mutation rates | The stationary distribution of a sample taken from a Wright-Fisher diffusion
with general small mutation rates is found using a coalescent approach. The
approximation is equivalent to having at most one mutation in the coalescent
tree to the first order in the rates. The sample probabilities characterize an
approximation for the stationary distribution from the Wright-Fisher diffusion.
The approach is different from Burden and Tang (2016,2017) who use a
probability flux argument to obtain the same results from a forward diffusion
generator equation. The solution has interest because the solution is not known
when rates are not small. An analogous solution is found for the configuration
of alleles in a general exchangeable binary coalescent tree. In particular an
explicit solution is found for a pure birth process tree when individuals
reproduce at rate lambda.
| q-bio.PE | the stationary distribution of a sample taken from a wrightfisher diffusion with general small mutation rates is found using a coalescent approach the approximation is equivalent to having at most one mutation in the coalescent tree to the first order in the rates the sample probabilities characterize an approximation for the stationary distribution from the wrightfisher diffusion the approach is different from burden and tang 20162017 who use a probability flux argument to obtain the same results from a forward diffusion generator equation the solution has interest because the solution is not known when rates are not small an analogous solution is found for the configuration of alleles in a general exchangeable binary coalescent tree in particular an explicit solution is found for a pure birth process tree when individuals reproduce at rate lambda | [['the', 'stationary', 'distribution', 'of', 'a', 'sample', 'taken', 'from', 'a', 'wrightfisher', 'diffusion', 'with', 'general', 'small', 'mutation', 'rates', 'is', 'found', 'using', 'a', 'coalescent', 'approach', 'the', 'approximation', 'is', 'equivalent', 'to', 'having', 'at', 'most', 'one', 'mutation', 'in', 'the', 'coalescent', 'tree', 'to', 'the', 'first', 'order', 'in', 'the', 'rates', 'the', 'sample', 'probabilities', 'characterize', 'an', 'approximation', 'for', 'the', 'stationary', 'distribution', 'from', 'the', 'wrightfisher', 'diffusion', 'the', 'approach', 'is', 'different', 'from', 'burden', 'and', 'tang', '20162017', 'who', 'use', 'a', 'probability', 'flux', 'argument', 'to', 'obtain', 'the', 'same', 'results', 'from', 'a', 'forward', 'diffusion', 'generator', 'equation', 'the', 'solution', 'has', 'interest', 'because', 'the', 'solution', 'is', 'not', 'known', 'when', 'rates', 'are', 'not', 'small', 'an', 'analogous', 'solution', 'is', 'found', 'for', 'the', 'configuration', 'of', 'alleles', 'in', 'a', 'general', 'exchangeable', 'binary', 'coalescent', 'tree', 'in', 'particular', 'an', 'explicit', 'solution', 'is', 'found', 'for', 'a', 'pure', 'birth', 'process', 'tree', 'when', 'individuals', 'reproduce', 'at', 'rate', 'lambda']] | [-0.024134796846018575, 0.09110279250210203, -0.08298721584602635, 0.12931852535665941, -0.035505501039103785, -0.14120883488012895, 0.08962305025857832, 0.34556340070357966, -0.27362302149413154, -0.23080491359039806, 0.09367064191653991, -0.2754962172519082, -0.10897793151324645, 0.15196414403061367, -0.06392202185077676, 0.02629326391398712, 0.1030939741358995, 0.08259731314297933, 0.04169471253234365, -0.22670123195571046, 0.29790120836479395, 0.08590880588197441, 0.30823517504579095, -0.05116636072521779, 0.1181099611098197, -0.026377703622678546, -0.027911092147731513, -0.023220660581962385, -0.1323906919196137, 0.03673535196584955, 0.24445499933442907, 0.12047154104003488, 0.29435222281782486, -0.36667416168239103, -0.17215086764364101, 0.10478815307176964, 0.15962156558881946, 0.2173908351044824, -0.051818714157414084, -0.23666336074203892, 0.06606978391741973, -0.16017638769612383, -0.15351041973874308, 0.02042475476193784, 0.0503621679633411, 0.04072235061078152, -0.35356762561662153, 0.06895516213001822, 0.05725076616700016, -0.0003892341906677431, -0.05740808741599599, -0.136813907900568, -0.020979313982595036, 0.12700908180237608, 0.08298878998946531, 0.03225438711719949, 0.08671128445951296, -0.11386722605849213, -0.11806421223749865, 0.3335176559943539, -0.08466164536735933, -0.23445409722973717, 0.20919180409843796, -0.19572781133395967, -0.142719444954323, 0.21326853477903432, 0.1409888101451502, 0.16130673522894173, -0.231238928565507, 0.10623338541889966, -0.02814032597972928, 0.12622346786031527, 0.08582468329817612, -0.04932650114294948, 0.1471937821635893, 0.1804732310519651, 0.07408510751799861, 0.11294305493269782, -0.08296679376985934, -0.14640602571611752, -0.2518598516471684, -0.13262449645214894, -0.19493626643827103, 0.0918270785141295, -0.13990095127780083, -0.17971357321992182, 0.3130884091647814, 0.11453554724384822, 0.2043249867369991, 0.13128513655687835, 0.21278123405706414, 0.17526864839384138, 0.033448278507801577, 0.09149261496252199, 0.14850392798656847, 0.139037086155766, 0.07200574253532868, -0.19079261624129185, 0.17332939568684616, 0.09205152766445457] |
1,802.07876 | Federated Meta-Learning with Fast Convergence and Efficient
Communication | Statistical and systematic challenges in collaboratively training machine
learning models across distributed networks of mobile devices have been the
bottlenecks in the real-world application of federated learning. In this work,
we show that meta-learning is a natural choice to handle these issues, and
propose a federated meta-learning framework FedMeta, where a parameterized
algorithm (or meta-learner) is shared, instead of a global model in previous
approaches. We conduct an extensive empirical evaluation on LEAF datasets and a
real-world production dataset, and demonstrate that FedMeta achieves a
reduction in required communication cost by 2.82-4.33 times with faster
convergence, and an increase in accuracy by 3.23%-14.84% as compared to
Federated Averaging (FedAvg) which is a leading optimization algorithm in
federated learning. Moreover, FedMeta preserves user privacy since only the
parameterized algorithm is transmitted between mobile devices and central
servers, and no raw data is collected onto the servers.
| cs.LG cs.IR | statistical and systematic challenges in collaboratively training machine learning models across distributed networks of mobile devices have been the bottlenecks in the realworld application of federated learning in this work we show that metalearning is a natural choice to handle these issues and propose a federated metalearning framework fedmeta where a parameterized algorithm or metalearner is shared instead of a global model in previous approaches we conduct an extensive empirical evaluation on leaf datasets and a realworld production dataset and demonstrate that fedmeta achieves a reduction in required communication cost by 282433 times with faster convergence and an increase in accuracy by 3231484 as compared to federated averaging fedavg which is a leading optimization algorithm in federated learning moreover fedmeta preserves user privacy since only the parameterized algorithm is transmitted between mobile devices and central servers and no raw data is collected onto the servers | [['statistical', 'and', 'systematic', 'challenges', 'in', 'collaboratively', 'training', 'machine', 'learning', 'models', 'across', 'distributed', 'networks', 'of', 'mobile', 'devices', 'have', 'been', 'the', 'bottlenecks', 'in', 'the', 'realworld', 'application', 'of', 'federated', 'learning', 'in', 'this', 'work', 'we', 'show', 'that', 'metalearning', 'is', 'a', 'natural', 'choice', 'to', 'handle', 'these', 'issues', 'and', 'propose', 'a', 'federated', 'metalearning', 'framework', 'fedmeta', 'where', 'a', 'parameterized', 'algorithm', 'or', 'metalearner', 'is', 'shared', 'instead', 'of', 'a', 'global', 'model', 'in', 'previous', 'approaches', 'we', 'conduct', 'an', 'extensive', 'empirical', 'evaluation', 'on', 'leaf', 'datasets', 'and', 'a', 'realworld', 'production', 'dataset', 'and', 'demonstrate', 'that', 'fedmeta', 'achieves', 'a', 'reduction', 'in', 'required', 'communication', 'cost', 'by', '282433', 'times', 'with', 'faster', 'convergence', 'and', 'an', 'increase', 'in', 'accuracy', 'by', '3231484', 'as', 'compared', 'to', 'federated', 'averaging', 'fedavg', 'which', 'is', 'a', 'leading', 'optimization', 'algorithm', 'in', 'federated', 'learning', 'moreover', 'fedmeta', 'preserves', 'user', 'privacy', 'since', 'only', 'the', 'parameterized', 'algorithm', 'is', 'transmitted', 'between', 'mobile', 'devices', 'and', 'central', 'servers', 'and', 'no', 'raw', 'data', 'is', 'collected', 'onto', 'the', 'servers']] | [-0.11828568095544642, -0.030708352597159806, -0.059123224473860064, 0.019077446528146386, -0.07748595146055688, -0.17862872047100584, 0.09610809959654867, 0.4265206268476978, -0.2747991284368638, -0.3663521720142379, 0.06222597061013672, -0.30320864942082215, -0.15081464488249482, 0.19588896102586786, -0.16122082792038858, 0.10095793995547148, 0.13537341675681758, 0.02366009578649873, -0.04222440576667792, -0.3271450649317301, 0.2599686585042075, 0.03962153081067274, 0.3505669113602752, 0.036741570192454776, 0.1114984041442242, -0.03643887518891986, -0.029361008584063212, -0.007155918122702082, -0.024631378441433337, 0.16382567526470923, 0.3436126088420256, 0.23496996881735419, 0.38126502237872967, -0.43289368952506446, -0.18828738039411919, 0.10222810055342385, 0.16947708242494142, 0.061507545713385285, -0.06528043474929905, -0.30793799412056383, 0.10295950953396116, -0.21005968802319971, 0.020677600023344907, -0.1306000778690951, -0.007389163493480481, -0.0029797592515152104, -0.31575965872821465, 0.015029948660579155, 0.02916793532105504, 0.092461818578312, -0.01345838335589473, -0.06228364440678081, 0.05039262200679473, 0.11325607240088546, 0.04662920670128021, 0.05032917834706867, 0.16395260603167117, -0.14728196785280245, -0.19559489049568352, 0.35894808869703976, -0.008933199897513424, -0.17469258425416243, 0.17120782331838993, 0.011294000739441581, -0.184092296756358, 0.08191974932478714, 0.27920324319947354, 0.11045183956870665, -0.18503912997392702, 0.08064627946841425, -0.04609334843625105, 0.18568500061355478, 0.02643345137008689, -0.03628148656581532, 0.11690884594097209, 0.2795971566811204, 0.10440930944021372, 0.13326427544480268, -0.07519279658986243, -0.13790967820448355, -0.20334867298812934, -0.13854505404383993, -0.2129374367486633, -0.005560910247240058, -0.11214969489769765, -0.11609541670694737, 0.3348311886820995, 0.2147370997986848, 0.21567782065437607, 0.09761776124733061, 0.39439684651057483, 0.025285177984648764, 0.12424070838655174, 0.18141367951978626, 0.1403910407589906, -0.034474884356621285, 0.1676768857504497, -0.17335681547410786, 0.09246090113047616, -0.015118419015648919] |
1,802.07877 | Pooling homogeneous ensembles to build heterogeneous ones | In ensemble methods, the outputs of a collection of diverse classifiers are
combined in the expectation that the global prediction be more accurate than
the individual ones. Heterogeneous ensembles consist of predictors of different
types, which are likely to have different biases. If these biases are
complementary, the combination of their decisions is beneficial. In this work,
a family of heterogeneous ensembles is built by pooling classifiers from M
homogeneous ensembles of different types of size T. Depending on the fraction
of base classifiers of each type, a particular heterogeneous combination in
this family is represented by a point in a regular simplex in M dimensions. The
M vertices of this simplex represent the different homogeneous ensembles. A
displacement away from one of these vertices effects a smooth transformation of
the corresponding homogeneous ensemble into a heterogeneous one. The optimal
composition of such heterogeneous ensemble can be determined using
cross-validation or, if bootstrap samples are used to build the individual
classifiers, out-of-bag data. An empirical analysis of such combinations of
bootstraped ensembles composed of neural networks, SVMs, and random trees (i.e.
from a standard random forest) illustrates the gains that can be achieved by
this heterogeneous ensemble creation method.
| cs.LG cs.AI stat.ML | in ensemble methods the outputs of a collection of diverse classifiers are combined in the expectation that the global prediction be more accurate than the individual ones heterogeneous ensembles consist of predictors of different types which are likely to have different biases if these biases are complementary the combination of their decisions is beneficial in this work a family of heterogeneous ensembles is built by pooling classifiers from m homogeneous ensembles of different types of size t depending on the fraction of base classifiers of each type a particular heterogeneous combination in this family is represented by a point in a regular simplex in m dimensions the m vertices of this simplex represent the different homogeneous ensembles a displacement away from one of these vertices effects a smooth transformation of the corresponding homogeneous ensemble into a heterogeneous one the optimal composition of such heterogeneous ensemble can be determined using crossvalidation or if bootstrap samples are used to build the individual classifiers outofbag data an empirical analysis of such combinations of bootstraped ensembles composed of neural networks svms and random trees ie from a standard random forest illustrates the gains that can be achieved by this heterogeneous ensemble creation method | [['in', 'ensemble', 'methods', 'the', 'outputs', 'of', 'a', 'collection', 'of', 'diverse', 'classifiers', 'are', 'combined', 'in', 'the', 'expectation', 'that', 'the', 'global', 'prediction', 'be', 'more', 'accurate', 'than', 'the', 'individual', 'ones', 'heterogeneous', 'ensembles', 'consist', 'of', 'predictors', 'of', 'different', 'types', 'which', 'are', 'likely', 'to', 'have', 'different', 'biases', 'if', 'these', 'biases', 'are', 'complementary', 'the', 'combination', 'of', 'their', 'decisions', 'is', 'beneficial', 'in', 'this', 'work', 'a', 'family', 'of', 'heterogeneous', 'ensembles', 'is', 'built', 'by', 'pooling', 'classifiers', 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1,802.07878 | A semi-analytical model of the Galilean satellites' dynamics | The Galilean satellites' dynamics has been studied extensively during the
last century. In the past it was common to use analytical expansions in order
to get simple models to integrate, but with the new generation computers it
became prevalent the numerical integration of very sophisticated and almost
complete equations of motion. In this article we aim to describe the resonant
and secular motion of the Galilean satellites through a Hamiltonian, depending
on the slow angles only, obtained with an analytical expansion of the
perturbing functions and an averaging operation. In order to have a model as
near as possible to the actual dynamics, we added perturbations and we
considered terms that in similar studies of the past were neglected, such as
the terms involving the inclinations and the Sun's perturbation. Moreover, we
added the tidal dissipation into the equations, in order to investigate how
well the model captures the evolution of the system.
| astro-ph.EP | the galilean satellites dynamics has been studied extensively during the last century in the past it was common to use analytical expansions in order to get simple models to integrate but with the new generation computers it became prevalent the numerical integration of very sophisticated and almost complete equations of motion in this article we aim to describe the resonant and secular motion of the galilean satellites through a hamiltonian depending on the slow angles only obtained with an analytical expansion of the perturbing functions and an averaging operation in order to have a model as near as possible to the actual dynamics we added perturbations and we considered terms that in similar studies of the past were neglected such as the terms involving the inclinations and the suns perturbation moreover we added the tidal dissipation into the equations in order to investigate how well the model captures the evolution of the system | [['the', 'galilean', 'satellites', 'dynamics', 'has', 'been', 'studied', 'extensively', 'during', 'the', 'last', 'century', 'in', 'the', 'past', 'it', 'was', 'common', 'to', 'use', 'analytical', 'expansions', 'in', 'order', 'to', 'get', 'simple', 'models', 'to', 'integrate', 'but', 'with', 'the', 'new', 'generation', 'computers', 'it', 'became', 'prevalent', 'the', 'numerical', 'integration', 'of', 'very', 'sophisticated', 'and', 'almost', 'complete', 'equations', 'of', 'motion', 'in', 'this', 'article', 'we', 'aim', 'to', 'describe', 'the', 'resonant', 'and', 'secular', 'motion', 'of', 'the', 'galilean', 'satellites', 'through', 'a', 'hamiltonian', 'depending', 'on', 'the', 'slow', 'angles', 'only', 'obtained', 'with', 'an', 'analytical', 'expansion', 'of', 'the', 'perturbing', 'functions', 'and', 'an', 'averaging', 'operation', 'in', 'order', 'to', 'have', 'a', 'model', 'as', 'near', 'as', 'possible', 'to', 'the', 'actual', 'dynamics', 'we', 'added', 'perturbations', 'and', 'we', 'considered', 'terms', 'that', 'in', 'similar', 'studies', 'of', 'the', 'past', 'were', 'neglected', 'such', 'as', 'the', 'terms', 'involving', 'the', 'inclinations', 'and', 'the', 'suns', 'perturbation', 'moreover', 'we', 'added', 'the', 'tidal', 'dissipation', 'into', 'the', 'equations', 'in', 'order', 'to', 'investigate', 'how', 'well', 'the', 'model', 'captures', 'the', 'evolution', 'of', 'the', 'system']] | [-0.13084892922361058, 0.07261624504538905, -0.08679600661541366, 0.07219869756288948, -0.05984154559391874, -0.03342707035150014, -0.021588496982539986, 0.34796991431020396, -0.26095771021095526, -0.3123070445106505, 0.1280485016668179, -0.2590768830424625, -0.1662462984388268, 0.19168928596404156, -0.04497663416516255, 0.05899931734208675, 0.04375698032265444, 0.06704690248790665, -0.07530677579898765, -0.2649570654931606, 0.28114670571061523, 0.09635751816182354, 0.17931551959828224, -0.010328098481788842, 0.10434204619073498, 0.005978663450447855, -0.017347557289111946, 0.006063059605414572, -0.15068050337601735, 0.08812710614814089, 0.18827181916174215, 0.07989693866293951, 0.2618809844750692, -0.48707396863028407, -0.22177965413121617, 0.061799496702174196, 0.17027861360777047, 0.13524541185767042, -0.017195400682253628, -0.2681616183577312, 0.04146878922805555, -0.2037116947242978, -0.17145885511307546, -0.10424983107600531, 0.04981710485127919, 0.013351263624488139, -0.22336081542330338, 0.06418911262348391, 0.06823092264205437, 0.05047754632929961, -0.0726807531063731, -0.06461658807139649, -0.029149073576311173, 0.16335518769859, 0.10197946580972986, -0.007877841597922097, 0.09192829471944339, -0.11643615563771402, -0.08424872628358357, 0.42209641872585624, -0.08537318436291945, -0.17937009018888467, 0.22767199659293968, -0.17859175527967464, -0.10999797994356139, 0.09756545139799272, 0.18910445243095844, 0.11478764201313549, -0.17593945932325, 0.05674990262110334, 0.011321447445749262, 0.11807735899944174, 0.08032977708091874, 0.007035721875605435, 0.19797683365375193, 0.1509562548131262, 0.023583196245097353, 0.11391477871783613, -0.07765217039740212, -0.15543093014656098, -0.27247783129736536, -0.12258070947836744, -0.13528342434704255, 0.026945250638413663, -0.03788918015968246, -0.14957467507376196, 0.4180691830838233, 0.1883139531736816, 0.19177129582556732, 0.008177595042617492, 0.3261227008454453, 0.15503000687530835, 0.10781212219530169, 0.06805338939116184, 0.2969492254048294, 0.12745268221828915, 0.1131665691477703, -0.21693572051537047, 0.06551860599760331, 0.03884145864315964] |
1,802.07879 | Work of a multi-cathode counter in a single electron counting mode | We describe a work of a multi-cathode counter of the developed design in a
single electron counting mode with a cathode made of aluminum alloy. The
results of the calibration of the counter are presented. The coefficient of gas
amplification was found from the calibration spectra. The electric fields and
operation of this detector in two configurations are described and the original
idea to find the effect from electrons emitted from the surface of a cathode by
difference of the rates measured in two volume configurations is expounded.
Furthermore, the advantage of using a multi-cathode counter for measurement of
the intensity of single electron emission from a metal is explained.
| physics.ins-det nucl-ex | we describe a work of a multicathode counter of the developed design in a single electron counting mode with a cathode made of aluminum alloy the results of the calibration of the counter are presented the coefficient of gas amplification was found from the calibration spectra the electric fields and operation of this detector in two configurations are described and the original idea to find the effect from electrons emitted from the surface of a cathode by difference of the rates measured in two volume configurations is expounded furthermore the advantage of using a multicathode counter for measurement of the intensity of single electron emission from a metal is explained | [['we', 'describe', 'a', 'work', 'of', 'a', 'multicathode', 'counter', 'of', 'the', 'developed', 'design', 'in', 'a', 'single', 'electron', 'counting', 'mode', 'with', 'a', 'cathode', 'made', 'of', 'aluminum', 'alloy', 'the', 'results', 'of', 'the', 'calibration', 'of', 'the', 'counter', 'are', 'presented', 'the', 'coefficient', 'of', 'gas', 'amplification', 'was', 'found', 'from', 'the', 'calibration', 'spectra', 'the', 'electric', 'fields', 'and', 'operation', 'of', 'this', 'detector', 'in', 'two', 'configurations', 'are', 'described', 'and', 'the', 'original', 'idea', 'to', 'find', 'the', 'effect', 'from', 'electrons', 'emitted', 'from', 'the', 'surface', 'of', 'a', 'cathode', 'by', 'difference', 'of', 'the', 'rates', 'measured', 'in', 'two', 'volume', 'configurations', 'is', 'expounded', 'furthermore', 'the', 'advantage', 'of', 'using', 'a', 'multicathode', 'counter', 'for', 'measurement', 'of', 'the', 'intensity', 'of', 'single', 'electron', 'emission', 'from', 'a', 'metal', 'is', 'explained']] | [-0.09301572478090582, 0.13635191384872253, -0.07762890454085375, 0.0038159177551278845, 0.03125954382121563, -0.10265222003429451, 0.04008944328366355, 0.35321810509670865, -0.2083972265901552, -0.3226077618924054, 0.0484720007029616, -0.3146637445231053, -0.05977470354939049, 0.2396880772747946, -0.03112188631838018, 0.028201687928627837, 0.015460124645720828, -0.0011134611421518704, -0.05378090338358148, -0.16904397706331856, 0.2849252939647572, 0.08323944192379713, 0.2942915821109306, 0.04862848237495531, 0.12747066893283443, -0.021494007131762125, -0.060235455581410365, 0.05609821752719158, -0.06937177988531237, 0.10080724065615372, 0.21923733199734918, 0.055516197253018616, 0.2006545858627016, -0.42680512045256114, -0.18044873476875098, 0.00920637223806063, 0.0753177104094489, 0.10281545968980274, -0.10550841089676727, -0.2460161900422959, 0.02982671263373711, -0.18779659117995337, -0.14144935888576915, 0.04021519811993295, -0.029387254221364855, 0.06703323560597545, -0.2646857215938243, 0.012058656142008576, 0.061022671788338236, 0.04334535997953604, -0.0593594645911997, -0.10058843551457605, -0.01065301654691046, 0.07184540620920334, 0.04258741757155142, 0.0009263637391003696, 0.17468408067202704, -0.102964998267337, -0.11360459104815329, 0.3604960799217224, -0.07534247753633694, -0.15607400188137863, 0.13080833936956796, -0.188724031066522, -0.02848877952518788, 0.19570093805139716, 0.12815371302739634, 0.10290563552301715, -0.1771974387620999, 0.0241946917355976, -0.0048076389526779005, 0.17832693466493352, 0.08930542637509378, 0.007898105707400562, 0.21088025818832895, 0.2026735167278358, -0.010721983375366438, 0.20255905233418822, -0.1862581049854105, -0.01361444910607216, -0.28977619502693414, -0.18166210526515814, -0.189376708643712, 0.0490673616274514, -0.0095216245387829, -0.15978363117266617, 0.4224658238024197, 0.10472755128179084, 0.18727589150552046, -0.04292371919039976, 0.32141532853076404, 0.09750968323046849, 0.08194787886829792, 0.003866662588817152, 0.300397726774893, 0.1521500554972921, 0.10199323550544002, -0.25318166132677683, 0.05152646660889414, 0.04569080572744662] |
1,802.0788 | Reflection Positivity Then and Now | We review the discovery of reflection positivity. We also explain a new
geometric approach and proof of the reflection positivity property.
| math.HO hep-th math-ph math.MP | we review the discovery of reflection positivity we also explain a new geometric approach and proof of the reflection positivity property | [['we', 'review', 'the', 'discovery', 'of', 'reflection', 'positivity', 'we', 'also', 'explain', 'a', 'new', 'geometric', 'approach', 'and', 'proof', 'of', 'the', 'reflection', 'positivity', 'property']] | [-0.14213400813085691, 0.016407870997985203, -0.17900427173645722, 0.057877179833927324, -0.2312017941758746, -0.1380984307532864, 0.09544537713130315, 0.3284452891065961, -0.29651997096481775, -0.27125941021811395, 0.14300748932042293, -0.18254739223491578, -0.24075964629827512, 0.12797794326962458, -0.12890413470034087, 0.026366209345204488, 0.003449510960351853, -0.031051732422340484, -0.12103512382046097, -0.21472744235680216, 0.3718207492714837, -0.0013346792686553229, 0.2751385676009314, 0.23418836016762293, 0.14219993672200612, 0.07885812067737182, -0.12561799568079768, -0.036411109424772714, -0.20597825744854553, 0.179526673186393, 0.11538232429440887, 0.17332812904247216, 0.17062937503769285, -0.3612764240020797, -0.140609754471197, 0.051441455348616556, 0.1000358167802915, 0.11778206837230495, -0.13691718419570298, -0.2582211373817353, 0.07817926013930923, -0.19588571112780345, -0.27151103424174444, -0.10805849841840211, -0.05342070988955952, -0.04769064352980682, -0.16327727949690252, 0.06820738143592496, 0.19727004337168874, 0.09461294868517489, -0.10286184081009456, -0.02974056547862433, 0.016362546810082028, -0.0036134697452542327, 0.051528664039714, -0.16002415728178762, 0.05212745181329194, -0.11036019823292181, -0.15145009568160667, 0.3492099026750241, -0.0003353547127473922, -0.10723433288789931, 0.18420455664662377, -0.1559666066563555, -0.2516842704443705, 0.11272314558958724, 0.13598459249451048, 0.11698251084557601, -0.12503278490510725, 0.09689389239896887, -0.14772440759199007, 0.07204030826687813, 0.10780062096282131, 0.11252020068821453, 0.1328762728898298, 0.06939752018522649, 0.08020205458714849, 0.12567038284171195, -0.03957168536172027, -0.040811222490100635, -0.4547445381592427, -0.27575593672337984, -0.1617091651562424, 0.09459328438554492, -0.045014092321036425, -0.15711581015161105, 0.42344883864834193, 0.1698036892783074, 0.21048327304777645, 0.0894650057113419, 0.2902334777948757, 0.17130708960550173, 0.009173377173110134, -0.03133894946603548, 0.1959420432824464, 0.2700413928500244, 0.08460750217948641, -0.20830081021856695, 0.07459768546479088, 0.1428034329742548] |
1,802.07881 | Diversity regularization in deep ensembles | Calibrating the confidence of supervised learning models is important for a
variety of contexts where the certainty over predictions should be reliable.
However, it has been reported that deep neural network models are often too
poorly calibrated for achieving complex tasks requiring reliable uncertainty
estimates in their prediction. In this work, we are proposing a strategy for
training deep ensembles with a diversity function regularization, which
improves the calibration property while maintaining a similar prediction
accuracy.
| cs.LG | calibrating the confidence of supervised learning models is important for a variety of contexts where the certainty over predictions should be reliable however it has been reported that deep neural network models are often too poorly calibrated for achieving complex tasks requiring reliable uncertainty estimates in their prediction in this work we are proposing a strategy for training deep ensembles with a diversity function regularization which improves the calibration property while maintaining a similar prediction accuracy | [['calibrating', 'the', 'confidence', 'of', 'supervised', 'learning', 'models', 'is', 'important', 'for', 'a', 'variety', 'of', 'contexts', 'where', 'the', 'certainty', 'over', 'predictions', 'should', 'be', 'reliable', 'however', 'it', 'has', 'been', 'reported', 'that', 'deep', 'neural', 'network', 'models', 'are', 'often', 'too', 'poorly', 'calibrated', 'for', 'achieving', 'complex', 'tasks', 'requiring', 'reliable', 'uncertainty', 'estimates', 'in', 'their', 'prediction', 'in', 'this', 'work', 'we', 'are', 'proposing', 'a', 'strategy', 'for', 'training', 'deep', 'ensembles', 'with', 'a', 'diversity', 'function', 'regularization', 'which', 'improves', 'the', 'calibration', 'property', 'while', 'maintaining', 'a', 'similar', 'prediction', 'accuracy']] | [-0.03304308630820168, 0.02169332826068919, -0.07073259470053017, 0.12684867716100262, -0.09614786973198582, -0.2163383991359488, 0.061825429028096165, 0.48747534197019904, -0.21176287173416072, -0.3744707186951449, 0.09732628166736838, -0.23006362975329944, -0.13098263894330317, 0.21060684053717474, -0.14963645764969682, 0.14766821172088385, 0.15423823167618952, 0.021733927614006558, -0.08622545937970771, -0.2831463474584253, 0.2507098438218236, 0.10761978499833372, 0.33221124276812924, 0.00020275472687851441, 0.12995295243729887, -0.04665447830063242, -0.03616366204560587, 0.012837519536811956, -0.046281624843973794, 0.18245121073222867, 0.34274700421682563, 0.17063424266617452, 0.3633863511985462, -0.3294447930659915, -0.31465390358904477, 0.16942254649352675, 0.16968729475660152, 0.12660458219684906, -0.01106043887863818, -0.26576156014772623, 0.08257277765752453, -0.16648548333844365, -0.005064414642555149, -0.1663363508598291, -0.013778818299454687, -0.006546186120862043, -0.33275626295883404, 0.07133213996176462, 0.05051872859659948, 0.09228669669430115, -0.03946351789330181, -0.13621656140496366, 0.035497220294353996, 0.17872134555670383, 0.01690176152317834, 0.08404808371989547, 0.10351604050083552, -0.2227065616232147, -0.08687633548795834, 0.3586400139978842, -0.0421327193096084, -0.2277852970873937, 0.19324454486272052, -0.03742170955152496, -0.2053761860159667, 0.09301392723940999, 0.19477449203106134, 0.10567301465198398, -0.1966713934426049, 0.0120717702237399, -0.014157563484715004, 0.16081871792649557, 0.016906942363436286, 0.027070424194741798, 0.20252598651782855, 0.32304426165003525, 0.005643285100201243, 0.0270875567358943, -0.08696984264411424, -0.09235788508024263, -0.21061747193973707, -0.07588173114498586, -0.15374004530818447, 0.002797250292803112, -0.11310408197612942, -0.14251488773152232, 0.3595878388732672, 0.21166323310401486, 0.22365084627802534, 0.14995283861552658, 0.34710429099045303, 0.0810668635194337, 0.12375523860407013, 0.07737676722095593, 0.2815715539174179, 0.042216457478628545, 0.061154164424423424, -0.10743937681208511, 0.18279804991509177, 0.008497835002153328] |
1,802.07882 | Production of $N^*(1535)$ and $N^*(1650)$ in
$\Lambda_c\rightarrow\bar{K}^0\eta p$ $(\pi N)$ decay | In order to study the properties of the $N^*$(1535) and $N^*$(1650) we
calculate the mass distributions of $M B$ in the $\Lambda_c \rightarrow
\bar{K}^0 M B$ decay, with $MB=\pi N(I=1/2),\eta p$ and $K\Sigma(I=1/2)$. We do
this by calculating the tree-level and loop contributions, mixing
pseudoscalar-baryon and vector-baryon channels using the local hidden gauge
formalism. The loop contributions for each channel are calculated using the
chiral unitary approach. We observe that for the $\eta N$ mass distribution
only the $N^*$(1535) is seen, with the $N^*$(1650) contributing to the width of
the curve, but for the $\pi N$ mass distribution both resonances are clearly
visible. In the case of $MB=K\Sigma$, we found that the strength of the
$K\Sigma$ mass distribution is smaller than that of the mass distributions of
the $\pi N$ and $\eta p$ in the $\Lambda_c^+\rightarrow\bar{K}^0\pi N$ and
$\Lambda_c^+\rightarrow\bar{K}^0\eta p$ processes, in spite of this channel
having a large coupling to the $N^*(1650)$. This is because the $K\Sigma$ pair
production is suppressed in the primary production from the $\Lambda_c$ decay.
| nucl-th hep-ph | in order to study the properties of the n1535 and n1650 we calculate the mass distributions of m b in the lambda_c rightarrow bark0 m b decay with mbpi ni12eta p and ksigmai12 we do this by calculating the treelevel and loop contributions mixing pseudoscalarbaryon and vectorbaryon channels using the local hidden gauge formalism the loop contributions for each channel are calculated using the chiral unitary approach we observe that for the eta n mass distribution only the n1535 is seen with the n1650 contributing to the width of the curve but for the pi n mass distribution both resonances are clearly visible in the case of mbksigma we found that the strength of the ksigma mass distribution is smaller than that of the mass distributions of the pi n and eta p in the lambda_crightarrowbark0pi n and lambda_crightarrowbark0eta p processes in spite of this channel having a large coupling to the n1650 this is because the ksigma pair production is suppressed in the primary production from the lambda_c decay | [['in', 'order', 'to', 'study', 'the', 'properties', 'of', 'the', 'n1535', 'and', 'n1650', 'we', 'calculate', 'the', 'mass', 'distributions', 'of', 'm', 'b', 'in', 'the', 'lambda_c', 'rightarrow', 'bark0', 'm', 'b', 'decay', 'with', 'mbpi', 'ni12eta', 'p', 'and', 'ksigmai12', 'we', 'do', 'this', 'by', 'calculating', 'the', 'treelevel', 'and', 'loop', 'contributions', 'mixing', 'pseudoscalarbaryon', 'and', 'vectorbaryon', 'channels', 'using', 'the', 'local', 'hidden', 'gauge', 'formalism', 'the', 'loop', 'contributions', 'for', 'each', 'channel', 'are', 'calculated', 'using', 'the', 'chiral', 'unitary', 'approach', 'we', 'observe', 'that', 'for', 'the', 'eta', 'n', 'mass', 'distribution', 'only', 'the', 'n1535', 'is', 'seen', 'with', 'the', 'n1650', 'contributing', 'to', 'the', 'width', 'of', 'the', 'curve', 'but', 'for', 'the', 'pi', 'n', 'mass', 'distribution', 'both', 'resonances', 'are', 'clearly', 'visible', 'in', 'the', 'case', 'of', 'mbksigma', 'we', 'found', 'that', 'the', 'strength', 'of', 'the', 'ksigma', 'mass', 'distribution', 'is', 'smaller', 'than', 'that', 'of', 'the', 'mass', 'distributions', 'of', 'the', 'pi', 'n', 'and', 'eta', 'p', 'in', 'the', 'lambda_crightarrowbark0pi', 'n', 'and', 'lambda_crightarrowbark0eta', 'p', 'processes', 'in', 'spite', 'of', 'this', 'channel', 'having', 'a', 'large', 'coupling', 'to', 'the', 'n1650', 'this', 'is', 'because', 'the', 'ksigma', 'pair', 'production', 'is', 'suppressed', 'in', 'the', 'primary', 'production', 'from', 'the', 'lambda_c', 'decay']] | [-0.14399461446630926, 0.23846698767170538, -0.0673584969964151, 0.07973802132920998, 0.018702828210335587, -0.11254802162236557, 0.05377409853063887, 0.3197935803498073, -0.2229504246014829, -0.25895780543001684, -0.04443496960448101, -0.3228250045283902, -0.06303989835489518, 0.10371263799748792, 0.0761624607257545, 0.0474618874325576, 0.02809111810879918, 0.08317867714184814, -0.040374713963346284, -0.17127576807695555, 0.33410235182041437, -0.004780349301787593, 0.19515386212577407, 0.090163016299967, -0.021433732889751655, 0.029742431423694985, -0.022346962635865344, -0.09089026074833804, -0.14257830035763264, 0.06164797618502479, 0.18332933144723407, 0.07917924113174128, 0.13687748149911896, -0.30827212029295725, -0.10932358094738093, 0.15288180294560222, 0.19889406862146244, 0.05563342784355372, 0.009438229393974946, -0.285924208848794, 0.14162330515966637, -0.15706417335924217, -0.11333595513914167, -0.026304061161127032, 0.0794118688748468, -0.05226194940467661, -0.3437880588519364, 0.07395299806305003, 0.022275838910079584, -0.001737093447889315, -0.006476294107326284, -0.21258205410998837, -0.06432175010914074, 0.12324858297133909, 0.11248976966968124, 0.05581891113216421, 0.13231471043488965, -0.1481704716364819, -0.0774189076278495, 0.3784298055191956, -0.08654008391740939, -0.18785034211156548, 0.1165785233429122, -0.23010827967664227, -0.11696506693970593, 0.1733342019199371, 0.1624714597589734, 0.11096946784137555, -0.13261321667445505, 0.1401358736918887, -0.035352557470238334, 0.16326666185021876, 0.07734269951470196, 0.05228283276736009, 0.1481922607991004, 0.12800251290190784, -0.02339822692631903, 0.07725050422737784, -0.12561813149907877, -0.07559105465699714, -0.3626364487175057, -0.14069298747059603, -0.12923009591404258, 0.07470692796689435, -0.050558349966084326, -0.08932642370928079, 0.3463064495377561, 0.0733640639327194, 0.2965635421867596, 0.05197014203635839, 0.2776435552982659, 0.13965337544043616, 0.09361136110468268, 0.07942823887938952, 0.2580468856116257, 0.21590091266652298, 0.06305452882562106, -0.3058821829390803, 0.04618083160773783, -0.006883332335458296] |
1,802.07883 | Non-invasive imaging through random media | When waves propagate through a strongly scattering medium the energy is
transferred to the incoherent wave part by scattering. The wave intensity then
forms a random speckle pattern seemingly without much useful information.
However, a number of recent physical experiments show how one can extract
useful information from this speckle pattern. Here we present the mathematical
analysis that explains the quite stunning performance of such a scheme for
speckle imaging. Our analysis identifies a scaling regime where the scheme
works well. This regime is the white-noise paraxial regime, which leads to the
Ito-Schrodinger model for the wave amplitude. The results presented in this
paper conform with the sophisticated physical intuition that has motivated
these schemes, but give a more detailed characterization of the performance.
The analysis gives a description of (i) the information that can be extracted
and with what resolution (ii) the statistical stability or signal-to-noise
ratio with which the information can be extracted.
| physics.optics math.PR | when waves propagate through a strongly scattering medium the energy is transferred to the incoherent wave part by scattering the wave intensity then forms a random speckle pattern seemingly without much useful information however a number of recent physical experiments show how one can extract useful information from this speckle pattern here we present the mathematical analysis that explains the quite stunning performance of such a scheme for speckle imaging our analysis identifies a scaling regime where the scheme works well this regime is the whitenoise paraxial regime which leads to the itoschrodinger model for the wave amplitude the results presented in this paper conform with the sophisticated physical intuition that has motivated these schemes but give a more detailed characterization of the performance the analysis gives a description of i the information that can be extracted and with what resolution ii the statistical stability or signaltonoise ratio with which the information can be extracted | [['when', 'waves', 'propagate', 'through', 'a', 'strongly', 'scattering', 'medium', 'the', 'energy', 'is', 'transferred', 'to', 'the', 'incoherent', 'wave', 'part', 'by', 'scattering', 'the', 'wave', 'intensity', 'then', 'forms', 'a', 'random', 'speckle', 'pattern', 'seemingly', 'without', 'much', 'useful', 'information', 'however', 'a', 'number', 'of', 'recent', 'physical', 'experiments', 'show', 'how', 'one', 'can', 'extract', 'useful', 'information', 'from', 'this', 'speckle', 'pattern', 'here', 'we', 'present', 'the', 'mathematical', 'analysis', 'that', 'explains', 'the', 'quite', 'stunning', 'performance', 'of', 'such', 'a', 'scheme', 'for', 'speckle', 'imaging', 'our', 'analysis', 'identifies', 'a', 'scaling', 'regime', 'where', 'the', 'scheme', 'works', 'well', 'this', 'regime', 'is', 'the', 'whitenoise', 'paraxial', 'regime', 'which', 'leads', 'to', 'the', 'itoschrodinger', 'model', 'for', 'the', 'wave', 'amplitude', 'the', 'results', 'presented', 'in', 'this', 'paper', 'conform', 'with', 'the', 'sophisticated', 'physical', 'intuition', 'that', 'has', 'motivated', 'these', 'schemes', 'but', 'give', 'a', 'more', 'detailed', 'characterization', 'of', 'the', 'performance', 'the', 'analysis', 'gives', 'a', 'description', 'of', 'i', 'the', 'information', 'that', 'can', 'be', 'extracted', 'and', 'with', 'what', 'resolution', 'ii', 'the', 'statistical', 'stability', 'or', 'signaltonoise', 'ratio', 'with', 'which', 'the', 'information', 'can', 'be', 'extracted']] | [-0.10021333754918868, 0.10252692868872997, -0.14960923017032685, 0.06450398155683351, -0.07868627525805946, -0.1241891032685676, 0.03003525413016999, 0.3419015285528956, -0.27865721132763993, -0.2858211832601697, 0.09622403112795926, -0.2603099639888012, -0.19651787948584365, 0.2093097011393477, -0.026515426940374797, 0.03682702813868321, 0.07967398948066177, 0.026523612307444697, -0.04204220938676548, -0.18950947975108942, 0.31075504796068754, 0.08790724469769386, 0.3139524484954534, 0.0392717900776094, 0.05977092186109193, 0.03369721778247866, -0.053069603115680715, 0.03746355910815539, -0.11635691394288686, 0.09673548934740886, 0.26696141092482234, 0.1314620665304603, 0.23438299888023925, -0.42091790519414407, -0.2757278814581373, 0.058263922548822816, 0.17135911274761442, 0.15618410374398434, -0.06517378496683969, -0.2811160253180611, 0.02946533020660882, -0.10925782446659381, -0.1233771872286114, -0.09593562959663329, -0.02788353194632838, 0.02692722277340269, -0.28499064465323765, 0.07242468913506356, 0.08147915675635299, 0.026358881580733483, 0.004860459032633733, -0.0665513846542566, 0.02583640240913918, 0.10079623912404773, 0.031791452296649016, 0.03828897895291448, 0.11201361725707688, -0.1463935202242987, -0.06293796583589527, 0.38755050844122324, -0.05098726730493288, -0.2025537474201091, 0.18134456573414706, -0.16051161534363223, -0.09051242741125246, 0.17683279781692451, 0.14881603230587057, 0.07510468113882046, -0.1426964693902729, 0.007044713780088651, -0.06614959528941977, 0.2185228771995753, 0.06995833179380204, 0.10159103494257696, 0.1963756243878555, 0.19143911455457488, 0.010429323074077406, 0.11759955699765874, -0.12699545161918768, -0.06841061746761684, -0.27769368751154794, -0.08716618147708716, -0.1680929006715756, 0.05606620354707458, -0.08260442786089581, -0.12004866775485777, 0.40507585391145945, 0.20195762062925965, 0.20717175897331008, 0.04672380925096091, 0.3500501384057345, 0.13600694508096503, 0.04363001224795176, 0.04792769581920678, 0.2594702814795798, 0.11996706095223705, 0.15104727782008628, -0.1999852599681265, 0.06422706675460382, 0.007906773181316714] |
1,802.07884 | Single-pulse observations of the Galactic Center magnetar PSR
J1745$-$2900 at 3.1 GHz | We report on single-pulse observations of the Galactic Center magnetar PSR
J1745$-$2900 that were made using the Parkes 64-m radio telescope with a
central frequency of 3.1 GHz at five observing epochs between 2013 July and
August. The shape of the integrated pulse profiles was relatively stable across
the five observations, indicating that the pulsar was in a stable state between
MJDs 56475 and 56514. This extends the known stable state of this pulsar to 6.8
months. Short term pulse shape variations were also detected. It is shown that
this pulsar switches between two emission modes frequently and that the typical
duration of each mode is about ten minutes. No giant pulses or subpulse
drifting were observed. Apparent nulls in the pulse emission were detected on
MJD 56500. Although there are many differences between the radio emission of
magnetars and normal radio pulsars, they also share some properties. The
detection of mode changing and pulse nulling in PSR J1745$-$2900 suggests that
the basic radio emission process for magnetars and normal pulsars is the same.
| astro-ph.HE | we report on singlepulse observations of the galactic center magnetar psr j17452900 that were made using the parkes 64m radio telescope with a central frequency of 31 ghz at five observing epochs between 2013 july and august the shape of the integrated pulse profiles was relatively stable across the five observations indicating that the pulsar was in a stable state between mjds 56475 and 56514 this extends the known stable state of this pulsar to 68 months short term pulse shape variations were also detected it is shown that this pulsar switches between two emission modes frequently and that the typical duration of each mode is about ten minutes no giant pulses or subpulse drifting were observed apparent nulls in the pulse emission were detected on mjd 56500 although there are many differences between the radio emission of magnetars and normal radio pulsars they also share some properties the detection of mode changing and pulse nulling in psr j17452900 suggests that the basic radio emission process for magnetars and normal pulsars is the same | [['we', 'report', 'on', 'singlepulse', 'observations', 'of', 'the', 'galactic', 'center', 'magnetar', 'psr', 'j17452900', 'that', 'were', 'made', 'using', 'the', 'parkes', '64m', 'radio', 'telescope', 'with', 'a', 'central', 'frequency', 'of', '31', 'ghz', 'at', 'five', 'observing', 'epochs', 'between', '2013', 'july', 'and', 'august', 'the', 'shape', 'of', 'the', 'integrated', 'pulse', 'profiles', 'was', 'relatively', 'stable', 'across', 'the', 'five', 'observations', 'indicating', 'that', 'the', 'pulsar', 'was', 'in', 'a', 'stable', 'state', 'between', 'mjds', '56475', 'and', '56514', 'this', 'extends', 'the', 'known', 'stable', 'state', 'of', 'this', 'pulsar', 'to', '68', 'months', 'short', 'term', 'pulse', 'shape', 'variations', 'were', 'also', 'detected', 'it', 'is', 'shown', 'that', 'this', 'pulsar', 'switches', 'between', 'two', 'emission', 'modes', 'frequently', 'and', 'that', 'the', 'typical', 'duration', 'of', 'each', 'mode', 'is', 'about', 'ten', 'minutes', 'no', 'giant', 'pulses', 'or', 'subpulse', 'drifting', 'were', 'observed', 'apparent', 'nulls', 'in', 'the', 'pulse', 'emission', 'were', 'detected', 'on', 'mjd', '56500', 'although', 'there', 'are', 'many', 'differences', 'between', 'the', 'radio', 'emission', 'of', 'magnetars', 'and', 'normal', 'radio', 'pulsars', 'they', 'also', 'share', 'some', 'properties', 'the', 'detection', 'of', 'mode', 'changing', 'and', 'pulse', 'nulling', 'in', 'psr', 'j17452900', 'suggests', 'that', 'the', 'basic', 'radio', 'emission', 'process', 'for', 'magnetars', 'and', 'normal', 'pulsars', 'is', 'the', 'same']] | [-0.13516697984621778, 0.1811290869927742, -0.062223499973048595, 0.0950966376817925, -0.147436095456108, -0.11364270933517064, 0.06639901118363901, 0.4975005922919379, -0.16190369485207556, -0.3320757669739817, 0.10951400331251476, -0.2854231554328611, -0.06254968193784487, 0.2591506819967834, -0.014216500557741226, -0.05188203985770151, 0.1062130967008048, -0.053270148431980295, -0.027677440925294325, -0.18397712675837202, 0.19483230654858272, 0.07307753019846366, 0.2313917235318811, -0.04735011676032292, 0.11664896517411985, -0.10523650454689493, -0.036386604638693976, -0.08482600361032532, -0.042545207714560176, 0.015668482073087093, 0.24074625060893595, 0.1348661959813962, 0.16504600466561248, -0.4059666983009866, -0.21125369377203465, 0.06355698104493036, 0.11681740238244118, -0.0073861904295599795, 0.004598328469958352, -0.3263375284912729, 0.06413185077430734, -0.21206748450095955, -0.16493747978640055, 0.11798627566572072, 0.11172337575450714, 0.08987734809978075, -0.1323049496859312, 0.098592112404199, 0.03858232881590637, 0.0806613957171726, -0.12833922383054133, -0.0696465750715058, 0.023020881085863545, 0.08732908854549697, 0.08471972878858289, 0.044700483756809774, 0.12283572191692485, -0.06445010637249035, -0.13706024932506228, 0.3189661605637629, -0.04600498886855199, 0.05338785435176558, 0.1827501919779556, -0.2651079984283761, -0.21271585466133225, 0.1947784971007369, 0.10470174802521691, 0.08159099107016592, -0.14435187454555967, -0.04657934228440322, -0.01111661876437434, 0.27049731737961286, 0.1582327827903829, 0.049709779699877644, 0.3048438038459124, 0.10850685592761197, 0.022480388335020373, 0.15013874311283318, -0.31515155761769553, -0.029372776044367225, -0.2377289275322872, -0.024123596713731165, -0.12306351037233065, 0.08841545748175803, -0.060749640107755305, -0.08927808425369488, 0.47071060799715814, 0.059214436863031655, 0.11958456165783586, 0.023532145160858994, 0.2797337642582188, 0.12491674408485448, 0.05051983682689262, 0.16362204332835972, 0.37292073486316324, 0.1582510686120051, 0.14541856549974336, -0.21300102531506915, 0.09201850851845236, -0.0895913848394735] |
1,802.07885 | On the economics of electrical storage for variable renewable energy
sources | The use of renewable energy sources is a major strategy to mitigate climate
change. Yet Sinn (2017) argues that excessive electrical storage requirements
limit the further expansion of variable wind and solar energy. We question, and
alter, strong implicit assumptions of Sinn's approach and find that storage
needs are considerably lower, up to two orders of magnitude. First, we move
away from corner solutions by allowing for combinations of storage and
renewable curtailment. Second, we specify a parsimonious optimization model
that explicitly considers an economic efficiency perspective. We conclude that
electrical storage is unlikely to limit the transition to renewable energy.
| physics.soc-ph cs.OH | the use of renewable energy sources is a major strategy to mitigate climate change yet sinn 2017 argues that excessive electrical storage requirements limit the further expansion of variable wind and solar energy we question and alter strong implicit assumptions of sinns approach and find that storage needs are considerably lower up to two orders of magnitude first we move away from corner solutions by allowing for combinations of storage and renewable curtailment second we specify a parsimonious optimization model that explicitly considers an economic efficiency perspective we conclude that electrical storage is unlikely to limit the transition to renewable energy | [['the', 'use', 'of', 'renewable', 'energy', 'sources', 'is', 'a', 'major', 'strategy', 'to', 'mitigate', 'climate', 'change', 'yet', 'sinn', '2017', 'argues', 'that', 'excessive', 'electrical', 'storage', 'requirements', 'limit', 'the', 'further', 'expansion', 'of', 'variable', 'wind', 'and', 'solar', 'energy', 'we', 'question', 'and', 'alter', 'strong', 'implicit', 'assumptions', 'of', 'sinns', 'approach', 'and', 'find', 'that', 'storage', 'needs', 'are', 'considerably', 'lower', 'up', 'to', 'two', 'orders', 'of', 'magnitude', 'first', 'we', 'move', 'away', 'from', 'corner', 'solutions', 'by', 'allowing', 'for', 'combinations', 'of', 'storage', 'and', 'renewable', 'curtailment', 'second', 'we', 'specify', 'a', 'parsimonious', 'optimization', 'model', 'that', 'explicitly', 'considers', 'an', 'economic', 'efficiency', 'perspective', 'we', 'conclude', 'that', 'electrical', 'storage', 'is', 'unlikely', 'to', 'limit', 'the', 'transition', 'to', 'renewable', 'energy']] | [-0.13496859722072257, 0.12250061664395616, -0.02208742992952466, 0.0657880955026485, -0.09646122807636857, -0.13347721408121288, 0.14715214391238987, 0.36210740263573826, -0.31623069616034627, -0.3701529556885362, 0.07576203188626096, -0.29082060161046686, -0.07552202079445124, 0.1911921797483228, -0.12102212616009637, 0.029210421706084164, 0.04631640047999099, -0.055929332422092554, -0.02964363886974752, -0.23229832221753896, 0.2662578163246508, 0.1349215373629704, 0.31682252045720816, 0.07653677091933787, 0.09981181412003934, -0.07479255187907256, -0.024228969318792225, -0.01525024649745319, -0.10044940306950594, 0.16999073987244628, 0.2647637710720301, 0.13748022902291268, 0.3066803012415767, -0.49028571642236785, -0.23599383706226945, 0.10902820212999359, 0.09009931905660779, 0.06312213438563048, -0.012606518529355525, -0.1455164251360111, 0.07220174763118849, -0.2597590360045433, -0.13219867281150072, -0.10944360228255391, 0.013996034571900963, 0.048423306019976735, -0.2906091917166486, 0.07151279704645276, 0.06998991017695516, 0.025281444734428078, -0.10736195815261454, -0.08836599043570459, -0.0532761670066975, 0.07901673857559217, 0.07022210901952348, -0.0336493015056476, 0.15125319157028572, -0.12561853531748057, -0.09308689083030913, 0.38132852146402, -0.007642858703620732, -0.1285274297185242, 0.1446488995081745, -0.1127192199206911, -0.13944898870773614, 0.1470852271973854, 0.2056801440054551, 0.05467307083225023, -0.18673637292115017, 0.06730740895494819, 0.04781321058981121, 0.19179848350584508, 0.07594460427295417, 0.041745892013423144, 0.21428434868576005, 0.1630922834482044, 0.1698271805047989, 0.13333835154771806, -0.0766690629441291, -0.10472711120499298, -0.25279438951984046, -0.12075197664089501, -0.14807643179781735, 0.08718771909829229, -0.08422414622211363, -0.09978373486934287, 0.36717640462797135, 0.23788536476902664, 0.10894277229905129, 0.015891122217290103, 0.3379913702025078, 0.14894243952818215, 0.04135999457794241, 0.14341157909482719, 0.21655518653802575, 0.015154997727368027, 0.16079952923581003, -0.21717160786531167, 0.09593398354481905, 0.02641997318714857] |
1,802.07886 | Would quantum entanglement be increased by anti-Unruh effect? | We study the "anti-Unruh effect" for an entangled quantum state in reference
to the counterintuitive cooling previously pointed out for an accelerated
detector coupled to the vacuum. We show that quantum entanglement for an
initially entangled (spacelike separated) bipartite state can be increased when
either a detector attached to one particle is accelerated or both detectors
attached to the two particles are in simultaneous accelerations. However, if
the two particles (e.g., detectors for the bipartite system) are not initially
entangled, entanglement cannot be created by the anti-Unruh effect. Thus,
within certain parameter regime, this work shows that the anti-Unruh effect can
be viewed as an amplification mechanism for quantum entanglement.
| gr-qc hep-th quant-ph | we study the antiunruh effect for an entangled quantum state in reference to the counterintuitive cooling previously pointed out for an accelerated detector coupled to the vacuum we show that quantum entanglement for an initially entangled spacelike separated bipartite state can be increased when either a detector attached to one particle is accelerated or both detectors attached to the two particles are in simultaneous accelerations however if the two particles eg detectors for the bipartite system are not initially entangled entanglement cannot be created by the antiunruh effect thus within certain parameter regime this work shows that the antiunruh effect can be viewed as an amplification mechanism for quantum entanglement | [['we', 'study', 'the', 'antiunruh', 'effect', 'for', 'an', 'entangled', 'quantum', 'state', 'in', 'reference', 'to', 'the', 'counterintuitive', 'cooling', 'previously', 'pointed', 'out', 'for', 'an', 'accelerated', 'detector', 'coupled', 'to', 'the', 'vacuum', 'we', 'show', 'that', 'quantum', 'entanglement', 'for', 'an', 'initially', 'entangled', 'spacelike', 'separated', 'bipartite', 'state', 'can', 'be', 'increased', 'when', 'either', 'a', 'detector', 'attached', 'to', 'one', 'particle', 'is', 'accelerated', 'or', 'both', 'detectors', 'attached', 'to', 'the', 'two', 'particles', 'are', 'in', 'simultaneous', 'accelerations', 'however', 'if', 'the', 'two', 'particles', 'eg', 'detectors', 'for', 'the', 'bipartite', 'system', 'are', 'not', 'initially', 'entangled', 'entanglement', 'can', 'not', 'be', 'created', 'by', 'the', 'antiunruh', 'effect', 'thus', 'within', 'certain', 'parameter', 'regime', 'this', 'work', 'shows', 'that', 'the', 'antiunruh', 'effect', 'can', 'be', 'viewed', 'as', 'an', 'amplification', 'mechanism', 'for', 'quantum', 'entanglement']] | [-0.11728527675475087, 0.27786358468169514, -0.10411324433202075, 0.042232393496879586, 0.005800053888411673, -0.21087028144497996, -0.03831143806235412, 0.36892320679685286, -0.2688484639558639, -0.2709588664877522, 0.055258993872206424, -0.30126608674926264, -0.05097900165941331, 0.2101928901445406, -0.032166606589295973, 0.047920042137103575, 0.08284633906205764, 0.05178036084943996, -0.006578060605370246, -0.23574622116378835, 0.2946507350734628, 0.09930163121945854, 0.2759403695167789, 0.04854025159383545, 0.09657896281983536, -0.004835501390819748, 0.08903655627960558, 0.0704443270659393, -0.05408152991233012, 0.0014123689500732464, 0.2665155153461472, 0.0889890882111079, 0.2407142822504849, -0.4475449873554008, -0.200001392068828, 0.1526927007949567, 0.1788118848988004, 0.17394189946437338, -0.04071494778786022, -0.3309088761809173, 0.0011273708093810725, -0.20314193640936268, -0.12560100069370222, -0.0445189921579718, -0.013985846560817581, -0.07155818057452068, -0.25425114757003814, 0.05666797317832977, 0.06387680209622518, -0.007810409440919086, -0.004765205794257355, -0.00881810301625346, 0.01747128243247668, 0.09500475628810162, -0.028455038926236936, 0.012200504409249973, 0.14648909137693342, -0.13720932249021758, -0.1436839711974031, 0.3182808525549869, -0.05358762511991904, -0.2301888041206644, 0.17753453780099884, -0.12307040221771007, -0.0848568780578438, 0.11223353868400729, 0.13037651950527016, 0.12097156105923827, -0.1548004011936362, -0.006594766585810765, -0.004189831204712391, 0.18200731733897785, 0.07016915760237959, 0.09118360271813718, 0.24950575560062854, 0.07462536885721928, 0.07155336088056231, 0.2261056483477807, -0.08223985381551462, -0.12050281064731681, -0.3004961100465677, -0.20941033155598618, -0.2380489490964022, 0.08809059051621647, -0.04157501634898352, -0.13379118808016582, 0.34881997848693114, 0.12366141095707142, 0.1595224694071992, -0.04917844948736397, 0.2547391032347003, 0.08453107684292738, 0.06728065485000476, 0.07927529396791314, 0.34711292305508173, 0.07849253069080815, 0.03600898820923658, -0.24377534090046277, 0.059621644747519006, 0.016773204747084026] |
1,802.07887 | Nonlinear Online Learning with Adaptive Nystr\"{o}m Approximation | Use of nonlinear feature maps via kernel approximation has led to success in
many online learning tasks. As a popular kernel approximation method,
Nystr\"{o}m approximation, has been well investigated, and various landmark
points selection methods have been proposed to improve the approximation
quality. However, these improved Nystr\"{o}m methods cannot be directly applied
to the online learning setting as they need to access the entire dataset to
learn the landmark points, while we need to update model on-the-fly in the
online setting. To address this challenge, we propose Adaptive Nystr\"{o}m
approximation for solving nonlinear online learning problems. The key idea is
to adaptively modify the landmark points via online kmeans and adjust the model
accordingly via solving least square problem followed by a gradient descent
step. We show that the resulting algorithm outperforms state-of-the-art online
learning methods under the same budget.
| cs.LG | use of nonlinear feature maps via kernel approximation has led to success in many online learning tasks as a popular kernel approximation method nystrom approximation has been well investigated and various landmark points selection methods have been proposed to improve the approximation quality however these improved nystrom methods cannot be directly applied to the online learning setting as they need to access the entire dataset to learn the landmark points while we need to update model onthefly in the online setting to address this challenge we propose adaptive nystrom approximation for solving nonlinear online learning problems the key idea is to adaptively modify the landmark points via online kmeans and adjust the model accordingly via solving least square problem followed by a gradient descent step we show that the resulting algorithm outperforms stateoftheart online learning methods under the same budget | [['use', 'of', 'nonlinear', 'feature', 'maps', 'via', 'kernel', 'approximation', 'has', 'led', 'to', 'success', 'in', 'many', 'online', 'learning', 'tasks', 'as', 'a', 'popular', 'kernel', 'approximation', 'method', 'nystrom', 'approximation', 'has', 'been', 'well', 'investigated', 'and', 'various', 'landmark', 'points', 'selection', 'methods', 'have', 'been', 'proposed', 'to', 'improve', 'the', 'approximation', 'quality', 'however', 'these', 'improved', 'nystrom', 'methods', 'can', 'not', 'be', 'directly', 'applied', 'to', 'the', 'online', 'learning', 'setting', 'as', 'they', 'need', 'to', 'access', 'the', 'entire', 'dataset', 'to', 'learn', 'the', 'landmark', 'points', 'while', 'we', 'need', 'to', 'update', 'model', 'onthefly', 'in', 'the', 'online', 'setting', 'to', 'address', 'this', 'challenge', 'we', 'propose', 'adaptive', 'nystrom', 'approximation', 'for', 'solving', 'nonlinear', 'online', 'learning', 'problems', 'the', 'key', 'idea', 'is', 'to', 'adaptively', 'modify', 'the', 'landmark', 'points', 'via', 'online', 'kmeans', 'and', 'adjust', 'the', 'model', 'accordingly', 'via', 'solving', 'least', 'square', 'problem', 'followed', 'by', 'a', 'gradient', 'descent', 'step', 'we', 'show', 'that', 'the', 'resulting', 'algorithm', 'outperforms', 'stateoftheart', 'online', 'learning', 'methods', 'under', 'the', 'same', 'budget']] | [0.0161596592779912, -0.0573233623505101, -0.1221370049933936, 0.0719798134263367, -0.14688060712069273, -0.18640358389375059, 0.05611847994637722, 0.4855568332742926, -0.3087880495103433, -0.31487347016520534, 0.11745083215976702, -0.23889917982015627, -0.2036802548145651, 0.17081435330885839, -0.11796331953204481, 0.1694026734970563, 0.11155581106563885, 0.0029090162604413134, -0.07673546720002217, -0.366294319263382, 0.26032714886551206, 0.08890976798423428, 0.3342953332244082, 0.004557982405419759, 0.16444330381275757, 0.01472943429736064, -0.0397802249665524, 0.017574088915469164, -0.048458270702425615, 0.15525648656139374, 0.35651239421192216, 0.1858422312363718, 0.42524363009708255, -0.401844196374931, -0.23026029415534321, 0.13744810570183322, 0.21123154056654808, 0.13294945816932155, -0.048685201859854636, -0.28922401667169645, 0.07994466045778906, -0.13037083166216315, -0.03033249661101834, -0.18326123714024292, -0.10083414704360544, 0.003431966823462978, -0.3217477716360215, 0.012826137759901107, 0.03575988304850824, 0.0060660829173123584, -0.04541277576977691, -0.138159018749675, 0.11128938524135065, 0.12949936657959055, 0.050239614521463714, 0.07256419813022652, 0.12567537235994394, -0.12469467031108943, -0.17046017382881795, 0.37396833341604213, -0.07411225513614556, -0.2139756819794734, 0.16242903094996322, 0.03428728694380228, -0.1392557341605425, 0.1250135691998302, 0.2720892288563575, 0.141694886216907, -0.16630616725970668, 0.08302170172885245, -0.033266359306079275, 0.12269716251456568, 0.044335686753616266, -0.060773156289381125, 0.07829328349969805, 0.19225775418268082, 0.11008869710086072, 0.11046331706010994, -0.08823960881799142, -0.10573733721179425, -0.16626311861909926, -0.0787018108584568, -0.21943211259241116, -0.0583947729665071, -0.11604048449406565, -0.16351363522544296, 0.38113641070452986, 0.23178912635978496, 0.2056215496912123, 0.055508667279484, 0.35815572364797404, 0.1082429945624123, 0.10725967354861134, 0.16223247969483442, 0.20438672578728473, 0.044266891145603136, 0.12076072486493974, -0.20082624666458854, 0.10935934007511283, 0.18081472169422935] |
1,802.07888 | Improved Techniques For Weakly-Supervised Object Localization | We propose an improved technique for weakly-supervised object localization.
Conventional methods have a limitation that they focus only on most
discriminative parts of the target objects. The recent study addressed this
issue and resolved this limitation by augmenting the training data for less
discriminative parts. To this end, we employ an effective data augmentation for
improving the accuracy of the object localization. In addition, we introduce
improved learning techniques by optimizing Convolutional Neural Networks (CNN)
based on the state-of-the-art model. Based on extensive experiments, we
evaluate the effectiveness of the proposed approach both qualitatively and
quantitatively. Especially, we observe that our method improves the Top-1
localization accuracy by 21.4 - 37.3% depending on configurations, compared to
the current state-of-the-art technique of the weakly-supervised object
localization.
| cs.CV | we propose an improved technique for weaklysupervised object localization conventional methods have a limitation that they focus only on most discriminative parts of the target objects the recent study addressed this issue and resolved this limitation by augmenting the training data for less discriminative parts to this end we employ an effective data augmentation for improving the accuracy of the object localization in addition we introduce improved learning techniques by optimizing convolutional neural networks cnn based on the stateoftheart model based on extensive experiments we evaluate the effectiveness of the proposed approach both qualitatively and quantitatively especially we observe that our method improves the top1 localization accuracy by 214 373 depending on configurations compared to the current stateoftheart technique of the weaklysupervised object localization | [['we', 'propose', 'an', 'improved', 'technique', 'for', 'weaklysupervised', 'object', 'localization', 'conventional', 'methods', 'have', 'a', 'limitation', 'that', 'they', 'focus', 'only', 'on', 'most', 'discriminative', 'parts', 'of', 'the', 'target', 'objects', 'the', 'recent', 'study', 'addressed', 'this', 'issue', 'and', 'resolved', 'this', 'limitation', 'by', 'augmenting', 'the', 'training', 'data', 'for', 'less', 'discriminative', 'parts', 'to', 'this', 'end', 'we', 'employ', 'an', 'effective', 'data', 'augmentation', 'for', 'improving', 'the', 'accuracy', 'of', 'the', 'object', 'localization', 'in', 'addition', 'we', 'introduce', 'improved', 'learning', 'techniques', 'by', 'optimizing', 'convolutional', 'neural', 'networks', 'cnn', 'based', 'on', 'the', 'stateoftheart', 'model', 'based', 'on', 'extensive', 'experiments', 'we', 'evaluate', 'the', 'effectiveness', 'of', 'the', 'proposed', 'approach', 'both', 'qualitatively', 'and', 'quantitatively', 'especially', 'we', 'observe', 'that', 'our', 'method', 'improves', 'the', 'top1', 'localization', 'accuracy', 'by', '214', '373', 'depending', 'on', 'configurations', 'compared', 'to', 'the', 'current', 'stateoftheart', 'technique', 'of', 'the', 'weaklysupervised', 'object', 'localization']] | [-0.03653459298244167, -0.03448089833851085, -0.058689758622823586, 0.05157580830517315, -0.06706121596770602, -0.15036964425141172, 0.05127767673806257, 0.4493443416281333, -0.18799095397022733, -0.34717096914837675, 0.06397831426734375, -0.2566352826092512, -0.19716676696008373, 0.21553517338085634, -0.15094955610637104, 0.10061881573018318, 0.16991519263847882, 0.029651903011272813, -0.11050431262194779, -0.3088997678527038, 0.335344773292872, 0.0725435398992211, 0.3783188504016688, 0.06226936275620134, 0.13034303793721203, 0.003030011537409718, -0.057456692748312506, 0.008484003855095755, -0.08498390125274571, 0.23704230719276012, 0.24527434258338726, 0.15205472940579057, 0.2913703139450762, -0.40607548653779013, -0.25633453636340076, 0.05626717797150054, 0.16425050129633276, 0.11424863046868855, -0.0429208634586464, -0.3773407392924832, 0.13271867785783065, -0.19416790546083282, 0.014192402520312763, -0.1337203358960969, -0.04585217017184703, -0.03813945584847862, -0.24904819438233972, 0.030747282450911663, 0.09027219510021349, 0.06169557013556421, -0.06201520003190625, -0.13103136499487464, 0.0972038506954578, 0.15111793040282903, 0.015998721144334864, 0.07488361155922194, 0.13480756973712554, -0.2115048197770633, -0.15785017056060174, 0.3199537776320452, -0.09165018902070099, -0.23278079725681775, 0.21699429723629426, -0.020934671509049593, -0.15376386145738163, 0.09980204869850329, 0.2170903554839653, 0.19422259558022262, -0.1317239727133945, 0.007019019102670192, -0.027876520424240058, 0.19803517275009183, 0.029884835177536814, 0.001802561254495935, 0.13235569331464508, 0.3052032489494811, 0.03265887219646585, 0.14695913542152172, -0.20820389207332365, -0.008216542450921429, -0.180611526097862, -0.05522548198895229, -0.21503052401221207, -0.05908075220988042, -0.08978806678257364, -0.09266015928193566, 0.439166359445681, 0.32135617495664665, 0.23929862162068247, 0.10035828869759796, 0.3752652955872397, 0.044959275537328196, 0.09384856628434311, 0.07116222253534943, 0.2558060051965332, -0.028902425244826103, 0.10782764741569766, -0.23224751887403638, 0.04426895248639818, 0.09948956525524057] |
1,802.07889 | Entropy Rate Estimation for Markov Chains with Large State Space | Estimating the entropy based on data is one of the prototypical problems in
distribution property testing and estimation. For estimating the Shannon
entropy of a distribution on $S$ elements with independent samples,
[Paninski2004] showed that the sample complexity is sublinear in $S$, and
[Valiant--Valiant2011] showed that consistent estimation of Shannon entropy is
possible if and only if the sample size $n$ far exceeds $\frac{S}{\log S}$. In
this paper we consider the problem of estimating the entropy rate of a
stationary reversible Markov chain with $S$ states from a sample path of $n$
observations. We show that:
(1) As long as the Markov chain mixes not too slowly, i.e., the relaxation
time is at most $O(\frac{S}{\ln^3 S})$, consistent estimation is achievable
when $n \gg \frac{S^2}{\log S}$.
(2) As long as the Markov chain has some slight dependency, i.e., the
relaxation time is at least $1+\Omega(\frac{\ln^2 S}{\sqrt{S}})$, consistent
estimation is impossible when $n \lesssim \frac{S^2}{\log S}$.
Under both assumptions, the optimal estimation accuracy is shown to be
$\Theta(\frac{S^2}{n \log S})$. In comparison, the empirical entropy rate
requires at least $\Omega(S^2)$ samples to be consistent, even when the Markov
chain is memoryless. In addition to synthetic experiments, we also apply the
estimators that achieve the optimal sample complexity to estimate the entropy
rate of the English language in the Penn Treebank and the Google One Billion
Words corpora, which provides a natural benchmark for language modeling and
relates it directly to the widely used perplexity measure.
| cs.LG math.ST stat.ML stat.TH | estimating the entropy based on data is one of the prototypical problems in distribution property testing and estimation for estimating the shannon entropy of a distribution on s elements with independent samples paninski2004 showed that the sample complexity is sublinear in s and valiantvaliant2011 showed that consistent estimation of shannon entropy is possible if and only if the sample size n far exceeds fracslog s in this paper we consider the problem of estimating the entropy rate of a stationary reversible markov chain with s states from a sample path of n observations we show that 1 as long as the markov chain mixes not too slowly ie the relaxation time is at most ofracsln3 s consistent estimation is achievable when n gg fracs2log s 2 as long as the markov chain has some slight dependency ie the relaxation time is at least 1omegafracln2 ssqrts consistent estimation is impossible when n lesssim fracs2log s under both assumptions the optimal estimation accuracy is shown to be thetafracs2n log s in comparison the empirical entropy rate requires at least omegas2 samples to be consistent even when the markov chain is memoryless in addition to synthetic experiments we also apply the estimators that achieve the optimal sample complexity to estimate the entropy rate of the english language in the penn treebank and the google one billion words corpora which provides a natural benchmark for language modeling and relates it directly to the widely used perplexity measure | [['estimating', 'the', 'entropy', 'based', 'on', 'data', 'is', 'one', 'of', 'the', 'prototypical', 'problems', 'in', 'distribution', 'property', 'testing', 'and', 'estimation', 'for', 'estimating', 'the', 'shannon', 'entropy', 'of', 'a', 'distribution', 'on', 's', 'elements', 'with', 'independent', 'samples', 'paninski2004', 'showed', 'that', 'the', 'sample', 'complexity', 'is', 'sublinear', 'in', 's', 'and', 'valiantvaliant2011', 'showed', 'that', 'consistent', 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1,802.0789 | Maxwell electrodynamics modified by CPT-even and Lorentz-violating
dimension-6 higher-derivative terms | In this paper, we investigate an electrodynamics in which the physical modes
are coupled to a Lorentz-violating (LV) background by means of a
higher-derivative term. We analyze the modes associated with the dispersion
relations (DRs) obtained from the poles of the propagator. More specifically,
we study Maxwell's electrodynamics modified by a LV operator of mass dimension
6. The modification has the form
${D_{\beta\alpha}}\partial_{\sigma}F^{\sigma\beta}\partial_{\lambda}
F^{\lambda\alpha}$, i.e., it possesses two additional derivatives coupled to a
\textit{CPT}-even tensor $D_{\beta\alpha}$ that plays the role of the fixed
background. We first evaluate the propagator and obtain the dispersion
relations of the theory. By doing so, we analyze some configurations of the
fixed background and search for sectors where the energy is well-defined and
causality is assured. A brief analysis of unitarity is included for particular
configurations. Afterwards, we perform the same kind of analysis for a more
general dimension-6 model. We conclude that the modes of both Lagrange
densities are possibly plagued by physical problems, including causality and
unitarity violation, and that signal propagation may become physically
meaningful only in the high-momentum regime.
| hep-th | in this paper we investigate an electrodynamics in which the physical modes are coupled to a lorentzviolating lv background by means of a higherderivative term we analyze the modes associated with the dispersion relations drs obtained from the poles of the propagator more specifically we study maxwells electrodynamics modified by a lv operator of mass dimension 6 the modification has the form d_betaalphapartial_sigmafsigmabetapartial_lambda flambdaalpha ie it possesses two additional derivatives coupled to a textitcpteven tensor d_betaalpha that plays the role of the fixed background we first evaluate the propagator and obtain the dispersion relations of the theory by doing so we analyze some configurations of the fixed background and search for sectors where the energy is welldefined and causality is assured a brief analysis of unitarity is included for particular configurations afterwards we perform the same kind of analysis for a more general dimension6 model we conclude that the modes of both lagrange densities are possibly plagued by physical problems including causality and unitarity violation and that signal propagation may become physically meaningful only in the highmomentum regime | [['in', 'this', 'paper', 'we', 'investigate', 'an', 'electrodynamics', 'in', 'which', 'the', 'physical', 'modes', 'are', 'coupled', 'to', 'a', 'lorentzviolating', 'lv', 'background', 'by', 'means', 'of', 'a', 'higherderivative', 'term', 'we', 'analyze', 'the', 'modes', 'associated', 'with', 'the', 'dispersion', 'relations', 'drs', 'obtained', 'from', 'the', 'poles', 'of', 'the', 'propagator', 'more', 'specifically', 'we', 'study', 'maxwells', 'electrodynamics', 'modified', 'by', 'a', 'lv', 'operator', 'of', 'mass', 'dimension', '6', 'the', 'modification', 'has', 'the', 'form', 'd_betaalphapartial_sigmafsigmabetapartial_lambda', 'flambdaalpha', 'ie', 'it', 'possesses', 'two', 'additional', 'derivatives', 'coupled', 'to', 'a', 'textitcpteven', 'tensor', 'd_betaalpha', 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1,802.07891 | A New Design of Binary MDS Array Codes with Asymptotically Weak-Optimal
Repair | Binary maximum distance separable (MDS) array codes are a special class of
erasure codes for distributed storage that not only provide fault tolerance
with minimum storage redundancy but also achieve low computational complexity.
They are constructed by encoding $k$ information columns into $r$ parity
columns, in which each element in a column is a bit, such that any $k$ out of
the $k+r$ columns suffice to recover all information bits. In addition to
providing fault tolerance, it is critical to improve repair performance in
practical applications. Specifically, if a single column fails, our goal is to
minimize the repair bandwidth by downloading the least amount of bits from $d$
healthy columns, where $k\leq d\leq k+r-1$. If one column of an MDS code is
failed, it is known that we need to download at least $1/(d-k+1)$ fraction of
the data stored in each of $d$ healthy columns. If this lower bound is achieved
for the repair of the failure column from accessing arbitrary $d$ healthy
columns, we say that the MDS code has optimal repair. However, if such lower
bound is only achieved by $d$ specific healthy columns, then we say the MDS
code has weak-optimal repair. In this paper, we propose two explicit
constructions of binary MDS array codes with more parity columns (i.e., $r\geq
3$) that achieve asymptotically weak-optimal repair, where $k+1\leq d\leq
k+\lfloor(r-1)/2\rfloor$, and "asymptotic" means that the repair bandwidth
achieves the minimum value asymptotically in $d$. Codes in the first
construction have odd number of parity columns and asymptotically weak-optimal
repair for any one information failure, while codes in the second construction
have even number of parity columns and asymptotically weak-optimal repair for
any one column failure.
| cs.IT math.IT | binary maximum distance separable mds array codes are a special class of erasure codes for distributed storage that not only provide fault tolerance with minimum storage redundancy but also achieve low computational complexity they are constructed by encoding k information columns into r parity columns in which each element in a column is a bit such that any k out of the kr columns suffice to recover all information bits in addition to providing fault tolerance it is critical to improve repair performance in practical applications specifically if a single column fails our goal is to minimize the repair bandwidth by downloading the least amount of bits from d healthy columns where kleq dleq kr1 if one column of an mds code is failed it is known that we need to download at least 1dk1 fraction of the data stored in each of d healthy columns if this lower bound is achieved for the repair of the failure column from accessing arbitrary d healthy columns we say that the mds code has optimal repair however if such lower bound is only achieved by d specific healthy columns then we say the mds code has weakoptimal repair in this paper we propose two explicit constructions of binary mds array codes with more parity columns ie rgeq 3 that achieve asymptotically weakoptimal repair where k1leq dleq klfloorr12rfloor and asymptotic means that the repair bandwidth achieves the minimum value asymptotically in d codes in the first construction have odd number of parity columns and asymptotically weakoptimal repair for any one information failure while codes in the second construction have even number of parity columns and asymptotically weakoptimal repair for any one column failure | [['binary', 'maximum', 'distance', 'separable', 'mds', 'array', 'codes', 'are', 'a', 'special', 'class', 'of', 'erasure', 'codes', 'for', 'distributed', 'storage', 'that', 'not', 'only', 'provide', 'fault', 'tolerance', 'with', 'minimum', 'storage', 'redundancy', 'but', 'also', 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1,802.07892 | Improving sensitivity to magnetic fields and electric dipole moments by
using measurements of individual magnetic sublevels | We explore ways to use the ability to measure the populations of individual
magnetic sublevels to improve the sensitivity of magnetic field measurements
and measurements of atomic electric dipole moments (EDMs). When atoms are
initialized in the $m=0$ magnetic sublevel, the shot-noise-limited uncertainty
of these measurements is $1/\sqrt{2F(F+1)}$ smaller than that of a Larmor
precession measurement. When the populations in the even (or odd) magnetic
sublevels are combined, we show that these measurements are independent of the
tensor Stark shift and the second order Zeeman shift. We discuss the
complicating effect of a transverse magnetic field and show that when the ratio
of the tensor Stark shift to the transverse magnetic field is sufficiently
large, an EDM measurement with atoms initialized in the superposition of the
stretched states can reach the optimal sensitivity.
| quant-ph | we explore ways to use the ability to measure the populations of individual magnetic sublevels to improve the sensitivity of magnetic field measurements and measurements of atomic electric dipole moments edms when atoms are initialized in the m0 magnetic sublevel the shotnoiselimited uncertainty of these measurements is 1sqrt2ff1 smaller than that of a larmor precession measurement when the populations in the even or odd magnetic sublevels are combined we show that these measurements are independent of the tensor stark shift and the second order zeeman shift we discuss the complicating effect of a transverse magnetic field and show that when the ratio of the tensor stark shift to the transverse magnetic field is sufficiently large an edm measurement with atoms initialized in the superposition of the stretched states can reach the optimal sensitivity | [['we', 'explore', 'ways', 'to', 'use', 'the', 'ability', 'to', 'measure', 'the', 'populations', 'of', 'individual', 'magnetic', 'sublevels', 'to', 'improve', 'the', 'sensitivity', 'of', 'magnetic', 'field', 'measurements', 'and', 'measurements', 'of', 'atomic', 'electric', 'dipole', 'moments', 'edms', 'when', 'atoms', 'are', 'initialized', 'in', 'the', 'm0', 'magnetic', 'sublevel', 'the', 'shotnoiselimited', 'uncertainty', 'of', 'these', 'measurements', 'is', '1sqrt2ff1', 'smaller', 'than', 'that', 'of', 'a', 'larmor', 'precession', 'measurement', 'when', 'the', 'populations', 'in', 'the', 'even', 'or', 'odd', 'magnetic', 'sublevels', 'are', 'combined', 'we', 'show', 'that', 'these', 'measurements', 'are', 'independent', 'of', 'the', 'tensor', 'stark', 'shift', 'and', 'the', 'second', 'order', 'zeeman', 'shift', 'we', 'discuss', 'the', 'complicating', 'effect', 'of', 'a', 'transverse', 'magnetic', 'field', 'and', 'show', 'that', 'when', 'the', 'ratio', 'of', 'the', 'tensor', 'stark', 'shift', 'to', 'the', 'transverse', 'magnetic', 'field', 'is', 'sufficiently', 'large', 'an', 'edm', 'measurement', 'with', 'atoms', 'initialized', 'in', 'the', 'superposition', 'of', 'the', 'stretched', 'states', 'can', 'reach', 'the', 'optimal', 'sensitivity']] | [-0.15645248555775845, 0.26242591202654614, 0.018552748472288702, 0.05838735617792488, -0.03218506136909127, -0.07365589648852068, 0.02196748614678103, 0.3899694039331128, -0.26189784632261953, -0.3435661774269785, 0.016598479353970932, -0.272318481940381, -0.009703233998593394, 0.1648765674873368, 0.021457836890476756, -0.008973053141468854, 0.05325478901310513, 0.06957335895717595, -0.07317868396234134, -0.19506851077136217, 0.31791688561806397, 0.04152957226544844, 0.28090927183317643, 0.02974780989373385, 0.05492426072614211, -0.008837784381202337, 0.07334626367259206, 0.06641425348987634, -0.0855524166703562, 0.10929615598544126, 0.1891120807620499, 0.029358126985464354, 0.21676856516437096, -0.4434482380395021, -0.10706609073994597, 0.11407124354842711, 0.12719480248492662, 0.18795469566953904, -0.004975023661796568, -0.29960590557223465, 0.027832217100005822, -0.10426134532529184, -0.11460919436914, -0.14044898707476078, 0.013912390853158397, 0.05249269556776254, -0.3340434054138534, 0.08241316428139919, 0.06569938256826859, 0.09228822798468173, -0.10723616824852246, -0.14030573956640155, 0.014187343559707657, 0.09133961858473909, 0.07031822834114516, 0.0671749205035722, 0.1977262843804166, -0.11944962368976451, -0.12053190422893474, 0.3385913317571535, -0.1279848068173151, -0.1546529204880988, 0.10450193250311934, -0.2807729253827622, -0.08229480196623075, 0.10094465418881031, 0.16565791432124874, 0.1128084393267548, -0.06865507729382829, 0.05061096322562221, 0.016341185804004923, 0.18368512084425398, 0.05842392310627143, 0.06030010521344869, 0.22219065133707994, 0.0963477622100265, 0.09422802863374466, 0.12924152349516976, -0.17633363658167195, -0.047145790864967486, -0.24210033112092677, -0.13455721120716949, -0.20405448087628678, 0.08203794578598304, -0.0689810405210389, -0.12884381031053085, 0.3791255075449237, 0.1880773924305245, 0.19613461168288873, -0.036328289336807124, 0.37725737052317004, 0.14222909734852499, 0.0822897056853187, 0.013855240458118109, 0.32896062006440124, 0.2397790844375832, 0.05506348058715406, -0.3258294472949329, 0.026223427818022726, -0.030917157482525163] |
1,802.07893 | Voltage-Controlled Topological-Spin Switch for Ultra-Low-Energy
Computing--Performance Modeling and Benchmarking | A voltage-controlled topological-spin switch (vTOPSS) that uses a hybrid
topological insulator-magnetic insulator multiferroic is presented that can
implement Boolean logic operations with sub-10 aJ energy-per-bit and
energy-delay product on the order of $10^{-27}$ Js. The device uses a
topological insulator (TI), which has the highest efficiency of conversion of
electric field to spin torque yet observed at room temperature, and a
low-moment magnetic insulator (MI) that can respond rapidly to a given spin
torque. We present the theory of operation of vTOPSS, develop analytic models
of its performance metrics, elucidate performance scaling with dimensions and
voltage, and benchmark vTOPSS against existing spin-based and CMOS devices.
Compared to existing spin-based devices, such as all-spin logic and charge-spin
logic, vTOPSS offers 100$\times$ lower energy dissipation and (40-100)$\times$
lower energy-delay product. With experimental advances and improved material
properties, we show that the energy-delay product of vTOPSS can be lowered to
$10^{-29}$ Js, competitive against existing CMOS technology. Finally, we
establish that interconnect issues that dominate the performance in CMOS logic
are relatively less significant for vTOPSS, implying that highly resistive
materials can indeed be used to interconnect vTOPSS devices.
| physics.app-ph cond-mat.mes-hall | a voltagecontrolled topologicalspin switch vtopss that uses a hybrid topological insulatormagnetic insulator multiferroic is presented that can implement boolean logic operations with sub10 aj energyperbit and energydelay product on the order of 1027 js the device uses a topological insulator ti which has the highest efficiency of conversion of electric field to spin torque yet observed at room temperature and a lowmoment magnetic insulator mi that can respond rapidly to a given spin torque we present the theory of operation of vtopss develop analytic models of its performance metrics elucidate performance scaling with dimensions and voltage and benchmark vtopss against existing spinbased and cmos devices compared to existing spinbased devices such as allspin logic and chargespin logic vtopss offers 100times lower energy dissipation and 40100times lower energydelay product with experimental advances and improved material properties we show that the energydelay product of vtopss can be lowered to 1029 js competitive against existing cmos technology finally we establish that interconnect issues that dominate the performance in cmos logic are relatively less significant for vtopss implying that highly resistive materials can indeed be used to interconnect vtopss devices | [['a', 'voltagecontrolled', 'topologicalspin', 'switch', 'vtopss', 'that', 'uses', 'a', 'hybrid', 'topological', 'insulatormagnetic', 'insulator', 'multiferroic', 'is', 'presented', 'that', 'can', 'implement', 'boolean', 'logic', 'operations', 'with', 'sub10', 'aj', 'energyperbit', 'and', 'energydelay', 'product', 'on', 'the', 'order', 'of', '1027', 'js', 'the', 'device', 'uses', 'a', 'topological', 'insulator', 'ti', 'which', 'has', 'the', 'highest', 'efficiency', 'of', 'conversion', 'of', 'electric', 'field', 'to', 'spin', 'torque', 'yet', 'observed', 'at', 'room', 'temperature', 'and', 'a', 'lowmoment', 'magnetic', 'insulator', 'mi', 'that', 'can', 'respond', 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1,802.07894 | Flexible paramagnetic membranes in fast precessing fields | Elastic membranes composed of paramagnetic beads offer the possibility of
assembling versatile actuators operated autonomously by external magnetic
fields. Here we develop a theoretical framework to study shapes of such
paramagnetic membranes under the influence of a fast precessing magnetic field.
Their conformations are determined by the competition of the elastic and
magnetic energies, arising as a result of their bending and the induced dipolar
interactions between nearest neighbors beads. In the harmonic approximation,
the elastic energy is quadratic in the surface curvatures. To account for the
magnetic energy we introduce a continuum limit energy, quadratic in the
projections of the surface tangents onto the precession axis. We derive the
Euler-Lagrange equation governing the equilibria of these membranes, as well as
the corresponding stresses. We apply this framework to examine paramagnetic
membranes with quasiplanar, cylindrical, and helicoidal geometries. In all
cases we found that their shape, energy, and stresses can be modified by means
of the parameters of the magnetic field, mainly by the angle of precession.
| cond-mat.soft | elastic membranes composed of paramagnetic beads offer the possibility of assembling versatile actuators operated autonomously by external magnetic fields here we develop a theoretical framework to study shapes of such paramagnetic membranes under the influence of a fast precessing magnetic field their conformations are determined by the competition of the elastic and magnetic energies arising as a result of their bending and the induced dipolar interactions between nearest neighbors beads in the harmonic approximation the elastic energy is quadratic in the surface curvatures to account for the magnetic energy we introduce a continuum limit energy quadratic in the projections of the surface tangents onto the precession axis we derive the eulerlagrange equation governing the equilibria of these membranes as well as the corresponding stresses we apply this framework to examine paramagnetic membranes with quasiplanar cylindrical and helicoidal geometries in all cases we found that their shape energy and stresses can be modified by means of the parameters of the magnetic field mainly by the angle of precession | [['elastic', 'membranes', 'composed', 'of', 'paramagnetic', 'beads', 'offer', 'the', 'possibility', 'of', 'assembling', 'versatile', 'actuators', 'operated', 'autonomously', 'by', 'external', 'magnetic', 'fields', 'here', 'we', 'develop', 'a', 'theoretical', 'framework', 'to', 'study', 'shapes', 'of', 'such', 'paramagnetic', 'membranes', 'under', 'the', 'influence', 'of', 'a', 'fast', 'precessing', 'magnetic', 'field', 'their', 'conformations', 'are', 'determined', 'by', 'the', 'competition', 'of', 'the', 'elastic', 'and', 'magnetic', 'energies', 'arising', 'as', 'a', 'result', 'of', 'their', 'bending', 'and', 'the', 'induced', 'dipolar', 'interactions', 'between', 'nearest', 'neighbors', 'beads', 'in', 'the', 'harmonic', 'approximation', 'the', 'elastic', 'energy', 'is', 'quadratic', 'in', 'the', 'surface', 'curvatures', 'to', 'account', 'for', 'the', 'magnetic', 'energy', 'we', 'introduce', 'a', 'continuum', 'limit', 'energy', 'quadratic', 'in', 'the', 'projections', 'of', 'the', 'surface', 'tangents', 'onto', 'the', 'precession', 'axis', 'we', 'derive', 'the', 'eulerlagrange', 'equation', 'governing', 'the', 'equilibria', 'of', 'these', 'membranes', 'as', 'well', 'as', 'the', 'corresponding', 'stresses', 'we', 'apply', 'this', 'framework', 'to', 'examine', 'paramagnetic', 'membranes', 'with', 'quasiplanar', 'cylindrical', 'and', 'helicoidal', 'geometries', 'in', 'all', 'cases', 'we', 'found', 'that', 'their', 'shape', 'energy', 'and', 'stresses', 'can', 'be', 'modified', 'by', 'means', 'of', 'the', 'parameters', 'of', 'the', 'magnetic', 'field', 'mainly', 'by', 'the', 'angle', 'of', 'precession']] | [-0.17624301409218487, 0.1844884203042846, -0.03521660407677482, 0.03872365559713391, -0.048262476305021416, -0.07128873308088832, 0.010344073131769717, 0.40190842030514146, -0.2872692498080098, -0.31343404412503817, 0.02160408656380535, -0.23845590649919954, -0.14226573163052342, 0.15825269927973384, 0.010702369628686034, 0.020660128283403634, -0.003640610153067433, -0.008077110200116555, -0.037750907279941404, -0.15093978611936423, 0.2893465695913859, 0.037171164273791864, 0.2541279842614191, 0.06188441356358224, 0.09473899298822953, 0.035045101622420693, 0.09391098966387039, 0.07549812560727424, -0.1904799878434923, 0.11206444656799831, 0.2071986635505573, -0.03473754407012623, 0.19887925054436909, -0.5064179575304963, -0.18502747289844074, 0.07333552161326443, 0.09644113737297896, 0.132038381847157, -0.02600268141121163, -0.266415528400974, 0.01706743544918446, -0.11638649703215384, -0.19422103085521675, -0.1103217169610382, -0.0069232730621550075, 0.10346502453663169, -0.21824141512597037, 0.10461567341723664, 0.09483380338126894, 0.0709136996563234, -0.15794091524757042, -0.08193503884448039, -0.06423993177522352, 0.0895859778072395, 0.11518376653952647, 0.012099128605485588, 0.2237454455744609, -0.11732885700895891, -0.08520611108721284, 0.3969498197185601, -0.03753065443904457, -0.21167735757447728, 0.15628091531420896, -0.13332383772692905, -0.04568902627302858, 0.16412826299020453, 0.20022134825274973, 0.11075054693543268, -0.17361661074348464, 0.08472828102900373, 0.016942357561484114, 0.11283115472109197, 0.09957733121561166, -0.02016930163051643, 0.2727069619340365, 0.15378156452004738, 0.026998609744296773, 0.19545761721339747, -0.13237842395455537, -0.07397072700069782, -0.2658856663473709, -0.14612570234078043, -0.1778431312483596, 0.05480055485205156, -0.09778616989406473, -0.1919639327725072, 0.3819633637677633, 0.0729819636368109, 0.18052242958393996, 0.005674312404262092, 0.283557181519841, 0.06479496297267584, 0.05768984819561645, 0.051539449899563355, 0.320696579231072, 0.19847705334558816, 0.08149823475305638, -0.2609550648251783, 0.007658250549038548, 0.04920633333528827] |
1,802.07895 | Learning Mixtures of Linear Regressions with Nearly Optimal Complexity | Mixtures of Linear Regressions (MLR) is an important mixture model with many
applications. In this model, each observation is generated from one of the
several unknown linear regression components, where the identity of the
generated component is also unknown. Previous works either assume strong
assumptions on the data distribution or have high complexity. This paper
proposes a fixed parameter tractable algorithm for the problem under general
conditions, which achieves global convergence and the sample complexity scales
nearly linearly in the dimension. In particular, different from previous works
that require the data to be from the standard Gaussian, the algorithm allows
the data from Gaussians with different covariances. When the conditional number
of the covariances and the number of components are fixed, the algorithm has
nearly optimal sample complexity $N = \tilde{O}(d)$ as well as nearly optimal
computational complexity $\tilde{O}(Nd)$, where $d$ is the dimension of the
data space. To the best of our knowledge, this approach provides the first such
recovery guarantee for this general setting.
| cs.LG | mixtures of linear regressions mlr is an important mixture model with many applications in this model each observation is generated from one of the several unknown linear regression components where the identity of the generated component is also unknown previous works either assume strong assumptions on the data distribution or have high complexity this paper proposes a fixed parameter tractable algorithm for the problem under general conditions which achieves global convergence and the sample complexity scales nearly linearly in the dimension in particular different from previous works that require the data to be from the standard gaussian the algorithm allows the data from gaussians with different covariances when the conditional number of the covariances and the number of components are fixed the algorithm has nearly optimal sample complexity n tildeod as well as nearly optimal computational complexity tildeond where d is the dimension of the data space to the best of our knowledge this approach provides the first such recovery guarantee for this general setting | [['mixtures', 'of', 'linear', 'regressions', 'mlr', 'is', 'an', 'important', 'mixture', 'model', 'with', 'many', 'applications', 'in', 'this', 'model', 'each', 'observation', 'is', 'generated', 'from', 'one', 'of', 'the', 'several', 'unknown', 'linear', 'regression', 'components', 'where', 'the', 'identity', 'of', 'the', 'generated', 'component', 'is', 'also', 'unknown', 'previous', 'works', 'either', 'assume', 'strong', 'assumptions', 'on', 'the', 'data', 'distribution', 'or', 'have', 'high', 'complexity', 'this', 'paper', 'proposes', 'a', 'fixed', 'parameter', 'tractable', 'algorithm', 'for', 'the', 'problem', 'under', 'general', 'conditions', 'which', 'achieves', 'global', 'convergence', 'and', 'the', 'sample', 'complexity', 'scales', 'nearly', 'linearly', 'in', 'the', 'dimension', 'in', 'particular', 'different', 'from', 'previous', 'works', 'that', 'require', 'the', 'data', 'to', 'be', 'from', 'the', 'standard', 'gaussian', 'the', 'algorithm', 'allows', 'the', 'data', 'from', 'gaussians', 'with', 'different', 'covariances', 'when', 'the', 'conditional', 'number', 'of', 'the', 'covariances', 'and', 'the', 'number', 'of', 'components', 'are', 'fixed', 'the', 'algorithm', 'has', 'nearly', 'optimal', 'sample', 'complexity', 'n', 'tildeod', 'as', 'well', 'as', 'nearly', 'optimal', 'computational', 'complexity', 'tildeond', 'where', 'd', 'is', 'the', 'dimension', 'of', 'the', 'data', 'space', 'to', 'the', 'best', 'of', 'our', 'knowledge', 'this', 'approach', 'provides', 'the', 'first', 'such', 'recovery', 'guarantee', 'for', 'this', 'general', 'setting']] | [-0.06669616056946902, 0.055545478243690986, -0.07191031215507991, 0.02269873318046604, -0.06326641568278031, -0.13992478130612432, 0.034993280850424684, 0.35489343576951, -0.288005487982002, -0.33045386807232097, 0.13278342878641902, -0.2546745057902959, -0.1245508552159796, 0.1919868382875149, -0.06793344569699157, 0.1158950035971385, 0.03283640704466961, 0.05830221362241612, -0.0469976199802193, -0.31025583013500335, 0.33332221311866306, 0.05607156782047596, 0.3020282974637045, -0.048525796310547396, 0.10927515575753116, 0.01623800166928005, -0.02856155399448897, 0.007102979340898611, -0.0812881769523789, 0.10893812048938921, 0.26041069241785786, 0.1829561282953009, 0.3014120485622254, -0.3770594342561863, -0.21131325498359596, 0.1495608964171147, 0.13160616756280566, 0.11685053305345497, -0.004392626781226703, -0.21699448265476015, 0.05801343409594421, -0.11802708870935731, -0.08733020078322691, -0.054183186716172935, -0.011536306338157595, 0.017594403962082252, -0.342940065896184, 0.07658676967637404, 0.09041887837555827, 0.053233087619357716, -0.0565987508122883, -0.15613255357489036, 0.03396787003489075, 0.12555681769796448, 0.08687875248781382, 0.031803912610928645, 0.07320097780917068, -0.1065847065311107, -0.09532314259842856, 0.35461415483320996, -0.06280313240557273, -0.2223796257507851, 0.21293455658895077, -0.12252947455023631, -0.1578248228037321, 0.13549166366957674, 0.19464040087910778, 0.11640417348400395, -0.13007831335447165, 0.1274199806027421, -0.0953227273449756, 0.18262608294806829, 0.02091370066684648, 0.024762144801348855, 0.10145166148885904, 0.18124556205542078, 0.11663402015335855, 0.13648449581204458, -0.08129811933634677, -0.07330594486670523, -0.288867303150388, -0.10915772087634938, -0.22582929263959026, -0.013527173872628227, -0.15856319537550273, -0.15787982051374344, 0.37674042694384186, 0.15387320576417374, 0.24769624415785074, 0.12240302017904114, 0.35547659785072205, 0.09487611734771124, 0.026576094613296956, 0.1271996581472638, 0.19026449944812623, 0.09451370270320827, 0.03312312880078069, -0.17228218516130456, 0.12527096006031171, 0.0023487494270339974] |
1,802.07896 | L2-Nonexpansive Neural Networks | This paper proposes a class of well-conditioned neural networks in which a
unit amount of change in the inputs causes at most a unit amount of change in
the outputs or any of the internal layers. We develop the known methodology of
controlling Lipschitz constants to realize its full potential in maximizing
robustness, with a new regularization scheme for linear layers, new ways to
adapt nonlinearities and a new loss function. With MNIST and CIFAR-10
classifiers, we demonstrate a number of advantages. Without needing any
adversarial training, the proposed classifiers exceed the state of the art in
robustness against white-box L2-bounded adversarial attacks. They generalize
better than ordinary networks from noisy data with partially random labels.
Their outputs are quantitatively meaningful and indicate levels of confidence
and generalization, among other desirable properties.
| cs.AI cs.LG | this paper proposes a class of wellconditioned neural networks in which a unit amount of change in the inputs causes at most a unit amount of change in the outputs or any of the internal layers we develop the known methodology of controlling lipschitz constants to realize its full potential in maximizing robustness with a new regularization scheme for linear layers new ways to adapt nonlinearities and a new loss function with mnist and cifar10 classifiers we demonstrate a number of advantages without needing any adversarial training the proposed classifiers exceed the state of the art in robustness against whitebox l2bounded adversarial attacks they generalize better than ordinary networks from noisy data with partially random labels their outputs are quantitatively meaningful and indicate levels of confidence and generalization among other desirable properties | [['this', 'paper', 'proposes', 'a', 'class', 'of', 'wellconditioned', 'neural', 'networks', 'in', 'which', 'a', 'unit', 'amount', 'of', 'change', 'in', 'the', 'inputs', 'causes', 'at', 'most', 'a', 'unit', 'amount', 'of', 'change', 'in', 'the', 'outputs', 'or', 'any', 'of', 'the', 'internal', 'layers', 'we', 'develop', 'the', 'known', 'methodology', 'of', 'controlling', 'lipschitz', 'constants', 'to', 'realize', 'its', 'full', 'potential', 'in', 'maximizing', 'robustness', 'with', 'a', 'new', 'regularization', 'scheme', 'for', 'linear', 'layers', 'new', 'ways', 'to', 'adapt', 'nonlinearities', 'and', 'a', 'new', 'loss', 'function', 'with', 'mnist', 'and', 'cifar10', 'classifiers', 'we', 'demonstrate', 'a', 'number', 'of', 'advantages', 'without', 'needing', 'any', 'adversarial', 'training', 'the', 'proposed', 'classifiers', 'exceed', 'the', 'state', 'of', 'the', 'art', 'in', 'robustness', 'against', 'whitebox', 'l2bounded', 'adversarial', 'attacks', 'they', 'generalize', 'better', 'than', 'ordinary', 'networks', 'from', 'noisy', 'data', 'with', 'partially', 'random', 'labels', 'their', 'outputs', 'are', 'quantitatively', 'meaningful', 'and', 'indicate', 'levels', 'of', 'confidence', 'and', 'generalization', 'among', 'other', 'desirable', 'properties']] | [-0.06949401074653548, 0.028260753881609577, -0.010797211822743217, 0.043960321268638254, -0.09844808686863292, -0.1867384887617928, 0.09578657052285659, 0.39284366900877404, -0.28079808019119257, -0.33098682834569254, 0.05137137743330448, -0.27896440605576517, -0.19520664474200175, 0.18301467818850087, -0.15568615106608238, 0.12180324708981172, 0.0945089822282281, 0.03945281141028373, -0.08367887991533446, -0.32556340338443546, 0.3266468416038675, 0.0270490046223682, 0.3044052470462647, -0.0016942001776910868, 0.12628186550644, -0.04366157600871344, 0.0157338524815824, -0.0064771796901230555, -0.04606897231177286, 0.1525005720252397, 0.25404694581150333, 0.16022660522580598, 0.3487451732102217, -0.42545890635246353, -0.24320695281141635, 0.14040096338474983, 0.08081155166269816, 0.13577721234336917, -0.029343405181972423, -0.3081142726446022, 0.11671323480902973, -0.16925382542875456, -0.05993912098788177, -0.14767621109036333, -0.048954259484272566, 0.034298418882606325, -0.3176326110930831, 0.04985056486982627, 0.08202486012570179, 0.06035880505684569, -0.06528316856499507, -0.11998483519401458, -0.019382345705349562, 0.14556359416967485, 0.00981042302164221, 0.022506483558875818, 0.11076949419679516, -0.18646491432710635, -0.15076531495398024, 0.32259006178796745, -0.07036840498932923, -0.26818153605563566, 0.19346705817786808, -0.06284211130078995, -0.12170657777813065, 0.10299102563735549, 0.24260450453695023, 0.11141100062311372, -0.11510619689061334, 0.0103238610406124, 0.0018666573433261929, 0.1960585419384932, 0.05521968207110397, 0.07165796093812044, 0.14426420819522304, 0.1996528125671444, 0.07760799423241141, 0.19351197458904193, -0.09386080168505115, -0.05573382592851748, -0.25986262026003026, -0.11255859368600685, -0.1867521821316614, 0.016070977435447276, -0.12343325972103754, -0.16945325207691922, 0.4149666847935364, 0.2113544788197473, 0.2501775156777126, 0.1355472703254429, 0.33693299587872444, 0.03290177809046299, 0.11164644170220885, 0.11539917053817066, 0.20428389794136764, 0.08004858129424974, 0.07055130541310504, -0.1628734975015642, 0.14991942396613234, 0.01707921956756653] |
1,802.07897 | Gradient flow and the Wilsonian renormalization group flow | The gradient flow is the evolution of fields and physical quantities along a
dimensionful parameter~$t$, the flow time. We give a simple argument that
relates this gradient flow and the Wilsonian renormalization group (RG) flow.
We then illustrate the Wilsonian RG flow on the basis of the gradient flow in
two examples that possess an infrared fixed point, the 4D many-flavor gauge
theory and the 3D $O(N)$ linear sigma model.
| hep-th hep-lat | the gradient flow is the evolution of fields and physical quantities along a dimensionful parametert the flow time we give a simple argument that relates this gradient flow and the wilsonian renormalization group rg flow we then illustrate the wilsonian rg flow on the basis of the gradient flow in two examples that possess an infrared fixed point the 4d manyflavor gauge theory and the 3d on linear sigma model | [['the', 'gradient', 'flow', 'is', 'the', 'evolution', 'of', 'fields', 'and', 'physical', 'quantities', 'along', 'a', 'dimensionful', 'parametert', 'the', 'flow', 'time', 'we', 'give', 'a', 'simple', 'argument', 'that', 'relates', 'this', 'gradient', 'flow', 'and', 'the', 'wilsonian', 'renormalization', 'group', 'rg', 'flow', 'we', 'then', 'illustrate', 'the', 'wilsonian', 'rg', 'flow', 'on', 'the', 'basis', 'of', 'the', 'gradient', 'flow', 'in', 'two', 'examples', 'that', 'possess', 'an', 'infrared', 'fixed', 'point', 'the', '4d', 'manyflavor', 'gauge', 'theory', 'and', 'the', '3d', 'on', 'linear', 'sigma', 'model']] | [-0.1534765684450774, 0.13617375650484473, -0.20933623976357604, 0.03140345852876055, -0.07213247187800058, -0.09362369663743438, -0.011376118187900578, 0.3714016596854165, -0.3057243070308713, -0.2042275302759979, 0.11256521690360176, -0.28243087653232657, -0.17423339881529304, 0.14215293710889376, -0.033273879627602684, 0.05413923320778902, -0.01781595835759156, 0.059120137986821544, -0.11828327565656407, -0.19406403512086556, 0.3518429971570014, -0.00701630879463493, 0.2919986012891151, 0.05840295738797041, 0.1512577624829567, -0.02118555544808075, -0.049810127814070904, 0.06314978199889479, -0.15240193147020772, 0.0871648720762544, 0.1566892275991647, 0.036334499568287014, 0.21214041390382024, -0.4147497187975956, -0.2898421531232695, 0.027929427588115566, 0.1318076602588205, 0.13405646335171617, -0.07673095183217547, -0.20626846068552224, 0.041899512076507446, -0.15611956465611423, -0.1360989568259, -0.09364249192826125, -0.03391935165458615, -0.04734970226991868, -0.24191053763733825, 0.08364506823051235, -0.012827911685841778, 0.12102022609147041, -0.03441467719233554, -0.02268883189105469, -0.0947367018274288, 0.1359366933963653, 0.12578418957697146, 0.07032413649764183, 0.18973295674726798, -0.19574392419240938, -0.06310292182868157, 0.41058156984871713, -0.1136509797576329, -0.21908456427247627, 0.17256967408879512, -0.06654473776132733, -0.12852625451320648, 0.06828453289884803, 0.17225709254515992, 0.16938614250039277, -0.12634247754012112, 0.14913972506073533, -0.119580686038387, 0.1213994285760724, -0.011774727291818977, -0.06218898766066717, 0.16142724138563094, 0.08646918409436509, 0.12657793836020256, 0.06876935599965678, -0.0377297256803275, -0.15415793704543856, -0.44106288804956106, -0.14873136254702357, -0.13216469697384298, 0.07728581033323122, -0.23952573728077012, -0.15580194899677366, 0.43098939822959725, 0.15831882566503802, 0.22243211144392472, 0.06457015413004716, 0.2590390992337379, 0.15932979214720536, 0.06542161138107379, 0.15899156697391384, 0.2353051861046233, 0.15455864189003687, 0.08512498950585723, -0.3251982592721132, -0.09752257504378972, 0.23528320810663095] |
1,802.07898 | Glimpse Clouds: Human Activity Recognition from Unstructured Feature
Points | We propose a method for human activity recognition from RGB data that does
not rely on any pose information during test time and does not explicitly
calculate pose information internally. Instead, a visual attention module
learns to predict glimpse sequences in each frame. These glimpses correspond to
interest points in the scene that are relevant to the classified activities. No
spatial coherence is forced on the glimpse locations, which gives the module
liberty to explore different points at each frame and better optimize the
process of scrutinizing visual information. Tracking and sequentially
integrating this kind of unstructured data is a challenge, which we address by
separating the set of glimpses from a set of recurrent tracking/recognition
workers. These workers receive glimpses, jointly performing subsequent motion
tracking and activity prediction. The glimpses are soft-assigned to the
workers, optimizing coherence of the assignments in space, time and feature
space using an external memory module. No hard decisions are taken, i.e. each
glimpse point is assigned to all existing workers, albeit with different
importance. Our methods outperform state-of-the-art methods on the largest
human activity recognition dataset available to-date; NTU RGB+D Dataset, and on
a smaller human action recognition dataset Northwestern-UCLA Multiview Action
3D Dataset. Our code is publicly available at
https://github.com/fabienbaradel/glimpse_clouds.
| cs.CV | we propose a method for human activity recognition from rgb data that does not rely on any pose information during test time and does not explicitly calculate pose information internally instead a visual attention module learns to predict glimpse sequences in each frame these glimpses correspond to interest points in the scene that are relevant to the classified activities no spatial coherence is forced on the glimpse locations which gives the module liberty to explore different points at each frame and better optimize the process of scrutinizing visual information tracking and sequentially integrating this kind of unstructured data is a challenge which we address by separating the set of glimpses from a set of recurrent trackingrecognition workers these workers receive glimpses jointly performing subsequent motion tracking and activity prediction the glimpses are softassigned to the workers optimizing coherence of the assignments in space time and feature space using an external memory module no hard decisions are taken ie each glimpse point is assigned to all existing workers albeit with different importance our methods outperform stateoftheart methods on the largest human activity recognition dataset available todate ntu rgbd dataset and on a smaller human action recognition dataset northwesternucla multiview action 3d dataset our code is publicly available at httpsgithubcomfabienbaradelglimpse_clouds | [['we', 'propose', 'a', 'method', 'for', 'human', 'activity', 'recognition', 'from', 'rgb', 'data', 'that', 'does', 'not', 'rely', 'on', 'any', 'pose', 'information', 'during', 'test', 'time', 'and', 'does', 'not', 'explicitly', 'calculate', 'pose', 'information', 'internally', 'instead', 'a', 'visual', 'attention', 'module', 'learns', 'to', 'predict', 'glimpse', 'sequences', 'in', 'each', 'frame', 'these', 'glimpses', 'correspond', 'to', 'interest', 'points', 'in', 'the', 'scene', 'that', 'are', 'relevant', 'to', 'the', 'classified', 'activities', 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1,802.07899 | Optical stimulated slowing of polar heavy-atom molecules with a constant
beat phase | Polar heavy-atom molecules have been well recognized as promising candidates
for precision measurements and tests of fundamental physics. A much slower
molecular beam to increase the interaction time should lead to a more sensitive
measurement. Here we theoretically demonstrate the possibility of the
stimulated longitudinal slowing of heavy-atom molecules by the coherent optical
bichromatic force with a constant beat phase. Taking the YbF meolecule as an
example, we show that a rapid and short-distance deceleration of heavy
molecules by a phase-compensation method is feasible with moderate conditions.
A molecular beam of YbF with a forward velocity of 120 m/s can be decelerated
below 10 m/s within a distance of 3.5 cm and with a laser irradiance for each
traveling wave of 107.2 W/cm$^2$. We also give a simple approach to estimate
the performance of the BCF on some other heavy molecules, which is helpful for
making a rapid evaluation on the feasibility of the stimulated slowing
experiment. Our proposed slowing method could be a promising approach to break
through the space constraint or the limited capture efficiency of molecules
loadable into a MOT in traditional deceleration schemes, opening the
possibility for a significant improvement of the precision measurement
sensitivity.
| physics.atom-ph | polar heavyatom molecules have been well recognized as promising candidates for precision measurements and tests of fundamental physics a much slower molecular beam to increase the interaction time should lead to a more sensitive measurement here we theoretically demonstrate the possibility of the stimulated longitudinal slowing of heavyatom molecules by the coherent optical bichromatic force with a constant beat phase taking the ybf meolecule as an example we show that a rapid and shortdistance deceleration of heavy molecules by a phasecompensation method is feasible with moderate conditions a molecular beam of ybf with a forward velocity of 120 ms can be decelerated below 10 ms within a distance of 35 cm and with a laser irradiance for each traveling wave of 1072 wcm2 we also give a simple approach to estimate the performance of the bcf on some other heavy molecules which is helpful for making a rapid evaluation on the feasibility of the stimulated slowing experiment our proposed slowing method could be a promising approach to break through the space constraint or the limited capture efficiency of molecules loadable into a mot in traditional deceleration schemes opening the possibility for a significant improvement of the precision measurement sensitivity | [['polar', 'heavyatom', 'molecules', 'have', 'been', 'well', 'recognized', 'as', 'promising', 'candidates', 'for', 'precision', 'measurements', 'and', 'tests', 'of', 'fundamental', 'physics', 'a', 'much', 'slower', 'molecular', 'beam', 'to', 'increase', 'the', 'interaction', 'time', 'should', 'lead', 'to', 'a', 'more', 'sensitive', 'measurement', 'here', 'we', 'theoretically', 'demonstrate', 'the', 'possibility', 'of', 'the', 'stimulated', 'longitudinal', 'slowing', 'of', 'heavyatom', 'molecules', 'by', 'the', 'coherent', 'optical', 'bichromatic', 'force', 'with', 'a', 'constant', 'beat', 'phase', 'taking', 'the', 'ybf', 'meolecule', 'as', 'an', 'example', 'we', 'show', 'that', 'a', 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1,802.079 | Unexpected Phenomenology in Particle-Based Ice Absent in Magnetic Spin
Ice | While particle-based ices are often considered essentially equivalent to
magnet-based spin ices, the two differ essentially in frustration and
energetics. We show that at equilibrium particle-based ices correspond exactly
to spin ices coupled to a background field. In trivial geometries, such a field
has no effect, and the two systems are indeed thermodynamically equivalent. In
other cases, however, the field controls a richer phenomenology, absent in
magnetic ices, and still largely unexplored: ice rule fragility, topological
charge transfer, radial polarization, decimation induced disorder, and
glassiness.
| cond-mat.soft cond-mat.mes-hall cond-mat.stat-mech | while particlebased ices are often considered essentially equivalent to magnetbased spin ices the two differ essentially in frustration and energetics we show that at equilibrium particlebased ices correspond exactly to spin ices coupled to a background field in trivial geometries such a field has no effect and the two systems are indeed thermodynamically equivalent in other cases however the field controls a richer phenomenology absent in magnetic ices and still largely unexplored ice rule fragility topological charge transfer radial polarization decimation induced disorder and glassiness | [['while', 'particlebased', 'ices', 'are', 'often', 'considered', 'essentially', 'equivalent', 'to', 'magnetbased', 'spin', 'ices', 'the', 'two', 'differ', 'essentially', 'in', 'frustration', 'and', 'energetics', 'we', 'show', 'that', 'at', 'equilibrium', 'particlebased', 'ices', 'correspond', 'exactly', 'to', 'spin', 'ices', 'coupled', 'to', 'a', 'background', 'field', 'in', 'trivial', 'geometries', 'such', 'a', 'field', 'has', 'no', 'effect', 'and', 'the', 'two', 'systems', 'are', 'indeed', 'thermodynamically', 'equivalent', 'in', 'other', 'cases', 'however', 'the', 'field', 'controls', 'a', 'richer', 'phenomenology', 'absent', 'in', 'magnetic', 'ices', 'and', 'still', 'largely', 'unexplored', 'ice', 'rule', 'fragility', 'topological', 'charge', 'transfer', 'radial', 'polarization', 'decimation', 'induced', 'disorder', 'and', 'glassiness']] | [-0.14414531866454386, 0.25705387057470425, -0.04626507588130023, 0.10556071844794565, -0.03313388496393427, -0.1670859344359044, -0.02060623484708014, 0.4131753294883917, -0.26686810731466504, -0.28920653450214084, 0.05638394006971447, -0.2588868949429265, -0.1418888907036966, 0.09494524750126791, 0.01627229753371683, -0.031231242007509406, -0.030826980381139686, -0.047116682443412994, -0.0701579848731247, -0.21652976060951395, 0.26367927890359644, 0.03174114208723906, 0.26665199060170425, 0.04702118394475076, 0.07538714779574159, -0.06703690523725181, 0.04793591031782506, 0.06942608983442933, -0.1619030534255303, 0.012179256337168183, 0.27163136309190167, -0.02380670629818702, 0.10471034500334922, -0.46711924748351086, -0.2304742104551267, 0.10353619506072607, 0.1376449312083423, 0.1692294978531122, -0.04395213124475309, -0.2095428784267001, -0.022758870202648853, -0.12293537391260975, -0.10297331880290239, -0.07701880993997856, 0.03878144638396667, -0.05980470381508071, -0.20996448304642745, 0.10295069937239446, 0.12104367575652543, 0.12875849194270336, -0.1156811402511916, -0.168655395205687, -0.12538973515343277, 0.022342277740660523, 0.04249600281140634, 0.03476973572590699, 0.23178578230796293, -0.17073453261261984, -0.11438378625150238, 0.38395168552441256, -0.044520441082394904, -0.1954715216111037, 0.2872003340051465, -0.1647057707831707, -0.15712059838032083, 0.24400739795306609, 0.06274753186984786, 0.10775757159682967, -0.16359305300284177, 0.06727554740860969, 0.006555912827718116, 0.15272188415041282, 0.021249408822595364, 0.09411458340556626, 0.3209019083352316, 0.10954799649993047, 0.05164432269382468, 0.12850495541005375, -0.04526815865011442, -0.18252004299401528, -0.1772394984007059, -0.14703647139304804, -0.19827280893167926, 0.08014740715069431, -0.05459872664332146, -0.1776800566419427, 0.32483554554069305, 0.19482065051921554, 0.11770905962302572, -0.0603202825240303, 0.2468256228825166, 0.024592146360581473, 0.052816228774775355, 0.09353319869288021, 0.29089841332530514, 0.1671350451485653, 0.10764805838698521, -0.2675374611918371, 0.09938729954661712, 0.013885219259897158] |
1,802.07901 | Symmetry of maximals for fractional ideals of curves | The purpose of this paper is to extend the symmetry of maximals of the ring
of a germ of reducible plane curve proved by Delgado to a relation between the
relative maximals of a fractional ideal and the absolute maximals of its dual
for any admissible ring. In particular, it includes the case of germs of
reduced reducible curve of any codimension. We then apply this symmetry to
characterize the elements in the set of values of a fractional ideal from some
of its projections and the irreducible absolute maximals of the dual ideal.
| math.AG | the purpose of this paper is to extend the symmetry of maximals of the ring of a germ of reducible plane curve proved by delgado to a relation between the relative maximals of a fractional ideal and the absolute maximals of its dual for any admissible ring in particular it includes the case of germs of reduced reducible curve of any codimension we then apply this symmetry to characterize the elements in the set of values of a fractional ideal from some of its projections and the irreducible absolute maximals of the dual ideal | [['the', 'purpose', 'of', 'this', 'paper', 'is', 'to', 'extend', 'the', 'symmetry', 'of', 'maximals', 'of', 'the', 'ring', 'of', 'a', 'germ', 'of', 'reducible', 'plane', 'curve', 'proved', 'by', 'delgado', 'to', 'a', 'relation', 'between', 'the', 'relative', 'maximals', 'of', 'a', 'fractional', 'ideal', 'and', 'the', 'absolute', 'maximals', 'of', 'its', 'dual', 'for', 'any', 'admissible', 'ring', 'in', 'particular', 'it', 'includes', 'the', 'case', 'of', 'germs', 'of', 'reduced', 'reducible', 'curve', 'of', 'any', 'codimension', 'we', 'then', 'apply', 'this', 'symmetry', 'to', 'characterize', 'the', 'elements', 'in', 'the', 'set', 'of', 'values', 'of', 'a', 'fractional', 'ideal', 'from', 'some', 'of', 'its', 'projections', 'and', 'the', 'irreducible', 'absolute', 'maximals', 'of', 'the', 'dual', 'ideal']] | [-0.1656329302672059, 0.03850800297322109, -0.10667428322770495, -0.0015406255929810095, -0.05820048154589343, -0.07698735414429549, 0.017587498371598332, 0.2882161747882182, -0.3105107744402708, -0.17554377971038698, 0.10366616026805515, -0.23376251972141734, -0.11459365171538864, 0.19247051415608285, -0.10499166765626758, 0.016387507842235673, -0.001867416374226834, 0.09917508319708855, -0.13676522471298008, -0.23131420849723386, 0.37730211213706655, -0.019970671922721443, 0.20591187678733247, 0.008591114736578248, 0.13810448999952604, 0.016837225270834057, -0.033253699907676335, 0.012547107017103662, -0.16336972886656828, 0.17455106312805352, 0.24390535047674117, 0.08183384551963907, 0.19260630360309114, -0.34008781657494763, -0.10671442323067087, 0.22871249911197006, 0.0896100261981817, 0.03058325770766811, 0.0293424887225983, -0.21772053653245516, 0.1280150849352333, -0.16761269059745557, -0.2309090939172088, -0.007825209590745098, 0.09381614867201511, 0.04783779206348861, -0.24569441834860978, 0.018106694927716507, 0.1420013919808472, 0.12596256273025844, -0.060469198280925604, -0.08165073551316844, -0.07500254176309372, 0.08528087144975174, -0.010311534908164213, 0.04724442222690646, 0.05292810695097247, -0.13496378544926088, -0.08897095258308059, 0.4170303441821895, -0.06130094533944701, -0.19933090918261478, 0.14830586448945898, -0.17723906345596102, -0.07965142275404899, 0.13840864167766684, 0.10689214175131093, 0.14188298575104552, -0.07872754221465042, 0.1690125900823524, -0.09658238270934275, 0.08698386245189195, 0.05904942517109374, 0.005823689810139068, 0.1587810251624026, 0.08652687702635105, 0.0762855361588547, 0.1792497588816951, -0.03074194039119051, -0.003730495051639353, -0.37606755526181546, -0.25013555045378333, -0.15824969128849223, 0.09112389186555718, -0.08606698329063836, -0.1538822370224652, 0.4523528997409851, 0.11848992491735423, 0.20189866390911507, 0.04610088865886977, 0.24204440563520851, 0.09812802983775483, 0.02817430491361054, 0.03673648039632021, 0.20142107652754157, 0.182385292253457, -0.01993070384289356, -0.24115168408025056, 0.0030046543304590467, 0.13634001858968367] |
1,802.07902 | On the implementation of a primal-dual algorithm for second order
time-dependent mean field games with local couplings | We study a numerical approximation of a time-dependent Mean Field Game (MFG)
system with local couplings. The discretization we consider stems from a
variational approach described in [Briceno-Arias, Kalise, and Silva, SIAM J.
Control Optim., 2017] for the stationary problem and leads to the finite
difference scheme introduced by Achdou and Capuzzo-Dolcetta in [SIAM J. Numer.
Anal., 48(3):1136-1162, 2010]. In order to solve the finite dimensional
variational problems, in [Briceno-Arias, Kalise, and Silva, SIAM J. Control
Optim., 2017] the authors implement the primal-dual algorithm introduced by
Chambolle and Pock in [J. Math. Imaging Vision, 40(1):120-145, 2011], whose
core consists in iteratively solving linear systems and applying a proximity
operator. We apply that method to time-dependent MFG and, for large viscosity
parameters, we improve the linear system solution by replacing the direct
approach used in [Briceno-Arias, Kalise, and Silva, SIAM J. Control Optim.,
2017] by suitable preconditioned iterative algorithms.
| math.OC math.NA | we study a numerical approximation of a timedependent mean field game mfg system with local couplings the discretization we consider stems from a variational approach described in bricenoarias kalise and silva siam j control optim 2017 for the stationary problem and leads to the finite difference scheme introduced by achdou and capuzzodolcetta in siam j numer anal 48311361162 2010 in order to solve the finite dimensional variational problems in bricenoarias kalise and silva siam j control optim 2017 the authors implement the primaldual algorithm introduced by chambolle and pock in j math imaging vision 401120145 2011 whose core consists in iteratively solving linear systems and applying a proximity operator we apply that method to timedependent mfg and for large viscosity parameters we improve the linear system solution by replacing the direct approach used in bricenoarias kalise and silva siam j control optim 2017 by suitable preconditioned iterative algorithms | [['we', 'study', 'a', 'numerical', 'approximation', 'of', 'a', 'timedependent', 'mean', 'field', 'game', 'mfg', 'system', 'with', 'local', 'couplings', 'the', 'discretization', 'we', 'consider', 'stems', 'from', 'a', 'variational', 'approach', 'described', 'in', 'bricenoarias', 'kalise', 'and', 'silva', 'siam', 'j', 'control', 'optim', '2017', 'for', 'the', 'stationary', 'problem', 'and', 'leads', 'to', 'the', 'finite', 'difference', 'scheme', 'introduced', 'by', 'achdou', 'and', 'capuzzodolcetta', 'in', 'siam', 'j', 'numer', 'anal', '48311361162', '2010', 'in', 'order', 'to', 'solve', 'the', 'finite', 'dimensional', 'variational', 'problems', 'in', 'bricenoarias', 'kalise', 'and', 'silva', 'siam', 'j', 'control', 'optim', '2017', 'the', 'authors', 'implement', 'the', 'primaldual', 'algorithm', 'introduced', 'by', 'chambolle', 'and', 'pock', 'in', 'j', 'math', 'imaging', 'vision', '401120145', '2011', 'whose', 'core', 'consists', 'in', 'iteratively', 'solving', 'linear', 'systems', 'and', 'applying', 'a', 'proximity', 'operator', 'we', 'apply', 'that', 'method', 'to', 'timedependent', 'mfg', 'and', 'for', 'large', 'viscosity', 'parameters', 'we', 'improve', 'the', 'linear', 'system', 'solution', 'by', 'replacing', 'the', 'direct', 'approach', 'used', 'in', 'bricenoarias', 'kalise', 'and', 'silva', 'siam', 'j', 'control', 'optim', '2017', 'by', 'suitable', 'preconditioned', 'iterative', 'algorithms']] | [-0.057834081547908894, -0.018340262987855058, -0.05923156953123335, -0.043007433771678844, -0.07716628618870083, -0.14593301884421747, 0.06611561157568421, 0.318779765813267, -0.27366044451418803, -0.37784834208974794, 0.09535870480682854, -0.22278374725991018, -0.1694337249133889, 0.15844310648190751, -0.14971066740252179, 0.11397403000203306, 0.04313765702871223, -0.1493820787330911, -0.03973104067829323, -0.2560704264635131, 0.24337319369517166, 0.0372738228303106, 0.22894829063862085, 0.005589207757921405, 0.14863792053991545, 0.09287518560599331, -0.09042608331528505, 0.05649959199347419, -0.1652121478757978, 0.09490965956850743, 0.29466085220138505, 0.06250965555696046, 0.35970724442948215, -0.36570708926971235, -0.17590683417343725, 0.06493540306668091, 0.05712310469084202, 0.07857923394655936, 0.017908607525049313, -0.3473236287516631, 0.06051409557862016, -0.16728447971559346, -0.09338809993143564, -0.10099970621107886, 0.08003630183959277, 0.04453976080937898, -0.37975672586527587, 0.13487297455359198, 0.08959045334900921, 0.06478420693478355, -0.06446225157849593, -0.1482762797171097, 0.007495970961204028, -0.013464543947707606, -0.0763737542454268, 0.08239121074239684, 0.023401455641150065, -0.037165870501554954, -0.19507398898394346, 0.31366817232170335, -0.0696795622711325, -0.18442117591860563, 0.19663884647649854, 0.04173847035287994, -0.10753840151600132, 0.08354313586749239, 0.23326666225329973, 0.19884219351511653, -0.17017927705565442, 0.24947507259096474, -0.050476326409421145, 0.09717887456924336, 0.10407296075543057, -0.13170098997206006, -0.0007590439285419576, 0.09105063987615174, 0.12016954990295209, 0.06940673167613169, -0.017591434428851083, -0.15534977901931088, -0.21071919266450256, -0.11857835895053752, -0.2019560507383861, 0.0276161418519659, 0.006164805644490016, -0.09422330949327921, 0.35561434590753166, 0.1588801832623263, 0.12122378057691792, -0.00291794798917405, 0.18999812859174323, 0.18075307494361106, -0.05789352883385456, 0.23373785412117634, 0.23651132758942828, 0.2371162498251803, 0.19227249866466306, -0.2801710684593984, -0.0768618010820132, 0.23826904688728176] |
1,802.07903 | Safety-Aware Optimal Control of Stochastic Systems Using Conditional
Value-at-Risk | In this paper, we consider a multi-objective control problem for stochastic
systems that seeks to minimize a cost of interest while ensuring safety. We
introduce a novel measure of safety risk using the conditional value-at-risk
and a set distance to formulate a safety risk-constrained optimal control
problem. Our reformulation method using an extremal representation of the
safety risk measure provides a computationally tractable dynamic programming
solution. A useful byproduct of the proposed solution is the notion of a
risk-constrained safe set, which is a new stochastic safety verification tool.
We also establish useful connections between the risk-constrained safe sets and
the popular probabilistic safe sets. The tradeoff between the risk tolerance
and the mean performance of our controller is examined through an inventory
control problem.
| math.OC cs.SY | in this paper we consider a multiobjective control problem for stochastic systems that seeks to minimize a cost of interest while ensuring safety we introduce a novel measure of safety risk using the conditional valueatrisk and a set distance to formulate a safety riskconstrained optimal control problem our reformulation method using an extremal representation of the safety risk measure provides a computationally tractable dynamic programming solution a useful byproduct of the proposed solution is the notion of a riskconstrained safe set which is a new stochastic safety verification tool we also establish useful connections between the riskconstrained safe sets and the popular probabilistic safe sets the tradeoff between the risk tolerance and the mean performance of our controller is examined through an inventory control problem | [['in', 'this', 'paper', 'we', 'consider', 'a', 'multiobjective', 'control', 'problem', 'for', 'stochastic', 'systems', 'that', 'seeks', 'to', 'minimize', 'a', 'cost', 'of', 'interest', 'while', 'ensuring', 'safety', 'we', 'introduce', 'a', 'novel', 'measure', 'of', 'safety', 'risk', 'using', 'the', 'conditional', 'valueatrisk', 'and', 'a', 'set', 'distance', 'to', 'formulate', 'a', 'safety', 'riskconstrained', 'optimal', 'control', 'problem', 'our', 'reformulation', 'method', 'using', 'an', 'extremal', 'representation', 'of', 'the', 'safety', 'risk', 'measure', 'provides', 'a', 'computationally', 'tractable', 'dynamic', 'programming', 'solution', 'a', 'useful', 'byproduct', 'of', 'the', 'proposed', 'solution', 'is', 'the', 'notion', 'of', 'a', 'riskconstrained', 'safe', 'set', 'which', 'is', 'a', 'new', 'stochastic', 'safety', 'verification', 'tool', 'we', 'also', 'establish', 'useful', 'connections', 'between', 'the', 'riskconstrained', 'safe', 'sets', 'and', 'the', 'popular', 'probabilistic', 'safe', 'sets', 'the', 'tradeoff', 'between', 'the', 'risk', 'tolerance', 'and', 'the', 'mean', 'performance', 'of', 'our', 'controller', 'is', 'examined', 'through', 'an', 'inventory', 'control', 'problem']] | [-0.12616782633960247, -0.036501184141030533, -0.11918629609048366, 0.11848184774257242, -0.09115787436813116, -0.1396775599680841, 0.14074644206557424, 0.33988942059874533, -0.3025867209881544, -0.28697111547738313, 0.140620683982037, -0.247633005335927, -0.17499285680055618, 0.19195575203746557, -0.21264624460041523, 0.17206347754597665, 0.03986109401192516, 0.02504558113962412, -0.0032041096673347054, -0.19745707830786705, 0.275319053680636, 0.046626709885895255, 0.3065128058977425, 0.06768021868768846, 0.16474338155984877, 0.05199568287283182, 0.04030708809848875, 0.07257166683487594, -0.12856673609866995, 0.20137486276496203, 0.30583056465908887, 0.2798743220418692, 0.44635766884684563, -0.3640258142501116, -0.1622293751910329, 0.14275377275515347, 0.05665119344135747, 0.04648209617938846, -0.05766760590672493, -0.2701298819333315, 0.05545981645397842, -0.18505767388641833, -0.10124381723767147, -0.10233022831380367, -0.028097489699721336, -0.025904347971547396, -0.34126523504406214, -0.011031082255998626, 0.005343891642056405, 0.04936905248463154, -0.06838101138174534, -0.06127388578653335, 0.022746239246800543, 0.14250643650069833, 0.033636163865216076, 0.0146710433550179, 0.1135742036504671, -0.08955950005166233, -0.16339547969400883, 0.359427959702909, -0.028138528026640415, -0.2454942774772644, 0.15635727303475142, 0.009861047372221947, -0.14869737896323204, 0.09180548164993524, 0.2512240066602826, 0.17083763302862645, -0.26068772287666797, 0.06366377602750435, -0.04269962451606989, 0.16667282987572252, 0.013059900030493737, 0.039851193454116585, 0.17080466388352214, 0.2730293552577496, 0.21705540028959514, 0.21308414397016168, -0.024169468339532613, -0.11871041248738766, -0.31729069059342146, -0.16659069176763297, -0.09990520003810525, -0.026763171963393687, -0.1301885868605459, -0.19446040198206901, 0.35839257469773295, 0.20260273611545562, 0.1193782280087471, 0.18375479087140412, 0.33553154696524146, 0.15218626301013866, -0.015020813902840019, 0.11795360754057765, 0.19820160012552515, 0.08873176334798336, 0.06199520497582853, -0.24373660791292787, 0.1450923865046352, 0.08015200793370604] |
1,802.07904 | Bulk viscosity of a hot QCD/QGP medium in strong magnetic field within
relaxation-time approximation | The bulk viscosity of hot QCD medium has been obtained in the presence of
strong magnetic field. The present investigation involves the estimation of the
quark damping rate and subsequently the thermal relaxation time for quarks in
the presence of magnetic field while realizing the hot QCD medium as an
effective Grand-canonical ensemble of effective gluons and quarks-antiquarks.
The dominant process in the strong field limit is $1\rightarrow 2$
($g\rightarrow q \bar{q}$) which contributes to the bulk viscosity in a most
significant way. Further, setting up the linearized transport equation in the
framework of an effective kinetic theory with hot QCD medium effects and
employing the relaxation time approximation, the bulk viscosity has been
estimated in lowest Landau level (LLL) and beyond. The temperature dependence
of the ratio of the bulk viscosity to entropy density indicates towards its
rising behavior near the transition temperature.
| nucl-th | the bulk viscosity of hot qcd medium has been obtained in the presence of strong magnetic field the present investigation involves the estimation of the quark damping rate and subsequently the thermal relaxation time for quarks in the presence of magnetic field while realizing the hot qcd medium as an effective grandcanonical ensemble of effective gluons and quarksantiquarks the dominant process in the strong field limit is 1rightarrow 2 grightarrow q barq which contributes to the bulk viscosity in a most significant way further setting up the linearized transport equation in the framework of an effective kinetic theory with hot qcd medium effects and employing the relaxation time approximation the bulk viscosity has been estimated in lowest landau level lll and beyond the temperature dependence of the ratio of the bulk viscosity to entropy density indicates towards its rising behavior near the transition temperature | [['the', 'bulk', 'viscosity', 'of', 'hot', 'qcd', 'medium', 'has', 'been', 'obtained', 'in', 'the', 'presence', 'of', 'strong', 'magnetic', 'field', 'the', 'present', 'investigation', 'involves', 'the', 'estimation', 'of', 'the', 'quark', 'damping', 'rate', 'and', 'subsequently', 'the', 'thermal', 'relaxation', 'time', 'for', 'quarks', 'in', 'the', 'presence', 'of', 'magnetic', 'field', 'while', 'realizing', 'the', 'hot', 'qcd', 'medium', 'as', 'an', 'effective', 'grandcanonical', 'ensemble', 'of', 'effective', 'gluons', 'and', 'quarksantiquarks', 'the', 'dominant', 'process', 'in', 'the', 'strong', 'field', 'limit', 'is', '1rightarrow', '2', 'grightarrow', 'q', 'barq', 'which', 'contributes', 'to', 'the', 'bulk', 'viscosity', 'in', 'a', 'most', 'significant', 'way', 'further', 'setting', 'up', 'the', 'linearized', 'transport', 'equation', 'in', 'the', 'framework', 'of', 'an', 'effective', 'kinetic', 'theory', 'with', 'hot', 'qcd', 'medium', 'effects', 'and', 'employing', 'the', 'relaxation', 'time', 'approximation', 'the', 'bulk', 'viscosity', 'has', 'been', 'estimated', 'in', 'lowest', 'landau', 'level', 'lll', 'and', 'beyond', 'the', 'temperature', 'dependence', 'of', 'the', 'ratio', 'of', 'the', 'bulk', 'viscosity', 'to', 'entropy', 'density', 'indicates', 'towards', 'its', 'rising', 'behavior', 'near', 'the', 'transition', 'temperature']] | [-0.12840504779402787, 0.2132930933425491, -0.11239529990901549, 0.025218756709831622, -0.014921742484956566, -0.050025288976030424, 0.04804949234615682, 0.303475634712312, -0.24276436967273993, -0.2767138987482112, 0.028132285234379297, -0.2839407211480041, -0.025979132847472403, 0.08585574730467568, 0.06389708253405185, 0.06654612178075088, -0.04258379412284638, 0.03228306383890514, -0.06331357617940132, -0.19241264339264794, 0.2987594278690974, 0.08864917144981316, 0.2760482301770632, 0.1538915289630596, 0.057366457677239344, 0.0027855793660920528, 0.01369528711721715, 0.03456807203555298, -0.12977103320736205, 0.005122541540509297, 0.18916071531445292, -0.03609573479884097, 0.2359819964104746, -0.40251166892671286, -0.25707076558966135, 0.04442176906579536, 0.16863573471588703, 0.11038212408392509, -0.04405142820582518, -0.20727247222869968, 0.03771899010623909, -0.1656589901023027, -0.16097621814292828, -0.09279521136260074, 0.026756278196343273, -0.07690242988569986, -0.2835919482814562, 0.16413653880287407, 0.033828716909435265, 0.026695291304753885, -0.07658789563882035, -0.17570750119112846, -0.047698681456192084, 0.08060753671129027, 0.11983786949814304, 0.10251131897712185, 0.18573364267811282, -0.22663517208517683, -0.057792010076809675, 0.3950020124628079, -0.150217699954131, -0.11371505542127933, 0.18934986729355943, -0.1780981354790533, -0.0797213587922872, 0.20426433148612785, 0.16706522260533851, 0.11308820903003733, -0.16378346322582932, 0.12515055838513137, -0.014065173463879747, 0.13921648949973234, 0.037120944755669266, 0.06864772093589029, 0.23582653091418454, 0.1939037342866262, 0.007618137295745934, 0.13324141845967258, -0.0812429384556405, -0.10172614253113149, -0.28436471662199536, -0.1453931770973011, -0.16097440510040745, 0.05582073101444015, -0.14804969129222123, -0.166903509367128, 0.355096138373483, 0.14899715709584094, 0.1707274978268995, -0.006439778616671295, 0.3052339618152473, 0.19734739028758164, 0.03881220396659854, 0.13207355890254904, 0.31392067474532975, 0.2262557086521863, 0.15148239917956138, -0.34429251248447046, 0.01615622584035413, 0.0877985457805658] |
1,802.07905 | Closed-loop control of a modular neuromorphic biohybrid | Neural networks modularity is a major challenge for the development of
control circuits of neural activity. Under physiological limitations, the
accessible regions for external stimulation are possibly different from the
functionally relevant ones, requiring complex indirect control designs.
Moreover, control over one region might affect activity of other downstream
networks, once sparse connections exist. We address these questions by
developing a hybrid device of a cortical culture functionally integrated with a
biomimetic hardware neural network. This design enables the study of modular
networks controllability, while connectivity is well-defined and key features
of cortical networks are accessible. Using a closed-loop control to monitor the
activity of the coupled hybrid, we show that both modules are congruently
modified, in the macroscopic as well as the microscopic activity levels.
Control impacts efficiently the activity on both sides whether the control
circuit is an indirect series one, or implemented independently only on one of
the modules. Hence, these results present global functional impacts of a local
control intervention. Overall, this strategy provides an experimental access to
the controllability of neural activity irregularities, when embedded in a
modular organization.
| q-bio.NC | neural networks modularity is a major challenge for the development of control circuits of neural activity under physiological limitations the accessible regions for external stimulation are possibly different from the functionally relevant ones requiring complex indirect control designs moreover control over one region might affect activity of other downstream networks once sparse connections exist we address these questions by developing a hybrid device of a cortical culture functionally integrated with a biomimetic hardware neural network this design enables the study of modular networks controllability while connectivity is welldefined and key features of cortical networks are accessible using a closedloop control to monitor the activity of the coupled hybrid we show that both modules are congruently modified in the macroscopic as well as the microscopic activity levels control impacts efficiently the activity on both sides whether the control circuit is an indirect series one or implemented independently only on one of the modules hence these results present global functional impacts of a local control intervention overall this strategy provides an experimental access to the controllability of neural activity irregularities when embedded in a modular organization | [['neural', 'networks', 'modularity', 'is', 'a', 'major', 'challenge', 'for', 'the', 'development', 'of', 'control', 'circuits', 'of', 'neural', 'activity', 'under', 'physiological', 'limitations', 'the', 'accessible', 'regions', 'for', 'external', 'stimulation', 'are', 'possibly', 'different', 'from', 'the', 'functionally', 'relevant', 'ones', 'requiring', 'complex', 'indirect', 'control', 'designs', 'moreover', 'control', 'over', 'one', 'region', 'might', 'affect', 'activity', 'of', 'other', 'downstream', 'networks', 'once', 'sparse', 'connections', 'exist', 'we', 'address', 'these', 'questions', 'by', 'developing', 'a', 'hybrid', 'device', 'of', 'a', 'cortical', 'culture', 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1,802.07906 | Stability of Granular Tunnel | We demonstrated the stability of tunnels made of granular matters is strongly
dependent on the grain size, tunnel diameter, and water content in the
granules. Larger tunnel radius, larger grain size, and too much water content
tend to destabilize the tunnel. We also develop a model to describe such
findings. We identified a phase diagram of stability which greatly controlled
by granular bond order. For granular bond order of larger than unity, we can
always made a stable tunnel. However, for granular bond order of less than
unity, we obtain a general expression for maximum tunnel thickness that can be
made. To best of our knowledge, this is the first exploration regarding the
granular tunnel stability.
| cond-mat.soft | we demonstrated the stability of tunnels made of granular matters is strongly dependent on the grain size tunnel diameter and water content in the granules larger tunnel radius larger grain size and too much water content tend to destabilize the tunnel we also develop a model to describe such findings we identified a phase diagram of stability which greatly controlled by granular bond order for granular bond order of larger than unity we can always made a stable tunnel however for granular bond order of less than unity we obtain a general expression for maximum tunnel thickness that can be made to best of our knowledge this is the first exploration regarding the granular tunnel stability | [['we', 'demonstrated', 'the', 'stability', 'of', 'tunnels', 'made', 'of', 'granular', 'matters', 'is', 'strongly', 'dependent', 'on', 'the', 'grain', 'size', 'tunnel', 'diameter', 'and', 'water', 'content', 'in', 'the', 'granules', 'larger', 'tunnel', 'radius', 'larger', 'grain', 'size', 'and', 'too', 'much', 'water', 'content', 'tend', 'to', 'destabilize', 'the', 'tunnel', 'we', 'also', 'develop', 'a', 'model', 'to', 'describe', 'such', 'findings', 'we', 'identified', 'a', 'phase', 'diagram', 'of', 'stability', 'which', 'greatly', 'controlled', 'by', 'granular', 'bond', 'order', 'for', 'granular', 'bond', 'order', 'of', 'larger', 'than', 'unity', 'we', 'can', 'always', 'made', 'a', 'stable', 'tunnel', 'however', 'for', 'granular', 'bond', 'order', 'of', 'less', 'than', 'unity', 'we', 'obtain', 'a', 'general', 'expression', 'for', 'maximum', 'tunnel', 'thickness', 'that', 'can', 'be', 'made', 'to', 'best', 'of', 'our', 'knowledge', 'this', 'is', 'the', 'first', 'exploration', 'regarding', 'the', 'granular', 'tunnel', 'stability']] | [-0.143823037566296, 0.20837460571482522, -0.052517682329976355, 0.04333932613572587, -0.0675284657787917, -0.11971329936982486, 0.0803234701301774, 0.37169416058118104, -0.22731339113369328, -0.33989412928449697, 0.07879049925370431, -0.2687162397878951, -0.08781072841595923, 0.1728837473522711, -0.017823934454695677, 0.03296994647524994, 0.018480635344468314, -0.008133184445764998, -0.041206218401604364, -0.23088169957567328, 0.26640423308809064, 0.07570526874945338, 0.2974911709637221, 0.10647372824364695, 0.027373185100290794, -0.05385409399931287, 0.04689127530758109, 0.11048339524081555, -0.25940912990292164, 0.11514216750571184, 0.21024901806657878, -0.03162559497989072, 0.20360287073357353, -0.48908312647635566, -0.2115314592254059, 0.06438081016651644, 0.15912469874180307, 0.12249068863557427, -0.00024449130006391425, -0.23365602702913998, 0.10320785098933968, -0.19366721287851446, -0.17814414072701515, -0.047577278238945996, 0.03438461252391852, 0.010506253110963433, -0.242259085437299, 0.013202592246545526, 0.06813649488773582, 0.05437339618320352, -0.013204225493546832, -0.1332022008347598, -0.06122193492523491, 0.09176510248828984, 0.02733980247987723, -0.01403673627847356, 0.18641332385194456, -0.13615925584173086, -0.007238606914299829, 0.387574871295485, -0.05365311955367737, -0.16519803529533011, 0.19986127717581031, -0.17762835947234698, -0.04476525612849871, 0.17329602270258654, 0.16778446567357228, 0.12370877747889608, -0.10659558805315916, -0.04492409606283563, -0.023899605219726096, 0.250049384953133, 0.09705531480521414, -0.02345535414973836, 0.21044371705020554, 0.26489561446139526, 0.11669437680393457, 0.17578508090609202, -0.103263527486104, -0.11811268998406313, -0.22127810826701722, -0.18862655053140018, -0.17976374700785905, 0.04305079055885817, -0.12694871517531534, -0.18466665650766087, 0.330947949452695, 0.16616056563236334, 0.1684476199704383, 0.014482336312508339, 0.25827593170909274, 0.08283565572065558, 0.10568771512520596, 0.039075734322601606, 0.2576220987107733, 0.12095386862297189, 0.11259929946993061, -0.1965242271082765, 0.1711538967692518, 0.02021425950806588] |
1,802.07907 | Intermediate valence in single crystalline Yb$_2$Si$_2$Al | Yb$_2$Si$_2$Al may be a prototype for exploring different aspects of the
Shastry-Sutherland lattice, formed by planes of orthogonally coupled Yb ions.
Measurements of the magnetic susceptibility find incoherently fluctuating
Yb$^{3+}$ moments coexisting with a weakly correlated metallic state that is
confirmed by measurements of the electrical resistivity. Increasing signs of
Kondo coherence are found with decreasing temperature, including an enhanced
Sommerfeld coefficient and Kadowaki-Woods ratio that signal that the metallic
state found at the lowest temperatures is a Fermi liquid where correlations
have become significantly stronger. A pronounced peak in the electronic and
magnetic specific heat indicates that the coupling of the Yb moments to the
conduction electrons leads to an effective Kondo temperature that is
approximately 30 K. The valence of Yb$_2$Si$_2$Al has been investigated with
electron spectroscopy methods. Yb$_2$Si$_2$Al is found to be strongly
intermediate valent ($v_F=2.68(2)$ at 80 K). Taken together, these experimental
data are consistent with a scenario where a coherent Kondo lattice forms in
Yb$_2$Si$_2$Al from an incoherently fluctuating ensemble of Yb moments with
incomplete Kondo compensation, and strong intermediate valence character.
| cond-mat.str-el | yb_2si_2al may be a prototype for exploring different aspects of the shastrysutherland lattice formed by planes of orthogonally coupled yb ions measurements of the magnetic susceptibility find incoherently fluctuating yb3 moments coexisting with a weakly correlated metallic state that is confirmed by measurements of the electrical resistivity increasing signs of kondo coherence are found with decreasing temperature including an enhanced sommerfeld coefficient and kadowakiwoods ratio that signal that the metallic state found at the lowest temperatures is a fermi liquid where correlations have become significantly stronger a pronounced peak in the electronic and magnetic specific heat indicates that the coupling of the yb moments to the conduction electrons leads to an effective kondo temperature that is approximately 30 k the valence of yb_2si_2al has been investigated with electron spectroscopy methods yb_2si_2al is found to be strongly intermediate valent v_f2682 at 80 k taken together these experimental data are consistent with a scenario where a coherent kondo lattice forms in yb_2si_2al from an incoherently fluctuating ensemble of yb moments with incomplete kondo compensation and strong intermediate valence character | [['yb_2si_2al', 'may', 'be', 'a', 'prototype', 'for', 'exploring', 'different', 'aspects', 'of', 'the', 'shastrysutherland', 'lattice', 'formed', 'by', 'planes', 'of', 'orthogonally', 'coupled', 'yb', 'ions', 'measurements', 'of', 'the', 'magnetic', 'susceptibility', 'find', 'incoherently', 'fluctuating', 'yb3', 'moments', 'coexisting', 'with', 'a', 'weakly', 'correlated', 'metallic', 'state', 'that', 'is', 'confirmed', 'by', 'measurements', 'of', 'the', 'electrical', 'resistivity', 'increasing', 'signs', 'of', 'kondo', 'coherence', 'are', 'found', 'with', 'decreasing', 'temperature', 'including', 'an', 'enhanced', 'sommerfeld', 'coefficient', 'and', 'kadowakiwoods', 'ratio', 'that', 'signal', 'that', 'the', 'metallic', 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1,802.07908 | Testing Charm Quark Equilibration in Ultra-High Energy Heavy Ion
Collisions with Fluctuations | Recent lattice QCD data on higher order susceptibilities of Charm quarks
provide the opportunity to explore Charm quark equilibration in the early quark
gluon plasma (QGP) phase. Here, we propose to use the lattice data on second
and fourth order net Charm susceptibilities to infer the Charm quark
equilibration temperature and the corresponding volume, in the early QGP stage,
via a combined analysis of experimentally measured multiplicity fluctuations.
Furthermore, the first perturbative results for the second and fourth order
Charm quark susceptibilities and their ratio are presented.
| hep-ph | recent lattice qcd data on higher order susceptibilities of charm quarks provide the opportunity to explore charm quark equilibration in the early quark gluon plasma qgp phase here we propose to use the lattice data on second and fourth order net charm susceptibilities to infer the charm quark equilibration temperature and the corresponding volume in the early qgp stage via a combined analysis of experimentally measured multiplicity fluctuations furthermore the first perturbative results for the second and fourth order charm quark susceptibilities and their ratio are presented | [['recent', 'lattice', 'qcd', 'data', 'on', 'higher', 'order', 'susceptibilities', 'of', 'charm', 'quarks', 'provide', 'the', 'opportunity', 'to', 'explore', 'charm', 'quark', 'equilibration', 'in', 'the', 'early', 'quark', 'gluon', 'plasma', 'qgp', 'phase', 'here', 'we', 'propose', 'to', 'use', 'the', 'lattice', 'data', 'on', 'second', 'and', 'fourth', 'order', 'net', 'charm', 'susceptibilities', 'to', 'infer', 'the', 'charm', 'quark', 'equilibration', 'temperature', 'and', 'the', 'corresponding', 'volume', 'in', 'the', 'early', 'qgp', 'stage', 'via', 'a', 'combined', 'analysis', 'of', 'experimentally', 'measured', 'multiplicity', 'fluctuations', 'furthermore', 'the', 'first', 'perturbative', 'results', 'for', 'the', 'second', 'and', 'fourth', 'order', 'charm', 'quark', 'susceptibilities', 'and', 'their', 'ratio', 'are', 'presented']] | [-0.03926324829641173, 0.2932989587137561, -0.15308637478142634, 0.11784101193556669, -0.06903309293155527, -0.022078060700247686, 0.10277736041395144, 0.31306846377750236, -0.17424803278569517, -0.2127605378627777, 0.030641210771262133, -0.3601895444223593, 0.06887984995719516, 0.03272733036642787, 0.08821772965442004, 0.15828411352831398, 0.0634429429379431, 0.022728435221815953, -0.07848785055838739, -0.30722457719645624, 0.3239290710838362, -0.015033354265508295, 0.23192599019164156, 0.256760864058274, 0.06316846249700021, -0.025105897596791046, -0.06429692971702108, -0.06002580635142566, -0.1415346023476423, 0.043984228659464025, 0.18225068494880936, -0.017263090098811978, 0.11613794431175994, -0.3890078459042071, -0.1393727480230489, 0.0651344356485696, 0.12650820529944767, 0.14728859077668052, -0.03056755080958293, -0.22946235388731476, 0.10445215104511757, -0.2377625884188489, -0.16747910575941205, -0.21179707626672997, -0.042024479204810214, -0.04012249788569137, -0.3256739057257943, 0.14313815518592796, -0.07621626974479563, 0.03332278205231688, 0.03429535308039223, -0.22511665756418103, -0.08622884904516154, 0.042715172984519566, 0.1032664696900067, 0.11893018746170504, 0.13679518194831694, -0.2006454211927351, -0.18096932571852345, 0.43632722701663257, -0.07695498349460848, -0.09641168878049772, 0.15421365538140994, -0.2509154700620592, -0.1122783593266089, 0.08370638810012532, 0.30105141318007106, 0.07739022658367095, -0.2257327475831255, 0.007467893035225998, 0.006871286993739249, 0.2044681137556146, 0.07561835617190976, 0.05905026260190697, 0.24193776113612728, 0.23198137956473378, -0.04825522313857901, 0.11011096383993589, -0.04979440393782724, -0.101893644373136, -0.3816435130891101, -0.09151617430107689, -0.13102694973215762, 0.010639535360862554, -0.1637359057096818, -0.12509462814349895, 0.41718980961147395, 0.1648480404789249, 0.2050011513149901, -0.030743744133318634, 0.3345276891286003, 0.09175775190494184, 0.009458589750267136, 0.10802216001989684, 0.2568045614886729, 0.25779740692212666, 0.27605159404077406, -0.35969113841741185, 0.01951980344742408, 0.1534957730628807] |
1,802.07909 | Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging utilizing
Deep Learning | Magnetic resonance spectroscopic imaging (SI) is a unique imaging technique
that provides biochemical information from in vivo tissues. The 1H spectra
acquired from several spatial regions are quantified to yield metabolite
concentrations reflective of tissue metabolism. However, since these
metabolites are found in tissues at very low concentrations, SI is often
acquired with limited spatial resolution. In this work we test the hypothesis
that deep learning is able to upscale low resolution SI, together with the
T1-weighted (T1w) image, to reconstruct high resolution SI. We report a novel
densely connected Unet (D-Unet) architecture capable of producing
super-resolution spectroscopic images. The inputs for the D-UNet are the T1w
image and the low resolution SI image while the output is the high resolution
SI. The results of the D-UNet are compared both qualitatively and
quantitatively to simulated and in vivo high resolution SI. It is found that
this deep learning approach can produce high quality spectroscopic images and
reconstruct entire 1H spectra from low resolution acquisitions, which can
greatly advance the current SI workflow.
| physics.med-ph | magnetic resonance spectroscopic imaging si is a unique imaging technique that provides biochemical information from in vivo tissues the 1h spectra acquired from several spatial regions are quantified to yield metabolite concentrations reflective of tissue metabolism however since these metabolites are found in tissues at very low concentrations si is often acquired with limited spatial resolution in this work we test the hypothesis that deep learning is able to upscale low resolution si together with the t1weighted t1w image to reconstruct high resolution si we report a novel densely connected unet dunet architecture capable of producing superresolution spectroscopic images the inputs for the dunet are the t1w image and the low resolution si image while the output is the high resolution si the results of the dunet are compared both qualitatively and quantitatively to simulated and in vivo high resolution si it is found that this deep learning approach can produce high quality spectroscopic images and reconstruct entire 1h spectra from low resolution acquisitions which can greatly advance the current si workflow | [['magnetic', 'resonance', 'spectroscopic', 'imaging', 'si', 'is', 'a', 'unique', 'imaging', 'technique', 'that', 'provides', 'biochemical', 'information', 'from', 'in', 'vivo', 'tissues', 'the', '1h', 'spectra', 'acquired', 'from', 'several', 'spatial', 'regions', 'are', 'quantified', 'to', 'yield', 'metabolite', 'concentrations', 'reflective', 'of', 'tissue', 'metabolism', 'however', 'since', 'these', 'metabolites', 'are', 'found', 'in', 'tissues', 'at', 'very', 'low', 'concentrations', 'si', 'is', 'often', 'acquired', 'with', 'limited', 'spatial', 'resolution', 'in', 'this', 'work', 'we', 'test', 'the', 'hypothesis', 'that', 'deep', 'learning', 'is', 'able', 'to', 'upscale', 'low', 'resolution', 'si', 'together', 'with', 'the', 't1weighted', 't1w', 'image', 'to', 'reconstruct', 'high', 'resolution', 'si', 'we', 'report', 'a', 'novel', 'densely', 'connected', 'unet', 'dunet', 'architecture', 'capable', 'of', 'producing', 'superresolution', 'spectroscopic', 'images', 'the', 'inputs', 'for', 'the', 'dunet', 'are', 'the', 't1w', 'image', 'and', 'the', 'low', 'resolution', 'si', 'image', 'while', 'the', 'output', 'is', 'the', 'high', 'resolution', 'si', 'the', 'results', 'of', 'the', 'dunet', 'are', 'compared', 'both', 'qualitatively', 'and', 'quantitatively', 'to', 'simulated', 'and', 'in', 'vivo', 'high', 'resolution', 'si', 'it', 'is', 'found', 'that', 'this', 'deep', 'learning', 'approach', 'can', 'produce', 'high', 'quality', 'spectroscopic', 'images', 'and', 'reconstruct', 'entire', '1h', 'spectra', 'from', 'low', 'resolution', 'acquisitions', 'which', 'can', 'greatly', 'advance', 'the', 'current', 'si', 'workflow']] | [0.0059500686505533276, 0.07175970280699995, -0.024255319683593266, 0.04722324389690902, -0.030465603443295804, -0.18023408110101902, -0.04855031277280474, 0.4676820775521053, -0.2521708628872063, -0.3614248993026829, 0.06898731433923172, -0.28607282722585425, -0.13806046424217003, 0.18302838582827083, -0.12265704749801824, 0.029239217733130464, 0.11630903432608669, -0.03004183739878584, -0.013016995513638439, -0.20826896645269508, 0.2040424775914289, 0.10865489967122706, 0.35699724105743796, 0.019244219021476414, 0.1354116994568125, -0.06729186738321427, -0.02319585934801157, 0.01723445422925748, -0.08158073987777793, 0.15449403523099284, 0.340664294782517, 0.16542109625473575, 0.20631910320425537, -0.44843313815938524, -0.2501449264805266, 0.01763865162298993, 0.17018225506424559, 0.09961060038835438, -0.06017738156870744, -0.26827434586296073, 0.12174669420481984, -0.06461553257513726, -0.02331116153360453, -0.1057558676233342, -0.05534054099062328, 0.010251864553009549, -0.26972704663937697, 0.10622735492625208, -0.023894813626484816, 0.12344669455359149, -0.13187668227108715, -0.08966205482977595, -0.045391926195385845, 0.14252360236051298, -0.05804391641056079, 0.021082242851302592, 0.1760357302846387, -0.16191482234497143, -0.02818829669525067, 0.3031707543820186, -0.021473771619047365, -0.11825208725451036, 0.23312567953605118, -0.20492744600118765, -0.1264128104274616, 0.24307362332420293, 0.13126265601732845, 0.11719444591746947, -0.14992165543290592, 0.011018447535312843, 0.026728204700576012, 0.23356926119223043, 0.0920367547216809, 0.053261232202964685, 0.1672356069483253, 0.22529544936341428, -0.026600845851177394, 0.06212705063639035, -0.2727258530738804, 0.06220678587479322, -0.1665056254037894, -0.14183112176481721, -0.18543293331424857, 0.040148781961761415, -0.08823775781587925, -0.11049876776307302, 0.3588709888470814, 0.15827892136456834, 0.2417757049742313, 0.035479023584928146, 0.36042691901499446, 0.009730156416311687, 0.1260722657492341, -0.0393992465633769, 0.2241054829859803, 0.11236670600835147, 0.1840259093712734, -0.2108182852429901, 0.07753182046110661, -0.04173433642460813] |
1,802.0791 | Carrier-Resolved Photo Hall Measurement in World-Record-Quality
Perovskite and Kesterite Solar Absorbers | Majority and minority carrier properties such as type, density and mobility
represent fundamental yet difficult to access parameters governing
semiconductor device performance, most notably solar cells. Obtaining this
information simultaneously under light illumination would unlock many critical
parameters such as recombination lifetime, recombination coefficient, and
diffusion length; while deeply interesting for optoelectronic devices, this
goal has remained elusive. We demonstrate here a new carrier-resolved
photo-Hall technique that rests on a new identity relating hole-electron
mobility difference ($\Delta\mu$), Hall coefficient ($h$), and conductivity
($\sigma$): $\Delta\mu=(2+d\ln h/d\ln \sigma)\,h\,\sigma$, and a rotating
parallel dipole line ac-field Hall system with Fourier/lock-in detection for
clean Hall signal measurement. We successfully apply this technique to recent
world-record-quality perovskite and kesterite films and map the results against
varying light intensities, demonstrating unprecedented simultaneous access to
the above-mentioned parameters.
| physics.app-ph cond-mat.mtrl-sci | majority and minority carrier properties such as type density and mobility represent fundamental yet difficult to access parameters governing semiconductor device performance most notably solar cells obtaining this information simultaneously under light illumination would unlock many critical parameters such as recombination lifetime recombination coefficient and diffusion length while deeply interesting for optoelectronic devices this goal has remained elusive we demonstrate here a new carrierresolved photohall technique that rests on a new identity relating holeelectron mobility difference deltamu hall coefficient h and conductivity sigma deltamu2dln hdln sigmahsigma and a rotating parallel dipole line acfield hall system with fourierlockin detection for clean hall signal measurement we successfully apply this technique to recent worldrecordquality perovskite and kesterite films and map the results against varying light intensities demonstrating unprecedented simultaneous access to the abovementioned parameters | [['majority', 'and', 'minority', 'carrier', 'properties', 'such', 'as', 'type', 'density', 'and', 'mobility', 'represent', 'fundamental', 'yet', 'difficult', 'to', 'access', 'parameters', 'governing', 'semiconductor', 'device', 'performance', 'most', 'notably', 'solar', 'cells', 'obtaining', 'this', 'information', 'simultaneously', 'under', 'light', 'illumination', 'would', 'unlock', 'many', 'critical', 'parameters', 'such', 'as', 'recombination', 'lifetime', 'recombination', 'coefficient', 'and', 'diffusion', 'length', 'while', 'deeply', 'interesting', 'for', 'optoelectronic', 'devices', 'this', 'goal', 'has', 'remained', 'elusive', 'we', 'demonstrate', 'here', 'a', 'new', 'carrierresolved', 'photohall', 'technique', 'that', 'rests', 'on', 'a', 'new', 'identity', 'relating', 'holeelectron', 'mobility', 'difference', 'deltamu', 'hall', 'coefficient', 'h', 'and', 'conductivity', 'sigma', 'deltamu2dln', 'hdln', 'sigmahsigma', 'and', 'a', 'rotating', 'parallel', 'dipole', 'line', 'acfield', 'hall', 'system', 'with', 'fourierlockin', 'detection', 'for', 'clean', 'hall', 'signal', 'measurement', 'we', 'successfully', 'apply', 'this', 'technique', 'to', 'recent', 'worldrecordquality', 'perovskite', 'and', 'kesterite', 'films', 'and', 'map', 'the', 'results', 'against', 'varying', 'light', 'intensities', 'demonstrating', 'unprecedented', 'simultaneous', 'access', 'to', 'the', 'abovementioned', 'parameters']] | [-0.12097934056818485, 0.11892114423587918, -0.024941027231514454, 0.0014919733544811607, -0.08980666296184063, -0.22354085458442569, 0.09161234221933409, 0.4159680195599794, -0.2746545231649652, -0.3170550191886723, 0.05299919776804745, -0.25145617298036815, -0.16481385447084904, 0.2428663312494755, -0.07307555717229842, 0.09449000027496368, -0.0005005116797983647, -0.06970140919554979, -0.021325633514672516, -0.177548196926713, 0.22782800906896591, 0.044346210144460205, 0.34285179487988354, 0.09608408339461312, 0.08440841478900984, 0.011047398693859577, 0.027557841902365907, 0.013065160904079675, -0.13965385902888375, 0.08370484776981175, 0.25248426136374474, -0.007132908284664154, 0.1944105659201741, -0.40014708109200003, -0.24633987259864806, 0.02474614442884922, 0.15803750922437756, 0.12280515526235104, -0.11289716229308397, -0.24575505959615113, 0.0471875698887743, -0.13233581672236322, -0.11454539863194804, -0.08145608805399387, 0.0685472365245223, -0.030791383017320186, -0.25458424995094536, 0.06505730841122567, 0.006007940137526021, 0.04705602931976318, -0.06744104703853372, -0.15330389262270183, 0.01835368450731039, 0.1406946185566485, 0.028477288426831365, -0.013032545161433517, 0.1956634609885514, -0.14218768890947103, -0.11070753097906709, 0.33890960378199814, -0.06916776894405484, -0.11541353928297758, 0.20226156769506634, -0.1761783114541322, -0.12139812154695391, 0.15273467360250653, 0.16931800194014796, 0.09284758871048689, -0.16960149788483977, 0.051893327491823585, -0.019244903557933866, 0.2032412091270089, 0.07353198156505823, 0.14099987667798997, 0.24395266916789116, 0.1962072480311617, 0.0414841007697396, 0.0628904716745019, -0.1351845671515912, -0.014197109581902623, -0.17534778270870446, -0.19149129431694745, -0.16992600217089057, 0.13129277561977507, -0.054436766789411194, -0.15949020983837545, 0.39711636342294515, 0.2033235069476068, 0.17482028721086681, -0.017154618844389916, 0.3220845798682421, 0.10034549148008227, 0.0732050308920443, 0.03816763582825661, 0.21451635678112507, 0.18870321571500973, 0.1295757326874882, -0.2730331247895956, 0.11924915779102593, -0.00839380007982254] |
1,802.07911 | The Intricate Structure of HH 508, the Brightest Microjet in the Orion
Nebula | We present Magellan adaptive optics H$\alpha$ imaging of HH 508, which has
the highest surface brightness among protostellar jets in the Orion Nebula. We
find that HH 508 actually has a shorter component to the west, and a longer and
knotty component to the east. The east component has a kink at 0.3" from the
jet-driving star $\theta^1$ Ori B2, so it may have been deflected by the
wind/radiation from the nearby $\theta^1$ Ori B1B5. The origin of both
components is unclear, but if each of them is a separate jet, then $\theta^1$
Ori B2 may be a tight binary. Alternatively, HH 508 may be a slow-moving
outflow, and each component represents an illuminated cavity wall. The
ionization front surrounding $\theta^1$ Ori B2B3 does not directly face
$\theta^1$ Ori B1B5, suggesting that the EUV radiation from $\theta^1$ Ori C
plays a dominant role in affecting the morphology of proplyds even in the
vicinity of $\theta^1$ Ori B1B5. Finally, we report an H$\alpha$ blob that
might be ejected by the binary proplyd LV 1.
| astro-ph.SR | we present magellan adaptive optics halpha imaging of hh 508 which has the highest surface brightness among protostellar jets in the orion nebula we find that hh 508 actually has a shorter component to the west and a longer and knotty component to the east the east component has a kink at 03 from the jetdriving star theta1 ori b2 so it may have been deflected by the windradiation from the nearby theta1 ori b1b5 the origin of both components is unclear but if each of them is a separate jet then theta1 ori b2 may be a tight binary alternatively hh 508 may be a slowmoving outflow and each component represents an illuminated cavity wall the ionization front surrounding theta1 ori b2b3 does not directly face theta1 ori b1b5 suggesting that the euv radiation from theta1 ori c plays a dominant role in affecting the morphology of proplyds even in the vicinity of theta1 ori b1b5 finally we report an halpha blob that might be ejected by the binary proplyd lv 1 | [['we', 'present', 'magellan', 'adaptive', 'optics', 'halpha', 'imaging', 'of', 'hh', '508', 'which', 'has', 'the', 'highest', 'surface', 'brightness', 'among', 'protostellar', 'jets', 'in', 'the', 'orion', 'nebula', 'we', 'find', 'that', 'hh', '508', 'actually', 'has', 'a', 'shorter', 'component', 'to', 'the', 'west', 'and', 'a', 'longer', 'and', 'knotty', 'component', 'to', 'the', 'east', 'the', 'east', 'component', 'has', 'a', 'kink', 'at', '03', 'from', 'the', 'jetdriving', 'star', 'theta1', 'ori', 'b2', 'so', 'it', 'may', 'have', 'been', 'deflected', 'by', 'the', 'windradiation', 'from', 'the', 'nearby', 'theta1', 'ori', 'b1b5', 'the', 'origin', 'of', 'both', 'components', 'is', 'unclear', 'but', 'if', 'each', 'of', 'them', 'is', 'a', 'separate', 'jet', 'then', 'theta1', 'ori', 'b2', 'may', 'be', 'a', 'tight', 'binary', 'alternatively', 'hh', '508', 'may', 'be', 'a', 'slowmoving', 'outflow', 'and', 'each', 'component', 'represents', 'an', 'illuminated', 'cavity', 'wall', 'the', 'ionization', 'front', 'surrounding', 'theta1', 'ori', 'b2b3', 'does', 'not', 'directly', 'face', 'theta1', 'ori', 'b1b5', 'suggesting', 'that', 'the', 'euv', 'radiation', 'from', 'theta1', 'ori', 'c', 'plays', 'a', 'dominant', 'role', 'in', 'affecting', 'the', 'morphology', 'of', 'proplyds', 'even', 'in', 'the', 'vicinity', 'of', 'theta1', 'ori', 'b1b5', 'finally', 'we', 'report', 'an', 'halpha', 'blob', 'that', 'might', 'be', 'ejected', 'by', 'the', 'binary', 'proplyd', 'lv', '1']] | [-0.08596555456772145, 0.11736852300337872, -0.08801357630597201, 0.015838052981904563, -0.1487673265278081, -0.16853749109808938, 0.025999775963210948, 0.44947342766244286, -0.224521649683788, -0.24408156044123092, 0.04666237414725706, -0.2553520612849321, -0.09078960188642962, 0.12725471297139032, -0.03654672712157615, -0.0974610574365825, 0.11747527057022351, -0.03319656824009396, 0.008452988347453146, -0.15544224925866792, 0.2551892363827008, 0.07789781386021934, 0.05301493176964322, 0.0062408518104011875, 0.04293307865501484, -0.12328002951713549, -0.011809323869936297, -0.057856362423391185, -0.1080489496658324, -0.007311744472776362, 0.18060022087719269, 0.13871804782393996, 0.23869243855317288, -0.33185127198916853, -0.20701529609437794, 0.009108319202965566, 0.23793446333982007, -0.06329745369508454, 0.022293440122803338, -0.2632443419391171, 0.09913964524482931, -0.18415294596763876, -0.1763573101899355, 0.15375742422029204, 0.12861968298049675, -0.01921409818261722, -0.24392249151213752, 0.08591870607732865, 0.036576412003110514, 0.06789208851711598, -0.10605947905478492, -0.1196895576542448, -0.0843362149057743, 0.06176082444824063, 0.0006045710855308985, 0.1938778965456702, 0.19543441586637858, -0.19456427663058645, -0.05407908939449601, 0.3893224827277695, -0.06039826075224787, -0.02738079222489816, 0.26708868377292905, -0.2514623536410704, -0.22392397534069902, 0.21991610624746694, 0.0581202518976848, 0.1307380536905587, -0.10853331075372939, 0.007614508582443279, -0.054957321775011246, 0.2181338936291, 0.10730544529246931, 0.0529623381265929, 0.29444131799812046, 0.06430212087455513, -0.0279131275147884, 0.1581924099621842, -0.3458192520359372, -0.03450935596002621, -0.2378893608033571, -0.13730118998105642, -0.09655229748372053, 0.09267187444367002, -0.14350925357125746, -0.1217631677705983, 0.3191186785859438, 0.07247797808289592, 0.2059950738650009, -0.07349003255744115, 0.26204931334325926, 0.08523390294628681, 0.10641592500712507, 0.20855875959016942, 0.3297220023854964, 0.13610338718183554, 0.113006467603933, -0.23977073865425855, 0.14535469837174508, 0.00585258427490561] |
1,802.07912 | Dynamic Sealing Using Magneto-Rheological Fluids | Micropumps are microfluidic components which are widely used in applications
such as chemical analysis, biological sensing and micro-robots. However, one
obstacle in developing micropumps is the extremely low efficiency relative to
their macro-scale counterparts. This paper presents a dynamic sealing method
for external gear pumps to reduce the volumetric losses through the clearance
between the tips of gears and the housing by using magneto-rheological (MR)
fluids. By mitigating these losses, we are able to achieve high efficiency and
high volumetric accuracy with current mechanical architectures and
manufacturing tolerances. Static and dynamic sealing using MR fluids are
investigated theoretically and experimentally. Two Mason numbers
$Mn\left(p\right)$ and $Mn\left(\Omega\right)$ which are defined in terms of
pressure gradient of the flow and velocity of the moving boundary respectively
are used to characterize and evaluate the sealing performance. A range of
magnetic field intensities is explored to determine optimal sealing
effectiveness, where effectiveness is evaluated using the ratio of volumetric
loss and friction factor. Finally, we quantify the effectiveness of this
dynamic sealing method under different working conditions for gear pumps.
| physics.app-ph physics.flu-dyn | micropumps are microfluidic components which are widely used in applications such as chemical analysis biological sensing and microrobots however one obstacle in developing micropumps is the extremely low efficiency relative to their macroscale counterparts this paper presents a dynamic sealing method for external gear pumps to reduce the volumetric losses through the clearance between the tips of gears and the housing by using magnetorheological mr fluids by mitigating these losses we are able to achieve high efficiency and high volumetric accuracy with current mechanical architectures and manufacturing tolerances static and dynamic sealing using mr fluids are investigated theoretically and experimentally two mason numbers mnleftpright and mnleftomegaright which are defined in terms of pressure gradient of the flow and velocity of the moving boundary respectively are used to characterize and evaluate the sealing performance a range of magnetic field intensities is explored to determine optimal sealing effectiveness where effectiveness is evaluated using the ratio of volumetric loss and friction factor finally we quantify the effectiveness of this dynamic sealing method under different working conditions for gear pumps | [['micropumps', 'are', 'microfluidic', 'components', 'which', 'are', 'widely', 'used', 'in', 'applications', 'such', 'as', 'chemical', 'analysis', 'biological', 'sensing', 'and', 'microrobots', 'however', 'one', 'obstacle', 'in', 'developing', 'micropumps', 'is', 'the', 'extremely', 'low', 'efficiency', 'relative', 'to', 'their', 'macroscale', 'counterparts', 'this', 'paper', 'presents', 'a', 'dynamic', 'sealing', 'method', 'for', 'external', 'gear', 'pumps', 'to', 'reduce', 'the', 'volumetric', 'losses', 'through', 'the', 'clearance', 'between', 'the', 'tips', 'of', 'gears', 'and', 'the', 'housing', 'by', 'using', 'magnetorheological', 'mr', 'fluids', 'by', 'mitigating', 'these', 'losses', 'we', 'are', 'able', 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1,802.07913 | Development of Aluminium Based Surface Nano Composites Using Friction
Stir Processing | Friction Stir Processing is a relatively new technique which has been
developed for microstructural modification of metallic materials through
intense, localized plastic deformation. The current research work deals with
the development of defect free Aluminium based surface nano composites, with
different volume fractions of second phase particles. The work is comprised of
development and deformation behavior of aluminium based surface nano
composites. Nano-structured second phases of Tungsten and Aluminium oxide were
introduced into the Aluminium matrix using a novel unique technique, friction
stir processing. Microstructural characterization was done using Scanning
Electron Microscopy and Xray Diffraction. Mechanical behavior was evaluated
using Vicker's micro hardness. Ultimately structure property correlations were
established.
| physics.app-ph | friction stir processing is a relatively new technique which has been developed for microstructural modification of metallic materials through intense localized plastic deformation the current research work deals with the development of defect free aluminium based surface nano composites with different volume fractions of second phase particles the work is comprised of development and deformation behavior of aluminium based surface nano composites nanostructured second phases of tungsten and aluminium oxide were introduced into the aluminium matrix using a novel unique technique friction stir processing microstructural characterization was done using scanning electron microscopy and xray diffraction mechanical behavior was evaluated using vickers micro hardness ultimately structure property correlations were established | [['friction', 'stir', 'processing', 'is', 'a', 'relatively', 'new', 'technique', 'which', 'has', 'been', 'developed', 'for', 'microstructural', 'modification', 'of', 'metallic', 'materials', 'through', 'intense', 'localized', 'plastic', 'deformation', 'the', 'current', 'research', 'work', 'deals', 'with', 'the', 'development', 'of', 'defect', 'free', 'aluminium', 'based', 'surface', 'nano', 'composites', 'with', 'different', 'volume', 'fractions', 'of', 'second', 'phase', 'particles', 'the', 'work', 'is', 'comprised', 'of', 'development', 'and', 'deformation', 'behavior', 'of', 'aluminium', 'based', 'surface', 'nano', 'composites', 'nanostructured', 'second', 'phases', 'of', 'tungsten', 'and', 'aluminium', 'oxide', 'were', 'introduced', 'into', 'the', 'aluminium', 'matrix', 'using', 'a', 'novel', 'unique', 'technique', 'friction', 'stir', 'processing', 'microstructural', 'characterization', 'was', 'done', 'using', 'scanning', 'electron', 'microscopy', 'and', 'xray', 'diffraction', 'mechanical', 'behavior', 'was', 'evaluated', 'using', 'vickers', 'micro', 'hardness', 'ultimately', 'structure', 'property', 'correlations', 'were', 'established']] | [-0.0772717745137324, 0.21601987974461886, -0.11245356440766278, -0.07937723521032122, -0.0521905586281535, -0.15883115212002624, -0.014182710525079913, 0.4202603033889051, -0.23078089344973138, -0.33479931894177145, 0.05087359912571745, -0.3070194632703558, -0.16789219830048466, 0.2052772424499923, -0.03416088309754199, 0.15424504205607223, -0.006575952360936261, -0.12503474863211905, -0.07974412551987062, -0.2029100179035695, 0.2338117985140293, 0.08942394283677049, 0.39123182899293, 0.09186009808503297, 0.08816124634697624, 0.0012897285077413288, 0.015646789248588436, 0.07518389415200971, -0.16443614741582252, 0.13856741425222419, 0.22338329154331613, -0.0409823688486198, 0.22989554151918296, -0.5275500070970129, -0.25266426013047816, -0.036725603394347044, 0.08706613856478843, 0.05261536664035761, -0.13535253392583732, -0.21931651398676252, 0.06010668444524118, -0.13014495562881642, -0.11052333334580473, -0.06594823846174831, 0.00706731727979052, 0.014094938801755325, -0.17334498839566073, 0.06257239229754981, 0.030115241780791672, 0.1397652584448491, -0.11566998201225875, -0.12298817310584795, -0.011914667301734379, 0.0542052331799214, -0.00586721938052172, -0.015138385935959944, 0.3000730965670984, -0.06888927536409929, -0.0707573538716592, 0.3534757961527607, 0.01194934398277637, -0.07399120227083428, 0.1823866898535725, -0.11167654974630141, -0.08515236397709595, 0.23208117491881783, 0.14527027349098834, 0.09012265530748105, -0.2537201068453798, 0.026716930268934732, 0.04568404191677723, 0.22820504385883997, 0.16239567168501265, 0.007734709308234924, 0.21099393349995307, 0.31711596074843046, -0.06101151224259937, 0.21119156506696476, -0.11184423248958561, 0.028110210416377138, -0.17495955720249085, -0.2286790359269725, -0.19757945460070847, 0.04783036537177929, -0.03695423445205627, -0.24224968538235087, 0.3186277311440523, 0.034684925185251604, 0.10855089820207976, -0.08410878858311154, 0.2585746202075324, -0.017282540824503527, 0.07860748685144503, -0.06685400598708095, 0.25177572767566375, 0.22474245090088849, 0.13091343861295407, -0.214592794448227, 0.10977314292760822, 0.07971624087183438] |
1,802.07914 | Synthesizing a Clock Signal with Reactions---Part I: Duty Cycle
Implementation Based on Gears | Timing is of fundamental importance in biology and our life. Borrowing ideas
from mechanism, we map our clock signals onto a gear system, in pursuit of
better depiction of a clock signal implemented with chemical reaction networks
(CRNs). On a chassis of gear theory, more quantitative descriptions are offered
for our method. Inspired by gears, our work to synthesize a tunable clock
signal could be divided into two parts. Part I, this paper, mainly focuses on
the implementation of clock signals with three types of duty cycles, namely
$1/2$, $1/N$ ($N > 2$), and $M/N$. Part II devotes itself in addressing
frequency alteration issues of clock signals. \textcolor{black}{Guaranteed by
existing literature, the experimental chassis can be taken care of by DNA
strand displacement reactions, which lay a solid foundation for the physical
implementation of nearly arbitrary CRNs.
| q-bio.MN physics.chem-ph | timing is of fundamental importance in biology and our life borrowing ideas from mechanism we map our clock signals onto a gear system in pursuit of better depiction of a clock signal implemented with chemical reaction networks crns on a chassis of gear theory more quantitative descriptions are offered for our method inspired by gears our work to synthesize a tunable clock signal could be divided into two parts part i this paper mainly focuses on the implementation of clock signals with three types of duty cycles namely 12 1n n 2 and mn part ii devotes itself in addressing frequency alteration issues of clock signals textcolorblackguaranteed by existing literature the experimental chassis can be taken care of by dna strand displacement reactions which lay a solid foundation for the physical implementation of nearly arbitrary crns | [['timing', 'is', 'of', 'fundamental', 'importance', 'in', 'biology', 'and', 'our', 'life', 'borrowing', 'ideas', 'from', 'mechanism', 'we', 'map', 'our', 'clock', 'signals', 'onto', 'a', 'gear', 'system', 'in', 'pursuit', 'of', 'better', 'depiction', 'of', 'a', 'clock', 'signal', 'implemented', 'with', 'chemical', 'reaction', 'networks', 'crns', 'on', 'a', 'chassis', 'of', 'gear', 'theory', 'more', 'quantitative', 'descriptions', 'are', 'offered', 'for', 'our', 'method', 'inspired', 'by', 'gears', 'our', 'work', 'to', 'synthesize', 'a', 'tunable', 'clock', 'signal', 'could', 'be', 'divided', 'into', 'two', 'parts', 'part', 'i', 'this', 'paper', 'mainly', 'focuses', 'on', 'the', 'implementation', 'of', 'clock', 'signals', 'with', 'three', 'types', 'of', 'duty', 'cycles', 'namely', '12', '1n', 'n', '2', 'and', 'mn', 'part', 'ii', 'devotes', 'itself', 'in', 'addressing', 'frequency', 'alteration', 'issues', 'of', 'clock', 'signals', 'textcolorblackguaranteed', 'by', 'existing', 'literature', 'the', 'experimental', 'chassis', 'can', 'be', 'taken', 'care', 'of', 'by', 'dna', 'strand', 'displacement', 'reactions', 'which', 'lay', 'a', 'solid', 'foundation', 'for', 'the', 'physical', 'implementation', 'of', 'nearly', 'arbitrary', 'crns']] | [-0.1399622181939237, 0.0958461419161823, -0.03787993542630122, -0.023076806480444415, -0.04914657969579653, -0.1793015079262356, 0.09586646442336065, 0.37172265432912993, -0.25431482643233955, -0.28402293095434156, 0.08282466482250365, -0.22784426707636427, -0.1528894392118134, 0.21607289557103757, -0.07444985646202608, 5.759633387680407e-05, 0.0660646680811489, 0.007766967958391264, 0.010117303320267066, -0.17895005008861148, 0.24130436540236352, 0.07862362636908612, 0.2625067825877556, 0.005635507328918686, 0.08942702474693458, -0.01808716521805359, -0.05341185810458329, -0.0335596244506262, -0.0681691397033218, 0.15452301223520878, 0.28850309330349166, 0.1870349808216647, 0.26229477662041234, -0.4842360831383202, -0.23821371590235718, 0.100838069162435, 0.12357019132511966, 0.1391145682522889, -0.06542697327127421, -0.2784794830199745, 0.0531848166482868, -0.16041377889751285, -0.0873900822294807, -0.04203596966065191, 0.023301752122050084, 0.035249247488186315, -0.2293762386118976, 0.006701966885615278, 0.08306360641770341, 0.10486516757281843, -0.0627665403523241, -0.1484449536410264, 0.03596541447633946, 0.16898574824617416, -0.021016436185756767, 0.026278432379519844, 0.1703165103163984, -0.06376443912309629, -0.16568786954438244, 0.4025825283524615, -0.03696957404242346, -0.17860828591855588, 0.16337760056075812, -0.07899317345926883, -0.16092944027580044, 0.10570138553847318, 0.16576094223117388, 0.06883517190106903, -0.17243542827372613, 0.03215578228355972, 0.06392159061851325, 0.2059596128658288, 0.08494513446672095, 0.018350732450683912, 0.21382794250492695, 0.22122599319727332, 0.027440659256858957, 0.108121480728948, -0.044070245412661246, -0.1104898626226242, -0.2604305029989013, -0.11682787303709322, -0.16368376548505492, 0.04689749826815117, -0.05768102484569816, -0.0921764733614745, 0.4330652733919797, 0.139576147151766, 0.15074203077151818, 0.04068559453115557, 0.3608294600310425, 0.028453817837914726, 0.055922812147548906, -0.015949788444709997, 0.2055359477435963, 0.11119746117404214, 0.12409011426519741, -0.20068856917356176, 0.06608670249029443, 0.06933798781009735] |
1,802.07915 | Longer distance continuous variable quantum key distribution protocol
with photon subtraction at receiver | One of the limitation of continuous variable quantum key distribution is
relatively short transmission distance of secure keys. In order to overcome the
limitation, some solutions have been proposed such as reverse reconciliation,
trusted noise concept, and non-Gaussian operation. In this paper, we propose a
protocol using photon subtraction at receiver which utilizes synergy of the
aforementioned properties. By simulations, we show performance of the proposed
protocol outperforms other conventional protocols. We also find the protocol is
more efficient in a practical case. Finally, we provide a guide for
provisioning a system based on the protocol through an analysis for noise from
a channel.
| quant-ph | one of the limitation of continuous variable quantum key distribution is relatively short transmission distance of secure keys in order to overcome the limitation some solutions have been proposed such as reverse reconciliation trusted noise concept and nongaussian operation in this paper we propose a protocol using photon subtraction at receiver which utilizes synergy of the aforementioned properties by simulations we show performance of the proposed protocol outperforms other conventional protocols we also find the protocol is more efficient in a practical case finally we provide a guide for provisioning a system based on the protocol through an analysis for noise from a channel | [['one', 'of', 'the', 'limitation', 'of', 'continuous', 'variable', 'quantum', 'key', 'distribution', 'is', 'relatively', 'short', 'transmission', 'distance', 'of', 'secure', 'keys', 'in', 'order', 'to', 'overcome', 'the', 'limitation', 'some', 'solutions', 'have', 'been', 'proposed', 'such', 'as', 'reverse', 'reconciliation', 'trusted', 'noise', 'concept', 'and', 'nongaussian', 'operation', 'in', 'this', 'paper', 'we', 'propose', 'a', 'protocol', 'using', 'photon', 'subtraction', 'at', 'receiver', 'which', 'utilizes', 'synergy', 'of', 'the', 'aforementioned', 'properties', 'by', 'simulations', 'we', 'show', 'performance', 'of', 'the', 'proposed', 'protocol', 'outperforms', 'other', 'conventional', 'protocols', 'we', 'also', 'find', 'the', 'protocol', 'is', 'more', 'efficient', 'in', 'a', 'practical', 'case', 'finally', 'we', 'provide', 'a', 'guide', 'for', 'provisioning', 'a', 'system', 'based', 'on', 'the', 'protocol', 'through', 'an', 'analysis', 'for', 'noise', 'from', 'a', 'channel']] | [-0.1775172172738866, 0.013851289172984812, -0.1228848699784766, 0.03482267102607203, -0.03253821616258042, -0.21959129258399257, 0.10649747436288565, 0.4169030526223091, -0.2698465161329995, -0.2641623304046404, 0.1028014279537064, -0.22258916208878732, -0.16129352524876595, 0.24496867076063958, -0.11999188839735535, 0.10651401229999745, 0.05059764082901753, -0.003425068915720868, -0.02957877403465458, -0.22984980616736442, 0.324411148026299, 0.07588478833405624, 0.3314520655056605, 0.04345475614088802, 0.11360915698325978, 0.022970475797102645, -0.03346401560366548, -0.03771467817848763, -0.09579574562555465, 0.09561977295267682, 0.24514985703102027, 0.16608592969266914, 0.31713174426784885, -0.3909867264961716, -0.23438024843254915, 0.08042071603995282, 0.1425629447465046, 0.14980542136226388, -0.09229840991009461, -0.25608535064160465, 0.10009369236202194, -0.25491161160439685, -0.0725031803550127, -0.07435435189332705, -0.06582553974854258, 0.04157420692857928, -0.29053852051639784, 0.03909377478115717, 0.03989321036407581, 0.025557801029488195, 0.03463525588337619, -0.05452262998061577, 0.08087879000679375, 0.12872443568350997, -0.029964623195925154, -0.0172647314119296, 0.10469443483116965, -0.10089536216960718, -0.17118731322877395, 0.35563720812877786, -0.05825661842503065, -0.1951100651998646, 0.14826428791331217, -0.04497515417796631, -0.14947207728311276, 0.09397044755034865, 0.16703586185870406, 0.10281731745299812, -0.1750466835275382, 0.017542449915568935, -0.006189074385194824, 0.2130819101338812, 0.04269517380565118, 0.12210069695272698, 0.13457526189785524, 0.20618067509852922, 0.11568015863304026, 0.17328641752660937, -0.1336105895036151, -0.09941432317897964, -0.2847654000461961, -0.17374378151725978, -0.22672622066994125, 0.025105644497671165, -0.06649964887079617, -0.09314590526628308, 0.37923646915274173, 0.24089710696492916, 0.1350175682723952, 0.04850854032534139, 0.41926622354926973, 0.07955370348981188, 0.04881310114601197, 0.10172179548177294, 0.22426566757992708, 0.08412567631995234, 0.10554330538910178, -0.17230426665852205, 0.12238508867225252, 0.008824795072611708] |
1,802.07916 | Guaranteed-cost consensus for multiagent networks with Lipschitz
nonlinear dynamics and switching topologies | Guaranteed-cost consensus for high-order nonlinear multi-agent networks with
switching topologies is investigated. By constructing a time-varying
nonsingular matrix with a specific structure, the whole dynamics of multi-agent
networks is decomposed into the consensus and disagreement parts with nonlinear
terms, which is the key challenge to be dealt with. An explicit expression of
the consensus dynamics, which contains the nonlinear term, is given and its
initial state is determined. Furthermore, by the structure property of the
time-varying nonsingular transformation matrix and the Lipschitz condition, the
impacts of the nonlinear term on the disagreement dynamics are linearized and
the gain matrix of the consensus protocol is determined on the basis of the
Riccati equation. Moreover, an approach to minimize the guaranteed cost is
given in terms of linear matrix inequalities. Finally, the numerical simulation
is shown to demonstrate the effectiveness of theoretical results.
| cs.SY | guaranteedcost consensus for highorder nonlinear multiagent networks with switching topologies is investigated by constructing a timevarying nonsingular matrix with a specific structure the whole dynamics of multiagent networks is decomposed into the consensus and disagreement parts with nonlinear terms which is the key challenge to be dealt with an explicit expression of the consensus dynamics which contains the nonlinear term is given and its initial state is determined furthermore by the structure property of the timevarying nonsingular transformation matrix and the lipschitz condition the impacts of the nonlinear term on the disagreement dynamics are linearized and the gain matrix of the consensus protocol is determined on the basis of the riccati equation moreover an approach to minimize the guaranteed cost is given in terms of linear matrix inequalities finally the numerical simulation is shown to demonstrate the effectiveness of theoretical results | [['guaranteedcost', 'consensus', 'for', 'highorder', 'nonlinear', 'multiagent', 'networks', 'with', 'switching', 'topologies', 'is', 'investigated', 'by', 'constructing', 'a', 'timevarying', 'nonsingular', 'matrix', 'with', 'a', 'specific', 'structure', 'the', 'whole', 'dynamics', 'of', 'multiagent', 'networks', 'is', 'decomposed', 'into', 'the', 'consensus', 'and', 'disagreement', 'parts', 'with', 'nonlinear', 'terms', 'which', 'is', 'the', 'key', 'challenge', 'to', 'be', 'dealt', 'with', 'an', 'explicit', 'expression', 'of', 'the', 'consensus', 'dynamics', 'which', 'contains', 'the', 'nonlinear', 'term', 'is', 'given', 'and', 'its', 'initial', 'state', 'is', 'determined', 'furthermore', 'by', 'the', 'structure', 'property', 'of', 'the', 'timevarying', 'nonsingular', 'transformation', 'matrix', 'and', 'the', 'lipschitz', 'condition', 'the', 'impacts', 'of', 'the', 'nonlinear', 'term', 'on', 'the', 'disagreement', 'dynamics', 'are', 'linearized', 'and', 'the', 'gain', 'matrix', 'of', 'the', 'consensus', 'protocol', 'is', 'determined', 'on', 'the', 'basis', 'of', 'the', 'riccati', 'equation', 'moreover', 'an', 'approach', 'to', 'minimize', 'the', 'guaranteed', 'cost', 'is', 'given', 'in', 'terms', 'of', 'linear', 'matrix', 'inequalities', 'finally', 'the', 'numerical', 'simulation', 'is', 'shown', 'to', 'demonstrate', 'the', 'effectiveness', 'of', 'theoretical', 'results']] | [-0.16771325793246084, 0.04390770911568518, -0.05755195428009627, 0.004255205303668342, -0.06914802206059296, -0.11260636066126221, -0.037913772954559284, 0.3496754331157563, -0.32575476114103136, -0.2481572707018531, 0.12814954858758745, -0.2486216334381689, -0.21068295727464112, 0.14423579230561112, -0.03885669351872453, 0.0986861206309586, 0.08486955624126585, 0.06846219507303644, -0.07805005554316222, -0.2699756165735212, 0.34343015011944905, 0.05715475492972009, 0.2719230883546728, 0.04675374086120609, 0.17676749713190482, -0.024423292283206544, -0.01455963393739352, 0.024622394700851688, -0.09846362113913006, 0.11082302701679315, 0.24343689869270257, 0.13941359381911392, 0.30882839053037003, -0.428130714764409, -0.20184753370861, 0.10039472379077702, 0.10195684561453072, 0.09775705784039096, -0.028227175732889603, -0.3113492830022377, 0.10257640506094652, -0.13916738388782485, -0.12251750788327756, -0.06852189447658123, -0.010031339953528017, 0.0431680689493181, -0.32699149371213976, 0.08086711398650646, 0.05489971621642352, 0.017326734439099985, -0.06984500689778794, -0.0775295925072348, -0.028134931892764274, 0.11484463402757038, 0.01851850616124769, -0.005911432655779182, 0.08348267812096903, -0.11891995814066637, -0.10820849801014105, 0.37666498230281453, -0.0374412352028501, -0.26748748577294, 0.1040874371199426, -0.07064130253006592, -0.07859761253204064, 0.12381117181779804, 0.16810820039678762, 0.10032969720476696, -0.17315419215844377, 0.10218664228500045, -0.03679121725413129, 0.19144842872752788, -0.007655702052466202, 0.001793060729161222, 0.11232501239324293, 0.19603381487573926, 0.10848307396873091, 0.12688282782175572, 0.02198473619898213, -0.19325051808082466, -0.29584095738035565, -0.08578774098518259, -0.20310232704274145, 0.035137755497431394, -0.13907957021832296, -0.16047019617535432, 0.42376704126966336, 0.0852274178042851, 0.17349029645812533, 0.08216555298517413, 0.2810004149358852, 0.1915525899447025, 0.016987596790418558, 0.06887247738699225, 0.24503502033781738, 0.18095161973545, 0.0675010061261396, -0.2817825692745441, 0.13913009410017296, 0.07660246456821337] |
1,802.07917 | Regional Multi-Armed Bandits | We consider a variant of the classic multi-armed bandit problem where the
expected reward of each arm is a function of an unknown parameter. The arms are
divided into different groups, each of which has a common parameter. Therefore,
when the player selects an arm at each time slot, information of other arms in
the same group is also revealed. This regional bandit model naturally bridges
the non-informative bandit setting where the player can only learn the chosen
arm, and the global bandit model where sampling one arms reveals information of
all arms. We propose an efficient algorithm, UCB-g, that solves the regional
bandit problem by combining the Upper Confidence Bound (UCB) and greedy
principles. Both parameter-dependent and parameter-free regret upper bounds are
derived. We also establish a matching lower bound, which proves the
order-optimality of UCB-g. Moreover, we propose SW-UCB-g, which is an extension
of UCB-g for a non-stationary environment where the parameters slowly vary over
time.
| cs.LG stat.ML | we consider a variant of the classic multiarmed bandit problem where the expected reward of each arm is a function of an unknown parameter the arms are divided into different groups each of which has a common parameter therefore when the player selects an arm at each time slot information of other arms in the same group is also revealed this regional bandit model naturally bridges the noninformative bandit setting where the player can only learn the chosen arm and the global bandit model where sampling one arms reveals information of all arms we propose an efficient algorithm ucbg that solves the regional bandit problem by combining the upper confidence bound ucb and greedy principles both parameterdependent and parameterfree regret upper bounds are derived we also establish a matching lower bound which proves the orderoptimality of ucbg moreover we propose swucbg which is an extension of ucbg for a nonstationary environment where the parameters slowly vary over time | [['we', 'consider', 'a', 'variant', 'of', 'the', 'classic', 'multiarmed', 'bandit', 'problem', 'where', 'the', 'expected', 'reward', 'of', 'each', 'arm', 'is', 'a', 'function', 'of', 'an', 'unknown', 'parameter', 'the', 'arms', 'are', 'divided', 'into', 'different', 'groups', 'each', 'of', 'which', 'has', 'a', 'common', 'parameter', 'therefore', 'when', 'the', 'player', 'selects', 'an', 'arm', 'at', 'each', 'time', 'slot', 'information', 'of', 'other', 'arms', 'in', 'the', 'same', 'group', 'is', 'also', 'revealed', 'this', 'regional', 'bandit', 'model', 'naturally', 'bridges', 'the', 'noninformative', 'bandit', 'setting', 'where', 'the', 'player', 'can', 'only', 'learn', 'the', 'chosen', 'arm', 'and', 'the', 'global', 'bandit', 'model', 'where', 'sampling', 'one', 'arms', 'reveals', 'information', 'of', 'all', 'arms', 'we', 'propose', 'an', 'efficient', 'algorithm', 'ucbg', 'that', 'solves', 'the', 'regional', 'bandit', 'problem', 'by', 'combining', 'the', 'upper', 'confidence', 'bound', 'ucb', 'and', 'greedy', 'principles', 'both', 'parameterdependent', 'and', 'parameterfree', 'regret', 'upper', 'bounds', 'are', 'derived', 'we', 'also', 'establish', 'a', 'matching', 'lower', 'bound', 'which', 'proves', 'the', 'orderoptimality', 'of', 'ucbg', 'moreover', 'we', 'propose', 'swucbg', 'which', 'is', 'an', 'extension', 'of', 'ucbg', 'for', 'a', 'nonstationary', 'environment', 'where', 'the', 'parameters', 'slowly', 'vary', 'over', 'time']] | [-0.11878526197586232, 0.04561701576743767, -0.10163621931443596, 0.08695568134904406, -0.1402505108238358, -0.19690427781604705, 0.10828047887285709, 0.3952683153796561, -0.3181101159684977, -0.3114930118558703, 0.08921010137586054, -0.23157602174883815, -0.14697948575114747, 0.132138819911274, -0.10572171428798442, 0.014226136912271427, -0.008217455447016722, 0.07559113460741225, -0.002708577057109422, -0.24551528934715613, 0.285053630928942, 0.04058424684153811, 0.22555665400140223, -0.061431221272440474, 0.14383852612419992, -0.0003482354758993224, 0.0018170306660756942, 0.0005045209352852433, -0.16744217522625676, 0.07546397436641536, 0.2869934718699972, 0.16700000680425459, 0.38933175822992805, -0.39538272338545627, -0.15421017132266454, 0.11102382115616351, 0.1522524543017576, 0.06917343025057203, -0.04457154394880791, -0.31283927790725685, 0.02097992815083237, -0.1311502606831999, -0.02074303227375932, 0.048670806838970654, -0.022823195512981932, -0.011653436510971968, -0.3771761032711169, 0.04087283223337986, 0.048575892531354525, -0.028077464281198727, -0.06713665181779818, -0.14723743974071019, 0.058393266132089554, 0.13104132727136283, 0.05317466139161639, 0.06261072011967041, 0.14762286887397386, -0.1377597271574507, -0.1807893281209336, 0.3318279867155394, -0.05623167800527232, -0.17984104114970204, 0.12401368973219092, -0.11411948454311224, -0.14696421804333662, 0.08483731930120403, 0.19892100993377768, 0.1543053089934668, -0.14769226530832638, 0.0745443780272517, -0.1628914746621944, 0.17726872927675344, 0.04664548132627918, 0.027248501620451167, 0.106576634063771, 0.1869096288377431, 0.19705325302780624, 0.1723952286637234, -0.07769870371624507, -0.15909187273703707, -0.27571845276705376, -0.10211467404870589, -0.14144273915485284, -0.06897147621360317, -0.16616727520571206, -0.12608758395340866, 0.3684996627478795, 0.11983495319979919, 0.22808409437454144, 0.1421623512039222, 0.32382159021083906, 0.12799647153254337, 0.02751584787096548, 0.15997032448352808, 0.19589398444220898, 0.018918737180376795, -0.01743457896803998, -0.19465080757809292, 0.15683431145408824, 0.04926287994725974] |
1,802.07918 | Video Person Re-identification by Temporal Residual Learning | In this paper, we propose a novel feature learning framework for video person
re-identification (re-ID). The proposed framework largely aims to exploit the
adequate temporal information of video sequences and tackle the poor spatial
alignment of moving pedestrians. More specifically, for exploiting the temporal
information, we design a temporal residual learning (TRL) module to
simultaneously extract the generic and specific features of consecutive frames.
The TRL module is equipped with two bi-directional LSTM (BiLSTM), which are
respectively responsible to describe a moving person in different aspects,
providing complementary information for better feature representations. To deal
with the poor spatial alignment in video re-ID datasets, we propose a
spatial-temporal transformer network (ST^2N) module. Transformation parameters
in the ST^2N module are learned by leveraging the high-level semantic
information of the current frame as well as the temporal context knowledge from
other frames. The proposed ST^2N module with less learnable parameters allows
effective person alignments under significant appearance changes. Extensive
experimental results on the large-scale MARS, PRID2011, ILIDS-VID and SDU-VID
datasets demonstrate that the proposed method achieves consistently superior
performance and outperforms most of the very recent state-of-the-art methods.
| cs.CV | in this paper we propose a novel feature learning framework for video person reidentification reid the proposed framework largely aims to exploit the adequate temporal information of video sequences and tackle the poor spatial alignment of moving pedestrians more specifically for exploiting the temporal information we design a temporal residual learning trl module to simultaneously extract the generic and specific features of consecutive frames the trl module is equipped with two bidirectional lstm bilstm which are respectively responsible to describe a moving person in different aspects providing complementary information for better feature representations to deal with the poor spatial alignment in video reid datasets we propose a spatialtemporal transformer network st2n module transformation parameters in the st2n module are learned by leveraging the highlevel semantic information of the current frame as well as the temporal context knowledge from other frames the proposed st2n module with less learnable parameters allows effective person alignments under significant appearance changes extensive experimental results on the largescale mars prid2011 ilidsvid and sduvid datasets demonstrate that the proposed method achieves consistently superior performance and outperforms most of the very recent stateoftheart methods | [['in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'feature', 'learning', 'framework', 'for', 'video', 'person', 'reidentification', 'reid', 'the', 'proposed', 'framework', 'largely', 'aims', 'to', 'exploit', 'the', 'adequate', 'temporal', 'information', 'of', 'video', 'sequences', 'and', 'tackle', 'the', 'poor', 'spatial', 'alignment', 'of', 'moving', 'pedestrians', 'more', 'specifically', 'for', 'exploiting', 'the', 'temporal', 'information', 'we', 'design', 'a', 'temporal', 'residual', 'learning', 'trl', 'module', 'to', 'simultaneously', 'extract', 'the', 'generic', 'and', 'specific', 'features', 'of', 'consecutive', 'frames', 'the', 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'prid2011', 'ilidsvid', 'and', 'sduvid', 'datasets', 'demonstrate', 'that', 'the', 'proposed', 'method', 'achieves', 'consistently', 'superior', 'performance', 'and', 'outperforms', 'most', 'of', 'the', 'very', 'recent', 'stateoftheart', 'methods']] | [-0.07027058881720075, -0.022763981132742923, -0.06886763709640405, 0.060585135286925614, -0.12617880056637365, -0.1915693549212773, -0.03727177006752557, 0.4768287181099122, -0.2852613363849201, -0.33284892927056076, 0.03791441247874015, -0.2468722143409478, -0.187485848629306, 0.1515404868568923, -0.18054841524241744, 0.06682776027308726, 0.15564709907158505, 0.06860189730572086, -0.08245789834449219, -0.24230141542046457, 0.31239544558842236, 0.08857694932486157, 0.3758068145932378, 0.01719710702372312, 0.2070989994835612, -0.005328533710358111, -0.08645716856070165, -0.015779247231202553, -0.046598446098780825, 0.19981797681842156, 0.32703925408926365, 0.18895362065672383, 0.30082287837600186, -0.41150191276258713, 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1,802.07919 | Class groups of imaginary quadratic fields of $3$-rank at least $2$ | We produce an infinite family of imaginary quadratic fields whose ideal class
groups have $3$-rank at least $2$.
| math.NT | we produce an infinite family of imaginary quadratic fields whose ideal class groups have 3rank at least 2 | [['we', 'produce', 'an', 'infinite', 'family', 'of', 'imaginary', 'quadratic', 'fields', 'whose', 'ideal', 'class', 'groups', 'have', '3rank', 'at', 'least', '2']] | [-0.19147151336073875, 0.18109089822408148, -0.08142080646939576, 0.007945091981026862, -0.10394951509725717, -0.16083436935312218, -0.1024870112628883, 0.37266503978106713, -0.2684733805557092, -0.2822680923466881, 0.11684947638099806, -0.3085389068971078, -0.09913711844839984, 0.2168199400831428, 0.0565584534779191, -0.03258695960458782, -0.06606048066169024, 0.1370933758508828, -0.041361501828456916, -0.3671847896443473, 0.3647052379221552, -0.06412372489770253, 0.12862985767424107, -0.08438446460705665, 0.17352519639664227, -0.021667373444264133, 0.02959859950674905, 0.03665719226571835, -0.10950647068158206, 0.08765657735057175, 0.31083896901044583, -0.02671889401972294, 0.3161689158942964, -0.33475158777501846, -0.1469272766262293, 0.29866093676537275, 0.11248386935848328, 0.07180048007931975, -0.0578650479308433, -0.11623875248349375, 0.15251920292697227, -0.20773616070962614, -0.24093782787935603, -0.04745085464997424, 0.05732013256702986, -0.014460051225291358, -0.26465554799263674, -0.01714140342341529, 0.10105716916344439, 0.2246158054201967, -0.07606816995475027, -0.20937481481168005, 0.017041676548413105, 0.050968918949365616, -0.01588768180873659, 0.013639751821756363, 0.016831284932171304, -0.08744220042394267, -0.15555001526243156, 0.3149505308926261, -0.09687453870558077, -0.1756632248353627, 0.20811975871523222, -0.16574584798783892, -0.1667934918983115, 0.2455157082941797, 0.20899488632049826, 0.1575849974114034, -0.05390781743658914, 0.19547992748104864, -0.1120763961225748, 0.05912144037170543, 0.10538437993576129, 0.04010416489715377, 0.21517306509324247, -0.03419524206159016, 0.10156679307369308, 0.18222061780074406, 0.04475492125170098, -0.003820362293885814, -0.35435443330142236, -0.17045778931222028, -0.15901697571906778, 0.12435459114688759, -0.11022165510803461, -0.27916599469932, 0.38656066585746074, 0.010426577801505724, 0.14164859511786038, 0.159990302235302, 0.12696733098063204, 0.13185720538927448, 0.13812969741411507, 0.1175685185007751, 0.11351961833942267, 0.1131993778463867, -0.10337700441272722, -0.14171269838698208, -0.05284041318938964, 0.11746625410806802] |
1,802.0792 | Quantum interference in laser spectroscopy of highly charged lithiumlike
ions | We investigate the quantum interference induced shifts between energetically
close states in highly charged ions, with the energy structure being observed
by laser spectroscopy. In this work, we focus on hyperfine states of
lithiumlike heavy-$Z$ isotopes and quantify how much quantum interference
changes the observed transition frequencies. The process of photon excitation
and subsequent photon decay for the transition $2s\rightarrow2p\rightarrow2s$
is implemented with fully relativistic and full-multipole frameworks, which are
relevant for such relativistic atomic systems. We consider the isotopes
$^{207}$Pb$^{79+}$ and $^{209}$Bi$^{80+}$ due to experimental interest, as well
as other examples of isotopes with lower $Z$, namely $^{141}$Pr$^{56+}$ and
$^{165}$Ho$^{64+}$. We conclude that quantum interference can induce shifts up
to 11% of the linewidth in the measurable resonances of the considered
isotopes, if interference between resonances is neglected. The inclusion of
relativity decreases the cross section by 35%, mainly due to the complete
retardation form of the electric dipole multipole. However, the contribution of
the next higher multipoles (e.g. magnetic quadrupole) to the cross section is
negligible. This makes the contribution of relativity and higher-order
multipoles to the quantum interference induced shifts a minor effect, even for
heavy-$Z$ elements.
| physics.atom-ph | we investigate the quantum interference induced shifts between energetically close states in highly charged ions with the energy structure being observed by laser spectroscopy in this work we focus on hyperfine states of lithiumlike heavyz isotopes and quantify how much quantum interference changes the observed transition frequencies the process of photon excitation and subsequent photon decay for the transition 2srightarrow2prightarrow2s is implemented with fully relativistic and fullmultipole frameworks which are relevant for such relativistic atomic systems we consider the isotopes 207pb79 and 209bi80 due to experimental interest as well as other examples of isotopes with lower z namely 141pr56 and 165ho64 we conclude that quantum interference can induce shifts up to 11 of the linewidth in the measurable resonances of the considered isotopes if interference between resonances is neglected the inclusion of relativity decreases the cross section by 35 mainly due to the complete retardation form of the electric dipole multipole however the contribution of the next higher multipoles eg magnetic quadrupole to the cross section is negligible this makes the contribution of relativity and higherorder multipoles to the quantum interference induced shifts a minor effect even for heavyz elements | [['we', 'investigate', 'the', 'quantum', 'interference', 'induced', 'shifts', 'between', 'energetically', 'close', 'states', 'in', 'highly', 'charged', 'ions', 'with', 'the', 'energy', 'structure', 'being', 'observed', 'by', 'laser', 'spectroscopy', 'in', 'this', 'work', 'we', 'focus', 'on', 'hyperfine', 'states', 'of', 'lithiumlike', 'heavyz', 'isotopes', 'and', 'quantify', 'how', 'much', 'quantum', 'interference', 'changes', 'the', 'observed', 'transition', 'frequencies', 'the', 'process', 'of', 'photon', 'excitation', 'and', 'subsequent', 'photon', 'decay', 'for', 'the', 'transition', '2srightarrow2prightarrow2s', 'is', 'implemented', 'with', 'fully', 'relativistic', 'and', 'fullmultipole', 'frameworks', 'which', 'are', 'relevant', 'for', 'such', 'relativistic', 'atomic', 'systems', 'we', 'consider', 'the', 'isotopes', '207pb79', 'and', '209bi80', 'due', 'to', 'experimental', 'interest', 'as', 'well', 'as', 'other', 'examples', 'of', 'isotopes', 'with', 'lower', 'z', 'namely', '141pr56', 'and', '165ho64', 'we', 'conclude', 'that', 'quantum', 'interference', 'can', 'induce', 'shifts', 'up', 'to', '11', 'of', 'the', 'linewidth', 'in', 'the', 'measurable', 'resonances', 'of', 'the', 'considered', 'isotopes', 'if', 'interference', 'between', 'resonances', 'is', 'neglected', 'the', 'inclusion', 'of', 'relativity', 'decreases', 'the', 'cross', 'section', 'by', '35', 'mainly', 'due', 'to', 'the', 'complete', 'retardation', 'form', 'of', 'the', 'electric', 'dipole', 'multipole', 'however', 'the', 'contribution', 'of', 'the', 'next', 'higher', 'multipoles', 'eg', 'magnetic', 'quadrupole', 'to', 'the', 'cross', 'section', 'is', 'negligible', 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1,802.07921 | Magnetoresistance in organic semiconductors: including pair correlations
in the kinetic equations for hopping transport | We derive the kinetic equations for polaron hopping in organics that
explicitly take into account the double occupation possibility and pair
intersite correlations. The equations include simplified phenomenological spin
dynamics and provide a self-consistent framework for the description of the
bipolaron mechanism of the organic magnetoresistance. At low applied voltages
the equations can be reduced to effective resistor network that generalizes the
Miller-Abrahams network and includes the effect of spin relaxation on the
system resistivity. Our theory discloses the close relationship between the
organic magnetoresistance and the intersite correlations. Moreover, in the
absence of correlations, as in ordered system with zero Hubbard energy, the
magnetoresistance vanishes.
| cond-mat.dis-nn | we derive the kinetic equations for polaron hopping in organics that explicitly take into account the double occupation possibility and pair intersite correlations the equations include simplified phenomenological spin dynamics and provide a selfconsistent framework for the description of the bipolaron mechanism of the organic magnetoresistance at low applied voltages the equations can be reduced to effective resistor network that generalizes the millerabrahams network and includes the effect of spin relaxation on the system resistivity our theory discloses the close relationship between the organic magnetoresistance and the intersite correlations moreover in the absence of correlations as in ordered system with zero hubbard energy the magnetoresistance vanishes | [['we', 'derive', 'the', 'kinetic', 'equations', 'for', 'polaron', 'hopping', 'in', 'organics', 'that', 'explicitly', 'take', 'into', 'account', 'the', 'double', 'occupation', 'possibility', 'and', 'pair', 'intersite', 'correlations', 'the', 'equations', 'include', 'simplified', 'phenomenological', 'spin', 'dynamics', 'and', 'provide', 'a', 'selfconsistent', 'framework', 'for', 'the', 'description', 'of', 'the', 'bipolaron', 'mechanism', 'of', 'the', 'organic', 'magnetoresistance', 'at', 'low', 'applied', 'voltages', 'the', 'equations', 'can', 'be', 'reduced', 'to', 'effective', 'resistor', 'network', 'that', 'generalizes', 'the', 'millerabrahams', 'network', 'and', 'includes', 'the', 'effect', 'of', 'spin', 'relaxation', 'on', 'the', 'system', 'resistivity', 'our', 'theory', 'discloses', 'the', 'close', 'relationship', 'between', 'the', 'organic', 'magnetoresistance', 'and', 'the', 'intersite', 'correlations', 'moreover', 'in', 'the', 'absence', 'of', 'correlations', 'as', 'in', 'ordered', 'system', 'with', 'zero', 'hubbard', 'energy', 'the', 'magnetoresistance', 'vanishes']] | [-0.1837759421971398, 0.15367612311669257, -0.059307351479974554, 0.11118198146182552, -0.02285196097075658, -0.1637900961817787, 0.05457022322126541, 0.2978926881585481, -0.2659618560870547, -0.2745112501752545, -0.053602446871150705, -0.3004439045863999, -0.14640323920087572, 0.15774905745968013, 0.07884589674056701, -0.038974745919541365, -0.0002908831646771364, -0.03480206492970882, -0.08923827431753348, -0.2258501222932641, 0.3016041551567263, 0.018607828203799588, 0.2899486471663827, 0.12677681667484203, 0.10532327574888631, 0.04629299862481619, 0.11027716502178249, 0.03453981335810825, -0.12856954250570918, 0.035150939536078854, 0.23474013841412258, -0.08071912691998735, 0.19498615191792543, -0.4759860553972001, -0.23780189616219052, 0.010733345835381802, 0.13621805362043166, 0.17300443526770357, -0.00818662874879456, -0.2665573155138431, 0.0031887136294313197, -0.21646967068103687, -0.10007235350719881, -0.12124227438965496, 0.007470712351243732, 0.018403276897755998, -0.2774171352447977, 0.16080706582249818, 0.0692108936941708, 0.03753655041207753, -0.12312659626949649, -0.1321947575406224, -0.06924571236815164, 0.09128550495864507, 0.029264441618854005, -0.013717251970379983, 0.12872158871954834, -0.1159491512819, -0.09500560725716224, 0.32853524691759134, -0.08694450281788858, -0.17368088332158602, 0.13262785433897012, -0.16763716645292798, -0.07734536305772809, 0.15587587596602598, 0.14771230978328945, 0.07065182108924074, -0.17870719938205099, 0.11061428347629942, 0.005182051530353866, 0.12852989057219535, -0.03143082280810219, 0.07767729445378173, 0.24726394315707093, 0.21498974159641085, 0.03712927392147974, 0.15287045149444514, -0.10762924863297914, -0.13760497586423848, -0.2705542168773289, -0.12979588923835247, -0.18578420462139514, 0.08117438482729068, -0.09992446459528885, -0.16758475768520445, 0.4161456268333461, 0.1851743339991443, 0.1766533743642833, 0.019651231865556736, 0.24809703696519136, 0.1667629428568103, 0.08504824927691722, 0.02458812330203144, 0.22454361369798206, 0.20371853980183038, 0.1505382830092578, -0.3553404533040692, 0.0864024502049499, 0.07538287781776404] |
1,802.07922 | Synthesizing a Clock Signal with Reactions---Part II: Frequency
Alteration Based on Gears | On a chassis of gear model, we have offered a quantitative description for
our method to synthesize a chemical clock signal with various duty cycles in
Part I. As Part II of the study, this paper devotes itself in proposing a
design methodology to handle frequency alteration issues for the chemical
clock, including both frequency division and frequency multiplication. Several
interesting examples are provided for a better explanation of our contribution.
All the simulation results verify and validate the correctness and efficiency
of our proposal.
| q-bio.MN physics.chem-ph | on a chassis of gear model we have offered a quantitative description for our method to synthesize a chemical clock signal with various duty cycles in part i as part ii of the study this paper devotes itself in proposing a design methodology to handle frequency alteration issues for the chemical clock including both frequency division and frequency multiplication several interesting examples are provided for a better explanation of our contribution all the simulation results verify and validate the correctness and efficiency of our proposal | [['on', 'a', 'chassis', 'of', 'gear', 'model', 'we', 'have', 'offered', 'a', 'quantitative', 'description', 'for', 'our', 'method', 'to', 'synthesize', 'a', 'chemical', 'clock', 'signal', 'with', 'various', 'duty', 'cycles', 'in', 'part', 'i', 'as', 'part', 'ii', 'of', 'the', 'study', 'this', 'paper', 'devotes', 'itself', 'in', 'proposing', 'a', 'design', 'methodology', 'to', 'handle', 'frequency', 'alteration', 'issues', 'for', 'the', 'chemical', 'clock', 'including', 'both', 'frequency', 'division', 'and', 'frequency', 'multiplication', 'several', 'interesting', 'examples', 'are', 'provided', 'for', 'a', 'better', 'explanation', 'of', 'our', 'contribution', 'all', 'the', 'simulation', 'results', 'verify', 'and', 'validate', 'the', 'correctness', 'and', 'efficiency', 'of', 'our', 'proposal']] | [-0.10521573071532389, -0.0035263517542796978, -0.06130997572532471, 0.007783126654377317, -0.0703485714545583, -0.11941796014742816, 0.10295883073498878, 0.3907984112992006, -0.22027460639638935, -0.321904508112108, 0.11410906654782593, -0.20176289004585296, -0.17538744221879718, 0.26244264595374905, -0.07431546907652826, 0.017949841259156957, 0.06487364362897899, 0.0006811226170290919, 0.00664511575254009, -0.19986793129458366, 0.2387973844046321, 0.10483470867004464, 0.2685991408084245, 0.058871710284010455, 0.07543958440313445, -0.05248348758391598, -0.07524318026707452, -0.006656678963233443, -0.09023407716304063, 0.12307982154409675, 0.2471399648936794, 0.16769262691959738, 0.271317606019404, -0.40064074638135294, -0.22022300510502912, 0.08069239674026475, 0.09300143746316762, 0.12592139912988334, -0.11765842756174286, -0.24471402762129027, 0.08908498462508707, -0.2141523496412179, -0.14115995088701738, -0.11207619645797154, 0.007459453624837539, 0.04367222460123765, -0.2835918811694308, 0.0004812266568050665, 0.08417606590425267, 0.08826291840523481, -0.0816798282568069, -0.1180975591079058, 0.0539581726264099, 0.1398047057309133, -0.0030748227898798443, -0.01900671690236777, 0.10711341910612057, -0.07594035054721376, -0.1629248996539151, 0.3861863090492347, -0.03955195476027096, -0.18528301911976408, 0.2113199425779064, -0.09628683931796866, -0.15065270371406395, 0.08246288234367967, 0.1723702422945815, 0.08011513785185183, -0.13209746687755208, 0.023355653710142872, 0.01912375961375587, 0.18262149980839562, 0.0705169370808803, 0.034185205358731124, 0.18005404914455378, 0.23448679233517716, 0.017397820766029113, 0.1427554220536395, -0.06054898239672184, -0.09707873264765915, -0.3169323503094561, -0.16406617433051854, -0.1427151719779324, -0.002824042918270125, -0.07524778844860575, -0.12640496930655312, 0.4931286913507125, 0.21791953086195623, 0.19686201769475112, 0.08035793174606036, 0.36760725216830475, 0.05929108943228665, 0.03772110661272617, 0.009015136047759477, 0.2012777536559631, 0.10448585074833211, 0.13076324832680472, -0.24400315948707216, 0.039648105132886594, 0.035108522895504445] |
1,802.07923 | Dynamic Output Feedback Guaranteed-Cost Synchronization for Multiagent
Networks with Given Cost Budgets | The current paper addresses the distributed guaranteed-cost synchronization
problems for general high-order linear multiagent networks. Existing works on
the guaranteed-cost synchronization usually require all state information of
neighboring agents and cannot give the cost budget previously. For both
leaderless and leader-following interaction topologies, the current paper
firstly proposes a dynamic output feedback synchronization protocol with
guaranteed-cost constraints, which can realize the tradeoff design between the
energy consumption and the synchronization regulation performance with the
given cost budget. Then, according to different structure features of
interaction topologies, leaderless and leader-following guaranteed-cost
synchronization analysis and design criteria are presented, respectively, and
an algorithm is proposed to deal with the impacts of nonlinear terms by using
both synchronization analysis and design criteria. Especially, an explicit
expression of the synchronization function is shown for leaderless cases, which
is independent of protocol states and the given cost budget. Finally, numerical
examples are presented to demonstrate theoretical results.
| cs.SY cs.DC | the current paper addresses the distributed guaranteedcost synchronization problems for general highorder linear multiagent networks existing works on the guaranteedcost synchronization usually require all state information of neighboring agents and cannot give the cost budget previously for both leaderless and leaderfollowing interaction topologies the current paper firstly proposes a dynamic output feedback synchronization protocol with guaranteedcost constraints which can realize the tradeoff design between the energy consumption and the synchronization regulation performance with the given cost budget then according to different structure features of interaction topologies leaderless and leaderfollowing guaranteedcost synchronization analysis and design criteria are presented respectively and an algorithm is proposed to deal with the impacts of nonlinear terms by using both synchronization analysis and design criteria especially an explicit expression of the synchronization function is shown for leaderless cases which is independent of protocol states and the given cost budget finally numerical examples are presented to demonstrate theoretical results | [['the', 'current', 'paper', 'addresses', 'the', 'distributed', 'guaranteedcost', 'synchronization', 'problems', 'for', 'general', 'highorder', 'linear', 'multiagent', 'networks', 'existing', 'works', 'on', 'the', 'guaranteedcost', 'synchronization', 'usually', 'require', 'all', 'state', 'information', 'of', 'neighboring', 'agents', 'and', 'can', 'not', 'give', 'the', 'cost', 'budget', 'previously', 'for', 'both', 'leaderless', 'and', 'leaderfollowing', 'interaction', 'topologies', 'the', 'current', 'paper', 'firstly', 'proposes', 'a', 'dynamic', 'output', 'feedback', 'synchronization', 'protocol', 'with', 'guaranteedcost', 'constraints', 'which', 'can', 'realize', 'the', 'tradeoff', 'design', 'between', 'the', 'energy', 'consumption', 'and', 'the', 'synchronization', 'regulation', 'performance', 'with', 'the', 'given', 'cost', 'budget', 'then', 'according', 'to', 'different', 'structure', 'features', 'of', 'interaction', 'topologies', 'leaderless', 'and', 'leaderfollowing', 'guaranteedcost', 'synchronization', 'analysis', 'and', 'design', 'criteria', 'are', 'presented', 'respectively', 'and', 'an', 'algorithm', 'is', 'proposed', 'to', 'deal', 'with', 'the', 'impacts', 'of', 'nonlinear', 'terms', 'by', 'using', 'both', 'synchronization', 'analysis', 'and', 'design', 'criteria', 'especially', 'an', 'explicit', 'expression', 'of', 'the', 'synchronization', 'function', 'is', 'shown', 'for', 'leaderless', 'cases', 'which', 'is', 'independent', 'of', 'protocol', 'states', 'and', 'the', 'given', 'cost', 'budget', 'finally', 'numerical', 'examples', 'are', 'presented', 'to', 'demonstrate', 'theoretical', 'results']] | [-0.20518685975857687, 0.03434448059685559, -0.01040747633593437, 0.0038734321776180973, -0.07897692323917997, -0.18645885136294987, 0.06078794786822221, 0.392975513792895, -0.2650427192090432, -0.3419950411843708, 0.11176042308349138, -0.2195983187240713, -0.20490899448909985, 0.1773596806999515, -0.097318667481696, 0.08779846712204269, 0.08827894021455637, 0.0365882050017735, -0.019145619939461813, -0.25584244933679356, 0.2856235441757865, 0.10090269732100317, 0.32792908566839557, 0.05155721460651679, 0.10756178215462593, -0.021952168612734847, -0.007496252333367962, 0.018139533367990176, -0.11369309186618896, 0.10328334359432345, 0.29413818332345343, 0.17604235682846314, 0.3031942241907339, -0.43015056090076376, -0.1967301815535167, 0.11686005876962631, 0.12868919323070668, 0.09831931725071341, -0.04904232776245967, -0.27820198060153356, 0.08021309694238737, -0.18033327853757572, -0.013387689181471098, -0.09049224066304566, -0.03252867087600083, 0.09582944272453009, -0.32987705887990754, 0.03538927997103314, 0.04036862602353924, 0.026889939716365798, -0.08171939038141977, -0.07783587215836556, 0.005756084618517776, 0.14366865430173337, -0.012496703290654457, -0.04458009276396041, 0.09157237094550034, -0.10636662359781612, -0.17607871776148434, 0.3637140409813987, 0.042441067084581806, -0.24220488504719695, 0.18776479592315512, -0.012699390691552872, -0.11995373932748205, 0.07060453694144848, 0.2138512475489109, 0.07378015790159016, -0.18272716829019106, 0.02490220967607171, 0.03121358211292258, 0.2059914843465378, 0.014375934555359623, 0.06946069260129364, 0.10918734405414975, 0.20885045113029824, 0.13697818253003669, 0.14036364609442553, -0.017905063144794172, -0.17229643660929247, -0.2837710210511741, -0.07406845260898468, -0.14663385270616905, -0.02501424911477241, -0.10168362053315112, -0.10375658892687818, 0.40756129581797745, 0.13996693004056618, 0.157501061306962, 0.12806055930997032, 0.3687082651539955, 0.1208540825599354, -0.003483663795919544, 0.12007621283113372, 0.2307806680113263, 0.09019385214006297, 0.10350265614749267, -0.25629770041449496, 0.11071114752478167, 0.029044074925527075] |
1,802.07924 | Simulations on a potential hybrid and compact attosecond X-ray source
based on RF and THz technologies | We investigate through beam dynamics simulations the potential of a hybrid
layout mixing RF and THz technologies to be a compact X-ray source based on
Inverse Compton Scattering (ICS), delivering few femtoseconds to
sub-femtosecond pulses. The layout consists of an S-band gun as electron source
and a dielectric-loaded circular waveguide driven by a multicycle THz pulse to
accelerate and longitudinally compress the bunch, which will then be used to
produce X-ray pulses via ICS with an infrared laser pulse. The beam dynamics
simulations we performed, from the photocathode up to the ICS point, allows to
have an insight in several important physical effects for the proposed scheme
and also in the influence on the achievable bunch properties of various
parameters of the accelerating and transverse focusing devices. The study
presented in this paper leads to a preliminary layout and set of parameters
able to deliver at the ICS point, according to our simulations, ultrashort
bunches (around 1 fs rms), at 15 MeV, with at least 1 pC charge and
transversely focused down to around 10 um rms or below while keeping a compact
beamline (less than 1.5 m), which has not yet been achieved using only
conventional RF technologies. Future studies will be devoted to the
investigation of several potential ways to improve the achieved bunch
properties, to overcome the limitations identified in the current study and to
the definition of the technical requirements. This will lead to an updated
layout and set of parameters.
| physics.acc-ph | we investigate through beam dynamics simulations the potential of a hybrid layout mixing rf and thz technologies to be a compact xray source based on inverse compton scattering ics delivering few femtoseconds to subfemtosecond pulses the layout consists of an sband gun as electron source and a dielectricloaded circular waveguide driven by a multicycle thz pulse to accelerate and longitudinally compress the bunch which will then be used to produce xray pulses via ics with an infrared laser pulse the beam dynamics simulations we performed from the photocathode up to the ics point allows to have an insight in several important physical effects for the proposed scheme and also in the influence on the achievable bunch properties of various parameters of the accelerating and transverse focusing devices the study presented in this paper leads to a preliminary layout and set of parameters able to deliver at the ics point according to our simulations ultrashort bunches around 1 fs rms at 15 mev with at least 1 pc charge and transversely focused down to around 10 um rms or below while keeping a compact beamline less than 15 m which has not yet been achieved using only conventional rf technologies future studies will be devoted to the investigation of several potential ways to improve the achieved bunch properties to overcome the limitations identified in the current study and to the definition of the technical requirements this will lead to an updated layout and set of parameters | [['we', 'investigate', 'through', 'beam', 'dynamics', 'simulations', 'the', 'potential', 'of', 'a', 'hybrid', 'layout', 'mixing', 'rf', 'and', 'thz', 'technologies', 'to', 'be', 'a', 'compact', 'xray', 'source', 'based', 'on', 'inverse', 'compton', 'scattering', 'ics', 'delivering', 'few', 'femtoseconds', 'to', 'subfemtosecond', 'pulses', 'the', 'layout', 'consists', 'of', 'an', 'sband', 'gun', 'as', 'electron', 'source', 'and', 'a', 'dielectricloaded', 'circular', 'waveguide', 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1,802.07925 | Study of thermal stability for different dark energy models | In the present work, we have made an attempt to investigate the dark energy
possibility from the thermodynamical point of view. For this purpose, we have
studied thermodynamic stability of three popular dark energy models in the
framework of an expanding, homogeneous, isotropic and spatially flat FRW
Universe filled with dark energy and cold dark matter. The models considered in
this work are Chevallier-Polarski-Linder (CPL) model, Generalized Chaplygin Gas
(GCG) model and Modified Chaplygin Gas (MCG) model. By considering the cosmic
components (dark energy and cold dark matter) as perfect fluid, we have
examined the constraints imposed on the total equation of state parameter
($w_{T}$) of the dark fluid by thermodynamics and found that the phantom nature
($w_{T}<-1$) is not thermodynamically stable. Our investigation indicates that
the dark fluid models (CPL, GCG and MCG) are thermodynamically stable under
some restrictions of the parameters of each model.
| gr-qc astro-ph.CO | in the present work we have made an attempt to investigate the dark energy possibility from the thermodynamical point of view for this purpose we have studied thermodynamic stability of three popular dark energy models in the framework of an expanding homogeneous isotropic and spatially flat frw universe filled with dark energy and cold dark matter the models considered in this work are chevallierpolarskilinder cpl model generalized chaplygin gas gcg model and modified chaplygin gas mcg model by considering the cosmic components dark energy and cold dark matter as perfect fluid we have examined the constraints imposed on the total equation of state parameter w_t of the dark fluid by thermodynamics and found that the phantom nature w_t1 is not thermodynamically stable our investigation indicates that the dark fluid models cpl gcg and mcg are thermodynamically stable under some restrictions of the parameters of each model | [['in', 'the', 'present', 'work', 'we', 'have', 'made', 'an', 'attempt', 'to', 'investigate', 'the', 'dark', 'energy', 'possibility', 'from', 'the', 'thermodynamical', 'point', 'of', 'view', 'for', 'this', 'purpose', 'we', 'have', 'studied', 'thermodynamic', 'stability', 'of', 'three', 'popular', 'dark', 'energy', 'models', 'in', 'the', 'framework', 'of', 'an', 'expanding', 'homogeneous', 'isotropic', 'and', 'spatially', 'flat', 'frw', 'universe', 'filled', 'with', 'dark', 'energy', 'and', 'cold', 'dark', 'matter', 'the', 'models', 'considered', 'in', 'this', 'work', 'are', 'chevallierpolarskilinder', 'cpl', 'model', 'generalized', 'chaplygin', 'gas', 'gcg', 'model', 'and', 'modified', 'chaplygin', 'gas', 'mcg', 'model', 'by', 'considering', 'the', 'cosmic', 'components', 'dark', 'energy', 'and', 'cold', 'dark', 'matter', 'as', 'perfect', 'fluid', 'we', 'have', 'examined', 'the', 'constraints', 'imposed', 'on', 'the', 'total', 'equation', 'of', 'state', 'parameter', 'w_t', 'of', 'the', 'dark', 'fluid', 'by', 'thermodynamics', 'and', 'found', 'that', 'the', 'phantom', 'nature', 'w_t1', 'is', 'not', 'thermodynamically', 'stable', 'our', 'investigation', 'indicates', 'that', 'the', 'dark', 'fluid', 'models', 'cpl', 'gcg', 'and', 'mcg', 'are', 'thermodynamically', 'stable', 'under', 'some', 'restrictions', 'of', 'the', 'parameters', 'of', 'each', 'model']] | [-0.10719550173324596, 0.12006742071718367, -0.13621422696909677, 0.08902603068487872, -0.06855227201794313, -0.1701166980536272, -0.05178263216528225, 0.31447882402994454, -0.2155576987153761, -0.33698013995388165, -0.0037617470890886394, -0.23503517696940124, -0.003615490047656612, 0.10044038052071039, 0.035047514938226304, 0.044125014332391015, -0.04733161487272137, -0.008340240140407258, 0.005782423033825543, -0.2929902839321286, 0.36258160642966986, 0.1212723141971478, 0.2609704789093198, 0.005282015873801779, 0.1236690194314116, -0.08896343935957204, -0.027364555428965553, 0.017613213911193283, -0.28390237691300707, 0.025817856656655362, 0.16996376233971067, 0.09178242504226733, 0.1912296476187057, -0.43362971897913166, -0.3410060506007851, 0.1959270547871312, 0.11513008616229979, 0.08128560439506881, -0.08421051076514494, -0.2800732496232815, -0.008745376310910876, -0.2457344347917258, -0.1533165074556377, -0.05655091687277827, -0.05009947895799598, 0.017869128150329608, -0.1528376568370333, 0.17650794140254594, 0.012553433608582677, -0.08954846296357373, -0.20853100164334148, -0.11441817030642334, -0.054037805332496046, -0.0670769115916313, 0.06731024908287808, -0.052839827005773755, 0.16435752628524214, -0.2053949433563864, -0.011579440594076703, 0.4550684022602357, -0.14387035749418892, -0.20340204196471773, 0.16578284388069983, -0.04883921969752146, -0.15311261427218784, 0.07248997985391738, 0.07628049611668931, 0.05005205091573808, -0.1730345875815782, 0.1641740691664705, -0.0557236152362997, 0.17849903280247953, 0.05831511004202782, -0.0321278413502525, 0.3334742766001249, 0.16986208076250728, -0.0073537878307521065, 0.12328457731549462, -0.05528917630707003, -0.15799421623782955, -0.32668520201456874, -0.1744638692511067, -0.12228223562483, -0.004374191904875485, -0.11506509834087983, -0.12898416664413087, 0.34651225636879057, 0.0998169824111033, 0.16098356011566028, -0.01357112394658568, 0.33087348824443474, 0.053293985870430785, -0.06627179534263807, 0.11957170089311285, 0.2990881281130236, 0.1321740527860565, 0.11969510430138405, -0.20966191652983632, -0.02371376266061928, 0.004223034844721017] |
1,802.07926 | Exploiting Inter-User Interference for Secure Massive Non-Orthogonal
Multiple Access | This paper considers the security issue of the fifth-generation (5G) wireless
networks with massive connections, where multiple eavesdroppers aim to
intercept the confidential messages through active eavesdropping. To realize
secure massive access, non-orthogonal channel estimation (NOCE) and
non-orthogonal multiple access (NOMA) techniques are combined to enhance the
signal quality at legitimate users, while the inter-user interference is
harnessed to deliberately confuse the eavesdroppers even without exploiting
artificial noise (AN). We first analyze the secrecy performance of the
considered secure massive access system and derive a closed-form expression for
the ergodic secrecy rate. In particular, we reveal the impact of some key
system parameters on the ergodic secrecy rate via asymptotic analysis with
respect to a large number of antennas and a high transmit power at the base
station (BS). Then, to fully exploit the inter-user interference for security
enhancement, we propose to optimize the transmit powers in the stages of
channel estimation and multiple access. Finally, extensive simulation results
validate the effectiveness of the proposed secure massive access scheme.
| cs.IT math.IT | this paper considers the security issue of the fifthgeneration 5g wireless networks with massive connections where multiple eavesdroppers aim to intercept the confidential messages through active eavesdropping to realize secure massive access nonorthogonal channel estimation noce and nonorthogonal multiple access noma techniques are combined to enhance the signal quality at legitimate users while the interuser interference is harnessed to deliberately confuse the eavesdroppers even without exploiting artificial noise an we first analyze the secrecy performance of the considered secure massive access system and derive a closedform expression for the ergodic secrecy rate in particular we reveal the impact of some key system parameters on the ergodic secrecy rate via asymptotic analysis with respect to a large number of antennas and a high transmit power at the base station bs then to fully exploit the interuser interference for security enhancement we propose to optimize the transmit powers in the stages of channel estimation and multiple access finally extensive simulation results validate the effectiveness of the proposed secure massive access scheme | [['this', 'paper', 'considers', 'the', 'security', 'issue', 'of', 'the', 'fifthgeneration', '5g', 'wireless', 'networks', 'with', 'massive', 'connections', 'where', 'multiple', 'eavesdroppers', 'aim', 'to', 'intercept', 'the', 'confidential', 'messages', 'through', 'active', 'eavesdropping', 'to', 'realize', 'secure', 'massive', 'access', 'nonorthogonal', 'channel', 'estimation', 'noce', 'and', 'nonorthogonal', 'multiple', 'access', 'noma', 'techniques', 'are', 'combined', 'to', 'enhance', 'the', 'signal', 'quality', 'at', 'legitimate', 'users', 'while', 'the', 'interuser', 'interference', 'is', 'harnessed', 'to', 'deliberately', 'confuse', 'the', 'eavesdroppers', 'even', 'without', 'exploiting', 'artificial', 'noise', 'an', 'we', 'first', 'analyze', 'the', 'secrecy', 'performance', 'of', 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1,802.07927 | The Hidden Vulnerability of Distributed Learning in Byzantium | While machine learning is going through an era of celebrated success,
concerns have been raised about the vulnerability of its backbone: stochastic
gradient descent (SGD). Recent approaches have been proposed to ensure the
robustness of distributed SGD against adversarial (Byzantine) workers sending
poisoned gradients during the training phase. Some of these approaches have
been proven Byzantine-resilient: they ensure the convergence of SGD despite the
presence of a minority of adversarial workers.
We show in this paper that convergence is not enough. In high dimension $d
\gg 1$, an adver\-sary can build on the loss function's non-convexity to make
SGD converge to ineffective models. More precisely, we bring to light that
existing Byzantine-resilient schemes leave a margin of poisoning of
$\Omega\left(f(d)\right)$, where $f(d)$ increases at least like $\sqrt{d~}$.
Based on this leeway, we build a simple attack, and experimentally show its
strong to utmost effectivity on CIFAR-10 and MNIST.
We introduce Bulyan, and prove it significantly reduces the attackers leeway
to a narrow $O( \frac{1}{\sqrt{d~}})$ bound. We empirically show that Bulyan
does not suffer the fragility of existing aggregation rules and, at a
reasonable cost in terms of required batch size, achieves convergence as if
only non-Byzantine gradients had been used to update the model.
| stat.ML cs.CR cs.DC cs.LG | while machine learning is going through an era of celebrated success concerns have been raised about the vulnerability of its backbone stochastic gradient descent sgd recent approaches have been proposed to ensure the robustness of distributed sgd against adversarial byzantine workers sending poisoned gradients during the training phase some of these approaches have been proven byzantineresilient they ensure the convergence of sgd despite the presence of a minority of adversarial workers we show in this paper that convergence is not enough in high dimension d gg 1 an adversary can build on the loss functions nonconvexity to make sgd converge to ineffective models more precisely we bring to light that existing byzantineresilient schemes leave a margin of poisoning of omegaleftfdright where fd increases at least like sqrtd based on this leeway we build a simple attack and experimentally show its strong to utmost effectivity on cifar10 and mnist we introduce bulyan and prove it significantly reduces the attackers leeway to a narrow o frac1sqrtd bound we empirically show that bulyan does not suffer the fragility of existing aggregation rules and at a reasonable cost in terms of required batch size achieves convergence as if only nonbyzantine gradients had been used to update the model | [['while', 'machine', 'learning', 'is', 'going', 'through', 'an', 'era', 'of', 'celebrated', 'success', 'concerns', 'have', 'been', 'raised', 'about', 'the', 'vulnerability', 'of', 'its', 'backbone', 'stochastic', 'gradient', 'descent', 'sgd', 'recent', 'approaches', 'have', 'been', 'proposed', 'to', 'ensure', 'the', 'robustness', 'of', 'distributed', 'sgd', 'against', 'adversarial', 'byzantine', 'workers', 'sending', 'poisoned', 'gradients', 'during', 'the', 'training', 'phase', 'some', 'of', 'these', 'approaches', 'have', 'been', 'proven', 'byzantineresilient', 'they', 'ensure', 'the', 'convergence', 'of', 'sgd', 'despite', 'the', 'presence', 'of', 'a', 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1,802.07928 | Asynchronous Byzantine Machine Learning (the case of SGD) | Asynchronous distributed machine learning solutions have proven very
effective so far, but always assuming perfectly functioning workers. In
practice, some of the workers can however exhibit Byzantine behavior, caused by
hardware failures, software bugs, corrupt data, or even malicious attacks. We
introduce \emph{Kardam}, the first distributed asynchronous stochastic gradient
descent (SGD) algorithm that copes with Byzantine workers. Kardam consists of
two complementary components: a filtering and a dampening component. The first
is scalar-based and ensures resilience against $\frac{1}{3}$ Byzantine workers.
Essentially, this filter leverages the Lipschitzness of cost functions and acts
as a self-stabilizer against Byzantine workers that would attempt to corrupt
the progress of SGD. The dampening component bounds the convergence rate by
adjusting to stale information through a generic gradient weighting scheme. We
prove that Kardam guarantees almost sure convergence in the presence of
asynchrony and Byzantine behavior, and we derive its convergence rate. We
evaluate Kardam on the CIFAR-100 and EMNIST datasets and measure its overhead
with respect to non Byzantine-resilient solutions. We empirically show that
Kardam does not introduce additional noise to the learning procedure but does
induce a slowdown (the cost of Byzantine resilience) that we both theoretically
and empirically show to be less than $f/n$, where $f$ is the number of
Byzantine failures tolerated and $n$ the total number of workers.
Interestingly, we also empirically observe that the dampening component is
interesting in its own right for it enables to build an SGD algorithm that
outperforms alternative staleness-aware asynchronous competitors in
environments with honest workers.
| stat.ML cs.CR cs.DC cs.LG | asynchronous distributed machine learning solutions have proven very effective so far but always assuming perfectly functioning workers in practice some of the workers can however exhibit byzantine behavior caused by hardware failures software bugs corrupt data or even malicious attacks we introduce emphkardam the first distributed asynchronous stochastic gradient descent sgd algorithm that copes with byzantine workers kardam consists of two complementary components a filtering and a dampening component the first is scalarbased and ensures resilience against frac13 byzantine workers essentially this filter leverages the lipschitzness of cost functions and acts as a selfstabilizer against byzantine workers that would attempt to corrupt the progress of sgd the dampening component bounds the convergence rate by adjusting to stale information through a generic gradient weighting scheme we prove that kardam guarantees almost sure convergence in the presence of asynchrony and byzantine behavior and we derive its convergence rate we evaluate kardam on the cifar100 and emnist datasets and measure its overhead with respect to non byzantineresilient solutions we empirically show that kardam does not introduce additional noise to the learning procedure but does induce a slowdown the cost of byzantine resilience that we both theoretically and empirically show to be less than fn where f is the number of byzantine failures tolerated and n the total number of workers interestingly we also empirically observe that the dampening component is interesting in its own right for it enables to build an sgd algorithm that outperforms alternative stalenessaware asynchronous competitors in environments with honest workers | [['asynchronous', 'distributed', 'machine', 'learning', 'solutions', 'have', 'proven', 'very', 'effective', 'so', 'far', 'but', 'always', 'assuming', 'perfectly', 'functioning', 'workers', 'in', 'practice', 'some', 'of', 'the', 'workers', 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1,802.07929 | Graph-Based Blind Image Deblurring From a Single Photograph | Blind image deblurring, i.e., deblurring without knowledge of the blur
kernel, is a highly ill-posed problem. The problem can be solved in two parts:
i) estimate a blur kernel from the blurry image, and ii) given estimated blur
kernel, de-convolve blurry input to restore the target image. In this paper, we
propose a graph-based blind image deblurring algorithm by interpreting an image
patch as a signal on a weighted graph. Specifically, we first argue that a
skeleton image---a proxy that retains the strong gradients of the target but
smooths out the details---can be used to accurately estimate the blur kernel
and has a unique bi-modal edge weight distribution. Then, we design a
reweighted graph total variation (RGTV) prior that can efficiently promote a
bi-modal edge weight distribution given a blurry patch. Further, to analyze
RGTV in the graph frequency domain, we introduce a new weight function to
represent RGTV as a graph $l_1$-Laplacian regularizer. This leads to a graph
spectral filtering interpretation of the prior with desirable properties,
including robustness to noise and blur, strong piecewise smooth (PWS) filtering
and sharpness promotion. Minimizing a blind image deblurring objective with
RGTV results in a non-convex non-differentiable optimization problem. We
leverage the new graph spectral interpretation for RGTV to design an efficient
algorithm that solves for the skeleton image and the blur kernel alternately.
Specifically for Gaussian blur, we propose a further speedup strategy for blind
Gaussian deblurring using accelerated graph spectral filtering. Finally, with
the computed blur kernel, recent non-blind image deblurring algorithms can be
applied to restore the target image. Experimental results demonstrate that our
algorithm successfully restores latent sharp images and outperforms
state-of-the-art methods quantitatively and qualitatively.
| cs.CV | blind image deblurring ie deblurring without knowledge of the blur kernel is a highly illposed problem the problem can be solved in two parts i estimate a blur kernel from the blurry image and ii given estimated blur kernel deconvolve blurry input to restore the target image in this paper we propose a graphbased blind image deblurring algorithm by interpreting an image patch as a signal on a weighted graph specifically we first argue that a skeleton imagea proxy that retains the strong gradients of the target but smooths out the detailscan be used to accurately estimate the blur kernel and has a unique bimodal edge weight distribution then we design a reweighted graph total variation rgtv prior that can efficiently promote a bimodal edge weight distribution given a blurry patch further to analyze rgtv in the graph frequency domain we introduce a new weight function to represent rgtv as a graph l_1laplacian regularizer this leads to a graph spectral filtering interpretation of the prior with desirable properties including robustness to noise and blur strong piecewise smooth pws filtering and sharpness promotion minimizing a blind image deblurring objective with rgtv results in a nonconvex nondifferentiable optimization problem we leverage the new graph spectral interpretation for rgtv to design an efficient algorithm that solves for the skeleton image and the blur kernel alternately specifically for gaussian blur we propose a further speedup strategy for blind gaussian deblurring using accelerated graph spectral filtering finally with the computed blur kernel recent nonblind image deblurring algorithms can be applied to restore the target image experimental results demonstrate that our algorithm successfully restores latent sharp images and outperforms stateoftheart methods quantitatively and qualitatively | [['blind', 'image', 'deblurring', 'ie', 'deblurring', 'without', 'knowledge', 'of', 'the', 'blur', 'kernel', 'is', 'a', 'highly', 'illposed', 'problem', 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1,802.0793 | The Isophotal Structure of Star-forming Galaxies at $0.5< z <1.8$ in
CANDELS: Implications for the Evolution of Galaxy Structure | We have measured the radial profiles of isophotal ellipticity ($\varepsilon$)
and disky/boxy parameter A$_4$ out to radii of about three times the semi-major
axes for $\sim4,600$ star-forming galaxies (SFGs) at intermediate redshifts
$0.5<z<1.8$ in the CANDELS/GOODS-S and UDS fields. Based on the average size
versus stellar-mass relation in each redshift bin, we divide our galaxies into
Small SFGs (SSFGs), i.e., smaller than average for its mass, and Large SFGs
(LSFGs), i.e., larger than average. We find that, at low masses ($M_{\ast} <
10^{10}M_{\odot}$), the SSFGs generally have nearly flat $\varepsilon$ and
A$_4$ profiles for both edge-on and face-on views, especially at redshifts
$z>1$. Moreover, the median A$_4$ values at all radii are almost zero. In
contrast, the highly-inclined, low-mass LSFGs in the same mass-redshift bins
generally have monotonically increasing $\varepsilon$ with radius and are
dominated by disky values at intermediate radii. These findings at intermediate
redshifts imply that low-mass SSFGs are not disk-like, while low-mass LSFGs
appear to harbour disk-like components flattened by significant rotation. At
high masses ($M_{\ast} > 10^{10}M_{\odot}$), highly-inclined SSFGs and LSFGs
both exhibit a general, distinct trend for both $\varepsilon$ and A$_4$
profiles: increasing values with radius at lower radii, reaching maxima at
intermediate radii, and then decreasing values at larger radii. Such a trend is
more prevalent for more massive ($M_{\ast} > 10^{10.5}M_{\odot}$) galaxies or
those at lower redshifts ($z<1.4$). The distinct trend in $\varepsilon$ and
A$_4$ can be simply explained if galaxies possess all three components: central
bulges, disks in the intermediate regions, and halo-like stellar components in
the outskirts.
| astro-ph.GA | we have measured the radial profiles of isophotal ellipticity varepsilon and diskyboxy parameter a_4 out to radii of about three times the semimajor axes for sim4600 starforming galaxies sfgs at intermediate redshifts 05z18 in the candelsgoodss and uds fields based on the average size versus stellarmass relation in each redshift bin we divide our galaxies into small sfgs ssfgs ie smaller than average for its mass and large sfgs lsfgs ie larger than average we find that at low masses m_ast 1010m_odot the ssfgs generally have nearly flat varepsilon and a_4 profiles for both edgeon and faceon views especially at redshifts z1 moreover the median a_4 values at all radii are almost zero in contrast the highlyinclined lowmass lsfgs in the same massredshift bins generally have monotonically increasing varepsilon with radius and are dominated by disky values at intermediate radii these findings at intermediate redshifts imply that lowmass ssfgs are not disklike while lowmass lsfgs appear to harbour disklike components flattened by significant rotation at high masses m_ast 1010m_odot highlyinclined ssfgs and lsfgs both exhibit a general distinct trend for both varepsilon and a_4 profiles increasing values with radius at lower radii reaching maxima at intermediate radii and then decreasing values at larger radii such a trend is more prevalent for more massive m_ast 10105m_odot galaxies or those at lower redshifts z14 the distinct trend in varepsilon and a_4 can be simply explained if galaxies possess all three components central bulges disks in the intermediate regions and halolike stellar components in the outskirts | [['we', 'have', 'measured', 'the', 'radial', 'profiles', 'of', 'isophotal', 'ellipticity', 'varepsilon', 'and', 'diskyboxy', 'parameter', 'a_4', 'out', 'to', 'radii', 'of', 'about', 'three', 'times', 'the', 'semimajor', 'axes', 'for', 'sim4600', 'starforming', 'galaxies', 'sfgs', 'at', 'intermediate', 'redshifts', '05z18', 'in', 'the', 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1,802.07931 | Where's YOUR focus: Personalized Attention | Human visual attention is subjective and biased according to the personal
preference of the viewer, however, current works of saliency detection are
general and objective, without counting the factor of the observer. This will
make the attention prediction for a particular person not accurate enough. In
this work, we present the novel idea of personalized attention prediction and
develop Personalized Attention Network (PANet), a convolutional network that
predicts saliency in images with personal preference. The model consists of two
streams which share common feature extraction layers, and one stream is
responsible for saliency prediction, while the other is adapted from the
detection model and used to fit user preference. We automatically collect user
preference from their albums and leaves them freedom to define what and how
many categories their preferences are divided into. To train PANet, we
dynamically generate ground truth saliency maps upon existing detection labels
and saliency labels, and the generation parameters are based upon our collected
datasets consists of 1k images. We evaluate the model with saliency prediction
metrics and test the trained model on different preference vectors. The results
have shown that our system is much better than general models in personalized
saliency prediction and is efficient to use for different preferences.
| cs.CV | human visual attention is subjective and biased according to the personal preference of the viewer however current works of saliency detection are general and objective without counting the factor of the observer this will make the attention prediction for a particular person not accurate enough in this work we present the novel idea of personalized attention prediction and develop personalized attention network panet a convolutional network that predicts saliency in images with personal preference the model consists of two streams which share common feature extraction layers and one stream is responsible for saliency prediction while the other is adapted from the detection model and used to fit user preference we automatically collect user preference from their albums and leaves them freedom to define what and how many categories their preferences are divided into to train panet we dynamically generate ground truth saliency maps upon existing detection labels and saliency labels and the generation parameters are based upon our collected datasets consists of 1k images we evaluate the model with saliency prediction metrics and test the trained model on different preference vectors the results have shown that our system is much better than general models in personalized saliency prediction and is efficient to use for different preferences | [['human', 'visual', 'attention', 'is', 'subjective', 'and', 'biased', 'according', 'to', 'the', 'personal', 'preference', 'of', 'the', 'viewer', 'however', 'current', 'works', 'of', 'saliency', 'detection', 'are', 'general', 'and', 'objective', 'without', 'counting', 'the', 'factor', 'of', 'the', 'observer', 'this', 'will', 'make', 'the', 'attention', 'prediction', 'for', 'a', 'particular', 'person', 'not', 'accurate', 'enough', 'in', 'this', 'work', 'we', 'present', 'the', 'novel', 'idea', 'of', 'personalized', 'attention', 'prediction', 'and', 'develop', 'personalized', 'attention', 'network', 'panet', 'a', 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1,802.07932 | Faster integer multiplication using short lattice vectors | We prove that $n$-bit integers may be multiplied in $O(n \log n \, 4^{\log^*
n})$ bit operations. This complexity bound had been achieved previously by
several authors, assuming various unproved number-theoretic hypotheses. Our
proof is unconditional, and depends in an essential way on Minkowski's theorem
concerning lattice vectors in symmetric convex sets.
| cs.SC cs.DS math.NT | we prove that nbit integers may be multiplied in on log n 4log n bit operations this complexity bound had been achieved previously by several authors assuming various unproved numbertheoretic hypotheses our proof is unconditional and depends in an essential way on minkowskis theorem concerning lattice vectors in symmetric convex sets | [['we', 'prove', 'that', 'nbit', 'integers', 'may', 'be', 'multiplied', 'in', 'on', 'log', 'n', '4log', 'n', 'bit', 'operations', 'this', 'complexity', 'bound', 'had', 'been', 'achieved', 'previously', 'by', 'several', 'authors', 'assuming', 'various', 'unproved', 'numbertheoretic', 'hypotheses', 'our', 'proof', 'is', 'unconditional', 'and', 'depends', 'in', 'an', 'essential', 'way', 'on', 'minkowskis', 'theorem', 'concerning', 'lattice', 'vectors', 'in', 'symmetric', 'convex', 'sets']] | [-0.20422203345772097, 0.10643894542448049, -0.1245251343603812, 0.08808476247313414, -0.021054013431364416, -0.1976114686717754, 0.0933551515872572, 0.3301159144908774, -0.23925185258335926, -0.29846610182750166, 0.08891929988521059, -0.23957409711518124, -0.1389490297776373, 0.22771678203899487, -0.18004141010197938, 0.09993131082578033, 0.004770902095033842, 0.049956707621687184, -0.05291635190209776, -0.43394292938504736, 0.2996851581641856, -0.016858899354131197, 0.21340924169521266, 0.06186929903924465, 0.07637046946797009, 0.013849102015442708, -0.034859716353536234, -0.06940167934197805, -0.13644037314981117, 0.0927087662595452, 0.263494815239135, 0.17631811664129296, 0.27203869008842635, -0.4335035717151329, -0.10961332347691424, 0.13990950570943966, 0.19402512369732208, 0.06485905215217203, -0.038386647269933245, -0.24829639235109674, 0.1173217235060007, -0.10833434932226059, -0.11231563658015255, -0.06646385686654671, 0.08906759003944256, 0.014391005199000823, -0.2774255310787874, 0.00999943653632905, 0.15955217992521675, 0.0971178318939957, -0.045842569147912314, -0.2211901976306941, 0.09666975081085648, 0.023394246932630446, 0.03159327828325331, 0.10027976357834596, 0.0703745204681421, -0.016527070910395944, -0.16207989907878287, 0.26454827715368834, -0.015017141295852614, -0.24928645698317126, 0.10560777578868118, -0.12933737783939303, -0.2134638803773651, 0.07278598337799456, 0.09216241679136075, 0.13179581802265317, -0.06513649095580273, 0.20011754806824578, -0.19352511804112615, 0.2355261460088157, 0.2340202947676766, 0.07930582552673478, 0.10183208322554242, 0.045409929427300016, 0.07147075774549853, 0.1380330493523027, 0.07273355868699796, -0.08241632047529314, -0.27882066500537533, -0.14868625939718685, -0.2746637010325988, 0.1565149855964324, -0.13702180651992368, -0.10362513440286777, 0.26708629491793756, 0.06640267941653363, 0.1657877156126322, 0.10730230289639212, 0.25632003873732745, 0.10403287324223522, 0.02236154964924151, 0.13060553272382594, 0.14552691407209517, 0.15150835650388664, -0.032919571136909666, -0.07517070167095345, 0.15059292079040817, 0.1966909214548365] |
1,802.07933 | Modelling chemotaxis of microswimmers: from individual to collective
behavior | We discuss recent progress in the theoretical description of chemotaxis by
coupling the diffusion equation of a chemical species to equations describing
the motion of sensing microorganisms. In particular, we discuss models for
autochemotaxis of a single microorganism which senses its own secretion leading
to phenomena such as self-localization and self-avoidance. For two
heterogeneous particles, chemotactic coupling can lead to predator-prey
behavior including chase and escape phenomena, and to the formation of active
molecules, where motility spontaneously emerges when the particles approach
each other. We close this review with some remarks on the collective behavior
of many particles where chemotactic coupling induces patterns involving
clusters, spirals or traveling waves.
| cond-mat.soft nlin.PS physics.bio-ph | we discuss recent progress in the theoretical description of chemotaxis by coupling the diffusion equation of a chemical species to equations describing the motion of sensing microorganisms in particular we discuss models for autochemotaxis of a single microorganism which senses its own secretion leading to phenomena such as selflocalization and selfavoidance for two heterogeneous particles chemotactic coupling can lead to predatorprey behavior including chase and escape phenomena and to the formation of active molecules where motility spontaneously emerges when the particles approach each other we close this review with some remarks on the collective behavior of many particles where chemotactic coupling induces patterns involving clusters spirals or traveling waves | [['we', 'discuss', 'recent', 'progress', 'in', 'the', 'theoretical', 'description', 'of', 'chemotaxis', 'by', 'coupling', 'the', 'diffusion', 'equation', 'of', 'a', 'chemical', 'species', 'to', 'equations', 'describing', 'the', 'motion', 'of', 'sensing', 'microorganisms', 'in', 'particular', 'we', 'discuss', 'models', 'for', 'autochemotaxis', 'of', 'a', 'single', 'microorganism', 'which', 'senses', 'its', 'own', 'secretion', 'leading', 'to', 'phenomena', 'such', 'as', 'selflocalization', 'and', 'selfavoidance', 'for', 'two', 'heterogeneous', 'particles', 'chemotactic', 'coupling', 'can', 'lead', 'to', 'predatorprey', 'behavior', 'including', 'chase', 'and', 'escape', 'phenomena', 'and', 'to', 'the', 'formation', 'of', 'active', 'molecules', 'where', 'motility', 'spontaneously', 'emerges', 'when', 'the', 'particles', 'approach', 'each', 'other', 'we', 'close', 'this', 'review', 'with', 'some', 'remarks', 'on', 'the', 'collective', 'behavior', 'of', 'many', 'particles', 'where', 'chemotactic', 'coupling', 'induces', 'patterns', 'involving', 'clusters', 'spirals', 'or', 'traveling', 'waves']] | [-0.14138203535929594, 0.21483528228698795, -0.033740689653322234, 0.010020235669799149, -0.08485299258048587, -0.16714655201659973, 0.018291215939925762, 0.3147585572367278, -0.2788259383043223, -0.26856502227553536, 0.026090232230329868, -0.29345440910701903, -0.21572163839687789, 0.12113887421709887, -0.028838541856411538, -0.01551942396193418, 0.03231065170924871, 0.01742217393694531, 0.052661162177357106, -0.17361215102687103, 0.25037990929558873, 0.005470381840345783, 0.24203557377775123, 0.04682391750361394, 0.14013973730103618, -0.024435561667239175, 0.035595082831697177, -0.001485328317124294, -0.1898673961896005, 0.0865690307851898, 0.2127670689133584, 0.07714551480042689, 0.2620172069254203, -0.5013210631291801, -0.2793701536346808, 0.10891579966052273, 0.2058028390784876, 0.18519928527103072, -0.10149276325876457, -0.3011054123726186, -0.026945959366516236, -0.13679425713580545, -0.17619588635776431, -0.04990615669227795, 0.05475166745146377, 0.11697943994151684, -0.25437056042100176, 0.11564388925021668, 0.06178984855549461, 0.03930295988305369, -0.10824662619249023, -0.05962392280984738, -0.012380750866931512, 0.12953825982062173, 0.1243926181709992, -0.06323018560715772, 0.22345666125963587, -0.2121789641315203, -0.13534789194070965, 0.4346517510712147, -0.059027906101402065, -0.22049157080719026, 0.295084292368126, -0.14622664805758026, -0.13469210852347657, 0.10771424491214779, 0.216591704594091, 0.0864875391932042, -0.14682718160321376, 0.014562434199108068, 0.0024617750607772706, 0.09904063315293112, 0.08207661870422714, 0.04036413446718126, 0.206921871160926, 0.2345790164844227, 0.027247248637733486, 0.08404574870108414, -0.050863916368368976, -0.1578140074810133, -0.2274320059618272, -0.143951767942347, -0.08399738890862246, 0.04425706454646697, -0.09097228754018626, -0.161328412801745, 0.3842510511295511, 0.13049980906455633, 0.21619787580256752, 0.020040376646948313, 0.23910340234912814, 0.048096443051173256, 0.021480950067640035, -0.006996767700077334, 0.24064609609729046, 0.11743798621485882, 0.11817018727883014, -0.283218201010599, 0.0869682697171277, 0.05118709781694166] |
1,802.07934 | Adversarial Learning for Semi-Supervised Semantic Segmentation | We propose a method for semi-supervised semantic segmentation using an
adversarial network. While most existing discriminators are trained to classify
input images as real or fake on the image level, we design a discriminator in a
fully convolutional manner to differentiate the predicted probability maps from
the ground truth segmentation distribution with the consideration of the
spatial resolution. We show that the proposed discriminator can be used to
improve semantic segmentation accuracy by coupling the adversarial loss with
the standard cross entropy loss of the proposed model. In addition, the fully
convolutional discriminator enables semi-supervised learning through
discovering the trustworthy regions in predicted results of unlabeled images,
thereby providing additional supervisory signals. In contrast to existing
methods that utilize weakly-labeled images, our method leverages unlabeled
images to enhance the segmentation model. Experimental results on the PASCAL
VOC 2012 and Cityscapes datasets demonstrate the effectiveness of the proposed
algorithm.
| cs.CV | we propose a method for semisupervised semantic segmentation using an adversarial network while most existing discriminators are trained to classify input images as real or fake on the image level we design a discriminator in a fully convolutional manner to differentiate the predicted probability maps from the ground truth segmentation distribution with the consideration of the spatial resolution we show that the proposed discriminator can be used to improve semantic segmentation accuracy by coupling the adversarial loss with the standard cross entropy loss of the proposed model in addition the fully convolutional discriminator enables semisupervised learning through discovering the trustworthy regions in predicted results of unlabeled images thereby providing additional supervisory signals in contrast to existing methods that utilize weaklylabeled images our method leverages unlabeled images to enhance the segmentation model experimental results on the pascal voc 2012 and cityscapes datasets demonstrate the effectiveness of the proposed algorithm | [['we', 'propose', 'a', 'method', 'for', 'semisupervised', 'semantic', 'segmentation', 'using', 'an', 'adversarial', 'network', 'while', 'most', 'existing', 'discriminators', 'are', 'trained', 'to', 'classify', 'input', 'images', 'as', 'real', 'or', 'fake', 'on', 'the', 'image', 'level', 'we', 'design', 'a', 'discriminator', 'in', 'a', 'fully', 'convolutional', 'manner', 'to', 'differentiate', 'the', 'predicted', 'probability', 'maps', 'from', 'the', 'ground', 'truth', 'segmentation', 'distribution', 'with', 'the', 'consideration', 'of', 'the', 'spatial', 'resolution', 'we', 'show', 'that', 'the', 'proposed', 'discriminator', 'can', 'be', 'used', 'to', 'improve', 'semantic', 'segmentation', 'accuracy', 'by', 'coupling', 'the', 'adversarial', 'loss', 'with', 'the', 'standard', 'cross', 'entropy', 'loss', 'of', 'the', 'proposed', 'model', 'in', 'addition', 'the', 'fully', 'convolutional', 'discriminator', 'enables', 'semisupervised', 'learning', 'through', 'discovering', 'the', 'trustworthy', 'regions', 'in', 'predicted', 'results', 'of', 'unlabeled', 'images', 'thereby', 'providing', 'additional', 'supervisory', 'signals', 'in', 'contrast', 'to', 'existing', 'methods', 'that', 'utilize', 'weaklylabeled', 'images', 'our', 'method', 'leverages', 'unlabeled', 'images', 'to', 'enhance', 'the', 'segmentation', 'model', 'experimental', 'results', 'on', 'the', 'pascal', 'voc', '2012', 'and', 'cityscapes', 'datasets', 'demonstrate', 'the', 'effectiveness', 'of', 'the', 'proposed', 'algorithm']] | [0.009951524225667724, -0.05606218820311541, -0.04066691047990242, 0.0789698252164935, -0.09968046462981382, -0.1549250365744622, 0.019790392476008146, 0.4721000222237529, -0.23985605402236074, -0.3889847306874455, 0.007069921182355264, -0.3000507974614487, -0.18417088892601896, 0.1701346584737326, -0.18091216651294884, 0.10746655733964872, 0.17981167469249182, 0.054021287706328205, -0.036632416307347246, -0.3022625166584574, 0.3029284526254176, 0.03874663361725775, 0.3926596245036234, 0.030890633946762898, 0.15870042764141248, -0.06079874348801535, -0.030100035864420904, -0.01571471802025052, -0.03156641597052914, 0.19439881346566049, 0.3135209243187706, 0.2188894851471461, 0.2701121711115529, -0.3925537501140875, -0.24396532291634562, 0.09408966393990291, 0.10719520514012894, 0.10471483444839455, -0.06270593647511576, -0.45151789558145244, 0.11659341198203431, -0.15716451886613425, 0.08537744682571674, -0.18019298386659371, -0.11057411525335566, -0.04353145444553308, -0.343742808232688, 0.05442105587005515, 0.07681362180517533, 0.0174333161762538, -0.08851570405877775, -0.07390027251283361, -0.0420463099946721, 0.18662424040549258, -0.00984181371058111, 0.07463091177448183, 0.12681887704388214, -0.2299605383241952, -0.17638246007452443, 0.31020772585494294, -0.07689147474357506, -0.23287390782246115, 0.19616906886693794, -0.038857295432732114, -0.09247159953244861, 0.12223899480572122, 0.23593724406060032, 0.12321380974498351, -0.12997195664541544, -0.012404768350549872, -0.048946314944407425, 0.2013403712850492, 0.04742190703227361, -0.04664419654314721, 0.14628909681089902, 0.2722350206175769, 0.010336919604309809, 0.18086086464589587, -0.24683186049082292, -0.01375025145338244, -0.23277918268364817, -0.0795689648696901, -0.21175848248389526, -0.06003030766481282, -0.1253537151653192, -0.13656392362365197, 0.41065428509200746, 0.29964545370564116, 0.2644609565645255, 0.1341496997110143, 0.39954457483002664, -0.023899469729135366, 0.1391273085657205, 0.07625097813748603, 0.20872683201073292, 0.022916992348335632, 0.10521502802116997, -0.15622878785880684, 0.09145961730816476, 0.09813914414986062] |
1,802.07935 | Asynchronous stochastic approximations with asymptotically biased errors
and deep multi-agent learning | Asynchronous stochastic approximations (SAs) are an important class of
model-free algorithms, tools and techniques that are popular in multi-agent and
distributed control scenarios. To counter Bellman's curse of dimensionality,
such algorithms are coupled with function approximations. Although the
learning/ control problem becomes more tractable, function approximations
affect stability and convergence. In this paper, we present verifiable
sufficient conditions for stability and convergence of asynchronous SAs with
biased approximation errors. The theory developed herein is used to analyze
Policy Gradient methods and noisy Value Iteration schemes. Specifically, we
analyze the asynchronous approximate counterparts of the policy gradient (A2PG)
and value iteration (A2VI) schemes. It is shown that the stability of these
algorithms is unaffected by biased approximation errors, provided they are
asymptotically bounded. With respect to convergence (of A2VI and A2PG), a
relationship between the limiting set and the approximation errors is
established. Finally, experimental results are presented that support the
theory.
| math.OC math.DS stat.ML | asynchronous stochastic approximations sas are an important class of modelfree algorithms tools and techniques that are popular in multiagent and distributed control scenarios to counter bellmans curse of dimensionality such algorithms are coupled with function approximations although the learning control problem becomes more tractable function approximations affect stability and convergence in this paper we present verifiable sufficient conditions for stability and convergence of asynchronous sas with biased approximation errors the theory developed herein is used to analyze policy gradient methods and noisy value iteration schemes specifically we analyze the asynchronous approximate counterparts of the policy gradient a2pg and value iteration a2vi schemes it is shown that the stability of these algorithms is unaffected by biased approximation errors provided they are asymptotically bounded with respect to convergence of a2vi and a2pg a relationship between the limiting set and the approximation errors is established finally experimental results are presented that support the theory | [['asynchronous', 'stochastic', 'approximations', 'sas', 'are', 'an', 'important', 'class', 'of', 'modelfree', 'algorithms', 'tools', 'and', 'techniques', 'that', 'are', 'popular', 'in', 'multiagent', 'and', 'distributed', 'control', 'scenarios', 'to', 'counter', 'bellmans', 'curse', 'of', 'dimensionality', 'such', 'algorithms', 'are', 'coupled', 'with', 'function', 'approximations', 'although', 'the', 'learning', 'control', 'problem', 'becomes', 'more', 'tractable', 'function', 'approximations', 'affect', 'stability', 'and', 'convergence', 'in', 'this', 'paper', 'we', 'present', 'verifiable', 'sufficient', 'conditions', 'for', 'stability', 'and', 'convergence', 'of', 'asynchronous', 'sas', 'with', 'biased', 'approximation', 'errors', 'the', 'theory', 'developed', 'herein', 'is', 'used', 'to', 'analyze', 'policy', 'gradient', 'methods', 'and', 'noisy', 'value', 'iteration', 'schemes', 'specifically', 'we', 'analyze', 'the', 'asynchronous', 'approximate', 'counterparts', 'of', 'the', 'policy', 'gradient', 'a2pg', 'and', 'value', 'iteration', 'a2vi', 'schemes', 'it', 'is', 'shown', 'that', 'the', 'stability', 'of', 'these', 'algorithms', 'is', 'unaffected', 'by', 'biased', 'approximation', 'errors', 'provided', 'they', 'are', 'asymptotically', 'bounded', 'with', 'respect', 'to', 'convergence', 'of', 'a2vi', 'and', 'a2pg', 'a', 'relationship', 'between', 'the', 'limiting', 'set', 'and', 'the', 'approximation', 'errors', 'is', 'established', 'finally', 'experimental', 'results', 'are', 'presented', 'that', 'support', 'the', 'theory']] | [-0.10684283586301314, 0.009601753155267671, -0.09473834582129304, 0.11495578615232466, -0.05731573963037306, -0.18631472086001719, 0.07951006495479342, 0.4419796916206374, -0.30331265363766224, -0.2654344443929521, 0.17325577702449294, -0.23603902193939402, -0.18449190762020698, 0.20006448555053497, -0.1239664810472073, 0.14405675703140142, 0.07082318123683434, -0.021985162961847927, -0.07954700250530197, -0.29966091631189445, 0.2634151005352448, 0.04611065030275356, 0.3002499865469377, -0.019795014842913874, 0.10651421996758503, -0.04901998404565514, -0.02356729385455703, 0.07389598959410677, -0.13102675086519083, 0.1312906029214449, 0.2848198185516458, 0.16675261444836653, 0.3523051562104501, -0.4003356261825075, -0.14406526574649575, 0.10654470484923939, 0.16723647982742934, 0.1318113070336126, -0.04794015476472603, -0.26509418894162995, 0.12868499217339519, -0.14140190589590138, -0.1088713282389807, -0.15567367378508254, -0.042301360744235364, 0.08914908664427748, -0.3419262916166462, 0.06925906269608358, 0.05933570983458539, 0.034650152460450216, -0.07233956159444108, -0.12207511157354936, 0.06034002747374023, 0.09607490488537113, 0.06299785012696064, -0.01190755518191323, 0.12636883645065028, -0.08412272530785274, -0.14123594993487837, 0.33084032225872384, -0.030257124899249827, -0.262025888033566, 0.20017201835162887, -0.03191690581857043, -0.13307640810820218, 0.11341375441981011, 0.20620238793052442, 0.15556966980323703, -0.14324595767776577, 0.10913384267363418, 0.018191930803083848, 0.13604774970092437, 0.020473773733769754, 0.03302513600523476, 0.05988619550999229, 0.16036853397448808, 0.16397965417503296, 0.10726494852573845, -0.015351698508954981, -0.18226746674690422, -0.2767596142936726, -0.06845199846073377, -0.1316852029381307, -0.04511575103693065, -0.10714341365798775, -0.18710191782661334, 0.32205021271139994, 0.19587142095856724, 0.1184515206358668, 0.12996193858459085, 0.36255492040646725, 0.17633816995232313, -0.029797094677682635, 0.15393765436067264, 0.2433893275407593, 0.1610517084240584, 0.09773710019392323, -0.21887264273297294, 0.13825808442039353, 0.0784949902067916] |
1,802.07936 | Two theorems on distribution of Gaussian quadratic forms | New results on comparison of distributions of Gaussian quadratic forms are
presented
| cs.IT math.IT math.PR | new results on comparison of distributions of gaussian quadratic forms are presented | [['new', 'results', 'on', 'comparison', 'of', 'distributions', 'of', 'gaussian', 'quadratic', 'forms', 'are', 'presented']] | [-0.12020786843883495, 0.039712791525137923, -0.12275079866716017, 0.08085927739739418, -0.06609364404963951, -0.11487624111274879, -0.047801078762859106, 0.3802584130316973, -0.19077034449825683, -0.24446437880396843, 0.03443810863730808, -0.31333999304721755, -0.15922926149020591, 0.3606153894215822, -0.03146680475523075, 0.11287715774960816, 0.0718928500233839, -0.015486455522477627, -0.13709645361329117, -0.31596647916982573, 0.40068349925180274, 0.035082435235381126, 0.25481814332306385, -0.030334338545799255, 0.05497833496580521, 0.026421286733238958, -0.14974233166625103, -0.06039760292818149, -0.17779581435024738, 0.207733688216346, 0.16296543658245355, 0.08990081876982003, 0.21968792902771384, -0.37082067752877873, -0.19543045479804277, 0.024701567366719246, 0.05370185660043111, 0.02933301559338967, -0.11824485742060158, -0.2573831882327795, 0.08485532154251511, -0.11094958963803947, -0.07937360430757205, -0.17330888658761978, -0.08022269296149413, 0.1536387810483575, -0.2976266760379076, 0.11434309450851288, 0.0744293484215935, 0.10199555630485217, -0.14711005935290208, -0.32337818543116253, 0.031089851167052984, -0.0010145300378402073, 0.019393879066531856, -0.06668103525104623, 0.06218562073384722, -0.08583402998435001, -0.18186813701565066, 0.29694782197475433, -0.12805690740545592, -0.2677780917535226, 0.24678861442953348, -0.135122879796351, -0.13213793471610794, 0.11629924255733688, 0.2857409705563138, 0.1331898745459815, -0.16550186617920795, 0.07619661465287209, -0.08781486377120018, 0.045235105169316135, 0.07822615075080346, -0.00434654609610637, 0.11941271585722764, 0.07677786828329165, 0.0338353686966002, 0.20478297314063335, -0.053175951567633696, -0.2590951727082332, -0.44465089589357376, -0.13525233906693757, -0.21446658546725908, -0.048736822296632454, -0.12917536372939745, -0.15583873819559813, 0.4031267749766509, 0.019915939095274855, 0.2212488641962409, 0.13204263523221016, 0.2181993272776405, 0.17669198685325682, 0.027820166510840256, -0.012760449821750322, 0.16536679739753404, 0.22863350622355938, -0.03733837833472838, -0.06642769494404395, 0.06745439325459301, -0.05455320448769877] |
1,802.07937 | Phase transition of vortex states in two-dimensional superconductors
under a oscillating magnetic field from the chiral helimagnet | We have investigated vortex states in two-dimensional superconductors under a
oscillating magnetic field from a chiral helimagnet. We have solved the
two-dimensional Ginzburg-Landau equations with finite element method. We have
found that when the magnetic field from the chiral helimagnet increases,
vortices appear all at once in all periodic regions. This transition is
different from that under the uniform magnetic field. Under the composite
magnetic field with the oscillating and uniform fields (down-vortices),
vortices antiparallel to the uniform magnetic field disappear. Then, the small
uniform magnetic field easily remove down-vortices.
| cond-mat.supr-con | we have investigated vortex states in twodimensional superconductors under a oscillating magnetic field from a chiral helimagnet we have solved the twodimensional ginzburglandau equations with finite element method we have found that when the magnetic field from the chiral helimagnet increases vortices appear all at once in all periodic regions this transition is different from that under the uniform magnetic field under the composite magnetic field with the oscillating and uniform fields downvortices vortices antiparallel to the uniform magnetic field disappear then the small uniform magnetic field easily remove downvortices | [['we', 'have', 'investigated', 'vortex', 'states', 'in', 'twodimensional', 'superconductors', 'under', 'a', 'oscillating', 'magnetic', 'field', 'from', 'a', 'chiral', 'helimagnet', 'we', 'have', 'solved', 'the', 'twodimensional', 'ginzburglandau', 'equations', 'with', 'finite', 'element', 'method', 'we', 'have', 'found', 'that', 'when', 'the', 'magnetic', 'field', 'from', 'the', 'chiral', 'helimagnet', 'increases', 'vortices', 'appear', 'all', 'at', 'once', 'in', 'all', 'periodic', 'regions', 'this', 'transition', 'is', 'different', 'from', 'that', 'under', 'the', 'uniform', 'magnetic', 'field', 'under', 'the', 'composite', 'magnetic', 'field', 'with', 'the', 'oscillating', 'and', 'uniform', 'fields', 'downvortices', 'vortices', 'antiparallel', 'to', 'the', 'uniform', 'magnetic', 'field', 'disappear', 'then', 'the', 'small', 'uniform', 'magnetic', 'field', 'easily', 'remove', 'downvortices']] | [-0.2051386012074848, 0.28829371489377487, -0.038647077237773275, 0.02373974726845821, -0.061744183239837484, -0.09466678910992211, -0.021400850294675262, 0.39906280173195735, -0.24337036791774963, -0.2532431449340139, 0.03582607637314747, -0.21251078486028646, -0.09124062389859723, 0.15962475189525221, 0.054533102539264494, -0.014606938216214378, -0.06409344944533789, 0.07970868586045173, -0.06974240099079906, -0.2303811862029963, 0.34734930974793515, -0.0901780168318914, 0.33520350319643816, -0.0025528529135044665, 0.03255747605322136, -0.026628790971719555, 0.14569440502673386, 0.1489413431328204, -0.15402646169871634, -0.036892523842268723, 0.16168486698427134, -0.10971042000585132, 0.19684712789280134, -0.5400352280379997, -0.20756427020921062, 0.06444577626211362, 0.17417827817973577, 0.17578104852388302, -0.09579327474865648, -0.30410187817696066, 0.11623464208096265, -0.07812804946055014, -0.16507057864736352, -0.10357166603207588, -0.027109610038395557, 0.07923026242189937, -0.30273551544588473, 0.06961608475281132, 0.05220174766274997, 0.15542574705969955, -0.14986273066865075, -0.08841815343023174, -0.05109838646215697, 0.04943946712139425, 0.12698233525475694, 0.13438733452931045, 0.13768540012857153, -0.1763852636821361, -0.056631093456720315, 0.30726867945243913, -0.09832699409065147, -0.1547835311334994, 0.12064829987163345, -0.20076701271658143, -0.09225862420118776, 0.21511415454248586, 0.12936113762358825, 0.12032324710550407, -0.11434574311214318, 0.12915445311033788, -0.09068008019692368, 0.11189709566274865, 0.08656386318099167, -0.0010726885456177923, 0.29744437432123555, 0.09857684339707097, 0.06792601008330368, 0.17666004998092022, -0.1570247088972893, -0.08744436773575015, -0.24717730974985494, -0.10197806241404679, -0.1782750524295908, 0.04060035799112585, -0.06753382575164626, -0.23937935726199713, 0.3745009057327277, 0.19199085862686235, 0.12220021488060916, -0.08293838924210932, 0.2560501576297813, 0.13803698026264707, 0.11524211169323988, 0.11061700812747909, 0.2536160267087527, 0.24527033431610715, 0.15806867490626045, -0.25047295855409984, -0.063079430018681, 0.0301532627393802] |
1,802.07938 | Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and
Reviews | Although latent factor models (e.g., matrix factorization) achieve good
accuracy in rating prediction, they suffer from several problems including
cold-start, non-transparency, and suboptimal recommendation for local users or
items. In this paper, we employ textual review information with ratings to
tackle these limitations. Firstly, we apply a proposed aspect-aware topic model
(ATM) on the review text to model user preferences and item features from
different aspects, and estimate the aspect importance of a user towards an
item. The aspect importance is then integrated into a novel aspect-aware latent
factor model (ALFM), which learns user's and item's latent factors based on
ratings. In particular, ALFM introduces a weighted matrix to associate those
latent factors with the same set of aspects discovered by ATM, such that the
latent factors could be used to estimate aspect ratings. Finally, the overall
rating is computed via a linear combination of the aspect ratings, which are
weighted by the corresponding aspect importance. To this end, our model could
alleviate the data sparsity problem and gain good interpretability for
recommendation. Besides, an aspect rating is weighted by an aspect importance,
which is dependent on the targeted user's preferences and targeted item's
features. Therefore, it is expected that the proposed method can model a user's
preferences on an item more accurately for each user-item pair locally.
Comprehensive experimental studies have been conducted on 19 datasets from
Amazon and Yelp 2017 Challenge dataset. Results show that our method achieves
significant improvement compared with strong baseline methods, especially for
users with only few ratings. Moreover, our model could interpret the
recommendation results in depth.
| cs.IR | although latent factor models eg matrix factorization achieve good accuracy in rating prediction they suffer from several problems including coldstart nontransparency and suboptimal recommendation for local users or items in this paper we employ textual review information with ratings to tackle these limitations firstly we apply a proposed aspectaware topic model atm on the review text to model user preferences and item features from different aspects and estimate the aspect importance of a user towards an item the aspect importance is then integrated into a novel aspectaware latent factor model alfm which learns users and items latent factors based on ratings in particular alfm introduces a weighted matrix to associate those latent factors with the same set of aspects discovered by atm such that the latent factors could be used to estimate aspect ratings finally the overall rating is computed via a linear combination of the aspect ratings which are weighted by the corresponding aspect importance to this end our model could alleviate the data sparsity problem and gain good interpretability for recommendation besides an aspect rating is weighted by an aspect importance which is dependent on the targeted users preferences and targeted items features therefore it is expected that the proposed method can model a users preferences on an item more accurately for each useritem pair locally comprehensive experimental studies have been conducted on 19 datasets from amazon and yelp 2017 challenge dataset results show that our method achieves significant improvement compared with strong baseline methods especially for users with only few ratings moreover our model could interpret the recommendation results in depth | [['although', 'latent', 'factor', 'models', 'eg', 'matrix', 'factorization', 'achieve', 'good', 'accuracy', 'in', 'rating', 'prediction', 'they', 'suffer', 'from', 'several', 'problems', 'including', 'coldstart', 'nontransparency', 'and', 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'show', 'that', 'our', 'method', 'achieves', 'significant', 'improvement', 'compared', 'with', 'strong', 'baseline', 'methods', 'especially', 'for', 'users', 'with', 'only', 'few', 'ratings', 'moreover', 'our', 'model', 'could', 'interpret', 'the', 'recommendation', 'results', 'in', 'depth']] | [-0.015117593018042568, -0.005904965970638352, -0.046924599980971274, 0.07444254974073444, -0.1647214697315716, -0.17492941655576802, 0.09935750712757, 0.44452778014999167, -0.2583571054256306, -0.3411713623338773, 0.06886354081058156, -0.3493868205875445, -0.18246825542256165, 0.14138151105726138, -0.11623875178784146, 0.0320401475113333, 0.10905074972542934, 0.07891409621359063, -0.04695913941339733, -0.32608849904992476, 0.331077585903068, 0.0850885043037124, 0.33691600397444116, 0.06330133572740193, 0.1023993393634625, -0.017680957039388327, -0.09180583047698467, 0.03705249657997718, -0.08776639538608344, 0.15746494597898653, 0.35502512735520914, 0.1971488304176511, 0.35225692284024823, 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1,802.07939 | Symmetric Tops Subject to Combined Electric Fields: Conditional
Quasi-Solvability via the Quantum Hamilton-Jacobi Theory | We make use of the Quantum Hamilton-Jacobi (QHJ) theory to investigate
conditional quasi-solvability of the quantum symmetric top subject to combined
electric fields (symmetric top pendulum). We derive the conditions of
quasi-solvability of the time-independent Schroedinger equation as well as the
corresponding finite sets of exact analytic solutions. We do so for this
prototypical trigonometric system as well as for its anti-isospectral
hyperbolic counterpart. An examination of the algebraic and numerical spectra
of these two systems reveals mutually closely related patterns. The QHJ
approach allows to retrieve the closed-form solutions for the spherical and
planar pendula and the Razavy system that had been obtained in our earlier work
via Supersymmetric Quantum Mechanics as well as to find a cornucopia of
additional exact analytic solutions.
| math-ph math.MP quant-ph | we make use of the quantum hamiltonjacobi qhj theory to investigate conditional quasisolvability of the quantum symmetric top subject to combined electric fields symmetric top pendulum we derive the conditions of quasisolvability of the timeindependent schroedinger equation as well as the corresponding finite sets of exact analytic solutions we do so for this prototypical trigonometric system as well as for its antiisospectral hyperbolic counterpart an examination of the algebraic and numerical spectra of these two systems reveals mutually closely related patterns the qhj approach allows to retrieve the closedform solutions for the spherical and planar pendula and the razavy system that had been obtained in our earlier work via supersymmetric quantum mechanics as well as to find a cornucopia of additional exact analytic solutions | [['we', 'make', 'use', 'of', 'the', 'quantum', 'hamiltonjacobi', 'qhj', 'theory', 'to', 'investigate', 'conditional', 'quasisolvability', 'of', 'the', 'quantum', 'symmetric', 'top', 'subject', 'to', 'combined', 'electric', 'fields', 'symmetric', 'top', 'pendulum', 'we', 'derive', 'the', 'conditions', 'of', 'quasisolvability', 'of', 'the', 'timeindependent', 'schroedinger', 'equation', 'as', 'well', 'as', 'the', 'corresponding', 'finite', 'sets', 'of', 'exact', 'analytic', 'solutions', 'we', 'do', 'so', 'for', 'this', 'prototypical', 'trigonometric', 'system', 'as', 'well', 'as', 'for', 'its', 'antiisospectral', 'hyperbolic', 'counterpart', 'an', 'examination', 'of', 'the', 'algebraic', 'and', 'numerical', 'spectra', 'of', 'these', 'two', 'systems', 'reveals', 'mutually', 'closely', 'related', 'patterns', 'the', 'qhj', 'approach', 'allows', 'to', 'retrieve', 'the', 'closedform', 'solutions', 'for', 'the', 'spherical', 'and', 'planar', 'pendula', 'and', 'the', 'razavy', 'system', 'that', 'had', 'been', 'obtained', 'in', 'our', 'earlier', 'work', 'via', 'supersymmetric', 'quantum', 'mechanics', 'as', 'well', 'as', 'to', 'find', 'a', 'cornucopia', 'of', 'additional', 'exact', 'analytic', 'solutions']] | [-0.10542471364756385, 0.034554859717313625, -0.09313619126095868, 0.08247159135193684, -0.08636734833482713, -0.14480543713415822, 0.012659577912868812, 0.3243240353561217, -0.2363198343082331, -0.2669896062148074, 0.10981914258821146, -0.27657753355519926, -0.18213157816940256, 0.22466644098054647, -0.02946748787156051, 0.1389208332998791, 0.030009178951713105, 0.0658241266951776, -0.0839235344845351, -0.1850283679987995, 0.3138014358175438, 0.005801564952801733, 0.23658097067269526, 0.01265157981505317, 0.11435585614526644, 0.021690201209557634, 0.005155192293797529, 0.00625931519278956, -0.15173778946037572, 0.10439195625874545, 0.21894507183911158, 0.07230146519366591, 0.18825473361310638, -0.4480048594996333, -0.18345078164260956, 0.06395438931987531, 0.16319899335353366, 0.1576938707571131, -0.030610603888729406, -0.30297238493879, 0.05601714244262586, -0.17370809549691096, -0.20618384973251172, -0.10112492515397589, 0.014538644482531855, 0.06902888830330584, -0.244652904754114, 0.08088611284901778, 0.05605720581426736, 0.0454742890001545, -0.09903700593924676, -0.1025325132584605, -0.01769466501953561, 0.12710704351024282, 0.03982413146314361, -0.01645898560602819, 0.07455440114426892, -0.09070686598105597, -0.15275828658993687, 0.3883790517255904, -0.06197790405900788, -0.2412596676017969, 0.19838669462161865, -0.11038736641902717, -0.10142772748780947, 0.06200756156824589, 0.1462858250973025, 0.15386732551269233, -0.15956400894379663, 0.1147172336092016, -0.0653106564272856, 0.11460981225301962, 0.06929682667795269, 0.035334406386790494, 0.18558372286779265, 0.07297006768414811, 0.05981861204547327, 0.19479223811668495, -0.0037845641847759964, -0.16961846670376196, -0.31117166475122493, -0.16127234681757288, -0.14619409264395794, 0.10239950564855169, -0.05471385318765721, -0.23379249905326194, 0.3682626988738775, 0.10407185660404784, 0.16136414919709485, 0.06000487889621347, 0.24562082378636865, 0.16173331654065423, 0.0038406949249967454, 0.020531531370755647, 0.24240356471179234, 0.19009263652767386, 0.09952662360944575, -0.22677375951541529, -0.02748053122101532, 0.09485311593931739] |
1,802.0794 | On detection of Gaussian stochastic sequences | The problem of minimax detection of Gaussian random signal vector in White
Gaussian additive noise is considered. It is supposed that an unknown vector
$\boldsymbol{\sigma}$ of the signal vector intensities belong to the given set
${\mathcal E}$. It is investigated when it is possible to replace the set
${\mathcal E}$ by a smaller set ${\mathcal E}_{0}$ without loss of quality
(and, in particular, to replace it by a single point
$\boldsymbol{\sigma}_{0}$).
| cs.IT math.IT | the problem of minimax detection of gaussian random signal vector in white gaussian additive noise is considered it is supposed that an unknown vector boldsymbolsigma of the signal vector intensities belong to the given set mathcal e it is investigated when it is possible to replace the set mathcal e by a smaller set mathcal e_0 without loss of quality and in particular to replace it by a single point boldsymbolsigma_0 | [['the', 'problem', 'of', 'minimax', 'detection', 'of', 'gaussian', 'random', 'signal', 'vector', 'in', 'white', 'gaussian', 'additive', 'noise', 'is', 'considered', 'it', 'is', 'supposed', 'that', 'an', 'unknown', 'vector', 'boldsymbolsigma', 'of', 'the', 'signal', 'vector', 'intensities', 'belong', 'to', 'the', 'given', 'set', 'mathcal', 'e', 'it', 'is', 'investigated', 'when', 'it', 'is', 'possible', 'to', 'replace', 'the', 'set', 'mathcal', 'e', 'by', 'a', 'smaller', 'set', 'mathcal', 'e_0', 'without', 'loss', 'of', 'quality', 'and', 'in', 'particular', 'to', 'replace', 'it', 'by', 'a', 'single', 'point', 'boldsymbolsigma_0']] | [-0.10290807799569197, 0.12274653134123323, -0.0029613450169563293, 0.04240387129331274, -0.06979020550580961, -0.1568323320576123, 0.0396569303569517, 0.37534139209559986, -0.3189075641799718, -0.21709664557129144, 0.06203025994888906, -0.27542724147705094, -0.12827332807438716, 0.15890220954482046, -0.10838372201459216, 0.09460706585752113, 0.022079101843493324, 0.15877695811962309, -0.006047760825770508, -0.27187044852346715, 0.34040856662073304, 0.038528109115681476, 0.25667823676818186, -0.07123526833685381, 0.11584018647138561, 0.021321306856615204, -0.004050183083329882, -0.041692369244992734, -0.07289399897199474, 0.06460835575625035, 0.23993115245747113, 0.17281615183954793, 0.3028854879949774, -0.3244275926612318, -0.2118319343492788, 0.23072829567162054, 0.06832532443638359, 0.00014475691797477858, 0.014101114350238017, -0.2706427145350192, 0.1723660836994116, -0.12717509429369653, -0.08512729216100914, -0.042647697823122145, 0.09028533944594008, -0.03445960897952318, -0.3688586457765528, 0.01705383746219533, 0.11410547271370888, -0.018671404809824058, -0.03605282987867083, -0.1269948533203985, -0.04611243515474988, 0.04307108370329453, 0.009387339831196837, 0.14654343512541215, 0.11476665391985859, -0.10301985610276461, -0.059071773809513874, 0.37715274507396057, -0.10504559873204146, -0.29278661029446607, 0.120121284328135, -0.13799366964293378, -0.06013095911060061, 0.181482194869646, 0.15778104622316147, 0.10364407179211932, -0.15980168374226195, 0.14875211010470854, -0.06294751987443306, 0.11592448340670672, 0.07424926143139601, 0.02387288752278047, 0.15307537538132499, 0.12825123463491245, 0.09126499178819358, 0.1295443550483989, -0.11191368930573975, -0.026796018718908143, -0.32980436948793274, -0.081559086780596, -0.24919042524748614, 0.10026260935036199, -0.06278239277536549, -0.18924264359021825, 0.3222053599277777, 0.14080278004652688, 0.2464125686056962, 0.016108450493110077, 0.27848879203998617, 0.16928630767485758, 0.020853012068463222, 0.07208469544670411, 0.19120637572237423, 0.171006929455325, -0.017379017007936325, -0.1344319716328755, 0.06505529446793454, 0.01997463002002665] |
1,802.07941 | Strain effect in highly-doped n-type 3C-SiC-on-glass substrate for
mechanical sensors and mobility enhancement | This work reports the strain effect on the electrical properties of highly
doped n-type single crystalline cubic silicon carbide (3C-SiC) transferred onto
a 6-inch glass substrate employing an anodic bonding technique. The
experimental data shows high gauge factors of -8.6 in longitudinal direction
and 10.5 in transverse direction along the [100] orientation. The
piezoresistive effect in the highly doped 3C-SiC film also exhibits an
excellent linearity and consistent reproducibility after several bending
cycles. The experimental result was in good agreement with the theoretical
analysis based on the phenomenon of electron transfer between many valleys in
the conduction band of n-type 3C-SiC. Our finding for the large gauge factor in
n-type 3C- SiC coupled with the elimination of the current leak to the
insulated substrate could pave the way for the development of single crystal
SiC-on-glass based MEMS applications.
| physics.app-ph cond-mat.mtrl-sci | this work reports the strain effect on the electrical properties of highly doped ntype single crystalline cubic silicon carbide 3csic transferred onto a 6inch glass substrate employing an anodic bonding technique the experimental data shows high gauge factors of 86 in longitudinal direction and 105 in transverse direction along the 100 orientation the piezoresistive effect in the highly doped 3csic film also exhibits an excellent linearity and consistent reproducibility after several bending cycles the experimental result was in good agreement with the theoretical analysis based on the phenomenon of electron transfer between many valleys in the conduction band of ntype 3csic our finding for the large gauge factor in ntype 3c sic coupled with the elimination of the current leak to the insulated substrate could pave the way for the development of single crystal siconglass based mems applications | [['this', 'work', 'reports', 'the', 'strain', 'effect', 'on', 'the', 'electrical', 'properties', 'of', 'highly', 'doped', 'ntype', 'single', 'crystalline', 'cubic', 'silicon', 'carbide', '3csic', 'transferred', 'onto', 'a', '6inch', 'glass', 'substrate', 'employing', 'an', 'anodic', 'bonding', 'technique', 'the', 'experimental', 'data', 'shows', 'high', 'gauge', 'factors', 'of', '86', 'in', 'longitudinal', 'direction', 'and', '105', 'in', 'transverse', 'direction', 'along', 'the', '100', 'orientation', 'the', 'piezoresistive', 'effect', 'in', 'the', 'highly', 'doped', '3csic', 'film', 'also', 'exhibits', 'an', 'excellent', 'linearity', 'and', 'consistent', 'reproducibility', 'after', 'several', 'bending', 'cycles', 'the', 'experimental', 'result', 'was', 'in', 'good', 'agreement', 'with', 'the', 'theoretical', 'analysis', 'based', 'on', 'the', 'phenomenon', 'of', 'electron', 'transfer', 'between', 'many', 'valleys', 'in', 'the', 'conduction', 'band', 'of', 'ntype', '3csic', 'our', 'finding', 'for', 'the', 'large', 'gauge', 'factor', 'in', 'ntype', '3c', 'sic', 'coupled', 'with', 'the', 'elimination', 'of', 'the', 'current', 'leak', 'to', 'the', 'insulated', 'substrate', 'could', 'pave', 'the', 'way', 'for', 'the', 'development', 'of', 'single', 'crystal', 'siconglass', 'based', 'mems', 'applications']] | [-0.11052295938644041, 0.13877879939637705, -0.03487789433748618, -0.0892232865261689, -0.02096992007449922, -0.14883122403161042, 0.06984046495852679, 0.45073419233552947, -0.23135271006311378, -0.31335872830483164, -0.007825574557208559, -0.3218747675010975, -0.1016315039872688, 0.22886366344118206, -0.016844136575848736, 0.03746407324053945, 0.043764287997615, -0.10269269747251686, -0.07349375217649949, -0.21215427106409504, 0.1872644640172213, 0.10909942909841508, 0.43651192716873477, 0.10928557007947434, 0.05503940633685077, 0.04481295990778038, 0.08233307590232278, -0.004003851796860677, -0.125193157925098, 0.11050684391147028, 0.2376932579221843, -0.11420533501536306, 0.19823766226479173, -0.481292255324767, -0.18350883339443347, -0.03874144012815434, 0.10176242461570803, 0.12990292016906244, -0.13894723910654821, -0.23100651916368, 0.06975834124660404, -0.11861751563881055, -0.11684906784951496, 0.0021364694379650763, -0.04394078092228105, -0.03582622342654606, -0.2028695120209366, 0.08863332121353426, 0.03766402790499647, 0.08584792435128433, -0.09939359901744844, -0.15270409256349027, -0.08903979477948462, 0.04693538639490513, 0.044224655745129515, 0.051705996957981455, 0.24391402285138186, -0.08725998822912356, -0.11476900421162, 0.36716422822707107, -0.07691692903699068, -0.11097451350445618, 0.16565097493534214, -0.1635062682721084, -0.09100471748324641, 0.1740801397364342, 0.11560552498499053, 0.08689530261785444, -0.1470372155206754, 0.044459920450467205, 0.007375350351153064, 0.18711395850269139, 0.09021306836664894, 0.06400581280972568, 0.22226509124203755, 0.24614067891966143, 0.019690552943498304, 0.14872603105843393, -0.11740261804733942, 0.010774882486511539, -0.20776125137272705, -0.1977500229985555, -0.19306482302014763, 0.08027553675189805, -0.15100411916415915, -0.19160574750743642, 0.43068819501552813, 0.11099598776570557, 0.1613051360948895, -0.08666396984680944, 0.2395768508954096, 0.02523973647481252, 0.08267718272106926, -0.0030089068841732984, 0.3154358747891103, 0.18677008952469612, 0.11580718835530272, -0.26995345987600483, 0.09127249615606818, -0.05483798280079598] |
1,802.07942 | Numerical integration in arbitrary-precision ball arithmetic | We present an implementation of arbitrary-precision numerical integration
with rigorous error bounds in the Arb library. Rapid convergence is ensured for
piecewise complex analytic integrals by use of the Petras algorithm, which
combines adaptive bisection with adaptive Gaussian quadrature where error
bounds are determined via complex magnitudes without evaluating derivatives.
The code is general, easy to use, and efficient, often outperforming existing
non-rigorous software.
| cs.MS cs.NA | we present an implementation of arbitraryprecision numerical integration with rigorous error bounds in the arb library rapid convergence is ensured for piecewise complex analytic integrals by use of the petras algorithm which combines adaptive bisection with adaptive gaussian quadrature where error bounds are determined via complex magnitudes without evaluating derivatives the code is general easy to use and efficient often outperforming existing nonrigorous software | [['we', 'present', 'an', 'implementation', 'of', 'arbitraryprecision', 'numerical', 'integration', 'with', 'rigorous', 'error', 'bounds', 'in', 'the', 'arb', 'library', 'rapid', 'convergence', 'is', 'ensured', 'for', 'piecewise', 'complex', 'analytic', 'integrals', 'by', 'use', 'of', 'the', 'petras', 'algorithm', 'which', 'combines', 'adaptive', 'bisection', 'with', 'adaptive', 'gaussian', 'quadrature', 'where', 'error', 'bounds', 'are', 'determined', 'via', 'complex', 'magnitudes', 'without', 'evaluating', 'derivatives', 'the', 'code', 'is', 'general', 'easy', 'to', 'use', 'and', 'efficient', 'often', 'outperforming', 'existing', 'nonrigorous', 'software']] | [-0.09064154367661104, -0.017685757282151826, -0.06484825009829365, 0.08354431749103242, -0.14656419420498423, -0.19728752071387134, 0.05499822995989234, 0.439437122317031, -0.22308544340194203, -0.29737804710748605, 0.1720792225569312, -0.1731620170394308, -0.16534392861649394, 0.28128482709871605, -0.09806734769153991, 0.14755092840641737, 0.11015612642950146, -0.05005498871469172, -0.11795288386929315, -0.280620696637925, 0.23870861160685308, 0.0889579110807972, 0.2363953876629239, -0.002471068572049262, 0.11159179810783826, 0.04594063492550049, -0.11520553562149871, -0.06285353563907847, -0.15442151539900806, 0.18270590190513758, 0.2587266249174718, 0.1489262617760687, 0.3110099878394976, -0.40044622877030633, -0.12898775756184477, 0.04201819338777568, 0.1817923244307167, 0.09578310909819265, -0.04591159296251135, -0.26430402175174095, 0.0831433973289677, -0.14418334716174286, -0.11973968116035394, -0.19176082663034322, -0.05427445397072006, 0.07172774791251868, -0.36557889863615856, 0.06347432441543788, -0.013936295203166083, 0.1395266240433557, 0.025143139479041565, -0.15078358506252698, 0.05961595181724988, 0.06894646148430184, -0.03523436774412403, 0.05112928750895662, 0.0915730224805884, -0.03240981475755689, -0.12941229568605195, 0.3136232731048949, -0.0761546245576028, -0.26641660986342686, 0.13688283596275141, -0.018171103300119285, -0.10308142790017882, 0.19851829911931418, 0.14747693091885594, 0.1260809878949658, -0.13077222460560733, 0.1394022790109375, 0.0767398855969077, 0.15390804344497155, 0.05173686378839193, -0.015269826336407277, 0.05269486689940095, 0.14537049385944556, 0.06445238759624772, 0.122585419259849, -0.01366524123295676, -0.17744162263988983, -0.30086864593613427, -0.13534002543747192, -0.2098123316609417, -0.035400490240135696, -0.1755645894297686, -0.23893703680005274, 0.33022930957667995, 0.15449963576975279, 0.07477642111189198, 0.17192301698560186, 0.4233537057880312, 0.1524088933947496, 0.05106203856121283, 0.18086550819862168, 0.18986858142307028, 0.10613866960557061, 0.043881874829821754, -0.1657054198003607, 0.09824479761300609, 0.13517667561245617] |
1,802.07943 | Exceptional Legendrian torus knots | We present classification results for exceptional Legendrian realisations of
torus knots. These are the first results of that kind for non-trivial
topological knot types. Enumeration results of Ding-Li-Zhang concerning tight
contact structures on certain Seifert fibred manifolds with boundary allow us
to place upper bounds on the number of tight contact structures on the
complements of torus knots; the classification of exceptional realisations of
these torus knots is then achieved by exhibiting sufficiently many realisations
in terms of contact surgery diagrams. We also discuss a couple of general
theorems about the existence of exceptional Legendrian knots.
| math.SG math.GT | we present classification results for exceptional legendrian realisations of torus knots these are the first results of that kind for nontrivial topological knot types enumeration results of dinglizhang concerning tight contact structures on certain seifert fibred manifolds with boundary allow us to place upper bounds on the number of tight contact structures on the complements of torus knots the classification of exceptional realisations of these torus knots is then achieved by exhibiting sufficiently many realisations in terms of contact surgery diagrams we also discuss a couple of general theorems about the existence of exceptional legendrian knots | [['we', 'present', 'classification', 'results', 'for', 'exceptional', 'legendrian', 'realisations', 'of', 'torus', 'knots', 'these', 'are', 'the', 'first', 'results', 'of', 'that', 'kind', 'for', 'nontrivial', 'topological', 'knot', 'types', 'enumeration', 'results', 'of', 'dinglizhang', 'concerning', 'tight', 'contact', 'structures', 'on', 'certain', 'seifert', 'fibred', 'manifolds', 'with', 'boundary', 'allow', 'us', 'to', 'place', 'upper', 'bounds', 'on', 'the', 'number', 'of', 'tight', 'contact', 'structures', 'on', 'the', 'complements', 'of', 'torus', 'knots', 'the', 'classification', 'of', 'exceptional', 'realisations', 'of', 'these', 'torus', 'knots', 'is', 'then', 'achieved', 'by', 'exhibiting', 'sufficiently', 'many', 'realisations', 'in', 'terms', 'of', 'contact', 'surgery', 'diagrams', 'we', 'also', 'discuss', 'a', 'couple', 'of', 'general', 'theorems', 'about', 'the', 'existence', 'of', 'exceptional', 'legendrian', 'knots']] | [-0.2922396552994063, 0.06393020524594345, -0.07944880362698122, 0.08448946782461318, -0.09917438361597689, -0.17122888717506277, 0.05718318854066494, 0.3840248638764024, -0.17548165421344733, -0.31750418058547536, 0.1086798165520457, -0.21070728785799522, -0.18699563649532042, 0.2874171507985968, -0.13045700718893816, 0.016108348862709183, 0.13207905750329557, 0.03188759756862725, -0.086865210177769, -0.30063133306409184, 0.40883076222319353, -0.0555286282869546, 0.14739415017201712, 0.10955674589219454, 0.07116213958514364, -0.025229720183108983, -0.030186279635190178, 0.012647255725766483, -0.28139724466056676, 0.1498103010370151, 0.22723454354625, -0.0028208868332991474, 0.05487477001979163, -0.39210335398583035, -0.17091193241312316, 0.13166310720537838, 0.15794566494755838, 0.01973578342677731, 0.01762025660320528, -0.2980159824125861, 0.06048099254870689, -0.1122283981720868, -0.18696710070791214, -0.10074261961210715, 0.0052130860815707, 0.06235756707426749, -0.10738216333924548, -0.002313079707336759, 0.11702168756409695, 0.09857232130200014, -0.023363560286203497, -0.07633253284852559, -0.02141790940475307, 0.1618102655108822, 0.051901378068386725, -0.02185491976622296, 0.08428200064717155, -0.18440664454706404, -0.1874936288100128, 0.33646284969229445, -0.02623606835688023, -0.2101579181261753, 0.23877633925723402, -0.14175197078209173, -0.26151259100848906, 0.24247937540670758, 0.10967788115928048, 0.1053687925009351, -0.03592101617618219, 0.09003621211618577, -0.1561528875333208, 0.06358194943321378, 0.14131964438741929, -0.00019131032688739268, 0.18102305434448154, 0.09726548313506339, 0.09540895881119037, 0.19320641094083457, -0.053294974026319226, -0.07864975934652121, -0.3747379092009444, -0.19887866973876953, -0.11390699278563261, 0.15204951791582924, -0.17068843866061223, -0.2022314862433919, 0.40250715367299944, 0.04166524773953777, 0.2063263619768948, 0.1413881883775742, 0.2220262563346248, 0.0037354952508681697, 0.06637020181668432, 0.06208478474107228, 0.17843509759067705, 0.20431856470133522, -0.06983244907797168, -0.06461799180037096, -0.034332353418300814, 0.19294295849180534] |
1,802.07944 | The Clever Shopper Problem | We investigate a variant of the so-called "Internet Shopping Problem"
introduced by Blazewicz et al. (2010), where a customer wants to buy a list of
products at the lowest possible total cost from shops which offer discounts
when purchases exceed a certain threshold. Although the problem is NP-hard, we
provide exact algorithms for several cases, e.g. when each shop sells only two
items, and an FPT algorithm for the number of items, or for the number of shops
when all prices are equal. We complement each result with hardness proofs in
order to draw a tight boundary between tractable and intractable cases.
Finally, we give an approximation algorithm and hardness results for the
problem of maximising the sum of discounts.
| cs.DS | we investigate a variant of the socalled internet shopping problem introduced by blazewicz et al 2010 where a customer wants to buy a list of products at the lowest possible total cost from shops which offer discounts when purchases exceed a certain threshold although the problem is nphard we provide exact algorithms for several cases eg when each shop sells only two items and an fpt algorithm for the number of items or for the number of shops when all prices are equal we complement each result with hardness proofs in order to draw a tight boundary between tractable and intractable cases finally we give an approximation algorithm and hardness results for the problem of maximising the sum of discounts | [['we', 'investigate', 'a', 'variant', 'of', 'the', 'socalled', 'internet', 'shopping', 'problem', 'introduced', 'by', 'blazewicz', 'et', 'al', '2010', 'where', 'a', 'customer', 'wants', 'to', 'buy', 'a', 'list', 'of', 'products', 'at', 'the', 'lowest', 'possible', 'total', 'cost', 'from', 'shops', 'which', 'offer', 'discounts', 'when', 'purchases', 'exceed', 'a', 'certain', 'threshold', 'although', 'the', 'problem', 'is', 'nphard', 'we', 'provide', 'exact', 'algorithms', 'for', 'several', 'cases', 'eg', 'when', 'each', 'shop', 'sells', 'only', 'two', 'items', 'and', 'an', 'fpt', 'algorithm', 'for', 'the', 'number', 'of', 'items', 'or', 'for', 'the', 'number', 'of', 'shops', 'when', 'all', 'prices', 'are', 'equal', 'we', 'complement', 'each', 'result', 'with', 'hardness', 'proofs', 'in', 'order', 'to', 'draw', 'a', 'tight', 'boundary', 'between', 'tractable', 'and', 'intractable', 'cases', 'finally', 'we', 'give', 'an', 'approximation', 'algorithm', 'and', 'hardness', 'results', 'for', 'the', 'problem', 'of', 'maximising', 'the', 'sum', 'of', 'discounts']] | [-0.0960091889318384, 0.04449047171143901, -0.0072159085250577005, 0.08693362359728414, -0.12412687403564694, -0.18828801858090177, 0.1803856089695537, 0.4030041947585194, -0.2726879914627731, -0.3470484233390884, 0.11134311244842604, -0.31797106006816656, -0.1227745148920681, 0.19531347934242746, -0.10578071080469095, 0.03090519252225381, 0.0713351908875551, 0.0659710744989179, 0.004610304326452941, -0.3742540196648666, 0.27470657341045274, 0.025120193146544845, 0.22378571691508053, 0.08313751138918915, 0.09118259979310218, 0.04079123606470985, -0.00352306298308951, 0.04118221202111845, -0.16679445731046633, 0.09290203380206709, 0.29792198156859695, 0.17492663401703373, 0.3574700479810478, -0.42119718757027585, -0.07951651268810847, 0.1844740341370534, 0.08316463418537262, 0.06628195763303421, 0.014336236959965038, -0.21160360586931223, 0.07535130599858005, -0.19525386085498983, -0.06213391722892137, -0.008832590523402855, 0.04457689657564737, 0.03900641994942136, -0.31865592696117, 0.005290996090082468, 0.010606523712768275, -0.01172478063454648, -0.05366358845964262, -0.161123850122642, 0.04467046735886516, 0.16648657205137973, 0.07849609308818378, -0.023191418113312174, 0.05485646906034911, -0.16479033667656803, -0.16063134304733023, 0.41293010841115935, 0.035491651051752116, -0.1596963877198795, 0.12162866680139378, -0.05708688141840721, -0.14754323688034407, 0.13625287094756083, 0.1753801183086358, 0.12674324872058293, -0.1137972288654223, 0.05065340516910724, -0.12480924914281878, 0.13003955921158195, 0.12338924337131511, 0.007091158365110765, 0.13296553572373732, 0.12371628376960504, 0.17760194216839217, 0.1762580545873483, 0.007367353819842849, -0.07104009331474002, -0.2502612343934529, -0.155754424978885, -0.17238339323436982, 0.02979871293064207, -0.12253571064918235, -0.17239043518838262, 0.34335660909404275, 0.14296189923340283, 0.19199332491956464, 0.13676005195798902, 0.31748091533756617, 0.10174317968649273, -0.034783954624509235, 0.17225134918982743, 0.14363243511854476, 0.040714276558328266, 0.07552959118038416, -0.1352946933793264, 0.1253668410124398, 0.08739056421772522] |
1,802.07945 | Actigraphy-based Sleep/Wake Pattern Detection using Convolutional Neural
Networks | Common medical conditions are often associated with sleep abnormalities.
Patients with medical disorders often suffer from poor sleep quality compared
to healthy individuals, which in turn may worsen the symptoms of the disorder.
Accurate detection of sleep/wake patterns is important in developing
personalized digital markers, which can be used for objective measurements and
efficient disease management. Big Data technologies and advanced analytics
methods hold the promise to revolutionize clinical research processes, enabling
the effective blending of digital data into clinical trials. Actigraphy, a
non-invasive activity monitoring method is heavily used to detect and evaluate
activities and movement disorders, and assess sleep/wake behavior. In order to
study the connection between sleep/wake patterns and a cluster headache
disorder, activity data was collected using a wearable device in the course of
a clinical trial. This study presents two novel modeling schemes that utilize
Deep Convolutional Neural Networks (CNN) to identify sleep/wake states. The
proposed methods are a sequential CNN, reminiscent of the bi-directional CNN
for slot filling, and a Multi-Task Learning (MTL) based model. Furthermore, we
expand standard "Sleep" and "Wake" activity states space by adding the "Falling
asleep" and "Siesta" states. We show that the proposed methods provide
promising results in accurate detection of the expanded sleep/wake states.
Finally, we explore the relations between the detected sleep/wake patterns and
onset of cluster headache attacks, and present preliminary observations.
| cs.LG | common medical conditions are often associated with sleep abnormalities patients with medical disorders often suffer from poor sleep quality compared to healthy individuals which in turn may worsen the symptoms of the disorder accurate detection of sleepwake patterns is important in developing personalized digital markers which can be used for objective measurements and efficient disease management big data technologies and advanced analytics methods hold the promise to revolutionize clinical research processes enabling the effective blending of digital data into clinical trials actigraphy a noninvasive activity monitoring method is heavily used to detect and evaluate activities and movement disorders and assess sleepwake behavior in order to study the connection between sleepwake patterns and a cluster headache disorder activity data was collected using a wearable device in the course of a clinical trial this study presents two novel modeling schemes that utilize deep convolutional neural networks cnn to identify sleepwake states the proposed methods are a sequential cnn reminiscent of the bidirectional cnn for slot filling and a multitask learning mtl based model furthermore we expand standard sleep and wake activity states space by adding the falling asleep and siesta states we show that the proposed methods provide promising results in accurate detection of the expanded sleepwake states finally we explore the relations between the detected sleepwake patterns and onset of cluster headache attacks and present preliminary observations | [['common', 'medical', 'conditions', 'are', 'often', 'associated', 'with', 'sleep', 'abnormalities', 'patients', 'with', 'medical', 'disorders', 'often', 'suffer', 'from', 'poor', 'sleep', 'quality', 'compared', 'to', 'healthy', 'individuals', 'which', 'in', 'turn', 'may', 'worsen', 'the', 'symptoms', 'of', 'the', 'disorder', 'accurate', 'detection', 'of', 'sleepwake', 'patterns', 'is', 'important', 'in', 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1,802.07946 | SecDec: a toolbox for the numerical evaluation of multi-scale integrals | We present a new version of $\texttt{SecDec}$, a program for the numerical
computation of parametric integrals in the context of dimensional
regularization. By its modular structure, the $\texttt{python}$ rewrite
$\texttt{pySecDec}$ is much more customizable than earlier versions of
$\texttt{SecDec}$. The numerical integration is accelerated using code
optimization available in $\texttt{FORM}$. With the new $\texttt{C++}$
interface, $\texttt{pySecDec}$ can provide numerical solutions of analytically
unknown integrals in user-defined code.
| hep-ph | we present a new version of textttsecdec a program for the numerical computation of parametric integrals in the context of dimensional regularization by its modular structure the textttpython rewrite textttpysecdec is much more customizable than earlier versions of textttsecdec the numerical integration is accelerated using code optimization available in textttform with the new textttc interface textttpysecdec can provide numerical solutions of analytically unknown integrals in userdefined code | [['we', 'present', 'a', 'new', 'version', 'of', 'textttsecdec', 'a', 'program', 'for', 'the', 'numerical', 'computation', 'of', 'parametric', 'integrals', 'in', 'the', 'context', 'of', 'dimensional', 'regularization', 'by', 'its', 'modular', 'structure', 'the', 'textttpython', 'rewrite', 'textttpysecdec', 'is', 'much', 'more', 'customizable', 'than', 'earlier', 'versions', 'of', 'textttsecdec', 'the', 'numerical', 'integration', 'is', 'accelerated', 'using', 'code', 'optimization', 'available', 'in', 'textttform', 'with', 'the', 'new', 'textttc', 'interface', 'textttpysecdec', 'can', 'provide', 'numerical', 'solutions', 'of', 'analytically', 'unknown', 'integrals', 'in', 'userdefined', 'code']] | [-0.1401027791434899, 0.002555686810482589, -0.10392159547301985, 0.07979706369177808, -0.10742761981156138, -0.14178430851519344, 0.0002548880025093991, 0.3683621629717804, -0.2567741640266918, -0.2902003585671385, 0.14718485692523361, -0.20200066696224173, -0.12754261310005355, 0.25557650956842637, -0.034942251267484466, 0.10178687084846878, 0.11616311893458404, -0.02790417226857417, -0.11706102498999191, -0.2518406400368327, 0.3072169119166949, 0.1050233453926113, 0.16682376962761203, -0.011950769328645297, 0.06756338873316371, 0.012761970072807301, -0.06480761261154262, -0.017441981605121067, -0.13596604506499946, 0.1990968769856004, 0.23568042373979495, 0.16585884292033456, 0.27994359168224037, -0.42445930610928273, -0.19620233317393632, -0.017839607753096117, 0.1838241703762111, 0.1169402174622057, -0.061741537522822104, -0.24713833449733635, 0.06061835553024023, -0.20426446113676305, -0.11620701335754896, -0.1507683057811052, -0.03945923460617898, 0.01202813593212456, -0.2658903543617473, 0.04275979763931698, -0.032605670259467194, 0.08155686637416246, -0.05676005243892885, -0.09962148173520016, -0.001435611042238417, 0.03932921134585899, 0.0003202414263796527, 0.022662373747499215, 0.04755647274266396, -0.10679150912469523, -0.14774627652433184, 0.35749270889579154, -0.04573109480649388, -0.2659204044926261, 0.16215528517458883, -0.07004399593949082, -0.1264024521741602, 0.1574269381780473, 0.17634005675328865, 0.18727071524139435, -0.17380610779611513, 0.1270100024440104, -0.01622977236374503, 0.1570468997316701, 0.04047516935194532, -0.03115903255751445, 0.12791310693137348, 0.1693763000121902, 0.03929112659442046, 0.23792086328778947, -0.0020797868067073443, -0.12875248492503213, -0.3466070496610233, -0.19220427531630746, -0.1488402679022993, -0.006043981147250013, -0.11948852499739991, -0.18533433435691726, 0.4063458034088687, 0.16968651663138723, 0.09212414878937933, 0.09036761736645112, 0.3287481094400088, 0.1464771838223059, 0.11789011490339088, 0.11358559814592202, 0.1779756511058954, 0.07724892621904257, 0.09047997408797817, -0.1825577471227873, 0.05233055998438171, 0.13078410199118984] |
1,802.07947 | A two-way photonic interface for linking Sr+ transition at 422 nm to the
telecommunications C-band | We report a single-stage bi-directional interface capable of linking Sr+
trapped ion qubits in a long-distance quantum network. Our interface converts
photons between the Sr+ emission wavelength at 422 nm and the telecoms C-band
to enable low-loss transmission over optical fiber. We have achieved both up-
and down-conversion at the single photon level with efficiencies of 9.4% and
1.1% respectively. Furthermore we demonstrate noise levels that are low enough
to allow for genuine quantum operation in the future.
| quant-ph | we report a singlestage bidirectional interface capable of linking sr trapped ion qubits in a longdistance quantum network our interface converts photons between the sr emission wavelength at 422 nm and the telecoms cband to enable lowloss transmission over optical fiber we have achieved both up and downconversion at the single photon level with efficiencies of 94 and 11 respectively furthermore we demonstrate noise levels that are low enough to allow for genuine quantum operation in the future | [['we', 'report', 'a', 'singlestage', 'bidirectional', 'interface', 'capable', 'of', 'linking', 'sr', 'trapped', 'ion', 'qubits', 'in', 'a', 'longdistance', 'quantum', 'network', 'our', 'interface', 'converts', 'photons', 'between', 'the', 'sr', 'emission', 'wavelength', 'at', '422', 'nm', 'and', 'the', 'telecoms', 'cband', 'to', 'enable', 'lowloss', 'transmission', 'over', 'optical', 'fiber', 'we', 'have', 'achieved', 'both', 'up', 'and', 'downconversion', 'at', 'the', 'single', 'photon', 'level', 'with', 'efficiencies', 'of', '94', 'and', '11', 'respectively', 'furthermore', 'we', 'demonstrate', 'noise', 'levels', 'that', 'are', 'low', 'enough', 'to', 'allow', 'for', 'genuine', 'quantum', 'operation', 'in', 'the', 'future']] | [-0.1247977244739349, 0.1658773630594787, 0.013093127642208949, -0.04442189815334785, 0.0491425741243009, -0.2382922488837861, 0.10452939810541768, 0.5010665802237315, -0.20605390767256418, -0.31431415419762904, 0.01076081106498933, -0.28839559924717134, -0.044635500746946305, 0.26301169893346155, -0.0023071060169082233, 0.07035570888994978, 0.042406247761578135, -0.05092729930467426, -0.014686968592473138, -0.16331250156061008, 0.21875648353195104, 0.08954649665751137, 0.3504217986542827, 0.08443730650469661, 0.183334399599773, -0.0070609299888392575, 0.03322483118599615, -0.10192273872552249, -0.043248910519674284, 0.13456777478448856, 0.29132400155783844, 0.03604777988631469, 0.21358112815337685, -0.42685674521952677, -0.19864749963072917, 0.04445317221763663, 0.14137372526770028, 0.15712781387339467, -0.03592600223297874, -0.27269618202430695, 0.11313310542773718, -0.1625035400621784, -0.038606187830177635, -0.045937877730466425, -0.04406054479141648, -0.00933406862597435, -0.2539592399142491, 0.03731011661390463, 0.01864024514827925, 0.07098715142227519, 0.029186437234807856, -0.020547325973613903, -0.0073587430539564826, 0.10454724694435032, -0.14590771311523917, -0.012536983102342138, 0.1500901268162311, -0.11518055390423307, -0.13540334340471488, 0.33582461205048436, -0.12935992816570574, -0.08367934236780573, 0.17998998748281828, -0.16783512278627127, -0.036712631051882334, 0.1927494145870113, 0.16835070056363177, 0.0807302674660698, -0.10643458656536844, -0.010093662218050433, 0.0715301290858919, 0.25721442781767295, 0.1466184578035982, 0.17666257148345885, 0.254458518854032, 0.16473744715301272, 0.022547786365836285, 0.1544108478300563, -0.23008124038386038, -0.034906621917915076, -0.2843733462027441, -0.190289605435772, -0.11228519194544508, 0.06312059033184479, -0.07974522553614896, -0.055576961230820954, 0.39619714533910155, 0.16281759321170214, 0.14274653473582405, 0.04518278550881988, 0.2786598903580736, 0.09264775362755291, 0.07717227529829894, 0.08416291260017225, 0.30748838094922787, 0.11929833465136397, 0.12766413179745612, -0.22940203814934462, -0.04632468269063303, -0.06720498944513309] |
1,802.07948 | Homological stability and densities of generalized configuration spaces | We prove that the factorization homologies of a scheme with coefficients in
truncated polynomial algebras compute the cohomologies of its generalized
configuration spaces. Using Koszul duality between commutative algebras and Lie
algebras, we obtain new expressions for the cohomologies of the latter. As a
consequence, we obtain a uniform and conceptual approach for treating
homological stability, homological densities, and arithmetic densities of
generalized configuration spaces. Our results categorify, generalize, and in
fact provide a conceptual understanding of the coincidences appearing in the
work of Farb--Wolfson--Wood. Our computation of the stable homological
densities also yields rational homotopy types which answer a question posed by
Vakil--Wood. Our approach hinges on the study of homological stability of
cohomological Chevalley complexes, which is of independent interest.
| math.AG math.AT math.NT | we prove that the factorization homologies of a scheme with coefficients in truncated polynomial algebras compute the cohomologies of its generalized configuration spaces using koszul duality between commutative algebras and lie algebras we obtain new expressions for the cohomologies of the latter as a consequence we obtain a uniform and conceptual approach for treating homological stability homological densities and arithmetic densities of generalized configuration spaces our results categorify generalize and in fact provide a conceptual understanding of the coincidences appearing in the work of farbwolfsonwood our computation of the stable homological densities also yields rational homotopy types which answer a question posed by vakilwood our approach hinges on the study of homological stability of cohomological chevalley complexes which is of independent interest | [['we', 'prove', 'that', 'the', 'factorization', 'homologies', 'of', 'a', 'scheme', 'with', 'coefficients', 'in', 'truncated', 'polynomial', 'algebras', 'compute', 'the', 'cohomologies', 'of', 'its', 'generalized', 'configuration', 'spaces', 'using', 'koszul', 'duality', 'between', 'commutative', 'algebras', 'and', 'lie', 'algebras', 'we', 'obtain', 'new', 'expressions', 'for', 'the', 'cohomologies', 'of', 'the', 'latter', 'as', 'a', 'consequence', 'we', 'obtain', 'a', 'uniform', 'and', 'conceptual', 'approach', 'for', 'treating', 'homological', 'stability', 'homological', 'densities', 'and', 'arithmetic', 'densities', 'of', 'generalized', 'configuration', 'spaces', 'our', 'results', 'categorify', 'generalize', 'and', 'in', 'fact', 'provide', 'a', 'conceptual', 'understanding', 'of', 'the', 'coincidences', 'appearing', 'in', 'the', 'work', 'of', 'farbwolfsonwood', 'our', 'computation', 'of', 'the', 'stable', 'homological', 'densities', 'also', 'yields', 'rational', 'homotopy', 'types', 'which', 'answer', 'a', 'question', 'posed', 'by', 'vakilwood', 'our', 'approach', 'hinges', 'on', 'the', 'study', 'of', 'homological', 'stability', 'of', 'cohomological', 'chevalley', 'complexes', 'which', 'is', 'of', 'independent', 'interest']] | [-0.1482291259414827, 0.02022993613112097, -0.13254223572245488, 0.11191196524014231, -0.07823533758055419, -0.12726731304234515, 0.0021539502427913248, 0.30619984537673495, -0.32550977608577036, -0.2341773752103715, 0.08566250947672718, -0.14820978017135833, -0.17379820197820664, 0.18480347984780868, -0.17120036550695658, -0.03892198638107705, 0.0529853001217513, 0.05993669312277537, -0.1269160764233675, -0.2930876266308284, 0.4148670107941143, -0.0017555112795283397, 0.23383104707212019, 0.09756475817994215, 0.13682477096638954, 0.020704682889239243, -0.0498769984425356, -0.0242863288197744, -0.19168148828739504, 0.1958967161733502, 0.3228934607061092, 0.061072959029540165, 0.2056180560835249, -0.3714816706410299, -0.114839970615382, 0.11959722869408627, 0.15352942545335585, 0.055609203225079305, -0.045949620508084384, -0.2848756649220983, 0.09966919864527882, -0.19683816974672178, -0.17023213959376637, -0.14657411365769804, 0.019090484734624623, 0.0462268252527186, -0.24704975589799386, 0.027067602140353603, 0.10728978617116809, 0.13111169124798228, -0.11384360663456998, -0.10291402526199818, -0.03315741418433996, 0.09643217984897395, -0.02948006966975451, -0.020590325670006373, 0.09197572241925324, -0.0971723722682024, -0.19993640823910633, 0.34743490697195134, 0.01260925038077403, -0.23920702897012233, 0.1356787081497411, -0.15520408742207412, -0.21215791568004835, 0.08602825718310972, 0.0451208047180747, 0.1752000706580778, -0.011243838320175807, 0.1643543989455793, -0.12423390102727959, 0.04870963073529613, 0.13587400369967023, 0.06894517750867332, 0.13067390396123907, 0.11285552352977296, 0.07242044360221674, 0.16048829144371363, 0.04064812634023838, -0.085275188475498, -0.331681317742914, -0.20686980770357574, -0.11016093979900082, 0.11144468115720277, -0.14372195155156078, -0.18049211777591456, 0.4181674460250785, 0.13797130478390804, 0.17515411160420627, 0.17202748422860167, 0.26172970872527607, 0.06268648137144434, 0.0439638762230364, -0.006164067925419658, 0.14899381600941222, 0.30381567846246377, 0.029666659072972834, -0.11897456646353627, -0.028931957945072403, 0.26239234470995143] |
1,802.07949 | Surface Interaction Effects to a Klein-Gordon Particle Embedded in a
Woods-Saxon Potential Well in terms of Thermodynamic Functions | Recently, it has been investigated how the thermodynamic functions vary when
the surface interactions are taken into account for a nucleon which is confined
in a Woods-Saxon potential well, with a non-relativistic point of view. In this
manuscript, the same problem is handled with a relativistic point of view. More
precisely, the Klein-Gordon equation is solved in presence of mixed
scalar-vector generalized symmetric Woods-Saxon potential energy that is
coupled to momentum and mass. Employing the continuity conditions the bound
state energy spectra of an arbitrarily parameterized well are derived. It is
observed that, when a term representing the surface effect is taken into
account, the character of Helmholtz free energy and entropy versus temperature
are modified in a similar fashion as this inclusion is done in the
non-relativistic regime. Whereas it is found that this inclusion leads to
different characters to internal energy and specific heat functions for
relativistic and non-relativistic regimes.
| nucl-th | recently it has been investigated how the thermodynamic functions vary when the surface interactions are taken into account for a nucleon which is confined in a woodssaxon potential well with a nonrelativistic point of view in this manuscript the same problem is handled with a relativistic point of view more precisely the kleingordon equation is solved in presence of mixed scalarvector generalized symmetric woodssaxon potential energy that is coupled to momentum and mass employing the continuity conditions the bound state energy spectra of an arbitrarily parameterized well are derived it is observed that when a term representing the surface effect is taken into account the character of helmholtz free energy and entropy versus temperature are modified in a similar fashion as this inclusion is done in the nonrelativistic regime whereas it is found that this inclusion leads to different characters to internal energy and specific heat functions for relativistic and nonrelativistic regimes | [['recently', 'it', 'has', 'been', 'investigated', 'how', 'the', 'thermodynamic', 'functions', 'vary', 'when', 'the', 'surface', 'interactions', 'are', 'taken', 'into', 'account', 'for', 'a', 'nucleon', 'which', 'is', 'confined', 'in', 'a', 'woodssaxon', 'potential', 'well', 'with', 'a', 'nonrelativistic', 'point', 'of', 'view', 'in', 'this', 'manuscript', 'the', 'same', 'problem', 'is', 'handled', 'with', 'a', 'relativistic', 'point', 'of', 'view', 'more', 'precisely', 'the', 'kleingordon', 'equation', 'is', 'solved', 'in', 'presence', 'of', 'mixed', 'scalarvector', 'generalized', 'symmetric', 'woodssaxon', 'potential', 'energy', 'that', 'is', 'coupled', 'to', 'momentum', 'and', 'mass', 'employing', 'the', 'continuity', 'conditions', 'the', 'bound', 'state', 'energy', 'spectra', 'of', 'an', 'arbitrarily', 'parameterized', 'well', 'are', 'derived', 'it', 'is', 'observed', 'that', 'when', 'a', 'term', 'representing', 'the', 'surface', 'effect', 'is', 'taken', 'into', 'account', 'the', 'character', 'of', 'helmholtz', 'free', 'energy', 'and', 'entropy', 'versus', 'temperature', 'are', 'modified', 'in', 'a', 'similar', 'fashion', 'as', 'this', 'inclusion', 'is', 'done', 'in', 'the', 'nonrelativistic', 'regime', 'whereas', 'it', 'is', 'found', 'that', 'this', 'inclusion', 'leads', 'to', 'different', 'characters', 'to', 'internal', 'energy', 'and', 'specific', 'heat', 'functions', 'for', 'relativistic', 'and', 'nonrelativistic', 'regimes']] | [-0.10194570056122948, 0.15819278082735286, -0.11712779674417106, 0.10986310456907009, -0.048550309290141355, -0.14619561197162656, -0.021402116018610907, 0.338763051194531, -0.25556600173494143, -0.29350808779954124, 0.017653389943389858, -0.27013220543066335, -0.07525920179231387, 0.1696661143122535, 0.003980552749692977, 0.01787454625101466, 0.0504514322245469, 0.05883441421840536, -0.0802402387075984, -0.18879817128426543, 0.3444484212791155, 0.0649108155469692, 0.25351217633578926, 0.09336989789306627, 0.0844241175555477, 0.012621934840449524, 0.03391917887462401, 0.07390746806662432, -0.10070503062845666, 0.050847835975889065, 0.222548106983978, 0.01722132653077623, 0.24421450815249332, -0.424463660848376, -0.2641512477329295, 0.09654963540685314, 0.12942453496170378, 0.12066359699498494, -0.04252379548348759, -0.26875157979022907, 0.02716291498233515, -0.1829670505356166, -0.17023158087517673, -0.06788424517358899, 0.029530015051070797, 0.011464964099056823, -0.2658834309243646, 0.11343764250724282, 0.04954919014064791, 5.193742751879128e-05, -0.1409531000076401, -0.127562798913507, -0.05308701242258968, 0.08721102162235184, 0.06324016929245677, 0.05720269264910664, 0.09833066203435392, -0.128933807261714, -0.010331199960905667, 0.4341418458957617, -0.04498522102757737, -0.2560199674856114, 0.1420284449283683, -0.12478277136841298, -0.08668062952959812, 0.12460277573125877, 0.14038734681794027, 0.1063941758750987, -0.19713185498844005, 0.1374990434958722, -0.03025129754601757, 0.12746585140695588, 0.07664053025349092, 0.023848639344673996, 0.19097578052223022, 0.1365360548186704, 0.004243031554659338, 0.1589677714938788, -0.05971577587402671, -0.15226101787074617, -0.3075076640387507, -0.1229000214788309, -0.1952185337967852, 0.04280273465280372, -0.046559792146389986, -0.1502454940713697, 0.3744626972069167, 0.07694453918108927, 0.16951525235230006, -0.002281510590508237, 0.28351262753437223, 0.23097201222844888, 0.06975648869564266, 0.07899629811780821, 0.25588896290374624, 0.13949041648945576, 0.0940328668067722, -0.22247921853130193, -0.000544224586950517, 0.06455613739825294] |
1,802.0795 | Photoinduced enhancement of excitonic order in the two-orbital Hubbard
model | Photoinduced dynamics in an excitonic insulator is studied theoretically by
using a two-orbital Hubbard model on the square lattice where the excitonic
phase in the ground state is characterized by the BCS-BEC crossover as a
function of the interorbital Coulomb interaction. We consider the case where
the order has a wave vector $Q=(0,0)$ and photoexcitation is introduced by a
dipole transition. Within the mean-field approximation, we show that the
excitonic order can be enhanced by the photoexcitation when the system is
initially in the BEC regime of the excitonic phase, whereas it is reduced if
the system is initially in the BCS regime. The origin of this difference is
discussed from behaviors of momentum distribution functions and
momentum-dependent excitonic pair condensation. In particular, we show that the
phases of the excitonic pair condensation have an important role in determining
whether the excitonic order is enhanced or not.
| cond-mat.str-el | photoinduced dynamics in an excitonic insulator is studied theoretically by using a twoorbital hubbard model on the square lattice where the excitonic phase in the ground state is characterized by the bcsbec crossover as a function of the interorbital coulomb interaction we consider the case where the order has a wave vector q00 and photoexcitation is introduced by a dipole transition within the meanfield approximation we show that the excitonic order can be enhanced by the photoexcitation when the system is initially in the bec regime of the excitonic phase whereas it is reduced if the system is initially in the bcs regime the origin of this difference is discussed from behaviors of momentum distribution functions and momentumdependent excitonic pair condensation in particular we show that the phases of the excitonic pair condensation have an important role in determining whether the excitonic order is enhanced or not | [['photoinduced', 'dynamics', 'in', 'an', 'excitonic', 'insulator', 'is', 'studied', 'theoretically', 'by', 'using', 'a', 'twoorbital', 'hubbard', 'model', 'on', 'the', 'square', 'lattice', 'where', 'the', 'excitonic', 'phase', 'in', 'the', 'ground', 'state', 'is', 'characterized', 'by', 'the', 'bcsbec', 'crossover', 'as', 'a', 'function', 'of', 'the', 'interorbital', 'coulomb', 'interaction', 'we', 'consider', 'the', 'case', 'where', 'the', 'order', 'has', 'a', 'wave', 'vector', 'q00', 'and', 'photoexcitation', 'is', 'introduced', 'by', 'a', 'dipole', 'transition', 'within', 'the', 'meanfield', 'approximation', 'we', 'show', 'that', 'the', 'excitonic', 'order', 'can', 'be', 'enhanced', 'by', 'the', 'photoexcitation', 'when', 'the', 'system', 'is', 'initially', 'in', 'the', 'bec', 'regime', 'of', 'the', 'excitonic', 'phase', 'whereas', 'it', 'is', 'reduced', 'if', 'the', 'system', 'is', 'initially', 'in', 'the', 'bcs', 'regime', 'the', 'origin', 'of', 'this', 'difference', 'is', 'discussed', 'from', 'behaviors', 'of', 'momentum', 'distribution', 'functions', 'and', 'momentumdependent', 'excitonic', 'pair', 'condensation', 'in', 'particular', 'we', 'show', 'that', 'the', 'phases', 'of', 'the', 'excitonic', 'pair', 'condensation', 'have', 'an', 'important', 'role', 'in', 'determining', 'whether', 'the', 'excitonic', 'order', 'is', 'enhanced', 'or', 'not']] | [-0.16288707340072814, 0.24218475191594976, -0.06737010797397011, 0.07616190305280619, 0.02536259659369584, -0.10323740390515855, 0.054104880073430894, 0.38014954289256714, -0.25237937634303964, -0.21876518168569017, 0.016110047886502884, -0.3008688850277642, -0.17771538302498763, 0.08826945835825842, 0.08522551147533315, -0.013325859390224527, -0.03068148731917787, 0.006327701513940583, -0.06553809001066145, -0.2235888684640455, 0.3800030949899331, -0.0006689515224575591, 0.26941625044053913, 0.12286930888349533, 0.030265817146266805, 0.01689608842704673, 0.1505199691033637, -0.008739071258274065, -0.13474139125218226, 0.01320938749530283, 0.24616221954205017, -0.05342540207325297, 0.2641492538078099, -0.38642218546168944, -0.22213697528821372, 0.06553261370879604, 0.18214553540103695, 0.16161529642852898, -0.044815079044537985, -0.3084522049262689, 0.01597783396647749, -0.2085376151482619, -0.11029150251767972, -0.06666628232061052, 0.018636055095881527, 0.012971689405084467, -0.2723430326829354, 0.09232342004345186, 0.06579671423964607, 0.033366527954800704, -0.07957622611920545, -0.06812766254372692, -0.06669716755891232, 0.05770683552231164, 0.016507399802216563, 0.06705397106453675, 0.09648606715546477, -0.1693371023704, -0.07035652184415431, 0.4140167861803099, -0.09343618494030849, -0.12626464255027423, 0.12136783989995313, -0.17782582666696806, -0.008530791839394642, 0.17112996352545054, 0.08865188191990134, 0.08871073270102545, -0.12629755783311747, 0.11388751010641734, -0.045858007247403715, 0.18143151802181892, -0.01321798810049524, 0.08271394412153635, 0.22094521172412793, 0.2191746332872735, 0.04482499704708909, 0.1806304446765266, -0.11130833813166689, -0.15444389745105236, -0.2644722496514164, -0.12972861193563967, -0.2620657068632898, 0.029769984079084554, -0.012476960215899701, -0.1468060345319258, 0.4206907219741712, 0.12971702665264787, 0.1877197791793745, -0.07342578848937945, 0.2450065704198795, 0.22305453224915403, 0.017874582882869205, 0.01664828709532589, 0.2994730731497715, 0.1344517685289235, 0.06303730739762081, -0.32610753587079644, 0.07748312628226114, 0.0925272042486107] |
1,802.07951 | The maximal abelian dimension of a Lie algebra, Rentschler's property
and Milovanov's conjecture | A finite dimensional Lie algebra L with magic number c(L) is said to satisfy
Rentschler's property if it admits an abelian Lie subalgebra H of dimension at
least c(L) - 1. We study the occurrence of this new property in various Lie
algebras, such as nonsolvable, solvable, nilpotent, metabelian and filiform Lie
algebras. Under some mild condition H gives rise to a complete Poisson
commutative subalgebra of the symmetric algebra S(L). Using this, we show that
Milovanov's conjecture holds for the filiform Lie algebras of type Ln, Qn, Rn,
Wn and also for all filiform Lie algebras of dimension at most eight. For the
latter the Poisson center of these Lie algebras is determined.
| math.RT | a finite dimensional lie algebra l with magic number cl is said to satisfy rentschlers property if it admits an abelian lie subalgebra h of dimension at least cl 1 we study the occurrence of this new property in various lie algebras such as nonsolvable solvable nilpotent metabelian and filiform lie algebras under some mild condition h gives rise to a complete poisson commutative subalgebra of the symmetric algebra sl using this we show that milovanovs conjecture holds for the filiform lie algebras of type ln qn rn wn and also for all filiform lie algebras of dimension at most eight for the latter the poisson center of these lie algebras is determined | [['a', 'finite', 'dimensional', 'lie', 'algebra', 'l', 'with', 'magic', 'number', 'cl', 'is', 'said', 'to', 'satisfy', 'rentschlers', 'property', 'if', 'it', 'admits', 'an', 'abelian', 'lie', 'subalgebra', 'h', 'of', 'dimension', 'at', 'least', 'cl', '1', 'we', 'study', 'the', 'occurrence', 'of', 'this', 'new', 'property', 'in', 'various', 'lie', 'algebras', 'such', 'as', 'nonsolvable', 'solvable', 'nilpotent', 'metabelian', 'and', 'filiform', 'lie', 'algebras', 'under', 'some', 'mild', 'condition', 'h', 'gives', 'rise', 'to', 'a', 'complete', 'poisson', 'commutative', 'subalgebra', 'of', 'the', 'symmetric', 'algebra', 'sl', 'using', 'this', 'we', 'show', 'that', 'milovanovs', 'conjecture', 'holds', 'for', 'the', 'filiform', 'lie', 'algebras', 'of', 'type', 'ln', 'qn', 'rn', 'wn', 'and', 'also', 'for', 'all', 'filiform', 'lie', 'algebras', 'of', 'dimension', 'at', 'most', 'eight', 'for', 'the', 'latter', 'the', 'poisson', 'center', 'of', 'these', 'lie', 'algebras', 'is', 'determined']] | [-0.1801324072923209, 0.08007278944995476, -0.0014391372920022354, 0.05215940172238662, -0.19300147240377358, -0.21817800944654253, -0.05617460152889426, 0.38806165231240763, -0.33382030373107774, -0.16626675564560806, 0.13610500069062417, -0.2182343621624986, -0.09310290810593345, 0.18831828980798926, -0.12446817340379632, -0.12458669448267198, 0.04797619386567726, 0.20669227294825218, -0.11506699299154517, -0.3171906123726486, 0.4050096125753076, -0.028718650325826527, 0.20009812347691608, -0.015134233719698648, 0.1430578347765379, -0.0009027133687390937, 0.06080334026551059, -0.016619797770840092, -0.18497750545079192, 0.041974536076645357, 0.3225486541255, 0.05188849369097535, 0.19829895512226062, -0.3004014858522931, -0.05509597280373176, 0.2390355741361844, 0.19117967433061217, -0.022115682302093185, -0.046718603524438164, -0.24178539037385638, 0.12348362710022107, -0.23388652201439883, -0.21034115550385132, -0.008347231726925652, 0.12037161064778899, -0.08882524755464548, -0.24121566941156178, 0.07876813164802042, 0.13886029561897656, 0.15520764214703409, -0.09822678926551866, -0.13404906383541995, -0.12489065413073813, 0.008813396790526338, -0.12482763810486004, -0.03082826182556649, 0.09417131244465038, -0.0165709660749443, -0.1764459824965646, 0.3988803978757681, 0.029612007206893182, -0.18727082001996595, 0.14745053182448353, -0.26526518187879977, -0.28027066102603804, 0.1326014234323625, -0.0013621368252479278, 0.11563577070865813, -0.06135222663146418, 0.2771316580673646, -0.16401364275900362, -0.042808203757656656, 0.0996194622303183, 0.024296284523196855, 0.09738710556632361, 0.1403581816147224, 0.0813680432803996, 0.07526838600736212, 0.07056889656159254, 0.061553605744061435, -0.41472611812925014, -0.16628940041000778, -0.07234505554220665, 0.19989896697403342, -0.16104195310984873, -0.1630031570188097, 0.3491808467855056, 0.1049341544616959, 0.17041963702151636, 0.13217704552687234, 0.09827444526295571, 0.12047267668179933, 0.1585741136757959, 0.0976987572907059, 0.09564092749156067, 0.310916546295892, -0.08053722991062714, -0.12215616080809284, -0.1206586258821525, 0.22492414198161378] |
1,802.07952 | Quantum walks assisted by particle number fluctuations | We study the spreading of a quantum particle placed in a single site of a
lattice or binary tree with the Hamiltonian permitting particle number changes.
We show that the particle number-changing interactions accelerate the spreading
beyond the ballistic expansion limit by inducing off-resonant Rabi oscillations
between states of different numbers of particles. We consider the effect of
perturbative number-changing couplings on Anderson localization in
one-dimensional disordered lattices and show that they lead to decrease of
localization. The effect of these couplings is shown to be larger at larger
disorder strength, which is a consequence of the disorder-induced broadening of
the particle dispersion bands.
| quant-ph | we study the spreading of a quantum particle placed in a single site of a lattice or binary tree with the hamiltonian permitting particle number changes we show that the particle numberchanging interactions accelerate the spreading beyond the ballistic expansion limit by inducing offresonant rabi oscillations between states of different numbers of particles we consider the effect of perturbative numberchanging couplings on anderson localization in onedimensional disordered lattices and show that they lead to decrease of localization the effect of these couplings is shown to be larger at larger disorder strength which is a consequence of the disorderinduced broadening of the particle dispersion bands | [['we', 'study', 'the', 'spreading', 'of', 'a', 'quantum', 'particle', 'placed', 'in', 'a', 'single', 'site', 'of', 'a', 'lattice', 'or', 'binary', 'tree', 'with', 'the', 'hamiltonian', 'permitting', 'particle', 'number', 'changes', 'we', 'show', 'that', 'the', 'particle', 'numberchanging', 'interactions', 'accelerate', 'the', 'spreading', 'beyond', 'the', 'ballistic', 'expansion', 'limit', 'by', 'inducing', 'offresonant', 'rabi', 'oscillations', 'between', 'states', 'of', 'different', 'numbers', 'of', 'particles', 'we', 'consider', 'the', 'effect', 'of', 'perturbative', 'numberchanging', 'couplings', 'on', 'anderson', 'localization', 'in', 'onedimensional', 'disordered', 'lattices', 'and', 'show', 'that', 'they', 'lead', 'to', 'decrease', 'of', 'localization', 'the', 'effect', 'of', 'these', 'couplings', 'is', 'shown', 'to', 'be', 'larger', 'at', 'larger', 'disorder', 'strength', 'which', 'is', 'a', 'consequence', 'of', 'the', 'disorderinduced', 'broadening', 'of', 'the', 'particle', 'dispersion', 'bands']] | [-0.16576475716227343, 0.2957977809357824, -0.04886063527765845, 0.06986050307974577, -0.005851867295300158, -0.14716770834862614, 0.06237458566185804, 0.33441943388718826, -0.26303325588994014, -0.2542585755089441, -0.006426634596069702, -0.302482320747983, -0.12490998401279704, 0.14293828482578436, 0.05305445287824394, 0.003524856623978569, 0.07460582595712577, 0.021559271146543324, -0.03407818125672817, -0.20325796735526708, 0.2901271789675005, 0.05360218923194155, 0.25942892442421556, 0.10418805420004691, 0.048548505713160224, 0.06536883047038618, 0.06755026701452713, 0.02679971739976631, -0.13122134415243636, 0.05028809850276817, 0.16615527014857015, -0.052517852369839184, 0.2268016707384959, -0.43102481234102297, -0.22489369775464113, 0.11062375479377806, 0.19368760791929582, 0.19736700757885745, -0.030670574052447382, -0.31375166734953663, 0.016779688556338303, -0.1811934063600627, -0.14865217542795178, -0.018900117282800447, 0.006302727238597492, 0.035100467706797644, -0.26983831252437085, 0.1092630130946278, 0.07699680104493521, 0.05539614417984222, 0.003852378682215483, -0.038401508202346474, -0.02630256866821303, 0.09524173433489452, 0.060828522035220746, -0.02487788463790471, 0.17212844314949158, -0.14948033721884713, -0.1329609229545055, 0.410703672190161, -0.09014738592220685, -0.18168414531660695, 0.2123588091837099, -0.200422174427121, -0.07423066994390236, 0.15761809837288007, 0.17811681310502955, 0.07100811879186389, -0.08537598855596465, 0.08190908736063508, -0.004074618775540819, 0.15149889656990687, 0.061558938871782556, 0.08840703543794987, 0.21261884305232132, 0.16788092577525487, 0.07541044840875727, 0.1469959032513613, -0.1256254253071697, -0.1159039525843512, -0.2555429715340814, -0.11989846311357374, -0.20736526586831763, 0.08227359396047317, -0.10039250097277265, -0.21924287049058386, 0.40972235968085724, 0.17516753735253587, 0.2153158743525497, 0.023812826594131857, 0.18292975227366418, 0.14755881228484213, 0.05667275492137728, 0.013932284928159788, 0.2775780398761316, 0.13507147003502512, 0.04688737603898447, -0.2892701533005143, 0.01356070808833465, 0.06903222893183389] |
1,802.07953 | Solutions to the affine quasi-Einstein equation for homogeneous surfaces | We examine the space of solutions to the affine quasi--Einstein equation in
the context of homogeneous surfaces. As these spaces can be used to create
gradient Yamabe solitions, conformally Einstein metrics, and warped product
Einstein manifolds using the modified Riemannian extension, we provide very
explicit descriptions of these solution spaces. We use the dimension of the
space of affine Killing vector fields to structure our discussion as this
provides a convenient organizational framework.
| math.DG | we examine the space of solutions to the affine quasieinstein equation in the context of homogeneous surfaces as these spaces can be used to create gradient yamabe solitions conformally einstein metrics and warped product einstein manifolds using the modified riemannian extension we provide very explicit descriptions of these solution spaces we use the dimension of the space of affine killing vector fields to structure our discussion as this provides a convenient organizational framework | [['we', 'examine', 'the', 'space', 'of', 'solutions', 'to', 'the', 'affine', 'quasieinstein', 'equation', 'in', 'the', 'context', 'of', 'homogeneous', 'surfaces', 'as', 'these', 'spaces', 'can', 'be', 'used', 'to', 'create', 'gradient', 'yamabe', 'solitions', 'conformally', 'einstein', 'metrics', 'and', 'warped', 'product', 'einstein', 'manifolds', 'using', 'the', 'modified', 'riemannian', 'extension', 'we', 'provide', 'very', 'explicit', 'descriptions', 'of', 'these', 'solution', 'spaces', 'we', 'use', 'the', 'dimension', 'of', 'the', 'space', 'of', 'affine', 'killing', 'vector', 'fields', 'to', 'structure', 'our', 'discussion', 'as', 'this', 'provides', 'a', 'convenient', 'organizational', 'framework']] | [-0.15339705197472278, 0.0050599988014118314, -0.0929565448186373, 0.15005246586045123, -0.183264078285341, -0.12093151329493482, -0.08473464357985618, 0.39433825294142716, -0.2523956263552688, -0.225295183976015, 0.13825573610286992, -0.22561840838688899, -0.17892952339902315, 0.15556804586380515, -0.10015888493954625, 0.04199093901743627, 0.015957311191277145, 0.05234316415320891, -0.15458885851086512, -0.3099657033142723, 0.4954749926388876, 0.021619048996586097, 0.2734819140846599, 0.021829119475226696, 0.15548154504089426, -0.04585359163888513, -0.009833531269216782, 0.052155371276145064, -0.201875789499242, 0.19202731332218606, 0.28129152784902245, 0.1341409685428267, 0.19392696809189472, -0.39600034179293536, -0.22302570497802116, 0.14065391931376636, 0.14628561394773934, 0.08658531909068562, -0.026256311429690007, -0.3595575683125078, 0.0014917336863605943, -0.1272087586558845, -0.19868413382528782, -0.19176055993629645, -0.04625756127045375, -0.029941180140443453, -0.19669877899545946, 0.02436725208408212, 0.05147173126349353, 0.02008020099609682, -0.1747553524025397, -0.055714277415823396, -0.03650292405565206, 0.08689676536955195, 0.04435590516826878, 0.06377795679265097, 0.11217237230109638, -0.03766197023501824, -0.11283564555445967, 0.37789153738891423, -0.15541186122453376, -0.3577114906519243, 0.12414391467679445, -0.0896231036964957, -0.11216652012519436, 0.05340696789630472, 0.22011169696175684, 0.16234942646824743, -0.11021676143609013, 0.14093839347104173, -0.0395828632586827, 0.052775539202641136, 0.09895701775301809, 0.016131092551840493, 0.15608963242744747, 0.12452107843981214, 0.11483987131194301, 0.14146911656987943, 0.01124989324925493, -0.10956860729652673, -0.37396161064301453, -0.26626261717269883, -0.07264002785086632, 0.15764216851596147, -0.17069823096473605, -0.21241539984635294, 0.3573583681263948, 0.045636042474118406, 0.14967279337754805, 0.08210304621862222, 0.2019869016917193, 0.026636661035136306, 0.051778412105081835, 0.10986313584885776, 0.22055251294849057, 0.19916291950487416, 0.10885389264966425, -0.1182398755001287, -0.09037593473386887, 0.1638319880816422] |
1,802.07954 | The State of the Art in Integrating Machine Learning into Visual
Analytics | Visual analytics systems combine machine learning or other analytic
techniques with interactive data visualization to promote sensemaking and
analytical reasoning. It is through such techniques that people can make sense
of large, complex data. While progress has been made, the tactful combination
of machine learning and data visualization is still under-explored. This
state-of-the-art report presents a summary of the progress that has been made
by highlighting and synthesizing select research advances. Further, it presents
opportunities and challenges to enhance the synergy between machine learning
and visual analytics for impactful future research directions.
| stat.ML cs.HC cs.LG | visual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning it is through such techniques that people can make sense of large complex data while progress has been made the tactful combination of machine learning and data visualization is still underexplored this stateoftheart report presents a summary of the progress that has been made by highlighting and synthesizing select research advances further it presents opportunities and challenges to enhance the synergy between machine learning and visual analytics for impactful future research directions | [['visual', 'analytics', 'systems', 'combine', 'machine', 'learning', 'or', 'other', 'analytic', 'techniques', 'with', 'interactive', 'data', 'visualization', 'to', 'promote', 'sensemaking', 'and', 'analytical', 'reasoning', 'it', 'is', 'through', 'such', 'techniques', 'that', 'people', 'can', 'make', 'sense', 'of', 'large', 'complex', 'data', 'while', 'progress', 'has', 'been', 'made', 'the', 'tactful', 'combination', 'of', 'machine', 'learning', 'and', 'data', 'visualization', 'is', 'still', 'underexplored', 'this', 'stateoftheart', 'report', 'presents', 'a', 'summary', 'of', 'the', 'progress', 'that', 'has', 'been', 'made', 'by', 'highlighting', 'and', 'synthesizing', 'select', 'research', 'advances', 'further', 'it', 'presents', 'opportunities', 'and', 'challenges', 'to', 'enhance', 'the', 'synergy', 'between', 'machine', 'learning', 'and', 'visual', 'analytics', 'for', 'impactful', 'future', 'research', 'directions']] | [-0.04754298416306623, 0.022038755979348016, -0.11141301039606333, 0.011649566043710724, -0.2278447626874997, -0.19528846165861238, 0.024075869573177873, 0.4653023693424005, -0.27465789322997186, -0.350310484198137, 0.10622328273685915, -0.3204714342910837, -0.20810881337396556, 0.24432170244476215, -0.11571512732061219, 0.12507807507415067, 0.16755907866940067, -0.015833559517677013, -0.04927329477536809, -0.2824162578384218, 0.26999688302013247, 0.05363276669919327, 0.3843336614708488, 0.08905567031783554, 0.08440358848643623, 0.009054234635166742, -0.1214792943395838, -0.02261791606740719, -0.10544268168290888, 0.2720220807746595, 0.43989278517335983, 0.2983736278090094, 0.40756522759713315, -0.43294990960262963, -0.25750611909757276, 0.04988872895917886, 0.18841048063976423, 0.09929879224900115, -0.14225378966184107, -0.3271402943326713, 0.06220294032591282, -0.1477448365415682, -0.06524246229513825, -0.2362086388517867, 0.043700587505904526, -0.017276873311237687, -0.20526300947268872, -0.0538119331902855, 0.0643188720159642, 0.17054950183891987, 0.03373059320294267, -0.11519628392716685, 0.09214764927606006, 0.19093089664078594, 0.08872956723668152, 0.11039916759582011, 0.13955799007153774, -0.2194304627821791, -0.2068891209245731, 0.3450640480515066, 0.004549198937448827, -0.14252823776217524, 0.24802047944023878, -0.023751364714161564, -0.2050667864546835, 0.05965804449630553, 0.22686447856108566, 0.030147202507398285, -0.18512288676472483, 0.06990223917994996, 0.04927963784455762, 0.14919200713316408, -0.007658592282006374, -0.011850324060235704, 0.26624793423196447, 0.3094866084815054, 0.018974541737646847, 0.08696703853374757, -0.054080406249920415, -0.07569413118391902, -0.1311627045314718, -0.14688274445994706, -0.10837148608394213, -0.03507873647242457, -0.007842600733715949, -0.10243822174699424, 0.3192536064454324, 0.23918772000655697, 0.16889752191747284, 0.01025981631815679, 0.3857974317948242, -0.004930894484149886, 0.10800948357311907, 0.08545932475641206, 0.22550855989690746, 0.02581692653053164, 0.21017501152959744, -0.12841498248719171, 0.11143360454282099, -0.04596291931734963] |
1,802.07955 | 2-D model of the global ionospheric conductor connected with the
magnetospheric conductors | A model of the ionospheric global conductor is designed. The ionospheric
conductor is considered in the framework of a two-dimensional approximation
based on high conductivity in the direction of the magnetic field. Under this
assumption the magnetic field lines are equipotential, and the charge transfer
between them is determined only by integral Pedersen and Hall conductivities.
The model is constructed as the first approximation in the small parameter
expansion of the solution of the three-dimensional problems of electrical
conductivity. The small parameter is the ratio of Pedersen and field-aligned
conductivities. The space distributions of the Pedersen and Hall conductivities
are calculated using the empirical models IRI, MSISE, IGRF and applied to
construct the maps of the integral conductivities. The parts of the
magnetosphere with high conductivity across the magnetic field lines, namely,
the cusps and the plasma layer are analyzed. It is shown that the connection of
these magnetospheric conductors to the ionosphere in parallel makes the auroral
zones equipotential regions. As a consequence, for the ionospheric electric
fields, which generators are located in the ionosphere or in the atmosphere,
the global problem of electrical conductivity is separated into three
independent boundary value problems in three regions: two polar caps and the
main part of the ionosphere which includes the mid- and low-latitude parts of
the ionosphere. The model can be used for the analysis of the ionospheric part
of the Global Electric Circuit, for calculation of the ionospheric dynamo
electric field and as a fragment in more complex ionospheric and magnetospheric
models.
| physics.space-ph | a model of the ionospheric global conductor is designed the ionospheric conductor is considered in the framework of a twodimensional approximation based on high conductivity in the direction of the magnetic field under this assumption the magnetic field lines are equipotential and the charge transfer between them is determined only by integral pedersen and hall conductivities the model is constructed as the first approximation in the small parameter expansion of the solution of the threedimensional problems of electrical conductivity the small parameter is the ratio of pedersen and fieldaligned conductivities the space distributions of the pedersen and hall conductivities are calculated using the empirical models iri msise igrf and applied to construct the maps of the integral conductivities the parts of the magnetosphere with high conductivity across the magnetic field lines namely the cusps and the plasma layer are analyzed it is shown that the connection of these magnetospheric conductors to the ionosphere in parallel makes the auroral zones equipotential regions as a consequence for the ionospheric electric fields which generators are located in the ionosphere or in the atmosphere the global problem of electrical conductivity is separated into three independent boundary value problems in three regions two polar caps and the main part of the ionosphere which includes the mid and lowlatitude parts of the ionosphere the model can be used for the analysis of the ionospheric part of the global electric circuit for calculation of the ionospheric dynamo electric field and as a fragment in more complex ionospheric and magnetospheric models | [['a', 'model', 'of', 'the', 'ionospheric', 'global', 'conductor', 'is', 'designed', 'the', 'ionospheric', 'conductor', 'is', 'considered', 'in', 'the', 'framework', 'of', 'a', 'twodimensional', 'approximation', 'based', 'on', 'high', 'conductivity', 'in', 'the', 'direction', 'of', 'the', 'magnetic', 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1,802.07956 | Stereo obstacle detection for unmanned surface vehicles by IMU-assisted
semantic segmentation | A new obstacle detection algorithm for unmanned surface vehicles (USVs) is
presented. A state-of-the-art graphical model for semantic segmentation is
extended to incorporate boat pitch and roll measurements from the on-board
inertial measurement unit (IMU), and a stereo verification algorithm that
consolidates tentative detections obtained from the segmentation is proposed.
The IMU readings are used to estimate the location of horizon line in the
image, which automatically adjusts the priors in the probabilistic semantic
segmentation model. We derive the equations for projecting the horizon into
images, propose an efficient optimization algorithm for the extended graphical
model, and offer a practical IMU-camera-USV calibration procedure. Using an USV
equipped with multiple synchronized sensors, we captured a new challenging
multi-modal dataset, and annotated its images with water edge and obstacles.
Experimental results show that the proposed algorithm significantly outperforms
the state of the art, with nearly 30% improvement in water-edge detection
accuracy, an over 21% reduction of false positive rate, an almost 60% reduction
of false negative rate, and an over 65% increase of true positive rate, while
its Matlab implementation runs in real-time.
| cs.RO cs.CV | a new obstacle detection algorithm for unmanned surface vehicles usvs is presented a stateoftheart graphical model for semantic segmentation is extended to incorporate boat pitch and roll measurements from the onboard inertial measurement unit imu and a stereo verification algorithm that consolidates tentative detections obtained from the segmentation is proposed the imu readings are used to estimate the location of horizon line in the image which automatically adjusts the priors in the probabilistic semantic segmentation model we derive the equations for projecting the horizon into images propose an efficient optimization algorithm for the extended graphical model and offer a practical imucamerausv calibration procedure using an usv equipped with multiple synchronized sensors we captured a new challenging multimodal dataset and annotated its images with water edge and obstacles experimental results show that the proposed algorithm significantly outperforms the state of the art with nearly 30 improvement in wateredge detection accuracy an over 21 reduction of false positive rate an almost 60 reduction of false negative rate and an over 65 increase of true positive rate while its matlab implementation runs in realtime | [['a', 'new', 'obstacle', 'detection', 'algorithm', 'for', 'unmanned', 'surface', 'vehicles', 'usvs', 'is', 'presented', 'a', 'stateoftheart', 'graphical', 'model', 'for', 'semantic', 'segmentation', 'is', 'extended', 'to', 'incorporate', 'boat', 'pitch', 'and', 'roll', 'measurements', 'from', 'the', 'onboard', 'inertial', 'measurement', 'unit', 'imu', 'and', 'a', 'stereo', 'verification', 'algorithm', 'that', 'consolidates', 'tentative', 'detections', 'obtained', 'from', 'the', 'segmentation', 'is', 'proposed', 'the', 'imu', 'readings', 'are', 'used', 'to', 'estimate', 'the', 'location', 'of', 'horizon', 'line', 'in', 'the', 'image', 'which', 'automatically', 'adjusts', 'the', 'priors', 'in', 'the', 'probabilistic', 'semantic', 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1,802.07957 | Non-rigid Object Tracking via Deep Multi-scale Spatial-temporal
Discriminative Saliency Maps | In this paper, we propose a novel effective non-rigid object tracking
framework based on the spatial-temporal consistent saliency detection. In
contrast to most existing trackers that utilize a bounding box to specify the
tracked target, the proposed framework can extract accurate regions of the
target as tracking outputs. It achieves a better description of the non-rigid
objects and reduces the background pollution for the tracking model.
Furthermore, our model has several unique features. First, a tailored fully
convolutional neural network (TFCN) is developed to model the local saliency
prior for a given image region, which not only provides the pixel-wise outputs
but also integrates the semantic information. Second, a novel multi-scale
multi-region mechanism is proposed to generate local saliency maps that
effectively consider visual perceptions with different spatial layouts and
scale variations. Subsequently, local saliency maps are fused via a weighted
entropy method, resulting in a final discriminative saliency map. Finally, we
present a non-rigid object tracking algorithm based on the predicted saliency
maps. By utilizing a spatial-temporal consistent saliency map (STCSM), we
conduct target-background classification and use a simple fine-tuning scheme
for online updating. Extensive experiments demonstrate that the proposed
algorithm achieves competitive performance in both saliency detection and
visual tracking, especially outperforming other related trackers on the
non-rigid object tracking datasets.
| cs.CV | in this paper we propose a novel effective nonrigid object tracking framework based on the spatialtemporal consistent saliency detection in contrast to most existing trackers that utilize a bounding box to specify the tracked target the proposed framework can extract accurate regions of the target as tracking outputs it achieves a better description of the nonrigid objects and reduces the background pollution for the tracking model furthermore our model has several unique features first a tailored fully convolutional neural network tfcn is developed to model the local saliency prior for a given image region which not only provides the pixelwise outputs but also integrates the semantic information second a novel multiscale multiregion mechanism is proposed to generate local saliency maps that effectively consider visual perceptions with different spatial layouts and scale variations subsequently local saliency maps are fused via a weighted entropy method resulting in a final discriminative saliency map finally we present a nonrigid object tracking algorithm based on the predicted saliency maps by utilizing a spatialtemporal consistent saliency map stcsm we conduct targetbackground classification and use a simple finetuning scheme for online updating extensive experiments demonstrate that the proposed algorithm achieves competitive performance in both saliency detection and visual tracking especially outperforming other related trackers on the nonrigid object tracking datasets | [['in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'effective', 'nonrigid', 'object', 'tracking', 'framework', 'based', 'on', 'the', 'spatialtemporal', 'consistent', 'saliency', 'detection', 'in', 'contrast', 'to', 'most', 'existing', 'trackers', 'that', 'utilize', 'a', 'bounding', 'box', 'to', 'specify', 'the', 'tracked', 'target', 'the', 'proposed', 'framework', 'can', 'extract', 'accurate', 'regions', 'of', 'the', 'target', 'as', 'tracking', 'outputs', 'it', 'achieves', 'a', 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1,802.07958 | A New Approach for Measuring Power Spectra and Reconstructing Time
Series in Active Galactic Nuclei | We provide a new approach to measure power spectra and reconstruct time
series in active galactic nuclei (AGNs) based on the fact that the Fourier
transform of AGN stochastic variations is a series of complex Gaussian random
variables. The approach parameterizes a stochastic series in frequency domain
and transforms it back to time domain to fit the observed data. The parameters
and their uncertainties are derived in a Bayesian framework, which also allows
us to compare the relative merits of different power spectral density models.
The well-developed fast Fourier transform algorithm together with parallel
computation enable an acceptable time complexity for the approach.
| astro-ph.IM astro-ph.HE | we provide a new approach to measure power spectra and reconstruct time series in active galactic nuclei agns based on the fact that the fourier transform of agn stochastic variations is a series of complex gaussian random variables the approach parameterizes a stochastic series in frequency domain and transforms it back to time domain to fit the observed data the parameters and their uncertainties are derived in a bayesian framework which also allows us to compare the relative merits of different power spectral density models the welldeveloped fast fourier transform algorithm together with parallel computation enable an acceptable time complexity for the approach | [['we', 'provide', 'a', 'new', 'approach', 'to', 'measure', 'power', 'spectra', 'and', 'reconstruct', 'time', 'series', 'in', 'active', 'galactic', 'nuclei', 'agns', 'based', 'on', 'the', 'fact', 'that', 'the', 'fourier', 'transform', 'of', 'agn', 'stochastic', 'variations', 'is', 'a', 'series', 'of', 'complex', 'gaussian', 'random', 'variables', 'the', 'approach', 'parameterizes', 'a', 'stochastic', 'series', 'in', 'frequency', 'domain', 'and', 'transforms', 'it', 'back', 'to', 'time', 'domain', 'to', 'fit', 'the', 'observed', 'data', 'the', 'parameters', 'and', 'their', 'uncertainties', 'are', 'derived', 'in', 'a', 'bayesian', 'framework', 'which', 'also', 'allows', 'us', 'to', 'compare', 'the', 'relative', 'merits', 'of', 'different', 'power', 'spectral', 'density', 'models', 'the', 'welldeveloped', 'fast', 'fourier', 'transform', 'algorithm', 'together', 'with', 'parallel', 'computation', 'enable', 'an', 'acceptable', 'time', 'complexity', 'for', 'the', 'approach']] | [-0.04043038480562493, 0.026013999030325172, -0.16099281079651226, 0.09649703923942865, -0.11835244152405598, -0.09753080717405503, 0.06600608286963215, 0.4155966117978096, -0.3045759385053828, -0.28880870277152476, 0.07870963304100143, -0.22009186980382933, -0.10968715848527777, 0.23192806409002797, -0.06280159449303134, 0.07762143939950512, 0.010929581015235156, -0.02618859479745208, -0.06688797550990237, -0.22182914080297195, 0.24907769469851718, 0.07642789365886485, 0.30291316198926527, -0.08504127156333004, 0.11940128772261834, -0.030804502687335592, -0.11889923866657377, -0.016592989120749954, -0.0791747652617135, 0.14204477270142835, 0.23891959866911916, 0.15795161341344124, 0.26673742943416234, -0.43440420616381953, -0.2225200543722626, 0.09573937764445554, 0.1412419610339199, 0.050867442463358496, -0.015057352232493606, -0.24617662257288844, 0.03499925034391938, -0.14615439895757484, -0.10618406726788839, -0.13191979044813265, 0.010929308515222906, 0.05826355799472014, -0.29720946993606473, 0.07967604335269764, 0.027481837625724367, 0.009919352151308824, -0.07864050093859669, -0.08595505039867701, 0.06053643913722588, 0.0972855967849276, 0.04765736296528824, 0.02770876732555408, 0.12326536985855659, -0.043997295652923075, -0.10277537443195876, 0.3487579563578356, -0.06625006802705596, -0.17359262666872982, 0.16232336982542162, -0.1582898498395259, -0.1602869562768531, 0.1692640234634859, 0.2318013892011735, 0.11709151096027164, -0.1371741735148108, 0.08777651501631871, 0.014303009497065061, 0.1979326694136829, 0.0019311443992971796, 0.02940586660943419, 0.16402427991400065, 0.115458672115742, 0.055035673312445, 0.12668191690395758, -0.15165264412390014, -0.10859940815445723, -0.2645681571549944, -0.13491751433087928, -0.19531061728168458, -0.019632536913403897, -0.13327811358598834, -0.1580211287861672, 0.4529972315847295, 0.12135266343547592, 0.24142699857757796, 0.10258936877385035, 0.3434086887672254, 0.14189470943642182, 0.03965129245646768, 0.07103101292950581, 0.16961037132491186, 0.17775739828866083, 0.1150459379502527, -0.23315535403010482, 0.020844901410085194, 0.040561184031635666] |
1,802.07959 | Power law analysis for temperature dependence of magnetocrystalline
anisotropy constants of Nd$_2$Fe$_{14}$B magnets | Phenomenological analysis for the temperature dependence of the
magnetocrystalline anisotropy (MA) in rare earth magnets is presented. We
define phenomenological power laws applicable to compound magnets using the
Zener theory, apply these laws to the magnetocrystalline anisotropy constants
(MACs) of Nd$_2$Fe$_{14}$B magnets. The results indicate that the MACs obey the
power law well, and a general understanding for the temperature-dependent MA in
rare earth magnets is obtained through the analysis. Furthermore, to examine
the validity of the power law, we discuss the temperature dependence of the
MACs in Dy$_2$Fe$_{14}$B and Y$_2$Fe$_{14}$B magnets as examples wherein it is
difficult to interpret the MA using the power law.
| cond-mat.mtrl-sci | phenomenological analysis for the temperature dependence of the magnetocrystalline anisotropy ma in rare earth magnets is presented we define phenomenological power laws applicable to compound magnets using the zener theory apply these laws to the magnetocrystalline anisotropy constants macs of nd_2fe_14b magnets the results indicate that the macs obey the power law well and a general understanding for the temperaturedependent ma in rare earth magnets is obtained through the analysis furthermore to examine the validity of the power law we discuss the temperature dependence of the macs in dy_2fe_14b and y_2fe_14b magnets as examples wherein it is difficult to interpret the ma using the power law | [['phenomenological', 'analysis', 'for', 'the', 'temperature', 'dependence', 'of', 'the', 'magnetocrystalline', 'anisotropy', 'ma', 'in', 'rare', 'earth', 'magnets', 'is', 'presented', 'we', 'define', 'phenomenological', 'power', 'laws', 'applicable', 'to', 'compound', 'magnets', 'using', 'the', 'zener', 'theory', 'apply', 'these', 'laws', 'to', 'the', 'magnetocrystalline', 'anisotropy', 'constants', 'macs', 'of', 'nd_2fe_14b', 'magnets', 'the', 'results', 'indicate', 'that', 'the', 'macs', 'obey', 'the', 'power', 'law', 'well', 'and', 'a', 'general', 'understanding', 'for', 'the', 'temperaturedependent', 'ma', 'in', 'rare', 'earth', 'magnets', 'is', 'obtained', 'through', 'the', 'analysis', 'furthermore', 'to', 'examine', 'the', 'validity', 'of', 'the', 'power', 'law', 'we', 'discuss', 'the', 'temperature', 'dependence', 'of', 'the', 'macs', 'in', 'dy_2fe_14b', 'and', 'y_2fe_14b', 'magnets', 'as', 'examples', 'wherein', 'it', 'is', 'difficult', 'to', 'interpret', 'the', 'ma', 'using', 'the', 'power', 'law']] | [-0.11948197577797916, 0.11570115624300133, -0.07300730028118078, 0.07086728425369634, -0.09537774589485846, -0.13075946762602633, 0.058686116616277456, 0.3096055382808957, -0.2297422140657615, -0.29918012687882695, 0.0329228718865824, -0.3007890893674742, -0.08490892514013328, 0.2500849923190589, 0.04120690307508294, 0.028487759203506775, -0.07876276028736566, -0.005140889830027635, -0.033933777594938874, -0.18124251558373755, 0.24401776156782246, 0.12887307102657639, 0.3351614845719618, 0.09367748014987089, 0.07853782703526892, -0.016953303210007455, 0.05645399416635673, 0.023971228188691802, -0.17552452613500252, 0.05814390304910306, 0.2280742101272783, 0.002950241269830328, 0.14788825917415893, -0.4091630475774694, -0.1996282806727462, 0.0366175518809961, 0.10829402759526811, 0.09770408467626951, -0.05412785238765467, -0.22822291527140456, 0.08838929269964305, -0.18291923080463535, -0.1748502909747633, -0.12135215922115514, -0.015702831144713294, 0.09933746700139287, -0.2893676341582949, 0.12670562064382607, 0.09009385884117084, 0.10679953282054228, -0.09100156529949835, -0.15616479486030024, 0.02655580216490377, 0.048707545949862555, 0.1204652115098165, -0.03336836973903701, 0.16845864527259927, -0.08550803185565971, -0.10299138859129296, 0.4172756588444687, -0.006875154338418865, -0.08726929794423856, 0.11718236335302488, -0.199632526617139, -0.18633709330326662, 0.08036988367362377, 0.16595531188739607, 0.0707397347207986, -0.14986386268775767, 0.09988559994627184, 0.017256921546784446, 0.16035109914418383, -0.014242308769518366, 0.013810448646836448, 0.21547825423140937, 0.15323103800339874, -0.02665336908494982, 0.1593068866887524, -0.11267764129353544, -0.10261358517723587, -0.2904550130479038, -0.1494155247659924, -0.2258178827782663, 0.06517335741395633, -0.10066946843933412, -0.12567521035760784, 0.35915568487297816, 0.15487517518564486, 0.1470619935202054, 0.03511957490655522, 0.26801637143496637, 0.12170093326466695, 0.08439169251897301, 0.027868326211598918, 0.289460747265436, 0.21920253963281328, 0.16746132048026013, -0.23987158757518046, 0.0655110964569478, 0.003651419887319207] |
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