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1,802.0496 | Vertex nomination: The canonical sampling and the extended spectral
nomination schemes | Suppose that one particular block in a stochastic block model is of interest,
but block labels are only observed for a few of the vertices in the network.
Utilizing a graph realized from the model and the observed block labels, the
vertex nomination task is to order the vertices with unobserved block labels
into a ranked nomination list with the goal of having an abundance of
interesting vertices near the top of the list. There are vertex nomination
schemes in the literature, including the optimally precise canonical nomination
scheme~$\mathcal{L}^C$ and the consistent spectral partitioning nomination
scheme~$\mathcal{L}^P$. While the canonical nomination scheme $\mathcal{L}^C$
is provably optimally precise, it is computationally intractable, being
impractical to implement even on modestly sized graphs. With this in mind, an
approximation of the canonical scheme---denoted the {\it canonical sampling
nomination scheme} $\mathcal{L}^{CS}$---is introduced; $\mathcal{L}^{CS}$
relies on a scalable, Markov chain Monte Carlo-based approximation of
$\mathcal{L}^{C}$, and converges to $\mathcal{L}^{C}$ as the amount of sampling
goes to infinity. The spectral partitioning nomination scheme is also extended
to the {\it extended spectral partitioning nomination scheme},
$\mathcal{L}^{EP}$, which introduces a novel semisupervised clustering
framework to improve upon the precision of $\mathcal{L}^P$. Real-data and
simulation experiments are employed to illustrate the precision of these vertex
nomination schemes, as well as their empirical computational complexity.
Keywords: vertex nomination, Markov chain Monte Carlo, spectral partitioning,
Mclust MSC[2010]: 60J22, 65C40, 62H30, 62H25
| stat.ML | suppose that one particular block in a stochastic block model is of interest but block labels are only observed for a few of the vertices in the network utilizing a graph realized from the model and the observed block labels the vertex nomination task is to order the vertices with unobserved block labels into a ranked nomination list with the goal of having an abundance of interesting vertices near the top of the list there are vertex nomination schemes in the literature including the optimally precise canonical nomination schememathcallc and the consistent spectral partitioning nomination schememathcallp while the canonical nomination scheme mathcallc is provably optimally precise it is computationally intractable being impractical to implement even on modestly sized graphs with this in mind an approximation of the canonical schemedenoted the it canonical sampling nomination scheme mathcallcsis introduced mathcallcs relies on a scalable markov chain monte carlobased approximation of mathcallc and converges to mathcallc as the amount of sampling goes to infinity the spectral partitioning nomination scheme is also extended to the it extended spectral partitioning nomination scheme mathcallep which introduces a novel semisupervised clustering framework to improve upon the precision of mathcallp realdata and simulation experiments are employed to illustrate the precision of these vertex nomination schemes as well as their empirical computational complexity keywords vertex nomination markov chain monte carlo spectral partitioning mclust msc2010 60j22 65c40 62h30 62h25 | [['suppose', 'that', 'one', 'particular', 'block', 'in', 'a', 'stochastic', 'block', 'model', 'is', 'of', 'interest', 'but', 'block', 'labels', 'are', 'only', 'observed', 'for', 'a', 'few', 'of', 'the', 'vertices', 'in', 'the', 'network', 'utilizing', 'a', 'graph', 'realized', 'from', 'the', 'model', 'and', 'the', 'observed', 'block', 'labels', 'the', 'vertex', 'nomination', 'task', 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1,802.04961 | A Unified Gas-kinetic Scheme for Continuum and Rarefied Flows VI: Dilute
Disperse Gas-Particle Multiphase System | In this paper, a unified gas kinetic scheme for multiphase dilute
gas-particle system is proposed. The UGKS multiphase (UGKS-M) is a finite
volume method, which captures flow physics in the regimes from collisionless
multispecies transport to the two-fluid hydrodynamic Navier-Stokes (NS)
solution with the variation of Knudsen number, and from granular flow regime to
dusty gas dynamics with the variation of Stokes number. The main reason for
preserving the multiscale nature in UGKS-M is mainly coming from the direct
modeling of the flow physics in the scales of discrete cell size and time step,
where the ratio of the time step over the particle collision time determines
flow behavior in different regimes. For the particle phase, the integral
solution of the kinetic equation is used in the construction of the numerical
flux, which takes into account the particle transport, collision, and
acceleration. The gas phase, which is assumed to be in the continuum flow
regime, evolves numerically by the gas kinetic scheme (GKS), which is a subset
of the UGKS for the Navier-Stokes (NS) solutions. The interaction between the
gas and particle phase is calculated based on a velocity space mapping method,
which solves accurately the kinetic acceleration process. The stability of
UGKS-M is determined by the CFL condition only. With the inclusion of the
material temperature evolution equation of solid particles, the UGKS-M
conserves the total mass, momentum, and energy for the whole multiphase system.
In the numerical tests, the UGKS-M shows good multiscale property in capturing
the particle trajectory crossing (PTC), particle wall reflecting phenomena, and
vortex-induced segregation of inertial particles under different Stokes
numbers. The scheme is also applied to simulate shock induced fluidization
problem and the simulation results agree well with experimental measurement.
| physics.comp-ph math.NA | in this paper a unified gas kinetic scheme for multiphase dilute gasparticle system is proposed the ugks multiphase ugksm is a finite volume method which captures flow physics in the regimes from collisionless multispecies transport to the twofluid hydrodynamic navierstokes ns solution with the variation of knudsen number and from granular flow regime to dusty gas dynamics with the variation of stokes number the main reason for preserving the multiscale nature in ugksm is mainly coming from the direct modeling of the flow physics in the scales of discrete cell size and time step where the ratio of the time step over the particle collision time determines flow behavior in different regimes for the particle phase the integral solution of the kinetic equation is used in the construction of the numerical flux which takes into account the particle transport collision and acceleration the gas phase which is assumed to be in the continuum flow regime evolves numerically by the gas kinetic scheme gks which is a subset of the ugks for the navierstokes ns solutions the interaction between the gas and particle phase is calculated based on a velocity space mapping method which solves accurately the kinetic acceleration process the stability of ugksm is determined by the cfl condition only with the inclusion of the material temperature evolution equation of solid particles the ugksm conserves the total mass momentum and energy for the whole multiphase system in the numerical tests the ugksm shows good multiscale property in capturing the particle trajectory crossing ptc particle wall reflecting phenomena and vortexinduced segregation of inertial particles under different stokes numbers the scheme is also applied to simulate shock induced fluidization problem and the simulation results agree well with experimental measurement | [['in', 'this', 'paper', 'a', 'unified', 'gas', 'kinetic', 'scheme', 'for', 'multiphase', 'dilute', 'gasparticle', 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1,802.04962 | Disjoint Multi-task Learning between Heterogeneous Human-centric Tasks | Human behavior understanding is arguably one of the most important mid-level
components in artificial intelligence. In order to efficiently make use of
data, multi-task learning has been studied in diverse computer vision tasks
including human behavior understanding. However, multi-task learning relies on
task specific datasets and constructing such datasets can be cumbersome. It
requires huge amounts of data, labeling efforts, statistical consideration etc.
In this paper, we leverage existing single-task datasets for human action
classification and captioning data for efficient human behavior learning. Since
the data in each dataset has respective heterogeneous annotations, traditional
multi-task learning is not effective in this scenario. To this end, we propose
a novel alternating directional optimization method to efficiently learn from
the heterogeneous data. We demonstrate the effectiveness of our model and show
performance improvements on both classification and sentence retrieval tasks in
comparison to the models trained on each of the single-task datasets.
| cs.CV | human behavior understanding is arguably one of the most important midlevel components in artificial intelligence in order to efficiently make use of data multitask learning has been studied in diverse computer vision tasks including human behavior understanding however multitask learning relies on task specific datasets and constructing such datasets can be cumbersome it requires huge amounts of data labeling efforts statistical consideration etc in this paper we leverage existing singletask datasets for human action classification and captioning data for efficient human behavior learning since the data in each dataset has respective heterogeneous annotations traditional multitask learning is not effective in this scenario to this end we propose a novel alternating directional optimization method to efficiently learn from the heterogeneous data we demonstrate the effectiveness of our model and show performance improvements on both classification and sentence retrieval tasks in comparison to the models trained on each of the singletask datasets | [['human', 'behavior', 'understanding', 'is', 'arguably', 'one', 'of', 'the', 'most', 'important', 'midlevel', 'components', 'in', 'artificial', 'intelligence', 'in', 'order', 'to', 'efficiently', 'make', 'use', 'of', 'data', 'multitask', 'learning', 'has', 'been', 'studied', 'in', 'diverse', 'computer', 'vision', 'tasks', 'including', 'human', 'behavior', 'understanding', 'however', 'multitask', 'learning', 'relies', 'on', 'task', 'specific', 'datasets', 'and', 'constructing', 'such', 'datasets', 'can', 'be', 'cumbersome', 'it', 'requires', 'huge', 'amounts', 'of', 'data', 'labeling', 'efforts', 'statistical', 'consideration', 'etc', 'in', 'this', 'paper', 'we', 'leverage', 'existing', 'singletask', 'datasets', 'for', 'human', 'action', 'classification', 'and', 'captioning', 'data', 'for', 'efficient', 'human', 'behavior', 'learning', 'since', 'the', 'data', 'in', 'each', 'dataset', 'has', 'respective', 'heterogeneous', 'annotations', 'traditional', 'multitask', 'learning', 'is', 'not', 'effective', 'in', 'this', 'scenario', 'to', 'this', 'end', 'we', 'propose', 'a', 'novel', 'alternating', 'directional', 'optimization', 'method', 'to', 'efficiently', 'learn', 'from', 'the', 'heterogeneous', 'data', 'we', 'demonstrate', 'the', 'effectiveness', 'of', 'our', 'model', 'and', 'show', 'performance', 'improvements', 'on', 'both', 'classification', 'and', 'sentence', 'retrieval', 'tasks', 'in', 'comparison', 'to', 'the', 'models', 'trained', 'on', 'each', 'of', 'the', 'singletask', 'datasets']] | [-0.03388780943894138, -0.04025666469708085, -0.06312954823796947, 0.07231418441127364, -0.1734118339147729, -0.17674416837282478, -0.00637850708871459, 0.47747073508799076, -0.24289517900984114, -0.38059272127846877, 0.07145595604165768, -0.28577542620225965, -0.21167203254376848, 0.20906061629454295, -0.1860158668862035, 0.0958920584549196, 0.1795253719513615, 0.07784895949686567, -0.05139192631157736, -0.30102168781139577, 0.30214261267644665, 0.013521211594343186, 0.40101241305470464, 0.03338699789096912, 0.11429630829409386, -0.03451293611084111, -0.037016348365383846, -0.04819697912782431, -0.029748881123960017, 0.21922644841639946, 0.4105474559104429, 0.24081728677731007, 0.3651486958439151, -0.41811475781102975, -0.2537929413995395, 0.1331731302694728, 0.15126623563468455, 0.09964180071256123, -0.04376455555281912, -0.3366871695468823, 0.047833254801419874, -0.15459399856006106, 0.06382741145168741, -0.20299091594293714, -0.012912718644365669, -0.06703425121222002, -0.2880966811378797, 0.038407668598811145, 0.07351494440498452, 0.1023133855778724, -0.05666432728370031, -0.12066262175949911, 0.0747658894630149, 0.19000397470779717, 0.07111107578113054, 0.027518877481731277, 0.15416523556845885, -0.23057506759185345, -0.18298935248826942, 0.3867496168613434, -0.041028784658604614, -0.22264690637229553, 0.25036266312003136, -0.01167860603891313, -0.20657882941576342, 0.06334150889577965, 0.28922165321807064, 0.13044671796572704, -0.2046757281245664, 0.025019524111412464, -0.03820119116610537, 0.176772461955746, 0.00029376646503806117, -0.044137546773999926, 0.16956765602109955, 0.33457344959800445, -0.0010550867762746444, 0.13707856421902154, -0.10733102271488558, -0.08382061994324128, -0.14334615192996958, -0.09246232204760114, -0.20928599687914054, -0.03573289557816073, -0.11650538535439409, -0.11274305803982619, 0.3757534356159158, 0.28114043907116865, 0.18992826881818473, 0.09338840110227466, 0.38401428918043773, -0.017698511120397598, 0.14357150970802954, 0.09007537546684034, 0.1643798827317854, -0.057362569991964846, 0.14946774760571618, -0.1972055034339428, 0.10204982230750223, 0.011828173169245322] |
1,802.04963 | Superconvergent recovery of Raviart--Thomas mixed finite elements on
triangular grids | For the second lowest-order Raviart--Thomas mixed method, we prove that the
canonical interpolant and finite element solution for the vector variable in
elliptic problems are superclose in the $H(\text{div})$-norm on mildly
structured meshes, where most pairs of adjacent triangles form approximate
parallelograms. We then develop a family of postprocessing operators for
Raviart--Thomas mixed elements on triangular grids by using the idea of local
least squares fittings. Super-approximation property of the postprocessing
operators for the lowest and second lowest order Raviart--Thomas elements is
proved under mild conditions. Combining the supercloseness and
super-approximation results, we prove that the postprocessed solution
superconverges to the exact solution in the $L^2$-norm on mildly structured
meshes.
| math.NA cs.NA | for the second lowestorder raviartthomas mixed method we prove that the canonical interpolant and finite element solution for the vector variable in elliptic problems are superclose in the htextdivnorm on mildly structured meshes where most pairs of adjacent triangles form approximate parallelograms we then develop a family of postprocessing operators for raviartthomas mixed elements on triangular grids by using the idea of local least squares fittings superapproximation property of the postprocessing operators for the lowest and second lowest order raviartthomas elements is proved under mild conditions combining the supercloseness and superapproximation results we prove that the postprocessed solution superconverges to the exact solution in the l2norm on mildly structured meshes | [['for', 'the', 'second', 'lowestorder', 'raviartthomas', 'mixed', 'method', 'we', 'prove', 'that', 'the', 'canonical', 'interpolant', 'and', 'finite', 'element', 'solution', 'for', 'the', 'vector', 'variable', 'in', 'elliptic', 'problems', 'are', 'superclose', 'in', 'the', 'htextdivnorm', 'on', 'mildly', 'structured', 'meshes', 'where', 'most', 'pairs', 'of', 'adjacent', 'triangles', 'form', 'approximate', 'parallelograms', 'we', 'then', 'develop', 'a', 'family', 'of', 'postprocessing', 'operators', 'for', 'raviartthomas', 'mixed', 'elements', 'on', 'triangular', 'grids', 'by', 'using', 'the', 'idea', 'of', 'local', 'least', 'squares', 'fittings', 'superapproximation', 'property', 'of', 'the', 'postprocessing', 'operators', 'for', 'the', 'lowest', 'and', 'second', 'lowest', 'order', 'raviartthomas', 'elements', 'is', 'proved', 'under', 'mild', 'conditions', 'combining', 'the', 'supercloseness', 'and', 'superapproximation', 'results', 'we', 'prove', 'that', 'the', 'postprocessed', 'solution', 'superconverges', 'to', 'the', 'exact', 'solution', 'in', 'the', 'l2norm', 'on', 'mildly', 'structured', 'meshes']] | [-0.08876592192559614, 0.051327525753391175, -0.06533994370165767, 0.05429176293813342, -0.04014176817038396, -0.12294849207829855, -0.012014263651308116, 0.3571684455003487, -0.2991430808270965, -0.21162250497455307, 0.1490709760211357, -0.28974541753462146, -0.08168989327659301, 0.14226548444616413, -0.05570271317291697, 0.08661691871911732, 0.10117686136386468, 0.008929835448742186, -0.11646205292899298, -0.2626994010274632, 0.3749008973496496, -0.059331698949799075, 0.2452199365089246, -0.010509636738538367, 0.13430912654265897, -0.03856042287645674, -0.02196985448565368, 0.027090288912279343, -0.09998646153015867, 0.16459422466268234, 0.22018802465674459, 0.05060943401068312, 0.27061674277375053, -0.44467747475687036, -0.15114933782932136, 0.0978432818905476, 0.10910004391142705, 0.07555444628307852, -0.06289917786943154, -0.20410211313806406, 0.16544190979839854, -0.11672075772059894, -0.15895702652718632, -0.10063180111459705, -0.05672263912856579, 0.04136712311707232, -0.38429208549269295, 0.0785743383767613, 0.07363541516552277, 0.05678933753777261, -0.08132133726244194, -0.19354258788698311, -0.02983939839492834, 0.03937577245620276, -0.03372644113778316, -0.04632452760028456, -0.025010189734647102, -0.06671062046063876, -0.059296843156842256, 0.38245505659035706, -0.09399161795944556, -0.27939942323995504, 0.09480830333879166, -0.12931893673648528, -0.1359659788335477, 0.09427764300051905, 0.16993597409380343, 0.22396161337169485, -0.09482993471325127, 0.10523193234998579, -0.07258274936792228, 0.1674932390793201, 0.10304313483263511, -0.03654484090036413, 0.06722137759174776, 0.07739694689725175, 0.15602685312031334, 0.10686906402580304, -0.04971417180399214, -0.09545491141942117, -0.33108452657972454, -0.15115291888103607, -0.19574270390589302, -0.036900017677524356, -0.1758654961431102, -0.24324030564978308, 0.3587410654424083, 0.08966548366812827, 0.13487129538841203, 0.05047991027235301, 0.28164969403467593, 0.1435331439325979, 0.04938707165548219, 0.11086773258044359, 0.18115251231084176, 0.19358852064373708, 0.011769202678814667, -0.19904619107747007, 0.05437810621181623, 0.2887538311524539] |
1,802.04964 | Indirect unitarity violation entangled with matter effects in reactor
antineutrino oscillations | If finite but tiny masses of the three active neutrinos are generated via the
canonical seesaw mechanism with three heavy sterile neutrinos, the 3\times 3
Pontecorvo-Maki-Nakagawa-Sakata neutrino mixing matrix V will not be exactly
unitary. This kind of indirect unitarity violation can be probed in a precision
reactor antineutrino oscillation experiment, but it may be entangled with
terrestrial matter effects as both of them are very small. We calculate the
probability of \overline{\nu}_e \to \overline{\nu}_e oscillations in a good
analytical approximation, and find that, besides the zero-distance effect, the
effect of unitarity violation is always smaller than matter effects, and their
entanglement does not appear until the next-to-leading-order oscillating terms
are taken into account. Given a 20-kiloton JUNO-like liquid scintillator
detector, we reaffirm that terrestrial matter effects should not be neglected
but indirect unitarity violation makes no difference, and demonstrate that the
experimental sensitivities to the neutrino mass ordering and a precision
measurement of \theta_{12} and \Delta_{21} \equiv m^2_2 - m^2_1 are robust.
| hep-ph | if finite but tiny masses of the three active neutrinos are generated via the canonical seesaw mechanism with three heavy sterile neutrinos the 3times 3 pontecorvomakinakagawasakata neutrino mixing matrix v will not be exactly unitary this kind of indirect unitarity violation can be probed in a precision reactor antineutrino oscillation experiment but it may be entangled with terrestrial matter effects as both of them are very small we calculate the probability of overlinenu_e to overlinenu_e oscillations in a good analytical approximation and find that besides the zerodistance effect the effect of unitarity violation is always smaller than matter effects and their entanglement does not appear until the nexttoleadingorder oscillating terms are taken into account given a 20kiloton junolike liquid scintillator detector we reaffirm that terrestrial matter effects should not be neglected but indirect unitarity violation makes no difference and demonstrate that the experimental sensitivities to the neutrino mass ordering and a precision measurement of theta_12 and delta_21 equiv m2_2 m2_1 are robust | [['if', 'finite', 'but', 'tiny', 'masses', 'of', 'the', 'three', 'active', 'neutrinos', 'are', 'generated', 'via', 'the', 'canonical', 'seesaw', 'mechanism', 'with', 'three', 'heavy', 'sterile', 'neutrinos', 'the', '3times', '3', 'pontecorvomakinakagawasakata', 'neutrino', 'mixing', 'matrix', 'v', 'will', 'not', 'be', 'exactly', 'unitary', 'this', 'kind', 'of', 'indirect', 'unitarity', 'violation', 'can', 'be', 'probed', 'in', 'a', 'precision', 'reactor', 'antineutrino', 'oscillation', 'experiment', 'but', 'it', 'may', 'be', 'entangled', 'with', 'terrestrial', 'matter', 'effects', 'as', 'both', 'of', 'them', 'are', 'very', 'small', 'we', 'calculate', 'the', 'probability', 'of', 'overlinenu_e', 'to', 'overlinenu_e', 'oscillations', 'in', 'a', 'good', 'analytical', 'approximation', 'and', 'find', 'that', 'besides', 'the', 'zerodistance', 'effect', 'the', 'effect', 'of', 'unitarity', 'violation', 'is', 'always', 'smaller', 'than', 'matter', 'effects', 'and', 'their', 'entanglement', 'does', 'not', 'appear', 'until', 'the', 'nexttoleadingorder', 'oscillating', 'terms', 'are', 'taken', 'into', 'account', 'given', 'a', '20kiloton', 'junolike', 'liquid', 'scintillator', 'detector', 'we', 'reaffirm', 'that', 'terrestrial', 'matter', 'effects', 'should', 'not', 'be', 'neglected', 'but', 'indirect', 'unitarity', 'violation', 'makes', 'no', 'difference', 'and', 'demonstrate', 'that', 'the', 'experimental', 'sensitivities', 'to', 'the', 'neutrino', 'mass', 'ordering', 'and', 'a', 'precision', 'measurement', 'of', 'theta_12', 'and', 'delta_21', 'equiv', 'm2_2', 'm2_1', 'are', 'robust']] | [-0.12413672849055819, 0.3220760270733363, -0.04706536925264767, 0.16866860674587164, -0.08126535625572993, -0.185826325893217, 0.05675936125649822, 0.3166908522755463, -0.20951237734219186, -0.31604307978442925, 0.054339302988630364, -0.3272605756216723, -0.04689916377158269, 0.1591394430573058, 0.03224808640014496, 0.04200028146252684, 0.07580919620459495, -0.00463606704095876, -0.13422098061176863, -0.22000185655927437, 0.23078197707069217, 0.08449605848894727, 0.21053526596808286, 0.11314311469124155, 0.07328343446661505, -0.07392371241552813, -0.030514630072559258, -0.011937122016867495, -0.06521139963916307, -0.015207219095929578, 0.23441903767470987, 0.11293228287741496, 0.11735960860846575, -0.43167262281412666, -0.16297609659464254, 0.21685248038077853, 0.15468814353724675, 0.08674577805242553, -0.06831496263498452, -0.31451826076376144, 0.04718510430045527, -0.23012629725756298, -0.10330132346438325, -0.07041349120709976, -0.030583383746861672, -0.08114798658007542, -0.31879659180141845, 0.12354833666836808, -0.01769889858518785, -0.0162698357201164, 0.014421323905785724, -0.18528877061600826, 0.006535768909495532, 0.06254290873531877, 0.10207533752054022, -0.054649525134020153, 0.1464140532199895, -0.10838749249731856, -0.04775248429454539, 0.43481997236239245, -0.056194250132495925, -0.1753976894354575, 0.10173961610001113, -0.22992613609961193, -0.09340724040123617, 0.12772194182309352, 0.11113963928941337, 0.04244354700449831, -0.1620743626595608, 0.06982999349769309, -0.07701941998386234, 0.192291232225086, 0.07259144575873054, 0.05952334845285307, 0.2777589244944454, 0.15726971574220228, 0.07649216336712981, -0.0425545852862715, -0.10652451937232219, -0.023315595607533587, -0.36608766257670355, -0.09957263470043122, -0.11862057435575017, 0.07998354587462074, -0.0643209986997333, -0.09647155324031848, 0.34395334217372, 0.126637986782354, 0.17074831964459664, 0.014235260020015957, 0.2935884705866161, 0.06796762797481132, 0.08093561663188226, 0.00760247190743222, 0.3776179608478217, 0.13389587286651505, 0.06143051850673112, -0.29203644545563723, 0.07727498489956991, 0.04245212207901182] |
1,802.04965 | Structural-elastic determination of the mechanical lifetime of
biomolecules | The lifetime of protein domains and ligand-receptor complexes under force is
crucial for mechanosensitive functions, while many aspects of how force affects
the lifetime still remain poorly understood. Here, we report a new analytical
expression of the force-dependent molecular lifetime to understand transitions
overcoming a single barrier. Unlike previous models derived in the framework of
Kramers theory that requires a presumed one-dimensional free energy landscape,
our model is derived based on the structural-elastic properties of molecules
which is not restricted by the shape and dimensionality of the underlying free
energy landscape. Importantly, the parameters of this model provide direct
information of the structural-elastic features of the molecules between the
transition and the native states. We demonstrate the applications of this model
by applying it to explain complex force-dependent lifetime data for several
molecules reported in recent experiments, and predict the structural-elastic
properties of the transition states of these molecules.
| physics.bio-ph | the lifetime of protein domains and ligandreceptor complexes under force is crucial for mechanosensitive functions while many aspects of how force affects the lifetime still remain poorly understood here we report a new analytical expression of the forcedependent molecular lifetime to understand transitions overcoming a single barrier unlike previous models derived in the framework of kramers theory that requires a presumed onedimensional free energy landscape our model is derived based on the structuralelastic properties of molecules which is not restricted by the shape and dimensionality of the underlying free energy landscape importantly the parameters of this model provide direct information of the structuralelastic features of the molecules between the transition and the native states we demonstrate the applications of this model by applying it to explain complex forcedependent lifetime data for several molecules reported in recent experiments and predict the structuralelastic properties of the transition states of these molecules | [['the', 'lifetime', 'of', 'protein', 'domains', 'and', 'ligandreceptor', 'complexes', 'under', 'force', 'is', 'crucial', 'for', 'mechanosensitive', 'functions', 'while', 'many', 'aspects', 'of', 'how', 'force', 'affects', 'the', 'lifetime', 'still', 'remain', 'poorly', 'understood', 'here', 'we', 'report', 'a', 'new', 'analytical', 'expression', 'of', 'the', 'forcedependent', 'molecular', 'lifetime', 'to', 'understand', 'transitions', 'overcoming', 'a', 'single', 'barrier', 'unlike', 'previous', 'models', 'derived', 'in', 'the', 'framework', 'of', 'kramers', 'theory', 'that', 'requires', 'a', 'presumed', 'onedimensional', 'free', 'energy', 'landscape', 'our', 'model', 'is', 'derived', 'based', 'on', 'the', 'structuralelastic', 'properties', 'of', 'molecules', 'which', 'is', 'not', 'restricted', 'by', 'the', 'shape', 'and', 'dimensionality', 'of', 'the', 'underlying', 'free', 'energy', 'landscape', 'importantly', 'the', 'parameters', 'of', 'this', 'model', 'provide', 'direct', 'information', 'of', 'the', 'structuralelastic', 'features', 'of', 'the', 'molecules', 'between', 'the', 'transition', 'and', 'the', 'native', 'states', 'we', 'demonstrate', 'the', 'applications', 'of', 'this', 'model', 'by', 'applying', 'it', 'to', 'explain', 'complex', 'forcedependent', 'lifetime', 'data', 'for', 'several', 'molecules', 'reported', 'in', 'recent', 'experiments', 'and', 'predict', 'the', 'structuralelastic', 'properties', 'of', 'the', 'transition', 'states', 'of', 'these', 'molecules']] | [-0.09656401035132124, 0.12335363948005158, -0.0631276701464499, 0.07828898457638395, -0.003731891772266002, -0.10240234709313552, 0.08976616417823496, 0.36006170493744366, -0.2793668047837513, -0.30286776134431764, 0.033959905915399824, -0.22262667392024257, -0.16303481203472656, 0.17606436604151077, -0.0024087265002597498, 0.028640752964521815, 0.054586921427898956, 0.026236835353259286, -0.017066153017929037, -0.16736093918549133, 0.30099832506275315, 0.07562618166983327, 0.30404489765556264, 0.12349599882789994, 0.0770881669697408, -0.018701771649238245, 0.031879518133767444, -0.030086669570847647, -0.19154696476720187, 0.1775496841588795, 0.2044922214187418, 0.0800990363201689, 0.2241937819174522, -0.48385770445152015, -0.2775521021986368, 0.0823213828715102, 0.13223807963123857, 0.15077768285968185, -0.05380662444169514, -0.26061223476075085, 0.03129051518845278, -0.1221591398344944, -0.1240689914623563, -0.09955679352595252, 0.017208401416897175, 0.05675519823687364, -0.20653197857521588, 0.11951087506631727, 0.03728140196169183, 0.044001450374622476, -0.11127158489247047, -0.1108904428312855, -0.03542295013141862, 0.15163807048393577, 0.04283716568282662, -0.017621565229671964, 0.17892117741761493, -0.16692494243522482, -0.12052815745978447, 0.3895205495404017, -0.031042561744458522, -0.176809473888286, 0.2135613256637257, -0.11370028326781655, -0.13264232633272874, 0.14826523980763334, 0.11690869883340377, 0.14968327649762767, -0.16544765729032107, 0.07717756086166623, -0.012596743439180439, 0.18703309202628465, 0.0049349308754598736, 0.05509894481553827, 0.19289663308589164, 0.20415870277773615, -0.004754425895684742, 0.13034651689262647, -0.09209205056915697, -0.14876094594247788, -0.2382988510340852, -0.15879078304563843, -0.19169167146374216, 0.028393371663647766, -0.018170959910185656, -0.1534961619658158, 0.41516346415667327, 0.13994295586325578, 0.22338259915802502, 0.03081987226372522, 0.2817173398993659, 0.06731530671842371, 0.07203069304572356, -0.003731423035739052, 0.24609760374718365, 0.12199522939279375, 0.06264798083161348, -0.2522759162852128, 0.11337849113780805, 0.0018635587407363542] |
1,802.04966 | Destination Choice Game: A Spatial Interaction Theory on Human Mobility | With remarkable significance in migration prediction, global disease
mitigation, urban planning and many others, an arresting challenge is to
predict human mobility fluxes between any two locations. A number of methods
have been proposed against the above challenge, including the gravity model,
the intervening opportunity model, the radiation model, the population-weighted
opportunity model, and so on. Despite their theoretical elegance, all models
ignored an intuitive and important ingredient in individual decision about
where to go, that is, the possible congestion on the way and the possible
crowding in the destination. Here we propose a microscopic mechanism underlying
mobility decisions, named destination choice game (DCG), which takes into
account the crowding effects resulted from spatial interactions among
individuals. In comparison with the state-of-the-art models, the present one
shows more accurate prediction on mobility fluxes across wide scales from
intracity trips to intercity travels, and further to internal migrations. The
well-known gravity model is proved to be the equilibrium solution of a
degenerated DCG neglecting the crowding effects in the destinations.
| physics.soc-ph cs.GT | with remarkable significance in migration prediction global disease mitigation urban planning and many others an arresting challenge is to predict human mobility fluxes between any two locations a number of methods have been proposed against the above challenge including the gravity model the intervening opportunity model the radiation model the populationweighted opportunity model and so on despite their theoretical elegance all models ignored an intuitive and important ingredient in individual decision about where to go that is the possible congestion on the way and the possible crowding in the destination here we propose a microscopic mechanism underlying mobility decisions named destination choice game dcg which takes into account the crowding effects resulted from spatial interactions among individuals in comparison with the stateoftheart models the present one shows more accurate prediction on mobility fluxes across wide scales from intracity trips to intercity travels and further to internal migrations the wellknown gravity model is proved to be the equilibrium solution of a degenerated dcg neglecting the crowding effects in the destinations | [['with', 'remarkable', 'significance', 'in', 'migration', 'prediction', 'global', 'disease', 'mitigation', 'urban', 'planning', 'and', 'many', 'others', 'an', 'arresting', 'challenge', 'is', 'to', 'predict', 'human', 'mobility', 'fluxes', 'between', 'any', 'two', 'locations', 'a', 'number', 'of', 'methods', 'have', 'been', 'proposed', 'against', 'the', 'above', 'challenge', 'including', 'the', 'gravity', 'model', 'the', 'intervening', 'opportunity', 'model', 'the', 'radiation', 'model', 'the', 'populationweighted', 'opportunity', 'model', 'and', 'so', 'on', 'despite', 'their', 'theoretical', 'elegance', 'all', 'models', 'ignored', 'an', 'intuitive', 'and', 'important', 'ingredient', 'in', 'individual', 'decision', 'about', 'where', 'to', 'go', 'that', 'is', 'the', 'possible', 'congestion', 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1,802.04967 | DESlib: A Dynamic ensemble selection library in Python | DESlib is an open-source python library providing the implementation of
several dynamic selection techniques. The library is divided into three
modules: (i) \emph{dcs}, containing the implementation of dynamic classifier
selection methods (DCS); (ii) \emph{des}, containing the implementation of
dynamic ensemble selection methods (DES); (iii) \emph{static}, with the
implementation of static ensemble techniques. The library is fully documented
(documentation available online on Read the Docs), has a high test coverage
(codecov.io) and is part of the scikit-learn-contrib supported projects.
Documentation, code and examples can be found on its GitHub page:
https://github.com/scikit-learn-contrib/DESlib.
| cs.LG | deslib is an opensource python library providing the implementation of several dynamic selection techniques the library is divided into three modules i emphdcs containing the implementation of dynamic classifier selection methods dcs ii emphdes containing the implementation of dynamic ensemble selection methods des iii emphstatic with the implementation of static ensemble techniques the library is fully documented documentation available online on read the docs has a high test coverage codecovio and is part of the scikitlearncontrib supported projects documentation code and examples can be found on its github page httpsgithubcomscikitlearncontribdeslib | [['deslib', 'is', 'an', 'opensource', 'python', 'library', 'providing', 'the', 'implementation', 'of', 'several', 'dynamic', 'selection', 'techniques', 'the', 'library', 'is', 'divided', 'into', 'three', 'modules', 'i', 'emphdcs', 'containing', 'the', 'implementation', 'of', 'dynamic', 'classifier', 'selection', 'methods', 'dcs', 'ii', 'emphdes', 'containing', 'the', 'implementation', 'of', 'dynamic', 'ensemble', 'selection', 'methods', 'des', 'iii', 'emphstatic', 'with', 'the', 'implementation', 'of', 'static', 'ensemble', 'techniques', 'the', 'library', 'is', 'fully', 'documented', 'documentation', 'available', 'online', 'on', 'read', 'the', 'docs', 'has', 'a', 'high', 'test', 'coverage', 'codecovio', 'and', 'is', 'part', 'of', 'the', 'scikitlearncontrib', 'supported', 'projects', 'documentation', 'code', 'and', 'examples', 'can', 'be', 'found', 'on', 'its', 'github', 'page', 'httpsgithubcomscikitlearncontribdeslib']] | [-0.10324762091650405, -0.05150109852807613, -0.050534960037718214, 0.025115848613149, -0.09517153325889792, -0.21609422480244012, 0.0004172628756523842, 0.4441379182417655, -0.23845192948578015, -0.3355146976232174, 0.16748425974288866, -0.2689362767906416, -0.05816275871447509, 0.22397179486021437, -0.033902401137830954, 0.017266300639242955, 0.14946503591047422, -0.00683319046428161, -0.03727563129117092, -0.3073089036514007, 0.23621294890264316, 0.13834016184721673, 0.32341467817258535, 0.00678108206817082, 0.07201690800277338, -0.0038056140543804282, -0.14946604999048368, 0.0008369105053134263, -0.07488860721544673, 0.14536157500974478, 0.3055712892008679, 0.32115544303364696, 0.3186050822259858, -0.3223779487113158, -0.10861821347359746, -0.03041943005796167, 0.13380256632808596, 0.11603712822432585, -0.044858084445530994, -0.2772319658570701, 0.07979349259819303, -0.24434672279520392, -0.051954963543851464, -0.0948195929550344, -0.03069986980491584, 0.04427211368012996, -0.2300364455052962, -0.044897969296601205, 0.01147587294690311, 0.13157910004346854, -0.03912226151598069, -0.17413451771495775, -0.03091189650530439, 0.13785848857618735, -0.035977281120029236, 0.014660663348400877, 0.18922036500381573, -0.06948739766985887, -0.14725887800921642, 0.38557550415307995, -0.037347045460981984, -0.17002893902272695, 0.20164720194658176, 0.02982745195982889, -0.12559617172727094, 0.12059188450941638, 0.20676388676899174, 0.10331593955024368, -0.20672352042137868, 0.13168850620526687, 0.0318541925877244, 0.2223983447599624, -0.004861231178178319, -0.02987024449144623, 0.1716070947891456, 0.248979889177939, -0.04507794569889527, 0.17056913907678486, -0.07089355984880101, -0.05765584610690851, -0.3092010419904476, -0.1383433391151595, -0.16494043722438315, -0.055743819795593265, -0.06031464070180109, -0.2500122445413754, 0.4052794968288037, 0.13492453048491457, 0.03926088736625388, 0.03247138480877593, 0.36934675672091544, 0.0013622691566568044, 0.15491154162390602, 0.16959292064642623, 0.09997099053968365, 0.011188098309849877, 0.14303133788607306, -0.17254955913882614, 0.061661785579330865, 0.042448587263823445] |
1,802.04968 | Median Shapes | We introduce and begin to explore the mean and median of finite sets of
shapes represented as integral currents. The median can be computed efficiently
in practice, and we focus most of our theoretical and computational attention
on medians. We consider questions on the existence and regularity of medians.
While the median might not exist in all cases, we show that a mass-regularized
median is guaranteed to exist. When the input shapes are modeled by integral
currents with shared boundaries in codimension $1$, we show that the median is
guaranteed to exist, and is contained in the \emph{envelope} of the input
currents. On the other hand, we show that medians can be \emph{wild} in this
setting, and smooth inputs can generate non-smooth medians.
For higher codimensions, we show that \emph{books} are minimizing for a
finite set of $1$-currents in $\Bbb{R}^3$ with shared boundaries. As part of
this proof, we present a new result in graph theory---that \emph{cozy} graphs
are \emph{comfortable}---which should be of independent interest. Further, we
show that regular points on the median have book-like tangent cones in this
case.
From the point of view of computation, we study the median shape in the
settings of a finite simplicial complex. When the input shapes are represented
by chains of the simplicial complex, we show that the problem of finding the
median shape can be formulated as an integer linear program. This optimization
problem can be solved as a linear program in practice, thus allowing one to
compute median shapes efficiently.
We provide open source code implementing our methods, which could also be
used by anyone to experiment with ideas of their own. The software could be
accessed at https://github.com/tbtraltaa/medianshape.
| math.DG cs.CG math.AT math.OC | we introduce and begin to explore the mean and median of finite sets of shapes represented as integral currents the median can be computed efficiently in practice and we focus most of our theoretical and computational attention on medians we consider questions on the existence and regularity of medians while the median might not exist in all cases we show that a massregularized median is guaranteed to exist when the input shapes are modeled by integral currents with shared boundaries in codimension 1 we show that the median is guaranteed to exist and is contained in the emphenvelope of the input currents on the other hand we show that medians can be emphwild in this setting and smooth inputs can generate nonsmooth medians for higher codimensions we show that emphbooks are minimizing for a finite set of 1currents in bbbr3 with shared boundaries as part of this proof we present a new result in graph theorythat emphcozy graphs are emphcomfortablewhich should be of independent interest further we show that regular points on the median have booklike tangent cones in this case from the point of view of computation we study the median shape in the settings of a finite simplicial complex when the input shapes are represented by chains of the simplicial complex we show that the problem of finding the median shape can be formulated as an integer linear program this optimization problem can be solved as a linear program in practice thus allowing one to compute median shapes efficiently we provide open source code implementing our methods which could also be used by anyone to experiment with ideas of their own the software could be accessed at httpsgithubcomtbtraltaamedianshape | [['we', 'introduce', 'and', 'begin', 'to', 'explore', 'the', 'mean', 'and', 'median', 'of', 'finite', 'sets', 'of', 'shapes', 'represented', 'as', 'integral', 'currents', 'the', 'median', 'can', 'be', 'computed', 'efficiently', 'in', 'practice', 'and', 'we', 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1,802.04969 | Anti-screening of the Galileon force around a disk center hole | The Vainshtein mechanism is known as an efficient way of screening the fifth
force around a matter source in modified gravity. This has been verified mainly
in highly symmetric matter configurations. To study how the Vainshtein
mechanism works in a less symmetric setup, we numerically solve the scalar
field equation around a disk with a hole at its center in the cubic Galileon
theory. We find, surprisingly, that the Galileon force is enhanced, rather than
suppressed, in the vicinity of the hole. This anti-screening effect is larger
for a thinner, less massive disk with a smaller hole. At this stage our setup
is only of academic interest and its astrophysical consequences are unclear,
but this result implies that the Vainshtein screening mechanism around less
symmetric matter configurations is quite nontrivial.
| gr-qc | the vainshtein mechanism is known as an efficient way of screening the fifth force around a matter source in modified gravity this has been verified mainly in highly symmetric matter configurations to study how the vainshtein mechanism works in a less symmetric setup we numerically solve the scalar field equation around a disk with a hole at its center in the cubic galileon theory we find surprisingly that the galileon force is enhanced rather than suppressed in the vicinity of the hole this antiscreening effect is larger for a thinner less massive disk with a smaller hole at this stage our setup is only of academic interest and its astrophysical consequences are unclear but this result implies that the vainshtein screening mechanism around less symmetric matter configurations is quite nontrivial | [['the', 'vainshtein', 'mechanism', 'is', 'known', 'as', 'an', 'efficient', 'way', 'of', 'screening', 'the', 'fifth', 'force', 'around', 'a', 'matter', 'source', 'in', 'modified', 'gravity', 'this', 'has', 'been', 'verified', 'mainly', 'in', 'highly', 'symmetric', 'matter', 'configurations', 'to', 'study', 'how', 'the', 'vainshtein', 'mechanism', 'works', 'in', 'a', 'less', 'symmetric', 'setup', 'we', 'numerically', 'solve', 'the', 'scalar', 'field', 'equation', 'around', 'a', 'disk', 'with', 'a', 'hole', 'at', 'its', 'center', 'in', 'the', 'cubic', 'galileon', 'theory', 'we', 'find', 'surprisingly', 'that', 'the', 'galileon', 'force', 'is', 'enhanced', 'rather', 'than', 'suppressed', 'in', 'the', 'vicinity', 'of', 'the', 'hole', 'this', 'antiscreening', 'effect', 'is', 'larger', 'for', 'a', 'thinner', 'less', 'massive', 'disk', 'with', 'a', 'smaller', 'hole', 'at', 'this', 'stage', 'our', 'setup', 'is', 'only', 'of', 'academic', 'interest', 'and', 'its', 'astrophysical', 'consequences', 'are', 'unclear', 'but', 'this', 'result', 'implies', 'that', 'the', 'vainshtein', 'screening', 'mechanism', 'around', 'less', 'symmetric', 'matter', 'configurations', 'is', 'quite', 'nontrivial']] | [-0.16354843143624467, 0.13842510328585586, -0.09702997768942553, 0.13836223325924948, -0.12559889186746798, -0.15633072066479003, -0.012865590541444432, 0.328865192988171, -0.18540765614463733, -0.2953037160403955, 0.055615242150647996, -0.24319603405892848, -0.16105251409686527, 0.19036970875727444, -0.02267302147184427, -0.057989939897715184, -0.04426796889971368, 0.055235298006580426, -0.05866430249566642, -0.25104651615166895, 0.332262819335581, 0.11946465414590561, 0.2218033549053451, 0.05461244203078632, 0.04877675484077862, -0.055381508232452546, 0.029976936646450597, 0.015608894824981689, -0.09936830783139718, 0.04156371893791052, 0.17506460168649657, 0.03578755767263759, 0.27060236536826077, -0.4055244445944062, -0.24618416142632038, 0.09221565492648201, 0.15856311513970678, 0.18581802657662103, -0.13641619147159734, -0.24015940506584368, 0.13447870041351193, -0.21959868592138473, -0.18597112821343426, 0.00019096762944872562, 0.07935519666643813, -0.10856253387084087, -0.24016858498530033, 0.10934943655828157, 0.06652393660579736, -0.03549187550177941, -0.06704902094788849, -0.0580173599641197, -0.021801906413524055, -0.0006052047623178134, 0.11342173432752203, 0.06783646970199278, 0.19043765949945038, -0.17017668083202667, -0.040242983179632576, 0.422038567925875, -0.05176784687624044, -0.17299450038430783, 0.1842936807526992, -0.20179219051049305, -0.11152407188469973, 0.14073930423563488, 0.12925501812535983, 0.2129081783959499, -0.15038570313212962, 0.11875108619390701, -0.039553592337940174, 0.17585733588874483, 0.09647959885545648, 0.020917535974429205, 0.30677911680764874, 0.17861928131717902, 0.07068905675282272, 0.13969250163063407, -0.04454956336233478, -0.12270079565843424, -0.2771074686629268, -0.06812567036025799, -0.15750305692020516, 0.023981010175954838, -0.11273390004543427, -0.1459886528802319, 0.3434832928630595, 0.12597395670600237, 0.13846288577366908, -0.0024845219790362396, 0.296728454501583, 0.07426535699588176, 0.12227343386621214, 0.08416404811432585, 0.3348073138730027, 0.12132817981227373, 0.12677304528904362, -0.24645108816464648, 0.024960283247324137, 0.025707504249965915] |
1,802.0497 | Abstract Family-based Model Checking using Modal Featured Transition
Systems: Preservation of CTL* (Extended Version) | Variational systems allow effective building of many custom variants by using
features (configuration options) to mark the variable functionality. In many of
the applications, their quality assurance and formal verification are of
paramount importance. Family-based model checking allows simultaneous
verification of all variants of a variational system in a single run by
exploiting the commonalities between the variants. Yet, its computational cost
still greatly depends on the number of variants (often huge).
In this work, we show how to achieve efficient family-based model checking of
CTL* temporal properties using variability abstractions and off-the-shelf
(single-system) tools. We use variability abstractions for deriving abstract
family-based model checking, where the variability model of a variational
system is replaced with an abstract (smaller) version of it, called modal
featured transition system, which preserves the satisfaction of both universal
and existential temporal properties, as expressible in CTL*. Modal featured
transition systems contain two kinds of transitions, termed may and must
transitions, which are defined by the conservative (over-approximating)
abstractions and their dual (under-approximating) abstractions, respectively.
The variability abstractions can be combined with different partitionings of
the set of variants to infer suitable divide-and-conquer verification plans for
the variational system. We illustrate the practicality of this approach for
several variational systems.
| cs.LO cs.PL cs.SE | variational systems allow effective building of many custom variants by using features configuration options to mark the variable functionality in many of the applications their quality assurance and formal verification are of paramount importance familybased model checking allows simultaneous verification of all variants of a variational system in a single run by exploiting the commonalities between the variants yet its computational cost still greatly depends on the number of variants often huge in this work we show how to achieve efficient familybased model checking of ctl temporal properties using variability abstractions and offtheshelf singlesystem tools we use variability abstractions for deriving abstract familybased model checking where the variability model of a variational system is replaced with an abstract smaller version of it called modal featured transition system which preserves the satisfaction of both universal and existential temporal properties as expressible in ctl modal featured transition systems contain two kinds of transitions termed may and must transitions which are defined by the conservative overapproximating abstractions and their dual underapproximating abstractions respectively the variability abstractions can be combined with different partitionings of the set of variants to infer suitable divideandconquer verification plans for the variational system we illustrate the practicality of this approach for several variational systems | [['variational', 'systems', 'allow', 'effective', 'building', 'of', 'many', 'custom', 'variants', 'by', 'using', 'features', 'configuration', 'options', 'to', 'mark', 'the', 'variable', 'functionality', 'in', 'many', 'of', 'the', 'applications', 'their', 'quality', 'assurance', 'and', 'formal', 'verification', 'are', 'of', 'paramount', 'importance', 'familybased', 'model', 'checking', 'allows', 'simultaneous', 'verification', 'of', 'all', 'variants', 'of', 'a', 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1,802.04971 | Hadronic Paschen-Back effect | We find a novel phenomenon induced by the interplay between a strong magnetic
field and finite orbital angular momenta in hadronic systems, which is
analogous to the Paschen-Back effect observed in the field of atomic physics.
This effect allows the wave functions to drastically deform. We discuss
anisotropic decay from the deformation as a possibility to measure the strength
of the magnetic field in heavy-ion collision at LHC, RHIC and SPS, which has
not experimentally been measured. As an example we investigate charmonia with a
finite orbital angular momentum in a strong magnetic field. We calculate the
mass spectra and mixing rates. To obtain anisotropic wave functions, we apply
the cylindrical Gaussian expansion method, where the Gaussian bases to expand
the wave functions have different widths along transverse and longitudinal
directions in the cylindrical coordinate.
| hep-ph hep-ex nucl-ex nucl-th physics.atom-ph | we find a novel phenomenon induced by the interplay between a strong magnetic field and finite orbital angular momenta in hadronic systems which is analogous to the paschenback effect observed in the field of atomic physics this effect allows the wave functions to drastically deform we discuss anisotropic decay from the deformation as a possibility to measure the strength of the magnetic field in heavyion collision at lhc rhic and sps which has not experimentally been measured as an example we investigate charmonia with a finite orbital angular momentum in a strong magnetic field we calculate the mass spectra and mixing rates to obtain anisotropic wave functions we apply the cylindrical gaussian expansion method where the gaussian bases to expand the wave functions have different widths along transverse and longitudinal directions in the cylindrical coordinate | [['we', 'find', 'a', 'novel', 'phenomenon', 'induced', 'by', 'the', 'interplay', 'between', 'a', 'strong', 'magnetic', 'field', 'and', 'finite', 'orbital', 'angular', 'momenta', 'in', 'hadronic', 'systems', 'which', 'is', 'analogous', 'to', 'the', 'paschenback', 'effect', 'observed', 'in', 'the', 'field', 'of', 'atomic', 'physics', 'this', 'effect', 'allows', 'the', 'wave', 'functions', 'to', 'drastically', 'deform', 'we', 'discuss', 'anisotropic', 'decay', 'from', 'the', 'deformation', 'as', 'a', 'possibility', 'to', 'measure', 'the', 'strength', 'of', 'the', 'magnetic', 'field', 'in', 'heavyion', 'collision', 'at', 'lhc', 'rhic', 'and', 'sps', 'which', 'has', 'not', 'experimentally', 'been', 'measured', 'as', 'an', 'example', 'we', 'investigate', 'charmonia', 'with', 'a', 'finite', 'orbital', 'angular', 'momentum', 'in', 'a', 'strong', 'magnetic', 'field', 'we', 'calculate', 'the', 'mass', 'spectra', 'and', 'mixing', 'rates', 'to', 'obtain', 'anisotropic', 'wave', 'functions', 'we', 'apply', 'the', 'cylindrical', 'gaussian', 'expansion', 'method', 'where', 'the', 'gaussian', 'bases', 'to', 'expand', 'the', 'wave', 'functions', 'have', 'different', 'widths', 'along', 'transverse', 'and', 'longitudinal', 'directions', 'in', 'the', 'cylindrical', 'coordinate']] | [-0.13420482253724778, 0.22528391793053337, -0.110604755004385, 0.10000356877291644, -0.07623470464583348, -0.04805607753978283, -0.04000497795641422, 0.40126449147032367, -0.26961644762368114, -0.24896445214679397, -0.023035536646946436, -0.22894815241894254, -0.06275152947615695, 0.16405469375076118, 0.08106658495272752, 0.04830221849735136, 0.016263832634797804, 0.007984156989388995, -0.11878092194803887, -0.14668849189593283, 0.33456712198719657, 0.06532663092021486, 0.28038935217040556, 0.10965189944124884, 0.08145764263226064, 0.04208448102214822, 0.013756995375647589, 0.0395157993460695, -0.1686354185902962, 0.035552354084534776, 0.2005581422812409, 0.015816838846162515, 0.2100173956680077, -0.40276534313129053, -0.17565503215624226, 0.09303523711515245, 0.1555750825683828, 0.16747805659521234, -0.056718705911879184, -0.2649133350579413, 0.03037466833160983, -0.1926569803721375, -0.18882030678775025, -0.08363564556326579, 0.031256695484949484, 0.05165381893791534, -0.2952892529778183, 0.08642536440036364, 0.016493283315665193, 0.07932287742970166, -0.07771905369030449, -0.11407573908153508, -0.0402355935683267, 0.03937148842615662, 0.0971790701823516, 0.08420621782920702, 0.1240114404199024, -0.12200500088122984, -0.11889795496094006, 0.3541171952944111, -0.07560962090889613, -0.20339352351956122, 0.16357295541092753, -0.24732132004573942, -0.0777142563800293, 0.14273335924717012, 0.24329145818051917, 0.09172952930891404, -0.14214458077870035, 0.0814465768928467, -0.007497612835033107, 0.12085283328951509, 0.0894767908224215, 0.07357703731567772, 0.22168080567347784, 0.10446209605671121, 0.014026570125241522, 0.16355696811633944, -0.15035388627848414, -0.07091268155447862, -0.2881251127631576, -0.13079306998600562, -0.15240332937488954, 0.061305195884132344, -0.057049762981478125, -0.15160418197305667, 0.4059530629052056, 0.14116534548709211, 0.2473395870308633, -0.03753296896573846, 0.29838043271943376, 0.12856130440443478, 0.08518231819228579, 0.06177159547115917, 0.30858754068613053, 0.2116528015325053, 0.15506402770816177, -0.2881456774228287, 0.006988451919621891, 0.04636239227666347] |
1,802.04972 | A velocity-space adaptive unified gas kinetic scheme for continuum and
rarefied flows | In this paper, a unified gas kinetic scheme with adaptive velocity space
(AUGKS) for multiscale flow transport will be developed. In near-equilibrium
flow regions, particle distribution function is close to the Chapman-Enskog
expansion and can be formulated with a continuous velocity space, where only
macroscopic conservative variables are updated. With the emerging of
non-equilibrium effects, the AUGKS automatically switches to a discrete
velocity space to follow the evolution of particle distribution function. Based
on the Chapman-Enskog expansion, a criterion is proposed in this paper to
quantify the intensity of non-equilibrium effects and is used for the
continuous-discrete velocity space transformation. Following the
scale-dependent local evolution solution, the AUGKS presents the discretized
gas dynamic equations directly on the cell size and time step scales, i.e., the
so-called direct modeling method. As a result, the scheme is able to capture
the cross-scale flow physics from particle transport to hydrodynamic wave
propagation, and provides a continuous variation of solutions from the
Boltzmann to the Navier-Stokes. Under the unified framework, different from
conventional DSMC-NS hybrid method, the AUGKS does not need a buffer zone to
match up kinetic and hydrodynamic solutions. Instead, a continuous and discrete
particle velocity space is naturally connected, which is feasible for the
numerical simulations with unsteadiness or complex geometries. Compared with
the asymptotic preserving (AP) methods which solves kinetic equations uniformly
over the entire flow field with discretized velocity space, the current
velocity-space adaptive unified scheme speeds up the computation and reduces
the memory requirement in multiscale flow problems, and maintains the
equivalent accuracy. The AUGKS provides an effective tool for non-equilibrium
flow simulations.
| physics.comp-ph | in this paper a unified gas kinetic scheme with adaptive velocity space augks for multiscale flow transport will be developed in nearequilibrium flow regions particle distribution function is close to the chapmanenskog expansion and can be formulated with a continuous velocity space where only macroscopic conservative variables are updated with the emerging of nonequilibrium effects the augks automatically switches to a discrete velocity space to follow the evolution of particle distribution function based on the chapmanenskog expansion a criterion is proposed in this paper to quantify the intensity of nonequilibrium effects and is used for the continuousdiscrete velocity space transformation following the scaledependent local evolution solution the augks presents the discretized gas dynamic equations directly on the cell size and time step scales ie the socalled direct modeling method as a result the scheme is able to capture the crossscale flow physics from particle transport to hydrodynamic wave propagation and provides a continuous variation of solutions from the boltzmann to the navierstokes under the unified framework different from conventional dsmcns hybrid method the augks does not need a buffer zone to match up kinetic and hydrodynamic solutions instead a continuous and discrete particle velocity space is naturally connected which is feasible for the numerical simulations with unsteadiness or complex geometries compared with the asymptotic preserving ap methods which solves kinetic equations uniformly over the entire flow field with discretized velocity space the current velocityspace adaptive unified scheme speeds up the computation and reduces the memory requirement in multiscale flow problems and maintains the equivalent accuracy the augks provides an effective tool for nonequilibrium flow simulations | [['in', 'this', 'paper', 'a', 'unified', 'gas', 'kinetic', 'scheme', 'with', 'adaptive', 'velocity', 'space', 'augks', 'for', 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1,802.04973 | Coproducts in brane topology | We extend the loop product and the loop coproduct to the mapping space from
the $k$-dimensional sphere, or more generally from any $k$-manifold, to a
$k$-connected space with finite dimensional rational homotopy group, $k\geq 1$.
The key to extending the loop coproduct is the fact that the embedding
$M\rightarrow M^{S^{k-1}}$ is of "finite codimension" in a sense of Gorenstein
spaces. Moreover, we prove the associativity, commutativity, and Frobenius
compatibility of them.
| math.AT | we extend the loop product and the loop coproduct to the mapping space from the kdimensional sphere or more generally from any kmanifold to a kconnected space with finite dimensional rational homotopy group kgeq 1 the key to extending the loop coproduct is the fact that the embedding mrightarrow msk1 is of finite codimension in a sense of gorenstein spaces moreover we prove the associativity commutativity and frobenius compatibility of them | [['we', 'extend', 'the', 'loop', 'product', 'and', 'the', 'loop', 'coproduct', 'to', 'the', 'mapping', 'space', 'from', 'the', 'kdimensional', 'sphere', 'or', 'more', 'generally', 'from', 'any', 'kmanifold', 'to', 'a', 'kconnected', 'space', 'with', 'finite', 'dimensional', 'rational', 'homotopy', 'group', 'kgeq', '1', 'the', 'key', 'to', 'extending', 'the', 'loop', 'coproduct', 'is', 'the', 'fact', 'that', 'the', 'embedding', 'mrightarrow', 'msk1', 'is', 'of', 'finite', 'codimension', 'in', 'a', 'sense', 'of', 'gorenstein', 'spaces', 'moreover', 'we', 'prove', 'the', 'associativity', 'commutativity', 'and', 'frobenius', 'compatibility', 'of', 'them']] | [-0.17486142794701404, 0.09648325938199248, -0.05003080087979989, 0.08094891170372388, -0.11894690039168511, -0.15555324739377413, 0.005166215709011469, 0.353802323940077, -0.3640005666496498, -0.15073520146044236, 0.10854406312407394, -0.24485085468207088, -0.14110737497851786, 0.12441224015118288, -0.16431701617049319, -0.018843274151108095, 0.05671852499113551, 0.13867409168077366, -0.1244749418160479, -0.2859210763392704, 0.48429195162441047, -0.02422245049050876, 0.2054118820023827, 0.03522494199153568, 0.13678394510809863, 0.014766414874299829, 0.010208956511425121, 0.03355995709758385, -0.14392960995288118, 0.1465400006139784, 0.27086633216323597, 0.07708532957559718, 0.19820656877543244, -0.3485810392802315, -0.14549202479954276, 0.19754560963649834, 0.1555964526587299, -0.01104893031130944, 0.04105266766585244, -0.2740373839025519, 0.12572229017636605, -0.1854279200014259, -0.11779438736183302, -0.08312169878876635, 0.021133928852421897, -0.04119509594248874, -0.2540605433019144, -0.04979172543223415, 0.1368737192824483, 0.06615170086068767, -0.04643681720897023, -0.07440758662830506, -0.09697683597914875, 0.1397354737223525, -0.039717053289392165, 0.095664495928213, 0.0871736123226583, -0.06799001970596562, -0.14162819747580216, 0.37211942741913456, -0.017918527525450503, -0.2269647075661591, 0.1314912016902651, -0.2208893909917346, -0.16308199623599648, 0.11258668153147612, 0.007187737045543535, 0.13054856337340814, -0.012367677395897253, 0.2177101960854738, -0.09144378031737038, 0.09889433999612396, 0.1088640925607511, -0.005397054939697097, 0.10448488840068292, 0.09505427121849996, 0.1437375072655933, 0.14021779586827116, 0.008008889005369772, -0.05994526762764768, -0.3769843363868339, -0.22567290712280996, -0.116978363573019, 0.13562971384464098, -0.1764435428589682, -0.17550997052208653, 0.34260604619713764, 0.08300100599132877, 0.16693517513506648, 0.15464614776096175, 0.30869135936456066, 0.04702874069501247, 0.10354236059023865, 0.09265775274751442, 0.12864376594245966, 0.22796866497290985, -0.026834173826500773, -0.12395709776984794, -0.05849291228888823, 0.25466149648917574] |
1,802.04974 | A Framework for Input-Output Analysis of Wall-Bounded Shear Flows | We propose a framework to understand input-output amplification properties of
non- linear partial differential equation (PDE) models of wall-bounded shear
flows, which are spatially invariant in one coordinate (e.g.,
streamwise-constant plane Couette flow). Our methodology is based on the notion
of dissipation inequalities in control theory. In particular, we consider flows
with body and other forcings, for which we study the input- to-output
properties, including energy growth, worst-case disturbance amplification, and
stability to persistent disturbances. The proposed method can be applied to a
large class of flow configurations as long as the base flow is described by a
polynomial. This includes many examples in both channel flows and pipe flows,
e.g., plane Couette flow, and Hagen-Poiseuille flow. The methodology we use is
numerically implemented as the solution of a (convex) optimization problem. We
use the framework to study input-output amplification mechanisms in rotating
Couette flow, plane Couette flow, plane Poiseuille flow, and Hagen-Poiseuille
flow. In addition to showing that the application of the proposed framework
leads to results that are consistent with theoretical and experimental
amplification scalings obtained in the literature through linearization around
the base flow, we demonstrate that the stability bounds to persistent forcings
can be used as a means to predict transition to turbulence in wall-bounded
shear flows.
| physics.flu-dyn math.OC | we propose a framework to understand inputoutput amplification properties of non linear partial differential equation pde models of wallbounded shear flows which are spatially invariant in one coordinate eg streamwiseconstant plane couette flow our methodology is based on the notion of dissipation inequalities in control theory in particular we consider flows with body and other forcings for which we study the input tooutput properties including energy growth worstcase disturbance amplification and stability to persistent disturbances the proposed method can be applied to a large class of flow configurations as long as the base flow is described by a polynomial this includes many examples in both channel flows and pipe flows eg plane couette flow and hagenpoiseuille flow the methodology we use is numerically implemented as the solution of a convex optimization problem we use the framework to study inputoutput amplification mechanisms in rotating couette flow plane couette flow plane poiseuille flow and hagenpoiseuille flow in addition to showing that the application of the proposed framework leads to results that are consistent with theoretical and experimental amplification scalings obtained in the literature through linearization around the base flow we demonstrate that the stability bounds to persistent forcings can be used as a means to predict transition to turbulence in wallbounded shear flows | [['we', 'propose', 'a', 'framework', 'to', 'understand', 'inputoutput', 'amplification', 'properties', 'of', 'non', 'linear', 'partial', 'differential', 'equation', 'pde', 'models', 'of', 'wallbounded', 'shear', 'flows', 'which', 'are', 'spatially', 'invariant', 'in', 'one', 'coordinate', 'eg', 'streamwiseconstant', 'plane', 'couette', 'flow', 'our', 'methodology', 'is', 'based', 'on', 'the', 'notion', 'of', 'dissipation', 'inequalities', 'in', 'control', 'theory', 'in', 'particular', 'we', 'consider', 'flows', 'with', 'body', 'and', 'other', 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1,802.04975 | High-Dimensional Entanglement in States with Positive Partial
Transposition | Genuine high-dimensional entanglement, i.e. the property of having a high
Schmidt number, constitutes a resource in quantum communication, overcoming
limitations of low-dimensional systems. States with a positive partial
transpose (PPT), on the other hand, are generally considered weakly entangled,
as they can never be distilled into pure entangled states. This naturally
raises the question, whether high Schmidt numbers are possible for PPT states.
Volume estimates suggest that optimal, i.e. linear, scaling in local dimension
should be possible, albeit without providing an insight into the possible
slope. We provide the first explicit construction of a family of PPT states
that achieves linear scaling in local dimension and we prove that random PPT
states typically share this feature. Our construction also allows us to answer
a recent question by Chen et al. on the existence of PPT states whose Schmidt
number increases by an arbitrarily large amount upon partial transposition.
Finally, we link the Schmidt number to entangled sub-block matrices of a
quantum state. We use this connection to prove that quantum states invariant
under partial transposition on the smaller of their two subsystems cannot have
maximal Schmidt number. This generalizes a well-known result by Kraus et al. We
also show that the Schmidt number of absolutely PPT states cannot be maximal,
contributing to an open problem in entanglement theory.
| quant-ph math-ph math.MP | genuine highdimensional entanglement ie the property of having a high schmidt number constitutes a resource in quantum communication overcoming limitations of lowdimensional systems states with a positive partial transpose ppt on the other hand are generally considered weakly entangled as they can never be distilled into pure entangled states this naturally raises the question whether high schmidt numbers are possible for ppt states volume estimates suggest that optimal ie linear scaling in local dimension should be possible albeit without providing an insight into the possible slope we provide the first explicit construction of a family of ppt states that achieves linear scaling in local dimension and we prove that random ppt states typically share this feature our construction also allows us to answer a recent question by chen et al on the existence of ppt states whose schmidt number increases by an arbitrarily large amount upon partial transposition finally we link the schmidt number to entangled subblock matrices of a quantum state we use this connection to prove that quantum states invariant under partial transposition on the smaller of their two subsystems cannot have maximal schmidt number this generalizes a wellknown result by kraus et al we also show that the schmidt number of absolutely ppt states cannot be maximal contributing to an open problem in entanglement theory | [['genuine', 'highdimensional', 'entanglement', 'ie', 'the', 'property', 'of', 'having', 'a', 'high', 'schmidt', 'number', 'constitutes', 'a', 'resource', 'in', 'quantum', 'communication', 'overcoming', 'limitations', 'of', 'lowdimensional', 'systems', 'states', 'with', 'a', 'positive', 'partial', 'transpose', 'ppt', 'on', 'the', 'other', 'hand', 'are', 'generally', 'considered', 'weakly', 'entangled', 'as', 'they', 'can', 'never', 'be', 'distilled', 'into', 'pure', 'entangled', 'states', 'this', 'naturally', 'raises', 'the', 'question', 'whether', 'high', 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1,802.04976 | Dihedral Group, 4-Torsion on an Elliptic Curve, and a Peculiar Eigenform
Modulo 4 | We work out a non-trivial example of lifting a so-called weak eigenform to a
true, characteristic 0 eigenform. The weak eigenform is closely related to
Ramanujan's tau function whereas the characteristic 0 eigenform is attached to
an elliptic curve defined over ${\mathbb Q}$. We produce the lift by showing
that the coefficients of the initial, weak eigenform (almost all) occur as
traces of Frobenii in the Galois representation on the 4-torsion of the
elliptic curve. The example is remarkable as the initial form is known not to
be liftable to any characteristic 0 eigenform of level 1. We use this example
as illustrating certain questions that have arisen lately in the theory of
modular forms modulo prime powers. We give a brief survey of those questions.
| math.NT | we work out a nontrivial example of lifting a socalled weak eigenform to a true characteristic 0 eigenform the weak eigenform is closely related to ramanujans tau function whereas the characteristic 0 eigenform is attached to an elliptic curve defined over mathbb q we produce the lift by showing that the coefficients of the initial weak eigenform almost all occur as traces of frobenii in the galois representation on the 4torsion of the elliptic curve the example is remarkable as the initial form is known not to be liftable to any characteristic 0 eigenform of level 1 we use this example as illustrating certain questions that have arisen lately in the theory of modular forms modulo prime powers we give a brief survey of those questions | [['we', 'work', 'out', 'a', 'nontrivial', 'example', 'of', 'lifting', 'a', 'socalled', 'weak', 'eigenform', 'to', 'a', 'true', 'characteristic', '0', 'eigenform', 'the', 'weak', 'eigenform', 'is', 'closely', 'related', 'to', 'ramanujans', 'tau', 'function', 'whereas', 'the', 'characteristic', '0', 'eigenform', 'is', 'attached', 'to', 'an', 'elliptic', 'curve', 'defined', 'over', 'mathbb', 'q', 'we', 'produce', 'the', 'lift', 'by', 'showing', 'that', 'the', 'coefficients', 'of', 'the', 'initial', 'weak', 'eigenform', 'almost', 'all', 'occur', 'as', 'traces', 'of', 'frobenii', 'in', 'the', 'galois', 'representation', 'on', 'the', '4torsion', 'of', 'the', 'elliptic', 'curve', 'the', 'example', 'is', 'remarkable', 'as', 'the', 'initial', 'form', 'is', 'known', 'not', 'to', 'be', 'liftable', 'to', 'any', 'characteristic', '0', 'eigenform', 'of', 'level', '1', 'we', 'use', 'this', 'example', 'as', 'illustrating', 'certain', 'questions', 'that', 'have', 'arisen', 'lately', 'in', 'the', 'theory', 'of', 'modular', 'forms', 'modulo', 'prime', 'powers', 'we', 'give', 'a', 'brief', 'survey', 'of', 'those', 'questions']] | [-0.21273394794173775, 0.048299237986077694, -0.1312649476143027, 0.08708278641810581, -0.11311070923878265, -0.1586364350532965, -0.03979292745971757, 0.2888864925101636, -0.35186325039877187, -0.24260175508254814, 0.07418414947229422, -0.27589617050918086, -0.17417328521269299, 0.25073773262371857, -0.08789636720237988, 0.020784519633115638, 0.038055807823270914, 0.12351962970200157, -0.09059451892232848, -0.31771403378141777, 0.4022893639288784, -0.02269060563828264, 0.17526305557805158, 0.04031393177334278, 0.08464059679369841, -0.015349865211026064, 0.03539221486934121, -0.08262975961117754, -0.15294585909035208, 0.09970803170036228, 0.305552593631936, 0.06942751486637881, 0.2422869509041664, -0.32069127899890265, -0.11003013818694782, 0.20925915616819457, 0.14454161784877734, 0.013243095498413794, 0.014692901610581588, -0.2152602874030847, 0.13955970076725832, -0.1396126904680083, -0.20812107135157382, -0.07583799003623426, 0.056449033257122784, 0.04237664945881873, -0.24764627571372935, 0.03883841973803346, 0.12474587794008946, 0.16672249550428536, -0.07558124703687749, -0.15192310863529288, -0.0016661940996224682, 0.08649066860772787, 0.04189374189942129, 0.1014854867865483, 0.08177394157142512, -0.15385745862121916, -0.06279004884455057, 0.3389289890460315, -0.08894980086257592, -0.1676578185121928, 0.12850096501550445, -0.19972114250921305, -0.15252430702186381, 0.15725902466949757, 0.0915900252995983, 0.12282099426975326, -0.012559838792575257, 0.1369702212516189, -0.1340292115355768, 0.13232107092774223, 0.12578535672103514, -0.039296032913539204, 0.16428106804821818, 0.019304045365147647, 0.05018477625442699, 0.14390586753327783, -0.017268711566141556, -0.01639048052796473, -0.379721970903495, -0.19026554926549868, -0.13864661839010844, 0.19232646824012692, -0.028143968477490403, -0.18850230034588586, 0.403897397122198, 0.0925953718020566, 0.22691023430883114, 0.09144632722295466, 0.19985692078868547, 0.16557433991785353, 0.09217800151941086, 0.004974509848074781, 0.12490723209292998, 0.16634093355276577, 0.0037007726394453102, -0.14525922534189054, 0.014962864014142681, 0.1191325683242804] |
1,802.04977 | Paraphrasing Complex Network: Network Compression via Factor Transfer | Many researchers have sought ways of model compression to reduce the size of
a deep neural network (DNN) with minimal performance degradation in order to
use DNNs in embedded systems. Among the model compression methods, a method
called knowledge transfer is to train a student network with a stronger teacher
network. In this paper, we propose a novel knowledge transfer method which uses
convolutional operations to paraphrase teacher's knowledge and to translate it
for the student. This is done by two convolutional modules, which are called a
paraphraser and a translator. The paraphraser is trained in an unsupervised
manner to extract the teacher factors which are defined as paraphrased
information of the teacher network. The translator located at the student
network extracts the student factors and helps to translate the teacher factors
by mimicking them. We observed that our student network trained with the
proposed factor transfer method outperforms the ones trained with conventional
knowledge transfer methods.
| cs.CV | many researchers have sought ways of model compression to reduce the size of a deep neural network dnn with minimal performance degradation in order to use dnns in embedded systems among the model compression methods a method called knowledge transfer is to train a student network with a stronger teacher network in this paper we propose a novel knowledge transfer method which uses convolutional operations to paraphrase teachers knowledge and to translate it for the student this is done by two convolutional modules which are called a paraphraser and a translator the paraphraser is trained in an unsupervised manner to extract the teacher factors which are defined as paraphrased information of the teacher network the translator located at the student network extracts the student factors and helps to translate the teacher factors by mimicking them we observed that our student network trained with the proposed factor transfer method outperforms the ones trained with conventional knowledge transfer methods | [['many', 'researchers', 'have', 'sought', 'ways', 'of', 'model', 'compression', 'to', 'reduce', 'the', 'size', 'of', 'a', 'deep', 'neural', 'network', 'dnn', 'with', 'minimal', 'performance', 'degradation', 'in', 'order', 'to', 'use', 'dnns', 'in', 'embedded', 'systems', 'among', 'the', 'model', 'compression', 'methods', 'a', 'method', 'called', 'knowledge', 'transfer', 'is', 'to', 'train', 'a', 'student', 'network', 'with', 'a', 'stronger', 'teacher', 'network', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'knowledge', 'transfer', 'method', 'which', 'uses', 'convolutional', 'operations', 'to', 'paraphrase', 'teachers', 'knowledge', 'and', 'to', 'translate', 'it', 'for', 'the', 'student', 'this', 'is', 'done', 'by', 'two', 'convolutional', 'modules', 'which', 'are', 'called', 'a', 'paraphraser', 'and', 'a', 'translator', 'the', 'paraphraser', 'is', 'trained', 'in', 'an', 'unsupervised', 'manner', 'to', 'extract', 'the', 'teacher', 'factors', 'which', 'are', 'defined', 'as', 'paraphrased', 'information', 'of', 'the', 'teacher', 'network', 'the', 'translator', 'located', 'at', 'the', 'student', 'network', 'extracts', 'the', 'student', 'factors', 'and', 'helps', 'to', 'translate', 'the', 'teacher', 'factors', 'by', 'mimicking', 'them', 'we', 'observed', 'that', 'our', 'student', 'network', 'trained', 'with', 'the', 'proposed', 'factor', 'transfer', 'method', 'outperforms', 'the', 'ones', 'trained', 'with', 'conventional', 'knowledge', 'transfer', 'methods']] | [-0.0056700353720976465, 0.01943174060518598, -0.06565893542682452, 0.055241788627069084, -0.14434735770487497, -0.2021653762447738, 0.044820433365361345, 0.44948180796458354, -0.29659883150410266, -0.35286273702738746, 0.004099448562990273, -0.2688569483166981, -0.2236939179771129, 0.15235531878086828, -0.11577726655579623, 0.04535545441772668, 0.1323863739482007, 0.07562193720931969, -0.04987674165787476, -0.31152731794263083, 0.35227569442452683, 0.0698384185575114, 0.3349191979114567, -0.018672670108536557, 0.15212305466073656, -0.05982197615348043, -0.01044172155539385, -0.041660713685315945, -0.042664409490657085, 0.22469986850816395, 0.34112218694100455, 0.21182904064114536, 0.3734940995146791, -0.4230834277166474, -0.22930939774359427, 0.07103950958098135, 0.08601738103485156, 0.12196191566500572, 0.013464127390855743, -0.3219773387611513, 0.08981356350817687, -0.2155937675146326, 0.026335815723324496, -0.1392355974763632, -0.08338539161749424, -0.03254933706935375, -0.31478081954823384, -0.041483420337880814, 0.13062256614887907, 0.05921478879547888, -0.014599627073133184, -0.12046971286632001, 0.04045834279949627, 0.22698785578832031, 0.023176255993424884, 0.10010172225339639, 0.1547703442914832, -0.19889396087176378, -0.13439985965528795, 0.32959506444392667, -0.05947589299025675, -0.2148667736880241, 0.16302097215046807, -0.017127581769900938, -0.10830783458847192, 0.07269258861460032, 0.257066485748416, 0.06022668906953186, -0.18417098283497316, -0.028359277280152684, -0.04114441078516745, 0.19819820680685582, 0.032246889648658614, -0.054757570892932914, 0.14011878480256024, 0.2709821944155039, -0.02159572528983136, 0.1539749444011719, -0.10088414427722925, -0.04160171117513411, -0.20030785231821, -0.11232542656362057, -0.20605150533853203, -0.003570185882985712, -0.0586142926684378, -0.13456752109266218, 0.42546332501355677, 0.1934472154615627, 0.18595443471436268, 0.12115970045974057, 0.3315280560854702, 0.017793855026003814, 0.19105613072432817, 0.15208797043549918, 0.19015896957547915, 0.053121702066592634, 0.16279721651827136, -0.13904274998292807, 0.12566885428743496, 0.06996524218890456] |
1,802.04978 | Singularly perturbed forward-backward stochastic differential equations:
application to the optimal control of bilinear systems | We study linear-quadratic stochastic optimal control problems with bilinear
state dependence for which the underlying stochastic differential equation
(SDE) consists of slow and fast degrees of freedom. We show that, in the same
way in which the underlying dynamics can be well approximated by a reduced
order effective dynamics in the time scale limit (using classical
homogenziation results), the associated optimal expected cost converges in the
time scale limit to an effective optimal cost. This entails that we can well
approximate the stochastic optimal control for the whole system by the reduced
order stochastic optimal control, which is clearly easier to solve because of
lower dimensionality. The approach uses an equivalent formulation of the
Hamilton-Jacobi-Bellman (HJB) equation, in terms of forward-backward SDEs
(FBSDEs). We exploit the efficient solvability of FBSDEs via a least squares
Monte Carlo algorithm and show its applicability by a suitable numerical
example.
| math.DS math.PR | we study linearquadratic stochastic optimal control problems with bilinear state dependence for which the underlying stochastic differential equation sde consists of slow and fast degrees of freedom we show that in the same way in which the underlying dynamics can be well approximated by a reduced order effective dynamics in the time scale limit using classical homogenziation results the associated optimal expected cost converges in the time scale limit to an effective optimal cost this entails that we can well approximate the stochastic optimal control for the whole system by the reduced order stochastic optimal control which is clearly easier to solve because of lower dimensionality the approach uses an equivalent formulation of the hamiltonjacobibellman hjb equation in terms of forwardbackward sdes fbsdes we exploit the efficient solvability of fbsdes via a least squares monte carlo algorithm and show its applicability by a suitable numerical example | [['we', 'study', 'linearquadratic', 'stochastic', 'optimal', 'control', 'problems', 'with', 'bilinear', 'state', 'dependence', 'for', 'which', 'the', 'underlying', 'stochastic', 'differential', 'equation', 'sde', 'consists', 'of', 'slow', 'and', 'fast', 'degrees', 'of', 'freedom', 'we', 'show', 'that', 'in', 'the', 'same', 'way', 'in', 'which', 'the', 'underlying', 'dynamics', 'can', 'be', 'well', 'approximated', 'by', 'a', 'reduced', 'order', 'effective', 'dynamics', 'in', 'the', 'time', 'scale', 'limit', 'using', 'classical', 'homogenziation', 'results', 'the', 'associated', 'optimal', 'expected', 'cost', 'converges', 'in', 'the', 'time', 'scale', 'limit', 'to', 'an', 'effective', 'optimal', 'cost', 'this', 'entails', 'that', 'we', 'can', 'well', 'approximate', 'the', 'stochastic', 'optimal', 'control', 'for', 'the', 'whole', 'system', 'by', 'the', 'reduced', 'order', 'stochastic', 'optimal', 'control', 'which', 'is', 'clearly', 'easier', 'to', 'solve', 'because', 'of', 'lower', 'dimensionality', 'the', 'approach', 'uses', 'an', 'equivalent', 'formulation', 'of', 'the', 'hamiltonjacobibellman', 'hjb', 'equation', 'in', 'terms', 'of', 'forwardbackward', 'sdes', 'fbsdes', 'we', 'exploit', 'the', 'efficient', 'solvability', 'of', 'fbsdes', 'via', 'a', 'least', 'squares', 'monte', 'carlo', 'algorithm', 'and', 'show', 'its', 'applicability', 'by', 'a', 'suitable', 'numerical', 'example']] | [-0.107016833309598, 0.04592623671472618, -0.08184457104171401, 0.10202721829108637, -0.0982815273041869, -0.12398645085571655, 0.049248966007846694, 0.3218866831012841, -0.3714606947939971, -0.2974671078942202, 0.1540557038135313, -0.22237893637462422, -0.16858957297457702, 0.18690064604683168, -0.07530401937727785, 0.13841957980084457, 0.06216917229527286, -0.005744041375623181, -0.07921837040158952, -0.24541385108685312, 0.27022597531402676, 0.05626225800028649, 0.25189209852271294, -0.024679977620213196, 0.2295005367490752, 0.01573250246683842, 0.028674383824370032, 0.04896491766136525, -0.11108022729177751, 0.1087673396482293, 0.2865790995849489, 0.06602816530663906, 0.3352304910277498, -0.4262916632189319, -0.16716086074774122, 0.09888490846798081, 0.1746978080791325, 0.13124702034020347, -0.020193512641407292, -0.24339170713812627, 0.06476312645165057, -0.13554619692651362, -0.17965447909985507, -0.10008022053295683, -0.049126366313932274, 0.061936578287839376, -0.32540893441001917, 0.11080017968940002, 0.034022617767211695, -0.020777948078667296, -0.04936477015645982, -0.0871874343949081, -0.0006916453965522092, 0.057085567340254786, 0.03299495294963106, -0.0020022314908946385, 0.10479458136933631, -0.10230715952749396, -0.16308202740318817, 0.344212193183344, -0.1140241085262648, -0.27618079525900296, 0.15693798385528399, -0.08679431062994589, -0.09507633833343099, 0.19369261710230132, 0.19522546455023232, 0.1855854916418421, -0.21378191761544038, 0.14033367753847792, -0.022306398058245924, 0.1823794232809852, -0.011681279543273408, 0.0158379422693417, 0.06203726641111204, 0.2089558631069316, 0.18240059867244343, 0.14922608795238596, -0.0008141932948813614, -0.21106994268002696, -0.3082017056515505, -0.14292295198839414, -0.1433411107816059, 0.0677539207683555, -0.14884963665009027, -0.11255582793262497, 0.35983204662093315, 0.18943131392669124, 0.15421785505424285, 0.09608102505946339, 0.28354475015196307, 0.2530337066871339, -0.00851907902678218, 0.12196596547768547, 0.2045237311964919, 0.12418989093877889, 0.10360071529345266, -0.31855832311678034, 0.09881379283836175, 0.1320811264281129] |
1,802.04979 | M4CD: A Robust Change Detection Method for Intelligent Visual
Surveillance | In this paper, we propose a robust change detection method for intelligent
visual surveillance. This method, named M4CD, includes three major steps.
Firstly, a sample-based background model that integrates color and texture cues
is built and updated over time. Secondly, multiple heterogeneous features
(including brightness variation, chromaticity variation, and texture variation)
are extracted by comparing the input frame with the background model, and a
multi-source learning strategy is designed to online estimate the probability
distributions for both foreground and background. The three features are
approximately conditionally independent, making multi-source learning feasible.
Pixel-wise foreground posteriors are then estimated with Bayes rule. Finally,
the Markov random field (MRF) optimization and heuristic post-processing
techniques are used sequentially to improve accuracy. In particular, a
two-layer MRF model is constructed to represent pixel-based and
superpixel-based contextual constraints compactly. Experimental results on the
CDnet dataset indicate that M4CD is robust under complex environments and ranks
among the top methods.
| cs.CV | in this paper we propose a robust change detection method for intelligent visual surveillance this method named m4cd includes three major steps firstly a samplebased background model that integrates color and texture cues is built and updated over time secondly multiple heterogeneous features including brightness variation chromaticity variation and texture variation are extracted by comparing the input frame with the background model and a multisource learning strategy is designed to online estimate the probability distributions for both foreground and background the three features are approximately conditionally independent making multisource learning feasible pixelwise foreground posteriors are then estimated with bayes rule finally the markov random field mrf optimization and heuristic postprocessing techniques are used sequentially to improve accuracy in particular a twolayer mrf model is constructed to represent pixelbased and superpixelbased contextual constraints compactly experimental results on the cdnet dataset indicate that m4cd is robust under complex environments and ranks among the top methods | [['in', 'this', 'paper', 'we', 'propose', 'a', 'robust', 'change', 'detection', 'method', 'for', 'intelligent', 'visual', 'surveillance', 'this', 'method', 'named', 'm4cd', 'includes', 'three', 'major', 'steps', 'firstly', 'a', 'samplebased', 'background', 'model', 'that', 'integrates', 'color', 'and', 'texture', 'cues', 'is', 'built', 'and', 'updated', 'over', 'time', 'secondly', 'multiple', 'heterogeneous', 'features', 'including', 'brightness', 'variation', 'chromaticity', 'variation', 'and', 'texture', 'variation', 'are', 'extracted', 'by', 'comparing', 'the', 'input', 'frame', 'with', 'the', 'background', 'model', 'and', 'a', 'multisource', 'learning', 'strategy', 'is', 'designed', 'to', 'online', 'estimate', 'the', 'probability', 'distributions', 'for', 'both', 'foreground', 'and', 'background', 'the', 'three', 'features', 'are', 'approximately', 'conditionally', 'independent', 'making', 'multisource', 'learning', 'feasible', 'pixelwise', 'foreground', 'posteriors', 'are', 'then', 'estimated', 'with', 'bayes', 'rule', 'finally', 'the', 'markov', 'random', 'field', 'mrf', 'optimization', 'and', 'heuristic', 'postprocessing', 'techniques', 'are', 'used', 'sequentially', 'to', 'improve', 'accuracy', 'in', 'particular', 'a', 'twolayer', 'mrf', 'model', 'is', 'constructed', 'to', 'represent', 'pixelbased', 'and', 'superpixelbased', 'contextual', 'constraints', 'compactly', 'experimental', 'results', 'on', 'the', 'cdnet', 'dataset', 'indicate', 'that', 'm4cd', 'is', 'robust', 'under', 'complex', 'environments', 'and', 'ranks', 'among', 'the', 'top', 'methods']] | [-0.019165032118056216, 0.03340564185556098, -0.07861107075239981, 0.08325847675129525, -0.10652453948848492, -0.18221684848729347, 0.01952976142966022, 0.4900112112626335, -0.2632705060647961, -0.3321183824307279, 0.076723665802351, -0.25624031533135583, -0.1690656269591345, 0.1551075430034925, -0.12169015086996092, 0.09600394056718303, 0.09632390292534074, 0.015909932482839617, -0.05626922730967057, -0.26857115054543174, 0.3043624176736304, 0.046754723004626714, 0.34428023521029794, -0.02696690082300257, 0.1624622245454877, 0.017563151644345448, -0.11704646861982464, 0.023844510674575308, -0.04535740479221336, 0.15422705698308123, 0.28371593704299125, 0.19447333241895956, 0.2564199918122432, -0.35223599733007666, -0.2585164153707886, 0.09209953626118206, 0.1166487369340974, 0.112748453896246, -0.03582180914737358, -0.3373393131009864, 0.10293558646696589, -0.1534958217687757, 0.012386702460588405, -0.12040363405594087, -0.029291140687318876, -0.0022779082924139914, -0.3695589704377367, 0.06798726393353959, 0.05428909752533358, 0.04929303446790783, -0.09043525255575086, -0.14028240960331892, 0.025495001805687187, 0.12515798385643603, 0.005149126901686044, 0.05441681298717166, 0.1793755276655988, -0.12187100107170987, -0.12732533164960733, 0.340158291987532, -0.07209450844868043, -0.23113942962943188, 0.15307721451837694, -0.0063388368195009155, -0.17670695592852814, 0.11648792041109456, 0.22289241553093028, 0.13288911907249037, -0.20340663251861782, 0.014544232307458358, -0.01706506030646381, 0.17095373426594876, 0.026269278526059446, -0.028871222124712555, 0.1997122978560306, 0.1929623795386453, 0.062458612641939484, 0.14033521396811088, -0.19613797910394307, -0.08151857611038629, -0.24492228517365883, -0.047469857525055774, -0.16661442345893318, -0.07813035130627231, -0.13733611969718254, -0.15883997401349023, 0.39698334185665607, 0.23496238982138404, 0.20794335218140275, 0.09778273662101995, 0.376021353293531, 0.049793014722253316, 0.04671518380648845, 0.08922421308974458, 0.1524514157227888, 0.05724958910619137, 0.07320194366921529, -0.1401869060023725, 0.11495891985304604, 0.06679093340621484] |
1,802.0498 | How to Simulate Patchy Particles | Patchy particles is the name given to a large class of systems of mesoscopic
particles characterized by a repulsive core and a discrete number of
short-range and highly directional interaction sites. Numerical simulations
have contributed significantly to our understanding of the behaviour of patchy
particles, but, although simple in principle, advanced simulation techniques
are often required to sample the low temperatures and long time scales
associated with their self-assembly behaviour. In this work we review the most
popular simulation techniques that have been used to study patchy particles,
with a special focus on Monte Carlo methods. We cover many of the tools
required to simulate patchy systems, from interaction potentials to biased
moves, cluster moves, and free energy methods. The review is complemented by an
educationally-oriented Monte Carlo computer code that implements all the
techniques described in the text to simulate a well-known tetrahedral patchy
particle model.
| cond-mat.soft | patchy particles is the name given to a large class of systems of mesoscopic particles characterized by a repulsive core and a discrete number of shortrange and highly directional interaction sites numerical simulations have contributed significantly to our understanding of the behaviour of patchy particles but although simple in principle advanced simulation techniques are often required to sample the low temperatures and long time scales associated with their selfassembly behaviour in this work we review the most popular simulation techniques that have been used to study patchy particles with a special focus on monte carlo methods we cover many of the tools required to simulate patchy systems from interaction potentials to biased moves cluster moves and free energy methods the review is complemented by an educationallyoriented monte carlo computer code that implements all the techniques described in the text to simulate a wellknown tetrahedral patchy particle model | [['patchy', 'particles', 'is', 'the', 'name', 'given', 'to', 'a', 'large', 'class', 'of', 'systems', 'of', 'mesoscopic', 'particles', 'characterized', 'by', 'a', 'repulsive', 'core', 'and', 'a', 'discrete', 'number', 'of', 'shortrange', 'and', 'highly', 'directional', 'interaction', 'sites', 'numerical', 'simulations', 'have', 'contributed', 'significantly', 'to', 'our', 'understanding', 'of', 'the', 'behaviour', 'of', 'patchy', 'particles', 'but', 'although', 'simple', 'in', 'principle', 'advanced', 'simulation', 'techniques', 'are', 'often', 'required', 'to', 'sample', 'the', 'low', 'temperatures', 'and', 'long', 'time', 'scales', 'associated', 'with', 'their', 'selfassembly', 'behaviour', 'in', 'this', 'work', 'we', 'review', 'the', 'most', 'popular', 'simulation', 'techniques', 'that', 'have', 'been', 'used', 'to', 'study', 'patchy', 'particles', 'with', 'a', 'special', 'focus', 'on', 'monte', 'carlo', 'methods', 'we', 'cover', 'many', 'of', 'the', 'tools', 'required', 'to', 'simulate', 'patchy', 'systems', 'from', 'interaction', 'potentials', 'to', 'biased', 'moves', 'cluster', 'moves', 'and', 'free', 'energy', 'methods', 'the', 'review', 'is', 'complemented', 'by', 'an', 'educationallyoriented', 'monte', 'carlo', 'computer', 'code', 'that', 'implements', 'all', 'the', 'techniques', 'described', 'in', 'the', 'text', 'to', 'simulate', 'a', 'wellknown', 'tetrahedral', 'patchy', 'particle', 'model']] | [-0.07849760391360328, 0.14820313056038248, -0.0821957554515094, 0.09030011754039649, -0.04973555361845671, -0.14810514897873547, -0.0030256568801857223, 0.3881998439000486, -0.2644913713966037, -0.3449997395876642, 0.0603526764850719, -0.27693938587517924, -0.12499375118593341, 0.2010316206038649, 0.014382411968218137, 0.03402166031316969, 0.07779201510528179, -0.0442916955372274, -0.04108345528987989, -0.23976561735218313, 0.2502962644530894, 0.13235975736879732, 0.2318467637332641, 0.031002374171368675, 0.09230864136990109, 0.009235534423081945, -0.06766975686362345, 0.06909737284359051, -0.18280091065618811, 0.09214355456967732, 0.21147792835557222, 0.06604642627524748, 0.2568834925210741, -0.4710325048659822, -0.25461391733372457, 0.12342864163347507, 0.16841235068907373, 0.14422246988556564, -0.08806010002783844, -0.24546763829070412, 0.0436083057349905, -0.18896133348517988, -0.14696114632773072, -0.0559725236603735, -0.006171610649700647, 0.09132220786007453, -0.2248989489592918, 0.05268040699134772, 0.029655390623191447, 0.06623168229699543, 0.0110252742840564, -0.10028359348477464, 0.005660165224083993, 0.09263870946597308, 0.032840894304745356, -0.0034212078564251733, 0.17329330334746063, -0.14012866627826828, -0.1460260710079376, 0.4092024151261335, -0.003922977921718808, -0.17818855136403278, 0.30907700175087743, -0.10427398860378012, -0.172252386023788, 0.19884643419597886, 0.18752553443462677, 0.14881139254988465, -0.1797388433351194, 0.07886734148448576, -0.0033269646826315008, 0.1881536549907688, -0.017268171495668692, -0.024196526692695404, 0.21257541827500276, 0.19365991914026082, 0.008531761495635705, 0.14201455019184783, -0.08290611194049595, -0.17105553970570128, -0.2069797532159312, -0.11477412210381908, -0.22316583229168255, -0.007104980511740743, -0.05530744857012856, -0.20510696478137005, 0.33786757012880214, 0.20304306782303658, 0.14658916259044144, 0.04819966157681423, 0.2851569886153487, 0.04083119809694512, 0.07931966171121506, 0.04490660530457605, 0.17679082004158847, 0.1117119684636797, 0.09866580821586492, -0.17855870431171067, 0.039223286814426314, 0.05084159959439341] |
1,802.04981 | Adaptive importance sampling with forward-backward stochastic
differential equations | We describe an adaptive importance sampling algorithm for rare events that is
based on a dual stochastic control formulation of a path sampling problem.
Specifically, we focus on path functionals that have the form of cumulate
generating functions, which appear relevant in the context of, e.g.~molecular
dynamics, and we discuss the construction of an optimal (i.e. minimum variance)
change of measure by solving a stochastic control problem. We show that the
associated semi-linear dynamic programming equations admit an equivalent
formulation as a system of uncoupled forward-backward stochastic differential
equations that can be solved efficiently by a least squares Monte Carlo
algorithm. We illustrate the approach with a suitable numerical example and
discuss the extension of the algorithm to high-dimensional systems.
| math.DS math.PR | we describe an adaptive importance sampling algorithm for rare events that is based on a dual stochastic control formulation of a path sampling problem specifically we focus on path functionals that have the form of cumulate generating functions which appear relevant in the context of egmolecular dynamics and we discuss the construction of an optimal ie minimum variance change of measure by solving a stochastic control problem we show that the associated semilinear dynamic programming equations admit an equivalent formulation as a system of uncoupled forwardbackward stochastic differential equations that can be solved efficiently by a least squares monte carlo algorithm we illustrate the approach with a suitable numerical example and discuss the extension of the algorithm to highdimensional systems | [['we', 'describe', 'an', 'adaptive', 'importance', 'sampling', 'algorithm', 'for', 'rare', 'events', 'that', 'is', 'based', 'on', 'a', 'dual', 'stochastic', 'control', 'formulation', 'of', 'a', 'path', 'sampling', 'problem', 'specifically', 'we', 'focus', 'on', 'path', 'functionals', 'that', 'have', 'the', 'form', 'of', 'cumulate', 'generating', 'functions', 'which', 'appear', 'relevant', 'in', 'the', 'context', 'of', 'egmolecular', 'dynamics', 'and', 'we', 'discuss', 'the', 'construction', 'of', 'an', 'optimal', 'ie', 'minimum', 'variance', 'change', 'of', 'measure', 'by', 'solving', 'a', 'stochastic', 'control', 'problem', 'we', 'show', 'that', 'the', 'associated', 'semilinear', 'dynamic', 'programming', 'equations', 'admit', 'an', 'equivalent', 'formulation', 'as', 'a', 'system', 'of', 'uncoupled', 'forwardbackward', 'stochastic', 'differential', 'equations', 'that', 'can', 'be', 'solved', 'efficiently', 'by', 'a', 'least', 'squares', 'monte', 'carlo', 'algorithm', 'we', 'illustrate', 'the', 'approach', 'with', 'a', 'suitable', 'numerical', 'example', 'and', 'discuss', 'the', 'extension', 'of', 'the', 'algorithm', 'to', 'highdimensional', 'systems']] | [-0.1247620673991051, 0.05169689291322647, -0.1042597552745783, 0.11206497448523912, -0.07581002361477673, -0.13702296616681733, 0.01498388672666233, 0.36083716476343947, -0.3261743830595197, -0.2836316524996978, 0.13785014818755112, -0.24309686456705218, -0.23215285571245084, 0.21965206263414702, -0.06910816912770178, 0.08266415869613655, 0.10007492052743353, -0.003963032825419507, -0.08923155888856366, -0.22236658988849206, 0.30089435600401726, 0.03483788789633442, 0.22353870675218204, -0.0353189250532569, 0.20956240259423978, 0.05204653716646135, -0.0243860989018586, 0.08415382372669312, -0.12957915350791857, 0.12106350346217949, 0.24312417885335555, 0.16378739758731187, 0.34313177375295084, -0.4124127817457589, -0.17775543372732774, 0.11735706422634486, 0.1321382272527299, 0.12521141594835408, -0.06676142585870787, -0.2310604590437367, 0.06950864670876444, -0.1465392247382395, -0.11664952361611884, -0.09284966620577484, -0.057695779616811445, 0.05474902561106602, -0.304373005686813, 0.04297208190042557, 0.03614225769963335, 0.01040969363672017, -0.05936670866149219, -0.10111259339091626, 0.03562289404001932, 0.022474982085082085, -0.004238913687799095, 0.009249912373361592, 0.08784343564428952, -0.08556713560643066, -0.20923804061412968, 0.3508616051002711, -0.06477286652642295, -0.2715310118857677, 0.12789907742549955, -0.05880889090701562, -0.1516961732941891, 0.15527430723593452, 0.2518842952607685, 0.20935878120954618, -0.2023209463570173, 0.11297637595063341, -0.0644890067261495, 0.1253610946660658, -0.00011495277168182264, -0.0015393424888744073, 0.13029931122478697, 0.19491553186251148, 0.15001511174457602, 0.15743479953527043, -0.03846411395694732, -0.1751341606654665, -0.304830585175953, -0.15802096476325445, -0.1518704760252271, 0.01698686961601136, -0.11237332087862227, -0.1905446309134552, 0.3524785222497401, 0.20921333666358674, 0.16702351099694102, 0.09030230886385064, 0.2739882549865782, 0.21529051992834836, 0.004753014958119255, 0.0897445260985371, 0.1485079685656526, 0.13155521927088373, 0.040217210593469, -0.28715172582579884, 0.07206608948616718, 0.13120908197798148] |
1,802.04982 | Craig Interpolation and Access Interpolation with Clausal First-Order
Tableaux | We develop foundations for computing Craig interpolants and similar
intermediates of two given formulas with first-order theorem provers that
construct clausal tableaux. Provers that can be understood in this way include
efficient machine-oriented systems based on calculi of two families:
goal-oriented like model elimination and the connection method, and bottom-up
like the hyper tableau calculus. The presented method for Craig-Lyndon
interpolation involves a lifting step where terms are replaced by quantified
variables, similar as known for resolution-based interpolation, but applied to
a differently characterized ground formula and proven correct more abstractly
on the basis of Herbrand's theorem, independently of a particular calculus.
Access interpolation is a recent form of interpolation for database query
reformulation that applies to first-order formulas with relativized quantifiers
and constrains the quantification patterns of predicate occurrences. It has
been previously investigated in the framework of Smullyan's non-clausal
tableaux. Here, in essence, we simulate these with the more machine-oriented
clausal tableaux through structural constraints that can be ensured either
directly by bottom-up tableau construction methods or, for closed clausal
tableaux constructed with arbitrary calculi, by postprocessing with
restructuring transformations.
| cs.LO | we develop foundations for computing craig interpolants and similar intermediates of two given formulas with firstorder theorem provers that construct clausal tableaux provers that can be understood in this way include efficient machineoriented systems based on calculi of two families goaloriented like model elimination and the connection method and bottomup like the hyper tableau calculus the presented method for craiglyndon interpolation involves a lifting step where terms are replaced by quantified variables similar as known for resolutionbased interpolation but applied to a differently characterized ground formula and proven correct more abstractly on the basis of herbrands theorem independently of a particular calculus access interpolation is a recent form of interpolation for database query reformulation that applies to firstorder formulas with relativized quantifiers and constrains the quantification patterns of predicate occurrences it has been previously investigated in the framework of smullyans nonclausal tableaux here in essence we simulate these with the more machineoriented clausal tableaux through structural constraints that can be ensured either directly by bottomup tableau construction methods or for closed clausal tableaux constructed with arbitrary calculi by postprocessing with restructuring transformations | [['we', 'develop', 'foundations', 'for', 'computing', 'craig', 'interpolants', 'and', 'similar', 'intermediates', 'of', 'two', 'given', 'formulas', 'with', 'firstorder', 'theorem', 'provers', 'that', 'construct', 'clausal', 'tableaux', 'provers', 'that', 'can', 'be', 'understood', 'in', 'this', 'way', 'include', 'efficient', 'machineoriented', 'systems', 'based', 'on', 'calculi', 'of', 'two', 'families', 'goaloriented', 'like', 'model', 'elimination', 'and', 'the', 'connection', 'method', 'and', 'bottomup', 'like', 'the', 'hyper', 'tableau', 'calculus', 'the', 'presented', 'method', 'for', 'craiglyndon', 'interpolation', 'involves', 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1,802.04983 | Quantum Fluctuation and Dissipation in Holographic Theories: A Unifying
Study Scheme | Motivated by the wide range of applicability of the fluctuation and
dissipation phenomena in non-equilibrium systems, we provide a universal study
scheme for the dissipation of the energy and the corresponding Brownian motion
analysis of massive particles due to quantum and thermal fluctuations in a wide
class of strongly coupled quantum field theories. The underlying reason for the
existence of such unified study scheme, is that our analytic methods turn out
to heavily depend on the order of the Bessel functions $\nu$, describing the
string fluctuations attached to the particle. Different values of the order are
associated to different theories.
The two-point function of the fluctuations exhibits two different late time
behaviors, depending purely on the value of the order of Bessel functions. We
then find that the coefficients and observables associated with the stochastic
motion at zero and finite temperature, depend on the scales of the theory
through powers of the order $\nu$. Moreover, the fluctuation-dissipation
theorem is verified from the bulk perspective to be universally satisfied for
the whole class of theories. Finally, we show that the analysis of certain
types of Dp-brane fluctuations can be mapped one-to-one to the string
fluctuations and therefore the stochastic brane observables can be read from
the string ones. In the closing remarks we demonstrate how our analysis
accommodates known results as special cases and provide more applications.
| hep-th cond-mat.str-el | motivated by the wide range of applicability of the fluctuation and dissipation phenomena in nonequilibrium systems we provide a universal study scheme for the dissipation of the energy and the corresponding brownian motion analysis of massive particles due to quantum and thermal fluctuations in a wide class of strongly coupled quantum field theories the underlying reason for the existence of such unified study scheme is that our analytic methods turn out to heavily depend on the order of the bessel functions nu describing the string fluctuations attached to the particle different values of the order are associated to different theories the twopoint function of the fluctuations exhibits two different late time behaviors depending purely on the value of the order of bessel functions we then find that the coefficients and observables associated with the stochastic motion at zero and finite temperature depend on the scales of the theory through powers of the order nu moreover the fluctuationdissipation theorem is verified from the bulk perspective to be universally satisfied for the whole class of theories finally we show that the analysis of certain types of dpbrane fluctuations can be mapped onetoone to the string fluctuations and therefore the stochastic brane observables can be read from the string ones in the closing remarks we demonstrate how our analysis accommodates known results as special cases and provide more applications | [['motivated', 'by', 'the', 'wide', 'range', 'of', 'applicability', 'of', 'the', 'fluctuation', 'and', 'dissipation', 'phenomena', 'in', 'nonequilibrium', 'systems', 'we', 'provide', 'a', 'universal', 'study', 'scheme', 'for', 'the', 'dissipation', 'of', 'the', 'energy', 'and', 'the', 'corresponding', 'brownian', 'motion', 'analysis', 'of', 'massive', 'particles', 'due', 'to', 'quantum', 'and', 'thermal', 'fluctuations', 'in', 'a', 'wide', 'class', 'of', 'strongly', 'coupled', 'quantum', 'field', 'theories', 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1,802.04984 | On ranks of polynomials | Let $V$ be a vector space over a field $k, P:V\to k, d\geq 3$. We show the
existence of a function $C(r,d)$ such that $rank (P)\leq C(r,d)$ for any field
$k,char (k)>d$, a finite-dimensional $k$-vector space $V$ and a polynomial
$P:V\to k$ of degree $d$ such that $rank(\partial P/\partial t)\leq r$ for all
$t\in V-0$. Our proof of this theorem is based on the application of results on
Gowers norms for finite fields $k$. We don't know a direct proof in the case
when $k=\mathbb C$.
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1,802.04985 | A class of fully nonlinear equations | In this paper we consider a class of fully nonlinear equations which cover
the equation introduced by S. Donaldson a decade ago and the equation
introduced by Gursky-Streets recently. We solve the equation with uniform weak
$C^2$ estimates, which hold for degenerate case.
| math.AP | in this paper we consider a class of fully nonlinear equations which cover the equation introduced by s donaldson a decade ago and the equation introduced by gurskystreets recently we solve the equation with uniform weak c2 estimates which hold for degenerate case | [['in', 'this', 'paper', 'we', 'consider', 'a', 'class', 'of', 'fully', 'nonlinear', 'equations', 'which', 'cover', 'the', 'equation', 'introduced', 'by', 's', 'donaldson', 'a', 'decade', 'ago', 'and', 'the', 'equation', 'introduced', 'by', 'gurskystreets', 'recently', 'we', 'solve', 'the', 'equation', 'with', 'uniform', 'weak', 'c2', 'estimates', 'which', 'hold', 'for', 'degenerate', 'case']] | [-0.10641159959743883, 0.07299521266547747, -0.0385585336751023, 0.04564311835362554, -0.08921291973701743, -0.16987788306852414, -0.01924214864875255, 0.2472492737998796, -0.2893861991374992, -0.2822223832495077, 0.1052887057668941, -0.22842094005453725, -0.1613753077595733, 0.16266867768582563, -0.05052832864917988, 0.09529549338540799, 0.07262345195509666, -0.044198932905876356, -0.10139466810235104, -0.314759882648887, 0.408086028946347, -0.056416108251311055, 0.1979066478305085, 0.015078665737365915, 0.17567338068904573, 0.011032109527827003, -0.008776677815720092, 0.06013079039579214, -0.25669833038781964, 0.13069830466668272, 0.2105712028610152, 0.005049811642302937, 0.30147092648630225, -0.3984514630811159, -0.309061597317977, 0.12666898103820723, 0.09254686582053817, 0.09547072670119273, -0.07049763892495702, -0.3100082477240628, 0.0815597880295976, -0.18324890171805785, -0.2158270679890763, -0.03904812503606081, 0.06336139263801796, 0.04802071416837185, -0.25342543496815273, 0.13228138477736434, 0.11249910942603682, -0.025393793467692164, -0.08563475209006736, -0.04809157515681067, 0.03464311014774234, -0.00569572085298078, 0.005801669887786861, 0.06603301568823151, -0.08907755411251686, -0.10784310244868488, -0.07201259851802227, 0.34440602680538285, -0.12483841507145012, -0.23773450166160284, 0.07639411977237784, -0.10964856799258742, -0.17550533481462058, 0.10632097929023034, 0.1381321205909169, 0.22544331580053928, -0.20517277243265578, 0.18875648824059468, -0.11343504779777208, 0.07127942779469629, 0.09852920931785605, -0.054739727552027204, 0.08798865605752136, 0.12373031709386512, 0.10508464193404761, 0.11731428323790084, 0.01131992565121415, -0.1295543423052444, -0.29217812912755237, -0.1660535767414542, -0.10891483624487422, 0.11394917471117752, 0.0380019706698963, -0.14374132441400095, 0.3828213774534159, 0.09988940175795971, 0.16070130580039912, 0.043521445228306706, 0.21353515418521182, 0.2247589721755926, 0.022994774909484265, 0.11476022574974787, 0.21762865435245426, 0.22278370432079184, 0.15369168558526178, -0.14182321498776937, 0.011968789676334276, 0.1912726293328803] |
1,802.04986 | Convolutional Neural Networks over Control Flow Graphs for Software
Defect Prediction | Existing defects in software components is unavoidable and leads to not only
a waste of time and money but also many serious consequences. To build
predictive models, previous studies focus on manually extracting features or
using tree representations of programs, and exploiting different machine
learning algorithms. However, the performance of the models is not high since
the existing features and tree structures often fail to capture the semantics
of programs. To explore deeply programs' semantics, this paper proposes to
leverage precise graphs representing program execution flows, and deep neural
networks for automatically learning defect features. Firstly, control flow
graphs are constructed from the assembly instructions obtained by compiling
source code; we thereafter apply multi-view multi-layer directed graph-based
convolutional neural networks (DGCNNs) to learn semantic features. The
experiments on four real-world datasets show that our method significantly
outperforms the baselines including several other deep learning approaches.
| cs.SE cs.LG cs.NE | existing defects in software components is unavoidable and leads to not only a waste of time and money but also many serious consequences to build predictive models previous studies focus on manually extracting features or using tree representations of programs and exploiting different machine learning algorithms however the performance of the models is not high since the existing features and tree structures often fail to capture the semantics of programs to explore deeply programs semantics this paper proposes to leverage precise graphs representing program execution flows and deep neural networks for automatically learning defect features firstly control flow graphs are constructed from the assembly instructions obtained by compiling source code we thereafter apply multiview multilayer directed graphbased convolutional neural networks dgcnns to learn semantic features the experiments on four realworld datasets show that our method significantly outperforms the baselines including several other deep learning approaches | [['existing', 'defects', 'in', 'software', 'components', 'is', 'unavoidable', 'and', 'leads', 'to', 'not', 'only', 'a', 'waste', 'of', 'time', 'and', 'money', 'but', 'also', 'many', 'serious', 'consequences', 'to', 'build', 'predictive', 'models', 'previous', 'studies', 'focus', 'on', 'manually', 'extracting', 'features', 'or', 'using', 'tree', 'representations', 'of', 'programs', 'and', 'exploiting', 'different', 'machine', 'learning', 'algorithms', 'however', 'the', 'performance', 'of', 'the', 'models', 'is', 'not', 'high', 'since', 'the', 'existing', 'features', 'and', 'tree', 'structures', 'often', 'fail', 'to', 'capture', 'the', 'semantics', 'of', 'programs', 'to', 'explore', 'deeply', 'programs', 'semantics', 'this', 'paper', 'proposes', 'to', 'leverage', 'precise', 'graphs', 'representing', 'program', 'execution', 'flows', 'and', 'deep', 'neural', 'networks', 'for', 'automatically', 'learning', 'defect', 'features', 'firstly', 'control', 'flow', 'graphs', 'are', 'constructed', 'from', 'the', 'assembly', 'instructions', 'obtained', 'by', 'compiling', 'source', 'code', 'we', 'thereafter', 'apply', 'multiview', 'multilayer', 'directed', 'graphbased', 'convolutional', 'neural', 'networks', 'dgcnns', 'to', 'learn', 'semantic', 'features', 'the', 'experiments', 'on', 'four', 'realworld', 'datasets', 'show', 'that', 'our', 'method', 'significantly', 'outperforms', 'the', 'baselines', 'including', 'several', 'other', 'deep', 'learning', 'approaches']] | [-0.05083648791737182, -0.014442885045557179, -0.08307612485562761, 0.10725661975528863, -0.15999538674885924, -0.19752683196566068, 0.021657252094074566, 0.46588925225660205, -0.3128627532569226, -0.3487315284728538, 0.09169317153898898, -0.27660324341721004, -0.1773529750595723, 0.20193327983886572, -0.12325763806842992, 0.10642968785638611, 0.1674424184085284, 0.005063266790885892, -0.0584810897012681, -0.28912499390894986, 0.33074073008093463, 0.040142836795793196, 0.3484416038975016, 0.027094357113431517, 0.11340311971919921, -0.043582736879923485, -0.06534179830163743, 0.018403634500120662, -0.05684265805459492, 0.18498662611495498, 0.37878262442614463, 0.2559218392287019, 0.2892548098833585, -0.4644910742645152, -0.256183931775417, 0.10207396078718982, 0.12318175060661612, 0.14403058293676926, 0.022865524753190886, -0.3313935257287489, 0.0695260844917761, -0.15334881045984933, 0.057022066744846396, -0.173201469057757, -0.037568321739349306, -0.006096081812251618, -0.22110364372040042, -0.04547207728986299, 0.10112097133322903, 0.07387920007588239, -0.01865969926358149, -0.14077205212541027, 0.0054619190907235155, 0.1542062674658761, 0.028833391230566323, 0.018811119405048277, 0.1742804829474254, -0.19271265576470695, -0.22119070239326297, 0.3440365655890976, -0.027564318236222282, -0.17484528895066534, 0.23312454090207918, 0.010376557174216336, -0.22465878510330287, 0.11262256916031926, 0.2523504310649716, 0.11909926342195831, -0.18935413768890108, 0.02832811359217481, -0.005677660303061, 0.19534809205975356, 0.04644147041674134, -0.007297353821437961, 0.18458740692100642, 0.2554441826796392, -9.810936095770255e-05, 0.12744985651847351, -0.07097582190827881, -0.08231816759022574, -0.1609281389165618, -0.06255774956662208, -0.13923592265766477, -0.07136211519355129, -0.09758422254637683, -0.17916973946850906, 0.39707071006867206, 0.2456070673846019, 0.17676416585325366, 0.16301275367247095, 0.3547909983770094, -0.010669258037523832, 0.17059546812540954, 0.15594730330566461, 0.14328512572521707, 0.02761982910386804, 0.15042254524370138, -0.1493853885286727, 0.127462079229493, 0.04895406648008955] |
1,802.04987 | PlayeRank: data-driven performance evaluation and player ranking in
soccer via a machine learning approach | The problem of evaluating the performance of soccer players is attracting the
interest of many companies and the scientific community, thanks to the
availability of massive data capturing all the events generated during a match
(e.g., tackles, passes, shots, etc.). Unfortunately, there is no consolidated
and widely accepted metric for measuring performance quality in all of its
facets. In this paper, we design and implement PlayeRank, a data-driven
framework that offers a principled multi-dimensional and role-aware evaluation
of the performance of soccer players. We build our framework by deploying a
massive dataset of soccer-logs and consisting of millions of match events
pertaining to four seasons of 18 prominent soccer competitions. By comparing
PlayeRank to known algorithms for performance evaluation in soccer, and by
exploiting a dataset of players' evaluations made by professional soccer
scouts, we show that PlayeRank significantly outperforms the competitors. We
also explore the ratings produced by {\sf PlayeRank} and discover interesting
patterns about the nature of excellent performances and what distinguishes the
top players from the others. At the end, we explore some applications of
PlayeRank -- i.e. searching players and player versatility --- showing its
flexibility and efficiency, which makes it worth to be used in the design of a
scalable platform for soccer analytics.
| stat.AP cs.AI | the problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community thanks to the availability of massive data capturing all the events generated during a match eg tackles passes shots etc unfortunately there is no consolidated and widely accepted metric for measuring performance quality in all of its facets in this paper we design and implement playerank a datadriven framework that offers a principled multidimensional and roleaware evaluation of the performance of soccer players we build our framework by deploying a massive dataset of soccerlogs and consisting of millions of match events pertaining to four seasons of 18 prominent soccer competitions by comparing playerank to known algorithms for performance evaluation in soccer and by exploiting a dataset of players evaluations made by professional soccer scouts we show that playerank significantly outperforms the competitors we also explore the ratings produced by sf playerank and discover interesting patterns about the nature of excellent performances and what distinguishes the top players from the others at the end we explore some applications of playerank ie searching players and player versatility showing its flexibility and efficiency which makes it worth to be used in the design of a scalable platform for soccer analytics | [['the', 'problem', 'of', 'evaluating', 'the', 'performance', 'of', 'soccer', 'players', 'is', 'attracting', 'the', 'interest', 'of', 'many', 'companies', 'and', 'the', 'scientific', 'community', 'thanks', 'to', 'the', 'availability', 'of', 'massive', 'data', 'capturing', 'all', 'the', 'events', 'generated', 'during', 'a', 'match', 'eg', 'tackles', 'passes', 'shots', 'etc', 'unfortunately', 'there', 'is', 'no', 'consolidated', 'and', 'widely', 'accepted', 'metric', 'for', 'measuring', 'performance', 'quality', 'in', 'all', 'of', 'its', 'facets', 'in', 'this', 'paper', 'we', 'design', 'and', 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1,802.04988 | The Depoissonisation quintet: Rice-Poisson-Mellin-Newton-Laplace | This paper is devoted to the Depoissonnisation process, which is central in
various analyses of the AofA domain. We first recall the two possible paths
that may be used in this process. The first path, called here the
Depoissonisation path, is better studied and is proven to apply in any
practical situation; however, it often uses technical tools, that are not so
easy to deal with. Moreover, the various results are scattered in the
litterature, and the most recent results are not well known within the AofA
domain. The present paper gathers in Section 2 all these results in a survey
style. The second path, called here the Rice-Mellin path, is less often used
within the AofA domain. It is often very easy to apply, but it needs a tameness
condition, which appears {\em a priori} to be quite restrictive, and is not
deeply studiedin the litterature. In Section 3, the paper precisely describes
the Rice-Mellin path, together with its tameness condition, in a survey style,
too. Finally, in Section 4, the paper presents original results for the
Rice-Mellin path: it exhibits a framework, of practical use, where the tameness
condition is proven to hold. It then proves that the Rice-Mellin path is both
of easy and practical use : even though (much?) less general than the
Depoissonisation path, it is easier to apply.
| math.PR | this paper is devoted to the depoissonnisation process which is central in various analyses of the aofa domain we first recall the two possible paths that may be used in this process the first path called here the depoissonisation path is better studied and is proven to apply in any practical situation however it often uses technical tools that are not so easy to deal with moreover the various results are scattered in the litterature and the most recent results are not well known within the aofa domain the present paper gathers in section 2 all these results in a survey style the second path called here the ricemellin path is less often used within the aofa domain it is often very easy to apply but it needs a tameness condition which appears em a priori to be quite restrictive and is not deeply studiedin the litterature in section 3 the paper precisely describes the ricemellin path together with its tameness condition in a survey style too finally in section 4 the paper presents original results for the ricemellin path it exhibits a framework of practical use where the tameness condition is proven to hold it then proves that the ricemellin path is both of easy and practical use even though much less general than the depoissonisation path it is easier to apply | [['this', 'paper', 'is', 'devoted', 'to', 'the', 'depoissonnisation', 'process', 'which', 'is', 'central', 'in', 'various', 'analyses', 'of', 'the', 'aofa', 'domain', 'we', 'first', 'recall', 'the', 'two', 'possible', 'paths', 'that', 'may', 'be', 'used', 'in', 'this', 'process', 'the', 'first', 'path', 'called', 'here', 'the', 'depoissonisation', 'path', 'is', 'better', 'studied', 'and', 'is', 'proven', 'to', 'apply', 'in', 'any', 'practical', 'situation', 'however', 'it', 'often', 'uses', 'technical', 'tools', 'that', 'are', 'not', 'so', 'easy', 'to', 'deal', 'with', 'moreover', 'the', 'various', 'results', 'are', 'scattered', 'in', 'the', 'litterature', 'and', 'the', 'most', 'recent', 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1,802.04989 | A second order scheme for a Robin boundary condition in random walk
algorithms | Random Walk (RW) is a common numerical tool for modeling the
Advection-Diffusion equation. In this work, we develop a second order scheme
for incorporating a heterogeneous reaction (i.e., a Robin boundary condition)
in the RW model. In addition, we apply the approach in two test cases. We
compare the second order scheme with the first order one as well as with
analytical and other numerical solution. We show that the new scheme can reduce
the computational error significantly, relative to the first order scheme. This
reduction comes at no additional computational cost.
| physics.comp-ph | random walk rw is a common numerical tool for modeling the advectiondiffusion equation in this work we develop a second order scheme for incorporating a heterogeneous reaction ie a robin boundary condition in the rw model in addition we apply the approach in two test cases we compare the second order scheme with the first order one as well as with analytical and other numerical solution we show that the new scheme can reduce the computational error significantly relative to the first order scheme this reduction comes at no additional computational cost | [['random', 'walk', 'rw', 'is', 'a', 'common', 'numerical', 'tool', 'for', 'modeling', 'the', 'advectiondiffusion', 'equation', 'in', 'this', 'work', 'we', 'develop', 'a', 'second', 'order', 'scheme', 'for', 'incorporating', 'a', 'heterogeneous', 'reaction', 'ie', 'a', 'robin', 'boundary', 'condition', 'in', 'the', 'rw', 'model', 'in', 'addition', 'we', 'apply', 'the', 'approach', 'in', 'two', 'test', 'cases', 'we', 'compare', 'the', 'second', 'order', 'scheme', 'with', 'the', 'first', 'order', 'one', 'as', 'well', 'as', 'with', 'analytical', 'and', 'other', 'numerical', 'solution', 'we', 'show', 'that', 'the', 'new', 'scheme', 'can', 'reduce', 'the', 'computational', 'error', 'significantly', 'relative', 'to', 'the', 'first', 'order', 'scheme', 'this', 'reduction', 'comes', 'at', 'no', 'additional', 'computational', 'cost']] | [-0.10047846590168774, 0.006257868280796253, -0.08945986280077309, 0.03479210082719953, -0.07509203647951716, -0.15843743651740902, 0.0627256931063881, 0.36450154174362187, -0.2529830454403292, -0.29658219075012626, 0.11735584265451231, -0.25138722311037226, -0.19229517030813123, 0.1669409960513408, -0.05449279455301028, 0.09933567632232672, 0.05873728672082981, 0.035149048750653215, -0.06292694762068214, -0.2584430071646753, 0.3106673280316223, 0.029432071962535545, 0.2550960907753071, 0.03022430454502287, 0.09890916780568659, -0.05060604329058981, -0.04086675739887616, 0.023649547511151624, -0.12377327070965333, 0.10666438028641531, 0.1873921160991101, 0.04074214811882247, 0.32415537163615227, -0.41552463976625836, -0.24509892498304986, 0.0748492646506866, 0.135715863313121, 0.17533772932770458, -0.04457794030895457, -0.21439693819569505, 0.11524539188805806, -0.20682005843390588, -0.1388442271095498, -0.0804222950018416, -0.060381846198731146, 0.0016297822737175486, -0.3368447881151477, 0.07426278852938634, 0.051234670048317006, -0.01175812020411958, -0.05987429224541816, -0.08872665938131673, 0.0387919344660907, 0.11424830798869548, 0.032124472856673456, 0.037767221757942185, 0.01811930335774694, -0.07587516824613609, -0.13463791383369622, 0.42741816857343784, -0.10303090705597044, -0.2497890790640984, 0.18478522030636668, -0.11495885588026242, -0.14669141832374685, 0.11083419452441613, 0.20228937695450758, 0.13970329788128805, -0.13478925977529876, 0.04204499706279223, 0.01111510453578692, 0.16637135885210466, 0.042303663081206054, -0.027576996743648677, 0.053286188307380224, 0.20442444282462416, 0.09738557482436906, 0.17672772040026283, -0.10080399042066268, -0.12658829379664815, -0.3610333327770881, -0.204006204928231, -0.16544409295665505, -0.008449535604323382, -0.1275317796818221, -0.11839607227138123, 0.36756662750643876, 0.20891796424478778, 0.17435672462654664, 0.07383091846966873, 0.36302657231040625, 0.16637450202783247, -0.0016605916696236186, 0.09385520304330504, 0.1707122474807598, 0.08261312955089481, 0.1272905821831006, -0.24071281879150774, 0.06520558568983055, 0.11085843440125008] |
1,802.0499 | American Options in the Hobson-Rogers Model | In this article, we consider a risky asset $X$ for which evolution follows a
model proposed by D.G. Hobson and L.C.G. Rogers\cite{HR98}. We assume that the
volatility of $X$ depends on the ratio of the present value and the
exponentially weighted average of the past value. Using the Markovian modelling
of the enlarged two-dimensional process, we show that, for the American put
option with $X$ as the underlying asset, the continuation region and the
stopped region are separated a striking curve . This striking curve lies
between the two striking curves from the basic BSM model, yet is {\em not}
monotone.
| math.PR | in this article we consider a risky asset x for which evolution follows a model proposed by dg hobson and lcg rogerscitehr98 we assume that the volatility of x depends on the ratio of the present value and the exponentially weighted average of the past value using the markovian modelling of the enlarged twodimensional process we show that for the american put option with x as the underlying asset the continuation region and the stopped region are separated a striking curve this striking curve lies between the two striking curves from the basic bsm model yet is em not monotone | [['in', 'this', 'article', 'we', 'consider', 'a', 'risky', 'asset', 'x', 'for', 'which', 'evolution', 'follows', 'a', 'model', 'proposed', 'by', 'dg', 'hobson', 'and', 'lcg', 'rogerscitehr98', 'we', 'assume', 'that', 'the', 'volatility', 'of', 'x', 'depends', 'on', 'the', 'ratio', 'of', 'the', 'present', 'value', 'and', 'the', 'exponentially', 'weighted', 'average', 'of', 'the', 'past', 'value', 'using', 'the', 'markovian', 'modelling', 'of', 'the', 'enlarged', 'twodimensional', 'process', 'we', 'show', 'that', 'for', 'the', 'american', 'put', 'option', 'with', 'x', 'as', 'the', 'underlying', 'asset', 'the', 'continuation', 'region', 'and', 'the', 'stopped', 'region', 'are', 'separated', 'a', 'striking', 'curve', 'this', 'striking', 'curve', 'lies', 'between', 'the', 'two', 'striking', 'curves', 'from', 'the', 'basic', 'bsm', 'model', 'yet', 'is', 'em', 'not', 'monotone']] | [-0.10905036777304956, 0.05192924091460729, -0.11586283814547715, 0.07903839537419742, -0.04700141750520678, -0.13995620187353155, 0.09198061061430383, 0.3863897808272429, -0.2864332978162124, -0.22714152559638023, 0.1289619518281666, -0.2559141285171864, -0.1342299508655237, 0.18103402047276948, -0.09046208077272626, -0.01088647765455523, 0.028398716620009656, 0.01578501800093988, -0.03900333423863607, -0.2227829577744647, 0.3176237890553294, 0.01878226443541923, 0.26123275993523576, 0.007316346741234413, 0.15698881172622092, 0.021353373828466343, -0.03156002657017624, 0.014656155718245892, -0.1493241501076328, 0.1346582274771098, 0.20989313708192603, 0.09439900984536066, 0.2659741412058021, -0.3735675182231147, -0.20856928058683571, 0.15624206973183336, 0.08493830491741648, 0.0029498428771286412, -0.023233143482216154, -0.24196766287140134, 0.0296542746123077, -0.15925977632610333, -0.13883748754501493, 0.023415778798869614, 0.06460069261039748, 0.029373413742040142, -0.2633089044771035, 0.07879663105452, 0.058685580102698594, 0.02619906741304963, -0.009528435197555356, -0.1417549554578433, -0.04133952837531464, 0.06815330430187962, 0.09044054624562227, 0.039614056566297406, 0.10392265069778218, -0.12328815423986977, -0.09824283743709927, 0.3571419205159099, -0.11328663083376607, -0.1530411315874921, 0.13484796992681844, -0.19924942676843416, -0.09830844242095176, 0.10331710782654659, 0.13748732154643295, 0.1168902742140221, -0.1407598993562237, 0.12535957379014975, -0.11240886446239069, 0.1610295419426014, 0.01259418638573602, -0.01761090239942676, 0.1989790578137594, 0.19532025474208323, 0.06213024857858516, 0.12003313210167255, -0.08868728088323177, -0.15916362866251307, -0.3692500073124062, -0.15793873219412158, -0.14772351757232852, 0.06734789608089334, -0.11294057372104344, -0.1541531045986998, 0.39676395761357114, 0.14281155004382434, 0.20842614070032583, 0.05784490771210668, 0.23459182598280034, 0.14880209033156397, -0.026929391890521997, 0.0953258096212239, 0.22204764811039873, 0.055389536782214886, 0.10945946804125502, -0.1846068705446228, 0.15192888770252466, 0.07574984517108385] |
1,802.04991 | Regularity of entropy, geodesic currents and entropy at infinity | In this work, we introduce the notion of entropy at infinity, and define a
wide class of noncompact manifolds with negative curvature, those which admit a
critical gap between entropy at infinity and topological entropy. We call them
strongly positively recurrent manifolds (SPR), and provide many examples. We
show that dynamically, they behave as compact manifolds. In particular, they
admit a finite measure of maximal entropy. Using the point of view of currents
at infinity, we show that on these SPR manifolds the topological entropy of the
geodesic flow varies in a C 1 -way along (uniformly) C 1 -perturbations of the
metric. This result generalizes former work of Katok (1982) and
Katok-Knieper-Weiss (1991) in the compact case.
| math.DS | in this work we introduce the notion of entropy at infinity and define a wide class of noncompact manifolds with negative curvature those which admit a critical gap between entropy at infinity and topological entropy we call them strongly positively recurrent manifolds spr and provide many examples we show that dynamically they behave as compact manifolds in particular they admit a finite measure of maximal entropy using the point of view of currents at infinity we show that on these spr manifolds the topological entropy of the geodesic flow varies in a c 1 way along uniformly c 1 perturbations of the metric this result generalizes former work of katok 1982 and katokknieperweiss 1991 in the compact case | [['in', 'this', 'work', 'we', 'introduce', 'the', 'notion', 'of', 'entropy', 'at', 'infinity', 'and', 'define', 'a', 'wide', 'class', 'of', 'noncompact', 'manifolds', 'with', 'negative', 'curvature', 'those', 'which', 'admit', 'a', 'critical', 'gap', 'between', 'entropy', 'at', 'infinity', 'and', 'topological', 'entropy', 'we', 'call', 'them', 'strongly', 'positively', 'recurrent', 'manifolds', 'spr', 'and', 'provide', 'many', 'examples', 'we', 'show', 'that', 'dynamically', 'they', 'behave', 'as', 'compact', 'manifolds', 'in', 'particular', 'they', 'admit', 'a', 'finite', 'measure', 'of', 'maximal', 'entropy', 'using', 'the', 'point', 'of', 'view', 'of', 'currents', 'at', 'infinity', 'we', 'show', 'that', 'on', 'these', 'spr', 'manifolds', 'the', 'topological', 'entropy', 'of', 'the', 'geodesic', 'flow', 'varies', 'in', 'a', 'c', '1', 'way', 'along', 'uniformly', 'c', '1', 'perturbations', 'of', 'the', 'metric', 'this', 'result', 'generalizes', 'former', 'work', 'of', 'katok', '1982', 'and', 'katokknieperweiss', '1991', 'in', 'the', 'compact', 'case']] | [-0.15807863496817076, 0.16229718452235922, -0.09048594846031986, 0.07680082593996747, -0.038930598439441785, -0.16888378539051002, 0.020588366181438424, 0.36238660187357, -0.26951913606041134, -0.22600686855805227, 0.08168655635717396, -0.32255259274035436, -0.17044503262075475, 0.1838132218640839, -0.1295684862515738, 0.02410552631586026, 0.05131411504271066, 0.08506468384806266, -0.08254563154326354, -0.23151780584723586, 0.42304429325919884, -0.006537638334000212, 0.26235750721942663, 0.10016267500324254, 0.09413848687948373, -0.03934623781018532, -0.012212079981517078, 0.09540448448039655, -0.18938690709518807, 0.12563147025310203, 0.2443408920755759, 0.1010903396572058, 0.23665500757021782, -0.3327385811533174, -0.23380080995778751, 0.14956303938634247, 0.0957977865182329, 0.061752394288499705, -0.024377375535674903, -0.2533657925708904, 0.12157769145794277, -0.13474681122132984, -0.16502833527385488, -0.07558395868788163, 0.017924524103410732, 0.008507622748167597, -0.1579027708627793, 0.048466641750409566, 0.16420374938056, 0.06111724799674036, -0.05834948921846783, -0.05048307856474207, -0.06058729284305651, 0.09695303687650679, 0.04790220123070937, 0.07368709412343705, 0.12178105415585332, -0.04175198813860551, -0.1186442140641057, 0.2940312308084188, -0.10951824454415558, -0.2494705542603619, 0.21791435407999998, -0.15980659986440188, -0.16325445274989575, 0.0944508168902089, 0.17054724966526094, 0.20781961234652588, -0.06414510101541622, 0.1336490473168719, -0.052022796848581895, 0.049234865544986725, 0.11540383769151492, 0.04063110554821662, 0.18182467221895343, 0.08058571015707512, 0.16369196601385155, 0.1740118301051677, -0.033562083039323315, -0.08791618690324518, -0.3432113602757454, -0.2174839094106076, -0.14907627904083198, 0.13085748593553773, -0.12219876107415503, -0.21427551469900924, 0.36772431601953304, 0.07884747818367094, 0.2527521970626126, 0.13334624670531986, 0.19475053342926896, 0.07084007808266, 0.022759799155979775, 0.15329068863334563, 0.19139119349698672, 0.13928803681340227, 0.09316281020705007, -0.1512891327500598, -0.040965213985371396, 0.11169263134654771] |
1,802.04992 | The Soul Conjecture in Alexandrov Geometry in dimension 4 | In this paper, we prove the Soul Conjecture in Alexandrov geometry in
dimension $4$, i.e. if $X$ is a complete non-compact $4$-dimensional Alexandrov
space of non-negative curvature and positive curvature around one point, then a
soul of $X$ is a point.
| math.MG | in this paper we prove the soul conjecture in alexandrov geometry in dimension 4 ie if x is a complete noncompact 4dimensional alexandrov space of nonnegative curvature and positive curvature around one point then a soul of x is a point | [['in', 'this', 'paper', 'we', 'prove', 'the', 'soul', 'conjecture', 'in', 'alexandrov', 'geometry', 'in', 'dimension', '4', 'ie', 'if', 'x', 'is', 'a', 'complete', 'noncompact', '4dimensional', 'alexandrov', 'space', 'of', 'nonnegative', 'curvature', 'and', 'positive', 'curvature', 'around', 'one', 'point', 'then', 'a', 'soul', 'of', 'x', 'is', 'a', 'point']] | [-0.19932481994080106, 0.0866334726579669, -0.10488538073784695, 0.08457053283785992, -0.08384093795562299, -0.17837754888005736, -0.007755812322834461, 0.34575385173282974, -0.24006648091372193, -0.13140387067616713, 0.15863586659259277, -0.33445414507239146, -0.19260653254871324, 0.10058495866293769, -0.1899765848676197, -0.03774298912641115, -0.00871358973133128, 0.13894076363706007, -0.10889383064719235, -0.31343723297482584, 0.4946407984669616, -0.11554739742380817, 0.15663365858164047, 0.16588881028043787, 0.17958523189967, -0.02166188311785823, 0.033293385058641434, 0.08022872082500082, -0.18524767250594934, 0.12771407107640875, 0.24012561087928166, 0.10031519090847635, 0.2580921233336373, -0.2938901354081747, -0.21654813494192574, 0.22881258833335666, 0.10426283162087202, -0.009629562451708608, -0.04573752481785671, -0.27005866215359875, 0.14863586855098243, -0.02034293178741525, -0.24363892788930638, -0.005444617703466154, 0.08480245426933213, -0.13239328601829162, -0.20389417867834975, 0.040438402080681266, 0.14943359194823155, 0.09091465781647258, -0.09310240839130995, -0.06082054931761288, -0.0881229543195265, 0.04436834134649849, -0.0035755505853491587, 0.15760964259403054, 0.03828960278911925, -0.015182699093867729, -0.1005032742509573, 0.3171837653442309, -0.08354399012537991, -0.2798688419890113, 0.03634040584651435, -0.217144920104524, -0.15486941822781797, 0.15507087243221154, 0.1636461588531369, 0.21560977472037804, -0.02701129203253403, 0.25271481391263945, -0.09499281962265874, 0.11094895373921977, 0.13445754094821652, -0.07161737038049756, 0.16475042219205602, 0.1472653972393856, 0.20417799930110936, 0.12332722858139654, -0.02856199643233927, -0.021682698404552732, -0.3863089426261623, -0.29319030087350345, -0.20579265968919527, 0.27291947566881414, -0.16694593037693, -0.1692513828279405, 0.3209190363995731, -0.001062177462367023, 0.19648698553806399, 0.10791269505805359, 0.24069653778541378, -0.025620556868067603, -0.0592096585144357, 0.15991173804987494, 0.17070365860694792, 0.14993979677376224, 0.06825963973362999, -0.012231337076916201, -0.09019559549122322, 0.19745737052999618] |
1,802.04993 | Heat Coulomb Blockade of One Ballistic Channel | Quantum mechanics and Coulomb interaction dictate the behavior of small
circuits. The thermal implications cover fundamental topics from quantum
control of heat to quantum thermodynamics, with prospects of novel thermal
machines and an ineluctably growing influence on nanocircuit engineering.
Experimentally, the rare observations thus far include the universal thermal
conductance quantum and heat interferometry. However, evidences for many-body
thermal effects paving the way to markedly different heat and electrical
behaviors in quantum circuits remain wanting. Here we report on the observation
of the Coulomb blockade of electronic heat flow from a small metallic circuit
node, beyond the widespread Wiedemann-Franz law paradigm. We demonstrate this
thermal many-body phenomenon for perfect (ballistic) conduction channels to the
node, where it amounts to the universal suppression of precisely one quantum of
conductance for the transport of heat, but none for electricity. The
inter-channel correlations that give rise to such selective heat current
reduction emerge from local charge conservation, in the floating node over the
full thermal frequency range ($\lesssim$temperature$\times k_\mathrm{B}/h$).
This observation establishes the different nature of the quantum laws for
thermal transport in nanocircuits.
| cond-mat.mes-hall cond-mat.stat-mech cond-mat.str-el quant-ph | quantum mechanics and coulomb interaction dictate the behavior of small circuits the thermal implications cover fundamental topics from quantum control of heat to quantum thermodynamics with prospects of novel thermal machines and an ineluctably growing influence on nanocircuit engineering experimentally the rare observations thus far include the universal thermal conductance quantum and heat interferometry however evidences for manybody thermal effects paving the way to markedly different heat and electrical behaviors in quantum circuits remain wanting here we report on the observation of the coulomb blockade of electronic heat flow from a small metallic circuit node beyond the widespread wiedemannfranz law paradigm we demonstrate this thermal manybody phenomenon for perfect ballistic conduction channels to the node where it amounts to the universal suppression of precisely one quantum of conductance for the transport of heat but none for electricity the interchannel correlations that give rise to such selective heat current reduction emerge from local charge conservation in the floating node over the full thermal frequency range lesssimtemperaturetimes k_mathrmbh this observation establishes the different nature of the quantum laws for thermal transport in nanocircuits | [['quantum', 'mechanics', 'and', 'coulomb', 'interaction', 'dictate', 'the', 'behavior', 'of', 'small', 'circuits', 'the', 'thermal', 'implications', 'cover', 'fundamental', 'topics', 'from', 'quantum', 'control', 'of', 'heat', 'to', 'quantum', 'thermodynamics', 'with', 'prospects', 'of', 'novel', 'thermal', 'machines', 'and', 'an', 'ineluctably', 'growing', 'influence', 'on', 'nanocircuit', 'engineering', 'experimentally', 'the', 'rare', 'observations', 'thus', 'far', 'include', 'the', 'universal', 'thermal', 'conductance', 'quantum', 'and', 'heat', 'interferometry', 'however', 'evidences', 'for', 'manybody', 'thermal', 'effects', 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1,802.04994 | Idempotent geometry in generic algebras | Using the syzygy method, established in our earlier paper, we characterize
the combinatorial stratification of the variety of two-dimensional real generic
algebras. We show that there exist exactly three different homotopic types of
such algebras and relate this result to potential applications and known facts
from qualitative theory of quadratic ODEs. The genericity condition is crucial.
For example, the idempotent geometry in Clifford algebras or Jordan algebras of
Clifford type is very different: such algebras always contain nontrivial
submanifolds of idempotents.
| math.RA math.AC math.DS | using the syzygy method established in our earlier paper we characterize the combinatorial stratification of the variety of twodimensional real generic algebras we show that there exist exactly three different homotopic types of such algebras and relate this result to potential applications and known facts from qualitative theory of quadratic odes the genericity condition is crucial for example the idempotent geometry in clifford algebras or jordan algebras of clifford type is very different such algebras always contain nontrivial submanifolds of idempotents | [['using', 'the', 'syzygy', 'method', 'established', 'in', 'our', 'earlier', 'paper', 'we', 'characterize', 'the', 'combinatorial', 'stratification', 'of', 'the', 'variety', 'of', 'twodimensional', 'real', 'generic', 'algebras', 'we', 'show', 'that', 'there', 'exist', 'exactly', 'three', 'different', 'homotopic', 'types', 'of', 'such', 'algebras', 'and', 'relate', 'this', 'result', 'to', 'potential', 'applications', 'and', 'known', 'facts', 'from', 'qualitative', 'theory', 'of', 'quadratic', 'odes', 'the', 'genericity', 'condition', 'is', 'crucial', 'for', 'example', 'the', 'idempotent', 'geometry', 'in', 'clifford', 'algebras', 'or', 'jordan', 'algebras', 'of', 'clifford', 'type', 'is', 'very', 'different', 'such', 'algebras', 'always', 'contain', 'nontrivial', 'submanifolds', 'of', 'idempotents']] | [-0.1547799811491536, 0.027189691505038444, -0.0390438150074103, 0.10822140945288364, -0.08511580561322195, -0.18470812531441083, -0.07507759325183284, 0.3373808222075487, -0.3598862353620338, -0.21941324465988596, 0.10074253841648223, -0.23533118079577423, -0.24532289912544744, 0.22806708667754988, -0.16119298289449493, 0.0016189271549659748, 0.07729063944224222, 0.0857935564270542, -0.11978145865110873, -0.2948673438556768, 0.4537299900016759, -0.07365925505722838, 0.22525871538177686, 0.05104973539135155, 0.09247800490077308, 0.0063265750219148615, -0.019116043906520913, 0.0191287866622543, -0.16211894515337333, 0.08019889824747763, 0.3330738260094536, 0.11456129527478306, 0.1832509767781529, -0.41036065562087815, -0.12166379185186492, 0.18775551615104677, 0.13319350495060653, 0.049173610802325934, -0.05402436679844273, -0.22975058870872966, 0.07944378186445568, -0.18269734160491713, -0.1616985083753128, -0.11997426651924113, 0.045776182090012746, 0.0028278321303703167, -0.22226778648716086, 0.024285338094664946, 0.1488829116612949, 0.1905653242619685, -0.12633764252273572, -0.10653883091714463, -0.07778413421014485, 0.10429751191483695, -0.021228059787119245, -0.045271881522587785, 0.09692527584869552, -0.02794168005340997, -0.17745966190058324, 0.35160678895305336, 0.03636368976928937, -0.23655022495069805, 0.2038026805392202, -0.15914308074804276, -0.2121354143227232, 0.07662296338282802, 0.05910782191764425, 0.13698284936217983, -0.0716078327278848, 0.17830116087197107, -0.13498474441951624, 0.022646582299515744, 0.12637042810703503, 0.020356050472603075, 0.14919922195007035, 0.08985842362529149, 0.04176977833296046, 0.12486759193218601, 0.07628814463308196, -0.07070399126336899, -0.3716832470309771, -0.18075759173083453, -0.10685452748159016, 0.12567789366692994, -0.14611707212091538, -0.21963282996489678, 0.44357808372350754, 0.15438388094857888, 0.1300329257975574, 0.054995852097133056, 0.2334631389627854, 0.049054705809491374, 0.11535288137096314, 0.023431604785591732, 0.17545496890850273, 0.24171461910009384, 0.009483334550886978, -0.09533380490747843, -0.04320156153429438, 0.17790210875969978] |
1,802.04995 | Breeze: Sharing Biofeedback Through Wearable Technologies | Digitally presenting physiological signals as biofeedback to users raises
awareness of both body and mind. This paper describes the effectiveness of
conveying a physiological signal often overlooked for communication: breathing.
We present the design and development of digital breathing patterns and their
evaluation along three output modalities: visual, audio, and haptic. We also
present Breeze, a wearable pendant placed around the neck that measures
breathing and sends biofeedback in real-time. We evaluated how the breathing
patterns were interpreted in a fixed environment and gathered qualitative data
on the wearable device's design. We found that participants intentionally
modified their own breathing to match the biofeedback, as a technique for
understanding the underlying emotion. Our results describe how the features of
the breathing patterns and the feedback modalities influenced participants'
perception. We include guidelines and suggested use cases, such as Breeze being
used by loved ones to increase connectedness and empathy.
| cs.HC | digitally presenting physiological signals as biofeedback to users raises awareness of both body and mind this paper describes the effectiveness of conveying a physiological signal often overlooked for communication breathing we present the design and development of digital breathing patterns and their evaluation along three output modalities visual audio and haptic we also present breeze a wearable pendant placed around the neck that measures breathing and sends biofeedback in realtime we evaluated how the breathing patterns were interpreted in a fixed environment and gathered qualitative data on the wearable devices design we found that participants intentionally modified their own breathing to match the biofeedback as a technique for understanding the underlying emotion our results describe how the features of the breathing patterns and the feedback modalities influenced participants perception we include guidelines and suggested use cases such as breeze being used by loved ones to increase connectedness and empathy | [['digitally', 'presenting', 'physiological', 'signals', 'as', 'biofeedback', 'to', 'users', 'raises', 'awareness', 'of', 'both', 'body', 'and', 'mind', 'this', 'paper', 'describes', 'the', 'effectiveness', 'of', 'conveying', 'a', 'physiological', 'signal', 'often', 'overlooked', 'for', 'communication', 'breathing', 'we', 'present', 'the', 'design', 'and', 'development', 'of', 'digital', 'breathing', 'patterns', 'and', 'their', 'evaluation', 'along', 'three', 'output', 'modalities', 'visual', 'audio', 'and', 'haptic', 'we', 'also', 'present', 'breeze', 'a', 'wearable', 'pendant', 'placed', 'around', 'the', 'neck', 'that', 'measures', 'breathing', 'and', 'sends', 'biofeedback', 'in', 'realtime', 'we', 'evaluated', 'how', 'the', 'breathing', 'patterns', 'were', 'interpreted', 'in', 'a', 'fixed', 'environment', 'and', 'gathered', 'qualitative', 'data', 'on', 'the', 'wearable', 'devices', 'design', 'we', 'found', 'that', 'participants', 'intentionally', 'modified', 'their', 'own', 'breathing', 'to', 'match', 'the', 'biofeedback', 'as', 'a', 'technique', 'for', 'understanding', 'the', 'underlying', 'emotion', 'our', 'results', 'describe', 'how', 'the', 'features', 'of', 'the', 'breathing', 'patterns', 'and', 'the', 'feedback', 'modalities', 'influenced', 'participants', 'perception', 'we', 'include', 'guidelines', 'and', 'suggested', 'use', 'cases', 'such', 'as', 'breeze', 'being', 'used', 'by', 'loved', 'ones', 'to', 'increase', 'connectedness', 'and', 'empathy']] | [-0.11290424212796969, 0.07815246986250249, -0.06843852614296363, 0.04476627491683318, -0.13096868724721616, -0.17980949208765423, 0.056518074013324045, 0.4163037590907524, -0.2376880989997529, -0.2931138766091942, 0.10899830130928964, -0.3278327159358551, -0.24930701624827098, 0.1811469288467861, -0.16412267689874407, 0.02284935226151407, 0.07328540944859961, 0.06947017642169341, 0.024686691510622333, -0.2142693299500134, 0.2563853342704875, 0.034784847220418434, 0.3285332800907977, 0.03957289703590358, 0.09740926812624796, 0.023839250366334747, -0.047114573063206974, -0.025590535684484515, -0.1344898520394005, 0.13258058014294546, 0.3147739851409757, 0.21472802246301967, 0.30850695114857796, -0.4749259661958122, -0.1922743103416924, 0.030858530683267937, 0.15563744744723476, 0.09362689315672688, -0.09319148314710482, -0.370289861099582, 0.06675545971265576, -0.17189757927827187, -0.07740837156344064, -0.08046811230280655, -0.010419505735821772, 0.028742517124873294, -0.23156925381455046, 0.04276893247093149, 0.041893570740150925, 0.16000491390692306, -0.11964647544224843, -0.0712461377849143, -0.017182040839274756, 0.24824525854056514, 0.06898480496875592, -0.018772122542367587, 0.236052781856, -0.15094980281065123, -0.13424407914218386, 0.3683313997524897, -0.0044538429094440985, -0.20615024933428971, 0.22620248738770066, -0.09232745617128059, -0.0685434913443989, 0.042826381380726024, 0.22250350805674524, 0.029459446348287417, -0.15677937552420385, -0.0959275223899964, 0.02045295526111036, 0.2097270012569095, 0.11175277652750229, 0.031006769408415628, 0.19171005551196985, 0.18083734625962958, -0.010088624867873154, 0.1403485874246162, -0.06736243636196561, -0.031781059107743204, -0.23799561107985912, -0.11230976962415665, -0.12981324993470847, -0.041868933689024224, -0.03525194894097005, -0.1022258270836604, 0.4255483695962185, 0.19357880224761298, 0.1570998970169149, 0.020650535631274818, 0.3259761531512259, -0.0040768944367691375, 0.07339496590547114, 0.023667673108436718, 0.1870734872508969, 0.025587599216679097, 0.19833601258332598, -0.23287928761326826, 0.11013409597549162, -0.013411670123170686] |
1,802.04996 | The algebraic de Rham realization of the elliptic polylogarithm via the
Poincar\'e bundle | In this paper, we describe the algebraic de Rham realization of the elliptic
polylogarithm for arbitrary families of elliptic curves in terms of the
Poincar\'e bundle. Our work builds on previous work of Scheider and generalizes
results of Bannai-Kobayashi-Tsuji and Scheider. As an application, we compute
the de Rham Eisenstein classes explicitly in terms of certain algebraic
Eisenstein series.
| math.NT | in this paper we describe the algebraic de rham realization of the elliptic polylogarithm for arbitrary families of elliptic curves in terms of the poincare bundle our work builds on previous work of scheider and generalizes results of bannaikobayashitsuji and scheider as an application we compute the de rham eisenstein classes explicitly in terms of certain algebraic eisenstein series | [['in', 'this', 'paper', 'we', 'describe', 'the', 'algebraic', 'de', 'rham', 'realization', 'of', 'the', 'elliptic', 'polylogarithm', 'for', 'arbitrary', 'families', 'of', 'elliptic', 'curves', 'in', 'terms', 'of', 'the', 'poincare', 'bundle', 'our', 'work', 'builds', 'on', 'previous', 'work', 'of', 'scheider', 'and', 'generalizes', 'results', 'of', 'bannaikobayashitsuji', 'and', 'scheider', 'as', 'an', 'application', 'we', 'compute', 'the', 'de', 'rham', 'eisenstein', 'classes', 'explicitly', 'in', 'terms', 'of', 'certain', 'algebraic', 'eisenstein', 'series']] | [-0.22695940190793149, -0.006679725099145019, -0.1519550574677331, 0.020110852806413147, -0.13343976787291467, -0.021045511987592493, -0.08298239741998259, 0.22469444493097918, -0.2553202970302664, -0.2787900536786765, 0.06322391126845364, -0.22589045802929572, -0.22283233784505033, 0.28762456989248414, -0.1935349998363693, 0.07199599494093231, -0.009482806107761073, 0.05201547563774511, -0.09886656264175794, -0.33752724312320687, 0.500347419641912, -0.002365287792469774, 0.23486234018179988, 0.02145890618807503, 0.10508493953550767, 0.06001153755642008, -0.07375574477815203, -0.12815085476696758, -0.17454841207446797, 0.23421285504134307, 0.3807249677234462, 0.005506171404184508, 0.14135467640257307, -0.38558896471347126, -0.13750452674659236, 0.16692845821048, 0.18083270326522843, 0.06092015336201127, 0.03315686405195655, -0.2376644233258308, 0.04082862202942904, -0.19959400126910104, -0.18295937319219643, -0.12276500579069502, -0.0009889841146234954, 0.07358397523473416, -0.2041985699158561, 0.01956421138519155, 0.10347907915378787, 0.1684766821563244, -0.1112362190532232, -0.08870404741277785, -0.010904706927249208, 0.03672119133573558, 0.01655794954526105, 0.009386936535260506, 0.057477841802340536, -0.0651778915988481, -0.1792036361137954, 0.3134515216307981, -0.1345093501399138, -0.19154954974406532, 0.07492591281022344, -0.1231063324958086, -0.23646085636158073, 0.06681668808284615, 0.13638227002229542, 0.22553252226706327, 0.015561694661820573, 0.22952393375661423, -0.09247653981271599, 0.019714384073657647, 0.1851738496708484, -0.013929403619840741, 0.0846120850058339, 0.03063388993697507, 0.007252308024492647, 0.13820744630772555, 0.049135816836496815, -0.10097694373689592, -0.39916026033461094, -0.2794563946663402, -0.11870404596889525, 0.08111283977216642, -0.10688538263899058, -0.23142653131591423, 0.4764762632548809, 0.0904959253301578, 0.2483226636125307, 0.14991520038373501, 0.21314935989877476, 0.10152918866203565, -0.014723526247377907, 0.015097866566585643, 0.11649742988603455, 0.17212913341687194, 0.06172882175971089, -0.16755125545231359, -0.030211494278254186, 0.22475870723636554] |
1,802.04997 | Quantum phase transitions of a two-leg bosonic ladder in an artificial
gauge field | We consider a two leg bosonic ladder in a $U(1)$ gauge field with both
interleg hopping and interleg repulsion. As a function of the flux, the
interleg interaction converts the commensurate-incommensurate transition from
the Meissner to a Vortex phase, into an Ising-type of transition towards a
density wave phase. A disorder point is also found after which the correlation
functions develop a damped sinusoid behavior signaling a melting of the vortex
phase. We discuss the differences on the phase diagram for attractive and
repulsive interleg interaction. In particular, we show how repulsion favors the
Meissner phase at low-flux and a phase with a second incommensuration in the
correlation functions for intermediate flux, leading to a richer phase diagram
than in the case of interleg attraction. The effect of the temperature on the
chiral current is also discussed.
| cond-mat.quant-gas | we consider a two leg bosonic ladder in a u1 gauge field with both interleg hopping and interleg repulsion as a function of the flux the interleg interaction converts the commensurateincommensurate transition from the meissner to a vortex phase into an isingtype of transition towards a density wave phase a disorder point is also found after which the correlation functions develop a damped sinusoid behavior signaling a melting of the vortex phase we discuss the differences on the phase diagram for attractive and repulsive interleg interaction in particular we show how repulsion favors the meissner phase at lowflux and a phase with a second incommensuration in the correlation functions for intermediate flux leading to a richer phase diagram than in the case of interleg attraction the effect of the temperature on the chiral current is also discussed | [['we', 'consider', 'a', 'two', 'leg', 'bosonic', 'ladder', 'in', 'a', 'u1', 'gauge', 'field', 'with', 'both', 'interleg', 'hopping', 'and', 'interleg', 'repulsion', 'as', 'a', 'function', 'of', 'the', 'flux', 'the', 'interleg', 'interaction', 'converts', 'the', 'commensurateincommensurate', 'transition', 'from', 'the', 'meissner', 'to', 'a', 'vortex', 'phase', 'into', 'an', 'isingtype', 'of', 'transition', 'towards', 'a', 'density', 'wave', 'phase', 'a', 'disorder', 'point', 'is', 'also', 'found', 'after', 'which', 'the', 'correlation', 'functions', 'develop', 'a', 'damped', 'sinusoid', 'behavior', 'signaling', 'a', 'melting', 'of', 'the', 'vortex', 'phase', 'we', 'discuss', 'the', 'differences', 'on', 'the', 'phase', 'diagram', 'for', 'attractive', 'and', 'repulsive', 'interleg', 'interaction', 'in', 'particular', 'we', 'show', 'how', 'repulsion', 'favors', 'the', 'meissner', 'phase', 'at', 'lowflux', 'and', 'a', 'phase', 'with', 'a', 'second', 'incommensuration', 'in', 'the', 'correlation', 'functions', 'for', 'intermediate', 'flux', 'leading', 'to', 'a', 'richer', 'phase', 'diagram', 'than', 'in', 'the', 'case', 'of', 'interleg', 'attraction', 'the', 'effect', 'of', 'the', 'temperature', 'on', 'the', 'chiral', 'current', 'is', 'also', 'discussed']] | [-0.20948907724126195, 0.24981368283231753, -0.08170634738244388, 0.0961876642213876, -0.02148303501715843, -0.12136879860063213, 0.09880577781693126, 0.36558355484837596, -0.19837680189482812, -0.21206678583347885, 0.028461011357768608, -0.30443048168544784, -0.16591945523056237, 0.08903167129623411, 0.09382975484923207, -0.05939896785429794, -0.056375756200375784, 0.0498498659580946, -0.14163369024648284, -0.14503625928709812, 0.3251112074910724, -0.03020556468557376, 0.28420391764464603, 0.08693711545970971, 0.06534278800925172, 0.016809935763097594, 0.09958047822566472, 0.025871866338471643, -0.12157485921982758, -0.022663431954196227, 0.1789499232689952, -0.07767664983080033, 0.2008339087376847, -0.3927636591404894, -0.21296226167303584, 0.09607024066299744, 0.17324080393670033, 0.15141288083587115, -0.0665804907886896, -0.3266571410268844, -0.0662705152801979, -0.184826510762082, -0.12317681257922311, -0.05323745330700474, 0.028636358906922822, 0.012069240054387573, -0.29573849168432753, 0.12648571610585005, 0.05574498074741042, 0.05145713487762387, -0.07218538855889091, -0.08266611943823578, -0.07370621557041568, 0.0646688856888073, 0.04192386981164425, 0.12201986505384863, 0.10164959451360424, -0.19965592446145566, -0.07752044659267676, 0.36256344779564514, -0.06785097505175423, -0.12710674983333714, 0.16123262430493632, -0.16876315893681829, -0.09227002866865291, 0.1966024235393988, 0.10639668145577294, 0.038679278234315585, -0.10211520073391551, 0.04562044186376538, 0.03534218182468219, 0.17036608380225596, -0.00935431376752192, 0.015011134649198638, 0.2745210640948184, 0.18920218691494942, 0.06727823189860821, 0.2451791948210584, -0.12941467578108184, -0.15321660670961668, -0.2914926484091221, -0.14663602243836996, -0.18917401103697118, 0.0018827571149322333, -0.09480328169571878, -0.22154426304827424, 0.43015615610630137, 0.15503099694487768, 0.22222907190257005, 0.007424923184286994, 0.24597499565812794, 0.1301818994633568, 0.051917165633372585, -0.004112372825765153, 0.2733752701897174, 0.1441135467013113, 0.14137512435592767, -0.2926275449990631, 0.012338311326465685, 0.10735840496545943] |
1,802.04998 | Interacting hadron resonance gas model in K-matrix formalism | An extension of Hadron Resonance Gas (HRG) model is constructed to include
interactions using relativistic virial expansion of partition function. The
non-interacting part of the expansion contains all the stable baryons and
mesons and the interacting part contains all the higher mass resonances which
decay into two stable hadrons. The virial coefficients are related to the phase
shifts which are calculated using K-matrix formalism in the present work. We
have calculated various thermodynamics quantities like pressure, energy
density, and entropy density of the system. A comparison of thermodynamic
quantities with non interacting HRG model, calculated using the same number of
hadrons, shows that the results of above formalism are larger. A good agreement
between equation of state calculated in K-matrix formalism and lattice QCD
simulations is observed. Specifically the lattice QCD calculated interaction
measure is well described in our formalism. We have also calculated second
order fluctuations and correlations of conserved charges in K-matrix formalism.
We observe a good agreement of second order fluctuations and baryon-strangeness
correlation with lattice data below the cross-over temperature.
| nucl-th hep-ph | an extension of hadron resonance gas hrg model is constructed to include interactions using relativistic virial expansion of partition function the noninteracting part of the expansion contains all the stable baryons and mesons and the interacting part contains all the higher mass resonances which decay into two stable hadrons the virial coefficients are related to the phase shifts which are calculated using kmatrix formalism in the present work we have calculated various thermodynamics quantities like pressure energy density and entropy density of the system a comparison of thermodynamic quantities with non interacting hrg model calculated using the same number of hadrons shows that the results of above formalism are larger a good agreement between equation of state calculated in kmatrix formalism and lattice qcd simulations is observed specifically the lattice qcd calculated interaction measure is well described in our formalism we have also calculated second order fluctuations and correlations of conserved charges in kmatrix formalism we observe a good agreement of second order fluctuations and baryonstrangeness correlation with lattice data below the crossover temperature | [['an', 'extension', 'of', 'hadron', 'resonance', 'gas', 'hrg', 'model', 'is', 'constructed', 'to', 'include', 'interactions', 'using', 'relativistic', 'virial', 'expansion', 'of', 'partition', 'function', 'the', 'noninteracting', 'part', 'of', 'the', 'expansion', 'contains', 'all', 'the', 'stable', 'baryons', 'and', 'mesons', 'and', 'the', 'interacting', 'part', 'contains', 'all', 'the', 'higher', 'mass', 'resonances', 'which', 'decay', 'into', 'two', 'stable', 'hadrons', 'the', 'virial', 'coefficients', 'are', 'related', 'to', 'the', 'phase', 'shifts', 'which', 'are', 'calculated', 'using', 'kmatrix', 'formalism', 'in', 'the', 'present', 'work', 'we', 'have', 'calculated', 'various', 'thermodynamics', 'quantities', 'like', 'pressure', 'energy', 'density', 'and', 'entropy', 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1,802.04999 | The syntomic realization of the elliptic polylogarithm via the
Poincar\'e bundle | We give an explicit description of the syntomic elliptic polylogarithm on the
universal elliptic curve over the ordinary locus of the modular curve in terms
of certain $p$-adic analytic moment functions associated to Katz' two-variable
$p$-adic Eisenstein measure. The present work generalizes previous results of
Bannai-Kobayashi-Tsuji and Bannai-Kings on the syntomic Eisenstein classes.
| math.NT math.AG | we give an explicit description of the syntomic elliptic polylogarithm on the universal elliptic curve over the ordinary locus of the modular curve in terms of certain padic analytic moment functions associated to katz twovariable padic eisenstein measure the present work generalizes previous results of bannaikobayashitsuji and bannaikings on the syntomic eisenstein classes | [['we', 'give', 'an', 'explicit', 'description', 'of', 'the', 'syntomic', 'elliptic', 'polylogarithm', 'on', 'the', 'universal', 'elliptic', 'curve', 'over', 'the', 'ordinary', 'locus', 'of', 'the', 'modular', 'curve', 'in', 'terms', 'of', 'certain', 'padic', 'analytic', 'moment', 'functions', 'associated', 'to', 'katz', 'twovariable', 'padic', 'eisenstein', 'measure', 'the', 'present', 'work', 'generalizes', 'previous', 'results', 'of', 'bannaikobayashitsuji', 'and', 'bannaikings', 'on', 'the', 'syntomic', 'eisenstein', 'classes']] | [-0.2600755751242532, -0.056802879788116184, -0.22741712854408166, 0.09926974952367007, -0.14350948782235967, -0.06351760508236932, -0.022420952077178907, 0.2370802287523653, -0.30430850783801255, -0.20664816594445237, -0.0016720616098895085, -0.2475631499169942, -0.1592237852586835, 0.3547052751094395, -0.1821766164445994, 0.09068359658304675, -0.0026510088503652928, 0.12775857288244308, -0.11232018573940092, -0.36684201387505905, 0.4699701564569099, -0.032087285856844165, 0.20399082169009775, 0.04127791385148086, 0.0834274941361418, 0.06347601637974673, -0.05639709306734742, -0.19365189366919153, -0.20606758270193548, 0.24073641378359467, 0.35843261181577746, -0.024555899184562413, 0.12951976871665785, -0.3653623061437233, -0.11853800092221183, 0.21316116536949195, 0.11294213162881195, -0.042245039661579276, 0.06289968967857752, -0.2087228178484913, 0.01707589209956281, -0.19610916226006606, -0.22905969393311762, -0.14443704638374494, 0.03519304310355116, 0.12593097100947417, -0.21407874572255156, 0.055021840896384386, 0.10233759204400521, 0.24998725382793768, -0.11359623841503087, -0.1640369754978547, 0.014340638776547183, -0.017019126783399022, 0.0260458598278609, 0.09623292000854716, 0.0741340987037356, -0.11946636215582782, -0.12014873724832546, 0.28147288439247536, -0.10236336929979277, -0.15805774193037958, 0.06527516939768604, -0.161164566144055, -0.1834978062988204, 0.12473733934993837, 0.11482370589567605, 0.1953781107623203, 0.010881394640926053, 0.1774379260297043, -0.16687398422144206, 0.06250697937702723, 0.14934549736333827, -0.07487462566909837, 0.10737253539264202, -0.041008457249286125, 0.0038271109737894114, 0.17941212870052778, 0.05457096244550913, -0.11857228108919134, -0.41539473283816786, -0.19591918888994875, -0.08014577999711037, 0.1168781299984046, -0.14528972697507034, -0.2297302380058111, 0.48804827914664556, 0.03778259244327452, 0.23054123311942698, 0.2175771986116089, 0.2177303312894176, 0.17817901790726418, 0.024580603960773672, -0.03415678367566537, 0.0654680082282307, 0.1989590173915905, -0.015445968458045493, -0.17403005235189317, -0.002707164268940687, 0.2994300228014004] |
1,802.05 | High magnetocaloric efficiency of a NiFe/NiCu/CoFe/MnIr multilayer in a
small magnetic field | The isothermal magnetic entropy changes are studied in
Ni80Fe20/Ni67Cu33/Co90Cu10/Mn80Ir20 stacks at temperatures near the Curie point
of the Ni67Cu33 spacer by applying magnetic fields in a few tens of Oersted.
Such low fields were sufficient for toggling magnetic moments in the soft
ferromagnetic (FM) layer (Ni80Fe20). It is found out that this switching
provides the magnetic entropy change, which is up to 20 times larger than that
achievable in a single Ni67Cu33 film subjected to such low fields. Our finding
holds promise to be utilized in the magnetocaloric devices that would be based
on FM/PM/FM heterostructures and would operate with moderate magnetic fields.
| cond-mat.mes-hall | the isothermal magnetic entropy changes are studied in ni80fe20ni67cu33co90cu10mn80ir20 stacks at temperatures near the curie point of the ni67cu33 spacer by applying magnetic fields in a few tens of oersted such low fields were sufficient for toggling magnetic moments in the soft ferromagnetic fm layer ni80fe20 it is found out that this switching provides the magnetic entropy change which is up to 20 times larger than that achievable in a single ni67cu33 film subjected to such low fields our finding holds promise to be utilized in the magnetocaloric devices that would be based on fmpmfm heterostructures and would operate with moderate magnetic fields | [['the', 'isothermal', 'magnetic', 'entropy', 'changes', 'are', 'studied', 'in', 'ni80fe20ni67cu33co90cu10mn80ir20', 'stacks', 'at', 'temperatures', 'near', 'the', 'curie', 'point', 'of', 'the', 'ni67cu33', 'spacer', 'by', 'applying', 'magnetic', 'fields', 'in', 'a', 'few', 'tens', 'of', 'oersted', 'such', 'low', 'fields', 'were', 'sufficient', 'for', 'toggling', 'magnetic', 'moments', 'in', 'the', 'soft', 'ferromagnetic', 'fm', 'layer', 'ni80fe20', 'it', 'is', 'found', 'out', 'that', 'this', 'switching', 'provides', 'the', 'magnetic', 'entropy', 'change', 'which', 'is', 'up', 'to', '20', 'times', 'larger', 'than', 'that', 'achievable', 'in', 'a', 'single', 'ni67cu33', 'film', 'subjected', 'to', 'such', 'low', 'fields', 'our', 'finding', 'holds', 'promise', 'to', 'be', 'utilized', 'in', 'the', 'magnetocaloric', 'devices', 'that', 'would', 'be', 'based', 'on', 'fmpmfm', 'heterostructures', 'and', 'would', 'operate', 'with', 'moderate', 'magnetic', 'fields']] | [-0.17970975876945738, 0.22137982426493458, -0.006095269868959381, 0.02210636740442215, -0.043708471510785094, -0.129398693048367, 0.048887395645689335, 0.4251805531481902, -0.25329414423969054, -0.3550741733592756, 0.06354017368390817, -0.25567280252774555, -0.050978474826975304, 0.2688482471111447, 0.011762342425157326, -0.004906566540776479, -0.0446417655588852, 0.01764964665029894, -0.08685003412943898, -0.2460183867187512, 0.2413501213257662, 0.021722265820235315, 0.31600118037125074, 0.08228228758606645, 0.04863728031120969, -0.04354329295650435, 0.15810351464379993, 0.07778022031539655, -0.09639488388141888, 0.029627846890306123, 0.24243882508957854, -0.07770759096331518, 0.21376743041580976, -0.47523892159112774, -0.20198520127392253, 0.04434239409976837, 0.10461524992503902, 0.1057978604456899, -0.07719782082895475, -0.22030705319849228, 0.1605039893442558, -0.10937543766516628, -0.0970704028160356, -0.1204530703035569, -0.012243906195943404, 0.030028115866254226, -0.310519261737213, 0.07731115963836813, 0.08771754647934377, 0.14665501470668146, -0.07193676230919223, -0.11600590515129193, -0.040039628219668465, 0.07463967259691069, 0.07029210241756054, 0.10832130156382165, 0.23786910353322524, -0.10546740417361655, -0.08566252450162376, 0.31654123896074415, -0.06453045407581176, -0.09669021733406216, 0.17912437252916696, -0.19915581559950504, -0.08058160492642359, 0.1950828828519643, 0.1402655210336576, 0.131323151393897, -0.15772432695622696, 0.05155947862188285, 0.04032625061826724, 0.1759554070501113, 0.09525954554497142, 0.0261779548426869, 0.27569502890298164, 0.1754350917086927, 0.06446063637996864, 0.18481873237113985, -0.13611484797567958, -0.029401960566338866, -0.20483990610022135, -0.15960877495253403, -0.19782529253691358, 0.11643975429372706, -0.10083048912973468, -0.16285259140222663, 0.3300469165310414, 0.21575068355998908, 0.15315258850324712, -0.053624929971945935, 0.2692793130996929, 0.11222618154421768, 0.16993341891264374, 0.07816814738702067, 0.29536527882546487, 0.1996383532514852, 0.16847392583425824, -0.1781813916820807, 0.07297446746190991, -0.04640871765694082] |
1,802.05001 | Angular clustering of point sources at 150 MHz in the TGSS survey | We study the angular clustering of point sources in The GMRT (Giant Meter
Wave Telescope) Sky Survey (TGSS). The survey at 150 MHz with delta > -53.5
degrees has a sky coverage of 3.6 pi steradians, i.e., 90% of the whole sky. We
created subsamples by applying different total flux thresholds limit (S >> 5
sigma) for good completeness and measured the angular correlation function
omega(theta) of point sources at large scales ( >= 1 degree). We find that the
amplitude of angular clustering is higher for brighter subsamples, this
indicates that higher threshold flux samples are hosted by massive halos and
cluster strongly: this conclusions is based on the assumption that the redshift
distribution of sources does not change with flux and this is supported by
models of radio sources. We compare our results with other low-frequency
studies of clustering of point sources and verify that the amplitude of
clustering varies with the flux limit. We quantify this variation as a power
law dependence of the amplitude of correlation function with the flux limit.
This dependence can be used to estimate foreground contamination due to
clustering of point sources for low frequency HI intensity mapping surveys for
studying the epoch of reionisation.
| astro-ph.GA astro-ph.CO | we study the angular clustering of point sources in the gmrt giant meter wave telescope sky survey tgss the survey at 150 mhz with delta 535 degrees has a sky coverage of 36 pi steradians ie 90 of the whole sky we created subsamples by applying different total flux thresholds limit s 5 sigma for good completeness and measured the angular correlation function omegatheta of point sources at large scales 1 degree we find that the amplitude of angular clustering is higher for brighter subsamples this indicates that higher threshold flux samples are hosted by massive halos and cluster strongly this conclusions is based on the assumption that the redshift distribution of sources does not change with flux and this is supported by models of radio sources we compare our results with other lowfrequency studies of clustering of point sources and verify that the amplitude of clustering varies with the flux limit we quantify this variation as a power law dependence of the amplitude of correlation function with the flux limit this dependence can be used to estimate foreground contamination due to clustering of point sources for low frequency hi intensity mapping surveys for studying the epoch of reionisation | [['we', 'study', 'the', 'angular', 'clustering', 'of', 'point', 'sources', 'in', 'the', 'gmrt', 'giant', 'meter', 'wave', 'telescope', 'sky', 'survey', 'tgss', 'the', 'survey', 'at', '150', 'mhz', 'with', 'delta', '535', 'degrees', 'has', 'a', 'sky', 'coverage', 'of', '36', 'pi', 'steradians', 'ie', '90', 'of', 'the', 'whole', 'sky', 'we', 'created', 'subsamples', 'by', 'applying', 'different', 'total', 'flux', 'thresholds', 'limit', 's', '5', 'sigma', 'for', 'good', 'completeness', 'and', 'measured', 'the', 'angular', 'correlation', 'function', 'omegatheta', 'of', 'point', 'sources', 'at', 'large', 'scales', '1', 'degree', 'we', 'find', 'that', 'the', 'amplitude', 'of', 'angular', 'clustering', 'is', 'higher', 'for', 'brighter', 'subsamples', 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1,802.05002 | Algebraic torus actions on contact manifolds | We prove the LeBrun-Salamon Conjecture in low dimensions. More precisely, we
show that a contact Fano manifold X of dimension 2n+1 that has reductive
automorphism group of rank at least n-2 is necessarily homogeneous. This
implies that any positive quaternion-Kahler manifold of real dimension at most
16 is necessarily a symmetric space, one of the Wolf spaces. A similar result
about contact Fano manifolds of dimension at most 9 with reductive automorphism
group also holds. The main difficulty in approaching the conjecture is how to
recognize a homogeneous space in an abstract variety. We contribute to such
problem in general, by studying the action of algebraic torus on varieties and
exploiting Bialynicki-Birula decomposition and equivariant Riemann-Roch
theorems. From the point of view of T-varieties (that is, varieties with a
torus action), our result is about high complexity T-manifolds. The complexity
here is at most 1/2(dim X+5) with dim X arbitrarily high, but we require this
special (contact) structure of X. Previous methods for studying T-varieties in
general usually only apply for complexity at most 2 or 3.
| math.AG math.DG | we prove the lebrunsalamon conjecture in low dimensions more precisely we show that a contact fano manifold x of dimension 2n1 that has reductive automorphism group of rank at least n2 is necessarily homogeneous this implies that any positive quaternionkahler manifold of real dimension at most 16 is necessarily a symmetric space one of the wolf spaces a similar result about contact fano manifolds of dimension at most 9 with reductive automorphism group also holds the main difficulty in approaching the conjecture is how to recognize a homogeneous space in an abstract variety we contribute to such problem in general by studying the action of algebraic torus on varieties and exploiting bialynickibirula decomposition and equivariant riemannroch theorems from the point of view of tvarieties that is varieties with a torus action our result is about high complexity tmanifolds the complexity here is at most 12dim x5 with dim x arbitrarily high but we require this special contact structure of x previous methods for studying tvarieties in general usually only apply for complexity at most 2 or 3 | [['we', 'prove', 'the', 'lebrunsalamon', 'conjecture', 'in', 'low', 'dimensions', 'more', 'precisely', 'we', 'show', 'that', 'a', 'contact', 'fano', 'manifold', 'x', 'of', 'dimension', '2n1', 'that', 'has', 'reductive', 'automorphism', 'group', 'of', 'rank', 'at', 'least', 'n2', 'is', 'necessarily', 'homogeneous', 'this', 'implies', 'that', 'any', 'positive', 'quaternionkahler', 'manifold', 'of', 'real', 'dimension', 'at', 'most', '16', 'is', 'necessarily', 'a', 'symmetric', 'space', 'one', 'of', 'the', 'wolf', 'spaces', 'a', 'similar', 'result', 'about', 'contact', 'fano', 'manifolds', 'of', 'dimension', 'at', 'most', '9', 'with', 'reductive', 'automorphism', 'group', 'also', 'holds', 'the', 'main', 'difficulty', 'in', 'approaching', 'the', 'conjecture', 'is', 'how', 'to', 'recognize', 'a', 'homogeneous', 'space', 'in', 'an', 'abstract', 'variety', 'we', 'contribute', 'to', 'such', 'problem', 'in', 'general', 'by', 'studying', 'the', 'action', 'of', 'algebraic', 'torus', 'on', 'varieties', 'and', 'exploiting', 'bialynickibirula', 'decomposition', 'and', 'equivariant', 'riemannroch', 'theorems', 'from', 'the', 'point', 'of', 'view', 'of', 'tvarieties', 'that', 'is', 'varieties', 'with', 'a', 'torus', 'action', 'our', 'result', 'is', 'about', 'high', 'complexity', 'tmanifolds', 'the', 'complexity', 'here', 'is', 'at', 'most', '12dim', 'x5', 'with', 'dim', 'x', 'arbitrarily', 'high', 'but', 'we', 'require', 'this', 'special', 'contact', 'structure', 'of', 'x', 'previous', 'methods', 'for', 'studying', 'tvarieties', 'in', 'general', 'usually', 'only', 'apply', 'for', 'complexity', 'at', 'most', '2', 'or', '3']] | [-0.1646888660433303, 0.06826400500664022, -0.09135781155366983, 0.06425877437261598, -0.08711928745665189, -0.17933518507384827, -0.00554946490164314, 0.3518364050984383, -0.24838701959965484, -0.2472247338321592, 0.11900289362496032, -0.25429771378503313, -0.17626082809641958, 0.20794275365104634, -0.15498603506579198, -0.04722257105633616, 0.024411475708309028, 0.0993549098420356, -0.10515876527343478, -0.3264340481113842, 0.4532297342164176, -0.030588117244520357, 0.22020457769877144, 0.05694269554652107, 0.11272064997947642, 0.018969584058171937, 0.02625322513548391, 0.015469517587750618, -0.09049928859624612, 0.13835529256977938, 0.3229474611367498, 0.08321396553888917, 0.20846433407627046, -0.3478063089932714, -0.1959882547360446, 0.16652943281989013, 0.12773715248065334, 0.0685199012780296, 0.0059130361173135625, -0.22410443893500737, 0.1443796022555658, -0.11271910504038844, -0.21534807634406855, -0.05849267153401992, 0.06430035647071365, -0.060649549649762255, -0.20541514568729327, -0.002048418842688469, 0.11220771315906729, 0.13282864224697863, -0.038838252015411856, -0.10204754843842238, -0.0407007984005447, 0.08743735810409167, -0.003050257425223078, 0.0906329420188974, 0.0791279378174139, -0.0957481215365364, -0.10946524929787431, 0.3666573987821383, -0.048270075265983384, -0.21973550462829214, 0.20123624170664697, -0.21118854414139476, -0.21602843079449874, 0.18027352828332888, 0.12261218059674969, 0.1708451213290183, -0.0012455050996504724, 0.1610123210727969, -0.1030900708027184, 0.13669311243791266, 0.107807008618755, -0.007864253533604953, 0.09507597919553518, 0.14292219094599465, 0.12487135865725577, 0.08709511997710381, -0.0007722481805831194, -0.016656091344609325, -0.3131655341599669, -0.18250478493947803, -0.15188621952863676, 0.19243805025837252, -0.15412175431032665, -0.11686002687151943, 0.3347182045770543, 0.06010710594377348, 0.19981343428205167, 0.10173155287779602, 0.23838092987026488, 0.047554895891807974, 0.019751191021683292, 0.1139140140105571, 0.15393333387162003, 0.17852938971482218, -0.023724449374713005, -0.12810181443845586, 3.286779991218022e-05, 0.14858943973335303] |
1,802.05003 | Evidence of Intermediate-Scale Energy Spectrum Anisotropy of Cosmic Rays
E$\geq$10$^{19.2}$ eV with the Telescope Array Surface Detector | An intermediate-scale energy spectrum anisotropy has been found in the
arrival directions of ultra-high energy cosmic rays of energies above
$10^{19.2}$ eV in the northern hemisphere, using 7 years of data from the
Telescope Array surface detector. A relative energy distribution test is done
comparing events inside oversampled spherical caps of equal exposure, to those
outside, using the Poisson likelihood ratio. The center of maximum significance
is at $9^h$$16^m$, $45^{\circ}$. and has a deficit of events with energies
$10^{19.2}$$\leq$$E$$<$$10^{19.75}$ eV and an excess for $E$$\geq$$10^{19.75}$
eV. The post-trial probability of this energy anisotropy, appearing by chance
anywhere on an isotropic sky, is found by Monte Carlo simulation to be
$9$$\times$$10^{-5}$ ($3.74$$\sigma_{global}$).
| astro-ph.HE | an intermediatescale energy spectrum anisotropy has been found in the arrival directions of ultrahigh energy cosmic rays of energies above 10192 ev in the northern hemisphere using 7 years of data from the telescope array surface detector a relative energy distribution test is done comparing events inside oversampled spherical caps of equal exposure to those outside using the poisson likelihood ratio the center of maximum significance is at 9h16m 45circ and has a deficit of events with energies 10192leqe101975 ev and an excess for egeq101975 ev the posttrial probability of this energy anisotropy appearing by chance anywhere on an isotropic sky is found by monte carlo simulation to be 9times105 374sigma_global | [['an', 'intermediatescale', 'energy', 'spectrum', 'anisotropy', 'has', 'been', 'found', 'in', 'the', 'arrival', 'directions', 'of', 'ultrahigh', 'energy', 'cosmic', 'rays', 'of', 'energies', 'above', '10192', 'ev', 'in', 'the', 'northern', 'hemisphere', 'using', '7', 'years', 'of', 'data', 'from', 'the', 'telescope', 'array', 'surface', 'detector', 'a', 'relative', 'energy', 'distribution', 'test', 'is', 'done', 'comparing', 'events', 'inside', 'oversampled', 'spherical', 'caps', 'of', 'equal', 'exposure', 'to', 'those', 'outside', 'using', 'the', 'poisson', 'likelihood', 'ratio', 'the', 'center', 'of', 'maximum', 'significance', 'is', 'at', '9h16m', '45circ', 'and', 'has', 'a', 'deficit', 'of', 'events', 'with', 'energies', '10192leqe101975', 'ev', 'and', 'an', 'excess', 'for', 'egeq101975', 'ev', 'the', 'posttrial', 'probability', 'of', 'this', 'energy', 'anisotropy', 'appearing', 'by', 'chance', 'anywhere', 'on', 'an', 'isotropic', 'sky', 'is', 'found', 'by', 'monte', 'carlo', 'simulation', 'to', 'be', '9times105', '374sigma_global']] | [-0.09251186493586502, 0.1556439779885278, -0.04835907153275637, 0.10594704622657583, -0.004627486350418965, -0.026080204885593563, 0.030917289739316504, 0.4095173067817429, -0.20771625525546525, -0.4150584857330991, 0.043412578913804914, -0.3641903156871503, 0.03312032214664626, 0.1990035354831906, 0.007171330230534604, -0.01246777243631066, 0.07654585816704158, 0.011532348692680727, -0.06841095022084016, -0.18401153552135066, 0.22026801736638793, 0.26860488946813177, 0.2983132869242427, 0.03620768457932292, 0.09856198321839021, -0.014820752342512726, 0.008888108515233363, -0.001447387162666276, -0.12260337985331579, 0.06594673644988534, 0.24567280702275346, 0.06312937261141345, 0.18094471117310262, -0.36624000034347737, -0.19613686112581558, 0.16281878931957455, 0.11084168718332636, 0.007187161348619551, -0.054045793113852235, -0.28759639302514634, 0.06615794942942711, -0.15342203100686366, -0.18498011283963076, 0.10757148074192645, 0.0006155188169049205, 0.02085153483522107, -0.21953489953423586, 0.1501324387126655, -0.05522917309644981, 0.08501892165667466, -0.06848796713550329, -0.17447004705351196, -0.04469242797536283, 0.029378413152441663, 0.08938317046223981, 0.06357348009170789, 0.1424600702341435, -0.07392727659865862, -0.11552500514366296, 0.35160748513837187, -0.02553314939668437, -0.1009756009460137, 0.10675648111687482, -0.18877525648699617, -0.0924889559523677, 0.27408807793245565, 0.173400495587936, 0.06666139744327597, -0.1836623535491526, 0.11696494084822436, 0.022259969527850736, 0.17001971533524207, 0.11815850439323287, -0.05330107526915183, 0.286052318289876, 0.15732791514206185, 0.12304102639087809, 0.09595333680154686, -0.2686070419303229, -0.025750207416010352, -0.26598004843899103, -0.11643886577144687, -0.22009590605410026, 0.09691943678091157, -0.08915751926872202, -0.09462062336992086, 0.3708627869392622, 0.10035352251615445, 0.19324002720257444, 0.014221359641765649, 0.280600693076849, 0.09322658859913782, 0.03638731552955677, 0.07657097805431991, 0.3106162817138335, 0.09971897380716466, 0.09050886131348615, -0.1298879729957267, 0.038667430185256, -0.03998954527800516] |
1,802.05004 | Zero-Knowledge Password Policy Check from Lattices | Passwords are ubiquitous and most commonly used to authenticate users when
logging into online services. Using high entropy passwords is critical to
prevent unauthorized access and password policies emerged to enforce this
requirement on passwords. However, with current methods of password storage,
poor practices and server breaches have leaked many passwords to the public. To
protect one's sensitive information in case of such events, passwords should be
hidden from servers. Verifier-based password authenticated key exchange,
proposed by Bellovin and Merrit (IEEE S\&P, 1992), allows authenticated secure
channels to be established with a hash of a password (verifier). Unfortunately,
this restricts password policies as passwords cannot be checked from their
verifier. To address this issue, Kiefer and Manulis (ESORICS 2014) proposed
zero-knowledge password policy check (ZKPPC). A ZKPPC protocol allows users to
prove in zero knowledge that a hash of the user's password satisfies the
password policy required by the server. Unfortunately, their proposal is not
quantum resistant with the use of discrete logarithm-based cryptographic tools
and there are currently no other viable alternatives. In this work, we
construct the first post-quantum ZKPPC using lattice-based tools. To this end,
we introduce a new randomised password hashing scheme for ASCII-based passwords
and design an accompanying zero-knowledge protocol for policy compliance.
Interestingly, our proposal does not follow the framework established by Kiefer
and Manulis and offers an alternate construction without homomorphic
commitments. Although our protocol is not ready to be used in practice, we
think it is an important first step towards a quantum-resistant
privacy-preserving password-based authentication and key exchange system.
| cs.CR | passwords are ubiquitous and most commonly used to authenticate users when logging into online services using high entropy passwords is critical to prevent unauthorized access and password policies emerged to enforce this requirement on passwords however with current methods of password storage poor practices and server breaches have leaked many passwords to the public to protect ones sensitive information in case of such events passwords should be hidden from servers verifierbased password authenticated key exchange proposed by bellovin and merrit ieee sp 1992 allows authenticated secure channels to be established with a hash of a password verifier unfortunately this restricts password policies as passwords cannot be checked from their verifier to address this issue kiefer and manulis esorics 2014 proposed zeroknowledge password policy check zkppc a zkppc protocol allows users to prove in zero knowledge that a hash of the users password satisfies the password policy required by the server unfortunately their proposal is not quantum resistant with the use of discrete logarithmbased cryptographic tools and there are currently no other viable alternatives in this work we construct the first postquantum zkppc using latticebased tools to this end we introduce a new randomised password hashing scheme for asciibased passwords and design an accompanying zeroknowledge protocol for policy compliance interestingly our proposal does not follow the framework established by kiefer and manulis and offers an alternate construction without homomorphic commitments although our protocol is not ready to be used in practice we think it is an important first step towards a quantumresistant privacypreserving passwordbased authentication and key exchange system | [['passwords', 'are', 'ubiquitous', 'and', 'most', 'commonly', 'used', 'to', 'authenticate', 'users', 'when', 'logging', 'into', 'online', 'services', 'using', 'high', 'entropy', 'passwords', 'is', 'critical', 'to', 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1,802.05005 | Using Longitudinal Targeted Maximum Likelihood Estimation in Complex
Settings with Dynamic Interventions | Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely
been used to estimate dynamic treatment effects in the context of
time-dependent confounding affected by prior treatment when faced with long
follow-up times, multiple time-varying confounders, and complex associational
relationships simultaneously. Reasons for this include the potential
computational burden, technical challenges, restricted modeling options for
long follow-up times, and limited practical guidance in the literature.
However, LTMLE has desirable asymptotic properties, i.e. it is doubly robust,
and can yield valid inference when used in conjunction with machine learning.
We use a topical and sophisticated question from HIV treatment research to show
that LTMLE can be used successfully in complex realistic settings and compare
results to competing estimators. Our example illustrates the following
practical challenges common to many epidemiological studies 1) long follow-up
time (30 months), 2) gradually declining sample size 3) limited support for
some intervention rules of interest 4) a high-dimensional set of potential
adjustment variables, increasing both the need and the challenge of integrating
appropriate machine learning methods 5) consideration of collider bias. Our
analyses, as well as simulations, shed new light on the application of LTMLE in
complex and realistic settings: we show that (i) LTMLE can yield stable and
good estimates, even when confronted with small samples and limited modeling
options; (ii) machine learning utilized with a small set of simple learners (if
more complex ones can't be fitted) can outperform a single, complex model,
which is tailored to incorporate prior clinical knowledge; (iii) performance
can vary considerably depending on interventions and their support in the data,
and therefore critical quality checks should accompany every LTMLE analysis.
| stat.ME | longitudinal targeted maximum likelihood estimation ltmle has very rarely been used to estimate dynamic treatment effects in the context of timedependent confounding affected by prior treatment when faced with long followup times multiple timevarying confounders and complex associational relationships simultaneously reasons for this include the potential computational burden technical challenges restricted modeling options for long followup times and limited practical guidance in the literature however ltmle has desirable asymptotic properties ie it is doubly robust and can yield valid inference when used in conjunction with machine learning we use a topical and sophisticated question from hiv treatment research to show that ltmle can be used successfully in complex realistic settings and compare results to competing estimators our example illustrates the following practical challenges common to many epidemiological studies 1 long followup time 30 months 2 gradually declining sample size 3 limited support for some intervention rules of interest 4 a highdimensional set of potential adjustment variables increasing both the need and the challenge of integrating appropriate machine learning methods 5 consideration of collider bias our analyses as well as simulations shed new light on the application of ltmle in complex and realistic settings we show that i ltmle can yield stable and good estimates even when confronted with small samples and limited modeling options ii machine learning utilized with a small set of simple learners if more complex ones cant be fitted can outperform a single complex model which is tailored to incorporate prior clinical knowledge iii performance can vary considerably depending on interventions and their support in the data and therefore critical quality checks should accompany every ltmle analysis | [['longitudinal', 'targeted', 'maximum', 'likelihood', 'estimation', 'ltmle', 'has', 'very', 'rarely', 'been', 'used', 'to', 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1,802.05006 | Longitudinal phase space reconstruction simulation studies using a novel
X-band transverse deflecting structure at the SINBAD facility at DESY | A transverse deflecting structure (TDS) is a well-known device for
characterizing the longitudinal properties of an electron bunch in a linear
accelerator. The standard use of such a cavity involves streaking the bunch
along a transverse axis and analysing the image on a screen downstream to find
the bunch length and slice properties along the other transverse axis. A novel
X-band deflecting structure, which will allow the polarization of the
deflecting field to be adjusted, is currently being designed as part of a
collaboration between CERN, DESY and PSI. This new design will allow bunches to
be streaked at any transverse angle within the cavity, which will open up the
possibility of new measurement techniques, which could be combined to
characterize the 6D phase space distribution of bunches. In this paper, a
method is presented for reconstructing the longitudinal phase space
distribution of bunches by using the TDS in combination with a dipole.
Simulations of this technique for the SINBAD-ARES beamline are presented and
the key limitations related to temporal resolution and induced energy spread
are discussed.
| physics.acc-ph | a transverse deflecting structure tds is a wellknown device for characterizing the longitudinal properties of an electron bunch in a linear accelerator the standard use of such a cavity involves streaking the bunch along a transverse axis and analysing the image on a screen downstream to find the bunch length and slice properties along the other transverse axis a novel xband deflecting structure which will allow the polarization of the deflecting field to be adjusted is currently being designed as part of a collaboration between cern desy and psi this new design will allow bunches to be streaked at any transverse angle within the cavity which will open up the possibility of new measurement techniques which could be combined to characterize the 6d phase space distribution of bunches in this paper a method is presented for reconstructing the longitudinal phase space distribution of bunches by using the tds in combination with a dipole simulations of this technique for the sinbadares beamline are presented and the key limitations related to temporal resolution and induced energy spread are discussed | [['a', 'transverse', 'deflecting', 'structure', 'tds', 'is', 'a', 'wellknown', 'device', 'for', 'characterizing', 'the', 'longitudinal', 'properties', 'of', 'an', 'electron', 'bunch', 'in', 'a', 'linear', 'accelerator', 'the', 'standard', 'use', 'of', 'such', 'a', 'cavity', 'involves', 'streaking', 'the', 'bunch', 'along', 'a', 'transverse', 'axis', 'and', 'analysing', 'the', 'image', 'on', 'a', 'screen', 'downstream', 'to', 'find', 'the', 'bunch', 'length', 'and', 'slice', 'properties', 'along', 'the', 'other', 'transverse', 'axis', 'a', 'novel', 'xband', 'deflecting', 'structure', 'which', 'will', 'allow', 'the', 'polarization', 'of', 'the', 'deflecting', 'field', 'to', 'be', 'adjusted', 'is', 'currently', 'being', 'designed', 'as', 'part', 'of', 'a', 'collaboration', 'between', 'cern', 'desy', 'and', 'psi', 'this', 'new', 'design', 'will', 'allow', 'bunches', 'to', 'be', 'streaked', 'at', 'any', 'transverse', 'angle', 'within', 'the', 'cavity', 'which', 'will', 'open', 'up', 'the', 'possibility', 'of', 'new', 'measurement', 'techniques', 'which', 'could', 'be', 'combined', 'to', 'characterize', 'the', '6d', 'phase', 'space', 'distribution', 'of', 'bunches', 'in', 'this', 'paper', 'a', 'method', 'is', 'presented', 'for', 'reconstructing', 'the', 'longitudinal', 'phase', 'space', 'distribution', 'of', 'bunches', 'by', 'using', 'the', 'tds', 'in', 'combination', 'with', 'a', 'dipole', 'simulations', 'of', 'this', 'technique', 'for', 'the', 'sinbadares', 'beamline', 'are', 'presented', 'and', 'the', 'key', 'limitations', 'related', 'to', 'temporal', 'resolution', 'and', 'induced', 'energy', 'spread', 'are', 'discussed']] | [-0.12027192766022794, 0.18095411330969827, -0.10664366582535546, 0.039277694308442405, -0.06481746890560978, -0.10979089958709665, -0.03361480496625353, 0.42157346926714206, -0.2661667175938915, -0.29188730200456287, 0.0665498763218321, -0.2376763014895418, -0.02629360027441924, 0.24431358006867496, -0.011709458653719841, 0.06861473473889584, 0.059060663838780864, -0.012538690942826426, -0.07164048162733459, -0.1325355257930906, 0.2995132015361874, 0.12519316396157426, 0.29440260824842635, 0.055135286010971125, 0.13501662388179367, 0.05136684518947732, -0.007078467236252353, 0.016800229410860498, -0.09567349333453669, 0.10589694539720024, 0.21518559963310094, 0.08327265255105555, 0.23902339207151355, -0.38735816395968536, -0.18185715567828578, 0.03703336680403233, 0.1586030708541247, 0.11667632867267291, -0.07780774046643107, -0.2723926516905935, 0.0717443714833776, -0.14728612822099504, -0.180668858935612, -0.02978332513223656, -0.020072877578389704, 0.05554751118391075, -0.26763839368901576, 0.007408692910261875, 0.013222260024948891, 0.04862903199814768, -0.0037674076659393245, -0.06698874088893221, 0.01056445642131042, 0.0879358455428949, 0.03211725859992756, 0.1198230286933143, 0.15272308273349403, -0.09334165044922636, -0.11559478246966716, 0.35120520735455846, -0.02227013983528278, -0.1820130346644543, 0.12182749487593272, -0.1970502610651734, -0.059096741631616496, 0.15674370873140023, 0.2134855917273936, 0.07743009266877462, -0.16046346328551986, 0.03318171758854243, 0.017579171621367674, 0.18767320695968176, 0.11113356649663976, 0.03656069256910335, 0.24389248722317544, 0.1803963404540396, 0.05078176152660903, 0.15025020972527933, -0.1746287921811348, -0.010794768493559042, -0.3288066937920204, -0.16647680889582261, -0.1481397076716927, 0.011020612667462874, -0.018962801888764345, -0.13165645832354625, 0.468116172330073, 0.11894565554369117, 0.19085325005421924, -0.034366580276003915, 0.34161994872953405, 0.06634450552998962, 0.1127271824503127, 0.03629540590405999, 0.24138420499366475, 0.1350700317859512, 0.13314763286457906, -0.2244604821263982, 0.011528601563027636, 0.016318798579794184] |
1,802.05007 | The step Sidorenko property and non-norming edge-transitive graphs | Sidorenko's Conjecture asserts that every bipartite graph H has the Sidorenko
property, i.e., a quasirandom graph minimizes the density of H among all graphs
with the same edge density. We study a stronger property, which requires that a
quasirandom multipartite graph minimizes the density of H among all graphs with
the same edge densities between its parts; this property is called the step
Sidorenko property. We show that many bipartite graphs fail to have the step
Sidorenko property and use our results to show the existence of a bipartite
edge-transitive graph that is not weakly norming; this answers a question of
Hatami [Israel J. Math. 175 (2010), 125-150].
| math.CO | sidorenkos conjecture asserts that every bipartite graph h has the sidorenko property ie a quasirandom graph minimizes the density of h among all graphs with the same edge density we study a stronger property which requires that a quasirandom multipartite graph minimizes the density of h among all graphs with the same edge densities between its parts this property is called the step sidorenko property we show that many bipartite graphs fail to have the step sidorenko property and use our results to show the existence of a bipartite edgetransitive graph that is not weakly norming this answers a question of hatami israel j math 175 2010 125150 | [['sidorenkos', 'conjecture', 'asserts', 'that', 'every', 'bipartite', 'graph', 'h', 'has', 'the', 'sidorenko', 'property', 'ie', 'a', 'quasirandom', 'graph', 'minimizes', 'the', 'density', 'of', 'h', 'among', 'all', 'graphs', 'with', 'the', 'same', 'edge', 'density', 'we', 'study', 'a', 'stronger', 'property', 'which', 'requires', 'that', 'a', 'quasirandom', 'multipartite', 'graph', 'minimizes', 'the', 'density', 'of', 'h', 'among', 'all', 'graphs', 'with', 'the', 'same', 'edge', 'densities', 'between', 'its', 'parts', 'this', 'property', 'is', 'called', 'the', 'step', 'sidorenko', 'property', 'we', 'show', 'that', 'many', 'bipartite', 'graphs', 'fail', 'to', 'have', 'the', 'step', 'sidorenko', 'property', 'and', 'use', 'our', 'results', 'to', 'show', 'the', 'existence', 'of', 'a', 'bipartite', 'edgetransitive', 'graph', 'that', 'is', 'not', 'weakly', 'norming', 'this', 'answers', 'a', 'question', 'of', 'hatami', 'israel', 'j', 'math', '175', '2010', '125150']] | [-0.1541104537124435, 0.1287176478912847, -0.09673074123242663, 0.039982076846408074, -0.09138327418757533, -0.1296636381410752, 0.034640211909491986, 0.3937049696256441, -0.24945850547454837, -0.2958004712989485, 0.05490799368837745, -0.31532752411483134, -0.1692041465624546, 0.06869562441069219, -0.10008547006981205, 0.04833181631800943, 0.15010840964020677, 0.05950166164310994, 0.02891569056858619, -0.291326384393162, 0.2948683132245033, -0.03243194292385683, 0.25786546156531487, 0.14018726746413718, 0.052092255992142275, 0.07224531544381063, 0.010506051553723713, 0.08689722974129298, -0.18094454041851418, 0.08639782138386552, 0.2748049637992625, 0.16747940064373393, 0.3248327692142791, -0.3288924061955725, -0.17422127549502034, 0.23955973041571538, 0.023380419489479175, 0.057293983718544175, 0.00899341369060696, -0.24057690948420377, 0.1394171637953992, -0.10736365969016871, -0.10136212393451759, -0.008653967507631966, 0.10346254884023909, -0.026293092374948576, -0.2758897720120364, 0.026373656994783907, 0.19461555490960125, -0.0017696110600674594, 0.07224041235598701, -0.10915369503372521, -0.08478108951520105, 0.10478779821035762, -0.08580966103666772, 0.03740807620730872, 0.03231477608453672, -0.09363668673473445, -0.160201666054221, 0.3572379884965442, -0.03171343753907691, -0.1164836492303207, 0.15948839602599577, -0.1401425711983056, -0.2673723168393028, 0.07738024403806776, 0.04096604056690854, 0.11694950379724442, -0.09956704544257028, 0.15717560118355323, -0.19620064263883116, 0.12319983612677013, 0.1325764342694095, 0.038491326716245604, 0.07722876629688674, 0.054138683101714206, 0.187561694275549, 0.18231418625563728, 0.012505204416811466, -0.004773086363760133, -0.24896201017933586, -0.17303519552849508, -0.29047438304190076, 0.07656952449246159, -0.1436216384041742, -0.2266358702995435, 0.41894221757711086, 0.11655082583806857, 0.19483287017377465, 0.10210165988623716, 0.16222629834104468, 0.05101112633861636, 0.03417503624546549, 0.22914607175280927, 0.14965217714025467, 0.2216290883478467, -0.003632418552620543, -0.16073531552683562, 0.0810944042351804, 0.15995620583244427] |
1,802.05008 | TIFR Near Infrared Imaging Camera-II on the 3.6-m Devasthal Optical
Telescope | TIFR Near Infrared Imaging Camera-II is a closed-cycle Helium cryo-cooled
imaging camera equipped with a Raytheon 512 x 512 pixels InSb Aladdin III
Quadrant focal plane array having sensitivity to photons in the 1-5 microns
wavelength band. In this paper, we present the performance of the camera on the
newly installed 3.6-m Devasthal Optical Telescope (DOT) based on the
calibration observations carried out during 2017 May 11-14 and 2017 October
7-31. After the preliminary characterization, the camera has been released to
the Indian and Belgian astronomical community for science observations since
2017 May. The camera offers a field-of-view of ~86.5 arcsec x 86.5 arcsec on
the DOT with a pixel scale of 0.169 arcsec. The seeing at the telescope site in
the near-infrared bands is typically sub-arcsecond with the best seeing of
~0.45 arcsec realized in the near-infrared K-band on 2017 October 16. The
camera is found to be capable of deep observations in the J, H and K bands
comparable to other 4-m class telescopes available world-wide. Another
highlight of this camera is the observational capability for sources up to
Wide-field Infrared Survey Explorer (WISE) W1-band (3.4 microns) magnitudes of
9.2 in the narrow L-band (nbL; lambda_{cen} ~3.59 microns). Hence, the camera
could be a good complementary instrument to observe the bright nbL-band sources
that are saturated in the Spitzer-Infrared Array Camera ([3.6] <= 7.92 mag) and
the WISE W1-band ([3.4] <= 8.1 mag). Sources with strong polycyclic aromatic
hydrocarbon (PAH) emission at 3.3 microns are also detected. Details of the
observations and estimated parameters are presented in this paper.
| astro-ph.IM | tifr near infrared imaging cameraii is a closedcycle helium cryocooled imaging camera equipped with a raytheon 512 x 512 pixels insb aladdin iii quadrant focal plane array having sensitivity to photons in the 15 microns wavelength band in this paper we present the performance of the camera on the newly installed 36m devasthal optical telescope dot based on the calibration observations carried out during 2017 may 1114 and 2017 october 731 after the preliminary characterization the camera has been released to the indian and belgian astronomical community for science observations since 2017 may the camera offers a fieldofview of 865 arcsec x 865 arcsec on the dot with a pixel scale of 0169 arcsec the seeing at the telescope site in the nearinfrared bands is typically subarcsecond with the best seeing of 045 arcsec realized in the nearinfrared kband on 2017 october 16 the camera is found to be capable of deep observations in the j h and k bands comparable to other 4m class telescopes available worldwide another highlight of this camera is the observational capability for sources up to widefield infrared survey explorer wise w1band 34 microns magnitudes of 92 in the narrow lband nbl lambda_cen 359 microns hence the camera could be a good complementary instrument to observe the bright nblband sources that are saturated in the spitzerinfrared array camera 36 792 mag and the wise w1band 34 81 mag sources with strong polycyclic aromatic hydrocarbon pah emission at 33 microns are also detected details of the observations and estimated parameters are presented in this paper | [['tifr', 'near', 'infrared', 'imaging', 'cameraii', 'is', 'a', 'closedcycle', 'helium', 'cryocooled', 'imaging', 'camera', 'equipped', 'with', 'a', 'raytheon', '512', 'x', '512', 'pixels', 'insb', 'aladdin', 'iii', 'quadrant', 'focal', 'plane', 'array', 'having', 'sensitivity', 'to', 'photons', 'in', 'the', '15', 'microns', 'wavelength', 'band', 'in', 'this', 'paper', 'we', 'present', 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1,802.05009 | Three-body correlations in direct reactions: Example of $^{6}$Be
populated in $(p,n)$ reaction | The $^{6}$Be continuum states were populated in the charge-exchange reaction
$^1$H($^{6}$Li,$^{6}$Be)$n$ collecting very high statistics data ($\sim 5
\times 10^6$ events) on the three-body $\alpha$+$p$+$p$ correlations. The
$^{6}$Be excitation energy region below $\sim 3$ MeV is considered, where the
data are dominated by contributions from the $0^+$ and $2^+$ states. It is
demonstrated how the high-statistics few-body correlation data can be used to
extract detailed information on the reaction mechanism. Such a derivation is
based on the fact that highly spin-aligned states are typically populated in
the direct reactions.
| nucl-ex | the 6be continuum states were populated in the chargeexchange reaction 1h6li6ben collecting very high statistics data sim 5 times 106 events on the threebody alphapp correlations the 6be excitation energy region below sim 3 mev is considered where the data are dominated by contributions from the 0 and 2 states it is demonstrated how the highstatistics fewbody correlation data can be used to extract detailed information on the reaction mechanism such a derivation is based on the fact that highly spinaligned states are typically populated in the direct reactions | [['the', '6be', 'continuum', 'states', 'were', 'populated', 'in', 'the', 'chargeexchange', 'reaction', '1h6li6ben', 'collecting', 'very', 'high', 'statistics', 'data', 'sim', '5', 'times', '106', 'events', 'on', 'the', 'threebody', 'alphapp', 'correlations', 'the', '6be', 'excitation', 'energy', 'region', 'below', 'sim', '3', 'mev', 'is', 'considered', 'where', 'the', 'data', 'are', 'dominated', 'by', 'contributions', 'from', 'the', '0', 'and', '2', 'states', 'it', 'is', 'demonstrated', 'how', 'the', 'highstatistics', 'fewbody', 'correlation', 'data', 'can', 'be', 'used', 'to', 'extract', 'detailed', 'information', 'on', 'the', 'reaction', 'mechanism', 'such', 'a', 'derivation', 'is', 'based', 'on', 'the', 'fact', 'that', 'highly', 'spinaligned', 'states', 'are', 'typically', 'populated', 'in', 'the', 'direct', 'reactions']] | [-0.07695011465429244, 0.21936045654795386, -0.05102351621198151, 0.15774418111488392, 0.030145723976933037, -0.09638888989469376, 0.04687066605203489, 0.3146373978815973, -0.20811498006382448, -0.32337460187475453, 0.03931580957776697, -0.396097318248146, -0.012255235606889155, 0.18190533183091742, 0.0892128827369809, 0.01616761562499133, 0.10987603760969994, 0.014500765786082908, 0.008239504957931455, -0.13761101599613373, 0.3105513171864335, 0.07584653264546598, 0.24819843023909594, 0.11085738384016705, 0.030772837062779054, -0.020657475363061003, -0.00018830383619801566, -0.10632738248254596, -0.12037627895626263, 0.0563149260924547, 0.2895458948967809, 0.08941023479829627, 0.17090345661960205, -0.4287338835314255, -0.17029473394028505, 0.08021103007856502, 0.17124009999679402, 0.10978469631465321, -0.024800983216581782, -0.3228275312788107, 0.04457373823705976, -0.17165847689929334, -0.08182783058939756, -0.07424329085783525, 0.058942207595629785, -0.009932417210868814, -0.27887458916732366, 0.11756426976221106, -0.027235237304756247, 0.04078687540128489, -0.06590442443054846, -0.1644815506627889, -0.052332721253730015, 0.08447897534775124, -0.002636235881998966, 0.043559186792249835, 0.19203463537533852, -0.1022130500271239, -0.06476570533480051, 0.35885268285214394, -0.01892700149487196, -0.1478184959533709, 0.16728306357187897, -0.16993112899680538, -0.14298018586784814, 0.24252431678839706, 0.153232617451894, 0.13565339070423346, -0.17029023290061476, 0.044635551663470156, 0.023915109081744133, 0.2131455694960261, 0.04811589522498914, 0.02893198455620388, 0.14198135636185974, 0.18269024181857027, -0.03069717308972031, 0.040921101779200726, -0.1674582818972836, -0.11181107080880213, -0.2649911694091067, -0.03180588894544847, -0.21917375367113642, 0.10423571233298969, -0.013074295307722588, -0.04250574070663953, 0.3495821530126374, 0.06671916615133258, 0.2604989115180532, -0.03812989065508274, 0.2698277590415356, 0.11970345641020685, 0.07991764544170689, 0.07128757769400677, 0.3137767025354234, 0.14050634659890254, 0.07624695007160137, -0.18011871056065007, 0.06392878621541472, -0.05116295388010754] |
1,802.0501 | Cycles of Singularities appearing in the Resolution Problem in positive
Characteristic | We present a hypersurface singularity in positive characteristic which is
defined by a purely inseparable power series, and a sequence of point blowups
so that, after applying the blowups to the singularity, the same type of
singularity reappears after the last blowup, with just certain exponents of the
defining power series shifted upwards. The construction hence yields a cycle.
Iterating this cycle leads to an infinite increase of the residual order of the
defining power series. This disproves a theorem claimed by Moh about the
stability of the residual order under sequences of blowups. It is not a
counter-example to the resolution in positive characteristic since larger
centers are also permissible and prevent the phenomenon from happening.
| math.AG | we present a hypersurface singularity in positive characteristic which is defined by a purely inseparable power series and a sequence of point blowups so that after applying the blowups to the singularity the same type of singularity reappears after the last blowup with just certain exponents of the defining power series shifted upwards the construction hence yields a cycle iterating this cycle leads to an infinite increase of the residual order of the defining power series this disproves a theorem claimed by moh about the stability of the residual order under sequences of blowups it is not a counterexample to the resolution in positive characteristic since larger centers are also permissible and prevent the phenomenon from happening | [['we', 'present', 'a', 'hypersurface', 'singularity', 'in', 'positive', 'characteristic', 'which', 'is', 'defined', 'by', 'a', 'purely', 'inseparable', 'power', 'series', 'and', 'a', 'sequence', 'of', 'point', 'blowups', 'so', 'that', 'after', 'applying', 'the', 'blowups', 'to', 'the', 'singularity', 'the', 'same', 'type', 'of', 'singularity', 'reappears', 'after', 'the', 'last', 'blowup', 'with', 'just', 'certain', 'exponents', 'of', 'the', 'defining', 'power', 'series', 'shifted', 'upwards', 'the', 'construction', 'hence', 'yields', 'a', 'cycle', 'iterating', 'this', 'cycle', 'leads', 'to', 'an', 'infinite', 'increase', 'of', 'the', 'residual', 'order', 'of', 'the', 'defining', 'power', 'series', 'this', 'disproves', 'a', 'theorem', 'claimed', 'by', 'moh', 'about', 'the', 'stability', 'of', 'the', 'residual', 'order', 'under', 'sequences', 'of', 'blowups', 'it', 'is', 'not', 'a', 'counterexample', 'to', 'the', 'resolution', 'in', 'positive', 'characteristic', 'since', 'larger', 'centers', 'are', 'also', 'permissible', 'and', 'prevent', 'the', 'phenomenon', 'from', 'happening']] | [-0.16181138264309838, 0.08666178898233622, -0.12486631993172514, 0.048378189404805504, -0.04279201304834559, -0.12297058900276947, 0.05800395300930254, 0.2744302268500209, -0.32150008257191914, -0.2146361868382774, 0.12483499992890562, -0.24808284896624905, -0.127329612039348, 0.18078219136382398, -0.10434931699727845, -0.0049644872978027174, 0.03001702165342549, 0.06950733403508098, -0.08888053283310281, -0.295892428399788, 0.3757687726925708, 0.06887666662706213, 0.22660176128817675, 0.050929958631113395, 0.10521837536337125, -0.020558638227546316, -0.017041918312191453, 0.035304604130040884, -0.12836562110038732, 0.08269296989091632, 0.2358209643110983, 0.11266481990997608, 0.2867716882759944, -0.3826497137291819, -0.18998926548604678, 0.17799363267791068, 0.14963406327968606, 0.10336191514029335, -0.006593580991547141, -0.22342600569956833, 0.15730331741317183, -0.14168022987213877, -0.18583535755642205, -0.029516940140443988, 0.027306759582721014, 0.016595737164856024, -0.21851743592753306, 0.06785988699596049, 0.1608760724735693, 0.13139737712251198, -0.017546669611882452, -0.04547327034509717, -0.02004071488841158, 0.10010377493981495, 0.06266280444354838, 0.02364748214872984, 0.08149007014914328, -0.09588348316466515, -0.0786442939653738, 0.33781016818605936, -0.04914837306898692, -0.10315438789854316, 0.11100279989365774, -0.15388860425346682, -0.09779516988012016, 0.201048424314214, 0.05822031948970169, 0.13047046292748335, -0.0645874191998926, 0.07385649508498131, -0.0036026878744109063, 0.1402006669491868, 0.16953763741856584, -0.029035499681615166, 0.20782517085377222, 0.09913295421462792, 0.12344481275440791, 0.14337560606515434, -0.03341305475188499, -0.0882417279908545, -0.36022870303887844, -0.13526012481047978, -0.16358698674469677, 0.16029862124429575, -0.1110318062991664, -0.18631258186621544, 0.4238869678388294, 0.0758248862818393, 0.2644807212930332, 0.07511763383025447, 0.24941515820658106, 0.16532233714834493, 0.08047482846842076, 0.02944114957896308, 0.17003559402158308, 0.12639139716425896, 0.09830953182779953, -0.16855039942659375, 0.03253960734806382, 0.13957265341001698] |
1,802.05011 | SIR epidemics and vaccination on random graphs with clustering | In this paper we consider SIR epidemics on random graphs with clustering. To
incorporate group structure of the underlying social network, we use a
generalized version of the configuration model in which each node is a member
of a specified number of triangles. SIR epidemics on this type of graph have
earlier been investigated under the assumption of homogeneous infectivity and
also under the assumption of Poisson transmission and recovery rates. We extend
known results from literature by relaxing the assumption of homogeneous
infectivity. An important special case of the epidemic model analyzed in this
paper is epidemics in continuous time with arbitrary infectious period
distribution. We use branching process approximations of the spread of the
disease to provide expressions for the basic reproduction number R0, the
probability of a major outbreak and the expected final size. In addition, the
impact of random vaccination with a perfect vaccine on the final outcome of the
epidemic is investigated. We find that, for this particular model, R0 equals
the perfect vaccine-associated reproduction number. Generalizations to groups
larger than three are discussed briefly.
| math.PR | in this paper we consider sir epidemics on random graphs with clustering to incorporate group structure of the underlying social network we use a generalized version of the configuration model in which each node is a member of a specified number of triangles sir epidemics on this type of graph have earlier been investigated under the assumption of homogeneous infectivity and also under the assumption of poisson transmission and recovery rates we extend known results from literature by relaxing the assumption of homogeneous infectivity an important special case of the epidemic model analyzed in this paper is epidemics in continuous time with arbitrary infectious period distribution we use branching process approximations of the spread of the disease to provide expressions for the basic reproduction number r0 the probability of a major outbreak and the expected final size in addition the impact of random vaccination with a perfect vaccine on the final outcome of the epidemic is investigated we find that for this particular model r0 equals the perfect vaccineassociated reproduction number generalizations to groups larger than three are discussed briefly | [['in', 'this', 'paper', 'we', 'consider', 'sir', 'epidemics', 'on', 'random', 'graphs', 'with', 'clustering', 'to', 'incorporate', 'group', 'structure', 'of', 'the', 'underlying', 'social', 'network', 'we', 'use', 'a', 'generalized', 'version', 'of', 'the', 'configuration', 'model', 'in', 'which', 'each', 'node', 'is', 'a', 'member', 'of', 'a', 'specified', 'number', 'of', 'triangles', 'sir', 'epidemics', 'on', 'this', 'type', 'of', 'graph', 'have', 'earlier', 'been', 'investigated', 'under', 'the', 'assumption', 'of', 'homogeneous', 'infectivity', 'and', 'also', 'under', 'the', 'assumption', 'of', 'poisson', 'transmission', 'and', 'recovery', 'rates', 'we', 'extend', 'known', 'results', 'from', 'literature', 'by', 'relaxing', 'the', 'assumption', 'of', 'homogeneous', 'infectivity', 'an', 'important', 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1,802.05012 | 'Getting out of the closet': Scientific authorship of literary fiction
and knowledge transfer | Some scientists write literary fiction books in their spare time. If these
books contain scientific knowledge, literary fiction becomes a mechanism of
knowledge transfer. In this case, we could conceptualize literary fiction as
non-formal knowledge transfer. We model knowledge transfer via literary fiction
as a function of the type of scientist (academic or non-academic) and his/her
scientific field. Academic scientists are those employed in academia and public
research organizations whereas non-academic scientists are those with a
scientific background employed in other sectors. We also distinguish between
direct knowledge transfer (the book includes the scientist's research topics),
indirect knowledge transfer (scientific authors talk about their research with
cultural agents) and reverse knowledge transfer (cultural agents give
scientists ideas for future research). Through mixed-methods research and a
sample from Spain, we find that scientific authorship accounts for a
considerable percentage of all literary fiction authorship. Academic scientists
do not transfer knowledge directly so often as non-academic scientists, but the
former engage into indirect and reverse transfer knowledge more often than the
latter. Scientists from History stand out in direct knowledge transfer. We draw
propositions about the role of the academic logic and scientific field on
knowledge transfer via literary fiction. We advance some tentative conclusions
regarding the consideration of scientific authorship of literary fiction as a
valuable knowledge transfer mechanism.
| cs.DL physics.soc-ph | some scientists write literary fiction books in their spare time if these books contain scientific knowledge literary fiction becomes a mechanism of knowledge transfer in this case we could conceptualize literary fiction as nonformal knowledge transfer we model knowledge transfer via literary fiction as a function of the type of scientist academic or nonacademic and hisher scientific field academic scientists are those employed in academia and public research organizations whereas nonacademic scientists are those with a scientific background employed in other sectors we also distinguish between direct knowledge transfer the book includes the scientists research topics indirect knowledge transfer scientific authors talk about their research with cultural agents and reverse knowledge transfer cultural agents give scientists ideas for future research through mixedmethods research and a sample from spain we find that scientific authorship accounts for a considerable percentage of all literary fiction authorship academic scientists do not transfer knowledge directly so often as nonacademic scientists but the former engage into indirect and reverse transfer knowledge more often than the latter scientists from history stand out in direct knowledge transfer we draw propositions about the role of the academic logic and scientific field on knowledge transfer via literary fiction we advance some tentative conclusions regarding the consideration of scientific authorship of literary fiction as a valuable knowledge transfer mechanism | [['some', 'scientists', 'write', 'literary', 'fiction', 'books', 'in', 'their', 'spare', 'time', 'if', 'these', 'books', 'contain', 'scientific', 'knowledge', 'literary', 'fiction', 'becomes', 'a', 'mechanism', 'of', 'knowledge', 'transfer', 'in', 'this', 'case', 'we', 'could', 'conceptualize', 'literary', 'fiction', 'as', 'nonformal', 'knowledge', 'transfer', 'we', 'model', 'knowledge', 'transfer', 'via', 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1,802.05013 | Nuclear spin-lattice relaxation in p-type GaAs | Spin-lattice relaxation of the nuclear spin system in p-type GaAs is studied
using a three-stage experimental protocol including optical pumping and
measuring the difference of the nuclear spin polarization before and after a
dark interval of variable length. This method allows us to measure the
spin-lattice relaxation time $T_1$ of optically pumped nuclei "in the dark",
that is, in the absence of illumination. The measured $T_1$ values fall into
the sub-second time range, being three orders of magnitude shorter than in
earlier studied n-type GaAs. The drastic difference is further emphasized by
magnetic-field and temperature dependences of $T_1$ in p-GaAs, showing no
similarity to those in n-GaAs. This unexpected behavior is explained within a
developed theoretical model involving quadrupole relaxation of nuclear spins,
which is induced by electric fields within closely spaced donor-acceptor pairs.
| cond-mat.other | spinlattice relaxation of the nuclear spin system in ptype gaas is studied using a threestage experimental protocol including optical pumping and measuring the difference of the nuclear spin polarization before and after a dark interval of variable length this method allows us to measure the spinlattice relaxation time t_1 of optically pumped nuclei in the dark that is in the absence of illumination the measured t_1 values fall into the subsecond time range being three orders of magnitude shorter than in earlier studied ntype gaas the drastic difference is further emphasized by magneticfield and temperature dependences of t_1 in pgaas showing no similarity to those in ngaas this unexpected behavior is explained within a developed theoretical model involving quadrupole relaxation of nuclear spins which is induced by electric fields within closely spaced donoracceptor pairs | [['spinlattice', 'relaxation', 'of', 'the', 'nuclear', 'spin', 'system', 'in', 'ptype', 'gaas', 'is', 'studied', 'using', 'a', 'threestage', 'experimental', 'protocol', 'including', 'optical', 'pumping', 'and', 'measuring', 'the', 'difference', 'of', 'the', 'nuclear', 'spin', 'polarization', 'before', 'and', 'after', 'a', 'dark', 'interval', 'of', 'variable', 'length', 'this', 'method', 'allows', 'us', 'to', 'measure', 'the', 'spinlattice', 'relaxation', 'time', 't_1', 'of', 'optically', 'pumped', 'nuclei', 'in', 'the', 'dark', 'that', 'is', 'in', 'the', 'absence', 'of', 'illumination', 'the', 'measured', 't_1', 'values', 'fall', 'into', 'the', 'subsecond', 'time', 'range', 'being', 'three', 'orders', 'of', 'magnitude', 'shorter', 'than', 'in', 'earlier', 'studied', 'ntype', 'gaas', 'the', 'drastic', 'difference', 'is', 'further', 'emphasized', 'by', 'magneticfield', 'and', 'temperature', 'dependences', 'of', 't_1', 'in', 'pgaas', 'showing', 'no', 'similarity', 'to', 'those', 'in', 'ngaas', 'this', 'unexpected', 'behavior', 'is', 'explained', 'within', 'a', 'developed', 'theoretical', 'model', 'involving', 'quadrupole', 'relaxation', 'of', 'nuclear', 'spins', 'which', 'is', 'induced', 'by', 'electric', 'fields', 'within', 'closely', 'spaced', 'donoracceptor', 'pairs']] | [-0.135511797432329, 0.2336492824034571, -0.05438316034562729, 0.04832373289721532, 0.02045116105130804, -0.12592980698265357, 0.026424716567314828, 0.43762457796108367, -0.24656392740252525, -0.32648827984873485, 0.01023033924171451, -0.253530295588421, -0.003493078115549105, 0.24009531238568085, 0.04398122092417038, -0.002418010781754552, -0.04235383798368275, -0.012965670851087059, -0.11148447835810983, -0.20267252947304593, 0.230721506859943, 0.02284466733968358, 0.26838132780768087, 0.07129134766674086, 0.07901238241326759, 0.03675506670719079, 0.04791981247649007, 0.006535038855899848, -0.12639105318092658, 0.06195959238224288, 0.2606825888653828, -0.02371524644098175, 0.21010145914407252, -0.4200940704921872, -0.18670366971350427, 0.06199407471177071, 0.1200409226480927, 0.12336259465508247, -0.05214701100155266, -0.26155080639326306, 0.008809908360951762, -0.14368625586233866, -0.06295347704427011, -0.038631183199528886, 0.05975074448979828, -0.0008744253836043957, -0.24932088124923713, 0.16099122035622931, 0.0761020106338173, 0.06194700798673083, -0.09246407293605118, -0.11266400775726218, 0.0018192845007488087, 0.044115159693591074, 0.08148286980663691, 0.0459219234562896, 0.2150833271582847, -0.03346448141643638, -0.13106024622180457, 0.33966565894574596, -0.09546594264703792, -0.05425549584307096, 0.1343209032636525, -0.23228145770228176, -0.04074939293439375, 0.1785863555356193, 0.1056607127217437, 0.14716899709831646, -0.1780711212855722, 0.037089044876733736, 0.009877731446732782, 0.19808698619747145, 0.07624592411387433, 0.09254499653496766, 0.21081114567315845, 0.2391946687173696, 0.02896989746464055, 0.1305127556465302, -0.10454194507658926, -0.10284049231767543, -0.22962513557416317, -0.11003329931522038, -0.2104278891034591, 0.08847467680357453, -0.06970259181274632, -0.0674731910590138, 0.44787115999844984, 0.09759497114130532, 0.19817733822682343, -0.02855042476161842, 0.2843535616159884, 0.10998664679850187, 0.1034188984776847, 0.023260975487655336, 0.26693088954676, 0.19183153609802545, 0.08872621229140838, -0.37218070517071705, 0.07946985357079599, -0.0018736560995787827] |
1,802.05014 | Distributional Term Set Expansion | This paper is a short empirical study of the performance of centrality and
classification based iterative term set expansion methods for distributional
semantic models. Iterative term set expansion is an interactive process using
distributional semantics models where a user labels terms as belonging to some
sought after term set, and a system uses this labeling to supply the user with
new, candidate, terms to label, trying to maximize the number of positive
examples found. While centrality based methods have a long history in term set
expansion, we compare them to classification methods based on the the Simple
Margin method, an Active Learning approach to classification using Support
Vector Machines. Examining the performance of various centrality and
classification based methods for a variety of distributional models over five
different term sets, we can show that active learning based methods
consistently outperform centrality based methods.
| cs.CL | this paper is a short empirical study of the performance of centrality and classification based iterative term set expansion methods for distributional semantic models iterative term set expansion is an interactive process using distributional semantics models where a user labels terms as belonging to some sought after term set and a system uses this labeling to supply the user with new candidate terms to label trying to maximize the number of positive examples found while centrality based methods have a long history in term set expansion we compare them to classification methods based on the the simple margin method an active learning approach to classification using support vector machines examining the performance of various centrality and classification based methods for a variety of distributional models over five different term sets we can show that active learning based methods consistently outperform centrality based methods | [['this', 'paper', 'is', 'a', 'short', 'empirical', 'study', 'of', 'the', 'performance', 'of', 'centrality', 'and', 'classification', 'based', 'iterative', 'term', 'set', 'expansion', 'methods', 'for', 'distributional', 'semantic', 'models', 'iterative', 'term', 'set', 'expansion', 'is', 'an', 'interactive', 'process', 'using', 'distributional', 'semantics', 'models', 'where', 'a', 'user', 'labels', 'terms', 'as', 'belonging', 'to', 'some', 'sought', 'after', 'term', 'set', 'and', 'a', 'system', 'uses', 'this', 'labeling', 'to', 'supply', 'the', 'user', 'with', 'new', 'candidate', 'terms', 'to', 'label', 'trying', 'to', 'maximize', 'the', 'number', 'of', 'positive', 'examples', 'found', 'while', 'centrality', 'based', 'methods', 'have', 'a', 'long', 'history', 'in', 'term', 'set', 'expansion', 'we', 'compare', 'them', 'to', 'classification', 'methods', 'based', 'on', 'the', 'the', 'simple', 'margin', 'method', 'an', 'active', 'learning', 'approach', 'to', 'classification', 'using', 'support', 'vector', 'machines', 'examining', 'the', 'performance', 'of', 'various', 'centrality', 'and', 'classification', 'based', 'methods', 'for', 'a', 'variety', 'of', 'distributional', 'models', 'over', 'five', 'different', 'term', 'sets', 'we', 'can', 'show', 'that', 'active', 'learning', 'based', 'methods', 'consistently', 'outperform', 'centrality', 'based', 'methods']] | [-0.04996894095158139, -0.041364192690535845, -0.1059891557535873, 0.07101671649613493, -0.13676480457864024, -0.15078343164136673, 0.06572195765207411, 0.4251281780848553, -0.26634915470034926, -0.3075668315233832, 0.05710699526720087, -0.29430891118839486, -0.1609003055137354, 0.196035965573746, -0.08803438203135779, 0.0879615060789706, 0.12166034346413832, 0.11457230997193683, -0.08924510329147683, -0.3212048263855643, 0.33328148757817444, 0.04288156990977851, 0.3133547598157417, 0.030261275934876052, 0.14804999665454863, -0.022763572491614238, -0.056722826848679284, 0.06484250415611517, -0.08341066674289653, 0.1666906115768308, 0.26842863847994813, 0.18978694433971613, 0.3570580459427792, -0.3436559373056972, -0.22435273105682402, 0.12893738605772387, 0.13540369181542078, 0.08102912729820953, -0.00011515093094610668, -0.29681745886646366, 0.10390107257949462, -0.2474342235136074, 0.007758950882988585, -0.16402022097051353, -0.00015045674778260551, 0.04472054323381777, -0.3138818966324109, 0.03466993870158269, 0.053385960796629765, 0.08954996383143263, -0.07479564917853454, -0.13648638555737722, 0.05568298559157191, 0.1247057721793808, 0.07704377959468532, 0.03676007481998523, 0.09872838405735947, -0.14029499590177075, -0.20027013084610235, 0.34442184156888017, -0.08185315580055169, -0.23755134659057314, 0.23322651322957103, 0.013122878402106828, -0.1397653875051887, 0.08359526431552701, 0.2453287763674125, 0.1533812626584114, -0.19611817256912226, 0.019396667123260953, -0.014338787158273837, 0.16140741740281767, 0.03545976494002592, 0.012845735179612062, 0.16276118312018006, 0.23219636915629352, 0.0418239823539279, 0.11744323776631088, -0.0854075677219495, -0.07168023061280797, -0.2699361368362512, -0.09126950334106292, -0.18032151324531207, -0.033391712814279655, -0.12408462581291903, -0.20392576143979194, 0.4205434365276169, 0.2041181597917282, 0.22106287210945275, 0.11139621863050478, 0.3151454666720612, 0.07065835418269181, 0.06396272923745266, 0.10043454296248672, 0.13431607206108642, 0.05281057752875637, 0.10172434151254048, -0.1604377980786864, 0.10869008871576899, 0.15776530144918527] |
1,802.05015 | Parameter estimation for discretely-observed linear birth-and-death
processes | Birth-and-death processes are widely used to model the development of
biological populations. Although they are relatively simple models, their
parameters can be challenging to estimate, because the likelihood can become
numerically unstable when data arise from the most common sampling schemes,
such as annual population censuses. Simple estimators may be based on an
embedded Galton-Watson process, but this presupposes that the observation times
are equi-spaced. We estimate the birth, death, and growth rates of a linear
birth-and-death process whose population size is periodically observed via an
embedded Galton-Watson process, and by maximizing a saddlepoint approximation
to the likelihood. We show that a Gaussian approximation to the
saddlepoint-based likelihood connects the two approaches, we establish
consistency and asymptotic normality of quasi-likelihood estimators, compare
our estimators on some numerical examples, and apply our results to census data
for two endangered bird populations and the H1N1 influenza pandemic.
| math.ST stat.TH | birthanddeath processes are widely used to model the development of biological populations although they are relatively simple models their parameters can be challenging to estimate because the likelihood can become numerically unstable when data arise from the most common sampling schemes such as annual population censuses simple estimators may be based on an embedded galtonwatson process but this presupposes that the observation times are equispaced we estimate the birth death and growth rates of a linear birthanddeath process whose population size is periodically observed via an embedded galtonwatson process and by maximizing a saddlepoint approximation to the likelihood we show that a gaussian approximation to the saddlepointbased likelihood connects the two approaches we establish consistency and asymptotic normality of quasilikelihood estimators compare our estimators on some numerical examples and apply our results to census data for two endangered bird populations and the h1n1 influenza pandemic | [['birthanddeath', 'processes', 'are', 'widely', 'used', 'to', 'model', 'the', 'development', 'of', 'biological', 'populations', 'although', 'they', 'are', 'relatively', 'simple', 'models', 'their', 'parameters', 'can', 'be', 'challenging', 'to', 'estimate', 'because', 'the', 'likelihood', 'can', 'become', 'numerically', 'unstable', 'when', 'data', 'arise', 'from', 'the', 'most', 'common', 'sampling', 'schemes', 'such', 'as', 'annual', 'population', 'censuses', 'simple', 'estimators', 'may', 'be', 'based', 'on', 'an', 'embedded', 'galtonwatson', 'process', 'but', 'this', 'presupposes', 'that', 'the', 'observation', 'times', 'are', 'equispaced', 'we', 'estimate', 'the', 'birth', 'death', 'and', 'growth', 'rates', 'of', 'a', 'linear', 'birthanddeath', 'process', 'whose', 'population', 'size', 'is', 'periodically', 'observed', 'via', 'an', 'embedded', 'galtonwatson', 'process', 'and', 'by', 'maximizing', 'a', 'saddlepoint', 'approximation', 'to', 'the', 'likelihood', 'we', 'show', 'that', 'a', 'gaussian', 'approximation', 'to', 'the', 'saddlepointbased', 'likelihood', 'connects', 'the', 'two', 'approaches', 'we', 'establish', 'consistency', 'and', 'asymptotic', 'normality', 'of', 'quasilikelihood', 'estimators', 'compare', 'our', 'estimators', 'on', 'some', 'numerical', 'examples', 'and', 'apply', 'our', 'results', 'to', 'census', 'data', 'for', 'two', 'endangered', 'bird', 'populations', 'and', 'the', 'h1n1', 'influenza', 'pandemic']] | [-0.04093953394880777, 0.09474520673736858, -0.1098963186248309, 0.15671216696479304, -0.0662701354691914, -0.1432115324067935, 0.06991640842251298, 0.40040766437111114, -0.24030092573714987, -0.2596479231182861, 0.19143591913274982, -0.27830823300044155, -0.16774009441481516, 0.21379122535614037, -0.11108450291147973, 0.051283186300780575, 0.09545196138949702, -0.012603828812845878, 0.027955884079953346, -0.2999953453222083, 0.27204050450382056, 0.05507346733227476, 0.2998780846828595, -0.038087038446974475, 0.08829072658651664, -0.025568462355295196, -0.03227899698605244, -0.019402639946848568, -0.14566233969415204, 0.08952141122750214, 0.25660382226844075, 0.1927440199320295, 0.30460800946133937, -0.4029574424429383, -0.21627798260791073, 0.17038747133402568, 0.19342398531605592, 0.13731678443825027, -0.027813063717177202, -0.2706479588943896, 0.02766606182881838, -0.16602692432611044, -0.13252461592007117, -0.0721114871476958, -0.021418229890211176, 0.070072302409244, -0.3339529305554202, 0.11000373031129129, 0.037820718108883336, 0.03663103091013101, -0.04283729596580896, -0.12896654772096858, -0.04814273899602187, 0.11223581256995709, 0.08570099769167427, -0.05648977248023988, 0.1504536953030361, -0.08520747686108937, -0.13050708554348806, 0.3051306085706326, -0.05168492079246789, -0.1969623207502688, 0.2447721928814038, -0.13438166616510394, -0.15022733641833635, 0.09562453778279531, 0.23780767289523888, 0.10437670416851891, -0.21979148448139718, 0.015360594453442091, -0.0020537473109369683, 0.1127188500831835, 0.042692127854226984, -0.03985450144197481, 0.19236452169651683, 0.1872520165440316, 0.04232737773696095, 0.09987896530785495, -0.10772748989014265, -0.16121261582076032, -0.2370084142894484, -0.0880414137229511, -0.18545923219385763, 0.042791495406870834, -0.15925874664501155, -0.22288945034637841, 0.353128799906699, 0.18398165801530317, 0.21277106175289695, 0.13853243428457063, 0.2628049730281216, 0.1397852225418319, 0.019228651392849214, 0.07810296726852863, 0.1644293869477325, 0.13887505326581756, 0.015352603578422632, -0.17713349097983963, 0.17360023192142965, 0.02166916250846245] |
1,802.05016 | Multilevel nested simulation for efficient risk estimation | We investigate the problem of computing a nested expectation of the form
$\mathbb{P}[\mathbb{E}[X|Y]
\!\geq\!0]\!=\!\mathbb{E}[\textrm{H}(\mathbb{E}[X|Y])]$ where $\textrm{H}$ is
the Heaviside function. This nested expectation appears, for example, when
estimating the probability of a large loss from a financial portfolio. We
present a method that combines the idea of using Multilevel Monte Carlo (MLMC)
for nested expectations with the idea of adaptively selecting the number of
samples in the approximation of the inner expectation, as proposed by (Broadie
et al., 2011). We propose and analyse an algorithm that adaptively selects the
number of inner samples on each MLMC level and prove that the resulting MLMC
method with adaptive sampling has an $\mathcal{O}\left(
\varepsilon^{-2}|\log\varepsilon|^2 \right)$ complexity to achieve a root
mean-squared error $\varepsilon$. The theoretical analysis is verified by
numerical experiments on a simple model problem. We also present a stochastic
root-finding algorithm that, combined with our adaptive methods, can be used to
compute other risk measures such as Value-at-Risk (VaR) and Conditional
Value-at-Risk (CVaR), with the latter being achieved with
$\mathcal{O}\left(\varepsilon^{-2}\right)$ complexity.
| q-fin.CP math.PR | we investigate the problem of computing a nested expectation of the form mathbbpmathbbexy geq0mathbbetextrmhmathbbexy where textrmh is the heaviside function this nested expectation appears for example when estimating the probability of a large loss from a financial portfolio we present a method that combines the idea of using multilevel monte carlo mlmc for nested expectations with the idea of adaptively selecting the number of samples in the approximation of the inner expectation as proposed by broadie et al 2011 we propose and analyse an algorithm that adaptively selects the number of inner samples on each mlmc level and prove that the resulting mlmc method with adaptive sampling has an mathcaloleft varepsilon2logvarepsilon2 right complexity to achieve a root meansquared error varepsilon the theoretical analysis is verified by numerical experiments on a simple model problem we also present a stochastic rootfinding algorithm that combined with our adaptive methods can be used to compute other risk measures such as valueatrisk var and conditional valueatrisk cvar with the latter being achieved with mathcaloleftvarepsilon2right complexity | [['we', 'investigate', 'the', 'problem', 'of', 'computing', 'a', 'nested', 'expectation', 'of', 'the', 'form', 'mathbbpmathbbexy', 'geq0mathbbetextrmhmathbbexy', 'where', 'textrmh', 'is', 'the', 'heaviside', 'function', 'this', 'nested', 'expectation', 'appears', 'for', 'example', 'when', 'estimating', 'the', 'probability', 'of', 'a', 'large', 'loss', 'from', 'a', 'financial', 'portfolio', 'we', 'present', 'a', 'method', 'that', 'combines', 'the', 'idea', 'of', 'using', 'multilevel', 'monte', 'carlo', 'mlmc', 'for', 'nested', 'expectations', 'with', 'the', 'idea', 'of', 'adaptively', 'selecting', 'the', 'number', 'of', 'samples', 'in', 'the', 'approximation', 'of', 'the', 'inner', 'expectation', 'as', 'proposed', 'by', 'broadie', 'et', 'al', '2011', 'we', 'propose', 'and', 'analyse', 'an', 'algorithm', 'that', 'adaptively', 'selects', 'the', 'number', 'of', 'inner', 'samples', 'on', 'each', 'mlmc', 'level', 'and', 'prove', 'that', 'the', 'resulting', 'mlmc', 'method', 'with', 'adaptive', 'sampling', 'has', 'an', 'mathcaloleft', 'varepsilon2logvarepsilon2', 'right', 'complexity', 'to', 'achieve', 'a', 'root', 'meansquared', 'error', 'varepsilon', 'the', 'theoretical', 'analysis', 'is', 'verified', 'by', 'numerical', 'experiments', 'on', 'a', 'simple', 'model', 'problem', 'we', 'also', 'present', 'a', 'stochastic', 'rootfinding', 'algorithm', 'that', 'combined', 'with', 'our', 'adaptive', 'methods', 'can', 'be', 'used', 'to', 'compute', 'other', 'risk', 'measures', 'such', 'as', 'valueatrisk', 'var', 'and', 'conditional', 'valueatrisk', 'cvar', 'with', 'the', 'latter', 'being', 'achieved', 'with', 'mathcaloleftvarepsilon2right', 'complexity']] | [-0.04192862472863811, 0.03759746167995741, -0.09630768846783956, 0.09594445574365443, -0.040261068982495506, -0.11313220162057515, 0.08702736199466568, 0.387880183124181, -0.27871378153830656, -0.3218909155916084, 0.11016754042004433, -0.2492583874782378, -0.15518434014397137, 0.18416660109704192, -0.11764594991268082, 0.10303319947173198, 0.06798511153284573, 0.002130195361590295, -0.05425780120545603, -0.2817461624741554, 0.2620672999105106, 0.12326671666268146, 0.2683533101504894, -0.05483632332109141, 0.1642445457224367, 0.017585288400225565, -0.016843345242369016, 0.04277431569485502, -0.12536497106863834, 0.16028012047295995, 0.23854430325639744, 0.16839676112021235, 0.39981845526984244, -0.37729091827588324, -0.16583762316625905, 0.11640481250360608, 0.11195695992880218, 0.083518247278125, -0.058199428261793924, -0.2630114614914143, 0.06378609891416448, -0.19302055889347686, -0.09618409918621182, -0.08878385484982353, -0.07614675487927866, 0.03611811489487688, -0.38082735364635784, 0.07500552215567564, 0.0003583345308222554, 0.019680582077214213, 0.004447796360843561, -0.17853306212434264, 0.016330292200048765, 0.04368999167998096, 0.045438306531727764, 0.023691388608880735, 0.08782353325619954, -0.06646558406593447, -0.17496894534790156, 0.3006942036374698, -0.06406813627673369, -0.2258944295262071, 0.11930268831607518, -0.07742028941089908, -0.11712775560321681, 0.10734347326091886, 0.18452863115041207, 0.12722687972709537, -0.12187826898077743, 0.09889091396118711, -0.06864994207227772, 0.14516509955142146, -0.0006945807416217797, -0.022224373790915266, 0.08669114440580773, 0.1960739409720356, 0.0991620631324071, 0.17205680610971863, -0.1333700817572235, -0.1286512245554618, -0.2887550106751874, -0.16062355554551522, -0.23023376447063956, -0.0024066501169176207, -0.14349035617558525, -0.2045122260114912, 0.3456993839774055, 0.2083176803676355, 0.21241297102109952, 0.15891052692225485, 0.3352340054557179, 0.17530581791052652, 0.016818561783116876, 0.11552577579789089, 0.16543227217696382, 0.0719973515066544, 0.017809321677707362, -0.235670048663054, 0.12839660312077314, 0.13050999414232192] |
1,802.05017 | Insisting on the role of experimental data: the pseudoscalar-pole piece
to the $(g_\mu-2)$ and the $|V_{ub}|$ from $B \to \pi \ell \nu_{\ell}$
differential branching ratio | We employ a mathematical framework based on rational approximants in order to
calculate meson form factors. The method profits from unitary, is systematic
and data based, and is able to ascribe a systematic uncertainty which provides
for the desired model independence. Two examples are discussed: the transition
form factor entering the pseudoscalar-pole piece of the hadronic light-by-light
contribution to the anomalous magnetic moment of the muon, and the $B \to \pi$
form factor participating the $B\to\pi\ell\nu_{\ell}$ differential branching
ratios which allows to determine the $|V_{ub}|$ CKM parameter.
| hep-ph hep-ex | we employ a mathematical framework based on rational approximants in order to calculate meson form factors the method profits from unitary is systematic and data based and is able to ascribe a systematic uncertainty which provides for the desired model independence two examples are discussed the transition form factor entering the pseudoscalarpole piece of the hadronic lightbylight contribution to the anomalous magnetic moment of the muon and the b to pi form factor participating the btopiellnu_ell differential branching ratios which allows to determine the v_ub ckm parameter | [['we', 'employ', 'a', 'mathematical', 'framework', 'based', 'on', 'rational', 'approximants', 'in', 'order', 'to', 'calculate', 'meson', 'form', 'factors', 'the', 'method', 'profits', 'from', 'unitary', 'is', 'systematic', 'and', 'data', 'based', 'and', 'is', 'able', 'to', 'ascribe', 'a', 'systematic', 'uncertainty', 'which', 'provides', 'for', 'the', 'desired', 'model', 'independence', 'two', 'examples', 'are', 'discussed', 'the', 'transition', 'form', 'factor', 'entering', 'the', 'pseudoscalarpole', 'piece', 'of', 'the', 'hadronic', 'lightbylight', 'contribution', 'to', 'the', 'anomalous', 'magnetic', 'moment', 'of', 'the', 'muon', 'and', 'the', 'b', 'to', 'pi', 'form', 'factor', 'participating', 'the', 'btopiellnu_ell', 'differential', 'branching', 'ratios', 'which', 'allows', 'to', 'determine', 'the', 'v_ub', 'ckm', 'parameter']] | [-0.0904744470493359, 0.13414580424771058, -0.0812280394440127, 0.07618079733287612, -0.12931649306204257, -0.07890967821139236, 0.10707698246636049, 0.30231032209730774, -0.2404641958365087, -0.2683569452140567, 0.008723997612494629, -0.3178063218109919, -0.08675197543045722, 0.13731596157290474, 0.027670614042341016, 0.0922982779515604, 0.010751035455668474, 0.06060902171140147, -0.08319571278285408, -0.18554336923109585, 0.32877416993480524, 0.026998151743481327, 0.2486142367232851, 0.07489379154799809, 0.07572842040776037, -0.021553046566327266, -0.06825095026883794, -0.05085594004539903, -0.14872526270229108, 0.13848606446692938, 0.2311234213411808, 0.07762643743338886, 0.14925572743942572, -0.3813813120603215, -0.04742256243345003, 0.09608127716942257, 0.10979785478056603, 0.09158649136377282, 0.01042612951091859, -0.26346749939067765, 0.06592266650350634, -0.19253650740828626, -0.13164998419842747, -0.15969712503774222, 0.0025045592987606694, -0.06427823143556367, -0.3734913428075785, 0.058497104888543656, -0.002300329701325228, 0.0035855033499903456, -0.0006609166665056851, -0.21216681608280472, 0.0743216969814628, 0.13810766009657188, 0.10476565461600372, 0.06807691685118994, 0.1647137787225548, -0.09800205423041831, -0.125919486682992, 0.4289632988660488, -0.04718137826624348, -0.19661069471865547, 0.06084471198643536, -0.1891362416763725, -0.15202789308251488, 0.17425047634115312, 0.22518417947427477, 0.04339729771451201, -0.21322979057900782, 0.06724180506750789, 0.006233877653992454, 0.1796571312575103, 0.013738373613937996, -0.012470242870581705, 0.16120321101368254, 0.147522512097778, 0.0005574855617745671, 0.08842054089574619, -0.08597690480772059, -0.08591233492763929, -0.3500087028802481, -0.13819969418765923, -0.09082031868896338, 0.07661142957743344, -0.08469317419414522, -0.1588434181825886, 0.385093214577822, 0.12729958022489798, 0.2286239058688976, 0.018000900672293853, 0.31785925673212595, 0.1376207362918649, 0.07191645909374211, 0.04260399667979326, 0.26355214028207713, 0.20304801391957458, 0.06073233876702224, -0.2713413713039657, 0.11836966975093928, 0.1317549489822975] |
1,802.05018 | Formation of recurring slope lineae on Mars by rarefied gas-triggered
granular flows | Active dark flows known as recurring slope lineae have been observed on the
warmest slopes of equatorial Mars. The morphology, composition and seasonality
of the lineae suggest a role of liquid water in their formation. However,
internal and atmospheric sources of water appear to be insufficient to sustain
the observed slope activity. Experimental evidence suggests that under the low
atmospheric pressure at the surface of Mars, gas can flow upwards through
porous Martian soil due to thermal creep under surface regions heated by the
Sun, and disturb small particles. Here we present numerical simulations to
demonstrate that such a dry process involving the pumping of rarefied gas in
the Martian soil due to temperature contrasts can explain the formation of the
recurring slope lineae. In our simulations, solar irradiation followed by
shadow significantly reduces the angle of repose due to the resulting temporary
temperature gradients over shaded terrain, and leads to flow at intermediate
slope angles. The simulated flow locations are consistent with observed
recurring slope lineae that initiate in rough and bouldered terrains with local
shadows over the soil. We suggest that this dry avalanche process can explain
the formation of the recurring slope lineae on Mars without requiring liquid
water or CO2 frost activity.
| astro-ph.EP | active dark flows known as recurring slope lineae have been observed on the warmest slopes of equatorial mars the morphology composition and seasonality of the lineae suggest a role of liquid water in their formation however internal and atmospheric sources of water appear to be insufficient to sustain the observed slope activity experimental evidence suggests that under the low atmospheric pressure at the surface of mars gas can flow upwards through porous martian soil due to thermal creep under surface regions heated by the sun and disturb small particles here we present numerical simulations to demonstrate that such a dry process involving the pumping of rarefied gas in the martian soil due to temperature contrasts can explain the formation of the recurring slope lineae in our simulations solar irradiation followed by shadow significantly reduces the angle of repose due to the resulting temporary temperature gradients over shaded terrain and leads to flow at intermediate slope angles the simulated flow locations are consistent with observed recurring slope lineae that initiate in rough and bouldered terrains with local shadows over the soil we suggest that this dry avalanche process can explain the formation of the recurring slope lineae on mars without requiring liquid water or co2 frost activity | [['active', 'dark', 'flows', 'known', 'as', 'recurring', 'slope', 'lineae', 'have', 'been', 'observed', 'on', 'the', 'warmest', 'slopes', 'of', 'equatorial', 'mars', 'the', 'morphology', 'composition', 'and', 'seasonality', 'of', 'the', 'lineae', 'suggest', 'a', 'role', 'of', 'liquid', 'water', 'in', 'their', 'formation', 'however', 'internal', 'and', 'atmospheric', 'sources', 'of', 'water', 'appear', 'to', 'be', 'insufficient', 'to', 'sustain', 'the', 'observed', 'slope', 'activity', 'experimental', 'evidence', 'suggests', 'that', 'under', 'the', 'low', 'atmospheric', 'pressure', 'at', 'the', 'surface', 'of', 'mars', 'gas', 'can', 'flow', 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1,802.05019 | Discovery of a strain-stabilised smectic electronic order in LiFeAs | In many high temperature superconductors, small orthorhombic distortions of
the lattice structure result in surprisingly large symmetry breaking of the
electronic states and macroscopic properties, an effect often referred to as
nematicity. To directly study the impact of symmetry-breaking lattice
distortions on the electronic states, using low-temperature scanning tunnelling
microscopy we image at the atomic scale the influence of strain-tuned lattice
distortions on the correlated electronic states in the iron-based
superconductor LiFeAs, a material which in its ground state is tetragonal, with
four-fold ($C_4$) symmetry. Our experiments uncover a new strain-stabilised
modulated phase which exhibits a smectic order in LiFeAs, an electronic state
which not only breaks rotational symmetry but also reduces translational
symmetry. We follow the evolution of the superconducting gap from the
unstrained material with $C_4$ symmetry through the new nematic phase with
two-fold ($C_2$) symmetry and charge-density-wave order to a state where
superconductivity is completely suppressed.
| cond-mat.str-el cond-mat.supr-con | in many high temperature superconductors small orthorhombic distortions of the lattice structure result in surprisingly large symmetry breaking of the electronic states and macroscopic properties an effect often referred to as nematicity to directly study the impact of symmetrybreaking lattice distortions on the electronic states using lowtemperature scanning tunnelling microscopy we image at the atomic scale the influence of straintuned lattice distortions on the correlated electronic states in the ironbased superconductor lifeas a material which in its ground state is tetragonal with fourfold c_4 symmetry our experiments uncover a new strainstabilised modulated phase which exhibits a smectic order in lifeas an electronic state which not only breaks rotational symmetry but also reduces translational symmetry we follow the evolution of the superconducting gap from the unstrained material with c_4 symmetry through the new nematic phase with twofold c_2 symmetry and chargedensitywave order to a state where superconductivity is completely suppressed | [['in', 'many', 'high', 'temperature', 'superconductors', 'small', 'orthorhombic', 'distortions', 'of', 'the', 'lattice', 'structure', 'result', 'in', 'surprisingly', 'large', 'symmetry', 'breaking', 'of', 'the', 'electronic', 'states', 'and', 'macroscopic', 'properties', 'an', 'effect', 'often', 'referred', 'to', 'as', 'nematicity', 'to', 'directly', 'study', 'the', 'impact', 'of', 'symmetrybreaking', 'lattice', 'distortions', 'on', 'the', 'electronic', 'states', 'using', 'lowtemperature', 'scanning', 'tunnelling', 'microscopy', 'we', 'image', 'at', 'the', 'atomic', 'scale', 'the', 'influence', 'of', 'straintuned', 'lattice', 'distortions', 'on', 'the', 'correlated', 'electronic', 'states', 'in', 'the', 'ironbased', 'superconductor', 'lifeas', 'a', 'material', 'which', 'in', 'its', 'ground', 'state', 'is', 'tetragonal', 'with', 'fourfold', 'c_4', 'symmetry', 'our', 'experiments', 'uncover', 'a', 'new', 'strainstabilised', 'modulated', 'phase', 'which', 'exhibits', 'a', 'smectic', 'order', 'in', 'lifeas', 'an', 'electronic', 'state', 'which', 'not', 'only', 'breaks', 'rotational', 'symmetry', 'but', 'also', 'reduces', 'translational', 'symmetry', 'we', 'follow', 'the', 'evolution', 'of', 'the', 'superconducting', 'gap', 'from', 'the', 'unstrained', 'material', 'with', 'c_4', 'symmetry', 'through', 'the', 'new', 'nematic', 'phase', 'with', 'twofold', 'c_2', 'symmetry', 'and', 'chargedensitywave', 'order', 'to', 'a', 'state', 'where', 'superconductivity', 'is', 'completely', 'suppressed']] | [-0.21410695776639105, 0.2553192323502043, -0.06439886192438772, -0.0021213731096075797, -0.09799133936522177, -0.12568750356896655, 0.10720152990288133, 0.38354965072829983, -0.30406008075570334, -0.24549455784034688, 0.02535907833717411, -0.32787728802980604, -0.12673507823382277, 0.06619417926373677, 0.04348654608081749, 0.033120885849662905, -0.09462478959530189, -0.032422560591127164, -0.16421786915963968, -0.22158755709234676, 0.3077928283899972, 0.01708728725144111, 0.37740431871498004, 0.06244303641771596, 0.03810763856823984, -0.02524042600841337, 0.18908961304790667, -0.00665201445903025, -0.165092315406828, 0.024976926116741616, 0.25312808970291467, -0.11827924071081183, 0.13035162753343732, -0.4659832488632182, -0.21452118059922312, 0.009672590410273924, 0.11182580855706506, 0.21302729226865907, -0.08116458981404887, -0.31879972333931744, 0.007215051902332218, -0.1372910348062932, -0.1339823210869941, -0.16855552164535667, -0.07432803594683474, -0.07573270702630759, -0.17957418945160178, 0.14503388014614954, 0.04635990032064099, 0.15196553637380586, -0.10877693330041587, -0.06579510213467418, -0.1314656594658044, 0.024790790440149705, 0.0901056798835713, 0.07571648079209735, 0.10294425871846191, -0.12682546459679567, -0.10478255323235046, 0.45031256176455803, 0.0038529334360154696, -0.0688831592230378, 0.11107745086711303, -0.18318454057884379, -0.1647580184508115, 0.19502400891616237, 0.07923910842667259, 0.06584515338260177, -0.06832021983486689, 0.05759461760454861, -0.013649370791893956, 0.2567197850392502, 0.00862473455522008, 0.12351614110347992, 0.20871202256278815, 0.18484102481523076, 0.07754094824407287, 0.14704817354347166, -0.11072344314920515, -0.06350316702328446, -0.2381690716735918, -0.13673350344588225, -0.2559901168821631, 0.053950306688961606, -0.05812544385392086, -0.20721673044357197, 0.4281599383574684, 0.112983990100376, 0.2125942968964778, -0.11615181545415465, 0.20129301187242507, 0.03706213127431535, 0.10472502105403692, 0.00416518616760653, 0.2263661592497138, 0.13874938258448163, 0.08817624225520303, -0.3497065349507171, 0.09198758760907662, 0.02099181993036984] |
1,802.0502 | The $\varepsilon$-form of the differential equations for Feynman
integrals in the elliptic case | Feynman integrals are easily solved if their system of differential equations
is in $\varepsilon$-form. In this letter we show by the explicit example of the
kite integral family that an $\varepsilon$-form can even be achieved, if the
Feynman integrals do not evaluate to multiple polylogarithms. The
$\varepsilon$-form is obtained by a (non-algebraic) change of basis for the
master integrals.
| hep-ph hep-th | feynman integrals are easily solved if their system of differential equations is in varepsilonform in this letter we show by the explicit example of the kite integral family that an varepsilonform can even be achieved if the feynman integrals do not evaluate to multiple polylogarithms the varepsilonform is obtained by a nonalgebraic change of basis for the master integrals | [['feynman', 'integrals', 'are', 'easily', 'solved', 'if', 'their', 'system', 'of', 'differential', 'equations', 'is', 'in', 'varepsilonform', 'in', 'this', 'letter', 'we', 'show', 'by', 'the', 'explicit', 'example', 'of', 'the', 'kite', 'integral', 'family', 'that', 'an', 'varepsilonform', 'can', 'even', 'be', 'achieved', 'if', 'the', 'feynman', 'integrals', 'do', 'not', 'evaluate', 'to', 'multiple', 'polylogarithms', 'the', 'varepsilonform', 'is', 'obtained', 'by', 'a', 'nonalgebraic', 'change', 'of', 'basis', 'for', 'the', 'master', 'integrals']] | [-0.20473356898558343, 0.0854902181843931, -0.11553016732746767, 0.08132876273662926, -0.11396353996469308, -0.0878918998148608, 0.02224871996095625, 0.36231919453810835, -0.2865466224187512, -0.26292629101140014, 0.09477698744937652, -0.24512744364249756, -0.20726434990637382, 0.25671865079370404, -0.09111024343045586, 0.021113267491997805, 0.15242795341537665, 0.05424730689264834, -0.06419596600867176, -0.3189978000660569, 0.34718642762656937, -0.03947556061449192, 0.13982193326672254, 0.03529018159734748, 0.14201567181528119, 0.04223281974209694, -0.022458181953278637, -0.004487150127731137, -0.08648592936552339, 0.1098520838481895, 0.2729557757029089, 0.07011253882388947, 0.21302778340118417, -0.40862221908518825, -0.15217579385044716, 0.09096100913771128, 0.21841239207029595, 0.08044493793494116, 0.05361389472954354, -0.23906957041630048, 0.03669252175585193, -0.19312169137647597, -0.18886181308051286, -0.1625570111229258, 0.0016529886367715012, 0.02384028749508878, -0.26675236479268744, 0.02642761202434362, 0.022389432683713354, 0.06325185944531429, -0.030101793557721173, -0.09722309088200268, -0.03446367779209957, 0.09042231226339936, -0.03693993308707693, 0.006177063565701246, 0.044888418538780034, -0.11622165286234261, -0.14997383901628397, 0.35336388595761353, -0.07724574253444512, -0.3030832067952823, 0.05084182685280566, -0.1715440407900487, -0.11754786454425273, 0.16648119107141332, 0.08147815865922277, 0.1955921557432009, -0.24370057562018854, 0.12494591334676844, -0.03455593907353231, 0.08039252381077257, 0.12135647353321566, -0.05608569975089976, 0.13410044126844, 0.016081517623437538, -0.018687388366403972, 0.1476250516578271, 0.024790280877407325, -0.11539379557815649, -0.3419565818029835, -0.2001649853536638, -0.17115252184034405, 0.0742528646776425, -0.08153053477674849, -0.17661704893334437, 0.3302786682053643, 0.1283957859169755, 0.13548970771795613, 0.06679543844913527, 0.24360381123625627, 0.26137407927505546, 0.11583447651700828, 0.026819556983093084, 0.20840882892736187, 0.07022100087981355, 0.05737214226086261, -0.20329642941449153, 0.030187222072696786, 0.1521488376656326] |
1,802.05021 | Rayleigh-Taylor turbulence with singular nonuniform initial conditions | We perform direct numerical simulations of three dimensional Rayleigh-Taylor
turbulence with a nonuniform singular initial temperature background. In such
conditions, the mixing layer evolves under the driving of a varying effective
Atwood number; the long-time growth is still self-similar, but not anymore
proportional to $t^2$ and depends on the singularity exponent $c$ of the
initial profile $\Delta T \propto z^c$. We show that the universality is
recovered when looking at the efficiency, defined as the ratio of the variation
rates of the kinetic energy over the heat flux. A closure model is proposed
that is able to reproduce analytically the time evolution of the mean
temperature profiles, in excellent agreement with the numerical results.
Finally, we reinterpret our findings in the light of spontaneous stochasticity
where the growth of the mixing layer is mapped into the propagation of a wave
of turbulent fluctuations on a rough background.
| physics.flu-dyn | we perform direct numerical simulations of three dimensional rayleightaylor turbulence with a nonuniform singular initial temperature background in such conditions the mixing layer evolves under the driving of a varying effective atwood number the longtime growth is still selfsimilar but not anymore proportional to t2 and depends on the singularity exponent c of the initial profile delta t propto zc we show that the universality is recovered when looking at the efficiency defined as the ratio of the variation rates of the kinetic energy over the heat flux a closure model is proposed that is able to reproduce analytically the time evolution of the mean temperature profiles in excellent agreement with the numerical results finally we reinterpret our findings in the light of spontaneous stochasticity where the growth of the mixing layer is mapped into the propagation of a wave of turbulent fluctuations on a rough background | [['we', 'perform', 'direct', 'numerical', 'simulations', 'of', 'three', 'dimensional', 'rayleightaylor', 'turbulence', 'with', 'a', 'nonuniform', 'singular', 'initial', 'temperature', 'background', 'in', 'such', 'conditions', 'the', 'mixing', 'layer', 'evolves', 'under', 'the', 'driving', 'of', 'a', 'varying', 'effective', 'atwood', 'number', 'the', 'longtime', 'growth', 'is', 'still', 'selfsimilar', 'but', 'not', 'anymore', 'proportional', 'to', 't2', 'and', 'depends', 'on', 'the', 'singularity', 'exponent', 'c', 'of', 'the', 'initial', 'profile', 'delta', 't', 'propto', 'zc', 'we', 'show', 'that', 'the', 'universality', 'is', 'recovered', 'when', 'looking', 'at', 'the', 'efficiency', 'defined', 'as', 'the', 'ratio', 'of', 'the', 'variation', 'rates', 'of', 'the', 'kinetic', 'energy', 'over', 'the', 'heat', 'flux', 'a', 'closure', 'model', 'is', 'proposed', 'that', 'is', 'able', 'to', 'reproduce', 'analytically', 'the', 'time', 'evolution', 'of', 'the', 'mean', 'temperature', 'profiles', 'in', 'excellent', 'agreement', 'with', 'the', 'numerical', 'results', 'finally', 'we', 'reinterpret', 'our', 'findings', 'in', 'the', 'light', 'of', 'spontaneous', 'stochasticity', 'where', 'the', 'growth', 'of', 'the', 'mixing', 'layer', 'is', 'mapped', 'into', 'the', 'propagation', 'of', 'a', 'wave', 'of', 'turbulent', 'fluctuations', 'on', 'a', 'rough', 'background']] | [-0.14207968456182807, 0.16601982225860362, -0.0878201223962123, 0.06234767788555473, -0.008529549050002302, -0.0934503113020997, 0.0257144251736958, 0.3247420986556784, -0.271748664034974, -0.2633916666845278, 0.08180098394708087, -0.2564283893435725, -0.08958230857868231, 0.19803454593729963, 0.006937490571860452, 0.045577325636432284, 0.020178080535633174, 0.028510686146336145, -0.07225908294516507, -0.2129604814377721, 0.31572644284619084, 0.08822218903980288, 0.3017312370012609, 0.06615948570982497, 0.08691241291548017, -0.07200292576186368, -0.019054885430983742, 0.04706042737095794, -0.18995177679662323, 0.008164933368288057, 0.14919657294074593, 0.05758917890172325, 0.21834000825349772, -0.40937774178578334, -0.25161562674381094, 0.08283012243760686, 0.15990122898044634, 0.07760063002557577, -0.03989810880105689, -0.21868971681545432, 0.06846666281415643, -0.12539357203058898, -0.1592341230463135, -0.011247259583704325, 0.029823418317020546, 0.051128562197301435, -0.31331355885925644, 0.14169524101200703, 0.04945391325318083, 0.024300288567382866, -0.07702449326352755, -0.05966446167776729, -0.08344788829238489, 0.10794590900475508, 0.08602918552235858, 0.03715223502874577, 0.14538141095149174, -0.1612862513350029, -0.02310966102558435, 0.3553408639597371, -0.12868483219706361, -0.20525681424480516, 0.18512670522505026, -0.18826000386794403, -0.07557433990913691, 0.15950356302212695, 0.1434659311915336, 0.09440038628325019, -0.07074895614433833, 0.08260091614939565, -0.04775624265599296, 0.18717067249017913, 0.052443010434761746, -0.026831738239434962, 0.17832027514762924, 0.19393827984597356, 0.040733215088645615, 0.12017855282118987, -0.10968105915813472, -0.12182830299447182, -0.33899813372210985, -0.12420315033166993, -0.17543265835752672, 0.08602949166329907, -0.12834390855861946, -0.16652273623823968, 0.40374843538643757, 0.15750386999709354, 0.22135305111961706, 0.07863135570755267, 0.27731641700656035, 0.1603981657872344, 0.03409114417376086, 0.09282974079314645, 0.23822828384787859, 0.15390364615386035, 0.1258895348679895, -0.2958054405884171, 0.07954017212297641, 0.028739691591587197] |
1,802.05022 | PyFml - a Textual Language For Feature Modeling | The Feature model is a typical approach to capture variability in a software
product line design and implementation. For that, most works automate feature
model using a limited graphical notation represented by propositional logic and
implemented by Prolog or Java programming languages. These works do not
properly combine the extensions of classical feature models and do not provide
scalability to implement large size problem issues. In this work, we propose a
textual feature modeling language based on Python programming language (PyFML),
that generalizes the classical feature models with instance feature
cardinalities and attributes which be extended with highlight of replication
and complex logical and mathematical cross-tree constraints. textX
Meta-language is used for building PyFML to describe and organize feature model
dependencies, and PyConstraint Problem Solver is used to implement feature
model variability and its constraints validation. The work provides a textual
human-readable language to represent feature model and maps the feature model
descriptions directly into the object-oriented representation to be used by
Constraint Problem Solver for computation. Furthermore, the proposed PyFML
makes the notation of feature modeling more expressive to deal with complex
software product line representations and using PyConstraint Problem Solver
| cs.SE | the feature model is a typical approach to capture variability in a software product line design and implementation for that most works automate feature model using a limited graphical notation represented by propositional logic and implemented by prolog or java programming languages these works do not properly combine the extensions of classical feature models and do not provide scalability to implement large size problem issues in this work we propose a textual feature modeling language based on python programming language pyfml that generalizes the classical feature models with instance feature cardinalities and attributes which be extended with highlight of replication and complex logical and mathematical crosstree constraints textx metalanguage is used for building pyfml to describe and organize feature model dependencies and pyconstraint problem solver is used to implement feature model variability and its constraints validation the work provides a textual humanreadable language to represent feature model and maps the feature model descriptions directly into the objectoriented representation to be used by constraint problem solver for computation furthermore the proposed pyfml makes the notation of feature modeling more expressive to deal with complex software product line representations and using pyconstraint problem solver | [['the', 'feature', 'model', 'is', 'a', 'typical', 'approach', 'to', 'capture', 'variability', 'in', 'a', 'software', 'product', 'line', 'design', 'and', 'implementation', 'for', 'that', 'most', 'works', 'automate', 'feature', 'model', 'using', 'a', 'limited', 'graphical', 'notation', 'represented', 'by', 'propositional', 'logic', 'and', 'implemented', 'by', 'prolog', 'or', 'java', 'programming', 'languages', 'these', 'works', 'do', 'not', 'properly', 'combine', 'the', 'extensions', 'of', 'classical', 'feature', 'models', 'and', 'do', 'not', 'provide', 'scalability', 'to', 'implement', 'large', 'size', 'problem', 'issues', 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1,802.05023 | Recursive Chaining of Reversible Image-to-image Translators For Face
Aging | This paper addresses the modeling and simulation of progressive changes over
time, such as human face aging. By treating the age phases as a sequence of
image domains, we construct a chain of transformers that map images from one
age domain to the next. Leveraging recent adversarial image translation
methods, our approach requires no training samples of the same individual at
different ages. Here, the model must be flexible enough to translate a child
face to a young adult, and all the way through the adulthood to old age. We
find that some transformers in the chain can be recursively applied on their
own output to cover multiple phases, compressing the chain. The structure of
the chain also unearths information about the underlying physical process. We
demonstrate the performance of our method with precise and intuitive metrics,
and visually match with the face aging state-of-the-art.
| cs.CV | this paper addresses the modeling and simulation of progressive changes over time such as human face aging by treating the age phases as a sequence of image domains we construct a chain of transformers that map images from one age domain to the next leveraging recent adversarial image translation methods our approach requires no training samples of the same individual at different ages here the model must be flexible enough to translate a child face to a young adult and all the way through the adulthood to old age we find that some transformers in the chain can be recursively applied on their own output to cover multiple phases compressing the chain the structure of the chain also unearths information about the underlying physical process we demonstrate the performance of our method with precise and intuitive metrics and visually match with the face aging stateoftheart | [['this', 'paper', 'addresses', 'the', 'modeling', 'and', 'simulation', 'of', 'progressive', 'changes', 'over', 'time', 'such', 'as', 'human', 'face', 'aging', 'by', 'treating', 'the', 'age', 'phases', 'as', 'a', 'sequence', 'of', 'image', 'domains', 'we', 'construct', 'a', 'chain', 'of', 'transformers', 'that', 'map', 'images', 'from', 'one', 'age', 'domain', 'to', 'the', 'next', 'leveraging', 'recent', 'adversarial', 'image', 'translation', 'methods', 'our', 'approach', 'requires', 'no', 'training', 'samples', 'of', 'the', 'same', 'individual', 'at', 'different', 'ages', 'here', 'the', 'model', 'must', 'be', 'flexible', 'enough', 'to', 'translate', 'a', 'child', 'face', 'to', 'a', 'young', 'adult', 'and', 'all', 'the', 'way', 'through', 'the', 'adulthood', 'to', 'old', 'age', 'we', 'find', 'that', 'some', 'transformers', 'in', 'the', 'chain', 'can', 'be', 'recursively', 'applied', 'on', 'their', 'own', 'output', 'to', 'cover', 'multiple', 'phases', 'compressing', 'the', 'chain', 'the', 'structure', 'of', 'the', 'chain', 'also', 'unearths', 'information', 'about', 'the', 'underlying', 'physical', 'process', 'we', 'demonstrate', 'the', 'performance', 'of', 'our', 'method', 'with', 'precise', 'and', 'intuitive', 'metrics', 'and', 'visually', 'match', 'with', 'the', 'face', 'aging', 'stateoftheart']] | [-0.037520735068567866, 0.07271994953846624, -0.09268566313809876, 0.05565884785917598, -0.0962601417707729, -0.10581748804141736, 0.060356361702775, 0.4602117203946771, -0.3079194754073075, -0.3213971984283677, 0.12162280884523202, -0.2506433643472927, -0.13940959064097241, 0.18765955613926052, -0.12688851744450372, 0.027775107662129248, 0.10911370377971566, 0.059476102758520125, -0.038604351379587475, -0.27018416018931773, 0.28864286455952015, 0.017900787138155308, 0.27856878455535605, -0.012781839059858486, 0.11636487982910255, -0.0324966345086758, -0.01664745088923594, 0.0002974241650823889, -0.08622491268234343, 0.1527757399166023, 0.26927802863125366, 0.1882738465411139, 0.26521390758229996, -0.4274368961566481, -0.21260349123642364, 0.08639969941678233, 0.15418186054789815, 0.13371018184156253, -0.04405114899132529, -0.3041453658827934, 0.10663388956755657, -0.1730292536727763, -0.05533066713411746, -0.05620769033015802, -0.015675478366781667, 0.013394847316346293, -0.24715963384851106, 0.04590462223156998, 0.07910923857145526, 0.09355220887488847, -0.07317895696434225, -0.1038161712106526, -0.016943267822779457, 0.23421761006566472, 0.053861889319197304, 0.04853582460802562, 0.14335826527776904, -0.15268281825099558, -0.10781999123764449, 0.34706469347122415, -0.030427277174874628, -0.17173738061482535, 0.22194166981197636, -0.10181758818076121, -0.11477569423551703, 0.09327946852667836, 0.16369818067338704, 0.10041474685843649, -0.17064453911975605, 0.0054404279144866195, -0.01700102419367638, 0.19668968327760952, 0.051302760068712566, -0.01810773232839359, 0.22475401196098918, 0.19549390150812165, 0.023901616512187595, 0.15887647800886168, -0.10622854617661154, -0.0750402159438918, -0.2261381606703849, -0.15364222416397313, -0.15061481964758372, 0.014165814040060122, -0.11672704234229529, -0.1707144920746314, 0.4380635091842249, 0.22263281038434923, 0.230205835318514, 0.1055476392972572, 0.3223720210251109, 0.017593983005218465, 0.11254557663863846, 0.04154598206795495, 0.12304322293192822, 0.04761610492774895, 0.09780877191123777, -0.19779690782668005, 0.1308903572799895, 0.019601859324130003] |
1,802.05024 | Totally non congruence Veech groups | Veech groups are discrete subgroups of SL(2, R) which play an important role
in the theory of translation surfaces. For a special class of translation
surfaces called origamis or square-tiled surfaces their Veech groups are
subgroups of finite index of SL(2, Z). We show that each stratum of the space
of translation surfaces contains infinitely many origamis whose Veech group is
a totally non congruence group, i.e. it surjects to SL(2, Z/nZ) for any n.
| math.GT | veech groups are discrete subgroups of sl2 r which play an important role in the theory of translation surfaces for a special class of translation surfaces called origamis or squaretiled surfaces their veech groups are subgroups of finite index of sl2 z we show that each stratum of the space of translation surfaces contains infinitely many origamis whose veech group is a totally non congruence group ie it surjects to sl2 znz for any n | [['veech', 'groups', 'are', 'discrete', 'subgroups', 'of', 'sl2', 'r', 'which', 'play', 'an', 'important', 'role', 'in', 'the', 'theory', 'of', 'translation', 'surfaces', 'for', 'a', 'special', 'class', 'of', 'translation', 'surfaces', 'called', 'origamis', 'or', 'squaretiled', 'surfaces', 'their', 'veech', 'groups', 'are', 'subgroups', 'of', 'finite', 'index', 'of', 'sl2', 'z', 'we', 'show', 'that', 'each', 'stratum', 'of', 'the', 'space', 'of', 'translation', 'surfaces', 'contains', 'infinitely', 'many', 'origamis', 'whose', 'veech', 'group', 'is', 'a', 'totally', 'non', 'congruence', 'group', 'ie', 'it', 'surjects', 'to', 'sl2', 'znz', 'for', 'any', 'n']] | [-0.24331044894332687, 0.15748367230815347, -0.13132242997487387, 0.06120382972837736, -0.09069514349102974, -0.183502015757064, -0.02295595118155082, 0.3819781157871087, -0.33539421012004217, -0.19754434195657572, 0.11220476081750046, -0.3095951218313227, -0.12439175001656015, 0.2546327114384621, -0.16292838180903346, -0.001059750293691953, 0.009904202098647754, 0.10979683679838975, -0.07159000194010635, -0.32414862121144933, 0.38025776044465603, -0.09697629260752971, 0.2519456430338323, -0.008873464241623878, 0.08856708829601606, 0.017597373792280754, 0.005580686752994855, -0.07585472259088419, -0.1025447339352104, 0.15081566583365202, 0.30837772123515605, -0.02488012800614039, 0.17034698993588487, -0.32699288374433916, -0.18291221737861632, 0.22307660070558388, 0.15178725494692724, -0.0030158291710540653, -0.07569407113517324, -0.24993630836407343, 0.07634778584043185, -0.15512968870500723, -0.17703044949720304, -0.06104441159715255, 0.11726316923896472, -0.03620907977223396, -0.11128037354598443, -0.01800634076197942, 0.16122807815670967, 0.22602982379496098, -0.021995406510929266, -0.09879797767847777, -0.11060367630794644, 0.18208767002138, 0.04896950793995832, 0.022668935502879323, 0.11503989055131872, -0.0718762564251665, -0.11510468824456135, 0.4641870550314585, -0.032633626187841096, -0.279794985242188, 0.1430689519214017, -0.17137800723314286, -0.288796108700335, 0.14952637283286702, 0.12208598556617896, 0.1409363777314623, -0.0007487929364045461, 0.2636171833549937, -0.18262565663705269, 0.09167897725477815, 0.11272737996031841, -0.0775082174129784, 0.13292921389763554, 0.03312336022034287, 0.059536517025747644, 0.09982948033759992, 0.05103692568062494, 0.03226879874865214, -0.3854027989010016, -0.288503538419803, -0.08181345024456581, 0.09251691023547513, -0.10862670044104258, -0.2763629115683337, 0.38410291862363616, -0.05968861650365094, 0.12255428174510598, 0.1323216443276033, 0.10416058391022186, -0.03795307011033098, 0.12202233062125742, 0.11612986555943887, 0.01899103537822763, 0.16578363998482626, -0.19722017589335641, -0.10767350002502402, -0.03487991162886222, 0.24289665845533212] |
1,802.05025 | Parity-Time Symmetry meets Photonics: A New Twist in non-Hermitian
Optics | In the past decade, the concept of parity-time ($\mathcal{PT}$) symmetry,
originally introduced in non-Hermitian extensions of quantum mechanical
theories, has come into thinking of photonics, providing a fertile ground for
studying, observing, and utilizing some of the peculiar aspects of
$\mathcal{PT}$ symmetry in optics. Together with related concepts of
non-Hermitian physics of open quantum systems, such as non-Hermitian
degeneracies (exceptional points) and spectral singularities, $\mathcal{PT}$
symmetry represents one among the most fruitful ideas introduced in optics in
the past few years. Judicious tailoring of optical gain and loss in integrated
photonic structures has emerged as a new paradigm in shaping the flow of light
in unprecedented ways, with major applications encompassing laser science and
technology, optical sensing, and optical material engineering. In this
perspective, I review some of the main achievements and emerging areas of
$\mathcal{PT}$-symmetric and non-Hermtian photonics, and provide an outline of
challenges and directions for future research in one of the fastest growing
research area of photonics.
| physics.optics quant-ph | in the past decade the concept of paritytime mathcalpt symmetry originally introduced in nonhermitian extensions of quantum mechanical theories has come into thinking of photonics providing a fertile ground for studying observing and utilizing some of the peculiar aspects of mathcalpt symmetry in optics together with related concepts of nonhermitian physics of open quantum systems such as nonhermitian degeneracies exceptional points and spectral singularities mathcalpt symmetry represents one among the most fruitful ideas introduced in optics in the past few years judicious tailoring of optical gain and loss in integrated photonic structures has emerged as a new paradigm in shaping the flow of light in unprecedented ways with major applications encompassing laser science and technology optical sensing and optical material engineering in this perspective i review some of the main achievements and emerging areas of mathcalptsymmetric and nonhermtian photonics and provide an outline of challenges and directions for future research in one of the fastest growing research area of photonics | [['in', 'the', 'past', 'decade', 'the', 'concept', 'of', 'paritytime', 'mathcalpt', 'symmetry', 'originally', 'introduced', 'in', 'nonhermitian', 'extensions', 'of', 'quantum', 'mechanical', 'theories', 'has', 'come', 'into', 'thinking', 'of', 'photonics', 'providing', 'a', 'fertile', 'ground', 'for', 'studying', 'observing', 'and', 'utilizing', 'some', 'of', 'the', 'peculiar', 'aspects', 'of', 'mathcalpt', 'symmetry', 'in', 'optics', 'together', 'with', 'related', 'concepts', 'of', 'nonhermitian', 'physics', 'of', 'open', 'quantum', 'systems', 'such', 'as', 'nonhermitian', 'degeneracies', 'exceptional', 'points', 'and', 'spectral', 'singularities', 'mathcalpt', 'symmetry', 'represents', 'one', 'among', 'the', 'most', 'fruitful', 'ideas', 'introduced', 'in', 'optics', 'in', 'the', 'past', 'few', 'years', 'judicious', 'tailoring', 'of', 'optical', 'gain', 'and', 'loss', 'in', 'integrated', 'photonic', 'structures', 'has', 'emerged', 'as', 'a', 'new', 'paradigm', 'in', 'shaping', 'the', 'flow', 'of', 'light', 'in', 'unprecedented', 'ways', 'with', 'major', 'applications', 'encompassing', 'laser', 'science', 'and', 'technology', 'optical', 'sensing', 'and', 'optical', 'material', 'engineering', 'in', 'this', 'perspective', 'i', 'review', 'some', 'of', 'the', 'main', 'achievements', 'and', 'emerging', 'areas', 'of', 'mathcalptsymmetric', 'and', 'nonhermtian', 'photonics', 'and', 'provide', 'an', 'outline', 'of', 'challenges', 'and', 'directions', 'for', 'future', 'research', 'in', 'one', 'of', 'the', 'fastest', 'growing', 'research', 'area', 'of', 'photonics']] | [-0.1282583356500254, 0.13668684921221938, -0.06334275592234917, -0.023178886847017566, -0.08744471059180796, -0.2058056256370037, -0.02266953791840933, 0.3932415973116804, -0.2615630675609282, -0.3034887930873083, 0.10322920491889817, -0.2727321009268053, -0.2106295708072139, 0.23740662777563556, -0.07340880281699355, 0.11188262819850933, -0.005880874322610907, -0.0710172365104654, -0.08808301357785239, -0.1853980406798655, 0.2645900132891256, 0.04109524229606905, 0.300237276032567, 0.07160483708721585, 0.08076045402849559, 0.04775141049176455, -0.033991754104499707, -0.0696353832463501, -0.11354550990490679, 0.20171872812206856, 0.3118701175262686, 0.12717286614351905, 0.3284367839980405, -0.4435086748097092, -0.2792877377651166, 0.06805824251787271, 0.16329862763232086, 0.12443633144430351, -0.14851474726983724, -0.32029172938782724, -0.02493324528222729, -0.15060344144294505, -0.2181019393785391, -0.04949501826922642, 0.042385342360648795, -0.009709104395005852, -0.1179715748221497, -0.034248586623289154, 0.05288652254239423, 0.13327973834311707, -0.01980141194508178, -0.10052449437207542, 0.022099588555283843, 0.09208165428135544, 0.014387618316686713, -0.017571864705678307, 0.09833309468012885, -0.17660510219138814, -0.19944014328648335, 0.43226968926610426, 0.04005488827824592, -0.06682768940809183, 0.16439337649499067, -0.11066878962810733, -0.1597441695208545, 0.06842261535930447, 0.18821760090067982, 0.02256121035570686, -0.12450011551054559, 0.11255059906652605, 0.030558213643962516, 0.0864427439570136, 0.07678915918513667, 0.1844972053761012, 0.2893848456296837, 0.21752670365967788, 0.07451508914818987, 0.12455795664573088, -0.011368820279312786, -0.15580668246257118, -0.2718401421778253, -0.17157704434066545, -0.17863699051667936, 0.05573065482749371, -0.049468117258857094, -0.1272441895416705, 0.46906181804370134, 0.14444817842158955, 0.1202885034319479, -0.12925850938336225, 0.25067342184775043, 0.07209040980815189, 0.11217196512734517, 0.012517404185928172, 0.2974380336851027, 0.18112687327693494, 0.16037768410751596, -0.15733521481161006, -0.05129362511797808, -0.01285504176048562] |
1,802.05026 | Directed cycles have the edge-Erd\H os-P\'osa property | In this short note we prove that for every $k\in \mathbb{N}$ there is a
$t_k\in\mathbb{N}$ such that for every digraph $G$ there are either $k$
edge-disjoint directed cycles in $G$ or a set $X$ of at most $t_k$ edges such
that $G-X$ contains no directed cycle.
| math.CO | in this short note we prove that for every kin mathbbn there is a t_kinmathbbn such that for every digraph g there are either k edgedisjoint directed cycles in g or a set x of at most t_k edges such that gx contains no directed cycle | [['in', 'this', 'short', 'note', 'we', 'prove', 'that', 'for', 'every', 'kin', 'mathbbn', 'there', 'is', 'a', 't_kinmathbbn', 'such', 'that', 'for', 'every', 'digraph', 'g', 'there', 'are', 'either', 'k', 'edgedisjoint', 'directed', 'cycles', 'in', 'g', 'or', 'a', 'set', 'x', 'of', 'at', 'most', 't_k', 'edges', 'such', 'that', 'gx', 'contains', 'no', 'directed', 'cycle']] | [-0.2776043695708116, 0.19856154101564447, -0.024809995759278537, -0.015047746669087146, -0.04705519721739822, -0.16240111173441013, 0.056677169269985624, 0.4851276738776101, -0.27226849590790353, -0.19311005179252888, 0.050137122673913834, -0.3975163930820094, -0.15441625874179105, 0.13579035967898864, -0.0713057708202137, -0.1151053707089482, 0.19324189157535632, 0.1783577953465283, 0.0872987661872887, -0.21280821826722887, 0.22774954995968275, -0.1665035103706436, 0.035063269175589086, 0.06686482364311815, 0.13147820124609602, 0.04354827501293686, 0.08322844834377369, 0.11162466076720091, -0.20393030579030488, -0.009184971948464711, 0.36764987053142656, 0.17427601646114554, 0.28542692073517373, -0.382013633447544, -0.21870351326134468, 0.34493902561565243, 0.08266332407171527, -0.030201364867389204, -0.00032008633327980834, -0.08914048526850012, 0.19143076528691583, -0.08336809372736348, -0.042160057183355096, 0.04792053534959753, 0.27857307597166964, -0.005089903043376075, -0.2963641174344553, -0.04506914185153114, 0.17784182478984198, 0.12325999784386821, 0.11281179962162342, -0.19684307540042534, -0.10810400138402151, 0.09563843695343369, -0.03592389913586279, 0.1919608295507108, -0.02497504240988443, -0.07455153836700548, -0.15295086755520768, 0.37604942586686874, -0.0745501917683416, -0.07829071277131637, 0.13927673664357926, -0.16264854091116124, -0.3000859565101564, 0.13888262667589718, 0.02703593209799793, 0.16635175024469692, -0.08567096476132671, 0.12470565643161535, -0.17418959513306617, 0.15442506083183818, 0.13396134410674373, -0.006284282338391576, 0.18635428350211847, 0.13053033381907475, 0.24012315807243187, 0.10604010274012883, 0.047691470301813546, 0.13465431183576584, -0.39039342328906057, -0.09218173617911007, -0.21924518128960496, 0.18055509859178628, -0.14405660443007945, -0.18662206770645248, 0.35913262748055985, 0.12556107433305846, 0.19602097049355507, 0.09425833446698056, 0.1545065653199951, 0.09331816175933151, 0.013399057320526077, 0.256646793283936, 0.03592078652646807, 0.11040051742974255, -0.03991814110842016, -0.1159510686269237, 0.04881432872886459, 0.12640187595453528] |
1,802.05027 | Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical
Care | Patients in the intensive care unit (ICU) require constant and close
supervision. To assist clinical staff in this task, hospitals use monitoring
systems that trigger audiovisual alarms if their algorithms indicate that a
patient's condition may be worsening. However, current monitoring systems are
extremely sensitive to movement artefacts and technical errors. As a result,
they typically trigger hundreds to thousands of false alarms per patient per
day - drowning the important alarms in noise and adding to the exhaustion of
clinical staff. In this setting, data is abundantly available, but obtaining
trustworthy annotations by experts is laborious and expensive. We frame the
problem of false alarm reduction from multivariate time series as a
machine-learning task and address it with a novel multitask network
architecture that utilises distant supervision through multiple related
auxiliary tasks in order to reduce the number of expensive labels required for
training. We show that our approach leads to significant improvements over
several state-of-the-art baselines on real-world ICU data and provide new
insights on the importance of task selection and architectural choices in
distantly supervised multitask learning.
| cs.LG cs.AI stat.ML | patients in the intensive care unit icu require constant and close supervision to assist clinical staff in this task hospitals use monitoring systems that trigger audiovisual alarms if their algorithms indicate that a patients condition may be worsening however current monitoring systems are extremely sensitive to movement artefacts and technical errors as a result they typically trigger hundreds to thousands of false alarms per patient per day drowning the important alarms in noise and adding to the exhaustion of clinical staff in this setting data is abundantly available but obtaining trustworthy annotations by experts is laborious and expensive we frame the problem of false alarm reduction from multivariate time series as a machinelearning task and address it with a novel multitask network architecture that utilises distant supervision through multiple related auxiliary tasks in order to reduce the number of expensive labels required for training we show that our approach leads to significant improvements over several stateoftheart baselines on realworld icu data and provide new insights on the importance of task selection and architectural choices in distantly supervised multitask learning | [['patients', 'in', 'the', 'intensive', 'care', 'unit', 'icu', 'require', 'constant', 'and', 'close', 'supervision', 'to', 'assist', 'clinical', 'staff', 'in', 'this', 'task', 'hospitals', 'use', 'monitoring', 'systems', 'that', 'trigger', 'audiovisual', 'alarms', 'if', 'their', 'algorithms', 'indicate', 'that', 'a', 'patients', 'condition', 'may', 'be', 'worsening', 'however', 'current', 'monitoring', 'systems', 'are', 'extremely', 'sensitive', 'to', 'movement', 'artefacts', 'and', 'technical', 'errors', 'as', 'a', 'result', 'they', 'typically', 'trigger', 'hundreds', 'to', 'thousands', 'of', 'false', 'alarms', 'per', 'patient', 'per', 'day', 'drowning', 'the', 'important', 'alarms', 'in', 'noise', 'and', 'adding', 'to', 'the', 'exhaustion', 'of', 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1,802.05028 | Inversions of synthetic umbral flashes: effects of the scanning time on
the inferred atmospheres | The use of instruments that record narrow band images at selected wavelengths
is a common approach in solar observations. They allow the scanning of a
spectral line by sampling the Stokes profiles with 2D images at each line
position, but require a compromise between spectral resolution and temporal
cadence. We evaluate the impact of the time-dependent acquisition of different
wavelengths on the inversion of spectropolarimetric profiles from chromospheric
lines during umbral flashes. Simulations of non-linear wave propagation in a
sunspot were performed with the code MANCHA. Synthetic Stokes parameters in the
Ca II 8542 A line in NLTE were computed for an umbral flash using the code
NICOLE. Artificial profiles with the same wavelength coverage and temporal
cadence from reported observations were constructed and inverted. The inferred
atmospheric stratifications were compared with the original models. The
inferred atmospheres provide a reasonable characterization of the thermodynamic
properties of the atmosphere during most of the phases of the umbral flash.
Only at the early stages of the flash, when the shock wave reaches the
formation height of the line, the Stokes profiles present apparent wavelength
shifts and other spurious deformations. These features are misinterpreted by
the inversion code, which can return unrealistic atmospheric models from a good
fit of the Stokes profiles. The misguided results include flashed atmospheres
with strong downflows, even though the simulation exhibits upflows during the
umbral flash, and large variations in the magnetic field strength. Our analyses
validate the inversion of Stokes profiles acquired by sequentially scanning
certain selected wavelengths of a line profile, even in the case of
rapidly-changing events such as umbral flashes. However, the inversions are
unreliable during a short period at the development phase of the flash.
| astro-ph.SR | the use of instruments that record narrow band images at selected wavelengths is a common approach in solar observations they allow the scanning of a spectral line by sampling the stokes profiles with 2d images at each line position but require a compromise between spectral resolution and temporal cadence we evaluate the impact of the timedependent acquisition of different wavelengths on the inversion of spectropolarimetric profiles from chromospheric lines during umbral flashes simulations of nonlinear wave propagation in a sunspot were performed with the code mancha synthetic stokes parameters in the ca ii 8542 a line in nlte were computed for an umbral flash using the code nicole artificial profiles with the same wavelength coverage and temporal cadence from reported observations were constructed and inverted the inferred atmospheric stratifications were compared with the original models the inferred atmospheres provide a reasonable characterization of the thermodynamic properties of the atmosphere during most of the phases of the umbral flash only at the early stages of the flash when the shock wave reaches the formation height of the line the stokes profiles present apparent wavelength shifts and other spurious deformations these features are misinterpreted by the inversion code which can return unrealistic atmospheric models from a good fit of the stokes profiles the misguided results include flashed atmospheres with strong downflows even though the simulation exhibits upflows during the umbral flash and large variations in the magnetic field strength our analyses validate the inversion of stokes profiles acquired by sequentially scanning certain selected wavelengths of a line profile even in the case of rapidlychanging events such as umbral flashes however the inversions are unreliable during a short period at the development phase of the flash | [['the', 'use', 'of', 'instruments', 'that', 'record', 'narrow', 'band', 'images', 'at', 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1,802.05029 | A co-located partitions strategy for parallel CFD-DEM couplings | In this work, a new partition-collocation strategy for the parallel execution
of CFD--DEM couplings is investigated. Having a good parallel performance is a
key issue for an Eulerian-Lagrangian software that aims to be applied to solve
industrially significant problems, as the computational cost of these couplings
is one of their main drawback. The approach presented here consists in
co-locating the overlapping parts of the simulation domain of each software on
the same MPI process, in order to reduce the cost of the data exchanges. It is
shown how this strategy allows reducing memory consumption and inter-process
communication between CFD and DEM to a minimum and therefore to overcome an
important parallelization bottleneck identified in the literature. Three
benchmarks are proposed to assess the consistency and scalability of this
approach. A coupled execution on 280 cores shows that less than 0.1% of the
time is used to perform inter-physics data exchange.
| cs.CE physics.comp-ph | in this work a new partitioncollocation strategy for the parallel execution of cfddem couplings is investigated having a good parallel performance is a key issue for an eulerianlagrangian software that aims to be applied to solve industrially significant problems as the computational cost of these couplings is one of their main drawback the approach presented here consists in colocating the overlapping parts of the simulation domain of each software on the same mpi process in order to reduce the cost of the data exchanges it is shown how this strategy allows reducing memory consumption and interprocess communication between cfd and dem to a minimum and therefore to overcome an important parallelization bottleneck identified in the literature three benchmarks are proposed to assess the consistency and scalability of this approach a coupled execution on 280 cores shows that less than 01 of the time is used to perform interphysics data exchange | [['in', 'this', 'work', 'a', 'new', 'partitioncollocation', 'strategy', 'for', 'the', 'parallel', 'execution', 'of', 'cfddem', 'couplings', 'is', 'investigated', 'having', 'a', 'good', 'parallel', 'performance', 'is', 'a', 'key', 'issue', 'for', 'an', 'eulerianlagrangian', 'software', 'that', 'aims', 'to', 'be', 'applied', 'to', 'solve', 'industrially', 'significant', 'problems', 'as', 'the', 'computational', 'cost', 'of', 'these', 'couplings', 'is', 'one', 'of', 'their', 'main', 'drawback', 'the', 'approach', 'presented', 'here', 'consists', 'in', 'colocating', 'the', 'overlapping', 'parts', 'of', 'the', 'simulation', 'domain', 'of', 'each', 'software', 'on', 'the', 'same', 'mpi', 'process', 'in', 'order', 'to', 'reduce', 'the', 'cost', 'of', 'the', 'data', 'exchanges', 'it', 'is', 'shown', 'how', 'this', 'strategy', 'allows', 'reducing', 'memory', 'consumption', 'and', 'interprocess', 'communication', 'between', 'cfd', 'and', 'dem', 'to', 'a', 'minimum', 'and', 'therefore', 'to', 'overcome', 'an', 'important', 'parallelization', 'bottleneck', 'identified', 'in', 'the', 'literature', 'three', 'benchmarks', 'are', 'proposed', 'to', 'assess', 'the', 'consistency', 'and', 'scalability', 'of', 'this', 'approach', 'a', 'coupled', 'execution', 'on', '280', 'cores', 'shows', 'that', 'less', 'than', '01', 'of', 'the', 'time', 'is', 'used', 'to', 'perform', 'interphysics', 'data', 'exchange']] | [-0.13143398230690886, 0.02268307270797605, -0.07014135248342378, 0.05463500872828435, -0.07221690343843924, -0.12708165630937326, 0.05186136342220109, 0.3850396740536608, -0.27811758849153145, -0.35700944488918457, 0.10228313532393626, -0.23866867198700453, -0.08810988799165431, 0.21339360447097067, -0.08690648093328786, 0.08186330032106992, 0.09759457230668615, -0.0018512080989878726, -0.014355883289386544, -0.28777515034056017, 0.2504169107933931, 0.09431490045500214, 0.3073829924152862, 0.07716606019027028, 0.09312776836245698, -0.05296141760914612, -0.04311870086805995, -0.005403212837975573, -0.06414197095580527, 0.1474457737058401, 0.28093203018746665, 0.13655135047156364, 0.338963482617023, -0.4322174068641018, -0.16943578025628184, 0.07068333567302623, 0.15058152071582595, 0.07332649988411749, -0.024169122550881945, -0.2027601706197586, 0.11946672384904043, -0.16493943392148092, -0.07466254339276536, -0.06581961427110473, -0.017197546637239488, -0.021649434014122833, -0.25321770020181666, 0.022535808979080536, 0.015922567667124944, 0.017682850461553882, -0.003963331906266535, -0.10222082911688532, 0.015511043146378486, 0.15344183698667818, 0.042036706259013214, 0.04047341362850086, 0.0943856252439169, -0.10858983483096282, -0.14576428241530634, 0.42148875241243355, -0.019308845804885465, -0.2157752485694112, 0.22670816435050722, -0.01697588013485074, -0.15137080702855177, 0.11527826522502142, 0.22044907212379306, 0.09470341610722244, -0.20048156495180888, 0.06447734505353445, 0.0474754059120912, 0.21351313866939195, 0.03831827046815306, -0.011187500122154283, 0.12883534405704564, 0.2511915678372355, 0.07776231519450005, 0.17335493917926215, -0.07328855463561627, -0.1348834246290042, -0.25966631733447415, -0.19434121530188397, -0.19437860274165114, -0.03594753206739001, -0.08225773583202485, -0.13993976092830496, 0.38658896732974696, 0.22995006279843683, 0.1450456226892719, 0.05633116824980322, 0.3731995333690901, 0.07124008502609827, 0.12611742999453437, 0.10271559311139926, 0.19373508289494124, 0.08245611788918944, 0.13250116428133804, -0.2646589751537839, 0.06947808386286015, -0.007110906926902464] |
1,802.0503 | Facebook Use of Sensitive Data for Advertising in Europe | The upcoming European General Data Protection Regulation (GDPR) prohibits the
processing and exploitation of some categories of personal data (health,
political orientation, sexual preferences, religious beliefs, ethnic origin,
etc.) due to the obvious privacy risks that may be derived from a malicious use
of such type of information. These categories are referred to as sensitive
personal data. Facebook has been recently fined EUR 1.2M in Spain for
collecting, storing and processing sensitive personal data for advertising
purposes. This paper quantifies the portion of Facebook users in the European
Union (EU) who are labeled with interests linked to sensitive personal data.
The results of our study reveal that Facebook labels 73% EU users with
sensitive interests. This corresponds to 40% of the overall EU population. We
also estimate that a malicious third-party could unveil the identity of
Facebook users that have been assigned a sensitive interest at a cost as low as
EUR 0.015 per user. Finally, we propose and implement a web browser extension
to inform Facebook users of the sensitive interests Facebook has assigned them.
| cs.SI cs.CY | the upcoming european general data protection regulation gdpr prohibits the processing and exploitation of some categories of personal data health political orientation sexual preferences religious beliefs ethnic origin etc due to the obvious privacy risks that may be derived from a malicious use of such type of information these categories are referred to as sensitive personal data facebook has been recently fined eur 12m in spain for collecting storing and processing sensitive personal data for advertising purposes this paper quantifies the portion of facebook users in the european union eu who are labeled with interests linked to sensitive personal data the results of our study reveal that facebook labels 73 eu users with sensitive interests this corresponds to 40 of the overall eu population we also estimate that a malicious thirdparty could unveil the identity of facebook users that have been assigned a sensitive interest at a cost as low as eur 0015 per user finally we propose and implement a web browser extension to inform facebook users of the sensitive interests facebook has assigned them | [['the', 'upcoming', 'european', 'general', 'data', 'protection', 'regulation', 'gdpr', 'prohibits', 'the', 'processing', 'and', 'exploitation', 'of', 'some', 'categories', 'of', 'personal', 'data', 'health', 'political', 'orientation', 'sexual', 'preferences', 'religious', 'beliefs', 'ethnic', 'origin', 'etc', 'due', 'to', 'the', 'obvious', 'privacy', 'risks', 'that', 'may', 'be', 'derived', 'from', 'a', 'malicious', 'use', 'of', 'such', 'type', 'of', 'information', 'these', 'categories', 'are', 'referred', 'to', 'as', 'sensitive', 'personal', 'data', 'facebook', 'has', 'been', 'recently', 'fined', 'eur', '12m', 'in', 'spain', 'for', 'collecting', 'storing', 'and', 'processing', 'sensitive', 'personal', 'data', 'for', 'advertising', 'purposes', 'this', 'paper', 'quantifies', 'the', 'portion', 'of', 'facebook', 'users', 'in', 'the', 'european', 'union', 'eu', 'who', 'are', 'labeled', 'with', 'interests', 'linked', 'to', 'sensitive', 'personal', 'data', 'the', 'results', 'of', 'our', 'study', 'reveal', 'that', 'facebook', 'labels', '73', 'eu', 'users', 'with', 'sensitive', 'interests', 'this', 'corresponds', 'to', '40', 'of', 'the', 'overall', 'eu', 'population', 'we', 'also', 'estimate', 'that', 'a', 'malicious', 'thirdparty', 'could', 'unveil', 'the', 'identity', 'of', 'facebook', 'users', 'that', 'have', 'been', 'assigned', 'a', 'sensitive', 'interest', 'at', 'a', 'cost', 'as', 'low', 'as', 'eur', '0015', 'per', 'user', 'finally', 'we', 'propose', 'and', 'implement', 'a', 'web', 'browser', 'extension', 'to', 'inform', 'facebook', 'users', 'of', 'the', 'sensitive', 'interests', 'facebook', 'has', 'assigned', 'them']] | [-0.09206088387873024, 0.024378350722227795, -0.01734576267666522, 0.12059517599184554, -0.20776187024073972, -0.1987080023635909, 0.13535722501546843, 0.37703254888765514, -0.23442262019538743, -0.3817133492663164, 0.09353758209181251, -0.4146532909706531, -0.13044535598237417, 0.15025078151533802, -0.17857954423313707, -0.058262656133923556, 0.05773244966423425, 0.07204779007059353, 0.05128904348814765, -0.31839461568345295, 0.27346822507851437, 0.09471588433106345, 0.3607747753849253, 0.07221682028929619, 0.028759648645725312, 0.005263744210506874, -0.11437860241064547, -0.008722751671236685, -0.10303992005306513, 0.15562793333744843, 0.3928099486828697, 0.24796826260386629, 0.38694136860695755, -0.39588948246620764, -0.13502622202081097, 0.0724868766827223, 0.08897015244557141, 0.05815240462834481, -0.06991478281402537, -0.3905624089476822, 0.09199347053601575, -0.26743860671889375, -0.08671586340642534, -0.06957187334906352, 0.041124291008930995, 0.0501423873044008, -0.2368826188242317, 0.019967079450824796, -0.06602195154350325, 0.15086166084405372, -0.0071598702639179964, -0.10176717037856262, -0.08477944389001509, 0.23833835459928113, 0.11143027351830494, -0.02449777774414873, 0.18832951680153862, -0.10290920896328647, -0.15218085384747776, 0.38885170448867773, 0.01540544055453872, -0.0928285384130008, 0.15347133286757692, -0.07022774374738881, -0.18163072564427488, 0.0611107422049496, 0.2571093376806278, 0.02857674288944426, -0.20091133744096046, 0.02158516814283344, -0.057812913627871734, 0.2047928490792401, 0.09179307845161847, 0.06542068231614064, 0.2113423203779596, 0.14037037238647992, 0.06909156850914852, 0.07004138667451282, -0.07648900876086952, -0.03949812082679604, -0.17347822868098525, -0.14269658209311523, -0.16469748020807112, 0.07048217284979975, -0.09233728207527747, -0.10489216465397146, 0.35923219280084595, 0.18348865849442186, 0.12826015976183539, -0.011602017351172188, 0.28385268749446946, -0.0423616227595961, 0.12283503656296736, 0.0965347093459224, 0.13250221327209807, -0.01170461470478172, 0.2448392758325843, -0.1235005094190869, 0.19699185622316276, -0.07454378473084944] |
1,802.05031 | Tackling Multilabel Imbalance through Label Decoupling and Data
Resampling Hybridization | The learning from imbalanced data is a deeply studied problem in standard
classification and, in recent times, also in multilabel classification. A
handful of multilabel resampling methods have been proposed in late years,
aiming to balance the labels distribution. However these methods have to face a
new obstacle, specific for multilabel data, as is the joint appearance of
minority and majority labels in the same data patterns. We proposed recently a
new algorithm designed to decouple imbalanced labels concurring in the same
instance, called REMEDIAL (\textit{REsampling MultilabEl datasets by Decoupling
highly ImbAlanced Labels}). The goal of this work is to propose a procedure to
hybridize this method with some of the best resampling algorithms available in
the literature, including random oversampling, heuristic undersampling and
synthetic sample generation techniques. These hybrid methods are then
empirically analyzed, determining how their behavior is influenced by the label
decoupling process. As a result, a noteworthy set of guidelines on the combined
use of these techniques can be drawn from the conducted experimentation.
| cs.LG | the learning from imbalanced data is a deeply studied problem in standard classification and in recent times also in multilabel classification a handful of multilabel resampling methods have been proposed in late years aiming to balance the labels distribution however these methods have to face a new obstacle specific for multilabel data as is the joint appearance of minority and majority labels in the same data patterns we proposed recently a new algorithm designed to decouple imbalanced labels concurring in the same instance called remedial textitresampling multilabel datasets by decoupling highly imbalanced labels the goal of this work is to propose a procedure to hybridize this method with some of the best resampling algorithms available in the literature including random oversampling heuristic undersampling and synthetic sample generation techniques these hybrid methods are then empirically analyzed determining how their behavior is influenced by the label decoupling process as a result a noteworthy set of guidelines on the combined use of these techniques can be drawn from the conducted experimentation | [['the', 'learning', 'from', 'imbalanced', 'data', 'is', 'a', 'deeply', 'studied', 'problem', 'in', 'standard', 'classification', 'and', 'in', 'recent', 'times', 'also', 'in', 'multilabel', 'classification', 'a', 'handful', 'of', 'multilabel', 'resampling', 'methods', 'have', 'been', 'proposed', 'in', 'late', 'years', 'aiming', 'to', 'balance', 'the', 'labels', 'distribution', 'however', 'these', 'methods', 'have', 'to', 'face', 'a', 'new', 'obstacle', 'specific', 'for', 'multilabel', 'data', 'as', 'is', 'the', 'joint', 'appearance', 'of', 'minority', 'and', 'majority', 'labels', 'in', 'the', 'same', 'data', 'patterns', 'we', 'proposed', 'recently', 'a', 'new', 'algorithm', 'designed', 'to', 'decouple', 'imbalanced', 'labels', 'concurring', 'in', 'the', 'same', 'instance', 'called', 'remedial', 'textitresampling', 'multilabel', 'datasets', 'by', 'decoupling', 'highly', 'imbalanced', 'labels', 'the', 'goal', 'of', 'this', 'work', 'is', 'to', 'propose', 'a', 'procedure', 'to', 'hybridize', 'this', 'method', 'with', 'some', 'of', 'the', 'best', 'resampling', 'algorithms', 'available', 'in', 'the', 'literature', 'including', 'random', 'oversampling', 'heuristic', 'undersampling', 'and', 'synthetic', 'sample', 'generation', 'techniques', 'these', 'hybrid', 'methods', 'are', 'then', 'empirically', 'analyzed', 'determining', 'how', 'their', 'behavior', 'is', 'influenced', 'by', 'the', 'label', 'decoupling', 'process', 'as', 'a', 'result', 'a', 'noteworthy', 'set', 'of', 'guidelines', 'on', 'the', 'combined', 'use', 'of', 'these', 'techniques', 'can', 'be', 'drawn', 'from', 'the', 'conducted', 'experimentation']] | [-0.02732776011766247, 0.04939595380139922, -0.06613369008530748, 0.08892931712188204, -0.1005650851122678, -0.15855014168177758, 0.08998976905501174, 0.43265230222019607, -0.253984029162229, -0.34125655431657315, 0.10401272817590124, -0.2661482921695549, -0.15347571565329046, 0.18075619218313319, -0.13659564466466625, 0.1071195656623312, 0.13780519620511136, 0.006406685757077115, -0.06216975169613244, -0.3222381411873858, 0.3235358733601567, 0.030983233690529525, 0.3738205058801317, -0.0007406294897957119, 0.07861441244095185, -0.03355218742313254, -0.06891917755888652, 0.030706309297953, -0.05435245079099909, 0.13868697177588069, 0.3118569785784818, 0.19802319368392488, 0.335119024086409, -0.37175081425441764, -0.22298218026021105, 0.10377318155812379, 0.15829544620585634, 0.14314140711970624, -0.08287675091843427, -0.31722984152907385, 0.09481113376569918, -0.15866266329728157, -0.006779834597432863, -0.11376008302430639, -0.01538052675440161, 0.012975881072067973, -0.2756984556194194, 0.0474802957940777, 0.057331318873633255, 0.048886055232745085, -0.055118994686953325, -0.1430713363691696, 0.04099309290996279, 0.1391720923812625, 0.07513405877834013, 0.029248447057060496, 0.07009396619828485, -0.16444013817347364, -0.17485221395614797, 0.3692907908775225, -0.030276692338555514, -0.208209928146056, 0.22521102805705573, -0.04778035098831811, -0.1804859887970288, 0.12665020170047164, 0.23865424414966283, 0.16256360439472123, -0.186807084399203, 0.014162437384181327, -0.061108391809943485, 0.1254635787886863, 0.020272875664766855, -0.03853343909572877, 0.15603115904691467, 0.23697366192936897, 0.016681188947875274, 0.1371716480283206, -0.1397835158333071, -0.058357617064953564, -0.20117283992268548, -0.07373310367626969, -0.23530431233993368, -0.028530540855177595, -0.07902302162996758, -0.14815890717649174, 0.3801600229173542, 0.22944973136619373, 0.24077370414833824, 0.03047435557257808, 0.3262681492163749, 0.06170363313371029, 0.11492163418446427, 0.06074140470511207, 0.18958653597817143, 0.051697474427543536, 0.09227549296198692, -0.18137920817812, 0.08487741305133116, 0.05184292005414065] |
1,802.05032 | The Interaction of Two Dyons in The Near Field Limit | We study the interaction of two dyons in the region of their cores where they
are non-linear and non-Abelian. We assume the superposition of two dyons as a
solution of the equation of motion. The terms due to the non-linearity of the
strength tensor are considered as the perturbation terms which deforms the
profile function of two individual dyons. As a result, the profile function of
dyons are obtained to be dependent on the polar angle and the spherical
symmetry is lost.
| hep-th | we study the interaction of two dyons in the region of their cores where they are nonlinear and nonabelian we assume the superposition of two dyons as a solution of the equation of motion the terms due to the nonlinearity of the strength tensor are considered as the perturbation terms which deforms the profile function of two individual dyons as a result the profile function of dyons are obtained to be dependent on the polar angle and the spherical symmetry is lost | [['we', 'study', 'the', 'interaction', 'of', 'two', 'dyons', 'in', 'the', 'region', 'of', 'their', 'cores', 'where', 'they', 'are', 'nonlinear', 'and', 'nonabelian', 'we', 'assume', 'the', 'superposition', 'of', 'two', 'dyons', 'as', 'a', 'solution', 'of', 'the', 'equation', 'of', 'motion', 'the', 'terms', 'due', 'to', 'the', 'nonlinearity', 'of', 'the', 'strength', 'tensor', 'are', 'considered', 'as', 'the', 'perturbation', 'terms', 'which', 'deforms', 'the', 'profile', 'function', 'of', 'two', 'individual', 'dyons', 'as', 'a', 'result', 'the', 'profile', 'function', 'of', 'dyons', 'are', 'obtained', 'to', 'be', 'dependent', 'on', 'the', 'polar', 'angle', 'and', 'the', 'spherical', 'symmetry', 'is', 'lost']] | [-0.17818228681231055, 0.1493551936682041, -0.07196538527382583, 0.06795866389775922, -0.048307926252075445, -0.0659933798810149, -0.031706146589230474, 0.317673413787128, -0.2455991267044915, -0.29697551451078275, 0.09065687205364201, -0.2702103216291928, -0.13823624914966343, 0.12396044056953454, 0.008645787621101523, 0.010171047922950692, -0.024351487265581766, 0.06940055720042437, -0.07362047553193052, -0.2176505414167101, 0.35694024981022243, -0.0237417191198868, 0.2697206074826238, 0.05678084000331781, 0.08403217019058945, -0.009571872492570703, 0.018695727439324666, 0.01628565391889069, -0.07361851875647539, 0.08699407454625499, 0.15681184897065822, 0.07632984951274788, 0.1913987063098608, -0.4527795003590787, -0.18791477264064113, 0.07573024165907466, 0.16566513553148182, 0.10566387339580305, -0.006388544097894848, -0.27483685460032486, 0.06709888079714757, -0.17011211499878456, -0.17641507842146406, -0.030650939667461123, 0.01839712383679864, 0.09665710968249364, -0.24756285535716793, 0.1196540771392969, 0.07969107704234264, 0.004735522097112929, -0.09850164565893753, -0.1105293793796857, -0.082594768598494, 0.13022349514677645, 0.12017569321537072, 0.020761811750850116, 0.14384042557539056, -0.20777659970562815, -0.04337009350292203, 0.40798360200189965, -0.06684764683610056, -0.2571064597222863, 0.14158514189170446, -0.13582494437819484, -0.05002983513560782, 0.09418791506394017, 0.152685626546239, 0.1603789222029197, -0.0929447683028695, 0.06931647124399272, -0.04567590077612095, 0.14437083686452087, 0.08772997927806545, 0.05798989934165303, 0.23348074774371413, 0.06039662302255903, 0.03115440227045882, 0.17873712208706932, -0.07561058561010968, -0.1308220636849178, -0.36297656601953615, -0.15309036420033564, -0.2017298289461107, 0.039989494775399204, -0.0888467264363809, -0.19564837705139526, 0.4275500698514828, 0.04390306398272514, 0.22018785258008325, 0.0009647813049235903, 0.22423450040017687, 0.17764664614692377, 0.0747476643740722, 0.010324042239339977, 0.27297855993142217, 0.18360713335810366, 0.08546079127913023, -0.2487981645702725, -0.005435470980024192, 0.09329617296050234] |
1,802.05033 | Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets | Multilabel classification is an emergent data mining task with a broad range
of real world applications. Learning from imbalanced multilabel data is being
deeply studied latterly, and several resampling methods have been proposed in
the literature. The unequal label distribution in most multilabel datasets,
with disparate imbalance levels, could be a handicap while learning new
classifiers. In addition, this characteristic challenges many of the existent
preprocessing algorithms. Furthermore, the concurrence between imbalanced
labels can make harder the learning from certain labels. These are what we call
\textit{difficult} labels. In this work, the problem of difficult labels is
deeply analyzed, its influence in multilabel classifiers is studied, and a
novel way to solve this problem is proposed. Specific metrics to assess this
trait in multilabel datasets, called \textit{SCUMBLE} (\textit{Score of
ConcUrrence among iMBalanced LabEls}) and \textit{SCUMBLELbl}, are presented
along with REMEDIAL (\textit{REsampling MultilabEl datasets by Decoupling
highly ImbAlanced Labels}), a new algorithm aimed to relax label concurrence.
How to deal with this problem using the R mldr package is also outlined.
| cs.LG | multilabel classification is an emergent data mining task with a broad range of real world applications learning from imbalanced multilabel data is being deeply studied latterly and several resampling methods have been proposed in the literature the unequal label distribution in most multilabel datasets with disparate imbalance levels could be a handicap while learning new classifiers in addition this characteristic challenges many of the existent preprocessing algorithms furthermore the concurrence between imbalanced labels can make harder the learning from certain labels these are what we call textitdifficult labels in this work the problem of difficult labels is deeply analyzed its influence in multilabel classifiers is studied and a novel way to solve this problem is proposed specific metrics to assess this trait in multilabel datasets called textitscumble textitscore of concurrence among imbalanced labels and textitscumblelbl are presented along with remedial textitresampling multilabel datasets by decoupling highly imbalanced labels a new algorithm aimed to relax label concurrence how to deal with this problem using the r mldr package is also outlined | [['multilabel', 'classification', 'is', 'an', 'emergent', 'data', 'mining', 'task', 'with', 'a', 'broad', 'range', 'of', 'real', 'world', 'applications', 'learning', 'from', 'imbalanced', 'multilabel', 'data', 'is', 'being', 'deeply', 'studied', 'latterly', 'and', 'several', 'resampling', 'methods', 'have', 'been', 'proposed', 'in', 'the', 'literature', 'the', 'unequal', 'label', 'distribution', 'in', 'most', 'multilabel', 'datasets', 'with', 'disparate', 'imbalance', 'levels', 'could', 'be', 'a', 'handicap', 'while', 'learning', 'new', 'classifiers', 'in', 'addition', 'this', 'characteristic', 'challenges', 'many', 'of', 'the', 'existent', 'preprocessing', 'algorithms', 'furthermore', 'the', 'concurrence', 'between', 'imbalanced', 'labels', 'can', 'make', 'harder', 'the', 'learning', 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0.09883910268488363, 0.010108300737423323] |
1,802.05034 | Cometary impactors on the TRAPPIST-1 planets can destroy all planetary
atmospheres and rebuild secondary atmospheres on planets f, g, h | The TRAPPIST-1 system is unique in that it has a chain of seven terrestrial
Earth-like planets located close to or in its habitable zone. In this paper, we
study the effect of potential cometary impacts on the TRAPPIST-1 planets and
how they would affect the primordial atmospheres of these planets. We consider
both atmospheric mass loss and volatile delivery with a view to assessing
whether any sort of life has a chance to develop. We ran N-body simulations to
investigate the orbital evolution of potential impacting comets, to determine
which planets are more likely to be impacted and the distributions of impact
velocities. We consider three scenarios that could potentially throw comets
into the inner region (i.e within 0.1au where the seven planets are located)
from an (as yet undetected) outer belt similar to the Kuiper belt or an Oort
cloud: Planet scattering, the Kozai-Lidov mechanism and Galactic tides. For the
different scenarios, we quantify, for each planet, how much atmospheric mass is
lost and what mass of volatiles can be delivered over the age of the system
depending on the mass scattered out of the outer belt. We find that the
resulting high velocity impacts can easily destroy the primordial atmospheres
of all seven planets, even if the mass scattered from the outer belt is as low
as that of the Kuiper belt. However, we find that the atmospheres of the
outermost planets f, g and h can also easily be replenished with cometary
volatiles (e.g. $\sim$ an Earth ocean mass of water could be delivered). These
scenarios would thus imply that the atmospheres of these outermost planets
could be more massive than those of the innermost planets, and have
volatiles-enriched composition.
| astro-ph.EP | the trappist1 system is unique in that it has a chain of seven terrestrial earthlike planets located close to or in its habitable zone in this paper we study the effect of potential cometary impacts on the trappist1 planets and how they would affect the primordial atmospheres of these planets we consider both atmospheric mass loss and volatile delivery with a view to assessing whether any sort of life has a chance to develop we ran nbody simulations to investigate the orbital evolution of potential impacting comets to determine which planets are more likely to be impacted and the distributions of impact velocities we consider three scenarios that could potentially throw comets into the inner region ie within 01au where the seven planets are located from an as yet undetected outer belt similar to the kuiper belt or an oort cloud planet scattering the kozailidov mechanism and galactic tides for the different scenarios we quantify for each planet how much atmospheric mass is lost and what mass of volatiles can be delivered over the age of the system depending on the mass scattered out of the outer belt we find that the resulting high velocity impacts can easily destroy the primordial atmospheres of all seven planets even if the mass scattered from the outer belt is as low as that of the kuiper belt however we find that the atmospheres of the outermost planets f g and h can also easily be replenished with cometary volatiles eg sim an earth ocean mass of water could be delivered these scenarios would thus imply that the atmospheres of these outermost planets could be more massive than those of the innermost planets and have volatilesenriched composition | [['the', 'trappist1', 'system', 'is', 'unique', 'in', 'that', 'it', 'has', 'a', 'chain', 'of', 'seven', 'terrestrial', 'earthlike', 'planets', 'located', 'close', 'to', 'or', 'in', 'its', 'habitable', 'zone', 'in', 'this', 'paper', 'we', 'study', 'the', 'effect', 'of', 'potential', 'cometary', 'impacts', 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1,802.05035 | Nonnegative PARAFAC2: a flexible coupling approach | Modeling variability in tensor decomposition methods is one of the challenges
of source separation. One possible solution to account for variations from one
data set to another, jointly analysed, is to resort to the PARAFAC2 model.
However, so far imposing constraints on the mode with variability has not been
possible. In the following manuscript, a relaxation of the PARAFAC2 model is
introduced, that allows for imposing nonnegativity constraints on the varying
mode. An algorithm to compute the proposed flexible PARAFAC2 model is derived,
and its performance is studied on both synthetic and chemometrics data.
| stat.ML | modeling variability in tensor decomposition methods is one of the challenges of source separation one possible solution to account for variations from one data set to another jointly analysed is to resort to the parafac2 model however so far imposing constraints on the mode with variability has not been possible in the following manuscript a relaxation of the parafac2 model is introduced that allows for imposing nonnegativity constraints on the varying mode an algorithm to compute the proposed flexible parafac2 model is derived and its performance is studied on both synthetic and chemometrics data | [['modeling', 'variability', 'in', 'tensor', 'decomposition', 'methods', 'is', 'one', 'of', 'the', 'challenges', 'of', 'source', 'separation', 'one', 'possible', 'solution', 'to', 'account', 'for', 'variations', 'from', 'one', 'data', 'set', 'to', 'another', 'jointly', 'analysed', 'is', 'to', 'resort', 'to', 'the', 'parafac2', 'model', 'however', 'so', 'far', 'imposing', 'constraints', 'on', 'the', 'mode', 'with', 'variability', 'has', 'not', 'been', 'possible', 'in', 'the', 'following', 'manuscript', 'a', 'relaxation', 'of', 'the', 'parafac2', 'model', 'is', 'introduced', 'that', 'allows', 'for', 'imposing', 'nonnegativity', 'constraints', 'on', 'the', 'varying', 'mode', 'an', 'algorithm', 'to', 'compute', 'the', 'proposed', 'flexible', 'parafac2', 'model', 'is', 'derived', 'and', 'its', 'performance', 'is', 'studied', 'on', 'both', 'synthetic', 'and', 'chemometrics', 'data']] | [-0.06718942590374896, -0.009034055476962401, -0.10526956100650925, 0.057118986684957795, -0.1393698972570611, -0.15986618979219744, 0.016037369176666153, 0.3772398108973148, -0.280915667065122, -0.3180174110655455, 0.14632679901254225, -0.2549473572390196, -0.10975332354056708, 0.1857588479736265, -0.08070734049134115, 0.07406547666524854, 0.056392677099830375, 0.01734964044249438, -0.037304001045413315, -0.23092257578242967, 0.29220806254678344, 0.07345263229960457, 0.3146206860930877, 0.05430432342666578, 0.14330414514443737, -0.02535925477128872, -0.04019105546374587, 0.02704211823800777, -0.08540642430222199, 0.1190788878147748, 0.18032363842816113, 0.19712381995471312, 0.24898536112952105, -0.4196557067929113, -0.2524537710928695, 0.1023068816321803, 0.11788904174488593, 0.09523924564486964, 0.01046209511634438, -0.23898170038344377, 0.0910440226719576, -0.13771724352177153, -0.0704676302873153, -0.09737114919389182, 0.0383615633670954, -0.05292069397376296, -0.3067139652111825, 0.03924155058190623, 0.039134023909239056, 0.011840939828927846, -0.10662931614206173, -0.11550090992030629, -0.013459206199610328, 0.12913363107400846, 0.1014933264950548, 0.022692177400111833, 0.06750562569829932, -0.10512553721151137, -0.10169758897353993, 0.4055076184127718, -0.058464095154975325, -0.2474941302987529, 0.1895076680787284, -0.061316160514871494, -0.17280432859316786, 0.12275954013928136, 0.15929009936541874, 0.10814473985080073, -0.20258926411971767, 0.08007801363636007, -0.007017079820024206, 0.18391514002801257, 0.021210147642550317, -0.001704852012521092, 0.1553234892892354, 0.20152324270655184, 0.05536398993547451, 0.1464341668303105, -0.11910350686385039, -0.08970556277013879, -0.22615761768588044, -0.06510045160440371, -0.20428488437430636, -0.026983484350723223, -0.04587410163460052, -0.12945018580896742, 0.4223074576758007, 0.1639290384333977, 0.18952072381123683, 0.03848820645857523, 0.34762656774143985, 0.1250204941782013, 0.1000090318910302, 0.04404832726403912, 0.2574049694763318, 0.1289421693332731, 0.08114269938371937, -0.20935745263581185, 0.10650825853201937, 0.021191363807450583] |
1,802.05036 | Robust Continuous Co-Clustering | Clustering consists of grouping together samples giving their similar
properties. The problem of modeling simultaneously groups of samples and
features is known as Co-Clustering. This paper introduces ROCCO - a Robust
Continuous Co-Clustering algorithm. ROCCO is a scalable, hyperparameter-free,
easy and ready to use algorithm to address Co-Clustering problems in practice
over massive cross-domain datasets. It operates by learning a graph-based
two-sided representation of the input matrix. The underlying proposed
optimization problem is non-convex, which assures a flexible pool of solutions.
Moreover, we prove that it can be solved with a near linear time complexity on
the input size. An exhaustive large-scale experimental testbed conducted with
both synthetic and real-world datasets demonstrates ROCCO's properties in
practice: (i) State-of-the-art performance in cross-domain real-world problems
including Biomedicine and Text Mining; (ii) very low sensitivity to
hyperparameter settings; (iii) robustness to noise and (iv) a linear empirical
scalability in practice. These results highlight ROCCO as a powerful
general-purpose co-clustering algorithm for cross-domain practitioners,
regardless of their technical background.
| cs.LG stat.ML | clustering consists of grouping together samples giving their similar properties the problem of modeling simultaneously groups of samples and features is known as coclustering this paper introduces rocco a robust continuous coclustering algorithm rocco is a scalable hyperparameterfree easy and ready to use algorithm to address coclustering problems in practice over massive crossdomain datasets it operates by learning a graphbased twosided representation of the input matrix the underlying proposed optimization problem is nonconvex which assures a flexible pool of solutions moreover we prove that it can be solved with a near linear time complexity on the input size an exhaustive largescale experimental testbed conducted with both synthetic and realworld datasets demonstrates roccos properties in practice i stateoftheart performance in crossdomain realworld problems including biomedicine and text mining ii very low sensitivity to hyperparameter settings iii robustness to noise and iv a linear empirical scalability in practice these results highlight rocco as a powerful generalpurpose coclustering algorithm for crossdomain practitioners regardless of their technical background | [['clustering', 'consists', 'of', 'grouping', 'together', 'samples', 'giving', 'their', 'similar', 'properties', 'the', 'problem', 'of', 'modeling', 'simultaneously', 'groups', 'of', 'samples', 'and', 'features', 'is', 'known', 'as', 'coclustering', 'this', 'paper', 'introduces', 'rocco', 'a', 'robust', 'continuous', 'coclustering', 'algorithm', 'rocco', 'is', 'a', 'scalable', 'hyperparameterfree', 'easy', 'and', 'ready', 'to', 'use', 'algorithm', 'to', 'address', 'coclustering', 'problems', 'in', 'practice', 'over', 'massive', 'crossdomain', 'datasets', 'it', 'operates', 'by', 'learning', 'a', 'graphbased', 'twosided', 'representation', 'of', 'the', 'input', 'matrix', 'the', 'underlying', 'proposed', 'optimization', 'problem', 'is', 'nonconvex', 'which', 'assures', 'a', 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1,802.05037 | Semiprojectivity and semiinjectivity in different categories | Projectivity and injectivity are fundamental notions in category theory. We
consider natural weakenings termed semiprojectivity and semiinjectivity, and
study these concepts in different categories.
For example, in the category of metric spaces, (semi)injective objects are
precisely the absolute (neighborhood) retracts. We show that the trivial group
is the only semiinjective group, while every free product of a finitely
presented group and a free group is semiprojective.
To a compact, metric space $X$ we associate the commutative C*-algebra
$C(X)$. This association is contravariant, whence semiinjectivity of $X$ is
related to semiprojectivity of $C(X)$. Together with Adam S{\o}rensen, we
showed that $C(X)$ is semiprojective in the category of all C*-algebras if and
only if $X$ is an absolute neighborhood retract with dimension at most one.
| math.CT math.GN math.GR math.OA | projectivity and injectivity are fundamental notions in category theory we consider natural weakenings termed semiprojectivity and semiinjectivity and study these concepts in different categories for example in the category of metric spaces semiinjective objects are precisely the absolute neighborhood retracts we show that the trivial group is the only semiinjective group while every free product of a finitely presented group and a free group is semiprojective to a compact metric space x we associate the commutative calgebra cx this association is contravariant whence semiinjectivity of x is related to semiprojectivity of cx together with adam sorensen we showed that cx is semiprojective in the category of all calgebras if and only if x is an absolute neighborhood retract with dimension at most one | [['projectivity', 'and', 'injectivity', 'are', 'fundamental', 'notions', 'in', 'category', 'theory', 'we', 'consider', 'natural', 'weakenings', 'termed', 'semiprojectivity', 'and', 'semiinjectivity', 'and', 'study', 'these', 'concepts', 'in', 'different', 'categories', 'for', 'example', 'in', 'the', 'category', 'of', 'metric', 'spaces', 'semiinjective', 'objects', 'are', 'precisely', 'the', 'absolute', 'neighborhood', 'retracts', 'we', 'show', 'that', 'the', 'trivial', 'group', 'is', 'the', 'only', 'semiinjective', 'group', 'while', 'every', 'free', 'product', 'of', 'a', 'finitely', 'presented', 'group', 'and', 'a', 'free', 'group', 'is', 'semiprojective', 'to', 'a', 'compact', 'metric', 'space', 'x', 'we', 'associate', 'the', 'commutative', 'calgebra', 'cx', 'this', 'association', 'is', 'contravariant', 'whence', 'semiinjectivity', 'of', 'x', 'is', 'related', 'to', 'semiprojectivity', 'of', 'cx', 'together', 'with', 'adam', 'sorensen', 'we', 'showed', 'that', 'cx', 'is', 'semiprojective', 'in', 'the', 'category', 'of', 'all', 'calgebras', 'if', 'and', 'only', 'if', 'x', 'is', 'an', 'absolute', 'neighborhood', 'retract', 'with', 'dimension', 'at', 'most', 'one']] | [-0.1459240147974804, 0.09565755393279597, -0.08452488408493232, 0.08484709670878793, -0.09494227194804544, -0.14248627536229727, -0.021216978108287165, 0.44033554057813873, -0.38816332812170873, -0.1662026079542827, 0.09247916393474606, -0.28246535603264883, -0.11469594258738082, 0.1653858015298351, -0.2174444462380503, -0.08872947722099998, 0.0708324780864718, 0.19255964288657362, -0.08740994585524044, -0.24690015546492616, 0.45685285280943533, -0.05100854286108135, 0.20536948101641225, 0.01304326599756302, 0.1289896294590055, -0.002867184144498642, -0.011902219346485847, 0.04408484141987918, -0.13132335199199496, 0.12598711137913846, 0.29770514179282814, 0.10272970146207093, 0.23989981557877565, -0.3053975853602852, -0.14059711466273986, 0.20124750191438173, 0.057291747686599406, -0.0504671745502567, -0.010730313866453107, -0.2829099979236229, 0.15152147641859579, -0.20188902429312713, -0.07610842892669203, -0.0877253352192977, 0.13117746075938555, -0.020373672395578992, -0.2270669917583712, -0.03357228706013565, 0.09023195988506325, 0.09542520218798198, -0.09892153496900188, -0.06925423277064788, -0.09217970104010637, 0.11317428996043727, -0.02016339122898846, 0.08184923093250283, 0.135154193212867, -0.06286606722326626, -0.0952045766074857, 0.38312755413892224, -0.04738277619827754, -0.20314088828615412, 0.20066763787753572, -0.20819813390993627, -0.1912052256463111, 0.10893594872298812, 0.019215325463162965, 0.1717632375426652, -0.019618427096134868, 0.2259311099658905, -0.15500054809395686, 0.1170450798264697, 0.04189115765019635, 0.04512517143633555, 0.08787087897369869, 0.11821420931003311, 0.0977397307230175, 0.10303264782448446, 0.04204567577612917, 0.009228687447184036, -0.360180706647802, -0.21809788910318012, -0.08842043678395542, 0.11625830933628681, -0.0743392872048517, -0.16283812069849782, 0.3470007070871301, 0.09539225281885833, 0.1493973983913537, 0.08502360909199727, 0.21642835735158672, 0.013148649739994368, 0.02538696694965205, 0.07980138195143659, 0.14927906228983698, 0.2304363723320902, -0.05363014356756567, -0.07149874417434547, -0.005397077569014524, 0.224395881914957] |
1,802.05038 | Motion of interfaces for a damped hyperbolic Allen-Cahn equation | Consider the Allen-Cahn equation $u_t=\varepsilon^2\Delta u-F'(u)$, where $F$
is a double well potential with wells of equal depth, located at $\pm1$. There
are a lot of papers devoted to the study of the limiting behavior of the
solutions as the diffusion coefficient $\varepsilon\to0^+$, and it is well
known that, if the initial datum $u(\cdot,0)$ takes the values $+1$ and $-1$ in
the regions $\Omega_+$ and $\Omega_-$, then the "interface" connecting
$\Omega_+$ and $\Omega_-$ moves with normal velocity equal to the sum of its
principal curvatures, i.e. the interface moves by mean curvature flow.
This paper concerns with the motion of the inteface for a damped hyperbolic
Allen-Cahn equation, in a bounded domain of $\mathbb{R}^n$, for $n=2$ or $n=3$.
In particular, we focus the attention on radially simmetric solutions, studying
in detail the differences with the classic parabolic case, and we prove that,
under appropriate assumptions on the initial data $u(\cdot,0)$ and
$u_t(\cdot,0)$, the interface moves by mean curvature as $\varepsilon\to0^+$
also in the hyperbolic framework.
| math.AP | consider the allencahn equation u_tvarepsilon2delta ufu where f is a double well potential with wells of equal depth located at pm1 there are a lot of papers devoted to the study of the limiting behavior of the solutions as the diffusion coefficient varepsilonto0 and it is well known that if the initial datum ucdot0 takes the values 1 and 1 in the regions omega_ and omega_ then the interface connecting omega_ and omega_ moves with normal velocity equal to the sum of its principal curvatures ie the interface moves by mean curvature flow this paper concerns with the motion of the inteface for a damped hyperbolic allencahn equation in a bounded domain of mathbbrn for n2 or n3 in particular we focus the attention on radially simmetric solutions studying in detail the differences with the classic parabolic case and we prove that under appropriate assumptions on the initial data ucdot0 and u_tcdot0 the interface moves by mean curvature as varepsilonto0 also in the hyperbolic framework | [['consider', 'the', 'allencahn', 'equation', 'u_tvarepsilon2delta', 'ufu', 'where', 'f', 'is', 'a', 'double', 'well', 'potential', 'with', 'wells', 'of', 'equal', 'depth', 'located', 'at', 'pm1', 'there', 'are', 'a', 'lot', 'of', 'papers', 'devoted', 'to', 'the', 'study', 'of', 'the', 'limiting', 'behavior', 'of', 'the', 'solutions', 'as', 'the', 'diffusion', 'coefficient', 'varepsilonto0', 'and', 'it', 'is', 'well', 'known', 'that', 'if', 'the', 'initial', 'datum', 'ucdot0', 'takes', 'the', 'values', '1', 'and', '1', 'in', 'the', 'regions', 'omega_', 'and', 'omega_', 'then', 'the', 'interface', 'connecting', 'omega_', 'and', 'omega_', 'moves', 'with', 'normal', 'velocity', 'equal', 'to', 'the', 'sum', 'of', 'its', 'principal', 'curvatures', 'ie', 'the', 'interface', 'moves', 'by', 'mean', 'curvature', 'flow', 'this', 'paper', 'concerns', 'with', 'the', 'motion', 'of', 'the', 'inteface', 'for', 'a', 'damped', 'hyperbolic', 'allencahn', 'equation', 'in', 'a', 'bounded', 'domain', 'of', 'mathbbrn', 'for', 'n2', 'or', 'n3', 'in', 'particular', 'we', 'focus', 'the', 'attention', 'on', 'radially', 'simmetric', 'solutions', 'studying', 'in', 'detail', 'the', 'differences', 'with', 'the', 'classic', 'parabolic', 'case', 'and', 'we', 'prove', 'that', 'under', 'appropriate', 'assumptions', 'on', 'the', 'initial', 'data', 'ucdot0', 'and', 'u_tcdot0', 'the', 'interface', 'moves', 'by', 'mean', 'curvature', 'as', 'varepsilonto0', 'also', 'in', 'the', 'hyperbolic', 'framework']] | [-0.14310512283921056, 0.10641774169591643, -0.039610512817845396, 0.023019098563218106, -0.04829105952037325, -0.1512526426990719, -0.00645910251975314, 0.32200317989502636, -0.2896732239526992, -0.22710704008661073, 0.1392398324168883, -0.321067278834511, -0.12359723358730329, 0.1616087596189601, -0.04606552550681976, 0.038665907739922664, 0.026957178433781478, 0.09422167173372756, -0.04182935493957737, -0.18078625566464912, 0.3755162590478333, -0.05625731240009299, 0.23696068920895041, 0.05067173304196783, 0.11078095821640599, -0.015745680015649854, 0.022471278191468914, 0.027658284670725373, -0.2294396583099527, 0.08239132694622374, 0.1870526568588124, 0.02307890543008443, 0.30033855937618, -0.38626982215560557, -0.19504930924115157, 0.1050926659795635, 0.15057811137832564, 0.03449014102264961, -0.03254245268542505, -0.2838568652658984, 0.06939822495972842, -0.07908006923299236, -0.19875166016220122, 0.03149768033806778, 0.06862386693506971, 0.07098846581492642, -0.25113713610425636, 0.1201751319594285, 0.10033964120597805, 0.03218268045449849, -0.09702358285748973, -0.1254487230835818, -0.0704756420212711, 0.10500811291598246, 0.09192436064017925, 0.05477136668535123, 0.08050170207380965, -0.1403508652421004, -0.023987495982498858, 0.39051093507025925, -0.1093192716354724, -0.27789981424901056, 0.13496840408256983, -0.1867644877016822, -0.07277875903831876, 0.09388271263968315, 0.14356349016429845, 0.14128386859799394, -0.07193963549545278, 0.15276003971201316, -0.028630842726608242, 0.1192205004966731, 0.11353464612610037, -0.05091951638228775, 0.13945972857424144, 0.13070629881723836, 0.13142417731654385, 0.14206546552837912, -0.08019882595305394, -0.10550500447312312, -0.34300681344748285, -0.1736636353961788, -0.15838558217134582, 0.067611319608755, -0.08949249178718527, -0.1782329490933255, 0.377525260764527, 0.0734803573060665, 0.20516804589236282, 0.07907255147786243, 0.264545130413257, 0.14605014133831104, 0.0017549373087999613, 0.11056396450687588, 0.19654760952396838, 0.14280589636102875, 0.1198477997511093, -0.19382190831824095, 0.014139969141934043, 0.06686751841542511] |
1,802.05039 | Super-blockers and the effect of network structure on information
cascades | Modelling information cascades over online social networks is important in
fields from marketing to civil unrest prediction, however the underlying
network structure strongly affects the probability and nature of such cascades.
Even with simple cascade dynamics the probability of large cascades are almost
entirely dictated by network properties, with well-known networks such as
Erdos-Renyi and Barabasi-Albert producing wildly different cascades from the
same model. Indeed, the notion of 'superspreaders' has arisen to describe
highly influential nodes promoting global cascades in a social network. Here we
use a simple model of global cascades to show that the presence of locality in
the network increases the probability of a global cascade due to the increased
vulnerability of connecting nodes. Rather than 'super-spreaders', we find that
the presence of these highly connected 'super-blockers' in heavy-tailed
networks in fact reduces the probability of global cascades, while promoting
information spread when targeted as the initial spreader.
| cs.SI physics.data-an physics.soc-ph | modelling information cascades over online social networks is important in fields from marketing to civil unrest prediction however the underlying network structure strongly affects the probability and nature of such cascades even with simple cascade dynamics the probability of large cascades are almost entirely dictated by network properties with wellknown networks such as erdosrenyi and barabasialbert producing wildly different cascades from the same model indeed the notion of superspreaders has arisen to describe highly influential nodes promoting global cascades in a social network here we use a simple model of global cascades to show that the presence of locality in the network increases the probability of a global cascade due to the increased vulnerability of connecting nodes rather than superspreaders we find that the presence of these highly connected superblockers in heavytailed networks in fact reduces the probability of global cascades while promoting information spread when targeted as the initial spreader | [['modelling', 'information', 'cascades', 'over', 'online', 'social', 'networks', 'is', 'important', 'in', 'fields', 'from', 'marketing', 'to', 'civil', 'unrest', 'prediction', 'however', 'the', 'underlying', 'network', 'structure', 'strongly', 'affects', 'the', 'probability', 'and', 'nature', 'of', 'such', 'cascades', 'even', 'with', 'simple', 'cascade', 'dynamics', 'the', 'probability', 'of', 'large', 'cascades', 'are', 'almost', 'entirely', 'dictated', 'by', 'network', 'properties', 'with', 'wellknown', 'networks', 'such', 'as', 'erdosrenyi', 'and', 'barabasialbert', 'producing', 'wildly', 'different', 'cascades', 'from', 'the', 'same', 'model', 'indeed', 'the', 'notion', 'of', 'superspreaders', 'has', 'arisen', 'to', 'describe', 'highly', 'influential', 'nodes', 'promoting', 'global', 'cascades', 'in', 'a', 'social', 'network', 'here', 'we', 'use', 'a', 'simple', 'model', 'of', 'global', 'cascades', 'to', 'show', 'that', 'the', 'presence', 'of', 'locality', 'in', 'the', 'network', 'increases', 'the', 'probability', 'of', 'a', 'global', 'cascade', 'due', 'to', 'the', 'increased', 'vulnerability', 'of', 'connecting', 'nodes', 'rather', 'than', 'superspreaders', 'we', 'find', 'that', 'the', 'presence', 'of', 'these', 'highly', 'connected', 'superblockers', 'in', 'heavytailed', 'networks', 'in', 'fact', 'reduces', 'the', 'probability', 'of', 'global', 'cascades', 'while', 'promoting', 'information', 'spread', 'when', 'targeted', 'as', 'the', 'initial', 'spreader']] | [-0.1414843411092332, 0.1218664847616575, -0.024916085946552504, 0.1115339407735868, -0.04449752350923735, -0.11320377818759013, 0.05560738786697289, 0.35640260241679006, -0.3091912686158687, -0.30236369590367507, 0.06838418770849779, -0.28149594090237523, -0.25220956126018274, 0.1150722791786176, -0.029497066088674577, 0.014047160824847143, 0.07574449166415, 0.06868716995139292, 0.04165274390352532, -0.2047593038088167, 0.3573161228282365, 0.13380853426550202, 0.3410310689699127, 0.04765438032644918, 0.06340956014414496, 0.024364343468124505, -0.060844586477522423, 0.03465123360726785, -0.05008167227846185, 0.12247899158538585, 0.2352119048144545, 0.17521677239619146, 0.3110491242953607, -0.4493459180022115, -0.28564684238556204, 0.18304194197434906, 0.15675766862981294, 0.10635228659371716, 0.011956014725940907, -0.29528742674614816, 0.09484011220702568, -0.19287112995979086, -0.09201966214151004, -0.05426248785922464, -0.007794677588274542, 0.06652329531105063, -0.2563582154022474, 0.0715776214558039, 0.05762302858172145, 0.038406854950081226, 0.006512359006712768, -0.0676771549396957, -0.09804255232393791, 0.17720995368439835, 0.09253771952738898, -0.02360432005228339, 0.169873203971232, -0.2260463550773184, -0.1367439051245074, 0.36767115078508755, -0.014979764262992204, -0.13785584253684574, 0.21742700533139586, -0.08802151383788923, -0.14722135007810866, 0.1568405197097593, 0.23973664736439973, 0.06380046742184964, -0.13144610101437668, -0.00040672778611422966, -0.034504917394739903, 0.1487354006154142, 0.048957270232417825, 0.045550605130657215, 0.15944003638200807, 0.22537065206854204, 0.11681614863063326, 0.12092279357564271, -0.04557462127120635, -0.14643821745050073, -0.20285193530444845, -0.07358718546730349, -0.17964738591216406, 0.09671487589520926, -0.1293851637691244, -0.18506644853230392, 0.42336411105579885, 0.15581242369167161, 0.2174678361413396, 0.06492060273484826, 0.24647383418378255, 0.032569147136050046, 0.07310221754692939, 0.1243065886495524, 0.20553344539335824, 0.08403094888615441, 0.12246012595553099, -0.13053738706381313, 0.17254675532203934, 0.008710405335989812] |
1,802.0504 | Virtual depth by active background suppression: Revisiting the cosmic
muon induced background of GERDA Phase II | In-situ production of long-lived isotopes by cosmic muon interactions may
generate a non-negligible background for deep underground rare event searches.
Previous Monte Carlo studies for the GERDA experiment at LNGS identified the
delayed decays of $^{77}$Ge and its metastable state $^{77m}$Ge as dominant
cosmogenic background in the search for neutrinoless double beta decay of
$^{76}$Ge. This might limit the sensitivity of next generation experiments
aiming for increased $^{76}$Ge mass at background-free conditions and thereby
define a minimum depth requirement. A re-evaluation of the $^{77(m)}$Ge
background for the GERDA experiment has been carried out by a set of Monte
Carlo simulations. The obtained $^{77(m)}$Ge production rate is (0.21$\pm$0.01)
nuclei/(kg$\cdot$yr). After application of state-of-the-art active background
suppression techniques and simple delayed coincidence cuts this corresponds to
a background contribution of (2.7$\pm$0.3)$\cdot10^{-6}$
cts/(keV$\cdot$kg$\cdot$yr). The suppression achieved by this strategy equals
an effective muon flux reduction of more than one order of magnitude. This
virtual depth increase opens the way for next generation rare event searches.
| hep-ex nucl-ex physics.ins-det | insitu production of longlived isotopes by cosmic muon interactions may generate a nonnegligible background for deep underground rare event searches previous monte carlo studies for the gerda experiment at lngs identified the delayed decays of 77ge and its metastable state 77mge as dominant cosmogenic background in the search for neutrinoless double beta decay of 76ge this might limit the sensitivity of next generation experiments aiming for increased 76ge mass at backgroundfree conditions and thereby define a minimum depth requirement a reevaluation of the 77mge background for the gerda experiment has been carried out by a set of monte carlo simulations the obtained 77mge production rate is 021pm001 nucleikgcdotyr after application of stateoftheart active background suppression techniques and simple delayed coincidence cuts this corresponds to a background contribution of 27pm03cdot106 ctskevcdotkgcdotyr the suppression achieved by this strategy equals an effective muon flux reduction of more than one order of magnitude this virtual depth increase opens the way for next generation rare event searches | [['insitu', 'production', 'of', 'longlived', 'isotopes', 'by', 'cosmic', 'muon', 'interactions', 'may', 'generate', 'a', 'nonnegligible', 'background', 'for', 'deep', 'underground', 'rare', 'event', 'searches', 'previous', 'monte', 'carlo', 'studies', 'for', 'the', 'gerda', 'experiment', 'at', 'lngs', 'identified', 'the', 'delayed', 'decays', 'of', '77ge', 'and', 'its', 'metastable', 'state', '77mge', 'as', 'dominant', 'cosmogenic', 'background', 'in', 'the', 'search', 'for', 'neutrinoless', 'double', 'beta', 'decay', 'of', '76ge', 'this', 'might', 'limit', 'the', 'sensitivity', 'of', 'next', 'generation', 'experiments', 'aiming', 'for', 'increased', '76ge', 'mass', 'at', 'backgroundfree', 'conditions', 'and', 'thereby', 'define', 'a', 'minimum', 'depth', 'requirement', 'a', 'reevaluation', 'of', 'the', '77mge', 'background', 'for', 'the', 'gerda', 'experiment', 'has', 'been', 'carried', 'out', 'by', 'a', 'set', 'of', 'monte', 'carlo', 'simulations', 'the', 'obtained', '77mge', 'production', 'rate', 'is', '021pm001', 'nucleikgcdotyr', 'after', 'application', 'of', 'stateoftheart', 'active', 'background', 'suppression', 'techniques', 'and', 'simple', 'delayed', 'coincidence', 'cuts', 'this', 'corresponds', 'to', 'a', 'background', 'contribution', 'of', '27pm03cdot106', 'ctskevcdotkgcdotyr', 'the', 'suppression', 'achieved', 'by', 'this', 'strategy', 'equals', 'an', 'effective', 'muon', 'flux', 'reduction', 'of', 'more', 'than', 'one', 'order', 'of', 'magnitude', 'this', 'virtual', 'depth', 'increase', 'opens', 'the', 'way', 'for', 'next', 'generation', 'rare', 'event', 'searches']] | [-0.06555706038763572, 0.2274264275901197, -0.029873339988294192, 0.1328870478919385, -0.010262172254763028, -0.10905177290287782, 0.0942654652124177, 0.30249088786325695, -0.19240769955956336, -0.3337233886474146, 0.05189491326132871, -0.336998359133261, -0.007701268613648911, 0.22156336626957562, 0.06461470691288042, 0.06385410953578158, 0.1234190546074273, 0.014702274161683829, -0.08083617970575842, -0.22513015008584228, 0.20694809940456171, 0.2335933185277328, 0.2777889042246337, 0.036588922137125106, 0.08128758406035204, -0.0030310188783274133, -0.09576010734718528, -0.07107183798772734, -0.12494163857128635, 0.04184698215510064, 0.25636287573900707, 0.1351103559414616, 0.17424729128174907, -0.4095375101615048, -0.17785092447474365, 0.1804121572336873, 0.1577536824610342, 0.08200660634181117, -0.14876778291528472, -0.3150626360175182, 0.08887696898185045, -0.20430209051009338, -0.1395745607145693, -0.02719519632923748, -0.011672493017647625, -0.045641823110182375, -0.30492804555658765, 0.04162410339805497, -0.03284170753293255, 0.03268846948836116, -0.002451806752386052, -0.1529583120777172, 0.06467170447679295, 0.051465616724746734, 0.07263056458700332, 0.07395243729353419, 0.18716556404251605, -0.1701894300757708, -0.17543095514271995, 0.3095653291393376, -0.10088707149475769, -0.0792778913772214, 0.14045752865639763, -0.1477985899879322, -0.14908597805777435, 0.25522074447476173, 0.15699991457304865, 0.1192347397837413, -0.19917699504854544, 0.06796832870488471, 0.04622937952982461, 0.16157181944944105, 0.06753296942125021, 0.021218574518021546, 0.24452127269234908, 0.29688462042747615, 0.0796439973578888, 0.09755581405318384, -0.19096836420186097, -0.031424441930007645, -0.34279814952949306, -0.14975069174484448, -0.08133939430469049, 0.06906827324825637, -0.024299888093036938, -0.10923061626483745, 0.3406101785623615, 0.11127784876548245, 0.12959257995785922, -0.005207004371163605, 0.3129584245169945, 0.055445509287400566, 0.06861660354214269, -0.062041653682984435, 0.31421099678809467, 0.11233708643026462, 0.11027882623328071, -0.2633245039457432, 0.09206699215332573, 0.05319234450295005] |
1,802.05041 | An extended Lagrangian formalism | A simple formal procedure makes the main properties of the lagrangian
binomial extendable to functions depending to any kind of order of the
time--derivatives of the lagrangian coordinates. Such a broadly formulated
binomial can provide the lagrangian components, in the classical sense of the
Newton's law, for a quite general class of forces. At the same time, the
generalized equations of motions recover some of the classical alternative
formulations of the Lagrangian equations.
| physics.class-ph math-ph math.MP | a simple formal procedure makes the main properties of the lagrangian binomial extendable to functions depending to any kind of order of the timederivatives of the lagrangian coordinates such a broadly formulated binomial can provide the lagrangian components in the classical sense of the newtons law for a quite general class of forces at the same time the generalized equations of motions recover some of the classical alternative formulations of the lagrangian equations | [['a', 'simple', 'formal', 'procedure', 'makes', 'the', 'main', 'properties', 'of', 'the', 'lagrangian', 'binomial', 'extendable', 'to', 'functions', 'depending', 'to', 'any', 'kind', 'of', 'order', 'of', 'the', 'timederivatives', 'of', 'the', 'lagrangian', 'coordinates', 'such', 'a', 'broadly', 'formulated', 'binomial', 'can', 'provide', 'the', 'lagrangian', 'components', 'in', 'the', 'classical', 'sense', 'of', 'the', 'newtons', 'law', 'for', 'a', 'quite', 'general', 'class', 'of', 'forces', 'at', 'the', 'same', 'time', 'the', 'generalized', 'equations', 'of', 'motions', 'recover', 'some', 'of', 'the', 'classical', 'alternative', 'formulations', 'of', 'the', 'lagrangian', 'equations']] | [-0.13581313058887035, 0.06811677957948757, -0.14879675184644453, 0.08307428800896423, -0.1291293417397019, -0.10758467278226394, -0.02323795936057625, 0.22943441891302802, -0.32744320581526787, -0.26241630518311404, 0.04229744347545943, -0.20707055942908134, -0.14740531003000598, 0.1853326039057072, -0.0813143422304053, 0.06207823078905564, -0.0018345715943723917, 0.06146080505506738, -0.11425798864754504, -0.2331909657366676, 0.31764263882021077, 0.005138976670074442, 0.19836704320695303, -0.004077291473338049, 0.17964022272355754, -0.008240195137946165, -0.04178642907677448, 0.046489721234275465, -0.1276174474201382, 0.1222974015782549, 0.23445201110196848, 0.06962675492802303, 0.24932993346289412, -0.4158539623149658, -0.19969945348646134, 0.10384529786286494, 0.08681172367236385, 0.10852123988307502, 0.02745617528076041, -0.2301164978017954, 0.06511778331980467, -0.14796547895322923, -0.25436540958407805, -0.06933422616287453, -0.005267764243922413, 0.09012209019330267, -0.26886628876912266, 0.07703519045464592, 0.1167836445830252, 0.020559582132080645, -0.061550567755858376, -0.11340123738883037, 0.012942276064191677, 0.08045577870886007, 0.0488680896208915, -0.023737966701745578, 0.10487916824656654, -0.1151719937381679, -0.11397871905969685, 0.4776163966560813, -0.05128222828482163, -0.2952376473918302, 0.1769743297402173, -0.09067283270957127, -0.16752130303480853, 0.08992235004034353, 0.12262982224458702, 0.17533185046171365, -0.17739293382388271, 0.11324141584081601, -0.026781549192454717, 0.09809161375646722, 0.06461463818862422, 0.01035746190559808, 0.14689952312898502, 0.04345527317451492, 0.07747176589118555, 0.11892289641530138, -0.012631444228583411, -0.17353692497700862, -0.38792401246012076, -0.18323775992269487, -0.1588062899608216, 0.0567484448204608, -0.16756664071716879, -0.21366328327623132, 0.4241290074096967, 0.10664727482530097, 0.15189340868837212, 0.1196785394918837, 0.2890250074536833, 0.18073383920302946, 0.05906814698461596, 0.04773182480289818, 0.23000080186486155, 0.17269092953878723, 0.07334151319929794, -0.1744215542144359, 0.04120098772037723, 0.17631770322124843] |
1,802.05042 | Wall effects on spatial correlations of non-affine strain in a 3D model
glass | Effects of hard planar walls with a particle scale roughness on the spatial
correlations of non-affine strain in amorphous solids are investigated via
molecular dynamics simulations. When determined within layers parallel to the
wall plane, normalized non-affine strain correlations are enhanced within
layers closer to the wall. The amplitude of these correlations, on the other
hand, is found to be suppressed by the wall. While the former is connected to
the effects of a hard boundary on the continuum mechanics scale, the latter is
attributed to molecular scale wall effects on the size of the region (nearest
neighbor cage), explored by particles on intermediate times scales.
| cond-mat.stat-mech | effects of hard planar walls with a particle scale roughness on the spatial correlations of nonaffine strain in amorphous solids are investigated via molecular dynamics simulations when determined within layers parallel to the wall plane normalized nonaffine strain correlations are enhanced within layers closer to the wall the amplitude of these correlations on the other hand is found to be suppressed by the wall while the former is connected to the effects of a hard boundary on the continuum mechanics scale the latter is attributed to molecular scale wall effects on the size of the region nearest neighbor cage explored by particles on intermediate times scales | [['effects', 'of', 'hard', 'planar', 'walls', 'with', 'a', 'particle', 'scale', 'roughness', 'on', 'the', 'spatial', 'correlations', 'of', 'nonaffine', 'strain', 'in', 'amorphous', 'solids', 'are', 'investigated', 'via', 'molecular', 'dynamics', 'simulations', 'when', 'determined', 'within', 'layers', 'parallel', 'to', 'the', 'wall', 'plane', 'normalized', 'nonaffine', 'strain', 'correlations', 'are', 'enhanced', 'within', 'layers', 'closer', 'to', 'the', 'wall', 'the', 'amplitude', 'of', 'these', 'correlations', 'on', 'the', 'other', 'hand', 'is', 'found', 'to', 'be', 'suppressed', 'by', 'the', 'wall', 'while', 'the', 'former', 'is', 'connected', 'to', 'the', 'effects', 'of', 'a', 'hard', 'boundary', 'on', 'the', 'continuum', 'mechanics', 'scale', 'the', 'latter', 'is', 'attributed', 'to', 'molecular', 'scale', 'wall', 'effects', 'on', 'the', 'size', 'of', 'the', 'region', 'nearest', 'neighbor', 'cage', 'explored', 'by', 'particles', 'on', 'intermediate', 'times', 'scales']] | [-0.12710548612236414, 0.22384922459440412, -0.059714259368912226, 0.061456103692762554, -0.012163282890435098, -0.07955736356989462, 0.01239032362464745, 0.4066257171930288, -0.3253250834092779, -0.2661273847246226, 0.08216205508478935, -0.25881360940424336, -0.07212650431495793, 0.1150669385294676, 0.04364766038373279, 0.0031130664025319143, 0.013358399254392903, -0.014749587553043692, -0.030429429409779468, -0.17930274957544962, 0.2830599127359302, 0.06917729074978884, 0.2929257567585358, 0.0981668142232833, 0.04201929600698487, -0.01517876063227513, -0.00011620048064527646, 0.08359003806803024, -0.14465903243454137, 0.087674095348086, 0.16822466698809052, -0.11514282291249882, 0.20489965509271846, -0.5040872331778958, -0.21215382712137587, 0.03501288543174149, 0.1648150102261735, 0.09423913845115886, 0.045841070287970756, -0.2959615284475972, 0.05491199947120446, -0.060381442194207095, -0.1335771564165798, 0.0169223703362733, 0.062129167910173255, 0.016917944850096973, -0.21791130820956994, 0.1683050450904049, 0.028255195051589806, 0.04240284388322594, -0.025149274999627245, -0.09670433423148012, -0.06876252732626251, 0.09013356206491634, 0.06616340208807434, 0.048275878951656366, 0.26316562435537016, -0.1631801921065967, -0.0785818124356908, 0.4096750190683623, -0.003315298734584226, -0.21435799072403242, 0.231232630888457, -0.17974429665449657, -0.06094357724529954, 0.1931080967715045, 0.18640009102956304, 0.0940149513134768, -0.12168547260986294, 0.06183318144703319, 0.02286391034129269, 0.20895845657829545, 0.05702714317583672, 0.0035191059270697944, 0.22602026343767373, 0.19107902652522513, 0.03440267814077296, 0.19019986925380886, -0.14128675168591007, -0.14849772796315966, -0.2533068139598055, -0.07139811153470907, -0.2362272831631104, -0.0067171937223734724, -0.14473616353780874, -0.16648673299998748, 0.34076961342526496, 0.10242003713787165, 0.19636759339866913, 0.013759015822115372, 0.24683748542348732, 0.06025466355407294, 0.15518365187003752, 0.05275792147489792, 0.3066670414728095, 0.13972818475866797, 0.0638608179419776, -0.26908157778165814, 0.07553409285544646, 0.04229349833210262] |
1,802.05043 | Projection methods based on spline quasi-interpolation for Urysohn
integral equations | In this paper we propose projection methods based on spline
quasi-interpolating projectors of degree $d$ and class $C^{d-1}$ on a bounded
interval for the numerical solution of nonlinear integral equations. We prove
that they have high order of convergence $2d+2$ if $d$ is odd and $2d+3$ if $d$
is even. We also present the implementation details of the above methods.
Finally, we provide numerical tests, that confirm the theoretical results.
Moreover, we compare the theoretical and numerical results with those obtained
by using a collocation method based on the same spline quasi-interpolating
projectors.
| math.NA | in this paper we propose projection methods based on spline quasiinterpolating projectors of degree d and class cd1 on a bounded interval for the numerical solution of nonlinear integral equations we prove that they have high order of convergence 2d2 if d is odd and 2d3 if d is even we also present the implementation details of the above methods finally we provide numerical tests that confirm the theoretical results moreover we compare the theoretical and numerical results with those obtained by using a collocation method based on the same spline quasiinterpolating projectors | [['in', 'this', 'paper', 'we', 'propose', 'projection', 'methods', 'based', 'on', 'spline', 'quasiinterpolating', 'projectors', 'of', 'degree', 'd', 'and', 'class', 'cd1', 'on', 'a', 'bounded', 'interval', 'for', 'the', 'numerical', 'solution', 'of', 'nonlinear', 'integral', 'equations', 'we', 'prove', 'that', 'they', 'have', 'high', 'order', 'of', 'convergence', '2d2', 'if', 'd', 'is', 'odd', 'and', '2d3', 'if', 'd', 'is', 'even', 'we', 'also', 'present', 'the', 'implementation', 'details', 'of', 'the', 'above', 'methods', 'finally', 'we', 'provide', 'numerical', 'tests', 'that', 'confirm', 'the', 'theoretical', 'results', 'moreover', 'we', 'compare', 'the', 'theoretical', 'and', 'numerical', 'results', 'with', 'those', 'obtained', 'by', 'using', 'a', 'collocation', 'method', 'based', 'on', 'the', 'same', 'spline', 'quasiinterpolating', 'projectors']] | [-0.08863056419036722, 0.020266888282632314, -0.1153770947969088, 0.02936988803482945, -0.04475857485686579, -0.1287177164146366, 0.03467487943263584, 0.408747324219314, -0.2122800892158862, -0.24426007386977955, 0.15576286085816202, -0.27673857108319316, -0.1800720259961572, 0.2187775601582822, -0.04989357808634879, 0.08357577716871616, 0.105124945767344, 0.00980664512063677, -0.13500804846520506, -0.3099630359279853, 0.31903916773616625, -0.002703747857281918, 0.2045140216497564, 0.07248333830546627, 0.1189468782695551, -0.04026892136341782, -0.050407179731435034, 0.040019917379443846, -0.19415160239582147, 0.15472013483284622, 0.2014936686077866, 0.11776005249140004, 0.2775456112038384, -0.40946200500012087, -0.14750772747661797, 0.08186078829670786, 0.1424034402845928, 0.08275924345618614, -0.058217493107452264, -0.24050108681843485, 0.14649433043775378, -0.11890167942141078, -0.14062907855697376, -0.15512650299777267, -0.006661649452902938, 0.06627349445550139, -0.3018729997278061, 0.07817765349561039, 0.06725850731625112, 0.08283517716492536, -0.06625482028410319, -0.16706247089721102, 0.011942776906434246, 0.021507824525757824, -0.010179518789593731, -0.0020454519238042577, 0.0002697676330083801, -0.04630287371385562, -0.1355425349326544, 0.3375540314222215, -0.086118235791062, -0.2831536945836839, 0.1731650454032245, -0.16619422847044565, -0.14301307270083055, 0.08962085972019342, 0.15192834500183341, 0.18651741122706764, -0.04519030420980867, 0.11111212064704848, -0.09144842487719831, 0.1597992636423598, 0.06299702871230341, -0.007897948938852517, 0.05763168743140595, 0.13890547869646902, 0.0837557899480265, 0.12340881283925746, -0.08226180114903517, -0.030512579341208743, -0.3581854650270074, -0.12016432030847476, -0.20701482612639666, 0.009926185049417039, -0.12500219130140644, -0.13545572625095104, 0.3844043553396258, 0.17741072527383284, 0.15982383887423704, 0.12339922995056196, 0.2829434403809168, 0.13924465255351157, -0.004311936076289864, 0.11283631565772818, 0.2175772307961378, 0.12137739183080773, 0.030599744925375587, -0.20328629083971503, 0.025099526494941723, 0.15283944781776393] |
1,802.05044 | Fermion masses and flavor mixings and strong CP problem | For all the success of the Standard Model (SM), it is on the verge of being
surpassed. In this regard we argue, by showing a minimal flavor-structured
model based on the non-Abelian discrete $SL_2(F_3)$ symmetry, that $U(1)$
mixed-gravitational anomaly cancellation could be of central importance in
constraining the fermion contents of a new chiral gauge theory. Such
anomaly-free condition together with the SM flavor structure demands a
condition $k_1\,X_1/2=k_2\,X_2$ with $X_i$ being a charge of $U(1)_{X_i}$ and
$k_i$ being an integer, both of which are flavor dependent. We show that
axionic domain-wall condition $N_{\rm DW}$ with the anomaly free-condition
depends on both $U(1)_X$ charged quark and lepton flavors; the seesaw scale
congruent to the scale of Peccei-Quinn symmetry breakdown can be constrained
through constraints coming from astrophysics and particle physics. Then the
model extended by $SL_2(F_3)\times U(1)_X$ symmetry can well be
flavor-structured in a unique way that $N_{\rm DW}=1$ with the $U(1)_X$
mixed-gravitational anomaly-free condition demands additional Majorana fermion
and the flavor puzzles of SM are well delineated by new expansion parameters
expressed in terms of $U(1)_X$ charges and $U(1)_X$-$[SU(3)_C]^2$ anomaly
coefficients. And the model provides remarkable results on neutrino
(hierarchical mass spectra and unmeasurable neutrinoless-double-beta decay rate
together with the predictions on atmospheric mixing angle and leptonic Dirac CP
phase favored by the recent long-baseline neutrino experiments), QCD axion, and
flavored-axion.
| hep-ph | for all the success of the standard model sm it is on the verge of being surpassed in this regard we argue by showing a minimal flavorstructured model based on the nonabelian discrete sl_2f_3 symmetry that u1 mixedgravitational anomaly cancellation could be of central importance in constraining the fermion contents of a new chiral gauge theory such anomalyfree condition together with the sm flavor structure demands a condition k_1x_12k_2x_2 with x_i being a charge of u1_x_i and k_i being an integer both of which are flavor dependent we show that axionic domainwall condition n_rm dw with the anomaly freecondition depends on both u1_x charged quark and lepton flavors the seesaw scale congruent to the scale of pecceiquinn symmetry breakdown can be constrained through constraints coming from astrophysics and particle physics then the model extended by sl_2f_3times u1_x symmetry can well be flavorstructured in a unique way that n_rm dw1 with the u1_x mixedgravitational anomalyfree condition demands additional majorana fermion and the flavor puzzles of sm are well delineated by new expansion parameters expressed in terms of u1_x charges and u1_xsu3_c2 anomaly coefficients and the model provides remarkable results on neutrino hierarchical mass spectra and unmeasurable neutrinolessdoublebeta decay rate together with the predictions on atmospheric mixing angle and leptonic dirac cp phase favored by the recent longbaseline neutrino experiments qcd axion and flavoredaxion | [['for', 'all', 'the', 'success', 'of', 'the', 'standard', 'model', 'sm', 'it', 'is', 'on', 'the', 'verge', 'of', 'being', 'surpassed', 'in', 'this', 'regard', 'we', 'argue', 'by', 'showing', 'a', 'minimal', 'flavorstructured', 'model', 'based', 'on', 'the', 'nonabelian', 'discrete', 'sl_2f_3', 'symmetry', 'that', 'u1', 'mixedgravitational', 'anomaly', 'cancellation', 'could', 'be', 'of', 'central', 'importance', 'in', 'constraining', 'the', 'fermion', 'contents', 'of', 'a', 'new', 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1,802.05045 | A probabilistic model for crystal growth applied to protein deposition
at the microscale | A probabilistic discrete model for 2D protein crystal growth is presented.
This model takes into account the available space and can describe growing
processes of different nature due to the versatility of its parameters which
gives the model great flexibility. The accuracy of the simulation is tested
against a real protein (SbpA) crystallization experiment showing high agreement
between the proposed model and the actual images of the nucleation process.
Finally, it is also discussed how the regularity of the interface (i.e. the
curve that separates the crystal from the substrate) affects to the evolution
of the simulation.
| physics.bio-ph cond-mat.soft | a probabilistic discrete model for 2d protein crystal growth is presented this model takes into account the available space and can describe growing processes of different nature due to the versatility of its parameters which gives the model great flexibility the accuracy of the simulation is tested against a real protein sbpa crystallization experiment showing high agreement between the proposed model and the actual images of the nucleation process finally it is also discussed how the regularity of the interface ie the curve that separates the crystal from the substrate affects to the evolution of the simulation | [['a', 'probabilistic', 'discrete', 'model', 'for', '2d', 'protein', 'crystal', 'growth', 'is', 'presented', 'this', 'model', 'takes', 'into', 'account', 'the', 'available', 'space', 'and', 'can', 'describe', 'growing', 'processes', 'of', 'different', 'nature', 'due', 'to', 'the', 'versatility', 'of', 'its', 'parameters', 'which', 'gives', 'the', 'model', 'great', 'flexibility', 'the', 'accuracy', 'of', 'the', 'simulation', 'is', 'tested', 'against', 'a', 'real', 'protein', 'sbpa', 'crystallization', 'experiment', 'showing', 'high', 'agreement', 'between', 'the', 'proposed', 'model', 'and', 'the', 'actual', 'images', 'of', 'the', 'nucleation', 'process', 'finally', 'it', 'is', 'also', 'discussed', 'how', 'the', 'regularity', 'of', 'the', 'interface', 'ie', 'the', 'curve', 'that', 'separates', 'the', 'crystal', 'from', 'the', 'substrate', 'affects', 'to', 'the', 'evolution', 'of', 'the', 'simulation']] | [-0.06046635790046343, 0.07925101046056784, -0.10919024260503422, 0.050112295632473984, -0.04888961202052144, -0.11559821857792354, 0.03679945161470126, 0.35882154455349646, -0.2818940042604491, -0.29703249521169467, 0.0642691807684575, -0.2464001254591438, -0.16501696784164488, 0.1982982606655851, -0.010996020083392481, 0.047767497852958314, 0.08069837563815191, -0.014688700763988741, -0.019730199682862333, -0.24547997868341423, 0.26756635477247925, 0.10657418996441304, 0.3617529621102953, 0.08094344985882569, 0.1403982531298528, -0.0052833568842447914, 0.004834393269776069, -0.0031690189051417844, -0.1566628838230564, 0.1231041332159537, 0.19251604796838515, 0.11216220944236542, 0.22393764391272647, -0.43574752579875214, -0.2523376780859742, 0.06731343771494233, 0.1192073437262845, 0.12188559096935445, -0.07203163469651926, -0.27106355275651534, 0.09009557016693133, -0.12091764568629645, -0.10716752922280179, -0.05219693509285751, -0.003952096181576015, 0.023184963591401608, -0.23999541330111654, 0.06618430371577468, 0.054420314575593494, 0.019196293297578992, -0.10342015073629883, -0.07259367456444846, -0.09952461999869838, 0.1568759546048709, 0.04219380352908947, 0.015560947286598768, 0.13574873287105912, -0.11961370376034726, -0.08101254090013885, 0.43955202266266663, -0.007278985534098537, -0.1859768126831995, 0.21728581781547093, -0.14259579699467292, -0.06789344156967457, 0.16154593656550056, 0.16001985214300185, 0.045179935733874126, -0.10775686723309733, 0.09839689951346822, -0.007532115660838245, 0.1932908236865223, 0.004626758912693441, -0.04742939393919684, 0.17272031847291539, 0.26002532164998277, -0.03851347182368495, 0.19296775292605162, -0.09933136579383779, -0.14851035338168792, -0.28665505490654636, -0.18048644177231593, -0.19036533680418027, -0.03181251517938661, -0.14358449136549079, -0.16528754334743181, 0.429602578599198, 0.17927370590551459, 0.1853446186875406, 0.037086122459251934, 0.2807427357363793, 0.07889419218966949, 0.0399634670226153, -0.016566380488772674, 0.2269163291316873, 0.09645862350259553, 0.09429092303916965, -0.25681224191974195, 0.1348143292533368, -0.005151334720346885] |
1,802.05046 | Benchmarking Framework for Performance-Evaluation of Causal Inference
Analysis | Causal inference analysis is the estimation of the effects of actions on
outcomes. In the context of healthcare data this means estimating the outcome
of counter-factual treatments (i.e. including treatments that were not
observed) on a patient's outcome. Compared to classic machine learning methods,
evaluation and validation of causal inference analysis is more challenging
because ground truth data of counter-factual outcome can never be obtained in
any real-world scenario. Here, we present a comprehensive framework for
benchmarking algorithms that estimate causal effect. The framework includes
unlabeled data for prediction, labeled data for validation, and code for
automatic evaluation of algorithm predictions using both established and novel
metrics. The data is based on real-world covariates, and the treatment
assignments and outcomes are based on simulations, which provides the basis for
validation. In this framework we address two questions: one of scaling, and the
other of data-censoring. The framework is available as open source code at
https://github.com/IBM-HRL-MLHLS/IBM-Causal-Inference-Benchmarking-Framework
| stat.ME cs.LG stat.ML | causal inference analysis is the estimation of the effects of actions on outcomes in the context of healthcare data this means estimating the outcome of counterfactual treatments ie including treatments that were not observed on a patients outcome compared to classic machine learning methods evaluation and validation of causal inference analysis is more challenging because ground truth data of counterfactual outcome can never be obtained in any realworld scenario here we present a comprehensive framework for benchmarking algorithms that estimate causal effect the framework includes unlabeled data for prediction labeled data for validation and code for automatic evaluation of algorithm predictions using both established and novel metrics the data is based on realworld covariates and the treatment assignments and outcomes are based on simulations which provides the basis for validation in this framework we address two questions one of scaling and the other of datacensoring the framework is available as open source code at httpsgithubcomibmhrlmlhlsibmcausalinferencebenchmarkingframework | [['causal', 'inference', 'analysis', 'is', 'the', 'estimation', 'of', 'the', 'effects', 'of', 'actions', 'on', 'outcomes', 'in', 'the', 'context', 'of', 'healthcare', 'data', 'this', 'means', 'estimating', 'the', 'outcome', 'of', 'counterfactual', 'treatments', 'ie', 'including', 'treatments', 'that', 'were', 'not', 'observed', 'on', 'a', 'patients', 'outcome', 'compared', 'to', 'classic', 'machine', 'learning', 'methods', 'evaluation', 'and', 'validation', 'of', 'causal', 'inference', 'analysis', 'is', 'more', 'challenging', 'because', 'ground', 'truth', 'data', 'of', 'counterfactual', 'outcome', 'can', 'never', 'be', 'obtained', 'in', 'any', 'realworld', 'scenario', 'here', 'we', 'present', 'a', 'comprehensive', 'framework', 'for', 'benchmarking', 'algorithms', 'that', 'estimate', 'causal', 'effect', 'the', 'framework', 'includes', 'unlabeled', 'data', 'for', 'prediction', 'labeled', 'data', 'for', 'validation', 'and', 'code', 'for', 'automatic', 'evaluation', 'of', 'algorithm', 'predictions', 'using', 'both', 'established', 'and', 'novel', 'metrics', 'the', 'data', 'is', 'based', 'on', 'realworld', 'covariates', 'and', 'the', 'treatment', 'assignments', 'and', 'outcomes', 'are', 'based', 'on', 'simulations', 'which', 'provides', 'the', 'basis', 'for', 'validation', 'in', 'this', 'framework', 'we', 'address', 'two', 'questions', 'one', 'of', 'scaling', 'and', 'the', 'other', 'of', 'datacensoring', 'the', 'framework', 'is', 'available', 'as', 'open', 'source', 'code', 'at', 'httpsgithubcomibmhrlmlhlsibmcausalinferencebenchmarkingframework']] | [-0.03773157177603304, -0.008706841687824016, -0.08691443870410177, 0.10940096030556566, -0.09282742118694229, -0.15712135528013402, 0.09045802158291384, 0.40032373775356733, -0.17362222514949202, -0.34768644261654785, 0.13246239612588134, -0.2776349063694867, -0.128191137846538, 0.25557959709146055, -0.08779488558336192, 0.10247901309086802, 0.17509332492801488, 0.037233369625812654, -0.03841055141764942, -0.2632615970990931, 0.331568997685061, 0.05774422784737658, 0.3421292089053667, 0.040261388750247706, 0.08268875575828323, 0.04260625795832549, -0.09059374052057274, 0.0424966527532567, -0.11403839966463719, 0.13288024971543147, 0.3126323086284162, 0.26570346027466596, 0.3447297555181423, -0.394023688545061, -0.23356074397452176, 0.07828533656140363, 0.07466713809316941, 0.13340966816720692, -0.02636535328653492, -0.3083049423682193, 0.0547896927950015, -0.14503772992616384, -0.011505323503276004, -0.14263336116210648, -0.02587653000479917, -0.055504739430605195, -0.3341584367330606, 0.0836968298094481, 0.014930591559390617, 0.12499066273030503, -0.09675530217636645, -0.12311024751416803, 0.03240227550679051, 0.15758324076735042, 0.07097428363863549, 0.0126443451264374, 0.12167521742982121, -0.11819399506868673, -0.2074643736553007, 0.3727104727337076, -0.01269842858359315, -0.22188322905000615, 0.1616256319235986, -0.062365294443260805, -0.17459762028990666, 0.045293993919211274, 0.23812441528661427, 0.12985144973446439, -0.20424172117259182, 0.013732934213133858, -0.039663474553331635, 0.15383018412265098, -0.01909542110827721, -0.029600188388333965, 0.1517920928757662, 0.2438994527557025, -0.030829968022219108, 0.08990476676681401, -0.10591672463464288, -0.11249052138171262, -0.2958194627213517, -0.1358695584805865, -0.16874200278844417, -0.029919809148874394, -0.08759846470909942, -0.18486679613505022, 0.3659280251735955, 0.2303375124267844, 0.14967336047903385, 0.05894876128363916, 0.3436965288509146, 0.029305413413299796, 0.0527814871333296, 0.07321723663701608, 0.18103430432790976, 0.052494834250240936, 0.03245016345693395, -0.19198807075108384, 0.1785182596193444, -0.002207782084511873] |
1,802.05047 | Dynamical and statistical bimodality in nuclear fragmentation | The origin of bimodal behavior in the residue distribution experimentally
measured in heavy ion reactions is reexamined using Boltzmann-Uehling-Uhlenbeck
simulations. We suggest that, depending on the incident energy and impact
parameter of the reaction, both entrance channel and exit channel effects can
be at the origin of the observed behavior. Specifically, fluctuations in the
reaction mechanism induced by fluctuations in the collision rate, as well as
thermal bimodality directly linked to the nuclear liquid-gas phase transition
are observed in our simulations. Both phenomenologies were previously proposed
in the literature, but presented as incompatible and contradictory
interpretations of the experimental measurements. These results indicate that
heavy ion collisions at intermediate energies can be viewed as a powerful tool
to study both bifurcations induced by out-of-equilibrium critical phenomena, as
well as finite size precursors of thermal phase transitions.
| nucl-th nucl-ex | the origin of bimodal behavior in the residue distribution experimentally measured in heavy ion reactions is reexamined using boltzmannuehlinguhlenbeck simulations we suggest that depending on the incident energy and impact parameter of the reaction both entrance channel and exit channel effects can be at the origin of the observed behavior specifically fluctuations in the reaction mechanism induced by fluctuations in the collision rate as well as thermal bimodality directly linked to the nuclear liquidgas phase transition are observed in our simulations both phenomenologies were previously proposed in the literature but presented as incompatible and contradictory interpretations of the experimental measurements these results indicate that heavy ion collisions at intermediate energies can be viewed as a powerful tool to study both bifurcations induced by outofequilibrium critical phenomena as well as finite size precursors of thermal phase transitions | [['the', 'origin', 'of', 'bimodal', 'behavior', 'in', 'the', 'residue', 'distribution', 'experimentally', 'measured', 'in', 'heavy', 'ion', 'reactions', 'is', 'reexamined', 'using', 'boltzmannuehlinguhlenbeck', 'simulations', 'we', 'suggest', 'that', 'depending', 'on', 'the', 'incident', 'energy', 'and', 'impact', 'parameter', 'of', 'the', 'reaction', 'both', 'entrance', 'channel', 'and', 'exit', 'channel', 'effects', 'can', 'be', 'at', 'the', 'origin', 'of', 'the', 'observed', 'behavior', 'specifically', 'fluctuations', 'in', 'the', 'reaction', 'mechanism', 'induced', 'by', 'fluctuations', 'in', 'the', 'collision', 'rate', 'as', 'well', 'as', 'thermal', 'bimodality', 'directly', 'linked', 'to', 'the', 'nuclear', 'liquidgas', 'phase', 'transition', 'are', 'observed', 'in', 'our', 'simulations', 'both', 'phenomenologies', 'were', 'previously', 'proposed', 'in', 'the', 'literature', 'but', 'presented', 'as', 'incompatible', 'and', 'contradictory', 'interpretations', 'of', 'the', 'experimental', 'measurements', 'these', 'results', 'indicate', 'that', 'heavy', 'ion', 'collisions', 'at', 'intermediate', 'energies', 'can', 'be', 'viewed', 'as', 'a', 'powerful', 'tool', 'to', 'study', 'both', 'bifurcations', 'induced', 'by', 'outofequilibrium', 'critical', 'phenomena', 'as', 'well', 'as', 'finite', 'size', 'precursors', 'of', 'thermal', 'phase', 'transitions']] | [-0.08083360999829464, 0.2300539847192875, -0.12729629821542937, 0.11356155444638502, 0.00599223915282089, -0.1122582848834367, 0.021270126960349873, 0.3425113941296278, -0.26637829412528147, -0.3147690000341219, 0.059379713762181756, -0.2984330338350607, -0.09238955896580592, 0.1626507144054117, 0.04979247520746225, 0.06125030409791233, 0.027346857222522992, 0.005422826109947089, -0.020516122275319716, -0.13301795043106027, 0.2963709993303329, 0.12871338882456151, 0.2765774282058427, 0.13319826789494768, 0.0382948912858196, -0.031685129453441783, 0.035254152950502056, 0.03972956818624345, -0.13857125057053482, -0.029518369977107366, 0.2749265352424974, 0.03830779092865722, 0.1583141443757888, -0.44396747940439074, -0.26226490340537995, 0.09488790582776453, 0.17272122770287646, 0.12024893181617646, -0.11035396735036664, -0.2738604354124297, 0.042389971818278464, -0.152455020483638, -0.15754781731897416, -0.038859711131354904, 0.0007216604255304179, 0.0639256130097612, -0.2636806854211232, 0.12916670403758282, 0.013116370326743516, 0.06524652661755681, -0.07753171268696486, -0.15356763867620268, -0.06490006897879272, 0.09817487812388744, 0.06520585445500995, 0.0015589040434433093, 0.20774233855156446, -0.09569016279163085, -0.138863085407031, 0.38186812422388944, -0.07396287866183282, -0.11796474525951506, 0.19687330091512514, -0.19136264251873775, -0.10545149573590606, 0.15614199968609577, 0.18349304767873356, 0.09623458723688279, -0.14250150941627318, -0.009801730672359768, 0.025835005071712658, 0.11013571435855471, 0.05051944759222405, 0.07460560757146381, 0.20412338422679835, 0.17966439721075242, -0.07184495195157498, 0.13446809373978313, -0.10639400436946958, -0.1437623035025728, -0.3111608330612345, -0.0900150017662193, -0.16760145830887588, 0.023004740346497035, -0.04932801575395227, -0.09972345265251693, 0.3487553118098089, 0.14385743190616587, 0.2601514600259286, -0.051062365274821574, 0.2670784804607084, 0.09298898544511758, 0.0453982404745629, 0.025047928201007274, 0.2885002586442758, 0.13405010623768354, 0.11532350198489011, -0.29544904353850354, 0.16681115512790926, 0.013125386005199021] |
1,802.05048 | Transport in quantum chains under strong monitoring | We study the transport properties of quantum 1D systems under strong
monitoring. The quantum Zeno effect inhibits transport and induces
localization. Beyond the Zeno freezing and on long time scales, a new dynamics
emerges in the form of a Markov process. Studying fermionic and bosonic chains
under strong monitoring, we are able to identify the quantum origin of the
classical exclusion process, inclusion process and a sub-class of the
misanthrope process. Moreover, we show that passive monitoring cannot break
time-reversal symmetry and that the transport generally loses its ballistic
nature existing for weak measurements.
| cond-mat.stat-mech | we study the transport properties of quantum 1d systems under strong monitoring the quantum zeno effect inhibits transport and induces localization beyond the zeno freezing and on long time scales a new dynamics emerges in the form of a markov process studying fermionic and bosonic chains under strong monitoring we are able to identify the quantum origin of the classical exclusion process inclusion process and a subclass of the misanthrope process moreover we show that passive monitoring cannot break timereversal symmetry and that the transport generally loses its ballistic nature existing for weak measurements | [['we', 'study', 'the', 'transport', 'properties', 'of', 'quantum', '1d', 'systems', 'under', 'strong', 'monitoring', 'the', 'quantum', 'zeno', 'effect', 'inhibits', 'transport', 'and', 'induces', 'localization', 'beyond', 'the', 'zeno', 'freezing', 'and', 'on', 'long', 'time', 'scales', 'a', 'new', 'dynamics', 'emerges', 'in', 'the', 'form', 'of', 'a', 'markov', 'process', 'studying', 'fermionic', 'and', 'bosonic', 'chains', 'under', 'strong', 'monitoring', 'we', 'are', 'able', 'to', 'identify', 'the', 'quantum', 'origin', 'of', 'the', 'classical', 'exclusion', 'process', 'inclusion', 'process', 'and', 'a', 'subclass', 'of', 'the', 'misanthrope', 'process', 'moreover', 'we', 'show', 'that', 'passive', 'monitoring', 'can', 'not', 'break', 'timereversal', 'symmetry', 'and', 'that', 'the', 'transport', 'generally', 'loses', 'its', 'ballistic', 'nature', 'existing', 'for', 'weak', 'measurements']] | [-0.19693993164324447, 0.1887590733013655, -0.08807673284685925, 0.07139903022455799, -0.05511523124418761, -0.1761965644447819, 0.079448363069739, 0.3598161986097693, -0.32387064809077665, -0.2027787151207265, 0.09829199717036988, -0.255564607013213, -0.1353874306537603, 0.18374073970082558, 0.015312483188647188, 0.05332153647782673, 0.03488106888498327, -0.023256022120384794, -0.062209454762112155, -0.17255189812399055, 0.26774444103633105, 0.0648390033956323, 0.3102411701613547, 0.073041094473171, 0.09783856832471333, 0.06990880434842486, 0.046794197894632815, -0.006924544421857909, -0.11587811117872326, 0.008471143559405678, 0.1534086730711064, 0.03644676005565806, 0.22243979394828017, -0.4544937206922393, -0.2600061571029456, 0.11302984487020264, 0.13568491087184828, 0.1540057359312318, -0.05416844193701093, -0.33248413725707093, 0.04338062054624683, -0.14579056395511877, -0.13004625772959308, -0.11002605091780424, -0.006698806534864401, -0.017028935197250624, -0.22692808185360933, 0.12511388385349786, 0.15613362020567845, 0.05306943173667318, -0.026468868557927443, 0.017302174179961806, -0.010017992889410571, 0.14013461719120018, 0.010298508157536976, -0.08389978561011192, 0.18577573790190446, -0.1719507245101819, -0.1551309596649126, 0.3840159367500363, -0.09055591289346156, -0.13849463543707602, 0.28725313038418165, -0.16302684848932059, -0.15138746510798995, 0.11030900747466245, 0.15550907292452298, 0.1111907081090306, -0.18122479563676996, 0.10057393625856524, -0.009896903259581641, 0.14182512879763778, -0.012020231472132237, 0.11517156649773058, 0.2166028325298899, 0.1869430464545363, 0.08999558228411172, 0.15402901777507444, -0.11157234053887231, -0.2058583610740147, -0.3044326600373576, -0.17648972157192858, -0.14686744656217726, 0.13377833029662725, -0.03040209730128194, -0.15590556995256952, 0.36339912642724814, 0.1890379953510618, 0.16679097905902093, 0.0385637158013292, 0.22401254967247186, 0.14363149417147628, 0.05029181968910914, 0.04884617725681317, 0.21424334519787838, 0.14147959747596792, 0.08267371382466272, -0.31798947121163734, 0.09648650995406666, 0.02287160255701134] |
1,802.05049 | Graphene ground states | Graphene is locally two-dimensional but not flat. Nanoscale ripples appear in
suspended samples and rolling-up often occurs when boundaries are not fixed. We
address this variety of graphene geometries by classifying all ground-state
deformations of the hexagonal lattice with respect to configurational energies
including two- and three-body terms. As a consequence, we prove that all
ground-state deformations are either periodic in one direction, as in the case
of ripples, or rolled up, as in the case of nanotubes.
| cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.soft math-ph math.AP math.MP | graphene is locally twodimensional but not flat nanoscale ripples appear in suspended samples and rollingup often occurs when boundaries are not fixed we address this variety of graphene geometries by classifying all groundstate deformations of the hexagonal lattice with respect to configurational energies including two and threebody terms as a consequence we prove that all groundstate deformations are either periodic in one direction as in the case of ripples or rolled up as in the case of nanotubes | [['graphene', 'is', 'locally', 'twodimensional', 'but', 'not', 'flat', 'nanoscale', 'ripples', 'appear', 'in', 'suspended', 'samples', 'and', 'rollingup', 'often', 'occurs', 'when', 'boundaries', 'are', 'not', 'fixed', 'we', 'address', 'this', 'variety', 'of', 'graphene', 'geometries', 'by', 'classifying', 'all', 'groundstate', 'deformations', 'of', 'the', 'hexagonal', 'lattice', 'with', 'respect', 'to', 'configurational', 'energies', 'including', 'two', 'and', 'threebody', 'terms', 'as', 'a', 'consequence', 'we', 'prove', 'that', 'all', 'groundstate', 'deformations', 'are', 'either', 'periodic', 'in', 'one', 'direction', 'as', 'in', 'the', 'case', 'of', 'ripples', 'or', 'rolled', 'up', 'as', 'in', 'the', 'case', 'of', 'nanotubes']] | [-0.15324789084768733, 0.19948544043999833, 0.02550357275714095, 0.0022044025886899386, 0.005986398118786896, -0.14055457884947267, -0.005925323614158118, 0.4567546894152959, -0.27549404753013873, -0.2465602366204481, 0.09048594349923615, -0.28351286134849757, -0.1510697567077258, 0.1805086215892329, -0.033634925535760626, 0.04005059420775909, 0.04219312801097448, -0.029652372719003603, -0.06674238003921719, -0.2425467269987656, 0.2935696955149372, -0.01918333966825277, 0.28700685944073856, 0.07941060086998802, 0.004939669677510093, 0.0002349417429799453, 0.09860154131475167, 0.08929142446663135, -0.1392982277623863, 0.0501986027826579, 0.26846443203827125, -0.11068809287061389, 0.18830421870240036, -0.47281097279240686, -0.20829194861774644, 0.09634412411469384, 0.17245123878073615, 0.18828882379696155, -0.00548819014026473, -0.23029392863958117, 0.10340101932151577, -0.1272435309484792, -0.15515309538190755, -0.09921250243981679, -0.00518372511335959, 0.04847772419452667, -0.14371341077658611, 0.08445257465474498, 0.0825963795889551, 0.060844042601111606, -0.12288713080581659, -0.09173205552491336, -0.1086970837130092, 0.10062232937921997, 0.07729091466320917, 0.02096931096046972, 0.16597213422378096, -0.1263784395906931, -0.09681614782088079, 0.4914148531089991, -0.025666540164727334, -0.23388384522583622, 0.2074512678485077, -0.17704528087200835, -0.10092754228315197, 0.14398192145073643, 0.11076729530349183, 0.11879170650186446, -0.13095712099386267, 0.09343752502433908, -0.03030051770978249, 0.10038343411034499, 0.1805954606940922, 0.045033887321224965, 0.22897700879436272, 0.13462830032520473, 0.10694165664533965, 0.16818257556177485, -0.07517851177507485, -0.058529309498576015, -0.27577130907239056, -0.15841066378813523, -0.18828056099561927, 0.08406514891174037, -0.048040010189885296, -0.26408721308391064, 0.37195319708627766, 0.0376193570988014, 0.23496526840310067, -0.005369919495513806, 0.2003593157726125, 0.02244409096863073, 0.0839525438988438, 0.029359617133218892, 0.2179890856391583, 0.08874863860770486, 0.01657594083688962, -0.14195610175374895, 0.003197292724880987, 0.04474666690788208] |
1,802.0505 | A Blockchain Based Liability Attribution Framework for Autonomous
Vehicles | The advent of autonomous vehicles is envisaged to disrupt the auto insurance
liability model.Compared to the the current model where liability is largely
attributed to the driver,autonomous vehicles necessitate the consideration of
other entities in the automotive ecosystem including the auto
manufacturer,software provider,service technician and the vehicle owner.The
proliferation of sensors and connecting technologies in autonomous vehicles
enables an autonomous vehicle to gather sufficient data for liability
attribution,yet increased connectivity exposes the vehicle to attacks from
interacting entities.These possibilities motivate potential liable entities to
repudiate their involvement in a collision event to evade liability. While the
data collected from vehicular sensors and vehicular communications is an
integral part of the evidence for arbitrating liability in the event of an
accident,there is also a need to record all interactions between the
aforementioned entities to identify potential instances of negligence that may
have played a role in the accident.In this paper,we propose a BlockChain(BC)
based framework that integrates the concerned entities in the liability model
and provides untampered evidence for liability attribution and adjudication.We
first describe the liability attribution model, identify key requirements and
describe the adversarial capabilities of entities. Also,we present a detailed
description of data contributing to evidence.Our framework uses permissioned BC
and partitions the BC to tailor data access to relevant BC
participants.Finally,we conduct a security analysis to verify that the
identified requirements are met and resilience of our proposed framework to
identified attacks.
| cs.CR cs.CY | the advent of autonomous vehicles is envisaged to disrupt the auto insurance liability modelcompared to the the current model where liability is largely attributed to the driverautonomous vehicles necessitate the consideration of other entities in the automotive ecosystem including the auto manufacturersoftware providerservice technician and the vehicle ownerthe proliferation of sensors and connecting technologies in autonomous vehicles enables an autonomous vehicle to gather sufficient data for liability attributionyet increased connectivity exposes the vehicle to attacks from interacting entitiesthese possibilities motivate potential liable entities to repudiate their involvement in a collision event to evade liability while the data collected from vehicular sensors and vehicular communications is an integral part of the evidence for arbitrating liability in the event of an accidentthere is also a need to record all interactions between the aforementioned entities to identify potential instances of negligence that may have played a role in the accidentin this paperwe propose a blockchainbc based framework that integrates the concerned entities in the liability model and provides untampered evidence for liability attribution and adjudicationwe first describe the liability attribution model identify key requirements and describe the adversarial capabilities of entities alsowe present a detailed description of data contributing to evidenceour framework uses permissioned bc and partitions the bc to tailor data access to relevant bc participantsfinallywe conduct a security analysis to verify that the identified requirements are met and resilience of our proposed framework to identified attacks | [['the', 'advent', 'of', 'autonomous', 'vehicles', 'is', 'envisaged', 'to', 'disrupt', 'the', 'auto', 'insurance', 'liability', 'modelcompared', 'to', 'the', 'the', 'current', 'model', 'where', 'liability', 'is', 'largely', 'attributed', 'to', 'the', 'driverautonomous', 'vehicles', 'necessitate', 'the', 'consideration', 'of', 'other', 'entities', 'in', 'the', 'automotive', 'ecosystem', 'including', 'the', 'auto', 'manufacturersoftware', 'providerservice', 'technician', 'and', 'the', 'vehicle', 'ownerthe', 'proliferation', 'of', 'sensors', 'and', 'connecting', 'technologies', 'in', 'autonomous', 'vehicles', 'enables', 'an', 'autonomous', 'vehicle', 'to', 'gather', 'sufficient', 'data', 'for', 'liability', 'attributionyet', 'increased', 'connectivity', 'exposes', 'the', 'vehicle', 'to', 'attacks', 'from', 'interacting', 'entitiesthese', 'possibilities', 'motivate', 'potential', 'liable', 'entities', 'to', 'repudiate', 'their', 'involvement', 'in', 'a', 'collision', 'event', 'to', 'evade', 'liability', 'while', 'the', 'data', 'collected', 'from', 'vehicular', 'sensors', 'and', 'vehicular', 'communications', 'is', 'an', 'integral', 'part', 'of', 'the', 'evidence', 'for', 'arbitrating', 'liability', 'in', 'the', 'event', 'of', 'an', 'accidentthere', 'is', 'also', 'a', 'need', 'to', 'record', 'all', 'interactions', 'between', 'the', 'aforementioned', 'entities', 'to', 'identify', 'potential', 'instances', 'of', 'negligence', 'that', 'may', 'have', 'played', 'a', 'role', 'in', 'the', 'accidentin', 'this', 'paperwe', 'propose', 'a', 'blockchainbc', 'based', 'framework', 'that', 'integrates', 'the', 'concerned', 'entities', 'in', 'the', 'liability', 'model', 'and', 'provides', 'untampered', 'evidence', 'for', 'liability', 'attribution', 'and', 'adjudicationwe', 'first', 'describe', 'the', 'liability', 'attribution', 'model', 'identify', 'key', 'requirements', 'and', 'describe', 'the', 'adversarial', 'capabilities', 'of', 'entities', 'alsowe', 'present', 'a', 'detailed', 'description', 'of', 'data', 'contributing', 'to', 'evidenceour', 'framework', 'uses', 'permissioned', 'bc', 'and', 'partitions', 'the', 'bc', 'to', 'tailor', 'data', 'access', 'to', 'relevant', 'bc', 'participantsfinallywe', 'conduct', 'a', 'security', 'analysis', 'to', 'verify', 'that', 'the', 'identified', 'requirements', 'are', 'met', 'and', 'resilience', 'of', 'our', 'proposed', 'framework', 'to', 'identified', 'attacks']] | [-0.17842646344850124, 0.004330329057592206, -0.06112218402123691, 0.06003662967280409, -0.10919805478959067, -0.15256919278679332, 0.07375536642356163, 0.33890087853462714, -0.24433421775245587, -0.3277473299688584, 0.0970309467814225, -0.3156806805090054, -0.12570224701938731, 0.1637686435898833, -0.14240930224391254, 0.060952682752867006, 0.05771380359294346, 0.038282434526319103, 0.06430942429070202, -0.2060833038087842, 0.3112927211075182, 0.05780523680444169, 0.32248332793824375, 0.09768032427533185, 0.0933797879392063, 0.010980923823710229, -0.07555281860137207, -0.035845263001114666, -0.07790636902132679, 0.1658875740666534, 0.3309504359725628, 0.21847145600026255, 0.3257937205804361, -0.4754719605316987, -0.20342882728908915, 0.10680353318693468, 0.11920487178648981, 0.05295812760543724, 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1,802.05051 | A note on packing of uniform hypergraphs | A packing of two $k$-uniform hypergraphs $H_1$ and $H_2$ is a set $\{H_1',
H_2'\}$ of edge-disjoint sub-hypergraphs of the complete $k$-uniform hypergraph
$K_n^{(k)}$ such that $H_1'\cong H_1$ and $H_2'\cong H_2$. Whilst the problem
of packing of graphs (i.e. 2-uniform hypergraphs) has been studied extensively
since seventies with many sharp results, much less is known about packing of
general hypergraphs. In this paper we attempt to find the minimum possible sum
of sizes $m(n,k)$ of two $k$-uniform, $n$-vertex hypergaphs which do not pack.
We also prove a sufficient condition on the product of maximum degrees, which
guarantees the packing.
| math.CO | a packing of two kuniform hypergraphs h_1 and h_2 is a set h_1 h_2 of edgedisjoint subhypergraphs of the complete kuniform hypergraph k_nk such that h_1cong h_1 and h_2cong h_2 whilst the problem of packing of graphs ie 2uniform hypergraphs has been studied extensively since seventies with many sharp results much less is known about packing of general hypergraphs in this paper we attempt to find the minimum possible sum of sizes mnk of two kuniform nvertex hypergaphs which do not pack we also prove a sufficient condition on the product of maximum degrees which guarantees the packing | [['a', 'packing', 'of', 'two', 'kuniform', 'hypergraphs', 'h_1', 'and', 'h_2', 'is', 'a', 'set', 'h_1', 'h_2', 'of', 'edgedisjoint', 'subhypergraphs', 'of', 'the', 'complete', 'kuniform', 'hypergraph', 'k_nk', 'such', 'that', 'h_1cong', 'h_1', 'and', 'h_2cong', 'h_2', 'whilst', 'the', 'problem', 'of', 'packing', 'of', 'graphs', 'ie', '2uniform', 'hypergraphs', 'has', 'been', 'studied', 'extensively', 'since', 'seventies', 'with', 'many', 'sharp', 'results', 'much', 'less', 'is', 'known', 'about', 'packing', 'of', 'general', 'hypergraphs', 'in', 'this', 'paper', 'we', 'attempt', 'to', 'find', 'the', 'minimum', 'possible', 'sum', 'of', 'sizes', 'mnk', 'of', 'two', 'kuniform', 'nvertex', 'hypergaphs', 'which', 'do', 'not', 'pack', 'we', 'also', 'prove', 'a', 'sufficient', 'condition', 'on', 'the', 'product', 'of', 'maximum', 'degrees', 'which', 'guarantees', 'the', 'packing']] | [-0.1533832848193318, 0.16514120824770848, -0.025601154377606388, 0.048656269445928046, -0.06653913444218536, -0.14364018891258942, 0.01528412698947553, 0.3873080687553738, -0.2307195963949198, -0.3327725160246094, 0.09940193867441849, -0.28941568545997143, -0.0880308387556094, 0.050615360341907945, -0.11551431473708362, 0.104312427516561, 0.11675387380334239, 0.08354402612773508, 0.0703532421921409, -0.3273019769306605, 0.2453106167910543, -0.06799804262118414, 0.1684880162307915, 0.1762019189482089, 0.045144559893136225, 0.0005972020589979365, 0.04224951239666552, 0.1044450533518102, -0.320033127364771, 0.10900255474674243, 0.23867549403318358, 0.19623405370900096, 0.26601366522178677, -0.37540649601335946, -0.13990571741790822, 0.30791952448998927, 0.15969957616349953, 0.03605773892437961, 0.030657576170294003, -0.15627739019691944, 0.10450551120690459, -0.09433433200562528, -0.045948955572384875, 0.020018578978124424, 0.09497239206393715, -0.00508957482331122, -0.30531329932273366, -0.00754409424826008, 0.1484893535283239, 0.03269187485178312, 0.046690199174918234, -0.23019085259511485, -0.07578488551128733, 0.046550559425668325, -0.0733177696383791, 0.038394872068844656, 0.05085396608531786, -0.11209288932877826, -0.1573693045647815, 0.41632325056707487, -0.007588819164084271, -0.12158908416313352, 0.13493394355949326, -0.16577917706066123, -0.25687605134832364, 0.16093610854295548, 0.10856935562211827, 0.16769274654992236, -0.12288577881311842, 0.10608713025067118, -0.20622804623174792, 0.12412361369933933, 0.1901743850806573, 0.07356587279173255, 0.09842406759222892, 0.09154990130627993, 0.23067182640261308, 0.21814944064681185, 0.04484712568470665, -0.007851549386032275, -0.2344740616196456, -0.1395056715021686, -0.23431984299289374, 0.08565549118323663, -0.17642859731343682, -0.2048466358198008, 0.3873669528014337, 0.07383274840928304, 0.1927886761695845, 0.12055515816367308, 0.23277738151955418, 0.02625235443292695, 0.012523278849888205, 0.14419536940113176, 0.17125021950657052, 0.2587846965761855, -0.0682136818310634, -0.1167890793197633, 0.04753727331990376, 0.11107695751222006] |
1,802.05052 | Universality of Poisson-driven plasma fluctuations in the Alcator C-Mod
scrape-off layer | Large-amplitude, intermittent fluctuations are ubiquitous in the boundary
region of magnetically confined plasmas and lead to detrimental plasma-wall
interactions in the next-generation, high duty cycle fusion power experiments.
Using gas puff imaging data time series from the scrape-off layer in the
Alcator C-Mod device, it is here demonstrated that the large-amplitude
fluctuations can be described as a super-position of pulses with fixed shape
and constant duration. By applying a new deconvolution algorithm on the data
time series with a two-sided exponential pulse function, the arrival times and
amplitudes of the pulses can be estimated and the measurement time series can
be reconstructed with high accuracy. The pulse amplitudes are shown to follow
an exponential distribution. The waiting times between pulses are uncorrelated,
their distribution has an exponential tail, and the number of arrivals is a
linear function of time. This demonstrates that pulse arrivals follow a
homogeneous Poisson process. Identical statistical properties apply to both
ohmic and high confinement mode plasmas, clearly demonstrating universality of
the fluctuation statistics in the boundary region of Alcator C-Mod.
| physics.plasm-ph | largeamplitude intermittent fluctuations are ubiquitous in the boundary region of magnetically confined plasmas and lead to detrimental plasmawall interactions in the nextgeneration high duty cycle fusion power experiments using gas puff imaging data time series from the scrapeoff layer in the alcator cmod device it is here demonstrated that the largeamplitude fluctuations can be described as a superposition of pulses with fixed shape and constant duration by applying a new deconvolution algorithm on the data time series with a twosided exponential pulse function the arrival times and amplitudes of the pulses can be estimated and the measurement time series can be reconstructed with high accuracy the pulse amplitudes are shown to follow an exponential distribution the waiting times between pulses are uncorrelated their distribution has an exponential tail and the number of arrivals is a linear function of time this demonstrates that pulse arrivals follow a homogeneous poisson process identical statistical properties apply to both ohmic and high confinement mode plasmas clearly demonstrating universality of the fluctuation statistics in the boundary region of alcator cmod | [['largeamplitude', 'intermittent', 'fluctuations', 'are', 'ubiquitous', 'in', 'the', 'boundary', 'region', 'of', 'magnetically', 'confined', 'plasmas', 'and', 'lead', 'to', 'detrimental', 'plasmawall', 'interactions', 'in', 'the', 'nextgeneration', 'high', 'duty', 'cycle', 'fusion', 'power', 'experiments', 'using', 'gas', 'puff', 'imaging', 'data', 'time', 'series', 'from', 'the', 'scrapeoff', 'layer', 'in', 'the', 'alcator', 'cmod', 'device', 'it', 'is', 'here', 'demonstrated', 'that', 'the', 'largeamplitude', 'fluctuations', 'can', 'be', 'described', 'as', 'a', 'superposition', 'of', 'pulses', 'with', 'fixed', 'shape', 'and', 'constant', 'duration', 'by', 'applying', 'a', 'new', 'deconvolution', 'algorithm', 'on', 'the', 'data', 'time', 'series', 'with', 'a', 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1,802.05053 | Ripples in graphene: A variational approach | Suspended graphene samples are observed to be gently rippled rather than
being flat. In [M. Friedrich, U. Stefanelli. Graphene ground states,
arXiv:1802.05049], we have checked that this nonplanarity can be rigorously
described within the classical molecular-mechanical frame of
configurational-energy minimization. There, we have identified all ground-state
configurations with graphene topology with respect to classes of
next-to-nearest neighbor interaction energies and classified their fine nonflat
geometries.
In this second paper on graphene nonflatness, we refine the analysis further
and prove the emergence of wave patterning. Moving within the frame of [M.
Friedrich, U. Stefanelli. Graphene ground states, arXiv:1802.05049], rippling
formation in graphene is reduced to a two-dimensional problem for
one-dimensional chains. Specifically, we show that almost minimizers of the
configurational energy develop waves with specific wavelength, independently of
the size of the sample. This corresponds remarkably to experiments and
simulations.
| cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.soft math-ph math.AP math.MP | suspended graphene samples are observed to be gently rippled rather than being flat in m friedrich u stefanelli graphene ground states arxiv180205049 we have checked that this nonplanarity can be rigorously described within the classical molecularmechanical frame of configurationalenergy minimization there we have identified all groundstate configurations with graphene topology with respect to classes of nexttonearest neighbor interaction energies and classified their fine nonflat geometries in this second paper on graphene nonflatness we refine the analysis further and prove the emergence of wave patterning moving within the frame of m friedrich u stefanelli graphene ground states arxiv180205049 rippling formation in graphene is reduced to a twodimensional problem for onedimensional chains specifically we show that almost minimizers of the configurational energy develop waves with specific wavelength independently of the size of the sample this corresponds remarkably to experiments and simulations | [['suspended', 'graphene', 'samples', 'are', 'observed', 'to', 'be', 'gently', 'rippled', 'rather', 'than', 'being', 'flat', 'in', 'm', 'friedrich', 'u', 'stefanelli', 'graphene', 'ground', 'states', 'arxiv180205049', 'we', 'have', 'checked', 'that', 'this', 'nonplanarity', 'can', 'be', 'rigorously', 'described', 'within', 'the', 'classical', 'molecularmechanical', 'frame', 'of', 'configurationalenergy', 'minimization', 'there', 'we', 'have', 'identified', 'all', 'groundstate', 'configurations', 'with', 'graphene', 'topology', 'with', 'respect', 'to', 'classes', 'of', 'nexttonearest', 'neighbor', 'interaction', 'energies', 'and', 'classified', 'their', 'fine', 'nonflat', 'geometries', 'in', 'this', 'second', 'paper', 'on', 'graphene', 'nonflatness', 'we', 'refine', 'the', 'analysis', 'further', 'and', 'prove', 'the', 'emergence', 'of', 'wave', 'patterning', 'moving', 'within', 'the', 'frame', 'of', 'm', 'friedrich', 'u', 'stefanelli', 'graphene', 'ground', 'states', 'arxiv180205049', 'rippling', 'formation', 'in', 'graphene', 'is', 'reduced', 'to', 'a', 'twodimensional', 'problem', 'for', 'onedimensional', 'chains', 'specifically', 'we', 'show', 'that', 'almost', 'minimizers', 'of', 'the', 'configurational', 'energy', 'develop', 'waves', 'with', 'specific', 'wavelength', 'independently', 'of', 'the', 'size', 'of', 'the', 'sample', 'this', 'corresponds', 'remarkably', 'to', 'experiments', 'and', 'simulations']] | [-0.15376893203595982, 0.13617129372569786, -0.03807732531362597, 0.02718911710133612, 0.0013787907390745684, -0.1465095239246319, 0.04815149780252421, 0.4263196802793947, -0.25226794428753613, -0.2880382967512774, 0.02037415947929463, -0.28185959562987967, -0.0976769605973352, 0.12748338552260333, -0.01296943610684727, 0.026021082543165368, 0.06899144086363616, -0.028687232851927334, -0.05989576748962624, -0.23798567624351777, 0.2883753127175356, 0.039400131383445114, 0.26652083899277973, 0.038924113569972926, 0.028724673695465112, -0.0020877535280305892, 0.0672011529947186, 0.05876074956990231, -0.2017365367660472, 0.09835217502276304, 0.235013323247532, -0.030906447239163647, 0.23810165075188064, -0.45295946235974577, -0.21273816617287913, 0.08301411434727282, 0.13575019250171916, 0.14016116294763326, -0.004821168160774773, -0.31214799230870355, 0.09918377233321628, -0.11867786534062094, -0.16204684220172247, -0.06021690005025662, 0.03447040460784646, 0.029667850371504968, -0.17690434206879752, 0.0823978602540378, 0.042035457560011896, 0.03117622671005152, -0.12009455376349198, -0.09255637904896181, -0.09789492787197507, 0.07424734404519447, 0.04400243532076916, 0.05370880477301612, 0.12873837128213114, -0.0603543518758242, -0.08401495503580116, 0.38678630737259106, -0.05459544583968904, -0.20598511912633993, 0.19284814292811514, -0.15164028712110045, -0.08502598798333887, 0.11953141354709207, 0.11592077805920888, 0.10459134949932751, -0.12313348135691793, 0.104312606986669, -0.06284971531428762, 0.14883968148698093, 0.12904260422424962, 0.02690379080526969, 0.19922634489194024, 0.18100639699054333, 0.06885956283247865, 0.1510028525483315, -0.08607813655843903, -0.049888115412185845, -0.26188984757070155, -0.1593906806425794, -0.2058572298170903, 0.08055383098936171, -0.0460410389552956, -0.19153850770774572, 0.4014884464593385, 0.10798942495228617, 0.17527670649167917, 0.04189478493507897, 0.20053266079904622, 0.09489510640816982, 0.055346246741999706, 0.06606398063398528, 0.2603385169538395, 0.1290490830947152, 0.06559045694816365, -0.18138600329150315, 0.002200595404514495, 0.0461088502266006] |
1,802.05054 | GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement
Learning Algorithms | In continuous action domains, standard deep reinforcement learning algorithms
like DDPG suffer from inefficient exploration when facing sparse or deceptive
reward problems. Conversely, evolutionary and developmental methods focusing on
exploration like Novelty Search, Quality-Diversity or Goal Exploration
Processes explore more robustly but are less efficient at fine-tuning policies
using gradient descent. In this paper, we present the GEP-PG approach, taking
the best of both worlds by sequentially combining a Goal Exploration Process
and two variants of DDPG. We study the learning performance of these components
and their combination on a low dimensional deceptive reward problem and on the
larger Half-Cheetah benchmark. We show that DDPG fails on the former and that
GEP-PG improves over the best DDPG variant in both environments. Supplementary
videos and discussion can be found at http://frama.link/gep_pg, the code at
http://github.com/flowersteam/geppg.
| cs.LG | in continuous action domains standard deep reinforcement learning algorithms like ddpg suffer from inefficient exploration when facing sparse or deceptive reward problems conversely evolutionary and developmental methods focusing on exploration like novelty search qualitydiversity or goal exploration processes explore more robustly but are less efficient at finetuning policies using gradient descent in this paper we present the geppg approach taking the best of both worlds by sequentially combining a goal exploration process and two variants of ddpg we study the learning performance of these components and their combination on a low dimensional deceptive reward problem and on the larger halfcheetah benchmark we show that ddpg fails on the former and that geppg improves over the best ddpg variant in both environments supplementary videos and discussion can be found at httpframalinkgep_pg the code at httpgithubcomflowersteamgeppg | [['in', 'continuous', 'action', 'domains', 'standard', 'deep', 'reinforcement', 'learning', 'algorithms', 'like', 'ddpg', 'suffer', 'from', 'inefficient', 'exploration', 'when', 'facing', 'sparse', 'or', 'deceptive', 'reward', 'problems', 'conversely', 'evolutionary', 'and', 'developmental', 'methods', 'focusing', 'on', 'exploration', 'like', 'novelty', 'search', 'qualitydiversity', 'or', 'goal', 'exploration', 'processes', 'explore', 'more', 'robustly', 'but', 'are', 'less', 'efficient', 'at', 'finetuning', 'policies', 'using', 'gradient', 'descent', 'in', 'this', 'paper', 'we', 'present', 'the', 'geppg', 'approach', 'taking', 'the', 'best', 'of', 'both', 'worlds', 'by', 'sequentially', 'combining', 'a', 'goal', 'exploration', 'process', 'and', 'two', 'variants', 'of', 'ddpg', 'we', 'study', 'the', 'learning', 'performance', 'of', 'these', 'components', 'and', 'their', 'combination', 'on', 'a', 'low', 'dimensional', 'deceptive', 'reward', 'problem', 'and', 'on', 'the', 'larger', 'halfcheetah', 'benchmark', 'we', 'show', 'that', 'ddpg', 'fails', 'on', 'the', 'former', 'and', 'that', 'geppg', 'improves', 'over', 'the', 'best', 'ddpg', 'variant', 'in', 'both', 'environments', 'supplementary', 'videos', 'and', 'discussion', 'can', 'be', 'found', 'at', 'httpframalinkgep_pg', 'the', 'code', 'at', 'httpgithubcomflowersteamgeppg']] | [-0.02119916927371047, 0.03799450938646315, -0.06200988820196609, 0.08709696473015631, -0.11635878749339926, -0.15995921350479353, 0.06831968591855415, 0.47586400592417427, -0.27824152369673055, -0.3209404827335454, 0.13526644691151116, -0.24694619971242818, -0.18615726812982536, 0.21809766389549512, -0.10658312617857574, 0.022678459070227815, 0.11262416853710558, -0.004477737002272272, -0.047953429561334124, -0.2750106371522909, 0.3122950914090104, 0.04279206507415052, 0.2840814751812793, -0.023451280222754136, 0.12454577926264117, 0.009656044340579572, -0.03884796743372907, 0.013167911533717856, -0.07572265116157889, 0.13862839990179054, 0.2867753129050305, 0.20576029376719485, 0.3549850626044314, -0.40250094409919146, -0.2007480725861211, 0.13316777764085794, 0.13686792142724505, 0.08743251134486248, -0.058441932184933015, -0.2992122284362488, 0.054734113294574796, -0.12444070796835038, 0.0012048269749026406, -0.1319240759423172, -0.06797815631073194, -0.01530782811195505, -0.2806608973099201, 0.014286820699150363, 0.07528536826033484, 0.03907919387248429, -0.057360450670151324, -0.1808711935123993, 0.060776883832824584, 0.11016768371535529, 0.04634165874515681, 0.0543927151628657, 0.153564957076345, -0.1929328113177083, -0.18086006713212666, 0.3612113921430357, -0.08270030787609743, -0.1633554220439471, 0.2758927621568243, -0.06387798970381757, -0.1518144681838087, 0.08771447600465211, 0.26037831400577544, 0.19344546990098685, -0.11591640543988571, 0.06357082150189496, 0.01413381715996586, 0.13265668583864515, 0.036682856237431144, -0.019970121171685274, 0.1554466554468187, 0.23979917921259944, 0.1263355829476385, 0.10935212529853522, -0.040626830625996896, -0.15901370014233346, -0.20729580919512294, -0.0897515764227137, -0.1480954382550959, -0.014648287558829355, -0.09204571770974188, -0.09429503213190897, 0.3480248540096606, 0.20764148286958295, 0.19073946508367293, 0.12375191304211815, 0.35730287535680516, 0.022557136793197555, 0.06003288570862038, 0.13865050979339602, 0.20086756690976804, -0.032125524941930605, 0.11185815038819176, -0.2218171988232908, 0.12775540603395324, 0.04136163803085572] |
1,802.05055 | Classification of Scientific Papers With Big Data Technologies | Data sizes that cannot be processed by conventional data storage and analysis
systems are named as Big Data.It also refers to nex technologies developed to
store, process and analyze large amounts of data. Automatic information
retrieval about the contents of a large number of documents produced by
different sources, identifying research fields and topics, extraction of the
document abstracts, or discovering patterns are some of the topics that have
been studied in the field of big data.In this study, Naive Bayes classification
algorithm, which is run on a data set consisting of scientific articles, has
been tried to automatically determine the classes to which these documents
belong. We have developed an efficient system that can analyze the Turkish
scientific documents with the distributed document classification algorithm run
on the Cloud Computing infrastructure. The Apache Mahout library is used in the
study. The servers required for classifying and clustering distributed
documents are
| cs.DC cs.DL | data sizes that cannot be processed by conventional data storage and analysis systems are named as big datait also refers to nex technologies developed to store process and analyze large amounts of data automatic information retrieval about the contents of a large number of documents produced by different sources identifying research fields and topics extraction of the document abstracts or discovering patterns are some of the topics that have been studied in the field of big datain this study naive bayes classification algorithm which is run on a data set consisting of scientific articles has been tried to automatically determine the classes to which these documents belong we have developed an efficient system that can analyze the turkish scientific documents with the distributed document classification algorithm run on the cloud computing infrastructure the apache mahout library is used in the study the servers required for classifying and clustering distributed documents are | [['data', 'sizes', 'that', 'can', 'not', 'be', 'processed', 'by', 'conventional', 'data', 'storage', 'and', 'analysis', 'systems', 'are', 'named', 'as', 'big', 'datait', 'also', 'refers', 'to', 'nex', 'technologies', 'developed', 'to', 'store', 'process', 'and', 'analyze', 'large', 'amounts', 'of', 'data', 'automatic', 'information', 'retrieval', 'about', 'the', 'contents', 'of', 'a', 'large', 'number', 'of', 'documents', 'produced', 'by', 'different', 'sources', 'identifying', 'research', 'fields', 'and', 'topics', 'extraction', 'of', 'the', 'document', 'abstracts', 'or', 'discovering', 'patterns', 'are', 'some', 'of', 'the', 'topics', 'that', 'have', 'been', 'studied', 'in', 'the', 'field', 'of', 'big', 'datain', 'this', 'study', 'naive', 'bayes', 'classification', 'algorithm', 'which', 'is', 'run', 'on', 'a', 'data', 'set', 'consisting', 'of', 'scientific', 'articles', 'has', 'been', 'tried', 'to', 'automatically', 'determine', 'the', 'classes', 'to', 'which', 'these', 'documents', 'belong', 'we', 'have', 'developed', 'an', 'efficient', 'system', 'that', 'can', 'analyze', 'the', 'turkish', 'scientific', 'documents', 'with', 'the', 'distributed', 'document', 'classification', 'algorithm', 'run', 'on', 'the', 'cloud', 'computing', 'infrastructure', 'the', 'apache', 'mahout', 'library', 'is', 'used', 'in', 'the', 'study', 'the', 'servers', 'required', 'for', 'classifying', 'and', 'clustering', 'distributed', 'documents', 'are']] | [-0.08691447137656676, 0.050989785719617715, -0.06260684843628521, 0.07408936359691229, -0.11051908235056448, -0.12013769837549741, 0.03612453178931518, 0.37820880373596755, -0.27738632380619255, -0.3752678795840199, 0.13977505402152401, -0.3273438612170714, -0.05657164848066474, 0.19860962886320377, -0.07925092596805801, 0.05008989860959302, 0.10527386449546994, 0.0504525587694891, -0.012879547375058266, -0.31889034564435287, 0.3278061997307783, 0.06262615232232124, 0.3643093482088788, 0.0021487157665481056, 0.04427680847890626, -0.033599494072596395, -0.13961852497212882, -0.01108033054410235, -0.07291668584476658, 0.16760014194848114, 0.3665501928679939, 0.27162290466520445, 0.28978306163519035, -0.3968919792984563, -0.17471617577891602, 0.10463074132751085, 0.15299223969065534, 0.0893622819505828, -0.058222658572240585, -0.30607604695557566, 0.13440548718024634, -0.17842385525383228, -0.026588405971108984, -0.14164407681183597, 0.0486088744586787, 0.041785131101373975, -0.21119959292761786, -0.029727651153064614, 0.019350922139174623, 0.09185530134556374, -0.005880783221647634, -0.12402360431932673, 0.0385375861453787, 0.1751083360240476, 0.037965066430555645, 0.0188371355202674, 0.14806462392076164, -0.12226093519252333, -0.1491761120912423, 0.3949464427454299, -0.0025461283098832752, -0.1289977671296679, 0.1764694727822452, -0.02428677674431942, -0.18115119165189467, 0.10073089654447119, 0.2615141089757488, 0.0856237635751696, -0.24374663129473398, 0.06204185003604691, -0.038608241734389016, 0.20059658979421088, 0.05946930398931727, 0.002521730123063255, 0.20185151416195654, 0.19933325891370737, -0.01839795944856872, 0.12890229766459302, -0.10686892210689716, -0.06804212224271491, -0.20579186068176855, -0.15587762178313969, -0.20222342111733987, -0.02948235905731915, -0.05528485223208248, -0.17257236225161346, 0.37807829804047577, 0.19862975806494146, 0.16768459587566262, -0.008844109157124828, 0.289066021537445, 0.01740687760062237, 0.14713357438890134, 0.13261250888708195, 0.11663244814879267, 0.015947834035614505, 0.18313327051797196, -0.1030134369135148, 0.07709944673115388, 0.015932829744231543] |
1,802.05056 | Three-dimensional effective theories for the two Higgs doublet model at
high temperature | Due to the infrared problem of high-temperature field theory, a robust study
of the electroweak phase transition (EWPT) requires use of non-perturbative
methods. We apply the method of high-temperature dimensional reduction to the
two Higgs doublet model (2HDM) to obtain three-dimensional effective theories
that can be used for non-perturbative simulations. A detailed derivation of the
mapping between the full four-dimensional and the effective three-dimensional
theories is presented. The results will be used in future lattice studies of
the 2HDM. In the limit of large mass mixing between the doublets, existing
lattice results can be recycled. The results of such a study are presented in a
companion paper.
| hep-ph | due to the infrared problem of hightemperature field theory a robust study of the electroweak phase transition ewpt requires use of nonperturbative methods we apply the method of hightemperature dimensional reduction to the two higgs doublet model 2hdm to obtain threedimensional effective theories that can be used for nonperturbative simulations a detailed derivation of the mapping between the full fourdimensional and the effective threedimensional theories is presented the results will be used in future lattice studies of the 2hdm in the limit of large mass mixing between the doublets existing lattice results can be recycled the results of such a study are presented in a companion paper | [['due', 'to', 'the', 'infrared', 'problem', 'of', 'hightemperature', 'field', 'theory', 'a', 'robust', 'study', 'of', 'the', 'electroweak', 'phase', 'transition', 'ewpt', 'requires', 'use', 'of', 'nonperturbative', 'methods', 'we', 'apply', 'the', 'method', 'of', 'hightemperature', 'dimensional', 'reduction', 'to', 'the', 'two', 'higgs', 'doublet', 'model', '2hdm', 'to', 'obtain', 'threedimensional', 'effective', 'theories', 'that', 'can', 'be', 'used', 'for', 'nonperturbative', 'simulations', 'a', 'detailed', 'derivation', 'of', 'the', 'mapping', 'between', 'the', 'full', 'fourdimensional', 'and', 'the', 'effective', 'threedimensional', 'theories', 'is', 'presented', 'the', 'results', 'will', 'be', 'used', 'in', 'future', 'lattice', 'studies', 'of', 'the', '2hdm', 'in', 'the', 'limit', 'of', 'large', 'mass', 'mixing', 'between', 'the', 'doublets', 'existing', 'lattice', 'results', 'can', 'be', 'recycled', 'the', 'results', 'of', 'such', 'a', 'study', 'are', 'presented', 'in', 'a', 'companion', 'paper']] | [-0.09608320501049823, 0.14947572150746377, -0.07329084075743629, 0.09850973460636163, -0.07514684955441506, -0.12815797261928566, 0.024943086134800774, 0.35023803880142274, -0.1854134581539188, -0.2572193061497724, 0.08932812725711683, -0.2297010238534797, -0.12826957208948714, 0.16950078851273545, -0.006586032754210668, 0.060893046626142255, 0.04660692160392058, -0.03073039949462514, -0.12219605027158335, -0.24771257461631827, 0.3064029407513406, 0.012857503066204977, 0.23953403373222762, 0.07300587548552273, 0.040065394892905636, -0.02470049782542982, -0.011355989895517303, 0.016890880782331263, -0.1665013918379636, 0.13687983966785022, 0.23521731644172536, 0.06784943097801967, 0.1658043623325267, -0.4032719238687342, -0.2237325543189578, 0.0926302860112356, 0.1472452424301235, 0.1794581866266084, -0.04848713892572951, -0.28624735955392644, 0.06415103481392698, -0.18645746445405148, -0.13869530590529613, -0.11208265855316525, -0.08489628125169253, -0.0734466816229032, -0.3302332980244934, 0.07159741064609751, -0.00520328105053055, 0.055504661897702194, -0.02845461209626677, -0.08276255675983206, -0.033966649619636136, 0.10007672716110562, 0.10897149882501288, 0.03827070839111214, 0.08758253366120647, -0.15671360779589827, -0.1459834234567063, 0.44287344346815183, -0.10776900025693892, -0.1459283390208626, 0.19401316949880082, -0.14442356765513945, -0.15583158740947875, 0.13247710219192727, 0.1833836294701932, 0.1426952340265858, -0.1576171583043429, 0.14991202620108324, -0.05659993347999091, 0.16097841491034934, -0.04079945499042623, 0.027891553516247284, 0.2523208791825259, 0.20773111926130602, 0.015166047716809211, 0.12159638277746772, -0.0693323254089141, -0.10078434318861115, -0.3608630264404221, -0.16687996465294996, -0.14114890893851625, 0.032972010596716235, -0.09836125860812696, -0.13953609708870682, 0.4021186410127399, 0.20769454555958075, 0.18478665058718663, -0.018501846130641403, 0.28782204340568907, 0.1243273679375927, 0.06872782704352252, -0.017273664887924898, 0.299521855009006, 0.16822088450611195, 0.08533839452315435, -0.24452031240580935, -0.0527762301161746, 0.1356805227087619] |
1,802.05057 | Understanding Book Popularity on Goodreads | Goodreads has launched the Readers Choice Awards since 2009 where users are
able to nominate/vote books of their choice, released in the given year. In
this work, we question if the number of votes that a book would receive (aka
the popularity of the book) can be predicted based on the characteristics of
various entities on Goodreads. We are successful in predicting the popularity
of the books with high prediction accuracy (correlation coefficient ~0.61) and
low RMSE (~1.25). User engagement and author's prestige are found to be crucial
factors for book popularity.
| cs.SI cs.IR | goodreads has launched the readers choice awards since 2009 where users are able to nominatevote books of their choice released in the given year in this work we question if the number of votes that a book would receive aka the popularity of the book can be predicted based on the characteristics of various entities on goodreads we are successful in predicting the popularity of the books with high prediction accuracy correlation coefficient 061 and low rmse 125 user engagement and authors prestige are found to be crucial factors for book popularity | [['goodreads', 'has', 'launched', 'the', 'readers', 'choice', 'awards', 'since', '2009', 'where', 'users', 'are', 'able', 'to', 'nominatevote', 'books', 'of', 'their', 'choice', 'released', 'in', 'the', 'given', 'year', 'in', 'this', 'work', 'we', 'question', 'if', 'the', 'number', 'of', 'votes', 'that', 'a', 'book', 'would', 'receive', 'aka', 'the', 'popularity', 'of', 'the', 'book', 'can', 'be', 'predicted', 'based', 'on', 'the', 'characteristics', 'of', 'various', 'entities', 'on', 'goodreads', 'we', 'are', 'successful', 'in', 'predicting', 'the', 'popularity', 'of', 'the', 'books', 'with', 'high', 'prediction', 'accuracy', 'correlation', 'coefficient', '061', 'and', 'low', 'rmse', '125', 'user', 'engagement', 'and', 'authors', 'prestige', 'are', 'found', 'to', 'be', 'crucial', 'factors', 'for', 'book', 'popularity']] | [-0.08629164032146826, 0.07136063316995585, -0.0514261051487935, 0.08709131608394763, -0.15274169214407576, -0.15397720213385893, 0.06353865290613292, 0.38130330021114467, -0.18409416300774256, -0.4012107151754937, 0.08456900870494012, -0.36070434560815057, -0.14112879885462942, 0.18931853620765302, -0.15795032376363352, 0.008503853701628171, 0.07762429605245816, 0.10847697742692716, -0.007439508238438885, -0.39816371353527347, 0.26712266332725737, 0.10783944281514038, 0.31161491527825924, 0.09970932154005373, 0.07240795906857654, 0.00019903653966529028, -0.08630204998061654, 0.017737983736199336, -0.1265021418404393, 0.14270279148915285, 0.3155813510887898, 0.16330173730358974, 0.3506302533896415, -0.36403236914794523, -0.13587737226715454, 0.06455858239064832, 0.10356209329380603, 0.02540628462108773, -0.008910032708177364, -0.3061066944725238, 0.11331179106587565, -0.24282340904452152, -0.051989793460202084, -0.026733531741998516, 0.07045438421050926, 0.042766197031916496, -0.19170768131760388, 0.039848101555605184, 0.002064102216736301, 0.07250217201986484, 0.008542382255565006, -0.15454797596148737, -0.003258687726754163, 0.22807978106928722, 0.13838902045716786, 0.018690545933198306, 0.1240794098536883, -0.16558112192561256, -0.11868885987384531, 0.4223056020890618, -0.06240435019340161, -0.16537767980288673, 0.1405842794120762, -0.11277563563435451, -0.13940118083341435, 0.07778594372691688, 0.2470063955246747, 0.01991999382664869, -0.12039892500839554, 0.0006817777217033186, -0.046634559108937094, 0.20670483652809327, 0.11428693875895587, 0.006467170900777801, 0.21337813726411417, 0.15324719684137092, -0.02998049649317841, 0.00827466533007612, -0.04362800090502088, -0.060243213252461215, -0.16996806775025286, -0.14769339690926475, -0.19230174775757305, 0.0502694911364425, -0.06254378822344293, -0.1336123679628964, 0.40640657030782856, 0.1606135490084333, 0.15820518620619242, 0.028119485538739424, 0.20829373989817124, 0.07991771802183363, 0.029038276781768096, 0.09615941297590405, 0.20744257757010368, 0.01571883269391217, 0.17976743663446262, -0.07657637904592596, 0.1505408961233775, 0.038768273583807786] |
1,802.05058 | The influence of online posting dates on the bibliometric indicators of
scientific articles | This article analyses the difference in timing between the online
availability of articles and their corresponding print publication and how it
affects two bibliometric indicators: Journal Impact Factor (JIF) and Immediacy
Index. This research examined 18,526 articles, the complete collection of
articles and reviews published by a set of 61 journals on Urology and
Nephrology in 2013 and 2014. The findings suggest that Advance Online
Publication (AOP) accelerates the citation of articles and affects the JIF and
Immediacy Index values. Regarding the JIF values, the comparison between
journals with or without AOP showed statistically significant differences
(P=0.001, Mann-Whitney U test). The Spearman's correlation between the JIF and
the median online-to-print publication delay was not statistically significant.
As to the Immediacy Index, a significant Spearman's correlation (rs=0.280,
P=0.029) was found regarding the median online-to-print publication delays for
journals published in 2014, although no statistically significant correlation
was found for those published in 2013. Most journals examined (n=52 out of 61)
published their articles in AOP. The analysis also showed different publisher
practices: eight journals did not include the online posting dates in the
full-text and nine journals published articles showing two different online
posting dates--the date provided on the journal website and another provided by
Elsevier's Science Direct. These practices suggest the need for transparency
and standardization of the AOP dates of scientific articles for calculating
bibliometric indicators for journals.
| cs.DL | this article analyses the difference in timing between the online availability of articles and their corresponding print publication and how it affects two bibliometric indicators journal impact factor jif and immediacy index this research examined 18526 articles the complete collection of articles and reviews published by a set of 61 journals on urology and nephrology in 2013 and 2014 the findings suggest that advance online publication aop accelerates the citation of articles and affects the jif and immediacy index values regarding the jif values the comparison between journals with or without aop showed statistically significant differences p0001 mannwhitney u test the spearmans correlation between the jif and the median onlinetoprint publication delay was not statistically significant as to the immediacy index a significant spearmans correlation rs0280 p0029 was found regarding the median onlinetoprint publication delays for journals published in 2014 although no statistically significant correlation was found for those published in 2013 most journals examined n52 out of 61 published their articles in aop the analysis also showed different publisher practices eight journals did not include the online posting dates in the fulltext and nine journals published articles showing two different online posting datesthe date provided on the journal website and another provided by elseviers science direct these practices suggest the need for transparency and standardization of the aop dates of scientific articles for calculating bibliometric indicators for journals | [['this', 'article', 'analyses', 'the', 'difference', 'in', 'timing', 'between', 'the', 'online', 'availability', 'of', 'articles', 'and', 'their', 'corresponding', 'print', 'publication', 'and', 'how', 'it', 'affects', 'two', 'bibliometric', 'indicators', 'journal', 'impact', 'factor', 'jif', 'and', 'immediacy', 'index', 'this', 'research', 'examined', '18526', 'articles', 'the', 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0.24851296780849094, -0.09427056876577537, 0.1581150738224555, -0.007569068029673921] |
1,802.05059 | Subordination for sequentially equicontinuous equibounded
$C_0$-semigroups | We consider operators $A$ on a sequentially complete Hausdorff locally convex
space $X$ such that $-A$ generates a (sequentially) equicontinuous equibounded
$C_0$-semigroup. For every Bernstein function $f$ we show that $-f(A)$
generates a semigroup which is of the same `kind' as the one generated by $-A$.
As a special case we obtain that fractional powers $-A^{\alpha}$, where $\alpha
\in (0,1)$, are generators.
| math.FA | we consider operators a on a sequentially complete hausdorff locally convex space x such that a generates a sequentially equicontinuous equibounded c_0semigroup for every bernstein function f we show that fa generates a semigroup which is of the same kind as the one generated by a as a special case we obtain that fractional powers aalpha where alpha in 01 are generators | [['we', 'consider', 'operators', 'a', 'on', 'a', 'sequentially', 'complete', 'hausdorff', 'locally', 'convex', 'space', 'x', 'such', 'that', 'a', 'generates', 'a', 'sequentially', 'equicontinuous', 'equibounded', 'c_0semigroup', 'for', 'every', 'bernstein', 'function', 'f', 'we', 'show', 'that', 'fa', 'generates', 'a', 'semigroup', 'which', 'is', 'of', 'the', 'same', 'kind', 'as', 'the', 'one', 'generated', 'by', 'a', 'as', 'a', 'special', 'case', 'we', 'obtain', 'that', 'fractional', 'powers', 'aalpha', 'where', 'alpha', 'in', '01', 'are', 'generators']] | [-0.1513690106033708, 0.15170752165478565, -0.033235199445287786, 0.0820416024709571, -0.07102425624391125, -0.12632896637754334, 0.0030311986713880495, 0.38453706221715095, -0.3254857838995034, -0.09161460301989029, 0.1213541413157908, -0.30413407584907665, -0.1451781820806284, 0.2450449044455684, -0.06304744333629647, 0.0007866375662776972, 0.03718957927588734, 0.12937149329621705, -0.10304024390831229, -0.20071019773416582, 0.3713693143349261, -0.06502488276530657, 0.15469723517796205, -0.03562048298396891, 0.1786955379272601, 0.006178867597613604, 0.028679369821123058, 0.05156812213704876, -0.1407601970618529, 0.08194089961809016, 0.2369135349027572, 0.11170348190071602, 0.34723358562276246, -0.3252309599282002, -0.17731184655079438, 0.19632801901729358, 0.07018859589081858, -0.045455121129165374, -0.08008397198207076, -0.22483824096965574, 0.15481143848287063, -0.172869932236931, -0.10791708519231648, -0.07869185491525117, 0.09144027655824058, 0.05618186377649827, -0.4092330625581165, -0.007762486122608665, 0.14074716338467214, 0.007010640651588479, -0.025082978104511575, -0.055328915241144354, -0.08115687819137689, 0.047995447819571824, -0.05855197841188901, 0.10992433096192056, 0.1019327424517307, -0.025645988520174738, -0.1191567181339187, 0.36013161595309934, -0.10653442192462183, -0.28242817295775297, 0.09821446717251092, -0.21655375308417266, -0.16068273389922275, 0.08656309275219458, 0.10667739246151366, 0.18671106652266556, -0.0790622194537953, 0.1945480308946102, -0.15354805843784444, 0.15352659508766187, 0.07640490520955814, 0.02246320532304385, 0.0792278817576927, 0.1092798673217335, 0.17981369644703885, 0.18668095044971955, 0.028296393105730174, 0.020503835970415704, -0.40761359047985846, -0.1794749298583596, -0.2013915195167365, 0.1435684923893742, -0.07955318796748836, -0.19182795069120342, 0.38332959741444117, 0.06352168679117196, 0.24989162920974195, 0.09623795346875165, 0.2180502656772132, 0.1539865962432457, 0.02421755352277673, 0.1021052596775154, 0.07573325072805728, 0.07912198824417446, 0.0009761308845613271, -0.11029235142162971, 0.027470245615639273, 0.20715991213857646] |
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