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1,802.0816 | Quantum Walk in Momentum Space with a Bose-Einstein Condensate | We present a discrete-time, one-dimensional quantum walk based on the
entanglement between the momentum of ultracold rubidium atoms (the walk space)
and two internal atomic states (the "coin" degree of freedom). Our scheme is
highly flexible and can provide a platform for a wide range of applications
such as quantum search algorithms, the observation of topological phases, and
the realization of walks with higher dimensionality. Along with the
investigation of the quantum-to-classical transition, we demonstrate the
distinctive features of a quantum walk and contrast them to those of its
classical counterpart. Also, by manipulating either the walk or coin operator,
we show how the walk dynamics can be steered or even reversed.
| quant-ph cond-mat.quant-gas physics.atom-ph | we present a discretetime onedimensional quantum walk based on the entanglement between the momentum of ultracold rubidium atoms the walk space and two internal atomic states the coin degree of freedom our scheme is highly flexible and can provide a platform for a wide range of applications such as quantum search algorithms the observation of topological phases and the realization of walks with higher dimensionality along with the investigation of the quantumtoclassical transition we demonstrate the distinctive features of a quantum walk and contrast them to those of its classical counterpart also by manipulating either the walk or coin operator we show how the walk dynamics can be steered or even reversed | [['we', 'present', 'a', 'discretetime', 'onedimensional', 'quantum', 'walk', 'based', 'on', 'the', 'entanglement', 'between', 'the', 'momentum', 'of', 'ultracold', 'rubidium', 'atoms', 'the', 'walk', 'space', 'and', 'two', 'internal', 'atomic', 'states', 'the', 'coin', 'degree', 'of', 'freedom', 'our', 'scheme', 'is', 'highly', 'flexible', 'and', 'can', 'provide', 'a', 'platform', 'for', 'a', 'wide', 'range', 'of', 'applications', 'such', 'as', 'quantum', 'search', 'algorithms', 'the', 'observation', 'of', 'topological', 'phases', 'and', 'the', 'realization', 'of', 'walks', 'with', 'higher', 'dimensionality', 'along', 'with', 'the', 'investigation', 'of', 'the', 'quantumtoclassical', 'transition', 'we', 'demonstrate', 'the', 'distinctive', 'features', 'of', 'a', 'quantum', 'walk', 'and', 'contrast', 'them', 'to', 'those', 'of', 'its', 'classical', 'counterpart', 'also', 'by', 'manipulating', 'either', 'the', 'walk', 'or', 'coin', 'operator', 'we', 'show', 'how', 'the', 'walk', 'dynamics', 'can', 'be', 'steered', 'or', 'even', 'reversed']] | [-0.13069361134798133, 0.2302376271774327, -0.09440922609064728, -0.007137844890719082, -0.0355589193911458, -0.2003326940341919, 0.07375972530280706, 0.42349347106314134, -0.2746061082247512, -0.2405252511047625, 0.09918435793640258, -0.2538366924771773, -0.16738750436759023, 0.18550053929876803, -0.0054687614860345745, 0.07965217485772362, 0.05143193229949767, 0.006603188927329029, -0.047165605333118164, -0.21234253269254363, 0.2736713524198941, 0.0280404097128277, 0.26795127712830435, 0.038720330817990804, 0.11407031563742619, 0.03222665316155014, 0.043544725277960036, -0.005245842135471841, -0.11004345510238116, 0.12771936090627736, 0.17472139566338488, 0.049818427550365287, 0.25097727768921424, -0.42774103640113026, -0.2163493205028187, 0.12895236614817154, 0.13641255321480067, 0.1941172175076125, -0.05642071332736772, -0.3761067615705542, -0.012366056980681606, -0.13939992335001858, -0.12806913323584013, -0.1021328665166428, -0.010694139321068568, 0.010906603752768465, -0.22066845664604834, 0.027279754588952137, 0.06857460431222405, 0.06775579270366247, 0.025657662447234282, -0.0391669554332371, 0.0038009065922649044, 0.11094749267795123, -0.06982601351878007, 0.0034620220841523924, 0.15837604117197251, -0.13674311639208878, -0.22986942139687017, 0.4280756768753885, -0.0674860045047743, -0.18661717440617004, 0.2097160444765385, -0.16617639063679235, -0.09453960925540221, 0.059088724898174405, 0.1503647780835828, 0.12226705584907904, -0.0876159497212419, 0.06500901514040638, -0.034953356512622644, 0.13977107698441874, 0.010809111458781575, 0.1274568747945263, 0.22179277864051983, 0.14339851576369256, 0.1056274679472803, 0.19680363577520307, -0.07655320821738444, -0.1781965865354453, -0.26608739867931164, -0.2233805900058152, -0.25074964616214857, 0.08235682839793819, -0.12830338508553854, -0.16868918780736358, 0.43835505814380277, 0.15961834659382085, 0.23037813875375182, 0.029313992309783186, 0.2703729946806561, 0.12650156959093042, 0.004495387930156929, 0.06297548591308962, 0.16351183890739257, 0.11663499170390423, 0.07965128564267486, -0.23318854367659828, 0.06495429049391532, 0.056272150499613156] |
1,802.08161 | Consistency of the maximum likelihood estimator in seasonal hidden
Markov models | In this paper, we introduce a variant of hidden Markov models in which the
transition probabilities between the states, as well as the emission
distributions, are not constant in time but vary in a periodic manner. This
class of models, that we will call seasonal hidden Markov models (SHMM) is
particularly useful in practice, as many applications involve a seasonal
behaviour. However, up to now, there is no theoretical result regarding this
kind of model. We show that under mild assumptions, SHMM are identifiable: we
can identify the transition matrices and the emission distributions from the
joint distribution of the observations on a period, up to state labelling. We
also give sufficient conditions for the strong consistency of the maximum
likelihood estimator (MLE). These results are applied to simulated data, using
the EM algorithm to compute the MLE. Finally, we show how SHMM can be used in
real world applications by applying our model to precipitation data, with
mixtures of exponential distributions as emission distributions.
| stat.AP stat.ME | in this paper we introduce a variant of hidden markov models in which the transition probabilities between the states as well as the emission distributions are not constant in time but vary in a periodic manner this class of models that we will call seasonal hidden markov models shmm is particularly useful in practice as many applications involve a seasonal behaviour however up to now there is no theoretical result regarding this kind of model we show that under mild assumptions shmm are identifiable we can identify the transition matrices and the emission distributions from the joint distribution of the observations on a period up to state labelling we also give sufficient conditions for the strong consistency of the maximum likelihood estimator mle these results are applied to simulated data using the em algorithm to compute the mle finally we show how shmm can be used in real world applications by applying our model to precipitation data with mixtures of exponential distributions as emission distributions | [['in', 'this', 'paper', 'we', 'introduce', 'a', 'variant', 'of', 'hidden', 'markov', 'models', 'in', 'which', 'the', 'transition', 'probabilities', 'between', 'the', 'states', 'as', 'well', 'as', 'the', 'emission', 'distributions', 'are', 'not', 'constant', 'in', 'time', 'but', 'vary', 'in', 'a', 'periodic', 'manner', 'this', 'class', 'of', 'models', 'that', 'we', 'will', 'call', 'seasonal', 'hidden', 'markov', 'models', 'shmm', 'is', 'particularly', 'useful', 'in', 'practice', 'as', 'many', 'applications', 'involve', 'a', 'seasonal', 'behaviour', 'however', 'up', 'to', 'now', 'there', 'is', 'no', 'theoretical', 'result', 'regarding', 'this', 'kind', 'of', 'model', 'we', 'show', 'that', 'under', 'mild', 'assumptions', 'shmm', 'are', 'identifiable', 'we', 'can', 'identify', 'the', 'transition', 'matrices', 'and', 'the', 'emission', 'distributions', 'from', 'the', 'joint', 'distribution', 'of', 'the', 'observations', 'on', 'a', 'period', 'up', 'to', 'state', 'labelling', 'we', 'also', 'give', 'sufficient', 'conditions', 'for', 'the', 'strong', 'consistency', 'of', 'the', 'maximum', 'likelihood', 'estimator', 'mle', 'these', 'results', 'are', 'applied', 'to', 'simulated', 'data', 'using', 'the', 'em', 'algorithm', 'to', 'compute', 'the', 'mle', 'finally', 'we', 'show', 'how', 'shmm', 'can', 'be', 'used', 'in', 'real', 'world', 'applications', 'by', 'applying', 'our', 'model', 'to', 'precipitation', 'data', 'with', 'mixtures', 'of', 'exponential', 'distributions', 'as', 'emission', 'distributions']] | [-0.05366426189430058, 0.11177666203090639, -0.10223488200625236, 0.12008262968579815, -0.051941622278624866, -0.1129532903715065, 0.046367526345067855, 0.4448191253299063, -0.26287833022123036, -0.3139814632323881, 0.13893642606721682, -0.24164430855519392, -0.16708082326998314, 0.18402800278343034, -0.08063342933204364, 0.06139046667764584, 0.0651955825784667, 0.009407196075401523, -0.05907998830080032, -0.24460105567775442, 0.29187647229568525, 0.04359877189818882, 0.27012810326661124, 0.02620297373293645, 0.07333664257135807, -0.02259489774534648, 0.016803215952434888, 0.005314104837563002, -0.12749499091781522, 0.08292277551954612, 0.24998325240870173, 0.19258578302846713, 0.23786603984507648, -0.3886799061840231, -0.23170850843501586, 0.16585006687056386, 0.1241463725673825, 0.10236700687515125, -0.02928250679026612, -0.25769206787262, 0.06745484704645632, -0.1570728864915895, -0.10472860482916461, -0.11472144771480199, -0.022339216458865187, 0.03739813800096851, -0.31653281067864913, 0.08718205290038675, 0.061625560863776074, 0.053579170886201385, -0.04084660374051468, -0.09775999340821397, 0.004272554016135859, 0.1089755468606723, 0.09119952522133562, -0.031889314255253834, 0.08468335373891574, -0.10683547438856102, -0.12127089101934072, 0.3405750837515701, -0.11026800111902765, -0.1973579287980542, 0.1937626948834143, -0.13886009477869127, -0.19674627824093807, 0.10654793671812073, 0.19327225369034393, 0.12287654027794347, -0.16253438538899928, 0.05230388760700765, -0.06802178555817315, 0.15353890489786864, 0.02914892825947115, 0.0008611915273253213, 0.1826754762819319, 0.12308052009197347, 0.06646171118605487, 0.16693708222768636, -0.11119985491686472, -0.11089843629831166, -0.31205491645430977, -0.1144839805903647, -0.18377453907618693, 0.03239604307940074, -0.08618831493967621, -0.17892553760585458, 0.3777435114296774, 0.2212576342012846, 0.23766004132163343, 0.08686802928180744, 0.23498566033403304, 0.11732154352710385, 0.038121863395755295, 0.08120586427830859, 0.18982719984046664, 0.12104955320669845, 0.07347260677453243, -0.1406513167389979, 0.15001213456588713, -0.01890254868194461] |
1,802.08162 | A counterexample to Herzog's Conjecture on the number of involutions | In 1979, Herzog put forward the following conjecture: if two simple groups
have the same number of involutions, then they are of the same order. We give a
counterexample to this conjecture.
| math.GR | in 1979 herzog put forward the following conjecture if two simple groups have the same number of involutions then they are of the same order we give a counterexample to this conjecture | [['in', '1979', 'herzog', 'put', 'forward', 'the', 'following', 'conjecture', 'if', 'two', 'simple', 'groups', 'have', 'the', 'same', 'number', 'of', 'involutions', 'then', 'they', 'are', 'of', 'the', 'same', 'order', 'we', 'give', 'a', 'counterexample', 'to', 'this', 'conjecture']] | [-0.176231901103165, 0.11847759576630779, -0.16269155382178724, 0.09655478626882541, -0.10067377416999079, -0.17801354154653382, 0.03349982760846615, 0.3365607352461666, -0.2761023053753888, -0.2740496439218987, 0.07104924664236023, -0.25776399740425404, -0.09947160966112278, 0.15731413837056607, -0.1419575842737686, -0.017232219412107952, 0.0281139281578362, 0.03820226201787591, -0.02340817578442511, -0.45740862318780273, 0.32853182370308787, -0.019719187868759036, 0.20105794668779708, 0.11798234414163744, 0.04453537725203205, -0.008043866284424439, -0.012896196174551733, -0.01847064303001389, -0.15021339792292565, 0.10318301891675219, 0.241561586066382, 0.11181119555840269, 0.2682597015227657, -0.4321552824594619, -0.1132192799996119, 0.19132610864471644, 0.11127375776413828, 0.11502104089595377, -0.06227578141260892, -0.2268494573654607, 0.15363555200747214, -0.18340840000018943, -0.15822984196711332, -0.005588743049884215, 0.07289913196291309, 0.006787759901271784, -0.16930111744295573, -0.011384174023987725, 0.15022496419260278, 0.07283240821561776, -0.011284065243671648, -0.08449092379305512, -0.039724975591525435, 0.1348356131784385, 0.05619903700426221, 0.004527587574557401, -0.06050541110744234, -0.0311492910477682, -0.17688594783248845, 0.3293185129004996, 0.03192059213688481, -0.18949955177959055, 0.1493439894693438, -0.1799991253647022, -0.25705749412009027, 0.0576423221064033, 0.08025864540104521, 0.11919043801026419, -0.05479679285781458, 0.08758798756753094, -0.24813933752011508, 0.037870016996748745, 0.21175809054693673, -0.06477706151781604, 0.12765330429829191, 0.0627720687771216, 0.04565134141739691, 0.1151517051475821, 0.03498013666830957, 0.0452863668469945, -0.3355552461289335, -0.1982188569236314, -0.11732356215361506, 0.10619891295209527, -0.05930493300547823, -0.1240100591458031, 0.3688672464340925, 0.1436988646746613, 0.19661974953487515, 0.13770436346385395, 0.20813888672273606, 0.13674231176264584, -0.006804611592087895, 0.09205627627670765, 0.22836430981988087, 0.21769224462332204, 0.011326762905810028, -0.09479943754558917, 0.03742459887871519, 0.2124834513233509] |
1,802.08163 | An Analysis of Categorical Distributional Reinforcement Learning | Distributional approaches to value-based reinforcement learning model the
entire distribution of returns, rather than just their expected values, and
have recently been shown to yield state-of-the-art empirical performance. This
was demonstrated by the recently proposed C51 algorithm, based on categorical
distributional reinforcement learning (CDRL) [Bellemare et al., 2017]. However,
the theoretical properties of CDRL algorithms are not yet well understood. In
this paper, we introduce a framework to analyse CDRL algorithms, establish the
importance of the projected distributional Bellman operator in distributional
RL, draw fundamental connections between CDRL and the Cram\'er distance, and
give a proof of convergence for sample-based categorical distributional
reinforcement learning algorithms.
| stat.ML | distributional approaches to valuebased reinforcement learning model the entire distribution of returns rather than just their expected values and have recently been shown to yield stateoftheart empirical performance this was demonstrated by the recently proposed c51 algorithm based on categorical distributional reinforcement learning cdrl bellemare et al 2017 however the theoretical properties of cdrl algorithms are not yet well understood in this paper we introduce a framework to analyse cdrl algorithms establish the importance of the projected distributional bellman operator in distributional rl draw fundamental connections between cdrl and the cramer distance and give a proof of convergence for samplebased categorical distributional reinforcement learning algorithms | [['distributional', 'approaches', 'to', 'valuebased', 'reinforcement', 'learning', 'model', 'the', 'entire', 'distribution', 'of', 'returns', 'rather', 'than', 'just', 'their', 'expected', 'values', 'and', 'have', 'recently', 'been', 'shown', 'to', 'yield', 'stateoftheart', 'empirical', 'performance', 'this', 'was', 'demonstrated', 'by', 'the', 'recently', 'proposed', 'c51', 'algorithm', 'based', 'on', 'categorical', 'distributional', 'reinforcement', 'learning', 'cdrl', 'bellemare', 'et', 'al', '2017', 'however', 'the', 'theoretical', 'properties', 'of', 'cdrl', 'algorithms', 'are', 'not', 'yet', 'well', 'understood', 'in', 'this', 'paper', 'we', 'introduce', 'a', 'framework', 'to', 'analyse', 'cdrl', 'algorithms', 'establish', 'the', 'importance', 'of', 'the', 'projected', 'distributional', 'bellman', 'operator', 'in', 'distributional', 'rl', 'draw', 'fundamental', 'connections', 'between', 'cdrl', 'and', 'the', 'cramer', 'distance', 'and', 'give', 'a', 'proof', 'of', 'convergence', 'for', 'samplebased', 'categorical', 'distributional', 'reinforcement', 'learning', 'algorithms']] | [0.009855485943678235, -0.040366938355423154, -0.16352971976489894, 0.12452931060633134, -0.14004457289175617, -0.13857556327822662, 0.07846257643264141, 0.4456850032366457, -0.2696249206772163, -0.32607937507120716, 0.0459463205521128, -0.22095768743809976, -0.2136673692347748, 0.18042409660549658, -0.18133833495279153, 0.12437487632560078, 0.059199757670008, 0.027917913606922543, -0.10694765713331955, -0.29952527483082597, 0.2785795164582807, 0.05493988801858255, 0.3379599858873657, 0.0062088821925239505, 0.15844842081756463, -0.025596864406196844, -0.041424521143060354, 0.015405090215305487, -0.14862847203122717, 0.18483414766156958, 0.29250156130819094, 0.21193045007197986, 0.3914877207905409, -0.35673235534202485, -0.20654862715995737, 0.12814161386340855, 0.1308277326613842, 0.05951329605166046, -0.041099596645550004, -0.3649340215715624, 0.06550225251107587, -0.1762103619320052, 0.004580366033284614, -0.16275982976491962, 0.021930487695637914, 0.0305767302922461, -0.2725828800128684, 0.04592489675574359, 0.13797386771267547, 0.08071423307770774, -0.020782156082402383, -0.1890071672564816, 0.08225035069155551, 0.06251062284268084, 0.06603745520004027, 0.03460118938680916, 0.08393328001367904, -0.09874557426554106, -0.18591132470894428, 0.2901901798588889, -0.012842236003156619, -0.16331957802176475, 0.21256621350711655, -0.02555211131084001, -0.15907857271266126, 0.012854944945623477, 0.2104197257508834, 0.15248976766708353, -0.17021032257803848, 0.13240572329266884, -0.05806607007980347, 0.10761646911324489, 0.04091498086761151, 0.015773195893104587, 0.10088256829240848, 0.20723679029338415, 0.03803648047725714, 0.08160793641360388, -0.045805601793385685, -0.15707544283331593, -0.19582520089600058, -0.11045608525386169, -0.1890571448331078, -0.0031033870363552565, -0.10448738170657418, -0.1827219555340153, 0.3255650644678445, 0.2427428105446909, 0.21347051158192612, 0.17313366671580643, 0.29008769935795237, 0.09655411420833497, 0.019078327566828757, 0.14558514808082865, 0.2863253074099443, 0.14643131380324206, 0.14378545084258632, -0.13966615589424258, 0.1774956415252139, 0.13104714511760643] |
1,802.08164 | A Multiple Ejecta-Circumstellar Medium Interaction Model and Its
Implications for Superluminous Supernovae iPTF15esb and iPTF13dcc | In this paper, we investigate two hydrogen-poor superluminous supernovae
(SLSNe) iPTF15esb and iPTF13dcc whose light curves (LCs) show significant
deviation from the smooth rise and fall. The LC of iPTF15esb exhibits two peaks
and a post-peak plateau, and furthermore the late-time spectrum of iPTF15esb
shows a strong, broad H$\alpha$ emission line. The early-time LC of iPTF13dcc
shows a long duration bump followed by the second peak. Here we propose an
ejecta-circumstellar medium (CSM) interaction model involving multiple
shells/winds and use it to explain the LCs of iPTF15esb and iPTF13dcc. We find
that the theoretical LCs reproduced by this model can well match the
observations of iPTF15esb and iPTF13dcc. Based on our results, we infer that
the progenitors have undergone multiple violent mass-loss processes before the
SN explosion. In addition, we find that the variation trend of our inferred
densities of the shells is consistent with that predicted by the stellar
mass-loss history before an SN explosion. Further investigations for other
bumpy SLSNe/SNe would shed light on their nature and provide a probe for the
mass-loss history of their progenitors.
| astro-ph.HE | in this paper we investigate two hydrogenpoor superluminous supernovae slsne iptf15esb and iptf13dcc whose light curves lcs show significant deviation from the smooth rise and fall the lc of iptf15esb exhibits two peaks and a postpeak plateau and furthermore the latetime spectrum of iptf15esb shows a strong broad halpha emission line the earlytime lc of iptf13dcc shows a long duration bump followed by the second peak here we propose an ejectacircumstellar medium csm interaction model involving multiple shellswinds and use it to explain the lcs of iptf15esb and iptf13dcc we find that the theoretical lcs reproduced by this model can well match the observations of iptf15esb and iptf13dcc based on our results we infer that the progenitors have undergone multiple violent massloss processes before the sn explosion in addition we find that the variation trend of our inferred densities of the shells is consistent with that predicted by the stellar massloss history before an sn explosion further investigations for other bumpy slsnesne would shed light on their nature and provide a probe for the massloss history of their progenitors | [['in', 'this', 'paper', 'we', 'investigate', 'two', 'hydrogenpoor', 'superluminous', 'supernovae', 'slsne', 'iptf15esb', 'and', 'iptf13dcc', 'whose', 'light', 'curves', 'lcs', 'show', 'significant', 'deviation', 'from', 'the', 'smooth', 'rise', 'and', 'fall', 'the', 'lc', 'of', 'iptf15esb', 'exhibits', 'two', 'peaks', 'and', 'a', 'postpeak', 'plateau', 'and', 'furthermore', 'the', 'latetime', 'spectrum', 'of', 'iptf15esb', 'shows', 'a', 'strong', 'broad', 'halpha', 'emission', 'line', 'the', 'earlytime', 'lc', 'of', 'iptf13dcc', 'shows', 'a', 'long', 'duration', 'bump', 'followed', 'by', 'the', 'second', 'peak', 'here', 'we', 'propose', 'an', 'ejectacircumstellar', 'medium', 'csm', 'interaction', 'model', 'involving', 'multiple', 'shellswinds', 'and', 'use', 'it', 'to', 'explain', 'the', 'lcs', 'of', 'iptf15esb', 'and', 'iptf13dcc', 'we', 'find', 'that', 'the', 'theoretical', 'lcs', 'reproduced', 'by', 'this', 'model', 'can', 'well', 'match', 'the', 'observations', 'of', 'iptf15esb', 'and', 'iptf13dcc', 'based', 'on', 'our', 'results', 'we', 'infer', 'that', 'the', 'progenitors', 'have', 'undergone', 'multiple', 'violent', 'massloss', 'processes', 'before', 'the', 'sn', 'explosion', 'in', 'addition', 'we', 'find', 'that', 'the', 'variation', 'trend', 'of', 'our', 'inferred', 'densities', 'of', 'the', 'shells', 'is', 'consistent', 'with', 'that', 'predicted', 'by', 'the', 'stellar', 'massloss', 'history', 'before', 'an', 'sn', 'explosion', 'further', 'investigations', 'for', 'other', 'bumpy', 'slsnesne', 'would', 'shed', 'light', 'on', 'their', 'nature', 'and', 'provide', 'a', 'probe', 'for', 'the', 'massloss', 'history', 'of', 'their', 'progenitors']] | [-0.05193357219877469, 0.08126128602119842, -0.13348559647966912, 0.13789660775294726, -0.09319393530403827, -0.11960655313490307, 0.058054179183370566, 0.46439846906558435, -0.19614114915415393, -0.29352055238507224, 0.059755172487085235, -0.2667221523568792, -0.10848357512662976, 0.21624667324799265, -0.056011515310454105, -0.07544274164079609, 0.10252525043373896, -0.06731590596642635, -0.08310630948856304, -0.2517253059175623, 0.3034402880722941, 0.03223513476063871, 0.20869399963662366, 0.017005134130549212, 0.06397261936612175, -0.06802829377100629, -0.0457592421016619, -0.03612063426292886, -0.15178441395276057, 0.06298972878328969, 0.13904135631930772, 0.16396544806627653, 0.16588610187593827, -0.42795567259739686, -0.2968327471740428, 0.10614143242465271, 0.18893268175941424, 0.06165400302658478, -0.07305435361577418, -0.22376768659973928, 0.022807092291413474, -0.1825124083381504, -0.16152972052410497, 0.03845820623307915, 0.03237840203084262, 0.0861046761448632, -0.20221505226241163, 0.11402067741429128, 0.04715257222858905, 0.041729047639284936, -0.08733282248242258, -0.04434160504632861, -0.0535916843370003, 0.012011093937260452, 0.09863115255891919, 0.018343230031988463, 0.0611260298407363, -0.12384389885464463, -0.05958207561581864, 0.40032651463239377, -0.11207064344563474, 0.08655011548665957, 0.20597036688136053, -0.14751442666869286, -0.12063561280463207, 0.16643674492751812, 0.13355801512071558, 0.09705279072836083, -0.13277880778788761, -0.0453741295791973, -0.01454639152786826, 0.15741554563233662, 0.012946790960317447, 0.061036418163149204, 0.2920385131922861, 0.16173520628994298, -0.06119189679354303, 0.0696678292160817, -0.17376299139992255, -0.02734093647713294, -0.2859654641495807, -0.11193979168205527, -0.10793167095247257, 0.11837640490467097, -0.13364976891224395, -0.15290964629480058, 0.3898592220690354, 0.09827699926635777, 0.273738189972674, 0.061653127599149773, 0.22421834491045967, 0.08329491604693065, 0.05425418499794047, 0.09089835868664296, 0.3386369005245509, 0.13168437897206658, 0.11898065562554672, -0.2736127781643898, 0.11652602593935395, 0.005008732352805676] |
1,802.08165 | A Coincidence Search for Cosmic Neutrino and Gamma-Ray Emitting Sources
Using IceCube and Fermi LAT Public Data | We present results of an archival coincidence analysis between Fermi LAT
gamma-ray data and public neutrino data from the IceCube neutrino observatory's
40-string (IC40) and 59-string (IC59) observing runs. Our analysis has the
potential to detect either a statistical excess of neutrino + gamma-ray
($\nu$+$\gamma$) emitting transients or, alternatively, individual high
gamma-multiplicity events, as might be produced by a neutrino observed by
IceCube coinciding with a LAT-detected gamma-ray burst. Dividing the neutrino
data into three datasets by hemisphere (IC40, IC59-North, and IC59-South), we
construct uncorrelated null distributions by Monte Carlo scrambling of the
neutrino datasets. We carry out signal-injection studies against these null
distributions, demonstrating sensitivity to individual $\nu$+$\gamma$ events of
sufficient gamma-ray multiplicity, and to $\nu$+$\gamma$ transient populations
responsible for $>$14% (IC40), $>$9% (IC59-North), or $>$8% (IC59-South) of the
gamma-coincident neutrinos observed in these datasets, respectively. Analyzing
the unscrambled neutrino data, we identify no individual high-significance
neutrino + high gamma-multiplicity events, and no significant deviations from
the test statistic null distributions. However, we observe a similar and
unexpected pattern in the IC59-North and IC59-South residual distributions that
we conclude reflects a possible correlation ($p=7.0\%$) between IC59 neutrino
positions and persistently bright portions of the Fermi gamma-ray sky. This
possible correlation should be readily testable using eight years of further
data already collected by IceCube. We are currently working with Astrophysical
Multimessenger Observatory Network (AMON) partner facilities to generate
low-latency $\nu$+$\gamma$ alerts from Fermi LAT gamma-ray, IceCube and ANTARES
neutrino data and distribute these in real time to AMON follow-up partners.
| astro-ph.HE | we present results of an archival coincidence analysis between fermi lat gammaray data and public neutrino data from the icecube neutrino observatorys 40string ic40 and 59string ic59 observing runs our analysis has the potential to detect either a statistical excess of neutrino gammaray nugamma emitting transients or alternatively individual high gammamultiplicity events as might be produced by a neutrino observed by icecube coinciding with a latdetected gammaray burst dividing the neutrino data into three datasets by hemisphere ic40 ic59north and ic59south we construct uncorrelated null distributions by monte carlo scrambling of the neutrino datasets we carry out signalinjection studies against these null distributions demonstrating sensitivity to individual nugamma events of sufficient gammaray multiplicity and to nugamma transient populations responsible for 14 ic40 9 ic59north or 8 ic59south of the gammacoincident neutrinos observed in these datasets respectively analyzing the unscrambled neutrino data we identify no individual highsignificance neutrino high gammamultiplicity events and no significant deviations from the test statistic null distributions however we observe a similar and unexpected pattern in the ic59north and ic59south residual distributions that we conclude reflects a possible correlation p70 between ic59 neutrino positions and persistently bright portions of the fermi gammaray sky this possible correlation should be readily testable using eight years of further data already collected by icecube we are currently working with astrophysical multimessenger observatory network amon partner facilities to generate lowlatency nugamma alerts from fermi lat gammaray icecube and antares neutrino data and distribute these in real time to amon followup partners | [['we', 'present', 'results', 'of', 'an', 'archival', 'coincidence', 'analysis', 'between', 'fermi', 'lat', 'gammaray', 'data', 'and', 'public', 'neutrino', 'data', 'from', 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1,802.08166 | When gluons go odd: how classical gluon fields generate odd azimuthal
harmonics for the two-gluon correlation function in high-energy collisions | We show that, in the saturation/Color Glass Condensate framework, odd
azimuthal harmonics of the two-gluon correlation function with a long-range
separation in rapidity are generated by the higher-order saturation corrections
in the interactions with the projectile and the target. At the very least, the
odd harmonics require three scatterings in the projectile and three scatterings
in the target. We derive the leading-order expression for the two-gluon
production cross section which generates odd harmonics: the expression includes
all-order interactions with the target and three interactions with the
projectile. We evaluate the obtained expression both analytically and
numerically, confirming that the odd-harmonics contribution to the two-gluon
production in the saturation framework is non-zero.
| hep-ph nucl-ex nucl-th | we show that in the saturationcolor glass condensate framework odd azimuthal harmonics of the twogluon correlation function with a longrange separation in rapidity are generated by the higherorder saturation corrections in the interactions with the projectile and the target at the very least the odd harmonics require three scatterings in the projectile and three scatterings in the target we derive the leadingorder expression for the twogluon production cross section which generates odd harmonics the expression includes allorder interactions with the target and three interactions with the projectile we evaluate the obtained expression both analytically and numerically confirming that the oddharmonics contribution to the twogluon production in the saturation framework is nonzero | [['we', 'show', 'that', 'in', 'the', 'saturationcolor', 'glass', 'condensate', 'framework', 'odd', 'azimuthal', 'harmonics', 'of', 'the', 'twogluon', 'correlation', 'function', 'with', 'a', 'longrange', 'separation', 'in', 'rapidity', 'are', 'generated', 'by', 'the', 'higherorder', 'saturation', 'corrections', 'in', 'the', 'interactions', 'with', 'the', 'projectile', 'and', 'the', 'target', 'at', 'the', 'very', 'least', 'the', 'odd', 'harmonics', 'require', 'three', 'scatterings', 'in', 'the', 'projectile', 'and', 'three', 'scatterings', 'in', 'the', 'target', 'we', 'derive', 'the', 'leadingorder', 'expression', 'for', 'the', 'twogluon', 'production', 'cross', 'section', 'which', 'generates', 'odd', 'harmonics', 'the', 'expression', 'includes', 'allorder', 'interactions', 'with', 'the', 'target', 'and', 'three', 'interactions', 'with', 'the', 'projectile', 'we', 'evaluate', 'the', 'obtained', 'expression', 'both', 'analytically', 'and', 'numerically', 'confirming', 'that', 'the', 'oddharmonics', 'contribution', 'to', 'the', 'twogluon', 'production', 'in', 'the', 'saturation', 'framework', 'is', 'nonzero']] | [-0.12000271162387353, 0.21005251121010865, -0.12608478170020404, 0.14480465521872346, 0.031374851459855434, -0.06681583232355413, -0.07192415149194432, 0.3446114734486417, -0.1689867449165028, -0.2559579605370894, -0.06749821147411592, -0.357591070355386, -0.06585394226534812, 0.09422532899666007, 0.11570089605955726, 0.035141518784200285, 0.049980483494011, 0.04539953681497692, -0.03339253053664826, -0.19922389523419845, 0.35058439224287197, 0.0035440867246539745, 0.25645110452430203, 0.19359942419068502, 0.10753704667057809, 0.10507599491340754, -0.019715245631691237, -0.05194714672125138, -0.09543209825498199, 0.08535528776596661, 0.22738198115414865, 0.03445715075442651, 0.14480530989968832, -0.39907132339168777, -0.10828743077948824, 0.05651821761585034, 0.17005427121730135, 0.14865122358251764, -0.04607200384274259, -0.23380073862620168, 0.008532806622653126, -0.2500113891185941, -0.1298917772810537, -0.09255918588170463, 0.039247990644595644, 0.029679027014739207, -0.34243857705344755, 0.09089942916657205, 0.0499573284172797, 0.01536453538364521, -0.06510300871807041, -0.17313432824370023, -0.05348160510949858, 0.09078318501092694, 0.10474017202373156, 0.033083317302133854, 0.1118670180439949, -0.1936867767755495, -0.09010226204771095, 0.37646714161645184, -0.08687377735334742, -0.22764874583210898, 0.0950702212390129, -0.24720207106338832, -0.10676796585405329, 0.19455000488003632, 0.17942696250136103, 0.12272830129399695, -0.14292569559168172, 0.05303362670337765, 0.03873826678724842, 0.14999425472893022, 0.1213813232308304, 0.01952141780104186, 0.13509891278672595, 0.1342285442845644, -0.05066918267088162, 0.17233585903572068, -0.15210495441682692, -0.11367631944993443, -0.3820555036937868, -0.08494186122809444, -0.12934299075120204, -0.020375858337895292, -0.10520844675363503, -0.09300273259145182, 0.3704320515195529, 0.10323275400426339, 0.20914710073119347, 0.055443044736150755, 0.3412455284951238, 0.14196062004057322, 0.08903836951221901, 0.05732225365506754, 0.2781352614060984, 0.15188055426335414, 0.07287026003321952, -0.3001321293119979, 0.04462566657142865, 0.08736760622343502] |
1,802.08167 | Learning Causally-Generated Stationary Time Series | We present the Causal Gaussian Process Convolution Model (CGPCM), a doubly
nonparametric model for causal, spectrally complex dynamical phenomena. The
CGPCM is a generative model in which white noise is passed through a causal,
nonparametric-window moving-average filter, a construction that we show to be
equivalent to a Gaussian process with a nonparametric kernel that is biased
towards causally-generated signals. We develop enhanced variational inference
and learning schemes for the CGPCM and its previous acausal variant, the GPCM
(Tobar et al., 2015b), that significantly improve statistical accuracy. These
modelling and inferential contributions are demonstrated on a range of
synthetic and real-world signals.
| stat.ML | we present the causal gaussian process convolution model cgpcm a doubly nonparametric model for causal spectrally complex dynamical phenomena the cgpcm is a generative model in which white noise is passed through a causal nonparametricwindow movingaverage filter a construction that we show to be equivalent to a gaussian process with a nonparametric kernel that is biased towards causallygenerated signals we develop enhanced variational inference and learning schemes for the cgpcm and its previous acausal variant the gpcm tobar et al 2015b that significantly improve statistical accuracy these modelling and inferential contributions are demonstrated on a range of synthetic and realworld signals | [['we', 'present', 'the', 'causal', 'gaussian', 'process', 'convolution', 'model', 'cgpcm', 'a', 'doubly', 'nonparametric', 'model', 'for', 'causal', 'spectrally', 'complex', 'dynamical', 'phenomena', 'the', 'cgpcm', 'is', 'a', 'generative', 'model', 'in', 'which', 'white', 'noise', 'is', 'passed', 'through', 'a', 'causal', 'nonparametricwindow', 'movingaverage', 'filter', 'a', 'construction', 'that', 'we', 'show', 'to', 'be', 'equivalent', 'to', 'a', 'gaussian', 'process', 'with', 'a', 'nonparametric', 'kernel', 'that', 'is', 'biased', 'towards', 'causallygenerated', 'signals', 'we', 'develop', 'enhanced', 'variational', 'inference', 'and', 'learning', 'schemes', 'for', 'the', 'cgpcm', 'and', 'its', 'previous', 'acausal', 'variant', 'the', 'gpcm', 'tobar', 'et', 'al', '2015b', 'that', 'significantly', 'improve', 'statistical', 'accuracy', 'these', 'modelling', 'and', 'inferential', 'contributions', 'are', 'demonstrated', 'on', 'a', 'range', 'of', 'synthetic', 'and', 'realworld', 'signals']] | [-0.014323283119925432, 0.04068650554732552, -0.11892905404164018, 0.11284483168577825, -0.12413180921682898, -0.1658574502822487, 0.06240234519735131, 0.437092227462147, -0.26145350805730844, -0.26131889531008745, 0.07322992107294006, -0.24157207184566223, -0.221994590004716, 0.1861490656274884, -0.1125474327037799, 0.09043227238711254, 0.09244273495575299, -0.03863133888808079, -0.022778560100978583, -0.2278374531781491, 0.26815473218923624, 0.08901813609183443, 0.28865818286134043, -0.052391212718675334, 0.15080080113886873, 0.002624403723344511, -0.07842473884360218, 0.01229781972016303, -0.09853779164263776, 0.1123096293351632, 0.2373305977136847, 0.1573894917727353, 0.3117535457357156, -0.34404064656463357, -0.3282320063026047, 0.12038892913818816, 0.10403635220279042, 0.11667096359555476, -0.027288655547320614, -0.34486070995656204, 0.06646101243736945, -0.17592714451329441, -0.022220938720702365, -0.10681658338907422, -0.029528022401643043, -0.011434325188094256, -0.3623632586903262, 0.11912594468579912, 0.12585458980857783, 0.02046403877094996, 0.016002431581965744, -0.11243675654868082, 0.015784936998638192, 0.03665151629996087, -0.03179206445810803, 0.011134897140139828, 0.11494821946288707, -0.10268686592521868, -0.16398212952748398, 0.2763237371257915, -0.0922509066330516, -0.23257421455654906, 0.18902268110565384, -0.06520390020189237, -0.16252560404661512, 0.1053927765579476, 0.22286620325579934, 0.11839101939225731, -0.1882173195956465, 0.06404862867677774, -0.01547393599068936, 0.14078228971303194, 0.005436885355952747, -0.04051559327683431, 0.16227765334770083, 0.1900571212885255, 0.008511390964671666, 0.12346311794399113, -0.13107621515815965, -0.13143347014319057, -0.2508261605885773, -0.12107703792036996, -0.15402846910387316, 0.008946865119933322, -0.1109739056894109, -0.2106970297505281, 0.3830489503713895, 0.21532111397317175, 0.2006813240598659, 0.10705946686995994, 0.3100363352450029, 0.12468403192921257, -0.0011267794761806726, 0.09009636001309798, 0.19845959610467281, 0.15433120833975927, 0.0480634159579569, -0.14100275701149462, 0.10882914223594173, 0.01001573126877145] |
1,802.08168 | Performance of missing transverse momentum reconstruction with the ATLAS
detector using proton-proton collisions at $\sqrt{s}$ = 13 TeV | The performance of the missing transverse momentum (E$_{T}^{miss}$)
reconstruction with the ATLAS detector is evaluated using data collected in
proton-proton collisions at the LHC at a center-of-mass energy of 13 TeV in
2015. To reconstruct E$_{T}^{miss}$, fully calibrated electrons, muons,
photons, hadronically decaying $\tau$-leptons, and jets reconstructed from
calorimeter energy deposits and charged-particle tracks are used. These are
combined with the soft hadronic activity measured by reconstructed
charged-particle tracks not associated with the hard objects. Possible double
counting of contributions from reconstructed charged-particle tracks from the
inner detector, energy deposits in the calorimeter, and reconstructed muons
from the muon spectrometer is avoided by applying a signal ambiguity resolution
procedure which rejects already used signals when combining the various
E$_{T}^{miss}$ contributions. The individual terms as well as the overall
reconstructed E$_{T}^{miss}$ are evaluated with various performance metrics for
scale (linearity), resolution, and sensitivity to the data-taking conditions.
The method developed to determine the systematic uncertainties of the
E$_{T}^{miss}$ scale and resolution is discussed. Results are shown based on
the full 2015 data sample corresponding to an integrated luminosity of 3.2
fb$^{-1}$.
| hep-ex | the performance of the missing transverse momentum e_tmiss reconstruction with the atlas detector is evaluated using data collected in protonproton collisions at the lhc at a centerofmass energy of 13 tev in 2015 to reconstruct e_tmiss fully calibrated electrons muons photons hadronically decaying tauleptons and jets reconstructed from calorimeter energy deposits and chargedparticle tracks are used these are combined with the soft hadronic activity measured by reconstructed chargedparticle tracks not associated with the hard objects possible double counting of contributions from reconstructed chargedparticle tracks from the inner detector energy deposits in the calorimeter and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various e_tmiss contributions the individual terms as well as the overall reconstructed e_tmiss are evaluated with various performance metrics for scale linearity resolution and sensitivity to the datataking conditions the method developed to determine the systematic uncertainties of the e_tmiss scale and resolution is discussed results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 32 fb1 | [['the', 'performance', 'of', 'the', 'missing', 'transverse', 'momentum', 'e_tmiss', 'reconstruction', 'with', 'the', 'atlas', 'detector', 'is', 'evaluated', 'using', 'data', 'collected', 'in', 'protonproton', 'collisions', 'at', 'the', 'lhc', 'at', 'a', 'centerofmass', 'energy', 'of', '13', 'tev', 'in', '2015', 'to', 'reconstruct', 'e_tmiss', 'fully', 'calibrated', 'electrons', 'muons', 'photons', 'hadronically', 'decaying', 'tauleptons', 'and', 'jets', 'reconstructed', 'from', 'calorimeter', 'energy', 'deposits', 'and', 'chargedparticle', 'tracks', 'are', 'used', 'these', 'are', 'combined', 'with', 'the', 'soft', 'hadronic', 'activity', 'measured', 'by', 'reconstructed', 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1,802.08169 | Two flat structures on minimal surfaces | In this expository article, we illustrate how two independent flat structures
on minimal surfaces induce a harmonic function, which captures the uniqueness
of Enneper's surface.
| math.DG | in this expository article we illustrate how two independent flat structures on minimal surfaces induce a harmonic function which captures the uniqueness of ennepers surface | [['in', 'this', 'expository', 'article', 'we', 'illustrate', 'how', 'two', 'independent', 'flat', 'structures', 'on', 'minimal', 'surfaces', 'induce', 'a', 'harmonic', 'function', 'which', 'captures', 'the', 'uniqueness', 'of', 'ennepers', 'surface']] | [-0.16088392928242684, 0.10473176795989275, -0.10737711333669722, 0.13143415508326142, -0.08180363476276398, -0.10338455734774471, -0.019165707640349864, 0.3755200454033911, -0.27829940646886825, -0.21492321157362312, 0.042485889713279906, -0.24704538986086846, -0.2750131268799305, 0.19305150836706161, -0.16329276625066996, -0.05632256254553795, 0.031171691473573446, -0.042973971334286036, -0.09353432059288025, -0.2795045839622617, 0.3979473593831062, -0.026698223799467086, 0.2921421952545643, 0.14325172320008278, 0.14159792486578227, 0.011394648533314466, -0.014751028642058373, 0.014720289707183839, -0.25066256418824195, 0.20161558527499437, 0.23230864897370337, -0.004615326810453553, 0.20942580997943877, -0.446735842525959, -0.19648687198758125, 0.10498438894748688, 0.08307966809719801, 0.06265697890426963, -0.05268283116165549, -0.19314133279025555, 0.05975684445351362, -0.0931165518052876, -0.20969588339328765, -0.056350325047969815, -0.02480322852730751, 0.043897708058357236, -0.11968376819044352, 0.0518458928540349, 0.1606084678694606, 0.10351561058312654, -0.08109286166727543, -0.04893649246543646, -0.06540832415223122, 0.08764038072898984, 0.0669624412059784, 0.008944522794336081, 0.10410076079890132, -0.026624731635674834, -0.04577389530837536, 0.3110978677868843, -0.14076754689216614, -0.3014357806742191, 0.17422030355781318, -0.12052297838032246, -0.13714594647288322, 0.1070347522571683, 0.2184316838532686, 0.14002201475203038, -0.1325989380478859, 0.17890951581299305, -0.09238926984369755, 0.1386196431517601, 0.13232079062610866, 0.0032862354815006256, 0.21988404855132104, 0.1350703214108944, 0.10599395552650094, 0.18511442080140114, 0.000953167574480176, -0.07914214964956046, -0.42252866059541705, -0.19374261568300427, -0.16259794149547815, 0.06715626561024692, -0.02256524359807372, -0.25990463465452196, 0.49563855409622193, 0.09078562214970588, 0.22176182568073272, 0.04737590492237359, 0.2504772487282753, 0.02054042138159275, -0.06668141826987267, 0.02026075854897499, 0.16999126663431524, 0.1562634348589927, -0.009820644035935402, -0.16498277926817537, -0.0013170752860605717, 0.11553867008537054] |
1,802.0817 | Web spaces and worldwide web spaces: topological aspects of domain
theory | Web spaces, wide web spaces and worldwide web spaces (alias C-spaces) provide
useful generalizations of continuous domains. We present new characterizations
of such spaces and their patch spaces, obtained by joining the original
topology with a second topology having the dual specialization order; these
patch spaces possess good convexity and separation properties and determine the
original web spaces. The category of C-spaces is concretely isomorphic to the
category of fan spaces; these are certain quasi-ordered spaces having
neighborhood bases of fans, obtained by deleting a finite number of principal
dual ideals from a principal dual ideal. Our approach has useful consequences
for domain theory, because the T$_0$ web spaces are exactly the generalized
Scott spaces of locally approximating ideal extensions, and the T$_0$ C-spaces
are exactly the generalized Scott spaces of globally approximating and
interpolating ideal extensions. We extend the characterization of continuous
lattices as meet-continuous lattices with T$_2$ Lawson topology and the
Fundamental Theorem of Compact Semilattices to non-complete posets. Finally,
cardinal invariants like density and weight of the involved objects are
investigated.
| math.GN | web spaces wide web spaces and worldwide web spaces alias cspaces provide useful generalizations of continuous domains we present new characterizations of such spaces and their patch spaces obtained by joining the original topology with a second topology having the dual specialization order these patch spaces possess good convexity and separation properties and determine the original web spaces the category of cspaces is concretely isomorphic to the category of fan spaces these are certain quasiordered spaces having neighborhood bases of fans obtained by deleting a finite number of principal dual ideals from a principal dual ideal our approach has useful consequences for domain theory because the t_0 web spaces are exactly the generalized scott spaces of locally approximating ideal extensions and the t_0 cspaces are exactly the generalized scott spaces of globally approximating and interpolating ideal extensions we extend the characterization of continuous lattices as meetcontinuous lattices with t_2 lawson topology and the fundamental theorem of compact semilattices to noncomplete posets finally cardinal invariants like density and weight of the involved objects are investigated | [['web', 'spaces', 'wide', 'web', 'spaces', 'and', 'worldwide', 'web', 'spaces', 'alias', 'cspaces', 'provide', 'useful', 'generalizations', 'of', 'continuous', 'domains', 'we', 'present', 'new', 'characterizations', 'of', 'such', 'spaces', 'and', 'their', 'patch', 'spaces', 'obtained', 'by', 'joining', 'the', 'original', 'topology', 'with', 'a', 'second', 'topology', 'having', 'the', 'dual', 'specialization', 'order', 'these', 'patch', 'spaces', 'possess', 'good', 'convexity', 'and', 'separation', 'properties', 'and', 'determine', 'the', 'original', 'web', 'spaces', 'the', 'category', 'of', 'cspaces', 'is', 'concretely', 'isomorphic', 'to', 'the', 'category', 'of', 'fan', 'spaces', 'these', 'are', 'certain', 'quasiordered', 'spaces', 'having', 'neighborhood', 'bases', 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1,802.08171 | Cocommutative Com-PreLie bialgebras | A Com-PreLie bialgebra is a commutative bialgebra with an extra preLie product satisfying some compatibilities with the product and coproduct. We here give a classification of connected, cocommutative Com-PreLie bialgebras over a field of characteristic zero: we obtain a main family of symmetric algebras on a space V of any dimension, and another family available only if V is one-dimensional. We also explore the case of Com-PreLie bialgebras over a group algebra and over a tensor product of a group algebra and of a symmetric algebra. | math.RA | a comprelie bialgebra is a commutative bialgebra with an extra prelie product satisfying some compatibilities with the product and coproduct we here give a classification of connected cocommutative comprelie bialgebras over a field of characteristic zero we obtain a main family of symmetric algebras on a space v of any dimension and another family available only if v is onedimensional we also explore the case of comprelie bialgebras over a group algebra and over a tensor product of a group algebra and of a symmetric algebra | [['a', 'comprelie', 'bialgebra', 'is', 'a', 'commutative', 'bialgebra', 'with', 'an', 'extra', 'prelie', 'product', 'satisfying', 'some', 'compatibilities', 'with', 'the', 'product', 'and', 'coproduct', 'we', 'here', 'give', 'a', 'classification', 'of', 'connected', 'cocommutative', 'comprelie', 'bialgebras', 'over', 'a', 'field', 'of', 'characteristic', 'zero', 'we', 'obtain', 'a', 'main', 'family', 'of', 'symmetric', 'algebras', 'on', 'a', 'space', 'v', 'of', 'any', 'dimension', 'and', 'another', 'family', 'available', 'only', 'if', 'v', 'is', 'onedimensional', 'we', 'also', 'explore', 'the', 'case', 'of', 'comprelie', 'bialgebras', 'over', 'a', 'group', 'algebra', 'and', 'over', 'a', 'tensor', 'product', 'of', 'a', 'group', 'algebra', 'and', 'of', 'a', 'symmetric', 'algebra']] | [-0.23144880382257493, 0.049856006629598534, -0.04441740993020493, 0.011638688132015252, -0.19031994958234907, -0.16913128316099213, -0.014698728540002606, 0.39542504976135356, -0.3775447091131016, -0.13422528169182843, 0.12150866153303447, -0.2043321803645339, -0.15367459211238596, 0.16772233264867303, -0.12918387403776652, -0.1438496522402369, 0.08756697474610667, 0.20414067042428394, -0.166849137180983, -0.2613107398542207, 0.4656505294057519, -0.032285589789755126, 0.2013431945220069, -0.007601697471664223, 0.17067406300541965, 0.028400045440553925, -0.007970894042532458, 0.0199599703932912, -0.1743137929155383, 0.09465542592129908, 0.26883601095137555, 0.04956334128401914, 0.21092990990511554, -0.3115903819196446, -0.06705653670157284, 0.17722729999073888, 0.13842842078681084, 0.020682986544141937, -0.03443350312218806, -0.28766503188011866, 0.07330064695371791, -0.3452784323545043, -0.06346975550661947, -0.06987459979258305, 0.11266191809053727, -0.05172040409321875, -0.2893709850086029, -0.02888823246487232, 0.09543556780662647, 0.15141412900046033, -0.102843860597458, -0.08234924292408449, -0.08841875486812273, 0.04176892916168368, -0.12529232328606033, 0.031153381888776324, 0.0965365287685377, -0.07265908990141957, -0.18346714412490295, 0.35596037385741597, -0.04468988588209762, -0.23521695136590753, 0.11897908415385457, -0.195183866895562, -0.15539458007443435, 0.07687143543410267, 0.047012448159241396, 0.1350355945245991, -0.04403811786323786, 0.23548172894854444, -0.182843578622005, 0.02760967686413625, 0.08822447920304745, 0.0025012362071551207, 0.12590962438302677, 0.1348897299707629, 0.0903130043298006, 0.1512287147776332, 0.07086191443065831, 0.009523134694846218, -0.3863330408064432, -0.23040704971699175, -0.06619128585944689, 0.19284879156323367, -0.12176048350019575, -0.21656777527789736, 0.4480725226999629, 0.07563448722236031, 0.17553130943439144, 0.10223703179508448, 0.19734986106930083, 0.052229229978090805, 0.16195916154876697, 0.0650444369259572, 0.06263228850933279, 0.3299448534434791, -0.006879085015646333, -0.05499426819124194, -0.08095185177638954, 0.17150798093440922] |
1,802.08172 | Shear strength of wet granular materials: macroscopic cohesion and
effective stress | Rheometric measurements on assemblies of wet polystyrene bead assemblies, in
steady uniform quasistatic shear flow, for varying liquid content within the
small saturation (pendular) range of isolated liquid bridges, are supplemented
with a systematic study by discrete numerical simulations. Numerical results
and experimental ones agree quantitatively is the intergranular friction
coefficient is set to 0.09, suitable for the dry material. Shear resistance and
solid fraction are recorded as functions of the reduced pressure p, comparing
normal stress to capillary bridge tensile strength. The Mohr-Coulomb relation
with p-independent cohesion c applies for p above 2. The assumption that
contact force contributions to stress act as effective stresses predicts shear
strength quite well throughout the numerically investigated range of
parameters.. A generalized Mohr-Coulomb cohesion c is defined, which relates to
the dry material internal friction, coordination numbers and capillary force
network anisotropy. The Rumpf formula approximation, ignoring capillary shear
stress is correct for the larger saturation range within the pendular regime,
but fails to describe its decrease for small liquid contents.
| cond-mat.soft physics.comp-ph | rheometric measurements on assemblies of wet polystyrene bead assemblies in steady uniform quasistatic shear flow for varying liquid content within the small saturation pendular range of isolated liquid bridges are supplemented with a systematic study by discrete numerical simulations numerical results and experimental ones agree quantitatively is the intergranular friction coefficient is set to 009 suitable for the dry material shear resistance and solid fraction are recorded as functions of the reduced pressure p comparing normal stress to capillary bridge tensile strength the mohrcoulomb relation with pindependent cohesion c applies for p above 2 the assumption that contact force contributions to stress act as effective stresses predicts shear strength quite well throughout the numerically investigated range of parameters a generalized mohrcoulomb cohesion c is defined which relates to the dry material internal friction coordination numbers and capillary force network anisotropy the rumpf formula approximation ignoring capillary shear stress is correct for the larger saturation range within the pendular regime but fails to describe its decrease for small liquid contents | [['rheometric', 'measurements', 'on', 'assemblies', 'of', 'wet', 'polystyrene', 'bead', 'assemblies', 'in', 'steady', 'uniform', 'quasistatic', 'shear', 'flow', 'for', 'varying', 'liquid', 'content', 'within', 'the', 'small', 'saturation', 'pendular', 'range', 'of', 'isolated', 'liquid', 'bridges', 'are', 'supplemented', 'with', 'a', 'systematic', 'study', 'by', 'discrete', 'numerical', 'simulations', 'numerical', 'results', 'and', 'experimental', 'ones', 'agree', 'quantitatively', 'is', 'the', 'intergranular', 'friction', 'coefficient', 'is', 'set', 'to', '009', 'suitable', 'for', 'the', 'dry', 'material', 'shear', 'resistance', 'and', 'solid', 'fraction', 'are', 'recorded', 'as', 'functions', 'of', 'the', 'reduced', 'pressure', 'p', 'comparing', 'normal', 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1,802.08173 | On Completely Solvable Lie Foliation | In this paper we try to generalize the Haefliger theorem on completly
solvable Lie foliations. We prove that: every completely solvable Lie foliation
on a compact manifold is the inverse image of a homogenus foliation. Every
manifold in this paper is compact and our Lie group G is connexe and simply
connexe.
| math.DG | in this paper we try to generalize the haefliger theorem on completly solvable lie foliations we prove that every completely solvable lie foliation on a compact manifold is the inverse image of a homogenus foliation every manifold in this paper is compact and our lie group g is connexe and simply connexe | [['in', 'this', 'paper', 'we', 'try', 'to', 'generalize', 'the', 'haefliger', 'theorem', 'on', 'completly', 'solvable', 'lie', 'foliations', 'we', 'prove', 'that', 'every', 'completely', 'solvable', 'lie', 'foliation', 'on', 'a', 'compact', 'manifold', 'is', 'the', 'inverse', 'image', 'of', 'a', 'homogenus', 'foliation', 'every', 'manifold', 'in', 'this', 'paper', 'is', 'compact', 'and', 'our', 'lie', 'group', 'g', 'is', 'connexe', 'and', 'simply', 'connexe']] | [-0.22096279084536374, 0.04307911519472506, -0.14755992638860263, 0.07310774861424066, -0.22393949538031044, -0.1551515809351615, -0.051380998176504294, 0.4323211958010991, -0.2638637622197469, -0.15098225182908423, 0.14594726163583496, -0.24363436184677423, -0.2023717055791149, 0.18169417670544455, -0.23433472168650113, -0.09987476088252722, 0.10327459658112596, 0.1393195292455893, -0.07211330413873143, -0.26602817692008673, 0.4908116240711773, -0.07059244070129067, 0.1644534680298438, 0.06188311524159622, 0.18086289791572913, -0.0035246668164344397, 0.060907782731102963, -0.0017068343118344452, -0.1525657582971297, 0.10093966199486863, 0.34232821724578444, 0.06173713044628647, 0.2076824309176528, -0.29280417833783134, -0.13959112219220282, 0.22882449283611542, 0.146818245560223, 0.01609714743772558, -0.008115829217393756, -0.3344674376661287, 0.13037664576561428, -0.13040359625044992, -0.1648803241916147, -0.030594446787647174, 0.05501744163898276, -0.09573002097507317, -0.12464726078506633, 0.006188512158890565, 0.17047232951895863, 0.08932494466445824, -0.07812230916255537, -0.008655070838536703, -0.02351517307425977, 0.03862821516653925, -0.09093796432146109, 0.13591882094224988, 0.15748118240084938, 0.042431804178026965, -0.129578050536414, 0.3739545673643257, -0.049305339270800934, -0.28422987614484396, 0.12314356134875733, -0.1866178736638497, -0.29144611669813886, 0.06346101160435115, 0.11010097993501261, 0.2169765856336145, -0.07927636537408712, 0.26242962108660195, -0.1540440587947766, 0.04436737379314853, 0.08066158564578668, -0.13788587905868305, 0.08094584569334984, 0.17701065618380465, 0.1636619322074979, 0.06116881493625103, 0.057910948453069315, 0.07966126768174124, -0.3412126882695684, -0.21392254102244682, -0.16203403429073446, 0.1901858392920272, -0.07736134645928555, -0.13576765831413806, 0.4213210536605295, 0.06675558998340778, 0.17406987817044936, 0.1631297647916511, 0.22087196691655644, 0.04577878084919397, 0.04704308945356923, 0.18846772164654205, 0.1205018714946859, 0.23404469180340862, -0.04394037099372523, -0.11205289438458196, -0.11727356526306738, 0.19888040726529618] |
1,802.08174 | p-Blocks Relative to a Character of a Normal Subgroup | Let G be a finite group, let N be a normal subgroup of G, and let theta in
Irr(N) be a G-invariant character. We fix a prime p, and we introduce a
canonical partition of Irr(G|theta) relative to p. We call each member B_theta
of this partition a theta-block, and to each theta-block B_theta we naturally
associate a conjugacy class of p-subgroups of G/N, which we call the
theta-defect groups of B_theta. If N is trivial, then the theta-blocks are the
Brauer p-blocks. Using theta-blocks, we can unify the Gluck-Wolf-Navarro-Tiep
theorem and Brauer's Height Zero conjecture in a single statement, which, after
work of B. Sambale, turns out to be equivalent to the the Height Zero
conjecture. We also prove that the k(B)-conjecture is true if and only if every
theta-block B_theta has size less than or equal the size of any of its
theta-defect groups, hence bringing normal subgroups to the k(B)-conjecture.
| math.RT math.GR | let g be a finite group let n be a normal subgroup of g and let theta in irrn be a ginvariant character we fix a prime p and we introduce a canonical partition of irrgtheta relative to p we call each member b_theta of this partition a thetablock and to each thetablock b_theta we naturally associate a conjugacy class of psubgroups of gn which we call the thetadefect groups of b_theta if n is trivial then the thetablocks are the brauer pblocks using thetablocks we can unify the gluckwolfnavarrotiep theorem and brauers height zero conjecture in a single statement which after work of b sambale turns out to be equivalent to the the height zero conjecture we also prove that the kbconjecture is true if and only if every thetablock b_theta has size less than or equal the size of any of its thetadefect groups hence bringing normal subgroups to the kbconjecture | [['let', 'g', 'be', 'a', 'finite', 'group', 'let', 'n', 'be', 'a', 'normal', 'subgroup', 'of', 'g', 'and', 'let', 'theta', 'in', 'irrn', 'be', 'a', 'ginvariant', 'character', 'we', 'fix', 'a', 'prime', 'p', 'and', 'we', 'introduce', 'a', 'canonical', 'partition', 'of', 'irrgtheta', 'relative', 'to', 'p', 'we', 'call', 'each', 'member', 'b_theta', 'of', 'this', 'partition', 'a', 'thetablock', 'and', 'to', 'each', 'thetablock', 'b_theta', 'we', 'naturally', 'associate', 'a', 'conjugacy', 'class', 'of', 'psubgroups', 'of', 'gn', 'which', 'we', 'call', 'the', 'thetadefect', 'groups', 'of', 'b_theta', 'if', 'n', 'is', 'trivial', 'then', 'the', 'thetablocks', 'are', 'the', 'brauer', 'pblocks', 'using', 'thetablocks', 'we', 'can', 'unify', 'the', 'gluckwolfnavarrotiep', 'theorem', 'and', 'brauers', 'height', 'zero', 'conjecture', 'in', 'a', 'single', 'statement', 'which', 'after', 'work', 'of', 'b', 'sambale', 'turns', 'out', 'to', 'be', 'equivalent', 'to', 'the', 'the', 'height', 'zero', 'conjecture', 'we', 'also', 'prove', 'that', 'the', 'kbconjecture', 'is', 'true', 'if', 'and', 'only', 'if', 'every', 'thetablock', 'b_theta', 'has', 'size', 'less', 'than', 'or', 'equal', 'the', 'size', 'of', 'any', 'of', 'its', 'thetadefect', 'groups', 'hence', 'bringing', 'normal', 'subgroups', 'to', 'the', 'kbconjecture']] | [-0.15977650903777718, 0.15091136117363732, -0.14689520747745283, 0.015744942046657256, -0.09810526302237421, -0.1865825525402053, 0.06189131250043642, 0.3104624032435224, -0.31691767840186924, -0.21282642582919423, 0.05860552812722346, -0.26349448561604605, -0.09924346011304233, 0.15601943663085416, -0.12178738013688117, -0.09465312913310561, 0.02338982284809016, 0.14644204982084363, -0.0924447238977922, -0.29707827936213665, 0.3235277505878563, -0.06963080845849767, 0.18778486222137175, 0.038517377189398835, 0.0634808897125305, 0.007040196586374755, 0.041953765563921976, 0.041387922020488715, -0.15011373080484838, 0.07588410851456327, 0.25652551554519787, 0.10205945310825545, 0.2971699149730577, -0.3156227996556506, -0.1059692803952103, 0.26910460177407924, 0.14771683298191693, -0.0038748701479388017, 0.026976463239805848, -0.2297339979910024, 0.21614951346129777, -0.1699613593263577, -0.17516684378592987, -0.0007305481544478911, 0.10929691860745724, -0.022965321610745503, -0.27779180086488925, -0.004208518315165635, 0.096922888227809, 0.06017605957179649, -0.0015572462691797887, -0.1159224240236903, -0.08222459927073693, 0.10520652171115914, -0.0014108455411400902, 0.0701336326358253, 0.06646165764039025, -0.060016869396698494, -0.09200845234899795, 0.4015077483164121, -0.05715022182575673, -0.19705545096594382, 0.0969912298613751, -0.1933440398903283, -0.17315602539448477, 0.09472691964944951, 0.08975728473638835, 0.15058745260745898, -0.010626474542109526, 0.17396111007299822, -0.17181360531496268, 0.13941994895329315, 0.09533382111232191, -0.055981290446951576, 0.14882480961666122, 0.0634770817569878, 0.09574916269805614, 0.15665840159476518, -0.01774460218259937, 0.07676084637913011, -0.3382976751213204, -0.2192115073191155, -0.1471674065998666, 0.16390215086891022, -0.07523006211903684, -0.1702549647769495, 0.37802104871362857, 0.1020185349266721, 0.18120693884892006, 0.1310367522687868, 0.17719522602409635, 0.09299274961893089, 0.08399821091834009, 0.11121528238625815, 0.06439195121861739, 0.20910149351502322, -0.11634691641984941, -0.15228738894124758, 0.025810475030607762, 0.14760977727654453] |
1,802.08175 | Algebra and geometry of tensors for modeling rater agreement data | We study three different quasi-symmetry models and three different mixture
models of $n\times n\times n$ tensors for modeling rater agreement data. For
these models we give a geometric description of the associated varieties and we
study their invariants distinguishing between the case $n=2$ and the case
$n>2$. Finally, for the two models for pairwise agreement we state some results
about the pairwise Cohen's $\kappa$ coefficients.
| math.ST math.AG stat.TH | we study three different quasisymmetry models and three different mixture models of ntimes ntimes n tensors for modeling rater agreement data for these models we give a geometric description of the associated varieties and we study their invariants distinguishing between the case n2 and the case n2 finally for the two models for pairwise agreement we state some results about the pairwise cohens kappa coefficients | [['we', 'study', 'three', 'different', 'quasisymmetry', 'models', 'and', 'three', 'different', 'mixture', 'models', 'of', 'ntimes', 'ntimes', 'n', 'tensors', 'for', 'modeling', 'rater', 'agreement', 'data', 'for', 'these', 'models', 'we', 'give', 'a', 'geometric', 'description', 'of', 'the', 'associated', 'varieties', 'and', 'we', 'study', 'their', 'invariants', 'distinguishing', 'between', 'the', 'case', 'n2', 'and', 'the', 'case', 'n2', 'finally', 'for', 'the', 'two', 'models', 'for', 'pairwise', 'agreement', 'we', 'state', 'some', 'results', 'about', 'the', 'pairwise', 'cohens', 'kappa', 'coefficients']] | [-0.14733567944226356, 0.08878020899943434, -0.013704069438748634, 0.10121197362358754, 0.026253941368598203, -0.17272983698460917, -0.016538260819820256, 0.37798172052089984, -0.1936829871784609, -0.30565857766912535, 0.07136216935200188, -0.35650944923982025, -0.16160753559536087, 0.17776903217801682, -0.0016625809017568826, 0.04357129258032028, 0.06968121517163056, 0.020800935161801485, -0.1186275025543112, -0.25889701465001475, 0.36183053336751003, -0.03291088927250642, 0.24282204629136966, 0.022705489671072707, 0.08436712244561372, -0.009345881096445597, -0.052854429457623225, 0.025349442632152483, -0.20553256002469705, 0.15723437012101596, 0.2543908345398869, 0.12007624865151369, 0.15359470934087696, -0.42891421111730427, -0.17387366241130692, 0.19597549613278645, 0.08833831148222089, 0.08226275670413788, 0.020519243223735918, -0.2214851300088832, 0.04844994188214724, -0.17145553908955594, -0.09817380314836135, -0.1092758739223847, 0.041134559420438914, -0.019068468741786023, -0.326005345575798, 0.04466172740436517, 0.11207595739441996, 0.11220258010121492, -0.13219627662060351, -0.21627155049130894, 0.024787739055374493, 0.14167182330901806, 0.031863767252518584, -0.056574778659985614, 0.0017073589018904245, -0.15827520430947725, -0.11116302274167537, 0.348805273610812, -0.06870951321996892, -0.24096231343081365, 0.243140075642329, -0.11406260184370555, -0.17779965917938031, 0.022840812569484115, 0.15128018520056055, 0.1373663250500193, -0.07759924449313145, 0.057531194758708944, -0.12266002094659667, 0.12735004121294388, 0.04554184976105507, -0.00880349321635619, 0.16420018069374448, 0.06343454371851225, -0.028789579811004492, 0.13336866825030974, -0.027160675280118503, -0.12324404203547881, -0.33045475697144866, -0.14364815344317602, -0.11913619734919988, 0.03900656879234773, -0.21751408253800877, -0.10383962007382741, 0.4121202417864249, 0.15785224512219428, 0.2431922770033662, 0.15899093761108815, 0.22953063897931805, 0.048437809170438696, -0.0701948795431795, 0.02351117071050864, 0.13510941515828911, 0.17342692589244016, -0.005526456136543017, -0.16859037801623344, 0.027041496651676985, 0.10164838612366181] |
1,802.08176 | Analyzing Real-Time Multimedia Content From Network Cameras Using CPUs
and GPUs in the Cloud | Millions of network cameras are streaming real-time multimedia content
(images or videos) for various environments (e.g., highways and malls) and can
be used for a variety of applications. Analyzing the content from many network
cameras requires significant amounts of computing resources. Cloud vendors
offer resources in the form of cloud instances with different capabilities and
hourly costs. Some instances include GPUs that can accelerate analysis
programs. Doing so incurs additional monetary cost because instances with GPUs
are more expensive. It is a challenging problem to reduce the overall monetary
cost of using the cloud to analyze the real-time multimedia content from
network cameras while meeting the desired analysis frame rates. This paper
describes a cloud resource manager that solves this problem by estimating the
resource requirements of executing analysis programs using CPU or GPU,
formulating the resource allocation problem as a multiple-choice vector bin
packing problem, and solving it using an existing algorithm. The experiments
show that the manager can reduce up to 61\% of the cost compared with other
allocation strategies.
| cs.DC | millions of network cameras are streaming realtime multimedia content images or videos for various environments eg highways and malls and can be used for a variety of applications analyzing the content from many network cameras requires significant amounts of computing resources cloud vendors offer resources in the form of cloud instances with different capabilities and hourly costs some instances include gpus that can accelerate analysis programs doing so incurs additional monetary cost because instances with gpus are more expensive it is a challenging problem to reduce the overall monetary cost of using the cloud to analyze the realtime multimedia content from network cameras while meeting the desired analysis frame rates this paper describes a cloud resource manager that solves this problem by estimating the resource requirements of executing analysis programs using cpu or gpu formulating the resource allocation problem as a multiplechoice vector bin packing problem and solving it using an existing algorithm the experiments show that the manager can reduce up to 61 of the cost compared with other allocation strategies | [['millions', 'of', 'network', 'cameras', 'are', 'streaming', 'realtime', 'multimedia', 'content', 'images', 'or', 'videos', 'for', 'various', 'environments', 'eg', 'highways', 'and', 'malls', 'and', 'can', 'be', 'used', 'for', 'a', 'variety', 'of', 'applications', 'analyzing', 'the', 'content', 'from', 'many', 'network', 'cameras', 'requires', 'significant', 'amounts', 'of', 'computing', 'resources', 'cloud', 'vendors', 'offer', 'resources', 'in', 'the', 'form', 'of', 'cloud', 'instances', 'with', 'different', 'capabilities', 'and', 'hourly', 'costs', 'some', 'instances', 'include', 'gpus', 'that', 'can', 'accelerate', 'analysis', 'programs', 'doing', 'so', 'incurs', 'additional', 'monetary', 'cost', 'because', 'instances', 'with', 'gpus', 'are', 'more', 'expensive', 'it', 'is', 'a', 'challenging', 'problem', 'to', 'reduce', 'the', 'overall', 'monetary', 'cost', 'of', 'using', 'the', 'cloud', 'to', 'analyze', 'the', 'realtime', 'multimedia', 'content', 'from', 'network', 'cameras', 'while', 'meeting', 'the', 'desired', 'analysis', 'frame', 'rates', 'this', 'paper', 'describes', 'a', 'cloud', 'resource', 'manager', 'that', 'solves', 'this', 'problem', 'by', 'estimating', 'the', 'resource', 'requirements', 'of', 'executing', 'analysis', 'programs', 'using', 'cpu', 'or', 'gpu', 'formulating', 'the', 'resource', 'allocation', 'problem', 'as', 'a', 'multiplechoice', 'vector', 'bin', 'packing', 'problem', 'and', 'solving', 'it', 'using', 'an', 'existing', 'algorithm', 'the', 'experiments', 'show', 'that', 'the', 'manager', 'can', 'reduce', 'up', 'to', '61', 'of', 'the', 'cost', 'compared', 'with', 'other', 'allocation', 'strategies']] | [-0.1524683522286576, -0.005462868444314957, -0.04199679351654066, 0.04622958484308816, -0.11140476576550755, -0.18428865542397077, 0.1050340223273663, 0.4230133583498469, -0.3090023063014933, -0.41855326371787244, 0.14565064157508206, -0.277752417058489, -0.08109548718527738, 0.20899320663586476, -0.1478757706882302, 0.09947192346877527, 0.1606040808966459, -0.01606883129733073, -0.017936199729203593, -0.31267836413801064, 0.2484402358146157, 0.0865083764453397, 0.31740965070419536, 0.041042246428036756, 0.08275676760172775, -0.014577194815924592, -0.04699006929538797, 0.011869306744449923, 0.00029431793607431625, 0.16371695416286414, 0.33517145991005914, 0.2790301410308064, 0.36028573937919856, -0.49181470337058525, -0.19251967965067515, 0.11249702267327108, 0.1267372105834257, 0.04108570674353084, -0.042439681815330706, -0.25671215530696084, 0.07727514187328864, -0.21513410572092548, -0.016635134720059414, -0.09555565092447323, -0.015562557555101596, 0.029590785354145718, -0.27841283161149816, -0.0020854893089055494, -0.07687813156760882, 0.046697035464349876, -0.052777008307816155, -0.12051140835920218, 0.03477595608646245, 0.17874990023542628, 0.04966245438405421, 0.025143052102066576, 0.1980139354140996, -0.1959916224356654, -0.14653022873870553, 0.4828614006739456, 0.02929574728883846, -0.18213835105010265, 0.17658153675675262, 0.005084778715553152, -0.1630214662967943, 0.13346062645283635, 0.26362976972974816, 0.08454144762173771, -0.1966965069187545, 0.04249201347133643, -0.028304726854616474, 0.19539896616756883, 0.08049049775175707, 0.057973210169219, 0.17576741442344215, 0.20884661934728366, 0.10858941276328973, 0.16597123773528946, -0.06131476482652604, -0.09863549558483714, -0.16199532976349665, -0.16092611452954453, -0.18665019342091022, -0.024197285245632926, -0.10986989512085255, -0.08495959091314309, 0.32582826926887337, 0.1984821101515229, 0.11423878623802096, 0.12155408235293878, 0.40088659981915425, 0.07204292968475953, 0.13747495672354024, 0.18006969718424992, 0.06990944610473424, -0.07482397602735694, 0.21632166445217377, -0.19274770666785582, 0.06890911467746984, 0.0033739905663614355] |
1,802.08177 | New constraints on Lyman-{\alpha} opacity with a sample of 62 quasars at
z > 5.7 | We present measurements of the mean and scatter of the IGM Lyman-{\alpha}
opacity at 4.9 < z < 6.1 along the lines of sight of 62 quasars at z > 5.7, the
largest sample assembled at these redshifts to date by a factor of two. The
sample size enables us to sample cosmic variance at these redshifts more
robustly than ever before. The spectra used here were obtained by the SDSS,
DES-VHS and SHELLQs collaborations, drawn from the ESI and X-Shooter archives,
reused from previous studies or observed specifically for this work. We measure
the effective optical depth of Lyman-{\alpha} in bins of 10, 30, 50 and 70 cMpc
h-1, construct cumulative distribution functions under two treatments of upper
limits on flux and explore an empirical analytic fit to residual Lyman-{\alpha}
transmission. We verify the consistency of our results with those of previous
studies via bootstrap re-sampling and confirm the existence of tails towards
high values in the opacity distributions, which may persist down to z = 5.2.
Comparing our results with predictions from cosmological simulations, we find
further strong evidence against models that include a spatially uniform
ionizing background and temperature-density relation. We also compare to IGM
models that include either a fluctuating UVB dominated by rare quasars or
temperature fluctuations due to patchy reionization. Although both models
produce better agreement with the observations, neither fully captures the
observed scatter in IGM opacity. Our sample of 62 z > 5.7 quasar spectra opens
many avenues for future study of the reionisation epoch.
| astro-ph.GA astro-ph.CO | we present measurements of the mean and scatter of the igm lymanalpha opacity at 49 z 61 along the lines of sight of 62 quasars at z 57 the largest sample assembled at these redshifts to date by a factor of two the sample size enables us to sample cosmic variance at these redshifts more robustly than ever before the spectra used here were obtained by the sdss desvhs and shellqs collaborations drawn from the esi and xshooter archives reused from previous studies or observed specifically for this work we measure the effective optical depth of lymanalpha in bins of 10 30 50 and 70 cmpc h1 construct cumulative distribution functions under two treatments of upper limits on flux and explore an empirical analytic fit to residual lymanalpha transmission we verify the consistency of our results with those of previous studies via bootstrap resampling and confirm the existence of tails towards high values in the opacity distributions which may persist down to z 52 comparing our results with predictions from cosmological simulations we find further strong evidence against models that include a spatially uniform ionizing background and temperaturedensity relation we also compare to igm models that include either a fluctuating uvb dominated by rare quasars or temperature fluctuations due to patchy reionization although both models produce better agreement with the observations neither fully captures the observed scatter in igm opacity our sample of 62 z 57 quasar spectra opens many avenues for future study of the reionisation epoch | [['we', 'present', 'measurements', 'of', 'the', 'mean', 'and', 'scatter', 'of', 'the', 'igm', 'lymanalpha', 'opacity', 'at', '49', 'z', '61', 'along', 'the', 'lines', 'of', 'sight', 'of', '62', 'quasars', 'at', 'z', '57', 'the', 'largest', 'sample', 'assembled', 'at', 'these', 'redshifts', 'to', 'date', 'by', 'a', 'factor', 'of', 'two', 'the', 'sample', 'size', 'enables', 'us', 'to', 'sample', 'cosmic', 'variance', 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1,802.08178 | Correlation-Adjusted Regression Survival Scores for High-Dimensional
Variable Selection | Background: The development of classification methods for personalized
medicine is highly dependent on the identification of predictive genetic
markers. In survival analysis it is often necessary to discriminate between
influential and non-influential markers. Usually, the first step is to perform
a univariate screening step that ranks the markers according to their
associations with the outcome. It is common to perform screening using Cox
scores, which quantify the associations between survival and each of the
markers individually. Since Cox scores do not account for dependencies between
the markers, their use is suboptimal in the presence highly correlated markers.
Methods: As an alternative to the Cox score, we propose the
correlation-adjusted regression survival (CARS) score for right-censored
survival outcomes. By removing the correlations between the markers, the CARS
score quantifies the associations between the outcome and the set of
"de-correlated" marker values. Estimation of the scores is based on inverse
probability weighting, which is applied to log-transformed event times. For
high-dimensional data, estimation is based on shrinkage techniques. Results:
The consistency of the CARS score is proven under mild regularity conditions.
In simulations, survival models based on CARS score rankings achieved higher
areas under the precision-recall curve than competing methods. Two example
applications on prostate and breast cancer confirmed these results. CARS scores
are implemented in the R package carSurv. Conclusions: In research applications
involving high-dimensional genetic data, the use of CARS scores for marker
selection is a favorable alternative to Cox scores even when correlations
between covariates are low. Having a straightforward interpretation and low
computational requirements, CARS scores are an easy-to-use screening tool in
personalized medicine research.
| stat.ME | background the development of classification methods for personalized medicine is highly dependent on the identification of predictive genetic markers in survival analysis it is often necessary to discriminate between influential and noninfluential markers usually the first step is to perform a univariate screening step that ranks the markers according to their associations with the outcome it is common to perform screening using cox scores which quantify the associations between survival and each of the markers individually since cox scores do not account for dependencies between the markers their use is suboptimal in the presence highly correlated markers methods as an alternative to the cox score we propose the correlationadjusted regression survival cars score for rightcensored survival outcomes by removing the correlations between the markers the cars score quantifies the associations between the outcome and the set of decorrelated marker values estimation of the scores is based on inverse probability weighting which is applied to logtransformed event times for highdimensional data estimation is based on shrinkage techniques results the consistency of the cars score is proven under mild regularity conditions in simulations survival models based on cars score rankings achieved higher areas under the precisionrecall curve than competing methods two example applications on prostate and breast cancer confirmed these results cars scores are implemented in the r package carsurv conclusions in research applications involving highdimensional genetic data the use of cars scores for marker selection is a favorable alternative to cox scores even when correlations between covariates are low having a straightforward interpretation and low computational requirements cars scores are an easytouse screening tool in personalized medicine research | [['background', 'the', 'development', 'of', 'classification', 'methods', 'for', 'personalized', 'medicine', 'is', 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1,802.08179 | Elements of the Kopula (eventological copula) theory | New in the probability theory and eventology theory, the concept of Kopula
(eventological copula) is introduced. The theorem on the characterization of
the sets of events by Kopula is proved, which serves as the eventological
pre-image of the well-known Sclar's theorem on copulas (1959). The Kopulas of
doublets and triplets of events are given, as well as of some N-sets of events.
| stat.OT | new in the probability theory and eventology theory the concept of kopula eventological copula is introduced the theorem on the characterization of the sets of events by kopula is proved which serves as the eventological preimage of the wellknown sclars theorem on copulas 1959 the kopulas of doublets and triplets of events are given as well as of some nsets of events | [['new', 'in', 'the', 'probability', 'theory', 'and', 'eventology', 'theory', 'the', 'concept', 'of', 'kopula', 'eventological', 'copula', 'is', 'introduced', 'the', 'theorem', 'on', 'the', 'characterization', 'of', 'the', 'sets', 'of', 'events', 'by', 'kopula', 'is', 'proved', 'which', 'serves', 'as', 'the', 'eventological', 'preimage', 'of', 'the', 'wellknown', 'sclars', 'theorem', 'on', 'copulas', '1959', 'the', 'kopulas', 'of', 'doublets', 'and', 'triplets', 'of', 'events', 'are', 'given', 'as', 'well', 'as', 'of', 'some', 'nsets', 'of', 'events']] | [-0.08242111584043195, 0.08796970478804975, -0.09068292600969816, 0.14333024796435673, -0.010353532154113054, -0.07653209017910834, 0.05406574401409859, 0.2546505841972499, -0.22616858600542464, -0.2886192088561325, 0.10183786634347755, -0.30025357136438635, -0.13517363504346075, 0.20634662481787583, -0.12334627831547425, 0.05378702634560137, -0.011799291852090893, 0.07733067213397088, 0.004113388151444238, -0.228766020772786, 0.34102917746801314, 0.05212879396878697, 0.2610077434540566, 0.07593840887320452, 0.14171274453562138, 0.05897892682395618, -0.07471184283976667, -0.0222675624094775, -0.10498627001050345, 0.11083046488206962, 0.22333245043610706, 0.2066316954181369, 0.26804885399881107, -0.3388100414183633, -0.1724181755823244, 0.07317880003568555, 0.04477770344739587, 0.04174168264003599, 0.013262209093101836, -0.3412396065120039, 0.06945272502569674, -0.14168556910891342, -0.14559436311688403, -0.056778968217509704, 0.011927995509628591, 0.06951453764762344, -0.28338579422441024, 0.09297467834027164, 0.141278620289462, 0.06507240791387599, -0.007180097225876847, -0.12635502447213592, -0.054826411342344665, 0.04995235599224167, 0.09591517621522834, -0.0043640954516314225, 0.0815121765842597, -0.092894462740113, -0.1932455855421722, 0.3635500226298283, -0.0338020999755325, -0.15378640251683778, 0.1728022802693384, -0.10693221702240407, -0.13903216920504025, 0.04421609203363287, 0.1309100167087183, 0.14774066405691977, -0.14312519142725344, 0.11443278072843456, -0.11307559884956171, 0.05205563837983485, 0.09855049903954155, 0.055623548394390224, 0.162481513613, 0.14509541486743197, 0.0637950985772728, 0.14238332839811157, -0.0695661710864254, -0.0802729117106004, -0.35287137715555406, -0.16944393785349254, -0.21553697318224044, 0.023773931015025954, -0.07883672217049652, -0.23599557337704405, 0.3919766529880721, 0.07423848924548204, 0.19528675426183076, 0.04216932002976858, 0.20991030873746835, 0.13174546748632565, 0.042826522655528165, -0.025090915977890635, 0.16036785242462867, 0.2184577382306151, 0.02169255448248366, -0.0686850977001776, 0.0931292459095732, 0.14908209676725853] |
1,802.0818 | Algebroid Structures on Para-Hermitian Manifolds | We present a global construction of a so-called D-bracket appearing in the
physics literature of Double Field Theory (DFT) and show that if certain
integrability criteria are satisfied, it can be seen as a sum of two Courant
algebroid brackets. In particular, we show that the local picture of the
extended space-time used in DFT fits naturally in the geometrical framework of
para-Hermitian manifolds and that the data of an (almost) para-Hermitian
manifold is sufficient to construct the D-bracket. Moreover, the twists of the
bracket appearing in DFT can be interpreted in this framework geometrically as
a consequence of certain deformations of the underlying para-Hermitian
structure.
| math.DG hep-th math-ph math.MP | we present a global construction of a socalled dbracket appearing in the physics literature of double field theory dft and show that if certain integrability criteria are satisfied it can be seen as a sum of two courant algebroid brackets in particular we show that the local picture of the extended spacetime used in dft fits naturally in the geometrical framework of parahermitian manifolds and that the data of an almost parahermitian manifold is sufficient to construct the dbracket moreover the twists of the bracket appearing in dft can be interpreted in this framework geometrically as a consequence of certain deformations of the underlying parahermitian structure | [['we', 'present', 'a', 'global', 'construction', 'of', 'a', 'socalled', 'dbracket', 'appearing', 'in', 'the', 'physics', 'literature', 'of', 'double', 'field', 'theory', 'dft', 'and', 'show', 'that', 'if', 'certain', 'integrability', 'criteria', 'are', 'satisfied', 'it', 'can', 'be', 'seen', 'as', 'a', 'sum', 'of', 'two', 'courant', 'algebroid', 'brackets', 'in', 'particular', 'we', 'show', 'that', 'the', 'local', 'picture', 'of', 'the', 'extended', 'spacetime', 'used', 'in', 'dft', 'fits', 'naturally', 'in', 'the', 'geometrical', 'framework', 'of', 'parahermitian', 'manifolds', 'and', 'that', 'the', 'data', 'of', 'an', 'almost', 'parahermitian', 'manifold', 'is', 'sufficient', 'to', 'construct', 'the', 'dbracket', 'moreover', 'the', 'twists', 'of', 'the', 'bracket', 'appearing', 'in', 'dft', 'can', 'be', 'interpreted', 'in', 'this', 'framework', 'geometrically', 'as', 'a', 'consequence', 'of', 'certain', 'deformations', 'of', 'the', 'underlying', 'parahermitian', 'structure']] | [-0.17474156904231328, 0.05921489893710084, -0.13987512346536207, 0.142224232146803, -0.07684258458455308, -0.08499998731825215, -0.03936045796301467, 0.3531530934426253, -0.32708825525612784, -0.2797346288123383, 0.08620876117940778, -0.17301610296663755, -0.24271545168728784, 0.15861602211729264, -0.10365783733029205, -0.008909727187039187, 0.04619791094536105, 0.08138148905261634, -0.13374965133082767, -0.24159874782960217, 0.379287174952109, 0.03215097958813063, 0.24671211439328125, 0.03422514667013624, 0.08643969981326685, -0.012649361017303398, 0.024830120976100892, 0.05400950248048712, -0.13645677404502538, 0.12766920909500465, 0.2648932948314513, 0.08585091805658661, 0.16824381043149444, -0.44408789857810077, -0.19013653822492835, 0.07729709377879491, 0.14163805201846677, 0.07564271794846998, -0.021931399512910642, -0.2644390150044973, 0.07349614807082197, -0.17055014091937876, -0.16258885682775423, -0.12330960266542836, -0.054909990575442165, 0.0031504825993369403, -0.2250484492021944, 0.07281636143139061, 0.1203024048165669, 0.044906730306907915, -0.11099888560084555, -0.07693752109144743, -0.07992188913228276, 0.06249631370883435, 0.027616171441667784, 0.02934565954358102, 0.1009103878795241, -0.08985920517051664, -0.13088293652309893, 0.4146009007862841, -0.0730664944209051, -0.237164049178738, 0.10735998614332996, -0.13889608896771768, -0.18910283555473703, 0.09977218717820226, 0.07544174738443242, 0.11717819650836575, -0.1403453150196583, 0.17077995445736002, -0.10833547590300441, 0.08037503625158794, 0.07783157288437136, 0.039101230271626264, 0.16735856535020643, 0.10745431402868305, 0.08138385088218805, 0.09825698938444614, -0.03553431044845358, -0.12006520999308962, -0.4104348414537246, -0.18096275974312448, -0.143177594901667, 0.11431956257393512, -0.10394216974936381, -0.2041647036989721, 0.38668117212812203, 0.09685880742752208, 0.21928548252729413, 0.026779411184529287, 0.19754848314467102, 0.09978730406538279, 0.09652054320223705, 0.04229631656870389, 0.221199948656319, 0.20115143152025455, 0.031100439104753044, -0.11934427045679723, -0.03227529608949016, 0.10592476818979216] |
1,802.08181 | Infrared study of the quasi-two-dimensional electron system at the
interface between SrTiO$_{3}$ and crystalline or amorphous LaAlO$_3$ | We have used grazing-angle infrared spectroscopy to detect the Berreman
effect (BE) in the quasi-two-dimensional electron system (q-2DES) which forms
spontaneously at the interface between SrTiO$_{3}$ (STO) and a thin film of
LaAlO$_3$ (LAO). From the BE, which allows one to study longitudinal optical
excitations in ultrathin films like the q-2DES, we have extracted at different
temperatures its thickness, the charge density and mobility of the carriers
under crystalline LAO (sample A), and the charge density under amorphous LAO
(sample B). This quantity turns out to be higher than in sample A, but a
comparison with Hall measurements shows that under amorphous LAO the charges
are partly localized at low $T$ with a low activation energy (about 190 K in
$k_B$ units), and are thermally activated according to a model for large
polarons. The thickness of the q-2DES extracted from our spectra turns out to
be 4 $\pm 1$ nm for crystalline LAO, 7 $\pm 2$ nm for amorphous LAO.
| cond-mat.mtrl-sci | we have used grazingangle infrared spectroscopy to detect the berreman effect be in the quasitwodimensional electron system q2des which forms spontaneously at the interface between srtio_3 sto and a thin film of laalo_3 lao from the be which allows one to study longitudinal optical excitations in ultrathin films like the q2des we have extracted at different temperatures its thickness the charge density and mobility of the carriers under crystalline lao sample a and the charge density under amorphous lao sample b this quantity turns out to be higher than in sample a but a comparison with hall measurements shows that under amorphous lao the charges are partly localized at low t with a low activation energy about 190 k in k_b units and are thermally activated according to a model for large polarons the thickness of the q2des extracted from our spectra turns out to be 4 pm 1 nm for crystalline lao 7 pm 2 nm for amorphous lao | [['we', 'have', 'used', 'grazingangle', 'infrared', 'spectroscopy', 'to', 'detect', 'the', 'berreman', 'effect', 'be', 'in', 'the', 'quasitwodimensional', 'electron', 'system', 'q2des', 'which', 'forms', 'spontaneously', 'at', 'the', 'interface', 'between', 'srtio_3', 'sto', 'and', 'a', 'thin', 'film', 'of', 'laalo_3', 'lao', 'from', 'the', 'be', 'which', 'allows', 'one', 'to', 'study', 'longitudinal', 'optical', 'excitations', 'in', 'ultrathin', 'films', 'like', 'the', 'q2des', 'we', 'have', 'extracted', 'at', 'different', 'temperatures', 'its', 'thickness', 'the', 'charge', 'density', 'and', 'mobility', 'of', 'the', 'carriers', 'under', 'crystalline', 'lao', 'sample', 'a', 'and', 'the', 'charge', 'density', 'under', 'amorphous', 'lao', 'sample', 'b', 'this', 'quantity', 'turns', 'out', 'to', 'be', 'higher', 'than', 'in', 'sample', 'a', 'but', 'a', 'comparison', 'with', 'hall', 'measurements', 'shows', 'that', 'under', 'amorphous', 'lao', 'the', 'charges', 'are', 'partly', 'localized', 'at', 'low', 't', 'with', 'a', 'low', 'activation', 'energy', 'about', '190', 'k', 'in', 'k_b', 'units', 'and', 'are', 'thermally', 'activated', 'according', 'to', 'a', 'model', 'for', 'large', 'polarons', 'the', 'thickness', 'of', 'the', 'q2des', 'extracted', 'from', 'our', 'spectra', 'turns', 'out', 'to', 'be', '4', 'pm', '1', 'nm', 'for', 'crystalline', 'lao', '7', 'pm', '2', 'nm', 'for', 'amorphous', 'lao']] | [-0.09517947777995178, 0.22558264619137788, -0.08450407605419087, -0.032672330813992, 0.043551846331208004, -0.167296819374223, 0.09879595067047472, 0.4148414681238011, -0.2481792276584596, -0.32983926615133036, 0.028350414457853954, -0.34771738698240734, -0.03648004262655411, 0.16474708172261315, 0.026072969396581065, -0.002940493647548013, -0.0656115344707977, -0.07186942243012863, -0.07788061889316067, -0.19762667904625525, 0.23983318881723303, 0.031895096771091036, 0.3400829312275896, 0.10130359131715454, 0.03334698043309691, -0.0317059756391085, 0.12269044195963714, 0.005732368074133099, -0.19238744479474654, 0.05574205302803209, 0.2854078802391418, -0.15267377135888585, 0.19221684679831233, -0.4731208804823951, -0.18183464842772334, -0.03275676180590999, 0.0857850009071752, 0.09144650073941657, -0.049571357777638, -0.234333829875192, 0.14111242809335836, -0.1096870929365919, -0.06436606595562126, -0.04337907899405409, 0.020524716567037242, -0.03976267558791962, -0.2670910561434579, 0.11454339685839594, 0.02982793057208541, 0.11856115673692112, -0.12509177094464535, -0.16341163180168108, -0.14745959191020788, 0.05685011348716399, 0.054036642148733466, 0.07267791271845242, 0.24576789212747002, -0.0895182125544199, -0.03175053777284451, 0.32110050851010585, -0.06049179892927341, -0.08004339798368255, 0.19125167576525853, -0.20252987625276517, -0.04760777904599343, 0.21143967684053774, 0.1336463880597075, 0.13553932562921453, -0.14792424688553554, 0.055878907175948435, -0.010561190914573535, 0.24289644247143524, 0.10890660697811008, 0.06866921559591198, 0.26270709485225613, 0.1877364061315948, 0.026727601525567052, 0.13642912706266502, -0.16462519450652055, 0.03624723416184948, -0.21390140022344464, -0.1976497306183871, -0.20300571761187752, 0.0993411003395259, -0.09106765663505344, -0.14069893313630386, 0.36081809162765555, 0.10637515161609103, 0.19348068849576064, -0.04702775349837593, 0.19821228387138848, 0.0588577369831315, 0.12802558927613739, 0.05612848174125659, 0.23353600084090476, 0.1711755571652602, 0.13332943015143572, -0.21585700802399582, 0.06291097255845396, -0.020620439444674447] |
1,802.08182 | User Perceptions of Smart Home IoT Privacy | Smart home Internet of Things (IoT) devices are rapidly increasing in
popularity, with more households including Internet-connected devices that
continuously monitor user activities. In this study, we conduct eleven
semi-structured interviews with smart home owners, investigating their reasons
for purchasing IoT devices, perceptions of smart home privacy risks, and
actions taken to protect their privacy from those external to the home who
create, manage, track, or regulate IoT devices and/or their data. We note
several recurring themes. First, users' desires for convenience and
connectedness dictate their privacy-related behaviors for dealing with external
entities, such as device manufacturers, Internet Service Providers,
governments, and advertisers. Second, user opinions about external entities
collecting smart home data depend on perceived benefit from these entities.
Third, users trust IoT device manufacturers to protect their privacy but do not
verify that these protections are in place. Fourth, users are unaware of
privacy risks from inference algorithms operating on data from non-audio/visual
devices. These findings motivate several recommendations for device designers,
researchers, and industry standards to better match device privacy features to
the expectations and preferences of smart home owners.
| cs.HC | smart home internet of things iot devices are rapidly increasing in popularity with more households including internetconnected devices that continuously monitor user activities in this study we conduct eleven semistructured interviews with smart home owners investigating their reasons for purchasing iot devices perceptions of smart home privacy risks and actions taken to protect their privacy from those external to the home who create manage track or regulate iot devices andor their data we note several recurring themes first users desires for convenience and connectedness dictate their privacyrelated behaviors for dealing with external entities such as device manufacturers internet service providers governments and advertisers second user opinions about external entities collecting smart home data depend on perceived benefit from these entities third users trust iot device manufacturers to protect their privacy but do not verify that these protections are in place fourth users are unaware of privacy risks from inference algorithms operating on data from nonaudiovisual devices these findings motivate several recommendations for device designers researchers and industry standards to better match device privacy features to the expectations and preferences of smart home owners | [['smart', 'home', 'internet', 'of', 'things', 'iot', 'devices', 'are', 'rapidly', 'increasing', 'in', 'popularity', 'with', 'more', 'households', 'including', 'internetconnected', 'devices', 'that', 'continuously', 'monitor', 'user', 'activities', 'in', 'this', 'study', 'we', 'conduct', 'eleven', 'semistructured', 'interviews', 'with', 'smart', 'home', 'owners', 'investigating', 'their', 'reasons', 'for', 'purchasing', 'iot', 'devices', 'perceptions', 'of', 'smart', 'home', 'privacy', 'risks', 'and', 'actions', 'taken', 'to', 'protect', 'their', 'privacy', 'from', 'those', 'external', 'to', 'the', 'home', 'who', 'create', 'manage', 'track', 'or', 'regulate', 'iot', 'devices', 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1,802.08183 | Projection-Free Online Optimization with Stochastic Gradient: From
Convexity to Submodularity | Online optimization has been a successful framework for solving large-scale
problems under computational constraints and partial information. Current
methods for online convex optimization require either a projection or exact
gradient computation at each step, both of which can be prohibitively expensive
for large-scale applications. At the same time, there is a growing trend of
non-convex optimization in machine learning community and a need for online
methods. Continuous DR-submodular functions, which exhibit a natural
diminishing returns condition, have recently been proposed as a broad class of
non-convex functions which may be efficiently optimized. Although online
methods have been introduced, they suffer from similar problems. In this work,
we propose Meta-Frank-Wolfe, the first online projection-free algorithm that
uses stochastic gradient estimates. The algorithm relies on a careful sampling
of gradients in each round and achieves the optimal $O( \sqrt{T})$ adversarial
regret bounds for convex and continuous submodular optimization. We also
propose One-Shot Frank-Wolfe, a simpler algorithm which requires only a single
stochastic gradient estimate in each round and achieves an $O(T^{2/3})$
stochastic regret bound for convex and continuous submodular optimization. We
apply our methods to develop a novel "lifting" framework for the online
discrete submodular maximization and also see that they outperform current
state-of-the-art techniques on various experiments.
| stat.ML cs.AI cs.DS cs.LG | online optimization has been a successful framework for solving largescale problems under computational constraints and partial information current methods for online convex optimization require either a projection or exact gradient computation at each step both of which can be prohibitively expensive for largescale applications at the same time there is a growing trend of nonconvex optimization in machine learning community and a need for online methods continuous drsubmodular functions which exhibit a natural diminishing returns condition have recently been proposed as a broad class of nonconvex functions which may be efficiently optimized although online methods have been introduced they suffer from similar problems in this work we propose metafrankwolfe the first online projectionfree algorithm that uses stochastic gradient estimates the algorithm relies on a careful sampling of gradients in each round and achieves the optimal o sqrtt adversarial regret bounds for convex and continuous submodular optimization we also propose oneshot frankwolfe a simpler algorithm which requires only a single stochastic gradient estimate in each round and achieves an ot23 stochastic regret bound for convex and continuous submodular optimization we apply our methods to develop a novel lifting framework for the online discrete submodular maximization and also see that they outperform current stateoftheart techniques on various experiments | [['online', 'optimization', 'has', 'been', 'a', 'successful', 'framework', 'for', 'solving', 'largescale', 'problems', 'under', 'computational', 'constraints', 'and', 'partial', 'information', 'current', 'methods', 'for', 'online', 'convex', 'optimization', 'require', 'either', 'a', 'projection', 'or', 'exact', 'gradient', 'computation', 'at', 'each', 'step', 'both', 'of', 'which', 'can', 'be', 'prohibitively', 'expensive', 'for', 'largescale', 'applications', 'at', 'the', 'same', 'time', 'there', 'is', 'a', 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1,802.08184 | Colour Confinement: a Dynamical Phenomenon of QCD | We study in this Letter the origin of the confinement in QCD by analyzing the
colour charge of physics states. We derive the colour charge operator in QCD
and compare it with the electromagnetic charge operator in QED. It shows that
the two charges have very similar structure, but the dynamical properties of
the gauge fields are different. The difference between the behaviours of the
gauge boson propagator at zero momentum for QCD and that for QED guarantees
that there occurs colour confinement in QCD but there is no confinement in QED.
We give then a universal relation between the confinement and the dynamical
property of QCD and reveals the origin of the colour confinement, which can be
demonstrated as the dynamical effect of QCD or more explicitly the dynamical
mass generation of the gluon.
| hep-ph hep-th | we study in this letter the origin of the confinement in qcd by analyzing the colour charge of physics states we derive the colour charge operator in qcd and compare it with the electromagnetic charge operator in qed it shows that the two charges have very similar structure but the dynamical properties of the gauge fields are different the difference between the behaviours of the gauge boson propagator at zero momentum for qcd and that for qed guarantees that there occurs colour confinement in qcd but there is no confinement in qed we give then a universal relation between the confinement and the dynamical property of qcd and reveals the origin of the colour confinement which can be demonstrated as the dynamical effect of qcd or more explicitly the dynamical mass generation of the gluon | [['we', 'study', 'in', 'this', 'letter', 'the', 'origin', 'of', 'the', 'confinement', 'in', 'qcd', 'by', 'analyzing', 'the', 'colour', 'charge', 'of', 'physics', 'states', 'we', 'derive', 'the', 'colour', 'charge', 'operator', 'in', 'qcd', 'and', 'compare', 'it', 'with', 'the', 'electromagnetic', 'charge', 'operator', 'in', 'qed', 'it', 'shows', 'that', 'the', 'two', 'charges', 'have', 'very', 'similar', 'structure', 'but', 'the', 'dynamical', 'properties', 'of', 'the', 'gauge', 'fields', 'are', 'different', 'the', 'difference', 'between', 'the', 'behaviours', 'of', 'the', 'gauge', 'boson', 'propagator', 'at', 'zero', 'momentum', 'for', 'qcd', 'and', 'that', 'for', 'qed', 'guarantees', 'that', 'there', 'occurs', 'colour', 'confinement', 'in', 'qcd', 'but', 'there', 'is', 'no', 'confinement', 'in', 'qed', 'we', 'give', 'then', 'a', 'universal', 'relation', 'between', 'the', 'confinement', 'and', 'the', 'dynamical', 'property', 'of', 'qcd', 'and', 'reveals', 'the', 'origin', 'of', 'the', 'colour', 'confinement', 'which', 'can', 'be', 'demonstrated', 'as', 'the', 'dynamical', 'effect', 'of', 'qcd', 'or', 'more', 'explicitly', 'the', 'dynamical', 'mass', 'generation', 'of', 'the', 'gluon']] | [-0.10952734779480293, 0.24045667520689742, -0.1579714113673954, 0.111503592485355, -0.009718225413450488, -0.0672062892673744, 0.025102931892292367, 0.4044427460818379, -0.184322814517482, -0.2491751435161051, 0.00891031070129463, -0.2652246737231811, -0.11709813825975827, 0.09644046921145033, 0.01978434470516664, 0.04094908794871083, -0.011875791012964867, 0.039012339611158325, -0.08738222171000584, -0.19185131799809083, 0.3559772872779932, -0.02971039279019115, 0.25214400158988104, 0.18227381822480648, 0.0834205191237507, 0.004676021764020401, -0.02631180569253586, 0.0084750904287729, -0.08045639082766785, 0.03089865383355775, 0.17677717257153105, 0.03708072487368352, 0.17647206903159343, -0.3790181889716122, -0.18879748061644258, 0.09274679662452803, 0.12865688584193036, 0.12642512309313234, -0.11315479277756013, -0.23348250025538383, 0.09340791449088741, -0.16146008617900037, -0.1507604476875039, -0.0820265040922634, 0.013294341446210941, -0.04433211371888993, -0.27623483201152543, 0.08552619351970929, 0.03333384140774056, 0.04798757255215336, -0.024027439331014953, -0.09473903050163278, -0.07541190927710247, 0.11381511125127199, 0.10441811426059791, 0.0635562441466997, 0.12218639608068366, -0.23062091878684307, -0.15912596794940462, 0.44801212338454743, -0.02614374964635957, -0.1806972203983201, 0.17615102071453023, -0.20967533301424096, -0.12458256267494074, 0.08852481909993071, 0.12250165801184873, 0.08142243008715687, -0.16188121253874635, 0.13041409983782581, -0.031803389053998724, 0.14264129798307462, 0.06474570210471198, 0.13954893605076465, 0.23696188210613198, 0.1412488925555307, 0.008079866832122206, 0.12287200147337797, -0.022775231496672387, -0.1299730799402352, -0.36675316795568774, -0.11907066682146655, -0.1637007715611684, 0.064020667064728, -0.13575512698487188, -0.17576822183198398, 0.40981251246951245, 0.18679478670711872, 0.20795650026347073, -0.0052794412908109805, 0.28121118700062786, 0.1607764856501793, 0.10827084365128367, 0.05700823447701556, 0.3159568428355097, 0.17929520289827552, 0.12311964473790593, -0.3302497117762902, -0.05116295138442958, 0.11209212721635899] |
1,802.08185 | On quaternion algebra over the composite of quadratic number fields and
over some dihedral fields | Let p and q be two positive primes. In this paper we obtain a complete
characterization of quaternion division algebras H_K(p,q) over the composite K
of n quadratic number fields. Also, in Section 6, we obtain a characterization
of quaternion division algebras H_K(p,q) over some dihedral fields K.
| math.NT | let p and q be two positive primes in this paper we obtain a complete characterization of quaternion division algebras h_kpq over the composite k of n quadratic number fields also in section 6 we obtain a characterization of quaternion division algebras h_kpq over some dihedral fields k | [['let', 'p', 'and', 'q', 'be', 'two', 'positive', 'primes', 'in', 'this', 'paper', 'we', 'obtain', 'a', 'complete', 'characterization', 'of', 'quaternion', 'division', 'algebras', 'h_kpq', 'over', 'the', 'composite', 'k', 'of', 'n', 'quadratic', 'number', 'fields', 'also', 'in', 'section', '6', 'we', 'obtain', 'a', 'characterization', 'of', 'quaternion', 'division', 'algebras', 'h_kpq', 'over', 'some', 'dihedral', 'fields', 'k']] | [-0.2643853214002498, 0.12488221498611181, -0.10236058550198442, -0.01763072408705383, -0.08704936350493328, -0.1351282371248564, -0.021660434261834977, 0.3367541390268699, -0.3158332818876142, -0.2500170058692279, 0.0413309934741372, -0.19382231338354555, -0.14813033485805374, 0.20129075549218967, -0.06659526792962266, -0.09666548892045798, -0.021290973071818767, 0.14871633915311616, -0.11573621081998167, -0.3985957977483454, 0.2982573662277149, -0.08385761739159732, 0.1399980560856183, 0.00539115196822778, 0.059120199501352465, 0.11664749421786678, -0.03170435796694263, -0.02095408242135106, -0.20882001551597015, 0.08575920930699162, 0.37118195254436653, 0.09967493907669964, 0.26273202612672164, -0.3218337125752283, -0.11871713269805617, 0.26794073220504366, 0.19506409956628215, -0.02276482805609703, -0.031138554073708212, -0.14470909564229456, 0.14582739523662577, -0.18960447398864705, -0.12880372592126546, -0.06306451648149801, 0.11073411035391947, -0.020903115818762908, -0.34108357495911745, 0.011603118076733232, 0.1179227786310746, 0.2495695367536467, -0.11267527274321765, -0.2248899820868088, 0.06217976837702419, 0.03430320018821437, -0.07145739350791859, -0.01245232185844899, 0.03435953910988958, -0.03955529405958141, -0.18689216503306574, 0.31797794657556905, -0.018087330760191315, -0.20265740010401476, 0.07315250534726225, -0.25548372895497345, -0.10104113813165737, 0.17862638997156982, 0.19833663607056698, 0.1454317950511999, -0.057309730828780193, 0.20036381351351534, -0.1569952683766251, 0.09169016069854083, 0.2038354747928679, 0.0028146162386173787, 0.12884085147601107, 0.013983951112174469, 0.0885578282987294, 0.12633999661572845, 0.031496675280125244, 0.026192614170925124, -0.3807255959381228, -0.2270422699942213, -0.10552329847427167, 0.1858413298082862, -0.1290586027617278, -0.1530350216704866, 0.4180805895720487, 0.03187690683357094, 0.1910894545726478, 0.11945484266818865, 0.2047823238712938, 0.026093627710867186, 0.08822407989519769, 0.0038704872738731942, 0.029287714382719612, 0.32327527807944495, -0.024777352430290826, -0.11883878924519471, -0.12425589315471766, 0.09318381781770807] |
1,802.08186 | Schr\"odinger-Koopman quasienergy states of quantum systems driven by a
classical flow | We study the properties of the quasienergy states of a quantum system driven
by a classical dynamical system. The quasienergies are defined in a same manner
as in light-matter interaction but where the Floquet approach is generalized by
the use of the Koopman approach of dynamical systems. We show how the
properties of the classical flow (fixed and cyclic points, ergodicity, chaos)
influence the driven quantum system. This approach of the Schr\"odinger-Koopman
quasienergies can be applied to quantum control, quantum information in
presence of noises, and dynamics of mixed classical-quantum systems. We treat
the example of a kicked spin ensemble where the kick modulation is governed by
discrete classical flows as the Arnold's cat map and the Chirikov standard map.
| math-ph math.MP nlin.CD quant-ph | we study the properties of the quasienergy states of a quantum system driven by a classical dynamical system the quasienergies are defined in a same manner as in lightmatter interaction but where the floquet approach is generalized by the use of the koopman approach of dynamical systems we show how the properties of the classical flow fixed and cyclic points ergodicity chaos influence the driven quantum system this approach of the schrodingerkoopman quasienergies can be applied to quantum control quantum information in presence of noises and dynamics of mixed classicalquantum systems we treat the example of a kicked spin ensemble where the kick modulation is governed by discrete classical flows as the arnolds cat map and the chirikov standard map | [['we', 'study', 'the', 'properties', 'of', 'the', 'quasienergy', 'states', 'of', 'a', 'quantum', 'system', 'driven', 'by', 'a', 'classical', 'dynamical', 'system', 'the', 'quasienergies', 'are', 'defined', 'in', 'a', 'same', 'manner', 'as', 'in', 'lightmatter', 'interaction', 'but', 'where', 'the', 'floquet', 'approach', 'is', 'generalized', 'by', 'the', 'use', 'of', 'the', 'koopman', 'approach', 'of', 'dynamical', 'systems', 'we', 'show', 'how', 'the', 'properties', 'of', 'the', 'classical', 'flow', 'fixed', 'and', 'cyclic', 'points', 'ergodicity', 'chaos', 'influence', 'the', 'driven', 'quantum', 'system', 'this', 'approach', 'of', 'the', 'schrodingerkoopman', 'quasienergies', 'can', 'be', 'applied', 'to', 'quantum', 'control', 'quantum', 'information', 'in', 'presence', 'of', 'noises', 'and', 'dynamics', 'of', 'mixed', 'classicalquantum', 'systems', 'we', 'treat', 'the', 'example', 'of', 'a', 'kicked', 'spin', 'ensemble', 'where', 'the', 'kick', 'modulation', 'is', 'governed', 'by', 'discrete', 'classical', 'flows', 'as', 'the', 'arnolds', 'cat', 'map', 'and', 'the', 'chirikov', 'standard', 'map']] | [-0.17486531231669755, 0.16855163494234576, -0.13581279964194076, 0.059455577660735476, 0.021339694550652214, -0.16091644387797868, 0.03419740733635776, 0.2794061241154911, -0.3483888922619219, -0.23137203547633997, 0.08170534902792267, -0.23677059708695328, -0.2246768649260537, 0.21018987052737415, -0.05443136198367892, 0.113158817729764, 0.04189823824176643, 0.02675803635512017, -0.059183257295429205, -0.18461986185450638, 0.3572585342741501, -0.0060917165300597535, 0.24347606170805125, -0.028421280443856195, 0.09847797925325752, 0.01918748118758139, 0.04646086214504502, 0.005352963397021116, -0.0927353846535337, 0.08787079067937952, 0.20627693238349223, 0.05809626486856772, 0.2720857334925848, -0.3823560727994983, -0.25121215151763765, 0.08603520660676814, 0.1389797103450391, 0.16244192864401502, -0.019804938774587225, -0.3516542081400251, 0.028766221672046084, -0.1849342351818473, -0.14962992805032796, -0.08090063810207639, -0.016808987630359016, 0.05638150237070225, -0.2330159312818481, 0.09809574049686183, 0.12587659556111477, 0.09895491651689806, -0.038757819523878335, 0.018022388958434787, -0.03439577882561613, 0.14767813913038924, -0.04315037379323059, -0.01687752257371243, 0.16406450242571094, -0.12520841517908296, -0.17572451228698513, 0.4137156336967434, -0.08478508829217435, -0.22863557611928642, 0.182399077650097, -0.12779574311815767, -0.0769222506885456, 0.06991362725697584, 0.1535385079807093, 0.10342523705276872, -0.13384450351850702, 0.11425578585060846, -0.027389095806587143, 0.1460175416001878, 0.010792099193771597, 0.06923695064752418, 0.20024104073581075, 0.131886379016532, 0.06081075053035963, 0.17800690296610833, -0.05341620793851765, -0.23123299522998453, -0.2681825523491667, -0.14109191666318088, -0.21996286718816566, 0.09667120663793523, -0.050347356387524585, -0.17003090005806265, 0.4331198821799094, 0.15626426815190314, 0.1779548915204819, -0.015028073561980444, 0.2663689282949732, 0.19851918556696163, -0.009118522548688059, 0.06341251130646267, 0.22279656615045643, 0.19162855100692758, 0.08499142003222172, -0.30399331012975517, -0.008130623070726624, 0.09798080666663767] |
1,802.08187 | A Logic of Strong Contact between Polytopes | We propose a new contact relation between polytopes. Intuitively, we say that
two polytopes are in strong contact if a small enough object can pass from one
of them to the other while remaining in their union. In the first half of the
paper we prove that this relation is indeed a contact relation between
polytopes, which turns out not to be the case for arbitrary regular closed in
Euclidean spaces sets. In the second half we study the universal fragments of
the logics of the resultant contact algebras. We prove that they all coincide
with the set of theorems of a standard quantifier-free formal system for
connected contact algebras, which also coincides with the universal fragments
of the logics of a variety of (classes of) contact algebras of interest.
| math.LO | we propose a new contact relation between polytopes intuitively we say that two polytopes are in strong contact if a small enough object can pass from one of them to the other while remaining in their union in the first half of the paper we prove that this relation is indeed a contact relation between polytopes which turns out not to be the case for arbitrary regular closed in euclidean spaces sets in the second half we study the universal fragments of the logics of the resultant contact algebras we prove that they all coincide with the set of theorems of a standard quantifierfree formal system for connected contact algebras which also coincides with the universal fragments of the logics of a variety of classes of contact algebras of interest | [['we', 'propose', 'a', 'new', 'contact', 'relation', 'between', 'polytopes', 'intuitively', 'we', 'say', 'that', 'two', 'polytopes', 'are', 'in', 'strong', 'contact', 'if', 'a', 'small', 'enough', 'object', 'can', 'pass', 'from', 'one', 'of', 'them', 'to', 'the', 'other', 'while', 'remaining', 'in', 'their', 'union', 'in', 'the', 'first', 'half', 'of', 'the', 'paper', 'we', 'prove', 'that', 'this', 'relation', 'is', 'indeed', 'a', 'contact', 'relation', 'between', 'polytopes', 'which', 'turns', 'out', 'not', 'to', 'be', 'the', 'case', 'for', 'arbitrary', 'regular', 'closed', 'in', 'euclidean', 'spaces', 'sets', 'in', 'the', 'second', 'half', 'we', 'study', 'the', 'universal', 'fragments', 'of', 'the', 'logics', 'of', 'the', 'resultant', 'contact', 'algebras', 'we', 'prove', 'that', 'they', 'all', 'coincide', 'with', 'the', 'set', 'of', 'theorems', 'of', 'a', 'standard', 'quantifierfree', 'formal', 'system', 'for', 'connected', 'contact', 'algebras', 'which', 'also', 'coincides', 'with', 'the', 'universal', 'fragments', 'of', 'the', 'logics', 'of', 'a', 'variety', 'of', 'classes', 'of', 'contact', 'algebras', 'of', 'interest']] | [-0.15147999887569594, 0.0869874468144889, -0.093874901232238, 0.08985653393991434, -0.0771575523325457, -0.1488153884581362, 0.05453927465087662, 0.3482899543399421, -0.330044352184408, -0.2287091982091974, 0.08010285223673026, -0.28965685887692066, -0.1394644941060016, 0.2046331160916732, -0.11356424764515116, -0.008593572998562685, 0.07212669719010592, 0.09611088793115834, -0.12489707827693425, -0.26263398144018046, 0.41346284791451093, -0.07726155722764536, 0.20321176658885984, 0.06818550969832218, 0.1131694395847332, 0.009622978657269134, 0.02133172322422839, 0.09596120302493756, -0.13832949137649847, 0.15304368239325972, 0.2721289650595281, 0.10845625584300321, 0.2290983162390498, -0.37798103554031026, -0.10796200809283898, 0.15990649456373202, 0.12322721655588025, 0.07361966098945301, 0.03199704021143799, -0.23729666954157158, 0.09972966353122431, -0.17881628803264063, -0.12092785780819562, -0.033486034434575304, 0.06003623528835865, 0.04371261160167006, -0.19064270900204205, 0.00491814872478314, 0.14902260852977633, 0.0654607933999684, -0.05920278874512475, -0.059728216583159965, -0.04822474828330227, 0.14355773941900293, -0.007322861578387137, -0.0002812504822101731, 0.06225561221273473, -0.09692838876687276, -0.12634933204031906, 0.3813345580540884, -0.006264357302839366, -0.2211575369278972, 0.18901425344117273, -0.20473759536129923, -0.17994749048151648, 0.11636556548138077, 0.10840369204704005, 0.13901971376572664, -0.13107356938461845, 0.09466835742171567, -0.10843215975194023, 0.10138901581701178, 0.10456757110256988, 0.010493578525403372, 0.22373112694431957, 0.13494799554777834, 0.07049128866682831, 0.1834675041524371, -0.007345722606987693, -0.10745909486386854, -0.36243164335878997, -0.17271421713253055, -0.11610549136799259, 0.04265560966461915, -0.11531442468359064, -0.19710530917375133, 0.3447623342096519, 0.1010213630193343, 0.21541903160082607, 0.13644646649213077, 0.2387357733427332, 0.06696483201913697, 0.11273970677553175, 0.06275462213402185, 0.22569355443120004, 0.1611178405672455, 0.023541073818117954, -0.12534832143103883, 0.03678496296589191, 0.09452609687040632] |
1,802.08188 | The spatial Lambda-Fleming-Viot process with fluctuating selection | We are interested in populations in which the fitness of different genetic
types fluctuates in time and space, driven by temporal and spatial fluctuations
in the environment. For simplicity, our population is assumed to be composed of
just two genetic types. Short bursts of selection acting in opposing directions
drive to maintain both types at intermediate frequencies, while the
fluctuations due to 'genetic drift' work to eliminate variation in the
population.
We consider first a population with no spatial structure, modelled by an
adaptation of the Lambda (or generalised) Fleming-Viot process, and derive a
stochastic differential equation as a scaling limit. This amounts to a limit
result for a Lambda-Fleming-Viot process in a rapidly fluctuating random
environment. We then extend to a population that is distributed across a
spatial continuum, which we model through a modification of the spatial
Lambda-Fleming-Viot process with selection. In this setting we show that the
scaling limit is a stochastic partial differential equation. As is usual with
spatially distributed populations, in dimensions greater than one, the 'genetic
drift' disappears in the scaling limit, but here we retain some stochasticity
due to the fluctuations in the environment, resulting in a stochastic p.d.e.
driven by a noise that is white in time but coloured in space.
We discuss the (rather limited) situations under which there is a duality
with a system of branching and annihilating particles. We also write down a
system of equations that captures the frequency of descendants of particular
subsets of the population and use this same idea of 'tracers', which we learned
from Hallatschek and Nelson (2008) and Durrett and Fan (2016), in numerical
experiments with a closely related model based on the classical Moran model.
| math.PR | we are interested in populations in which the fitness of different genetic types fluctuates in time and space driven by temporal and spatial fluctuations in the environment for simplicity our population is assumed to be composed of just two genetic types short bursts of selection acting in opposing directions drive to maintain both types at intermediate frequencies while the fluctuations due to genetic drift work to eliminate variation in the population we consider first a population with no spatial structure modelled by an adaptation of the lambda or generalised flemingviot process and derive a stochastic differential equation as a scaling limit this amounts to a limit result for a lambdaflemingviot process in a rapidly fluctuating random environment we then extend to a population that is distributed across a spatial continuum which we model through a modification of the spatial lambdaflemingviot process with selection in this setting we show that the scaling limit is a stochastic partial differential equation as is usual with spatially distributed populations in dimensions greater than one the genetic drift disappears in the scaling limit but here we retain some stochasticity due to the fluctuations in the environment resulting in a stochastic pde driven by a noise that is white in time but coloured in space we discuss the rather limited situations under which there is a duality with a system of branching and annihilating particles we also write down a system of equations that captures the frequency of descendants of particular subsets of the population and use this same idea of tracers which we learned from hallatschek and nelson 2008 and durrett and fan 2016 in numerical experiments with a closely related model based on the classical moran model | [['we', 'are', 'interested', 'in', 'populations', 'in', 'which', 'the', 'fitness', 'of', 'different', 'genetic', 'types', 'fluctuates', 'in', 'time', 'and', 'space', 'driven', 'by', 'temporal', 'and', 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1,802.08189 | Complexity of the Steiner Network Problem with Respect to the Number of
Terminals | In the Directed Steiner Network problem we are given an arc-weighted digraph
$G$, a set of terminals $T \subseteq V(G)$, and an (unweighted) directed
request graph $R$ with $V(R)=T$. Our task is to output a subgraph $G' \subseteq
G$ of the minimum cost such that there is a directed path from $s$ to $t$ in
$G'$ for all $st \in A(R)$.
It is known that the problem can be solved in time $|V(G)|^{O(|A(R)|)}$
[Feldman&Ruhl, SIAM J. Comput. 2006] and cannot be solved in time
$|V(G)|^{o(|A(R)|)}$ even if $G$ is planar, unless Exponential-Time Hypothesis
(ETH) fails [Chitnis et al., SODA 2014]. However, as this reduction (and other
reductions showing hardness of the problem) only shows that the problem cannot
be solved in time $|V(G)|^{o(|T|)}$ unless ETH fails, there is a significant
gap in the complexity with respect to $|T|$ in the exponent.
We show that Directed Steiner Network is solvable in time $f(R)\cdot
|V(G)|^{O(c_g \cdot |T|)}$, where $c_g$ is a constant depending solely on the
genus of $G$ and $f$ is a computable function. We complement this result by
showing that there is no $f(R)\cdot |V(G)|^{o(|T|^2/ \log |T|)}$ algorithm for
any function $f$ for the problem on general graphs, unless ETH fails.
| cs.DM | in the directed steiner network problem we are given an arcweighted digraph g a set of terminals t subseteq vg and an unweighted directed request graph r with vrt our task is to output a subgraph g subseteq g of the minimum cost such that there is a directed path from s to t in g for all st in ar it is known that the problem can be solved in time vgoar feldmanruhl siam j comput 2006 and cannot be solved in time vgoar even if g is planar unless exponentialtime hypothesis eth fails chitnis et al soda 2014 however as this reduction and other reductions showing hardness of the problem only shows that the problem cannot be solved in time vgot unless eth fails there is a significant gap in the complexity with respect to t in the exponent we show that directed steiner network is solvable in time frcdot vgoc_g cdot t where c_g is a constant depending solely on the genus of g and f is a computable function we complement this result by showing that there is no frcdot vgot2 log t algorithm for any function f for the problem on general graphs unless eth fails | [['in', 'the', 'directed', 'steiner', 'network', 'problem', 'we', 'are', 'given', 'an', 'arcweighted', 'digraph', 'g', 'a', 'set', 'of', 'terminals', 't', 'subseteq', 'vg', 'and', 'an', 'unweighted', 'directed', 'request', 'graph', 'r', 'with', 'vrt', 'our', 'task', 'is', 'to', 'output', 'a', 'subgraph', 'g', 'subseteq', 'g', 'of', 'the', 'minimum', 'cost', 'such', 'that', 'there', 'is', 'a', 'directed', 'path', 'from', 's', 'to', 't', 'in', 'g', 'for', 'all', 'st', 'in', 'ar', 'it', 'is', 'known', 'that', 'the', 'problem', 'can', 'be', 'solved', 'in', 'time', 'vgoar', 'feldmanruhl', 'siam', 'j', 'comput', '2006', 'and', 'can', 'not', 'be', 'solved', 'in', 'time', 'vgoar', 'even', 'if', 'g', 'is', 'planar', 'unless', 'exponentialtime', 'hypothesis', 'eth', 'fails', 'chitnis', 'et', 'al', 'soda', '2014', 'however', 'as', 'this', 'reduction', 'and', 'other', 'reductions', 'showing', 'hardness', 'of', 'the', 'problem', 'only', 'shows', 'that', 'the', 'problem', 'can', 'not', 'be', 'solved', 'in', 'time', 'vgot', 'unless', 'eth', 'fails', 'there', 'is', 'a', 'significant', 'gap', 'in', 'the', 'complexity', 'with', 'respect', 'to', 't', 'in', 'the', 'exponent', 'we', 'show', 'that', 'directed', 'steiner', 'network', 'is', 'solvable', 'in', 'time', 'frcdot', 'vgoc_g', 'cdot', 't', 'where', 'c_g', 'is', 'a', 'constant', 'depending', 'solely', 'on', 'the', 'genus', 'of', 'g', 'and', 'f', 'is', 'a', 'computable', 'function', 'we', 'complement', 'this', 'result', 'by', 'showing', 'that', 'there', 'is', 'no', 'frcdot', 'vgot2', 'log', 't', 'algorithm', 'for', 'any', 'function', 'f', 'for', 'the', 'problem', 'on', 'general', 'graphs', 'unless', 'eth', 'fails']] | [-0.1701151882416479, 0.11135594213580963, -0.04327748157911305, 0.010797634368010697, -0.08670755326044675, -0.18590925970979905, 0.06984936132516503, 0.4059725205075979, -0.30456607436895994, -0.33907263721179853, 0.0518807305482826, -0.2738385910173018, -0.1493261696293307, 0.18139542621172738, -0.1214486887409035, 0.03362158027732849, 0.0990117312536627, 0.07419107175493603, -0.001283942106319355, -0.30581378594332204, 0.23207569495138952, -0.0050994395101112006, 0.1652221702150634, 0.10671730514445583, 0.06347423197989953, 0.014167876121101116, 0.04319535734056292, 0.10481227726231182, -0.12476873682516533, -0.015493937702447667, 0.30365199182267644, 0.18059747156493253, 0.2629297765227139, -0.3721488429053786, -0.17956461557919906, 0.22110353644315608, 0.09206289135458581, 0.0204452411827116, 0.038105456524902034, -0.18792207249756998, 0.132565213984876, -0.09384903062588823, -0.05069344386879147, 0.033522385268278304, 0.168213586235504, -0.03366959436624051, -0.32761113057480323, 0.04478230107774211, 0.13936844188010858, 0.007761852041965789, 0.03541341961153457, -0.12377865242518882, -0.025852551858701986, 0.0541559028546184, -0.04735536887877748, 0.16548758018631865, 0.010701974378756914, -0.09178716964253844, -0.1528180281307813, 0.38234741864773225, -0.07501709105229469, -0.16003324253234047, 0.1362478088771896, -0.1137043653708424, -0.19511635948284553, 0.10921595363433326, 0.1016962026236437, 0.16990326784922255, -0.09460455372333905, 0.2256717705179649, -0.13705186416787393, 0.17301131718730564, 0.08800000401194855, -0.07694292638857428, 0.07621477579398507, 0.132134691164427, 0.17215179768509142, 0.11755524133302526, 0.023560985377522867, 0.023605918725964323, -0.2932504726961482, -0.1277669748943772, -0.2591865396541945, 0.0916480094581183, -0.10899996778308438, -0.144743294176187, 0.3404941880900583, 0.11377342032306463, 0.18780437855139792, 0.12147312719129064, 0.20093888475507649, 0.1553562446941325, 0.02260772123705917, 0.251414901394631, 0.14392683309914195, 0.10192195081085836, 0.022439874888298475, -0.223704939286182, 0.10223327921159793, 0.13271988179950697] |
1,802.0819 | Large and realistic models of Amorphous Silicon | Amorphous silicon (a-Si) models are analyzed for structural, electronic and
vibrational characteristics. Several models of various sizes have been
computationally fabricated for this analysis. It is shown that a recently
developed structural modeling algorithm known as force-enhanced atomic
refinement (FEAR) provides results in agreement with experimental neutron and
x-ray diffraction data while producing a total energy below conventional
schemes. We also show that a large model (500 atoms) and a complete basis is
necessary to properly describe vibrational and thermal properties. We compute
the density for a-Si, and compare with experimental results.
| cond-mat.dis-nn | amorphous silicon asi models are analyzed for structural electronic and vibrational characteristics several models of various sizes have been computationally fabricated for this analysis it is shown that a recently developed structural modeling algorithm known as forceenhanced atomic refinement fear provides results in agreement with experimental neutron and xray diffraction data while producing a total energy below conventional schemes we also show that a large model 500 atoms and a complete basis is necessary to properly describe vibrational and thermal properties we compute the density for asi and compare with experimental results | [['amorphous', 'silicon', 'asi', 'models', 'are', 'analyzed', 'for', 'structural', 'electronic', 'and', 'vibrational', 'characteristics', 'several', 'models', 'of', 'various', 'sizes', 'have', 'been', 'computationally', 'fabricated', 'for', 'this', 'analysis', 'it', 'is', 'shown', 'that', 'a', 'recently', 'developed', 'structural', 'modeling', 'algorithm', 'known', 'as', 'forceenhanced', 'atomic', 'refinement', 'fear', 'provides', 'results', 'in', 'agreement', 'with', 'experimental', 'neutron', 'and', 'xray', 'diffraction', 'data', 'while', 'producing', 'a', 'total', 'energy', 'below', 'conventional', 'schemes', 'we', 'also', 'show', 'that', 'a', 'large', 'model', '500', 'atoms', 'and', 'a', 'complete', 'basis', 'is', 'necessary', 'to', 'properly', 'describe', 'vibrational', 'and', 'thermal', 'properties', 'we', 'compute', 'the', 'density', 'for', 'asi', 'and', 'compare', 'with', 'experimental', 'results']] | [-0.015320133974335596, 0.12404263181263929, -0.09011136808504279, 0.0808659025869629, -0.018968886706036525, -0.11374251647842126, 0.03486872089586661, 0.470654869718211, -0.20218953730763642, -0.3348473628143688, 0.07580413959362636, -0.30913792918999117, -0.13846955075860023, 0.2362225147573134, -3.333234197490818e-06, 0.10679789890463535, 0.0701769310418148, -0.049124278097444185, -0.062231164817074004, -0.20794754048712183, 0.2247474143220173, 0.10656601630642519, 0.3461760372783129, 0.08814777095628144, 0.08549296786461108, -0.037773227567303475, -0.008368570608301805, 0.05905392937935316, -0.1786235215222005, 0.11659337533637881, 0.2764227024346218, 0.057177711715717075, 0.22057723553830777, -0.4759777366173464, -0.2575349841870695, 0.03771391450197201, 0.08709415031730064, 0.13134847671704386, -0.08791502076456999, -0.20254433802380176, 0.1195874916860363, -0.16622599334696533, -0.10255015047093095, -0.18646788347389673, 0.015676661614574247, 0.04003290543371075, -0.2419361823064449, 0.021661908636675574, 0.018775301276716394, 0.07579955981614497, -0.1437534864654171, -0.15376297217681184, -0.04027523529833531, 0.05522964720788238, -0.021081092988734472, -0.020982114662119484, 0.14068848036925544, -0.06329032348642884, -0.12376935045224624, 0.38966348407032725, -0.03448222059203864, -0.10896033126410547, 0.20945653622294522, -0.11090010387188458, -0.13150035536203247, 0.15045674451995272, 0.11274685605894774, 0.08579474382082021, -0.165059683383903, 0.04124703163800474, -0.04263455890359582, 0.21870802169548, 0.05238504672249022, 0.08521591375028947, 0.15661816848544302, 0.21226405583777475, -0.0014544946965403282, 0.14736178098246455, -0.12765974200402314, -0.057653703762648195, -0.2051173906292316, -0.14027969543003366, -0.17019477173184547, 0.0063426555710036185, -0.05667462445469957, -0.149754427057105, 0.3480910942685064, 0.13897804311568757, 0.1808433404990605, 0.020000852621416307, 0.31626137217844497, 0.07189821521879512, 0.06234625878789882, 0.042439005798199675, 0.24087511156532135, 0.1568245557802064, 0.08132052813799909, -0.21736382773903373, 0.07686489301600627, -0.008566380209790973] |
1,802.08191 | Phases and Stability of Non-Uniform Black Strings | We construct solutions of non-uniform black strings in dimensions from $D
\approx 9$ all the way up to $D = \infty$, and investigate their thermodynamics
and dynamical stability. Our approach employs the large-$D$ perturbative
expansion beyond the leading order, including corrections up to $1/D^4$.
Combining both analytical techniques and relatively simple numerical solution
of ODEs, we map out the ranges of parameters in which non-uniform black strings
exist in each dimension and compute their thermodynamics and quasinormal modes
with accuracy. We establish with very good precision the existence of Sorkin's
critical dimension and we prove that not only the thermodynamic stability, but
also the dynamic stability of the solutions changes at it.
| hep-th gr-qc | we construct solutions of nonuniform black strings in dimensions from d approx 9 all the way up to d infty and investigate their thermodynamics and dynamical stability our approach employs the larged perturbative expansion beyond the leading order including corrections up to 1d4 combining both analytical techniques and relatively simple numerical solution of odes we map out the ranges of parameters in which nonuniform black strings exist in each dimension and compute their thermodynamics and quasinormal modes with accuracy we establish with very good precision the existence of sorkins critical dimension and we prove that not only the thermodynamic stability but also the dynamic stability of the solutions changes at it | [['we', 'construct', 'solutions', 'of', 'nonuniform', 'black', 'strings', 'in', 'dimensions', 'from', 'd', 'approx', '9', 'all', 'the', 'way', 'up', 'to', 'd', 'infty', 'and', 'investigate', 'their', 'thermodynamics', 'and', 'dynamical', 'stability', 'our', 'approach', 'employs', 'the', 'larged', 'perturbative', 'expansion', 'beyond', 'the', 'leading', 'order', 'including', 'corrections', 'up', 'to', '1d4', 'combining', 'both', 'analytical', 'techniques', 'and', 'relatively', 'simple', 'numerical', 'solution', 'of', 'odes', 'we', 'map', 'out', 'the', 'ranges', 'of', 'parameters', 'in', 'which', 'nonuniform', 'black', 'strings', 'exist', 'in', 'each', 'dimension', 'and', 'compute', 'their', 'thermodynamics', 'and', 'quasinormal', 'modes', 'with', 'accuracy', 'we', 'establish', 'with', 'very', 'good', 'precision', 'the', 'existence', 'of', 'sorkins', 'critical', 'dimension', 'and', 'we', 'prove', 'that', 'not', 'only', 'the', 'thermodynamic', 'stability', 'but', 'also', 'the', 'dynamic', 'stability', 'of', 'the', 'solutions', 'changes', 'at', 'it']] | [-0.13286439635421712, 0.08252508944605251, -0.08821681771125342, 0.05865810170501202, -0.013271569672904842, -0.13522294369790502, 0.09236286230687354, 0.2967533659408087, -0.2357921451330185, -0.28291394774642614, 0.11867625116232179, -0.30582604042111755, -0.1106160988041141, 0.1546461052924126, -0.0024364816175924766, 0.08564157047317372, 0.007266140605851605, 0.040779144335370346, -0.10096322819129103, -0.24947895325388894, 0.29098571398975076, 0.021923573507281306, 0.25130987288178624, 0.04720487849762493, 0.09420239558728698, -0.05832711726779471, -0.004051928551078917, 0.037771149366456376, -0.22083570160684102, 0.07973775415643808, 0.2249532192022548, 0.06810897886795034, 0.1954303058283823, -0.39195025618280377, -0.17964664872144223, 0.0855450697310336, 0.16833777937131958, 0.14774530006232797, -0.01958708180458629, -0.22480730002594962, 0.12470138115338511, -0.1731758643327667, -0.19440788628852312, -0.18755629965783777, 0.030886593467748916, 0.023842582093165803, -0.24837226581315067, 0.10232547127514834, 0.0672650211855144, 0.014629087754869246, -0.09044515467584469, -0.07133267205292443, -0.006702524964353657, 0.14219657211933653, 0.08146984282375506, 0.0040818015197375875, 0.0700560018864905, -0.12064573082963827, -0.10261416943693483, 0.36331470885842637, -0.05772663766165843, -0.2111606604633601, 0.2338752328095169, -0.19989311725513692, -0.13668300037331008, 0.11527499164714738, 0.1412858278889142, 0.16903931881995402, -0.09777707243254324, 0.14065784887674995, 0.04537902938134901, 0.19205197656678186, 0.14569786480451757, 0.05632581687238705, 0.20406976768428142, 0.1207080930807032, 0.04685483510429795, 0.1310435747308237, -0.039265660212484295, -0.12078619878403507, -0.31837606847890326, -0.10272598576622906, -0.11493762079227783, 0.0632589151517767, -0.18464820031501428, -0.17312677454639663, 0.372605958701791, 0.16633301883566756, 0.1852414801817488, 0.09397823983690122, 0.24569671778092245, 0.10705332731228187, 0.016514900041157316, 0.12380598695646669, 0.27008547348301726, 0.1427867531772233, 0.10213629248224802, -0.23532464818217214, -0.028055801903745077, 0.10739109578735388] |
1,802.08192 | Large-scale limit of interface fluctuation models | We extend the weak universality of KPZ in [Hairer-Quastel] to weakly
asymmetric interface models with general growth mechanisms beyond polynomials.
A key new ingredient is a pointwise bound on correlations of trigonometric
functions of Gaussians in terms of their polynomial counterparts. This enables
us to reduce the problem of a general nonlinearity with sufficient regularity
to that of a polynomial.
| math.PR math-ph math.AP math.MP | we extend the weak universality of kpz in hairerquastel to weakly asymmetric interface models with general growth mechanisms beyond polynomials a key new ingredient is a pointwise bound on correlations of trigonometric functions of gaussians in terms of their polynomial counterparts this enables us to reduce the problem of a general nonlinearity with sufficient regularity to that of a polynomial | [['we', 'extend', 'the', 'weak', 'universality', 'of', 'kpz', 'in', 'hairerquastel', 'to', 'weakly', 'asymmetric', 'interface', 'models', 'with', 'general', 'growth', 'mechanisms', 'beyond', 'polynomials', 'a', 'key', 'new', 'ingredient', 'is', 'a', 'pointwise', 'bound', 'on', 'correlations', 'of', 'trigonometric', 'functions', 'of', 'gaussians', 'in', 'terms', 'of', 'their', 'polynomial', 'counterparts', 'this', 'enables', 'us', 'to', 'reduce', 'the', 'problem', 'of', 'a', 'general', 'nonlinearity', 'with', 'sufficient', 'regularity', 'to', 'that', 'of', 'a', 'polynomial']] | [-0.11484818337327343, 0.045277257292073665, -0.10394213160981376, 0.1000539220601194, -0.11184614135931104, -0.15768427018202463, 0.03716702652716283, 0.28273630667067434, -0.29199133813381195, -0.21924068671414407, 0.0645964543564024, -0.21105295552288073, -0.14207734044451834, 0.20951510012402372, -0.06463256816111379, 0.10805740980115736, -0.0033230694421267104, -0.03928888513375137, -0.11584615741730116, -0.28342258008354804, 0.3583314232843912, 0.04420900636873508, 0.22882760631836066, 0.08002487950468973, 0.09550629996584128, -0.017950399920849475, 0.0047591703004693075, -0.04565116652619031, -0.1690792973490947, 0.1833511486282509, 0.2147257940287399, 0.08040660183276918, 0.28860565574871283, -0.3961366976342969, -0.18422253540385577, 0.16546082572411683, 0.1580533307969128, 0.11818463871476509, -0.00510331768526743, -0.2510605875276408, 0.06966914116578588, -0.12010864220891085, -0.22435378574497872, -0.05546779447566655, 0.009932176707217754, 0.09708013809069012, -0.3334104974706799, 0.13283834760314076, 0.1312276121797198, 0.04133087529216783, -0.0318275133179406, -0.045235820915707846, 0.05067271972075105, 0.07465049056178433, -0.003534105177218947, 0.015809200120048, 0.02189460037654992, -0.1704481752171039, -0.12293572433419146, 0.37109771997557356, -0.09477508124911178, -0.2677797764634429, 0.23868232747634588, -0.19735502744571037, -0.1573393535879204, 0.11639382222951469, 0.21697456643016913, 0.11997335629884974, -0.14083804183844792, 0.11774865682315776, -0.07093618699680951, 0.15398708961398924, 0.03835502966165037, 0.06950250542051774, 0.12968356386458468, 0.10861158121566651, 0.12615509828457894, 0.20210069907292472, 0.01906213886104524, -0.10643179986183926, -0.3424983671471729, -0.17011579176336053, -0.15896047056668391, 0.042947740893874126, -0.14393622417918453, -0.21943001629847844, 0.4358344340728501, 0.14354514602129742, 0.18946675544652014, 0.13279721764374083, 0.20341639890004012, 0.14243945757507237, 0.08341106491052877, 0.04143872991267402, 0.20676809932910284, 0.19587585825662493, 0.08477982658482457, -0.15631983723191512, 0.10395479529022665, 0.11661353562090357] |
1,802.08193 | Localization theory for derivators | We outline the theory of reflections for prederivators, derivators and stable
derivators. In order to parallel the classical theory valid for categories, we
outline how reflections can be equivalently described as categories of
fractions, reflective factorization systems, and categories of algebras for
idempotent monads. This is a further development of the theory of monads and
factorization systems for derivators.
| math.CT | we outline the theory of reflections for prederivators derivators and stable derivators in order to parallel the classical theory valid for categories we outline how reflections can be equivalently described as categories of fractions reflective factorization systems and categories of algebras for idempotent monads this is a further development of the theory of monads and factorization systems for derivators | [['we', 'outline', 'the', 'theory', 'of', 'reflections', 'for', 'prederivators', 'derivators', 'and', 'stable', 'derivators', 'in', 'order', 'to', 'parallel', 'the', 'classical', 'theory', 'valid', 'for', 'categories', 'we', 'outline', 'how', 'reflections', 'can', 'be', 'equivalently', 'described', 'as', 'categories', 'of', 'fractions', 'reflective', 'factorization', 'systems', 'and', 'categories', 'of', 'algebras', 'for', 'idempotent', 'monads', 'this', 'is', 'a', 'further', 'development', 'of', 'the', 'theory', 'of', 'monads', 'and', 'factorization', 'systems', 'for', 'derivators']] | [-0.12933230205139112, 0.09313513395392288, -0.11610180639930195, 0.16902184467447007, -0.05132884765833111, -0.11525676540746274, 0.008991732185122446, 0.39254190996920657, -0.38845947799983166, -0.1941789519673182, 0.09767010560164512, -0.1851832944331533, -0.13850047344626007, 0.16154571676279528, -0.1721862506721232, -0.04707499405653295, 0.05134954688660169, 0.03677280108302326, -0.10448898652852592, -0.2512235474157131, 0.41323252365592933, -0.008780226083788074, 0.23416699936329308, 0.0535559436539188, 0.06558021159558478, 0.058020521657762385, 0.0017189130629018201, 0.046814449194629314, -0.09789484333625789, 0.18347844352424778, 0.4049171874204935, 0.1156971272854608, 0.17761590102119212, -0.42515574411441714, -0.07564496967183837, 0.038625837508904734, 0.11210654821183721, 0.1040313311505242, -0.007807612134996107, -0.3175975171438718, 0.12518396640543716, -0.2781514942851233, -0.0995539787809475, -0.15552761967656975, 0.0858918338939074, 0.017847744890062484, -0.26337194079691073, -0.016316198554458254, 0.12563709097014644, 0.09599425965699099, -0.0925075290764098, -0.08399876049261983, 0.006031087078785492, 0.09822447087331596, -0.015112743653767443, -0.07022346631166036, 0.15437651300897537, -0.1490344390296772, -0.21252397217361604, 0.40153301096821237, -0.007774245714121577, -0.18582077107344896, 0.1779641455386655, -0.08034815383538352, -0.13464319257665489, 0.09560175176899312, 0.10320712240823245, 0.14841379796675705, -0.06926911310056004, 0.16366539972598004, -0.07738191355019808, 0.08622565701351327, 0.11595334597247636, 0.04206913191888292, 0.20492616930376675, 0.14839640341825405, 0.030934244062814673, 0.1304529450687785, 0.0413432947470475, -0.0871902076622187, -0.3728998794390078, -0.2002109293273445, 0.034212936252608135, 0.07087593785313479, -0.04057308546809077, -0.2032113049368737, 0.34379945660672956, 0.17331742733160538, 0.09890522725753866, 0.12317272805277321, 0.24217287214251898, 0.08367545894639156, 0.060347428340149126, -0.039153281859737835, 0.15427651265793937, 0.27981711791481, 0.027592029288348, -0.0561040789599262, -0.03739018180265517, 0.17076702010265346] |
1,802.08194 | Seeing the forest for the trees? An investigation of network knowledge | This paper assesses the empirical content of one of the most prevalent
assumptions in the economics of networks literature, namely the assumption that
decision makers have full knowledge about the networks they interact on. Using
network data from 75 villages, we ask 4,554 individuals to assess whether five
randomly chosen pairs of households in their village are linked through
financial, social, and informational relationships. We find that network
knowledge is low and highly localized, declining steeply with the pair's
network distance to the respondent. 46% of respondents are not even able to
offer a guess about the status of a potential link between a given pair of
individuals. Even when willing to offer a guess, respondents can only correctly
identify the links 37% of the time. We also find that a one-step increase in
the social distance to the pair corresponds to a 10pp increase in the
probability of misidentifying the link. We then investigate the theoretical
implications of this assumption by showing that the predictions of various
models change substantially if agents behave under the more realistic
assumption of incomplete knowledge about the network. Taken together, our
results suggest that the assumption of full network knowledge (i) may serve as
a poor approximation to the real world and (ii) is not innocuous: allowing for
incomplete network knowledge may have first-order implications for a range of
qualitative and quantitative results in various contexts.
| physics.soc-ph stat.AP stat.OT | this paper assesses the empirical content of one of the most prevalent assumptions in the economics of networks literature namely the assumption that decision makers have full knowledge about the networks they interact on using network data from 75 villages we ask 4554 individuals to assess whether five randomly chosen pairs of households in their village are linked through financial social and informational relationships we find that network knowledge is low and highly localized declining steeply with the pairs network distance to the respondent 46 of respondents are not even able to offer a guess about the status of a potential link between a given pair of individuals even when willing to offer a guess respondents can only correctly identify the links 37 of the time we also find that a onestep increase in the social distance to the pair corresponds to a 10pp increase in the probability of misidentifying the link we then investigate the theoretical implications of this assumption by showing that the predictions of various models change substantially if agents behave under the more realistic assumption of incomplete knowledge about the network taken together our results suggest that the assumption of full network knowledge i may serve as a poor approximation to the real world and ii is not innocuous allowing for incomplete network knowledge may have firstorder implications for a range of qualitative and quantitative results in various contexts | [['this', 'paper', 'assesses', 'the', 'empirical', 'content', 'of', 'one', 'of', 'the', 'most', 'prevalent', 'assumptions', 'in', 'the', 'economics', 'of', 'networks', 'literature', 'namely', 'the', 'assumption', 'that', 'decision', 'makers', 'have', 'full', 'knowledge', 'about', 'the', 'networks', 'they', 'interact', 'on', 'using', 'network', 'data', 'from', '75', 'villages', 'we', 'ask', '4554', 'individuals', 'to', 'assess', 'whether', 'five', 'randomly', 'chosen', 'pairs', 'of', 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1,802.08195 | Adversarial Examples that Fool both Computer Vision and Time-Limited
Humans | Machine learning models are vulnerable to adversarial examples: small changes
to images can cause computer vision models to make mistakes such as identifying
a school bus as an ostrich. However, it is still an open question whether
humans are prone to similar mistakes. Here, we address this question by
leveraging recent techniques that transfer adversarial examples from computer
vision models with known parameters and architecture to other models with
unknown parameters and architecture, and by matching the initial processing of
the human visual system. We find that adversarial examples that strongly
transfer across computer vision models influence the classifications made by
time-limited human observers.
| cs.LG cs.CV q-bio.NC stat.ML | machine learning models are vulnerable to adversarial examples small changes to images can cause computer vision models to make mistakes such as identifying a school bus as an ostrich however it is still an open question whether humans are prone to similar mistakes here we address this question by leveraging recent techniques that transfer adversarial examples from computer vision models with known parameters and architecture to other models with unknown parameters and architecture and by matching the initial processing of the human visual system we find that adversarial examples that strongly transfer across computer vision models influence the classifications made by timelimited human observers | [['machine', 'learning', 'models', 'are', 'vulnerable', 'to', 'adversarial', 'examples', 'small', 'changes', 'to', 'images', 'can', 'cause', 'computer', 'vision', 'models', 'to', 'make', 'mistakes', 'such', 'as', 'identifying', 'a', 'school', 'bus', 'as', 'an', 'ostrich', 'however', 'it', 'is', 'still', 'an', 'open', 'question', 'whether', 'humans', 'are', 'prone', 'to', 'similar', 'mistakes', 'here', 'we', 'address', 'this', 'question', 'by', 'leveraging', 'recent', 'techniques', 'that', 'transfer', 'adversarial', 'examples', 'from', 'computer', 'vision', 'models', 'with', 'known', 'parameters', 'and', 'architecture', 'to', 'other', 'models', 'with', 'unknown', 'parameters', 'and', 'architecture', 'and', 'by', 'matching', 'the', 'initial', 'processing', 'of', 'the', 'human', 'visual', 'system', 'we', 'find', 'that', 'adversarial', 'examples', 'that', 'strongly', 'transfer', 'across', 'computer', 'vision', 'models', 'influence', 'the', 'classifications', 'made', 'by', 'timelimited', 'human', 'observers']] | [-0.04273305225741261, 0.06616957468017623, -0.0253849868895486, 0.08751503207727532, -0.11761264734937307, -0.2451564303102294, -0.006620742687328647, 0.4514111237457165, -0.307695987706001, -0.4222788167042801, 0.10070880549028516, -0.2849105248729197, -0.28432550964554626, 0.23382002051668957, -0.2349452573734407, 0.11316144415356505, 0.15783410125788158, 0.02224373662633857, -0.020567524871484447, -0.3168058075870459, 0.3074585253713079, 0.05892823743096624, 0.2632834757096134, -0.004811252006150495, 0.06962116976949172, -0.07956797235797589, -0.004250817757565528, -0.023902374351074777, -0.08413874714229817, 0.1456936312450545, 0.36274044662426463, 0.21680860393322432, 0.3522050832935537, -0.4309511446716407, -0.2588345405842679, 0.10080689047306525, 0.12053365997585039, 0.15422785413200193, -0.06543812506760542, -0.34443281235983775, 0.08947332489277379, -0.16444410943390372, -0.02207109132835355, -0.12207484397983465, 0.04516965773319288, -0.025227277106471144, -0.23138012569576788, -0.009456265887890298, 0.09509654444319984, 0.11279616789229643, -0.03599634773294943, -0.052282353472457126, 0.016282216927860506, 0.20988821182310438, 0.0680652866341496, 0.050023909994007014, 0.19021614339166823, -0.2533144883177906, -0.1901186264361828, 0.35169483200073814, 0.022423765579543006, -0.21296819804522854, 0.2639592552306847, 0.020896908766679607, -0.13542067335220054, 0.03348102812798551, 0.22722578551978445, 0.08671571316573626, -0.1647625011123287, 0.016733631841466725, -0.005323622429456849, 0.19981445317814808, 0.03743064328311728, -0.04469559019735943, 0.22714547305188787, 0.1552036574979026, -0.017920302800261058, 0.11634290958094286, -0.035022229000997655, -0.07499039019099794, -0.196049506471564, -0.021449006126763728, -0.1683150032768026, 0.024008556036278605, -0.02113919153033259, -0.1611129942153079, 0.3487701559206471, 0.2817619048873894, 0.2062591888422433, 0.04765948108951516, 0.36688518274100856, 0.007721760567689601, 0.0993415389675647, 0.12130105146654667, 0.18788966671406973, 0.025725230778334662, 0.12186366067124674, -0.14922694758122537, 0.11743757931645422, -0.007772220983707274] |
1,802.08196 | The role of canting and depleted-triplet minima in superconducting spin
valve structures | The trilayer and pentalayer spin valve structures are revisited to determine
the behavior of pair correlations and Josephson current when the magnetic
layers are canted at arbitrary angle. The two systems display markedly
different behaviors in the center magnetic layer. While the trilayer generates
a triplet component that is weakly affected by canting, the pentalayer tunes in
singlet pair correlations depending heavily on canting. We also show that a
minimum with depleted $m=\pm1$ triplet components, rather than a $0-\pi$
transition, may be observed in the current profile $I_c(d_F)$ of a trilayer
spin valve. The depleted-triplet minimum (DTM) is directly attributable to a
decrease of $m=\pm1$ triplet correlations with increased thickness of the
central ferromagnet, accompanied by a hidden, simultaneous sign change of the
Gor'kov functions contributed from the left and right superconductors. We
introduce a toy model for superconducting-magnetic proximity systems to better
illuminate the behavior of individual components of the Gor'kov function and
compare with a full numerical calculation.
| cond-mat.supr-con | the trilayer and pentalayer spin valve structures are revisited to determine the behavior of pair correlations and josephson current when the magnetic layers are canted at arbitrary angle the two systems display markedly different behaviors in the center magnetic layer while the trilayer generates a triplet component that is weakly affected by canting the pentalayer tunes in singlet pair correlations depending heavily on canting we also show that a minimum with depleted mpm1 triplet components rather than a 0pi transition may be observed in the current profile i_cd_f of a trilayer spin valve the depletedtriplet minimum dtm is directly attributable to a decrease of mpm1 triplet correlations with increased thickness of the central ferromagnet accompanied by a hidden simultaneous sign change of the gorkov functions contributed from the left and right superconductors we introduce a toy model for superconductingmagnetic proximity systems to better illuminate the behavior of individual components of the gorkov function and compare with a full numerical calculation | [['the', 'trilayer', 'and', 'pentalayer', 'spin', 'valve', 'structures', 'are', 'revisited', 'to', 'determine', 'the', 'behavior', 'of', 'pair', 'correlations', 'and', 'josephson', 'current', 'when', 'the', 'magnetic', 'layers', 'are', 'canted', 'at', 'arbitrary', 'angle', 'the', 'two', 'systems', 'display', 'markedly', 'different', 'behaviors', 'in', 'the', 'center', 'magnetic', 'layer', 'while', 'the', 'trilayer', 'generates', 'a', 'triplet', 'component', 'that', 'is', 'weakly', 'affected', 'by', 'canting', 'the', 'pentalayer', 'tunes', 'in', 'singlet', 'pair', 'correlations', 'depending', 'heavily', 'on', 'canting', 'we', 'also', 'show', 'that', 'a', 'minimum', 'with', 'depleted', 'mpm1', 'triplet', 'components', 'rather', 'than', 'a', '0pi', 'transition', 'may', 'be', 'observed', 'in', 'the', 'current', 'profile', 'i_cd_f', 'of', 'a', 'trilayer', 'spin', 'valve', 'the', 'depletedtriplet', 'minimum', 'dtm', 'is', 'directly', 'attributable', 'to', 'a', 'decrease', 'of', 'mpm1', 'triplet', 'correlations', 'with', 'increased', 'thickness', 'of', 'the', 'central', 'ferromagnet', 'accompanied', 'by', 'a', 'hidden', 'simultaneous', 'sign', 'change', 'of', 'the', 'gorkov', 'functions', 'contributed', 'from', 'the', 'left', 'and', 'right', 'superconductors', 'we', 'introduce', 'a', 'toy', 'model', 'for', 'superconductingmagnetic', 'proximity', 'systems', 'to', 'better', 'illuminate', 'the', 'behavior', 'of', 'individual', 'components', 'of', 'the', 'gorkov', 'function', 'and', 'compare', 'with', 'a', 'full', 'numerical', 'calculation']] | [-0.17552099593832524, 0.1783382597400017, -0.022306874102641698, 0.05627679425922423, -0.056293014366226864, -0.17169119658160814, 0.024484069239866884, 0.37939462382523226, -0.2656089412553171, -0.2962277135045468, 0.0020962672115044222, -0.3388158683724041, -0.09120187384984162, 0.14394318655021252, 0.04440039179140121, -0.03793278353029414, -0.00962555828751831, 0.0031122057227111317, -0.12757531289067237, -0.16882951327016035, 0.32570511356727044, -0.020547555329254532, 0.31507372225434344, 0.05603300826181953, 0.05603789927178546, 0.008491338077413885, 0.09359268532753509, 0.022228189587852436, -0.0855158367287257, 0.05962509659997223, 0.19434761088871974, -0.05695015057933198, 0.17993408831645427, -0.4427550952598641, -0.16112287776084924, 0.04048361244929742, 0.15348208518227255, 0.10115347115199164, -0.018506525429201465, -0.28525572613211747, 0.07904427598342535, -0.17240805662667402, -0.11113365318278393, -0.03984418637531845, -0.0025767238230055456, 0.0064845267735580804, -0.2860182966238265, 0.11126022070150415, 0.07166847777225024, 0.09210706261558388, -0.04688540993765279, -0.14043643003362055, -0.11385700755599368, 0.05979682964252903, 0.04768134021388862, 0.06944119138643146, 0.17533718649433525, -0.15861682464734098, -0.1196163457603182, 0.2796775261080187, -0.0691082012325509, -0.14598547955061297, 0.14362047744407966, -0.18349097465766193, -0.03602662248259905, 0.1261266832891262, 0.09966411875248474, 0.10208930149364957, -0.12845926749996348, 0.016854039721980785, -0.018669494340797486, 0.20231855471465218, 0.009002805955684449, 0.05339153627039794, 0.2733948637482333, 0.17246330966082507, 0.051504562501324035, 0.15567993262378924, -0.12441369079354019, -0.08495816924090532, -0.22527449488745932, -0.12955430817283406, -0.1640904542939926, 0.03169633584736944, -0.052770585424408226, -0.17978054516995914, 0.4538154048915905, 0.16909133282540179, 0.230519497083335, -0.04185173989868947, 0.2596548456857806, 0.1276583523796046, 0.11049886884851547, 0.029313197182609312, 0.23934047148692644, 0.16001152310113695, 0.097714728488634, -0.2992816110527662, 0.13586675920641592, -0.006595675535853716] |
1,802.08197 | Chaos in Dirac electron optics: Emergence of a relativistic quantum
chimera | We uncover a remarkable quantum scattering phenomenon in two-dimensional
Dirac material systems where the manifestations of both classically integrable
and chaotic dynamics emerge simultaneously and are electrically controllable.
The distinct relativistic quantum fingerprints associated with different
electron spin states are due to a physical mechanism analogous to chiroptical
effect in the presence of degeneracy breaking. The phenomenon mimics a chimera
state in classical complex dynamical systems but here in a relativistic quantum
setting - henceforth the term "Dirac quantum chimera," associated with which
are physical phenomena with potentially significant applications such as
enhancement of spin polarization, unusual coexisting quasibound states for
distinct spin configurations, and spin selective caustics. Experimental
observations of these phenomena are possible through, e.g., optical
realizations of ballistic Dirac fermion systems.
| quant-ph cond-mat.mes-hall nlin.CD | we uncover a remarkable quantum scattering phenomenon in twodimensional dirac material systems where the manifestations of both classically integrable and chaotic dynamics emerge simultaneously and are electrically controllable the distinct relativistic quantum fingerprints associated with different electron spin states are due to a physical mechanism analogous to chiroptical effect in the presence of degeneracy breaking the phenomenon mimics a chimera state in classical complex dynamical systems but here in a relativistic quantum setting henceforth the term dirac quantum chimera associated with which are physical phenomena with potentially significant applications such as enhancement of spin polarization unusual coexisting quasibound states for distinct spin configurations and spin selective caustics experimental observations of these phenomena are possible through eg optical realizations of ballistic dirac fermion systems | [['we', 'uncover', 'a', 'remarkable', 'quantum', 'scattering', 'phenomenon', 'in', 'twodimensional', 'dirac', 'material', 'systems', 'where', 'the', 'manifestations', 'of', 'both', 'classically', 'integrable', 'and', 'chaotic', 'dynamics', 'emerge', 'simultaneously', 'and', 'are', 'electrically', 'controllable', 'the', 'distinct', 'relativistic', 'quantum', 'fingerprints', 'associated', 'with', 'different', 'electron', 'spin', 'states', 'are', 'due', 'to', 'a', 'physical', 'mechanism', 'analogous', 'to', 'chiroptical', 'effect', 'in', 'the', 'presence', 'of', 'degeneracy', 'breaking', 'the', 'phenomenon', 'mimics', 'a', 'chimera', 'state', 'in', 'classical', 'complex', 'dynamical', 'systems', 'but', 'here', 'in', 'a', 'relativistic', 'quantum', 'setting', 'henceforth', 'the', 'term', 'dirac', 'quantum', 'chimera', 'associated', 'with', 'which', 'are', 'physical', 'phenomena', 'with', 'potentially', 'significant', 'applications', 'such', 'as', 'enhancement', 'of', 'spin', 'polarization', 'unusual', 'coexisting', 'quasibound', 'states', 'for', 'distinct', 'spin', 'configurations', 'and', 'spin', 'selective', 'caustics', 'experimental', 'observations', 'of', 'these', 'phenomena', 'are', 'possible', 'through', 'eg', 'optical', 'realizations', 'of', 'ballistic', 'dirac', 'fermion', 'systems']] | [-0.2211637688456179, 0.28052449523948314, -0.059326338905432235, 0.093543847174785, -0.05473717222391529, -0.20770787051405637, 0.00479707089669215, 0.3276392616922172, -0.278022478130169, -0.2799391745158085, 0.017148664006319776, -0.2876145184282365, -0.2379545553367797, 0.18759942654807998, 0.031827472922642056, 0.0797564049433099, 0.0033436748781241477, -0.030213442774928684, -0.06757985191785057, -0.12612731251638473, 0.3376582689068424, -0.0178530025120817, 0.26074008541787425, 0.03451087835010111, 0.08855876670128143, -0.020360624292729106, 0.0936152511882043, 0.0022190839763942772, -0.07141939038789369, 0.022818634399152323, 0.26102024702188686, -0.04131046067393286, 0.17147438147112848, -0.44876534366465315, -0.26842876934120813, 0.06415686671569096, 0.1596696870007535, 0.21003887341528132, -0.08484640820481913, -0.337662321189797, 0.0017785709805604889, -0.15942129250085815, -0.18788130080130527, -0.10125219469465982, 0.004704797625299391, -0.02767955328951158, -0.20239800884865405, 0.13098169396143045, 0.06150338807161254, 0.05750842904766673, -0.05751649705064672, -0.04148212341947587, -0.05258678046918315, 0.07063609654295856, 0.0008300145391405113, -0.042857491013752975, 0.13387007739894638, -0.15503282802807908, -0.2343306893433588, 0.40433645057226947, -0.01145408183196181, -0.16500761805786524, 0.25680973548517844, -0.16330664632917663, -0.10584341166768133, 0.13963661749461076, 0.16247817463567102, 0.06655343584583814, -0.11091651383227086, 0.05419453649783537, -0.03912353546669086, 0.08335065454759491, 0.03411543727057373, 0.21707499218438336, 0.3256359222549491, 0.12578135997632411, 0.017410184453597398, 0.12130142913721227, -0.08582967955986326, -0.2009788867435418, -0.24567767405291882, -0.13116782739932642, -0.17724092897572896, 0.11764509032472847, -0.04901804790486169, -0.18192651507073665, 0.43640023469924927, 0.12931625191567134, 0.190054571661129, -0.10871658459536701, 0.23567064690055342, 0.1009720110332563, 0.050350450691047724, 0.014533398115469855, 0.23981411332913818, 0.1719208241069341, 0.08736444898025413, -0.3036598935799022, 0.02367405620653455, -0.027949694968093703] |
1,802.08198 | What stellar orbit is needed to measure the spin of the Galactic center black hole from astrometric data? | Astrometric and spectroscopic monitoring of individual stars orbiting the supermassive black hole in the Galactic Center offer a promising way to detect general relativistic effects. While low-order effects are expected to be detected following the periastron passage of S2 in Spring 2018, detecting higher-order effects due to black hole spin will require the discovery of closer stars. In this paper, we set out to determine the requirements such a star would have to satisfy to allow the detection of black hole spin. We focus on the instrument GRAVITY, which saw first light in 2016 and which is expected to achieve astrometric accuracies $10-100 \mu$as. For an observing campaign with duration $T$ years, $N_{obs}$ total observations, astrometric precision $\sigma_x$ and normalized black hole spin $\chi$, we find that $a_{orb}(1-e^2)^{3/4} \lesssim 300 R_S \sqrt{\frac{T}{4 \text{years}}} \left(\frac{N_{obs}}{120}\right)^{0.25} \sqrt{\frac{10 \mu as}{\sigma_x}} \sqrt{\frac{\chi}{0.9}}$ is needed. For $\chi=0.9$ and a potential observing campaign with $\sigma_x = 10 \mu$as, 30 observations/year and duration 4-10 years, we expect $\sim 0.1$ star with $K<19$ satisfying this constraint based on the current knowledge about the stellar population in the central 1". We also propose a method through which GRAVITY could potentially measure radial velocities with precision $\sim 50$ km/s. If the astrometric precision can be maintained, adding radial velocity information increases the expected number of stars by roughly a factor of two. While we focus on GRAVITY, the results can also be scaled to parameters relevant for future extremely large telescopes. | astro-ph.GA gr-qc | astrometric and spectroscopic monitoring of individual stars orbiting the supermassive black hole in the galactic center offer a promising way to detect general relativistic effects while loworder effects are expected to be detected following the periastron passage of s2 in spring 2018 detecting higherorder effects due to black hole spin will require the discovery of closer stars in this paper we set out to determine the requirements such a star would have to satisfy to allow the detection of black hole spin we focus on the instrument gravity which saw first light in 2016 and which is expected to achieve astrometric accuracies 10100 muas for an observing campaign with duration t years n_obs total observations astrometric precision sigma_x and normalized black hole spin chi we find that a_orb1e234 lesssim 300 r_s sqrtfract4 textyears leftfracn_obs120right025 sqrtfrac10 mu assigma_x sqrtfracchi09 is needed for chi09 and a potential observing campaign with sigma_x 10 muas 30 observationsyear and duration 410 years we expect sim 01 star with k19 satisfying this constraint based on the current knowledge about the stellar population in the central 1 we also propose a method through which gravity could potentially measure radial velocities with precision sim 50 kms if the astrometric precision can be maintained adding radial velocity information increases the expected number of stars by roughly a factor of two while we focus on gravity the results can also be scaled to parameters relevant for future extremely large telescopes | [['astrometric', 'and', 'spectroscopic', 'monitoring', 'of', 'individual', 'stars', 'orbiting', 'the', 'supermassive', 'black', 'hole', 'in', 'the', 'galactic', 'center', 'offer', 'a', 'promising', 'way', 'to', 'detect', 'general', 'relativistic', 'effects', 'while', 'loworder', 'effects', 'are', 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1,802.08199 | Effects of Grain Boundary Disorder on Yield Strength | It was recently reported that segregation of Zr to grain boundaries (GB) in
nanocrystalline Cu can lead to the formation of disordered intergranular films
[1,2]. In this study we employ atomistic computer simulations to study how the
formation of these films affects the dislocation nucleation from the GBs. We
found that full disorder of the grain boundary structure leads to the
suppression of dislocation emission and significant increase of the yield
stress. Depending on the solute concentration and heat-treatment, however, a
partial disorder may also occur and this aids dislocation nucleation rather
than suppressing it, resulting in elimination of the strengthening effect.
| cond-mat.mtrl-sci | it was recently reported that segregation of zr to grain boundaries gb in nanocrystalline cu can lead to the formation of disordered intergranular films 12 in this study we employ atomistic computer simulations to study how the formation of these films affects the dislocation nucleation from the gbs we found that full disorder of the grain boundary structure leads to the suppression of dislocation emission and significant increase of the yield stress depending on the solute concentration and heattreatment however a partial disorder may also occur and this aids dislocation nucleation rather than suppressing it resulting in elimination of the strengthening effect | [['it', 'was', 'recently', 'reported', 'that', 'segregation', 'of', 'zr', 'to', 'grain', 'boundaries', 'gb', 'in', 'nanocrystalline', 'cu', 'can', 'lead', 'to', 'the', 'formation', 'of', 'disordered', 'intergranular', 'films', '12', 'in', 'this', 'study', 'we', 'employ', 'atomistic', 'computer', 'simulations', 'to', 'study', 'how', 'the', 'formation', 'of', 'these', 'films', 'affects', 'the', 'dislocation', 'nucleation', 'from', 'the', 'gbs', 'we', 'found', 'that', 'full', 'disorder', 'of', 'the', 'grain', 'boundary', 'structure', 'leads', 'to', 'the', 'suppression', 'of', 'dislocation', 'emission', 'and', 'significant', 'increase', 'of', 'the', 'yield', 'stress', 'depending', 'on', 'the', 'solute', 'concentration', 'and', 'heattreatment', 'however', 'a', 'partial', 'disorder', 'may', 'also', 'occur', 'and', 'this', 'aids', 'dislocation', 'nucleation', 'rather', 'than', 'suppressing', 'it', 'resulting', 'in', 'elimination', 'of', 'the', 'strengthening', 'effect']] | [-0.09064550090617701, 0.17729200565201395, -0.0715917409329182, 0.013341347922059689, -0.024852176635142637, -0.05158800862309541, 0.07198260720549882, 0.3947130258231625, -0.23973844950909123, -0.3118115987117384, 0.032010345559398294, -0.2586889186800987, -0.16206241341983424, 0.10093975491712198, -0.018855357378282967, -0.013432434595683041, 0.013862163428783271, -0.07544613289007661, -0.06878500913415908, -0.28801928525881876, 0.28068838049383726, 0.0794266955013953, 0.3413173145084989, 0.14944220183179804, -0.022667948791172867, -0.03495297468194336, 0.019030990469379023, 0.05712594647946603, -0.22405891890672386, 0.07814906503293007, 0.20900453641718508, -0.05811648856501515, 0.19059547745650085, -0.5282388283122404, -0.26692197522075445, 0.04762783159237063, 0.16060626434673572, 0.18036106388614165, -0.06110622120482445, -0.22108607507064282, 0.10930260076922566, -0.09564795904089789, -0.0970064270882622, 0.0082669331436502, 0.020163071419422824, -0.0041010255535023615, -0.23976643571422399, 0.17134745924604608, 0.10013253951568485, 0.07936503890874412, -0.1201585031059735, -0.0779410501458116, -0.1545859568286687, 0.05412971512665607, 0.0486694956768998, 0.023148446098453932, 0.24937656073484057, -0.11668269790471623, -0.08453317586327995, 0.3968944435610491, 0.018144992909904376, -0.105105196417985, 0.21750041082793592, -0.19288088467574732, -0.08928832895232036, 0.22829936559690966, 0.15564848162124262, 0.07145793449736255, -0.09929678147469245, 0.004112584094685849, 0.03987021903238058, 0.1839476784545125, 0.12793068592345305, -0.003604830233562811, 0.1742420577097173, 0.22898122033003865, 0.02780281261577472, 0.17130036855700845, -0.15901725073618925, -0.09673157880338383, -0.22682624054597875, -0.20169235064702876, -0.15130039338278128, 0.06848321110694944, -0.14211634666229228, -0.22876588694349514, 0.3037555158850463, 0.19186856298520247, 0.15475718006856887, -0.03605105789999167, 0.1385269055106476, 0.063189762311773, 0.10902910335354653, 0.006227662047261701, 0.23412933016730034, 0.16000748935210354, 0.13492134697370084, -0.32409917152094125, 0.16857497866480045, -0.013572598917081076] |
1,802.082 | Multiparametric Deep Learning Tissue Signatures for a Radiological
Biomarker of Breast Cancer: Preliminary Results | A new paradigm is beginning to emerge in Radiology with the advent of
increased computational capabilities and algorithms. This has led to the
ability of real time learning by computer systems of different lesion types to
help the radiologist in defining disease. For example, using a deep learning
network, we developed and tested a multiparametric deep learning (MPDL) network
for segmentation and classification using multiparametric magnetic resonance
imaging (mpMRI) radiological images. The MPDL network was constructed from
stacked sparse autoencoders with inputs from mpMRI. Evaluation of MPDL
consisted of cross-validation, sensitivity, and specificity. Dice similarity
between MPDL and post-DCE lesions were evaluated. We demonstrate high
sensitivity and specificity for differentiation of malignant from benign
lesions of 90% and 85% respectively with an AUC of 0.93. The Integrated MPDL
method accurately segmented and classified different breast tissue from
multiparametric breast MRI using deep leaning tissue signatures.
| physics.med-ph cs.AI cs.CV q-bio.QM | a new paradigm is beginning to emerge in radiology with the advent of increased computational capabilities and algorithms this has led to the ability of real time learning by computer systems of different lesion types to help the radiologist in defining disease for example using a deep learning network we developed and tested a multiparametric deep learning mpdl network for segmentation and classification using multiparametric magnetic resonance imaging mpmri radiological images the mpdl network was constructed from stacked sparse autoencoders with inputs from mpmri evaluation of mpdl consisted of crossvalidation sensitivity and specificity dice similarity between mpdl and postdce lesions were evaluated we demonstrate high sensitivity and specificity for differentiation of malignant from benign lesions of 90 and 85 respectively with an auc of 093 the integrated mpdl method accurately segmented and classified different breast tissue from multiparametric breast mri using deep leaning tissue signatures | [['a', 'new', 'paradigm', 'is', 'beginning', 'to', 'emerge', 'in', 'radiology', 'with', 'the', 'advent', 'of', 'increased', 'computational', 'capabilities', 'and', 'algorithms', 'this', 'has', 'led', 'to', 'the', 'ability', 'of', 'real', 'time', 'learning', 'by', 'computer', 'systems', 'of', 'different', 'lesion', 'types', 'to', 'help', 'the', 'radiologist', 'in', 'defining', 'disease', 'for', 'example', 'using', 'a', 'deep', 'learning', 'network', 'we', 'developed', 'and', 'tested', 'a', 'multiparametric', 'deep', 'learning', 'mpdl', 'network', 'for', 'segmentation', 'and', 'classification', 'using', 'multiparametric', 'magnetic', 'resonance', 'imaging', 'mpmri', 'radiological', 'images', 'the', 'mpdl', 'network', 'was', 'constructed', 'from', 'stacked', 'sparse', 'autoencoders', 'with', 'inputs', 'from', 'mpmri', 'evaluation', 'of', 'mpdl', 'consisted', 'of', 'crossvalidation', 'sensitivity', 'and', 'specificity', 'dice', 'similarity', 'between', 'mpdl', 'and', 'postdce', 'lesions', 'were', 'evaluated', 'we', 'demonstrate', 'high', 'sensitivity', 'and', 'specificity', 'for', 'differentiation', 'of', 'malignant', 'from', 'benign', 'lesions', 'of', '90', 'and', '85', 'respectively', 'with', 'an', 'auc', 'of', '093', 'the', 'integrated', 'mpdl', 'method', 'accurately', 'segmented', 'and', 'classified', 'different', 'breast', 'tissue', 'from', 'multiparametric', 'breast', 'mri', 'using', 'deep', 'leaning', 'tissue', 'signatures']] | [0.049399853968578905, -0.022264698029478797, -0.030487029570698116, 0.0562711632525558, -0.054456916754134, -0.17703229233868317, 0.025994904827611107, 0.41543842235114425, -0.20333830984398243, -0.3682066070355682, 0.08582404231128749, -0.2946499137647657, -0.22108002050663345, 0.22155884555023578, -0.13290266750846058, 0.1073520294481164, 0.12192493305014472, 0.023118108894171503, -0.025533885148534965, -0.2598861194241585, 0.2548063954357834, 0.030737700517420308, 0.3578191634698871, 0.012420816581450507, 0.17442597175896582, -0.03433035872714956, -0.03727949515450746, 0.008078435785945557, -0.05886433982393808, 0.1892337859608233, 0.3459619822177855, 0.22983034262627675, 0.31364231850602664, -0.3971039539125438, -0.20346728077210072, 0.10650576490540213, 0.13824355262719715, 0.053676915502162754, -0.027554577197103452, -0.4077753702489038, 0.10173716701683588, -0.13251033479981641, 0.028990827976182725, -0.1298504088449085, -0.036997395848124545, -0.015562109810869314, -0.2790887687927655, 0.13376130143943657, -0.03675984768617329, 0.19682553508674674, -0.12241123800696288, -0.15827593845218266, 0.013912183145293966, 0.19221954046063022, -0.020518572038983822, 0.07421262192575442, 0.18079012817987758, -0.21435726104957414, -0.14351270702253613, 0.257372546323394, -0.011289995390042249, -0.12998508882527757, 0.21460968993293741, -0.041403191341992676, -0.09312672044810218, 0.16690290032420307, 0.22953457573182984, 0.08121345585055274, -0.18410613640703055, -0.05303791000106786, 0.057381768212912396, 0.18926641138710287, 0.0884440160330592, -0.09425014160418262, 0.17271077424407444, 0.30389216606919134, -0.08998045749629252, 0.15074909537603767, -0.2448204721440561, 0.03166475894411431, -0.14519292573984582, -0.15945992047070628, -0.14733438642765073, -0.003914904381316673, -0.10632340300475739, -0.15382859986534136, 0.4274950077815447, 0.14949537084935904, 0.1679609127572298, 0.07411836410594536, 0.2768758792662993, -0.02485165021304662, 0.13979818301999736, -0.022095576977234386, 0.20164901683892822, 0.07617449133997273, 0.10954397447898777, -0.19258249808182074, 0.052894312303073496, 0.03469055735169806] |
1,802.08201 | A Polynomial Time Subsumption Algorithm for Nominal Safe
$\mathcal{ELO}_\bot$ under Rational Closure | Description Logics (DLs) under Rational Closure (RC) is a well-known
framework for non-monotonic reasoning in DLs. In this paper, we address the
concept subsumption decision problem under RC for nominal safe
$\mathcal{ELO}_\bot$, a notable and practically important DL representative of
the OWL 2 profile OWL 2 EL.
Our contribution here is to define a polynomial time subsumption procedure
for nominal safe $\mathcal{ELO}_\bot$ under RC that relies entirely on a series
of classical, monotonic $\mathcal{EL}_\bot$ subsumption tests. Therefore, any
existing classical monotonic $\mathcal{EL}_\bot$ reasoner can be used as a
black box to implement our method. We then also adapt the method to one of the
known extensions of RC for DLs, namely Defeasible Inheritance-based DLs without
losing the computational tractability.
| cs.AI | description logics dls under rational closure rc is a wellknown framework for nonmonotonic reasoning in dls in this paper we address the concept subsumption decision problem under rc for nominal safe mathcalelo_bot a notable and practically important dl representative of the owl 2 profile owl 2 el our contribution here is to define a polynomial time subsumption procedure for nominal safe mathcalelo_bot under rc that relies entirely on a series of classical monotonic mathcalel_bot subsumption tests therefore any existing classical monotonic mathcalel_bot reasoner can be used as a black box to implement our method we then also adapt the method to one of the known extensions of rc for dls namely defeasible inheritancebased dls without losing the computational tractability | [['description', 'logics', 'dls', 'under', 'rational', 'closure', 'rc', 'is', 'a', 'wellknown', 'framework', 'for', 'nonmonotonic', 'reasoning', 'in', 'dls', 'in', 'this', 'paper', 'we', 'address', 'the', 'concept', 'subsumption', 'decision', 'problem', 'under', 'rc', 'for', 'nominal', 'safe', 'mathcalelo_bot', 'a', 'notable', 'and', 'practically', 'important', 'dl', 'representative', 'of', 'the', 'owl', '2', 'profile', 'owl', '2', 'el', 'our', 'contribution', 'here', 'is', 'to', 'define', 'a', 'polynomial', 'time', 'subsumption', 'procedure', 'for', 'nominal', 'safe', 'mathcalelo_bot', 'under', 'rc', 'that', 'relies', 'entirely', 'on', 'a', 'series', 'of', 'classical', 'monotonic', 'mathcalel_bot', 'subsumption', 'tests', 'therefore', 'any', 'existing', 'classical', 'monotonic', 'mathcalel_bot', 'reasoner', 'can', 'be', 'used', 'as', 'a', 'black', 'box', 'to', 'implement', 'our', 'method', 'we', 'then', 'also', 'adapt', 'the', 'method', 'to', 'one', 'of', 'the', 'known', 'extensions', 'of', 'rc', 'for', 'dls', 'namely', 'defeasible', 'inheritancebased', 'dls', 'without', 'losing', 'the', 'computational', 'tractability']] | [-0.03838717070777483, -0.019408194765705485, -0.12645732592951892, 0.12884531462071303, -0.16430055519469597, -0.1941787087527136, 0.11310867941235835, 0.3503547480554673, -0.3057502747778299, -0.2697348127358368, 0.058725188088860236, -0.20216492508088463, -0.1261627150073262, 0.2222196476309207, -0.13787698278861954, 0.09315209266938397, 0.0032665667381009153, 0.02255423801373048, -0.05946225924357162, -0.2318496005990992, 0.30616065807207005, 0.0027120037682771938, 0.28131464210836665, 0.042548418041531415, 0.1170699671231981, 0.06696057155053935, 0.0014424475094560406, 0.09729349363900336, -0.11830580734743401, 0.10791007929044005, 0.31170288861954004, 0.2640301198146611, 0.2925031832258763, -0.38791415613979613, -0.15840122688176303, 0.06899988576508898, 0.14092029578148804, 0.06285736145820983, 0.012803593549098626, -0.20915902211282658, 0.10592289410274604, -0.19583104193363146, -0.0849857729145101, -0.10811504712107527, 0.04619911647951712, 0.013229216806237298, -0.2808498589026918, 0.010161641131883793, 0.1676733284578498, 0.07867489188331468, -0.051142195681238484, -0.10827783776993125, 0.08280893340947684, 0.03690368176743003, -0.03938757442339356, 0.02118184278992101, 0.1278313445168194, -0.08984514371821142, -0.1450496521670018, 0.34747878667609444, -0.037573779779105, -0.20164872907053935, 0.18642104253301334, -0.04518175380834346, -0.15526743360056444, 0.09379290047117733, 0.0914860069671453, 0.1543187640029295, -0.18935618686072272, 0.12592593574011296, -0.048913285272709765, 0.22767316373185545, 0.11792406212169163, 0.00358655274412113, 0.16512820023063826, 0.2071907844852078, 0.06417426953477592, 0.1449871668260914, -0.024730632163921434, -0.10535283513559864, -0.2965217557372445, -0.1347647901797057, -0.06103612855879654, -0.050560629794149305, -0.09486645079959999, -0.19951802798233734, 0.35163914294239007, 0.17731401353074913, 0.10898491875710094, 0.16712462163433947, 0.354954442898502, 0.09278923144277008, 0.10145276389185115, 0.05113269095630225, 0.19655104838452173, 0.07146552930072207, 0.12288007034181521, -0.18827298298831388, 0.11880209657427823, 0.06612470371980854] |
1,802.08202 | Nonequilibrium dynamics of the O(N) model on dS_3 and AdS crunches | We study the nonperturbative quantum evolution of the interacting O(N) vector
model at large-N, formulated on a spatial two-sphere, with time dependent
couplings which diverge at finite time. This model - the so-called "E-frame"
theory, is related via a conformal transformation to the interacting O(N) model
in three dimensional global de Sitter spacetime with time independent
couplings. We show that with a purely quartic, relevant deformation the quantum
evolution of the E-frame model is regular even when the classical theory is
rendered singular at the end of time by the diverging coupling. Time evolution
drives the E-frame theory to the large-N Wilson-Fisher fixed point when the
classical coupling diverges. We study the quantum evolution numerically for a
variety of initial conditions and demonstrate the finiteness of the energy at
the classical "end of time". With an additional (time dependent) mass
deformation, quantum backreaction lowers the mass, with a putative smooth time
evolution only possible in the limit of infinite quartic coupling. We discuss
the relevance of these results for the resolution of crunch singularities in
AdS geometries dual to E-frame theories with a classical gravity dual.
| hep-th gr-qc | we study the nonperturbative quantum evolution of the interacting on vector model at largen formulated on a spatial twosphere with time dependent couplings which diverge at finite time this model the socalled eframe theory is related via a conformal transformation to the interacting on model in three dimensional global de sitter spacetime with time independent couplings we show that with a purely quartic relevant deformation the quantum evolution of the eframe model is regular even when the classical theory is rendered singular at the end of time by the diverging coupling time evolution drives the eframe theory to the largen wilsonfisher fixed point when the classical coupling diverges we study the quantum evolution numerically for a variety of initial conditions and demonstrate the finiteness of the energy at the classical end of time with an additional time dependent mass deformation quantum backreaction lowers the mass with a putative smooth time evolution only possible in the limit of infinite quartic coupling we discuss the relevance of these results for the resolution of crunch singularities in ads geometries dual to eframe theories with a classical gravity dual | [['we', 'study', 'the', 'nonperturbative', 'quantum', 'evolution', 'of', 'the', 'interacting', 'on', 'vector', 'model', 'at', 'largen', 'formulated', 'on', 'a', 'spatial', 'twosphere', 'with', 'time', 'dependent', 'couplings', 'which', 'diverge', 'at', 'finite', 'time', 'this', 'model', 'the', 'socalled', 'eframe', 'theory', 'is', 'related', 'via', 'a', 'conformal', 'transformation', 'to', 'the', 'interacting', 'on', 'model', 'in', 'three', 'dimensional', 'global', 'de', 'sitter', 'spacetime', 'with', 'time', 'independent', 'couplings', 'we', 'show', 'that', 'with', 'a', 'purely', 'quartic', 'relevant', 'deformation', 'the', 'quantum', 'evolution', 'of', 'the', 'eframe', 'model', 'is', 'regular', 'even', 'when', 'the', 'classical', 'theory', 'is', 'rendered', 'singular', 'at', 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1,802.08203 | Grothendieck-Lefschetz for vector bundles | According to the Grothendieck-Lefschetz theorem from SGA 2, there are no
nontrivial line bundles on the punctured spectrum $U_R$ of a local ring $R$
that is a complete intersection of dimension $\ge 4$. Dao conjectured a
generalization for vector bundles $\mathscr{V}$ of arbitrary rank on $U_R$:
such a $\mathscr{V}$ is free if and only if
$\mathrm{depth}_R(\mathrm{End}_R(\Gamma(U_R, \mathscr{V}))) \ge 4$. We use
deformation theoretic techniques to settle Dao's conjecture. We also present
examples showing that its assumptions are sharp and draw consequences for
splitting of vector bundles on complete intersections in projective space.
| math.AG math.AC | according to the grothendiecklefschetz theorem from sga 2 there are no nontrivial line bundles on the punctured spectrum u_r of a local ring r that is a complete intersection of dimension ge 4 dao conjectured a generalization for vector bundles mathscrv of arbitrary rank on u_r such a mathscrv is free if and only if mathrmdepth_rmathrmend_rgammau_r mathscrv ge 4 we use deformation theoretic techniques to settle daos conjecture we also present examples showing that its assumptions are sharp and draw consequences for splitting of vector bundles on complete intersections in projective space | [['according', 'to', 'the', 'grothendiecklefschetz', 'theorem', 'from', 'sga', '2', 'there', 'are', 'no', 'nontrivial', 'line', 'bundles', 'on', 'the', 'punctured', 'spectrum', 'u_r', 'of', 'a', 'local', 'ring', 'r', 'that', 'is', 'a', 'complete', 'intersection', 'of', 'dimension', 'ge', '4', 'dao', 'conjectured', 'a', 'generalization', 'for', 'vector', 'bundles', 'mathscrv', 'of', 'arbitrary', 'rank', 'on', 'u_r', 'such', 'a', 'mathscrv', 'is', 'free', 'if', 'and', 'only', 'if', 'mathrmdepth_rmathrmend_rgammau_r', 'mathscrv', 'ge', '4', 'we', 'use', 'deformation', 'theoretic', 'techniques', 'to', 'settle', 'daos', 'conjecture', 'we', 'also', 'present', 'examples', 'showing', 'that', 'its', 'assumptions', 'are', 'sharp', 'and', 'draw', 'consequences', 'for', 'splitting', 'of', 'vector', 'bundles', 'on', 'complete', 'intersections', 'in', 'projective', 'space']] | [-0.16944965375536172, 0.05994572471072488, -0.06430457625026395, 0.0792094376066106, -0.08099430724773761, -0.19394926072333704, 0.018359305140060875, 0.37928745780999845, -0.2488571473673641, -0.1958601051435555, 0.13700263579196942, -0.25179315529057533, -0.15301167597011714, 0.19285679016528384, -0.10352030689674584, -0.03871109593559855, 0.028865817808904327, 0.10327726939263251, -0.0926120767912285, -0.31637702405498785, 0.39405001561249514, -0.04974909845015525, 0.21386778764017336, 0.11845393478358676, 0.0872866286369102, 0.05683979225456254, -0.002388182794675231, 0.02007609874080127, -0.1895232304662356, 0.126996546254524, 0.23597743427687948, 0.13854744494892657, 0.18859768840279634, -0.3723479848007088, -0.1657403007298094, 0.19189525100883548, 0.10688227570390554, 0.03156395737532076, -0.01658906512458778, -0.20674908105898035, 0.181980501952489, -0.12271965838518444, -0.16226135886141232, -0.08976241902212848, 0.10427954108172843, -0.014491362742834038, -0.2506316817483281, -0.018216928265346623, 0.12640349321312958, 0.12998918245964208, -0.046244300944106344, -0.10266427665304106, -0.0908740997150704, 0.04787749656256043, -0.018513277027523145, 0.033334297876405926, 0.07278725483127266, -0.0752577733371284, -0.12099244106806568, 0.3208787673930791, -0.05658242993752707, -0.19836086202873388, 0.15031582075631716, -0.13154207394908662, -0.1702819487315367, 0.1423634825233411, 0.0972656258637761, 0.15788270239903757, 0.06203161329440363, 0.19064158994504915, -0.14328077774249262, 0.14266987550225887, 0.10912315337662841, -0.018929824050116752, 0.13378982409671114, 0.06059946910641924, 0.11553452598925035, 0.07747959877763476, -0.02609624284073956, -0.02617639700298781, -0.37659708246752455, -0.21930766918256386, -0.14504541505824078, 0.17655033059418201, -0.11199771516136364, -0.14843174421924402, 0.3534732369225022, 0.049353061126197105, 0.2345090316107067, 0.10330314770632597, 0.23592298696902428, 0.02573020965536381, 0.03869393294431515, 0.09948513252599227, 0.17425960828780432, 0.22898458320504197, -0.03562140984174151, -0.07076007839302523, -0.050650461965782954, 0.1644669703955015] |
1,802.08204 | SCRank: Spammer and Celebrity Ranking in Directed Social Networks | Many online social networks allow directed edges: Alice can unilaterally add
an "edge" to Bob, typically indicating interest in Bob or Bob's content,
without Bob's permission or reciprocation. In directed social networks we
observe the rise of two distinctive classes of users: celebrities who accrue
unreciprocated incoming links, and follow spammers, who generate unreciprocated
outgoing links. Identifying users in these two classes is important for abuse
detection, user and content ranking, privacy choices, and other social network
features.
In this paper we develop SCRank, an iterative algorithm to identify such
users. We analyze SCRank both theoretically and experimentally. The
spammer-celebrity definition is not amenable to analysis using standard power
iteration, so we develop a novel potential function argument to show
convergence to an approximate equilibrium point for a class of algorithms
including SCRank. We then use experimental evaluation on a real global-scale
social network and on synthetically generated graphs to observe that the
algorithm converges quickly and consistently. Using synthetic data with
built-in ground truth, we also experimentally show that the algorithm provides
a good approximation to planted celebrities and spammers.
| cs.SI | many online social networks allow directed edges alice can unilaterally add an edge to bob typically indicating interest in bob or bobs content without bobs permission or reciprocation in directed social networks we observe the rise of two distinctive classes of users celebrities who accrue unreciprocated incoming links and follow spammers who generate unreciprocated outgoing links identifying users in these two classes is important for abuse detection user and content ranking privacy choices and other social network features in this paper we develop scrank an iterative algorithm to identify such users we analyze scrank both theoretically and experimentally the spammercelebrity definition is not amenable to analysis using standard power iteration so we develop a novel potential function argument to show convergence to an approximate equilibrium point for a class of algorithms including scrank we then use experimental evaluation on a real globalscale social network and on synthetically generated graphs to observe that the algorithm converges quickly and consistently using synthetic data with builtin ground truth we also experimentally show that the algorithm provides a good approximation to planted celebrities and spammers | [['many', 'online', 'social', 'networks', 'allow', 'directed', 'edges', 'alice', 'can', 'unilaterally', 'add', 'an', 'edge', 'to', 'bob', 'typically', 'indicating', 'interest', 'in', 'bob', 'or', 'bobs', 'content', 'without', 'bobs', 'permission', 'or', 'reciprocation', 'in', 'directed', 'social', 'networks', 'we', 'observe', 'the', 'rise', 'of', 'two', 'distinctive', 'classes', 'of', 'users', 'celebrities', 'who', 'accrue', 'unreciprocated', 'incoming', 'links', 'and', 'follow', 'spammers', 'who', 'generate', 'unreciprocated', 'outgoing', 'links', 'identifying', 'users', 'in', 'these', 'two', 'classes', 'is', 'important', 'for', 'abuse', 'detection', 'user', 'and', 'content', 'ranking', 'privacy', 'choices', 'and', 'other', 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1,802.08205 | In-depth study of long-term variability in the X-ray emission of the
Be/X-ray binary system AX J0049.4-7323 | AX J0049.4-7323 is a Be/X-ray binary in the Small Magellanic Cloud hosting a
~750 s pulsar which has been observed over the last ~17 years by several X-ray
telescopes. Despite numerous observations, little is known about its X-ray
behaviour. Therefore, we coherently analysed archival Swift, Chandra,
XMM-Newton, RXTE, and INTEGRAL data, and we compared them with already
published ASCA data, to study its X-ray long-term spectral and flux
variability. AX J0049.4-7323 shows a high X-ray variability, spanning more than
three orders of magnitudes, from L ~ 1.6E37 erg/s (0.3-8 keV, d=62 kpc) down to
L ~ 8E33 erg/s. RXTE, Chandra, Swift, and ASCA observed, in addition to the
expected enhancement of X-ray luminosity at periastron, flux variations by a
factor of ~ 270 with peak luminosities of ~2.1E36 erg/s far from periastron.
These properties are difficult to reconcile with the typical long-term
variability of Be/XRBs, traditionally interpreted in terms of type I and type
II outbursts. The study of AX J0049.4-7323 is complemented with a spectral
analysis of Swift, Chandra, and XMM-Newton data which showed a softening trend
when the emission becomes fainter, and an analysis of optical/UV data collected
by the UVOT telescope on board Swift. In addition, we measured a secular
spin-up rate of $\dot{P}=(-3.00\pm0.12)\times 10^{-3}$ s day$^{-1}$, which
suggests that the pulsar has not yet achieved its equilibrium period. Assuming
spherical accretion, we estimated an upper limit for the magnetic field
strength of the pulsar of ~3E12 G.
| astro-ph.HE | ax j004947323 is a bexray binary in the small magellanic cloud hosting a 750 s pulsar which has been observed over the last 17 years by several xray telescopes despite numerous observations little is known about its xray behaviour therefore we coherently analysed archival swift chandra xmmnewton rxte and integral data and we compared them with already published asca data to study its xray longterm spectral and flux variability ax j004947323 shows a high xray variability spanning more than three orders of magnitudes from l 16e37 ergs 038 kev d62 kpc down to l 8e33 ergs rxte chandra swift and asca observed in addition to the expected enhancement of xray luminosity at periastron flux variations by a factor of 270 with peak luminosities of 21e36 ergs far from periastron these properties are difficult to reconcile with the typical longterm variability of bexrbs traditionally interpreted in terms of type i and type ii outbursts the study of ax j004947323 is complemented with a spectral analysis of swift chandra and xmmnewton data which showed a softening trend when the emission becomes fainter and an analysis of opticaluv data collected by the uvot telescope on board swift in addition we measured a secular spinup rate of dotp300pm012times 103 s day1 which suggests that the pulsar has not yet achieved its equilibrium period assuming spherical accretion we estimated an upper limit for the magnetic field strength of the pulsar of 3e12 g | [['ax', 'j004947323', 'is', 'a', 'bexray', 'binary', 'in', 'the', 'small', 'magellanic', 'cloud', 'hosting', 'a', '750', 's', 'pulsar', 'which', 'has', 'been', 'observed', 'over', 'the', 'last', '17', 'years', 'by', 'several', 'xray', 'telescopes', 'despite', 'numerous', 'observations', 'little', 'is', 'known', 'about', 'its', 'xray', 'behaviour', 'therefore', 'we', 'coherently', 'analysed', 'archival', 'swift', 'chandra', 'xmmnewton', 'rxte', 'and', 'integral', 'data', 'and', 'we', 'compared', 'them', 'with', 'already', 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1,802.08206 | Gravitational Waves from Binary Mergers of Sub-solar Mass Dark Black
Holes | We explore the possible spectrum of binary mergers of sub-solar mass black
holes formed out of dark matter particles interacting via a dark
electromagnetism. We estimate the properties of these dark black holes by
assuming that their formation process is parallel to Population-III star
formation; except that dark molecular cooling can yield smaller opacity limit.
We estimate the binary coalescence rates for the Advanced LIGO and Einstein
telescope, and find that scenarios compatible with all current constraints
could produce dark black holes at rates high enough for detection by Advanced
LIGO.
| astro-ph.CO hep-ph | we explore the possible spectrum of binary mergers of subsolar mass black holes formed out of dark matter particles interacting via a dark electromagnetism we estimate the properties of these dark black holes by assuming that their formation process is parallel to populationiii star formation except that dark molecular cooling can yield smaller opacity limit we estimate the binary coalescence rates for the advanced ligo and einstein telescope and find that scenarios compatible with all current constraints could produce dark black holes at rates high enough for detection by advanced ligo | [['we', 'explore', 'the', 'possible', 'spectrum', 'of', 'binary', 'mergers', 'of', 'subsolar', 'mass', 'black', 'holes', 'formed', 'out', 'of', 'dark', 'matter', 'particles', 'interacting', 'via', 'a', 'dark', 'electromagnetism', 'we', 'estimate', 'the', 'properties', 'of', 'these', 'dark', 'black', 'holes', 'by', 'assuming', 'that', 'their', 'formation', 'process', 'is', 'parallel', 'to', 'populationiii', 'star', 'formation', 'except', 'that', 'dark', 'molecular', 'cooling', 'can', 'yield', 'smaller', 'opacity', 'limit', 'we', 'estimate', 'the', 'binary', 'coalescence', 'rates', 'for', 'the', 'advanced', 'ligo', 'and', 'einstein', 'telescope', 'and', 'find', 'that', 'scenarios', 'compatible', 'with', 'all', 'current', 'constraints', 'could', 'produce', 'dark', 'black', 'holes', 'at', 'rates', 'high', 'enough', 'for', 'detection', 'by', 'advanced', 'ligo']] | [-0.14284346391866495, 0.17473279274386036, -0.07210260631956651, 0.19229744228347384, -0.09927059936715843, -0.09712773376748293, 0.004643903349290837, 0.34301254319047536, -0.12562599629266086, -0.3870464471260925, 0.061831761770728196, -0.2752344857410088, -0.02280740891352992, 0.21868551450853163, 0.05032038607808587, -0.005404991798798789, 0.08450131349465144, -0.05116998496373276, -0.07271267792816366, -0.28100572555111003, 0.34584980952722316, 0.13892578507599596, 0.1458713350776624, -0.03159718338277314, 0.08220918578924713, -0.042417324148118496, -0.016247613823737253, -0.05033495032566262, -0.20644012696465033, 0.02537275974608057, 0.23713255534460256, 0.16833400197204326, 0.15884633746847593, -0.44715240043025095, -0.24539170873602137, 0.1344834638114732, 0.1659302346531179, 0.12056198122573424, -0.17005268482307156, -0.27506354281034034, 0.10314622585492843, -0.2738652487725511, -0.13733275570384748, 0.020042443077417683, 0.03258097742346453, 0.03275103856563814, -0.21916993652153147, 0.1382610617348781, 0.015461025329736562, -0.178832852834283, -0.12382221289470301, -0.06736439420677885, -0.07242833432654472, 0.021359610043793588, 0.05226689486752858, -0.013907515638313451, 0.2634583171610567, -0.1752969088176122, -0.09042547850941236, 0.3753651427002726, -0.13166754141675083, -0.061367407195515686, 0.2478334110378605, -0.21733625567323722, -0.16488364579381196, 0.15005279092404705, 0.17177902317636615, 0.1423072189675992, -0.14109925920614502, 0.03993597919259548, 0.0564773984887934, 0.21386777336842247, 0.13160104371075118, 0.07030906684691557, 0.4967160886255922, 0.1564244123298552, 0.02476144049848829, 0.06481849258908859, -0.14079172743463908, -0.05541347082420303, -0.24590352077323657, -0.12264221403133738, -0.12975636893335812, 0.09460224091730357, -0.14340764052806432, -0.09467765525147155, 0.22209073374928026, 0.10205632362739889, 0.16029528201209728, 0.03492110848662208, 0.2764881163346437, 0.06413777629015865, 0.048696486614542185, 0.08063596107352239, 0.3947124142036006, 0.12851354368747428, 0.0773073823989502, -0.23134820992229405, 0.014994051629820695, -0.004832682680788931] |
1,802.08207 | P-adic Asai L-functions of Bianchi modular forms | The Asai (or twisted tensor) $L$-function of a Bianchi modular form $\Psi$ is
the $L$-function attached to the tensor induction to $\mathbb{Q}$ of its
associated Galois representation. In this paper, when $\Psi$ is ordinary at $p$
we construct a $p$-adic analogue of this $L$-function: that is, a $p$-adic
measure on $\mathbb{Z}_p^\times$ that interpolates the critical values of the
Asai $L$-function twisted by Dirichlet characters of $p$-power conductor. The
construction uses techniques analogous to those used by Lei, Zerbes and the
first author in order to construct an Euler system attached to the Asai
representation of a quadratic Hilbert modular form.
| math.NT | the asai or twisted tensor lfunction of a bianchi modular form psi is the lfunction attached to the tensor induction to mathbbq of its associated galois representation in this paper when psi is ordinary at p we construct a padic analogue of this lfunction that is a padic measure on mathbbz_ptimes that interpolates the critical values of the asai lfunction twisted by dirichlet characters of ppower conductor the construction uses techniques analogous to those used by lei zerbes and the first author in order to construct an euler system attached to the asai representation of a quadratic hilbert modular form | [['the', 'asai', 'or', 'twisted', 'tensor', 'lfunction', 'of', 'a', 'bianchi', 'modular', 'form', 'psi', 'is', 'the', 'lfunction', 'attached', 'to', 'the', 'tensor', 'induction', 'to', 'mathbbq', 'of', 'its', 'associated', 'galois', 'representation', 'in', 'this', 'paper', 'when', 'psi', 'is', 'ordinary', 'at', 'p', 'we', 'construct', 'a', 'padic', 'analogue', 'of', 'this', 'lfunction', 'that', 'is', 'a', 'padic', 'measure', 'on', 'mathbbz_ptimes', 'that', 'interpolates', 'the', 'critical', 'values', 'of', 'the', 'asai', 'lfunction', 'twisted', 'by', 'dirichlet', 'characters', 'of', 'ppower', 'conductor', 'the', 'construction', 'uses', 'techniques', 'analogous', 'to', 'those', 'used', 'by', 'lei', 'zerbes', 'and', 'the', 'first', 'author', 'in', 'order', 'to', 'construct', 'an', 'euler', 'system', 'attached', 'to', 'the', 'asai', 'representation', 'of', 'a', 'quadratic', 'hilbert', 'modular', 'form']] | [-0.22905310790985822, 0.009910669830278494, -0.2109816056722775, 0.04573034779750742, -0.1624003473483026, -0.11320754074957222, -0.06459214783157222, 0.21131065104156732, -0.32918348725885155, -0.20938887317664923, 0.05643499610247091, -0.24306229226058348, -0.14771355932578445, 0.19954318093834444, -0.08879829655401408, 0.04021713587295381, -0.003483739965595305, 0.16599499345757068, -0.08612656320445239, -0.29452427657321095, 0.4357149709016085, 0.005920244762673974, 0.21260904107475653, -0.05759229577612132, 0.08831974608357995, 0.0039020933606661854, 0.06479180858004838, -0.16803405187558382, -0.1330734712125559, 0.19687880435492844, 0.332828020285815, -0.0398887326894328, 0.21988300938159228, -0.38135797342285516, -0.07077228955196915, 0.21425823038443922, 0.08511269750073552, -0.04463436362566427, 0.07125998638453894, -0.2590998974069953, 0.09275759583921171, -0.22296987302601337, -0.1915077540371567, -0.09042010883335024, 0.04023613531142473, 0.001765772468643263, -0.30320818612352013, 0.0023640108248218893, 0.028798881099792197, 0.15973467825446278, -0.12888961228425613, -0.17685384568641893, 0.02464157176669687, 0.0508195127142244, 0.02101010370301083, 0.1251221809303388, 0.06774923393968493, -0.16385681981686503, -0.08023182631935924, 0.32988670023158195, -0.1240924643148901, -0.20944308652775362, 0.07541219511651434, -0.1652723699156195, -0.17993845127522945, 0.1136332652065903, 0.07838842778466643, 0.11729263986926526, -0.006815177435782971, 0.18262272918538655, -0.14037801053375007, 0.08381301942688879, 0.13359225512482226, -0.1500876904372126, 0.1620903945947066, -0.01520420380635187, 0.01768314329907298, 0.19637376357568428, -0.005953771125641652, -0.038255792711861435, -0.34868193823844196, -0.2734925870344159, -0.1684279744606465, 0.1505087376886513, -0.051427794205810645, -0.18991096570156515, 0.40422382585238664, 0.10134072366170585, 0.16184458398376592, 0.1332153908442706, 0.20615679774506135, 0.1594155873078853, 0.12071883759112097, 0.02974226149264723, 0.07285033188876695, 0.23998615932185202, 0.021804064963944256, -0.17296192127629184, -0.011995064867660403, 0.23569519306998699] |
1,802.08208 | Thermally driven anomalous Hall effect transitions in FeRh | Materials exhibiting controllable magnetic phase transitions are currently in
demand for many spintronics applications. Here we investigate from first
principles the electronic structure and intrinsic anomalous Hall, spin Hall and
anomalous Nernst response properties of the FeRh metallic alloy which undergoes
a thermally driven antiferromagnetic-to-ferromagnetic phase transition. We show
that the energy band structures and underlying Berry curvatures have important
signatures in the various Hall effects. Specifically, the suppression of the
anomalous Hall and Nernst effects in the AFM state and a sign change in the
spin Hall conductivity across the transition are found. It is suggested that
the FeRh can be used a spin current detector capable of differentiating the
spin Hall effect from other anomalous transverse effects. The implications of
this material and its thermally driven phases as a spin current detection
scheme are also discussed.
| cond-mat.mtrl-sci | materials exhibiting controllable magnetic phase transitions are currently in demand for many spintronics applications here we investigate from first principles the electronic structure and intrinsic anomalous hall spin hall and anomalous nernst response properties of the ferh metallic alloy which undergoes a thermally driven antiferromagnetictoferromagnetic phase transition we show that the energy band structures and underlying berry curvatures have important signatures in the various hall effects specifically the suppression of the anomalous hall and nernst effects in the afm state and a sign change in the spin hall conductivity across the transition are found it is suggested that the ferh can be used a spin current detector capable of differentiating the spin hall effect from other anomalous transverse effects the implications of this material and its thermally driven phases as a spin current detection scheme are also discussed | [['materials', 'exhibiting', 'controllable', 'magnetic', 'phase', 'transitions', 'are', 'currently', 'in', 'demand', 'for', 'many', 'spintronics', 'applications', 'here', 'we', 'investigate', 'from', 'first', 'principles', 'the', 'electronic', 'structure', 'and', 'intrinsic', 'anomalous', 'hall', 'spin', 'hall', 'and', 'anomalous', 'nernst', 'response', 'properties', 'of', 'the', 'ferh', 'metallic', 'alloy', 'which', 'undergoes', 'a', 'thermally', 'driven', 'antiferromagnetictoferromagnetic', 'phase', 'transition', 'we', 'show', 'that', 'the', 'energy', 'band', 'structures', 'and', 'underlying', 'berry', 'curvatures', 'have', 'important', 'signatures', 'in', 'the', 'various', 'hall', 'effects', 'specifically', 'the', 'suppression', 'of', 'the', 'anomalous', 'hall', 'and', 'nernst', 'effects', 'in', 'the', 'afm', 'state', 'and', 'a', 'sign', 'change', 'in', 'the', 'spin', 'hall', 'conductivity', 'across', 'the', 'transition', 'are', 'found', 'it', 'is', 'suggested', 'that', 'the', 'ferh', 'can', 'be', 'used', 'a', 'spin', 'current', 'detector', 'capable', 'of', 'differentiating', 'the', 'spin', 'hall', 'effect', 'from', 'other', 'anomalous', 'transverse', 'effects', 'the', 'implications', 'of', 'this', 'material', 'and', 'its', 'thermally', 'driven', 'phases', 'as', 'a', 'spin', 'current', 'detection', 'scheme', 'are', 'also', 'discussed']] | [-0.19166202119052195, 0.2635996329827585, -0.06537594930673747, 0.03223392283510201, -0.07215267650789811, -0.11864159066918427, 0.014588303175633368, 0.3724294587585103, -0.3038009138663124, -0.28580693730517576, 0.06734818012278149, -0.31346735923105606, -0.22311419660252504, 0.21207680286117492, 0.05475887931559397, 0.03273806876303211, -0.09102818161583222, -0.062313371442555304, -0.10628254753132553, -0.14485258383480698, 0.28265765401116316, -0.026421237473740526, 0.3394009840549847, 0.08538379172619054, 0.06848571785604177, -0.0419212324012588, 0.08195929262328192, 0.07678916824954575, -0.12743019048123286, -0.01229958296449774, 0.26545731966937147, -0.16077223654323514, 0.12434988371535217, -0.44878835623840924, -0.20105624064614158, 0.03144305653183002, 0.06300297083731309, 0.18212587270713615, -0.10883874321302427, -0.3006701093315538, 0.008360489703498888, -0.18770323924895754, -0.09274057039073196, -0.11611486684220533, 0.037523915613259094, -0.07578546969233539, -0.2062180518072294, 0.12840718538243073, 0.10116025771561038, 0.06731704203327578, -0.08064225794025359, -0.15806939871644304, -0.09041739988522064, 0.09462408727520834, 0.048596901358510164, 0.012463437339317972, 0.21616864178086753, -0.17173972022820913, -0.2193166902094769, 0.3413989077983559, -0.040459766079658184, -0.10340797135849362, 0.14698818857120216, -0.23457416276410778, -0.09440918618718674, 0.16683816950957198, 0.14120851986893063, 0.06084642657821161, -0.13387694083317858, 0.057675622738526625, 0.050677552819252014, 0.1227893316173467, -0.015957699140425826, 0.12550705941596432, 0.3130109792244553, 0.20433804295295716, 0.011557378274290755, 0.15725142777976714, -0.1676984097862589, -0.02095853198873068, -0.22421335137408713, -0.2040174315292118, -0.21951577779364542, 0.09204782228376987, -0.0511931019383432, -0.1753798632113182, 0.4214671988005569, 0.21332207868007294, 0.14118349417011536, -0.1176575363482487, 0.27664933575695194, 0.12372153453727969, 0.05319622293978497, 0.046163280167198485, 0.2812530945993258, 0.19741104468298348, 0.17077634780181813, -0.3489802647921918, 0.14775595815001946, -0.016729025333863345] |
1,802.08209 | Touch Sensors with Overlapping Signals: Concept Investigation on Planar
Sensors with Resistive or Optical Transduction | Traditional methods for achieving high localization accuracy on tactile
sensors usually involve a matrix of miniaturized individual sensors distributed
on the area of interest. This approach usually comes at a price of increased
complexity in fabrication and circuitry, and can be hard to adapt to non-planar
geometries. We propose a method where sensing terminals are embedded in a
volume of soft material. Mechanical strain in this material results in a
measurable signal between any two given terminals. By having multiple terminals
and pairing them against each other in all possible combinations, we obtain a
rich signal set using few wires. We mine this data to learn the mapping between
the signals we extract and the contact parameters of interest. Our approach is
general enough that it can be applied with different transduction methods, and
achieves high accuracy in identifying indentation location and depth. Moreover,
this method lends itself to simple fabrication techniques and makes no
assumption about the underlying geometry, potentially simplifying future
integration in robot hands.
| cs.RO | traditional methods for achieving high localization accuracy on tactile sensors usually involve a matrix of miniaturized individual sensors distributed on the area of interest this approach usually comes at a price of increased complexity in fabrication and circuitry and can be hard to adapt to nonplanar geometries we propose a method where sensing terminals are embedded in a volume of soft material mechanical strain in this material results in a measurable signal between any two given terminals by having multiple terminals and pairing them against each other in all possible combinations we obtain a rich signal set using few wires we mine this data to learn the mapping between the signals we extract and the contact parameters of interest our approach is general enough that it can be applied with different transduction methods and achieves high accuracy in identifying indentation location and depth moreover this method lends itself to simple fabrication techniques and makes no assumption about the underlying geometry potentially simplifying future integration in robot hands | [['traditional', 'methods', 'for', 'achieving', 'high', 'localization', 'accuracy', 'on', 'tactile', 'sensors', 'usually', 'involve', 'a', 'matrix', 'of', 'miniaturized', 'individual', 'sensors', 'distributed', 'on', 'the', 'area', 'of', 'interest', 'this', 'approach', 'usually', 'comes', 'at', 'a', 'price', 'of', 'increased', 'complexity', 'in', 'fabrication', 'and', 'circuitry', 'and', 'can', 'be', 'hard', 'to', 'adapt', 'to', 'nonplanar', 'geometries', 'we', 'propose', 'a', 'method', 'where', 'sensing', 'terminals', 'are', 'embedded', 'in', 'a', 'volume', 'of', 'soft', 'material', 'mechanical', 'strain', 'in', 'this', 'material', 'results', 'in', 'a', 'measurable', 'signal', 'between', 'any', 'two', 'given', 'terminals', 'by', 'having', 'multiple', 'terminals', 'and', 'pairing', 'them', 'against', 'each', 'other', 'in', 'all', 'possible', 'combinations', 'we', 'obtain', 'a', 'rich', 'signal', 'set', 'using', 'few', 'wires', 'we', 'mine', 'this', 'data', 'to', 'learn', 'the', 'mapping', 'between', 'the', 'signals', 'we', 'extract', 'and', 'the', 'contact', 'parameters', 'of', 'interest', 'our', 'approach', 'is', 'general', 'enough', 'that', 'it', 'can', 'be', 'applied', 'with', 'different', 'transduction', 'methods', 'and', 'achieves', 'high', 'accuracy', 'in', 'identifying', 'indentation', 'location', 'and', 'depth', 'moreover', 'this', 'method', 'lends', 'itself', 'to', 'simple', 'fabrication', 'techniques', 'and', 'makes', 'no', 'assumption', 'about', 'the', 'underlying', 'geometry', 'potentially', 'simplifying', 'future', 'integration', 'in', 'robot', 'hands']] | [-0.1196237684333485, 0.06881868190963022, -0.05252415150638201, -0.0018656435053137515, -0.1144775090304142, -0.19253305464210602, 0.06777247975295979, 0.4525502167117899, -0.28105456834870896, -0.3372726286649927, 0.09098052344365815, -0.26878627701132685, -0.17412089021363392, 0.2280757288716198, -0.1207338852869224, 0.06656637720897526, 0.06367786212065843, 0.02031899226026353, -0.05913138177983385, -0.2120216956067953, 0.23872376849294868, 0.02282422398562783, 0.29970781284824993, 0.055885731504705854, 0.1169207042974035, 0.024861115683427828, -0.0016859526324927985, 0.03688149083918797, -0.08265759381867316, 0.1736819449920921, 0.3248747997445997, 0.12876299174759023, 0.25760498106696444, -0.450447974989015, -0.21761332044634454, 0.0925716837801173, 0.09243432656878572, 0.12560695516848994, -0.04377113113285762, -0.2658119755936508, 0.10387012024492326, -0.1444080566686249, -0.07766104807162624, -0.09226029521986441, -0.012928464516863495, 0.004389214638932915, -0.2638975356922981, 0.01524567670986324, 0.023733157002294582, 0.04770840221073501, -0.04124724947635508, -0.07926039041151031, 0.045033124610112454, 0.16309720824868557, 0.006591652245344427, 0.009434414249538127, 0.19239256659370685, -0.14165172979659485, -0.09292751228057607, 0.35348269052268144, -0.004206833150795477, -0.2321740335988405, 0.24047800164368605, -0.11168206611635655, -0.12022116258573122, 0.1470765651811561, 0.199684754198049, 0.08852144808461053, -0.1721412726861988, 0.04362796237280949, 0.03520555704731695, 0.18663846637808276, 0.08293952156014428, 0.037777242460915496, 0.20452764237433405, 0.21799119554660812, 0.08611583839655815, 0.14194048015110775, -0.10212878763141016, -0.019586947264531796, -0.2639255085221107, -0.13752994883643788, -0.206513260068054, 0.020542902218088688, -0.12135450560210934, -0.14924907112540467, 0.3617952494508403, 0.20030496038028045, 0.21056284361329308, 0.025363554073843414, 0.3517394920652119, 0.05694953824017367, 0.10960083218391783, 0.04724618826273405, 0.215887559073821, 0.08264598246345932, 0.08996846224355629, -0.16073453122217343, 0.09380632568942662, -0.01287816807315378] |
1,802.0821 | Half-space Macdonald processes | Macdonald processes are measures on sequences of integer partitions built
using the Cauchy summation identity for Macdonald symmetric functions. These
measures are a useful tool to uncover the integrability of many probabilistic
systems, including the Kardar-Parisi-Zhang (KPZ) equation and a number of other
models in its universality class. In this paper we develop the structural
theory behind half-space variants of these models and the corresponding
half-space Macdonald processes. These processes are built using a Littlewood
summation identity instead of the Cauchy identity, and their analysis is
considerably harder than their full-space counterparts.
We compute moments and Laplace transforms of observables for general
half-space Macdonald measures. Introducing new dynamics preserving this class
of measures, we relate them to various stochastic processes, in particular the
log-gamma polymer in a half-quadrant (they are also related to the stochastic
six-vertex model in a half-quadrant and the half-space ASEP). For the polymer
model, we provide explicit integral formulas for the Laplace transform of the
partition function. Non-rigorous saddle point asymptotics yield convergence of
the directed polymer free energy to either the Tracy-Widom GOE, GSE or the
Gaussian distribution depending on the average size of weights on the boundary.
| math.PR cond-mat.stat-mech math-ph math.CO math.MP | macdonald processes are measures on sequences of integer partitions built using the cauchy summation identity for macdonald symmetric functions these measures are a useful tool to uncover the integrability of many probabilistic systems including the kardarparisizhang kpz equation and a number of other models in its universality class in this paper we develop the structural theory behind halfspace variants of these models and the corresponding halfspace macdonald processes these processes are built using a littlewood summation identity instead of the cauchy identity and their analysis is considerably harder than their fullspace counterparts we compute moments and laplace transforms of observables for general halfspace macdonald measures introducing new dynamics preserving this class of measures we relate them to various stochastic processes in particular the loggamma polymer in a halfquadrant they are also related to the stochastic sixvertex model in a halfquadrant and the halfspace asep for the polymer model we provide explicit integral formulas for the laplace transform of the partition function nonrigorous saddle point asymptotics yield convergence of the directed polymer free energy to either the tracywidom goe gse or the gaussian distribution depending on the average size of weights on the boundary | [['macdonald', 'processes', 'are', 'measures', 'on', 'sequences', 'of', 'integer', 'partitions', 'built', 'using', 'the', 'cauchy', 'summation', 'identity', 'for', 'macdonald', 'symmetric', 'functions', 'these', 'measures', 'are', 'a', 'useful', 'tool', 'to', 'uncover', 'the', 'integrability', 'of', 'many', 'probabilistic', 'systems', 'including', 'the', 'kardarparisizhang', 'kpz', 'equation', 'and', 'a', 'number', 'of', 'other', 'models', 'in', 'its', 'universality', 'class', 'in', 'this', 'paper', 'we', 'develop', 'the', 'structural', 'theory', 'behind', 'halfspace', 'variants', 'of', 'these', 'models', 'and', 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1,802.08211 | Resonant torsion magnetometry in anisotropic quantum materials | Unusual behavior of quantum materials commonly arises from their effective
low-dimensional physics, which reflects the underlying anisotropy in the spin
and charge degrees of freedom. Torque magnetometry is a highly sensitive
technique to directly quantify the anisotropy in quantum materials, such as the
layered high-T$_c$ superconductors, anisotropic quantum spin-liquids, and the
surface states of topological insulators. Here we introduce the magnetotropic
coefficient $k=\partial^2 F/\partial \theta^2$, the second derivative of the
free energy F with respect to the angle $\theta$ between the sample and the
applied magnetic field, and report a simple and effective method to
experimentally detect it. A sub-$\mu$g crystallite is placed at the tip of a
commercially available atomic force microscopy cantilever, and we show that $k$
can be quantitatively inferred from a shift in the resonant frequency under
magnetic field. While related to the magnetic torque $\tau=\partial F/\partial
\theta$, $k$ takes the role of torque susceptibility, and thus provides
distinct insights into anisotropic materials akin to the difference between
magnetization and magnetic susceptibility. The thermodynamic coefficient $k$ is
discontinuous at second-order phase transitions and subject to Ehrenfest
relations with the specific heat and magnetic susceptibility. We apply this
simple yet quantitative method on the exemplary cases of the Weyl-semimetal NbP
and the spin-liquid candidate RuCl$_3$, yet it is broadly applicable in quantum
materials research.
| cond-mat.str-el | unusual behavior of quantum materials commonly arises from their effective lowdimensional physics which reflects the underlying anisotropy in the spin and charge degrees of freedom torque magnetometry is a highly sensitive technique to directly quantify the anisotropy in quantum materials such as the layered hight_c superconductors anisotropic quantum spinliquids and the surface states of topological insulators here we introduce the magnetotropic coefficient kpartial2 fpartial theta2 the second derivative of the free energy f with respect to the angle theta between the sample and the applied magnetic field and report a simple and effective method to experimentally detect it a submug crystallite is placed at the tip of a commercially available atomic force microscopy cantilever and we show that k can be quantitatively inferred from a shift in the resonant frequency under magnetic field while related to the magnetic torque taupartial fpartial theta k takes the role of torque susceptibility and thus provides distinct insights into anisotropic materials akin to the difference between magnetization and magnetic susceptibility the thermodynamic coefficient k is discontinuous at secondorder phase transitions and subject to ehrenfest relations with the specific heat and magnetic susceptibility we apply this simple yet quantitative method on the exemplary cases of the weylsemimetal nbp and the spinliquid candidate rucl_3 yet it is broadly applicable in quantum materials research | [['unusual', 'behavior', 'of', 'quantum', 'materials', 'commonly', 'arises', 'from', 'their', 'effective', 'lowdimensional', 'physics', 'which', 'reflects', 'the', 'underlying', 'anisotropy', 'in', 'the', 'spin', 'and', 'charge', 'degrees', 'of', 'freedom', 'torque', 'magnetometry', 'is', 'a', 'highly', 'sensitive', 'technique', 'to', 'directly', 'quantify', 'the', 'anisotropy', 'in', 'quantum', 'materials', 'such', 'as', 'the', 'layered', 'hight_c', 'superconductors', 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1,802.08212 | $^4{\rm He}$ vs. $^4{\rm Li}$ and production of light nuclei in
relativistic heavy-ion collisions | We propose to measure the yields of $^4{\rm He}$ and $^4{\rm Li}$ in
relativistic heavy-ion collisions to clarify a mechanism of light nuclei
production. Since the masses of $^4{\rm He}$ and $^4{\rm Li}$ are almost equal,
the yield of $^4{\rm Li}$ predicted by the thermal model is 5 times bigger than
that of $^4{\rm He}$ which reflects the different numbers of internal degrees
of freedom of the two nuclides. Their internal structure is, however, very
different: the alpha particle is well bound and compact while $^4{\rm Li}$ is
weakly bound and loose. Within the coalescence model the ratio of yields of
$^4{\rm Li}$ to $^4{\rm He}$ is shown to be significantly smaller than that in
the thermal model and the ratio decreases fast from central to peripheral
collisions of relativistic heavy-ion collisions because the coalescence rate
strongly depends on the nucleon source radius. Since the nuclide $^4{\rm Li}$
is unstable and it decays into $^3{\rm He}$ and $p$ after roughly $30~{\rm
fm}/c$, the yield of $^4{\rm Li}$ can be experimentally obtained through a
measurement of the $^3{\rm He}\!-\!p$ correlation function.
| nucl-th hep-ph nucl-ex | we propose to measure the yields of 4rm he and 4rm li in relativistic heavyion collisions to clarify a mechanism of light nuclei production since the masses of 4rm he and 4rm li are almost equal the yield of 4rm li predicted by the thermal model is 5 times bigger than that of 4rm he which reflects the different numbers of internal degrees of freedom of the two nuclides their internal structure is however very different the alpha particle is well bound and compact while 4rm li is weakly bound and loose within the coalescence model the ratio of yields of 4rm li to 4rm he is shown to be significantly smaller than that in the thermal model and the ratio decreases fast from central to peripheral collisions of relativistic heavyion collisions because the coalescence rate strongly depends on the nucleon source radius since the nuclide 4rm li is unstable and it decays into 3rm he and p after roughly 30rm fmc the yield of 4rm li can be experimentally obtained through a measurement of the 3rm hep correlation function | [['we', 'propose', 'to', 'measure', 'the', 'yields', 'of', '4rm', 'he', 'and', '4rm', 'li', 'in', 'relativistic', 'heavyion', 'collisions', 'to', 'clarify', 'a', 'mechanism', 'of', 'light', 'nuclei', 'production', 'since', 'the', 'masses', 'of', '4rm', 'he', 'and', '4rm', 'li', 'are', 'almost', 'equal', 'the', 'yield', 'of', '4rm', 'li', 'predicted', 'by', 'the', 'thermal', 'model', 'is', '5', 'times', 'bigger', 'than', 'that', 'of', '4rm', 'he', 'which', 'reflects', 'the', 'different', 'numbers', 'of', 'internal', 'degrees', 'of', 'freedom', 'of', 'the', 'two', 'nuclides', 'their', 'internal', 'structure', 'is', 'however', 'very', 'different', 'the', 'alpha', 'particle', 'is', 'well', 'bound', 'and', 'compact', 'while', '4rm', 'li', 'is', 'weakly', 'bound', 'and', 'loose', 'within', 'the', 'coalescence', 'model', 'the', 'ratio', 'of', 'yields', 'of', '4rm', 'li', 'to', '4rm', 'he', 'is', 'shown', 'to', 'be', 'significantly', 'smaller', 'than', 'that', 'in', 'the', 'thermal', 'model', 'and', 'the', 'ratio', 'decreases', 'fast', 'from', 'central', 'to', 'peripheral', 'collisions', 'of', 'relativistic', 'heavyion', 'collisions', 'because', 'the', 'coalescence', 'rate', 'strongly', 'depends', 'on', 'the', 'nucleon', 'source', 'radius', 'since', 'the', 'nuclide', '4rm', 'li', 'is', 'unstable', 'and', 'it', 'decays', 'into', '3rm', 'he', 'and', 'p', 'after', 'roughly', '30rm', 'fmc', 'the', 'yield', 'of', '4rm', 'li', 'can', 'be', 'experimentally', 'obtained', 'through', 'a', 'measurement', 'of', 'the', '3rm', 'hep', 'correlation', 'function']] | [-0.03782061670014324, 0.2848305756174442, -0.10226345507738491, 0.11306554451455465, 0.042073157859138316, -0.1353819119084316, 0.028946603083750234, 0.30171028652952775, -0.20759115733930633, -0.33056043561341036, -0.03043080442973102, -0.31132009025378565, 0.049079673563958044, 0.16112236236157412, 0.01951843084793331, -0.02033728292832772, 0.07688177178820801, 0.05361340674765718, -0.02744626257271092, -0.24822831888838362, 0.2788740261613081, 0.1450239572674036, 0.21319135950826523, 0.13385816649016408, 0.013900191318761143, -0.02405285553670385, -0.01406027186603751, -0.03961628887595402, -0.12446913015293022, 0.08410751276258249, 0.16427067863858408, 0.13421133454475137, 0.1762230799313531, -0.36561946714969557, -0.15991359143970638, 0.1081713794135592, 0.17307308357105486, 0.0993569791478674, -0.021828713805654036, -0.23951316623327631, 0.10486104726845345, -0.19971636797935288, -0.1393415028281096, 0.013085770110289255, 0.14367081786040217, 0.03569030128581087, -0.2794254623001002, 0.10643759950374564, 0.061341202114838074, 0.01960020654239795, -0.0518421170870877, -0.2080465929556845, -0.07372217708293141, 0.0027928083333083327, 0.03886222409330205, 0.0692373393698492, 0.1689853775056286, -0.09858707385590404, -0.021071483973840562, 0.42691550221708086, -0.06132648458216055, -0.08094205759051773, 0.17877176222391428, -0.18911992754631987, -0.08350436128934638, 0.1992087806057599, 0.1416627548997187, 0.14082383175070087, -0.13812892165895188, 0.05273318427207414, -0.006208716001128778, 0.195684295362379, 0.10768937943632612, 0.03347912209574133, 0.15250137145113613, 0.17282621395101563, -0.015731994843938283, 0.026199136360082774, -0.11904462432462928, -0.10200763990999095, -0.2670708240941167, -0.15085980234370153, -0.12046882773930621, 0.08249729060723136, -0.05414850538824491, -0.074097734478063, 0.3013024352180461, 0.04787399958909696, 0.26261133014017507, -0.06284556330841345, 0.21634710527076903, 0.1322200957349398, 0.015445602619891158, 0.10405359408533614, 0.332545599160302, 0.23275992472837162, 0.11048626058036462, -0.2640857986937691, 0.09997188657418721, 0.06037343870719067] |
1,802.08213 | SDSS-IV MaNGA: Stellar angular momentum of about 2300 galaxies:
unveiling the bimodality of massive galaxy properties | We measure $\lambda_{R_e}$, a proxy for galaxy specific stellar angular
momentum within one effective radius, and the ellipticity, $\epsilon$, for
about 2300 galaxies of all morphological types observed with integral field
spectroscopy as part of the MaNGA survey, the largest such sample to date. We
use the $(\lambda_{R_e}, \epsilon)$ diagram to separate early-type galaxies
into fast and slow rotators. We also visually classify each galaxy according to
its optical morphology and two-dimensional stellar velocity field. Comparing
these classifications to quantitative $\lambda_{R_e}$ measurements reveals
tight relationships between angular momentum and galaxy structure. In order to
account for atmospheric seeing, we use realistic models of galaxy kinematics to
derive a general approximate analytic correction for $\lambda_{R_e}$. Thanks to
the size of the sample and the large number of massive galaxies, we
unambiguously detect a clear bimodality in the $(\lambda_{R_e}, \epsilon)$
diagram which may result from fundamental differences in galaxy assembly
history. There is a sharp secondary density peak inside the region of the
diagram with low $\lambda_{R_e}$ and $\epsilon < 0.4$, previously suggested as
the definition for slow rotators. Most of these galaxies are visually
classified as non-regular rotators and have high velocity dispersion. The
intrinsic bimodality must be stronger, as it tends to be smoothed by noise and
inclination. The large sample of slow rotators allows us for the first time to
unveil a secondary peak at +/-90 degrees in their distribution of the
misalignments between the photometric and kinematic position angles. We confirm
that genuine slow rotators start appearing above a stellar mass of
2\times10^{11} M_{\odot}$ where a significant number of high-mass fast rotators
also exist.
| astro-ph.GA | we measure lambda_r_e a proxy for galaxy specific stellar angular momentum within one effective radius and the ellipticity epsilon for about 2300 galaxies of all morphological types observed with integral field spectroscopy as part of the manga survey the largest such sample to date we use the lambda_r_e epsilon diagram to separate earlytype galaxies into fast and slow rotators we also visually classify each galaxy according to its optical morphology and twodimensional stellar velocity field comparing these classifications to quantitative lambda_r_e measurements reveals tight relationships between angular momentum and galaxy structure in order to account for atmospheric seeing we use realistic models of galaxy kinematics to derive a general approximate analytic correction for lambda_r_e thanks to the size of the sample and the large number of massive galaxies we unambiguously detect a clear bimodality in the lambda_r_e epsilon diagram which may result from fundamental differences in galaxy assembly history there is a sharp secondary density peak inside the region of the diagram with low lambda_r_e and epsilon 04 previously suggested as the definition for slow rotators most of these galaxies are visually classified as nonregular rotators and have high velocity dispersion the intrinsic bimodality must be stronger as it tends to be smoothed by noise and inclination the large sample of slow rotators allows us for the first time to unveil a secondary peak at 90 degrees in their distribution of the misalignments between the photometric and kinematic position angles we confirm that genuine slow rotators start appearing above a stellar mass of 2times1011 m_odot where a significant number of highmass fast rotators also exist | [['we', 'measure', 'lambda_r_e', 'a', 'proxy', 'for', 'galaxy', 'specific', 'stellar', 'angular', 'momentum', 'within', 'one', 'effective', 'radius', 'and', 'the', 'ellipticity', 'epsilon', 'for', 'about', '2300', 'galaxies', 'of', 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1,802.08214 | Projected Entangled Pair States: Fundamental analytical and numerical
limitations | Matrix Product States (MPS) and Projected Entangled Pair States (PEPS) are
powerful analytical and numerical tools to assess quantum many-body systems in
one and higher dimensions, respectively. While MPS are comprehensively
understood, in PEPS fundamental questions, relevant analytically as well as
numerically, remain open, such as how to encode symmetries in full generality,
or how to stabilize numerical methods using canonical forms. Here, we show that
these key problems, as well as a number of related questions, are
algorithmically undecidable, that is, they cannot be fully resolved in a
systematic way. Our work thereby exposes fundamental limitations to a full and
unbiased understanding of quantum many-body systems using PEPS.
| quant-ph cond-mat.str-el | matrix product states mps and projected entangled pair states peps are powerful analytical and numerical tools to assess quantum manybody systems in one and higher dimensions respectively while mps are comprehensively understood in peps fundamental questions relevant analytically as well as numerically remain open such as how to encode symmetries in full generality or how to stabilize numerical methods using canonical forms here we show that these key problems as well as a number of related questions are algorithmically undecidable that is they cannot be fully resolved in a systematic way our work thereby exposes fundamental limitations to a full and unbiased understanding of quantum manybody systems using peps | [['matrix', 'product', 'states', 'mps', 'and', 'projected', 'entangled', 'pair', 'states', 'peps', 'are', 'powerful', 'analytical', 'and', 'numerical', 'tools', 'to', 'assess', 'quantum', 'manybody', 'systems', 'in', 'one', 'and', 'higher', 'dimensions', 'respectively', 'while', 'mps', 'are', 'comprehensively', 'understood', 'in', 'peps', 'fundamental', 'questions', 'relevant', 'analytically', 'as', 'well', 'as', 'numerically', 'remain', 'open', 'such', 'as', 'how', 'to', 'encode', 'symmetries', 'in', 'full', 'generality', 'or', 'how', 'to', 'stabilize', 'numerical', 'methods', 'using', 'canonical', 'forms', 'here', 'we', 'show', 'that', 'these', 'key', 'problems', 'as', 'well', 'as', 'a', 'number', 'of', 'related', 'questions', 'are', 'algorithmically', 'undecidable', 'that', 'is', 'they', 'can', 'not', 'be', 'fully', 'resolved', 'in', 'a', 'systematic', 'way', 'our', 'work', 'thereby', 'exposes', 'fundamental', 'limitations', 'to', 'a', 'full', 'and', 'unbiased', 'understanding', 'of', 'quantum', 'manybody', 'systems', 'using', 'peps']] | [-0.05542405125769702, 0.13533215650611302, -0.06981768888336691, 0.156715860189235, -0.030068810912780464, -0.16474199616773563, 0.03428947210989215, 0.39110893058505924, -0.30499432675794447, -0.29729498686607586, 0.12608590197156777, -0.2343163054383529, -0.19028326834509657, 0.20578564098104835, -0.02311344062062827, 0.12834818872030485, 0.06058201069139283, -0.029593663747337733, -0.1178438757345165, -0.26314039138907735, 0.32577692660164426, 0.01936326151163402, 0.21691400239836764, 0.08012929206121375, 0.0501498384189538, -0.02485029544596645, 0.024973890309179708, 0.04541671005585654, -0.09276080283042658, 0.1251861622101966, 0.359516538429836, 0.14535280405967074, 0.25446597085842354, -0.444031795266677, -0.19877979015423494, 0.03430004292167723, 0.23526849860579452, 0.19106615176001054, 0.0003738327290524136, -0.30243872846053405, 0.07921127203881043, -0.19663719126362014, -0.17448077808896248, -0.2459131469463252, -0.013205562100153077, -0.024448833147339016, -0.16959008076228202, 0.11005901082164862, 0.02590260625689883, 0.02738733622668819, -0.010397939654913816, -0.09151996133679693, -0.02879079496276311, 0.19138222003397956, -0.033769387714677246, 0.009380015019666064, 0.10065137335437943, -0.1182812762721865, -0.2074133700818162, 0.40385520431128413, 0.009724389160559937, -0.27890227116983046, 0.250771144258959, -0.07896996358070861, -0.16396245989017189, 0.03819831854938953, 0.16342056054960596, 0.11735198057087308, -0.13048323777991094, 0.0593306543792344, -0.05942080581814728, 0.17705779035723854, 0.01775672700340775, 0.1135552210055969, 0.2332464044786651, 0.13280915225940673, 0.06502626924352213, 0.13490338074572553, 0.03468180675144222, -0.1455101524776017, -0.2701556926423853, -0.1680611201985316, -0.2156879762039435, 0.07611046036591605, -0.0031989264211998406, -0.14436605414375664, 0.3874511750245636, 0.16702731563709677, 0.1494109589775855, 0.019693347528068856, 0.29435139357070017, 0.07498670993796126, 0.0460716845637018, 0.06895658827217466, 0.2039353593337265, 0.18580180566165258, -0.008748676405626942, -0.1997718058018522, 0.010702683192423798, 0.04359823524189944] |
1,802.08215 | ArduSoar: an Open-Source Thermalling Controller for Resource-Constrained
Autopilots | Autonomous soaring capability has the potential to significantly increase
time aloft for fixed-wing UAVs. In this paper, we introduce ArduSoar, the first
soaring controller integrated into a major autopilot software suite for small
UAVs. We describe ArduSoar from the algorithmic standpoint, outline its
integration with the ArduPlane autopilot, discuss parameter tuning for it, and
conduct a series of flight tests on real sUAVs that show ArduSoar's robustness
even in highly non-ideal atmospheric conditions.
| cs.RO cs.SY | autonomous soaring capability has the potential to significantly increase time aloft for fixedwing uavs in this paper we introduce ardusoar the first soaring controller integrated into a major autopilot software suite for small uavs we describe ardusoar from the algorithmic standpoint outline its integration with the arduplane autopilot discuss parameter tuning for it and conduct a series of flight tests on real suavs that show ardusoars robustness even in highly nonideal atmospheric conditions | [['autonomous', 'soaring', 'capability', 'has', 'the', 'potential', 'to', 'significantly', 'increase', 'time', 'aloft', 'for', 'fixedwing', 'uavs', 'in', 'this', 'paper', 'we', 'introduce', 'ardusoar', 'the', 'first', 'soaring', 'controller', 'integrated', 'into', 'a', 'major', 'autopilot', 'software', 'suite', 'for', 'small', 'uavs', 'we', 'describe', 'ardusoar', 'from', 'the', 'algorithmic', 'standpoint', 'outline', 'its', 'integration', 'with', 'the', 'arduplane', 'autopilot', 'discuss', 'parameter', 'tuning', 'for', 'it', 'and', 'conduct', 'a', 'series', 'of', 'flight', 'tests', 'on', 'real', 'suavs', 'that', 'show', 'ardusoars', 'robustness', 'even', 'in', 'highly', 'nonideal', 'atmospheric', 'conditions']] | [-0.14093406695494617, 0.04472698298944296, -0.04594788919000522, -0.014434506679696125, -0.05423039844111148, -0.14756819271765972, 0.019388419496691855, 0.41171835735440254, -0.23142800340428948, -0.35722598881609197, 0.158005386830537, -0.1928304465069179, -0.17620307716635475, 0.24940202215119547, -0.13003192734027255, 0.10829892043155902, 0.1333763018871347, -0.05680218568422656, 0.004892790325633858, -0.21495549123990687, 0.2588818397278479, 0.10072490078923495, 0.2536745422580482, 0.04822235091494909, 0.14552345989352983, -0.014978865951137699, -0.023851795837391113, 0.002556274798985544, -0.13709454086958853, 0.07230992578779874, 0.28507953212744946, 0.17168005597035307, 0.3259378099085196, -0.4485042071968749, -0.20431188526360886, 0.08850028313210477, 0.13437211284400435, 0.04123053608624184, -0.07764613265644058, -0.30664566198390897, 0.10013981667293263, -0.25426070821350033, -0.14554260382715586, -0.1128366830509048, 0.009833349022960318, 0.029033986409954, -0.2507456130874546, -0.07436100588908987, -0.03546521988818827, 0.08866852203357047, -0.09019728868936552, -0.06267807179171106, 0.03020933610589608, 0.16330054306857072, 0.029283861666782828, -0.02497591451654022, 0.1558709010866511, -0.10854927790216237, -0.09285290889522951, 0.407250323076395, -0.0018936933728569336, -0.19112387129470057, 0.1671059155850199, -0.08934891147646999, -0.1360519143914723, 0.09624171340518566, 0.267290011898655, 0.04720151954182032, -0.13991556126300408, 0.04803199128608854, 0.03728756919989119, 0.15898659238186869, 0.009302695467393252, -0.024867664968621903, 0.15816994023549816, 0.2525994263427413, 0.16152884358324218, 0.15454966976455803, -0.10367881751322336, -0.10320959391369336, -0.26930073311255465, -0.19066861675431332, -0.13189412254259747, 0.00030594086949376094, -0.06297099172535008, -0.13007051948511947, 0.40699052964539634, 0.25280160946852487, 0.11262653754565163, 0.1066608240665949, 0.39700526758974447, 0.07317221481892941, 0.04223643474793737, 0.06891737562482772, 0.23971259931399339, 0.009360426753435446, 0.15943954353544698, -0.24135716607375746, 0.07448720337445106, -0.01541960458068744] |
1,802.08216 | ChatPainter: Improving Text to Image Generation using Dialogue | Synthesizing realistic images from text descriptions on a dataset like
Microsoft Common Objects in Context (MS COCO), where each image can contain
several objects, is a challenging task. Prior work has used text captions to
generate images. However, captions might not be informative enough to capture
the entire image and insufficient for the model to be able to understand which
objects in the images correspond to which words in the captions. We show that
adding a dialogue that further describes the scene leads to significant
improvement in the inception score and in the quality of generated images on
the MS COCO dataset.
| cs.CV | synthesizing realistic images from text descriptions on a dataset like microsoft common objects in context ms coco where each image can contain several objects is a challenging task prior work has used text captions to generate images however captions might not be informative enough to capture the entire image and insufficient for the model to be able to understand which objects in the images correspond to which words in the captions we show that adding a dialogue that further describes the scene leads to significant improvement in the inception score and in the quality of generated images on the ms coco dataset | [['synthesizing', 'realistic', 'images', 'from', 'text', 'descriptions', 'on', 'a', 'dataset', 'like', 'microsoft', 'common', 'objects', 'in', 'context', 'ms', 'coco', 'where', 'each', 'image', 'can', 'contain', 'several', 'objects', 'is', 'a', 'challenging', 'task', 'prior', 'work', 'has', 'used', 'text', 'captions', 'to', 'generate', 'images', 'however', 'captions', 'might', 'not', 'be', 'informative', 'enough', 'to', 'capture', 'the', 'entire', 'image', 'and', 'insufficient', 'for', 'the', 'model', 'to', 'be', 'able', 'to', 'understand', 'which', 'objects', 'in', 'the', 'images', 'correspond', 'to', 'which', 'words', 'in', 'the', 'captions', 'we', 'show', 'that', 'adding', 'a', 'dialogue', 'that', 'further', 'describes', 'the', 'scene', 'leads', 'to', 'significant', 'improvement', 'in', 'the', 'inception', 'score', 'and', 'in', 'the', 'quality', 'of', 'generated', 'images', 'on', 'the', 'ms', 'coco', 'dataset']] | [6.958703948732684e-05, -0.0011408215242565847, -0.0832582949044402, 0.12298547358402763, -0.12134882082304388, -0.10279993462266729, 0.0009253370979636469, 0.4709100908435443, -0.23568802257068455, -0.38523659551534434, 0.05452751385061728, -0.31512248895688016, -0.11377565156412768, 0.2158397265564988, -0.20977212598218636, 0.010855803375735003, 0.1872119899843728, 0.09776942934110469, -0.030590321928007053, -0.3100157863387436, 0.27742079614921855, -0.005549433495045877, 0.31342854285064864, 0.003312246298746151, 0.13432609647005686, -0.10152980998414111, -0.02244585620093287, -0.028454515389075466, -0.013994681142874327, 0.15466192266995124, 0.35034861744326706, 0.20637678161409556, 0.24750146197209902, -0.39601777136033656, -0.1731406891303064, 0.08727701613451262, 0.1275528560976918, 0.11295621268515128, -0.030806186711689568, -0.4132079598037343, 0.13461125353876247, -0.13387128296216913, 0.07931124481062095, -0.1179638652897933, 0.04339798253632205, -0.05519773069867298, -0.29189918807698595, 0.05394870379492275, 0.07565457222688779, 0.028371612258328526, -0.05775876481807334, -0.04241921253246712, -0.00547684049781631, 0.23404173442966067, 0.03594626633532565, 0.1185585463456079, 0.13169583104386487, -0.2629365928798649, -0.08704301774246144, 0.46915994255858307, -0.07012960769911754, -0.2133071959091752, 0.20897690358790844, -0.08427968242790039, -0.11682177364241843, 0.12646373144040504, 0.22286665984703338, 0.11607553127139587, -0.16568157666673264, -0.03712655801962897, -0.11180704753553751, 0.24900490175658727, 0.10038656219109601, -0.01030794239840379, 0.2278910654724813, 0.20858562065690173, -0.03690828553254844, 0.14548879813667678, -0.16311638586350954, -0.028495678093795683, -0.19870900306120223, -0.10841236240687031, -0.1786053034878683, -0.017895746466962795, -0.04188664845965903, -0.13896255135449453, 0.4226181892696403, 0.33379803471468095, 0.23686593444561402, 0.031004061239917634, 0.30324406129326303, -0.03892039937679382, 0.15931334446056508, 0.03750198139459826, 0.11904478186796255, -0.05647578463871397, 0.11301443122975602, -0.10769678424135325, 0.08767131007249084, 0.03544352498298109] |
1,802.08217 | A new model for Cerebellar computation | The standard state space model is widely believed to account for the
cerebellar computation in motor adaptation tasks [1]. Here we show that several
recent experiments [2-4] where the visual feedback is irrelevant to the motor
response challenge the standard model. Furthermore, we propose a new model that
accounts for the the results presented in [2-4]. According to this new model,
learning and forgetting are coupled and are error size dependent. We also show
that under reasonable assumptions, our proposed model is the only model that
accounts for both the classical adaptation paradigm as well as the recent
experiments [2-4].
| cs.NE q-bio.NC | the standard state space model is widely believed to account for the cerebellar computation in motor adaptation tasks 1 here we show that several recent experiments 24 where the visual feedback is irrelevant to the motor response challenge the standard model furthermore we propose a new model that accounts for the the results presented in 24 according to this new model learning and forgetting are coupled and are error size dependent we also show that under reasonable assumptions our proposed model is the only model that accounts for both the classical adaptation paradigm as well as the recent experiments 24 | [['the', 'standard', 'state', 'space', 'model', 'is', 'widely', 'believed', 'to', 'account', 'for', 'the', 'cerebellar', 'computation', 'in', 'motor', 'adaptation', 'tasks', '1', 'here', 'we', 'show', 'that', 'several', 'recent', 'experiments', '24', 'where', 'the', 'visual', 'feedback', 'is', 'irrelevant', 'to', 'the', 'motor', 'response', 'challenge', 'the', 'standard', 'model', 'furthermore', 'we', 'propose', 'a', 'new', 'model', 'that', 'accounts', 'for', 'the', 'the', 'results', 'presented', 'in', '24', 'according', 'to', 'this', 'new', 'model', 'learning', 'and', 'forgetting', 'are', 'coupled', 'and', 'are', 'error', 'size', 'dependent', 'we', 'also', 'show', 'that', 'under', 'reasonable', 'assumptions', 'our', 'proposed', 'model', 'is', 'the', 'only', 'model', 'that', 'accounts', 'for', 'both', 'the', 'classical', 'adaptation', 'paradigm', 'as', 'well', 'as', 'the', 'recent', 'experiments', '24']] | [-0.03162506625056267, 0.09010990751441568, -0.05210177262313664, 0.07160780320176854, -0.06240910205524415, -0.16715556429233402, 0.03277654761448503, 0.38800304892472925, -0.2620140578970313, -0.3324580401927233, 0.1042421388567891, -0.23452724768780173, -0.24813379362225532, 0.2173270921735093, -0.096739900354587, 0.07060585061088204, 0.05626564656384289, 0.04462809444172308, -0.012731884671375156, -0.24695291163399816, 0.2684964596736245, 0.051554138604551554, 0.3266206442983821, 0.04475181842863094, 0.12258093394339084, -0.03190676076337695, -0.016597269251942635, -0.0012376320243492956, -0.08989344156143489, 0.10440847934223711, 0.20537216564640404, 0.13382430812809618, 0.2950613699108362, -0.41548999889753757, -0.26063515378162266, 0.08791007385589182, 0.11563795170746743, 0.13315487140789628, -0.06752667307853699, -0.25685312336077915, 0.10534091397188604, -0.17930097829084843, -0.01867413754109293, -0.11471820576582104, 0.011145870164036752, 0.007033396639253624, -0.3118879565875977, 0.08343414126167772, 0.08991380040883086, 0.005588286938145757, -0.10553729709703476, -0.10619367504492402, 0.03410285571590066, 0.14702007471991238, 0.04641093706246466, 0.05864110356662423, 0.14288463668199256, -0.1416349521675147, -0.15042455333285035, 0.3905479938723147, -0.07506457125768065, -0.21068716591224074, 0.21447594925295563, -0.08831117659807206, -0.14815639936365188, 0.058735604556277396, 0.15803122597746552, 0.09080338871048298, -0.17384942756034433, 0.03686221895623021, -0.07424204727634788, 0.20370018064044415, -0.05562529921066016, -0.02459444008767605, 0.12648882136680187, 0.23966651604510844, 0.003411011826246977, 0.11637962403940037, -0.1199231867538765, -0.15226767792599274, -0.3275892363768071, -0.11853496327064932, -0.13441507276147605, -0.03677075991407037, -0.07008779955533101, -0.08109156679362059, 0.3876460562599823, 0.2427538414968876, 0.21971370401792228, 0.0991592569835484, 0.32035395052284005, 0.0880737359856721, 0.09550125589594245, 0.0848727911291644, 0.24263866426423192, 0.04934690012596547, 0.08153279408812523, -0.2118697665585205, 0.09046096501639113, 0.01809116166085005] |
1,802.08218 | VizWiz Grand Challenge: Answering Visual Questions from Blind People | The study of algorithms to automatically answer visual questions currently is
motivated by visual question answering (VQA) datasets constructed in artificial
VQA settings. We propose VizWiz, the first goal-oriented VQA dataset arising
from a natural VQA setting. VizWiz consists of over 31,000 visual questions
originating from blind people who each took a picture using a mobile phone and
recorded a spoken question about it, together with 10 crowdsourced answers per
visual question. VizWiz differs from the many existing VQA datasets because (1)
images are captured by blind photographers and so are often poor quality, (2)
questions are spoken and so are more conversational, and (3) often visual
questions cannot be answered. Evaluation of modern algorithms for answering
visual questions and deciding if a visual question is answerable reveals that
VizWiz is a challenging dataset. We introduce this dataset to encourage a
larger community to develop more generalized algorithms that can assist blind
people.
| cs.CV cs.CL cs.HC | the study of algorithms to automatically answer visual questions currently is motivated by visual question answering vqa datasets constructed in artificial vqa settings we propose vizwiz the first goaloriented vqa dataset arising from a natural vqa setting vizwiz consists of over 31000 visual questions originating from blind people who each took a picture using a mobile phone and recorded a spoken question about it together with 10 crowdsourced answers per visual question vizwiz differs from the many existing vqa datasets because 1 images are captured by blind photographers and so are often poor quality 2 questions are spoken and so are more conversational and 3 often visual questions cannot be answered evaluation of modern algorithms for answering visual questions and deciding if a visual question is answerable reveals that vizwiz is a challenging dataset we introduce this dataset to encourage a larger community to develop more generalized algorithms that can assist blind people | [['the', 'study', 'of', 'algorithms', 'to', 'automatically', 'answer', 'visual', 'questions', 'currently', 'is', 'motivated', 'by', 'visual', 'question', 'answering', 'vqa', 'datasets', 'constructed', 'in', 'artificial', 'vqa', 'settings', 'we', 'propose', 'vizwiz', 'the', 'first', 'goaloriented', 'vqa', 'dataset', 'arising', 'from', 'a', 'natural', 'vqa', 'setting', 'vizwiz', 'consists', 'of', 'over', '31000', 'visual', 'questions', 'originating', 'from', 'blind', 'people', 'who', 'each', 'took', 'a', 'picture', 'using', 'a', 'mobile', 'phone', 'and', 'recorded', 'a', 'spoken', 'question', 'about', 'it', 'together', 'with', '10', 'crowdsourced', 'answers', 'per', 'visual', 'question', 'vizwiz', 'differs', 'from', 'the', 'many', 'existing', 'vqa', 'datasets', 'because', '1', 'images', 'are', 'captured', 'by', 'blind', 'photographers', 'and', 'so', 'are', 'often', 'poor', 'quality', '2', 'questions', 'are', 'spoken', 'and', 'so', 'are', 'more', 'conversational', 'and', '3', 'often', 'visual', 'questions', 'can', 'not', 'be', 'answered', 'evaluation', 'of', 'modern', 'algorithms', 'for', 'answering', 'visual', 'questions', 'and', 'deciding', 'if', 'a', 'visual', 'question', 'is', 'answerable', 'reveals', 'that', 'vizwiz', 'is', 'a', 'challenging', 'dataset', 'we', 'introduce', 'this', 'dataset', 'to', 'encourage', 'a', 'larger', 'community', 'to', 'develop', 'more', 'generalized', 'algorithms', 'that', 'can', 'assist', 'blind', 'people']] | [-0.03831468799677617, 0.02206612638252267, -0.02092945049577332, 0.12890710534872607, -0.1742987164187354, -0.23434085469366378, 0.03935674202701004, 0.4160883795324858, -0.2532812052938555, -0.4163080444317553, 0.06386963892561782, -0.33778201450605866, -0.16990139249821085, 0.2414773782207207, -0.2469154067712461, 0.022668578093508623, 0.1546409631196361, 0.043305542320013046, 0.013054446773089517, -0.360016973065545, 0.3177591943266717, -0.0014281372468640376, 0.2366802664715555, 0.061210041985901485, 0.09125841679803683, -0.07485079046870981, -0.09395301254169847, -0.028952172594507792, -0.05939500284875976, 0.176001399526049, 0.39516315631895, 0.27665295549245045, 0.39974244648172835, -0.35461451292231483, -0.16880399789872833, 0.08047279558755312, 0.17732221688530952, 0.08380041376089635, -0.030125399920885306, -0.4076361384835433, 0.08782384397050777, -0.0980935659162797, 0.059765047416417534, -0.09385046937394065, 0.0234768151331318, -0.08926553260376253, -0.2732844873264964, 0.026499716413824204, 0.10366047148943527, 0.1574661243849059, -0.01856924046447815, -0.08266458726282437, 0.09111613442202086, 0.22785741406154225, 0.04095494793656534, 0.08130885741534316, 0.14458604354121082, -0.2154350724304095, -0.16693842247757432, 0.4245323349612874, 0.007559108035336551, -0.182630168890895, 0.20632849602548817, -0.049404727293529196, -0.14335970130866973, 0.06840069460767237, 0.19698947062337915, 0.11829606031333005, -0.1941668833726896, 0.01901695346452187, -0.16503204181094883, 0.26647407399466283, 0.09150691920754012, -0.04121484186548691, 0.23324417821796878, 0.23440745514031355, -0.0062512010279226465, 0.07433379944580208, -0.017380015756753454, -0.03048806758476542, -0.10029638759404808, -0.06481982725249096, -0.12458912353333715, 0.03234993765599702, -0.01135558770111892, -0.1041130047025425, 0.3637902426182643, 0.27019519803972986, 0.2065234439048384, 0.04410431015474552, 0.3248731931429598, -0.043121764781074476, 0.051951489241963085, 0.09317531154261201, 0.09828810552104872, -0.05292611963768768, 0.1662969359177068, -0.09462252104474994, 0.0595488927051933, 0.05858443553573467] |
1,802.08219 | Tensor field networks: Rotation- and translation-equivariant neural
networks for 3D point clouds | We introduce tensor field neural networks, which are locally equivariant to
3D rotations, translations, and permutations of points at every layer. 3D
rotation equivariance removes the need for data augmentation to identify
features in arbitrary orientations. Our network uses filters built from
spherical harmonics; due to the mathematical consequences of this filter
choice, each layer accepts as input (and guarantees as output) scalars,
vectors, and higher-order tensors, in the geometric sense of these terms. We
demonstrate the capabilities of tensor field networks with tasks in geometry,
physics, and chemistry.
| cs.LG cs.AI cs.CV cs.NE | we introduce tensor field neural networks which are locally equivariant to 3d rotations translations and permutations of points at every layer 3d rotation equivariance removes the need for data augmentation to identify features in arbitrary orientations our network uses filters built from spherical harmonics due to the mathematical consequences of this filter choice each layer accepts as input and guarantees as output scalars vectors and higherorder tensors in the geometric sense of these terms we demonstrate the capabilities of tensor field networks with tasks in geometry physics and chemistry | [['we', 'introduce', 'tensor', 'field', 'neural', 'networks', 'which', 'are', 'locally', 'equivariant', 'to', '3d', 'rotations', 'translations', 'and', 'permutations', 'of', 'points', 'at', 'every', 'layer', '3d', 'rotation', 'equivariance', 'removes', 'the', 'need', 'for', 'data', 'augmentation', 'to', 'identify', 'features', 'in', 'arbitrary', 'orientations', 'our', 'network', 'uses', 'filters', 'built', 'from', 'spherical', 'harmonics', 'due', 'to', 'the', 'mathematical', 'consequences', 'of', 'this', 'filter', 'choice', 'each', 'layer', 'accepts', 'as', 'input', 'and', 'guarantees', 'as', 'output', 'scalars', 'vectors', 'and', 'higherorder', 'tensors', 'in', 'the', 'geometric', 'sense', 'of', 'these', 'terms', 'we', 'demonstrate', 'the', 'capabilities', 'of', 'tensor', 'field', 'networks', 'with', 'tasks', 'in', 'geometry', 'physics', 'and', 'chemistry']] | [-0.0937612233578824, 0.07570084584144395, -0.029594639509790733, 0.019530416873095327, -0.11255277611650108, -0.13802182552041067, -0.03611937829743275, 0.4155593987533383, -0.3237278794534923, -0.28890965680141795, 0.06629745043903129, -0.2211176900747703, -0.2041425681843035, 0.11098031029419116, -0.10767217120221094, 0.06831005957563606, 0.07816798752173781, 0.019591753907355198, -0.08890166429258632, -0.22154260301809456, 0.3471383920509703, 0.036136339941805, 0.316956836353527, -0.04075034063837878, 0.17417159584858402, 0.008528078359478478, -0.027136149931322323, -0.0015107012063453203, -0.04829847267985846, 0.14752801299733476, 0.28903404476769856, 0.13636600971221924, 0.2188446217247944, -0.47154572959093305, -0.20152390774161544, 0.0810048964523365, 0.09604905878999427, 0.1402760925087973, -0.006709220683139362, -0.294639849726613, 0.0807327261414337, -0.12046165653148645, -0.07835445305322077, -0.16194444569874178, -0.0013600281005453194, 0.010584583867006423, -0.30527680221254405, 0.0023132636829206114, 0.10426017056543672, 0.09943916416318899, -0.0456422290586856, -0.11786308215951986, -0.0737296697249364, 0.14990931587147244, 0.024960304537181104, 0.03137479900916138, 0.1600089758167598, -0.16000936152884382, -0.15463556771119533, 0.3848288293634908, -0.038118864775875984, -0.28073448117487554, 0.16148909225698896, -0.09603781508428327, -0.13366452198517456, 0.08358736311901738, 0.20313748363614753, 0.08361258492229527, -0.07995222366592858, 0.0853683375988909, -0.02401015406220712, 0.17096596767372463, 0.09486067886830549, 0.055214836795845726, 0.186000510443295, 0.09141812569807085, 0.06073381677479221, 0.16437709754270113, -0.11424600998995292, -0.045333052033118985, -0.30712774524653563, -0.14609783914023905, -0.1735559520285493, 6.504190478766903e-05, -0.14002044633321276, -0.17849687230511663, 0.4370648250234931, 0.17515602457242901, 0.2023579512155102, 0.09491732034157292, 0.30884094318647065, 0.02829245052410269, 0.14576946529612111, 0.11492217050111864, 0.17210033761201363, 0.1631141221778614, 0.10467535906649206, -0.1084279562268155, 0.026157368822127915, 0.1320877368928174] |
1,802.0822 | The optical properties of transferred graphene and the dielectrics grown
on it obtained by ellipsometry | Graphene layers grown by chemical vapour deposition (CVD) method and
transferred from Cu-foils to the oxidized Si-substrates were investigated by
spectroscopic ellipsometry (SE), Raman and X-Ray Photoelectron Spectroscopy
(XPS) methods. The optical properties of transferred CVD graphene layers do not
always correspond to the ones of the exfoliated graphene due to the
contamination from the chemicals used in the transfer process. However, the
real thickness and the mean properties of the transferred CVD graphene layers
can be found using ellipsometry if a real thickness of the SiO2 layer is taken
into account. The pulsed layer deposition (PLD) and atomic layer deposition
(ALD) methods were used to grow dielectric layers on the transferred graphene
and the obtained structures were characterized using optical methods. The
approach demonstrated in this work could be useful for the characterization of
various materials grown on graphene.
| cond-mat.mtrl-sci | graphene layers grown by chemical vapour deposition cvd method and transferred from cufoils to the oxidized sisubstrates were investigated by spectroscopic ellipsometry se raman and xray photoelectron spectroscopy xps methods the optical properties of transferred cvd graphene layers do not always correspond to the ones of the exfoliated graphene due to the contamination from the chemicals used in the transfer process however the real thickness and the mean properties of the transferred cvd graphene layers can be found using ellipsometry if a real thickness of the sio2 layer is taken into account the pulsed layer deposition pld and atomic layer deposition ald methods were used to grow dielectric layers on the transferred graphene and the obtained structures were characterized using optical methods the approach demonstrated in this work could be useful for the characterization of various materials grown on graphene | [['graphene', 'layers', 'grown', 'by', 'chemical', 'vapour', 'deposition', 'cvd', 'method', 'and', 'transferred', 'from', 'cufoils', 'to', 'the', 'oxidized', 'sisubstrates', 'were', 'investigated', 'by', 'spectroscopic', 'ellipsometry', 'se', 'raman', 'and', 'xray', 'photoelectron', 'spectroscopy', 'xps', 'methods', 'the', 'optical', 'properties', 'of', 'transferred', 'cvd', 'graphene', 'layers', 'do', 'not', 'always', 'correspond', 'to', 'the', 'ones', 'of', 'the', 'exfoliated', 'graphene', 'due', 'to', 'the', 'contamination', 'from', 'the', 'chemicals', 'used', 'in', 'the', 'transfer', 'process', 'however', 'the', 'real', 'thickness', 'and', 'the', 'mean', 'properties', 'of', 'the', 'transferred', 'cvd', 'graphene', 'layers', 'can', 'be', 'found', 'using', 'ellipsometry', 'if', 'a', 'real', 'thickness', 'of', 'the', 'sio2', 'layer', 'is', 'taken', 'into', 'account', 'the', 'pulsed', 'layer', 'deposition', 'pld', 'and', 'atomic', 'layer', 'deposition', 'ald', 'methods', 'were', 'used', 'to', 'grow', 'dielectric', 'layers', 'on', 'the', 'transferred', 'graphene', 'and', 'the', 'obtained', 'structures', 'were', 'characterized', 'using', 'optical', 'methods', 'the', 'approach', 'demonstrated', 'in', 'this', 'work', 'could', 'be', 'useful', 'for', 'the', 'characterization', 'of', 'various', 'materials', 'grown', 'on', 'graphene']] | [-0.001874423533529583, 0.13880905385493583, -0.06167373392204552, -0.077125651395284, 0.03718158726890882, -0.1321295457655915, 0.10733282739006361, 0.4909165734425187, -0.3333192686584063, -0.31097050061098475, 0.023908809497210103, -0.3228916093653095, -0.11361467895988861, 0.22951918918440334, 0.009693413459952328, 0.09478741063587907, 0.052499556319241455, -0.19276149305717452, -0.05877727329852465, -0.2593114610315989, 0.2871966758790169, 0.06440024395756748, 0.3820649182248483, 0.09306916344381086, 0.0537365869672942, -0.0313546948870509, 0.048513995567876576, -0.0040430387033257575, -0.16333354651557613, 0.12288495743532489, 0.2297941398759629, -0.09607709768444192, 0.1851637227244783, -0.5416370874702714, -0.29718236777040624, -0.05272144542845047, 0.13941202736695876, 0.08824656286384013, -0.10630978088896803, -0.24981633457692637, 0.07057962117487214, -0.08027349345291546, -0.0365782971088977, -0.06680658218734291, -0.12156157689573972, -0.0030011460969589002, -0.22910385059894642, 0.02775365854545996, -0.010428924299523478, 0.07702744252763796, -0.1501722825333422, -0.1628111008208509, -0.18563049722317795, 0.12134216483209984, -0.00023898104584499168, -0.010154832351912299, 0.3026145582671102, -0.06727379382810676, -0.029284850816559585, 0.3572351241491033, -0.05095909408249798, -0.10611167362472718, 0.19380272376060864, -0.15312817210898452, -0.0003721167255813877, 0.1521616888779175, 0.11015356720283466, 0.19218938849002554, -0.20368716602746828, 0.03855877388496478, 0.03145062564737231, 0.22909221328133583, 0.2115570677484831, 0.04536333045773748, 0.19272690742492568, 0.21385374447656458, -0.038878721055115806, 0.1590367385365096, -0.1609000309161248, 0.09208644535122575, -0.10695033451623243, -0.20410840604049357, -0.25658788173493213, 0.1053744329653547, -0.04831105104824309, -0.19242753691387537, 0.39599187766620214, 0.10989323036704698, 0.16545219106964118, -0.09796301307210671, 0.3002068887235246, 0.0816498484691956, 0.174684439544512, -0.05021017831176573, 0.2955295321855532, 0.20289721423118928, 0.17279878353524575, -0.17128717624987272, 0.15611553159407407, -0.004766346974487322] |
1,802.08221 | Uncovering Weyl Fermions in the Quantum Limit of NbP | The Fermi surface topology of a Weyl semimetal (WSM) depends strongly on the
position of the chemical potential. If it resides close to the band touching
points (Weyl nodes), as it does in TaAs, separate Fermi surfaces of opposite
chirality emerge, leading to novel phenomena such as the chiral magnetic
effect. If the chemical potential lies too far from the nodes, however, the
chiral Fermi surfaces merge into a single large Fermi surface with no net
chirality. This is realized in the WSM NbP, where the Weyl nodes lie far below
the Fermi energy and where the transport properties in low magnetic fields show
no evidence of chiral Fermi surfaces. Here we show that the behavior of NbP in
high magnetic fields is nonetheless dominated by the presence of the Weyl
nodes. Torque magnetometry up to 60 tesla reveals a change in the slope of
$\tau/B$ at the quantum limit B$^\star$ ($\approx 32\,\rm{T}$), where the
chemical potential enters the $n=0$ Landau level. Numerical simulations show
that this behaviour results from the magnetic field pulling the chemical
potential to the chiral $n=0$ Landau level belonging to the Weyl nodes. These
results show that high magnetic fields can uncover topological singularities in
the underlying band structure of a potential WSM, and can recover topologically
non-trivial experimental properties, even when the position of the chemical
potential precludes their observation in zero magnetic field.
| cond-mat.str-el | the fermi surface topology of a weyl semimetal wsm depends strongly on the position of the chemical potential if it resides close to the band touching points weyl nodes as it does in taas separate fermi surfaces of opposite chirality emerge leading to novel phenomena such as the chiral magnetic effect if the chemical potential lies too far from the nodes however the chiral fermi surfaces merge into a single large fermi surface with no net chirality this is realized in the wsm nbp where the weyl nodes lie far below the fermi energy and where the transport properties in low magnetic fields show no evidence of chiral fermi surfaces here we show that the behavior of nbp in high magnetic fields is nonetheless dominated by the presence of the weyl nodes torque magnetometry up to 60 tesla reveals a change in the slope of taub at the quantum limit bstar approx 32rmt where the chemical potential enters the n0 landau level numerical simulations show that this behaviour results from the magnetic field pulling the chemical potential to the chiral n0 landau level belonging to the weyl nodes these results show that high magnetic fields can uncover topological singularities in the underlying band structure of a potential wsm and can recover topologically nontrivial experimental properties even when the position of the chemical potential precludes their observation in zero magnetic field | [['the', 'fermi', 'surface', 'topology', 'of', 'a', 'weyl', 'semimetal', 'wsm', 'depends', 'strongly', 'on', 'the', 'position', 'of', 'the', 'chemical', 'potential', 'if', 'it', 'resides', 'close', 'to', 'the', 'band', 'touching', 'points', 'weyl', 'nodes', 'as', 'it', 'does', 'in', 'taas', 'separate', 'fermi', 'surfaces', 'of', 'opposite', 'chirality', 'emerge', 'leading', 'to', 'novel', 'phenomena', 'such', 'as', 'the', 'chiral', 'magnetic', 'effect', 'if', 'the', 'chemical', 'potential', 'lies', 'too', 'far', 'from', 'the', 'nodes', 'however', 'the', 'chiral', 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1,802.08222 | Spin-1 Topological Monopoles in Parameter Space of Ultracold Atoms | Magnetic monopole, a hypothetical elementary particle with isolated magnetic
pole, is crucial for the quantization of electric charge. In recent years,
analogues of magnetic monopoles, represented by topological defects in
parameter spaces, have been studied in a wide range of physical systems. These
works mainly focused on Abelian Dirac monopoles in spin-1/2 or non-Abelian Yang
monopoles in spin-3/2 systems. Here we propose to realize three types of spin-1
topological monopoles and study their geometric properties using the parameter
space formed by three hyperfine states of ultracold atoms coupled by
radio-frequency fields. These spin-1 monopoles, characterized by different
monopole charges, possess distinct Berry curvature fields and spin textures,
which are directly measurable in experiments. The topological phase transitions
between different monopoles are accompanied by the emergence of spin "vortex",
and can be intuitively visualized using Majorana's stellar representation. We
show how to determine the Berry curvature, hence the geometric phase and
monopole charge from dynamical effects. Our scheme provides a simple and highly
tunable platform for observing and manipulating spin-1 topological monopoles,
paving the way for exploring new topological quantum matter.
| cond-mat.quant-gas quant-ph | magnetic monopole a hypothetical elementary particle with isolated magnetic pole is crucial for the quantization of electric charge in recent years analogues of magnetic monopoles represented by topological defects in parameter spaces have been studied in a wide range of physical systems these works mainly focused on abelian dirac monopoles in spin12 or nonabelian yang monopoles in spin32 systems here we propose to realize three types of spin1 topological monopoles and study their geometric properties using the parameter space formed by three hyperfine states of ultracold atoms coupled by radiofrequency fields these spin1 monopoles characterized by different monopole charges possess distinct berry curvature fields and spin textures which are directly measurable in experiments the topological phase transitions between different monopoles are accompanied by the emergence of spin vortex and can be intuitively visualized using majoranas stellar representation we show how to determine the berry curvature hence the geometric phase and monopole charge from dynamical effects our scheme provides a simple and highly tunable platform for observing and manipulating spin1 topological monopoles paving the way for exploring new topological quantum matter | [['magnetic', 'monopole', 'a', 'hypothetical', 'elementary', 'particle', 'with', 'isolated', 'magnetic', 'pole', 'is', 'crucial', 'for', 'the', 'quantization', 'of', 'electric', 'charge', 'in', 'recent', 'years', 'analogues', 'of', 'magnetic', 'monopoles', 'represented', 'by', 'topological', 'defects', 'in', 'parameter', 'spaces', 'have', 'been', 'studied', 'in', 'a', 'wide', 'range', 'of', 'physical', 'systems', 'these', 'works', 'mainly', 'focused', 'on', 'abelian', 'dirac', 'monopoles', 'in', 'spin12', 'or', 'nonabelian', 'yang', 'monopoles', 'in', 'spin32', 'systems', 'here', 'we', 'propose', 'to', 'realize', 'three', 'types', 'of', 'spin1', 'topological', 'monopoles', 'and', 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1,802.08223 | Achievable Rate of Private Function Retrieval from MDS Coded Databases | We study the problem of private function retrieval (PFR) in a distributed
storage system. In PFR the user wishes to retrieve a linear combination of $M$
messages stored in non-colluding $(N,K)$ MDS coded databases while revealing no
information about the coefficients of the intended linear combination to any of
the individual databases. We present an achievable scheme for MDS coded PFR
with a rate that matches the capacity for coded private information retrieval
derived recently, $R=(1+R_c+R_c^2+\dots+R_c^{M-1})^{-1}=\frac{1-R_c}{1-R_c^M}$,
where $R_c=\frac{K}{N}$ is the rate of the MDS code. This achievable rate is
tight in some special cases.
| cs.IT math.IT | we study the problem of private function retrieval pfr in a distributed storage system in pfr the user wishes to retrieve a linear combination of m messages stored in noncolluding nk mds coded databases while revealing no information about the coefficients of the intended linear combination to any of the individual databases we present an achievable scheme for mds coded pfr with a rate that matches the capacity for coded private information retrieval derived recently r1r_cr_c2dotsr_cm11frac1r_c1r_cm where r_cfrackn is the rate of the mds code this achievable rate is tight in some special cases | [['we', 'study', 'the', 'problem', 'of', 'private', 'function', 'retrieval', 'pfr', 'in', 'a', 'distributed', 'storage', 'system', 'in', 'pfr', 'the', 'user', 'wishes', 'to', 'retrieve', 'a', 'linear', 'combination', 'of', 'm', 'messages', 'stored', 'in', 'noncolluding', 'nk', 'mds', 'coded', 'databases', 'while', 'revealing', 'no', 'information', 'about', 'the', 'coefficients', 'of', 'the', 'intended', 'linear', 'combination', 'to', 'any', 'of', 'the', 'individual', 'databases', 'we', 'present', 'an', 'achievable', 'scheme', 'for', 'mds', 'coded', 'pfr', 'with', 'a', 'rate', 'that', 'matches', 'the', 'capacity', 'for', 'coded', 'private', 'information', 'retrieval', 'derived', 'recently', 'r1r_cr_c2dotsr_cm11frac1r_c1r_cm', 'where', 'r_cfrackn', 'is', 'the', 'rate', 'of', 'the', 'mds', 'code', 'this', 'achievable', 'rate', 'is', 'tight', 'in', 'some', 'special', 'cases']] | [-0.2485194574730248, -0.01933057112578156, -0.017719790552054412, 0.050527340933710904, -0.03288463056441802, -0.25118675971727655, 0.15089912810008568, 0.3466693666237204, -0.34871694812571385, -0.2674246584875104, 0.1418450856227023, -0.3203000847032577, -0.09580445490428247, 0.17371202980765424, -0.1332002854956638, 0.09160727970605798, 0.008801340087539638, 0.1421599506840879, -0.06494224008486565, -0.36175867089110875, 0.27443035759927664, 0.1558332201118743, 0.2847407234468214, 0.0049133765227768736, 0.0923895568323686, 0.06607955770374721, -0.07672898594350756, -0.04588948495029399, -0.15918131927877688, 0.1414700597980181, 0.3582328042501341, 0.27237783097054646, 0.2198232236146198, -0.3538463098077994, -0.21313653179727818, 0.08419159750717328, 0.13185189730163827, 0.13015566934051964, -0.09227708731676736, -0.1939190600026885, 0.09752719061013879, -0.18357102467637995, 0.015262918546795845, -0.002729056104410278, 0.0008409849201005114, 0.03627669246571199, -0.3644394663709175, 0.01096585816855583, 0.024914441997205595, 0.05900136483124579, -0.052111184062517205, -0.10175790354665167, 0.05181181328067475, 0.19709896039136726, -0.020064272328138188, 0.04561430660744562, 0.05116569307511267, -0.09621968776058487, -0.09360772776721127, 0.3573791763097372, -0.07204194593941793, -0.183966835915192, 0.07683377177707608, -0.09248402883784602, -0.10091507504694164, 0.15086742080166005, 0.23559891406203742, 0.11554221719827341, -0.18384522322119903, 0.06947972405064122, -0.1328860291927729, 0.27961130911970267, 0.08255961497881166, 0.15398930967152727, 0.14281930191361386, 0.11445790885583214, 0.07058501392020844, 0.2074352526207171, -0.06514221743640045, -0.11461007215447076, -0.225397670821226, -0.1635571495204678, -0.240318413823843, -0.025712558392273342, -0.13233072184147718, -0.07219638329242235, 0.30374652757599624, 0.12605928890812007, 0.1330980963944255, 0.08267594459871559, 0.36796456093535473, 0.021055099939036627, 0.09203498483554501, 0.23260800760117886, 0.1444406680748216, 0.07152921830698766, 0.12098129506921396, -0.21362452545081792, 0.10449509204709498, 0.02742831148561495] |
1,802.08224 | Thresholds for vanishing of `Isolated' faces in random \v{C}ech and
Vietoris-Rips complexes | We study combinatorial connectivity for two models of random geometric
complexes. These two models - \v{C}ech and Vietoris-Rips complexes - are built
on a homogeneous Poisson point process of intensity $n$ on a $d$-dimensional
torus using balls of radius $r_n$. In the former, the $k$-simplices/faces are
formed by subsets of $(k+1)$ Poisson points such that the balls of radius $r_n$
centred at these points have a mutual interesection and in the latter, we
require only a pairwise intersection of the balls. Given a (simplicial) complex
(i.e., a collection of $k$-simplices for all $k \geq 1$), we can connect
$k$-simplices via $(k+1)$-simplices (`up-connectivity') or via
$(k-1)$-simplices (`down-connectivity). Our interest is to understand these two
combinatorial notions of connectivity for the random \v{C}ech and Vietoris-Rips
complexes asymptically as $n \to \infty$. In particular, we analyse in detail
the threshold radius for vanishing of isolated $k$-faces for up and down
connectivity of both types of random geometric complexes. Though it is expected
that the threshold radius $r_n = \Theta((\frac{\log n}{n})^{1/d})$ in coarse
scale, our results give tighter bounds on the constants in the logarithmic
scale as well as shed light on the possible second-order correction factors.
Further, they also reveal interesting differences between the phase transition
in the \v{C}ech and Vietoris-Rips cases. The analysis is interesting due to the
non-monotonicity of the number of isolated $k$-faces (as a function of the
radius) and leads one to consider `monotonic' vanishing of isolated $k$-faces.
The latter coincides with the vanishing threshold mentioned above at a coarse
scale (i.e., $\log n$ scale) but differs in the $\log \log n$ scale for the
\v{C}ech complex with $k = 1$ in the up-connected case.
| math.PR math.CO | we study combinatorial connectivity for two models of random geometric complexes these two models vcech and vietorisrips complexes are built on a homogeneous poisson point process of intensity n on a ddimensional torus using balls of radius r_n in the former the ksimplicesfaces are formed by subsets of k1 poisson points such that the balls of radius r_n centred at these points have a mutual interesection and in the latter we require only a pairwise intersection of the balls given a simplicial complex ie a collection of ksimplices for all k geq 1 we can connect ksimplices via k1simplices upconnectivity or via k1simplices downconnectivity our interest is to understand these two combinatorial notions of connectivity for the random vcech and vietorisrips complexes asymptically as n to infty in particular we analyse in detail the threshold radius for vanishing of isolated kfaces for up and down connectivity of both types of random geometric complexes though it is expected that the threshold radius r_n thetafraclog nn1d in coarse scale our results give tighter bounds on the constants in the logarithmic scale as well as shed light on the possible secondorder correction factors further they also reveal interesting differences between the phase transition in the vcech and vietorisrips cases the analysis is interesting due to the nonmonotonicity of the number of isolated kfaces as a function of the radius and leads one to consider monotonic vanishing of isolated kfaces the latter coincides with the vanishing threshold mentioned above at a coarse scale ie log n scale but differs in the log log n scale for the vcech complex with k 1 in the upconnected case | [['we', 'study', 'combinatorial', 'connectivity', 'for', 'two', 'models', 'of', 'random', 'geometric', 'complexes', 'these', 'two', 'models', 'vcech', 'and', 'vietorisrips', 'complexes', 'are', 'built', 'on', 'a', 'homogeneous', 'poisson', 'point', 'process', 'of', 'intensity', 'n', 'on', 'a', 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1,802.08225 | How does relativistic kinetic theory remember about initial conditions? | Understanding hydrodynamization in microscopic models of heavy-ion collisions
has been an important topic in current research. Many lessons obtained within
the strongly-coupled (holographic) models originate from the properties of
transient excitations of equilibrium encapsulated by short-lived quasinormal
modes of black holes. This paper aims to develop similar intuition for
expanding plasma systems described by a simple model from the weakly-coupled
domain, the Boltzmann equation in the relaxation time approximation. We show
that in this kinetic theory setup there are infinitely many transient modes
carrying information about the initial distribution function. They all have the
same exponential damping set by the relaxation time but are distinguished by
different power-law suppressions and different frequencies of oscillations,
logarithmic in proper time. We also analyze the resurgent interplay between the
hydrodynamics and transients in this setup.
| nucl-th hep-ph hep-th | understanding hydrodynamization in microscopic models of heavyion collisions has been an important topic in current research many lessons obtained within the stronglycoupled holographic models originate from the properties of transient excitations of equilibrium encapsulated by shortlived quasinormal modes of black holes this paper aims to develop similar intuition for expanding plasma systems described by a simple model from the weaklycoupled domain the boltzmann equation in the relaxation time approximation we show that in this kinetic theory setup there are infinitely many transient modes carrying information about the initial distribution function they all have the same exponential damping set by the relaxation time but are distinguished by different powerlaw suppressions and different frequencies of oscillations logarithmic in proper time we also analyze the resurgent interplay between the hydrodynamics and transients in this setup | [['understanding', 'hydrodynamization', 'in', 'microscopic', 'models', 'of', 'heavyion', 'collisions', 'has', 'been', 'an', 'important', 'topic', 'in', 'current', 'research', 'many', 'lessons', 'obtained', 'within', 'the', 'stronglycoupled', 'holographic', 'models', 'originate', 'from', 'the', 'properties', 'of', 'transient', 'excitations', 'of', 'equilibrium', 'encapsulated', 'by', 'shortlived', 'quasinormal', 'modes', 'of', 'black', 'holes', 'this', 'paper', 'aims', 'to', 'develop', 'similar', 'intuition', 'for', 'expanding', 'plasma', 'systems', 'described', 'by', 'a', 'simple', 'model', 'from', 'the', 'weaklycoupled', 'domain', 'the', 'boltzmann', 'equation', 'in', 'the', 'relaxation', 'time', 'approximation', 'we', 'show', 'that', 'in', 'this', 'kinetic', 'theory', 'setup', 'there', 'are', 'infinitely', 'many', 'transient', 'modes', 'carrying', 'information', 'about', 'the', 'initial', 'distribution', 'function', 'they', 'all', 'have', 'the', 'same', 'exponential', 'damping', 'set', 'by', 'the', 'relaxation', 'time', 'but', 'are', 'distinguished', 'by', 'different', 'powerlaw', 'suppressions', 'and', 'different', 'frequencies', 'of', 'oscillations', 'logarithmic', 'in', 'proper', 'time', 'we', 'also', 'analyze', 'the', 'resurgent', 'interplay', 'between', 'the', 'hydrodynamics', 'and', 'transients', 'in', 'this', 'setup']] | [-0.12632722950498151, 0.19176875718502825, -0.1480415042517989, 0.09845531727346084, -0.034931911258326814, -0.12428584763653237, -0.01535666215645368, 0.3395911339656309, -0.26493161355117056, -0.27882303769178124, 0.04624283386113926, -0.28794557596627396, -0.10913545943119309, 0.17287312963250742, 0.014074516424443573, 0.05668922880608024, 0.051151297093989946, -0.013815461234612898, -0.04385101036997653, -0.18372279639130062, 0.29492609901353717, 0.06380087911560567, 0.2866979113561242, 0.025416934922704415, 0.06744880127635869, -0.03175674353472211, -0.004118524953920507, 0.022120322659964477, -0.1599153180774341, 0.047905737070488445, 0.27057178198099957, 0.0990848009735628, 0.2622900372706213, -0.49791046819000534, -0.2654756495841976, 0.06268649808639153, 0.18681738968007267, 0.14345282190410988, -0.06032538350590392, -0.2322229236173867, 0.02243561419362033, -0.1851464087094152, -0.14860273672225463, -0.0780108652014116, 0.0357638883870095, 0.019582880126439373, -0.18761202928991141, 0.11930228167043286, 0.07298144475895572, 0.02696865454852355, -0.08050662157245714, -0.08321610228581862, 0.014553455447171335, 0.09434660620437088, 0.1195459106423765, 0.0026423532902051443, 0.12336518766471383, -0.1579718687280547, -0.12768855664145315, 0.3464261055782889, -0.06493300513300876, -0.14760069785794863, 0.22052020286774318, -0.20055413075412312, -0.12674756976775825, 0.1373240840780041, 0.17401938372032336, 0.14188268853026922, -0.21249152083372325, 0.08388158391062461, -0.02334950554932496, 0.1284534289064168, 0.07987339752479315, 0.08392667808838075, 0.27266066528461647, 0.16736175082923815, -0.052067153655860406, 0.1333249677717862, 0.002695038663329218, -0.11743802506349642, -0.3202720950357616, -0.06316256317112481, -0.17252527859002867, 0.07864203839915607, -0.08250536462164194, -0.13368425540146278, 0.41257481803327345, 0.14077971777243709, 0.18891874437262726, -0.0036204029597821786, 0.2533957437295116, 0.1176065640043596, 0.02764202832159671, 0.11045470704591549, 0.26426623849362263, 0.1042828220030942, 0.13894777372126665, -0.2610082419511552, 0.028036718634239427, 0.06073556535976064] |
1,802.08226 | Generating, from scratch, the near-field asymptotic forms of scalar
resistance functions for two unequal rigid spheres in low Reynolds number
flow | The motion of rigid spherical particles suspended in a low Reynolds number
fluid can be related to the forces, torques and stresslets acting upon them by
22 scalar resistance functions, commonly notated $X^A_{11}$, $X^A_{12}$,
$Y^A_{11}$, etc. Near-field asymptotic forms of these resistance functions were
derived in Jeffrey and Onishi (J. Fluid Mech., 1984) and Jeffrey (Phys. Fluids
A, 1992); these forms are now used in several numerical methods for suspension
mechanics. However, the first of these important papers contains a number of
small errors which make it difficult for the reader to correctly evaluate the
functions for parameters not explicitly tabulated. This short article
comprehensively corrects these errors, and adds formulae that were originally
omitted from both papers, so that the reader can verify and implement the
equations independently. The corrected expressions, rationalised and using
contemporary nondimensionalisation, are shown to match mid-field values of
these scalars which are calculated through an alternative method. A Python
script to generate and evaluate these functions is provided.
| physics.flu-dyn | the motion of rigid spherical particles suspended in a low reynolds number fluid can be related to the forces torques and stresslets acting upon them by 22 scalar resistance functions commonly notated xa_11 xa_12 ya_11 etc nearfield asymptotic forms of these resistance functions were derived in jeffrey and onishi j fluid mech 1984 and jeffrey phys fluids a 1992 these forms are now used in several numerical methods for suspension mechanics however the first of these important papers contains a number of small errors which make it difficult for the reader to correctly evaluate the functions for parameters not explicitly tabulated this short article comprehensively corrects these errors and adds formulae that were originally omitted from both papers so that the reader can verify and implement the equations independently the corrected expressions rationalised and using contemporary nondimensionalisation are shown to match midfield values of these scalars which are calculated through an alternative method a python script to generate and evaluate these functions is provided | [['the', 'motion', 'of', 'rigid', 'spherical', 'particles', 'suspended', 'in', 'a', 'low', 'reynolds', 'number', 'fluid', 'can', 'be', 'related', 'to', 'the', 'forces', 'torques', 'and', 'stresslets', 'acting', 'upon', 'them', 'by', '22', 'scalar', 'resistance', 'functions', 'commonly', 'notated', 'xa_11', 'xa_12', 'ya_11', 'etc', 'nearfield', 'asymptotic', 'forms', 'of', 'these', 'resistance', 'functions', 'were', 'derived', 'in', 'jeffrey', 'and', 'onishi', 'j', 'fluid', 'mech', '1984', 'and', 'jeffrey', 'phys', 'fluids', 'a', '1992', 'these', 'forms', 'are', 'now', 'used', 'in', 'several', 'numerical', 'methods', 'for', 'suspension', 'mechanics', 'however', 'the', 'first', 'of', 'these', 'important', 'papers', 'contains', 'a', 'number', 'of', 'small', 'errors', 'which', 'make', 'it', 'difficult', 'for', 'the', 'reader', 'to', 'correctly', 'evaluate', 'the', 'functions', 'for', 'parameters', 'not', 'explicitly', 'tabulated', 'this', 'short', 'article', 'comprehensively', 'corrects', 'these', 'errors', 'and', 'adds', 'formulae', 'that', 'were', 'originally', 'omitted', 'from', 'both', 'papers', 'so', 'that', 'the', 'reader', 'can', 'verify', 'and', 'implement', 'the', 'equations', 'independently', 'the', 'corrected', 'expressions', 'rationalised', 'and', 'using', 'contemporary', 'nondimensionalisation', 'are', 'shown', 'to', 'match', 'midfield', 'values', 'of', 'these', 'scalars', 'which', 'are', 'calculated', 'through', 'an', 'alternative', 'method', 'a', 'python', 'script', 'to', 'generate', 'and', 'evaluate', 'these', 'functions', 'is', 'provided']] | [-0.07807323871316353, 0.11293296857807686, -0.07675259511032784, 0.062157120561423876, -0.08774609012697007, -0.14313626818370467, -0.011172218977109245, 0.34136219731653517, -0.22387808269202153, -0.34437382156434265, 0.061922428569097, -0.2642495242982918, -0.177055563690916, 0.22951381972857884, -0.09629363470359399, 0.08339116450622229, 0.026484191352617203, -0.01824615746071296, -0.019845201645439826, -0.2695575169119868, 0.2418323682522783, 0.05304525995638615, 0.23222766029276098, 0.04666565869130796, 0.08805872113675295, -0.0274944737062266, -0.08663417346578856, 0.045408293593281544, -0.179660030814652, 0.0856797020768122, 0.26292222309481605, 0.05069290234863481, 0.22469903414733478, -0.4452594861920391, -0.1754878647538677, 0.037659163450856944, 0.11538947048027254, 0.12724139765252052, 0.01746732405707188, -0.2676383513286247, 0.07298031925969983, -0.1929742640509091, -0.10080329489876858, -0.13413588757054035, 0.07085004536527562, 0.07068899075640944, -0.24328136263322664, 0.08325002377604059, 0.03780654578336647, 0.06017667517031294, -0.04163074785531123, -0.16090419599139247, -0.019132190128001644, 0.14291785992334904, 0.0662939005809032, 0.01480703378133823, 0.1399651656291731, -0.09374588411252567, -0.07143653523262232, 0.35814644285240527, -0.02436025058908492, -0.2541354243117182, 0.20233574525383735, -0.06978199485492725, -0.09255106574624361, 0.12405269315339024, 0.14548789234058238, 0.12719662377924618, -0.19110510306814626, 0.05698987844661139, -0.03261747442602371, 0.14216029637649377, 0.1356041730954225, -0.056999744587109324, 0.18545400525981226, 0.025035187862350705, -0.07128276439276611, 0.11869428365387208, -0.04381703690449296, -0.07935910924303097, -0.3154697184919478, -0.16702670197187697, -0.16948517516287195, 0.016461281126212497, -0.03277728850571858, -0.16309910219054966, 0.3385317142118601, 0.1666658570561905, 0.15941906080187895, 0.036608711545939865, 0.2855314410447797, 0.08937434971864734, 0.06368416338227689, 0.10760677505215133, 0.24983486753847936, 0.15355675406204478, 0.10478155291377153, -0.1447026832130454, 0.04689561055614526, 0.09391265523801443] |
1,802.08227 | Quantum linear systems algorithms: a primer | The Harrow-Hassidim-Lloyd (HHL) quantum algorithm for sampling from the
solution of a linear system provides an exponential speed-up over its classical
counterpart. The problem of solving a system of linear equations has a wide
scope of applications, and thus HHL constitutes an important algorithmic
primitive. In these notes, we present the HHL algorithm and its improved
versions in detail, including explanations of the constituent sub- routines.
More specifically, we discuss various quantum subroutines such as quantum phase
estimation and amplitude amplification, as well as the important question of
loading data into a quantum computer, via quantum RAM. The improvements to the
original algorithm exploit variable-time amplitude amplification as well as a
method for implementing linear combinations of unitary operations (LCUs) based
on a decomposition of the operators using Fourier and Chebyshev series.
Finally, we discuss a linear solver based on the quantum singular value
estimation (QSVE) subroutine.
| quant-ph cs.DS math.NA | the harrowhassidimlloyd hhl quantum algorithm for sampling from the solution of a linear system provides an exponential speedup over its classical counterpart the problem of solving a system of linear equations has a wide scope of applications and thus hhl constitutes an important algorithmic primitive in these notes we present the hhl algorithm and its improved versions in detail including explanations of the constituent sub routines more specifically we discuss various quantum subroutines such as quantum phase estimation and amplitude amplification as well as the important question of loading data into a quantum computer via quantum ram the improvements to the original algorithm exploit variabletime amplitude amplification as well as a method for implementing linear combinations of unitary operations lcus based on a decomposition of the operators using fourier and chebyshev series finally we discuss a linear solver based on the quantum singular value estimation qsve subroutine | [['the', 'harrowhassidimlloyd', 'hhl', 'quantum', 'algorithm', 'for', 'sampling', 'from', 'the', 'solution', 'of', 'a', 'linear', 'system', 'provides', 'an', 'exponential', 'speedup', 'over', 'its', 'classical', 'counterpart', 'the', 'problem', 'of', 'solving', 'a', 'system', 'of', 'linear', 'equations', 'has', 'a', 'wide', 'scope', 'of', 'applications', 'and', 'thus', 'hhl', 'constitutes', 'an', 'important', 'algorithmic', 'primitive', 'in', 'these', 'notes', 'we', 'present', 'the', 'hhl', 'algorithm', 'and', 'its', 'improved', 'versions', 'in', 'detail', 'including', 'explanations', 'of', 'the', 'constituent', 'sub', 'routines', 'more', 'specifically', 'we', 'discuss', 'various', 'quantum', 'subroutines', 'such', 'as', 'quantum', 'phase', 'estimation', 'and', 'amplitude', 'amplification', 'as', 'well', 'as', 'the', 'important', 'question', 'of', 'loading', 'data', 'into', 'a', 'quantum', 'computer', 'via', 'quantum', 'ram', 'the', 'improvements', 'to', 'the', 'original', 'algorithm', 'exploit', 'variabletime', 'amplitude', 'amplification', 'as', 'well', 'as', 'a', 'method', 'for', 'implementing', 'linear', 'combinations', 'of', 'unitary', 'operations', 'lcus', 'based', 'on', 'a', 'decomposition', 'of', 'the', 'operators', 'using', 'fourier', 'and', 'chebyshev', 'series', 'finally', 'we', 'discuss', 'a', 'linear', 'solver', 'based', 'on', 'the', 'quantum', 'singular', 'value', 'estimation', 'qsve', 'subroutine']] | [-0.10467736921608066, 0.034236717961404844, -0.1128573788247033, 0.051744658016752806, -0.06603187945837231, -0.13901232108027253, 0.0457343887075246, 0.33120171732766784, -0.30186852048572205, -0.28595159109681845, 0.16773098866113983, -0.21110995361032858, -0.18964227393894673, 0.2871217705653853, -0.028547501859688903, 0.1521091876887997, 0.05295317279683643, 0.02011787345033292, -0.1214540273809091, -0.24837967647599976, 0.24876294321099884, 0.0640231458301184, 0.22804339095784273, 0.005180633344610975, 0.14782337692633193, 0.048933949042430584, -0.024087989254701524, -0.006508329991659481, -0.08355118207512297, 0.1074796183766759, 0.2545871694447881, 0.16592054004934043, 0.29957324588330053, -0.41448658934398874, -0.1663669099017008, 0.06641985644101586, 0.15316529302779675, 0.15145385069517445, -0.047219873588290606, -0.2632841751675523, 0.05457431360702859, -0.1705490138273278, -0.0802579919316436, -0.11337103109092336, -0.007920235194495483, -0.0028554033392351377, -0.25672687711321734, 0.05072770011611283, 0.0795510755070447, 0.06220949552506719, -0.025295890479393252, -0.13776500645246714, 0.09223108926440321, 0.0816606893746361, -0.04284385596051149, 0.005486231720655493, 0.12649565361909032, -0.14655638994706463, -0.19196196625484407, 0.41313562185777836, -0.07070786065034479, -0.18186103155810948, 0.14474668475952357, -0.030735349419769156, -0.12755381396958884, 0.06533503272468606, 0.20263738003368043, 0.1066959774383178, -0.0947061897724331, 0.1296299909965505, -0.027491716804857562, 0.164723174219109, 0.05398382089572818, 0.07783635715915732, 0.1529733456865795, 0.1513675519696609, 0.08295033943093037, 0.19500644635472905, -0.062175335018091825, -0.1419140986973828, -0.29858322709492624, -0.1856629760738156, -0.16821595346746482, 0.03290837756294298, -0.12430830169046514, -0.19950352698542204, 0.416898182759138, 0.15366010315044884, 0.16798235026940908, 0.03738939230113405, 0.337467337524748, 0.1580490859198282, 0.05387622567191911, 0.08102682240446671, 0.16807568797918215, 0.17324352347170807, 0.08328972605283512, -0.22218888259830896, 0.027605014583670012, 0.10113327409625564] |
1,802.08228 | Energy Transfer and Spectra in Simulations of Two-dimensional
Compressible Turbulence | We present results of high-resolution numerical simulations of compressible
2D turbulence forced at intermediate spatial scales with a solenoidal
white-in-time external acceleration. A case with an isothermal equation of
state, low energy injection rate, and turbulent Mach number $M\approx0.34$
without energy condensate is studied in detail. Analysis of energy spectra and
fluxes shows that the classical dual-cascade picture familiar from the
incompressible case is substantially modified by compressibility effects. While
the small-scale direct enstrophy cascade remains largely intact, a large-scale
energy flux loop forms with the direct acoustic energy cascade compensating for
the inverse transfer of solenoidal kinetic energy. At small scales, the direct
enstrophy and acoustic energy cascades are fully decoupled at small Mach
numbers and hence the corresponding spectral energy slopes comply with
theoretical predictions, as expected. At large scales, dispersion of acoustic
waves on vortices softens the dilatational velocity spectrum, while the
pseudo-sound component of the potential energy associated with coherent
vortices steepens the potential energy spectrum.
| astro-ph.GA nlin.AO physics.comp-ph physics.flu-dyn | we present results of highresolution numerical simulations of compressible 2d turbulence forced at intermediate spatial scales with a solenoidal whiteintime external acceleration a case with an isothermal equation of state low energy injection rate and turbulent mach number mapprox034 without energy condensate is studied in detail analysis of energy spectra and fluxes shows that the classical dualcascade picture familiar from the incompressible case is substantially modified by compressibility effects while the smallscale direct enstrophy cascade remains largely intact a largescale energy flux loop forms with the direct acoustic energy cascade compensating for the inverse transfer of solenoidal kinetic energy at small scales the direct enstrophy and acoustic energy cascades are fully decoupled at small mach numbers and hence the corresponding spectral energy slopes comply with theoretical predictions as expected at large scales dispersion of acoustic waves on vortices softens the dilatational velocity spectrum while the pseudosound component of the potential energy associated with coherent vortices steepens the potential energy spectrum | [['we', 'present', 'results', 'of', 'highresolution', 'numerical', 'simulations', 'of', 'compressible', '2d', 'turbulence', 'forced', 'at', 'intermediate', 'spatial', 'scales', 'with', 'a', 'solenoidal', 'whiteintime', 'external', 'acceleration', 'a', 'case', 'with', 'an', 'isothermal', 'equation', 'of', 'state', 'low', 'energy', 'injection', 'rate', 'and', 'turbulent', 'mach', 'number', 'mapprox034', 'without', 'energy', 'condensate', 'is', 'studied', 'in', 'detail', 'analysis', 'of', 'energy', 'spectra', 'and', 'fluxes', 'shows', 'that', 'the', 'classical', 'dualcascade', 'picture', 'familiar', 'from', 'the', 'incompressible', 'case', 'is', 'substantially', 'modified', 'by', 'compressibility', 'effects', 'while', 'the', 'smallscale', 'direct', 'enstrophy', 'cascade', 'remains', 'largely', 'intact', 'a', 'largescale', 'energy', 'flux', 'loop', 'forms', 'with', 'the', 'direct', 'acoustic', 'energy', 'cascade', 'compensating', 'for', 'the', 'inverse', 'transfer', 'of', 'solenoidal', 'kinetic', 'energy', 'at', 'small', 'scales', 'the', 'direct', 'enstrophy', 'and', 'acoustic', 'energy', 'cascades', 'are', 'fully', 'decoupled', 'at', 'small', 'mach', 'numbers', 'and', 'hence', 'the', 'corresponding', 'spectral', 'energy', 'slopes', 'comply', 'with', 'theoretical', 'predictions', 'as', 'expected', 'at', 'large', 'scales', 'dispersion', 'of', 'acoustic', 'waves', 'on', 'vortices', 'softens', 'the', 'dilatational', 'velocity', 'spectrum', 'while', 'the', 'pseudosound', 'component', 'of', 'the', 'potential', 'energy', 'associated', 'with', 'coherent', 'vortices', 'steepens', 'the', 'potential', 'energy', 'spectrum']] | [-0.1694972765870699, 0.23102208686547865, -0.04878880676542279, 0.09521115767103443, -0.047363271988350664, -0.06529518368335653, -0.04457219955481919, 0.2991570981832433, -0.29800856102823836, -0.33017760593019707, 0.02736992191794458, -0.2684196409326536, 0.007888522329209726, 0.2064623818850687, 0.0836317046586707, 0.06350240055243249, 0.07639017471891851, -0.0074232743428194825, -0.02029775947632999, -0.08672925463989613, 0.3397740087754836, 0.17894453078484798, 0.3336243734907217, 0.0361720503011683, 0.09332182426653991, -0.08006980843676985, -0.038622895149584814, 0.036294628482141024, -0.16076249990169633, 0.01748295639615058, 0.1888106877332011, -0.040420889472028924, 0.24145469140214257, -0.4631345353171795, -0.2862720239931081, 0.06861214959239469, 0.16400845003438835, 0.09048536543946571, -0.05862797040468718, -0.2121742752032897, 0.058478372124365616, -0.1576002351556539, -0.15481115489479014, -0.037296138188059005, -0.002201515488633061, 0.06898158077737081, -0.2507610372208719, 0.23976595620948915, 0.02434301584564102, 0.047980953028751244, -0.1327688353271754, -0.09833899960864949, -0.11564666181478556, 0.039693704235243696, 0.09419011892279304, -0.00709290553143696, 0.14731610955705843, -0.1934199942146204, -0.024000621990218192, 0.36973941949773814, -0.06385309298528664, -0.1632392607641088, 0.20526545243986138, -0.13265100581743872, -0.0440365964947622, 0.2423872137913787, 0.1528558943927571, 0.030241864037853252, -0.027085703830057872, 0.06322363082373285, -0.004786203278647146, 0.18304884609400848, 0.05820207804429663, 0.018902286648443792, 0.2345661668083336, 0.15262815484164072, 0.04782390459646954, 0.08829336727916298, -0.15870302167457317, -0.07939656340528893, -0.30588849603280993, -0.09854839219346265, -0.18877049519376876, 0.07404721083629381, -0.08664812158208925, -0.1310965065885618, 0.3839983126661398, 0.08122557044564156, 0.1779057889752373, 0.07744655245178249, 0.38363994893771186, 0.17133477871833794, 0.03876611024223834, 0.13966715571623814, 0.2788749725994053, 0.15586397217003087, 0.2012364987955912, -0.2594949485412858, -0.06333531451977412, 0.05938769151055832] |
1,802.08229 | A Better (Bayesian) Interval Estimate for Within-Subject Designs | We develop a Bayesian highest-density interval (HDI) for use in
within-subject designs. This credible interval is based on a standard
noninformative prior and a modified posterior distribution that conditions on
both the data and point estimates of the subject-specific random effects.
Conditioning on the estimated random effects removes between-subject variance
and produces intervals that are the Bayesian analogue of the within-subject
confidence interval proposed in Loftus and Masson (1994). We show that the
latter interval can also be derived as a Bayesian within-subject HDI under a
certain improper prior. We argue that the proposed new interval is superior to
the original within-subject confidence interval, on the grounds of (a) it being
based on a more sensible prior, (b) it having a clear and intuitively appealing
interpretation, and (c) because its length is always smaller. A generalization
of the new interval that can be applied to heteroscedastic data is also
derived, and we show that the resulting interval is numerically equivalent to
the normalization method discussed in Franz and Loftus (2012); however, our
work provides a Bayesian formulation for the normalization method, and in doing
so we identify the associated prior distribution.
| stat.ME | we develop a bayesian highestdensity interval hdi for use in withinsubject designs this credible interval is based on a standard noninformative prior and a modified posterior distribution that conditions on both the data and point estimates of the subjectspecific random effects conditioning on the estimated random effects removes betweensubject variance and produces intervals that are the bayesian analogue of the withinsubject confidence interval proposed in loftus and masson 1994 we show that the latter interval can also be derived as a bayesian withinsubject hdi under a certain improper prior we argue that the proposed new interval is superior to the original withinsubject confidence interval on the grounds of a it being based on a more sensible prior b it having a clear and intuitively appealing interpretation and c because its length is always smaller a generalization of the new interval that can be applied to heteroscedastic data is also derived and we show that the resulting interval is numerically equivalent to the normalization method discussed in franz and loftus 2012 however our work provides a bayesian formulation for the normalization method and in doing so we identify the associated prior distribution | [['we', 'develop', 'a', 'bayesian', 'highestdensity', 'interval', 'hdi', 'for', 'use', 'in', 'withinsubject', 'designs', 'this', 'credible', 'interval', 'is', 'based', 'on', 'a', 'standard', 'noninformative', 'prior', 'and', 'a', 'modified', 'posterior', 'distribution', 'that', 'conditions', 'on', 'both', 'the', 'data', 'and', 'point', 'estimates', 'of', 'the', 'subjectspecific', 'random', 'effects', 'conditioning', 'on', 'the', 'estimated', 'random', 'effects', 'removes', 'betweensubject', 'variance', 'and', 'produces', 'intervals', 'that', 'are', 'the', 'bayesian', 'analogue', 'of', 'the', 'withinsubject', 'confidence', 'interval', 'proposed', 'in', 'loftus', 'and', 'masson', '1994', 'we', 'show', 'that', 'the', 'latter', 'interval', 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1,802.0823 | Mitigating Foreground Biases in CMB Lensing Reconstruction Using Cleaned
Gradients | Reconstructed maps of the lensing convergence of the cosmic microwave
background (CMB) will play a major role in precision cosmology in coming years.
CMB lensing maps will enable calibration of the masses of high-redshift galaxy
clusters and will yield precise measurements of the growth of cosmic structure
through cross-correlations with galaxy surveys. During the next decade, CMB
lensing reconstruction will rely heavily on temperature data, rather than
polarization, thus necessitating a detailed understanding of biases due to
extragalactic foregrounds. In the near term, the most significant bias among
these is that due to the thermal Sunyaev-Zel'dovich (tSZ) effect. Moreover,
high-resolution observations will be available at only a few frequencies,
making full foreground cleaning challenging. In this paper, we demonstrate a
solution to the foreground bias problem that involves cleaning only the
large-scale gradients of the CMB temperature map. We show that the data
necessary for tSZ-bias-free CMB lensing maps already exist in the form of
large-scale measurements of the CMB across multiple frequencies by the Planck
and WMAP satellite experiments. Specifically, we show that the bias to halo
masses inferred from CMB lensing is eliminated by the utilization of clean
gradients obtained from multi-frequency component separation involving Planck
and WMAP data, and that special lensing maps for galaxy cross-correlations can
be prepared with only a small penalty in signal-to-noise while requiring no
masking, in-painting, modeling, or simulation effort for the tSZ bias. While we
focus on cross-correlations, we also show that gradient cleaning can mitigate
biases to the CMB lensing autospectrum that arise from the presence of
foregrounds in temperature and polarization with minimal loss of
signal-to-noise.
| astro-ph.CO | reconstructed maps of the lensing convergence of the cosmic microwave background cmb will play a major role in precision cosmology in coming years cmb lensing maps will enable calibration of the masses of highredshift galaxy clusters and will yield precise measurements of the growth of cosmic structure through crosscorrelations with galaxy surveys during the next decade cmb lensing reconstruction will rely heavily on temperature data rather than polarization thus necessitating a detailed understanding of biases due to extragalactic foregrounds in the near term the most significant bias among these is that due to the thermal sunyaevzeldovich tsz effect moreover highresolution observations will be available at only a few frequencies making full foreground cleaning challenging in this paper we demonstrate a solution to the foreground bias problem that involves cleaning only the largescale gradients of the cmb temperature map we show that the data necessary for tszbiasfree cmb lensing maps already exist in the form of largescale measurements of the cmb across multiple frequencies by the planck and wmap satellite experiments specifically we show that the bias to halo masses inferred from cmb lensing is eliminated by the utilization of clean gradients obtained from multifrequency component separation involving planck and wmap data and that special lensing maps for galaxy crosscorrelations can be prepared with only a small penalty in signaltonoise while requiring no masking inpainting modeling or simulation effort for the tsz bias while we focus on crosscorrelations we also show that gradient cleaning can mitigate biases to the cmb lensing autospectrum that arise from the presence of foregrounds in temperature and polarization with minimal loss of signaltonoise | [['reconstructed', 'maps', 'of', 'the', 'lensing', 'convergence', 'of', 'the', 'cosmic', 'microwave', 'background', 'cmb', 'will', 'play', 'a', 'major', 'role', 'in', 'precision', 'cosmology', 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1,802.08231 | Proper holomorphic mappings onto symmetric products of a Riemann surface | We show that the structure of proper holomorphic maps between the $n$-fold
symmetric products, $n\geq 2$, of a pair of non-compact Riemann surfaces $X$
and $Y$, provided these are reasonably nice, is very rigid. Specifically, any
such map is determined by a proper holomorphic map of $X$ onto $Y$. This
extends existing results concerning bounded planar domains, and is a
non-compact analogue of a phenomenon observed in symmetric products of compact
Riemann surfaces. Along the way, we also provide a condition for the complete
hyperbolicity of all $n$-fold symmetric products of a non-compact Riemann
surface.
| math.CV math.AG | we show that the structure of proper holomorphic maps between the nfold symmetric products ngeq 2 of a pair of noncompact riemann surfaces x and y provided these are reasonably nice is very rigid specifically any such map is determined by a proper holomorphic map of x onto y this extends existing results concerning bounded planar domains and is a noncompact analogue of a phenomenon observed in symmetric products of compact riemann surfaces along the way we also provide a condition for the complete hyperbolicity of all nfold symmetric products of a noncompact riemann surface | [['we', 'show', 'that', 'the', 'structure', 'of', 'proper', 'holomorphic', 'maps', 'between', 'the', 'nfold', 'symmetric', 'products', 'ngeq', '2', 'of', 'a', 'pair', 'of', 'noncompact', 'riemann', 'surfaces', 'x', 'and', 'y', 'provided', 'these', 'are', 'reasonably', 'nice', 'is', 'very', 'rigid', 'specifically', 'any', 'such', 'map', 'is', 'determined', 'by', 'a', 'proper', 'holomorphic', 'map', 'of', 'x', 'onto', 'y', 'this', 'extends', 'existing', 'results', 'concerning', 'bounded', 'planar', 'domains', 'and', 'is', 'a', 'noncompact', 'analogue', 'of', 'a', 'phenomenon', 'observed', 'in', 'symmetric', 'products', 'of', 'compact', 'riemann', 'surfaces', 'along', 'the', 'way', 'we', 'also', 'provide', 'a', 'condition', 'for', 'the', 'complete', 'hyperbolicity', 'of', 'all', 'nfold', 'symmetric', 'products', 'of', 'a', 'noncompact', 'riemann', 'surface']] | [-0.2099126527674104, 0.08878949504639758, -0.08587080453963657, 0.06669816123076568, -0.09208432104389526, -0.1023070573218559, -0.014957194206746, 0.4032654322781845, -0.2700102537674339, -0.1700372857384776, 0.12948781683134208, -0.24269777244251026, -0.15708595047165688, 0.21724983142002632, -0.10299016574005547, 0.009764294796868375, 0.06699932908737345, 0.053404264681739734, -0.16903392257610042, -0.24180777343847837, 0.4292421625632989, -0.10288828808023888, 0.20606668212107923, 0.10309296022904546, 0.14187227884601605, -0.004201898571888083, -0.0357758356503358, 0.019838966968420305, -0.1413745886919634, 0.15299941008714468, 0.25228974128043963, 0.06629024369544105, 0.15608501963954616, -0.3799109635580527, -0.19746014405360543, 0.191100981370791, 0.06451417230755875, -0.014345453439378425, -0.059935509609548666, -0.27439995368844583, 0.10538616011801519, -0.12495180732129436, -0.21621175298075143, -0.06086451951414347, 0.06052312336273884, 0.029574611028166192, -0.2381618519050167, 0.02095841607293359, 0.1778112036421111, 0.05846352585052189, -0.0685469601756746, -0.08325795071493639, -0.1440127804630289, 0.10153426451020335, -0.016576394455899535, 0.11438039856913843, 0.06376371398372085, -0.05804678206577113, -0.07312284728242574, 0.3571471522513189, -0.10142506095335672, -0.27780566197516715, 0.14097523652017116, -0.18905077241851312, -0.15608026529907396, 0.16101487435302453, 0.1109557203703413, 0.2071022159174869, -0.06604771595999696, 0.19495587897805594, -0.13772310470475962, 0.06979663609404509, 0.11777338575277674, -0.04731949896698719, 0.19373306781543712, 0.10303120531729962, 0.1169775388840782, 0.14984488826196052, -0.02323902615983235, -0.04181505859780468, -0.3755730996398549, -0.21403704054261508, -0.1403770558290968, 0.16816097543035682, -0.12221835807523396, -0.20485424044492997, 0.35249662942400106, -0.05216805746374456, 0.21871511228872756, 0.1101367570925504, 0.2191010125569607, 0.016381909352678217, 0.02990416683697779, 0.05119039771686259, 0.11880322794773077, 0.2093411875374027, -0.02673713419782488, -0.0866212790758398, -0.016407726656057334, 0.12794426363987824] |
1,802.08232 | The Secret Sharer: Evaluating and Testing Unintended Memorization in
Neural Networks | This paper describes a testing methodology for quantitatively assessing the
risk that rare or unique training-data sequences are unintentionally memorized
by generative sequence models---a common type of machine-learning model.
Because such models are sometimes trained on sensitive data (e.g., the text of
users' private messages), this methodology can benefit privacy by allowing
deep-learning practitioners to select means of training that minimize such
memorization.
In experiments, we show that unintended memorization is a persistent,
hard-to-avoid issue that can have serious consequences. Specifically, for
models trained without consideration of memorization, we describe new,
efficient procedures that can extract unique, secret sequences, such as credit
card numbers. We show that our testing strategy is a practical and easy-to-use
first line of defense, e.g., by describing its application to quantitatively
limit data exposure in Google's Smart Compose, a commercial text-completion
neural network trained on millions of users' email messages.
| cs.LG cs.AI cs.CR | this paper describes a testing methodology for quantitatively assessing the risk that rare or unique trainingdata sequences are unintentionally memorized by generative sequence modelsa common type of machinelearning model because such models are sometimes trained on sensitive data eg the text of users private messages this methodology can benefit privacy by allowing deeplearning practitioners to select means of training that minimize such memorization in experiments we show that unintended memorization is a persistent hardtoavoid issue that can have serious consequences specifically for models trained without consideration of memorization we describe new efficient procedures that can extract unique secret sequences such as credit card numbers we show that our testing strategy is a practical and easytouse first line of defense eg by describing its application to quantitatively limit data exposure in googles smart compose a commercial textcompletion neural network trained on millions of users email messages | [['this', 'paper', 'describes', 'a', 'testing', 'methodology', 'for', 'quantitatively', 'assessing', 'the', 'risk', 'that', 'rare', 'or', 'unique', 'trainingdata', 'sequences', 'are', 'unintentionally', 'memorized', 'by', 'generative', 'sequence', 'modelsa', 'common', 'type', 'of', 'machinelearning', 'model', 'because', 'such', 'models', 'are', 'sometimes', 'trained', 'on', 'sensitive', 'data', 'eg', 'the', 'text', 'of', 'users', 'private', 'messages', 'this', 'methodology', 'can', 'benefit', 'privacy', 'by', 'allowing', 'deeplearning', 'practitioners', 'to', 'select', 'means', 'of', 'training', 'that', 'minimize', 'such', 'memorization', 'in', 'experiments', 'we', 'show', 'that', 'unintended', 'memorization', 'is', 'a', 'persistent', 'hardtoavoid', 'issue', 'that', 'can', 'have', 'serious', 'consequences', 'specifically', 'for', 'models', 'trained', 'without', 'consideration', 'of', 'memorization', 'we', 'describe', 'new', 'efficient', 'procedures', 'that', 'can', 'extract', 'unique', 'secret', 'sequences', 'such', 'as', 'credit', 'card', 'numbers', 'we', 'show', 'that', 'our', 'testing', 'strategy', 'is', 'a', 'practical', 'and', 'easytouse', 'first', 'line', 'of', 'defense', 'eg', 'by', 'describing', 'its', 'application', 'to', 'quantitatively', 'limit', 'data', 'exposure', 'in', 'googles', 'smart', 'compose', 'a', 'commercial', 'textcompletion', 'neural', 'network', 'trained', 'on', 'millions', 'of', 'users', 'email', 'messages']] | [-0.07605177023178585, 0.008540078372388453, -0.046546594181156656, 0.13733090428387992, -0.14985370423670832, -0.2507624585096809, 0.11040756667124016, 0.42544334892418, -0.28297254986331594, -0.3363754156247511, 0.10064030979300842, -0.3101198688209288, -0.19698808449515878, 0.19880020921607014, -0.168708179859197, 0.06605964349753751, 0.11680891208832601, 0.03801692840545536, 0.020149274095827778, -0.30750389874691364, 0.3092177788681396, 0.03618516556436678, 0.32808492224096886, 0.016157580940117995, 0.0892185695089605, -0.002849690091854834, -0.03668739578940652, -0.014463181015579486, -0.0637666216571742, 0.13586702035785608, 0.3421642382593497, 0.2500783764216658, 0.363789687249028, -0.4413426479103265, -0.20480790514811562, 0.11115878397416505, 0.1237089175690646, 0.13123060151986726, -0.06679036325719728, -0.3217186256657009, 0.12249421575139244, -0.21334986842865894, -0.021722581146376117, -0.16987878047711366, -0.035374600008794374, 0.033153145634276154, -0.303293553682474, -0.026868151271246844, 0.04398191545054421, 0.08827771601276115, 0.016102458000300336, -0.08541972430461979, 0.01101805717469408, 0.19828039778468126, 0.06987331805496731, -0.00861335534055333, 0.15871884544555853, -0.1339076217003427, -0.15376310222912448, 0.3513200850766543, -0.04614640352270612, -0.16716748087706004, 0.13965960546442263, 0.020064039287723965, -0.1712824055840346, 0.07906626505204119, 0.2573561340650231, 0.07088269619678206, -0.21590080293680222, -0.01500828627218538, -0.049709301295371114, 0.20496712868603376, 0.05662846536264866, -0.004478062827048914, 0.20152389707607118, 0.21664316707349324, 0.0009591518103477213, 0.11306211453621516, -0.08888918400735601, -0.0476610488877013, -0.21705402433790813, -0.14736765308201416, -0.20309567724849534, 0.04963241373612122, -0.08869735395991311, -0.15533756518938377, 0.373040072313816, 0.25014896386374647, 0.13755188820154204, 0.08382580826918666, 0.345605561060349, -0.0030257780971070687, 0.10248201188369421, 0.07517972301489875, 0.12401009500482595, -0.047300766701679806, 0.11418403708213172, -0.122493765626259, 0.17189558811967712, 0.008605140121328039] |
1,802.08233 | Pattern-based Modeling of Multiresilience Solutions for High-Performance
Computing | Resiliency is the ability of large-scale high-performance computing (HPC)
applications to gracefully handle errors, and recover from failures. In this
paper, we propose a pattern-based approach to constructing resilience solutions
that handle multiple error modes. Using resilience patterns, we evaluate the
performance and reliability characteristics of detection, containment and
mitigation techniques for transient errors that cause silent data corruptions
and techniques for fail-stop errors that result in process failures. We
demonstrate the design and implementation of the multiresilience solution based
on patterns instantiated across multiple layers of the system stack. The
patterns are integrated to work together to achieve resiliency to different
error types in a performance-efficient manner.
| cs.DC | resiliency is the ability of largescale highperformance computing hpc applications to gracefully handle errors and recover from failures in this paper we propose a patternbased approach to constructing resilience solutions that handle multiple error modes using resilience patterns we evaluate the performance and reliability characteristics of detection containment and mitigation techniques for transient errors that cause silent data corruptions and techniques for failstop errors that result in process failures we demonstrate the design and implementation of the multiresilience solution based on patterns instantiated across multiple layers of the system stack the patterns are integrated to work together to achieve resiliency to different error types in a performanceefficient manner | [['resiliency', 'is', 'the', 'ability', 'of', 'largescale', 'highperformance', 'computing', 'hpc', 'applications', 'to', 'gracefully', 'handle', 'errors', 'and', 'recover', 'from', 'failures', 'in', 'this', 'paper', 'we', 'propose', 'a', 'patternbased', 'approach', 'to', 'constructing', 'resilience', 'solutions', 'that', 'handle', 'multiple', 'error', 'modes', 'using', 'resilience', 'patterns', 'we', 'evaluate', 'the', 'performance', 'and', 'reliability', 'characteristics', 'of', 'detection', 'containment', 'and', 'mitigation', 'techniques', 'for', 'transient', 'errors', 'that', 'cause', 'silent', 'data', 'corruptions', 'and', 'techniques', 'for', 'failstop', 'errors', 'that', 'result', 'in', 'process', 'failures', 'we', 'demonstrate', 'the', 'design', 'and', 'implementation', 'of', 'the', 'multiresilience', 'solution', 'based', 'on', 'patterns', 'instantiated', 'across', 'multiple', 'layers', 'of', 'the', 'system', 'stack', 'the', 'patterns', 'are', 'integrated', 'to', 'work', 'together', 'to', 'achieve', 'resiliency', 'to', 'different', 'error', 'types', 'in', 'a', 'performanceefficient', 'manner']] | [-0.16319490925250751, -0.023319341198383074, -0.04041837662774718, 0.05103548114330583, -0.05465193280844756, -0.1380161851521511, 0.10285455878178221, 0.38769726999947485, -0.2952761774320366, -0.3415789814195859, 0.13590805261189398, -0.2508884262802071, -0.21259287584854183, 0.20511400733002513, -0.1943761605795754, 0.12481812181232392, 0.12092886032220328, -0.07287300228501477, -0.040998265663390314, -0.27183160189328326, 0.29061568990999936, 0.07348924281321606, 0.35675120133168575, 0.016887129741316696, 0.05341281341322926, -0.03236260595248204, -0.021947257903037715, 0.0328974327762207, -0.05581575567401091, 0.12738846387397848, 0.3284358026103978, 0.20088587570847627, 0.2903405901325761, -0.4629921916309955, -0.19859638109908634, 0.0789740254513849, 0.12640190480786534, 0.13150593281705986, -0.026248960205538303, -0.29468377095862414, 0.18411477433763584, -0.20541813138450654, -0.09268193821563332, -0.13713012251756945, -0.03650730605817066, 0.03734894899897418, -0.29411538811576254, 0.03345310728434684, 0.06789062809163951, 0.02932920990256979, -0.024533470297443134, -0.051007097739647234, 0.06919529134811798, 0.16940455737453447, 0.029732056667990895, -0.02464189614226409, 0.1528992098800065, -0.10565154677862905, -0.19997321252869266, 0.34971969562389377, -0.013703050651974132, -0.2079860400496367, 0.19485604088481093, 0.007556446994883272, -0.15456788030119156, 0.11311159173536273, 0.30035969923812683, 0.04922360301298915, -0.1565644889454937, -0.007502499109525058, 0.10319153476234104, 0.1924329053584205, 0.0784929701553236, 0.07836313431457625, 0.13925840805135317, 0.19258225431121043, 0.08069567833939251, 0.15131459382520812, -0.12104533829963503, -0.06718276124799026, -0.21700476131177912, -0.10197689563018393, -0.12053006398052259, -0.04142021915638151, -0.07725089827905528, -0.20461318665623385, 0.41847244015771823, 0.2845277704280924, 0.17106411043106456, 0.12043919683327538, 0.3962171323122984, 0.03824394880266825, 0.06349956089595579, 0.1235176009468664, 0.1477511174875786, 0.03603033138931079, 0.10053120485840822, -0.21229480247382285, 0.1273200959977606, -0.014647965517141065] |
1,802.08234 | What's the Over/Under? Probabilistic Bounds on Information Leakage | Quantitative information flow (QIF) is concerned with measuring how much of a
secret is leaked to an adversary who observes the result of a computation that
uses it. Prior work has shown that QIF techniques based on abstract
interpretation with probabilistic polyhedra can be used to analyze the
worst-case leakage of a query, on-line, to determine whether that query can be
safely answered. While this approach can provide precise estimates, it does not
scale well. This paper shows how to solve the scalability problem by augmenting
the baseline technique with sampling and symbolic execution. We prove that our
approach never underestimates a query's leakage (it is sound), and detailed
experimental results show that we can match the precision of the baseline
technique but with orders of magnitude better performance.
| cs.PL | quantitative information flow qif is concerned with measuring how much of a secret is leaked to an adversary who observes the result of a computation that uses it prior work has shown that qif techniques based on abstract interpretation with probabilistic polyhedra can be used to analyze the worstcase leakage of a query online to determine whether that query can be safely answered while this approach can provide precise estimates it does not scale well this paper shows how to solve the scalability problem by augmenting the baseline technique with sampling and symbolic execution we prove that our approach never underestimates a querys leakage it is sound and detailed experimental results show that we can match the precision of the baseline technique but with orders of magnitude better performance | [['quantitative', 'information', 'flow', 'qif', 'is', 'concerned', 'with', 'measuring', 'how', 'much', 'of', 'a', 'secret', 'is', 'leaked', 'to', 'an', 'adversary', 'who', 'observes', 'the', 'result', 'of', 'a', 'computation', 'that', 'uses', 'it', 'prior', 'work', 'has', 'shown', 'that', 'qif', 'techniques', 'based', 'on', 'abstract', 'interpretation', 'with', 'probabilistic', 'polyhedra', 'can', 'be', 'used', 'to', 'analyze', 'the', 'worstcase', 'leakage', 'of', 'a', 'query', 'online', 'to', 'determine', 'whether', 'that', 'query', 'can', 'be', 'safely', 'answered', 'while', 'this', 'approach', 'can', 'provide', 'precise', 'estimates', 'it', 'does', 'not', 'scale', 'well', 'this', 'paper', 'shows', 'how', 'to', 'solve', 'the', 'scalability', 'problem', 'by', 'augmenting', 'the', 'baseline', 'technique', 'with', 'sampling', 'and', 'symbolic', 'execution', 'we', 'prove', 'that', 'our', 'approach', 'never', 'underestimates', 'a', 'querys', 'leakage', 'it', 'is', 'sound', 'and', 'detailed', 'experimental', 'results', 'show', 'that', 'we', 'can', 'match', 'the', 'precision', 'of', 'the', 'baseline', 'technique', 'but', 'with', 'orders', 'of', 'magnitude', 'better', 'performance']] | [-0.054319849115969654, 0.024710760550332514, -0.15245287196869536, 0.08958348601085474, -0.13645801292515772, -0.1723029608242647, 0.08044783880685044, 0.40016626016518403, -0.2830813270307673, -0.36076891641746195, 0.11791641174187494, -0.26293362405642057, -0.1404240812886102, 0.22601031149600365, -0.1603813735845358, 0.0686608936507688, 0.1083322452370424, 0.05097584082594307, -0.038218984490462626, -0.30245883696416553, 0.2615865909245385, 0.10106752649339479, 0.28088597889787464, 0.0792712306625448, 0.07864204165706223, -0.009663359641075828, -0.041414420373102494, 0.06437505002660576, -0.12146300298497739, 0.13644354713831616, 0.2865035480676605, 0.21473294037553056, 0.2788960552348416, -0.4000825306848269, -0.20515329048918315, 0.10705364020897776, 0.17314319539401868, 0.13880642457294834, -0.0049681028327724155, -0.2724037426740451, 0.11621861438295811, -0.16172852812067773, -0.06003874220141722, -0.13493142031808203, -0.04502460242848295, -0.02522926700487372, -0.30038013734111146, 0.025284880097204632, 0.09164493401036707, 0.022991598013413043, 0.016333241136600226, -0.05607728090686832, 0.04476375328449085, 0.1511221265478074, 0.04103413051221693, 0.06813677512163427, 0.12106505815344032, -0.08360543041742703, -0.16684447607213213, 0.3614409705118615, -0.06830742813163083, -0.20783876988661382, 0.15053549362887997, -0.10477554519812382, -0.09844011110217535, 0.10792640202440494, 0.14928926879453452, 0.10363184554816418, -0.14989860574606545, 0.03416237810197063, -0.0757269723875116, 0.27035152496654513, 0.04592568589764279, 0.03189020971009551, 0.1305415537172221, 0.1952949009886257, 0.11336382456816906, 0.139425776151637, -0.02704232596691207, -0.07128591882786894, -0.23642882792813372, -0.12934855434095105, -0.1881265013402891, 0.03744107285388583, -0.06247149287635468, -0.12009860096610324, 0.36077375562370634, 0.26079672511464863, 0.17810527737389587, 0.11337707421287548, 0.3798251693216405, 0.10152066489338672, 0.05603098676787227, 0.1264404279699679, 0.2269199535484397, 0.03608120972283416, 0.10160351546603984, -0.19203537227062495, 0.16158502864066598, 0.047052863310271684] |
1,802.08235 | Vector Field Based Neural Networks | A novel Neural Network architecture is proposed using the mathematically and
physically rich idea of vector fields as hidden layers to perform nonlinear
transformations in the data. The data points are interpreted as particles
moving along a flow defined by the vector field which intuitively represents
the desired movement to enable classification. The architecture moves the data
points from their original configuration to anew one following the streamlines
of the vector field with the objective of achieving a final configuration where
classes are separable. An optimization problem is solved through gradient
descent to learn this vector field.
| cs.LG cs.AI stat.ML | a novel neural network architecture is proposed using the mathematically and physically rich idea of vector fields as hidden layers to perform nonlinear transformations in the data the data points are interpreted as particles moving along a flow defined by the vector field which intuitively represents the desired movement to enable classification the architecture moves the data points from their original configuration to anew one following the streamlines of the vector field with the objective of achieving a final configuration where classes are separable an optimization problem is solved through gradient descent to learn this vector field | [['a', 'novel', 'neural', 'network', 'architecture', 'is', 'proposed', 'using', 'the', 'mathematically', 'and', 'physically', 'rich', 'idea', 'of', 'vector', 'fields', 'as', 'hidden', 'layers', 'to', 'perform', 'nonlinear', 'transformations', 'in', 'the', 'data', 'the', 'data', 'points', 'are', 'interpreted', 'as', 'particles', 'moving', 'along', 'a', 'flow', 'defined', 'by', 'the', 'vector', 'field', 'which', 'intuitively', 'represents', 'the', 'desired', 'movement', 'to', 'enable', 'classification', 'the', 'architecture', 'moves', 'the', 'data', 'points', 'from', 'their', 'original', 'configuration', 'to', 'anew', 'one', 'following', 'the', 'streamlines', 'of', 'the', 'vector', 'field', 'with', 'the', 'objective', 'of', 'achieving', 'a', 'final', 'configuration', 'where', 'classes', 'are', 'separable', 'an', 'optimization', 'problem', 'is', 'solved', 'through', 'gradient', 'descent', 'to', 'learn', 'this', 'vector', 'field']] | [-0.1270862223158024, 0.07367686486275526, -0.08190965732156309, 0.028628512198038247, -0.12429752995346471, -0.15425606459359995, 0.013938993629315369, 0.39532388558553666, -0.35754956289664985, -0.3049414654252763, 0.065730163550302, -0.22535424785131647, -0.15344600346822715, 0.1448816985429562, -0.06783506534897636, 0.0680939872969979, 0.06541585991370309, 0.08777820631458434, -0.05928603193444228, -0.2484302503829726, 0.3314905102057478, 0.025367334715484344, 0.30661300454557555, -0.0759967195983861, 0.16415418781695368, 0.024256723281686175, 0.02616383820368918, 0.01946966329795913, -0.032289808069370186, 0.15752595282740622, 0.25988449302943634, 0.18921647003861433, 0.2931810557246976, -0.41900094626435397, -0.21739092147092998, 0.08080185488941743, 0.13737300629775548, 0.10867182409616437, -0.020900823406337463, -0.325185510032263, 0.0672003132358347, -0.07989359604790039, -0.11662506719225461, -0.10168569666554325, -0.03653563009503, 0.020252337765678304, -0.2922114824357721, -0.0018636661284055906, 0.05122921447456843, 0.0540038085297787, -0.07622123294097093, -0.06641471299904485, -0.05108138972643724, 0.12498552019506232, 0.06090663517009198, 0.13926557207134427, 0.15873910836364172, -0.16314906393389036, -0.13844927646863014, 0.37526924608601736, -0.05481707696447667, -0.27770707283898727, 0.1486428675779439, -0.011312902273763855, -0.07106163761261658, 0.1342893750886865, 0.22161836017489664, 0.12236979696899652, -0.17406934821382933, 0.03304838752026007, -0.06446292680044918, 0.11905859176731985, 0.007338400968571299, -0.03100601218691211, 0.2019959035468739, 0.1750985446125605, 0.08612723353789332, 0.16229103719239535, -0.10210479978356779, -0.13969450384455243, -0.289054612897951, -0.14123938104963488, -0.18633996584865542, -0.014234580089981408, -0.08650811468764118, -0.168931228389091, 0.42779005910317924, 0.1338481510480501, 0.28180590884510387, 0.04436783868574643, 0.3169460025107123, 0.08957417872638355, 0.11342321511912495, 0.11360036332601893, 0.22063767643088533, 0.13897542568336518, 0.13647831702057617, -0.14178626421483753, 0.02881089362229422, 0.08966294375305861] |
1,802.08236 | NetChain: Scale-Free Sub-RTT Coordination (Extended Version) | Coordination services are a fundamental building block of modern cloud
systems, providing critical functionalities like configuration management and
distributed locking. The major challenge is to achieve low latency and high
throughput while providing strong consistency and fault-tolerance. Traditional
server-based solutions require multiple round-trip times (RTTs) to process a
query. This paper presents NetChain, a new approach that provides scale-free
sub-RTT coordination in datacenters. NetChain exploits recent advances in
programmable switches to store data and process queries entirely in the network
data plane. This eliminates the query processing at coordination servers and
cuts the end-to-end latency to as little as half of an RTT---clients only
experience processing delay from their own software stack plus network delay,
which in a datacenter setting is typically much smaller. We design new
protocols and algorithms based on chain replication to guarantee strong
consistency and to efficiently handle switch failures. We implement a prototype
with four Barefoot Tofino switches and four commodity servers. Evaluation
results show that compared to traditional server-based solutions like
ZooKeeper, our prototype provides orders of magnitude higher throughput and
lower latency, and handles failures gracefully.
| cs.DC | coordination services are a fundamental building block of modern cloud systems providing critical functionalities like configuration management and distributed locking the major challenge is to achieve low latency and high throughput while providing strong consistency and faulttolerance traditional serverbased solutions require multiple roundtrip times rtts to process a query this paper presents netchain a new approach that provides scalefree subrtt coordination in datacenters netchain exploits recent advances in programmable switches to store data and process queries entirely in the network data plane this eliminates the query processing at coordination servers and cuts the endtoend latency to as little as half of an rttclients only experience processing delay from their own software stack plus network delay which in a datacenter setting is typically much smaller we design new protocols and algorithms based on chain replication to guarantee strong consistency and to efficiently handle switch failures we implement a prototype with four barefoot tofino switches and four commodity servers evaluation results show that compared to traditional serverbased solutions like zookeeper our prototype provides orders of magnitude higher throughput and lower latency and handles failures gracefully | [['coordination', 'services', 'are', 'a', 'fundamental', 'building', 'block', 'of', 'modern', 'cloud', 'systems', 'providing', 'critical', 'functionalities', 'like', 'configuration', 'management', 'and', 'distributed', 'locking', 'the', 'major', 'challenge', 'is', 'to', 'achieve', 'low', 'latency', 'and', 'high', 'throughput', 'while', 'providing', 'strong', 'consistency', 'and', 'faulttolerance', 'traditional', 'serverbased', 'solutions', 'require', 'multiple', 'roundtrip', 'times', 'rtts', 'to', 'process', 'a', 'query', 'this', 'paper', 'presents', 'netchain', 'a', 'new', 'approach', 'that', 'provides', 'scalefree', 'subrtt', 'coordination', 'in', 'datacenters', 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1,802.08237 | Improved Massively Parallel Computation Algorithms for MIS, Matching,
and Vertex Cover | We present $O(\log\log n)$-round algorithms in the Massively Parallel
Computation (MPC) model, with $\tilde{O}(n)$ memory per machine, that compute a
maximal independent set, a $1+\epsilon$ approximation of maximum matching, and
a $2+\epsilon$ approximation of minimum vertex cover, for any $n$-vertex graph
and any constant $\epsilon>0$. These improve the state of the art as follows:
- Our MIS algorithm leads to a simple $O(\log\log \Delta)$-round MIS
algorithm in the Congested Clique model of distributed computing, which
improves on the $\tilde{O}(\sqrt{\log \Delta})$-round algorithm of Ghaffari
[PODC'17].
- Our $O(\log\log n)$-round $(1+\epsilon)$-approximate maximum matching
algorithm simplifies or improves on the following prior work: $O(\log^2\log
n)$-round $(1+\epsilon)$-approximation algorithm of Czumaj et al. [STOC'18] and
$O(\log\log n)$-round $(1+\epsilon)$-approximation algorithm of Assadi et al.
[SODA'19].
- Our $O(\log\log n)$-round $(2+\epsilon)$-approximate minimum vertex cover
algorithm improves on an $O(\log\log n)$-round $O(1)$-approximation of Assadi
et al. [arXiv'17].
| cs.DS cs.DC | we present ologlog nround algorithms in the massively parallel computation mpc model with tildeon memory per machine that compute a maximal independent set a 1epsilon approximation of maximum matching and a 2epsilon approximation of minimum vertex cover for any nvertex graph and any constant epsilon0 these improve the state of the art as follows our mis algorithm leads to a simple ologlog deltaround mis algorithm in the congested clique model of distributed computing which improves on the tildeosqrtlog deltaround algorithm of ghaffari podc17 our ologlog nround 1epsilonapproximate maximum matching algorithm simplifies or improves on the following prior work olog2log nround 1epsilonapproximation algorithm of czumaj et al stoc18 and ologlog nround 1epsilonapproximation algorithm of assadi et al soda19 our ologlog nround 2epsilonapproximate minimum vertex cover algorithm improves on an ologlog nround o1approximation of assadi et al arxiv17 | [['we', 'present', 'ologlog', 'nround', 'algorithms', 'in', 'the', 'massively', 'parallel', 'computation', 'mpc', 'model', 'with', 'tildeon', 'memory', 'per', 'machine', 'that', 'compute', 'a', 'maximal', 'independent', 'set', 'a', '1epsilon', 'approximation', 'of', 'maximum', 'matching', 'and', 'a', '2epsilon', 'approximation', 'of', 'minimum', 'vertex', 'cover', 'for', 'any', 'nvertex', 'graph', 'and', 'any', 'constant', 'epsilon0', 'these', 'improve', 'the', 'state', 'of', 'the', 'art', 'as', 'follows', 'our', 'mis', 'algorithm', 'leads', 'to', 'a', 'simple', 'ologlog', 'deltaround', 'mis', 'algorithm', 'in', 'the', 'congested', 'clique', 'model', 'of', 'distributed', 'computing', 'which', 'improves', 'on', 'the', 'tildeosqrtlog', 'deltaround', 'algorithm', 'of', 'ghaffari', 'podc17', 'our', 'ologlog', 'nround', '1epsilonapproximate', 'maximum', 'matching', 'algorithm', 'simplifies', 'or', 'improves', 'on', 'the', 'following', 'prior', 'work', 'olog2log', 'nround', '1epsilonapproximation', 'algorithm', 'of', 'czumaj', 'et', 'al', 'stoc18', 'and', 'ologlog', 'nround', '1epsilonapproximation', 'algorithm', 'of', 'assadi', 'et', 'al', 'soda19', 'our', 'ologlog', 'nround', '2epsilonapproximate', 'minimum', 'vertex', 'cover', 'algorithm', 'improves', 'on', 'an', 'ologlog', 'nround', 'o1approximation', 'of', 'assadi', 'et', 'al', 'arxiv17']] | [-0.15685389727465252, 0.014533661173091014, -0.045825273867995384, -0.06059759556239387, -0.0990791736976869, -0.21419061748519427, 0.18553855511231293, 0.3368713127365753, -0.21673448043076127, -0.4760920754147332, 0.03357272011874272, -0.2620700295013723, -0.15865912330128365, 0.14696202758845608, -0.1497374061499844, 0.12578078376480253, 0.08653794374984147, -0.033128382971704895, 0.048674726850047374, -0.4222086119622343, 0.08989700577100183, 0.09165845961577551, 0.23788010513187566, 0.03820916555766294, 0.11724551648089189, 0.09525791235848455, -0.021206184043618504, 0.0036217549880063022, -0.19133948965143427, 0.06160357246981628, 0.2058735488072983, 0.27020415948192833, 0.26754952942146293, -0.3693630231071764, -0.1020394987313758, 0.1467072596432947, 0.1932387722624855, 0.10003542178223576, 0.02036249366981575, -0.20629345393155826, 0.11371490365387733, -0.14338663865381213, -0.0022197989347293528, 0.013439190219531752, 0.08527063025481332, -0.031363553082598236, -0.381117070302256, 0.02810735561113471, 0.11802663254628042, -0.09457130312794514, 0.05911734914789393, -0.21720623988797194, 0.12740252266026367, 0.02180167017921583, -0.19162747922958112, 0.22821478747220628, 0.02302717890785034, -0.06327086892813, -0.25248614098848915, 0.2943239909433412, -0.05662652397000078, -0.0474103267457503, 0.030807473408336294, 0.039567499869714196, -0.20227965985341415, 0.14046908487607515, 0.19642902988377514, 0.21892731942570032, -0.019862748698571197, 0.23675744678806027, -0.16341229291882978, 0.16902758936925943, 0.13548543152691267, -0.026795184430874773, -0.09146685412834718, 0.18564190850732154, 0.22419529982908531, 0.09927093963931079, 0.032330962440082385, -0.08894128323517003, -0.22023333567381426, -0.1261017208418517, -0.2636747871205878, -0.007777573234999358, -0.25663511310462966, -0.19858438915003146, 0.3600111158092075, 0.17000952312277992, 0.20915033556729443, 0.23883884903408392, 0.3329760084943429, 0.03300411837731936, -0.03032998981670157, 0.38017664757429503, 0.12491164139798606, 0.07230298665227063, 0.03875543051156035, -0.2787543123886823, 0.11688992465714187, 0.1873488071726013] |
1,802.08238 | What are the most important factors that influence the changes in London
Real Estate Prices? How to quantify them? | In recent years, real estate industry has captured government and public
attention around the world. The factors influencing the prices of real estate
are diversified and complex. However, due to the limitations and one-sidedness
of their respective views, they did not provide enough theoretical basis for
the fluctuation of house price and its influential factors. The purpose of this
paper is to build a housing price model to make the scientific and objective
analysis of London's real estate market trends from the year 1996 to 2016 and
proposes some countermeasures to reasonably control house prices. Specifically,
the paper analyzes eight factors which affect the house prices from two
aspects: housing supply and demand and find out the factor which is of vital
importance to the increase of housing price per square meter. The problem of a
high level of multicollinearity between them is solved by using principal
components analysis.
| stat.AP q-fin.GN | in recent years real estate industry has captured government and public attention around the world the factors influencing the prices of real estate are diversified and complex however due to the limitations and onesidedness of their respective views they did not provide enough theoretical basis for the fluctuation of house price and its influential factors the purpose of this paper is to build a housing price model to make the scientific and objective analysis of londons real estate market trends from the year 1996 to 2016 and proposes some countermeasures to reasonably control house prices specifically the paper analyzes eight factors which affect the house prices from two aspects housing supply and demand and find out the factor which is of vital importance to the increase of housing price per square meter the problem of a high level of multicollinearity between them is solved by using principal components analysis | [['in', 'recent', 'years', 'real', 'estate', 'industry', 'has', 'captured', 'government', 'and', 'public', 'attention', 'around', 'the', 'world', 'the', 'factors', 'influencing', 'the', 'prices', 'of', 'real', 'estate', 'are', 'diversified', 'and', 'complex', 'however', 'due', 'to', 'the', 'limitations', 'and', 'onesidedness', 'of', 'their', 'respective', 'views', 'they', 'did', 'not', 'provide', 'enough', 'theoretical', 'basis', 'for', 'the', 'fluctuation', 'of', 'house', 'price', 'and', 'its', 'influential', 'factors', 'the', 'purpose', 'of', 'this', 'paper', 'is', 'to', 'build', 'a', 'housing', 'price', 'model', 'to', 'make', 'the', 'scientific', 'and', 'objective', 'analysis', 'of', 'londons', 'real', 'estate', 'market', 'trends', 'from', 'the', 'year', '1996', 'to', '2016', 'and', 'proposes', 'some', 'countermeasures', 'to', 'reasonably', 'control', 'house', 'prices', 'specifically', 'the', 'paper', 'analyzes', 'eight', 'factors', 'which', 'affect', 'the', 'house', 'prices', 'from', 'two', 'aspects', 'housing', 'supply', 'and', 'demand', 'and', 'find', 'out', 'the', 'factor', 'which', 'is', 'of', 'vital', 'importance', 'to', 'the', 'increase', 'of', 'housing', 'price', 'per', 'square', 'meter', 'the', 'problem', 'of', 'a', 'high', 'level', 'of', 'multicollinearity', 'between', 'them', 'is', 'solved', 'by', 'using', 'principal', 'components', 'analysis']] | [-0.06951419527223646, 0.03573057737401468, -0.06972278851856346, 0.084702288556919, -0.09876319856989203, -0.1117175737592773, 0.13311395998075354, 0.36787733575641707, -0.2321820591932675, -0.3428209628534797, 0.16920654801573703, -0.3278728582546265, -0.15250483786549746, 0.21486430018421437, -0.1400338081742993, 0.01601191574431043, 0.029911588623513462, 0.0043074755443825745, 0.04120289724892093, -0.3368659729869324, 0.28915225031188746, 0.08783022387128249, 0.31662819440314083, 0.07674873454790038, 0.09425388193992436, -0.030811617347793092, -0.09873545371486661, -0.020560329301038995, -0.0911300436935611, 0.20851267526166875, 0.3016432701538148, 0.15708753907890527, 0.3704647323079157, -0.44747091423495106, -0.13561549523514038, 0.13113121592264698, 0.03119177569872731, 0.009578531529073097, 0.026939529837296663, -0.2426122668724282, 0.02862252429715239, -0.23639290375109986, -0.13789925633948422, -0.09237092262174584, 0.0540889122479614, 0.025932154729931097, -0.2351407925145163, 0.04389271215534138, 0.010544984188905898, 0.08683007105484905, -0.04591982968576602, -0.13599485205798942, -0.03807807041070094, 0.22673640469864212, 0.13078295852931923, -0.055006403059365806, 0.16443458978702383, -0.14908730921073, -0.1328376531241549, 0.41371083055816643, -0.008888496764179243, -0.11610302226867952, 0.1477498456120066, -0.16204730644134568, -0.09422261927639378, 0.09040683241257906, 0.23937942953342758, -0.005130969434851568, -0.17092859423750598, 0.0426476942781584, -0.02987977521237761, 0.17966816122737406, 0.07109864779448, -0.036688968186085455, 0.227914037489201, 0.15833839459107227, 0.06308898169834647, 0.10041824343611155, -0.06411805604904852, -0.14270596232283986, -0.21435059968463377, -0.13608880303393825, -0.13050436424466488, 0.03852504300238368, -0.07801520309001582, -0.14080971836631231, 0.42391186681944854, 0.17002076156212378, 0.1430609290294299, 0.020672843480582705, 0.31936113278837813, 0.06230576924554654, 0.04831772501464783, 0.08483628221731258, 0.18953294974643167, -0.002652121181193514, 0.1888310412670042, -0.1453541605803653, 0.13654922343393625, -0.024451510325986768] |
1,802.08239 | AGAMA: Action-based galaxy modelling architecture | Agama is a publicly available software library for a broad range of
applications in the field of stellar dynamics. It provides methods for
computing the gravitational potential of arbitrary analytic density profiles or
N-body models; orbit integration and analysis; transformations between
position/velocity and action/angle variables; distribution functions expressed
in terms of actions and their moments; iterative construction of
self-consistent multicomponent galaxy models. Applications include the
inference about the structure of Milky Way or other galaxies from observations
of stellar kinematics; preparation of equilibrium initial conditions for N-body
simulations; analysis of snapshots from simulations. The library is written in
C++, provides a Python interface, and can be coupled to other stellar-dynamical
software: Amuse, Galpy and Nemo.
| astro-ph.GA | agama is a publicly available software library for a broad range of applications in the field of stellar dynamics it provides methods for computing the gravitational potential of arbitrary analytic density profiles or nbody models orbit integration and analysis transformations between positionvelocity and actionangle variables distribution functions expressed in terms of actions and their moments iterative construction of selfconsistent multicomponent galaxy models applications include the inference about the structure of milky way or other galaxies from observations of stellar kinematics preparation of equilibrium initial conditions for nbody simulations analysis of snapshots from simulations the library is written in c provides a python interface and can be coupled to other stellardynamical software amuse galpy and nemo | [['agama', 'is', 'a', 'publicly', 'available', 'software', 'library', 'for', 'a', 'broad', 'range', 'of', 'applications', 'in', 'the', 'field', 'of', 'stellar', 'dynamics', 'it', 'provides', 'methods', 'for', 'computing', 'the', 'gravitational', 'potential', 'of', 'arbitrary', 'analytic', 'density', 'profiles', 'or', 'nbody', 'models', 'orbit', 'integration', 'and', 'analysis', 'transformations', 'between', 'positionvelocity', 'and', 'actionangle', 'variables', 'distribution', 'functions', 'expressed', 'in', 'terms', 'of', 'actions', 'and', 'their', 'moments', 'iterative', 'construction', 'of', 'selfconsistent', 'multicomponent', 'galaxy', 'models', 'applications', 'include', 'the', 'inference', 'about', 'the', 'structure', 'of', 'milky', 'way', 'or', 'other', 'galaxies', 'from', 'observations', 'of', 'stellar', 'kinematics', 'preparation', 'of', 'equilibrium', 'initial', 'conditions', 'for', 'nbody', 'simulations', 'analysis', 'of', 'snapshots', 'from', 'simulations', 'the', 'library', 'is', 'written', 'in', 'c', 'provides', 'a', 'python', 'interface', 'and', 'can', 'be', 'coupled', 'to', 'other', 'stellardynamical', 'software', 'amuse', 'galpy', 'and', 'nemo']] | [-0.10633132447002698, 0.005805476317587106, -0.1305957404329725, 0.07334313774278954, -0.08207817411090693, -0.09580662443667003, -0.03152270534116289, 0.3987403569419099, -0.21019670157490866, -0.3702285401523113, 0.0654650824640513, -0.23343090790769327, -0.06939764839354093, 0.23820672388714942, 0.045882931827446044, 0.06096023304954819, 0.14853273484369983, -0.0874203625459062, -0.09885307726976664, -0.22155941714451688, 0.27783183944614037, 0.06275942825266849, 0.1730674657970667, -0.03168389686666753, 0.08682624019844376, -0.0052815117225374865, -0.10043407193506541, -0.030944142140620187, -0.14644463429146487, 0.1071209522207146, 0.2829191060684262, 0.22322346759231193, 0.22489002103431394, -0.39621716983130445, -0.20457166014618808, 0.01464495689648649, 0.18055827581202205, 0.1161141796341247, -0.06321755373526526, -0.27959481202389885, 0.02258770434266847, -0.23524768135469892, -0.17359914612025024, -0.0796401121167709, 0.02345496440488521, 0.08887580168716934, -0.2692289365359339, 0.09001413250908903, -0.015786665528202834, 0.12473740889184663, -0.09036934451078592, -0.08985711429268121, -0.06527584821552686, 0.1313618950404065, -0.017501124152508766, 0.03439509769415726, 0.19637589199144556, -0.13895231160264382, -0.06239318985330022, 0.4197459756356219, -0.06566014053381007, -0.16590299218812066, 0.22758916478361124, -0.09852323072517048, -0.15305039128693548, 0.0679131221147659, 0.19321384546549425, 0.12113499937821989, -0.1998327537728271, 0.14265867486019093, 0.016402359020329365, 0.18640693139446818, 0.023653371482277693, -0.022405270525411216, 0.2662369079604421, 0.09745172024906977, 0.007122884901321453, 0.09985218609318786, -0.061472985342792844, -0.13153507574157708, -0.2805813269122787, -0.1379964468294613, -0.13923784506952633, 0.034434647175847835, -0.12891211396667843, -0.2014214547674941, 0.38547880753226904, 0.15244703407034926, 0.1058293747715652, 0.04715087990904146, 0.3402657872308856, 0.05579622222778752, 0.08714493743002252, 0.10272842098796821, 0.15120515090453884, 0.1577163461757743, 0.08879123142029605, -0.1848067784641424, 0.054508094930940346, 0.028217421911413902] |
1,802.0824 | Bounds on mean energy in the Kuramoto-Sivashinsky equation computed
using semidefinite programming | We present methods for bounding infinite-time averages in dynamical systems
governed by nonlinear PDEs. The methods rely on auxiliary functionals, which
are similar to Lyapunov functionals but satisfy different inequalities. The
inequalities are enforced by requiring certain expressions to be sums of
squares of polynomials, and the optimal choice of auxiliary functional is posed
as a semidefinite program (SDP) that can be solved computationally. To
formulate these SDPs we approximate the PDE by truncated systems of ODEs and
proceed in one of two ways. The first approach is to compute bounds for the ODE
systems, increasing the truncation order until bounds converge numerically. The
second approach incorporates the ODE systems with analytical estimates on their
deviation from the PDE, thereby using finite truncations to produce bounds for
the full PDE. We apply both methods to the Kuramoto-Sivashinsky equation, where
we compute upper bounds on the spatiotemporal average of energy by employing
polynomial auxiliary functionals up to degree six. The first approach is used
for most computations, but a subset of results are checked using the second
approach, and the results agree to high precision. These bounds apply to all
odd solutions of period $2\pi L$, where $L$ is varied. Sharp bounds are
obtained for $L\le10$, and trends suggest that more expensive computations
would yield sharp bounds at larger $L$ also. The bounds are known to be sharp
(to within 0.1% numerical error) because they are saturated by the simplest
nonzero steady states, which apparently have the largest mean energy among all
odd solutions. Prior authors have conjectured that mean energy remains $O(1)$
for $L\gg1$ since no particular solutions with larger energy have been found.
Our bounds constitute the first positive evidence for this conjecture, albeit
up to finite $L$, and they offer some guidance for analytical proofs.
| math.DS math.NA physics.flu-dyn | we present methods for bounding infinitetime averages in dynamical systems governed by nonlinear pdes the methods rely on auxiliary functionals which are similar to lyapunov functionals but satisfy different inequalities the inequalities are enforced by requiring certain expressions to be sums of squares of polynomials and the optimal choice of auxiliary functional is posed as a semidefinite program sdp that can be solved computationally to formulate these sdps we approximate the pde by truncated systems of odes and proceed in one of two ways the first approach is to compute bounds for the ode systems increasing the truncation order until bounds converge numerically the second approach incorporates the ode systems with analytical estimates on their deviation from the pde thereby using finite truncations to produce bounds for the full pde we apply both methods to the kuramotosivashinsky equation where we compute upper bounds on the spatiotemporal average of energy by employing polynomial auxiliary functionals up to degree six the first approach is used for most computations but a subset of results are checked using the second approach and the results agree to high precision these bounds apply to all odd solutions of period 2pi l where l is varied sharp bounds are obtained for lle10 and trends suggest that more expensive computations would yield sharp bounds at larger l also the bounds are known to be sharp to within 01 numerical error because they are saturated by the simplest nonzero steady states which apparently have the largest mean energy among all odd solutions prior authors have conjectured that mean energy remains o1 for lgg1 since no particular solutions with larger energy have been found our bounds constitute the first positive evidence for this conjecture albeit up to finite l and they offer some guidance for analytical proofs | [['we', 'present', 'methods', 'for', 'bounding', 'infinitetime', 'averages', 'in', 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1,802.08241 | Hessian-based Analysis of Large Batch Training and Robustness to
Adversaries | Large batch size training of Neural Networks has been shown to incur accuracy
loss when trained with the current methods. The exact underlying reasons for
this are still not completely understood. Here, we study large batch size
training through the lens of the Hessian operator and robust optimization. In
particular, we perform a Hessian based study to analyze exactly how the
landscape of the loss function changes when training with large batch size. We
compute the true Hessian spectrum, without approximation, by back-propagating
the second derivative. Extensive experiments on multiple networks show that
saddle-points are not the cause for generalization gap of large batch size
training, and the results consistently show that large batch converges to
points with noticeably higher Hessian spectrum. Furthermore, we show that
robust training allows one to favor flat areas, as points with large Hessian
spectrum show poor robustness to adversarial perturbation. We further study
this relationship, and provide empirical and theoretical proof that the inner
loop for robust training is a saddle-free optimization problem \textit{almost
everywhere}. We present detailed experiments with five different network
architectures, including a residual network, tested on MNIST, CIFAR-10, and
CIFAR-100 datasets. We have open sourced our method which can be accessed at
[1].
| cs.CV cs.LG stat.ML | large batch size training of neural networks has been shown to incur accuracy loss when trained with the current methods the exact underlying reasons for this are still not completely understood here we study large batch size training through the lens of the hessian operator and robust optimization in particular we perform a hessian based study to analyze exactly how the landscape of the loss function changes when training with large batch size we compute the true hessian spectrum without approximation by backpropagating the second derivative extensive experiments on multiple networks show that saddlepoints are not the cause for generalization gap of large batch size training and the results consistently show that large batch converges to points with noticeably higher hessian spectrum furthermore we show that robust training allows one to favor flat areas as points with large hessian spectrum show poor robustness to adversarial perturbation we further study this relationship and provide empirical and theoretical proof that the inner loop for robust training is a saddlefree optimization problem textitalmost everywhere we present detailed experiments with five different network architectures including a residual network tested on mnist cifar10 and cifar100 datasets we have open sourced our method which can be accessed at 1 | [['large', 'batch', 'size', 'training', 'of', 'neural', 'networks', 'has', 'been', 'shown', 'to', 'incur', 'accuracy', 'loss', 'when', 'trained', 'with', 'the', 'current', 'methods', 'the', 'exact', 'underlying', 'reasons', 'for', 'this', 'are', 'still', 'not', 'completely', 'understood', 'here', 'we', 'study', 'large', 'batch', 'size', 'training', 'through', 'the', 'lens', 'of', 'the', 'hessian', 'operator', 'and', 'robust', 'optimization', 'in', 'particular', 'we', 'perform', 'a', 'hessian', 'based', 'study', 'to', 'analyze', 'exactly', 'how', 'the', 'landscape', 'of', 'the', 'loss', 'function', 'changes', 'when', 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1,802.08242 | Structured low-rank matrix completion for forecasting in time series
analysis | In this paper we consider the low-rank matrix completion problem with
specific application to forecasting in time series analysis. Briefly, the
low-rank matrix completion problem is the problem of imputing missing values of
a matrix under a rank constraint. We consider a matrix completion problem for
Hankel matrices and a convex relaxation based on the nuclear norm. Based on new
theoretical results and a number of numerical and real examples, we investigate
the cases when the proposed approach can work. Our results highlight the
importance of choosing a proper weighting scheme for the known observations.
| stat.ME cs.SY math.NA stat.ML | in this paper we consider the lowrank matrix completion problem with specific application to forecasting in time series analysis briefly the lowrank matrix completion problem is the problem of imputing missing values of a matrix under a rank constraint we consider a matrix completion problem for hankel matrices and a convex relaxation based on the nuclear norm based on new theoretical results and a number of numerical and real examples we investigate the cases when the proposed approach can work our results highlight the importance of choosing a proper weighting scheme for the known observations | [['in', 'this', 'paper', 'we', 'consider', 'the', 'lowrank', 'matrix', 'completion', 'problem', 'with', 'specific', 'application', 'to', 'forecasting', 'in', 'time', 'series', 'analysis', 'briefly', 'the', 'lowrank', 'matrix', 'completion', 'problem', 'is', 'the', 'problem', 'of', 'imputing', 'missing', 'values', 'of', 'a', 'matrix', 'under', 'a', 'rank', 'constraint', 'we', 'consider', 'a', 'matrix', 'completion', 'problem', 'for', 'hankel', 'matrices', 'and', 'a', 'convex', 'relaxation', 'based', 'on', 'the', 'nuclear', 'norm', 'based', 'on', 'new', 'theoretical', 'results', 'and', 'a', 'number', 'of', 'numerical', 'and', 'real', 'examples', 'we', 'investigate', 'the', 'cases', 'when', 'the', 'proposed', 'approach', 'can', 'work', 'our', 'results', 'highlight', 'the', 'importance', 'of', 'choosing', 'a', 'proper', 'weighting', 'scheme', 'for', 'the', 'known', 'observations']] | [-0.07118343789816688, 0.005177695078677253, -0.03667750850987719, 0.049849001705450445, -0.07708419290322223, -0.08496738174243977, 0.04959691314051222, 0.38650920308734243, -0.299322317501432, -0.2580664170268727, 0.1943450602678288, -0.2478412464064987, -0.23248249157086798, 0.15972257882944849, -0.09462992732266062, 0.10522461759407489, 0.11880154408710568, 0.04171148990035841, -0.16907328392231935, -0.28004922275186367, 0.35561753634951615, 0.041325972190028745, 0.2517357818096092, 0.07145059235381747, 0.12698568997316453, 0.04663604217287349, -0.0703332497297149, 0.013257722800584529, -0.08251350070104788, 0.1327339196210041, 0.272975267469883, 0.19448499335466246, 0.33003939611739236, -0.42502972762051383, -0.1965198709874561, 0.1440057872414687, 0.07222464522837024, 0.0835608644018832, -0.08572590096461538, -0.24714091610359518, 0.08393550507822319, -0.16952534959112342, -0.06370991395884439, -0.09240418503943243, -0.02811059532074356, -0.03725028398054603, -0.3793724930796184, 0.060308355842962076, 0.009447076053995836, -0.008916507759376576, -0.10717616397152213, -0.18601640530028626, 0.1589588703023956, 0.06612473959746575, 0.09155455914473062, -0.03807360952425944, 0.08291573335759733, -0.08812929555822752, -0.11045543315183175, 0.3889883789969118, -0.044758547817994106, -0.2504165236887179, 0.10850721628552204, -0.09055670978207338, -0.18118130939179344, 0.05273225203548607, 0.2034269929128258, 0.15680244146435718, -0.09982613204368758, 0.11388567895199614, -0.1257589083753134, 0.12657108829895916, -0.009664754491103322, -0.015484020765870809, 0.10436777912423406, 0.19240083224630278, 0.09936250425066406, 0.13752174972507514, -0.06655074937857296, -0.06090396729444987, -0.3072202338984138, -0.11995224221119363, -0.2553224186756109, 0.017680675193275278, -0.13759687491891734, -0.15248651277077827, 0.45212554658014836, 0.13868936194171272, 0.24666742102095957, 0.11507725130374494, 0.3192910177829234, 0.11103063177341889, -0.01828662933977811, 0.05859299787369213, 0.14783248426882845, 0.1809236009654246, 0.06362070990205547, -0.23292515661665483, 0.0468892085414968, 0.12851094160915205] |
1,802.08243 | Magnetic properties of metal-organic coordination networks based on 3d
transition metal atoms | The magnetic anisotropy and exchange coupling between spins localized at the
positions of 3d transition metal atoms forming two-dimensional metal-organic
coordination networks (MOCNs) grown on the Au(111) metal surface are studied.
In particular, we consider MOCNs made of Ni or Mn metal centers linked by TCNQ
(7,7,8,8-tetracyanoquinodimethane) organic ligands, which form rectangular
networks with 1:1 stoichiometry. Based on the analysis of X-ray magnetic
circular dichroism (XMCD) data taken at T= 2.5 K, we find that Ni atoms in the
Ni-TCNQ MOCNs are coupled ferromagnetically and do not show any significant
magnetic anisotropy, while Mn atoms in the Mn-TCNQ MOCNs are coupled
antiferromagnetically and do show a weak magnetic anisotropy with
in-planemagnetization. We explain these observations using both
amodelHamiltonian based on mean-fieldWeiss theory and density functional theory
calculations that include spin-orbit coupling. Our main conclusion is that the
antiferromagnetic coupling between Mn spins and the in-plane magnetization of
the Mn spins can be explained neglecting effects due to the presence of the
Au(111) surface, while for Ni-TCNQ the metal surface plays a role in
determining the absence of magnetic anisotropy in the system.
| cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.str-el | the magnetic anisotropy and exchange coupling between spins localized at the positions of 3d transition metal atoms forming twodimensional metalorganic coordination networks mocns grown on the au111 metal surface are studied in particular we consider mocns made of ni or mn metal centers linked by tcnq 7788tetracyanoquinodimethane organic ligands which form rectangular networks with 11 stoichiometry based on the analysis of xray magnetic circular dichroism xmcd data taken at t 25 k we find that ni atoms in the nitcnq mocns are coupled ferromagnetically and do not show any significant magnetic anisotropy while mn atoms in the mntcnq mocns are coupled antiferromagnetically and do show a weak magnetic anisotropy with inplanemagnetization we explain these observations using both amodelhamiltonian based on meanfieldweiss theory and density functional theory calculations that include spinorbit coupling our main conclusion is that the antiferromagnetic coupling between mn spins and the inplane magnetization of the mn spins can be explained neglecting effects due to the presence of the au111 surface while for nitcnq the metal surface plays a role in determining the absence of magnetic anisotropy in the system | [['the', 'magnetic', 'anisotropy', 'and', 'exchange', 'coupling', 'between', 'spins', 'localized', 'at', 'the', 'positions', 'of', '3d', 'transition', 'metal', 'atoms', 'forming', 'twodimensional', 'metalorganic', 'coordination', 'networks', 'mocns', 'grown', 'on', 'the', 'au111', 'metal', 'surface', 'are', 'studied', 'in', 'particular', 'we', 'consider', 'mocns', 'made', 'of', 'ni', 'or', 'mn', 'metal', 'centers', 'linked', 'by', 'tcnq', '7788tetracyanoquinodimethane', 'organic', 'ligands', 'which', 'form', 'rectangular', 'networks', 'with', '11', 'stoichiometry', 'based', 'on', 'the', 'analysis', 'of', 'xray', 'magnetic', 'circular', 'dichroism', 'xmcd', 'data', 'taken', 'at', 't', '25', 'k', 'we', 'find', 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1,802.08244 | Neutron stars exclude light dark baryons | Exotic new particles carrying baryon number and with mass of order the
nucleon mass have been proposed for various reasons including baryogenesis,
dark matter, mirror worlds, and the neutron lifetime puzzle. We show that the
existence of neutron stars with mass greater than 0.7 $M_\odot$ places severe
constraints on such particles, requiring them to be heavier than 1.2 GeV or to
have strongly repulsive self-interactions.
| hep-ph astro-ph.CO nucl-ex nucl-th | exotic new particles carrying baryon number and with mass of order the nucleon mass have been proposed for various reasons including baryogenesis dark matter mirror worlds and the neutron lifetime puzzle we show that the existence of neutron stars with mass greater than 07 m_odot places severe constraints on such particles requiring them to be heavier than 12 gev or to have strongly repulsive selfinteractions | [['exotic', 'new', 'particles', 'carrying', 'baryon', 'number', 'and', 'with', 'mass', 'of', 'order', 'the', 'nucleon', 'mass', 'have', 'been', 'proposed', 'for', 'various', 'reasons', 'including', 'baryogenesis', 'dark', 'matter', 'mirror', 'worlds', 'and', 'the', 'neutron', 'lifetime', 'puzzle', 'we', 'show', 'that', 'the', 'existence', 'of', 'neutron', 'stars', 'with', 'mass', 'greater', 'than', '07', 'm_odot', 'places', 'severe', 'constraints', 'on', 'such', 'particles', 'requiring', 'them', 'to', 'be', 'heavier', 'than', '12', 'gev', 'or', 'to', 'have', 'strongly', 'repulsive', 'selfinteractions']] | [-0.08297318758872839, 0.2845841355693455, -0.04822523598201, 0.16067535215272352, -0.14277268345825947, -0.1276886802739822, 0.021656026526425894, 0.30525408576314267, -0.10566133358157598, -0.45017347576526495, 0.01215296836140064, -0.33691877834498885, 0.06422553917464728, 0.16629030901240185, 0.04395623096049978, 0.026530122756958006, 0.03999344397049684, 0.05260971058160067, -0.05714152629773777, -0.27808861158465825, 0.360411657493275, 0.000641040733227363, 0.13110328232153104, 0.12486589047341393, 0.06360212990727562, -0.058943828775619087, 0.0293941431822112, -0.06260278637592609, -0.15740699906029756, 0.018313085237661234, 0.13837847162324649, 0.09701387116040748, 0.15117904082871975, -0.4435169090445225, -0.21705259099029578, 0.2584557407034131, 0.17639309456213736, 0.07564737194647583, -0.15012010141240004, -0.3071101577236102, 0.11324748450245421, -0.2503976242115291, -0.1733159207380735, -0.07102782833748139, 0.034222087951806875, -0.0033013371320871204, -0.25030787200308763, 0.12423649619584187, -0.025386488330192292, -0.030058192705305724, -0.05766257792711258, -0.22812998755834996, -0.047152586290254615, -0.03397207296310136, 0.17874053586990787, 0.01909667759990463, 0.184608077752189, -0.1770951619801613, -0.07903891268831033, 0.43494023313889135, -0.019457083614990833, -0.10776091205099454, 0.2012456425322363, -0.18176499483390496, -0.14969464913010597, 0.16215328114966934, 0.1717831340833352, 0.10360938327167578, -0.1446518168139916, 0.006741831618217895, -0.03221805554169875, 0.22719717310884824, 0.11885237100605782, 0.11645807856693864, 0.35954154226928947, 0.24437697209561102, 0.06114369415893005, -0.021804799341883223, -0.13866734963958152, -0.06143789355858014, -0.21967170469176311, -0.12022617988001842, -0.09903051900462462, 0.06447319368151232, -0.09871483567627505, -0.04877365591147771, 0.301083006681158, 0.12069575354958383, 0.18523377569822164, 0.0101714786571952, 0.31013521417402307, 0.06214412598369213, 0.14376436643875562, 0.07043403077584047, 0.33728658723859833, 0.17429077490591086, 0.07924621113074513, -0.22838550926401066, -0.024386858839828236, -0.0029039992950856686] |
1,802.08245 | Arbitrarily Substantial Number Representation for Complex Number | Researchers are often perplexed when their machine learning algorithms are
required to deal with complex number. Various strategies are commonly employed
to project complex number into real number, although it is frequently
sacrificing the information contained in the complex number. This paper
proposes a new method and four techniques to represent complex number as real
number, without having to sacrifice the information contained. The proposed
techniques are also capable of retrieving the original complex number from the
representing real number, with little to none of information loss. The
promising applicability of the proposed techniques has been demonstrated and
worth to receive further exploration in representing the complex number.
| cs.NA | researchers are often perplexed when their machine learning algorithms are required to deal with complex number various strategies are commonly employed to project complex number into real number although it is frequently sacrificing the information contained in the complex number this paper proposes a new method and four techniques to represent complex number as real number without having to sacrifice the information contained the proposed techniques are also capable of retrieving the original complex number from the representing real number with little to none of information loss the promising applicability of the proposed techniques has been demonstrated and worth to receive further exploration in representing the complex number | [['researchers', 'are', 'often', 'perplexed', 'when', 'their', 'machine', 'learning', 'algorithms', 'are', 'required', 'to', 'deal', 'with', 'complex', 'number', 'various', 'strategies', 'are', 'commonly', 'employed', 'to', 'project', 'complex', 'number', 'into', 'real', 'number', 'although', 'it', 'is', 'frequently', 'sacrificing', 'the', 'information', 'contained', 'in', 'the', 'complex', 'number', 'this', 'paper', 'proposes', 'a', 'new', 'method', 'and', 'four', 'techniques', 'to', 'represent', 'complex', 'number', 'as', 'real', 'number', 'without', 'having', 'to', 'sacrifice', 'the', 'information', 'contained', 'the', 'proposed', 'techniques', 'are', 'also', 'capable', 'of', 'retrieving', 'the', 'original', 'complex', 'number', 'from', 'the', 'representing', 'real', 'number', 'with', 'little', 'to', 'none', 'of', 'information', 'loss', 'the', 'promising', 'applicability', 'of', 'the', 'proposed', 'techniques', 'has', 'been', 'demonstrated', 'and', 'worth', 'to', 'receive', 'further', 'exploration', 'in', 'representing', 'the', 'complex', 'number']] | [-0.07103310160864904, 0.05035056863669996, -0.003973449080216664, 0.05871189773002967, -0.1598595390333449, -0.1278990151627955, 0.001274588596532811, 0.3840770351321057, -0.25943487504479923, -0.4227470533698107, 0.10515825799774137, -0.2670502692754208, -0.19581127615216515, 0.25157528764706244, -0.1067634436034563, 0.118147026695725, 0.04615831204379598, 0.09643502996294517, -0.00773373045484294, -0.3308579922088905, 0.3058050058402673, 0.012108970838771374, 0.2872991534812307, 0.008536602598959926, 0.0540003398416081, 0.0327714858662889, -0.07762394169198901, 0.048740673818866966, -0.024920320323737408, 0.178396407549304, 0.2937937500429581, 0.23978046224995828, 0.3458384449628216, -0.4334836909547448, -0.24710860088709052, 0.1978276775572104, 0.15145143520957963, 0.10854044555324233, -0.037667850433434874, -0.24303616262558433, 0.1336675898443597, -0.14924960424131886, -0.1028678213953282, -0.16216820716875158, -0.018085403010007686, 0.02137905943069469, -0.22677745842547328, -0.031054582380252046, -0.02030498199854736, 0.07082384893739666, 0.03452269844193426, -0.13719462344629896, -0.010461316371759124, 0.17251446613253965, 0.05530443134571046, 0.011099077165083683, 0.07984244882094639, -0.12442031934538304, -0.09522430181149738, 0.38956665544322244, 0.055613974038149334, -0.2676335308976747, 0.25931664891713474, -0.09032096071341247, -0.1372518200530774, 0.19820015269969762, 0.19240611256100237, 0.08408952393586298, -0.13008738692736155, 0.04196004345646576, -0.005477495948542599, 0.15829010834675972, 0.05730743991659471, 0.0738311437200065, 0.16970404752107612, 0.18310860818827576, 0.016082735421756904, 0.11925219077427217, -0.06952671934333113, -0.125534457999661, -0.19856894743646047, -0.14490092835923726, -0.20044126605649512, -0.0061803666909259775, -0.06834058024617627, -0.1470861928537488, 0.36859573600641277, 0.18761923895389945, 0.207346889255051, 0.032257513026706874, 0.37027864854920794, 0.04045285487922633, 0.10280685682071769, 0.07232506170920613, 0.14999738850316066, 0.08984257003154468, 0.11961218357707064, -0.1623460286996474, 0.07793232473906958, 0.009367722813126252] |
1,802.08246 | Characterizing Implicit Bias in Terms of Optimization Geometry | We study the implicit bias of generic optimization methods, such as mirror
descent, natural gradient descent, and steepest descent with respect to
different potentials and norms, when optimizing underdetermined linear
regression or separable linear classification problems. We explore the question
of whether the specific global minimum (among the many possible global minima)
reached by an algorithm can be characterized in terms of the potential or norm
of the optimization geometry, and independently of hyperparameter choices such
as step-size and momentum.
| stat.ML cs.LG | we study the implicit bias of generic optimization methods such as mirror descent natural gradient descent and steepest descent with respect to different potentials and norms when optimizing underdetermined linear regression or separable linear classification problems we explore the question of whether the specific global minimum among the many possible global minima reached by an algorithm can be characterized in terms of the potential or norm of the optimization geometry and independently of hyperparameter choices such as stepsize and momentum | [['we', 'study', 'the', 'implicit', 'bias', 'of', 'generic', 'optimization', 'methods', 'such', 'as', 'mirror', 'descent', 'natural', 'gradient', 'descent', 'and', 'steepest', 'descent', 'with', 'respect', 'to', 'different', 'potentials', 'and', 'norms', 'when', 'optimizing', 'underdetermined', 'linear', 'regression', 'or', 'separable', 'linear', 'classification', 'problems', 'we', 'explore', 'the', 'question', 'of', 'whether', 'the', 'specific', 'global', 'minimum', 'among', 'the', 'many', 'possible', 'global', 'minima', 'reached', 'by', 'an', 'algorithm', 'can', 'be', 'characterized', 'in', 'terms', 'of', 'the', 'potential', 'or', 'norm', 'of', 'the', 'optimization', 'geometry', 'and', 'independently', 'of', 'hyperparameter', 'choices', 'such', 'as', 'stepsize', 'and', 'momentum']] | [-0.0697131130262278, 0.01733372965409217, -0.060609971013400356, 0.0946384362061508, -0.0696099619846791, -0.21372862758580596, -0.0003014602611074224, 0.4137150349764852, -0.41524655777029695, -0.3270405729512277, 0.14217651036015014, -0.2057020991574973, -0.17518382864654997, 0.16534960253047756, -0.11709579366724938, 0.12650516030262224, 0.04754326721886173, 0.017738191620446743, -0.15920087748745573, -0.3069369448814541, 0.31444964432157574, 0.0642210774065461, 0.23255489200819285, -0.012234660424292087, 0.15979744305368512, 0.04121353396913037, 0.013067613411112688, 0.06608232493745163, -0.0674140123417601, 0.1093403483449947, 0.2632447565672919, 0.19298610980622471, 0.3567849448416382, -0.39763785535469653, -0.16323730551812332, 0.22039622914162466, 0.15951132898917422, 0.08690625848248601, -0.032494648406282065, -0.2330272130551748, 0.05020754060242325, -0.0840015743393451, -0.08809560587396845, -0.135727829055395, -0.03952532325638458, 0.11727266150701325, -0.3146474169567227, 0.0631911357777426, 0.059516626002732664, 0.10043265948770567, -0.0906513111491222, -0.1570260601816699, -0.01637093804893084, 0.06060857309676067, 0.12216120404191315, 0.05405705732118804, 0.1515975774731487, -0.14180166544392706, -0.12262461800710298, 0.3451821780297905, -0.05451080033672042, -0.2379180480260402, 0.18169167559826746, -0.0133793706423603, -0.10555887986556627, 0.041185964772012085, 0.23128510776441544, 0.17161476978217252, -0.12173199940971244, 0.09194922638416755, -0.020068771269870923, 0.10658353684702888, 0.06978382990928367, -0.014760048942116554, 0.13139017476351, 0.11961073699349072, 0.2143926932818431, 0.10501497610093793, -0.047665820477413946, -0.0954153761274938, -0.2886883735889569, -0.10403295371943386, -0.17528085466474294, 0.01203006019059103, -0.16489220994917558, -0.16677075918996706, 0.4246107635088265, 0.08685472247616417, 0.23210379674565046, 0.050609058164991436, 0.2851786607410759, 0.12370015737542417, 0.036666475841775535, 0.09082495363545603, 0.22087418314185925, 0.12343676964810583, 0.056249223521444944, -0.2827631659572944, 0.061895015608752144, 0.11303915175958537] |
1,802.08247 | Quality Assurance on Un-Doped CsI Crystals for the Mu2e Experiment | The Mu2e experiment is constructing a calorimeter consisting of 1,348 undoped
CsI crystals in two disks. Each crystal has a dimension of 34 x 34 x 200 mm,
and is readout by a large area silicon PMT array. A series of technical
specifications was defined according to physics requirements. Preproduction CsI
crystals were procured from three firms: Amcrys, Saint-Gobain and Shanghai
Institute of Ceramics. We report the quality assurance on crystal's
scintillation properties and their radiation hardness against ionization dose
and neutrons. With a fast decay time of 30 ns and a light output of more than
100 p.e./MeV measured with a bi-alkali PMT, undoped CsI crystals provide a
cost-effective solution for the Mu2e experiment.
| physics.ins-det hep-ex | the mu2e experiment is constructing a calorimeter consisting of 1348 undoped csi crystals in two disks each crystal has a dimension of 34 x 34 x 200 mm and is readout by a large area silicon pmt array a series of technical specifications was defined according to physics requirements preproduction csi crystals were procured from three firms amcrys saintgobain and shanghai institute of ceramics we report the quality assurance on crystals scintillation properties and their radiation hardness against ionization dose and neutrons with a fast decay time of 30 ns and a light output of more than 100 pemev measured with a bialkali pmt undoped csi crystals provide a costeffective solution for the mu2e experiment | [['the', 'mu2e', 'experiment', 'is', 'constructing', 'a', 'calorimeter', 'consisting', 'of', '1348', 'undoped', 'csi', 'crystals', 'in', 'two', 'disks', 'each', 'crystal', 'has', 'a', 'dimension', 'of', '34', 'x', '34', 'x', '200', 'mm', 'and', 'is', 'readout', 'by', 'a', 'large', 'area', 'silicon', 'pmt', 'array', 'a', 'series', 'of', 'technical', 'specifications', 'was', 'defined', 'according', 'to', 'physics', 'requirements', 'preproduction', 'csi', 'crystals', 'were', 'procured', 'from', 'three', 'firms', 'amcrys', 'saintgobain', 'and', 'shanghai', 'institute', 'of', 'ceramics', 'we', 'report', 'the', 'quality', 'assurance', 'on', 'crystals', 'scintillation', 'properties', 'and', 'their', 'radiation', 'hardness', 'against', 'ionization', 'dose', 'and', 'neutrons', 'with', 'a', 'fast', 'decay', 'time', 'of', '30', 'ns', 'and', 'a', 'light', 'output', 'of', 'more', 'than', '100', 'pemev', 'measured', 'with', 'a', 'bialkali', 'pmt', 'undoped', 'csi', 'crystals', 'provide', 'a', 'costeffective', 'solution', 'for', 'the', 'mu2e', 'experiment']] | [-0.08609482914458536, 0.1754078362300469, -0.04543442642643002, -0.027846849786950963, -0.022232342192805128, -0.18345455771818625, 0.059606449948133605, 0.4228254698805119, -0.13016397244013078, -0.3569082431985359, 0.09821661868185752, -0.3834571116032046, 0.030338216483135495, 0.19930199797575673, -0.029509853187687042, 0.0909420011050411, 0.05036114658670206, -0.06532340123202741, -0.08128898007501113, -0.25301910378038883, 0.14781920530163406, 0.12696054641958, 0.34981520480492656, 0.0021575769785334145, 0.1759308378065103, -0.027603897872675014, 0.02213985360178508, -0.033806425521904375, -0.11986917544262517, 0.06968199358762879, 0.3346404663303442, 0.05881988190792566, 0.20316228049954302, -0.4350037634568779, -0.14151671945052058, 0.0265486296215258, 0.017234178586238016, -0.0029568773563624475, -0.10885790947034829, -0.25299857275789245, 0.09335072759310142, -0.1785032215871309, -0.08038921795148206, 0.05248908832947021, -0.049400963416127, 0.038005207060721885, -0.22787758523369567, -0.02690792121319917, -0.03263298485003281, 0.09137500741666085, -0.08200284478810142, -0.18337569892479988, 0.026766316225882946, 0.023192560250192815, -0.018993820468159884, 0.045890337706894796, 0.20610828576364407, -0.09511126058274194, -0.11493282450215989, 0.36037760936622426, -0.018544186655816974, -0.0954322803381569, 0.12503804405334226, -0.23008566897509522, -0.05213407884564316, 0.26235964878772694, 0.14656843865043157, 0.07967509129983291, -0.2106967688897592, 0.021516359057338712, 0.0043209039773628635, 0.30819968414378535, 0.12852507752872872, 0.07371768774056252, 0.17950030973818348, 0.30723692040804673, 0.004812117711959505, 0.1537999707798008, -0.16235860477772485, 0.05528648795760155, -0.25950638418138977, -0.24442544515528553, -0.13738212263080896, 0.11942829611392594, -0.06440352677255808, -0.12051195384967223, 0.3696031917638162, 0.015806391202076747, 0.06923913389542385, -0.024595971840123337, 0.2673960206621702, -0.028681255198949783, 0.047882177227732255, 0.008180484273716024, 0.2566287757730798, 0.16290090982434585, 0.17406515413364232, -0.15801835625244534, 0.07231910035357271, -0.0049876198417654165] |
1,802.08248 | PSR J1755$-$2550: A young radio pulsar with a massive, compact companion | Radio pulsars found in binary systems with short orbital periods are usually
fast spinning as a consequence of recycling via mass transfer from their
companion stars; this process is also thought to decrease the magnetic field of
the neutron star being recycled. Here, we report on timing observations of the
recently discovered binary PSR J1755$-$2550 and find that this pulsar is an
exception: with a characteristic age of 2.1 Myr, it is relatively young;
furthermore, with a spin period of 315 ms and a surface magnetic field strength
at its poles of 0.88$\times$10$^{12}$ G the pulsar shows no sign of having been
recycled. Based on its timing and orbital characteristics, the pulsar either
has a massive white dwarf (WD) or a neutron star (NS) companion. To distinguish
between these two cases, we searched radio observations for a potential
recycled pulsar companion and analysed archival optical data for a potential WD
companion. Neither work returned conclusive detections. We apply population
synthesis modelling and find that both solutions are roughly equally probable.
Our population synthesis also predicts a minimum mass of 0.90 M$_{\odot}$ for
the companion star to PSR J1755$-$2550 and we simulate the systemic runaway
velocities for the resulting WDNS systems which may merge and possibly produce
Ca-rich supernovae. Whether PSR J1755$-$2550 hosts a WD or a NS companion star,
it is certainly a member of a rare subpopulation of binary radio pulsars.
| astro-ph.HE astro-ph.SR | radio pulsars found in binary systems with short orbital periods are usually fast spinning as a consequence of recycling via mass transfer from their companion stars this process is also thought to decrease the magnetic field of the neutron star being recycled here we report on timing observations of the recently discovered binary psr j17552550 and find that this pulsar is an exception with a characteristic age of 21 myr it is relatively young furthermore with a spin period of 315 ms and a surface magnetic field strength at its poles of 088times1012 g the pulsar shows no sign of having been recycled based on its timing and orbital characteristics the pulsar either has a massive white dwarf wd or a neutron star ns companion to distinguish between these two cases we searched radio observations for a potential recycled pulsar companion and analysed archival optical data for a potential wd companion neither work returned conclusive detections we apply population synthesis modelling and find that both solutions are roughly equally probable our population synthesis also predicts a minimum mass of 090 m_odot for the companion star to psr j17552550 and we simulate the systemic runaway velocities for the resulting wdns systems which may merge and possibly produce carich supernovae whether psr j17552550 hosts a wd or a ns companion star it is certainly a member of a rare subpopulation of binary radio pulsars | [['radio', 'pulsars', 'found', 'in', 'binary', 'systems', 'with', 'short', 'orbital', 'periods', 'are', 'usually', 'fast', 'spinning', 'as', 'a', 'consequence', 'of', 'recycling', 'via', 'mass', 'transfer', 'from', 'their', 'companion', 'stars', 'this', 'process', 'is', 'also', 'thought', 'to', 'decrease', 'the', 'magnetic', 'field', 'of', 'the', 'neutron', 'star', 'being', 'recycled', 'here', 'we', 'report', 'on', 'timing', 'observations', 'of', 'the', 'recently', 'discovered', 'binary', 'psr', 'j17552550', 'and', 'find', 'that', 'this', 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1,802.08249 | On the Convergence and Robustness of Training GANs with Regularized
Optimal Transport | Generative Adversarial Networks (GANs) are one of the most practical methods
for learning data distributions. A popular GAN formulation is based on the use
of Wasserstein distance as a metric between probability distributions.
Unfortunately, minimizing the Wasserstein distance between the data
distribution and the generative model distribution is a computationally
challenging problem as its objective is non-convex, non-smooth, and even hard
to compute. In this work, we show that obtaining gradient information of the
smoothed Wasserstein GAN formulation, which is based on regularized Optimal
Transport (OT), is computationally effortless and hence one can apply first
order optimization methods to minimize this objective. Consequently, we
establish theoretical convergence guarantee to stationarity for a proposed
class of GAN optimization algorithms. Unlike the original non-smooth
formulation, our algorithm only requires solving the discriminator to
approximate optimality. We apply our method to learning MNIST digits as well as
CIFAR-10images. Our experiments show that our method is computationally
efficient and generates images comparable to the state of the art algorithms
given the same architecture and computational power.
| cs.LG math.OC stat.ML | generative adversarial networks gans are one of the most practical methods for learning data distributions a popular gan formulation is based on the use of wasserstein distance as a metric between probability distributions unfortunately minimizing the wasserstein distance between the data distribution and the generative model distribution is a computationally challenging problem as its objective is nonconvex nonsmooth and even hard to compute in this work we show that obtaining gradient information of the smoothed wasserstein gan formulation which is based on regularized optimal transport ot is computationally effortless and hence one can apply first order optimization methods to minimize this objective consequently we establish theoretical convergence guarantee to stationarity for a proposed class of gan optimization algorithms unlike the original nonsmooth formulation our algorithm only requires solving the discriminator to approximate optimality we apply our method to learning mnist digits as well as cifar10images our experiments show that our method is computationally efficient and generates images comparable to the state of the art algorithms given the same architecture and computational power | [['generative', 'adversarial', 'networks', 'gans', 'are', 'one', 'of', 'the', 'most', 'practical', 'methods', 'for', 'learning', 'data', 'distributions', 'a', 'popular', 'gan', 'formulation', 'is', 'based', 'on', 'the', 'use', 'of', 'wasserstein', 'distance', 'as', 'a', 'metric', 'between', 'probability', 'distributions', 'unfortunately', 'minimizing', 'the', 'wasserstein', 'distance', 'between', 'the', 'data', 'distribution', 'and', 'the', 'generative', 'model', 'distribution', 'is', 'a', 'computationally', 'challenging', 'problem', 'as', 'its', 'objective', 'is', 'nonconvex', 'nonsmooth', 'and', 'even', 'hard', 'to', 'compute', 'in', 'this', 'work', 'we', 'show', 'that', 'obtaining', 'gradient', 'information', 'of', 'the', 'smoothed', 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1,802.0825 | SeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural
Networks by Selective Network Augmentation | Lifelong learning aims to develop machine learning systems that can learn new
tasks while preserving the performance on previous learned tasks. In this paper
we present a method to overcome catastrophic forgetting on convolutional neural
networks, that learns new tasks and preserves the performance on old tasks
without accessing the data of the original model, by selective network
augmentation. The experiment results showed that SeNA-CNN, in some scenarios,
outperforms the state-of-art Learning without Forgetting algorithm. Results
also showed that in some situations it is better to use SeNA-CNN instead of
training a neural network using isolated learning.
| cs.LG stat.ML | lifelong learning aims to develop machine learning systems that can learn new tasks while preserving the performance on previous learned tasks in this paper we present a method to overcome catastrophic forgetting on convolutional neural networks that learns new tasks and preserves the performance on old tasks without accessing the data of the original model by selective network augmentation the experiment results showed that senacnn in some scenarios outperforms the stateofart learning without forgetting algorithm results also showed that in some situations it is better to use senacnn instead of training a neural network using isolated learning | [['lifelong', 'learning', 'aims', 'to', 'develop', 'machine', 'learning', 'systems', 'that', 'can', 'learn', 'new', 'tasks', 'while', 'preserving', 'the', 'performance', 'on', 'previous', 'learned', 'tasks', 'in', 'this', 'paper', 'we', 'present', 'a', 'method', 'to', 'overcome', 'catastrophic', 'forgetting', 'on', 'convolutional', 'neural', 'networks', 'that', 'learns', 'new', 'tasks', 'and', 'preserves', 'the', 'performance', 'on', 'old', 'tasks', 'without', 'accessing', 'the', 'data', 'of', 'the', 'original', 'model', 'by', 'selective', 'network', 'augmentation', 'the', 'experiment', 'results', 'showed', 'that', 'senacnn', 'in', 'some', 'scenarios', 'outperforms', 'the', 'stateofart', 'learning', 'without', 'forgetting', 'algorithm', 'results', 'also', 'showed', 'that', 'in', 'some', 'situations', 'it', 'is', 'better', 'to', 'use', 'senacnn', 'instead', 'of', 'training', 'a', 'neural', 'network', 'using', 'isolated', 'learning']] | [-0.030604345723986626, -0.02136327434135111, -0.08915127776563167, 0.0621579848425953, -0.15015297518356852, -0.21735364395732942, 0.059106042146633724, 0.47987062115418283, -0.2669410206769642, -0.32295338319320427, 0.02453298604630522, -0.2382499401616913, -0.26143053914175224, 0.22876808833281853, -0.22372633752069976, 0.1122252429823244, 0.2091992186535591, 0.058870241967471024, -0.11388477621367202, -0.3472833857871592, 0.3389647364714428, 0.04579797894938996, 0.34404764831262197, -0.012291549533409508, 0.15237323126853689, -0.036792509573952935, 0.02382540671081331, -0.03870287793443391, -0.03299615202428724, 0.18167500997844496, 0.3258503518630996, 0.2524323543288598, 0.39563897030526085, -0.41254156692639776, -0.2800051486756849, 0.11896307471477868, 0.14449952249660303, 0.12534099080795913, -0.03562759532421631, -0.34176784912614444, 0.12368558011213808, -0.15997213109543448, 0.0463116022464084, -0.20589673623050514, -0.09374146136504255, -0.035141711386447574, -0.28263895295952496, 0.006562208504060675, 0.14492438247329312, 0.04597500561840685, -0.042734209526526304, -0.09894672478549182, 0.07165316109986682, 0.1484101741599213, 0.026198123524112528, 0.0717711557045971, 0.15863824130379056, -0.21850538717729873, -0.2214677961714762, 0.3262816725985, -0.04534816196139314, -0.17614160629087372, 0.21345023488331782, 0.021575868624801698, -0.19585830867290496, 0.08019251971456566, 0.24733596641178193, 0.08329989228789744, -0.16174870915220757, 0.006500425404795495, -0.060409781807347344, 0.17319406073442414, 0.0341093499409525, -0.04719092129288535, 0.09734267159610202, 0.2964476637266527, 0.03690584853879715, 0.14971812524783767, -0.09489011666737497, -0.06085530737120854, -0.1814546079227799, -0.06807637922955971, -0.20602214605988642, -0.024481276589396753, -0.08771983069891576, -0.0753540573563537, 0.3890364249089831, 0.28268376562352243, 0.23594440340407585, 0.1657423024090301, 0.38472868253133796, -0.027320994871766553, 0.15602415289521512, 0.15818395474925637, 0.1672483799347997, -0.018592456176778988, 0.18810738715049075, -0.21590907778100749, 0.12253833692520857, 0.04858034994257124] |
1,802.08251 | SMAGEXP: a galaxy tool suite for transcriptomics data meta-analysis | Bakground: With the proliferation of available microarray and high throughput
sequencing experiments in the public domain, the use of meta-analysis methods
increases. In these experiments, where the sample size is often limited,
meta-analysis offers the possibility to considerably enhance the statistical
power and give more accurate results. For those purposes, it combines either
effect sizes or results of single studies in a appropriate manner. R packages
metaMA and metaRNASeq perform meta-analysis on microarray and NGS data,
respectively. They are not interchangeable as they rely on statistical modeling
specific to each technology.
Results: SMAGEXP (Statistical Meta-Analysis for Gene EXPression) integrates
metaMA and metaRNAseq packages into Galaxy. We aim to propose a unified way to
carry out meta-analysis of gene expression data, while taking care of their
specificities. We have developed this tool suite to analyse microarray data
from Gene Expression Omnibus (GEO) database or custom data from affymetrix
microarrays. These data are then combined to carry out meta-analysis using
metaMA package. SMAGEXP also offers to combine raw read counts from Next
Generation Sequencing (NGS) experiments using DESeq2 and metaRNASeq package. In
both cases, key values, independent from the technology type, are reported to
judge the quality of the meta-analysis. These tools are available on the Galaxy
main tool shed. Source code, help and installation instructions are available
on github.
Conclusion: The use of Galaxy offers an easy-to-use gene expression
meta-analysis tool suite based on the metaMA and metaRNASeq packages.
| q-bio.GN q-bio.QM stat.AP | bakground with the proliferation of available microarray and high throughput sequencing experiments in the public domain the use of metaanalysis methods increases in these experiments where the sample size is often limited metaanalysis offers the possibility to considerably enhance the statistical power and give more accurate results for those purposes it combines either effect sizes or results of single studies in a appropriate manner r packages metama and metarnaseq perform metaanalysis on microarray and ngs data respectively they are not interchangeable as they rely on statistical modeling specific to each technology results smagexp statistical metaanalysis for gene expression integrates metama and metarnaseq packages into galaxy we aim to propose a unified way to carry out metaanalysis of gene expression data while taking care of their specificities we have developed this tool suite to analyse microarray data from gene expression omnibus geo database or custom data from affymetrix microarrays these data are then combined to carry out metaanalysis using metama package smagexp also offers to combine raw read counts from next generation sequencing ngs experiments using deseq2 and metarnaseq package in both cases key values independent from the technology type are reported to judge the quality of the metaanalysis these tools are available on the galaxy main tool shed source code help and installation instructions are available on github conclusion the use of galaxy offers an easytouse gene expression metaanalysis tool suite based on the metama and metarnaseq packages | [['bakground', 'with', 'the', 'proliferation', 'of', 'available', 'microarray', 'and', 'high', 'throughput', 'sequencing', 'experiments', 'in', 'the', 'public', 'domain', 'the', 'use', 'of', 'metaanalysis', 'methods', 'increases', 'in', 'these', 'experiments', 'where', 'the', 'sample', 'size', 'is', 'often', 'limited', 'metaanalysis', 'offers', 'the', 'possibility', 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1,802.08252 | The iisignature library: efficient calculation of iterated-integral
signatures and log signatures | Iterated-integral signatures and log signatures are vectors calculated from a
path that characterise its shape. They come from the theory of differential
equations driven by rough paths, and also have applications in statistics and
machine learning. We present algorithms for efficiently calculating these
signatures, and benchmark their performance. We release the methods as a Python
package.
| cs.DS cs.MS math.RA | iteratedintegral signatures and log signatures are vectors calculated from a path that characterise its shape they come from the theory of differential equations driven by rough paths and also have applications in statistics and machine learning we present algorithms for efficiently calculating these signatures and benchmark their performance we release the methods as a python package | [['iteratedintegral', 'signatures', 'and', 'log', 'signatures', 'are', 'vectors', 'calculated', 'from', 'a', 'path', 'that', 'characterise', 'its', 'shape', 'they', 'come', 'from', 'the', 'theory', 'of', 'differential', 'equations', 'driven', 'by', 'rough', 'paths', 'and', 'also', 'have', 'applications', 'in', 'statistics', 'and', 'machine', 'learning', 'we', 'present', 'algorithms', 'for', 'efficiently', 'calculating', 'these', 'signatures', 'and', 'benchmark', 'their', 'performance', 'we', 'release', 'the', 'methods', 'as', 'a', 'python', 'package']] | [-0.04717784500514556, 0.06267991163102644, -0.11617998273660694, 0.1097924071655143, -0.07613574201241136, -0.1269036961031296, 0.017578764716745354, 0.4278922529691564, -0.3331667315713795, -0.3370305437128991, 0.0987733341483233, -0.3277204663359693, -0.1804179909106876, 0.28767107154375743, -0.017505183117464185, 0.07158675366476278, 0.13437274714721884, -0.018962515335130905, -0.08890054124432416, -0.23116997177047388, 0.26997773242653367, 0.03184054689648162, 0.23032651410072244, -0.002592090400867164, 0.09502774628344923, -0.03209931142295578, -0.08978876985825732, 0.05356408625084441, -0.20146106677527445, 0.15056963341443666, 0.2791801935860089, 0.20124614551397307, 0.22123445397508995, -0.4015342784114182, -0.17488522455096245, 0.08536350342910737, 0.11932532046090014, 0.1344877120032574, -0.07039663100814712, -0.27932808604756637, 0.07446615078203779, -0.15785757952003873, -0.07547240290607858, -0.1436396502415716, 0.0063848333915562504, 0.06819833598897926, -0.21517821148570096, 0.028972013948597514, 0.02593074817975451, 0.09566185387250568, -0.04530817379418295, -0.11720028651013438, -0.01799967110855505, 0.13507985975593328, 0.004845467539520801, -0.01640341045900381, 0.1339296758607296, -0.15821741256929403, -0.194747322704643, 0.36055729844208273, -0.08381265655459304, -0.17395095592032053, 0.20645185537120728, -0.03113019367447123, -0.14913529913506604, 0.13062084807149535, 0.245831351569255, 0.16034426633268595, -0.1689097246354712, 0.10064607946385097, 0.03349557314400694, 0.0870048004560106, 0.029978135176601688, 0.03452803880541718, 0.1984484860104203, 0.09180681314319372, -0.022447001750281612, 0.11117899891853865, -0.09586844874346363, -0.08738705415245411, -0.2901200783838119, -0.14146027334001182, -0.13932776525117724, -0.023378675737019097, -0.05264999324052561, -0.17518486099184624, 0.3603168547353042, 0.19017479647715976, 0.1964700773491391, 0.05516708066820034, 0.306791413841503, 0.11701705090360649, 0.07563444007869943, 0.1432486520414906, 0.1652871879185633, 0.10461080967875855, 0.11721295643863934, -0.16953208161950378, 0.06384522448726264, 0.0511413678759709] |
1,802.08253 | A 5D, polarised, Bethe-Heitler event generator for $\gamma \to e^+e^-$
conversion | We describe a new version of the 5D, exact, polarised, Bethe-Heitler event
generator of $\gamma$-ray conversions to $e^+e^-$, developed in the context of
the HARPO project, that is able to simulate successive events with different
photon energies and on different atomic targets without any substantial CPU
overhead. The strong correlation between kinematic variables in the divergence
of the five-dimensional differential cross section are mitigated by performing
each step of the conversion in the appropriate Lorentz frame. We extend the
verification range down to 1 keV above threshold and up to 1 EeV. This work
could pave the way to the precise simulation of the high-performance
$\gamma$-ray telescopes and polarimeters of the post-Fermi-LAT area.
| hep-ph astro-ph.IM physics.data-an physics.ins-det | we describe a new version of the 5d exact polarised betheheitler event generator of gammaray conversions to ee developed in the context of the harpo project that is able to simulate successive events with different photon energies and on different atomic targets without any substantial cpu overhead the strong correlation between kinematic variables in the divergence of the fivedimensional differential cross section are mitigated by performing each step of the conversion in the appropriate lorentz frame we extend the verification range down to 1 kev above threshold and up to 1 eev this work could pave the way to the precise simulation of the highperformance gammaray telescopes and polarimeters of the postfermilat area | [['we', 'describe', 'a', 'new', 'version', 'of', 'the', '5d', 'exact', 'polarised', 'betheheitler', 'event', 'generator', 'of', 'gammaray', 'conversions', 'to', 'ee', 'developed', 'in', 'the', 'context', 'of', 'the', 'harpo', 'project', 'that', 'is', 'able', 'to', 'simulate', 'successive', 'events', 'with', 'different', 'photon', 'energies', 'and', 'on', 'different', 'atomic', 'targets', 'without', 'any', 'substantial', 'cpu', 'overhead', 'the', 'strong', 'correlation', 'between', 'kinematic', 'variables', 'in', 'the', 'divergence', 'of', 'the', 'fivedimensional', 'differential', 'cross', 'section', 'are', 'mitigated', 'by', 'performing', 'each', 'step', 'of', 'the', 'conversion', 'in', 'the', 'appropriate', 'lorentz', 'frame', 'we', 'extend', 'the', 'verification', 'range', 'down', 'to', '1', 'kev', 'above', 'threshold', 'and', 'up', 'to', '1', 'eev', 'this', 'work', 'could', 'pave', 'the', 'way', 'to', 'the', 'precise', 'simulation', 'of', 'the', 'highperformance', 'gammaray', 'telescopes', 'and', 'polarimeters', 'of', 'the', 'postfermilat', 'area']] | [-0.0868259591640838, 0.12937677082040214, -0.03295792816009323, 0.11739373177104946, -0.0608101806297522, -0.08282633831342016, 0.048147569568495134, 0.40879062430134844, -0.21720556965945953, -0.36040261374520405, 0.005958477526811683, -0.2794677624146321, -0.012640430979185371, 0.2243745048929538, -0.007439813776207822, 0.07657573324727959, 0.0789248220950997, -0.03680043299183516, -0.09541279896802735, -0.21193846372105846, 0.28795370924386327, 0.15714217162121713, 0.2613889317976178, 0.04669884743842496, 0.1279403395684702, 0.019000769100135324, -0.050525270718415935, -0.053043446877771724, -0.0978969722848108, 0.12444545697923916, 0.26943639465831176, 0.12093861406434112, 0.17873633257113397, -0.41145311392444583, -0.1682678192404897, 0.10199726933102024, 0.12296366919222887, 0.07200557935902907, -0.020288884096122013, -0.2866708862212753, 0.07954273324243591, -0.20581265708980417, -0.11984985808625684, -0.018659370327700993, -0.01072994213401606, 0.023315429978538305, -0.23478910818396667, 0.03419946266512852, 0.031556789773666036, 0.01810348920532436, -0.028749352142248035, -0.0816182061930054, 0.017129300989576483, 0.10518531853449531, 0.05173902408777004, 0.0549623354922265, 0.1456659421175053, -0.11549086650484242, -0.14149386208477413, 0.3645602784984346, -0.04426001999049082, -0.11937662573265177, 0.15714024191506074, -0.1752281712002254, -0.14927315394119692, 0.18374301250358777, 0.2147836593628329, 0.10106556583195925, -0.1771735427028034, 0.06472689296164649, 0.031142266365350224, 0.18855717933911365, 0.09545346445728294, 0.015863993608426035, 0.17301457416033372, 0.16721615471604828, 0.06876410297783357, 0.12475384153159601, -0.16300355261358032, -0.04887414988895346, -0.3668399678177333, -0.15747165631182725, -0.10084503473730624, 0.07019656501298803, -0.06891073768370656, -0.07021346599296001, 0.3803715564967466, 0.1591293282577421, 0.18969595145192994, 0.028476111058677946, 0.32174096402013674, 0.10161383539837386, 0.09203627547997582, 0.0349997744986987, 0.29592461203407894, 0.0960090004893053, 0.11467905434048069, -0.22317338622191787, 0.002470416996012708, 0.020106741480828662] |
1,802.08254 | BigDataBench: A Scalable and Unified Big Data and AI Benchmark Suite | Several fundamental changes in technology indicate domain-specific hardware
and software co-design is the only path left. In this context, architecture,
system, data management, and machine learning communities pay greater attention
to innovative big data and AI algorithms, architecture, and systems.
Unfortunately, complexity, diversity, frequently-changed workloads, and rapid
evolution of big data and AI systems raise great challenges. First, the
traditional benchmarking methodology that creates a new benchmark or proxy for
every possible workload is not scalable, or even impossible for Big Data and AI
benchmarking. Second, it is prohibitively expensive to tailor the architecture
to characteristics of one or more application or even a domain of applications.
We consider each big data and AI workload as a pipeline of one or more classes
of units of computation performed on different initial or intermediate data
inputs, each class of which we call a data motif. On the basis of our previous
work that identifies eight data motifs taking up most of the run time of a wide
variety of big data and AI workloads, we propose a scalable benchmarking
methodology that uses the combination of one or more data motifs---to represent
diversity of big data and AI workloads. Following this methodology, we present
a unified big data and AI benchmark suite---BigDataBench 4.0, publicly
available from~\url{http://prof.ict.ac.cn/BigDataBench}. This unified benchmark
suite sheds new light on domain-specific hardware and software co-design:
tailoring the system and architecture to characteristics of the unified eight
data motifs other than one or more application case by case. Also, for the
first time, we comprehensively characterize the CPU pipeline efficiency using
the benchmarks of seven workload types in BigDataBench 4.0.
| cs.DC cs.AI cs.PF | several fundamental changes in technology indicate domainspecific hardware and software codesign is the only path left in this context architecture system data management and machine learning communities pay greater attention to innovative big data and ai algorithms architecture and systems unfortunately complexity diversity frequentlychanged workloads and rapid evolution of big data and ai systems raise great challenges first the traditional benchmarking methodology that creates a new benchmark or proxy for every possible workload is not scalable or even impossible for big data and ai benchmarking second it is prohibitively expensive to tailor the architecture to characteristics of one or more application or even a domain of applications we consider each big data and ai workload as a pipeline of one or more classes of units of computation performed on different initial or intermediate data inputs each class of which we call a data motif on the basis of our previous work that identifies eight data motifs taking up most of the run time of a wide variety of big data and ai workloads we propose a scalable benchmarking methodology that uses the combination of one or more data motifsto represent diversity of big data and ai workloads following this methodology we present a unified big data and ai benchmark suitebigdatabench 40 publicly available fromurlhttpprofictaccnbigdatabench this unified benchmark suite sheds new light on domainspecific hardware and software codesign tailoring the system and architecture to characteristics of the unified eight data motifs other than one or more application case by case also for the first time we comprehensively characterize the cpu pipeline efficiency using the benchmarks of seven workload types in bigdatabench 40 | [['several', 'fundamental', 'changes', 'in', 'technology', 'indicate', 'domainspecific', 'hardware', 'and', 'software', 'codesign', 'is', 'the', 'only', 'path', 'left', 'in', 'this', 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1,802.08255 | Agama reference documentation | Agama (Action-based Galaxy Modelling Architecture) is a software library
intended for a broad range of tasks within the field of stellar dynamics. As
the name suggests, it is centered around the use of action/angle formalism to
describe the structure of stellar systems, but this is only one of its many
facets. The library contains a powerful framework for dealing with arbitrary
density/potential profiles and distribution functions (analytic, extracted from
N-body models, or fitted to the data), a vast collection of general-purpose
mathematical routines, and covers many aspects of galaxy dynamics up to the
very high-level interface for constructing self-consistent galaxy models.
This document serves two purposes. First of all, this is a detailed reference
for the library itself. Second, it describes various mathematical and numerical
methods that could be applicable in a broader context. These include: (1) one-
and multidimensional interpolation using cubic and quintic splines; (2)
penalized spline fitting of noisy data and penalized spline density estimation;
(3) adaptive rejection sampling from multidimensional probability
distributions; (4) computation of gravitational potentials using spherical- and
azimuthal-harmonic expansions; (5) Staeckel fudge method for computing
action/angle variables; (6) a general discussion about good programming
practices.
| astro-ph.IM astro-ph.GA | agama actionbased galaxy modelling architecture is a software library intended for a broad range of tasks within the field of stellar dynamics as the name suggests it is centered around the use of actionangle formalism to describe the structure of stellar systems but this is only one of its many facets the library contains a powerful framework for dealing with arbitrary densitypotential profiles and distribution functions analytic extracted from nbody models or fitted to the data a vast collection of generalpurpose mathematical routines and covers many aspects of galaxy dynamics up to the very highlevel interface for constructing selfconsistent galaxy models this document serves two purposes first of all this is a detailed reference for the library itself second it describes various mathematical and numerical methods that could be applicable in a broader context these include 1 one and multidimensional interpolation using cubic and quintic splines 2 penalized spline fitting of noisy data and penalized spline density estimation 3 adaptive rejection sampling from multidimensional probability distributions 4 computation of gravitational potentials using spherical and azimuthalharmonic expansions 5 staeckel fudge method for computing actionangle variables 6 a general discussion about good programming practices | [['agama', 'actionbased', 'galaxy', 'modelling', 'architecture', 'is', 'a', 'software', 'library', 'intended', 'for', 'a', 'broad', 'range', 'of', 'tasks', 'within', 'the', 'field', 'of', 'stellar', 'dynamics', 'as', 'the', 'name', 'suggests', 'it', 'is', 'centered', 'around', 'the', 'use', 'of', 'actionangle', 'formalism', 'to', 'describe', 'the', 'structure', 'of', 'stellar', 'systems', 'but', 'this', 'is', 'only', 'one', 'of', 'its', 'many', 'facets', 'the', 'library', 'contains', 'a', 'powerful', 'framework', 'for', 'dealing', 'with', 'arbitrary', 'densitypotential', 'profiles', 'and', 'distribution', 'functions', 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1,802.08256 | Error correction for gate operations in systems of exchange-coupled
singlet-triplet qubits in double quantum dots | We present a scheme for correcting for crosstalk- and noise-induced errors in
exchange-coupled singlet-triplet semiconductor double quantum dot qubits. While
exchange coupling allows the coupling strength to be controlled independently
of the intraqubit exchange couplings, there is also the problem of leakage,
which must be addressed. We show that, if a large magnetic field difference is
present between the two qubits, leakage is suppressed. We then develop pulse
sequences that correct for crosstalk- and noise-induced errors and present
parameters describing them for the 24 Clifford gates. We determine the
infidelity for both the uncorrected and corrected gates as a function of the
error-inducing terms and show that our corrected pulse sequences reduce the
error by several orders of magnitude.
| cond-mat.mes-hall quant-ph | we present a scheme for correcting for crosstalk and noiseinduced errors in exchangecoupled singlettriplet semiconductor double quantum dot qubits while exchange coupling allows the coupling strength to be controlled independently of the intraqubit exchange couplings there is also the problem of leakage which must be addressed we show that if a large magnetic field difference is present between the two qubits leakage is suppressed we then develop pulse sequences that correct for crosstalk and noiseinduced errors and present parameters describing them for the 24 clifford gates we determine the infidelity for both the uncorrected and corrected gates as a function of the errorinducing terms and show that our corrected pulse sequences reduce the error by several orders of magnitude | [['we', 'present', 'a', 'scheme', 'for', 'correcting', 'for', 'crosstalk', 'and', 'noiseinduced', 'errors', 'in', 'exchangecoupled', 'singlettriplet', 'semiconductor', 'double', 'quantum', 'dot', 'qubits', 'while', 'exchange', 'coupling', 'allows', 'the', 'coupling', 'strength', 'to', 'be', 'controlled', 'independently', 'of', 'the', 'intraqubit', 'exchange', 'couplings', 'there', 'is', 'also', 'the', 'problem', 'of', 'leakage', 'which', 'must', 'be', 'addressed', 'we', 'show', 'that', 'if', 'a', 'large', 'magnetic', 'field', 'difference', 'is', 'present', 'between', 'the', 'two', 'qubits', 'leakage', 'is', 'suppressed', 'we', 'then', 'develop', 'pulse', 'sequences', 'that', 'correct', 'for', 'crosstalk', 'and', 'noiseinduced', 'errors', 'and', 'present', 'parameters', 'describing', 'them', 'for', 'the', '24', 'clifford', 'gates', 'we', 'determine', 'the', 'infidelity', 'for', 'both', 'the', 'uncorrected', 'and', 'corrected', 'gates', 'as', 'a', 'function', 'of', 'the', 'errorinducing', 'terms', 'and', 'show', 'that', 'our', 'corrected', 'pulse', 'sequences', 'reduce', 'the', 'error', 'by', 'several', 'orders', 'of', 'magnitude']] | [-0.17431675697976756, 0.18251634603050554, 0.021233075213523866, 0.10645216363146744, 0.05355058248170604, -0.19760876884131487, 0.0946974182694803, 0.4066299597685367, -0.2657217759544314, -0.3341335797193066, 0.05616476919829561, -0.25588740085824335, -0.11731134772584853, 0.24139184901743369, -0.06443998107629417, 0.01717221838327409, 0.06564404276373276, -0.03931185296515666, -0.07351291132104283, -0.2601732583716512, 0.27667755439435526, 0.0041466801480579555, 0.235975939938325, 0.059925374006694655, 0.12880932205451368, 0.014485977376984843, 0.04103962313068115, -0.008026371394299854, -0.11426249017905181, 0.0796953899109089, 0.2252755773143243, 0.02963996557045286, 0.2233775557587081, -0.4261440171828588, -0.14907247101161944, 0.09899370258642455, 0.15286629880636426, 0.20075167113642792, -0.055890482408389196, -0.2643349595778322, 0.07357236550986704, -0.16588258017959484, -0.02106251353713668, -0.09251926202421724, 0.027988268043727504, 0.018289112493344504, -0.304848476739253, 0.06817348427864352, 0.06081142757971913, 0.029969260450482163, 0.03153105178143498, -0.06551816173181949, 0.023516304516707057, 0.1682804823119067, -0.0008252314311625846, 0.03093545591079835, 0.16406674685067166, -0.07281030604805229, -0.1268449899764195, 0.2976841666435791, -0.07604960574752699, -0.19130049223993842, 0.05975769695399676, -0.10847500670243497, -0.057997025873006904, 0.09224103171757217, 0.1022834506761914, 0.06179108508562638, -0.15231766834286814, 0.0633986022750555, 0.0808734342345368, 0.2576419791617131, 0.05276873090572781, 0.10380456966379563, 0.15500315244041257, 0.10025253114527312, 0.0899644400529816, 0.1625676755142256, -0.12602504470481307, -0.07005543874229415, -0.33287561414921185, -0.1435938068049944, -0.1503151111083768, 0.0592710982053146, -0.09034461271887452, -0.14819480394313145, 0.4241622878640031, 0.19828958906256988, 0.15666127771975757, 0.03658930400990234, 0.31428775128166553, 0.17154848001013367, 0.09115512744263131, 0.04554130118024551, 0.28616092972046997, 0.18431770520963534, 0.009758628891994072, -0.31295961366524383, 0.0582614241994649, 0.007516196297513226] |
1,802.08257 | Detection of a Millimeter Flare From Proxima Centauri | We present new analyses of ALMA 12-m and ACA observations at 233 GHz (1.3 mm)
of the Proxima Centauri system with sensitivities of 9.5 and 47 $\mu$Jy
beam$^{-1}$, respectively, taken from 2017 January 21 through 2017 April 25.
These analyses reveal that the star underwent a significant flaring event
during one of the ACA observations on 2017 March 24. The complete event lasted
for approximately 1 minute and reached a peak flux density of $100\pm4$ mJy,
nearly a factor of $1000\times$ brighter than the star's quiescent emission. At
the flare peak, the continuum emission is characterized by a steeply falling
spectral index with frequency, $F_\nu \propto \nu^\alpha$ with $\alpha =
-1.77\pm0.45$, and a lower limit on the fractional linear polarization of
$|Q/I| = 0.19\pm0.02$. Since the ACA observations do not show any quiescent
excess emission, we conclude that there is no need to invoke the presence of a
dust belt at $1-4$ AU. We also posit that the slight excess flux density of
$101\pm9$ $\mu$Jy observed in the 12-m observations compared to the
photospheric flux density of $74\pm4$ $\mu$Jy extrapolated from infrared
wavelengths may be due to coronal heating from continual smaller flares, as is
seen for AU Mic, another nearby, well-studied, M dwarf flare star. If this is
true, then the need for warm dust at $\sim0.4$ AU is also removed.
| astro-ph.EP astro-ph.SR | we present new analyses of alma 12m and aca observations at 233 ghz 13 mm of the proxima centauri system with sensitivities of 95 and 47 mujy beam1 respectively taken from 2017 january 21 through 2017 april 25 these analyses reveal that the star underwent a significant flaring event during one of the aca observations on 2017 march 24 the complete event lasted for approximately 1 minute and reached a peak flux density of 100pm4 mjy nearly a factor of 1000times brighter than the stars quiescent emission at the flare peak the continuum emission is characterized by a steeply falling spectral index with frequency f_nu propto nualpha with alpha 177pm045 and a lower limit on the fractional linear polarization of qi 019pm002 since the aca observations do not show any quiescent excess emission we conclude that there is no need to invoke the presence of a dust belt at 14 au we also posit that the slight excess flux density of 101pm9 mujy observed in the 12m observations compared to the photospheric flux density of 74pm4 mujy extrapolated from infrared wavelengths may be due to coronal heating from continual smaller flares as is seen for au mic another nearby wellstudied m dwarf flare star if this is true then the need for warm dust at sim04 au is also removed | [['we', 'present', 'new', 'analyses', 'of', 'alma', '12m', 'and', 'aca', 'observations', 'at', '233', 'ghz', '13', 'mm', 'of', 'the', 'proxima', 'centauri', 'system', 'with', 'sensitivities', 'of', '95', 'and', '47', 'mujy', 'beam1', 'respectively', 'taken', 'from', '2017', 'january', '21', 'through', '2017', 'april', '25', 'these', 'analyses', 'reveal', 'that', 'the', 'star', 'underwent', 'a', 'significant', 'flaring', 'event', 'during', 'one', 'of', 'the', 'aca', 'observations', 'on', '2017', 'march', '24', 'the', 'complete', 'event', 'lasted', 'for', 'approximately', '1', 'minute', 'and', 'reached', 'a', 'peak', 'flux', 'density', 'of', '100pm4', 'mjy', 'nearly', 'a', 'factor', 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1,802.08258 | Stellar variability at the main-sequence turnoff of the intermediate-age
LMC cluster NGC 1846 | Intermediate-age star clusters in the LMC present extended main sequence
turnoffs (MSTO) that have been attributed to either multiple stellar
populations or an effect of stellar rotation. Recently it has been proposed
that these extended main sequences can also be produced by ill-characterized
stellar variability. Here we present Gemini-S/GMOS time series observations of
the intermediate-age cluster NGC 1846. Using differential image analysis, we
identified 73 new variable stars, with 55 of those being of the Delta Scuti
type, that is, pulsating variables close the MSTO for the cluster age.
Considering completeness and background contamination effects we estimate the
number of Delta Scuti belonging to the cluster between 40 and 60 members,
although this number is based on the detection of a single Delta Scuti within
the cluster half-light radius. This amount of variable stars at the MSTO level
will not produce significant broadening of the MSTO, albeit higher resolution
imaging will be needed to rule out variable stars as a major contributor to the
extended MSTO phenomenon. Though modest, this amount of Delta Scuti makes NGC
1846 the star cluster with the highest number of these variables ever
discovered. Lastly, our results are a cautionary tale about the adequacy of
shallow variability surveys in the LMC (like OGLE) to derive properties of its
Delta Scuti population.
| astro-ph.SR astro-ph.GA | intermediateage star clusters in the lmc present extended main sequence turnoffs msto that have been attributed to either multiple stellar populations or an effect of stellar rotation recently it has been proposed that these extended main sequences can also be produced by illcharacterized stellar variability here we present geminisgmos time series observations of the intermediateage cluster ngc 1846 using differential image analysis we identified 73 new variable stars with 55 of those being of the delta scuti type that is pulsating variables close the msto for the cluster age considering completeness and background contamination effects we estimate the number of delta scuti belonging to the cluster between 40 and 60 members although this number is based on the detection of a single delta scuti within the cluster halflight radius this amount of variable stars at the msto level will not produce significant broadening of the msto albeit higher resolution imaging will be needed to rule out variable stars as a major contributor to the extended msto phenomenon though modest this amount of delta scuti makes ngc 1846 the star cluster with the highest number of these variables ever discovered lastly our results are a cautionary tale about the adequacy of shallow variability surveys in the lmc like ogle to derive properties of its delta scuti population | [['intermediateage', 'star', 'clusters', 'in', 'the', 'lmc', 'present', 'extended', 'main', 'sequence', 'turnoffs', 'msto', 'that', 'have', 'been', 'attributed', 'to', 'either', 'multiple', 'stellar', 'populations', 'or', 'an', 'effect', 'of', 'stellar', 'rotation', 'recently', 'it', 'has', 'been', 'proposed', 'that', 'these', 'extended', 'main', 'sequences', 'can', 'also', 'be', 'produced', 'by', 'illcharacterized', 'stellar', 'variability', 'here', 'we', 'present', 'geminisgmos', 'time', 'series', 'observations', 'of', 'the', 'intermediateage', 'cluster', 'ngc', '1846', 'using', 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1,802.08259 | Gravitational Radiation Background from Boson Star Binaries | We calculate the gravitational radiation background generated from boson star
binaries formed in locally dense clusters with formation rate tracked by the
regular star formation rate. We compute how the the frequency window in
gravitational waves is affected by the boson field mass and repulsive
self-coupling, anticipating constraints from EPTA and LISA. We also comment on
the possible detectability of these binaries.
| hep-ph astro-ph.CO | we calculate the gravitational radiation background generated from boson star binaries formed in locally dense clusters with formation rate tracked by the regular star formation rate we compute how the the frequency window in gravitational waves is affected by the boson field mass and repulsive selfcoupling anticipating constraints from epta and lisa we also comment on the possible detectability of these binaries | [['we', 'calculate', 'the', 'gravitational', 'radiation', 'background', 'generated', 'from', 'boson', 'star', 'binaries', 'formed', 'in', 'locally', 'dense', 'clusters', 'with', 'formation', 'rate', 'tracked', 'by', 'the', 'regular', 'star', 'formation', 'rate', 'we', 'compute', 'how', 'the', 'the', 'frequency', 'window', 'in', 'gravitational', 'waves', 'is', 'affected', 'by', 'the', 'boson', 'field', 'mass', 'and', 'repulsive', 'selfcoupling', 'anticipating', 'constraints', 'from', 'epta', 'and', 'lisa', 'we', 'also', 'comment', 'on', 'the', 'possible', 'detectability', 'of', 'these', 'binaries']] | [-0.15961818302410744, 0.21553839005589967, -0.008953123766508314, 0.14647321848596837, -0.12010949690480746, -0.026379828010835955, 0.05880911023386063, 0.35399205802429107, -0.21208654353094678, -0.2747273538862505, 0.05941135393110134, -0.26255087752736384, -0.10301340027381817, 0.2213127189015429, 0.031224555456109585, -0.013847120947414828, 0.10206499903823339, 0.023384057526146213, -0.031168818377116093, -0.2881831040515775, 0.3818926941603422, 0.1378336335201898, 0.12009337006677542, 0.019891500165085157, 0.0587878406701249, 0.004095232290696473, -0.08839360744722428, -0.03894372586341154, -0.21163092864932673, 0.009486750704273883, 0.1774535408513921, 0.16727904603073013, 0.15628150621459128, -0.38980771111504686, -0.19927613548333606, 0.09050758498450441, 0.13427377273253496, 0.10871097196133868, -0.1285606040713197, -0.36382555312687354, 0.07404386698298397, -0.2473424598424425, -0.14102655136957765, 0.03773882724870477, 0.020792154882538823, 0.06029095996036044, -0.23680800949073127, 0.12843883771687792, -0.010013203767518844, -0.0756555741649091, -0.11896455627415449, -0.011554643429154831, -0.07584790628959215, 0.050019674243465546, 0.0771133666182117, 0.09064164590991793, 0.23115623801676255, -0.16919598271769862, -0.08707684792217708, 0.38369838370671194, -0.13541174440779874, -0.11891325103539613, 0.2226248857595267, -0.24683153683379774, -0.13937639012452094, 0.14245092041129548, 0.22795341070741415, 0.13008891602587555, -0.14710953141254704, 0.06935858284686541, 0.10169836162259022, 0.20276299815985463, 0.16869138828628966, 0.07385344473615048, 0.42502155668673014, 0.14108407482384674, 0.0010931773351565484, 0.11775594590712458, -0.16788932509464963, -0.02847688044365045, -0.2481622625923445, -0.020027673839532297, -0.13644368202620816, 0.06044941704209533, -0.0917191405197598, -0.09826761186723748, 0.32640836462979356, 0.14577649208912324, 0.15927122835250151, 0.034852976985876596, 0.27138886285284836, 0.11731327498226517, 0.04691094282081336, 0.09370576911005041, 0.36675171632199516, 0.15106385388231325, 0.06359814471685357, -0.2822986045972474, -0.005226806129118608, 0.053689433952733394] |
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