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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1,802.0376 | Distributed Evaluation of Subgraph Queries Using Worstcase Optimal
LowMemory Dataflows | We study the problem of finding and monitoring fixed-size subgraphs in a
continually changing large-scale graph. We present the first approach that (i)
performs worst-case optimal computation and communication, (ii) maintains a
total memory footprint linear in the number of input edges, and (iii) scales
down per-worker computation, communication, and memory requirements linearly as
the number of workers increases, even on adversarially skewed inputs.
Our approach is based on worst-case optimal join algorithms, recast as a
data-parallel dataflow computation. We describe the general algorithm and
modifications that make it robust to skewed data, prove theoretical bounds on
its resource requirements in the massively parallel computing model, and
implement and evaluate it on graphs containing as many as 64 billion edges. The
underlying algorithm and ideas generalize from finding and monitoring subgraphs
to the more general problem of computing and maintaining relational equi-joins
over dynamic relations.
| cs.DC cs.DB | we study the problem of finding and monitoring fixedsize subgraphs in a continually changing largescale graph we present the first approach that i performs worstcase optimal computation and communication ii maintains a total memory footprint linear in the number of input edges and iii scales down perworker computation communication and memory requirements linearly as the number of workers increases even on adversarially skewed inputs our approach is based on worstcase optimal join algorithms recast as a dataparallel dataflow computation we describe the general algorithm and modifications that make it robust to skewed data prove theoretical bounds on its resource requirements in the massively parallel computing model and implement and evaluate it on graphs containing as many as 64 billion edges the underlying algorithm and ideas generalize from finding and monitoring subgraphs to the more general problem of computing and maintaining relational equijoins over dynamic relations | [['we', 'study', 'the', 'problem', 'of', 'finding', 'and', 'monitoring', 'fixedsize', 'subgraphs', 'in', 'a', 'continually', 'changing', 'largescale', 'graph', 'we', 'present', 'the', 'first', 'approach', 'that', 'i', 'performs', 'worstcase', 'optimal', 'computation', 'and', 'communication', 'ii', 'maintains', 'a', 'total', 'memory', 'footprint', 'linear', 'in', 'the', 'number', 'of', 'input', 'edges', 'and', 'iii', 'scales', 'down', 'perworker', 'computation', 'communication', 'and', 'memory', 'requirements', 'linearly', 'as', 'the', 'number', 'of', 'workers', 'increases', 'even', 'on', 'adversarially', 'skewed', 'inputs', 'our', 'approach', 'is', 'based', 'on', 'worstcase', 'optimal', 'join', 'algorithms', 'recast', 'as', 'a', 'dataparallel', 'dataflow', 'computation', 'we', 'describe', 'the', 'general', 'algorithm', 'and', 'modifications', 'that', 'make', 'it', 'robust', 'to', 'skewed', 'data', 'prove', 'theoretical', 'bounds', 'on', 'its', 'resource', 'requirements', 'in', 'the', 'massively', 'parallel', 'computing', 'model', 'and', 'implement', 'and', 'evaluate', 'it', 'on', 'graphs', 'containing', 'as', 'many', 'as', '64', 'billion', 'edges', 'the', 'underlying', 'algorithm', 'and', 'ideas', 'generalize', 'from', 'finding', 'and', 'monitoring', 'subgraphs', 'to', 'the', 'more', 'general', 'problem', 'of', 'computing', 'and', 'maintaining', 'relational', 'equijoins', 'over', 'dynamic', 'relations']] | [-0.13950841557475385, 0.050345824434068695, -0.02596755607760158, 0.05841112836055329, -0.10656126450972053, -0.17799199556546477, 0.11946880817895049, 0.3887633024361627, -0.2921649052922068, -0.40271938633623305, 0.11837183727866746, -0.25778716403854496, -0.1482841181376114, 0.17128535811147041, -0.09451100078897133, 0.08791649466789937, 0.10114475609413509, 0.012888400296776972, -0.019428703880965195, -0.2827707486526222, 0.23797938562608484, 0.0486250768704661, 0.2928528001449665, 0.016734014366400138, 0.06660941515262399, 0.037663517193868755, -0.08638448253402423, 0.04956022954449572, -0.06915479110090207, 0.13131757131777705, 0.26099432449916316, 0.2410691873828784, 0.296329973541714, -0.46435279184631234, -0.11992317906356063, 0.1033375376305575, 0.13118619972695436, 0.09904230290397616, 0.0012849007447145815, -0.22573487420309463, 0.102713799818443, -0.1511681953396905, -0.029225419818198886, -0.10421282476263827, 0.04139230764503109, 0.006489003685720522, -0.2685259200889489, -0.005784158775550795, 0.060485597911836775, 0.01417820061846026, -0.008652175101451576, -0.10757243351043394, 0.020141142772125274, 0.11327612150845856, -0.024417853485271014, 0.025537426312100785, 0.14427541286267084, -0.12533667665250914, -0.1687414360104193, 0.3914033160866078, -0.014857512276523328, -0.16725943805971022, 0.14452372377112122, -0.03464178712727454, -0.18130657751663137, 0.07492061136290432, 0.2610651552869842, 0.12063100822912208, -0.10030984509864758, 0.0996950041051103, -0.03770098485502189, 0.15412539928380786, 0.0514258479169602, 0.07946905232725086, 0.1126152702639329, 0.21345419030122717, 0.14671127364513112, 0.17514341679112663, -0.02950978868737303, -0.1232828817619332, -0.22860673894656117, -0.13254560573379798, -0.2101773794547751, -0.011185856426841227, -0.15695955512045626, -0.17941933810502161, 0.3969273180732953, 0.17580527972975937, 0.1992710922170302, 0.18629781045661917, 0.36935759058286405, 0.04274540279654722, 0.08797935528905484, 0.22136001130566002, 0.12038032854746641, 0.0852901261267734, 0.11597865678867775, -0.20576112217205608, 0.08777529712413148, 0.02113916439160801] |
1,802.03761 | On the Latent Space of Wasserstein Auto-Encoders | We study the role of latent space dimensionality in Wasserstein auto-encoders
(WAEs). Through experimentation on synthetic and real datasets, we argue that
random encoders should be preferred over deterministic encoders. We highlight
the potential of WAEs for representation learning with promising results on a
benchmark disentanglement task.
| stat.ML cs.LG | we study the role of latent space dimensionality in wasserstein autoencoders waes through experimentation on synthetic and real datasets we argue that random encoders should be preferred over deterministic encoders we highlight the potential of waes for representation learning with promising results on a benchmark disentanglement task | [['we', 'study', 'the', 'role', 'of', 'latent', 'space', 'dimensionality', 'in', 'wasserstein', 'autoencoders', 'waes', 'through', 'experimentation', 'on', 'synthetic', 'and', 'real', 'datasets', 'we', 'argue', 'that', 'random', 'encoders', 'should', 'be', 'preferred', 'over', 'deterministic', 'encoders', 'we', 'highlight', 'the', 'potential', 'of', 'waes', 'for', 'representation', 'learning', 'with', 'promising', 'results', 'on', 'a', 'benchmark', 'disentanglement', 'task']] | [-0.061416687186252567, 0.019918543990067344, -0.06931870991978398, 0.07459021591893496, -0.10585750796970853, -0.17926662949290365, 0.04921782191129441, 0.5083361876771805, -0.26723402595900475, -0.24391208268067938, 0.04327000394968831, -0.26109634472572424, -0.23869771684737914, 0.245358870067495, -0.09143881339262774, 0.06838467427866256, 0.16537173024992993, 0.031186849592213937, -0.08742974854589618, -0.31465164928677236, 0.35990379675430184, 0.058844660101656586, 0.3339924183376926, 0.006493295741049533, 0.1473903800063628, -0.008335799791235873, -0.03766244728157812, -0.03273966731664606, -0.059647732870832845, 0.12709583353964574, 0.29374467985744174, 0.18479189338122912, 0.32333995576234575, -0.36585691809020143, -0.2660605249966079, 0.14023856408497754, 0.1345553220586574, 0.09799235294594062, -0.06102748818081269, -0.3661290623168362, 0.0531785351402582, -0.11107393978361754, 0.0652670140323685, -0.21900158821347546, -0.02472261726816601, -0.015893365360519038, -0.2982743111379603, 0.039168991775133034, 0.044399899371126865, 0.07251934887484666, -0.09500632591129458, -0.14064229636433276, 0.021402568595999098, 0.13157973582162819, 0.06274473131881987, 0.05946243111975491, 0.09038994874448535, -0.12514837870889522, -0.20324324865013044, 0.3358074761134513, -0.1125894648993903, -0.26233200496062636, 0.20852677706391254, -0.03958394854983434, -0.17770528024498453, 0.021609095896178102, 0.30354829209836875, 0.10615054545725913, -0.09472593068680231, 0.05088910610945103, -0.07811312508234318, 0.1355956741460064, 0.018909325625034088, 0.014864747917794801, 0.15450386114002385, 0.2857729574229489, 0.02039585319010818, 0.17117078248857262, -0.13484791506755542, -0.1514371058883819, -0.24767612826396176, -0.16592864068026872, -0.23809252100739073, 0.020866744656195032, -0.20241927591299866, -0.0928172452494185, 0.3551285171366118, 0.2480828735699996, 0.2164205955539612, 0.1022942019824652, 0.30011288972294076, -0.006084119782168815, 0.06581572712735927, 0.09718425782828374, 0.1473820911660949, 0.043565797124137266, 0.07684523785397648, -0.16525162064886473, 0.07064840142575508, 0.029625062018315843] |
1,802.03762 | Embedding derived categories of Enriques surfaces into derived
categories of Fano varieties | We show that the derived category of a general Enriques surface can be
realized as a semiorthogonal component in the derived category of a smooth Fano
variety with a diagonal Hodge diamond.
| math.AG | we show that the derived category of a general enriques surface can be realized as a semiorthogonal component in the derived category of a smooth fano variety with a diagonal hodge diamond | [['we', 'show', 'that', 'the', 'derived', 'category', 'of', 'a', 'general', 'enriques', 'surface', 'can', 'be', 'realized', 'as', 'a', 'semiorthogonal', 'component', 'in', 'the', 'derived', 'category', 'of', 'a', 'smooth', 'fano', 'variety', 'with', 'a', 'diagonal', 'hodge', 'diamond']] | [-0.15271428698906675, -0.002078788595099468, -0.12233810825273395, 0.08676111255772412, -0.08319274825043976, -0.18368248891783878, -0.034948586420796346, 0.38881710171699524, -0.3641621791757643, -0.1734165282396134, 0.10698264155871584, -0.1197775756008923, -0.2011334125418216, 0.24065608042292297, -0.21224968635942787, -0.10025008919183165, 0.06898980362166185, 0.08534687175415456, -0.10469093513529515, -0.2745059134904295, 0.45685728872194886, -0.11106292431941256, 0.2990825703018345, 0.06252980785211548, 0.1295496153179556, -0.02925045826123096, 0.08844787714770064, 0.0833767217991408, -0.07961504793024687, 0.21265358751406893, 0.3741041877074167, 0.018502376857213676, 0.09847399037244031, -0.35701427422463894, -0.2287936583161354, 0.15266399388201535, 0.08002081423182972, 0.11892992278444581, -0.07374980836175382, -0.29071728052804247, 0.11123848432907835, -0.23648416029755026, -0.19076632460928522, -0.03724742020131089, 0.0032689870276954025, 0.011192849284270778, -0.2463432252407074, -0.06898172509681899, 0.08101513428846374, 0.1055486254626885, -0.07997575376066379, -0.12428605826789862, -0.1706892295042053, 0.01653005470870994, -0.07475961877207737, 0.04768639866961166, 0.15670862402475905, -0.10175627307035029, -0.08895110769663006, 0.3760937290498987, -0.18767726316582412, -0.20594195829471573, 0.09211396613682155, -0.11226940853521228, -0.08661589617258869, 0.1629515381064266, 0.0801239826832898, 0.16700573172420263, -0.04348757001571357, 0.14237831276841462, -0.1734704984119162, 0.11053233381244354, 0.08520436595426872, 0.016766326714787283, 0.16545514421886764, 0.12791650125291198, 0.03422405227320269, 0.15029426087494357, -0.10174922160513233, 0.011844484019093215, -0.3479992240900174, -0.18780689549748786, -0.15141932695405558, 0.18638626066967845, -0.10575351348961703, -0.18585661181714386, 0.4119644569000229, -0.051643221740960144, 0.25425124360481277, 0.07540773783694021, 0.2197273352649063, 0.05929529363857, 0.05378041137009859, 0.002528426586650312, 0.1690894092898816, 0.24464823125163093, -0.06504388045868836, -0.1130984152041492, -0.015370496810646728, 0.15095503885822836] |
1,802.03763 | Comment on the stability of decorated C 48 B 12 heterofullerene | A good hydrogen storage material should adsorb hydrogen in high
concentrations and with optimal binding energies. Numerous mixed carbon boron
fullerenes which are decorated with metal atoms were previously constructed by
hand and proposed as a promising material in this context. We present a fully
ab-initio, unbiased structure search in the configurational space of decorated
C48B12 and find that most of the hitherto postulated ground state structures
are not ground states. We determine the energetically lowest configurations for
Be, Ca, Li and Sc decorated C48B12 clusters.
| cond-mat.mtrl-sci | a good hydrogen storage material should adsorb hydrogen in high concentrations and with optimal binding energies numerous mixed carbon boron fullerenes which are decorated with metal atoms were previously constructed by hand and proposed as a promising material in this context we present a fully abinitio unbiased structure search in the configurational space of decorated c48b12 and find that most of the hitherto postulated ground state structures are not ground states we determine the energetically lowest configurations for be ca li and sc decorated c48b12 clusters | [['a', 'good', 'hydrogen', 'storage', 'material', 'should', 'adsorb', 'hydrogen', 'in', 'high', 'concentrations', 'and', 'with', 'optimal', 'binding', 'energies', 'numerous', 'mixed', 'carbon', 'boron', 'fullerenes', 'which', 'are', 'decorated', 'with', 'metal', 'atoms', 'were', 'previously', 'constructed', 'by', 'hand', 'and', 'proposed', 'as', 'a', 'promising', 'material', 'in', 'this', 'context', 'we', 'present', 'a', 'fully', 'abinitio', 'unbiased', 'structure', 'search', 'in', 'the', 'configurational', 'space', 'of', 'decorated', 'c48b12', 'and', 'find', 'that', 'most', 'of', 'the', 'hitherto', 'postulated', 'ground', 'state', 'structures', 'are', 'not', 'ground', 'states', 'we', 'determine', 'the', 'energetically', 'lowest', 'configurations', 'for', 'be', 'ca', 'li', 'and', 'sc', 'decorated', 'c48b12', 'clusters']] | [-0.06462727819702455, 0.1905811146744305, 0.012529848234927548, 0.0572978229701264, -0.0036538141042304537, -0.16462144729060432, 0.10542813357841667, 0.4643020672014072, -0.23254211803682015, -0.3288156275327007, 0.014821498833563445, -0.29487975832030533, -0.09535191211866081, 0.0964620802135739, 0.0466087385319129, -0.003108489597382556, 0.07511878492576736, -0.041172226020578476, -0.051576930056658706, -0.24171044816917164, 0.25366939983463715, 0.11998866586890515, 0.29401859573997735, 0.03195133704381684, 0.008313238942286088, -0.07508581319069933, 0.10241538003486182, 0.05919579311705006, -0.15759043294946468, 0.17451876248898252, 0.28315749218953506, -0.016240346134595927, 0.16677572478684374, -0.4664096149305503, -0.23383802776446655, 0.07480208373384639, 0.13292587726443475, 0.1993386069537207, -0.10304580739189294, -0.25869286259902374, 0.04045617950309645, -0.15444716258484514, -0.12389524212353752, -0.10180204789642067, 0.029596461975459187, 0.05380812648772484, -0.19933982163881106, 0.0364195627071673, -0.022655664918212488, 0.035294881279003765, -0.16044423529334986, -0.21749313527141653, -0.14066034037664177, 0.06098314406283732, -0.07387331134772726, 0.0056509746604466015, 0.15357134770047629, -0.06805168395762198, -0.07444523321464658, 0.41085825073311016, -0.040816876627061335, -0.1258618883688801, 0.21656424022235332, -0.12903333036367604, -0.17808555557054379, 0.1933071483037479, 0.052993765965636284, 0.15092971204735695, -0.1606432436307105, 0.06109763604555545, -0.050136728766596035, 0.16773454625425593, 0.06619377514081341, 0.07197489922067948, 0.23860888153735904, 0.18204969651110114, 0.03766733452877296, 0.14705218546441756, -0.09268156388064935, -0.0755939643187005, -0.1783481736090921, -0.22996694776451304, -0.19375151908025146, 0.016286422185484775, -0.011308611871624765, -0.2218393135505418, 0.29502602316261756, 0.05849994090385735, 0.2003875285764003, -0.06414241738301436, 0.20341821625230036, 0.020443330420502684, 0.06913349841211346, 0.03851555534804772, 0.2548096560418517, 0.14885779718003636, 0.030356555373319202, -0.1965196412063614, 0.12117095302147347, 0.04496764933823475] |
1,802.03764 | Cosmic Ray Origin: beyond the Standard Model(s). The case of Pulsar Wind
Nebulae and Unidentified very high energy gamma-ray sources | The riddle of the origin of Cosmic Rays is open since one century. Recently
we got the experimental proof of hadronic acceleration in Supernovae Remnants,
however new questions rised and no final answer has been provided so far. Gamma
ray observations above 100 MeV reveal the sites of cosmic ray acceleration to
energies where they are unaffected by solar modulation. In the last years the
knowledge in this field of research widely increased, however almost 50% of the
TeV (> 10^12 eV) Galactic sources are still unidentified, at GeV (> 10^9 eV)
energies, 67% of EGRET sources were unidentified and also with the newer
generation of gamma-ray satellites we have the same result: in fact, at low
Galactic latitudes (b<10 deg), 62% of the Fermi LAT detected sources have no
formal counterpart. Hence understanding the high energy unidentified sources
will be a crucial brick in solving the whole riddle of Cosmic Rays origin.
Several examples will be shown, underlining the importance of the so-called
"dark sources". Both theoretical aspects (with particular emphasis to the
so-called Ancient Pulsar Wind Nebulae scenario) and their observational proofs
will be discussed.
| astro-ph.HE | the riddle of the origin of cosmic rays is open since one century recently we got the experimental proof of hadronic acceleration in supernovae remnants however new questions rised and no final answer has been provided so far gamma ray observations above 100 mev reveal the sites of cosmic ray acceleration to energies where they are unaffected by solar modulation in the last years the knowledge in this field of research widely increased however almost 50 of the tev 1012 ev galactic sources are still unidentified at gev 109 ev energies 67 of egret sources were unidentified and also with the newer generation of gammaray satellites we have the same result in fact at low galactic latitudes b10 deg 62 of the fermi lat detected sources have no formal counterpart hence understanding the high energy unidentified sources will be a crucial brick in solving the whole riddle of cosmic rays origin several examples will be shown underlining the importance of the socalled dark sources both theoretical aspects with particular emphasis to the socalled ancient pulsar wind nebulae scenario and their observational proofs will be discussed | [['the', 'riddle', 'of', 'the', 'origin', 'of', 'cosmic', 'rays', 'is', 'open', 'since', 'one', 'century', 'recently', 'we', 'got', 'the', 'experimental', 'proof', 'of', 'hadronic', 'acceleration', 'in', 'supernovae', 'remnants', 'however', 'new', 'questions', 'rised', 'and', 'no', 'final', 'answer', 'has', 'been', 'provided', 'so', 'far', 'gamma', 'ray', 'observations', 'above', '100', 'mev', 'reveal', 'the', 'sites', 'of', 'cosmic', 'ray', 'acceleration', 'to', 'energies', 'where', 'they', 'are', 'unaffected', 'by', 'solar', 'modulation', 'in', 'the', 'last', 'years', 'the', 'knowledge', 'in', 'this', 'field', 'of', 'research', 'widely', 'increased', 'however', 'almost', '50', 'of', 'the', 'tev', '1012', 'ev', 'galactic', 'sources', 'are', 'still', 'unidentified', 'at', 'gev', '109', 'ev', 'energies', '67', 'of', 'egret', 'sources', 'were', 'unidentified', 'and', 'also', 'with', 'the', 'newer', 'generation', 'of', 'gammaray', 'satellites', 'we', 'have', 'the', 'same', 'result', 'in', 'fact', 'at', 'low', 'galactic', 'latitudes', 'b10', 'deg', '62', 'of', 'the', 'fermi', 'lat', 'detected', 'sources', 'have', 'no', 'formal', 'counterpart', 'hence', 'understanding', 'the', 'high', 'energy', 'unidentified', 'sources', 'will', 'be', 'a', 'crucial', 'brick', 'in', 'solving', 'the', 'whole', 'riddle', 'of', 'cosmic', 'rays', 'origin', 'several', 'examples', 'will', 'be', 'shown', 'underlining', 'the', 'importance', 'of', 'the', 'socalled', 'dark', 'sources', 'both', 'theoretical', 'aspects', 'with', 'particular', 'emphasis', 'to', 'the', 'socalled', 'ancient', 'pulsar', 'wind', 'nebulae', 'scenario', 'and', 'their', 'observational', 'proofs', 'will', 'be', 'discussed']] | [-0.08100068119599962, 0.18426850590653515, -0.00987153437643035, 0.1719012338869475, -0.11832595195297177, -0.061208484140602315, 0.03996359208548391, 0.391279428729133, -0.20518151050735567, -0.3935655148750221, 0.048476282740641086, -0.3407947687306315, 0.006687047501170152, 0.25443906281646844, -0.024581483088322045, -0.02504889774765517, 0.08196701708476285, -0.03947335723409983, -0.0010914033788533227, -0.27478525992235125, 0.22510357930803218, 0.19751463102780886, 0.20765975147164803, 0.10154255181802689, 0.10245429062712434, -0.11627338342997874, -0.07219438114379709, -0.07120006023088117, -0.10748197973982708, 0.06901692604430561, 0.2875270999363951, 0.12231883345222151, 0.2030421115067863, -0.3849808144785867, -0.25633694001951735, 0.126034883794853, 0.17305922744594313, 0.02424591383582132, -0.0895724094800047, -0.29478872283991125, 0.08493817276384279, -0.14762313243354092, -0.20595555542590652, 0.057776497590758306, 0.021323451475945075, 0.0419445175023095, -0.08687142919075701, 0.07548585669876932, 0.03283181997469148, 0.08286249933613313, -0.11912179067856758, -0.15274892333341208, 0.027136038386615345, 0.04622339982338048, 0.1295268948091148, 0.07469356801436358, 0.12340292065951822, -0.12184247293358517, -0.13193378640540146, 0.408540197935056, 0.008892395088096729, -0.024357110923911268, 0.1873793509524517, -0.2168804755207856, -0.22802921944373364, 0.20479279622007665, 0.11936525076728415, 0.0577653775948125, -0.19902732103364543, 0.10802054779298881, -0.0038417521562125233, 0.15300733200589045, 0.10113571310113813, 0.05389676649828215, 0.29484148567190044, 0.1311675506986904, 0.04246498791349901, 0.03968551597192984, -0.18969116677102205, -0.029720859811012003, -0.26794065060345706, -0.0948353315854596, -0.1366196588361384, 0.11975446812607146, -0.05924869602321131, -0.0919537770072615, 0.3708026842642072, 0.11630701273679733, 0.17421415868794193, -0.05760550720356027, 0.277162429232251, 0.04444186949498347, 0.0426379097579991, 0.1350837936297663, 0.3760138736584702, 0.12689078776165844, 0.135925107731207, -0.1167893324475232, 0.07430186104281127, -0.013704649051903068] |
1,802.03765 | Convex Formulations for Fair Principal Component Analysis | Though there is a growing body of literature on fairness for supervised
learning, the problem of incorporating fairness into unsupervised learning has
been less well-studied. This paper studies fairness in the context of principal
component analysis (PCA). We first present a definition of fairness for
dimensionality reduction, and our definition can be interpreted as saying that
a reduction is fair if information about a protected class (e.g., race or
gender) cannot be inferred from the dimensionality-reduced data points. Next,
we develop convex optimization formulations that can improve the fairness (with
respect to our definition) of PCA and kernel PCA. These formulations are
semidefinite programs (SDP's), and we demonstrate the effectiveness of our
formulations using several datasets. We conclude by showing how our approach
can be used to perform a fair (with respect to age) clustering of health data
that may be used to set health insurance rates.
| cs.LG math.OC stat.ML | though there is a growing body of literature on fairness for supervised learning the problem of incorporating fairness into unsupervised learning has been less wellstudied this paper studies fairness in the context of principal component analysis pca we first present a definition of fairness for dimensionality reduction and our definition can be interpreted as saying that a reduction is fair if information about a protected class eg race or gender cannot be inferred from the dimensionalityreduced data points next we develop convex optimization formulations that can improve the fairness with respect to our definition of pca and kernel pca these formulations are semidefinite programs sdps and we demonstrate the effectiveness of our formulations using several datasets we conclude by showing how our approach can be used to perform a fair with respect to age clustering of health data that may be used to set health insurance rates | [['though', 'there', 'is', 'a', 'growing', 'body', 'of', 'literature', 'on', 'fairness', 'for', 'supervised', 'learning', 'the', 'problem', 'of', 'incorporating', 'fairness', 'into', 'unsupervised', 'learning', 'has', 'been', 'less', 'wellstudied', 'this', 'paper', 'studies', 'fairness', 'in', 'the', 'context', 'of', 'principal', 'component', 'analysis', 'pca', 'we', 'first', 'present', 'a', 'definition', 'of', 'fairness', 'for', 'dimensionality', 'reduction', 'and', 'our', 'definition', 'can', 'be', 'interpreted', 'as', 'saying', 'that', 'a', 'reduction', 'is', 'fair', 'if', 'information', 'about', 'a', 'protected', 'class', 'eg', 'race', 'or', 'gender', 'can', 'not', 'be', 'inferred', 'from', 'the', 'dimensionalityreduced', 'data', 'points', 'next', 'we', 'develop', 'convex', 'optimization', 'formulations', 'that', 'can', 'improve', 'the', 'fairness', 'with', 'respect', 'to', 'our', 'definition', 'of', 'pca', 'and', 'kernel', 'pca', 'these', 'formulations', 'are', 'semidefinite', 'programs', 'sdps', 'and', 'we', 'demonstrate', 'the', 'effectiveness', 'of', 'our', 'formulations', 'using', 'several', 'datasets', 'we', 'conclude', 'by', 'showing', 'how', 'our', 'approach', 'can', 'be', 'used', 'to', 'perform', 'a', 'fair', 'with', 'respect', 'to', 'age', 'clustering', 'of', 'health', 'data', 'that', 'may', 'be', 'used', 'to', 'set', 'health', 'insurance', 'rates']] | [-0.058291843274255864, -0.011319136374466424, -0.1406052601405709, 0.0778695326872686, -0.13508896194744502, -0.15211721818982246, 0.051712766677499876, 0.4152091103588228, -0.2965875475736637, -0.3152269042967001, 0.1462799365344344, -0.29381344695827244, -0.13882606527673685, 0.19304482561907405, -0.17663605238084454, 0.05266627007969529, 0.10968473607932243, 0.02197389689752379, -0.06026863860677475, -0.3055985234174374, 0.3094568126268584, 0.02486113933028301, 0.29118721674800524, 0.05059426243580576, 0.06521133705187035, -0.015557762542173165, -0.03193303162540385, 0.10844101032519059, -0.0597325699172133, 0.1729880709293915, 0.3638143254793249, 0.2718837999933827, 0.35897300739118176, -0.373620435469658, -0.21970492410410597, 0.1468850286006715, 0.14987913829404656, 0.07461166035982142, -0.02204655554866091, -0.2743694681337582, 0.09977782946205824, -0.19656266176418677, -0.039628107833827066, -0.15142527849388285, -0.0568466839928029, -0.02495725028770598, -0.29490311367978417, 0.0692508512969456, 0.06330844880446691, 0.06904952776352041, -0.07670391998820107, -0.1484473976086372, 0.014432998775265406, 0.11385740137602379, 0.11308782159608814, 0.010651028956557196, 0.12897121495995167, -0.07930764718125952, -0.19974903153677195, 0.3856267365453941, -0.045016653412588044, -0.2224068927918435, 0.1972201221458916, -0.035184906408618634, -0.17939565744804772, 0.04740003091157288, 0.21628119770085086, 0.09444867801928036, -0.156686389202101, 0.009343390550064804, -0.09677440776942751, 0.1957404440382143, 0.030290715459331468, 0.012701987166184227, 0.15038407027974687, 0.20620578849323196, 0.11236662689495731, 0.13731218345315396, -0.0545951291223409, -0.06922475905220553, -0.24031778116949606, -0.1316569403405427, -0.18040490222188668, 0.02333596748753366, -0.10500075750187042, -0.11434128826383401, 0.3697520486642355, 0.18467769138216092, 0.16211998657436688, 0.11372068490379968, 0.3171790285158676, 0.10088948776634375, 0.10308466122070378, 0.1050877967098967, 0.20301093762375516, 0.07399155857274309, 0.07178485631074354, -0.2073926276045952, 0.11344226177567868, 0.02095325940722801] |
1,802.03766 | On slowly rotating black holes and nonlinear electrodynamics | We discuss the solution to Einstein's equations for a Lense-Thirring inspired
metric describing a slowly rotating black hole coupled to nonlinear
electrodynamics. We show that different schemes of rotation for the black hole
exist; they depend on a parameter $\gamma$ defining the dependence of the
metric on the polar angle. The fulfilment of the complete set of gravitational
field equations and conservation laws implies constraints on this parameter and
the metric functions. The vanishing of $\gamma$ provides the Lense-Thirring
line element associated to any non-linear electrodynamics; the Kerr-Newman
metric for slow rotation arises when $\gamma$ is not vanishing, a feature that
emphasises the unique role played by Maxwell's electrodynamics.
| gr-qc | we discuss the solution to einsteins equations for a lensethirring inspired metric describing a slowly rotating black hole coupled to nonlinear electrodynamics we show that different schemes of rotation for the black hole exist they depend on a parameter gamma defining the dependence of the metric on the polar angle the fulfilment of the complete set of gravitational field equations and conservation laws implies constraints on this parameter and the metric functions the vanishing of gamma provides the lensethirring line element associated to any nonlinear electrodynamics the kerrnewman metric for slow rotation arises when gamma is not vanishing a feature that emphasises the unique role played by maxwells electrodynamics | [['we', 'discuss', 'the', 'solution', 'to', 'einsteins', 'equations', 'for', 'a', 'lensethirring', 'inspired', 'metric', 'describing', 'a', 'slowly', 'rotating', 'black', 'hole', 'coupled', 'to', 'nonlinear', 'electrodynamics', 'we', 'show', 'that', 'different', 'schemes', 'of', 'rotation', 'for', 'the', 'black', 'hole', 'exist', 'they', 'depend', 'on', 'a', 'parameter', 'gamma', 'defining', 'the', 'dependence', 'of', 'the', 'metric', 'on', 'the', 'polar', 'angle', 'the', 'fulfilment', 'of', 'the', 'complete', 'set', 'of', 'gravitational', 'field', 'equations', 'and', 'conservation', 'laws', 'implies', 'constraints', 'on', 'this', 'parameter', 'and', 'the', 'metric', 'functions', 'the', 'vanishing', 'of', 'gamma', 'provides', 'the', 'lensethirring', 'line', 'element', 'associated', 'to', 'any', 'nonlinear', 'electrodynamics', 'the', 'kerrnewman', 'metric', 'for', 'slow', 'rotation', 'arises', 'when', 'gamma', 'is', 'not', 'vanishing', 'a', 'feature', 'that', 'emphasises', 'the', 'unique', 'role', 'played', 'by', 'maxwells', 'electrodynamics']] | [-0.21195694573497006, 0.10793013028680869, -0.07341499033665985, 0.0857880572497913, -0.16131506749181027, -0.13984744539569824, -0.005530582288057979, 0.27844589677801646, -0.22432548146045536, -0.23980411439450508, 0.045015155743068476, -0.2780808289236295, -0.11575328406595856, 0.24053812291528687, -0.05764788569489477, 0.0531772937147169, -0.01642401160142564, 0.03783062768997539, -0.11697077096029775, -0.1551864431111501, 0.41189514418397477, 0.0712795945465428, 0.24754029740536704, 0.0030227981234362366, 0.16922257265605783, -0.006723393352890234, -0.015435075976911489, 0.07085639626693425, -0.15406015068316647, 0.0452289882440701, 0.17614748143727696, 0.12875055589653348, 0.22217642354411543, -0.3884938484177404, -0.23810948634844856, 0.0870599775284597, 0.07500220992956994, 0.12477766599403609, -0.08273250030016167, -0.2718718239242946, 0.03494906207170645, -0.14784867942563917, -0.18800184125862504, -0.05187508075523677, 0.06754481062878333, -0.007554031293326562, -0.23913159462358427, 0.07177633663571072, 0.11387609814319315, -0.015639942542301628, -0.11416752105301092, -0.03455193094276917, -0.014621767798575377, 0.08866122000505763, 0.12387790375628398, 0.05850074760650003, 0.14700767478196447, -0.12371209378080836, -0.08451744417634306, 0.4143406268072511, -0.08741454187131256, -0.28384031700568463, 0.11175321174119043, -0.20487986027408356, -0.10663495887895413, 0.1097959052705112, 0.175562333319883, 0.17612861556112083, -0.11800791637466285, 0.15080494010380957, -0.011806088055424187, 0.1720046500948796, 0.09176842527412767, 0.03747616347711567, 0.27368761197484415, 0.08039881657048581, 0.04958100014242318, 0.08478125148888575, -0.03608592059473943, -0.11716709436780405, -0.3728426615237643, -0.1544220564308055, -0.1170915288150037, 0.11966766107951851, -0.18319967638571968, -0.20568078586301947, 0.35017224406362124, 0.08139341305770459, 0.14253550737993706, 0.0031833792374460794, 0.23061575497064843, 0.16136837642601962, 0.03450405539051894, 0.10101579133968014, 0.35988975847738053, 0.17088674991861533, 0.10265998693541922, -0.3057585194223099, -0.003974567496414305, 0.13003851539976552] |
1,802.03767 | Determinism and the Theory of Every Thing | Recently Gerard 't Hooft proposed a structure for a universe overwhelmed with
a control by a Theory of Everything (arXiv:1709.02874). He concludes, among
many other things, that such a universe could be fully deterministic and that,
accordingly, the divine intervention will be eliminated. Here I discuss such a
possibility and show that a fully deterministic universe will turn out to
become the divine himself, thus verifying the consistency of Einstein's belief.
| quant-ph | recently gerard t hooft proposed a structure for a universe overwhelmed with a control by a theory of everything arxiv170902874 he concludes among many other things that such a universe could be fully deterministic and that accordingly the divine intervention will be eliminated here i discuss such a possibility and show that a fully deterministic universe will turn out to become the divine himself thus verifying the consistency of einsteins belief | [['recently', 'gerard', 't', 'hooft', 'proposed', 'a', 'structure', 'for', 'a', 'universe', 'overwhelmed', 'with', 'a', 'control', 'by', 'a', 'theory', 'of', 'everything', 'arxiv170902874', 'he', 'concludes', 'among', 'many', 'other', 'things', 'that', 'such', 'a', 'universe', 'could', 'be', 'fully', 'deterministic', 'and', 'that', 'accordingly', 'the', 'divine', 'intervention', 'will', 'be', 'eliminated', 'here', 'i', 'discuss', 'such', 'a', 'possibility', 'and', 'show', 'that', 'a', 'fully', 'deterministic', 'universe', 'will', 'turn', 'out', 'to', 'become', 'the', 'divine', 'himself', 'thus', 'verifying', 'the', 'consistency', 'of', 'einsteins', 'belief']] | [-0.10891440334463758, 0.13827908422265733, -0.12599738524960621, 0.08728403471011137, -0.13449186248970882, -0.1723316689753639, 0.06119440161190661, 0.32623976685738726, -0.26815627089568544, -0.26494466055716787, 0.10443330470339528, -0.23564287873450668, -0.15552199984501516, 0.16634293108945714, -0.0677973833134664, -0.008424985901053462, 0.046196534509571, 0.012857157151613917, 0.025199626098453467, -0.3017276773661641, 0.29885906792644945, 0.07701681176133986, 0.2162402432345386, 0.026246982027909586, 0.09300084664885487, -0.04047124194912612, -0.03213266568657543, 0.12128808844967612, -0.06126999018337561, 0.06245635146541255, 0.2665300877232637, 0.20917899460930908, 0.35465606086820894, -0.4254674914159945, -0.2571559684883271, 0.11961934461058783, 0.16655912320794805, 0.1453698973304459, -0.060297552975160734, -0.32021945806752355, 0.08699535665634488, -0.209328974114864, -0.13987555061134377, -0.09798990965687802, 0.035218357960028306, -0.03643985871624734, -0.2336107815856979, -0.029057349184794086, 0.07080273595971188, -0.015186897425779274, -0.0142294724338821, -0.05173056617329296, -0.0034531527065805026, 0.07444680767200355, 0.03002350285699192, 0.03874006277349378, 0.11043972867940154, -0.13792382460087538, -0.1308627043983766, 0.3506607340083325, -0.06702615818940102, -0.14187034407098378, 0.153742820147558, -0.10182495398579963, -0.18205875224832976, 0.0559081307579098, 0.03730837284986462, 0.08134226813646299, -0.21045060189124862, 0.10972815729245278, -0.04143890413854803, 0.15409070033846156, 0.0837532462685236, 0.011343968480027148, 0.27281882351796544, 0.12006185264991863, 0.052959933044621724, 0.02691268659213425, 0.05271741642749735, -0.07713646420078087, -0.32226275902773655, -0.21585505518264003, -0.13226087957487576, 0.0963814611979095, -0.043079871204931154, -0.13811791032286627, 0.32522045238209624, 0.18964600721374153, 0.16282667073288135, 0.058169764819155846, 0.25539606091167244, 0.035612329747527836, 0.04814230562686654, 0.10165588156253631, 0.2868081984442792, 0.08306111746933312, 0.15500764116378768, -0.17892069412129266, 0.09622034373959261, 0.0403511692104595] |
1,802.03768 | Machine Learning and Evolutionary Computing for GUI-based Regression
Testing | ReTest is a novel testing tool for Java applications with a graphical user
interface (GUI), combining monkey testing and difference testing. Since this
combination sidesteps the oracle problem, it enables the generation of
GUI-based regression tests. ReTest makes use of evolutionary computing (EC),
particularly a genetic algorithm (GA), to optimize these tests towards code
coverage. While this is indeed a desirable goal in terms of software testing
and potentially finds many bugs, it lacks one major ingredient: human behavior.
Consequently, human testers often find the results less reasonable and
difficult to interpret.
This thesis proposes a new approach to improve the initial population of the
GA with the aid of machine learning (ML), forming an ML-technique enhanced-EC
(MLEC) algorithm. In order to do so, existing tests are exploited to extract
information on how human testers use the given GUI. The obtained data is then
utilized to train an artificial neural network (ANN), which ranks the available
GUI actions respectively their underlying GUI components at runtime---reducing
the gap between manually created and automatically generated regression tests.
Although the approach is implemented on top of ReTest, it can be easily used to
guide any form of monkey testing.
The results show that with only little training data, the ANN is able to
reach an accuracy of 82% and the resulting tests represent an improvement
without reducing the overall code coverage and performance significantly.
| cs.SE | retest is a novel testing tool for java applications with a graphical user interface gui combining monkey testing and difference testing since this combination sidesteps the oracle problem it enables the generation of guibased regression tests retest makes use of evolutionary computing ec particularly a genetic algorithm ga to optimize these tests towards code coverage while this is indeed a desirable goal in terms of software testing and potentially finds many bugs it lacks one major ingredient human behavior consequently human testers often find the results less reasonable and difficult to interpret this thesis proposes a new approach to improve the initial population of the ga with the aid of machine learning ml forming an mltechnique enhancedec mlec algorithm in order to do so existing tests are exploited to extract information on how human testers use the given gui the obtained data is then utilized to train an artificial neural network ann which ranks the available gui actions respectively their underlying gui components at runtimereducing the gap between manually created and automatically generated regression tests although the approach is implemented on top of retest it can be easily used to guide any form of monkey testing the results show that with only little training data the ann is able to reach an accuracy of 82 and the resulting tests represent an improvement without reducing the overall code coverage and performance significantly | [['retest', 'is', 'a', 'novel', 'testing', 'tool', 'for', 'java', 'applications', 'with', 'a', 'graphical', 'user', 'interface', 'gui', 'combining', 'monkey', 'testing', 'and', 'difference', 'testing', 'since', 'this', 'combination', 'sidesteps', 'the', 'oracle', 'problem', 'it', 'enables', 'the', 'generation', 'of', 'guibased', 'regression', 'tests', 'retest', 'makes', 'use', 'of', 'evolutionary', 'computing', 'ec', 'particularly', 'a', 'genetic', 'algorithm', 'ga', 'to', 'optimize', 'these', 'tests', 'towards', 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1,802.03769 | Learning Deep Convolutional Networks for Demosaicing | This paper presents a comprehensive study of applying the convolutional
neural network (CNN) to solving the demosaicing problem. The paper presents two
CNN models that learn end-to-end mappings between the mosaic samples and the
original image patches with full information. In the case the Bayer color
filter array (CFA) is used, an evaluation with ten competitive methods on
popular benchmarks confirms that the data-driven, automatically learned
features by the CNN models are very effective. Experiments show that the
proposed CNN models can perform equally well in both the sRGB space and the
linear space. It is also demonstrated that the CNN model can perform joint
denoising and demosaicing. The CNN model is very flexible and can be easily
adopted for demosaicing with any CFA design. We train CNN models for
demosaicing with three different CFAs and obtain better results than existing
methods. With the great flexibility to be coupled with any CFA, we present the
first data-driven joint optimization of the CFA design and the demosaicing
method using CNN. Experiments show that the combination of the automatically
discovered CFA pattern and the automatically devised demosaicing method
significantly outperforms the current best demosaicing results. Visual
comparisons confirm that the proposed methods reduce more visual artifacts than
existing methods. Finally, we show that the CNN model is also effective for the
more general demosaicing problem with spatially varying exposure and color and
can be used for taking images of higher dynamic ranges with a single shot. The
proposed models and the thorough experiments together demonstrate that CNN is
an effective and versatile tool for solving the demosaicing problem.
| cs.CV | this paper presents a comprehensive study of applying the convolutional neural network cnn to solving the demosaicing problem the paper presents two cnn models that learn endtoend mappings between the mosaic samples and the original image patches with full information in the case the bayer color filter array cfa is used an evaluation with ten competitive methods on popular benchmarks confirms that the datadriven automatically learned features by the cnn models are very effective experiments show that the proposed cnn models can perform equally well in both the srgb space and the linear space it is also demonstrated that the cnn model can perform joint denoising and demosaicing the cnn model is very flexible and can be easily adopted for demosaicing with any cfa design we train cnn models for demosaicing with three different cfas and obtain better results than existing methods with the great flexibility to be coupled with any cfa we present the first datadriven joint optimization of the cfa design and the demosaicing method using cnn experiments show that the combination of the automatically discovered cfa pattern and the automatically devised demosaicing method significantly outperforms the current best demosaicing results visual comparisons confirm that the proposed methods reduce more visual artifacts than existing methods finally we show that the cnn model is also effective for the more general demosaicing problem with spatially varying exposure and color and can be used for taking images of higher dynamic ranges with a single shot the proposed models and the thorough experiments together demonstrate that cnn is an effective and versatile tool for solving the demosaicing problem | [['this', 'paper', 'presents', 'a', 'comprehensive', 'study', 'of', 'applying', 'the', 'convolutional', 'neural', 'network', 'cnn', 'to', 'solving', 'the', 'demosaicing', 'problem', 'the', 'paper', 'presents', 'two', 'cnn', 'models', 'that', 'learn', 'endtoend', 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1,802.0377 | A simple solver for the fractional Laplacian in multiple dimensions | We present a simple discretization scheme for the hypersingular integral
representation of the fractional Laplace operator and solver for the
corresponding fractional Laplacian problem. Through singularity subtraction, we
obtain a regularized integrand that is amenable to the trapezoidal rule with
equispaced nodes, assuming a high degree of regularity in the underlying
function (i.e., $u\in C^6(R^d)$). The resulting quadrature scheme gives a
discrete operator on a regular grid that is translation-invariant and thus can
be applied quickly with the fast Fourier transform. For discretizations of
problems related to space-fractional diffusion on bounded domains, we observe
that the underlying linear system can be efficiently solved via preconditioned
Krylov methods with a preconditioner based on the finite-difference
(non-fractional) Laplacian. We show numerical results illustrating the error of
our simple scheme as well the efficiency of our preconditioning approach, both
for the elliptic (steady-state) fractional diffusion problem and the
time-dependent problem.
| math.NA cs.NA | we present a simple discretization scheme for the hypersingular integral representation of the fractional laplace operator and solver for the corresponding fractional laplacian problem through singularity subtraction we obtain a regularized integrand that is amenable to the trapezoidal rule with equispaced nodes assuming a high degree of regularity in the underlying function ie uin c6rd the resulting quadrature scheme gives a discrete operator on a regular grid that is translationinvariant and thus can be applied quickly with the fast fourier transform for discretizations of problems related to spacefractional diffusion on bounded domains we observe that the underlying linear system can be efficiently solved via preconditioned krylov methods with a preconditioner based on the finitedifference nonfractional laplacian we show numerical results illustrating the error of our simple scheme as well the efficiency of our preconditioning approach both for the elliptic steadystate fractional diffusion problem and the timedependent problem | [['we', 'present', 'a', 'simple', 'discretization', 'scheme', 'for', 'the', 'hypersingular', 'integral', 'representation', 'of', 'the', 'fractional', 'laplace', 'operator', 'and', 'solver', 'for', 'the', 'corresponding', 'fractional', 'laplacian', 'problem', 'through', 'singularity', 'subtraction', 'we', 'obtain', 'a', 'regularized', 'integrand', 'that', 'is', 'amenable', 'to', 'the', 'trapezoidal', 'rule', 'with', 'equispaced', 'nodes', 'assuming', 'a', 'high', 'degree', 'of', 'regularity', 'in', 'the', 'underlying', 'function', 'ie', 'uin', 'c6rd', 'the', 'resulting', 'quadrature', 'scheme', 'gives', 'a', 'discrete', 'operator', 'on', 'a', 'regular', 'grid', 'that', 'is', 'translationinvariant', 'and', 'thus', 'can', 'be', 'applied', 'quickly', 'with', 'the', 'fast', 'fourier', 'transform', 'for', 'discretizations', 'of', 'problems', 'related', 'to', 'spacefractional', 'diffusion', 'on', 'bounded', 'domains', 'we', 'observe', 'that', 'the', 'underlying', 'linear', 'system', 'can', 'be', 'efficiently', 'solved', 'via', 'preconditioned', 'krylov', 'methods', 'with', 'a', 'preconditioner', 'based', 'on', 'the', 'finitedifference', 'nonfractional', 'laplacian', 'we', 'show', 'numerical', 'results', 'illustrating', 'the', 'error', 'of', 'our', 'simple', 'scheme', 'as', 'well', 'the', 'efficiency', 'of', 'our', 'preconditioning', 'approach', 'both', 'for', 'the', 'elliptic', 'steadystate', 'fractional', 'diffusion', 'problem', 'and', 'the', 'timedependent', 'problem']] | [-0.08520673383154893, 0.004518687169303582, -0.11476972156319104, 0.05689806435719668, -0.1061850025187795, -0.14968556803587366, 0.012755027613347422, 0.39070444053983033, -0.3580543579763337, -0.23286915271963976, 0.16640652878423642, -0.24624019384077966, -0.15598994566204205, 0.2259993982291621, -0.06637655790777214, 0.13243375779831246, 0.11343528037214626, 0.0011677432243954646, -0.1082762613053727, -0.21676556227014285, 0.3231146710937562, -0.0038254890744000266, 0.2200165560009749, 0.04735085594608155, 0.15838025657983165, -0.030651276891298387, -0.03830709835922677, -0.0016906528752807476, -0.08781302321222029, 0.12709915710829217, 0.2200134628586318, 0.04341819945863155, 0.3030818028388264, -0.42606748155101315, -0.2099871186679867, 0.09313897563986583, 0.16905587925320517, 0.07217545198174576, -0.045593434701552485, -0.27149473848012723, 0.08861276028958494, -0.12718136653980663, -0.15446503903104425, -0.12873966142388493, -0.044600567772461436, 0.05671884479760256, -0.36058718519770117, 0.12781670079757906, 0.053638294914080314, -0.005159918148284268, -0.06761718045741524, -0.12760095986496173, 0.026340418576569078, 0.026025141264018538, -0.0327753019455361, -0.006087304587310103, 0.04526665597143009, -0.058732771302720095, -0.1217542758374156, 0.37252360555241265, -0.08428678172162084, -0.35099869721556365, 0.11155065348250665, -0.1089144286457194, -0.08003763727403616, 0.12391802465083869, 0.16800928140403576, 0.20021246102230292, -0.08771086433162428, 0.13148144628311992, -0.03859377092975255, 0.13969738678911012, 0.04501665537947253, -0.023580260718343397, 0.056034735053114286, 0.15607679442483421, 0.1741788839946871, 0.1383441178166397, -0.05933129182324604, -0.12427568247650227, -0.3129041106503916, -0.14683991125529658, -0.2416214467606775, 0.0390647598406721, -0.16316120946839252, -0.2190452777487162, 0.3939873800489245, 0.12794730819806405, 0.1454475973605191, 0.09025293934375864, 0.29517335571310394, 0.2603812521931154, 0.030822515908679734, 0.1079035271278085, 0.11533561772475504, 0.15107784203209035, 0.1141950854176834, -0.2942695431219899, -0.013020586519030063, 0.2079655554958688] |
1,802.03771 | Heusler, Weyl, and Berry | Heusler materials, initially discovered by Fritz Heusler more than a century
ago, have grown into a family of more than 1000 compounds, synthesized from
combinations of more than 40 elements. These materials show a wide range of
properties, but new properties are constantly being found. Most recently, by
incorporating heavy elements that can give rise to strong spin-orbit coupling
(SOC), non-trivial topological phases of matter, such as topological insulators
(TIs), have been discovered in Heusler materials. Moreover, the interplay of
symmetry, SOC and magnetic structure allows for the realization of a wide
variety of topological phases through Berry curvature design. Weyl points and
nodal lines can be manipulated by various external perturbations, which results
in exotic properties such as the chiral anomaly, and large anomalous spin and
topological Hall effects. The combination of a non-collinear magnetic structure
and Berry curvature gives rise a non-zero anomalous Hall effect, which was
first observed in the antiferromagnets Mn3Sn and Mn3Ge. Besides this k-space
Berry curvature, Heusler compounds with non-collinear magnetic structures also
possess real-space topological states in the form of magnetic antiskyrmions,
which have not yet been observed in other materials. The possibility of
directly manipulating the Berry curvature shows the importance of understanding
both the electronic and magnetic structures of Heusler compounds. Together,
with the new topological viewpoint and the high tunability, novel physical
properties and phenomena await discovery in Heusler compounds.
| cond-mat.mtrl-sci | heusler materials initially discovered by fritz heusler more than a century ago have grown into a family of more than 1000 compounds synthesized from combinations of more than 40 elements these materials show a wide range of properties but new properties are constantly being found most recently by incorporating heavy elements that can give rise to strong spinorbit coupling soc nontrivial topological phases of matter such as topological insulators tis have been discovered in heusler materials moreover the interplay of symmetry soc and magnetic structure allows for the realization of a wide variety of topological phases through berry curvature design weyl points and nodal lines can be manipulated by various external perturbations which results in exotic properties such as the chiral anomaly and large anomalous spin and topological hall effects the combination of a noncollinear magnetic structure and berry curvature gives rise a nonzero anomalous hall effect which was first observed in the antiferromagnets mn3sn and mn3ge besides this kspace berry curvature heusler compounds with noncollinear magnetic structures also possess realspace topological states in the form of magnetic antiskyrmions which have not yet been observed in other materials the possibility of directly manipulating the berry curvature shows the importance of understanding both the electronic and magnetic structures of heusler compounds together with the new topological viewpoint and the high tunability novel physical properties and phenomena await discovery in heusler compounds | [['heusler', 'materials', 'initially', 'discovered', 'by', 'fritz', 'heusler', 'more', 'than', 'a', 'century', 'ago', 'have', 'grown', 'into', 'a', 'family', 'of', 'more', 'than', '1000', 'compounds', 'synthesized', 'from', 'combinations', 'of', 'more', 'than', '40', 'elements', 'these', 'materials', 'show', 'a', 'wide', 'range', 'of', 'properties', 'but', 'new', 'properties', 'are', 'constantly', 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0.1250336878907705, 0.020093637605643144] |
1,802.03772 | The BiEntropy of Some Knots on the Simple Cubic Lattice | Binary representations of the trefoil and other knots of up to ten crossings
in the simple cubic lattice were created. The BiEntropy of each knot was
computed using a variety of binary encodings and compared against controls.
This showed that binary encoded knots are highly disordered information
objects. The BiEntropy of knots on the simple cubic lattice increases slightly
as the number of crossings and length of encoding increases. We show that the
non-alternating knots of nine and ten crossings are more disordered than the
alternating knots of nine and ten crossings.
| math.GM | binary representations of the trefoil and other knots of up to ten crossings in the simple cubic lattice were created the bientropy of each knot was computed using a variety of binary encodings and compared against controls this showed that binary encoded knots are highly disordered information objects the bientropy of knots on the simple cubic lattice increases slightly as the number of crossings and length of encoding increases we show that the nonalternating knots of nine and ten crossings are more disordered than the alternating knots of nine and ten crossings | [['binary', 'representations', 'of', 'the', 'trefoil', 'and', 'other', 'knots', 'of', 'up', 'to', 'ten', 'crossings', 'in', 'the', 'simple', 'cubic', 'lattice', 'were', 'created', 'the', 'bientropy', 'of', 'each', 'knot', 'was', 'computed', 'using', 'a', 'variety', 'of', 'binary', 'encodings', 'and', 'compared', 'against', 'controls', 'this', 'showed', 'that', 'binary', 'encoded', 'knots', 'are', 'highly', 'disordered', 'information', 'objects', 'the', 'bientropy', 'of', 'knots', 'on', 'the', 'simple', 'cubic', 'lattice', 'increases', 'slightly', 'as', 'the', 'number', 'of', 'crossings', 'and', 'length', 'of', 'encoding', 'increases', 'we', 'show', 'that', 'the', 'nonalternating', 'knots', 'of', 'nine', 'and', 'ten', 'crossings', 'are', 'more', 'disordered', 'than', 'the', 'alternating', 'knots', 'of', 'nine', 'and', 'ten', 'crossings']] | [-0.23496984700129056, 0.16184189943596722, -0.03230811301618815, 0.0665136517271296, -0.05870922690567871, -0.16902351379911934, 0.05332858610587816, 0.4091398376143641, -0.2407645798805687, -0.3507494430989027, 0.07439085388840694, -0.295160634484556, -0.142492943831409, 0.23011769416431585, -0.005019720716194974, -0.009985411718177298, 0.0896340290394922, 0.05450704320230418, -0.10119906321892308, -0.3340433284950753, 0.2831253927304513, -0.027562779715905587, 0.15683792533559932, -0.02283208858118289, 0.07133660418395367, -0.0010560060437354777, -0.041909526134582445, 0.03284878417228659, -0.11115726808477322, 0.14700255919661787, 0.1764719635222314, 0.038660190637326904, 0.12892406015501667, -0.4053710504124562, -0.17051257521121038, 0.06296869294924869, 0.19174566859793332, 0.09657413833257225, 0.008388037809345406, -0.23267542057437823, 0.09471000354581822, -0.18574612755845818, -0.11707142858455578, -0.03282947552700837, 0.02916994382523828, 0.06844383887170503, -0.1226984020943443, 0.034779329542329325, 0.03449717236475812, 0.11923406129806406, -0.006663526703293125, -0.13495850438614274, -0.06963507254711455, 0.11749840101175424, 0.004318380024698046, 0.05018626514485934, 0.07871686044769982, -0.18177141536855035, -0.1885990608509423, 0.41472016390826966, -0.01064492792696304, -0.14166616671201254, 0.234249552546276, -0.12406759976098934, -0.1598250325956744, 0.27850931288881436, 0.08967740432255798, 0.13482423041843705, -0.045832010979453726, -0.017975044251135032, -0.10279190761761534, 0.1862880722891229, 0.16603039825956026, -0.003655294334102008, 0.17435816688165587, 0.0885415594610903, 0.003282998347034057, 0.2518459723130541, -0.14182340478877853, -0.0644820857896573, -0.22996753085818555, -0.1736054717977014, -0.1537166917981166, 0.02572226483737015, -0.13719685426832356, -0.16837176047265529, 0.4471223220332629, 0.02780590559123084, 0.20259559113635786, 0.0880785233548118, 0.22836633866859807, 0.044367793881489585, 0.10161326558639606, 0.09843048881739377, 0.17162163948847187, 0.1138672266026131, -0.06298124612205558, -0.14208985664364365, 0.03177427138822774, 0.07507650938092006] |
1,802.03773 | QRkit: Sparse, Composable QR Decompositions for Efficient and Stable
Solutions to Problems in Computer Vision | Embedded computer vision applications increasingly require the speed and
power benefits of single-precision (32 bit) floating point. However,
applications which make use of Levenberg-like optimization can lose significant
accuracy when reducing to single precision, sometimes unrecoverably so. This
accuracy can be regained using solvers based on QR rather than Cholesky
decomposition, but the absence of sparse QR solvers for common sparsity
patterns found in computer vision means that many applications cannot benefit.
We introduce an open-source suite of solvers for Eigen, which efficiently
compute the QR decomposition for matrices with some common sparsity patterns
(block diagonal, horizontal and vertical concatenation, and banded). For
problems with very particular sparsity structures, these elements can be
composed together in 'kit' form, hence the name QRkit. We apply our methods to
several computer vision problems, showing competitive performance and
suitability especially in single precision arithmetic.
| cs.NA cs.MS | embedded computer vision applications increasingly require the speed and power benefits of singleprecision 32 bit floating point however applications which make use of levenberglike optimization can lose significant accuracy when reducing to single precision sometimes unrecoverably so this accuracy can be regained using solvers based on qr rather than cholesky decomposition but the absence of sparse qr solvers for common sparsity patterns found in computer vision means that many applications cannot benefit we introduce an opensource suite of solvers for eigen which efficiently compute the qr decomposition for matrices with some common sparsity patterns block diagonal horizontal and vertical concatenation and banded for problems with very particular sparsity structures these elements can be composed together in kit form hence the name qrkit we apply our methods to several computer vision problems showing competitive performance and suitability especially in single precision arithmetic | [['embedded', 'computer', 'vision', 'applications', 'increasingly', 'require', 'the', 'speed', 'and', 'power', 'benefits', 'of', 'singleprecision', '32', 'bit', 'floating', 'point', 'however', 'applications', 'which', 'make', 'use', 'of', 'levenberglike', 'optimization', 'can', 'lose', 'significant', 'accuracy', 'when', 'reducing', 'to', 'single', 'precision', 'sometimes', 'unrecoverably', 'so', 'this', 'accuracy', 'can', 'be', 'regained', 'using', 'solvers', 'based', 'on', 'qr', 'rather', 'than', 'cholesky', 'decomposition', 'but', 'the', 'absence', 'of', 'sparse', 'qr', 'solvers', 'for', 'common', 'sparsity', 'patterns', 'found', 'in', 'computer', 'vision', 'means', 'that', 'many', 'applications', 'can', 'not', 'benefit', 'we', 'introduce', 'an', 'opensource', 'suite', 'of', 'solvers', 'for', 'eigen', 'which', 'efficiently', 'compute', 'the', 'qr', 'decomposition', 'for', 'matrices', 'with', 'some', 'common', 'sparsity', 'patterns', 'block', 'diagonal', 'horizontal', 'and', 'vertical', 'concatenation', 'and', 'banded', 'for', 'problems', 'with', 'very', 'particular', 'sparsity', 'structures', 'these', 'elements', 'can', 'be', 'composed', 'together', 'in', 'kit', 'form', 'hence', 'the', 'name', 'qrkit', 'we', 'apply', 'our', 'methods', 'to', 'several', 'computer', 'vision', 'problems', 'showing', 'competitive', 'performance', 'and', 'suitability', 'especially', 'in', 'single', 'precision', 'arithmetic']] | [-0.07086462189930008, 0.014595260177910655, -0.06833246619969928, 0.04356077617861786, -0.11344164527162053, -0.18514165376051725, -0.023956215082795072, 0.41632074053338963, -0.3419857781326814, -0.34101592430429495, 0.17801304631313752, -0.21117326395130523, -0.17863583997588792, 0.24746529169367265, -0.10845894606368577, 0.12105470366454382, 0.16713846471033347, 0.020316834936735872, -0.1616557950820613, -0.27422877386875666, 0.213810225727586, 0.058170854247999275, 0.29067623894661665, 0.00941086454290173, 0.0633016383617098, -0.016405351285775787, 0.0031270257150419326, 0.01647185714473184, -0.0014390406961885295, 0.16043191421576006, 0.32861832116073897, 0.18653463937757578, 0.32144898933479094, -0.4743433449176147, -0.17119096901616176, 0.10281402008815689, 0.22256289279463587, 0.08150293442869572, -0.08893970644232153, -0.2258117887787789, 0.13704907229729668, -0.15854083375817687, -0.06808116250330576, -0.15613242536330957, -0.0319947267969628, 0.011689746399785279, -0.2880927399705372, 0.027365325869684168, 0.03144381186596567, 0.08824313371006748, 0.05821609184005224, -0.21290291694374822, 0.06877372182885573, 0.11274984236425559, -0.005674563056836239, -0.013429833820639111, 0.15945654562691214, -0.15682139873283532, -0.14368363040693694, 0.4159861643054931, -0.02511173883055608, -0.24768293344770834, 0.20692261425684466, -0.04247758323795718, -0.16527428710498185, 0.1118105962946207, 0.21601921687465456, 0.08294509868171039, -0.0787238073992759, 0.07704063902086437, -0.011592581090952852, 0.22906787814208132, 0.1280808006245777, 0.024304497260064315, 0.19000620535648555, 0.14304480490127325, 0.07825579101566507, 0.09248125572729078, -0.06327292284084042, -0.10054719529496572, -0.15827172838499864, -0.1373306807941295, -0.18355246768969533, -0.015137140010881385, -0.13450464881703647, -0.1942249393599818, 0.3617472099525546, 0.18937852888924184, 0.1397363748099896, 0.05516909941086184, 0.3710226181747137, 0.06982273605640428, 0.13362649770574175, 0.1359263151137011, 0.15957950787361638, 0.10692339904418738, 0.11115289437283071, -0.15941316265907648, 0.06180870635836995, 0.050378670155492834] |
1,802.03774 | On Kernel Method-Based Connectionist Models and Supervised Deep Learning
Without Backpropagation | We propose a novel family of connectionist models based on kernel machines
and consider the problem of learning layer-by-layer a compositional hypothesis
class, i.e., a feedforward, multilayer architecture, in a supervised setting.
In terms of the models, we present a principled method to "kernelize" (partly
or completely) any neural network (NN). With this method, we obtain a
counterpart of any given NN that is powered by kernel machines instead of
neurons. In terms of learning, when learning a feedforward deep architecture in
a supervised setting, one needs to train all the components simultaneously
using backpropagation (BP) since there are no explicit targets for the hidden
layers (Rumelhart86). We consider without loss of generality the two-layer case
and present a general framework that explicitly characterizes a target for the
hidden layer that is optimal for minimizing the objective function of the
network. This characterization then makes possible a purely greedy training
scheme that learns one layer at a time, starting from the input layer. We
provide realizations of the abstract framework under certain architectures and
objective functions. Based on these realizations, we present a layer-wise
training algorithm for an l-layer feedforward network for classification, where
l>=2 can be arbitrary. This algorithm can be given an intuitive geometric
interpretation that makes the learning dynamics transparent. Empirical results
are provided to complement our theory. We show that the kernelized networks,
trained layer-wise, compare favorably with classical kernel machines as well as
other connectionist models trained by BP. We also visualize the inner workings
of the greedy kernelized models to validate our claim on the transparency of
the layer-wise algorithm.
| cs.LG cs.AI stat.ML | we propose a novel family of connectionist models based on kernel machines and consider the problem of learning layerbylayer a compositional hypothesis class ie a feedforward multilayer architecture in a supervised setting in terms of the models we present a principled method to kernelize partly or completely any neural network nn with this method we obtain a counterpart of any given nn that is powered by kernel machines instead of neurons in terms of learning when learning a feedforward deep architecture in a supervised setting one needs to train all the components simultaneously using backpropagation bp since there are no explicit targets for the hidden layers rumelhart86 we consider without loss of generality the twolayer case and present a general framework that explicitly characterizes a target for the hidden layer that is optimal for minimizing the objective function of the network this characterization then makes possible a purely greedy training scheme that learns one layer at a time starting from the input layer we provide realizations of the abstract framework under certain architectures and objective functions based on these realizations we present a layerwise training algorithm for an llayer feedforward network for classification where l2 can be arbitrary this algorithm can be given an intuitive geometric interpretation that makes the learning dynamics transparent empirical results are provided to complement our theory we show that the kernelized networks trained layerwise compare favorably with classical kernel machines as well as other connectionist models trained by bp we also visualize the inner workings of the greedy kernelized models to validate our claim on the transparency of the layerwise algorithm | [['we', 'propose', 'a', 'novel', 'family', 'of', 'connectionist', 'models', 'based', 'on', 'kernel', 'machines', 'and', 'consider', 'the', 'problem', 'of', 'learning', 'layerbylayer', 'a', 'compositional', 'hypothesis', 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1,802.03775 | An Algebraic Framework for Runtime Verification | Runtime verification (RV) is a pragmatic and scalable, yet rigorous
technique, to assess the correctness of complex systems, including
cyber-physical systems (CPS). By measuring how robustly a CPS run satisfies a
specification, RV allows in addition, to quantify the resiliency of a CPS to
perturbations. In this paper we propose Algebraic Runtime Verification (ARV), a
general, semantic framework for RV, which takes advantage of the monoidal
structure of runs (w.r.t. concatenation) and the semiring structure of a
specification automaton (w.r.t. choice and concatenation), to compute in an
incremental and application specific fashion the resiliency measure. This
allows us to expose the core aspects of RV, by developing an abstract
monitoring algorithm, and to strengthen and unify the various qualitative and
quantitative approaches to RV, by instantiating choice and concatenation with
real-valued functions as dictated by the application. We demonstrate the power
and effectiveness of our framework on two case studies from the automotive
domain.
| cs.LO | runtime verification rv is a pragmatic and scalable yet rigorous technique to assess the correctness of complex systems including cyberphysical systems cps by measuring how robustly a cps run satisfies a specification rv allows in addition to quantify the resiliency of a cps to perturbations in this paper we propose algebraic runtime verification arv a general semantic framework for rv which takes advantage of the monoidal structure of runs wrt concatenation and the semiring structure of a specification automaton wrt choice and concatenation to compute in an incremental and application specific fashion the resiliency measure this allows us to expose the core aspects of rv by developing an abstract monitoring algorithm and to strengthen and unify the various qualitative and quantitative approaches to rv by instantiating choice and concatenation with realvalued functions as dictated by the application we demonstrate the power and effectiveness of our framework on two case studies from the automotive domain | [['runtime', 'verification', 'rv', 'is', 'a', 'pragmatic', 'and', 'scalable', 'yet', 'rigorous', 'technique', 'to', 'assess', 'the', 'correctness', 'of', 'complex', 'systems', 'including', 'cyberphysical', 'systems', 'cps', 'by', 'measuring', 'how', 'robustly', 'a', 'cps', 'run', 'satisfies', 'a', 'specification', 'rv', 'allows', 'in', 'addition', 'to', 'quantify', 'the', 'resiliency', 'of', 'a', 'cps', 'to', 'perturbations', 'in', 'this', 'paper', 'we', 'propose', 'algebraic', 'runtime', 'verification', 'arv', 'a', 'general', 'semantic', 'framework', 'for', 'rv', 'which', 'takes', 'advantage', 'of', 'the', 'monoidal', 'structure', 'of', 'runs', 'wrt', 'concatenation', 'and', 'the', 'semiring', 'structure', 'of', 'a', 'specification', 'automaton', 'wrt', 'choice', 'and', 'concatenation', 'to', 'compute', 'in', 'an', 'incremental', 'and', 'application', 'specific', 'fashion', 'the', 'resiliency', 'measure', 'this', 'allows', 'us', 'to', 'expose', 'the', 'core', 'aspects', 'of', 'rv', 'by', 'developing', 'an', 'abstract', 'monitoring', 'algorithm', 'and', 'to', 'strengthen', 'and', 'unify', 'the', 'various', 'qualitative', 'and', 'quantitative', 'approaches', 'to', 'rv', 'by', 'instantiating', 'choice', 'and', 'concatenation', 'with', 'realvalued', 'functions', 'as', 'dictated', 'by', 'the', 'application', 'we', 'demonstrate', 'the', 'power', 'and', 'effectiveness', 'of', 'our', 'framework', 'on', 'two', 'case', 'studies', 'from', 'the', 'automotive', 'domain']] | [-0.11477061763104178, -0.023282686316267613, -0.09215888279405507, 0.04244064423180028, -0.1162834387853161, -0.12943081283645536, 0.08932522065142266, 0.35814137814125024, -0.28982513429984064, -0.31056941214755374, 0.10446848055157303, -0.20352207597472868, -0.15314304887720795, 0.1849020981477791, -0.15206392995964785, 0.11857869418023469, 0.06892222239539124, -0.029516936519845424, -0.06269234562498312, -0.22047419869114174, 0.3215121591657207, 0.04127804071842028, 0.25959633344893235, 0.03402247062473038, 0.08505974170092687, 0.02734175472907335, -0.06496761061626112, 0.018644584392729615, -0.083528024489181, 0.1572060628080523, 0.29676554817432316, 0.23795367429915865, 0.293547327010348, -0.4025312703610821, -0.1581471060015648, 0.07024003261573274, 0.1194385385538403, 0.05867774786303642, -0.010574252226740702, -0.320080493049176, 0.1291303467504414, -0.22465786734571705, -0.07967066352388688, -0.16461809282115503, 0.03673314877979264, 0.029607310606916615, -0.291396696691238, -0.030930351986029704, 0.09740715068855697, 0.11895630570346272, -0.05159485253411672, -0.04497544560430257, 0.02194243627252638, 0.12121503259502835, 0.007178009833910732, 0.020586202725429426, 0.14597218229387005, -0.07002431057187934, -0.16169933801782982, 0.39048586229872345, -0.06628975284892677, -0.19845590500354574, 0.2161419645750097, -0.056978951879571395, -0.16909853960750262, 0.0466439050452953, 0.19647272077522107, 0.0780045189864498, -0.17304606020356855, 0.08604381783440553, 0.006598231244330331, 0.22520671428072375, 0.05604528509346502, 0.028064489638653597, 0.1735352088558161, 0.20689142603644883, 0.08502967388357048, 0.16277168313791227, -0.03336208145430481, -0.10535039316088736, -0.2783759939907627, -0.18406213941233981, -0.10440272924961982, -0.023301168328284154, -0.09596141111988245, -0.15607030653431045, 0.43640962622261475, 0.216244564178591, 0.158365589282294, 0.1377927697386121, 0.366028878635231, 0.09641593907862998, 0.061310299189138384, 0.0714679577647914, 0.14560041880210886, 0.11907059696877932, 0.11160592006991146, -0.21157089854415215, 0.13938511908961485, 0.05098948153280109] |
1,802.03776 | Correlation between Superconductivity and Magnetic Fluctuations in
Fe(Se1-xSx) Revealed by 77Se NMR | We present $^{77}$Se-NMR measurements on FeSe$_{1-x}$S$_x$ samples with
sulfur content $x=0,9,15$ and $29\%$. Twinned nematic domains are observed in
the NMR spectrum for all samples except $x=29\%$. The NMR spin-lattice
relaxation rate shows that magnetic fluctuations are initially enhanced between
$x=0\%$ and $x=9\%$, but are strongly suppressed for higher $x$ values. The
observed behavior of the magnetic fluctuations parallels the superconducting
transition temperature $T_c$ in these materials, providing strong evidence for
the primary importance of magnetic fluctuations for superconductivity, despite
the presence of nematic quantum criticality in this system.
| cond-mat.supr-con cond-mat.str-el | we present 77senmr measurements on fese_1xs_x samples with sulfur content x0915 and 29 twinned nematic domains are observed in the nmr spectrum for all samples except x29 the nmr spinlattice relaxation rate shows that magnetic fluctuations are initially enhanced between x0 and x9 but are strongly suppressed for higher x values the observed behavior of the magnetic fluctuations parallels the superconducting transition temperature t_c in these materials providing strong evidence for the primary importance of magnetic fluctuations for superconductivity despite the presence of nematic quantum criticality in this system | [['we', 'present', '77senmr', 'measurements', 'on', 'fese_1xs_x', 'samples', 'with', 'sulfur', 'content', 'x0915', 'and', '29', 'twinned', 'nematic', 'domains', 'are', 'observed', 'in', 'the', 'nmr', 'spectrum', 'for', 'all', 'samples', 'except', 'x29', 'the', 'nmr', 'spinlattice', 'relaxation', 'rate', 'shows', 'that', 'magnetic', 'fluctuations', 'are', 'initially', 'enhanced', 'between', 'x0', 'and', 'x9', 'but', 'are', 'strongly', 'suppressed', 'for', 'higher', 'x', 'values', 'the', 'observed', 'behavior', 'of', 'the', 'magnetic', 'fluctuations', 'parallels', 'the', 'superconducting', 'transition', 'temperature', 't_c', 'in', 'these', 'materials', 'providing', 'strong', 'evidence', 'for', 'the', 'primary', 'importance', 'of', 'magnetic', 'fluctuations', 'for', 'superconductivity', 'despite', 'the', 'presence', 'of', 'nematic', 'quantum', 'criticality', 'in', 'this', 'system']] | [-0.2052408998424653, 0.2551404147260738, -0.010996445314958692, 0.027264853578261947, 0.0035538488247601144, -0.1302938116396862, 0.06355550983359783, 0.3885718524794687, -0.2082924578571692, -0.2903499089774083, 0.0254424440698296, -0.3877500696531074, -0.08184180914593692, 0.18045426714657384, 0.07463389641435986, 0.0019257970259125366, -0.07829538937023078, -0.010257249256193807, -0.1266864795457381, -0.22636760397422637, 0.2708677028369328, 0.02764280038139656, 0.3463134170425209, 0.07089627954833717, -0.0077318773943592205, -0.040190541844243526, 0.1281445143871348, 0.0409596693194048, -0.16199204529179537, 0.02077925020024519, 0.2913470638556067, -0.05169479822507128, 0.14797364196841623, -0.39534149335866625, -0.22410099738573824, 0.07101426380739378, 0.12802834673890506, 0.11044860326960175, -0.11788293834780977, -0.2529357802969488, 0.06745938372676558, -0.0554249909420667, -0.09920203288360922, -0.12479682555633852, -0.004183679231738841, 0.009334748587041924, -0.2569892187814482, 0.20671730681153183, 0.0921163486359133, 0.163077379333448, -0.1384283762441059, -0.1509942683928371, -0.029334138523236932, 0.0499098542813127, 0.08257059863006527, 0.07201310039222748, 0.1936498571303673, -0.12085985965148377, -0.06772017023864794, 0.2985014884219378, -0.04231779009304856, -0.01905342797875743, 0.16420709536495534, -0.2781520682196556, -0.14150499037615108, 0.21469403005374427, 0.09684806278991429, 0.07313254666620526, -0.10960214914203706, 0.031488086944922215, 0.03357293260474266, 0.2188760033618151, -0.025378737355243753, 0.10821967860366302, 0.2659883626408621, 0.17607667816231365, -0.007773581722920591, 0.14671143520073118, -0.11416869686747139, -0.06139003765367141, -0.21814297369564883, -0.14913328725312816, -0.18714148675578393, 0.05146310181722087, -0.09175990104367057, -0.1562534972220998, 0.3276036369709552, 0.15600499913720836, 0.2067103248237717, -0.04925199119712819, 0.19644642948829147, 0.05382779113477392, 0.038019221000881356, 0.05661086939190599, 0.26820480261548335, 0.19675294987709177, 0.17342303913954477, -0.32207940361166204, 0.13415397692535241, -0.03284337751525031] |
1,802.03777 | On Separable $\A^2$ and $\A^3$-forms | In this paper, we will prove that any $\A^3$-form over a field $k$ of
characteristic zero is trivial provided it has a locally nilpotent derivation
satisfying certain properties. We will also show that the result of T.
Kambayashi on the triviality of separable $\A^2$-forms over a field $k$ extends
to $\A^2$-forms over any one-dimensional Noetherian domain containing $\bQ$.
| math.AC | in this paper we will prove that any a3form over a field k of characteristic zero is trivial provided it has a locally nilpotent derivation satisfying certain properties we will also show that the result of t kambayashi on the triviality of separable a2forms over a field k extends to a2forms over any onedimensional noetherian domain containing bq | [['in', 'this', 'paper', 'we', 'will', 'prove', 'that', 'any', 'a3form', 'over', 'a', 'field', 'k', 'of', 'characteristic', 'zero', 'is', 'trivial', 'provided', 'it', 'has', 'a', 'locally', 'nilpotent', 'derivation', 'satisfying', 'certain', 'properties', 'we', 'will', 'also', 'show', 'that', 'the', 'result', 'of', 't', 'kambayashi', 'on', 'the', 'triviality', 'of', 'separable', 'a2forms', 'over', 'a', 'field', 'k', 'extends', 'to', 'a2forms', 'over', 'any', 'onedimensional', 'noetherian', 'domain', 'containing', 'bq']] | [-0.21658954219202753, 0.1106797022814, -0.12771462178271678, -0.05403968990194025, -0.09441135827607165, -0.13039958667596457, -0.0004870916147612863, 0.37357562756234847, -0.3046944656719764, -0.14185355971049932, 0.07281645779558285, -0.20893351661248338, -0.09959999883236985, 0.2429053239800312, -0.08689592811451466, -0.08091855980455875, 0.03805542699302788, 0.17976146536292853, -0.12444772013394093, -0.32953485011778494, 0.35026017714429786, -0.07534957704720674, 0.17451834523429474, 0.08447736088634918, 0.11078006058017274, 0.03958503381970028, 0.027550586999428493, 0.08053728275828892, -0.19037350352677837, 0.06520651819839797, 0.2844384374028003, 0.10587589977809263, 0.2825460398086795, -0.3195863915607333, -0.23125896030278117, 0.21874043637783164, 0.15373747492278064, 0.04851688303191353, -0.020839386205706332, -0.23651453699157746, 0.24332697087622904, -0.15962708989347987, -0.14440497466259533, -0.07813173880869592, 0.05547655455302447, 0.0013602703844231587, -0.27485491336254336, -0.01445771352424614, 0.17990115478082938, 0.11875311312852083, -0.08534778126825888, -0.08475147357077933, -0.0006582587267513629, 0.028624819134603494, -0.01599460945861345, 0.0704717416126557, 0.07123645658915241, -0.06664120612441804, -0.08295371254940552, 0.3219567513334806, -0.1310851688893443, -0.17977735382953175, 0.18799377703625295, -0.2035516820744508, -0.1024046558369365, 0.1452381328455414, 0.06903273058641288, 0.16296832342804582, -0.06902407861694142, 0.25055578375166215, -0.17534629993692594, 0.1410620473276746, 0.06950131381206491, 0.02185529899886913, 0.13980108233927577, 0.09164091257412953, 0.16534325463214405, 0.13227441182567012, -0.012742584023659152, -0.013103781466337817, -0.4076673247747951, -0.20813391561171524, -0.16363229786683978, 0.18463762683138527, -0.0340619019612118, -0.16976685194229638, 0.41903008900030897, 0.1460550812728427, 0.17077448248380311, 0.10637218640530827, 0.22397650088425036, 0.08150980011042622, 0.0757007179091926, 0.10808096614804256, 0.11652429491557457, 0.1778690805486231, 0.022152773550866794, -0.15028703310181973, -0.009013429206485549, 0.07033401310305905] |
1,802.03778 | Sample Design for Audit Populations | We develop several tools for the determination of sample size and design for
MediCal audits. This audit setting involves a population of claims for
reimbursement by a healthcare provider which need to be reviewed by an auditor
to determine the correct amount for each claim. The existing literature
regarding sample planning for audits is incomplete and often includes
restrictive assumptions. To fill these gaps, we exploit the special
relationship between the known claim amounts and the unknown post-audit
amounts. We propose a hypergeometric generative process for audit populations
which we use to derive estimators of variances needed for sample size
determination. We further develop a criterion for choosing between simple
expansion and ratio estimation and an efficient method for determining exact
optimal strata breakpoints in populations with repeated values. We also derive
a variance estimator under a more general "partial error" model than previous
researchers have used. These tools apply more generally to audits where an
overstated book/claim amount is the primary concern and estimation of the total
dollar value of the claim errors is the goal. The sample design methods we
develop are illustrated on two simulated audit populations.
| stat.ME stat.AP | we develop several tools for the determination of sample size and design for medical audits this audit setting involves a population of claims for reimbursement by a healthcare provider which need to be reviewed by an auditor to determine the correct amount for each claim the existing literature regarding sample planning for audits is incomplete and often includes restrictive assumptions to fill these gaps we exploit the special relationship between the known claim amounts and the unknown postaudit amounts we propose a hypergeometric generative process for audit populations which we use to derive estimators of variances needed for sample size determination we further develop a criterion for choosing between simple expansion and ratio estimation and an efficient method for determining exact optimal strata breakpoints in populations with repeated values we also derive a variance estimator under a more general partial error model than previous researchers have used these tools apply more generally to audits where an overstated bookclaim amount is the primary concern and estimation of the total dollar value of the claim errors is the goal the sample design methods we develop are illustrated on two simulated audit populations | [['we', 'develop', 'several', 'tools', 'for', 'the', 'determination', 'of', 'sample', 'size', 'and', 'design', 'for', 'medical', 'audits', 'this', 'audit', 'setting', 'involves', 'a', 'population', 'of', 'claims', 'for', 'reimbursement', 'by', 'a', 'healthcare', 'provider', 'which', 'need', 'to', 'be', 'reviewed', 'by', 'an', 'auditor', 'to', 'determine', 'the', 'correct', 'amount', 'for', 'each', 'claim', 'the', 'existing', 'literature', 'regarding', 'sample', 'planning', 'for', 'audits', 'is', 'incomplete', 'and', 'often', 'includes', 'restrictive', 'assumptions', 'to', 'fill', 'these', 'gaps', 'we', 'exploit', 'the', 'special', 'relationship', 'between', 'the', 'known', 'claim', 'amounts', 'and', 'the', 'unknown', 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1,802.03779 | Formation of the UV Spectrum of Molecular Hydrogen in the Sun | Ultraviolet lines of molecular hydrogen have been observed in solar spectra
for almost four decades, but the behavior of the molecular spectrum and its
implications for solar atmospheric structure are not fully understood. Data
from the HRTS instrument revealed that H2 emission forms in particular regions,
selectively excited by bright UV transition region and chromospheric lines. We
test the conditions under which H2 emission can originate by studying non-LTE
models sampling a broad range of temperature stratifications and radiation
conditions. Stratification plays the dominant role in determining the
population densities of H2, which forms in greatest abundance near the
continuum photosphere. However, opacity due to photoionization of silicon and
other neutrals determines the depth to which UV radiation can penetrate to
excite the H2. Thus the majority of H2 emission forms in a narrow region, at
about 650 km in standard 1D models of the quiet-Sun, near the tau=1 opacity
surface for the exciting UV radiation, generally coming from above. When
irradiated from above using observed intensities of bright UV emission lines,
detailed non-LTE calculations show that the spectrum of H2 seen in the
quiet-Sun SUMER atlas spectrum and HRTS light bridge spectrum can be
satisfactorily reproduced in 1D stratified atmospheres, without including 3D or
time dependent thermal structures. A detailed comparison to observations from
1205 to 1550 Angstroms is presented, and the success of this 1D approach to
modeling solar UV H2 emission is illustrated by the identification of
previously unidentified lines and upper levels in HRTS spectra.
| astro-ph.SR | ultraviolet lines of molecular hydrogen have been observed in solar spectra for almost four decades but the behavior of the molecular spectrum and its implications for solar atmospheric structure are not fully understood data from the hrts instrument revealed that h2 emission forms in particular regions selectively excited by bright uv transition region and chromospheric lines we test the conditions under which h2 emission can originate by studying nonlte models sampling a broad range of temperature stratifications and radiation conditions stratification plays the dominant role in determining the population densities of h2 which forms in greatest abundance near the continuum photosphere however opacity due to photoionization of silicon and other neutrals determines the depth to which uv radiation can penetrate to excite the h2 thus the majority of h2 emission forms in a narrow region at about 650 km in standard 1d models of the quietsun near the tau1 opacity surface for the exciting uv radiation generally coming from above when irradiated from above using observed intensities of bright uv emission lines detailed nonlte calculations show that the spectrum of h2 seen in the quietsun sumer atlas spectrum and hrts light bridge spectrum can be satisfactorily reproduced in 1d stratified atmospheres without including 3d or time dependent thermal structures a detailed comparison to observations from 1205 to 1550 angstroms is presented and the success of this 1d approach to modeling solar uv h2 emission is illustrated by the identification of previously unidentified lines and upper levels in hrts spectra | [['ultraviolet', 'lines', 'of', 'molecular', 'hydrogen', 'have', 'been', 'observed', 'in', 'solar', 'spectra', 'for', 'almost', 'four', 'decades', 'but', 'the', 'behavior', 'of', 'the', 'molecular', 'spectrum', 'and', 'its', 'implications', 'for', 'solar', 'atmospheric', 'structure', 'are', 'not', 'fully', 'understood', 'data', 'from', 'the', 'hrts', 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1,802.0378 | Spontaneous decay of a soft optical phonon in the relaxor ferroelectric
PbMg$_{1/3}$Nb$_{2/3}$O$_{3}$ | We report the spontaneous decay of a soft, optical phonon in a solid. Using
neutron spectroscopy, we find that specific phonon lifetimes in the relaxor
PbMg$_{1/3}$Nb$_{2/3}$O$_{3}$ are anomalously short within well-defined ranges
of energy and momentum. This behavior is independent of ferroelectric order and
occurs when the optical phonon with a specific energy and momentum can
kinematically decay into two acoustic phonons with lower phase velocity. We
interpret the well-known relaxor "waterfall" effect as a form of quasiparticle
decay analogous to that previously reported in quantum spin liquids and quantum
fluids.
| cond-mat.mtrl-sci | we report the spontaneous decay of a soft optical phonon in a solid using neutron spectroscopy we find that specific phonon lifetimes in the relaxor pbmg_13nb_23o_3 are anomalously short within welldefined ranges of energy and momentum this behavior is independent of ferroelectric order and occurs when the optical phonon with a specific energy and momentum can kinematically decay into two acoustic phonons with lower phase velocity we interpret the wellknown relaxor waterfall effect as a form of quasiparticle decay analogous to that previously reported in quantum spin liquids and quantum fluids | [['we', 'report', 'the', 'spontaneous', 'decay', 'of', 'a', 'soft', 'optical', 'phonon', 'in', 'a', 'solid', 'using', 'neutron', 'spectroscopy', 'we', 'find', 'that', 'specific', 'phonon', 'lifetimes', 'in', 'the', 'relaxor', 'pbmg_13nb_23o_3', 'are', 'anomalously', 'short', 'within', 'welldefined', 'ranges', 'of', 'energy', 'and', 'momentum', 'this', 'behavior', 'is', 'independent', 'of', 'ferroelectric', 'order', 'and', 'occurs', 'when', 'the', 'optical', 'phonon', 'with', 'a', 'specific', 'energy', 'and', 'momentum', 'can', 'kinematically', 'decay', 'into', 'two', 'acoustic', 'phonons', 'with', 'lower', 'phase', 'velocity', 'we', 'interpret', 'the', 'wellknown', 'relaxor', 'waterfall', 'effect', 'as', 'a', 'form', 'of', 'quasiparticle', 'decay', 'analogous', 'to', 'that', 'previously', 'reported', 'in', 'quantum', 'spin', 'liquids', 'and', 'quantum', 'fluids']] | [-0.13083755871751807, 0.3137866794182868, -0.10641840358193104, 0.04648520762694406, -0.09794732544489287, -0.11968230212537143, 0.07159035568442809, 0.4082907250376193, -0.2466805158745866, -0.21834473293479328, -0.0024654917063314345, -0.2979373165641676, -0.09332832732944044, 0.20722465364487616, 0.05290622385679283, 0.0357318584510422, -0.028992926376963872, 0.0017469112689678485, -0.0719992487926732, -0.11889162650050411, 0.2529401613583604, -0.0002094928512943315, 0.2974234500306321, 0.07841834742454351, 0.06365712892755375, -0.008013421910108773, 0.08085990332803883, -0.009050812182057609, -0.1782587757546795, 0.03730410479705085, 0.2605103387850449, -0.08463887967481751, 0.18077972116828947, -0.41160863480315757, -0.21705133723642595, 0.06816766471960224, 0.18221347408041685, 0.17642538222883428, -0.06540922469019399, -0.23044424331081764, 0.022037152037188246, -0.16084500014075784, -0.09831866032474644, -0.09650889632629824, 0.017392493502984007, 0.01260785751075453, -0.19558700741074242, 0.18096340412867593, 0.04735676949884701, 0.0541836381019963, -0.1276952404743777, -0.11113260496039312, -0.03047097816162712, 0.016365591358907704, 0.08859407148774263, 0.012560079959067669, 0.1550977152035377, -0.08831012189122182, -0.11035425995814276, 0.37413245707668447, -0.08598815419347855, -0.07246016807199179, 0.16701086310178534, -0.21222545388717573, -0.06983302947604558, 0.20014257470125352, 0.13450361654203344, 0.09477437091581933, -0.14338033816058848, 0.017588493808244284, 0.011873977610606004, 0.19107382612528054, 0.06285021087451541, 0.17762995117272323, 0.22888238109893852, 0.18425150766359785, -0.06849770707456948, 0.17082375999294466, -0.14463788904454355, -0.06384880318828337, -0.2767488598851692, -0.17109705430230351, -0.18433311088829413, 0.09719729312224784, -0.05679389016106622, -0.16553242546557398, 0.3956892458225631, 0.06751961905252096, 0.19572338083206298, -0.007277061058090652, 0.2735435422202879, 0.12795513111888177, 0.0818460468448453, 0.059986433889307494, 0.31826482103257386, 0.16059803202809705, 0.12646936393946737, -0.33071574193405007, 0.03478555595195228, -0.000751386350532482] |
1,802.03781 | The speed of gravitational waves and power-law solutions in a
scalar-tensor model | One of the most relevant solutions in any cosmological model concerning the
evolution of the universe is the power-law solution. For the scalar-tensor
model of dark energy with kinetic and Gauss Bonnet couplings, it is shown that
we can conserve the power-law solution and at the same time meet the recent
observational bound on the speed of gravitational waves. In the FRW background
the anomalous contribution to the speed of gravitational waves, coming from the
kinetic and Gauss-Bonnet couplings, cancel each other for power-law solutions.
It is shown that by simple restriction on the model parameters we can achieve a
non-time-dependent cancellation of the defect in the velocity of the
gravitational waves. The model can realize the cosmic expansion with
contributions from the kinetic and Gauss-Bonnet couplings of the order of
${\cal O}(1)$ to the dark energy density parameter. The results are valid on
the homogeneous FRW background and the limitations of the approach are
discussed.
| gr-qc | one of the most relevant solutions in any cosmological model concerning the evolution of the universe is the powerlaw solution for the scalartensor model of dark energy with kinetic and gauss bonnet couplings it is shown that we can conserve the powerlaw solution and at the same time meet the recent observational bound on the speed of gravitational waves in the frw background the anomalous contribution to the speed of gravitational waves coming from the kinetic and gaussbonnet couplings cancel each other for powerlaw solutions it is shown that by simple restriction on the model parameters we can achieve a nontimedependent cancellation of the defect in the velocity of the gravitational waves the model can realize the cosmic expansion with contributions from the kinetic and gaussbonnet couplings of the order of cal o1 to the dark energy density parameter the results are valid on the homogeneous frw background and the limitations of the approach are discussed | [['one', 'of', 'the', 'most', 'relevant', 'solutions', 'in', 'any', 'cosmological', 'model', 'concerning', 'the', 'evolution', 'of', 'the', 'universe', 'is', 'the', 'powerlaw', 'solution', 'for', 'the', 'scalartensor', 'model', 'of', 'dark', 'energy', 'with', 'kinetic', 'and', 'gauss', 'bonnet', 'couplings', 'it', 'is', 'shown', 'that', 'we', 'can', 'conserve', 'the', 'powerlaw', 'solution', 'and', 'at', 'the', 'same', 'time', 'meet', 'the', 'recent', 'observational', 'bound', 'on', 'the', 'speed', 'of', 'gravitational', 'waves', 'in', 'the', 'frw', 'background', 'the', 'anomalous', 'contribution', 'to', 'the', 'speed', 'of', 'gravitational', 'waves', 'coming', 'from', 'the', 'kinetic', 'and', 'gaussbonnet', 'couplings', 'cancel', 'each', 'other', 'for', 'powerlaw', 'solutions', 'it', 'is', 'shown', 'that', 'by', 'simple', 'restriction', 'on', 'the', 'model', 'parameters', 'we', 'can', 'achieve', 'a', 'nontimedependent', 'cancellation', 'of', 'the', 'defect', 'in', 'the', 'velocity', 'of', 'the', 'gravitational', 'waves', 'the', 'model', 'can', 'realize', 'the', 'cosmic', 'expansion', 'with', 'contributions', 'from', 'the', 'kinetic', 'and', 'gaussbonnet', 'couplings', 'of', 'the', 'order', 'of', 'cal', 'o1', 'to', 'the', 'dark', 'energy', 'density', 'parameter', 'the', 'results', 'are', 'valid', 'on', 'the', 'homogeneous', 'frw', 'background', 'and', 'the', 'limitations', 'of', 'the', 'approach', 'are', 'discussed']] | [-0.15888295818317252, 0.14240402655783468, -0.0775061066244514, 0.08919449724504748, -0.09064902230434549, -0.10023595835380734, -0.04039751492942182, 0.2819714332238222, -0.22929433892997436, -0.308132457278239, 0.04683051081090712, -0.3063228565017478, -0.08185030912789397, 0.1759210412736791, 0.02812177421620641, 0.04093500445611799, -0.015202170506549569, 0.06985786813311279, -0.028826269428603925, -0.24942261847452477, 0.33562068715213966, 0.0934441175717765, 0.24616150081923338, 0.06844719690390122, 0.11155208779904896, -0.08664266704521978, -0.029391931862427063, 0.015223889671361599, -0.15939073357479244, 0.05997145125039447, 0.14748245524839523, 0.08987890512575038, 0.1762090232402373, -0.42684152761760813, -0.2628933485680952, 0.10653893610175985, 0.12192207356864133, 0.14980039424979344, -0.029336148376713913, -0.2771611159506182, 0.04076581777562984, -0.17471716253277966, -0.12999377484606484, -0.03506007407588932, -0.009201356209814548, 0.02823792843339153, -0.24615980789232522, 0.1227055032653973, 0.02430135347784903, -0.09581424958574083, -0.10416526838283365, -0.06986581281317064, -0.04329124231858609, 0.05721388811257501, 0.14118042305702916, 0.033800007172454245, 0.10282619964355269, -0.1807822346305236, -0.08078687316857469, 0.41576757102918166, -0.1433578108486612, -0.20841940887009677, 0.16491639813802278, -0.1595554645591153, -0.12873009704531002, 0.13602136291984396, 0.1295894960908649, 0.09071694430018304, -0.1422905282338317, 0.1785475581937368, 0.04942233150583119, 0.15733003918938218, 0.09312356512348813, 0.026746511673524927, 0.25496701385754234, 0.11120549764764757, 0.04863005274166472, 0.07945379407707757, -0.07325377476921019, -0.0825905265370145, -0.381096598572838, -0.1356609457650801, -0.16998841355029398, 0.04707471901574769, -0.17090962256126938, -0.1404313349104576, 0.4139753856863349, 0.1606521172902714, 0.14186814260513833, 0.07342159518828759, 0.2767368607963316, 0.13849784215227162, 0.053161726121265344, 0.08151172906554376, 0.33563233241558266, 0.12838777544973895, 0.11329063494919794, -0.2473423451734468, 0.011053275646050818, 0.06987990389387004] |
1,802.03782 | Evolution of spatially resolved star formation main sequence and surface
density profiles in massive disc galaxies at $0\lesssim z \lesssim 1$:
inside-out stellar mass buildup and quenching | We investigate a relation between surface densities of star formation rate
(SFR) and stellar mass ($M_{*}$) at a $\sim 1$ kpc scale namely spatially
resolved star formation main sequence (SFMS) in massive
($\log(M_{*}/M_{\odot})>10.5$) face-on disc galaxies at $0.01<z<0.02$ and
$0.8<z<1.8$ and examine evolution of the relation. The spatially resolved SFMS
of $z\sim 0$ galaxies is discussed in a companion paper. For $z\sim 1$ sample,
we use 8 bands imaging dataset from CANDELS and 3D-HST and perform a
pixel-to-pixel SED fitting to derive the spatially resolved SFR and $M_{*}$. We
find a linear spatially resolved SFMS in the $z\sim 1$ galaxies that lie on the
global SFMS, while a 'flattening' at high $\Sigma_{*}$ end is found in that
relation for the galaxies that lie below the global SFMS. Comparison with the
spatially resolved SFMS of the $z\sim 0$ galaxies shows smaller difference in
the specific SFR (sSFR) at low $\Sigma_{*}$ than that at high $\Sigma_{*}$.
This trend is consistent with the evolution of the sSFR$(r)$ radial profile,
which shows a faster decrease in the central region than in the outskirt,
agrees with the inside-out quenching scenario. We then derive an empirical
model for the evolution of the $\Sigma_{*}(r)$, $\Sigma_{\rm SFR}(r)$ and
sSFR$(r)$ radial profiles. Based on the empirical model, we estimate the radial
profile of the quenching timescale and reproduce the observed spatially
resolved SFMS at $z\sim 1$ and $z\sim 0$.
| astro-ph.GA | we investigate a relation between surface densities of star formation rate sfr and stellar mass m_ at a sim 1 kpc scale namely spatially resolved star formation main sequence sfms in massive logm_m_odot105 faceon disc galaxies at 001z002 and 08z18 and examine evolution of the relation the spatially resolved sfms of zsim 0 galaxies is discussed in a companion paper for zsim 1 sample we use 8 bands imaging dataset from candels and 3dhst and perform a pixeltopixel sed fitting to derive the spatially resolved sfr and m_ we find a linear spatially resolved sfms in the zsim 1 galaxies that lie on the global sfms while a flattening at high sigma_ end is found in that relation for the galaxies that lie below the global sfms comparison with the spatially resolved sfms of the zsim 0 galaxies shows smaller difference in the specific sfr ssfr at low sigma_ than that at high sigma_ this trend is consistent with the evolution of the ssfrr radial profile which shows a faster decrease in the central region than in the outskirt agrees with the insideout quenching scenario we then derive an empirical model for the evolution of the sigma_r sigma_rm sfrr and ssfrr radial profiles based on the empirical model we estimate the radial profile of the quenching timescale and reproduce the observed spatially resolved sfms at zsim 1 and zsim 0 | [['we', 'investigate', 'a', 'relation', 'between', 'surface', 'densities', 'of', 'star', 'formation', 'rate', 'sfr', 'and', 'stellar', 'mass', 'm_', 'at', 'a', 'sim', '1', 'kpc', 'scale', 'namely', 'spatially', 'resolved', 'star', 'formation', 'main', 'sequence', 'sfms', 'in', 'massive', 'logm_m_odot105', 'faceon', 'disc', 'galaxies', 'at', '001z002', 'and', '08z18', 'and', 'examine', 'evolution', 'of', 'the', 'relation', 'the', 'spatially', 'resolved', 'sfms', 'of', 'zsim', '0', 'galaxies', 'is', 'discussed', 'in', 'a', 'companion', 'paper', 'for', 'zsim', '1', 'sample', 'we', 'use', '8', 'bands', 'imaging', 'dataset', 'from', 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1,802.03783 | Surrealistic Bohmian trajectories do not occur with macroscopic pointers | We discuss whether position measurements in quantum mechanics can be
contradictory with Bohmian trajectories, leading to what has been called
\textquotedblleft surrealistic trajectories\textquotedblright\ in the
literature. Previous work has considered that a single Bohmian position can be
ascribed to the pointer. Nevertheless, a correct treatment of a macroscopic
pointer requires that many particle positions should be included in the
dynamics of the system, and that statistical averages should be made over their
random initial values. Using numerical as well as analytical calculations, we
show that these surrealistic trajectories exist only if the pointer contains a
small number of particles; they completely disappear with macroscopic pointers.
With microscopic pointers, non-local effects of quantum entanglement can
indeed take place and introduce unexpected trajectories, as in Bell
experiments; moreover, the initial values of the Bohmian positions associated
with the measurement apparatus may influence the trajectory of the test
particle, and determine the result of measurement. Nevertheless, a detailed
observation of the trajectories of the particles of the pointer can still
reveal the nature of the trajectory of the test particle; nothing looks
surrealistic if all trajectories are properly interpreted.
| quant-ph | we discuss whether position measurements in quantum mechanics can be contradictory with bohmian trajectories leading to what has been called textquotedblleft surrealistic trajectoriestextquotedblright in the literature previous work has considered that a single bohmian position can be ascribed to the pointer nevertheless a correct treatment of a macroscopic pointer requires that many particle positions should be included in the dynamics of the system and that statistical averages should be made over their random initial values using numerical as well as analytical calculations we show that these surrealistic trajectories exist only if the pointer contains a small number of particles they completely disappear with macroscopic pointers with microscopic pointers nonlocal effects of quantum entanglement can indeed take place and introduce unexpected trajectories as in bell experiments moreover the initial values of the bohmian positions associated with the measurement apparatus may influence the trajectory of the test particle and determine the result of measurement nevertheless a detailed observation of the trajectories of the particles of the pointer can still reveal the nature of the trajectory of the test particle nothing looks surrealistic if all trajectories are properly interpreted | [['we', 'discuss', 'whether', 'position', 'measurements', 'in', 'quantum', 'mechanics', 'can', 'be', 'contradictory', 'with', 'bohmian', 'trajectories', 'leading', 'to', 'what', 'has', 'been', 'called', 'textquotedblleft', 'surrealistic', 'trajectoriestextquotedblright', 'in', 'the', 'literature', 'previous', 'work', 'has', 'considered', 'that', 'a', 'single', 'bohmian', 'position', 'can', 'be', 'ascribed', 'to', 'the', 'pointer', 'nevertheless', 'a', 'correct', 'treatment', 'of', 'a', 'macroscopic', 'pointer', 'requires', 'that', 'many', 'particle', 'positions', 'should', 'be', 'included', 'in', 'the', 'dynamics', 'of', 'the', 'system', 'and', 'that', 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1,802.03784 | Uncertainty Principles Associated with the Offset Linear Canonical
Transform | As a time-shifted and frequency-modulated version of the linear canonical
transform (LCT), the offset linear canonical transform (OLCT) provides a more
general framework of most existing linear integral transforms in signal
processing and optics. To study simultaneous localization of a signal and its
OLCT, the classical Heisenberg's uncertainty principle has been recently
generalized for the OLCT. In this paper, we complement it by presenting another
two uncertainty principles, i.e., Donoho-Stark's uncertainty principle and
Amrein-Berthier-Benedicks's uncertainty principle, for the OLCT. Moreover, we
generalize the short-time LCT to the short-time OLCT. We likewise present
Lieb's uncertainty principle for the short-time OLCT and give a lower bound for
its essential support.
| eess.SP | as a timeshifted and frequencymodulated version of the linear canonical transform lct the offset linear canonical transform olct provides a more general framework of most existing linear integral transforms in signal processing and optics to study simultaneous localization of a signal and its olct the classical heisenbergs uncertainty principle has been recently generalized for the olct in this paper we complement it by presenting another two uncertainty principles ie donohostarks uncertainty principle and amreinberthierbenedickss uncertainty principle for the olct moreover we generalize the shorttime lct to the shorttime olct we likewise present liebs uncertainty principle for the shorttime olct and give a lower bound for its essential support | [['as', 'a', 'timeshifted', 'and', 'frequencymodulated', 'version', 'of', 'the', 'linear', 'canonical', 'transform', 'lct', 'the', 'offset', 'linear', 'canonical', 'transform', 'olct', 'provides', 'a', 'more', 'general', 'framework', 'of', 'most', 'existing', 'linear', 'integral', 'transforms', 'in', 'signal', 'processing', 'and', 'optics', 'to', 'study', 'simultaneous', 'localization', 'of', 'a', 'signal', 'and', 'its', 'olct', 'the', 'classical', 'heisenbergs', 'uncertainty', 'principle', 'has', 'been', 'recently', 'generalized', 'for', 'the', 'olct', 'in', 'this', 'paper', 'we', 'complement', 'it', 'by', 'presenting', 'another', 'two', 'uncertainty', 'principles', 'ie', 'donohostarks', 'uncertainty', 'principle', 'and', 'amreinberthierbenedickss', 'uncertainty', 'principle', 'for', 'the', 'olct', 'moreover', 'we', 'generalize', 'the', 'shorttime', 'lct', 'to', 'the', 'shorttime', 'olct', 'we', 'likewise', 'present', 'liebs', 'uncertainty', 'principle', 'for', 'the', 'shorttime', 'olct', 'and', 'give', 'a', 'lower', 'bound', 'for', 'its', 'essential', 'support']] | [-0.07599964743493265, 0.04537534071483983, -0.1617425195082038, 0.13442388967993088, -0.11299194204664947, -0.11082434816777988, 0.03568067717835975, 0.3348681334898157, -0.3137454409646485, -0.247140007831578, 0.13513136130454512, -0.22392370341837686, -0.1814244362824368, 0.25112280063331127, -0.10110724029320134, 0.1242787534467665, 0.04480799907853581, 0.04273605793011638, -0.12425098032910237, -0.1405236465243605, 0.24314088509681653, 0.05230726429397451, 0.2929602314340267, 0.022303081119766914, 0.15992974947681124, 0.09887598924567255, -0.03618619804938306, -0.010749811148446685, -0.12785674700126895, 0.19726108269379386, 0.23345276837254753, 0.15328092916367822, 0.28469357844980275, -0.38919593279583836, -0.2277979760327517, 0.1223254962824285, 0.0868617022401249, 0.0965130220756005, -0.023381395031119266, -0.3020522755236839, 0.02128865147632204, -0.13767694364266717, -0.10171037668555553, -0.08088984405885469, 0.01613001880358975, -0.020105923771998793, -0.2540500180198337, 0.15525374029991482, 0.15567968550708172, 0.0435835994551626, -0.03691189826679205, -0.07984374918566384, 0.09140790608834545, 0.07907389994394386, 0.00014052844940210289, 0.019044952851474145, 0.07094087238195089, -0.037564566835567775, -0.12698917717339014, 0.3647718830209858, -0.06520896390045308, -0.20932321071203025, 0.13173143405748425, -0.12784989745211173, -0.17966463108424027, 0.0741884665847053, 0.13802822618657407, 0.05712223091197886, -0.19521344036197746, 0.0706587072724327, -0.03787493628432166, 0.16044072203891668, 0.05991525511380355, 0.08466115609999693, 0.12007421380752381, 0.1321233026046341, 0.10743959056090494, 0.1721348613939898, -0.11156776439363383, -0.09451562178514476, -0.29238418479151324, -0.20244077596437837, -0.1816623302787226, 0.012978559748691349, -0.08167284572832528, -0.10709342003782403, 0.3587912808892862, 0.15788225765627772, 0.11766593055777638, 0.13457977075902922, 0.31551366940773323, 0.18253772233872023, 0.030526433091716102, 0.02818024344742298, 0.2692735838826816, 0.2007377542542153, 0.09362608188200953, -0.21151623061313382, 0.0029804200452383397, 0.12480047245878938] |
1,802.03785 | Uncertainty Principles for the Offset Linear Canonical Transform | The offset linear canonical transform (OLCT) provides a more general
framework for a number of well known linear integral transforms in signal
processing and optics, such as Fourier transform, fractional Fourier transform,
linear canonical transform. In this paper, to characterize simultaneous
localization of a signal and its OLCT, we extend some different uncertainty
principles (UPs), including Nazarov's UP, Hardy's UP, Beurling's UP,
logarithmic UP and entropic UP, which have already been well studied in the
Fourier transform domain over the last few decades, to the OLCT domain in a
broader sense.
| eess.SP | the offset linear canonical transform olct provides a more general framework for a number of well known linear integral transforms in signal processing and optics such as fourier transform fractional fourier transform linear canonical transform in this paper to characterize simultaneous localization of a signal and its olct we extend some different uncertainty principles ups including nazarovs up hardys up beurlings up logarithmic up and entropic up which have already been well studied in the fourier transform domain over the last few decades to the olct domain in a broader sense | [['the', 'offset', 'linear', 'canonical', 'transform', 'olct', 'provides', 'a', 'more', 'general', 'framework', 'for', 'a', 'number', 'of', 'well', 'known', 'linear', 'integral', 'transforms', 'in', 'signal', 'processing', 'and', 'optics', 'such', 'as', 'fourier', 'transform', 'fractional', 'fourier', 'transform', 'linear', 'canonical', 'transform', 'in', 'this', 'paper', 'to', 'characterize', 'simultaneous', 'localization', 'of', 'a', 'signal', 'and', 'its', 'olct', 'we', 'extend', 'some', 'different', 'uncertainty', 'principles', 'ups', 'including', 'nazarovs', 'up', 'hardys', 'up', 'beurlings', 'up', 'logarithmic', 'up', 'and', 'entropic', 'up', 'which', 'have', 'already', 'been', 'well', 'studied', 'in', 'the', 'fourier', 'transform', 'domain', 'over', 'the', 'last', 'few', 'decades', 'to', 'the', 'olct', 'domain', 'in', 'a', 'broader', 'sense']] | [-0.04651606689171436, 0.04140492769183366, -0.13588825250965553, 0.0882616808962916, -0.11986068103994642, -0.10482701693487527, 0.014481913618510589, 0.37007365142414855, -0.3772081505957541, -0.26240849855181936, 0.1440532986729682, -0.23649973629022036, -0.16533824365463232, 0.26700087329679795, -0.08287178259854625, 0.1642648419051861, -0.03192089166451287, 0.031209917063568973, -0.162023617842511, -0.2207265250726378, 0.22178621321998454, 0.007657415878314238, 0.24940050370059907, -0.018495791530298008, 0.12064718454052786, 0.03843852046974372, -0.0768986751177031, -0.054615088733383915, -0.10122619879401319, 0.1357188777189579, 0.2568483731023722, 0.0963164319083252, 0.30444928324157067, -0.40331602773813346, -0.23474523872341757, 0.09376666837264426, 0.14228525496814604, 0.03774178865657362, -0.03748291474591127, -0.28253244683351164, 0.03670645020946932, -0.1502857838788039, -0.07903015087512168, -0.12909538952817956, 0.033751075969661, 0.014902868847986991, -0.22849777797339382, 0.09698892685656364, 0.10975772356531317, 0.06011740576762419, -0.021699504943431487, -0.09911357095480415, 0.11764991662598082, 0.07288092954575524, 0.00926380665911423, 0.059846421578325905, 0.05835995089856314, -0.05833723712814869, -0.10662322344161201, 0.3724903936323884, -0.06115767381225641, -0.17633656514194476, 0.15247067169460293, -0.19324482185510242, -0.15000238204323738, 0.13334131024644844, 0.16027167482444873, 0.11197251181762952, -0.164382420828218, 0.13542806003869584, -0.033284516186340825, 0.145746212125152, 0.17204938357143285, 0.09243415261600883, 0.10424187112149301, 0.10821531676677065, 0.11180017165747563, 0.17232202928881724, -0.08227004581591585, -0.0951987647932473, -0.30275323214316435, -0.20120849544284763, -0.19818295039502637, 0.042987106582866266, -0.06841489936658156, -0.12156123166122208, 0.40700935981758346, 0.0807304226148587, 0.17096925159445503, 0.08414450992067642, 0.2699949444721934, 0.17270513009766097, 0.10158357686352926, 0.023815330670593857, 0.18573249111644116, 0.19149050892300004, 0.11900647144616264, -0.152707014724121, -0.06536236919135183, 0.05973457585979294] |
1,802.03786 | Serial factorizations of right ideals | In a Dedekind domain $D$, every non-zero proper ideal $A$ factors as a
product $A=P_1^{t_1}\cdots P_k^{t_k}$ of powers of distinct prime ideals $P_i$.
For a Dedekind domain $D$, the $D$-modules $D/P_i^{t_i}$ are uniserial. We
extend this property studying suitable factorizations $A=A_1\dots A_n$ of a
right ideal $A$ of an arbitrary ring $R$ as a product of proper right ideals
$A_1,\dots,A_n$ with all the modules $R/A_i$ uniserial modules. When such
factorizations exist, they are unique up to the order of the factors. Serial
factorizations turn out to have connections with the theory of $h$-local
Pr\"ufer domains and that of semirigid commutative GCD domains.
| math.RA | in a dedekind domain d every nonzero proper ideal a factors as a product ap_1t_1cdots p_kt_k of powers of distinct prime ideals p_i for a dedekind domain d the dmodules dp_it_i are uniserial we extend this property studying suitable factorizations aa_1dots a_n of a right ideal a of an arbitrary ring r as a product of proper right ideals a_1dotsa_n with all the modules ra_i uniserial modules when such factorizations exist they are unique up to the order of the factors serial factorizations turn out to have connections with the theory of hlocal prufer domains and that of semirigid commutative gcd domains | [['in', 'a', 'dedekind', 'domain', 'd', 'every', 'nonzero', 'proper', 'ideal', 'a', 'factors', 'as', 'a', 'product', 'ap_1t_1cdots', 'p_kt_k', 'of', 'powers', 'of', 'distinct', 'prime', 'ideals', 'p_i', 'for', 'a', 'dedekind', 'domain', 'd', 'the', 'dmodules', 'dp_it_i', 'are', 'uniserial', 'we', 'extend', 'this', 'property', 'studying', 'suitable', 'factorizations', 'aa_1dots', 'a_n', 'of', 'a', 'right', 'ideal', 'a', 'of', 'an', 'arbitrary', 'ring', 'r', 'as', 'a', 'product', 'of', 'proper', 'right', 'ideals', 'a_1dotsa_n', 'with', 'all', 'the', 'modules', 'ra_i', 'uniserial', 'modules', 'when', 'such', 'factorizations', 'exist', 'they', 'are', 'unique', 'up', 'to', 'the', 'order', 'of', 'the', 'factors', 'serial', 'factorizations', 'turn', 'out', 'to', 'have', 'connections', 'with', 'the', 'theory', 'of', 'hlocal', 'prufer', 'domains', 'and', 'that', 'of', 'semirigid', 'commutative', 'gcd', 'domains']] | [-0.22982327782130818, 0.058403425594721683, -0.07031859245094262, 0.024942544615608925, -0.08547067946317244, -0.1714063687867732, -0.046977277418684064, 0.34902883267828394, -0.4080399609912111, -0.1107642333574441, 0.11940290229406911, -0.26510278157633255, -0.04820586873541529, 0.15626067832606483, -0.0799278439621308, -0.019282478817776606, 0.05095675593356089, 0.09121993047955008, -0.09675613173868089, -0.2868880630489819, 0.3951091761463227, -0.06790620306202648, 0.1908003902823037, 0.002540137471404872, 0.10786739754851679, -0.023009667690957383, -0.025481741331346636, 0.027846653739864134, -0.16927415973838592, 0.12437814447496619, 0.34992125906211763, 0.08589919909302678, 0.2709925397470289, -0.38319222312937345, -0.056186175563049556, 0.2205312599389985, 0.16490566845013932, -0.06107786290670688, 0.03479878741972225, -0.2005951689100083, 0.15768317692456957, -0.24919798351083028, -0.12911332765895855, -0.09460382412035702, 0.14613372214822745, 0.0719274161003378, -0.34020386923018997, -0.041300164488125214, 0.1245471361872493, 0.13040961084735334, 0.003820289378957253, -0.15525959574674464, 0.011037737900885393, 0.11670220774338268, -0.02707678715375309, 0.011401934409038904, 0.0659231298367911, -0.1293098663659386, -0.16641102784089934, 0.3567608988710812, 0.009994957827706347, -0.247286871721854, 0.12966703331544616, -0.2009852380344492, -0.0841665190231169, 0.10189254589530887, 0.011300570426546797, 0.16687552705502176, -0.017976574503076596, 0.1899977318119324, -0.15852251300132092, 0.05466457958124122, 0.16430167838626977, 0.05374793203424945, 0.17441677628085017, 0.07204539303867412, 0.03775660448727835, 0.11345558734586919, 0.041682688937503466, 0.04122035763207443, -0.35699424789078077, -0.2129878265431569, -0.13004820005687867, 0.14436994200811143, -0.15077339888687544, -0.20784915085615857, 0.4206366590604338, 0.03314108396785296, 0.19327945265044666, 0.07924405246858998, 0.22012098779787823, 0.012976857127944882, 0.11954807605812973, 0.023615143784530918, 0.045242227499886434, 0.2286790660820065, -0.02755351266728676, -0.09418938921381985, -0.012262926294411324, 0.13236689559012957] |
1,802.03787 | The continuum limit of the Kuramoto model on sparse random graphs | In this paper, we study convergence of coupled dynamical systems on
convergent sequences of graphs to a continuum limit. We show that the solutions
of the initial value problem for the dynamical system on a convergent graph
sequence tend to that for the nonlocal diffusion equation on a unit interval,
as the graph size tends to infinity. We improve our earlier results in [Arch.
Ration. Mech. Anal., 21 (2014), pp. 781--803] and extend them to a larger class
of graphs, which includes directed and undirected, sparse and dense, random and
deterministic graphs.
There are three main ingredients of our approach. First, we employ a flexible
framework for incorporating random graphs into the models of interacting
dynamical systems, which fits seamlessly with the derivation of the continuum
limit. Next, we prove the averaging principle for approximating a dynamical
system on a random graph by its deterministic (averaged) counterpart. The proof
covers systems on sparse graphs and yields almost sure convergence on time
intervals of order $\log n,$ where $n$ is the number of vertices. Finally, a
Galerkin scheme is developed to show convergence of the averaged model to the
continuum limit.
The analysis of this paper covers the Kuramoto model of coupled phase
oscillators on a variety of graphs including sparse Erd\H{o}s-R{\' e}nyi,
small-world, and power law graphs.
| math.DS nlin.AO | in this paper we study convergence of coupled dynamical systems on convergent sequences of graphs to a continuum limit we show that the solutions of the initial value problem for the dynamical system on a convergent graph sequence tend to that for the nonlocal diffusion equation on a unit interval as the graph size tends to infinity we improve our earlier results in arch ration mech anal 21 2014 pp 781803 and extend them to a larger class of graphs which includes directed and undirected sparse and dense random and deterministic graphs there are three main ingredients of our approach first we employ a flexible framework for incorporating random graphs into the models of interacting dynamical systems which fits seamlessly with the derivation of the continuum limit next we prove the averaging principle for approximating a dynamical system on a random graph by its deterministic averaged counterpart the proof covers systems on sparse graphs and yields almost sure convergence on time intervals of order log n where n is the number of vertices finally a galerkin scheme is developed to show convergence of the averaged model to the continuum limit the analysis of this paper covers the kuramoto model of coupled phase oscillators on a variety of graphs including sparse erdhosr enyi smallworld and power law graphs | [['in', 'this', 'paper', 'we', 'study', 'convergence', 'of', 'coupled', 'dynamical', 'systems', 'on', 'convergent', 'sequences', 'of', 'graphs', 'to', 'a', 'continuum', 'limit', 'we', 'show', 'that', 'the', 'solutions', 'of', 'the', 'initial', 'value', 'problem', 'for', 'the', 'dynamical', 'system', 'on', 'a', 'convergent', 'graph', 'sequence', 'tend', 'to', 'that', 'for', 'the', 'nonlocal', 'diffusion', 'equation', 'on', 'a', 'unit', 'interval', 'as', 'the', 'graph', 'size', 'tends', 'to', 'infinity', 'we', 'improve', 'our', 'earlier', 'results', 'in', 'arch', 'ration', 'mech', 'anal', '21', '2014', 'pp', '781803', 'and', 'extend', 'them', 'to', 'a', 'larger', 'class', 'of', 'graphs', 'which', 'includes', 'directed', 'and', 'undirected', 'sparse', 'and', 'dense', 'random', 'and', 'deterministic', 'graphs', 'there', 'are', 'three', 'main', 'ingredients', 'of', 'our', 'approach', 'first', 'we', 'employ', 'a', 'flexible', 'framework', 'for', 'incorporating', 'random', 'graphs', 'into', 'the', 'models', 'of', 'interacting', 'dynamical', 'systems', 'which', 'fits', 'seamlessly', 'with', 'the', 'derivation', 'of', 'the', 'continuum', 'limit', 'next', 'we', 'prove', 'the', 'averaging', 'principle', 'for', 'approximating', 'a', 'dynamical', 'system', 'on', 'a', 'random', 'graph', 'by', 'its', 'deterministic', 'averaged', 'counterpart', 'the', 'proof', 'covers', 'systems', 'on', 'sparse', 'graphs', 'and', 'yields', 'almost', 'sure', 'convergence', 'on', 'time', 'intervals', 'of', 'order', 'log', 'n', 'where', 'n', 'is', 'the', 'number', 'of', 'vertices', 'finally', 'a', 'galerkin', 'scheme', 'is', 'developed', 'to', 'show', 'convergence', 'of', 'the', 'averaged', 'model', 'to', 'the', 'continuum', 'limit', 'the', 'analysis', 'of', 'this', 'paper', 'covers', 'the', 'kuramoto', 'model', 'of', 'coupled', 'phase', 'oscillators', 'on', 'a', 'variety', 'of', 'graphs', 'including', 'sparse', 'erdhosr', 'enyi', 'smallworld', 'and', 'power', 'law', 'graphs']] | [-0.12415808430374708, 0.049662639562387104, -0.08429823351894007, 0.0374133151381948, -0.03310772711844292, -0.10485293432030567, 0.05644480297531456, 0.36639878939035847, -0.24232743733757456, -0.27220336213534657, 0.11736184948687117, -0.2792931046423524, -0.1601040971010577, 0.15789956260515853, -0.06611638303824462, 0.08335458335472097, 0.10026585892990751, 0.025891435437031676, -0.008995025305803, -0.24945806531319503, 0.303200934336759, -0.006144096951411907, 0.22559477647030077, 0.014148983523942704, 0.12328192504518123, 0.029063212522847014, -0.030586243986130454, 0.056090048282558834, -0.14021446725798956, 0.1156723235522635, 0.20579554633920008, 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1,802.03788 | Influence-Directed Explanations for Deep Convolutional Networks | We study the problem of explaining a rich class of behavioral properties of
deep neural networks. Distinctively, our influence-directed explanations
approach this problem by peering inside the network to identify neurons with
high influence on a quantity and distribution of interest, using an
axiomatically-justified influence measure, and then providing an interpretation
for the concepts these neurons represent. We evaluate our approach by
demonstrating a number of its unique capabilities on convolutional neural
networks trained on ImageNet. Our evaluation demonstrates that
influence-directed explanations (1) identify influential concepts that
generalize across instances, (2) can be used to extract the "essence" of what
the network learned about a class, and (3) isolate individual features the
network uses to make decisions and distinguish related classes.
| cs.LG cs.AI stat.ML | we study the problem of explaining a rich class of behavioral properties of deep neural networks distinctively our influencedirected explanations approach this problem by peering inside the network to identify neurons with high influence on a quantity and distribution of interest using an axiomaticallyjustified influence measure and then providing an interpretation for the concepts these neurons represent we evaluate our approach by demonstrating a number of its unique capabilities on convolutional neural networks trained on imagenet our evaluation demonstrates that influencedirected explanations 1 identify influential concepts that generalize across instances 2 can be used to extract the essence of what the network learned about a class and 3 isolate individual features the network uses to make decisions and distinguish related classes | [['we', 'study', 'the', 'problem', 'of', 'explaining', 'a', 'rich', 'class', 'of', 'behavioral', 'properties', 'of', 'deep', 'neural', 'networks', 'distinctively', 'our', 'influencedirected', 'explanations', 'approach', 'this', 'problem', 'by', 'peering', 'inside', 'the', 'network', 'to', 'identify', 'neurons', 'with', 'high', 'influence', 'on', 'a', 'quantity', 'and', 'distribution', 'of', 'interest', 'using', 'an', 'axiomaticallyjustified', 'influence', 'measure', 'and', 'then', 'providing', 'an', 'interpretation', 'for', 'the', 'concepts', 'these', 'neurons', 'represent', 'we', 'evaluate', 'our', 'approach', 'by', 'demonstrating', 'a', 'number', 'of', 'its', 'unique', 'capabilities', 'on', 'convolutional', 'neural', 'networks', 'trained', 'on', 'imagenet', 'our', 'evaluation', 'demonstrates', 'that', 'influencedirected', 'explanations', '1', 'identify', 'influential', 'concepts', 'that', 'generalize', 'across', 'instances', '2', 'can', 'be', 'used', 'to', 'extract', 'the', 'essence', 'of', 'what', 'the', 'network', 'learned', 'about', 'a', 'class', 'and', '3', 'isolate', 'individual', 'features', 'the', 'network', 'uses', 'to', 'make', 'decisions', 'and', 'distinguish', 'related', 'classes']] | [-0.038822131120931296, -0.005571708215106578, -0.07245935966118665, 0.09618334333566254, -0.1117639238472586, -0.15430585787063306, 0.06501430204390722, 0.3994714145438146, -0.2867602760650975, -0.34759878287470697, 0.03335103711805906, -0.27335077265309077, -0.26290877934908335, 0.19291699539191262, -0.08932336235529412, 0.013740374347080588, 0.08237460805734588, 0.0570343285246547, -0.02261972271095393, -0.255978587943808, 0.3488880803066669, 0.013054310847063927, 0.3129790716477023, 0.0367810991967602, 0.1292541576470485, -0.05492478511217287, -0.05363312435446907, 0.020697287616312062, -0.0972409253508115, 0.20596051556097691, 0.2781286589738171, 0.22007614910657816, 0.3344734478741884, -0.42301025478390314, -0.25548590712596553, 0.10619402785738141, 0.09374435902652094, 0.08029950322520177, 0.0316802502730151, -0.33305858282798556, 0.12399325849610712, -0.15869226749449716, -0.06375380757785702, -0.152308172530542, -0.011425344490493506, 0.014813779567178907, -0.24773675258571315, -0.0338855009423411, 0.06536723289962353, 0.04549217104154118, -0.040237095807797385, -0.09547025957381573, 0.024943809536033135, 0.19740136647675882, 0.01658987128905857, 0.012856027598776933, 0.16090511148637635, -0.18660213300602863, -0.16059478110696931, 0.3268160594595691, -0.023084298936429166, -0.19223411261277684, 0.20272067223943896, -0.039937843830064254, -0.16437187924255, 0.07524460975191224, 0.23906621830222213, 0.09060649453145372, -0.16488759701882125, -0.05053128450082899, -0.07433809482855565, 0.19856849245695493, 0.03610204980053576, 0.05161151628530884, 0.2245331504984001, 0.2537697402334188, 0.00512089585822265, 0.1624652644120141, -0.10561683340298043, -0.06301009026947983, -0.2337046690774545, -0.09510848106090296, -0.18351882941018538, 0.030031349630316055, -0.09881619347004868, -0.13840717461031182, 0.46025834006052146, 0.24257566836086433, 0.2500810058455977, 0.11779735370916986, 0.24765225529860138, 0.004943859194192278, 0.11019083945637063, 0.07716746263647989, 0.1844891642172963, 0.0902020842294698, 0.10557801290257376, -0.18317779970860457, 0.12683532770202197, 0.033560095540389925] |
1,802.03789 | A new convolution theorem associated with the linear canonical transform | In this paper, we first introduce a new notion of canonical convolution
operator, and show that it satisfies the commutative, associative, and
distributive properties, which may be quite useful in signal processing.
Moreover, it is proved that the generalized convolution theorem and generalized
Young's inequality are also hold for the new canonical convolution operator
associated with the LCT. Finally, we investigate the sufficient and necessary
conditions for solving a class of convolution equations associated with the
LCT.
| eess.SP | in this paper we first introduce a new notion of canonical convolution operator and show that it satisfies the commutative associative and distributive properties which may be quite useful in signal processing moreover it is proved that the generalized convolution theorem and generalized youngs inequality are also hold for the new canonical convolution operator associated with the lct finally we investigate the sufficient and necessary conditions for solving a class of convolution equations associated with the lct | [['in', 'this', 'paper', 'we', 'first', 'introduce', 'a', 'new', 'notion', 'of', 'canonical', 'convolution', 'operator', 'and', 'show', 'that', 'it', 'satisfies', 'the', 'commutative', 'associative', 'and', 'distributive', 'properties', 'which', 'may', 'be', 'quite', 'useful', 'in', 'signal', 'processing', 'moreover', 'it', 'is', 'proved', 'that', 'the', 'generalized', 'convolution', 'theorem', 'and', 'generalized', 'youngs', 'inequality', 'are', 'also', 'hold', 'for', 'the', 'new', 'canonical', 'convolution', 'operator', 'associated', 'with', 'the', 'lct', 'finally', 'we', 'investigate', 'the', 'sufficient', 'and', 'necessary', 'conditions', 'for', 'solving', 'a', 'class', 'of', 'convolution', 'equations', 'associated', 'with', 'the', 'lct']] | [-0.0623991826379841, 0.0823819452001677, -0.10529455530469294, 0.12167440272577397, -0.11427409738580419, -0.16351007774181955, -0.049811496697184814, 0.37513326420206816, -0.38785989519644093, -0.1771322539705154, 0.12133958459190734, -0.18971969111060555, -0.2463987199226757, 0.22905058479057505, -0.12788858176692836, 0.05170604234180329, 0.10631718284559327, 0.062012519518082794, -0.14066177654660658, -0.19571770031259142, 0.3777558692283445, 0.023614637405526908, 0.25604780640017677, 0.060704569646774176, 0.1405188168653033, 0.0030480451011038446, -0.04248691450913328, 0.03839174747563802, -0.13527291409112666, 0.1301573072862509, 0.21568966874635065, 0.11454925975193839, 0.2491024373486251, -0.4109284001366272, -0.14566779285427425, 0.16585197626286513, 0.08683623452731348, -0.00874942510733502, -0.04858792459519653, -0.25385905976419326, 0.13710203530325846, -0.18327501442815577, -0.12568963002473987, -0.13779938511260145, 0.014825967297732057, 0.057519821329163265, -0.33658718684228595, 0.09467632718068282, 0.14412781956542114, 0.03374116845102376, -0.09244866100103631, -0.059046765000184444, 0.039929084779162495, 0.04826087464711496, -0.055360840820985566, -0.005309381492000508, 0.05141318750918492, -0.09585726337035658, -0.07693365594831766, 0.35190956033282467, -0.0196785643589441, -0.2594166832262432, 0.11859092182652153, -0.1251541534053198, -0.2183909229994691, 0.03747977829816473, 0.09123670411380855, 0.12062609302146095, -0.16948166438801723, 0.10066925332421897, -0.10774262779235065, 0.10413097648264526, 0.1041387722694448, 0.07739719622707986, 0.08571646177488101, 0.09453669178916456, 0.12258476339425746, 0.21439830125339765, -0.031765020804709526, -0.08499040616095646, -0.35042351871341854, -0.22685810359944772, -0.1498984943821349, 0.07746609160374221, -0.09390698379894429, -0.15778183236766558, 0.3750673707139182, 0.15830023479254843, 0.13369631781787067, 0.13133525385902348, 0.2212501827433899, 0.1910752447816398, 0.11464408849208772, 0.062086034901803, 0.153945274980642, 0.23632428460065033, 0.12413907923143018, -0.1454198827253437, 0.008145780750102811, 0.15489158850139031] |
1,802.0379 | Neutron-rich rare isotope production with stable and radioactive beams
in the mass range A=40-60 at beam energy around 15 MeV/nucleon | We studied the production of neutron-rich nuclides in multinucleon transfer
collisions of stable and radioactive beams in the mass range A=40-60. We first
presented our experimental cross section data of projectile fragments from the
reaction of 40Ar(15 MeV/nucleon) with 64Ni, 58Ni and 27Al. We then compared
them with calculations based on either the deep-inelastic transfer (DIT) model
or the constrained molecular dynamics (CoMD) model, followed by the statistical
multifragmentation model (SMM). An overall good agreement of the calculations
with the experimental data is obtained. We continued with calculations of the
reaction of 40Ar (15 MeV/nucleon) with 238U target and then with reactions of
48Ca (15 MeV/nucleon) with 64Ni and 238U targets. In these reactions,
neutron-rich rare isotopes with large cross sections are produced. These
nuclides, in turn, can be assumed to form radioactive beams and interact with a
subsequent target (preferably 238U), leading to the production of extremely
neutron-rich and even new isotopes (e.g. 60Ca) in this mass range. We conclude
that multinucleon transfer reactions with stable or radioactive beams at the
energy of around 15 MeV/nucleon offer an effective route to access extremely
neutron-rich rare isotopes for nuclear structure or reaction studies.
| nucl-ex | we studied the production of neutronrich nuclides in multinucleon transfer collisions of stable and radioactive beams in the mass range a4060 we first presented our experimental cross section data of projectile fragments from the reaction of 40ar15 mevnucleon with 64ni 58ni and 27al we then compared them with calculations based on either the deepinelastic transfer dit model or the constrained molecular dynamics comd model followed by the statistical multifragmentation model smm an overall good agreement of the calculations with the experimental data is obtained we continued with calculations of the reaction of 40ar 15 mevnucleon with 238u target and then with reactions of 48ca 15 mevnucleon with 64ni and 238u targets in these reactions neutronrich rare isotopes with large cross sections are produced these nuclides in turn can be assumed to form radioactive beams and interact with a subsequent target preferably 238u leading to the production of extremely neutronrich and even new isotopes eg 60ca in this mass range we conclude that multinucleon transfer reactions with stable or radioactive beams at the energy of around 15 mevnucleon offer an effective route to access extremely neutronrich rare isotopes for nuclear structure or reaction studies | [['we', 'studied', 'the', 'production', 'of', 'neutronrich', 'nuclides', 'in', 'multinucleon', 'transfer', 'collisions', 'of', 'stable', 'and', 'radioactive', 'beams', 'in', 'the', 'mass', 'range', 'a4060', 'we', 'first', 'presented', 'our', 'experimental', 'cross', 'section', 'data', 'of', 'projectile', 'fragments', 'from', 'the', 'reaction', 'of', '40ar15', 'mevnucleon', 'with', '64ni', '58ni', 'and', '27al', 'we', 'then', 'compared', 'them', 'with', 'calculations', 'based', 'on', 'either', 'the', 'deepinelastic', 'transfer', 'dit', 'model', 'or', 'the', 'constrained', 'molecular', 'dynamics', 'comd', 'model', 'followed', 'by', 'the', 'statistical', 'multifragmentation', 'model', 'smm', 'an', 'overall', 'good', 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1,802.03791 | Metasurface Optics for Full-color Computational Imaging | Conventional imaging systems comprise large and expensive optical components
which successively mitigate aberrations. Metasurface optics offers a route to
miniaturize imaging systems by replacing bulky components with flat and compact
implementations. The diffractive nature of these devices, however, induces
severe chromatic aberrations and current multi-wavelength and narrowband
achromatic metasurfaces cannot support full visible spectum imaging (400-700
nm). We combine principles of both computational imaging and metasurface optics
to build a system with a single metalens of NA ~ 0.45 which generates in-focus
images under white light illumination. Our metalens exhibits a spectrally
invariant point spread function which enables computational reconstruction of
captured images with a single digital filter. This work connects computational
imaging and metasurface optics and demonstrates the capabilities of combining
these disciplines by simultaneously reducing aberrations and downsizing imaging
systems with simpler optics.
| physics.optics | conventional imaging systems comprise large and expensive optical components which successively mitigate aberrations metasurface optics offers a route to miniaturize imaging systems by replacing bulky components with flat and compact implementations the diffractive nature of these devices however induces severe chromatic aberrations and current multiwavelength and narrowband achromatic metasurfaces cannot support full visible spectum imaging 400700 nm we combine principles of both computational imaging and metasurface optics to build a system with a single metalens of na 045 which generates infocus images under white light illumination our metalens exhibits a spectrally invariant point spread function which enables computational reconstruction of captured images with a single digital filter this work connects computational imaging and metasurface optics and demonstrates the capabilities of combining these disciplines by simultaneously reducing aberrations and downsizing imaging systems with simpler optics | [['conventional', 'imaging', 'systems', 'comprise', 'large', 'and', 'expensive', 'optical', 'components', 'which', 'successively', 'mitigate', 'aberrations', 'metasurface', 'optics', 'offers', 'a', 'route', 'to', 'miniaturize', 'imaging', 'systems', 'by', 'replacing', 'bulky', 'components', 'with', 'flat', 'and', 'compact', 'implementations', 'the', 'diffractive', 'nature', 'of', 'these', 'devices', 'however', 'induces', 'severe', 'chromatic', 'aberrations', 'and', 'current', 'multiwavelength', 'and', 'narrowband', 'achromatic', 'metasurfaces', 'can', 'not', 'support', 'full', 'visible', 'spectum', 'imaging', '400700', 'nm', 'we', 'combine', 'principles', 'of', 'both', 'computational', 'imaging', 'and', 'metasurface', 'optics', 'to', 'build', 'a', 'system', 'with', 'a', 'single', 'metalens', 'of', 'na', '045', 'which', 'generates', 'infocus', 'images', 'under', 'white', 'light', 'illumination', 'our', 'metalens', 'exhibits', 'a', 'spectrally', 'invariant', 'point', 'spread', 'function', 'which', 'enables', 'computational', 'reconstruction', 'of', 'captured', 'images', 'with', 'a', 'single', 'digital', 'filter', 'this', 'work', 'connects', 'computational', 'imaging', 'and', 'metasurface', 'optics', 'and', 'demonstrates', 'the', 'capabilities', 'of', 'combining', 'these', 'disciplines', 'by', 'simultaneously', 'reducing', 'aberrations', 'and', 'downsizing', 'imaging', 'systems', 'with', 'simpler', 'optics']] | [-0.12123955559865054, 0.10896584870190257, -0.09204305108912565, -0.034475879613482564, -0.12220074944198131, -0.22983760418439353, -0.005416178213501418, 0.47159305112781347, -0.25863692186151943, -0.33912943096279546, 0.08221310204826296, -0.2797343175582312, -0.1991551982394109, 0.22120440112495865, -0.1495344920894476, 0.07462985991603799, 0.0853257709234539, -0.17982740880516185, -0.02589917213621515, -0.16146168758816742, 0.22161234486158246, 0.04863494621175859, 0.2959829356107447, -0.03725227386630313, 0.16352133926702664, 0.07672790077480453, -0.039724366518634334, 0.004421187609140934, -0.057055488622023, 0.13121235937707953, 0.2859496091113046, 0.09440867130351425, 0.2405395652650407, -0.41376867107702076, -0.26305828428378814, 0.02670600470672879, 0.16247226019579641, 0.07280221886467189, -0.11030609861223234, -0.2943743359538968, 0.00043336404832424943, -0.05838265029920472, -0.14859440690240633, -0.053217089928134724, -0.08396229830708493, 0.018273649322455406, -0.2691427338247498, -0.0072863282635807994, -0.006737476072481109, 0.09978894340219321, -0.03018646606349783, -0.07987264603359141, -0.006772915242699027, 0.06920152264819653, -0.12781555858048335, 0.01716573731628833, 0.13602361581978148, -0.16899008841460778, -0.10522312067828521, 0.3828249731847016, -2.2350141295680293e-05, -0.10741031721527516, 0.20389440369930256, -0.15640016443751475, -0.027299177334471434, 0.2381160030969315, 0.17220773975951253, 0.08959317069265699, -0.13756738630709825, 0.03430667004582506, 0.05379936442951913, 0.25658959601941106, 0.11910939577587501, 0.16569750727740704, 0.2556123024646055, 0.21327717884409206, 0.04517212160593503, 0.13618628792982135, -0.20042612614730995, 0.024531113510709947, -0.20141918695083372, -0.14252159889373514, -0.1692690087258126, 0.018714861915106195, -0.0738763849992581, -0.17367380232446725, 0.34791945216280445, 0.17256341638664405, 0.08901120168329389, 0.01719220648088527, 0.44334100867035214, 0.06000792871970959, 0.18125166480636432, -0.022686434823467775, 0.25960392297280055, 0.14997317123666612, 0.17503588353801106, -0.17222605656090847, -0.031050354559664373, -0.0565774812914983] |
1,802.03792 | A new 2-D Model to analyze uncertainty sources of sparse sea surface CO2
partial pressure | In order to better comprehend the global carbon cycle and predict the
prognosis for the response to climate change, accurate assessment of sea-air
CO2 flux is necessary. Comparing to the relative homogeneously distribution of
atmospheric CO2 , the pCO2 in the sea surface water is exposed to huge
spatio-temporal variability, which leaves a prominent uncertainty resource.
Many regional studies typically divided the observational pCO2 data into grid
boxes so as to obtain enough data points statistically for their calculatio.
However, using the data inside the grid box areas to represent its holistic
property (such as standard deviation to represent spatial variance) will mix up
three different uncertainty sources. First, the analytical error in the pCO2
determination and the associated environmental parameters used in deriving pCO2
. Second, the spatial variance because of inhomogenous spatial pattern of sea
surface pCO2 , especially the region with a dramatically dynamic circumstance
like: coastal areas, boundaries or fronts and etc. Third, the estimation
process in undersampling condition, specifically, this kind of uncertainty
origins from the process that using a sparse data to represent its holistic
property of the box area. Common uncertainty quantification by Standard
Deviation will mix up the different sources of uncertainty. In this paper, it
introduces an optimized procedure to determine three sources of uncertainty
(1st analytical error, 2nd spatial variance, 3rd bias from undersampling.)
using the combined remote sensing-derived and field-measured pCO2 data. In
order to provide a comprehensive error assessment report.
| physics.ao-ph | in order to better comprehend the global carbon cycle and predict the prognosis for the response to climate change accurate assessment of seaair co2 flux is necessary comparing to the relative homogeneously distribution of atmospheric co2 the pco2 in the sea surface water is exposed to huge spatiotemporal variability which leaves a prominent uncertainty resource many regional studies typically divided the observational pco2 data into grid boxes so as to obtain enough data points statistically for their calculatio however using the data inside the grid box areas to represent its holistic property such as standard deviation to represent spatial variance will mix up three different uncertainty sources first the analytical error in the pco2 determination and the associated environmental parameters used in deriving pco2 second the spatial variance because of inhomogenous spatial pattern of sea surface pco2 especially the region with a dramatically dynamic circumstance like coastal areas boundaries or fronts and etc third the estimation process in undersampling condition specifically this kind of uncertainty origins from the process that using a sparse data to represent its holistic property of the box area common uncertainty quantification by standard deviation will mix up the different sources of uncertainty in this paper it introduces an optimized procedure to determine three sources of uncertainty 1st analytical error 2nd spatial variance 3rd bias from undersampling using the combined remote sensingderived and fieldmeasured pco2 data in order to provide a comprehensive error assessment report | [['in', 'order', 'to', 'better', 'comprehend', 'the', 'global', 'carbon', 'cycle', 'and', 'predict', 'the', 'prognosis', 'for', 'the', 'response', 'to', 'climate', 'change', 'accurate', 'assessment', 'of', 'seaair', 'co2', 'flux', 'is', 'necessary', 'comparing', 'to', 'the', 'relative', 'homogeneously', 'distribution', 'of', 'atmospheric', 'co2', 'the', 'pco2', 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1,802.03793 | Large-Scale Validation of Hypothesis Generation Systems via Candidate
Ranking | The first step of many research projects is to define and rank a short list
of candidates for study. In the modern rapidity of scientific progress, some
turn to automated hypothesis generation (HG) systems to aid this process. These
systems can identify implicit or overlooked connections within a large
scientific corpus, and while their importance grows alongside the pace of
science, they lack thorough validation. Without any standard numerical
evaluation method, many validate general-purpose HG systems by rediscovering a
handful of historical findings, and some wishing to be more thorough may run
laboratory experiments based on automatic suggestions. These methods are
expensive, time consuming, and cannot scale. Thus, we present a numerical
evaluation framework for the purpose of validating HG systems that leverages
thousands of validation hypotheses. This method evaluates a HG system by its
ability to rank hypotheses by plausibility; a process reminiscent of human
candidate selection. Because HG systems do not produce a ranking criteria,
specifically those that produce topic models, we additionally present novel
metrics to quantify the plausibility of hypotheses given topic model system
output. Finally, we demonstrate that our proposed validation method aligns with
real-world research goals by deploying our method within Moliere, our recent
topic-driven HG system, in order to automatically generate a set of candidate
genes related to HIV-associated neurodegenerative disease (HAND). By performing
laboratory experiments based on this candidate set, we discover a new
connection between HAND and Dead Box RNA Helicase 3 (DDX3). Reproducibility:
code, validation data, and results can be found at
sybrandt.com/2018/validation.
| cs.IR cs.CL | the first step of many research projects is to define and rank a short list of candidates for study in the modern rapidity of scientific progress some turn to automated hypothesis generation hg systems to aid this process these systems can identify implicit or overlooked connections within a large scientific corpus and while their importance grows alongside the pace of science they lack thorough validation without any standard numerical evaluation method many validate generalpurpose hg systems by rediscovering a handful of historical findings and some wishing to be more thorough may run laboratory experiments based on automatic suggestions these methods are expensive time consuming and cannot scale thus we present a numerical evaluation framework for the purpose of validating hg systems that leverages thousands of validation hypotheses this method evaluates a hg system by its ability to rank hypotheses by plausibility a process reminiscent of human candidate selection because hg systems do not produce a ranking criteria specifically those that produce topic models we additionally present novel metrics to quantify the plausibility of hypotheses given topic model system output finally we demonstrate that our proposed validation method aligns with realworld research goals by deploying our method within moliere our recent topicdriven hg system in order to automatically generate a set of candidate genes related to hivassociated neurodegenerative disease hand by performing laboratory experiments based on this candidate set we discover a new connection between hand and dead box rna helicase 3 ddx3 reproducibility code validation data and results can be found at sybrandtcom2018validation | [['the', 'first', 'step', 'of', 'many', 'research', 'projects', 'is', 'to', 'define', 'and', 'rank', 'a', 'short', 'list', 'of', 'candidates', 'for', 'study', 'in', 'the', 'modern', 'rapidity', 'of', 'scientific', 'progress', 'some', 'turn', 'to', 'automated', 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1,802.03794 | Dark photon production through positron annihilation in beam-dump
experiments | High energy positron annihilation is a viable mechanism to produce dark
photons ($A^\prime$). This reaction plays a significant role in beam-dump
experiments using experiments using multi-GeV electron-beams on thick targets
by enhancing the sensitivity to $A^\prime$ production. The positrons produced
by the electromagnetic shower can produce an $A^\prime$ via non-resonant ($e^+
+ e^- \to \gamma + A^\prime$) and resonant ($e^+ + e^- \to A^\prime$)
annihilation on atomic electrons. For visible decays, the contribution of
resonant annihilation results in a larger sensitivity with respect to limits
derived by the commonly used $A^\prime$-strahlung in certain kinematic regions.
When included in the evaluation of the E137 beam-dump experiment reach,
positron annihilation pushes the current limit on $\varepsilon$ downwards by a
factor of two in the range 33 MeV/c$^2<m_{A^\prime}<120$ MeV/c$^2$.
| hep-ex hep-ph | high energy positron annihilation is a viable mechanism to produce dark photons aprime this reaction plays a significant role in beamdump experiments using experiments using multigev electronbeams on thick targets by enhancing the sensitivity to aprime production the positrons produced by the electromagnetic shower can produce an aprime via nonresonant e e to gamma aprime and resonant e e to aprime annihilation on atomic electrons for visible decays the contribution of resonant annihilation results in a larger sensitivity with respect to limits derived by the commonly used aprimestrahlung in certain kinematic regions when included in the evaluation of the e137 beamdump experiment reach positron annihilation pushes the current limit on varepsilon downwards by a factor of two in the range 33 mevc2m_aprime120 mevc2 | [['high', 'energy', 'positron', 'annihilation', 'is', 'a', 'viable', 'mechanism', 'to', 'produce', 'dark', 'photons', 'aprime', 'this', 'reaction', 'plays', 'a', 'significant', 'role', 'in', 'beamdump', 'experiments', 'using', 'experiments', 'using', 'multigev', 'electronbeams', 'on', 'thick', 'targets', 'by', 'enhancing', 'the', 'sensitivity', 'to', 'aprime', 'production', 'the', 'positrons', 'produced', 'by', 'the', 'electromagnetic', 'shower', 'can', 'produce', 'an', 'aprime', 'via', 'nonresonant', 'e', 'e', 'to', 'gamma', 'aprime', 'and', 'resonant', 'e', 'e', 'to', 'aprime', 'annihilation', 'on', 'atomic', 'electrons', 'for', 'visible', 'decays', 'the', 'contribution', 'of', 'resonant', 'annihilation', 'results', 'in', 'a', 'larger', 'sensitivity', 'with', 'respect', 'to', 'limits', 'derived', 'by', 'the', 'commonly', 'used', 'aprimestrahlung', 'in', 'certain', 'kinematic', 'regions', 'when', 'included', 'in', 'the', 'evaluation', 'of', 'the', 'e137', 'beamdump', 'experiment', 'reach', 'positron', 'annihilation', 'pushes', 'the', 'current', 'limit', 'on', 'varepsilon', 'downwards', 'by', 'a', 'factor', 'of', 'two', 'in', 'the', 'range', '33', 'mevc2m_aprime120', 'mevc2']] | [-0.04932626229516852, 0.22775674655676995, -0.03327089416779927, 0.0938144525202612, -0.025174345112948988, -0.05802383653741951, 0.058209900609411606, 0.3471315195783973, -0.21870404531558355, -0.3366414191458413, -0.10008585569545782, -0.33896691113865624, 0.07632846733710417, 0.2571847528840105, 0.0900940165350524, 0.039074435574002565, 0.09688269101898186, -0.007020277085636432, 0.036344936187379065, -0.1630099314187343, 0.2433526629737268, 0.15614000768982805, 0.24644290469198799, 0.13614294899938006, 0.05898926776911442, 0.020649544093369818, -0.048645977370809605, -0.09803586420603097, -0.12424874936890168, 0.0825917149350668, 0.23554722362702402, 0.06471766195221183, 0.13969456115543533, -0.4077677332330495, -0.1491512997308746, 0.18731215193741566, 0.17846114529141535, -0.013183957780711353, -0.0886783562435691, -0.3393237700064977, 0.09308537818336239, -0.18653874601589754, -0.08154850454690556, -0.02207249836064875, 0.037110740043378124, -0.043788483261596414, -0.3166252531421681, 0.04805693654925562, -0.0061313016509908875, -0.04688288569644404, -0.03797952717674586, -0.12857426225673407, -0.009812770085409284, -0.014769825312881343, 0.0659791236180657, 0.07613507425727827, 0.26075640070873, -0.16401115380964862, -0.1554557389424493, 0.39075349200866183, -0.15964672102515276, -0.14702950538291285, 0.16883492728035587, -0.16802642804880938, -0.07800544891894484, 0.27134762685357905, 0.18908214278053492, 0.08005854864992822, -0.1463385058708809, 0.12720770122978137, -0.0020032477089747167, 0.13645197383787794, 0.12894633352213228, 0.029171106537493566, 0.2237615241727326, 0.1991043798373236, 0.04271189831197262, 0.07986034165951424, -0.16747795994742773, 0.0185275797576954, -0.3588844353953997, -0.11555665112876644, -0.08059635604731738, 0.07892751477872177, 0.006505458389923054, -0.047636472969315946, 0.32373657589778304, 0.0769320235055299, 0.2723131474573165, -0.07712177099310794, 0.33386586703418286, 0.11416095849854173, 0.04840162019439352, -0.0006480282133755585, 0.369954728288576, 0.12443419250970085, 0.07648686247800167, -0.24187568439908017, 0.03738225788789957, -0.0296148027991876] |
1,802.03795 | Almost sure local well-posedness and scattering for the 4D cubic
nonlinear Schr\"odinger equation | We consider the Cauchy problem for the defocusing cubic nonlinear
Schr\"odinger equation in four space dimensions and establish almost sure local
well-posedness and conditional almost sure scattering for random initial data
in $H^s_x(\mathbb{R}^4)$ with $\frac{1}{3} < s < 1$. The main ingredient in the
proofs is the introduction of a functional framework for the study of the
associated forced cubic nonlinear Schr\"odinger equation, which is inspired by
certain function spaces used in the study of the Schr\"odinger maps problem,
and is based on Strichartz spaces as well as variants of local smoothing,
inhomogeneous local smoothing, and maximal function spaces. Additionally, we
prove an almost sure scattering result for randomized radially symmetric
initial data in $H^s_x(\mathbb{R}^4)$ with $\frac{1}{2} < s < 1$.
| math.AP | we consider the cauchy problem for the defocusing cubic nonlinear schrodinger equation in four space dimensions and establish almost sure local wellposedness and conditional almost sure scattering for random initial data in hs_xmathbbr4 with frac13 s 1 the main ingredient in the proofs is the introduction of a functional framework for the study of the associated forced cubic nonlinear schrodinger equation which is inspired by certain function spaces used in the study of the schrodinger maps problem and is based on strichartz spaces as well as variants of local smoothing inhomogeneous local smoothing and maximal function spaces additionally we prove an almost sure scattering result for randomized radially symmetric initial data in hs_xmathbbr4 with frac12 s 1 | [['we', 'consider', 'the', 'cauchy', 'problem', 'for', 'the', 'defocusing', 'cubic', 'nonlinear', 'schrodinger', 'equation', 'in', 'four', 'space', 'dimensions', 'and', 'establish', 'almost', 'sure', 'local', 'wellposedness', 'and', 'conditional', 'almost', 'sure', 'scattering', 'for', 'random', 'initial', 'data', 'in', 'hs_xmathbbr4', 'with', 'frac13', 's', '1', 'the', 'main', 'ingredient', 'in', 'the', 'proofs', 'is', 'the', 'introduction', 'of', 'a', 'functional', 'framework', 'for', 'the', 'study', 'of', 'the', 'associated', 'forced', 'cubic', 'nonlinear', 'schrodinger', 'equation', 'which', 'is', 'inspired', 'by', 'certain', 'function', 'spaces', 'used', 'in', 'the', 'study', 'of', 'the', 'schrodinger', 'maps', 'problem', 'and', 'is', 'based', 'on', 'strichartz', 'spaces', 'as', 'well', 'as', 'variants', 'of', 'local', 'smoothing', 'inhomogeneous', 'local', 'smoothing', 'and', 'maximal', 'function', 'spaces', 'additionally', 'we', 'prove', 'an', 'almost', 'sure', 'scattering', 'result', 'for', 'randomized', 'radially', 'symmetric', 'initial', 'data', 'in', 'hs_xmathbbr4', 'with', 'frac12', 's', '1']] | [-0.09301962003929731, 0.06688786544511194, -0.04733105185322273, 0.1334578019206643, -0.030236483209280886, -0.1321632419872042, -0.049167542782031066, 0.3364433405809423, -0.29357596470886826, -0.20592045390771496, 0.1646769330349281, -0.29750211260671544, -0.15021980467101193, 0.17018459068460023, -0.025902344208433587, 0.1297555852514238, 0.01826554904373474, 0.014660439382378872, -0.07649603470937054, -0.2912421766977009, 0.41572206104413056, -0.04870035436450162, 0.2427722027159145, 0.013436639295397406, 0.11569654284260021, 0.11950932694678633, -0.033173380925073326, -0.04536637927740852, -0.18994146724366862, 0.09903933796195839, 0.18837057260207385, 0.061984835385591686, 0.31121507962035316, -0.40856025169372684, -0.19769319794817358, 0.15194510706724265, 0.15031665017525864, 0.09875980745821905, -0.030574762424589414, -0.3030312792437836, 0.0652890632657382, -0.06200707462640145, -0.22361638895673758, -0.06000263294061789, 0.04046836186550621, 0.07237946168463837, -0.3436695649965197, 0.13459444885006827, 0.11602076571773037, 0.023343179788854387, -0.15731472694678192, -0.07318287771433973, -0.012434068886149261, 0.027480561819532488, 0.021763147918595016, 0.04928533498070434, 0.019631232966820143, -0.09240615629774128, -0.10379322063830546, 0.3386513024616318, -0.10254878743400431, -0.21161853941356462, 0.09995420960287571, -0.12463868375565125, -0.11744278016436495, 0.07080709878912467, 0.16017835372342512, 0.13909966319910863, -0.1334991953534703, 0.17533325152989063, -0.07154876713314627, 0.1250951965399182, 0.09696188958313985, 0.033322754992633805, 0.03884222961834863, 0.14925470564048737, 0.20394670894035163, 0.1287020452034015, -0.0016788440685854573, -0.08197911067031977, -0.3400055471744038, -0.13337210432077065, -0.18825479697945535, 0.10653611277349484, -0.15148178772537166, -0.20678795333931813, 0.3555280895641026, 0.11084233111359625, 0.17713726525250664, 0.08657164617071454, 0.2172813490908752, 0.14863377755794388, -0.01670290611964913, 0.09310338643785471, 0.1674891192984417, 0.17911080992780626, 0.11888208325840852, -0.1642655236686333, 0.022684382744388193, 0.16922303336935166] |
1,802.03796 | Curriculum Learning by Transfer Learning: Theory and Experiments with
Deep Networks | We provide theoretical investigation of curriculum learning in the context of
stochastic gradient descent when optimizing the convex linear regression loss.
We prove that the rate of convergence of an ideal curriculum learning method is
monotonically increasing with the difficulty of the examples. Moreover, among
all equally difficult points, convergence is faster when using points which
incur higher loss with respect to the current hypothesis. We then analyze
curriculum learning in the context of training a CNN. We describe a method
which infers the curriculum by way of transfer learning from another network,
pre-trained on a different task. While this approach can only approximate the
ideal curriculum, we observe empirically similar behavior to the one predicted
by the theory, namely, a significant boost in convergence speed at the
beginning of training. When the task is made more difficult, improvement in
generalization performance is also observed. Finally, curriculum learning
exhibits robustness against unfavorable conditions such as excessive
regularization.
| cs.LG | we provide theoretical investigation of curriculum learning in the context of stochastic gradient descent when optimizing the convex linear regression loss we prove that the rate of convergence of an ideal curriculum learning method is monotonically increasing with the difficulty of the examples moreover among all equally difficult points convergence is faster when using points which incur higher loss with respect to the current hypothesis we then analyze curriculum learning in the context of training a cnn we describe a method which infers the curriculum by way of transfer learning from another network pretrained on a different task while this approach can only approximate the ideal curriculum we observe empirically similar behavior to the one predicted by the theory namely a significant boost in convergence speed at the beginning of training when the task is made more difficult improvement in generalization performance is also observed finally curriculum learning exhibits robustness against unfavorable conditions such as excessive regularization | [['we', 'provide', 'theoretical', 'investigation', 'of', 'curriculum', 'learning', 'in', 'the', 'context', 'of', 'stochastic', 'gradient', 'descent', 'when', 'optimizing', 'the', 'convex', 'linear', 'regression', 'loss', 'we', 'prove', 'that', 'the', 'rate', 'of', 'convergence', 'of', 'an', 'ideal', 'curriculum', 'learning', 'method', 'is', 'monotonically', 'increasing', 'with', 'the', 'difficulty', 'of', 'the', 'examples', 'moreover', 'among', 'all', 'equally', 'difficult', 'points', 'convergence', 'is', 'faster', 'when', 'using', 'points', 'which', 'incur', 'higher', 'loss', 'with', 'respect', 'to', 'the', 'current', 'hypothesis', 'we', 'then', 'analyze', 'curriculum', 'learning', 'in', 'the', 'context', 'of', 'training', 'a', 'cnn', 'we', 'describe', 'a', 'method', 'which', 'infers', 'the', 'curriculum', 'by', 'way', 'of', 'transfer', 'learning', 'from', 'another', 'network', 'pretrained', 'on', 'a', 'different', 'task', 'while', 'this', 'approach', 'can', 'only', 'approximate', 'the', 'ideal', 'curriculum', 'we', 'observe', 'empirically', 'similar', 'behavior', 'to', 'the', 'one', 'predicted', 'by', 'the', 'theory', 'namely', 'a', 'significant', 'boost', 'in', 'convergence', 'speed', 'at', 'the', 'beginning', 'of', 'training', 'when', 'the', 'task', 'is', 'made', 'more', 'difficult', 'improvement', 'in', 'generalization', 'performance', 'is', 'also', 'observed', 'finally', 'curriculum', 'learning', 'exhibits', 'robustness', 'against', 'unfavorable', 'conditions', 'such', 'as', 'excessive', 'regularization']] | [-0.01463997889692735, 0.03468986547036337, -0.0954500447846, 0.07616937017160212, -0.09355937384193538, -0.1872991449926286, 0.05424907429894183, 0.43305947917519483, -0.29819715205746095, -0.31869500549695495, 0.06278271502429608, -0.2401482003390979, -0.2008211416582381, 0.20100780620364248, -0.14488076830466698, 0.06562073183969659, 0.11960014642756077, 0.04780068081691653, -0.12163757696409656, -0.3266485938031203, 0.31977963544243715, 0.07207897906102667, 0.33994399230618766, 0.005785468698829223, 0.12157235924854495, -0.04207759365664831, 0.019389774816431057, 0.00932239612288607, -0.06022528458593723, 0.15019798410202193, 0.2973899967407891, 0.1844332446359027, 0.406820961054723, -0.3787202528339757, -0.18815210220777684, 0.12408531717896747, 0.1358676235468474, 0.11728376511982672, -0.060097458126979204, -0.2558660815309757, 0.0972736519487029, -0.17031425842718714, -0.046980132689924944, -0.13221446324472025, -0.039088490006816426, -0.002962666612999383, -0.2864172835330105, 0.04525122686958824, 0.09798949861982066, 0.08875242020138821, -0.05241722772253832, -0.11074490124021603, 0.004828246547632916, 0.09935000738863844, 0.09446814392877233, 0.06828527876537792, 0.12846982072754082, -0.18735143971543428, -0.11737510449531827, 0.34877706441885914, -0.07060181413915091, -0.19411214280897265, 0.19189140335864321, -0.06798457628365155, -0.1156182461047462, 0.10339650390135824, 0.2264943375507263, 0.1041642741721337, -0.12665032165020831, 0.03557308119644595, -0.0188808662247411, 0.1352051277852552, 0.048456943635443214, -0.028318734307162415, 0.1352125726222019, 0.24075062462176156, 0.10331103174537895, 0.1626015260317333, -0.08184201480186051, -0.10863936395876726, -0.27390199865861115, -0.1455479156871765, -0.19859459321088732, -0.0018574437171007228, -0.1174336605568885, -0.11617143996131078, 0.3858654764955448, 0.20902504666506722, 0.2025521732866764, 0.11357278934128251, 0.3221932161261274, 0.10101765919414461, 0.0676811935534333, 0.12733875531747724, 0.23288047126239272, 0.033022876820010934, 0.10690862910709326, -0.22743372317139582, 0.11659675336051377, 0.042153269396560965] |
1,802.03797 | Great circle fibrations and contact structures on the 3-sphere | Given any smooth fibration of the unit 3-sphere by great circles, we show
that the distribution of 2-planes orthogonal to the great circle fibres is a
tight contact structure, a fact well known in the special case of the Hopf
fibrations. The proof expresses hypothesis and conclusion as differential
inequalities involving functions on disks transverse to the fibres, and shows
that one inequality implies the other.
| math.DG math.AT math.GT math.SG | given any smooth fibration of the unit 3sphere by great circles we show that the distribution of 2planes orthogonal to the great circle fibres is a tight contact structure a fact well known in the special case of the hopf fibrations the proof expresses hypothesis and conclusion as differential inequalities involving functions on disks transverse to the fibres and shows that one inequality implies the other | [['given', 'any', 'smooth', 'fibration', 'of', 'the', 'unit', '3sphere', 'by', 'great', 'circles', 'we', 'show', 'that', 'the', 'distribution', 'of', '2planes', 'orthogonal', 'to', 'the', 'great', 'circle', 'fibres', 'is', 'a', 'tight', 'contact', 'structure', 'a', 'fact', 'well', 'known', 'in', 'the', 'special', 'case', 'of', 'the', 'hopf', 'fibrations', 'the', 'proof', 'expresses', 'hypothesis', 'and', 'conclusion', 'as', 'differential', 'inequalities', 'involving', 'functions', 'on', 'disks', 'transverse', 'to', 'the', 'fibres', 'and', 'shows', 'that', 'one', 'inequality', 'implies', 'the', 'other']] | [-0.22011464894449367, -0.010509923255691925, -0.06952427028480804, 0.09037927522810853, -0.09484602400863712, -0.15532339899800718, -0.0050116791389882565, 0.3382998869726152, -0.2862574935636737, -0.23115241200183378, 0.08642965896852371, -0.26678244927968603, -0.1969188089327266, 0.23196906731887298, -0.1479674210546143, 0.05070083575661887, 0.09310060241400744, 0.044831651601601734, -0.06617366282311692, -0.271542800361093, 0.38830803447600565, -0.032008485910906034, 0.25896449092860246, 0.1144494623665444, 0.14534173036615053, 0.06366584239753359, 0.006303488156955802, -0.008592738341328433, -0.16121511600993638, 0.11703970010928584, 0.20559585427470278, 0.07879781013947319, 0.19227711707141928, -0.36809949133770936, -0.18083329851541555, 0.16904036297328826, 0.14879896456488606, 0.006324995506667729, 0.004188844501958088, -0.25072567489096953, 0.022855901145235155, -0.09301428256951498, -0.21295265326361087, -0.03480955418622629, 0.01526857235214927, 0.06843670404332718, -0.2112256568322085, 0.010846017267216335, 0.15347736892043473, 0.07640324843602932, -0.03781909779222174, -0.07593745859622052, -0.09044821683500866, 0.08138278771586942, 0.07470966854033935, 0.08646001683717425, 0.12306133642877368, -0.08594257044464801, -0.10753127634807517, 0.3807270911127103, -0.07091796432029117, -0.27200584954610374, 0.1190959837333525, -0.22497440631868262, -0.18082283389274822, 0.12529074277368968, 0.08239711887400711, 0.12229467038008751, -0.04644146077705293, 0.09690711800905058, -0.13378639055846372, 0.11213437045896144, 0.11543410360305147, -0.017873940252078075, 0.16316376494554183, 0.0696072936989367, 0.1158582451488738, 0.1437794936857906, -0.02825420292334236, -0.11333763944408433, -0.33639918899897375, -0.22718221543949435, -0.16858633077407087, 0.11950224539208593, -0.13778667676105574, -0.1734444251933107, 0.3523475962063072, -0.052849201654846016, 0.23386451551888252, 0.08431959094366792, 0.25338322886576253, 0.04867985528350497, 0.13359634665010328, 0.03198942812300767, 0.25139548623877944, 0.21249410098376262, 0.028188536656230237, -0.07076130498017212, 0.014100259811984319, 0.128592573628394] |
1,802.03798 | Perversity equals weight for Painlev\'e spaces | We provide further evidence to the $P=W$ conjecture of de Cataldo, Hausel and
Migliorini, by checking it in the Painlev\'e cases. Namely, we compare the
perverse Leray filtration induced by the Hitchin map on the cohomology spaces
of the Dolbeault moduli space and the weight filtration on the cohomology
spaces of the irregular character variety corresponding to each of the
Painlev\'e $I-VI$ systems. We find that the two filtrations agree. Along the
way, we prove the Geometric $P=W$ conjecture of Katzarkov, Noll, Pandit and
Simpson in the Painlev\'e cases, and show that in these cases the Geometric
$P=W$ conjecture implies the $P=W$ conjecture.
| math.AG | we provide further evidence to the pw conjecture of de cataldo hausel and migliorini by checking it in the painleve cases namely we compare the perverse leray filtration induced by the hitchin map on the cohomology spaces of the dolbeault moduli space and the weight filtration on the cohomology spaces of the irregular character variety corresponding to each of the painleve ivi systems we find that the two filtrations agree along the way we prove the geometric pw conjecture of katzarkov noll pandit and simpson in the painleve cases and show that in these cases the geometric pw conjecture implies the pw conjecture | [['we', 'provide', 'further', 'evidence', 'to', 'the', 'pw', 'conjecture', 'of', 'de', 'cataldo', 'hausel', 'and', 'migliorini', 'by', 'checking', 'it', 'in', 'the', 'painleve', 'cases', 'namely', 'we', 'compare', 'the', 'perverse', 'leray', 'filtration', 'induced', 'by', 'the', 'hitchin', 'map', 'on', 'the', 'cohomology', 'spaces', 'of', 'the', 'dolbeault', 'moduli', 'space', 'and', 'the', 'weight', 'filtration', 'on', 'the', 'cohomology', 'spaces', 'of', 'the', 'irregular', 'character', 'variety', 'corresponding', 'to', 'each', 'of', 'the', 'painleve', 'ivi', 'systems', 'we', 'find', 'that', 'the', 'two', 'filtrations', 'agree', 'along', 'the', 'way', 'we', 'prove', 'the', 'geometric', 'pw', 'conjecture', 'of', 'katzarkov', 'noll', 'pandit', 'and', 'simpson', 'in', 'the', 'painleve', 'cases', 'and', 'show', 'that', 'in', 'these', 'cases', 'the', 'geometric', 'pw', 'conjecture', 'implies', 'the', 'pw', 'conjecture']] | [-0.16088703359269257, -0.0020371367804507172, -0.14036535359557392, 0.11263960005389978, -0.06250033424082167, -0.12487274428232781, -0.013247301358982775, 0.2948951927845556, -0.31749140927274216, -0.20253318976791737, 0.0720077908645357, -0.22572907883203724, -0.20088585836867107, 0.20099723105798067, -0.1879685552230159, 0.011758385678228823, 0.047369357718389876, -0.006893641724267034, -0.06968142302185229, -0.32657773137201096, 0.41122520111899064, -0.037016483385441376, 0.2359002075040514, 0.05424380573462152, 0.08802634328875003, 0.026068113222085302, -0.030527603127586754, -0.09714423703558919, -0.2014835085952937, 0.15544856006948693, 0.2659825137409481, 0.07531427771748198, 0.1634198504509133, -0.3541760316968543, -0.13087883753051022, 0.14540340181313527, 0.09506647122653147, 0.04640203351787861, 0.034943151925193164, -0.3154242892740566, 0.08592065056623185, -0.15313021950785397, -0.18089339521360917, -0.0741916662391481, 0.06264904814148411, 0.07169492744379541, -0.1763835917000921, 0.040034321823962105, 0.08989000152253988, 0.07937755974606403, -0.09390672009655283, -0.08979505439768139, -0.13271227409809971, 0.01651928807129559, 0.03126695736772516, 0.014093366433477517, 0.009216752183596485, -0.13278373923758496, -0.1325125897719154, 0.34370133847911455, -0.0743104835917938, -0.1427005028478729, 0.11842479731308893, -0.1615195386473415, -0.20934377639617735, 0.08928124285619525, 0.004186560268721823, 0.1297854209189909, 0.05619148541585479, 0.16978819052309016, -0.10216966073155331, 0.05855901599906891, 0.17947412785866018, -0.01360431967248905, 0.0978821831782466, 0.04649676962583823, 0.02003811531388246, 0.09341890459825981, -0.04172381795761944, -0.055888742781515476, -0.3317669313943502, -0.25594012363298424, -0.09662532630530231, 0.07719524481867268, -0.13462304240443013, -0.1220305988076821, 0.3844868616671166, 0.11373166243988768, 0.16831647404876438, 0.16015664222469392, 0.183263900065885, 0.09017904198647124, 0.004540025193280387, 0.03537011414639724, 0.20257940716607478, 0.20840299873187848, 0.05873475280348483, -0.19801166022051742, -0.009723104663968574, 0.2681623903889824] |
1,802.03799 | Further results for starlike functions related with Booth lemniscate | In this paper we investigate an interesting subclass $\mathcal{BS}(\alpha)$
($0\leq \alpha<1$) of starlike functions in the unit disk $\Delta$. The class
$\mathcal{BS}(\alpha)$ was introduced by Kargar et al. [R. Kargar, A. Ebadian
and J. Sok\'o{\l}, {\it On Booth lemniscate and starlike functions}, Anal.
Math. Phys. (2017) DOI: 10.1007/s13324-017-0187-3] which is strongly related to
the Booth lemniscate. Some geometric properties of this class of analytic
functions including, radius of starlikeness of order $\gamma$
($0\leq\gamma<1$), the image of $f(\{z:|z|<r\})$ when $f\in
\mathcal{BS}(\alpha)$, an special example and estimate of bounds for ${\rm
Re}\{f(z)/z\}$ are studied.
| math.CV | in this paper we investigate an interesting subclass mathcalbsalpha 0leq alpha1 of starlike functions in the unit disk delta the class mathcalbsalpha was introduced by kargar et al r kargar a ebadian and j sokol it on booth lemniscate and starlike functions anal math phys 2017 doi 101007s1332401701873 which is strongly related to the booth lemniscate some geometric properties of this class of analytic functions including radius of starlikeness of order gamma 0leqgamma1 the image of fzzr when fin mathcalbsalpha an special example and estimate of bounds for rm refzz are studied | [['in', 'this', 'paper', 'we', 'investigate', 'an', 'interesting', 'subclass', 'mathcalbsalpha', '0leq', 'alpha1', 'of', 'starlike', 'functions', 'in', 'the', 'unit', 'disk', 'delta', 'the', 'class', 'mathcalbsalpha', 'was', 'introduced', 'by', 'kargar', 'et', 'al', 'r', 'kargar', 'a', 'ebadian', 'and', 'j', 'sokol', 'it', 'on', 'booth', 'lemniscate', 'and', 'starlike', 'functions', 'anal', 'math', 'phys', '2017', 'doi', '101007s1332401701873', 'which', 'is', 'strongly', 'related', 'to', 'the', 'booth', 'lemniscate', 'some', 'geometric', 'properties', 'of', 'this', 'class', 'of', 'analytic', 'functions', 'including', 'radius', 'of', 'starlikeness', 'of', 'order', 'gamma', '0leqgamma1', 'the', 'image', 'of', 'fzzr', 'when', 'fin', 'mathcalbsalpha', 'an', 'special', 'example', 'and', 'estimate', 'of', 'bounds', 'for', 'rm', 'refzz', 'are', 'studied']] | [-0.0990105767022161, 0.030159263874691748, 0.013145361588720013, 0.011199135644197026, -0.09675782112514271, -0.08547310449511689, -0.019772126907756662, 0.3477828482823337, -0.2347164328703109, -0.2762428066528895, 0.09279601654065225, -0.28481829846003914, -0.19456218834760983, 0.2303985980722834, -0.10689187667825643, 0.06415082021232914, -0.043786345214089924, -0.029650538257898436, -0.07948391081436593, -0.25735432526288443, 0.2975676755694782, 0.0387980201993795, 0.13543257029514816, 0.08283072560614742, 0.023625811067519382, 0.03740395749097361, -0.05611815823461203, -0.031784322474370984, -0.3084591829272754, 0.09942604727796553, 0.21956028309376802, 0.08577125801102203, 0.2724945440833621, -0.2926987715175047, -0.16805107271408334, 0.13560618141337352, 0.04947498639607254, -0.05769094445277005, 0.02075398116619052, -0.2801334414631128, 0.08602374396629303, -0.15172528736293317, -0.15273877066176603, -0.02089955291012302, 0.1753544664941728, 0.10379462620955618, -0.32116546376663097, 0.0981453024837024, 0.1655377093976473, 0.05002609531888191, -0.0263087887522381, -0.15187698947265743, -0.014377515078248346, 0.012610012636971934, -0.04154348474488977, 0.11842906491502243, 0.03022462929982473, -0.0944385311949779, -0.07344695924069075, 0.32097433249959173, 0.0031527341165415506, -0.18676400408148766, 0.17043552452917485, -0.16212516606182736, -0.20118883145315683, 0.057401203935253706, 0.16119099870762404, 0.20211112021523364, -0.13967524995729463, 0.20142399299520014, -0.1181552183252814, 0.11286722675842398, 0.1584215378114844, 0.004193952331757721, 0.0873503225033774, 0.04035481145769796, 0.02263159531113856, 0.1760712971417781, -0.04927324754569461, -0.057594643196994984, -0.31410881683011266, -0.17147592340102968, -0.19377123680623137, 0.07048294048701577, -0.05750940051974099, -0.17272626421113005, 0.38668191694818876, 0.04245104600730188, 0.19378981451668284, 0.04681291519527269, 0.10157861809574945, 0.10918637009008843, -0.012077402602881194, 0.14620148638153777, 0.18051944067872897, 0.18587029071469954, 0.06866361648392151, -0.141806289876866, 0.008854944264406667, 0.14288482623284354] |
1,802.038 | Drug response prediction by ensemble learning and drug-induced gene
expression signatures | Chemotherapeutic response of cancer cells to a given compound is one of the
most fundamental information one requires to design anti-cancer drugs. Recent
advances in producing large drug screens against cancer cell lines provided an
opportunity to apply machine learning methods for this purpose. In addition to
cytotoxicity databases, considerable amount of drug-induced gene expression
data has also become publicly available. Following this, several methods that
exploit omics data were proposed to predict drug activity on cancer cells.
However, due to the complexity of cancer drug mechanisms, none of the existing
methods are perfect. One possible direction, therefore, is to combine the
strengths of both the methods and the databases for improved performance. We
demonstrate that integrating a large number of predictions by the proposed
method improves the performance for this task. The predictors in the ensemble
differ in several aspects such as the method itself, the number of tasks method
considers (multi-task vs. single-task) and the subset of data considered
(sub-sampling). We show that all these different aspects contribute to the
success of the final ensemble. In addition, we attempt to use the drug screen
data together with two novel signatures produced from the drug-induced gene
expression profiles of cancer cell lines. Finally, we evaluate the method
predictions by in vitro experiments in addition to the tests on data sets.The
predictions of the methods, the signatures and the software are available from
\url{http://mtan.etu.edu.tr/drug-response-prediction/}.
| q-bio.GN cs.LG stat.ML | chemotherapeutic response of cancer cells to a given compound is one of the most fundamental information one requires to design anticancer drugs recent advances in producing large drug screens against cancer cell lines provided an opportunity to apply machine learning methods for this purpose in addition to cytotoxicity databases considerable amount of druginduced gene expression data has also become publicly available following this several methods that exploit omics data were proposed to predict drug activity on cancer cells however due to the complexity of cancer drug mechanisms none of the existing methods are perfect one possible direction therefore is to combine the strengths of both the methods and the databases for improved performance we demonstrate that integrating a large number of predictions by the proposed method improves the performance for this task the predictors in the ensemble differ in several aspects such as the method itself the number of tasks method considers multitask vs singletask and the subset of data considered subsampling we show that all these different aspects contribute to the success of the final ensemble in addition we attempt to use the drug screen data together with two novel signatures produced from the druginduced gene expression profiles of cancer cell lines finally we evaluate the method predictions by in vitro experiments in addition to the tests on data setsthe predictions of the methods the signatures and the software are available from urlhttpmtanetuedutrdrugresponseprediction | [['chemotherapeutic', 'response', 'of', 'cancer', 'cells', 'to', 'a', 'given', 'compound', 'is', 'one', 'of', 'the', 'most', 'fundamental', 'information', 'one', 'requires', 'to', 'design', 'anticancer', 'drugs', 'recent', 'advances', 'in', 'producing', 'large', 'drug', 'screens', 'against', 'cancer', 'cell', 'lines', 'provided', 'an', 'opportunity', 'to', 'apply', 'machine', 'learning', 'methods', 'for', 'this', 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0.001105898790511078] |
1,802.03801 | SGD and Hogwild! Convergence Without the Bounded Gradients Assumption | Stochastic gradient descent (SGD) is the optimization algorithm of choice in
many machine learning applications such as regularized empirical risk
minimization and training deep neural networks. The classical convergence
analysis of SGD is carried out under the assumption that the norm of the
stochastic gradient is uniformly bounded. While this might hold for some loss
functions, it is always violated for cases where the objective function is
strongly convex. In (Bottou et al.,2016), a new analysis of convergence of SGD
is performed under the assumption that stochastic gradients are bounded with
respect to the true gradient norm. Here we show that for stochastic problems
arising in machine learning such bound always holds; and we also propose an
alternative convergence analysis of SGD with diminishing learning rate regime,
which results in more relaxed conditions than those in (Bottou et al.,2016). We
then move on the asynchronous parallel setting, and prove convergence of
Hogwild! algorithm in the same regime, obtaining the first convergence results
for this method in the case of diminished learning rate.
| math.OC cs.LG stat.ML | stochastic gradient descent sgd is the optimization algorithm of choice in many machine learning applications such as regularized empirical risk minimization and training deep neural networks the classical convergence analysis of sgd is carried out under the assumption that the norm of the stochastic gradient is uniformly bounded while this might hold for some loss functions it is always violated for cases where the objective function is strongly convex in bottou et al2016 a new analysis of convergence of sgd is performed under the assumption that stochastic gradients are bounded with respect to the true gradient norm here we show that for stochastic problems arising in machine learning such bound always holds and we also propose an alternative convergence analysis of sgd with diminishing learning rate regime which results in more relaxed conditions than those in bottou et al2016 we then move on the asynchronous parallel setting and prove convergence of hogwild algorithm in the same regime obtaining the first convergence results for this method in the case of diminished learning rate | [['stochastic', 'gradient', 'descent', 'sgd', 'is', 'the', 'optimization', 'algorithm', 'of', 'choice', 'in', 'many', 'machine', 'learning', 'applications', 'such', 'as', 'regularized', 'empirical', 'risk', 'minimization', 'and', 'training', 'deep', 'neural', 'networks', 'the', 'classical', 'convergence', 'analysis', 'of', 'sgd', 'is', 'carried', 'out', 'under', 'the', 'assumption', 'that', 'the', 'norm', 'of', 'the', 'stochastic', 'gradient', 'is', 'uniformly', 'bounded', 'while', 'this', 'might', 'hold', 'for', 'some', 'loss', 'functions', 'it', 'is', 'always', 'violated', 'for', 'cases', 'where', 'the', 'objective', 'function', 'is', 'strongly', 'convex', 'in', 'bottou', 'et', 'al2016', 'a', 'new', 'analysis', 'of', 'convergence', 'of', 'sgd', 'is', 'performed', 'under', 'the', 'assumption', 'that', 'stochastic', 'gradients', 'are', 'bounded', 'with', 'respect', 'to', 'the', 'true', 'gradient', 'norm', 'here', 'we', 'show', 'that', 'for', 'stochastic', 'problems', 'arising', 'in', 'machine', 'learning', 'such', 'bound', 'always', 'holds', 'and', 'we', 'also', 'propose', 'an', 'alternative', 'convergence', 'analysis', 'of', 'sgd', 'with', 'diminishing', 'learning', 'rate', 'regime', 'which', 'results', 'in', 'more', 'relaxed', 'conditions', 'than', 'those', 'in', 'bottou', 'et', 'al2016', 'we', 'then', 'move', 'on', 'the', 'asynchronous', 'parallel', 'setting', 'and', 'prove', 'convergence', 'of', 'hogwild', 'algorithm', 'in', 'the', 'same', 'regime', 'obtaining', 'the', 'first', 'convergence', 'results', 'for', 'this', 'method', 'in', 'the', 'case', 'of', 'diminished', 'learning', 'rate']] | [-0.07614465147124191, 0.022294562891464774, -0.10853953474657448, 0.10450601720435242, -0.043646456975608976, -0.1630036065132942, 0.02731336394479217, 0.4130053628929133, -0.3351469123654804, -0.2503110401019005, 0.12428902940104478, -0.23389973578606407, -0.1835368063170896, 0.2229909931233716, -0.13472513282444154, 0.09816085623081795, 0.10371921812170619, 0.0055001800728225435, -0.0840094395558523, -0.33541979742517997, 0.2644105092243313, 0.04697437975186784, 0.3053274777972378, -0.0002576765491962866, 0.1156677043730079, -0.011289810296148062, 0.03704362258932358, 0.026500449212055046, -0.09006628995624386, 0.12680525959741465, 0.23483292098958478, 0.19446897598627824, 0.41103751189773396, -0.3886443579049651, -0.18848979786081715, 0.17789746131368933, 0.16181958254174936, 0.08051896918914281, -0.07367732053256099, -0.22647859840951642, 0.11122669432268933, -0.09688961298237446, -0.06623463503485762, -0.12285066030237304, -0.06299129374552691, 0.07309440752663271, -0.3443712029703568, 0.09441063332836398, 0.1332072911020585, 0.05312114309378748, -0.08078699129861021, -0.13396041865763797, 0.05009233520831913, 0.027139658763528217, 0.10884463271738008, 0.0821506756596094, 0.13992282763112682, -0.1259880764436973, -0.09980830884007953, 0.304022571256081, -0.08213496146844443, -0.22387528011228802, 0.1662737827691883, -0.06923501751234018, -0.1896387587124103, 0.07995316905895421, 0.2099349110625511, 0.18991274716938997, -0.14247413925003521, 0.09669337838348055, -0.05582715365406245, 0.0980834215446267, 0.03630202258517424, -0.0055608270780540744, 0.04185844615756989, 0.18488357197980634, 0.19665866697831133, 0.14031602607987181, -0.058517748188108294, -0.17360825767350752, -0.2914257415916857, -0.11729919271669513, -0.18567718025215707, 0.02197572112091557, -0.12503838572398351, -0.15016483560375068, 0.3080544371406959, 0.1477680348904213, 0.17282756422321463, 0.15938122869471932, 0.3124436485082951, 0.1275544740350343, 0.03474828185172492, 0.17786930030385076, 0.26899139437134795, 0.12290584967000583, 0.13055211480376636, -0.21275613265556045, 0.12484073402024372, 0.0914194643134346] |
1,802.03802 | MeltdownPrime and SpectrePrime: Automatically-Synthesized Attacks
Exploiting Invalidation-Based Coherence Protocols | The recent Meltdown and Spectre attacks highlight the importance of automated
verification techniques for identifying hardware security vulnerabilities. We
have developed a tool for synthesizing microarchitecture-specific programs
capable of producing any user-specified hardware execution pattern of interest.
Our tool takes two inputs: a formal description of (i) a microarchitecture in a
domain-specific language, and (ii) a microarchitectural execution pattern of
interest, e.g. a threat pattern. All programs synthesized by our tool are
capable of producing the specified execution pattern on the supplied
microarchitecture.
We used our tool to specify a hardware execution pattern common to
Flush+Reload attacks and automatically synthesized security litmus tests
representative of those that have been publicly disclosed for conducting
Meltdown and Spectre attacks. We also formulated a Prime+Probe threat pattern,
enabling our tool to synthesize a new variant of each---MeltdownPrime and
SpectrePrime. Both of these new exploits use Prime+Probe approaches to conduct
the timing attack. They are both also novel in that they are 2-core attacks
which leverage the cache line invalidation mechanism in modern cache coherence
protocols. These are the first proposed Prime+Probe variants of Meltdown and
Spectre. But more importantly, both Prime attacks exploit invalidation-based
coherence protocols to achieve the same level of precision as a Flush+Reload
attack. While mitigation techniques in software (e.g., barriers that prevent
speculation) will likely be the same for our Prime variants as for original
Spectre and Meltdown, we believe that hardware protection against them will be
distinct. As a proof of concept, we implemented SpectrePrime as a C program and
ran it on an Intel x86 processor, averaging about the same accuracy as Spectre
over 100 runs---97.9% for Spectre and 99.95% for SpectrePrime.
| cs.CR cs.AR | the recent meltdown and spectre attacks highlight the importance of automated verification techniques for identifying hardware security vulnerabilities we have developed a tool for synthesizing microarchitecturespecific programs capable of producing any userspecified hardware execution pattern of interest our tool takes two inputs a formal description of i a microarchitecture in a domainspecific language and ii a microarchitectural execution pattern of interest eg a threat pattern all programs synthesized by our tool are capable of producing the specified execution pattern on the supplied microarchitecture we used our tool to specify a hardware execution pattern common to flushreload attacks and automatically synthesized security litmus tests representative of those that have been publicly disclosed for conducting meltdown and spectre attacks we also formulated a primeprobe threat pattern enabling our tool to synthesize a new variant of eachmeltdownprime and spectreprime both of these new exploits use primeprobe approaches to conduct the timing attack they are both also novel in that they are 2core attacks which leverage the cache line invalidation mechanism in modern cache coherence protocols these are the first proposed primeprobe variants of meltdown and spectre but more importantly both prime attacks exploit invalidationbased coherence protocols to achieve the same level of precision as a flushreload attack while mitigation techniques in software eg barriers that prevent speculation will likely be the same for our prime variants as for original spectre and meltdown we believe that hardware protection against them will be distinct as a proof of concept we implemented spectreprime as a c program and ran it on an intel x86 processor averaging about the same accuracy as spectre over 100 runs979 for spectre and 9995 for spectreprime | [['the', 'recent', 'meltdown', 'and', 'spectre', 'attacks', 'highlight', 'the', 'importance', 'of', 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1,802.03803 | FlipDial: A Generative Model for Two-Way Visual Dialogue | We present FlipDial, a generative model for visual dialogue that
simultaneously plays the role of both participants in a visually-grounded
dialogue. Given context in the form of an image and an associated caption
summarising the contents of the image, FlipDial learns both to answer questions
and put forward questions, capable of generating entire sequences of dialogue
(question-answer pairs) which are diverse and relevant to the image. To do
this, FlipDial relies on a simple but surprisingly powerful idea: it uses
convolutional neural networks (CNNs) to encode entire dialogues directly,
implicitly capturing dialogue context, and conditional VAEs to learn the
generative model. FlipDial outperforms the state-of-the-art model in the
sequential answering task (one-way visual dialogue) on the VisDial dataset by 5
points in Mean Rank using the generated answers. We are the first to extend
this paradigm to full two-way visual dialogue, where our model is capable of
generating both questions and answers in sequence based on a visual input, for
which we propose a set of novel evaluation measures and metrics.
| cs.CV | we present flipdial a generative model for visual dialogue that simultaneously plays the role of both participants in a visuallygrounded dialogue given context in the form of an image and an associated caption summarising the contents of the image flipdial learns both to answer questions and put forward questions capable of generating entire sequences of dialogue questionanswer pairs which are diverse and relevant to the image to do this flipdial relies on a simple but surprisingly powerful idea it uses convolutional neural networks cnns to encode entire dialogues directly implicitly capturing dialogue context and conditional vaes to learn the generative model flipdial outperforms the stateoftheart model in the sequential answering task oneway visual dialogue on the visdial dataset by 5 points in mean rank using the generated answers we are the first to extend this paradigm to full twoway visual dialogue where our model is capable of generating both questions and answers in sequence based on a visual input for which we propose a set of novel evaluation measures and metrics | [['we', 'present', 'flipdial', 'a', 'generative', 'model', 'for', 'visual', 'dialogue', 'that', 'simultaneously', 'plays', 'the', 'role', 'of', 'both', 'participants', 'in', 'a', 'visuallygrounded', 'dialogue', 'given', 'context', 'in', 'the', 'form', 'of', 'an', 'image', 'and', 'an', 'associated', 'caption', 'summarising', 'the', 'contents', 'of', 'the', 'image', 'flipdial', 'learns', 'both', 'to', 'answer', 'questions', 'and', 'put', 'forward', 'questions', 'capable', 'of', 'generating', 'entire', 'sequences', 'of', 'dialogue', 'questionanswer', 'pairs', 'which', 'are', 'diverse', 'and', 'relevant', 'to', 'the', 'image', 'to', 'do', 'this', 'flipdial', 'relies', 'on', 'a', 'simple', 'but', 'surprisingly', 'powerful', 'idea', 'it', 'uses', 'convolutional', 'neural', 'networks', 'cnns', 'to', 'encode', 'entire', 'dialogues', 'directly', 'implicitly', 'capturing', 'dialogue', 'context', 'and', 'conditional', 'vaes', 'to', 'learn', 'the', 'generative', 'model', 'flipdial', 'outperforms', 'the', 'stateoftheart', 'model', 'in', 'the', 'sequential', 'answering', 'task', 'oneway', 'visual', 'dialogue', 'on', 'the', 'visdial', 'dataset', 'by', '5', 'points', 'in', 'mean', 'rank', 'using', 'the', 'generated', 'answers', 'we', 'are', 'the', 'first', 'to', 'extend', 'this', 'paradigm', 'to', 'full', 'twoway', 'visual', 'dialogue', 'where', 'our', 'model', 'is', 'capable', 'of', 'generating', 'both', 'questions', 'and', 'answers', 'in', 'sequence', 'based', 'on', 'a', 'visual', 'input', 'for', 'which', 'we', 'propose', 'a', 'set', 'of', 'novel', 'evaluation', 'measures', 'and', 'metrics']] | [-0.04194044485029203, 0.014137077427296273, -0.05426519971929098, 0.10974606755257676, -0.1338447753655893, -0.15477460740700538, 0.041722415608070704, 0.4264004682109021, -0.2640693716334495, -0.32590895509946416, 0.004555546626181761, -0.2752818431138818, -0.19483655354291288, 0.207855861761324, -0.1656338524942052, 0.07131421525502436, 0.10008917765130905, 0.07291113801997656, -0.021742950997598556, -0.29409241668705705, 0.35835826004125526, 0.024360676214360354, 0.3334447609108181, 0.010581349401887267, 0.18488479020585966, 0.001486413145426944, -0.06155324333731346, -0.07214895237444176, -0.05722148603663885, 0.21317763861516567, 0.3354240976020759, 0.23971371147073586, 0.33665383279552324, -0.38986667391588115, -0.20627144194474956, 0.06826208615253478, 0.11107900237109054, 0.10863713812142915, -0.04289996605407316, -0.3642626161529133, 0.093723770226243, -0.15138988992490682, 0.059988253624641406, -0.13187701748520658, -0.007518642853635053, -0.04189483789735261, -0.30004156589622427, 0.002692481769760798, 0.14868036504529897, 0.05724983793895757, -0.05556197524648051, -0.038910180474604254, 0.02646868348350389, 0.21472442678410059, -0.00660168814413987, 0.09399910142906663, 0.10024020384877311, -0.21341318400047055, -0.15990148474767324, 0.3646782917564201, -0.06939006889135474, -0.225311035948941, 0.180235793426012, -0.028836022926309303, -0.14360224103081254, 0.04537259242415689, 0.2276925120056111, 0.1247866885756668, -0.16553439564828637, 0.010113307956350173, -0.11646517093037391, 0.2116632262184911, 0.04419606184989911, -0.0057095832801396735, 0.23124046685250357, 0.24112965003995782, -0.030434874590344684, 0.12192948075005926, -0.06962936288133885, -0.10914480367032757, -0.21635659865501244, -0.10945490136339564, -0.15693564988994066, -0.02096215354779746, -0.04756595217163282, -0.16387114270526593, 0.42155055603562525, 0.2509423986850688, 0.23241675176183907, 0.12113186257363062, 0.30979968291402343, 0.0065608831036227284, 0.0741702431944956, 0.08953558163253089, 0.09945549546299796, 0.019182113125887617, 0.11531832477905685, -0.14009016690835663, 0.1077626280919567, 0.1054324082736122] |
1,802.03804 | Physical and Geometrical Parameters of VCBS XIII: HIP 105947 | The perfect physical and geometrical parameters of the main-sequence close
visual binary system (CVBS), HIP\,105947, are explicitly presented. These
parameters have been constructed conclusively using Al-Wardat's complex method
for analyzing CVBSs, which is a method for constructing a synthetic spectral
energy distribution (SED) for the entire binary system using individual SED for
each component star. Which in its turn built using Kurucz
({\fontfamily{cmtt}\selectfont ATLAS9}) line-blanketed plane-parallel models.
At the same time, the orbital parameters for the system are calculated using
Tokovinin's dynamical method for constructing the best orbits of the
interferometric binary system. Henceforth, the mass-sum of the components, the
$\triangle\theta $ and $\triangle\rho $ residuals for the system are
introduced. The combination of Al-Wardat's and Tokovinin's methods yields the
estimation of the physical and geometrical parameters to their best values. The
positions of the components of the system on the evolutionary tracks and
isochrones are plotted, and their formation and evolution are discussed.
| astro-ph.SR | the perfect physical and geometrical parameters of the mainsequence close visual binary system cvbs hip105947 are explicitly presented these parameters have been constructed conclusively using alwardats complex method for analyzing cvbss which is a method for constructing a synthetic spectral energy distribution sed for the entire binary system using individual sed for each component star which in its turn built using kurucz fontfamilycmttselectfont atlas9 lineblanketed planeparallel models at the same time the orbital parameters for the system are calculated using tokovinins dynamical method for constructing the best orbits of the interferometric binary system henceforth the masssum of the components the triangletheta and trianglerho residuals for the system are introduced the combination of alwardats and tokovinins methods yields the estimation of the physical and geometrical parameters to their best values the positions of the components of the system on the evolutionary tracks and isochrones are plotted and their formation and evolution are discussed | [['the', 'perfect', 'physical', 'and', 'geometrical', 'parameters', 'of', 'the', 'mainsequence', 'close', 'visual', 'binary', 'system', 'cvbs', 'hip105947', 'are', 'explicitly', 'presented', 'these', 'parameters', 'have', 'been', 'constructed', 'conclusively', 'using', 'alwardats', 'complex', 'method', 'for', 'analyzing', 'cvbss', 'which', 'is', 'a', 'method', 'for', 'constructing', 'a', 'synthetic', 'spectral', 'energy', 'distribution', 'sed', 'for', 'the', 'entire', 'binary', 'system', 'using', 'individual', 'sed', 'for', 'each', 'component', 'star', 'which', 'in', 'its', 'turn', 'built', 'using', 'kurucz', 'fontfamilycmttselectfont', 'atlas9', 'lineblanketed', 'planeparallel', 'models', 'at', 'the', 'same', 'time', 'the', 'orbital', 'parameters', 'for', 'the', 'system', 'are', 'calculated', 'using', 'tokovinins', 'dynamical', 'method', 'for', 'constructing', 'the', 'best', 'orbits', 'of', 'the', 'interferometric', 'binary', 'system', 'henceforth', 'the', 'masssum', 'of', 'the', 'components', 'the', 'triangletheta', 'and', 'trianglerho', 'residuals', 'for', 'the', 'system', 'are', 'introduced', 'the', 'combination', 'of', 'alwardats', 'and', 'tokovinins', 'methods', 'yields', 'the', 'estimation', 'of', 'the', 'physical', 'and', 'geometrical', 'parameters', 'to', 'their', 'best', 'values', 'the', 'positions', 'of', 'the', 'components', 'of', 'the', 'system', 'on', 'the', 'evolutionary', 'tracks', 'and', 'isochrones', 'are', 'plotted', 'and', 'their', 'formation', 'and', 'evolution', 'are', 'discussed']] | [-0.0627738957187426, 0.054001309797361806, -0.10207798758347053, 0.0733400954826114, -0.03970448416981122, -0.09281503947972346, 0.026342577297732025, 0.39916415279731154, -0.21629676786122015, -0.3654149996065017, 0.10676676745465051, -0.2253674983528779, -0.07873273517503145, 0.22423463169899252, -0.005657818614660452, 0.09326450611327648, 0.09596233063752556, -0.017713231088742357, -0.0805851536489273, -0.23669256011231077, 0.34399431508306105, 0.06841944063489791, 0.18993048794962103, -0.07752151114012425, 0.10955057987788071, -0.014440894043622797, -0.04952622568816878, -0.008977694100596838, -0.13805879844585434, 0.11234147233173847, 0.18088593032040182, 0.14987088389494196, 0.1543150062562846, -0.3344107667152356, -0.24018602620021234, 0.060364022876860365, 0.12377325837021796, 0.08203313950313411, -0.004356278472793444, -0.25607495084841503, 0.0846555543458736, -0.17520859510275638, -0.127506788622769, -0.053599046953927934, 0.03285588939777679, 0.09365476878722095, -0.27531718366501284, 0.03926527853925816, 0.025472987951515178, 0.08675543853152906, -0.14653284561629537, -0.18170696106487108, -0.09849516123843689, 0.18990490140600336, -0.03434932874936041, -0.00464659928305385, 0.1115171062022758, -0.08510203464862166, -0.06662380998063276, 0.3924745686106487, -0.04989831810396734, -0.17398845859376402, 0.19463768496643752, -0.08337006109326871, -0.11369224143951821, 0.11297542368831476, 0.14952272233980088, 0.13254272328211097, -0.19736087278902736, 0.041515887327275576, 0.006557815510960709, 0.18008286938452833, 0.021433593896088295, 0.017198588320752606, 0.29045180034720236, 0.14775013677232587, -0.058939208628342184, 0.09782434865418407, -0.15067373021318214, -0.12122591394775857, -0.234467987184568, -0.0917092095155062, -0.18259590266582867, -0.04114844857475772, -0.14274675885351623, -0.171720744524565, 0.4394439034577873, 0.13088367718834584, 0.20716365202436768, 0.03699492402989159, 0.30890331091520945, 0.14042873677357826, 0.04795471427819899, 0.0871453685783005, 0.2761304858625711, 0.13512384509926456, 0.07452188284433861, -0.25897713168888004, 0.09742084606356609, 0.06890841200624385] |
1,802.03805 | Quantum mechanics, ontology, and non-reflexive logics | This is a general philosophical paper where I overview some ideas concerning
the non-reflexive foundations of quantum mechanics (NRFQM). By NRFQM I mean
formalism and an interpretation of QM that considers an involved ontology of
non-individuals as explained in the text. Thus, I do not endorse a purely
instrumentalist view of QM, but believe that it speaks of something, and then I
try to show that one of the plausible views of this `something' is as entities
devoid of identity conditions. Warning note: This is a revised version of a
paper with the same name that was written by invitation to be published in a
book titled \textit{The Mammoth Book on Quantum Mechanics Interpretations},
edited by Open Academic Press, Berlin, and having as editor a certain Ulf
Edvinsson, who has invited me. The book was announced in the page of OAP and
should appear by 2016. This never happened. Later I discovered that OAP is in a
list of predatory editorial houses and that "Ulf Edvinsson" is (apparently) a
fake name. Furthermore, I couldn't contact anyone responding by OAP to retire
my name from the announcement of the book and for impeding them to publish the
paper. I strongly apologize for such a fault, which is completely mine. Since
the subject presented here has been among my preoccupations ever since I met
Franscicso Antonio Doria for the first time (in 1987), it is a pleasure to
dedicate the stuff to him. And of course I thank the editors for accepting this
version of the paper for this book.
| math.LO | this is a general philosophical paper where i overview some ideas concerning the nonreflexive foundations of quantum mechanics nrfqm by nrfqm i mean formalism and an interpretation of qm that considers an involved ontology of nonindividuals as explained in the text thus i do not endorse a purely instrumentalist view of qm but believe that it speaks of something and then i try to show that one of the plausible views of this something is as entities devoid of identity conditions warning note this is a revised version of a paper with the same name that was written by invitation to be published in a book titled textitthe mammoth book on quantum mechanics interpretations edited by open academic press berlin and having as editor a certain ulf edvinsson who has invited me the book was announced in the page of oap and should appear by 2016 this never happened later i discovered that oap is in a list of predatory editorial houses and that ulf edvinsson is apparently a fake name furthermore i couldnt contact anyone responding by oap to retire my name from the announcement of the book and for impeding them to publish the paper i strongly apologize for such a fault which is completely mine since the subject presented here has been among my preoccupations ever since i met franscicso antonio doria for the first time in 1987 it is a pleasure to dedicate the stuff to him and of course i thank the editors for accepting this version of the paper for this book | [['this', 'is', 'a', 'general', 'philosophical', 'paper', 'where', 'i', 'overview', 'some', 'ideas', 'concerning', 'the', 'nonreflexive', 'foundations', 'of', 'quantum', 'mechanics', 'nrfqm', 'by', 'nrfqm', 'i', 'mean', 'formalism', 'and', 'an', 'interpretation', 'of', 'qm', 'that', 'considers', 'an', 'involved', 'ontology', 'of', 'nonindividuals', 'as', 'explained', 'in', 'the', 'text', 'thus', 'i', 'do', 'not', 'endorse', 'a', 'purely', 'instrumentalist', 'view', 'of', 'qm', 'but', 'believe', 'that', 'it', 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1,802.03806 | ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error
Resilience for Energy Efficient Deep Neural Network Accelerators | Hardware accelerators are being increasingly deployed to boost the
performance and energy efficiency of deep neural network (DNN) inference. In
this paper we propose Thundervolt, a new framework that enables aggressive
voltage underscaling of high-performance DNN accelerators without compromising
classification accuracy even in the presence of high timing error rates. Using
post-synthesis timing simulations of a DNN accelerator modeled on the Google
TPU, we show that Thundervolt enables between 34%-57% energy savings on
state-of-the-art speech and image recognition benchmarks with less than 1% loss
in classification accuracy and no performance loss. Further, we show that
Thundervolt is synergistic with and can further increase the energy efficiency
of commonly used run-time DNN pruning techniques like Zero-Skip.
| cs.NE cs.AR cs.LG | hardware accelerators are being increasingly deployed to boost the performance and energy efficiency of deep neural network dnn inference in this paper we propose thundervolt a new framework that enables aggressive voltage underscaling of highperformance dnn accelerators without compromising classification accuracy even in the presence of high timing error rates using postsynthesis timing simulations of a dnn accelerator modeled on the google tpu we show that thundervolt enables between 3457 energy savings on stateoftheart speech and image recognition benchmarks with less than 1 loss in classification accuracy and no performance loss further we show that thundervolt is synergistic with and can further increase the energy efficiency of commonly used runtime dnn pruning techniques like zeroskip | [['hardware', 'accelerators', 'are', 'being', 'increasingly', 'deployed', 'to', 'boost', 'the', 'performance', 'and', 'energy', 'efficiency', 'of', 'deep', 'neural', 'network', 'dnn', 'inference', 'in', 'this', 'paper', 'we', 'propose', 'thundervolt', 'a', 'new', 'framework', 'that', 'enables', 'aggressive', 'voltage', 'underscaling', 'of', 'highperformance', 'dnn', 'accelerators', 'without', 'compromising', 'classification', 'accuracy', 'even', 'in', 'the', 'presence', 'of', 'high', 'timing', 'error', 'rates', 'using', 'postsynthesis', 'timing', 'simulations', 'of', 'a', 'dnn', 'accelerator', 'modeled', 'on', 'the', 'google', 'tpu', 'we', 'show', 'that', 'thundervolt', 'enables', 'between', '3457', 'energy', 'savings', 'on', 'stateoftheart', 'speech', 'and', 'image', 'recognition', 'benchmarks', 'with', 'less', 'than', '1', 'loss', 'in', 'classification', 'accuracy', 'and', 'no', 'performance', 'loss', 'further', 'we', 'show', 'that', 'thundervolt', 'is', 'synergistic', 'with', 'and', 'can', 'further', 'increase', 'the', 'energy', 'efficiency', 'of', 'commonly', 'used', 'runtime', 'dnn', 'pruning', 'techniques', 'like', 'zeroskip']] | [-0.09375770183812294, -0.01585279745423967, -0.017629464707819613, 0.05583054257398804, -0.055070878696694435, -0.1708868177790594, 0.06007054061566513, 0.4878512253718717, -0.22077954844904266, -0.3827209881258438, 0.06478190701974589, -0.2534852400422096, -0.1622582867483808, 0.2751516258576885, -0.13695248809277213, 0.12257759607330497, 0.17901013429842091, 0.024759395921137184, -0.10723626015429286, -0.28893813403764007, 0.21090036909403612, 0.1711060882077748, 0.35666756433368263, 0.06812528642227075, 0.10849014131651659, -0.062216359309137, 0.030649095265939, -0.03188984687793501, -0.004672375393251319, 0.16832651077337296, 0.2843164110069795, 0.1834983761156244, 0.3277462369016056, -0.45600753763989943, -0.22297493663583218, 0.12916239243349992, 0.15063074347978858, 0.058235513545306664, -0.06730086527178562, -0.26244389613150687, 0.13345384838924343, -0.25353515477451893, 0.01971983150412728, -0.15228279736558242, -0.07760188474120307, 0.06194589824216174, -0.26006586004015325, 0.06494550542057757, 0.0744328014219978, 0.06298211512122569, -0.017727258877130225, -0.1359112723564197, 0.017518662930732325, 0.10926611996053127, 0.007982258441708317, 0.04359471638703586, 0.17963915364401015, -0.20037788186579877, -0.15368478269582347, 0.31216659393560675, -0.0718644746964076, -0.19962099937921657, 0.2215018945945693, -0.016276339006643475, -0.12417362218340193, 0.11169893899516735, 0.29740269385456486, 0.042642977913991284, -0.14726081547061248, 0.016104772955129323, 0.07891205198497378, 0.26029693877977217, 0.0957377828349958, 0.026883039173428967, 0.13533471238250577, 0.3334746501558194, 0.048133711613315554, 0.14808510322057242, -0.17457637318251987, -0.012337785950876423, -0.1794388917624019, -0.11675093589916027, -0.15038180084333622, 0.013863424298246432, -0.1264307446456639, -0.09323096317530144, 0.3835827864324009, 0.23501875156320498, 0.12287233442007814, 0.1359168026662831, 0.3959074081919555, 0.05359181296652033, 0.14189184721076994, 0.14196906052114042, 0.22144346719973587, -0.025622461889205233, 0.13505382130720786, -0.20931163871240901, 0.06462254198101748, 0.009241290024614759] |
1,802.03807 | From Feast To Famine: the Role of HI in Group Evolution | Galaxies in the local universe are most commonly found in groups and are
thought to be "pre-processed" in this environment before being consumed by
clusters. Yet we know very little about the gastrophysics of these systems, how
they evolve and how this environment is connected to the quenching of
star-forming galaxies. In particular, the role of intragroup gas has been
challenging to uncover due to observational constraints and the limitations of
radio telescopes to date. Sensitive, interferometric \HI\ observations of
galaxy groups, combined with multiwavelength tracers of stellar mass, star
formation and shocks, is necessary to examine the physical processes
transforming galaxies from star-forming to quenched. These laboratories may be
key to understanding the dominant mechanisms driving galaxy evolution. MeerKAT
uniquely combines a large field of view, column density sensitivity, and
excellent UV coverage on short baselines ensuring sensitivity to diffuse gas.
This design makes it a compelling instrument for the study of intragroup and
circumgroup gas, quenching in galaxy groups, and for tracing evolutionary
pathways within the group environment.
| astro-ph.GA astro-ph.CO | galaxies in the local universe are most commonly found in groups and are thought to be preprocessed in this environment before being consumed by clusters yet we know very little about the gastrophysics of these systems how they evolve and how this environment is connected to the quenching of starforming galaxies in particular the role of intragroup gas has been challenging to uncover due to observational constraints and the limitations of radio telescopes to date sensitive interferometric hi observations of galaxy groups combined with multiwavelength tracers of stellar mass star formation and shocks is necessary to examine the physical processes transforming galaxies from starforming to quenched these laboratories may be key to understanding the dominant mechanisms driving galaxy evolution meerkat uniquely combines a large field of view column density sensitivity and excellent uv coverage on short baselines ensuring sensitivity to diffuse gas this design makes it a compelling instrument for the study of intragroup and circumgroup gas quenching in galaxy groups and for tracing evolutionary pathways within the group environment | [['galaxies', 'in', 'the', 'local', 'universe', 'are', 'most', 'commonly', 'found', 'in', 'groups', 'and', 'are', 'thought', 'to', 'be', 'preprocessed', 'in', 'this', 'environment', 'before', 'being', 'consumed', 'by', 'clusters', 'yet', 'we', 'know', 'very', 'little', 'about', 'the', 'gastrophysics', 'of', 'these', 'systems', 'how', 'they', 'evolve', 'and', 'how', 'this', 'environment', 'is', 'connected', 'to', 'the', 'quenching', 'of', 'starforming', 'galaxies', 'in', 'particular', 'the', 'role', 'of', 'intragroup', 'gas', 'has', 'been', 'challenging', 'to', 'uncover', 'due', 'to', 'observational', 'constraints', 'and', 'the', 'limitations', 'of', 'radio', 'telescopes', 'to', 'date', 'sensitive', 'interferometric', 'hi', 'observations', 'of', 'galaxy', 'groups', 'combined', 'with', 'multiwavelength', 'tracers', 'of', 'stellar', 'mass', 'star', 'formation', 'and', 'shocks', 'is', 'necessary', 'to', 'examine', 'the', 'physical', 'processes', 'transforming', 'galaxies', 'from', 'starforming', 'to', 'quenched', 'these', 'laboratories', 'may', 'be', 'key', 'to', 'understanding', 'the', 'dominant', 'mechanisms', 'driving', 'galaxy', 'evolution', 'meerkat', 'uniquely', 'combines', 'a', 'large', 'field', 'of', 'view', 'column', 'density', 'sensitivity', 'and', 'excellent', 'uv', 'coverage', 'on', 'short', 'baselines', 'ensuring', 'sensitivity', 'to', 'diffuse', 'gas', 'this', 'design', 'makes', 'it', 'a', 'compelling', 'instrument', 'for', 'the', 'study', 'of', 'intragroup', 'and', 'circumgroup', 'gas', 'quenching', 'in', 'galaxy', 'groups', 'and', 'for', 'tracing', 'evolutionary', 'pathways', 'within', 'the', 'group', 'environment']] | [-0.07856156225281986, 0.0991478795213077, -0.09336853625581545, 0.12566861695993473, -0.11795336496845052, -0.04919922031729263, 0.03211152925265624, 0.4721127639579422, -0.18282707370064386, -0.3448211295201498, 0.08034227593076032, -0.2438287474516341, -0.06944338384851376, 0.16584416569265373, -0.0269829814116854, -0.03677236173671725, 0.031592606665457, -0.09687878319664914, 0.0006929550669156015, -0.29273433891289374, 0.30796190770342946, 0.133036863617599, 0.1931252328600214, 0.004631093393682557, 0.059684894901618143, -0.11260804541354232, -0.11960631230442018, -0.03752141243654906, -0.12197187853538814, 0.03364945702316404, 0.30422105432542806, 0.1470650752691333, 0.24710374058169476, -0.41949508206042296, -0.22371115148314, 0.10177502839634305, 0.20381133183836936, 0.05021741896977319, -0.08109816800022279, -0.28724025971502726, 0.045411901838858335, -0.16182009667870315, -0.1548033119220396, 0.009720140618874747, 0.027078064824865362, 0.04477972354438594, -0.2040447483797941, 0.10791648750686471, -0.017607107903698786, 0.05852645690662458, -0.07117817158646443, -0.047859182515565084, -0.031724776964470305, 0.1736614642705878, 0.014352381069843165, 0.06608378538341426, 0.23728899451808128, -0.1979786878958454, -0.006108240759931505, 0.4501880734830218, -0.015365422982722522, -0.02867295692455681, 0.304329125868047, -0.20908376449883423, -0.22477588337599574, 0.10765915761414148, 0.17715256545360555, 0.05722134196035126, -0.19876928562024498, -0.002437161054010229, 4.4137687997563794e-05, 0.19168450757929617, 0.008537340243620907, 0.09652010311590001, 0.31442148151040517, 0.15532606604837756, 0.08305148368098718, 0.0908302965656142, -0.10751961250378586, -0.05480124831802267, -0.20510211218258037, -0.10830584577120403, -0.12195462984964252, 0.09853455500458093, -0.07860037364170079, -0.08407858175992527, 0.343058254243806, 0.14619056525818236, 0.17833432631347987, 0.01749554489951526, 0.3240705384270233, 0.03171114303062067, 0.13463125007555765, 0.07900792031603701, 0.26270074776428587, 0.1955089448417044, 0.04472478493116796, -0.22802349678891273, 0.10420951904482482, -0.030423612386221065] |
1,802.03808 | Transport of nano-objects in narrow channels: influence of Brownian
diffusion, confinement and particle nature | This paper presents experimental results about transport of dilute
suspensions of nano-objects in silicon-glass micrometric and sub-micrometric
channels. Two kinds of objects are used: solid, rigid latex beads and spherical
capsule-shaped, soft polymersomes. They are tracked using fluorescence
microscopy. Three parameters are studied: confinement (ratio between particle
diameter and channel depth), Brownian diffusion and particle nature. The aim of
this work is to understand how these different parameters affect the transport
of suspensions in narrow channels and to understand the different mechanisms at
play. Concerning the solid beads we observe the appearance of two regimes, one
where the experimental mean velocity is close to the expected one and another
where this velocity is lower. This is directly related to a competition between
confinement, Brownian diffusion and advection. These two regimes are shown to
be linked to the homogeneity of particles distribution in the channel depth,
which we experimentally deduce from velocity distributions. This inhomogeneity
appears during the entrance process into the sub-micrometric channels, as for
hydrodynamic separation or deterministic lateral displacement. Concerning the
nature of the particles we observed a shift of transition towards the second
regime likely due to the relationships between shear stress and polymersomes
mechanical properties which could reduce the inhomogeneity imposed by the
geometry of our device.
| physics.flu-dyn cond-mat.soft | this paper presents experimental results about transport of dilute suspensions of nanoobjects in siliconglass micrometric and submicrometric channels two kinds of objects are used solid rigid latex beads and spherical capsuleshaped soft polymersomes they are tracked using fluorescence microscopy three parameters are studied confinement ratio between particle diameter and channel depth brownian diffusion and particle nature the aim of this work is to understand how these different parameters affect the transport of suspensions in narrow channels and to understand the different mechanisms at play concerning the solid beads we observe the appearance of two regimes one where the experimental mean velocity is close to the expected one and another where this velocity is lower this is directly related to a competition between confinement brownian diffusion and advection these two regimes are shown to be linked to the homogeneity of particles distribution in the channel depth which we experimentally deduce from velocity distributions this inhomogeneity appears during the entrance process into the submicrometric channels as for hydrodynamic separation or deterministic lateral displacement concerning the nature of the particles we observed a shift of transition towards the second regime likely due to the relationships between shear stress and polymersomes mechanical properties which could reduce the inhomogeneity imposed by the geometry of our device | [['this', 'paper', 'presents', 'experimental', 'results', 'about', 'transport', 'of', 'dilute', 'suspensions', 'of', 'nanoobjects', 'in', 'siliconglass', 'micrometric', 'and', 'submicrometric', 'channels', 'two', 'kinds', 'of', 'objects', 'are', 'used', 'solid', 'rigid', 'latex', 'beads', 'and', 'spherical', 'capsuleshaped', 'soft', 'polymersomes', 'they', 'are', 'tracked', 'using', 'fluorescence', 'microscopy', 'three', 'parameters', 'are', 'studied', 'confinement', 'ratio', 'between', 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1,802.03809 | RF-based Energy Harvesting in Decode-and-Forward Relaying Systems:
Ergodic and Outage Capacities | Radio-frequency energy harvesting constitutes an effective way to prolong the
lifetime of wireless networks, wean communication devices off the battery and
power line, benefit the energy saving and lower the carbon footprint of
wireless communications. In this paper, an interference aided energy harvesting
scheme is proposed for cooperative relaying systems, where energy-constrained
relays harvest energy from the received information signal and co-channel
interference signals, and then use that harvested energy to forward the
correctly decoded signal to the destination. The time-switching scheme (TS), in
which the receiver switches between decoding information and harvesting energy,
as well as the power-splitting scheme (PS), where a portion of the received
power is used for energy harvesting and the remaining power is utilized for
information processing, are adopted separately. Applying the proposed energy
harvesting approach to a decode-and-forward relaying system with the
three-terminal model, the analytical expressions of the ergodic capacity and
the outage capacity are derived, and the corresponding achievable throughputs
are determined. Comparative results are provided and show that PS is superior
to TS at high signal-to-noise ratio (SNR) in terms of throughput, while at low
SNR, TS outperforms PS. Furthermore, considering different interference power
distributions with equal aggregate interference power at the relay, the
corresponding system capacity relationship, i.e., the ordering of capacities,
is obtained.
| cs.IT math.IT | radiofrequency energy harvesting constitutes an effective way to prolong the lifetime of wireless networks wean communication devices off the battery and power line benefit the energy saving and lower the carbon footprint of wireless communications in this paper an interference aided energy harvesting scheme is proposed for cooperative relaying systems where energyconstrained relays harvest energy from the received information signal and cochannel interference signals and then use that harvested energy to forward the correctly decoded signal to the destination the timeswitching scheme ts in which the receiver switches between decoding information and harvesting energy as well as the powersplitting scheme ps where a portion of the received power is used for energy harvesting and the remaining power is utilized for information processing are adopted separately applying the proposed energy harvesting approach to a decodeandforward relaying system with the threeterminal model the analytical expressions of the ergodic capacity and the outage capacity are derived and the corresponding achievable throughputs are determined comparative results are provided and show that ps is superior to ts at high signaltonoise ratio snr in terms of throughput while at low snr ts outperforms ps furthermore considering different interference power distributions with equal aggregate interference power at the relay the corresponding system capacity relationship ie the ordering of capacities is obtained | [['radiofrequency', 'energy', 'harvesting', 'constitutes', 'an', 'effective', 'way', 'to', 'prolong', 'the', 'lifetime', 'of', 'wireless', 'networks', 'wean', 'communication', 'devices', 'off', 'the', 'battery', 'and', 'power', 'line', 'benefit', 'the', 'energy', 'saving', 'and', 'lower', 'the', 'carbon', 'footprint', 'of', 'wireless', 'communications', 'in', 'this', 'paper', 'an', 'interference', 'aided', 'energy', 'harvesting', 'scheme', 'is', 'proposed', 'for', 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1,802.0381 | Floquet spectroscopy of a strongly driven quantum dot charge qubit with
a microwave resonator | We experimentally investigate a strongly driven GaAs double quantum dot
charge qubit weakly coupled to a superconducting microwave resonator. The
Floquet states emerging from strong driving are probed by tracing the qubit -
resonator resonance condition. This way we probe the resonance of a qubit that
is driven in an adiabatic, a non-adiabatic, or an intermediate rate showing
distinct quantum features of multi-photon processes and
Landau-Zener-St\"uckelberg interference pattern. Our resonant detection scheme
enables the investigation of novel features when the drive frequency is
comparable to the resonator frequency. Models based on adiabatic approximation,
rotating wave approximation, and Floquet theory explain our experimental
observations.
| cond-mat.mes-hall | we experimentally investigate a strongly driven gaas double quantum dot charge qubit weakly coupled to a superconducting microwave resonator the floquet states emerging from strong driving are probed by tracing the qubit resonator resonance condition this way we probe the resonance of a qubit that is driven in an adiabatic a nonadiabatic or an intermediate rate showing distinct quantum features of multiphoton processes and landauzenerstuckelberg interference pattern our resonant detection scheme enables the investigation of novel features when the drive frequency is comparable to the resonator frequency models based on adiabatic approximation rotating wave approximation and floquet theory explain our experimental observations | [['we', 'experimentally', 'investigate', 'a', 'strongly', 'driven', 'gaas', 'double', 'quantum', 'dot', 'charge', 'qubit', 'weakly', 'coupled', 'to', 'a', 'superconducting', 'microwave', 'resonator', 'the', 'floquet', 'states', 'emerging', 'from', 'strong', 'driving', 'are', 'probed', 'by', 'tracing', 'the', 'qubit', 'resonator', 'resonance', 'condition', 'this', 'way', 'we', 'probe', 'the', 'resonance', 'of', 'a', 'qubit', 'that', 'is', 'driven', 'in', 'an', 'adiabatic', 'a', 'nonadiabatic', 'or', 'an', 'intermediate', 'rate', 'showing', 'distinct', 'quantum', 'features', 'of', 'multiphoton', 'processes', 'and', 'landauzenerstuckelberg', 'interference', 'pattern', 'our', 'resonant', 'detection', 'scheme', 'enables', 'the', 'investigation', 'of', 'novel', 'features', 'when', 'the', 'drive', 'frequency', 'is', 'comparable', 'to', 'the', 'resonator', 'frequency', 'models', 'based', 'on', 'adiabatic', 'approximation', 'rotating', 'wave', 'approximation', 'and', 'floquet', 'theory', 'explain', 'our', 'experimental', 'observations']] | [-0.21664354523789942, 0.23122325741632285, -0.04789421108423495, 0.01570052554598078, -0.026462406760045125, -0.22619038541783013, 0.08822572008505755, 0.38750561267393185, -0.2522729003537154, -0.2272635832173275, -0.024283664635446508, -0.25699192634327156, -0.13913393653609663, 0.2605215575724073, 0.0421473024351358, 0.08832438353120405, 0.05416544741384831, -0.04244443829007009, -0.01425215698477319, -0.10720250076687365, 0.2947516657512489, 0.05378774332119992, 0.34168002245874673, 0.026096970002696503, 0.0736385263758255, -0.046399072506556324, 0.06813350007595385, -0.08515194694822033, -0.10795601736789845, 0.054518194498800146, 0.2640783962645347, 0.00794500537107096, 0.23950970386994966, -0.4752597698905304, -0.2031494931810919, 0.025424897177692724, 0.18069381406530738, 0.19891419377196215, -0.0569162951056462, -0.3464695658425198, -0.006862753805905289, -0.15729728121967876, -0.10655680575462825, -0.09839650317935236, -0.04622978325385381, -0.02537985295787746, -0.2845242114545887, 0.06589175212909193, 0.08289877518865407, 0.019736546192172112, -0.02569136212981653, 0.06605932147552569, 0.041658189640763926, 0.024020780529883944, -0.07581190121652302, 0.028962519193323804, 0.24522949365314609, -0.10124964727198377, -0.17389829009406121, 0.2954621901244893, -0.11719542493422826, -0.12128421194011382, 0.17681084391797947, -0.16811488359235227, -0.035500954854868205, 0.10716238407436393, 0.11179411444612139, 0.10901982764092584, -0.13691159928666644, 0.05743664561191062, 0.026602642980601648, 0.23883866024769695, 0.07214796844888113, 0.12111269856127453, 0.2469817147471522, 0.17101524729856893, 0.046333939896202554, 0.16233586674948752, -0.12430142150853998, -0.12640749466349827, -0.2594881084446302, -0.09948696862614038, -0.2125962571989672, 0.09136755505902579, -0.04427455794311576, -0.16947356616740353, 0.46256707449723694, 0.131584488846106, 0.17087218936249687, -0.08443836623108854, 0.3579235825021112, 0.21589452825148828, 0.03973919088386145, 0.011718968271880466, 0.3070817270576406, 0.21977697252341563, 0.0336519794849058, -0.37734377373685585, -0.022427363289227963, -0.021474769238528667] |
1,802.03811 | Physical and Geometrical Parameters of CVBS XII: Fin 350 (Hip 64838) | A complete astrophysical and dynamical study of the close visual binary
system (CVBS) (A7V + F0V), Finsen 350, is presented. Beginning with the entire
observational spectral energy distribution (SED) and the magnitude difference
between the subcomponents, Al-Wardat's complex method for analyzing close
visual binary stars (CVBS) was applied as a reverse method of building the
individual and entire synthetic SEDs of the system. This was combined with
Docobo's analytic method to calculate the new orbits. Although possible short
($\approx$ 9 years) and long period ($\approx$ 18 years) orbits could be
considered taking into account the similar results of the stellar masses
obtained for each of them (3.07 and 3.41 $M_{\odot}$, respectively), we
confirmed that the short solution is correct. In addition, other physical,
geometrical and dynamical parameters of this system such as the effective
temperatures, surface gravity accelerations, absolute magnitudes, radii, the
dynamical parallax, etc., are reported. The main sequence phase of both
components with age around 0.79 Gy is approved.
| astro-ph.SR | a complete astrophysical and dynamical study of the close visual binary system cvbs a7v f0v finsen 350 is presented beginning with the entire observational spectral energy distribution sed and the magnitude difference between the subcomponents alwardats complex method for analyzing close visual binary stars cvbs was applied as a reverse method of building the individual and entire synthetic seds of the system this was combined with docobos analytic method to calculate the new orbits although possible short approx 9 years and long period approx 18 years orbits could be considered taking into account the similar results of the stellar masses obtained for each of them 307 and 341 m_odot respectively we confirmed that the short solution is correct in addition other physical geometrical and dynamical parameters of this system such as the effective temperatures surface gravity accelerations absolute magnitudes radii the dynamical parallax etc are reported the main sequence phase of both components with age around 079 gy is approved | [['a', 'complete', 'astrophysical', 'and', 'dynamical', 'study', 'of', 'the', 'close', 'visual', 'binary', 'system', 'cvbs', 'a7v', 'f0v', 'finsen', '350', 'is', 'presented', 'beginning', 'with', 'the', 'entire', 'observational', 'spectral', 'energy', 'distribution', 'sed', 'and', 'the', 'magnitude', 'difference', 'between', 'the', 'subcomponents', 'alwardats', 'complex', 'method', 'for', 'analyzing', 'close', 'visual', 'binary', 'stars', 'cvbs', 'was', 'applied', 'as', 'a', 'reverse', 'method', 'of', 'building', 'the', 'individual', 'and', 'entire', 'synthetic', 'seds', 'of', 'the', 'system', 'this', 'was', 'combined', 'with', 'docobos', 'analytic', 'method', 'to', 'calculate', 'the', 'new', 'orbits', 'although', 'possible', 'short', 'approx', '9', 'years', 'and', 'long', 'period', 'approx', '18', 'years', 'orbits', 'could', 'be', 'considered', 'taking', 'into', 'account', 'the', 'similar', 'results', 'of', 'the', 'stellar', 'masses', 'obtained', 'for', 'each', 'of', 'them', '307', 'and', '341', 'm_odot', 'respectively', 'we', 'confirmed', 'that', 'the', 'short', 'solution', 'is', 'correct', 'in', 'addition', 'other', 'physical', 'geometrical', 'and', 'dynamical', 'parameters', 'of', 'this', 'system', 'such', 'as', 'the', 'effective', 'temperatures', 'surface', 'gravity', 'accelerations', 'absolute', 'magnitudes', 'radii', 'the', 'dynamical', 'parallax', 'etc', 'are', 'reported', 'the', 'main', 'sequence', 'phase', 'of', 'both', 'components', 'with', 'age', 'around', '079', 'gy', 'is', 'approved']] | [-0.0927179076579991, 0.1167338775769579, -0.09493828230426184, 0.09506490064342653, -0.06583076957964672, -0.09085624006652981, 0.043321085992011496, 0.38721366882699093, -0.19116836227476597, -0.37648339623456484, 0.09046063892859614, -0.2612694266351795, -0.0655314481506745, 0.22936844278592616, -0.04964848512889079, 0.0295781447477463, 0.08839699800152613, 0.0012192571892274205, -0.09344257023251387, -0.24433010340076666, 0.25397760739678854, 0.03520673794932546, 0.1604860477569021, -0.010394013721509412, 0.08495616711640977, -0.029144234898201418, -0.05176228745193433, -0.022990119158811634, -0.15594047382160026, 0.06029503283957781, 0.2069463140928661, 0.10301303647388264, 0.20958120294747018, -0.3201906178263748, -0.19386649355819485, 0.06899528409231384, 0.12974482442035615, 0.05732773461103814, -0.022597654359473748, -0.27523339310303657, 0.09599097733021239, -0.1960088202529206, -0.1566847140356055, -0.006282525741840777, 0.1009245741374369, 0.03927780476650633, -0.21919498914770735, 0.11232030682420246, 0.03363947425372225, 0.09689588882263352, -0.14633939007982472, -0.18341171130634634, -0.052425891944388826, 0.15604161881291126, 0.029059039781736972, 0.07178602303940591, 0.1076685727636898, -0.045849534934796626, -0.04362402916680904, 0.39369911268212887, -0.06792144862965699, -0.0504720584378115, 0.21550100322508212, -0.1455813478854186, -0.10266648516726662, 0.1467050077487369, 0.14285244947920242, 0.11810300570660792, -0.20001384244833445, 0.006090395127674975, 0.026001005880124634, 0.21327709031742323, 0.06329059883448407, 0.015214131111220556, 0.2952594042421793, 0.16375913734126063, -0.02682438349896206, 0.07938380633830824, -0.15732965956507222, -0.07615426909683694, -0.22924099142704182, -0.11639711286860911, -0.12695465001435774, 0.059159136063905444, -0.1485904122773432, -0.09592547437978569, 0.38811114725053497, 0.13314607742377235, 0.20895113955902042, 0.04205686773858824, 0.2779379941130631, 0.09873716728673931, 0.07988512161572767, 0.07200642562406899, 0.2794813569137276, 0.14592747511371454, 0.08043187393209422, -0.21157324840256111, 0.032043455937156476, 0.02743265330615752] |
1,802.03812 | A category of wide subcategories | An algebra is said to be \emph{$\tau$-tilting finite} provided it has only a
finite number of $\tau$-rigid objects up to isomorphism. We associate a
category to each such algebra. The objects are the wide subcategories of its
category of finite dimensional modules, and the morphisms are indexed by
support $\tau$-tilting pairs.
| math.RT math.RA | an algebra is said to be emphtautilting finite provided it has only a finite number of taurigid objects up to isomorphism we associate a category to each such algebra the objects are the wide subcategories of its category of finite dimensional modules and the morphisms are indexed by support tautilting pairs | [['an', 'algebra', 'is', 'said', 'to', 'be', 'emphtautilting', 'finite', 'provided', 'it', 'has', 'only', 'a', 'finite', 'number', 'of', 'taurigid', 'objects', 'up', 'to', 'isomorphism', 'we', 'associate', 'a', 'category', 'to', 'each', 'such', 'algebra', 'the', 'objects', 'are', 'the', 'wide', 'subcategories', 'of', 'its', 'category', 'of', 'finite', 'dimensional', 'modules', 'and', 'the', 'morphisms', 'are', 'indexed', 'by', 'support', 'tautilting', 'pairs']] | [-0.15569386836141347, 0.10257600843237015, -0.05613413019571453, 0.03851520371856168, -0.160339070931077, -0.12706696030683814, -0.0343808002024889, 0.4111555256694555, -0.45911051765084265, -0.19691646400140597, 0.10884926070459187, -0.2574113929644227, -0.03316042173653841, 0.16682337475940584, -0.18886038363911212, -0.08013600045931525, 0.09908712174743414, 0.15412762952968478, -0.015081787426024675, -0.3080990295857191, 0.43456578984856603, -0.03749910209327936, 0.22861215780023486, 0.008774613263085485, 0.1786281854659319, -0.035387980081140996, 0.0002237903792411089, 0.06387609165161848, -0.0876333288429305, 0.11692166505381466, 0.3829136256314814, 0.11055223613977433, 0.2321248446078971, -0.29381232051644474, -0.07429218573495745, 0.21325229654088618, 0.1332657174114138, 0.03912193246185779, -0.02385765210259706, -0.3064965638332069, 0.21770950198173522, -0.3039552091807127, -0.051310978094115854, -0.08862998229451477, 0.12756426580250263, 0.025725186429917814, -0.25929869391024113, -0.1257230469584465, 0.06066173627972603, 0.14979270504787565, -0.1109879799024202, -0.04144501380622387, -0.11152129866182804, 0.14282454983331264, -0.10122378863859921, 0.026394739865791054, 0.10619072354398668, -0.10276570586676825, -0.1525874052941799, 0.3696169085800648, 0.03473179036751389, -0.2540308500826359, 0.25777464531362054, -0.1460027734003961, -0.08673310574144125, 0.1707989327609539, 0.020735285244882107, 0.1409982275031507, -0.044205895494669675, 0.20782399890827946, -0.16149670624174178, 0.07969638800248503, 0.06837823374196887, 0.019805780220776795, 0.20162028271704913, 0.1526103150472045, -0.005576628558337689, 0.15234717961167918, 0.03084450341761112, 0.0289807415753603, -0.36159510746598245, -0.2080391019396484, -0.09530735868960619, 0.07988224158063531, -0.09821017636888428, -0.21485693253576754, 0.3879196553304791, 0.13019033869146368, 0.2250072050653398, 0.11243130264803768, 0.16662895565852523, 0.06924986202269792, 0.1688604751136154, 0.02627666634507477, 0.08749158918857575, 0.2824753793375567, -0.07429714277386665, -0.043736584186553955, -0.042934533329680565, 0.1843069415539503] |
1,802.03813 | Universality for 1d random band matrices: sigma-model approximation | The paper continues the development of the rigorous supersymmetric transfer
matrix approach to the random band matrices started in J Stat Phys 164:1233 --
1260, 2016; Commun Math Phys 351:1009 -- 1044, 2017. We consider random
Hermitian block band matrices consisting of $W\times W$ random Gaussian blocks
(parametrized by $j,k \in\Lambda=[1,n]^d\cap \mathbb{Z}^d$) with a fixed
entry's variance $J_{jk}=\delta_{j,k}W^{-1}+\beta\Delta_{j,k}W^{-2}$, $\beta>0$
in each block. Taking the limit $W\to\infty$ with fixed $n$ and $\beta$, we
derive the sigma-model approximation of the second correlation function similar
to Efetov's one. Then, considering the limit $\beta, n\to\infty$, we prove that
in the dimension $d=1$ the behaviour of the sigma-model approximation in the
bulk of the spectrum, as $\beta\gg n$, is determined by the classical Wigner --
Dyson statistics.
| math-ph math.MP | the paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in j stat phys 1641233 1260 2016 commun math phys 3511009 1044 2017 we consider random hermitian block band matrices consisting of wtimes w random gaussian blocks parametrized by jk inlambda1ndcap mathbbzd with a fixed entrys variance j_jkdelta_jkw1betadelta_jkw2 beta0 in each block taking the limit wtoinfty with fixed n and beta we derive the sigmamodel approximation of the second correlation function similar to efetovs one then considering the limit beta ntoinfty we prove that in the dimension d1 the behaviour of the sigmamodel approximation in the bulk of the spectrum as betagg n is determined by the classical wigner dyson statistics | [['the', 'paper', 'continues', 'the', 'development', 'of', 'the', 'rigorous', 'supersymmetric', 'transfer', 'matrix', 'approach', 'to', 'the', 'random', 'band', 'matrices', 'started', 'in', 'j', 'stat', 'phys', '1641233', '1260', '2016', 'commun', 'math', 'phys', '3511009', '1044', '2017', 'we', 'consider', 'random', 'hermitian', 'block', 'band', 'matrices', 'consisting', 'of', 'wtimes', 'w', 'random', 'gaussian', 'blocks', 'parametrized', 'by', 'jk', 'inlambda1ndcap', 'mathbbzd', 'with', 'a', 'fixed', 'entrys', 'variance', 'j_jkdelta_jkw1betadelta_jkw2', 'beta0', 'in', 'each', 'block', 'taking', 'the', 'limit', 'wtoinfty', 'with', 'fixed', 'n', 'and', 'beta', 'we', 'derive', 'the', 'sigmamodel', 'approximation', 'of', 'the', 'second', 'correlation', 'function', 'similar', 'to', 'efetovs', 'one', 'then', 'considering', 'the', 'limit', 'beta', 'ntoinfty', 'we', 'prove', 'that', 'in', 'the', 'dimension', 'd1', 'the', 'behaviour', 'of', 'the', 'sigmamodel', 'approximation', 'in', 'the', 'bulk', 'of', 'the', 'spectrum', 'as', 'betagg', 'n', 'is', 'determined', 'by', 'the', 'classical', 'wigner', 'dyson', 'statistics']] | [-0.08576270586201114, 0.14500137984719688, -0.019514937168069645, -0.015584176746238253, 0.008265584238508173, -0.1499905498838464, 0.05804064632104957, 0.32003607417135377, -0.20323869584960683, -0.24306607327992674, 0.05099437984769785, -0.303394483418855, -0.1653604572535847, 0.07615348947877311, -0.047435660970158285, 0.0816797995733806, -0.013900417187539614, -0.010804253873472985, -0.1126695328610496, -0.26502555849615783, 0.23299220305727383, 0.05981010429363335, 0.2526683804233439, -0.034330579180237464, 0.07126527125699923, 0.11064852906423991, -0.04892434753411639, -0.07307407646378156, -0.16858875848162574, 0.06450161576452376, 0.22864394152817208, 0.021157692907691265, 0.24385899714960724, -0.35469556067435615, -0.18528244932454113, 0.14339708581781097, 0.1351974213874973, 0.04211435039770847, 0.08606269541278944, -0.28390053001982446, 0.07115637987854156, -0.17729091074779235, -0.17847397894623268, 0.005920448635119648, 0.0941255323555881, -0.011076107926139262, -0.330389370878054, 0.11482872765313472, 0.10235215016368744, 0.020932314653707818, 0.02233306336241354, -0.1950148460970351, -0.019491318580323616, 0.06549773026830558, 0.0025054973239013183, 0.047858165884060805, 0.09502990495936896, -0.054487671736067375, -0.09978135059066363, 0.34592696999182176, -0.1068792061517592, -0.17138063647259907, 0.1046130803817537, -0.1809653003320955, -0.16991072140667027, 0.10151583728570063, 0.1399940393650822, 0.10483979701839255, -0.1279746248403284, 0.25016537606994316, -0.08259482681751251, 0.1332739282077986, 0.09861626122476516, -0.02274016527442542, 0.13419393097273016, 0.09583833710644889, 0.0325076744698021, 0.11321025287765449, -0.07059347852899701, -0.10456710980831134, -0.3380061841891271, -0.13723635793028943, -0.2510219716067236, 0.15697808566181798, -0.1288305427486322, -0.16531739592453285, 0.35817463272374817, 0.09121015930983065, 0.2147796074736171, 0.10156073209425781, 0.14440639702751573, 0.17282403528636767, -0.037430724331004694, 0.1442711747012439, 0.17578896850479386, 0.23971195385247404, 0.09243099437202368, -0.1767697418791106, -0.06542243594015264, 0.1664997556090223] |
1,802.03814 | $L^p$ Sobolev regularity of averaging operators over hypersurfaces and
the Newton polyhedron | $L^p$ to $L^p_{\beta}$ boundedness theorems are proven for translation
invariant averaging operators over hypersurfaces in Euclidean space. The
operators can either be Radon transforms or averaging operators with
multiparameter fractional integral kernel. In many cases, the amount $\beta > 0
$ of smoothing proven is optimal up to endpoints, and in such situations this
amount of smoothing can be computed explicitly through the use of appropriate
Newton polyhedra.
| math.CA | lp to lp_beta boundedness theorems are proven for translation invariant averaging operators over hypersurfaces in euclidean space the operators can either be radon transforms or averaging operators with multiparameter fractional integral kernel in many cases the amount beta 0 of smoothing proven is optimal up to endpoints and in such situations this amount of smoothing can be computed explicitly through the use of appropriate newton polyhedra | [['lp', 'to', 'lp_beta', 'boundedness', 'theorems', 'are', 'proven', 'for', 'translation', 'invariant', 'averaging', 'operators', 'over', 'hypersurfaces', 'in', 'euclidean', 'space', 'the', 'operators', 'can', 'either', 'be', 'radon', 'transforms', 'or', 'averaging', 'operators', 'with', 'multiparameter', 'fractional', 'integral', 'kernel', 'in', 'many', 'cases', 'the', 'amount', 'beta', '0', 'of', 'smoothing', 'proven', 'is', 'optimal', 'up', 'to', 'endpoints', 'and', 'in', 'such', 'situations', 'this', 'amount', 'of', 'smoothing', 'can', 'be', 'computed', 'explicitly', 'through', 'the', 'use', 'of', 'appropriate', 'newton', 'polyhedra']] | [-0.08955841438414959, 0.09304271459292907, -0.09628826700724089, 0.13852767654909537, -0.07430048646190418, -0.12308657547602286, -0.001599398756829592, 0.4052670688010179, -0.37457955400101267, -0.21733758724652805, 0.21265271125683705, -0.2789002948798812, -0.0884380543210472, 0.2300478793716488, -0.1545054800163668, 0.13994152733626275, 0.04563768570168087, 0.025921048682469586, -0.14056101625588222, -0.30022729757564287, 0.3396864450035187, -0.024820568999991965, 0.1881991326665649, 0.002472243794741539, 0.08813335538770144, 0.019946234259539498, -0.041991727476796276, -0.01577467139154928, -0.10112030150798651, 0.13263996849373844, 0.29755102400309763, 0.06671987257611293, 0.25569558570591305, -0.39196216897465863, -0.2222955717346989, 0.23867108406355747, 0.1868532019094206, 0.004181889079224605, 0.020625526350564683, -0.297684579106191, 0.05626486456738068, -0.07521339746621938, -0.1467342777804543, -0.1832170873020704, 0.00580940364071956, 0.05406788804102689, -0.3396977378897226, 0.07023922866210341, 0.07429018530708092, 0.0705347348864262, -0.08974867988950931, -0.11742805634410336, 0.018364790791215804, 0.07893736356367859, 0.04585010517890064, 0.0470723031876752, 0.11423466837463471, -0.05503199262043031, -0.08881651625986425, 0.31220818316707244, -0.054574793978379325, -0.3268237181007862, 0.10164729906962468, -0.1535426850359027, -0.1220478243767642, 0.11341011246236471, 0.13590413417953712, 0.16787827795801255, -0.1506251415094504, 0.19689013649834894, -0.00021928755136636587, 0.07737457601066966, 0.14942275289302834, 0.04540711866261867, 0.09156088904620936, 0.021552904380055575, 0.17780433812698063, 0.13663424250239936, -0.030113298044754908, -0.11340882690766683, -0.332289928656358, -0.1892462535832937, -0.1923631459259643, 0.07487411758360954, -0.14982722556339398, -0.16329914918885782, 0.32812421865618, 0.07376531214238359, 0.17502125180684602, 0.06871043415740133, 0.21836436574275678, 0.17245107321247746, 0.1383110383597131, 0.07002052264288068, 0.14389171474971452, 0.0895727998075577, 0.06930726303611524, -0.13450205723683423, 0.013708845239419204, 0.2178869954811839] |
1,802.03815 | Recognizing Read-Once Functions from Depth-Three Formulas | Consider the following decision problem: for a given monotone Boolean
function $f$ decide, whether $f$ is read-once. For this problem, it is
essential how the input function $f$ is represented. Our contribution consists
of the following two results. We show that we can test in polynomial-time
whether a given expression $C\lor D$ computes a read-once function, provided
that $C$ is a read-once monotone CNF and $D$ is a read-once monotone DNF and
all the variables of $C$ occur also in $D$ (recall that due to Gurvich, the
problem is coNP-complete when $C$ is read-2). The second result states that
this is a coNP-complete problem to decide whether the expression $\Psi\land
D_n$ computes a read-once function, where $D_n$ is as above and $\Psi$ is the
$\bigwedge-\bigvee-\bigwedge$ depth-3 read-once monotone Boolean formula (so
that the entire expression $\Psi\land D_n$ is depth-3 read-2). This result
improves the result of \cite{elbassioni2011readability} in the depth and the
result of \cite{gurvich2010it} in the readability of the input formula.
| cs.CC | consider the following decision problem for a given monotone boolean function f decide whether f is readonce for this problem it is essential how the input function f is represented our contribution consists of the following two results we show that we can test in polynomialtime whether a given expression clor d computes a readonce function provided that c is a readonce monotone cnf and d is a readonce monotone dnf and all the variables of c occur also in d recall that due to gurvich the problem is conpcomplete when c is read2 the second result states that this is a conpcomplete problem to decide whether the expression psiland d_n computes a readonce function where d_n is as above and psi is the bigwedgebigveebigwedge depth3 readonce monotone boolean formula so that the entire expression psiland d_n is depth3 read2 this result improves the result of citeelbassioni2011readability in the depth and the result of citegurvich2010it in the readability of the input formula | [['consider', 'the', 'following', 'decision', 'problem', 'for', 'a', 'given', 'monotone', 'boolean', 'function', 'f', 'decide', 'whether', 'f', 'is', 'readonce', 'for', 'this', 'problem', 'it', 'is', 'essential', 'how', 'the', 'input', 'function', 'f', 'is', 'represented', 'our', 'contribution', 'consists', 'of', 'the', 'following', 'two', 'results', 'we', 'show', 'that', 'we', 'can', 'test', 'in', 'polynomialtime', 'whether', 'a', 'given', 'expression', 'clor', 'd', 'computes', 'a', 'readonce', 'function', 'provided', 'that', 'c', 'is', 'a', 'readonce', 'monotone', 'cnf', 'and', 'd', 'is', 'a', 'readonce', 'monotone', 'dnf', 'and', 'all', 'the', 'variables', 'of', 'c', 'occur', 'also', 'in', 'd', 'recall', 'that', 'due', 'to', 'gurvich', 'the', 'problem', 'is', 'conpcomplete', 'when', 'c', 'is', 'read2', 'the', 'second', 'result', 'states', 'that', 'this', 'is', 'a', 'conpcomplete', 'problem', 'to', 'decide', 'whether', 'the', 'expression', 'psiland', 'd_n', 'computes', 'a', 'readonce', 'function', 'where', 'd_n', 'is', 'as', 'above', 'and', 'psi', 'is', 'the', 'bigwedgebigveebigwedge', 'depth3', 'readonce', 'monotone', 'boolean', 'formula', 'so', 'that', 'the', 'entire', 'expression', 'psiland', 'd_n', 'is', 'depth3', 'read2', 'this', 'result', 'improves', 'the', 'result', 'of', 'citeelbassioni2011readability', 'in', 'the', 'depth', 'and', 'the', 'result', 'of', 'citegurvich2010it', 'in', 'the', 'readability', 'of', 'the', 'input', 'formula']] | [-0.13763641149059616, 0.07432065135799348, -0.025119912706303423, 0.08252998049274184, -0.07020253606455086, -0.19663159006468758, 0.08442699874436797, 0.3252132753841579, -0.3101124663704208, -0.2572043634975305, 0.06157471232612122, -0.24381188932177308, -0.18605584415982102, 0.20735121112582938, -0.08582134980575315, 0.08161090544195145, 0.033555258292245205, 0.09135863337327134, -0.018883752003130683, -0.29311958259174165, 0.31691510925770966, -0.06526808081460851, 0.19748211278906697, 0.09906992598968957, 0.07803900104753866, 0.022782596599238068, 0.012265681729095613, -0.003248358820602842, -0.11434827198229267, 0.06387012488890573, 0.28758920345140937, 0.2981351727571387, 0.2566364294450198, -0.34272807349100126, -0.07336333390195285, 0.2011257753550232, 0.11360855056759116, 0.055376916313422966, 0.013141297819939527, -0.18289987175338357, 0.10814341832127712, -0.1312289078623153, -0.09790232919108172, -0.004300076042773661, 0.1587860695654889, 0.005396599690853195, -0.3563583615695598, 0.011085587816559347, 0.18612024172620437, 0.008916780800111108, -0.008195238859187087, -0.1581505392315229, 0.01921848500262365, 0.09808969303497639, -0.04866821279782536, 0.16735325711960722, 0.08111122272932877, -0.1320956305528132, -0.13490352949865356, 0.33494526904995564, -0.05756422163398525, -0.26852972051673024, 0.07917017497079955, -0.12473632411973841, -0.1649261113473928, 0.0906373407425625, 0.0961724549513794, 0.16834571705405393, -0.08419867795818356, 0.1870452347196421, -0.16825857724655757, 0.20964922706366745, 0.10595143736981145, -0.05022764032670333, 0.09520801476825803, 0.12847574198370582, 0.08582684640808926, 0.22785528798666238, 0.03644584763383904, -0.004622120228777458, -0.3327056567922428, -0.1762821208746112, -0.20277269152008215, 0.0775388676685269, -0.07784239099891675, -0.19509060118444166, 0.36668189691210334, 0.09499053962758512, 0.17525832269827582, 0.21060262070726846, 0.28536999126436646, 0.19694807737507833, 0.01889881666359649, 0.08253660433103222, 0.11485446411995338, 0.13824780362162303, 0.006271659605229249, -0.20005710026065596, 0.19917403047831803, 0.15208606330629487] |
1,802.03816 | Understanding Recurrent Neural State Using Memory Signatures | We demonstrate a network visualization technique to analyze the recurrent
state inside the LSTMs/GRUs used commonly in language and acoustic models.
Interpreting intermediate state and network activations inside end-to-end
models remains an open challenge. Our method allows users to understand exactly
how much and what history is encoded inside recurrent state in grapheme
sequence models. Our procedure trains multiple decoders that predict prior
input history. Compiling results from these decoders, a user can obtain a
signature of the recurrent kernel that characterizes its memory behavior. We
demonstrate this method's usefulness in revealing information divergence in the
bases of recurrent factorized kernels, visualizing the character-level
differences between the memory of n-gram and recurrent language models, and
extracting knowledge of history encoded in the layers of grapheme-based
end-to-end ASR networks.
| cs.CL | we demonstrate a network visualization technique to analyze the recurrent state inside the lstmsgrus used commonly in language and acoustic models interpreting intermediate state and network activations inside endtoend models remains an open challenge our method allows users to understand exactly how much and what history is encoded inside recurrent state in grapheme sequence models our procedure trains multiple decoders that predict prior input history compiling results from these decoders a user can obtain a signature of the recurrent kernel that characterizes its memory behavior we demonstrate this methods usefulness in revealing information divergence in the bases of recurrent factorized kernels visualizing the characterlevel differences between the memory of ngram and recurrent language models and extracting knowledge of history encoded in the layers of graphemebased endtoend asr networks | [['we', 'demonstrate', 'a', 'network', 'visualization', 'technique', 'to', 'analyze', 'the', 'recurrent', 'state', 'inside', 'the', 'lstmsgrus', 'used', 'commonly', 'in', 'language', 'and', 'acoustic', 'models', 'interpreting', 'intermediate', 'state', 'and', 'network', 'activations', 'inside', 'endtoend', 'models', 'remains', 'an', 'open', 'challenge', 'our', 'method', 'allows', 'users', 'to', 'understand', 'exactly', 'how', 'much', 'and', 'what', 'history', 'is', 'encoded', 'inside', 'recurrent', 'state', 'in', 'grapheme', 'sequence', 'models', 'our', 'procedure', 'trains', 'multiple', 'decoders', 'that', 'predict', 'prior', 'input', 'history', 'compiling', 'results', 'from', 'these', 'decoders', 'a', 'user', 'can', 'obtain', 'a', 'signature', 'of', 'the', 'recurrent', 'kernel', 'that', 'characterizes', 'its', 'memory', 'behavior', 'we', 'demonstrate', 'this', 'methods', 'usefulness', 'in', 'revealing', 'information', 'divergence', 'in', 'the', 'bases', 'of', 'recurrent', 'factorized', 'kernels', 'visualizing', 'the', 'characterlevel', 'differences', 'between', 'the', 'memory', 'of', 'ngram', 'and', 'recurrent', 'language', 'models', 'and', 'extracting', 'knowledge', 'of', 'history', 'encoded', 'in', 'the', 'layers', 'of', 'graphemebased', 'endtoend', 'asr', 'networks']] | [-0.08745434628726226, 0.028404698627528837, -0.07184700384794727, 0.14352576733808817, -0.09653558563734368, -0.17972331188296473, 0.06481690379317967, 0.4701511657496137, -0.33847184521769447, -0.28373007320864935, 0.04003944609765198, -0.2615510651523909, -0.2245215482072076, 0.1680634066235186, -0.0726599132231488, 0.06260376737139547, 0.1476971006798228, 0.08047458946734197, -0.06867771994645201, -0.2444843266188629, 0.2895460011273454, 0.0532555912701985, 0.33826450065812314, -0.02669995069672449, 0.13837621316559406, -0.044527065619829984, -0.041535622080949346, -0.09529756758028392, -0.04410827543467786, 0.1635957209129385, 0.30450878896730804, 0.21941364916613487, 0.27218498643047695, -0.47217819416587514, -0.272210021011942, 0.04848391485701161, 0.16763520735777973, 0.13789048245704666, 0.02618408745052073, -0.31351813173112203, 0.07737823340429477, -0.18902471525535927, 0.028699872417624776, -0.13301101761804088, -0.03148329633427417, -0.011527719498633987, -0.2463092595635818, 0.03093952256232852, 0.14090123331537707, 0.022726447678970422, -0.06856817219133203, -0.07582143243992569, 0.0013868294318947266, 0.21534560487686297, -0.004014462659751454, 0.06651575085578677, 0.10953210050049494, -0.19429917865642254, -0.14157871310837478, 0.28039188970496337, -0.08614447529383708, -0.21473184314475754, 0.1738373737224913, -0.04957173108013244, -0.1346973644415518, 0.03809379686520794, 0.2369665115261377, 0.07777354364672046, -0.18127228268312187, 0.01839314247105696, -0.01328739010560231, 0.24625139581094546, 0.05452329097095671, 0.03640788038605897, 0.22857029708175677, 0.26394814126721516, -0.08620401654634478, 0.180720797939754, -0.10346555380942667, -0.10392457758274487, -0.20470793360860753, -0.11295318285527632, -0.1926608227396051, -0.0027638222127566187, -0.10618527395974782, -0.17705503770509573, 0.43769479381639187, 0.22576931049299287, 0.23270334289262556, 0.10619735377144039, 0.3244556035758473, 0.012432590205823695, 0.11928104380453665, 0.13861297580274187, 0.11924882096377766, 0.07598418033293147, 0.14362179709407757, -0.19390546222672042, 0.15202834329193854, 0.08044501842828247] |
1,802.03817 | Inducibility of d-ary trees | Imitating a recently introduced invariant of trees, we initiate the study of
the inducibility of $d$-ary trees (rooted trees whose vertex outdegrees are
bounded from above by $d\geq 2$) with a given number of leaves. We determine
the exact inducibility for stars and binary caterpillars. For $T$ in the family
of strictly $d$-ary trees (every vertex has $0$ or $d$ children), we prove that
the difference between the maximum density of a $d$-ary tree $D$ in $T$ and the
inducibility of $D$ is of order $\mathcal{O}(|T|^{-1/2})$ compared to the
general case where it is shown that the difference is $\mathcal{O}(|T|^{-1})$
which, in particular, responds positively to an existing conjecture on the
inducibility in binary trees. We also discover that the inducibility of a
binary tree in $d$-ary trees is independent of $d$. Furthermore, we establish a
general lower bound on the inducibility and also provide a bound for some
special trees. Moreover, we find that the maximum inducibility is attained for
binary caterpillars for every $d$.
| math.CO | imitating a recently introduced invariant of trees we initiate the study of the inducibility of dary trees rooted trees whose vertex outdegrees are bounded from above by dgeq 2 with a given number of leaves we determine the exact inducibility for stars and binary caterpillars for t in the family of strictly dary trees every vertex has 0 or d children we prove that the difference between the maximum density of a dary tree d in t and the inducibility of d is of order mathcalot12 compared to the general case where it is shown that the difference is mathcalot1 which in particular responds positively to an existing conjecture on the inducibility in binary trees we also discover that the inducibility of a binary tree in dary trees is independent of d furthermore we establish a general lower bound on the inducibility and also provide a bound for some special trees moreover we find that the maximum inducibility is attained for binary caterpillars for every d | [['imitating', 'a', 'recently', 'introduced', 'invariant', 'of', 'trees', 'we', 'initiate', 'the', 'study', 'of', 'the', 'inducibility', 'of', 'dary', 'trees', 'rooted', 'trees', 'whose', 'vertex', 'outdegrees', 'are', 'bounded', 'from', 'above', 'by', 'dgeq', '2', 'with', 'a', 'given', 'number', 'of', 'leaves', 'we', 'determine', 'the', 'exact', 'inducibility', 'for', 'stars', 'and', 'binary', 'caterpillars', 'for', 't', 'in', 'the', 'family', 'of', 'strictly', 'dary', 'trees', 'every', 'vertex', 'has', '0', 'or', 'd', 'children', 'we', 'prove', 'that', 'the', 'difference', 'between', 'the', 'maximum', 'density', 'of', 'a', 'dary', 'tree', 'd', 'in', 't', 'and', 'the', 'inducibility', 'of', 'd', 'is', 'of', 'order', 'mathcalot12', 'compared', 'to', 'the', 'general', 'case', 'where', 'it', 'is', 'shown', 'that', 'the', 'difference', 'is', 'mathcalot1', 'which', 'in', 'particular', 'responds', 'positively', 'to', 'an', 'existing', 'conjecture', 'on', 'the', 'inducibility', 'in', 'binary', 'trees', 'we', 'also', 'discover', 'that', 'the', 'inducibility', 'of', 'a', 'binary', 'tree', 'in', 'dary', 'trees', 'is', 'independent', 'of', 'd', 'furthermore', 'we', 'establish', 'a', 'general', 'lower', 'bound', 'on', 'the', 'inducibility', 'and', 'also', 'provide', 'a', 'bound', 'for', 'some', 'special', 'trees', 'moreover', 'we', 'find', 'that', 'the', 'maximum', 'inducibility', 'is', 'attained', 'for', 'binary', 'caterpillars', 'for', 'every', 'd']] | [-0.1587008675042165, 0.19553770726660577, -0.04353916905138914, 0.0628734483765495, -0.06628226551011478, -0.1366465212720469, 0.11536179721233344, 0.33991369402899246, -0.25876157764322694, -0.2616374158050592, 0.08727286850235698, -0.30979963973528, -0.17548522527653315, 0.14582534057369298, -0.06779810915155927, 0.022086180735197736, 0.09238158629230428, 0.17467593803605003, -0.011653909218361283, -0.3053041539927263, 0.3572389019380619, 0.001998085846624723, 0.15914175113117912, 0.06494608490795988, 0.10746110449317933, 0.04656665539936867, -0.006993539412733077, 0.05852462777231888, -0.20658263053674755, 0.07441049624552451, 0.22701469264504295, 0.1822976338731323, 0.19703902664208195, -0.30878309229006934, -0.16048613177163798, 0.19612390421637585, 0.11712268751438298, 0.09257985876728327, -0.015760373892035426, -0.18073181521357606, 0.16882105314786114, -0.14447285033046928, -0.11062734893227859, 0.03780767914168991, 0.14668617645142282, 0.019820020986982143, -0.28980492218965437, 0.013039943518290274, 0.1619978261793532, 0.029675577222028883, 0.0029109571322162705, -0.1768288704120872, -0.06616214310279026, 0.09093100154380564, -0.05456130795334125, 0.0901202059637687, -0.020666047735508848, -0.11393153081966065, -0.1719697841340903, 0.3055595623328572, -0.05741569522282722, -0.18390749708363197, 0.17875084524801024, -0.1787108667336813, -0.22109493890368356, 0.07155482447493208, 0.17441945049412003, 0.19774924241369818, -0.1008858294510169, 0.13867781064139464, -0.11505908101709082, 0.11792773685259063, 0.15956742717123523, -0.027117541244412523, 0.15009138223760557, 0.17107736703048165, 0.14798851037488842, 0.2238925688888696, -0.0481113279550677, -0.018855400593587902, -0.2513638264272453, -0.12926666940727113, -0.16794638292829892, 0.04285233115589973, -0.16064279150367194, -0.2184930401973117, 0.34057445324128266, 0.11053126464915894, 0.2241815982994101, 0.17987179667078435, 0.16563254001510624, 0.08902864119537719, 0.0023039962767010054, 0.16050893382067088, 0.14111430684999682, 0.18888641094395653, -0.02411650192196958, -0.17422945033006437, 0.1069445058578489, 0.1266511211830309] |
1,802.03818 | Gromov-Hausdorff limits of flat Riemannian surfaces | I study Gromov-Hausdorff limits of complex curves endowed with singular flat
metrics of constant diameter. I formulate a criterion that the limit is
collapsed in terms of a certain piecewise affine weight function on the dual
intersection complex of a semi-stable model of the degeneration introduced by
Kontsevich and Soibelman. I describe the collapsed and non-collapsed limits,
which are, respectively, metric graphs and finite collections of complex curves
with flat metrics glued along finitely many points. I show that the collapsed
limit of any positive genus can occur.
| math.AG math.DG | i study gromovhausdorff limits of complex curves endowed with singular flat metrics of constant diameter i formulate a criterion that the limit is collapsed in terms of a certain piecewise affine weight function on the dual intersection complex of a semistable model of the degeneration introduced by kontsevich and soibelman i describe the collapsed and noncollapsed limits which are respectively metric graphs and finite collections of complex curves with flat metrics glued along finitely many points i show that the collapsed limit of any positive genus can occur | [['i', 'study', 'gromovhausdorff', 'limits', 'of', 'complex', 'curves', 'endowed', 'with', 'singular', 'flat', 'metrics', 'of', 'constant', 'diameter', 'i', 'formulate', 'a', 'criterion', 'that', 'the', 'limit', 'is', 'collapsed', 'in', 'terms', 'of', 'a', 'certain', 'piecewise', 'affine', 'weight', 'function', 'on', 'the', 'dual', 'intersection', 'complex', 'of', 'a', 'semistable', 'model', 'of', 'the', 'degeneration', 'introduced', 'by', 'kontsevich', 'and', 'soibelman', 'i', 'describe', 'the', 'collapsed', 'and', 'noncollapsed', 'limits', 'which', 'are', 'respectively', 'metric', 'graphs', 'and', 'finite', 'collections', 'of', 'complex', 'curves', 'with', 'flat', 'metrics', 'glued', 'along', 'finitely', 'many', 'points', 'i', 'show', 'that', 'the', 'collapsed', 'limit', 'of', 'any', 'positive', 'genus', 'can', 'occur']] | [-0.18736644971861757, 0.11180223636223342, -0.07962102252482013, 0.0679310438373994, -0.07954756951552223, -0.17797927313420753, 0.01554503197654743, 0.3548453864006495, -0.28877536658282305, -0.18456212215030313, 0.10463270554927559, -0.2519911192780869, -0.17503844739191912, 0.1732661618761168, -0.16473634604533965, 0.003616380153372037, 0.07933447017884729, 0.05515740912365304, -0.10542604709784924, -0.28675374619408767, 0.430737913723781, -0.05017932857894762, 0.2684918060708283, 0.05073582343968817, 0.15399239018593522, -0.024520183495372872, -0.0008913983553859659, 0.0870776769099228, -0.19709465161725925, 0.1391374057222327, 0.26599362439116125, 0.09932322185804052, 0.1596735497296322, -0.3400191960102926, -0.18871009932957927, 0.21347108341499485, 0.10065400531113317, -0.021790088446736758, 0.050433352233746766, -0.27458085389596154, 0.11435854616998271, -0.10946009087968957, -0.18881913844432513, -0.061633109358477996, 0.028010645558507265, 0.06531722959797745, -0.13824884581845254, -0.0043932360342957754, 0.10550165661367249, 0.06665390215560117, -0.08277076576434245, -0.08528695687842132, -0.09242391269336539, 0.059723286460873416, 0.008126119475822303, 0.04853736105062787, 0.08456956587245011, -0.088686753735105, -0.10779922309765508, 0.3327946081170177, -0.10014028970247389, -0.23915189235809853, 0.1396366311343048, -0.12872883992862294, -0.13332708323882383, 0.14301073193465444, 0.12219554304399273, 0.18841545249398967, -0.02967197405946949, 0.20890122516390297, -0.043777056419375265, 0.055075182103213265, 0.12780365543916228, -0.03263348814586855, 0.1933886040510102, 0.08859188031320545, 0.06874052865830228, 0.12869168126119554, -0.02682922103452835, -0.10337767407128756, -0.3714789897838438, -0.1936636469115249, -0.13719235801148566, 0.15990665852388536, -0.22236210243747997, -0.2657635182311589, 0.37404465985442087, -0.00021841322516345164, 0.28253411923916166, 0.13451774752915793, 0.22079722000423566, 0.0627618672019294, 0.013996336347190663, 0.06586496385915036, 0.16964200829071077, 0.17803976591147314, -0.04018304175273939, -0.10254853469086811, 0.0008935545857556546, 0.15847596681719137] |
1,802.03819 | Nonsymmetric Rogers-Ramanujan sums and thick Demazure modules | We consider expansions of products of theta-functions associated with
arbitrary root systems in terms of nonsymmetric Macdonald polynomials at
$t=\infty$ divided by their norms. The latter are identified with the graded
characters of Demazure slices, some canonical quotients of thick (upper)
level-one Demazure modules, directly related to recent theory of generalized
(nonsymmetric) global Weyl modules. The symmetric Rogers-Ramanujan-type series
considered by Cherednik-Feigin were expected to have some interpretation of
this kind; the nonsymmetric setting appeared necessary to achieve this. As an
application, the coefficients of the nonsymmetric Rogers-Ramanujan series
provide formulas for the multiplicities of the expansions of tensor products of
level-one Kac-Moody representations in terms of Demazure slices.
| math.RT math.QA | we consider expansions of products of thetafunctions associated with arbitrary root systems in terms of nonsymmetric macdonald polynomials at tinfty divided by their norms the latter are identified with the graded characters of demazure slices some canonical quotients of thick upper levelone demazure modules directly related to recent theory of generalized nonsymmetric global weyl modules the symmetric rogersramanujantype series considered by cherednikfeigin were expected to have some interpretation of this kind the nonsymmetric setting appeared necessary to achieve this as an application the coefficients of the nonsymmetric rogersramanujan series provide formulas for the multiplicities of the expansions of tensor products of levelone kacmoody representations in terms of demazure slices | [['we', 'consider', 'expansions', 'of', 'products', 'of', 'thetafunctions', 'associated', 'with', 'arbitrary', 'root', 'systems', 'in', 'terms', 'of', 'nonsymmetric', 'macdonald', 'polynomials', 'at', 'tinfty', 'divided', 'by', 'their', 'norms', 'the', 'latter', 'are', 'identified', 'with', 'the', 'graded', 'characters', 'of', 'demazure', 'slices', 'some', 'canonical', 'quotients', 'of', 'thick', 'upper', 'levelone', 'demazure', 'modules', 'directly', 'related', 'to', 'recent', 'theory', 'of', 'generalized', 'nonsymmetric', 'global', 'weyl', 'modules', 'the', 'symmetric', 'rogersramanujantype', 'series', 'considered', 'by', 'cherednikfeigin', 'were', 'expected', 'to', 'have', 'some', 'interpretation', 'of', 'this', 'kind', 'the', 'nonsymmetric', 'setting', 'appeared', 'necessary', 'to', 'achieve', 'this', 'as', 'an', 'application', 'the', 'coefficients', 'of', 'the', 'nonsymmetric', 'rogersramanujan', 'series', 'provide', 'formulas', 'for', 'the', 'multiplicities', 'of', 'the', 'expansions', 'of', 'tensor', 'products', 'of', 'levelone', 'kacmoody', 'representations', 'in', 'terms', 'of', 'demazure', 'slices']] | [-0.1673873763108902, 0.06781129281982969, -0.04740708824936991, 0.042698967014008236, -0.07716037898703858, -0.08457392960769573, -0.07453322050019374, 0.3134684518272816, -0.3569843881478947, -0.19044918741996367, 0.12964003557485906, -0.22070267818074812, -0.14914246914580603, 0.1843752889275223, -0.10044181166166607, 0.0040121556048688944, 0.0224622900304557, 0.09747382485619271, -0.15129429107764736, -0.3407521196662586, 0.3778664763128661, 0.046139100873713486, 0.2365152722535034, -0.005575153155304078, 0.09989389118790212, -0.006400440711769517, -0.07261078129522502, -0.08685992103225242, -0.1281538573503322, 0.19482337020518672, 0.3471779990941286, 0.04344756052725845, 0.19301993854093813, -0.4135499738363756, -0.0601297016061532, 0.1496913165492178, 0.17116719022548446, -0.0009352950965640721, 0.016556976095738786, -0.2601138932492446, 0.052211557190376984, -0.2647992957478251, -0.1982664688990486, -0.1192044654895586, 0.012889560087825413, 0.07434440529538767, -0.24977154715883512, 0.07957429717363859, 0.0808954533406197, 0.09273495893958844, -0.11290708276943338, -0.21220476021214077, -0.007828511198534182, 0.09027125188569901, 0.016622899207976407, -0.08385752032821377, 0.051106944615538746, -0.12911313635278795, -0.18941648752877005, 0.3375429307041621, -0.018316772072231053, -0.2594336128483216, 0.1142102260890641, -0.21150498825159889, -0.15709311438344972, 0.12713880033266764, 0.10554428493897258, 0.12080715538037044, -0.06412086402997375, 0.13111129261691262, -0.10517590015229804, -0.018608950602895306, 0.19735596319488077, 0.04843114920098473, 0.17371434569401942, -0.008270854492568307, -0.02531487981711204, 0.2147443309529788, 0.07661500451461135, -0.05904643194474004, -0.376107896540176, -0.21789622981170262, -0.1163380895202324, 0.08474611730694219, -0.1601014678599313, -0.21838035773598002, 0.3674492135092064, 0.03754090588470852, 0.19807986180455406, 0.10723820575556063, 0.1613670331598432, 0.14827353650320288, 0.12825330645379532, -0.04403485682430781, 0.11604930166666033, 0.26344592831339, 0.07054691332288915, -0.1358135394704597, 0.00899760006750175, 0.2376478766479219] |
1,802.0382 | Power law viscoelasticity of a fractal colloidal gel | Power law rheology is of widespread occurrence in complex materials that are
characterized by the presence of a very broad range of microstructural length
and time scales. Although phenomenological models able to reproduce the
observed rheological features exist, in general a well-established connection
with the microscopic origin of this mechanical behavior is still missing. As a
model system, this work focuses on a fractal colloidal gel. We thoroughly
characterize the linear power law rheology of the sample and its age
dependence. We show that at all sample ages and for a variety of rheological
tests the gel linear viscoelasticity is very accurately described by a
Fractional Maxwell (FM) model, characterized by a power law behavior. Thanks to
a unique set-up that couples small-angle static and dynamic light scattering to
rheological measurements, we demonstrate that the power law rheology observed
in the linear regime originates from reversible non-affine rearrangements and
discuss the possible relationship between the FM model and the microscopic
structure of the gel.
| cond-mat.soft | power law rheology is of widespread occurrence in complex materials that are characterized by the presence of a very broad range of microstructural length and time scales although phenomenological models able to reproduce the observed rheological features exist in general a wellestablished connection with the microscopic origin of this mechanical behavior is still missing as a model system this work focuses on a fractal colloidal gel we thoroughly characterize the linear power law rheology of the sample and its age dependence we show that at all sample ages and for a variety of rheological tests the gel linear viscoelasticity is very accurately described by a fractional maxwell fm model characterized by a power law behavior thanks to a unique setup that couples smallangle static and dynamic light scattering to rheological measurements we demonstrate that the power law rheology observed in the linear regime originates from reversible nonaffine rearrangements and discuss the possible relationship between the fm model and the microscopic structure of the gel | [['power', 'law', 'rheology', 'is', 'of', 'widespread', 'occurrence', 'in', 'complex', 'materials', 'that', 'are', 'characterized', 'by', 'the', 'presence', 'of', 'a', 'very', 'broad', 'range', 'of', 'microstructural', 'length', 'and', 'time', 'scales', 'although', 'phenomenological', 'models', 'able', 'to', 'reproduce', 'the', 'observed', 'rheological', 'features', 'exist', 'in', 'general', 'a', 'wellestablished', 'connection', 'with', 'the', 'microscopic', 'origin', 'of', 'this', 'mechanical', 'behavior', 'is', 'still', 'missing', 'as', 'a', 'model', 'system', 'this', 'work', 'focuses', 'on', 'a', 'fractal', 'colloidal', 'gel', 'we', 'thoroughly', 'characterize', 'the', 'linear', 'power', 'law', 'rheology', 'of', 'the', 'sample', 'and', 'its', 'age', 'dependence', 'we', 'show', 'that', 'at', 'all', 'sample', 'ages', 'and', 'for', 'a', 'variety', 'of', 'rheological', 'tests', 'the', 'gel', 'linear', 'viscoelasticity', 'is', 'very', 'accurately', 'described', 'by', 'a', 'fractional', 'maxwell', 'fm', 'model', 'characterized', 'by', 'a', 'power', 'law', 'behavior', 'thanks', 'to', 'a', 'unique', 'setup', 'that', 'couples', 'smallangle', 'static', 'and', 'dynamic', 'light', 'scattering', 'to', 'rheological', 'measurements', 'we', 'demonstrate', 'that', 'the', 'power', 'law', 'rheology', 'observed', 'in', 'the', 'linear', 'regime', 'originates', 'from', 'reversible', 'nonaffine', 'rearrangements', 'and', 'discuss', 'the', 'possible', 'relationship', 'between', 'the', 'fm', 'model', 'and', 'the', 'microscopic', 'structure', 'of', 'the', 'gel']] | [-0.10791151209382295, 0.1566857513630899, -0.12806401345254173, 0.029439280088565018, -0.07968066813049429, -0.14758857120419058, 0.025388914708434265, 0.3434153540605089, -0.31067094136108986, -0.2834836514098797, 0.051489648582746, -0.27499961890507396, -0.2022048588272943, 0.1754883363198421, -0.016571177408190037, 0.07942204183306852, -0.02724972644482921, -0.04312338704305769, -0.01566766496079054, -0.148431963187915, 0.2646937017135958, 0.053006742087124685, 0.30211271643610216, 0.045656998799375556, 0.12016394998730592, -0.02867610390417323, -0.000468463509161843, 0.0978019175846584, -0.17453416522181303, 0.05985173846562336, 0.24038626500306437, 0.02079482068216837, 0.20846536273148092, -0.4183510836754555, -0.268317189851276, 0.07015165276030397, 0.08507569567243592, 0.061580798793129804, -0.024292560428432076, -0.20065810516612922, 0.06740643481564958, -0.15004388047325448, -0.16007333773219526, -0.10401145114688339, 0.055549469322147896, 0.03805827659770574, -0.23133996723499434, 0.1600807964171442, 0.0725669238663835, 0.09273626592873437, -0.10003740138661048, -0.028000373430475563, 0.006806882413490335, 0.09150258731735847, 0.07233229524203258, -0.05645278046509569, 0.18743461410787593, -0.15710633915207325, -0.06523470380684225, 0.4059610864837518, -0.032823498466225315, -0.13393706115666867, 0.21070847348537206, -0.1907207327873571, -0.09898917707926934, 0.14063418618397697, 0.18225338767572283, 0.07968234768646298, -0.19199618096385299, 0.05626674557021122, -0.04937512921623704, 0.2427091808654595, 0.019684037402351726, 0.008326312543032123, 0.2191409580530201, 0.24046537622088204, -0.03570743419354918, 0.14745307875024835, -0.0833968411032224, -0.10447445001613587, -0.28244453373864836, -0.10712891324741267, -0.20325646432267117, 0.06100019195298778, -0.12944225320062264, -0.1591419516267573, 0.37944587816132186, 0.10165174513282936, 0.20454183951901875, 0.10569794505845936, 0.2449380963154864, 0.048868781732247644, 0.05317432205930988, 0.016475765159489904, 0.28307893044647486, 0.16738359059317878, 0.15634228416616325, -0.2745778235055296, 0.1154314759641704, 0.004694935412816249] |
1,802.03821 | Distributed Readability Analysis Of Turkish Elementary School Textbooks | The readability assessment deals with estimating the level of difficulty in
reading texts.Many readability tests, which do not indicate execution
efficiency, have been applied on specific texts to measure the reading grade
level in science textbooks. In this paper, we analyze the content covered in
elementary school Turkish textbooks by employing a distributed parallel
processing framework based on popular MapReduce paradigm. We outline the
architecture of a distributed Big Data processing system which uses Hadoop for
full-text readability analysis. The readability scores of the textbooks and
system performance measurements are also given in the paper.
| cs.DC cs.CL | the readability assessment deals with estimating the level of difficulty in reading textsmany readability tests which do not indicate execution efficiency have been applied on specific texts to measure the reading grade level in science textbooks in this paper we analyze the content covered in elementary school turkish textbooks by employing a distributed parallel processing framework based on popular mapreduce paradigm we outline the architecture of a distributed big data processing system which uses hadoop for fulltext readability analysis the readability scores of the textbooks and system performance measurements are also given in the paper | [['the', 'readability', 'assessment', 'deals', 'with', 'estimating', 'the', 'level', 'of', 'difficulty', 'in', 'reading', 'textsmany', 'readability', 'tests', 'which', 'do', 'not', 'indicate', 'execution', 'efficiency', 'have', 'been', 'applied', 'on', 'specific', 'texts', 'to', 'measure', 'the', 'reading', 'grade', 'level', 'in', 'science', 'textbooks', 'in', 'this', 'paper', 'we', 'analyze', 'the', 'content', 'covered', 'in', 'elementary', 'school', 'turkish', 'textbooks', 'by', 'employing', 'a', 'distributed', 'parallel', 'processing', 'framework', 'based', 'on', 'popular', 'mapreduce', 'paradigm', 'we', 'outline', 'the', 'architecture', 'of', 'a', 'distributed', 'big', 'data', 'processing', 'system', 'which', 'uses', 'hadoop', 'for', 'fulltext', 'readability', 'analysis', 'the', 'readability', 'scores', 'of', 'the', 'textbooks', 'and', 'system', 'performance', 'measurements', 'are', 'also', 'given', 'in', 'the', 'paper']] | [-0.08532293307089663, -0.007819136465959092, -0.06852371204691503, 0.05901942372772882, -0.11455575658127348, -0.14800189185808313, 0.06610666895334787, 0.39920194234025286, -0.226902511664369, -0.39572925663533365, 0.09438625515929047, -0.28884113940628287, -0.10018322295620741, 0.20392784355530277, -0.17512388958625416, 0.0819131753115142, 0.12831527112606675, 0.06965448742514437, -0.03716108957404628, -0.32106063664553963, 0.2585045199747138, 0.10112232423605437, 0.4144973066595799, 0.04895458374410234, 0.03345938319305671, 0.0006643052738001372, -0.09974176320247352, 0.025445076765769972, -0.06539922907448156, 0.19535151089323646, 0.3331753178004255, 0.2613885928752852, 0.33564616217614807, -0.4182889131467512, -0.12352680761188745, 0.020366666050865612, 0.13615465910728783, 0.06886108588963559, -0.07870446862974897, -0.28321598466247955, 0.07879972712513297, -0.17421352976011706, 0.010227119698724214, -0.07633507440976323, 0.0021890426213119893, 0.01785020479446951, -0.16742045754329005, 0.029917870263972794, 0.06253743897306119, 0.18251270513506013, 0.008628185823599392, -0.14848498424188175, 0.09938185035865357, 0.14355422334963494, 0.003947598394006491, -0.014574852773914748, 0.166773896981427, -0.12166178557139999, -0.18798010829994652, 0.4314692718710037, -0.051250037509933156, -0.2034692158328092, 0.15101117526052243, -0.06897169877675936, -0.21757822765651694, 0.0098559366529213, 0.24770374097638426, 0.05523421020343642, -0.19642909286305943, 0.09361726522354033, 0.021703072318292046, 0.2264807512785526, 0.10900340255528213, -0.012027403369466675, 0.19881179541636734, 0.24026206343811243, -0.04636341119878628, 0.13107275223716142, -0.02039470741069539, -0.07598471222940753, -0.26515990995029187, -0.20225477284699817, -0.21305537364505073, -0.05261538937261224, -0.03182280509954968, -0.18392685267261843, 0.41507498031244316, 0.22300882718511586, 0.0786441729126617, 0.04725312023235366, 0.36133932964281834, 0.04811557298996783, 0.06807224766693097, 0.12247320292319389, 0.13718108970057616, 0.02329173705174013, 0.2154163248178133, -0.11505060248631746, 0.09754699711846386, 0.047124042126171765] |
1,802.03822 | Developments of highly-multiplexed, multi-chroic pixels for
Balloon-Borne Platforms | We present our work to develop and characterize low thermal conductance
bolometers that are part of sinuous antenna multi-chroic pixels (SAMP). We use
longer, thinner and meandered bolometer legs to achieve 9 pW/K thermal
conductance bolometers. We also discuss the development of inductor-capacitor
chips operated at 4 K to extend the multiplexing factor of the frequency domain
multiplexing to 105, an increase of 60% compared to the factor currently
demonstrated for this readout system. This technology development is motivated
by EBEX-IDS, a balloon-borne polarimeter designed to characterize the
polarization of foregrounds and to detect the primordial gravity waves through
their B-mode signature on the polarization of the cosmic microwave background.
EBEX-IDS will operate 20,562 transition edge sensor bolometers spread over 7
frequency bands between 150 and 360 GHz. Balloon and satellite platforms enable
observations at frequencies inaccessible from the ground and with higher
instantaneous sensitivity. This development improves the readiness of the SAMP
and frequency domain readout technologies for future satellite applications.
| astro-ph.IM astro-ph.CO | we present our work to develop and characterize low thermal conductance bolometers that are part of sinuous antenna multichroic pixels samp we use longer thinner and meandered bolometer legs to achieve 9 pwk thermal conductance bolometers we also discuss the development of inductorcapacitor chips operated at 4 k to extend the multiplexing factor of the frequency domain multiplexing to 105 an increase of 60 compared to the factor currently demonstrated for this readout system this technology development is motivated by ebexids a balloonborne polarimeter designed to characterize the polarization of foregrounds and to detect the primordial gravity waves through their bmode signature on the polarization of the cosmic microwave background ebexids will operate 20562 transition edge sensor bolometers spread over 7 frequency bands between 150 and 360 ghz balloon and satellite platforms enable observations at frequencies inaccessible from the ground and with higher instantaneous sensitivity this development improves the readiness of the samp and frequency domain readout technologies for future satellite applications | [['we', 'present', 'our', 'work', 'to', 'develop', 'and', 'characterize', 'low', 'thermal', 'conductance', 'bolometers', 'that', 'are', 'part', 'of', 'sinuous', 'antenna', 'multichroic', 'pixels', 'samp', 'we', 'use', 'longer', 'thinner', 'and', 'meandered', 'bolometer', 'legs', 'to', 'achieve', '9', 'pwk', 'thermal', 'conductance', 'bolometers', 'we', 'also', 'discuss', 'the', 'development', 'of', 'inductorcapacitor', 'chips', 'operated', 'at', '4', 'k', 'to', 'extend', 'the', 'multiplexing', 'factor', 'of', 'the', 'frequency', 'domain', 'multiplexing', 'to', '105', 'an', 'increase', 'of', '60', 'compared', 'to', 'the', 'factor', 'currently', 'demonstrated', 'for', 'this', 'readout', 'system', 'this', 'technology', 'development', 'is', 'motivated', 'by', 'ebexids', 'a', 'balloonborne', 'polarimeter', 'designed', 'to', 'characterize', 'the', 'polarization', 'of', 'foregrounds', 'and', 'to', 'detect', 'the', 'primordial', 'gravity', 'waves', 'through', 'their', 'bmode', 'signature', 'on', 'the', 'polarization', 'of', 'the', 'cosmic', 'microwave', 'background', 'ebexids', 'will', 'operate', '20562', 'transition', 'edge', 'sensor', 'bolometers', 'spread', 'over', '7', 'frequency', 'bands', 'between', '150', 'and', '360', 'ghz', 'balloon', 'and', 'satellite', 'platforms', 'enable', 'observations', 'at', 'frequencies', 'inaccessible', 'from', 'the', 'ground', 'and', 'with', 'higher', 'instantaneous', 'sensitivity', 'this', 'development', 'improves', 'the', 'readiness', 'of', 'the', 'samp', 'and', 'frequency', 'domain', 'readout', 'technologies', 'for', 'future', 'satellite', 'applications']] | [-0.15854663996383953, 0.1631475095608771, 0.0034489128123617397, -0.05695783087556139, -0.07400420220984649, -0.12957550511759874, 0.021136282484849576, 0.4138993166105927, -0.19501158224020457, -0.33791692247145677, 0.10759898726154798, -0.30156810889196284, -0.08482256741995144, 0.23960045237334315, -0.025610062640757776, 0.02442554541301193, 0.026158101452549674, -0.07503813036143452, -0.00481855503939467, -0.19838822290737698, 0.1941255711095185, 0.1887733267807642, 0.3371021451813655, 0.03312477042400476, 0.13170230668184565, -0.05316170672563918, -0.05969426698533162, -0.06435044161366217, -0.12369028729414633, 0.06631676280291153, 0.33070181687684647, 0.0883186868298213, 0.18640381110972673, -0.42245393077719884, -0.17992117053260967, 0.09210269250204119, 0.0955649893335506, 0.03951869039274986, 0.025451853721982467, -0.30304354718013565, 0.08371584154716723, -0.18503731462036246, -0.12640412510577706, -0.01842310401367949, -0.013320732777191431, -0.037002948024925195, -0.22278217356593447, -0.0006336143502816207, -0.014516676196231032, 0.06060077960283712, -0.03383597564069355, -0.12650035384020317, 0.043664405305442286, 0.09458770417555604, -0.06635124610777968, 0.04247582326321013, 0.20445666672169882, -0.08757936003992814, -0.11931952412984094, 0.3016771188960557, -0.10524283330331105, -0.06995562540730403, 0.16829736097920803, -0.22022605400661346, -0.08161624855180301, 0.16024064038932886, 0.18868250375226983, 0.03263619731900827, -0.1454300975680363, 0.012983611956752732, 0.1376537913280838, 0.23336272102300334, 0.1518642413429916, 0.11010261212545887, 0.279875941026909, 0.209459871949874, 0.13382689923424357, 0.15177077078773002, -0.210006047453169, 0.044689624822177226, -0.22694598809587505, -0.12481933550135989, -0.17211000930514983, 0.05438908685572407, -0.052436186708806454, -0.10768133745112884, 0.3982447474585764, 0.21283163668576088, 0.11485463171705322, 0.04221257366058446, 0.3683105379829195, 0.036138971380848414, 0.11636642603967493, 0.027778760295027412, 0.2849830031254382, 0.14120107837191215, 0.18202828138893903, -0.2086489147040993, -0.04651058523523264, -0.09283298701516488] |
1,802.03823 | Zero-cycles on a product of elliptic curves over a $p$-adic field | We consider a product $X=E_1\times\cdots\times E_d$ of elliptic curves over a
finite extension $K$ of $\mathbb{Q}_p$ with a combination of good or split
multiplicative reduction. We assume that at most one of the elliptic curves has
supersingular reduction. Under these assumptions, we prove that the Albanese
kernel of $X$ is the direct sum of a finite group and a divisible group,
extending work of Raskind and Spiess to cases that include supersingular
phenomena. Our method involves studying the kernel of the cycle map
$CH_0(X)/p^n\rightarrow H^{2d}_{\text{\'{e}t}}(X, \mu_{p^n}^{\otimes d})$. We
give specific criteria that guarantee this map is injective for every $n\geq
1$. When all curves have good ordinary reduction, we show that it suffices to
extend to a specific finite extension $L$ of $K$ for these criteria to be
satisfied. This extends previous work of Yamazaki and Hiranouchi.
| math.NT math.AG | we consider a product xe_1timescdotstimes e_d of elliptic curves over a finite extension k of mathbbq_p with a combination of good or split multiplicative reduction we assume that at most one of the elliptic curves has supersingular reduction under these assumptions we prove that the albanese kernel of x is the direct sum of a finite group and a divisible group extending work of raskind and spiess to cases that include supersingular phenomena our method involves studying the kernel of the cycle map ch_0xpnrightarrow h2d_textetx mu_pnotimes d we give specific criteria that guarantee this map is injective for every ngeq 1 when all curves have good ordinary reduction we show that it suffices to extend to a specific finite extension l of k for these criteria to be satisfied this extends previous work of yamazaki and hiranouchi | [['we', 'consider', 'a', 'product', 'xe_1timescdotstimes', 'e_d', 'of', 'elliptic', 'curves', 'over', 'a', 'finite', 'extension', 'k', 'of', 'mathbbq_p', 'with', 'a', 'combination', 'of', 'good', 'or', 'split', 'multiplicative', 'reduction', 'we', 'assume', 'that', 'at', 'most', 'one', 'of', 'the', 'elliptic', 'curves', 'has', 'supersingular', 'reduction', 'under', 'these', 'assumptions', 'we', 'prove', 'that', 'the', 'albanese', 'kernel', 'of', 'x', 'is', 'the', 'direct', 'sum', 'of', 'a', 'finite', 'group', 'and', 'a', 'divisible', 'group', 'extending', 'work', 'of', 'raskind', 'and', 'spiess', 'to', 'cases', 'that', 'include', 'supersingular', 'phenomena', 'our', 'method', 'involves', 'studying', 'the', 'kernel', 'of', 'the', 'cycle', 'map', 'ch_0xpnrightarrow', 'h2d_textetx', 'mu_pnotimes', 'd', 'we', 'give', 'specific', 'criteria', 'that', 'guarantee', 'this', 'map', 'is', 'injective', 'for', 'every', 'ngeq', '1', 'when', 'all', 'curves', 'have', 'good', 'ordinary', 'reduction', 'we', 'show', 'that', 'it', 'suffices', 'to', 'extend', 'to', 'a', 'specific', 'finite', 'extension', 'l', 'of', 'k', 'for', 'these', 'criteria', 'to', 'be', 'satisfied', 'this', 'extends', 'previous', 'work', 'of', 'yamazaki', 'and', 'hiranouchi']] | [-0.1595766719982547, 0.038345768550083835, -0.14215227442914408, 0.04392634932918631, -0.09271027382022438, -0.16434760409485522, 0.041111418973825135, 0.3544250265872888, -0.286153128449734, -0.2265514139128664, 0.08641092550322299, -0.2668484587552033, -0.12988583335674275, 0.23507339895333212, -0.11123506157154231, 0.008118077793570933, 0.04888532947720462, 0.07057075892070322, -0.08901126762916056, -0.33183430279036347, 0.3508165101342984, -0.0516980615842604, 0.19767303208159354, 0.05972194502917509, 0.13140119448346832, 0.040980426674706055, -0.03151735095378324, -0.00135929514031081, -0.16088525440775164, 0.12313472480648233, 0.29588524855047693, 0.07478021141248294, 0.22965214324702743, -0.3406835814023956, -0.24636331237035, 0.23325920226550056, 0.0965835620286583, 0.030265192302185617, 0.007837892648628877, -0.1603979979542205, 0.1813270244516347, -0.17513459844102386, -0.15630954897514623, -0.0843094254787016, 0.05896942088565298, 0.02258682098125911, -0.28776662950119614, 0.02893693420950693, 0.15850138997673305, 0.1321186297182136, -0.03782172142776824, -0.13797457432303264, -0.006355953717405218, 0.06592216572074668, 0.006497448522647316, 0.04945711679543362, 0.05363575139976967, -0.08440515916538603, -0.09147397660870703, 0.36388811955356415, -0.1054277233601697, -0.17881352509165765, 0.14965348830268868, -0.15299791238405777, -0.1504300539808362, 0.14388236351567144, 0.09987837948502247, 0.15581432778658416, -0.044684723487593954, 0.153082960831332, -0.14401238723053733, 0.12114026903917743, 0.08216514540765121, -0.03375805441275922, 0.07505113812063942, 0.10827609121831461, 0.12237685296474778, 0.1335894850576794, -0.006143518144136849, -0.0004752647906598699, -0.37250674621180724, -0.18562977560369284, -0.11575462524014887, 0.11173871826053462, -0.08881563965783486, -0.1329397951458929, 0.38682473229087944, 0.10919500609796728, 0.21361144287298425, 0.09729970530215792, 0.22966148154028043, 0.12039914660116671, 0.05541856587505215, 0.0781285933712995, 0.13257525036758425, 0.16851742740876915, -0.029823516539070498, -0.17816241782688258, -0.0073483785657027295, 0.11295083780481502] |
1,802.03824 | Physics-constrained, data-driven discovery of coarse-grained dynamics | The combination of high-dimensionality and disparity of time scales
encountered in many problems in computational physics has motivated the
development of coarse-grained (CG) models. In this paper, we advocate the
paradigm of data-driven discovery for extract- ing governing equations by
employing fine-scale simulation data. In particular, we cast the
coarse-graining process under a probabilistic state-space model where the
transition law dic- tates the evolution of the CG state variables and the
emission law the coarse-to-fine map. The directed probabilistic graphical model
implied, suggests that given values for the fine- grained (FG) variables,
probabilistic inference tools must be employed to identify the cor- responding
values for the CG states and to that end, we employ Stochastic Variational In-
ference. We advocate a sparse Bayesian learning perspective which avoids
overfitting and reveals the most salient features in the CG evolution law. The
formulation adopted enables the quantification of a crucial, and often
neglected, component in the CG process, i.e. the pre- dictive uncertainty due
to information loss. Furthermore, it is capable of reconstructing the evolution
of the full, fine-scale system. We demonstrate the efficacy of the proposed
frame- work in high-dimensional systems of random walkers.
| physics.comp-ph stat.ML | the combination of highdimensionality and disparity of time scales encountered in many problems in computational physics has motivated the development of coarsegrained cg models in this paper we advocate the paradigm of datadriven discovery for extract ing governing equations by employing finescale simulation data in particular we cast the coarsegraining process under a probabilistic statespace model where the transition law dic tates the evolution of the cg state variables and the emission law the coarsetofine map the directed probabilistic graphical model implied suggests that given values for the fine grained fg variables probabilistic inference tools must be employed to identify the cor responding values for the cg states and to that end we employ stochastic variational in ference we advocate a sparse bayesian learning perspective which avoids overfitting and reveals the most salient features in the cg evolution law the formulation adopted enables the quantification of a crucial and often neglected component in the cg process ie the pre dictive uncertainty due to information loss furthermore it is capable of reconstructing the evolution of the full finescale system we demonstrate the efficacy of the proposed frame work in highdimensional systems of random walkers | [['the', 'combination', 'of', 'highdimensionality', 'and', 'disparity', 'of', 'time', 'scales', 'encountered', 'in', 'many', 'problems', 'in', 'computational', 'physics', 'has', 'motivated', 'the', 'development', 'of', 'coarsegrained', 'cg', 'models', 'in', 'this', 'paper', 'we', 'advocate', 'the', 'paradigm', 'of', 'datadriven', 'discovery', 'for', 'extract', 'ing', 'governing', 'equations', 'by', 'employing', 'finescale', 'simulation', 'data', 'in', 'particular', 'we', 'cast', 'the', 'coarsegraining', 'process', 'under', 'a', 'probabilistic', 'statespace', 'model', 'where', 'the', 'transition', 'law', 'dic', 'tates', 'the', 'evolution', 'of', 'the', 'cg', 'state', 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1,802.03825 | Decentralized Submodular Maximization: Bridging Discrete and Continuous
Settings | In this paper, we showcase the interplay between discrete and continuous
optimization in network-structured settings. We propose the first fully
decentralized optimization method for a wide class of non-convex objective
functions that possess a diminishing returns property. More specifically, given
an arbitrary connected network and a global continuous submodular function,
formed by a sum of local functions, we develop Decentralized Continuous Greedy
(DCG), a message passing algorithm that converges to the tight (1-1/e)
approximation factor of the optimum global solution using only local
computation and communication. We also provide strong convergence bounds as a
function of network size and spectral characteristics of the underlying
topology. Interestingly, DCG readily provides a simple recipe for decentralized
discrete submodular maximization through the means of continuous relaxations.
Formally, we demonstrate that by lifting the local discrete functions to
continuous domains and using DCG as an interface we can develop a consensus
algorithm that also achieves the tight (1-1/e) approximation guarantee of the
global discrete solution once a proper rounding scheme is applied.
| math.OC | in this paper we showcase the interplay between discrete and continuous optimization in networkstructured settings we propose the first fully decentralized optimization method for a wide class of nonconvex objective functions that possess a diminishing returns property more specifically given an arbitrary connected network and a global continuous submodular function formed by a sum of local functions we develop decentralized continuous greedy dcg a message passing algorithm that converges to the tight 11e approximation factor of the optimum global solution using only local computation and communication we also provide strong convergence bounds as a function of network size and spectral characteristics of the underlying topology interestingly dcg readily provides a simple recipe for decentralized discrete submodular maximization through the means of continuous relaxations formally we demonstrate that by lifting the local discrete functions to continuous domains and using dcg as an interface we can develop a consensus algorithm that also achieves the tight 11e approximation guarantee of the global discrete solution once a proper rounding scheme is applied | [['in', 'this', 'paper', 'we', 'showcase', 'the', 'interplay', 'between', 'discrete', 'and', 'continuous', 'optimization', 'in', 'networkstructured', 'settings', 'we', 'propose', 'the', 'first', 'fully', 'decentralized', 'optimization', 'method', 'for', 'a', 'wide', 'class', 'of', 'nonconvex', 'objective', 'functions', 'that', 'possess', 'a', 'diminishing', 'returns', 'property', 'more', 'specifically', 'given', 'an', 'arbitrary', 'connected', 'network', 'and', 'a', 'global', 'continuous', 'submodular', 'function', 'formed', 'by', 'a', 'sum', 'of', 'local', 'functions', 'we', 'develop', 'decentralized', 'continuous', 'greedy', 'dcg', 'a', 'message', 'passing', 'algorithm', 'that', 'converges', 'to', 'the', 'tight', '11e', 'approximation', 'factor', 'of', 'the', 'optimum', 'global', 'solution', 'using', 'only', 'local', 'computation', 'and', 'communication', 'we', 'also', 'provide', 'strong', 'convergence', 'bounds', 'as', 'a', 'function', 'of', 'network', 'size', 'and', 'spectral', 'characteristics', 'of', 'the', 'underlying', 'topology', 'interestingly', 'dcg', 'readily', 'provides', 'a', 'simple', 'recipe', 'for', 'decentralized', 'discrete', 'submodular', 'maximization', 'through', 'the', 'means', 'of', 'continuous', 'relaxations', 'formally', 'we', 'demonstrate', 'that', 'by', 'lifting', 'the', 'local', 'discrete', 'functions', 'to', 'continuous', 'domains', 'and', 'using', 'dcg', 'as', 'an', 'interface', 'we', 'can', 'develop', 'a', 'consensus', 'algorithm', 'that', 'also', 'achieves', 'the', 'tight', '11e', 'approximation', 'guarantee', 'of', 'the', 'global', 'discrete', 'solution', 'once', 'a', 'proper', 'rounding', 'scheme', 'is', 'applied']] | [-0.13980771172420992, -0.0211631749565034, -0.12019389975882534, 0.09643929137659836, -0.08640037739228103, -0.15846647963570876, 0.11377037147827823, 0.4357361431189236, -0.3482772625117962, -0.26136349197345443, 0.087808346134677, -0.16905058969167017, -0.22800812700353118, 0.13605070273236683, -0.060121191742967185, 0.09388180979571882, 0.02530458947599289, -0.028812458767788485, -0.10121959562197194, -0.2593817696282973, 0.2663837009417226, 0.031052916427142918, 0.28547275785378934, 0.05361391672132803, 0.15605347838122507, 0.050411655980583635, 0.03177982704281541, 0.06804585660124542, -0.12942564566054943, 0.1253518600008517, 0.24735604953353427, 0.2080911208800639, 0.36796882044429713, -0.4070448504006934, -0.1570781691365742, 0.14080282763045812, 0.13177625593102893, 0.07588396152312357, -0.0725658237273213, -0.23501282973198354, 0.11998534378584563, -0.1701473256384599, -0.05759109549468294, -0.1169610301842026, -0.04046504369970145, 0.06393729724610846, -0.3632873551520918, 0.06113363438461896, 0.06923211504527856, 0.00017884870855292925, -0.07908645767643716, -0.06124139276965122, 0.009312373128653104, 0.09708694852833148, -0.016194302745307573, 0.05623286441619885, 0.10729915992262595, -0.07162482463726996, -0.1512340041046541, 0.3454826816145907, -0.07768081064153064, -0.2337068895470847, 0.16526924717167968, -0.04791017901706731, -0.14728960168126615, 0.1485608276977603, 0.22631213600592068, 0.16771484002293574, -0.1671770454794612, 0.09937174181028413, -0.1182319365685717, 0.1734829454674452, 0.0173110263228106, 0.03290448003515069, 0.10106845370319206, 0.1766525322732161, 0.23775421698865967, 0.18225875582789913, 0.003022732841297208, -0.13504071179444768, -0.28957484917399207, -0.11520347806037448, -0.22445136684525227, 0.016355657234920988, -0.15152476651348393, -0.17717817517682088, 0.4145065774896466, 0.09025360323721543, 0.17950630353741526, 0.1688249081933117, 0.31350432328569394, 0.1547306334153594, 0.0062225846067165205, 0.15149276608246423, 0.19328742341964417, 0.0773334167592804, 0.06387047791178616, -0.17301442295761912, 0.10768807607625301, 0.115494998152523] |
1,802.03826 | Model-independent constraints on dark matter annihilation in dwarf
spheroidal galaxies | We present a general, model-independent formalism for determining bounds on
the production of photons in dwarf spheroidal galaxies via dark matter
annihilation, applicable to any set of assumptions about dark matter particle
physics or astrophysics. As an illustration, we analyze gamma-ray data from the
Fermi Large Area Telescope to constrain a variety of nonstandard dark matter
models, several of which have not previously been studied in the context of
dwarf galaxy searches.
| hep-ph astro-ph.HE hep-ex | we present a general modelindependent formalism for determining bounds on the production of photons in dwarf spheroidal galaxies via dark matter annihilation applicable to any set of assumptions about dark matter particle physics or astrophysics as an illustration we analyze gammaray data from the fermi large area telescope to constrain a variety of nonstandard dark matter models several of which have not previously been studied in the context of dwarf galaxy searches | [['we', 'present', 'a', 'general', 'modelindependent', 'formalism', 'for', 'determining', 'bounds', 'on', 'the', 'production', 'of', 'photons', 'in', 'dwarf', 'spheroidal', 'galaxies', 'via', 'dark', 'matter', 'annihilation', 'applicable', 'to', 'any', 'set', 'of', 'assumptions', 'about', 'dark', 'matter', 'particle', 'physics', 'or', 'astrophysics', 'as', 'an', 'illustration', 'we', 'analyze', 'gammaray', 'data', 'from', 'the', 'fermi', 'large', 'area', 'telescope', 'to', 'constrain', 'a', 'variety', 'of', 'nonstandard', 'dark', 'matter', 'models', 'several', 'of', 'which', 'have', 'not', 'previously', 'been', 'studied', 'in', 'the', 'context', 'of', 'dwarf', 'galaxy', 'searches']] | [-0.04390048085608416, 0.10707460798686144, -0.14465442433073702, 0.20604975855288407, -0.17825693866082779, -0.07916871896142968, -0.01155916656069975, 0.3031383570697572, -0.1463070291534273, -0.4183505888407429, 0.010964317328115512, -0.26194330987830955, -0.006068405090546649, 0.2715889199995824, 0.024436991299606033, 0.025167380123295717, 0.03338301104703431, -0.029284145909413282, -0.043228395800623626, -0.2789493018838887, 0.3317058507560028, 0.06222641158900741, 0.1567151262521899, 0.017707226002433647, 0.0811826292532108, -0.01730929102308841, -0.10704160736107345, -0.08127977880131868, -0.2133122255585881, 0.036798195434837706, 0.25779966844680124, 0.13028552801309465, 0.1479321811574563, -0.4197350006757511, -0.2615122474445444, 0.22069753828044567, 0.18829651744777542, 0.08898439468369664, -0.14613404414881692, -0.3492161108491321, 0.01467702579611796, -0.24008070467971265, -0.13278089051729897, -0.022245739554313734, 0.011385609424905851, 0.008086080792256527, -0.17908174915161604, 0.07170297144653483, -0.007608403257715206, -0.0011897093920399332, -0.08413601931533776, -0.11137995661152268, 0.038908486120312266, -0.011197609377429925, 0.07323908983057158, -0.014352978802182607, 0.22584484744584188, -0.2191339261027881, -0.07272284718540807, 0.45171403595142895, -0.11528350756270811, -0.09114713911225812, 0.22376275992590106, -0.16533277057007784, -0.2357779188379128, 0.07973161319063769, 0.23369878789203036, 0.08832298502481233, -0.2328081919113174, 0.16571068105986342, -0.07793010590830818, 0.16199207520306422, 0.03926587544588579, 0.07321360402278919, 0.345567368540085, 0.18389302933226442, 0.06489362957331145, 0.030226195780819073, -0.18499222349297875, -0.04039919349209716, -0.33257525026177365, -0.14730689438516087, -0.1843012841547736, 0.04770747753617696, -0.05398848053300753, -0.12274850752146449, 0.35665552380184334, 0.08057023397931415, 0.19003099657129496, -0.0023864570911326963, 0.30526603466003305, 0.04060635460599668, 0.05515265232598823, 0.057730823561238744, 0.3358322592232273, 0.16134978684648457, 0.0497266616504122, -0.17616401965885112, 0.003849121683742851, -0.01824567703685413] |
1,802.03827 | Successive Convexification for 6-DoF Mars Rocket Powered Landing with
Free-Final-Time | In this paper, we employ successive convexification to solve the minimum-time
6-DoF rocket powered landing problem. The contribution of this paper is the
development and demonstration of a free-final-time problem formulation that can
be solved iteratively using a successive convexification framework. This paper
is an extension of our previous work on the 3-DoF free-final-time and the 6-DoF
fixed-final-time minimum-fuel problems. Herein, the vehicle is modeled as a
6-DoF rigid-body controlled by a single gimbaled rocket engine. The trajectory
is subject to a variety of convex and non-convex state- and
control-constraints, and aerodynamic effects are assumed negligible. The
objective of the problem is to determine the optimal thrust commands that will
minimize the time-of-flight while satisfying the aforementioned constraints.
Solving this problem quickly and reliably is challenging because (a) it is
nonlinear and non-convex, (b) the validity of the solution is heavily dependent
on the accuracy of the discretization scheme, and (c) it can be difficult to
select a suitable reference trajectory to initialize an iterative solution
process. To deal with these issues, our algorithm (a) uses successive
convexification to eliminate non-convexities, (b) computes the discrete
linear-time-variant system matrices to ensure that the converged solution
perfectly satisfies the original nonlinear dynamics, and (c) can be initialized
with a simple, dynamically inconsistent reference trajectory. Using the
proposed convex formulation and successive convexification framework, we are
able to convert the original non-convex problem into a sequence of convex
second-order cone programming (SOCP) sub-problems. Through the use of Interior
Point Method (IPM) solvers, this sequence can be solved quickly and reliably,
thus enabling higher fidelity real-time guidance for rocket powered landings on
Mars.
| math.OC | in this paper we employ successive convexification to solve the minimumtime 6dof rocket powered landing problem the contribution of this paper is the development and demonstration of a freefinaltime problem formulation that can be solved iteratively using a successive convexification framework this paper is an extension of our previous work on the 3dof freefinaltime and the 6dof fixedfinaltime minimumfuel problems herein the vehicle is modeled as a 6dof rigidbody controlled by a single gimbaled rocket engine the trajectory is subject to a variety of convex and nonconvex state and controlconstraints and aerodynamic effects are assumed negligible the objective of the problem is to determine the optimal thrust commands that will minimize the timeofflight while satisfying the aforementioned constraints solving this problem quickly and reliably is challenging because a it is nonlinear and nonconvex b the validity of the solution is heavily dependent on the accuracy of the discretization scheme and c it can be difficult to select a suitable reference trajectory to initialize an iterative solution process to deal with these issues our algorithm a uses successive convexification to eliminate nonconvexities b computes the discrete lineartimevariant system matrices to ensure that the converged solution perfectly satisfies the original nonlinear dynamics and c can be initialized with a simple dynamically inconsistent reference trajectory using the proposed convex formulation and successive convexification framework we are able to convert the original nonconvex problem into a sequence of convex secondorder cone programming socp subproblems through the use of interior point method ipm solvers this sequence can be solved quickly and reliably thus enabling higher fidelity realtime guidance for rocket powered landings on mars | [['in', 'this', 'paper', 'we', 'employ', 'successive', 'convexification', 'to', 'solve', 'the', 'minimumtime', '6dof', 'rocket', 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1,802.03828 | New Models for Generating Hard Random Boolean Formulas and Disjunctive
Logic Programs | We propose two models of random quantified boolean formulas and their natural
random disjunctive logic program counterparts. The models extend the standard
models of random k-CNF formulas and the Chen-Interian model of random 2QBFs.
The first model controls the generation of programs and QSAT formulas by
imposing a specific structure on rules and clauses, respectively. The second
model is based on a family of QSAT formulas in a non-clausal form. We provide
theoretical bounds for the phase transition region in our models, and show
experimentally the presence of the easy-hard-easy pattern and its alignment
with the location of the phase transition. We show that boolean formulas and
logic programs from our models are significantly harder than those obtained
from the standard k-CNF and Chen-Interian models, and that their combination
yields formulas and programs that are "super-hard" to evaluate. We also provide
evidence suggesting that formulas from one of our models are well suited for
assessing solvers tuned to real-world instances. Finally, it is noteworthy
that, to the best of our knowledge, our models and results on random
disjunctive logic programs are the first of their kind.
| cs.LO | we propose two models of random quantified boolean formulas and their natural random disjunctive logic program counterparts the models extend the standard models of random kcnf formulas and the cheninterian model of random 2qbfs the first model controls the generation of programs and qsat formulas by imposing a specific structure on rules and clauses respectively the second model is based on a family of qsat formulas in a nonclausal form we provide theoretical bounds for the phase transition region in our models and show experimentally the presence of the easyhardeasy pattern and its alignment with the location of the phase transition we show that boolean formulas and logic programs from our models are significantly harder than those obtained from the standard kcnf and cheninterian models and that their combination yields formulas and programs that are superhard to evaluate we also provide evidence suggesting that formulas from one of our models are well suited for assessing solvers tuned to realworld instances finally it is noteworthy that to the best of our knowledge our models and results on random disjunctive logic programs are the first of their kind | [['we', 'propose', 'two', 'models', 'of', 'random', 'quantified', 'boolean', 'formulas', 'and', 'their', 'natural', 'random', 'disjunctive', 'logic', 'program', 'counterparts', 'the', 'models', 'extend', 'the', 'standard', 'models', 'of', 'random', 'kcnf', 'formulas', 'and', 'the', 'cheninterian', 'model', 'of', 'random', '2qbfs', 'the', 'first', 'model', 'controls', 'the', 'generation', 'of', 'programs', 'and', 'qsat', 'formulas', 'by', 'imposing', 'a', 'specific', 'structure', 'on', 'rules', 'and', 'clauses', 'respectively', 'the', 'second', 'model', 'is', 'based', 'on', 'a', 'family', 'of', 'qsat', 'formulas', 'in', 'a', 'nonclausal', 'form', 'we', 'provide', 'theoretical', 'bounds', 'for', 'the', 'phase', 'transition', 'region', 'in', 'our', 'models', 'and', 'show', 'experimentally', 'the', 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0.12852116260433294, 0.064507026998886, -0.15784731970688384, 0.14817313644577002, 0.051754113046269194] |
1,802.03829 | Smale Strategies For The N-Person Iterated Prisoner's Dilemma | Adapting methods introduced by Steven Smale, we describe good strategies for
a symmetric version of the Iterated Prisoner's Dilemma with n players.
| math.DS cs.GT | adapting methods introduced by steven smale we describe good strategies for a symmetric version of the iterated prisoners dilemma with n players | [['adapting', 'methods', 'introduced', 'by', 'steven', 'smale', 'we', 'describe', 'good', 'strategies', 'for', 'a', 'symmetric', 'version', 'of', 'the', 'iterated', 'prisoners', 'dilemma', 'with', 'n', 'players']] | [-0.07852385684170506, 0.05858417668125846, -0.17143507005477493, 0.14894396083598788, -0.0017139495943080294, -0.3025864972838793, 0.0751850429753011, 0.3680217557332732, -0.1850294154137373, -0.25054919203235343, 0.032565321709791366, -0.20894171179018237, -0.2636423529316248, 0.018787155012515457, -0.2637153608639809, 0.011671805838969622, 0.08774430888958952, -0.08953117075460879, 0.06462656198577447, -0.39079564496536146, 0.4099343949082223, 0.06814941145818341, 0.1827695435759696, -0.06147341565652327, 0.1344959195703268, 0.1535291659476405, -0.10237478625706652, 0.11170405359007418, -0.2335824071937664, 0.06082362063567747, 0.2840922821990468, 0.1344992033290592, 0.43601797275583853, -0.3495198842138052, -0.10659599240699952, 0.20402851747348905, 0.141961605923081, 0.07243873576887629, -0.013942129063335333, -0.3901118486696346, 0.04488341793925925, -0.2727417978034778, -0.18294858418151058, -0.08709313919429075, 0.015378506854176521, 0.053476677276194096, -0.31829536299813876, -0.08727841307832436, 0.0731309308162467, 0.13402924250642007, -0.0059257310984486885, -0.1390899782153693, 0.052053978497331795, 0.1294139092576436, 0.009260796349156986, -0.0646250638475811, 0.06444493107582358, -0.09061922708695586, -0.3648217696357857, 0.3526840342039412, -0.11094336939806287, -0.1968041809106415, 0.0900279421528632, -0.02420143192549321, -0.11714656062593515, 0.0398604969853874, 0.024415506049990654, 0.21224753653884612, -0.08018397505987775, 0.1346173161132769, -0.13353227735073728, 0.08878302110083909, 0.14044274117755282, -0.05191260506398976, 0.03236384821039709, 0.17712844252078372, 0.1424919556276026, 0.083717125213959, 0.11234423839910464, -0.3061725553125143, -0.17531449838795446, -0.09834130197255449, -0.09371593143706294, 0.06619895334270867, -0.112098449354314, -0.08345639248463241, 0.3228612140837041, 0.050655989315022125, 0.10881786088628526, 0.14622025560079652, 0.24381562386935746, 0.0007629324682056904, -0.0010427948595447974, 0.06804657460783016, 0.11452645215798508, 0.13296281378081237, 0.13844487583264709, -0.2203187714330852, 0.06648378088985654, 0.27054896767103026] |
1,802.0383 | Distributed Stochastic Multi-Task Learning with Graph Regularization | We propose methods for distributed graph-based multi-task learning that are
based on weighted averaging of messages from other machines. Uniform averaging
or diminishing stepsize in these methods would yield consensus (single task)
learning. We show how simply skewing the averaging weights or controlling the
stepsize allows learning different, but related, tasks on the different
machines.
| stat.ML cs.LG | we propose methods for distributed graphbased multitask learning that are based on weighted averaging of messages from other machines uniform averaging or diminishing stepsize in these methods would yield consensus single task learning we show how simply skewing the averaging weights or controlling the stepsize allows learning different but related tasks on the different machines | [['we', 'propose', 'methods', 'for', 'distributed', 'graphbased', 'multitask', 'learning', 'that', 'are', 'based', 'on', 'weighted', 'averaging', 'of', 'messages', 'from', 'other', 'machines', 'uniform', 'averaging', 'or', 'diminishing', 'stepsize', 'in', 'these', 'methods', 'would', 'yield', 'consensus', 'single', 'task', 'learning', 'we', 'show', 'how', 'simply', 'skewing', 'the', 'averaging', 'weights', 'or', 'controlling', 'the', 'stepsize', 'allows', 'learning', 'different', 'but', 'related', 'tasks', 'on', 'the', 'different', 'machines']] | [-0.0751701800787652, 0.10597528161650355, -0.10759725387800824, 0.05759321144697341, -0.15642293503677304, -0.26180262289602646, 0.10240299339321526, 0.5302818752147934, -0.3403889658098871, -0.2730825901073827, 0.05568098335061222, -0.1866873789284992, -0.1174111740578982, 0.1885194993747229, -0.16337422423742035, 0.10252976563166488, 0.11551396245644852, 0.07593108447776599, -0.09630565102720125, -0.34093255746093665, 0.3538985957497392, -0.00048323487862944603, 0.368529058417136, -0.04008257472040978, 0.12909153108855456, 0.03960276267237284, -0.057767170498316936, 0.008838086185807531, -0.04977166311119535, 0.16631185419180178, 0.2852520646019415, 0.22101670459590175, 0.4064528857611797, -0.39566491652618757, -0.2194977872412313, 0.1592160111462528, 0.20639700568704442, 0.11072732071307573, -0.0036153017500923437, -0.27827659510076047, 0.054209163285453214, -0.11272598344155334, 0.06651747902347283, -0.19960040354000574, -0.10855320023203438, 0.09577953490343961, -0.31342154842886055, 0.06836514821784064, 0.09143549305471507, 0.061416516935622154, -0.07037511136996645, -0.19953154355118222, 0.11100577212531458, 0.13470418620431288, 0.05102510391311212, -0.0051390821706842294, 0.21360131097449497, -0.10371225792914629, -0.21711580451916565, 0.329888126660477, -0.03050896926275031, -0.23569067739299498, 0.1866029613947665, 0.05131249129772186, -0.17753485795957122, 0.03847278681668368, 0.26594019992785023, 0.18713781725276601, -0.13001128719611602, -0.022708736427805642, -0.012076995860446584, 0.1609374239194122, 0.05114115626466545, -0.01411568768830462, 0.12407030105929483, 0.19094804535535248, 0.11946578300981359, 0.08198685414178974, -0.10477328183637424, -0.14576262755488809, -0.2147495218298652, -0.05738665347664871, -0.20268408803438598, 0.020867010790177366, -0.16709934441711416, -0.15411801534620198, 0.33564195666800845, 0.21251250225203958, 0.197891845444048, 0.18049538206647742, 0.3302686598151922, 0.0810461098836227, 0.14889776229181073, 0.15642207898517055, 0.17077032219279897, 0.0018861173059452664, 0.11374214952176606, -0.2122228320476345, 0.1242405978708782, 0.07861474076793952] |
1,802.03831 | Algorithmic Randomness For Amenable Groups | We develop the theory of algorithmic randomness for the space $A^G$ where $A$
is a finite alphabet and $G$ is a computable amenable group. We give an
effective version of the Shannon-McMillan-Breiman theorem in this setting. We
also extend a result of Simpson equating topological entropy and Hausdorff
dimension. This proof makes use of work of Ornstein and Weiss which we also
present.
| math.LO | we develop the theory of algorithmic randomness for the space ag where a is a finite alphabet and g is a computable amenable group we give an effective version of the shannonmcmillanbreiman theorem in this setting we also extend a result of simpson equating topological entropy and hausdorff dimension this proof makes use of work of ornstein and weiss which we also present | [['we', 'develop', 'the', 'theory', 'of', 'algorithmic', 'randomness', 'for', 'the', 'space', 'ag', 'where', 'a', 'is', 'a', 'finite', 'alphabet', 'and', 'g', 'is', 'a', 'computable', 'amenable', 'group', 'we', 'give', 'an', 'effective', 'version', 'of', 'the', 'shannonmcmillanbreiman', 'theorem', 'in', 'this', 'setting', 'we', 'also', 'extend', 'a', 'result', 'of', 'simpson', 'equating', 'topological', 'entropy', 'and', 'hausdorff', 'dimension', 'this', 'proof', 'makes', 'use', 'of', 'work', 'of', 'ornstein', 'and', 'weiss', 'which', 'we', 'also', 'present']] | [-0.11944008198019768, 0.12393240581311854, -0.17982852830743742, 0.1055478041193315, -0.10408741813744345, -0.10914544533524248, 0.13072694860406162, 0.31341792983076877, -0.27615111545171767, -0.19187116111436534, 0.10204467293529194, -0.2313109864850366, -0.17985237531718754, 0.20397021540159743, -0.18104968746266667, -0.01819296722256002, 0.003284923820978119, 0.06331876062211536, -0.05226846443607457, -0.28203797588745755, 0.35323819648178795, -0.00987397123956018, 0.21216231189845575, 0.12569226626129376, 0.10836510638159419, 0.049914789587510604, -0.04612495503314431, 0.04054151904826526, -0.21960471174310123, 0.20414082933631209, 0.25554804498004535, 0.11273897680572219, 0.27624921154763016, -0.30341890826821327, -0.19576560221760284, 0.12131811750106632, 0.10050903613279973, 0.13557599128467873, -0.04100684447598363, -0.2569969313012229, 0.11354992204781858, -0.22349998137603203, -0.12874145930012068, -0.0965761122042461, 0.06548200875875496, -0.0595276104581971, -0.2727798699504799, 0.05368414344238339, 0.17402273465302728, 0.1268023665521353, -0.027973122687803373, -0.04058655526577717, 0.04449226858005637, 0.07690421747420692, 0.003851724256362234, 0.060146249483324705, 0.05638003279085434, -0.0046814667016622565, -0.13616852555423975, 0.3407201379877589, -0.09613734928684102, -0.1977239967183402, 0.1748463967741127, -0.10510425973269674, -0.17825884743046666, 0.0496143453481001, 0.11390008119356242, 0.17741242374130894, -0.07043495663397369, 0.2161300940899223, -0.12462757777659193, 0.16154637803427047, 0.06774062327744942, 0.038035053331109264, 0.059649383545749717, 0.14570280708860428, 0.13190314327440564, 0.2250779266690924, 0.0016321528126441297, -0.013017888143954296, -0.3522134122276117, -0.23400984722233953, -0.20419795473017507, 0.1028307606244371, -0.10165046629914459, -0.20127083672328838, 0.3573529565899027, 0.15714583697447937, 0.15534812207555487, 0.15912006224971265, 0.23259233801610887, 0.12100581128505014, -0.048385499843529294, 0.10142947603312749, 0.12465303408957663, 0.22450056210869834, 0.041843891742506197, -0.13988796467818912, 0.011146585035714366, 0.22763345291512826] |
1,802.03832 | Quadrature-based features for kernel approximation | We consider the problem of improving kernel approximation via randomized
feature maps. These maps arise as Monte Carlo approximation to integral
representations of kernel functions and scale up kernel methods for larger
datasets. Based on an efficient numerical integration technique, we propose a
unifying approach that reinterprets the previous random features methods and
extends to better estimates of the kernel approximation. We derive the
convergence behaviour and conduct an extensive empirical study that supports
our hypothesis.
| cs.LG stat.ML | we consider the problem of improving kernel approximation via randomized feature maps these maps arise as monte carlo approximation to integral representations of kernel functions and scale up kernel methods for larger datasets based on an efficient numerical integration technique we propose a unifying approach that reinterprets the previous random features methods and extends to better estimates of the kernel approximation we derive the convergence behaviour and conduct an extensive empirical study that supports our hypothesis | [['we', 'consider', 'the', 'problem', 'of', 'improving', 'kernel', 'approximation', 'via', 'randomized', 'feature', 'maps', 'these', 'maps', 'arise', 'as', 'monte', 'carlo', 'approximation', 'to', 'integral', 'representations', 'of', 'kernel', 'functions', 'and', 'scale', 'up', 'kernel', 'methods', 'for', 'larger', 'datasets', 'based', 'on', 'an', 'efficient', 'numerical', 'integration', 'technique', 'we', 'propose', 'a', 'unifying', 'approach', 'that', 'reinterprets', 'the', 'previous', 'random', 'features', 'methods', 'and', 'extends', 'to', 'better', 'estimates', 'of', 'the', 'kernel', 'approximation', 'we', 'derive', 'the', 'convergence', 'behaviour', 'and', 'conduct', 'an', 'extensive', 'empirical', 'study', 'that', 'supports', 'our', 'hypothesis']] | [-0.03962070705663217, -0.04842545498602129, -0.15990036314255313, 0.1258999184693063, -0.07039575430711634, -0.0862793658069629, 0.07472242332847887, 0.4451943197483687, -0.26852177279866546, -0.26755541400052607, 0.10438071826080743, -0.27304943709781293, -0.19422611282942326, 0.24189430025657394, 0.0037197602643190245, 0.11885168708517756, 0.11327779195026348, -0.0818468593168195, -0.1418202971659699, -0.2469423120951672, 0.3227590783254096, 0.10178738046976689, 0.2936790187009855, 0.027447646318346654, 0.14257373678571494, 0.003216931939517197, -0.0949562917996541, -0.03504788973613789, -0.14431623200748858, 0.17770966990256534, 0.2239355432623262, 0.1514785707266511, 0.3266696401988156, -0.421809702180326, -0.24091289095629595, 0.10865650327238989, 0.16432136212671666, 0.07062953433782432, -0.023693291551592808, -0.27486406505647065, 0.06608806179505528, -0.14914089263612895, -0.09645050166689448, -0.19958401319117433, -0.0833649996998965, 0.024047840835440804, -0.3456098015273088, 0.09132830139347597, 0.07789425276170828, 0.05315195150232237, -0.05977966500397183, -0.1522674248982711, 0.1485086440776573, 0.09751614413567279, 0.022100576594790543, 0.042387165597909574, 0.09917357737370032, -0.0957295412540828, -0.16739558908892305, 0.2935927561851905, -0.12045316376086128, -0.2295489601398769, 0.2059748415302142, -0.05940298451796958, -0.16063504342577958, 0.10767401546533954, 0.19851788054955632, 0.18323785976175905, -0.12351995020320541, 0.10161179560619578, -0.06950839847865466, 0.11560281981579273, -0.028974387034969896, -0.028989735868220266, 0.057387541440364565, 0.18261986679250472, 0.10108523075713922, 0.18163123354315758, -0.08244951842904188, -0.13781449248352529, -0.2703752606420925, -0.12953279210303567, -0.19465817526705856, -0.0069894083824596906, -0.17731710502477271, -0.2213339811852692, 0.35740791221982554, 0.24990567042933484, 0.20962073770351708, 0.1580230363914253, 0.3212064354141292, 0.14303199834141292, 0.05784663701380946, 0.11158515928974866, 0.13832415369535356, 0.10223511600327727, 0.030989160117889315, -0.18676834819856786, 0.03997799122436462, 0.16249212773982435] |
1,802.03833 | New geometric and field theoretic aspects of a radiation dominated
universe | The homogeneous and isotropic radiation dominated universe, following the
inflationary stage, is expressed as a spherically symmetric and inhomogeneous
spacetime upon a power law type conformal transformation of the null
(cosmological) coordinates. This new spacetime metric has many interesting
properties. While the static observers, at a fixed position in this new
spacetime, do not see any horizon, some non-static observers encounter a
horizon due to their motion which is analogous to the situation of Rindler
observers in Minkowski spacetime. The symmetry of the new metric offers a
unitarily inequivalent quantization of the massless scalar field and provides a
new example of particle creation. We calculate the particle content of the
cosmological vacuum state with respect to the static observer in this new
spacetime who, with respect to cosmological time, is freely falling in
asymptotic past and future but accelerated in between.
| gr-qc astro-ph.CO hep-th | the homogeneous and isotropic radiation dominated universe following the inflationary stage is expressed as a spherically symmetric and inhomogeneous spacetime upon a power law type conformal transformation of the null cosmological coordinates this new spacetime metric has many interesting properties while the static observers at a fixed position in this new spacetime do not see any horizon some nonstatic observers encounter a horizon due to their motion which is analogous to the situation of rindler observers in minkowski spacetime the symmetry of the new metric offers a unitarily inequivalent quantization of the massless scalar field and provides a new example of particle creation we calculate the particle content of the cosmological vacuum state with respect to the static observer in this new spacetime who with respect to cosmological time is freely falling in asymptotic past and future but accelerated in between | [['the', 'homogeneous', 'and', 'isotropic', 'radiation', 'dominated', 'universe', 'following', 'the', 'inflationary', 'stage', 'is', 'expressed', 'as', 'a', 'spherically', 'symmetric', 'and', 'inhomogeneous', 'spacetime', 'upon', 'a', 'power', 'law', 'type', 'conformal', 'transformation', 'of', 'the', 'null', 'cosmological', 'coordinates', 'this', 'new', 'spacetime', 'metric', 'has', 'many', 'interesting', 'properties', 'while', 'the', 'static', 'observers', 'at', 'a', 'fixed', 'position', 'in', 'this', 'new', 'spacetime', 'do', 'not', 'see', 'any', 'horizon', 'some', 'nonstatic', 'observers', 'encounter', 'a', 'horizon', 'due', 'to', 'their', 'motion', 'which', 'is', 'analogous', 'to', 'the', 'situation', 'of', 'rindler', 'observers', 'in', 'minkowski', 'spacetime', 'the', 'symmetry', 'of', 'the', 'new', 'metric', 'offers', 'a', 'unitarily', 'inequivalent', 'quantization', 'of', 'the', 'massless', 'scalar', 'field', 'and', 'provides', 'a', 'new', 'example', 'of', 'particle', 'creation', 'we', 'calculate', 'the', 'particle', 'content', 'of', 'the', 'cosmological', 'vacuum', 'state', 'with', 'respect', 'to', 'the', 'static', 'observer', 'in', 'this', 'new', 'spacetime', 'who', 'with', 'respect', 'to', 'cosmological', 'time', 'is', 'freely', 'falling', 'in', 'asymptotic', 'past', 'and', 'future', 'but', 'accelerated', 'in', 'between']] | [-0.15055711032882174, 0.15861600304207374, -0.14667053136921732, 0.05969138839818762, -0.13055965837573383, -0.16673871072286622, -0.04564194786791683, 0.3499726405935296, -0.2091852372499011, -0.24592625343237495, 0.06343510837033259, -0.2526104131462515, -0.062100876882302425, 0.11853550532618075, -0.08003363883162433, 0.020192607660143774, -0.02330368466127056, 0.09336285094948525, -0.09495242910809709, -0.22540843173372724, 0.371876629148709, 0.1432331381167503, 0.26033383374373226, -0.051458470784259816, 0.140749671103446, -0.0007023411036753063, -0.04670508278877283, 0.07331503909213323, -0.12476917964729137, 0.04685620027462166, 0.19559248557301068, 0.13799342074504134, 0.22688942591507807, -0.3926365344474713, -0.22130354363735474, 0.13427070175885414, 0.154427468624785, 0.17508033384050486, -0.08799707986487089, -0.33021855299486547, 0.011501795197391208, -0.1683188438983568, -0.1954020209121683, -0.021361594768703408, 0.03620569035163189, -0.05992152450436145, -0.19343329973333906, 0.1084827482255276, 0.04784563525434557, -0.014976342948457452, -0.12693664481275524, -0.00129908616555498, 0.013643601296654513, 0.09195052467762156, 0.13299952973017193, 0.0607331944365345, 0.14080316549355282, -0.11039374504363865, -0.09897246776587917, 0.41303037549534166, -0.06384562413003428, -0.24211216810430194, 0.15834593593228793, -0.2064651115103922, -0.08491794615719758, 0.09728664463775642, 0.15356105392805386, 0.15150033299926155, -0.16435128681573039, 0.16756683171079462, 0.007624491190551021, 0.11382237565786255, 0.13916418394932512, 0.0426188635355826, 0.30264742275805656, 0.03968080355874956, 0.07295410264925767, 0.13701901493712942, 0.006016907460511999, -0.1470334200479143, -0.4023994325267164, -0.2057239948672817, -0.15174610398590882, 0.10921509314920004, -0.19750088086006634, -0.2169414543685444, 0.36497055913539644, 0.11565817264558877, 0.14567854893823148, 0.01001802338567952, 0.24636007826907416, 0.051867878076897814, 0.004071725273161387, 0.132762043865675, 0.28882798490280465, 0.08141512478576272, 0.1621033292080454, -0.19877785496770384, -0.029756403716399947, 0.05214788200472422] |
1,802.03834 | Continuum directed random polymers on disordered hierarchical diamond
lattices | I discuss models for a continuum directed random polymer in a disordered
environment in which the polymer lives on a fractal called the \textit{diamond
hierarchical lattice}, a self-similar metric space forming a network of
interweaving pathways. This fractal depends on a branching parameter $b\in
\mathbb{N}$ and a segmenting number $s\in \mathbb{N}$. For $s>b$ my focus is on
random measures on the set of directed paths that can be formulated as a
subcritical Gaussian multiplicative chaos. This path measure is analogous to
the continuum directed random polymer introduced by Alberts, Khanin, Quastel
[Journal of Statistical Physics \textbf{154}, 305-326 (2014)].
| math.PR | i discuss models for a continuum directed random polymer in a disordered environment in which the polymer lives on a fractal called the textitdiamond hierarchical lattice a selfsimilar metric space forming a network of interweaving pathways this fractal depends on a branching parameter bin mathbbn and a segmenting number sin mathbbn for sb my focus is on random measures on the set of directed paths that can be formulated as a subcritical gaussian multiplicative chaos this path measure is analogous to the continuum directed random polymer introduced by alberts khanin quastel journal of statistical physics textbf154 305326 2014 | [['i', 'discuss', 'models', 'for', 'a', 'continuum', 'directed', 'random', 'polymer', 'in', 'a', 'disordered', 'environment', 'in', 'which', 'the', 'polymer', 'lives', 'on', 'a', 'fractal', 'called', 'the', 'textitdiamond', 'hierarchical', 'lattice', 'a', 'selfsimilar', 'metric', 'space', 'forming', 'a', 'network', 'of', 'interweaving', 'pathways', 'this', 'fractal', 'depends', 'on', 'a', 'branching', 'parameter', 'bin', 'mathbbn', 'and', 'a', 'segmenting', 'number', 'sin', 'mathbbn', 'for', 'sb', 'my', 'focus', 'is', 'on', 'random', 'measures', 'on', 'the', 'set', 'of', 'directed', 'paths', 'that', 'can', 'be', 'formulated', 'as', 'a', 'subcritical', 'gaussian', 'multiplicative', 'chaos', 'this', 'path', 'measure', 'is', 'analogous', 'to', 'the', 'continuum', 'directed', 'random', 'polymer', 'introduced', 'by', 'alberts', 'khanin', 'quastel', 'journal', 'of', 'statistical', 'physics', 'textbf154', '305326', '2014']] | [-0.11835811650196679, 0.21296329728425725, -0.08030458973524601, 0.04345131637896166, -0.06725220807680958, -0.14599385716413196, 0.0694568119992159, 0.3655678988875527, -0.26182699830418354, -0.16298051124536678, 0.05655652887776102, -0.24201195447852736, -0.17943438542026438, 0.11522482144401262, -0.0959264633637902, 0.06086720549746564, 0.04207558371126652, 0.0213365246786883, 0.0309272075880711, -0.2006869443300131, 0.28253042686517704, 0.02739148567871828, 0.25926410490401874, -0.005093383651814963, 0.09286200790420959, 0.025808841460629513, -0.04934370517872402, 0.07582196253443774, -0.21787103118756357, 0.10709974443736045, 0.19148073137763086, 0.07846238812137592, 0.29809615023826297, -0.34701023466492953, -0.278801309307547, 0.14495770107268502, 0.12833438653891024, 0.05374420378724799, 0.021241236576124242, -0.30323720164597034, 0.06987764984369278, -0.12781660296267977, -0.0983028016494293, 0.02163456590650113, 0.11045905010480629, 0.056151100208884794, -0.26208352372050286, 0.038807712436506624, 0.10154114135197903, 0.05419710880439532, 0.016544228873068566, -0.12681143200515133, -0.02433629958571768, 0.06684811178006624, -0.07180910163902138, 0.08396188169105076, 0.17343343763097532, -0.08382045420278844, -0.16942591950125796, 0.3793857599216464, -0.024543366992944165, -0.2326378266670202, 0.1453111071433676, -0.1115863640498566, -0.21804287040508108, 0.11757678154267763, 0.21994903867721166, 0.082920662568588, -0.15587008172940267, 0.13068176398580697, -0.10542510981230359, 0.1470858635674966, 0.08240940535539075, -0.024057213741501694, 0.1721955507476722, 0.202261508256197, 0.06686235968219606, 0.15769777941934177, -0.03733707081869637, -0.13118686098605395, -0.25013464964240006, -0.1547455541397396, -0.23363050455166223, 0.12172937640234044, -0.16441029491941567, -0.25672630851990297, 0.37308935584549446, 0.08119932071943033, 0.21648698258948953, 0.10443573521670739, 0.16930498743772898, 0.09073204414591218, -0.029106908270746076, 0.0526888056339598, 0.12033395177047504, 0.16748264142998348, 0.09745607917246066, -0.13136101651838736, 0.06578234376777944, 0.15486225347818905] |
1,802.03835 | Edge-Host Partitioning of Deep Neural Networks with Feature Space
Encoding for Resource-Constrained Internet-of-Things Platforms | This paper introduces partitioning an inference task of a deep neural network
between an edge and a host platform in the IoT environment. We present a DNN as
an encoding pipeline, and propose to transmit the output feature space of an
intermediate layer to the host. The lossless or lossy encoding of the feature
space is proposed to enhance the maximum input rate supported by the edge
platform and/or reduce the energy of the edge platform. Simulation results show
that partitioning a DNN at the end of convolutional (feature extraction) layers
coupled with feature space encoding enables significant improvement in the
energy-efficiency and throughput over the baseline configurations that perform
the entire inference at the edge or at the host.
| cs.CV | this paper introduces partitioning an inference task of a deep neural network between an edge and a host platform in the iot environment we present a dnn as an encoding pipeline and propose to transmit the output feature space of an intermediate layer to the host the lossless or lossy encoding of the feature space is proposed to enhance the maximum input rate supported by the edge platform andor reduce the energy of the edge platform simulation results show that partitioning a dnn at the end of convolutional feature extraction layers coupled with feature space encoding enables significant improvement in the energyefficiency and throughput over the baseline configurations that perform the entire inference at the edge or at the host | [['this', 'paper', 'introduces', 'partitioning', 'an', 'inference', 'task', 'of', 'a', 'deep', 'neural', 'network', 'between', 'an', 'edge', 'and', 'a', 'host', 'platform', 'in', 'the', 'iot', 'environment', 'we', 'present', 'a', 'dnn', 'as', 'an', 'encoding', 'pipeline', 'and', 'propose', 'to', 'transmit', 'the', 'output', 'feature', 'space', 'of', 'an', 'intermediate', 'layer', 'to', 'the', 'host', 'the', 'lossless', 'or', 'lossy', 'encoding', 'of', 'the', 'feature', 'space', 'is', 'proposed', 'to', 'enhance', 'the', 'maximum', 'input', 'rate', 'supported', 'by', 'the', 'edge', 'platform', 'andor', 'reduce', 'the', 'energy', 'of', 'the', 'edge', 'platform', 'simulation', 'results', 'show', 'that', 'partitioning', 'a', 'dnn', 'at', 'the', 'end', 'of', 'convolutional', 'feature', 'extraction', 'layers', 'coupled', 'with', 'feature', 'space', 'encoding', 'enables', 'significant', 'improvement', 'in', 'the', 'energyefficiency', 'and', 'throughput', 'over', 'the', 'baseline', 'configurations', 'that', 'perform', 'the', 'entire', 'inference', 'at', 'the', 'edge', 'or', 'at', 'the', 'host']] | [-0.14633296669926493, 0.02884486289161335, -0.051953438060202944, -0.041573951343889345, -0.06804607703040043, -0.1545633978288, 0.06935847858646109, 0.4251155157961572, -0.31293252607186633, -0.32856206006060046, 0.05981961507544232, -0.25252519101680565, -0.17027582490894322, 0.13531582991126925, -0.0447342711306798, 0.06460537571304788, 0.10914801069884561, 0.026941038171450295, -0.055253429637135316, -0.2535421238746494, 0.29761526399136834, 0.1328782544527106, 0.37928332400042564, 0.01316901391837746, 0.11476574381813406, 0.009833635131750876, -0.026457260572351517, -0.0628426414737381, -0.056967179233348965, 0.16764140129089355, 0.30113711232940354, 0.16687103243311868, 0.30244024021085353, -0.42898146822117267, -0.23666312988692273, 0.05302172262842456, 0.15820024245864867, 0.09488332812519124, -0.03089823035988957, -0.2847463599949454, 0.10126210098678712, -0.1953236612258479, -0.019771394913550466, -0.04421504099154845, -0.019628035261606176, -0.04365161260357127, -0.2962441179746141, -0.007897933619096876, 0.07094561584526674, 0.01673994416487403, -0.05230410559452139, -0.059119616930062575, -0.03115534771932289, 0.14952953452496634, -0.04674657340510748, 0.07406759558167929, 0.13290236656321214, -0.18498961466248148, -0.11892016588230944, 0.31636767618668576, -0.05584196811153864, -0.1799899187249442, 0.18198919442947953, -0.008993037929758429, -0.09439121210404361, 0.12594984114014854, 0.25880532085817926, 0.06870720714796334, -0.11872594270389528, 0.016363579656172078, -0.0075837100157514215, 0.21656353092597178, 0.03693466697198649, 0.08739862533984706, 0.22461798986575257, 0.2793061998323537, 0.09735532472453391, 0.21420109428969833, -0.17711427470567287, -0.04192559368966613, -0.24383611532393842, -0.16693046341339748, -0.21057709864301918, -0.03410128294490278, -0.12493375838154558, -0.151368692672501, 0.42872421799305205, 0.17313337874754023, 0.23830397073998028, 0.08993706465698778, 0.35289363777264954, 0.07613614871224854, 0.1360563985731763, 0.1538211279505049, 0.1927537501634409, 0.030283995905968673, 0.09887307319925943, -0.2141191354467689, 0.06174032103541928, 0.02839804472750984] |
1,802.03836 | On the wake meandering of a model wind turbine operating in two
different regimes | The flows behind a model wind turbine under two turbine operating regimes are
investigated using wind tunnel experiments and large-eddy simulations.
Measurements from the model wind turbine experiment reveal that the power
coefficient and turbine wake are affected by the operating regime. Simulations
employing a new class of actuator surface methods which parameterize both the
turbine blades and nacelle with and without a nacelle model are carried out for
each operating condition to study the influence of the operating regime and
nacelle. For simulations with a nacelle model, the mean flow field is composed
of an outer wake, caused by energy extraction from the incoming wind by the
turbine blades, and an inner wake directly behind the nacelle, while for the
simulations without a nacelle model, the central region of the wake is occupied
by a jet. The simulations with the nacelle model reveal an unstable helical hub
vortex expanding outwards towards the outer wake; while the simulations without
a nacelle model show a stable and columnar hub vortex. The hub vortex for the
turbine operating in Region 3 remains in a tight helical spiral and intercepts
the outer wake a few diameters further downstream than for the turbine
operating in Region 2. Wake meandering commences in a region of high turbulence
intensity for all simulations indicating that neither a nacelle model nor an
unstable hub vortex is a necessary requirement for wake meandering. However,
further analysis of the wake meandering using a filtering technique and dynamic
mode decomposition show that the unstable hub vortex energizes the wake
meandering. The turbine operating regime affects the shape and expansion of the
hub vortex altering the location of the onset of the wake meandering and its
oscillating intensity. The unstable hub vortex promotes a energetic meandering
which cannot be predicted without a nacelle model.
| physics.flu-dyn | the flows behind a model wind turbine under two turbine operating regimes are investigated using wind tunnel experiments and largeeddy simulations measurements from the model wind turbine experiment reveal that the power coefficient and turbine wake are affected by the operating regime simulations employing a new class of actuator surface methods which parameterize both the turbine blades and nacelle with and without a nacelle model are carried out for each operating condition to study the influence of the operating regime and nacelle for simulations with a nacelle model the mean flow field is composed of an outer wake caused by energy extraction from the incoming wind by the turbine blades and an inner wake directly behind the nacelle while for the simulations without a nacelle model the central region of the wake is occupied by a jet the simulations with the nacelle model reveal an unstable helical hub vortex expanding outwards towards the outer wake while the simulations without a nacelle model show a stable and columnar hub vortex the hub vortex for the turbine operating in region 3 remains in a tight helical spiral and intercepts the outer wake a few diameters further downstream than for the turbine operating in region 2 wake meandering commences in a region of high turbulence intensity for all simulations indicating that neither a nacelle model nor an unstable hub vortex is a necessary requirement for wake meandering however further analysis of the wake meandering using a filtering technique and dynamic mode decomposition show that the unstable hub vortex energizes the wake meandering the turbine operating regime affects the shape and expansion of the hub vortex altering the location of the onset of the wake meandering and its oscillating intensity the unstable hub vortex promotes a energetic meandering which cannot be predicted without a nacelle model | [['the', 'flows', 'behind', 'a', 'model', 'wind', 'turbine', 'under', 'two', 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1,802.03837 | Integrated Millimeter Wave and Sub-6 GHz Wireless Networks: A Roadmap
for Joint Mobile Broadband and Ultra-Reliable Low-Latency Communications | Next-generation wireless networks must enable emerging technologies such as
augmented reality and connected autonomous vehicles via wide range of wireless
services that span enhanced mobile broadband (eMBB), as well as ultra-reliable
low-latency communication (URLLC). Existing wireless systems that solely rely
on the scarce sub-6 GHz, microwave ($\mu$W) frequency bands will be unable to
meet such stringent and mixed service requirements for future wireless services
due to spectrum scarcity. Meanwhile, operating at high-frequency millimeter
wave (mmWave) bands is seen as an attractive solution, primarily due to the
bandwidth availability and possibility of large-scale multi-antenna
communication. However, mmWave communication is inherently unreliable due to
its susceptibility to blockage, high path loss, and channel uncertainty. Hence,
to provide URLLC and high-speed wireless access, it is desirable to seamlessly
integrate the reliability of $\mu$W networks with the high capacity of mmWave
networks. To this end, in this paper, the first comprehensive tutorial for
\emph{integrated mmWave-$\mu$W} communications is introduced. This envisioned
integrated design will enable wireless networks to achieve URLLC along with
eMBB by leveraging the best of two worlds: reliable, long-range communications
at the $\mu$W bands and directional high-speed communications at the mmWave
frequencies. To achieve this goal, key solution concepts are discussed that
include new architectures for the radio interface, URLLC-aware frame structure
and resource allocation methods along with mobility management, to realize the
potential of integrated mmWave-$\mu$W communications. The opportunities and
challenges of each proposed scheme are discussed and key results are presented
to show the merits of the developed integrated mmWave-$\mu$W framework.
| eess.SP cs.IT cs.NI math.IT | nextgeneration wireless networks must enable emerging technologies such as augmented reality and connected autonomous vehicles via wide range of wireless services that span enhanced mobile broadband embb as well as ultrareliable lowlatency communication urllc existing wireless systems that solely rely on the scarce sub6 ghz microwave muw frequency bands will be unable to meet such stringent and mixed service requirements for future wireless services due to spectrum scarcity meanwhile operating at highfrequency millimeter wave mmwave bands is seen as an attractive solution primarily due to the bandwidth availability and possibility of largescale multiantenna communication however mmwave communication is inherently unreliable due to its susceptibility to blockage high path loss and channel uncertainty hence to provide urllc and highspeed wireless access it is desirable to seamlessly integrate the reliability of muw networks with the high capacity of mmwave networks to this end in this paper the first comprehensive tutorial for emphintegrated mmwavemuw communications is introduced this envisioned integrated design will enable wireless networks to achieve urllc along with embb by leveraging the best of two worlds reliable longrange communications at the muw bands and directional highspeed communications at the mmwave frequencies to achieve this goal key solution concepts are discussed that include new architectures for the radio interface urllcaware frame structure and resource allocation methods along with mobility management to realize the potential of integrated mmwavemuw communications the opportunities and challenges of each proposed scheme are discussed and key results are presented to show the merits of the developed integrated mmwavemuw framework | [['nextgeneration', 'wireless', 'networks', 'must', 'enable', 'emerging', 'technologies', 'such', 'as', 'augmented', 'reality', 'and', 'connected', 'autonomous', 'vehicles', 'via', 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1,802.03838 | The Discovery of the Most Accelerated Binary Pulsar | Pulsars in relativistic binary systems have emerged as fantastic natural
laboratories for testing theories of gravity, the most prominent example being
the double pulsar, PSR J0737$-$3039. The HTRU-South Low Latitude pulsar survey
represents one of the most sensitive blind pulsar surveys taken of the southern
Galactic plane to date, and its primary aim has been the discovery of new
relativistic binary pulsars. Here we present our binary pulsar searching
strategy and report on the survey's flagship discovery, PSR J1757$-$1854. A
21.5-ms pulsar in a relativistic binary with an orbital period of 4.4 hours and
an eccentricity of 0.61, this double neutron star (DNS) system is the most
accelerated pulsar binary known, and probes a relativistic parameter space not
yet explored by previous pulsar binaries.
| astro-ph.HE | pulsars in relativistic binary systems have emerged as fantastic natural laboratories for testing theories of gravity the most prominent example being the double pulsar psr j07373039 the htrusouth low latitude pulsar survey represents one of the most sensitive blind pulsar surveys taken of the southern galactic plane to date and its primary aim has been the discovery of new relativistic binary pulsars here we present our binary pulsar searching strategy and report on the surveys flagship discovery psr j17571854 a 215ms pulsar in a relativistic binary with an orbital period of 44 hours and an eccentricity of 061 this double neutron star dns system is the most accelerated pulsar binary known and probes a relativistic parameter space not yet explored by previous pulsar binaries | [['pulsars', 'in', 'relativistic', 'binary', 'systems', 'have', 'emerged', 'as', 'fantastic', 'natural', 'laboratories', 'for', 'testing', 'theories', 'of', 'gravity', 'the', 'most', 'prominent', 'example', 'being', 'the', 'double', 'pulsar', 'psr', 'j07373039', 'the', 'htrusouth', 'low', 'latitude', 'pulsar', 'survey', 'represents', 'one', 'of', 'the', 'most', 'sensitive', 'blind', 'pulsar', 'surveys', 'taken', 'of', 'the', 'southern', 'galactic', 'plane', 'to', 'date', 'and', 'its', 'primary', 'aim', 'has', 'been', 'the', 'discovery', 'of', 'new', 'relativistic', 'binary', 'pulsars', 'here', 'we', 'present', 'our', 'binary', 'pulsar', 'searching', 'strategy', 'and', 'report', 'on', 'the', 'surveys', 'flagship', 'discovery', 'psr', 'j17571854', 'a', '215ms', 'pulsar', 'in', 'a', 'relativistic', 'binary', 'with', 'an', 'orbital', 'period', 'of', '44', 'hours', 'and', 'an', 'eccentricity', 'of', '061', 'this', 'double', 'neutron', 'star', 'dns', 'system', 'is', 'the', 'most', 'accelerated', 'pulsar', 'binary', 'known', 'and', 'probes', 'a', 'relativistic', 'parameter', 'space', 'not', 'yet', 'explored', 'by', 'previous', 'pulsar', 'binaries']] | [-0.17291234130207755, 0.13297751476653263, -0.06131238915926975, 0.10661354270901104, -0.22742279495501921, -0.11729898057939088, 0.06043793697322368, 0.3248176630281034, -0.1874823031296236, -0.31978858677578753, 0.08053211774104505, -0.2835717787279091, -0.04006094024631149, 0.31612430843448297, -0.007032400898141099, 0.01999245908304087, 0.13626134876575946, -0.014292505089751564, -0.031969079167627895, -0.22072339747361094, 0.23678533274100208, 0.14822554270752142, 0.0807103904509978, -0.08855841440133384, 0.12712843260788892, -0.013625600846621712, -0.03803950833079413, -0.07536022026940119, -0.10165525348685285, 0.025567825477127534, 0.2635299253361452, 0.1775085664922982, 0.17824309612395334, -0.3472842540225533, -0.2065917959925337, 0.04479241754084856, 0.1618032081999251, 0.024704820300895172, -0.1026807988919394, -0.2978651938477119, 0.047611219079432186, -0.34404944765121964, -0.1844485513007146, 0.043204304945395615, 0.08358732386602882, 0.06311452551935723, -0.12091101188838604, 0.05401246767055976, 0.06102043968915451, 0.06859749162447501, -0.13684018080973936, -0.1510182840045404, 0.09283089727835088, 0.03753820436502822, 0.07133186093081155, 0.13771756116270287, 0.06404796328594084, -0.13460267934619952, -0.16188494561881314, 0.43927298307602036, -0.01708761855891188, -0.02998400868115122, 0.2115832437249664, -0.27107785521914846, -0.2620969663190915, 0.09275421704123651, 0.1722545844905191, 0.1700275126676701, -0.21799886416735464, 0.0285863576604332, -0.03282273622596117, 0.23648178835922365, 0.033020235835211964, 0.04606308224305632, 0.4194711103470477, 0.18757454235990317, 0.01883815723417907, 0.12100928463041782, -0.32030385859180854, -0.03742665299748788, -0.16169037573520462, -0.05759074571771455, -0.14162868659534936, 0.09259447837489386, -0.10291948287364203, -0.12663217224028023, 0.37086357111034945, 0.07547537616590519, 0.06570860594854552, -0.03635920176939031, 0.29447265699139386, 0.09193677734201927, 0.029793809694414537, 0.11112160589469627, 0.38316745008723657, 0.1754854028819312, 0.11712029681647898, -0.21367279506578554, 0.11974294923368048, -0.032286239822288273] |
1,802.03839 | Band Target Entropy Minimization and Target Partial Least Squares for
Spectral Recovery and Calibration | The resolution and calibration of pure spectra of minority components in
measurements of chemical mixtures without prior knowledge of the mixture is a
challenging problem. In this work, a combination of band target entropy
minimization (BTEM) and target partial least squares (T-PLS) was used to obtain
estimates for single pure component spectra and to calibrate those estimates in
a true, one-at-a-time fashion. This approach allows for minor components to be
targeted and their relative amounts estimated in the presence of other varying
components in spectral data. The use of T-PLS estimation is an improvement to
the BTEM method because it overcomes the need to identify all of the pure
components prior to estimation. Estimated amounts from this combination were
found to be similar to those obtained from a standard method, multivariate
curve resolution-alternating least squares (MCR-ALS), on a simple, three
component mixture dataset. Studies from two experimental datasets demonstrate
where the combination of BTEM and T-PLS could model the pure component spectra
and obtain concentration profiles of minor components but MCR-ALS could not.
| stat.ML stat.AP | the resolution and calibration of pure spectra of minority components in measurements of chemical mixtures without prior knowledge of the mixture is a challenging problem in this work a combination of band target entropy minimization btem and target partial least squares tpls was used to obtain estimates for single pure component spectra and to calibrate those estimates in a true oneatatime fashion this approach allows for minor components to be targeted and their relative amounts estimated in the presence of other varying components in spectral data the use of tpls estimation is an improvement to the btem method because it overcomes the need to identify all of the pure components prior to estimation estimated amounts from this combination were found to be similar to those obtained from a standard method multivariate curve resolutionalternating least squares mcrals on a simple three component mixture dataset studies from two experimental datasets demonstrate where the combination of btem and tpls could model the pure component spectra and obtain concentration profiles of minor components but mcrals could not | [['the', 'resolution', 'and', 'calibration', 'of', 'pure', 'spectra', 'of', 'minority', 'components', 'in', 'measurements', 'of', 'chemical', 'mixtures', 'without', 'prior', 'knowledge', 'of', 'the', 'mixture', 'is', 'a', 'challenging', 'problem', 'in', 'this', 'work', 'a', 'combination', 'of', 'band', 'target', 'entropy', 'minimization', 'btem', 'and', 'target', 'partial', 'least', 'squares', 'tpls', 'was', 'used', 'to', 'obtain', 'estimates', 'for', 'single', 'pure', 'component', 'spectra', 'and', 'to', 'calibrate', 'those', 'estimates', 'in', 'a', 'true', 'oneatatime', 'fashion', 'this', 'approach', 'allows', 'for', 'minor', 'components', 'to', 'be', 'targeted', 'and', 'their', 'relative', 'amounts', 'estimated', 'in', 'the', 'presence', 'of', 'other', 'varying', 'components', 'in', 'spectral', 'data', 'the', 'use', 'of', 'tpls', 'estimation', 'is', 'an', 'improvement', 'to', 'the', 'btem', 'method', 'because', 'it', 'overcomes', 'the', 'need', 'to', 'identify', 'all', 'of', 'the', 'pure', 'components', 'prior', 'to', 'estimation', 'estimated', 'amounts', 'from', 'this', 'combination', 'were', 'found', 'to', 'be', 'similar', 'to', 'those', 'obtained', 'from', 'a', 'standard', 'method', 'multivariate', 'curve', 'resolutionalternating', 'least', 'squares', 'mcrals', 'on', 'a', 'simple', 'three', 'component', 'mixture', 'dataset', 'studies', 'from', 'two', 'experimental', 'datasets', 'demonstrate', 'where', 'the', 'combination', 'of', 'btem', 'and', 'tpls', 'could', 'model', 'the', 'pure', 'component', 'spectra', 'and', 'obtain', 'concentration', 'profiles', 'of', 'minor', 'components', 'but', 'mcrals', 'could', 'not']] | [-0.031050798185047867, 0.03709500394215019, -0.0976355676349729, 0.027408014282416335, -0.059338783165764845, -0.12914451498397475, 0.036748726619407535, 0.3878081018798227, -0.2577794383653591, -0.36056333712063904, 0.12146377341949034, -0.2903003765685182, -0.06104255055597182, 0.1710761284691195, -0.08197980879286174, 0.0304166070553799, 0.0909111741537683, -0.012208850891870815, -0.07194422765061, -0.2292882171256446, 0.28269959740384026, 0.017208317397595492, 0.2823424417265626, -0.006364349159412086, 0.08784637165182746, 0.007028607413345991, -0.07070158109702386, 0.006133223542683693, -0.06967898867997276, 0.14416508269726386, 0.25878304846281575, 0.12280380794356122, 0.2197877249929534, -0.3665459000743752, -0.2403802155032429, 0.1322558947790111, 0.1258467442388538, 0.10056484351822968, -3.643138239398425e-05, -0.2197045015907565, 0.06431859840441301, -0.16232365767233248, -0.11689203276385575, -0.08352276541192497, -0.026087598225489655, -0.003342554146467253, -0.3024463241156407, 0.10741526644601118, 0.045550521705673565, 0.056511090078856796, -0.07539964306640688, -0.1887234958202773, -0.01212978842235062, 0.12202021238383252, 0.041006931754879565, 0.0010530010412642082, 0.11559031827126218, -0.1277584845923039, -0.08255398337361078, 0.35017030917346303, -0.12266721398275898, -0.18646460748277605, 0.21408580338817934, -0.11232032572720634, -0.12971517752631306, 0.1490217516297572, 0.17173777829580208, 0.1258910708779166, -0.18147236937765293, -0.007178673717642723, -0.014731543931871826, 0.21605015235552347, 0.03623067869785848, -0.029948554532385843, 0.17854765982388757, 0.11625860184485223, 0.05369185158917051, 0.13089936788547188, -0.13923475217361134, -0.041977204664320644, -0.23535376610938286, -0.13968766206296074, -0.1853829709803523, 0.0051166219150324, -0.0808968605804609, -0.14892366783541822, 0.3653630990599997, 0.12479062030784958, 0.21957264889876338, 0.02957891784933244, 0.3138222123136159, 0.07417792917248187, 0.07805319650093266, 0.041227545272450636, 0.2152398365717598, 0.1410513283362677, 0.03144189662592442, -0.1817279273581821, 0.10349913255641843, 0.0016075246696641973] |
1,802.0384 | Uncharted Forest a Technique for Exploratory Data Analysis | Exploratory data analysis is crucial for developing and understanding
classification models from high-dimensional datasets. We explore the utility of
a new unsupervised tree ensemble called uncharted forest for visualizing class
associations, sample-sample associations, class heterogeneity, and
uninformative classes for provenance studies. The uncharted forest algorithm
can be used to partition data using random selections of variables and metrics
based on statistical spread. After each tree is grown, a tally of the samples
that arrive at every terminal node is maintained. Those tallies are stored in
single sample association matrix and a likelihood measure for each sample being
partitioned with one another can be made. That matrix may be readily viewed as
a heat map, and the probabilities can be quantified via new metrics that
account for class or cluster membership. We display the advantages and
limitations of using this technique by applying it to two classification
datasets and three provenance study datasets. Two of the metrics presented in
this paper are also compared with widely used metrics from two algorithms that
have variance-based clustering mechanisms.
| stat.ML cs.LG stat.ME | exploratory data analysis is crucial for developing and understanding classification models from highdimensional datasets we explore the utility of a new unsupervised tree ensemble called uncharted forest for visualizing class associations samplesample associations class heterogeneity and uninformative classes for provenance studies the uncharted forest algorithm can be used to partition data using random selections of variables and metrics based on statistical spread after each tree is grown a tally of the samples that arrive at every terminal node is maintained those tallies are stored in single sample association matrix and a likelihood measure for each sample being partitioned with one another can be made that matrix may be readily viewed as a heat map and the probabilities can be quantified via new metrics that account for class or cluster membership we display the advantages and limitations of using this technique by applying it to two classification datasets and three provenance study datasets two of the metrics presented in this paper are also compared with widely used metrics from two algorithms that have variancebased clustering mechanisms | [['exploratory', 'data', 'analysis', 'is', 'crucial', 'for', 'developing', 'and', 'understanding', 'classification', 'models', 'from', 'highdimensional', 'datasets', 'we', 'explore', 'the', 'utility', 'of', 'a', 'new', 'unsupervised', 'tree', 'ensemble', 'called', 'uncharted', 'forest', 'for', 'visualizing', 'class', 'associations', 'samplesample', 'associations', 'class', 'heterogeneity', 'and', 'uninformative', 'classes', 'for', 'provenance', 'studies', 'the', 'uncharted', 'forest', 'algorithm', 'can', 'be', 'used', 'to', 'partition', 'data', 'using', 'random', 'selections', 'of', 'variables', 'and', 'metrics', 'based', 'on', 'statistical', 'spread', 'after', 'each', 'tree', 'is', 'grown', 'a', 'tally', 'of', 'the', 'samples', 'that', 'arrive', 'at', 'every', 'terminal', 'node', 'is', 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1,802.03841 | Scalar curvature and properness on Sasaki manifolds | We study (transverse) scalar curvature type equation on compact Sasaki
manifolds, in view of recent breakthrough of Chen-Cheng \cite{CC1, CC2, CC3} on
existence of K\"ahler metrics with constant scalar curvature (csck) on compact
K\"ahler manifolds. Following their strategy, we prove that given a Sasaki
structure (with Reeb vector field and complex structure on its cone fixed ),
there exists a Sasaki structure with transverse constant scalar curvature
(cscs) if and only if the $\mathcal{K}$-energy is reduced proper modulo the
identity component of the automorphism group which preserves both the Reeb
vector field and transverse complex structure. Technically, the proof mainly
consists of two parts. The first part is a priori estimates for scalar
curvature type equations which are parallel to Chen-Cheng's results in
\cite{CC2, CC3} in Sasaki setting. The second part is geometric pluripotential
theory on a compact Sasaki manifold, building up on profound results in
geometric pluripotential theory on K\"ahler manifolds. There are notable, and
indeed subtle differences in Sasaki setting (compared with K\"ahler setting)
for both parts (PDE and pluripotential theory). The PDE part is an adaption of
deep work of Chen-Cheng \cite{CC1, CC2, CC3} to Sasaki setting with necessary
modifications. While the geometric pluripotential theory on a compact Sasaki
manifold has new difficulties, compared with geometric pluripotential theory in
K\"ahler setting which is very intricate. We shall present the details of
geometric pluripotential on Sasaki manifolds in a separate paper \cite{HL}
(joint work with Jun Li).
| math.DG math.AP | we study transverse scalar curvature type equation on compact sasaki manifolds in view of recent breakthrough of chencheng citecc1 cc2 cc3 on existence of kahler metrics with constant scalar curvature csck on compact kahler manifolds following their strategy we prove that given a sasaki structure with reeb vector field and complex structure on its cone fixed there exists a sasaki structure with transverse constant scalar curvature cscs if and only if the mathcalkenergy is reduced proper modulo the identity component of the automorphism group which preserves both the reeb vector field and transverse complex structure technically the proof mainly consists of two parts the first part is a priori estimates for scalar curvature type equations which are parallel to chenchengs results in citecc2 cc3 in sasaki setting the second part is geometric pluripotential theory on a compact sasaki manifold building up on profound results in geometric pluripotential theory on kahler manifolds there are notable and indeed subtle differences in sasaki setting compared with kahler setting for both parts pde and pluripotential theory the pde part is an adaption of deep work of chencheng citecc1 cc2 cc3 to sasaki setting with necessary modifications while the geometric pluripotential theory on a compact sasaki manifold has new difficulties compared with geometric pluripotential theory in kahler setting which is very intricate we shall present the details of geometric pluripotential on sasaki manifolds in a separate paper citehl joint work with jun li | [['we', 'study', 'transverse', 'scalar', 'curvature', 'type', 'equation', 'on', 'compact', 'sasaki', 'manifolds', 'in', 'view', 'of', 'recent', 'breakthrough', 'of', 'chencheng', 'citecc1', 'cc2', 'cc3', 'on', 'existence', 'of', 'kahler', 'metrics', 'with', 'constant', 'scalar', 'curvature', 'csck', 'on', 'compact', 'kahler', 'manifolds', 'following', 'their', 'strategy', 'we', 'prove', 'that', 'given', 'a', 'sasaki', 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|
1,802.03842 | Circular polarization of gravitational waves from non-rotating supernova
cores: a new probe into the pre-explosion hydrodynamics | We present an analysis of the circular polarization of gravitational-waves
(GWs) using results from three-dimensional (3D), general relativistic (GR)
core-collapse simulations of a non-rotating $15 M_{\odot}$ star. For the signal
detection, we perform a coherent network analysis taking into account the four
interferometers of LIGO Hanford, LIGO Livingston, VIRGO, and KAGRA. We focus on
the Stokes $V$ parameter, which directly characterizes the asymmetry of the GW
circular polarization. We find that the amplitude of the GW polarization
becomes bigger for our 3D-GR model that exhibits strong activity of the
standing accretion shock instability (SASI). Our results suggest that the
SASI-induced accretion flows to the proto-neutron star (PNS) lead to a
characteristic, low-frequency modulation (100 $\sim$ 200 Hz) in both the
waveform and the GW circular polarization. During the vigorous SASI phase, we
observe that the GW polarization switches from the right- to left-handed mode,
which is clearly visible in the spectrogram. By estimating the signal-to-noise
ratio of the GW polarization, we demonstrate that the detection horizon of the
circular polarization extends by more than a factor of several times farther
comparing to that of the GW amplitude. Our results suggest that the GW circular
polarization, if detected, could provide a new probe into the pre-explosion
hydrodynamics such as the SASI activity and the $g$-mode oscillation of the
PNS.
| astro-ph.HE gr-qc | we present an analysis of the circular polarization of gravitationalwaves gws using results from threedimensional 3d general relativistic gr corecollapse simulations of a nonrotating 15 m_odot star for the signal detection we perform a coherent network analysis taking into account the four interferometers of ligo hanford ligo livingston virgo and kagra we focus on the stokes v parameter which directly characterizes the asymmetry of the gw circular polarization we find that the amplitude of the gw polarization becomes bigger for our 3dgr model that exhibits strong activity of the standing accretion shock instability sasi our results suggest that the sasiinduced accretion flows to the protoneutron star pns lead to a characteristic lowfrequency modulation 100 sim 200 hz in both the waveform and the gw circular polarization during the vigorous sasi phase we observe that the gw polarization switches from the right to lefthanded mode which is clearly visible in the spectrogram by estimating the signaltonoise ratio of the gw polarization we demonstrate that the detection horizon of the circular polarization extends by more than a factor of several times farther comparing to that of the gw amplitude our results suggest that the gw circular polarization if detected could provide a new probe into the preexplosion hydrodynamics such as the sasi activity and the gmode oscillation of the pns | [['we', 'present', 'an', 'analysis', 'of', 'the', 'circular', 'polarization', 'of', 'gravitationalwaves', 'gws', 'using', 'results', 'from', 'threedimensional', '3d', 'general', 'relativistic', 'gr', 'corecollapse', 'simulations', 'of', 'a', 'nonrotating', '15', 'm_odot', 'star', 'for', 'the', 'signal', 'detection', 'we', 'perform', 'a', 'coherent', 'network', 'analysis', 'taking', 'into', 'account', 'the', 'four', 'interferometers', 'of', 'ligo', 'hanford', 'ligo', 'livingston', 'virgo', 'and', 'kagra', 'we', 'focus', 'on', 'the', 'stokes', 'v', 'parameter', 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1,802.03843 | Spectrum Sensing Strategy to Enhance the QoS in White-Fi Networks | The rapidly growing number of wireless devices running applications that
require high bandwidths, has resulted in increasing demands for the unlicensed
frequency spectrum. Given the scarcity of allocated unlicensed frequencies,
meeting such demands can become a serious concern. Cognitive Radio
(CR)technology opens the door for the opportunistic use of the licensed
spectrum to partially address the issues relevant to the limited availability
of unlicensed frequencies. Combining CR and Wi-Fi to form the socalled White-Fi
networks, has been proposed for achieving higher spectrum utilization. This
article discusses the spectrum sensing in White-Fi networks and the impacts
that it has on the QoS of typical applications. It also reports the analysis of
such impacts through various simulation studies. Our results demonstrate the
advantages of an adaptive sensing strategy that is capable of changing the
related parameters based on QoS requirements. We also propose such a sensing
strategy that can adapt to the IEEE 802.11e requirements. The goal of the
proposed strategy is the enhancement of the overall QoS of the applications
while maintaining efficient sensing of the spectrum. Simulation results of the
scenarios that implement the proposed mechanisms demonstrate noticeable QoS
improvements compared to cases where common sensing methods are utilized in
IEEE802.11 networks.
| cs.NI | the rapidly growing number of wireless devices running applications that require high bandwidths has resulted in increasing demands for the unlicensed frequency spectrum given the scarcity of allocated unlicensed frequencies meeting such demands can become a serious concern cognitive radio crtechnology opens the door for the opportunistic use of the licensed spectrum to partially address the issues relevant to the limited availability of unlicensed frequencies combining cr and wifi to form the socalled whitefi networks has been proposed for achieving higher spectrum utilization this article discusses the spectrum sensing in whitefi networks and the impacts that it has on the qos of typical applications it also reports the analysis of such impacts through various simulation studies our results demonstrate the advantages of an adaptive sensing strategy that is capable of changing the related parameters based on qos requirements we also propose such a sensing strategy that can adapt to the ieee 80211e requirements the goal of the proposed strategy is the enhancement of the overall qos of the applications while maintaining efficient sensing of the spectrum simulation results of the scenarios that implement the proposed mechanisms demonstrate noticeable qos improvements compared to cases where common sensing methods are utilized in ieee80211 networks | [['the', 'rapidly', 'growing', 'number', 'of', 'wireless', 'devices', 'running', 'applications', 'that', 'require', 'high', 'bandwidths', 'has', 'resulted', 'in', 'increasing', 'demands', 'for', 'the', 'unlicensed', 'frequency', 'spectrum', 'given', 'the', 'scarcity', 'of', 'allocated', 'unlicensed', 'frequencies', 'meeting', 'such', 'demands', 'can', 'become', 'a', 'serious', 'concern', 'cognitive', 'radio', 'crtechnology', 'opens', 'the', 'door', 'for', 'the', 'opportunistic', 'use', 'of', 'the', 'licensed', 'spectrum', 'to', 'partially', 'address', 'the', 'issues', 'relevant', 'to', 'the', 'limited', 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1,802.03844 | Reducing Compare-and-Swap to Consensus Number One Primitives | The consensus number of an object is the maximum number of processes among
which binary consensus can be solved using any number of instances of the
object and read-write registers. Herlihy [6] showed in his seminal work that if
an object has a consensus number of n, then there is a universal construction
for a wait-free and linearizable implementation of any non-trivial concurrent
object or data structure that is shared among n processes. Thus, a
synchronization object such as compare-and-swap with an infinite consensus
number and the corresponding instruction can be viewed as "strong". On the
other hand, a synchronization object such as fetch-and-add with consensus
number two and the corresponding fetch-and-add instruction can be viewed as
"weak".
Ellen et al. [2] observed recently that an object supporting two weak
instructions can also achieve infinite consensus number like an object that
supports one strong instruction. Using Herlihy's universal construction, this
implies that ignoring concerns about efficiency, one can design any concurrent
data structure or algorithm using only weak instructions. However, is it
possible that a combination of weak instructions is really powerful enough to
efficiently replace a strong instruction, like compare-and-swap, without
incurring a large overhead in time or space? In this paper, we answer this
question by giving an O(1) time wait-free and linearizable implementation of a
compare-and-swap register shared among n processes using read-write registers
and O(1) registers that support two synchronization primitives half-max and
max-write, each having consensus number one. Thus, any algorithm that solves
some arbitrary synchronization problem using read-write and compare-and-swap
registers can be transformed into an algorithm that has the same asymptotic
time complexity and only uses consensus number one instructions.
| cs.DS cs.DC | the consensus number of an object is the maximum number of processes among which binary consensus can be solved using any number of instances of the object and readwrite registers herlihy 6 showed in his seminal work that if an object has a consensus number of n then there is a universal construction for a waitfree and linearizable implementation of any nontrivial concurrent object or data structure that is shared among n processes thus a synchronization object such as compareandswap with an infinite consensus number and the corresponding instruction can be viewed as strong on the other hand a synchronization object such as fetchandadd with consensus number two and the corresponding fetchandadd instruction can be viewed as weak ellen et al 2 observed recently that an object supporting two weak instructions can also achieve infinite consensus number like an object that supports one strong instruction using herlihys universal construction this implies that ignoring concerns about efficiency one can design any concurrent data structure or algorithm using only weak instructions however is it possible that a combination of weak instructions is really powerful enough to efficiently replace a strong instruction like compareandswap without incurring a large overhead in time or space in this paper we answer this question by giving an o1 time waitfree and linearizable implementation of a compareandswap register shared among n processes using readwrite registers and o1 registers that support two synchronization primitives halfmax and maxwrite each having consensus number one thus any algorithm that solves some arbitrary synchronization problem using readwrite and compareandswap registers can be transformed into an algorithm that has the same asymptotic time complexity and only uses consensus number one instructions | [['the', 'consensus', 'number', 'of', 'an', 'object', 'is', 'the', 'maximum', 'number', 'of', 'processes', 'among', 'which', 'binary', 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1,802.03845 | $T_2$-limited sensing of static magnetic fields via fast rotation of
quantum spins | Diamond-based quantum magnetometers are more sensitive to oscillating (AC)
magnetic fields than static (DC) fields because the crystal impurity-induced
ensemble dephasing time $T_2^*$, the relevant sensing time for a DC field, is
much shorter than the spin coherence time $T_2$, which determines the
sensitivity to AC fields. Here we demonstrate measurement of DC magnetic fields
using a physically rotating ensemble of nitrogen-vacancy centres at a precision
ultimately limited by $T_2$ rather than $T_2^*$. The rotation period of the
diamond is comparable to $T_2$ and the angle between the NV axis and the target
magnetic field changes as a function of time, thus upconverting the static
magnetic field to an oscillating field in the physically rotating frame. Using
spin-echo interferometry of the rotating NV centres, we are able to perform
measurements for over a hundred times longer compared to a conventional Ramsey
experiment. With modifications our scheme could realise DC sensitivities
equivalent to demonstrated NV center AC magnetic field sensitivities of order
$0.1$\,nT\,Hz$^{-1/2}$.
| quant-ph | diamondbased quantum magnetometers are more sensitive to oscillating ac magnetic fields than static dc fields because the crystal impurityinduced ensemble dephasing time t_2 the relevant sensing time for a dc field is much shorter than the spin coherence time t_2 which determines the sensitivity to ac fields here we demonstrate measurement of dc magnetic fields using a physically rotating ensemble of nitrogenvacancy centres at a precision ultimately limited by t_2 rather than t_2 the rotation period of the diamond is comparable to t_2 and the angle between the nv axis and the target magnetic field changes as a function of time thus upconverting the static magnetic field to an oscillating field in the physically rotating frame using spinecho interferometry of the rotating nv centres we are able to perform measurements for over a hundred times longer compared to a conventional ramsey experiment with modifications our scheme could realise dc sensitivities equivalent to demonstrated nv center ac magnetic field sensitivities of order 01nthz12 | [['diamondbased', 'quantum', 'magnetometers', 'are', 'more', 'sensitive', 'to', 'oscillating', 'ac', 'magnetic', 'fields', 'than', 'static', 'dc', 'fields', 'because', 'the', 'crystal', 'impurityinduced', 'ensemble', 'dephasing', 'time', 't_2', 'the', 'relevant', 'sensing', 'time', 'for', 'a', 'dc', 'field', 'is', 'much', 'shorter', 'than', 'the', 'spin', 'coherence', 'time', 't_2', 'which', 'determines', 'the', 'sensitivity', 'to', 'ac', 'fields', 'here', 'we', 'demonstrate', 'measurement', 'of', 'dc', 'magnetic', 'fields', 'using', 'a', 'physically', 'rotating', 'ensemble', 'of', 'nitrogenvacancy', 'centres', 'at', 'a', 'precision', 'ultimately', 'limited', 'by', 't_2', 'rather', 'than', 't_2', 'the', 'rotation', 'period', 'of', 'the', 'diamond', 'is', 'comparable', 'to', 't_2', 'and', 'the', 'angle', 'between', 'the', 'nv', 'axis', 'and', 'the', 'target', 'magnetic', 'field', 'changes', 'as', 'a', 'function', 'of', 'time', 'thus', 'upconverting', 'the', 'static', 'magnetic', 'field', 'to', 'an', 'oscillating', 'field', 'in', 'the', 'physically', 'rotating', 'frame', 'using', 'spinecho', 'interferometry', 'of', 'the', 'rotating', 'nv', 'centres', 'we', 'are', 'able', 'to', 'perform', 'measurements', 'for', 'over', 'a', 'hundred', 'times', 'longer', 'compared', 'to', 'a', 'conventional', 'ramsey', 'experiment', 'with', 'modifications', 'our', 'scheme', 'could', 'realise', 'dc', 'sensitivities', 'equivalent', 'to', 'demonstrated', 'nv', 'center', 'ac', 'magnetic', 'field', 'sensitivities', 'of', 'order', '01nthz12']] | [-0.1589205709238311, 0.23248961411197078, -0.012920883146869538, 0.025156917069280832, -0.02874305004959706, -0.12593837236057856, 0.034866983150508, 0.47425375110614376, -0.23477297020000146, -0.3014057546749896, 0.07457067671026572, -0.2407199496530598, 0.014471692615911734, 0.2761035690688592, 0.0029893283940481473, 0.014699005828418347, 0.0036885204236167743, 0.09534196664365183, -0.10036786576958592, -0.1854421656133364, 0.20534094640701686, 0.0498254756864033, 0.3246523568215809, -0.014128972226695985, 0.09318967672174808, 0.007387298228716629, 0.08533189925766457, 0.057010557984077136, -0.07446479350791214, 0.061420137329890774, 0.2286749401705351, 0.011537922933836531, 0.20030814133908437, -0.4613492735054182, -0.17118408359726023, 0.11478369391627424, 0.1304583452578333, 0.19392658161362403, -0.04294624921234154, -0.29622491779852866, 0.03872077467671295, -0.0872022184461604, -0.11216721508322249, -0.11394265082936665, 0.04949731821764075, 0.008510736650237756, -0.28302061816341945, 0.09741625277418064, 0.03344835306558272, 0.1085818916593927, -0.06593706668788417, -0.06064068230291285, 0.047178685072207856, 0.04868385141356761, 0.022488951286798495, 0.15021549381484908, 0.2719846558236511, -0.0986507040714579, -0.1383958061439743, 0.3272600250307077, -0.10697416632111915, -0.1038173375165333, 0.1480206976910787, -0.21563673088246066, -0.02407827435252228, 0.12030840154609973, 0.10491964018394627, 0.18511924883697806, -0.1660165395645529, 0.009109958554386677, 0.036824541121955545, 0.2075946452790258, 0.10691681628907967, 0.09365228926820784, 0.2513632325669577, 0.15972838843507425, 0.12084404969882938, 0.1390085440557103, -0.1604299115202164, -0.0690923621075413, -0.20014947178478568, -0.11554733496043623, -0.17766826103516617, 0.12820787521755983, -0.07581156179846137, -0.10790933795007211, 0.4117626284664851, 0.19684295211079883, 0.14608054222851435, -0.02440051870892021, 0.3418042216079761, 0.08916797238960283, 0.14616316203752847, 0.020566001514215834, 0.2530376907519024, 0.2593282344461829, 0.12657598288576494, -0.33586752234801925, -0.02569069395200436, -0.04617566511364688] |
1,802.03846 | Equidimensionality and regularity | The existence of an equidimensional morphism f with etale local sections from
a regular algebraic space X to a locally noetherian normal algebraic space S of
characteristic zero with excellent local rings implies that S is regular and f
flat.
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1,802.03847 | Evolution of the quantum Hall bulk spectrum into chiral edge states | One of the most intriguing and fundamental properties of topological
materials is the correspondence between the conducting edge states and the
gapped bulk spectrum. So far, it has been impossible to access the full
evolution of edge states with critical parameters such as magnetic field due to
poor resolution, remnant bulk conductivity, or disorder. Here, we use a GaAs
cleaved edge quantum wire to perform momentum-resolved tunneling spectroscopy.
This allows us to probe the evolution of the chiral quantum Hall edge states
and their positions from the sample edge with unprecedented precision from very
low magnetic fields all the way to high fields where depopulation occurs. We
present consistent analytical and numerical models, inferring the edge states
from the well known bulk spectrum, finding excellent agreement with the
experiment -- thus providing direct evidence for the bulk to edge
correspondence. In addition, we observe various features beyond the
single-particle picture, such as Fermi level pinning, exchange-enhanced spin
splitting and signatures of edge-state reconstruction.
| cond-mat.mes-hall | one of the most intriguing and fundamental properties of topological materials is the correspondence between the conducting edge states and the gapped bulk spectrum so far it has been impossible to access the full evolution of edge states with critical parameters such as magnetic field due to poor resolution remnant bulk conductivity or disorder here we use a gaas cleaved edge quantum wire to perform momentumresolved tunneling spectroscopy this allows us to probe the evolution of the chiral quantum hall edge states and their positions from the sample edge with unprecedented precision from very low magnetic fields all the way to high fields where depopulation occurs we present consistent analytical and numerical models inferring the edge states from the well known bulk spectrum finding excellent agreement with the experiment thus providing direct evidence for the bulk to edge correspondence in addition we observe various features beyond the singleparticle picture such as fermi level pinning exchangeenhanced spin splitting and signatures of edgestate reconstruction | [['one', 'of', 'the', 'most', 'intriguing', 'and', 'fundamental', 'properties', 'of', 'topological', 'materials', 'is', 'the', 'correspondence', 'between', 'the', 'conducting', 'edge', 'states', 'and', 'the', 'gapped', 'bulk', 'spectrum', 'so', 'far', 'it', 'has', 'been', 'impossible', 'to', 'access', 'the', 'full', 'evolution', 'of', 'edge', 'states', 'with', 'critical', 'parameters', 'such', 'as', 'magnetic', 'field', 'due', 'to', 'poor', 'resolution', 'remnant', 'bulk', 'conductivity', 'or', 'disorder', 'here', 'we', 'use', 'a', 'gaas', 'cleaved', 'edge', 'quantum', 'wire', 'to', 'perform', 'momentumresolved', 'tunneling', 'spectroscopy', 'this', 'allows', 'us', 'to', 'probe', 'the', 'evolution', 'of', 'the', 'chiral', 'quantum', 'hall', 'edge', 'states', 'and', 'their', 'positions', 'from', 'the', 'sample', 'edge', 'with', 'unprecedented', 'precision', 'from', 'very', 'low', 'magnetic', 'fields', 'all', 'the', 'way', 'to', 'high', 'fields', 'where', 'depopulation', 'occurs', 'we', 'present', 'consistent', 'analytical', 'and', 'numerical', 'models', 'inferring', 'the', 'edge', 'states', 'from', 'the', 'well', 'known', 'bulk', 'spectrum', 'finding', 'excellent', 'agreement', 'with', 'the', 'experiment', 'thus', 'providing', 'direct', 'evidence', 'for', 'the', 'bulk', 'to', 'edge', 'correspondence', 'in', 'addition', 'we', 'observe', 'various', 'features', 'beyond', 'the', 'singleparticle', 'picture', 'such', 'as', 'fermi', 'level', 'pinning', 'exchangeenhanced', 'spin', 'splitting', 'and', 'signatures', 'of', 'edgestate', 'reconstruction']] | [-0.1375143087733491, 0.1658686867535666, -0.08505683481394324, 0.04770748633718877, -0.0738790299611189, -0.15160532382799796, 0.09502036532927534, 0.3774931762528456, -0.2652643872575869, -0.3578644616552341, 0.03753987003482855, -0.3198684153081828, -0.11998793476025493, 0.1428535158737321, 0.04553742702032819, 0.09542680859212177, 0.030301927926628218, -0.017922407821004772, -0.07318422682353376, -0.13381394609179417, 0.2847480051805852, 0.07457622563046759, 0.331417613832372, 0.09481666426182966, 0.016086703735507198, 0.01866341385714434, 0.05133528663650339, 0.04241506193396578, -0.15872142937632255, 0.07379219288230632, 0.2730455028857609, -0.034031767849408, 0.15853147937076878, -0.4728603985008872, -0.20287648249125786, 0.026123160382813232, 0.16010481222779893, 0.17656445350745165, -0.07055514126751618, -0.28033143748747713, 0.05629591176999204, -0.14455268585215103, -0.15332146123573356, -0.08951379148358549, -0.015343224174877698, -0.07955164598289555, -0.20994450300816953, 0.09690324461409523, 0.006226177887134484, 0.06443801139952776, -0.08079997352561569, -0.08408724531002434, -0.07692912383002148, 0.16654025640821568, 0.024260384606608523, 0.0345344823667633, 0.13838451633224103, -0.19692998810708637, -0.14400526649968262, 0.35873794513697055, -0.04886264864205854, -0.0839226478351464, 0.26394994142838973, -0.22033914690837264, -0.07849485600183223, 0.13789472945126485, 0.07843978029681531, 0.07269954613846853, -0.08904838516451648, 0.08077391053756187, -0.020434830573467927, 0.11093741737702792, 0.03735063999120928, 0.15600969429363398, 0.2851707491532175, 0.1522256628492341, 0.07411092034552569, 0.12905292165893947, -0.15347904808830792, -0.04326612050328864, -0.24700483554157854, -0.17024521550370586, -0.240887079288016, 0.07838110863461079, -0.035372049845327526, -0.19891554843289433, 0.4369145120540059, 0.16060162862090188, 0.22512380603447923, -0.03443730533134514, 0.28170100530540504, 0.11207792013279956, 0.06296161409139771, 0.06485224697727388, 0.2511085660804428, 0.1915663265361577, 0.06674631815806123, -0.2644599395010758, 0.03300645406053252, -0.020372192404106444] |
1,802.03848 | Region Detection in Markov Random Fields: Gaussian Case | We consider the problem of model selection in Gaussian Markov fields in the
sample deficient scenario. The benchmark information-theoretic results in the
case of d-regular graphs require the number of samples to be at least
proportional to the logarithm of the number of vertices to allow consistent
graph recovery. When the number of samples is less than this amount, reliable
detection of all edges is impossible. In many applications, it is more
important to learn the distribution of the edge (coupling) parameters over the
network than the specific locations of the edges. Assuming that the entire
graph can be partitioned into a number of spatial regions with similar edge
parameters and reasonably regular boundaries, we develop new
information-theoretic sample complexity bounds and show that a bounded number
of samples can be sufficient to consistently recover these regions. Finally, we
introduce and analyze an efficient region growing algorithm capable of
recovering the regions with high accuracy. We show that it is consistent and
demonstrate its performance benefits in synthetic simulations.
| stat.ML | we consider the problem of model selection in gaussian markov fields in the sample deficient scenario the benchmark informationtheoretic results in the case of dregular graphs require the number of samples to be at least proportional to the logarithm of the number of vertices to allow consistent graph recovery when the number of samples is less than this amount reliable detection of all edges is impossible in many applications it is more important to learn the distribution of the edge coupling parameters over the network than the specific locations of the edges assuming that the entire graph can be partitioned into a number of spatial regions with similar edge parameters and reasonably regular boundaries we develop new informationtheoretic sample complexity bounds and show that a bounded number of samples can be sufficient to consistently recover these regions finally we introduce and analyze an efficient region growing algorithm capable of recovering the regions with high accuracy we show that it is consistent and demonstrate its performance benefits in synthetic simulations | [['we', 'consider', 'the', 'problem', 'of', 'model', 'selection', 'in', 'gaussian', 'markov', 'fields', 'in', 'the', 'sample', 'deficient', 'scenario', 'the', 'benchmark', 'informationtheoretic', 'results', 'in', 'the', 'case', 'of', 'dregular', 'graphs', 'require', 'the', 'number', 'of', 'samples', 'to', 'be', 'at', 'least', 'proportional', 'to', 'the', 'logarithm', 'of', 'the', 'number', 'of', 'vertices', 'to', 'allow', 'consistent', 'graph', 'recovery', 'when', 'the', 'number', 'of', 'samples', 'is', 'less', 'than', 'this', 'amount', 'reliable', 'detection', 'of', 'all', 'edges', 'is', 'impossible', 'in', 'many', 'applications', 'it', 'is', 'more', 'important', 'to', 'learn', 'the', 'distribution', 'of', 'the', 'edge', 'coupling', 'parameters', 'over', 'the', 'network', 'than', 'the', 'specific', 'locations', 'of', 'the', 'edges', 'assuming', 'that', 'the', 'entire', 'graph', 'can', 'be', 'partitioned', 'into', 'a', 'number', 'of', 'spatial', 'regions', 'with', 'similar', 'edge', 'parameters', 'and', 'reasonably', 'regular', 'boundaries', 'we', 'develop', 'new', 'informationtheoretic', 'sample', 'complexity', 'bounds', 'and', 'show', 'that', 'a', 'bounded', 'number', 'of', 'samples', 'can', 'be', 'sufficient', 'to', 'consistently', 'recover', 'these', 'regions', 'finally', 'we', 'introduce', 'and', 'analyze', 'an', 'efficient', 'region', 'growing', 'algorithm', 'capable', 'of', 'recovering', 'the', 'regions', 'with', 'high', 'accuracy', 'we', 'show', 'that', 'it', 'is', 'consistent', 'and', 'demonstrate', 'its', 'performance', 'benefits', 'in', 'synthetic', 'simulations']] | [-0.10015277531667552, 0.08968127008671142, -0.03943116519429319, 0.052241097655582665, -0.06509197587918865, -0.11151781772847491, 0.0607388354975664, 0.39675201519276015, -0.25177831857151095, -0.3654582815343988, 0.10213471152172177, -0.28370331520953124, -0.13208654738918563, 0.1723587871487831, -0.09016860683449301, 0.04377438341950744, 0.08202687773671685, 0.059135902159125404, -0.00913574496659894, -0.27508557036955783, 0.2820343069770765, 0.04817924670566469, 0.2818531026118628, 0.015614761122276444, 0.05978962122848445, -0.015033351601867457, -0.00990514205934028, 0.06715187651295347, -0.1069771760995703, 0.10697157738782664, 0.26375647280475445, 0.15847000206294387, 0.2706473548042439, -0.42171588952240835, -0.2189976577399045, 0.17084837108905587, 0.15543458193331164, 0.09892217302832686, -0.023924502902736573, -0.23239038581959903, 0.1398590618052889, -0.12507108422895183, -0.09050555243542606, -0.06497743663504808, 0.003601957561679669, -0.002157675731960221, -0.3178166392529328, 0.056921574096994464, 0.026165359579825763, 0.004793637349496226, -0.018849355866443696, -0.12421974565244152, -0.024345894027280914, 0.14403908697839346, 0.013174304835768362, 0.010567247936469034, 0.09754898709096235, -0.14843117681431126, -0.08741674003791967, 0.3404289187020319, -0.03640046820286303, -0.18915498954899743, 0.20321721110228427, -0.1609216350180334, -0.13400046101402072, 0.15914568329263015, 0.19636260778725853, 0.1452917215089209, -0.11965438215375104, 0.051250880825217573, -0.072462151893387, 0.17858710834624233, 0.029398436027099573, 0.05693351939808269, 0.16112630328951547, 0.18018280874976347, 0.11516739083309355, 0.19313082164194786, -0.10298404681149143, -0.06234579849933114, -0.27781660915435064, -0.12759050072760447, -0.22585343833001517, -0.015653981601257295, -0.17416577326848873, -0.15016856894612426, 0.40179171468842134, 0.21814376370268032, 0.25393515684953255, 0.10175354122432202, 0.2977012495383532, 0.0777408765093699, 0.07025290685898718, 0.14236417905422005, 0.18183451837490824, 0.10192535871077747, -0.005460087169297921, -0.1693540596590548, 0.10703978385809346, 0.011981375355906536] |
1,802.03849 | Large Deviations of Convex Polyominoes | Enumeration of various types of lattice polygons and in particular
polyominoes is of primary importance in many machine learning, pattern
recognition, and geometric analysis problems. In this work, we develop a large
deviation principle for convex polyominoes under different restrictions, such
as fixed area and/or perimeter.
| math.PR | enumeration of various types of lattice polygons and in particular polyominoes is of primary importance in many machine learning pattern recognition and geometric analysis problems in this work we develop a large deviation principle for convex polyominoes under different restrictions such as fixed area andor perimeter | [['enumeration', 'of', 'various', 'types', 'of', 'lattice', 'polygons', 'and', 'in', 'particular', 'polyominoes', 'is', 'of', 'primary', 'importance', 'in', 'many', 'machine', 'learning', 'pattern', 'recognition', 'and', 'geometric', 'analysis', 'problems', 'in', 'this', 'work', 'we', 'develop', 'a', 'large', 'deviation', 'principle', 'for', 'convex', 'polyominoes', 'under', 'different', 'restrictions', 'such', 'as', 'fixed', 'area', 'andor', 'perimeter']] | [-0.11659817593982039, 0.09295304569051317, -0.05239311842571782, 0.09300932646526591, -0.1040914983579727, -0.14879197164681618, 0.051304524238018887, 0.3796728153348617, -0.31325195987870835, -0.3151069354751836, 0.14713005129622458, -0.2640568025248206, -0.19079352757367102, 0.18670004306604032, -0.20493002693452264, 0.1312217201794619, 0.0775467607030726, -0.024216085631886253, -0.0649148802495683, -0.24831891845425832, 0.29212363635230326, -0.04604583959419118, 0.3138521005925925, 0.07331246430302323, 0.07404655664551842, 0.09064147934196112, 0.028740388432355678, 0.10948699210648952, -0.17312398034593332, 0.18188368341804523, 0.30956694499953935, 0.16215686565872445, 0.2753364608987518, -0.4118588951051883, -0.18837826038994218, 0.16827106992106722, 0.13225046761394682, 0.07702989613070436, -0.05807367584708592, -0.18218159570318201, 0.05594379752975605, -0.10627861693501472, -0.12019463944370332, -0.05572544957470635, 0.06600786452991483, 0.06428070698419343, -0.21805921895429492, -0.015833312200139397, 0.12316733744481335, 0.19356548235468243, -0.02736516580309557, -0.1668429954746819, 0.08699075277115259, 0.11582665506790837, 0.10133900602206426, 0.005465127117729381, 0.13521943566308398, -0.12223316716414917, -0.16551327029162127, 0.4156815472828305, 0.04800965120691968, -0.2519974838132444, 0.1972381609653973, -0.10756283192692892, -0.26990639679538814, 0.09515369678442569, 0.24360279724730746, 0.14529230832324727, -0.1686078456999815, 0.10267061466583982, -0.08981170933491187, 0.06389924348585065, 0.16015277072058423, 0.007297174478678599, 0.2150100485279994, 0.1961464913835263, 0.13453702065643205, 0.2087257031108374, -0.08947758992081103, -0.12444041648110293, -0.2735799195487862, -0.09366580574651776, -0.19397528167895, -0.0187384681852089, -0.16552199810963508, -0.21166313688635177, 0.3478488739701393, 0.09309813058327722, 0.15056844741996864, 0.13294073287903777, 0.24996045167031494, 0.00545430565809669, 0.09073505042444753, 0.026139452840889924, 0.12098322553388045, 0.07566078962839168, 0.033291055294482605, -0.16571567686396124, 0.03209436911603679, 0.09439411866681083] |
1,802.0385 | Scientific Methodology: A View from Early String Theory | This paper addresses the question as to whether the methodology followed in
building and assessing string theory can be considered scientific in the same
sense, say, that the methodology followed in building and assessing the
Standard Model of particle physics is scientific, by focussing on the
"founding" period of the theory. More precisely, its aim is to argue for a
positive answer to the above question (there is no real change of scientific
status in the way of proceeding and reasoning in fundamental physical research)
in the light of a historical analysis of the early developments of the string
theoretical framework.
| physics.hist-ph | this paper addresses the question as to whether the methodology followed in building and assessing string theory can be considered scientific in the same sense say that the methodology followed in building and assessing the standard model of particle physics is scientific by focussing on the founding period of the theory more precisely its aim is to argue for a positive answer to the above question there is no real change of scientific status in the way of proceeding and reasoning in fundamental physical research in the light of a historical analysis of the early developments of the string theoretical framework | [['this', 'paper', 'addresses', 'the', 'question', 'as', 'to', 'whether', 'the', 'methodology', 'followed', 'in', 'building', 'and', 'assessing', 'string', 'theory', 'can', 'be', 'considered', 'scientific', 'in', 'the', 'same', 'sense', 'say', 'that', 'the', 'methodology', 'followed', 'in', 'building', 'and', 'assessing', 'the', 'standard', 'model', 'of', 'particle', 'physics', 'is', 'scientific', 'by', 'focussing', 'on', 'the', 'founding', 'period', 'of', 'the', 'theory', 'more', 'precisely', 'its', 'aim', 'is', 'to', 'argue', 'for', 'a', 'positive', 'answer', 'to', 'the', 'above', 'question', 'there', 'is', 'no', 'real', 'change', 'of', 'scientific', 'status', 'in', 'the', 'way', 'of', 'proceeding', 'and', 'reasoning', 'in', 'fundamental', 'physical', 'research', 'in', 'the', 'light', 'of', 'a', 'historical', 'analysis', 'of', 'the', 'early', 'developments', 'of', 'the', 'string', 'theoretical', 'framework']] | [-0.06700880496214043, 0.1129681953127579, -0.0907557228451023, 0.08467221556295927, -0.08719363442557578, -0.09400626379387951, 0.05582032269581525, 0.30513673722006307, -0.2611808855049681, -0.3406665139001135, 0.09515583690136008, -0.23810557764724338, -0.18346954154606798, 0.2148450218950223, -0.0972246613427259, 0.0313185306795006, 0.0391130809174242, 0.0651413576336264, -0.029186453797052255, -0.2704722622483231, 0.3160624555127677, 0.08684833619125777, 0.28107532967887083, 0.09905427594733711, 0.039696728893657135, 0.011830614188151194, -0.13212573551486412, -0.004463131419650399, -0.11396468624434869, 0.1651639118421786, 0.285220014761285, 0.23938219996150767, 0.3400586672348551, -0.4198973462594175, -0.1980334762391625, 0.0709644484951502, 0.12251027877036814, 0.09866927403006887, -0.0405945799442868, -0.24886183396424397, 0.09158344355199745, -0.12703199879183333, -0.159940283298308, -0.008144354885720675, 0.04925432202802731, -0.05801667072948548, -0.1806720630680718, 0.016495154005254038, 0.09297571707480025, 0.09754664051152839, -0.038631690187739334, -0.0769367773860398, 0.03467569615470596, 0.13779671320525727, 0.10282664529272056, 0.07849983152089696, 0.10724586763852599, -0.15167462973772447, -0.14711867790959665, 0.42090921955976157, -0.044434707044706784, -0.15619938529677468, 0.1550919835059212, -0.1509013238482841, -0.1673135869112788, 0.01673299461686154, 0.16599216481836715, 0.09108973625530996, -0.16392346440196628, 0.11796036383683452, -0.02035117315331308, 0.1429035635572849, 0.041983532313589415, -0.014876840697223375, 0.2781471055517397, 0.2325537803555184, 0.01394937503944603, 0.08752206471831639, -0.00033553403405712384, -0.12135154459311968, -0.32348022724289704, -0.16743830359070608, -0.15126124130432853, 0.035529253572124136, -0.008203719945026257, -0.1714828133601511, 0.42519306417296426, 0.19553888541655523, 0.17175591680783742, -0.015281239270905751, 0.27484617184958243, 0.06883351317961875, -0.019666329847324852, 0.02965008626728881, 0.23013894465558304, 0.11115478943009852, 0.1220108490889099, -0.17075779581543907, 0.08269464178010821, 0.05090999288834853] |
1,802.03851 | Webs for permutation supermodules of type Q | We give a diagrammatic calculus for the intertwiners between permutation
supermodules over the Sergeev superalgebra. We also give a diagrammatic basis
for the space of intertwiners between two permutation supermodules.
| math.RT | we give a diagrammatic calculus for the intertwiners between permutation supermodules over the sergeev superalgebra we also give a diagrammatic basis for the space of intertwiners between two permutation supermodules | [['we', 'give', 'a', 'diagrammatic', 'calculus', 'for', 'the', 'intertwiners', 'between', 'permutation', 'supermodules', 'over', 'the', 'sergeev', 'superalgebra', 'we', 'also', 'give', 'a', 'diagrammatic', 'basis', 'for', 'the', 'space', 'of', 'intertwiners', 'between', 'two', 'permutation', 'supermodules']] | [-0.18578391432141264, 0.10677417078986765, -0.15604638227572043, 0.07773057346542676, -0.1158990565687418, -0.10494302321846287, 0.044578589995702106, 0.3879874107738336, -0.31168477833271024, -0.16180582282443842, -0.0003236126775542895, -0.18533374030763905, -0.18227172953387102, 0.21213801155487697, -0.08606571344037851, -0.08963702227920294, 0.0424094141771396, 0.09387397083143394, -0.20869627421100934, -0.28437577399114766, 0.33504970197876294, -0.04046087401608626, 0.20966228016962607, 0.013699413339296976, 0.1861767662378649, 0.1235902493664374, -0.028751962011059125, -0.08904374296253081, -0.13385442501554887, 0.1728312149643898, 0.36629787683486936, 0.12318594828248024, 0.12789775412529708, -0.44832032937556504, 0.006421742308884859, 0.1313887539630135, 0.1606875058573981, 0.10679647425810496, -0.027737036657830078, -0.31387528291282557, 0.014624620104829471, -0.33205702863633635, -0.028498656675219537, -0.13012200482189656, 0.11141781198481719, -0.09135022337237994, -0.20319164209067822, -0.007593948371747198, 0.028478586052854856, 0.19662525871147712, -0.026563677564263345, -0.13135410696268082, 0.003815776544312636, 0.10559975480039914, -0.11284827577571074, -0.027165491553023457, 0.01861146977171302, -0.039322471246123314, -0.25511023175592223, 0.28322719087203346, -0.0028652376184860866, -0.2832675551374753, 0.08455707281827926, -0.17376631125807762, -0.2093177828937769, 0.01754596208532651, -0.00700185385843118, 0.09856999597201745, -0.08256211473296086, 0.2013180616001288, -0.19375590775161983, 0.007113944801191489, 0.14203151573116582, 0.03234805129468441, 0.14049403499811888, 0.040520022188623744, 0.03325605848804116, 0.18399431103219588, 0.024359939495722453, -0.07239318086455265, -0.4343642776211103, -0.2712819198767344, -0.02105544169122974, 0.09861555496851603, -0.1572531501762569, -0.1792878617377331, 0.45060743160235384, 0.17242887997999787, 0.18544229244192442, 0.21011334691817563, 0.1473851313193639, 0.09698717687278986, 0.10139431127657493, -0.009944566463430723, 0.06822426995883385, 0.3384668527171016, -0.03410859370681767, -0.13780512946347395, -0.10185205922462046, 0.34560383558273317] |
1,802.03852 | A Personalized Method for Calorie Consumption Assessment | This paper proposes an image-processing-based method for personalization of
calorie consumption assessment during exercising. An experiment is carried out
where several actions are required in an exercise called broadcast gymnastics,
especially popular in Japan and China. We use Kinect, which captures body
actions by separating the body into joints and segments that contain them, to
monitor body movements to test the velocity of each body joint and capture the
subject's image for calculating the mass of each body joint that differs for
each subject. By a kinetic energy formula, we obtain the kinetic energy of each
body joint, and calories consumed during exercise are calculated in this
process. We evaluate the performance of our method by benchmarking it to
Fitbit, a smart watch well-known for health monitoring during exercise. The
experimental results in this paper show that our method outperforms a
state-of-the-art calorie assessment method, which we base on and improve, in
terms of the error rate from Fitbit's ground-truth values.
| cs.HC | this paper proposes an imageprocessingbased method for personalization of calorie consumption assessment during exercising an experiment is carried out where several actions are required in an exercise called broadcast gymnastics especially popular in japan and china we use kinect which captures body actions by separating the body into joints and segments that contain them to monitor body movements to test the velocity of each body joint and capture the subjects image for calculating the mass of each body joint that differs for each subject by a kinetic energy formula we obtain the kinetic energy of each body joint and calories consumed during exercise are calculated in this process we evaluate the performance of our method by benchmarking it to fitbit a smart watch wellknown for health monitoring during exercise the experimental results in this paper show that our method outperforms a stateoftheart calorie assessment method which we base on and improve in terms of the error rate from fitbits groundtruth values | [['this', 'paper', 'proposes', 'an', 'imageprocessingbased', 'method', 'for', 'personalization', 'of', 'calorie', 'consumption', 'assessment', 'during', 'exercising', 'an', 'experiment', 'is', 'carried', 'out', 'where', 'several', 'actions', 'are', 'required', 'in', 'an', 'exercise', 'called', 'broadcast', 'gymnastics', 'especially', 'popular', 'in', 'japan', 'and', 'china', 'we', 'use', 'kinect', 'which', 'captures', 'body', 'actions', 'by', 'separating', 'the', 'body', 'into', 'joints', 'and', 'segments', 'that', 'contain', 'them', 'to', 'monitor', 'body', 'movements', 'to', 'test', 'the', 'velocity', 'of', 'each', 'body', 'joint', 'and', 'capture', 'the', 'subjects', 'image', 'for', 'calculating', 'the', 'mass', 'of', 'each', 'body', 'joint', 'that', 'differs', 'for', 'each', 'subject', 'by', 'a', 'kinetic', 'energy', 'formula', 'we', 'obtain', 'the', 'kinetic', 'energy', 'of', 'each', 'body', 'joint', 'and', 'calories', 'consumed', 'during', 'exercise', 'are', 'calculated', 'in', 'this', 'process', 'we', 'evaluate', 'the', 'performance', 'of', 'our', 'method', 'by', 'benchmarking', 'it', 'to', 'fitbit', 'a', 'smart', 'watch', 'wellknown', 'for', 'health', 'monitoring', 'during', 'exercise', 'the', 'experimental', 'results', 'in', 'this', 'paper', 'show', 'that', 'our', 'method', 'outperforms', 'a', 'stateoftheart', 'calorie', 'assessment', 'method', 'which', 'we', 'base', 'on', 'and', 'improve', 'in', 'terms', 'of', 'the', 'error', 'rate', 'from', 'fitbits', 'groundtruth', 'values']] | [-0.052542442939121206, 0.026627191169163265, -0.07922469283331116, 0.008140991216819861, -0.056633443066428577, -0.12098691758037831, 0.057959214766632836, 0.38528961170488185, -0.20635302556069485, -0.3279675715280779, 0.09201460816229712, -0.30019107730854183, -0.15285712974907467, 0.2346445873493926, -0.16284551537074382, 0.03804483200775228, 0.12785953666235805, 0.06973587180657675, -0.022041791519911598, -0.24602232711776248, 0.2667263472297539, 0.06549487389190672, 0.3077114076593762, 0.05090271919649446, 0.14182978916881056, 0.04405537102980621, -0.058906129973577394, -0.002621080702955618, -0.11315603210489557, 0.14868100094220912, 0.28198091081290877, 0.19716839152300414, 0.315266932510191, -0.4208945414613722, -0.19813836133400411, 0.08055152546514834, 0.08886904606805036, 0.053393754285156914, -0.036941899907037196, -0.31293874122085247, 0.07365877259487533, -0.2271345139689064, -0.05608223873917628, -0.08038165583128824, 0.015596489345877425, 0.010969273775300515, -0.2922798523199071, 0.054687995774050556, 0.00649895560019796, 0.07897297119569478, -0.12030210394013978, -0.0984911849640263, 0.016270370118202107, 0.23233572384576845, 0.11299449651858641, 0.01772507434160267, 0.17784996113136597, -0.12620337241809373, -0.10162398553271808, 0.3698521762626515, -0.014282228009271546, -0.18749946990319816, 0.1521360521811008, -0.0796994180887141, -0.1315723275084857, 0.11202895486838647, 0.22478764280149677, 0.11139499347323095, -0.19541416807486764, -0.019082548517408728, -0.020660610711377748, 0.17666314724018597, 0.06570694574488783, -0.0658663542759634, 0.17934978077387284, 0.19612512056007045, 0.05901670663283681, 0.15759947167565963, -0.1268104478724538, -0.07931747790074574, -0.2722737704273372, -0.17233476356702782, -0.1785762666390752, -0.042920115950031194, -0.03825568845859837, -0.10949677550497483, 0.4195792658500514, 0.2025471995789675, 0.1678424821229382, 0.06807512194123236, 0.366501168142887, 0.04197113093357744, 0.05550270553959428, 0.08711444962558881, 0.1941721444801609, -0.011104082400213528, 0.12464807213887384, -0.21837097695595203, 0.08577585101432209, 0.05882080959468427] |
1,802.03853 | Geodesic planes in the convex core of an acylindrical 3-manifold | Let $M$ be a convex cocompact acylindrical hyperbolic 3-manifold of infinite
volume, and let $M^*$ denote the interior of the convex core of $M$. In this
paper we show that any geodesic plane in $M^*$ is either closed or dense. We
also show that only countably many planes are closed. These are the first
rigidity theorems for planes in convex cocompact 3-manifolds of infinite volume
that depend only on the topology of M.
| math.DS math.GT | let m be a convex cocompact acylindrical hyperbolic 3manifold of infinite volume and let m denote the interior of the convex core of m in this paper we show that any geodesic plane in m is either closed or dense we also show that only countably many planes are closed these are the first rigidity theorems for planes in convex cocompact 3manifolds of infinite volume that depend only on the topology of m | [['let', 'm', 'be', 'a', 'convex', 'cocompact', 'acylindrical', 'hyperbolic', '3manifold', 'of', 'infinite', 'volume', 'and', 'let', 'm', 'denote', 'the', 'interior', 'of', 'the', 'convex', 'core', 'of', 'm', 'in', 'this', 'paper', 'we', 'show', 'that', 'any', 'geodesic', 'plane', 'in', 'm', 'is', 'either', 'closed', 'or', 'dense', 'we', 'also', 'show', 'that', 'only', 'countably', 'many', 'planes', 'are', 'closed', 'these', 'are', 'the', 'first', 'rigidity', 'theorems', 'for', 'planes', 'in', 'convex', 'cocompact', '3manifolds', 'of', 'infinite', 'volume', 'that', 'depend', 'only', 'on', 'the', 'topology', 'of', 'm']] | [-0.24389114269144732, 0.18634998788164087, -0.06231784948135075, 0.014802701490586751, -0.1154477781399268, -0.12020118142261285, 0.012020895004030061, 0.3778878249840377, -0.2804471412546014, -0.20424232708468829, 0.1384262840904627, -0.305244543474831, -0.1094500230488125, 0.2195759580521653, -0.1890576506186634, -0.048987232403804176, 0.09256013440708183, 0.10085308002563168, -0.11969050415791571, -0.2718613363087994, 0.38108774190385863, -0.15740906704880603, 0.1552436526048265, 0.11715416816280108, 0.12593149862009778, 0.00011337202756780467, 0.01907056170094707, 0.12642272414754413, -0.20088425242772234, 0.11925843096504064, 0.3042838669458583, 0.08416680437640274, 0.20745064270657118, -0.4079084559471334, -0.21587092826168422, 0.23716332351355113, 0.1718487594251151, -0.11819089163247853, -0.032470393264092096, -0.24452072549101017, 0.15092894564421006, -0.05915982074627321, -0.14811304933710456, -0.031459935200847174, 0.0746362491459777, 0.044249302822433105, -0.17815442472594242, -0.005245370793950502, 0.17501645698531032, 0.07731218406394737, -0.07551955095530577, -0.10216662533938477, -0.0849403425387732, 0.09688239082477171, -0.0263359786795886, 0.09265003999861034, 0.08907064699810253, 0.05189747820378677, -0.06464183410910303, 0.3854577552131696, -0.07139912271259787, -0.3112155007428094, 0.13734686614511765, -0.24110465059184458, -0.1697822732544721, 0.17648194359028585, 0.20734493654501968, 0.20583820653033175, -0.058623489962048726, 0.2708711712804546, -0.18040452392338074, 0.0816223681713008, 0.10769456854625924, -0.0456084474516165, 0.16903685445399724, 0.09510957982952464, 0.1723554464422281, 0.12640931659811877, 0.024398126974319145, 0.006780326136783378, -0.37909906525930315, -0.20482597088007487, -0.21652053109823075, 0.1421882116860927, -0.16977805714421962, -0.22866962135654606, 0.24854808641208515, -0.035944523085674196, 0.1511990945939332, 0.13459718250350594, 0.25154629191511296, -0.011646278479219452, 0.0063909437532906664, 0.17017903526581518, 0.09664132992724238, 0.16452714915655248, -0.1252398815401511, -0.1704692711945215, -0.04322339710460542, 0.1766674635319473] |
1,802.03854 | Steinberg's theorem for crystallographic complex reflection groups | Popov classified crystallographic complex reflection groups by determining
lattices they stabilize. These analogs of affine Weyl groups have infinite
order and are generated by reflections about affine hyperplanes; most arise as
the semi-direct product of a finite complex reflection group and a full rank
lattice. Steinberg's fixed point theorem asserts that the regular orbits under
the action of a reflection group are exactly the orbits lying off of reflecting
hyperplanes. This theorem holds for finite reflection groups (real or complex)
and also affine Weyl groups but fails for some crystallographic complex
reflection groups. We determine when Steinberg's theorem holds for the infinite
family of crystallographic complex reflection groups. We include
crystallographic groups built on finite Coxeter groups.
| math.CO math.RT | popov classified crystallographic complex reflection groups by determining lattices they stabilize these analogs of affine weyl groups have infinite order and are generated by reflections about affine hyperplanes most arise as the semidirect product of a finite complex reflection group and a full rank lattice steinbergs fixed point theorem asserts that the regular orbits under the action of a reflection group are exactly the orbits lying off of reflecting hyperplanes this theorem holds for finite reflection groups real or complex and also affine weyl groups but fails for some crystallographic complex reflection groups we determine when steinbergs theorem holds for the infinite family of crystallographic complex reflection groups we include crystallographic groups built on finite coxeter groups | [['popov', 'classified', 'crystallographic', 'complex', 'reflection', 'groups', 'by', 'determining', 'lattices', 'they', 'stabilize', 'these', 'analogs', 'of', 'affine', 'weyl', 'groups', 'have', 'infinite', 'order', 'and', 'are', 'generated', 'by', 'reflections', 'about', 'affine', 'hyperplanes', 'most', 'arise', 'as', 'the', 'semidirect', 'product', 'of', 'a', 'finite', 'complex', 'reflection', 'group', 'and', 'a', 'full', 'rank', 'lattice', 'steinbergs', 'fixed', 'point', 'theorem', 'asserts', 'that', 'the', 'regular', 'orbits', 'under', 'the', 'action', 'of', 'a', 'reflection', 'group', 'are', 'exactly', 'the', 'orbits', 'lying', 'off', 'of', 'reflecting', 'hyperplanes', 'this', 'theorem', 'holds', 'for', 'finite', 'reflection', 'groups', 'real', 'or', 'complex', 'and', 'also', 'affine', 'weyl', 'groups', 'but', 'fails', 'for', 'some', 'crystallographic', 'complex', 'reflection', 'groups', 'we', 'determine', 'when', 'steinbergs', 'theorem', 'holds', 'for', 'the', 'infinite', 'family', 'of', 'crystallographic', 'complex', 'reflection', 'groups', 'we', 'include', 'crystallographic', 'groups', 'built', 'on', 'finite', 'coxeter', 'groups']] | [-0.21665310236211452, 0.17150258493378887, -0.0918377441728217, 0.04811543068136128, -0.15289349616584805, -0.16250770993960592, 0.05823245700289551, 0.4264599213169681, -0.30534098770282364, -0.1851704509403461, 0.11782944797434741, -0.24136860176331848, -0.11340259014167146, 0.21259872708270627, -0.0945331857770554, -0.06049543692686587, -0.012053953659598582, 0.08193912733401944, -0.11106211465731677, -0.316840077097663, 0.4069554900798278, -0.09947259386635235, 0.26868313395728666, -0.012356295256823715, 0.09162791828728384, 0.1261841010135145, -0.026189413817169573, 0.009936179273212567, -0.07382871992081358, 0.11127444914378957, 0.3367453018227258, -0.03377677581838181, 0.13460786915264833, -0.3549533625786057, -0.17236693386529756, 0.1585913628228327, 0.12078355711339535, 0.05467902573072312, -0.06578703892604312, -0.3067405631638363, 0.10416645145553172, -0.16383978520305112, -0.2533295738598348, -0.023446233566993706, 0.008151262116013493, -0.01115230216175063, -0.15408950029179835, 0.0355754751594176, 0.13441715882613492, 0.18650589353986022, -0.09482221814413738, -0.09467377125994007, -0.08236030861337343, 0.16387452112046133, -0.011993131548580196, -0.08336659787923224, 0.12517864601766196, 0.003243027722590372, -0.1634187449195669, 0.5024061108054793, 0.07687039012547073, -0.18903168680894578, 0.18584656714597064, -0.2179570172666612, -0.1874196901678657, 0.17409573329819572, 0.1287150730012765, 0.09019769082750337, 0.005045817290710357, 0.19890654323330054, -0.162135896153557, 0.03717531282260703, 0.16696056460913938, -0.050572179994171754, 0.13183443953529891, -0.01786845771030674, 0.0963142244801976, 0.09008066654284923, 0.06462712280858213, -0.002376082842835249, -0.3245324873739583, -0.19570331782914507, -0.10244671217540008, 0.10893007233722979, -0.1376260801982861, -0.21484731855746517, 0.3308428584032843, -0.0035103216735471007, 0.1327297948101838, 0.07453474384915625, 0.15378356830746287, 0.0789053053386175, 0.08254948138203631, 0.0420993085588432, 0.046160802556824684, 0.25563628847002345, -0.11992874355493192, -0.1468201600608185, -0.034578795007501655, 0.1896653424343492] |
1,802.03855 | MedTQ: Dynamic Topic Discovery and Query Generation for Medical
Ontologies | Biomedical ontology refers to a shared conceptualization for a biomedical
domain of interest that has vastly improved data management and data sharing
through the open data movement. The rapid growth and availability of biomedical
data make it impractical and computationally expensive to perform manual
analysis and query processing with the large scale ontologies. The lack of
ability in analyzing ontologies from such a variety of sources, and supporting
knowledge discovery for clinical practice and biomedical research should be
overcome with new technologies. In this study, we developed a Medical Topic
discovery and Query generation framework (MedTQ), which was composed by a
series of approaches and algorithms. A predicate neighborhood pattern-based
approach introduced has the ability to compute the similarity of predicates
(relations) in ontologies. Given a predicate similarity metric, machine
learning algorithms have been developed for automatic topic discovery and query
generation. The topic discovery algorithm, called the hierarchical K-Means
algorithm was designed by extending an existing supervised algorithm (K-means
clustering) for the construction of a topic hierarchy. In the hierarchical
K-Means algorithm, a level-by-level optimization strategy was selected for
consistent with the strongly association between elements within a topic.
Automatic query generation was facilitated for discovered topic that could be
guided users for interactive query design and processing. Evaluation was
conducted to generate topic hierarchy for DrugBank ontology as a case study.
Results demonstrated that the MedTQ framework can enhance knowledge discovery
by capturing underlying structures from domain specific data and ontologies.
| cs.DB cs.AI cs.IR | biomedical ontology refers to a shared conceptualization for a biomedical domain of interest that has vastly improved data management and data sharing through the open data movement the rapid growth and availability of biomedical data make it impractical and computationally expensive to perform manual analysis and query processing with the large scale ontologies the lack of ability in analyzing ontologies from such a variety of sources and supporting knowledge discovery for clinical practice and biomedical research should be overcome with new technologies in this study we developed a medical topic discovery and query generation framework medtq which was composed by a series of approaches and algorithms a predicate neighborhood patternbased approach introduced has the ability to compute the similarity of predicates relations in ontologies given a predicate similarity metric machine learning algorithms have been developed for automatic topic discovery and query generation the topic discovery algorithm called the hierarchical kmeans algorithm was designed by extending an existing supervised algorithm kmeans clustering for the construction of a topic hierarchy in the hierarchical kmeans algorithm a levelbylevel optimization strategy was selected for consistent with the strongly association between elements within a topic automatic query generation was facilitated for discovered topic that could be guided users for interactive query design and processing evaluation was conducted to generate topic hierarchy for drugbank ontology as a case study results demonstrated that the medtq framework can enhance knowledge discovery by capturing underlying structures from domain specific data and ontologies | [['biomedical', 'ontology', 'refers', 'to', 'a', 'shared', 'conceptualization', 'for', 'a', 'biomedical', 'domain', 'of', 'interest', 'that', 'has', 'vastly', 'improved', 'data', 'management', 'and', 'data', 'sharing', 'through', 'the', 'open', 'data', 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1,802.03856 | Quantum Algorithm for Optimization and Polynomial System Solving over
Finite Field and Application to Cryptanalysis | In this paper, we give quantum algorithms for two fundamental computation
problems: solving polynomial systems over finite fields and optimization where
the arguments of the objective function and constraints take values from a
finite field or a bounded interval of integers. The quantum algorithms can
solve these problems with any given success probability and have polynomial
runtime complexities in the size of the input, the degree of the inequality
constraints, and the condition number of certain matrices derived from the
problem. So, we achieved exponential speedup for these problems when their
condition numbers are small. As applications, quantum algorithms are given to
three basic computational problems in cryptography: the polynomial system with
noise problem, the short integer solution problem, the shortest vector problem,
as well as the cryptanalysis for the lattice based NTRU cryptosystem. It is
shown that these problems and NTRU can against quantum computer attacks only if
their condition numbers are large, so the condition number could be used as a
new criterion for the lattice based post-quantum cryptosystems.
| cs.SC cs.CC cs.CR quant-ph | in this paper we give quantum algorithms for two fundamental computation problems solving polynomial systems over finite fields and optimization where the arguments of the objective function and constraints take values from a finite field or a bounded interval of integers the quantum algorithms can solve these problems with any given success probability and have polynomial runtime complexities in the size of the input the degree of the inequality constraints and the condition number of certain matrices derived from the problem so we achieved exponential speedup for these problems when their condition numbers are small as applications quantum algorithms are given to three basic computational problems in cryptography the polynomial system with noise problem the short integer solution problem the shortest vector problem as well as the cryptanalysis for the lattice based ntru cryptosystem it is shown that these problems and ntru can against quantum computer attacks only if their condition numbers are large so the condition number could be used as a new criterion for the lattice based postquantum cryptosystems | [['in', 'this', 'paper', 'we', 'give', 'quantum', 'algorithms', 'for', 'two', 'fundamental', 'computation', 'problems', 'solving', 'polynomial', 'systems', 'over', 'finite', 'fields', 'and', 'optimization', 'where', 'the', 'arguments', 'of', 'the', 'objective', 'function', 'and', 'constraints', 'take', 'values', 'from', 'a', 'finite', 'field', 'or', 'a', 'bounded', 'interval', 'of', 'integers', 'the', 'quantum', 'algorithms', 'can', 'solve', 'these', 'problems', 'with', 'any', 'given', 'success', 'probability', 'and', 'have', 'polynomial', 'runtime', 'complexities', 'in', 'the', 'size', 'of', 'the', 'input', 'the', 'degree', 'of', 'the', 'inequality', 'constraints', 'and', 'the', 'condition', 'number', 'of', 'certain', 'matrices', 'derived', 'from', 'the', 'problem', 'so', 'we', 'achieved', 'exponential', 'speedup', 'for', 'these', 'problems', 'when', 'their', 'condition', 'numbers', 'are', 'small', 'as', 'applications', 'quantum', 'algorithms', 'are', 'given', 'to', 'three', 'basic', 'computational', 'problems', 'in', 'cryptography', 'the', 'polynomial', 'system', 'with', 'noise', 'problem', 'the', 'short', 'integer', 'solution', 'problem', 'the', 'shortest', 'vector', 'problem', 'as', 'well', 'as', 'the', 'cryptanalysis', 'for', 'the', 'lattice', 'based', 'ntru', 'cryptosystem', 'it', 'is', 'shown', 'that', 'these', 'problems', 'and', 'ntru', 'can', 'against', 'quantum', 'computer', 'attacks', 'only', 'if', 'their', 'condition', 'numbers', 'are', 'large', 'so', 'the', 'condition', 'number', 'could', 'be', 'used', 'as', 'a', 'new', 'criterion', 'for', 'the', 'lattice', 'based', 'postquantum', 'cryptosystems']] | [-0.15929512420808078, 0.07713637154614716, -0.0795920839075718, 0.08246529465051074, -0.07634769931805936, -0.21072684371931075, 0.024705819080975886, 0.32967438085048256, -0.3497192669790565, -0.3306087271381191, 0.16435786142839087, -0.21569306475698555, -0.17009277043357623, 0.2627244413522622, -0.08534940436454518, 0.18195659931068656, 0.06411659627763434, 0.04872116215979103, -0.06462506713530822, -0.3677361289894328, 0.3026699285820802, -0.024125044345746787, 0.22993805715324064, 0.08250104633469015, 0.10550448500168508, -0.01904912058356605, 0.039330882200023586, 0.041253335648679244, -0.10563995988859301, 0.09704231785348895, 0.28245039677454364, 0.1918925114673132, 0.32529475439710226, -0.42214949131665525, -0.17055690433688417, 0.17671513596511507, 0.1343333508822065, 0.1382008836070574, -0.019819514376617837, -0.24521431047605535, 0.12587226595054243, -0.12621231650743342, -0.07394580936810949, -0.036703024794788736, 0.007775544810479191, 0.04838962691471155, -0.289406636936797, 0.023361126381675142, 0.04738732825893887, 0.07838076203026706, -0.01672144161846369, -0.14627592347777443, 0.0814998649041664, 0.09865066064715695, 0.02468296605412854, 0.0016008099971328213, 0.07980409084835596, -0.1367698932020266, -0.18847075830164708, 0.41763361197030335, 0.01591667427670494, -0.24965927300277596, 0.12247259167229964, -0.04858295121556965, -0.14838936581815543, 0.09316371530308035, 0.17744512201902288, 0.13901920680076493, -0.07636893744219969, 0.1263217703035586, -0.0625354234913462, 0.1570590868107539, 0.053561734497187694, 0.08696866456598959, 0.14398819474062244, 0.07762553916198381, 0.11570260801477826, 0.1465169644270539, -0.014999625232201396, -0.11930954934517193, -0.28911496397129627, -0.12653745011540882, -0.22807603229752235, 0.03388226484847173, -0.11904580312417153, -0.17683021017341405, 0.33629844078184135, 0.12856005316556632, 0.16796776534695373, 0.11312372974740963, 0.3105436628030842, 0.15400693741795873, 0.049770735794125526, 0.09720202637726559, 0.14985634307976137, 0.14468495142019805, 0.07638479246314049, -0.18143660836847642, 0.08647674651358996, 0.11010315221601931] |
1,802.03857 | Critical varieties and motivic equivalence for algebras with involution | Motivic equivalence for algebraic groups was recently introduced in [9],
where a characterization of motivic equivalent groups in terms of higher Tits
indexes is given. As a consequence, if the quadrics associated to two quadratic
forms have the same Chow motives with coefficients in F_2, this remains true
for any two projective homogeneous varieties of the same type under the
orthogonal groups of those two quadratic forms. Our main result extends this to
all groups of classical type, and to some exceptional groups, introducing a
notion of critical variety. On the way, we prove that motivic equivalence of
the automorphism groups of two involutions can be checked after extending
scalars to some index reduction field, which depends on the type of the
involutions. In addition, we describe conditions on the base field which
guarantee that motivic equivalent involutions actually are isomorphic,
extending a result of Hoffmann on quadratic forms.
| math.AG | motivic equivalence for algebraic groups was recently introduced in 9 where a characterization of motivic equivalent groups in terms of higher tits indexes is given as a consequence if the quadrics associated to two quadratic forms have the same chow motives with coefficients in f_2 this remains true for any two projective homogeneous varieties of the same type under the orthogonal groups of those two quadratic forms our main result extends this to all groups of classical type and to some exceptional groups introducing a notion of critical variety on the way we prove that motivic equivalence of the automorphism groups of two involutions can be checked after extending scalars to some index reduction field which depends on the type of the involutions in addition we describe conditions on the base field which guarantee that motivic equivalent involutions actually are isomorphic extending a result of hoffmann on quadratic forms | [['motivic', 'equivalence', 'for', 'algebraic', 'groups', 'was', 'recently', 'introduced', 'in', '9', 'where', 'a', 'characterization', 'of', 'motivic', 'equivalent', 'groups', 'in', 'terms', 'of', 'higher', 'tits', 'indexes', 'is', 'given', 'as', 'a', 'consequence', 'if', 'the', 'quadrics', 'associated', 'to', 'two', 'quadratic', 'forms', 'have', 'the', 'same', 'chow', 'motives', 'with', 'coefficients', 'in', 'f_2', 'this', 'remains', 'true', 'for', 'any', 'two', 'projective', 'homogeneous', 'varieties', 'of', 'the', 'same', 'type', 'under', 'the', 'orthogonal', 'groups', 'of', 'those', 'two', 'quadratic', 'forms', 'our', 'main', 'result', 'extends', 'this', 'to', 'all', 'groups', 'of', 'classical', 'type', 'and', 'to', 'some', 'exceptional', 'groups', 'introducing', 'a', 'notion', 'of', 'critical', 'variety', 'on', 'the', 'way', 'we', 'prove', 'that', 'motivic', 'equivalence', 'of', 'the', 'automorphism', 'groups', 'of', 'two', 'involutions', 'can', 'be', 'checked', 'after', 'extending', 'scalars', 'to', 'some', 'index', 'reduction', 'field', 'which', 'depends', 'on', 'the', 'type', 'of', 'the', 'involutions', 'in', 'addition', 'we', 'describe', 'conditions', 'on', 'the', 'base', 'field', 'which', 'guarantee', 'that', 'motivic', 'equivalent', 'involutions', 'actually', 'are', 'isomorphic', 'extending', 'a', 'result', 'of', 'hoffmann', 'on', 'quadratic', 'forms']] | [-0.20151085247779452, 0.07535067046898723, -0.1222960902940507, 0.06985175183422601, -0.08785029943726157, -0.12451206148295794, 0.012812449371804728, 0.3192792682589701, -0.30912860907964257, -0.2363278078877886, 0.09898056942210126, -0.19676670255201975, -0.15787160611495019, 0.236009516543865, -0.16349193311277652, -0.03886374337098643, -0.01057743222527706, 0.08490870052623568, -0.11367401472236587, -0.35336886231331216, 0.44925461937642136, -0.04510565692771401, 0.24149688393746396, 0.0168288325891973, 0.07645395390326845, 0.012651308016201493, -0.029110237562266373, -0.014093809267709144, -0.09771395672549066, 0.13019864850258767, 0.3079088192633134, 0.03997183939435788, 0.20852542323007203, -0.3552302139492443, -0.1376051623186709, 0.19990288746549478, 0.12143699040686425, 0.02101806268539755, -0.020116202939526748, -0.24303083654943128, 0.1255282480949411, -0.17579569817901958, -0.1561695506027431, -0.0407696766153778, 0.02828282646166048, 0.043931220745630314, -0.21375054262356596, -0.004917904597100796, 0.09405155827435072, 0.15667548100307785, -0.12097826111286679, -0.10498091377764815, -0.04078443939078774, 0.09589701129636108, 0.028191557871302803, 0.007751142421749814, 0.07871991659252085, -0.07411274479720867, -0.14832875122872474, 0.3977593714558838, -0.051231047697990334, -0.19520775517511288, 0.1664446101652071, -0.1530722937977954, -0.19920300716306114, 0.11887926370493018, 0.06694775369743373, 0.1406805720742817, -0.03651499448831649, 0.1529611197840141, -0.12893743674277058, 0.08396974842270348, 0.1611253377886164, -0.0006996277585350628, 0.11085031123131814, 0.031925037622001745, 0.076968395473098, 0.14111236714673597, 0.06541347297982018, -0.044106963306240386, -0.3501967876749551, -0.22197056249496622, -0.06943949842247361, 0.13232194268747838, -0.1247334836968713, -0.1642650274916133, 0.4263800419929544, 0.07677267629132863, 0.15737943014367514, 0.1330392459460578, 0.2131254573199498, 0.05812135245494744, 0.09461807994893322, 0.013204665612366875, 0.17493569410223225, 0.23988930437551348, -0.060131362345594686, -0.10319758105660545, 0.006513259754884963, 0.19942970786887476] |
1,802.03858 | Machine Learning-based Variability Handling in IoT Agents | Agent-based IoT applications have recently been proposed in several domains,
such as health care, smart cities and agriculture. Deploying these applications
in specific settings has been very challenging for many reasons including the
complex static and dynamic variability of the physical devices such as sensors
and actuators, the software application behavior and the environment in which
the application is embedded. In this paper, we propose a self-configurable IoT
agent approach based on feedback-evaluative machine-learning. The approach
involves: i) a variability model of IoT agents; ii) generation of sets of
customized agents; iii) feedback evaluative machine learning; iv) modeling and
composition of a group of IoT agents; and v) a feature-selection method based
on manual and automatic feedback.
| cs.MA cs.LG | agentbased iot applications have recently been proposed in several domains such as health care smart cities and agriculture deploying these applications in specific settings has been very challenging for many reasons including the complex static and dynamic variability of the physical devices such as sensors and actuators the software application behavior and the environment in which the application is embedded in this paper we propose a selfconfigurable iot agent approach based on feedbackevaluative machinelearning the approach involves i a variability model of iot agents ii generation of sets of customized agents iii feedback evaluative machine learning iv modeling and composition of a group of iot agents and v a featureselection method based on manual and automatic feedback | [['agentbased', 'iot', 'applications', 'have', 'recently', 'been', 'proposed', 'in', 'several', 'domains', 'such', 'as', 'health', 'care', 'smart', 'cities', 'and', 'agriculture', 'deploying', 'these', 'applications', 'in', 'specific', 'settings', 'has', 'been', 'very', 'challenging', 'for', 'many', 'reasons', 'including', 'the', 'complex', 'static', 'and', 'dynamic', 'variability', 'of', 'the', 'physical', 'devices', 'such', 'as', 'sensors', 'and', 'actuators', 'the', 'software', 'application', 'behavior', 'and', 'the', 'environment', 'in', 'which', 'the', 'application', 'is', 'embedded', 'in', 'this', 'paper', 'we', 'propose', 'a', 'selfconfigurable', 'iot', 'agent', 'approach', 'based', 'on', 'feedbackevaluative', 'machinelearning', 'the', 'approach', 'involves', 'i', 'a', 'variability', 'model', 'of', 'iot', 'agents', 'ii', 'generation', 'of', 'sets', 'of', 'customized', 'agents', 'iii', 'feedback', 'evaluative', 'machine', 'learning', 'iv', 'modeling', 'and', 'composition', 'of', 'a', 'group', 'of', 'iot', 'agents', 'and', 'v', 'a', 'featureselection', 'method', 'based', 'on', 'manual', 'and', 'automatic', 'feedback']] | [-0.11110519660347752, 0.003490762756976845, -0.04049907004910296, 0.017096403013746223, -0.12711060511606648, -0.18352973172922843, 0.04549002637865889, 0.43125378395077485, -0.20909692515224693, -0.3380687049517793, 0.1458720913566328, -0.25661972823857876, -0.22109687931691135, 0.21598352674758142, -0.14991087889587829, 0.09056459419461417, 0.05176812267043339, 0.011910290260606542, 0.051886952851481476, -0.24265958379315822, 0.31098978807507405, -0.024621499339038313, 0.34532344499040907, 0.05211604354453498, 0.11956501837643184, -0.011094875730060298, -0.027797674419005113, 0.02137697248213828, -0.0415399806024025, 0.18327362568856315, 0.3549837087891225, 0.2216850013737085, 0.3931323806735173, -0.4378485901939586, -0.2500803997631763, 0.09492402756787387, 0.14462784384297014, 0.04630717235629383, -0.09293273483314712, -0.3180654598480283, 0.07323049288443771, -0.2694321859563733, -0.07263607357752586, -0.08647255905390043, 0.05633016452112974, 0.0751441788958079, -0.2630570764926359, -0.04019805608349371, 0.009421577785517377, 0.13695916169571914, -0.0798991713769471, -0.09077830564086165, 0.02512859740868564, 0.19551714596434913, 0.02466440414869355, -0.04307740066072036, 0.20710255847872508, -0.17418618939198746, -0.16158172709803129, 0.3931495473431102, 0.04678862537096801, -0.14748111170523898, 0.23720823477447867, 0.008712935771247179, -0.1954010654008016, 0.017647391191185934, 0.27549826407580286, 0.11901447526819037, -0.19959005727111523, 0.0852544530267739, 0.04466991482206203, 0.13508457672011492, -0.0032726924300418587, 0.02125354381759876, 0.1785380545690463, 0.275522375334825, 0.07675328859728199, 0.07395860614206899, -0.05524704158697518, -0.08711298285373326, -0.21779448447492103, -0.15952424169518054, -0.15923723346826718, 0.027435404094987837, -0.09091133134881665, -0.174882046717765, 0.3825318020013771, 0.19636979368969432, 0.12390995682377753, -0.0030238703846658483, 0.3718222152393568, 0.03784595282772427, 0.11350173168667142, 0.07549462311074202, 0.1443823649957455, 0.006443200753359446, 0.21842135000042617, -0.17292027946577632, 0.12388640405120456, -0.004167902871468586] |
1,802.03859 | The GAPS Programme with HARPS-N at TNG XVI: Measurement of the
Rossiter-McLaughlin effect of the transiting planetary systems HAT-P-3,
HAT-P-12, HAT-P-22, WASP-39 and WASP-60 | We characterised five transiting planetary systems (HAT-P-3, HAT-P-12,
HAT-P-22, WASP-39 and WASP-60) and determined their sky-projected planet
orbital obliquity through the measurement of the RM effect. We used HARPS-N
high-precision radial velocity measurements, gathered during transit events, to
measure the RM effect in the target systems and determine the sky-projected
angle between the planetary orbital plane and the stellar equator. The
characterisation of stellar atmospheric parameters was performed exploiting the
HARPS-N spectra, using line equivalent width ratios, and spectral synthesis
methods. Photometric parameters of the five transiting exoplanets were
re-analysed through 17 new light curves, obtained with an array of medium-class
telescopes, and other light curves from the literature. Survey-time-series
photometric data were analysed for determining the rotation periods of the five
stars and their spin inclination. From the analysis of the RM effect we derived
a sky-projected obliquity of 21.2 degree, -54 degree, -2.1 degree, 0 degree and
-129 degree for HAT-P-3b, HAT-P-12b, HAT-P-22b, WASP-39b and WASP-60b,
respectively. The latter value indicates that WASP-60b is moving on a
retrograde orbit. These values represent the first measurements of \lambda for
the five exoplanetary systems under study. The stellar activity of HAT-P-22
indicates a rotation period of 28.7 days, which allowed us to estimate the true
misalignment angle of HAT-P-22b, \psi=24 degree. The revision of the physical
parameters of the five exoplanetary systems returned values that are fully
compatible with those existing in the literature. The exception to this is the
WASP-60 system, for which, based on higher quality spectroscopic and
photometric data, we found a more massive and younger star and a larger and
hotter planet.
| astro-ph.EP | we characterised five transiting planetary systems hatp3 hatp12 hatp22 wasp39 and wasp60 and determined their skyprojected planet orbital obliquity through the measurement of the rm effect we used harpsn highprecision radial velocity measurements gathered during transit events to measure the rm effect in the target systems and determine the skyprojected angle between the planetary orbital plane and the stellar equator the characterisation of stellar atmospheric parameters was performed exploiting the harpsn spectra using line equivalent width ratios and spectral synthesis methods photometric parameters of the five transiting exoplanets were reanalysed through 17 new light curves obtained with an array of mediumclass telescopes and other light curves from the literature surveytimeseries photometric data were analysed for determining the rotation periods of the five stars and their spin inclination from the analysis of the rm effect we derived a skyprojected obliquity of 212 degree 54 degree 21 degree 0 degree and 129 degree for hatp3b hatp12b hatp22b wasp39b and wasp60b respectively the latter value indicates that wasp60b is moving on a retrograde orbit these values represent the first measurements of lambda for the five exoplanetary systems under study the stellar activity of hatp22 indicates a rotation period of 287 days which allowed us to estimate the true misalignment angle of hatp22b psi24 degree the revision of the physical parameters of the five exoplanetary systems returned values that are fully compatible with those existing in the literature the exception to this is the wasp60 system for which based on higher quality spectroscopic and photometric data we found a more massive and younger star and a larger and hotter planet | [['we', 'characterised', 'five', 'transiting', 'planetary', 'systems', 'hatp3', 'hatp12', 'hatp22', 'wasp39', 'and', 'wasp60', 'and', 'determined', 'their', 'skyprojected', 'planet', 'orbital', 'obliquity', 'through', 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