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1,802.0416 | Inflationary predictions of double-well, Coleman-Weinberg, and hilltop
potentials with non-minimal coupling | We discuss how the non-minimal coupling $\xi\phi^2R$ between the inflaton and
the Ricci scalar affects the predictions of single field inflation models where
the inflaton has a non-zero vacuum expectation value (VEV) $v$ after inflation.
We show that, for inflaton values both above the VEV and below the VEV during
inflation, under certain conditions the inflationary predictions become
approximately the same as the predictions of the Starobinsky model. We then
analyze inflation with double-well and Coleman-Weinberg potentials in detail,
displaying the regions in the $v$-$\xi$ plane for which the spectral index
$n_s$ and the tensor-to-scalar ratio $r$ values are compatible with the current
observations. $r$ is always larger than 0.002 in these regions. Finally, we
consider the effect of $\xi$ on small field inflation (hilltop) potentials.
| astro-ph.CO hep-ph | we discuss how the nonminimal coupling xiphi2r between the inflaton and the ricci scalar affects the predictions of single field inflation models where the inflaton has a nonzero vacuum expectation value vev v after inflation we show that for inflaton values both above the vev and below the vev during inflation under certain conditions the inflationary predictions become approximately the same as the predictions of the starobinsky model we then analyze inflation with doublewell and colemanweinberg potentials in detail displaying the regions in the vxi plane for which the spectral index n_s and the tensortoscalar ratio r values are compatible with the current observations r is always larger than 0002 in these regions finally we consider the effect of xi on small field inflation hilltop potentials | [['we', 'discuss', 'how', 'the', 'nonminimal', 'coupling', 'xiphi2r', 'between', 'the', 'inflaton', 'and', 'the', 'ricci', 'scalar', 'affects', 'the', 'predictions', 'of', 'single', 'field', 'inflation', 'models', 'where', 'the', 'inflaton', 'has', 'a', 'nonzero', 'vacuum', 'expectation', 'value', 'vev', 'v', 'after', 'inflation', 'we', 'show', 'that', 'for', 'inflaton', 'values', 'both', 'above', 'the', 'vev', 'and', 'below', 'the', 'vev', 'during', 'inflation', 'under', 'certain', 'conditions', 'the', 'inflationary', 'predictions', 'become', 'approximately', 'the', 'same', 'as', 'the', 'predictions', 'of', 'the', 'starobinsky', 'model', 'we', 'then', 'analyze', 'inflation', 'with', 'doublewell', 'and', 'colemanweinberg', 'potentials', 'in', 'detail', 'displaying', 'the', 'regions', 'in', 'the', 'vxi', 'plane', 'for', 'which', 'the', 'spectral', 'index', 'n_s', 'and', 'the', 'tensortoscalar', 'ratio', 'r', 'values', 'are', 'compatible', 'with', 'the', 'current', 'observations', 'r', 'is', 'always', 'larger', 'than', '0002', 'in', 'these', 'regions', 'finally', 'we', 'consider', 'the', 'effect', 'of', 'xi', 'on', 'small', 'field', 'inflation', 'hilltop', 'potentials']] | [-0.17489973232307146, 0.22927373472512477, -0.04479547621430977, 0.11234229955071998, -0.051692173807024365, -0.20950917002656275, -0.04793126863752684, 0.3369810759415111, -0.18757022468702098, -0.2714447435804658, 0.07070720913572355, -0.2362898762249166, -0.11456869803147302, 0.13037431141405942, -0.0169221174714732, -0.008109090370929889, 0.021331146961846757, 0.06723494237909715, -0.027729151613404234, -0.2584664607808615, 0.31794156704194076, 0.0771037264069217, 0.21800113498558482, 0.03243668453669959, 0.04101643884657986, -0.10197899115109255, 0.07257939628990633, -0.03380280254142625, -0.2148650545456067, 0.04128243084553452, 0.0967449074243401, 0.08565949338547413, 0.23087682130761325, -0.3656744573280097, -0.20454004987896907, 0.2336767452384626, 0.11021102416293976, 0.10520796514659499, -0.008921442771448738, -0.27351492771967534, 0.07995284805333035, -0.14104918625006185, -0.08758220298258247, -0.04623953624081517, 0.03807049594442582, -0.09111206746467995, -0.36267002529394443, 0.1010998873121386, -0.08869742384062164, 0.014952429875154934, -0.08390629335513546, -0.11859152806250171, -0.10470512766198861, -0.019446103926008894, 0.1772913409559618, 0.03043297391397775, 0.1746000265961306, -0.22596849152256573, -0.016801446817615733, 0.36956339750054573, -0.2099208062938978, -0.11806703234342711, 0.043367429632723095, -0.17901547808968832, -0.10964512964341021, 0.04829767628735493, 0.08029136529547118, 0.09332386514408485, -0.05387586893306838, 0.2210231844154704, 0.06960264680581907, 0.13820667220427404, 0.10444842596420102, 0.014440595161258465, 0.3253975585990009, 0.07897051479963083, 0.04488538309473485, 0.11441405894722612, -0.04292862852185314, -0.13753613570912016, -0.4342215153580857, -0.0596713940261878, -0.12924502545132463, 0.03318758822223615, -0.22178257432801368, -0.15445919269843708, 0.4710370304565581, 0.18241155174900853, 0.266211622372447, 0.10031627194072666, 0.25763204587357386, 0.12523727025744313, 0.061178495390488516, 0.061746206550326733, 0.3414022526408117, 0.12679730895315372, 0.1711165330276662, -0.21603202290042112, -0.05297682047008522, 0.03356305200473538] |
1,802.04161 | Risk Factors Associated with Mortality in Game of Thrones: A
Longitudinal Cohort Study | Objective: To assess mortality, and identify the risk factors associated with
mortality in Game of Thrones (GoT). Design and Setting: A longitudinal cohort
study in the fictional kingdom of Westeros and Essos. Participants: All the
characters appearing in the GoT since airing of its first episode with screen
time of greater than or equal to 5 minutes. Main Outcome Measures: All-cause
mortality. Multivariate Cox proportional hazard model was used to assess the
risk factors associated with mortality, represented by hazard ratios, with
episodes as the unit of time. Results: Of the 132 characters, followed up for a
median time of 32 episodes, a total 89 (67.4%) characters died; with external
invasive injury as the most common cause of death, attributing to 42.4% of the
total deaths. Age (in decades) was a significant risk factor for death [HR,
1.24 (95% CI, 1.08-1.43), P=0.0001]. Although statistically non-significant,
allegiance to house Targaryen [HR, 1.10 (95% CI, 0.32-3.77)] was associated
with a higher risk for mortality per episode than house Stark. Characters
residing in South were less likely to die than characters residing in North
[HR, 0.58 (95% CI, 0.29-1.16), P=0.12]. Advisors showed a lower risk of
mortality than the members of houses, with some statistical significance [HR,
0.39 (95% CI, 0.14-1.08), P=0.07]. Conclusions: There is a high mortality rate
among the characters in GoT. Residing in the North and being a member of a
house is very dangerous in GoT. Allegiance to house Stark trended to be safer
than house Targaryen.
| stat.OT | objective to assess mortality and identify the risk factors associated with mortality in game of thrones got design and setting a longitudinal cohort study in the fictional kingdom of westeros and essos participants all the characters appearing in the got since airing of its first episode with screen time of greater than or equal to 5 minutes main outcome measures allcause mortality multivariate cox proportional hazard model was used to assess the risk factors associated with mortality represented by hazard ratios with episodes as the unit of time results of the 132 characters followed up for a median time of 32 episodes a total 89 674 characters died with external invasive injury as the most common cause of death attributing to 424 of the total deaths age in decades was a significant risk factor for death hr 124 95 ci 108143 p00001 although statistically nonsignificant allegiance to house targaryen hr 110 95 ci 032377 was associated with a higher risk for mortality per episode than house stark characters residing in south were less likely to die than characters residing in north hr 058 95 ci 029116 p012 advisors showed a lower risk of mortality than the members of houses with some statistical significance hr 039 95 ci 014108 p007 conclusions there is a high mortality rate among the characters in got residing in the north and being a member of a house is very dangerous in got allegiance to house stark trended to be safer than house targaryen | [['objective', 'to', 'assess', 'mortality', 'and', 'identify', 'the', 'risk', 'factors', 'associated', 'with', 'mortality', 'in', 'game', 'of', 'thrones', 'got', 'design', 'and', 'setting', 'a', 'longitudinal', 'cohort', 'study', 'in', 'the', 'fictional', 'kingdom', 'of', 'westeros', 'and', 'essos', 'participants', 'all', 'the', 'characters', 'appearing', 'in', 'the', 'got', 'since', 'airing', 'of', 'its', 'first', 'episode', 'with', 'screen', 'time', 'of', 'greater', 'than', 'or', 'equal', 'to', '5', 'minutes', 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1,802.04162 | Policy Gradients for Contextual Recommendations | Decision making is a challenging task in online recommender systems. The
decision maker often needs to choose a contextual item at each step from a set
of candidates. Contextual bandit algorithms have been successfully deployed to
such applications, for the trade-off between exploration and exploitation and
the state-of-art performance on minimizing online costs. However, the
applicability of existing contextual bandit methods is limited by the
over-simplified assumptions of the problem, such as assuming a simple form of
the reward function or assuming a static environment where the states are not
affected by previous actions. In this work, we put forward Policy Gradients for
Contextual Recommendations (PGCR) to solve the problem without those
unrealistic assumptions. It optimizes over a restricted class of policies where
the marginal probability of choosing an item (in expectation of other items)
has a simple closed form, and the gradient of the expected return over the
policy in this class is in a succinct form. Moreover, PGCR leverages two useful
heuristic techniques called Time-Dependent Greed and Actor-Dropout. The former
ensures PGCR to be empirically greedy in the limit, and the latter addresses
the trade-off between exploration and exploitation by using the policy network
with Dropout as a Bayesian approximation. PGCR can solve the standard
contextual bandits as well as its Markov Decision Process generalization.
Therefore it can be applied to a wide range of realistic settings of
recommendations, such as personalized advertising. We evaluate PGCR on toy
datasets as well as a real-world dataset of personalized music recommendations.
Experiments show that PGCR enables fast convergence and low regret, and
outperforms both classic contextual-bandits and vanilla policy gradient
methods.
| cs.LG | decision making is a challenging task in online recommender systems the decision maker often needs to choose a contextual item at each step from a set of candidates contextual bandit algorithms have been successfully deployed to such applications for the tradeoff between exploration and exploitation and the stateofart performance on minimizing online costs however the applicability of existing contextual bandit methods is limited by the oversimplified assumptions of the problem such as assuming a simple form of the reward function or assuming a static environment where the states are not affected by previous actions in this work we put forward policy gradients for contextual recommendations pgcr to solve the problem without those unrealistic assumptions it optimizes over a restricted class of policies where the marginal probability of choosing an item in expectation of other items has a simple closed form and the gradient of the expected return over the policy in this class is in a succinct form moreover pgcr leverages two useful heuristic techniques called timedependent greed and actordropout the former ensures pgcr to be empirically greedy in the limit and the latter addresses the tradeoff between exploration and exploitation by using the policy network with dropout as a bayesian approximation pgcr can solve the standard contextual bandits as well as its markov decision process generalization therefore it can be applied to a wide range of realistic settings of recommendations such as personalized advertising we evaluate pgcr on toy datasets as well as a realworld dataset of personalized music recommendations experiments show that pgcr enables fast convergence and low regret and outperforms both classic contextualbandits and vanilla policy gradient methods | [['decision', 'making', 'is', 'a', 'challenging', 'task', 'in', 'online', 'recommender', 'systems', 'the', 'decision', 'maker', 'often', 'needs', 'to', 'choose', 'a', 'contextual', 'item', 'at', 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1,802.04163 | Two-Color Pump-Probe Measurement of Photonic Quantum Correlations
Mediated by a Single Phonon | We propose and demonstrate a versatile technique to measure the lifetime of
the one-phonon Fock state using two-color pump-probe Raman scattering and
spectrally-resolved, time-correlated photon counting. Following pulsed laser
excitation, the $n=1$ phonon Fock state is probabilistically prepared by
projective measurement of a single Stokes photon. The detection of an
anti-Stokes photon generated by a second, time-delayed laser pulse probes the
phonon population with sub-picosecond time resolution. We observe strongly
non-classical Stokes--anti-Stokes correlations, whose decay maps the single
phonon dynamics. Our scheme can be applied to any Raman-active vibrational
mode. It can be modified to measure the lifetime of $n \geq 1$ Fock states or
the phonon quantum coherences through the preparation and detection of two-mode
entangled vibrational states.
| quant-ph cond-mat.mes-hall | we propose and demonstrate a versatile technique to measure the lifetime of the onephonon fock state using twocolor pumpprobe raman scattering and spectrallyresolved timecorrelated photon counting following pulsed laser excitation the n1 phonon fock state is probabilistically prepared by projective measurement of a single stokes photon the detection of an antistokes photon generated by a second timedelayed laser pulse probes the phonon population with subpicosecond time resolution we observe strongly nonclassical stokesantistokes correlations whose decay maps the single phonon dynamics our scheme can be applied to any ramanactive vibrational mode it can be modified to measure the lifetime of n geq 1 fock states or the phonon quantum coherences through the preparation and detection of twomode entangled vibrational states | [['we', 'propose', 'and', 'demonstrate', 'a', 'versatile', 'technique', 'to', 'measure', 'the', 'lifetime', 'of', 'the', 'onephonon', 'fock', 'state', 'using', 'twocolor', 'pumpprobe', 'raman', 'scattering', 'and', 'spectrallyresolved', 'timecorrelated', 'photon', 'counting', 'following', 'pulsed', 'laser', 'excitation', 'the', 'n1', 'phonon', 'fock', 'state', 'is', 'probabilistically', 'prepared', 'by', 'projective', 'measurement', 'of', 'a', 'single', 'stokes', 'photon', 'the', 'detection', 'of', 'an', 'antistokes', 'photon', 'generated', 'by', 'a', 'second', 'timedelayed', 'laser', 'pulse', 'probes', 'the', 'phonon', 'population', 'with', 'subpicosecond', 'time', 'resolution', 'we', 'observe', 'strongly', 'nonclassical', 'stokesantistokes', 'correlations', 'whose', 'decay', 'maps', 'the', 'single', 'phonon', 'dynamics', 'our', 'scheme', 'can', 'be', 'applied', 'to', 'any', 'ramanactive', 'vibrational', 'mode', 'it', 'can', 'be', 'modified', 'to', 'measure', 'the', 'lifetime', 'of', 'n', 'geq', '1', 'fock', 'states', 'or', 'the', 'phonon', 'quantum', 'coherences', 'through', 'the', 'preparation', 'and', 'detection', 'of', 'twomode', 'entangled', 'vibrational', 'states']] | [-0.09876754799928172, 0.3209218273083376, -0.11736130255798832, -0.008282299461664961, 0.026684130956770993, -0.18667538865164174, 0.07059780597205453, 0.45217025462350174, -0.2797617332289825, -0.21439212831441595, -0.04717147727340397, -0.2883366177723344, -0.0021117581171961894, 0.2032361571508765, 0.03343905078857636, 0.09115433892892565, 0.07784437240498089, -0.03369381415321171, 0.05028380485282851, -0.16812580157591797, 0.28680831433993864, 0.02197958136803056, 0.33640392057347196, 0.02923853711240745, 0.13208022474178246, 0.07595316257265185, 0.04319124553595208, -0.1193531803051088, -0.09646750779572029, 0.07528710924186784, 0.2844411352582808, 0.04856922459483397, 0.23630272136108965, -0.4118235527436022, -0.22485155741558918, 0.09435156344616112, 0.15425944957537813, 0.2116415533410804, -0.004464202227869204, -0.3578473574231465, -0.06215193021666853, -0.14498804927952275, -0.10418648055183287, -0.13229317763162887, -0.0321217849733261, 0.00036502431710289806, -0.24699949483316735, 0.08566904692527126, -0.012726385782261481, 0.015147908222900719, -0.030081752797260004, 0.0032400635791112894, -0.07202938816337964, 0.018573484385480024, -0.08844429643006854, -0.01836362512422209, 0.20184522891464104, -0.09611597472993548, -0.18904039553296165, 0.3210463989682558, -0.14449593277663744, -0.11920892473451104, 0.10883193333171495, -0.19121329335323653, -0.03003350903667478, 0.20701699287575834, 0.07539968538240377, 0.19047499780676194, -0.09614584282698001, -0.01507976553706108, 0.009935424937044872, 0.2920494132984367, 0.1326572330900421, 0.17886375626470863, 0.13357325148193494, 0.1258861580922292, 0.00919936127088056, 0.17641121225564607, -0.1718684987266775, -0.0034559855174993268, -0.2763804167180377, -0.1343777263654443, -0.24514101973236851, 0.15997609430376222, -0.03207967811063061, -0.09944841332005791, 0.4461760750313291, 0.06682432303400788, 0.11136683220231608, -0.018666724596141267, 0.32668586909583136, 0.21080251624357707, -0.0011280556248516596, -0.02532592392330911, 0.2674745297012459, 0.21481343230796085, 0.03358514972340253, -0.36623801823784674, -0.023824235117219452, -0.014396925628999201] |
1,802.04164 | A high-efficiency gas target setup for underground experiments, and
redetermination of the branching ratio of the 189.5 keV
$\mathbf{^{22}Ne(p,\gamma)^{23}Na}$ resonance | The experimental study of nuclear reactions of astrophysical interest is
greatly facilitated by a low-background, high-luminosity setup. The Laboratory
for Underground Nuclear Astrophysics (LUNA) 400 kV accelerator offers ultra-low
cosmic-ray induced background due to its location deep underground in the Gran
Sasso National Laboratory (INFN-LNGS), Italy, and high intensity, 250-500
$\mu$A, proton and $\alpha$ ion beams. In order to fully exploit these
features, a high-purity, recirculating gas target system for isotopically
enriched gases is coupled to a high-efficiency, six-fold optically segmented
bismuth germanate (BGO) $\gamma$-ray detector. The beam intensity is measured
with a beam calorimeter with constant temperature gradient. Pressure and
temperature measurements have been carried out at several positions along the
beam path, and the resultant gas density profile has been determined.
Calibrated $\gamma$-intensity standards and the well-known $E_p$ = 278 keV
$\mathrm{^{14}N(p,\gamma)^{15}O}$ resonance were used to determine the
$\gamma$-ray detection efficiency and to validate the simulation of the target
and detector setup. As an example, the recently measured resonance at $E_p$ =
189.5 keV in the $^{22}$Ne(p,$\gamma$)$^{23}$Na reaction has been investigated
with high statistics, and the $\gamma$-decay branching ratios of the resonance
have been determined.
| nucl-ex astro-ph.IM | the experimental study of nuclear reactions of astrophysical interest is greatly facilitated by a lowbackground highluminosity setup the laboratory for underground nuclear astrophysics luna 400 kv accelerator offers ultralow cosmicray induced background due to its location deep underground in the gran sasso national laboratory infnlngs italy and high intensity 250500 mua proton and alpha ion beams in order to fully exploit these features a highpurity recirculating gas target system for isotopically enriched gases is coupled to a highefficiency sixfold optically segmented bismuth germanate bgo gammaray detector the beam intensity is measured with a beam calorimeter with constant temperature gradient pressure and temperature measurements have been carried out at several positions along the beam path and the resultant gas density profile has been determined calibrated gammaintensity standards and the wellknown e_p 278 kev mathrm14npgamma15o resonance were used to determine the gammaray detection efficiency and to validate the simulation of the target and detector setup as an example the recently measured resonance at e_p 1895 kev in the 22nepgamma23na reaction has been investigated with high statistics and the gammadecay branching ratios of the resonance have been determined | [['the', 'experimental', 'study', 'of', 'nuclear', 'reactions', 'of', 'astrophysical', 'interest', 'is', 'greatly', 'facilitated', 'by', 'a', 'lowbackground', 'highluminosity', 'setup', 'the', 'laboratory', 'for', 'underground', 'nuclear', 'astrophysics', 'luna', '400', 'kv', 'accelerator', 'offers', 'ultralow', 'cosmicray', 'induced', 'background', 'due', 'to', 'its', 'location', 'deep', 'underground', 'in', 'the', 'gran', 'sasso', 'national', 'laboratory', 'infnlngs', 'italy', 'and', 'high', 'intensity', '250500', 'mua', 'proton', 'and', 'alpha', 'ion', 'beams', 'in', 'order', 'to', 'fully', 'exploit', 'these', 'features', 'a', 'highpurity', 'recirculating', 'gas', 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'reaction', 'has', 'been', 'investigated', 'with', 'high', 'statistics', 'and', 'the', 'gammadecay', 'branching', 'ratios', 'of', 'the', 'resonance', 'have', 'been', 'determined']] | [-0.031212954479717434, 0.18734233171218856, -0.048901063849500916, 0.042462341500840224, 0.0012754909387165374, -0.14288390500203624, 0.005673337730343689, 0.42624567871514174, -0.18023252016148314, -0.35899717516808227, 0.03105365708636652, -0.34475506463466765, 0.06932410168983452, 0.2366623065951229, 0.04855559670857594, 0.12239679571731747, 0.05456050892442383, -0.005526283996404855, -0.03056914686253499, -0.16901968379510096, 0.18707223246411347, 0.24158632062144633, 0.34047422131554195, 0.09587585201466477, 0.1694588505120559, -0.07116264612081327, -0.013197577023714945, -0.06496783240332402, -0.13192457737014782, 0.03867075449254896, 0.3390790349215392, 0.0672606706413297, 0.1696604159814152, -0.41342372257917465, -0.20979807865396552, 0.10440425832172508, 0.09259873139160266, 0.014529877546970006, 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1,802.04165 | Understanding Electric Current Using Agent-Based Models: Connecting the
Micro-level with Flow Rate | Rate-based processes comprise an important set of scientific phenomena, as
well as an important part of the K12 science curricula. Electric current is one
such phenomenon, which is taught in various forms from 4th - 12th grades.
Research shows that students at all levels find electricity difficult to
understand, and the difficulties persist even after classroom instruction. In
this paper, we present a design-based research study and argue that interacting
with multi-agent-based computational models based on the microscopic theory of
electrical conduction, can enable 5th grade and 7th students to develop a deep
understanding of electric current as an emergent process of flow in terms of
its microscopic level entities and their attributes, by bootstrapping their
repertoire of intuitive knowledge. We present a particular design strategy -
representing electric current as a fictive and transient process of charge
accumulation, without falling in previously reported traps of the "source sink"
mental models - and show how this strategy was effectively implemented in the
computational model as well as in the learning activities performed by the
students. We identify the mental models that students developed through their
interactions with the model, and show that after their interactions, students
were able to provide correct, multi-level explanations of the behavior of
electric current in a resistive circuit.
| physics.ed-ph | ratebased processes comprise an important set of scientific phenomena as well as an important part of the k12 science curricula electric current is one such phenomenon which is taught in various forms from 4th 12th grades research shows that students at all levels find electricity difficult to understand and the difficulties persist even after classroom instruction in this paper we present a designbased research study and argue that interacting with multiagentbased computational models based on the microscopic theory of electrical conduction can enable 5th grade and 7th students to develop a deep understanding of electric current as an emergent process of flow in terms of its microscopic level entities and their attributes by bootstrapping their repertoire of intuitive knowledge we present a particular design strategy representing electric current as a fictive and transient process of charge accumulation without falling in previously reported traps of the source sink mental models and show how this strategy was effectively implemented in the computational model as well as in the learning activities performed by the students we identify the mental models that students developed through their interactions with the model and show that after their interactions students were able to provide correct multilevel explanations of the behavior of electric current in a resistive circuit | [['ratebased', 'processes', 'comprise', 'an', 'important', 'set', 'of', 'scientific', 'phenomena', 'as', 'well', 'as', 'an', 'important', 'part', 'of', 'the', 'k12', 'science', 'curricula', 'electric', 'current', 'is', 'one', 'such', 'phenomenon', 'which', 'is', 'taught', 'in', 'various', 'forms', 'from', '4th', '12th', 'grades', 'research', 'shows', 'that', 'students', 'at', 'all', 'levels', 'find', 'electricity', 'difficult', 'to', 'understand', 'and', 'the', 'difficulties', 'persist', 'even', 'after', 'classroom', 'instruction', 'in', 'this', 'paper', 'we', 'present', 'a', 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1,802.04166 | Permutation monoids and MB-homogeneity for graphs and relational
structures | In this paper, we investigate the connection between infinite permutation
monoids and bimorphism monoids of first-order structures. Taking our lead from
the study of automorphism groups of structures as infinite permutation groups
and the more recent developments in the field of homomorphism-homogeneous
structures, we establish a series of results that underline this connection. Of
particular interest is the idea of MB-homogeneity; a relational structure
$\mathcal{M}$ is MB-homogeneous if every monomorphism between finite
substructures of $\mathcal{M}$ extends to a bimorphism of $\mathcal{M}$. The
results in question include a characterisation of closed permutation monoids, a
Fra\"{i}ss\'{e}-like theorem for MB-homogeneous structures, and the
construction of $2^{\aleph_0}$ pairwise non-isomorphic countable MB-homogeneous
graphs. We prove that any finite group arises as the automorphism group of some
MB-homogeneous graph and use this to construct oligomorphic permutation monoids
with any given finite group of units. We also consider MB-homogeneity for
various well-known examples of homogeneous structures and in particular give a
complete classification of countable homogeneous undirected graphs that are
also MB-homogeneous.
| math.GR math.CO | in this paper we investigate the connection between infinite permutation monoids and bimorphism monoids of firstorder structures taking our lead from the study of automorphism groups of structures as infinite permutation groups and the more recent developments in the field of homomorphismhomogeneous structures we establish a series of results that underline this connection of particular interest is the idea of mbhomogeneity a relational structure mathcalm is mbhomogeneous if every monomorphism between finite substructures of mathcalm extends to a bimorphism of mathcalm the results in question include a characterisation of closed permutation monoids a fraisselike theorem for mbhomogeneous structures and the construction of 2aleph_0 pairwise nonisomorphic countable mbhomogeneous graphs we prove that any finite group arises as the automorphism group of some mbhomogeneous graph and use this to construct oligomorphic permutation monoids with any given finite group of units we also consider mbhomogeneity for various wellknown examples of homogeneous structures and in particular give a complete classification of countable homogeneous undirected graphs that are also mbhomogeneous | [['in', 'this', 'paper', 'we', 'investigate', 'the', 'connection', 'between', 'infinite', 'permutation', 'monoids', 'and', 'bimorphism', 'monoids', 'of', 'firstorder', 'structures', 'taking', 'our', 'lead', 'from', 'the', 'study', 'of', 'automorphism', 'groups', 'of', 'structures', 'as', 'infinite', 'permutation', 'groups', 'and', 'the', 'more', 'recent', 'developments', 'in', 'the', 'field', 'of', 'homomorphismhomogeneous', 'structures', 'we', 'establish', 'a', 'series', 'of', 'results', 'that', 'underline', 'this', 'connection', 'of', 'particular', 'interest', 'is', 'the', 'idea', 'of', 'mbhomogeneity', 'a', 'relational', 'structure', 'mathcalm', 'is', 'mbhomogeneous', 'if', 'every', 'monomorphism', 'between', 'finite', 'substructures', 'of', 'mathcalm', 'extends', 'to', 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1,802.04167 | First transmission of electrons and ions through the KATRIN beamline | The Karlsruhe Tritium Neutrino (KATRIN) experiment is a large-scale effort to
probe the absolute neutrino mass scale with a sensitivity of 0.2 eV (90%
confidence level), via a precise measurement of the endpoint spectrum of
tritium beta decay. This work documents several KATRIN commissioning
milestones: the complete assembly of the experimental beamline, the successful
transmission of electrons from three sources through the beamline to the
primary detector, and tests of ion transport and retention. In the First Light
commissioning campaign of Autumn 2016, photoelectrons were generated at the
rear wall and ions were created by a dedicated ion source attached to the rear
section; in July 2017, gaseous Kr-83m was injected into the KATRIN source
section, and a condensed Kr-83m source was deployed in the transport section.
In this paper we describe the technical details of the apparatus and the
configuration for each measurement, and give first results on source and system
performance. We have successfully achieved transmission from all four sources,
established system stability, and characterized many aspects of the apparatus.
| physics.ins-det nucl-ex | the karlsruhe tritium neutrino katrin experiment is a largescale effort to probe the absolute neutrino mass scale with a sensitivity of 02 ev 90 confidence level via a precise measurement of the endpoint spectrum of tritium beta decay this work documents several katrin commissioning milestones the complete assembly of the experimental beamline the successful transmission of electrons from three sources through the beamline to the primary detector and tests of ion transport and retention in the first light commissioning campaign of autumn 2016 photoelectrons were generated at the rear wall and ions were created by a dedicated ion source attached to the rear section in july 2017 gaseous kr83m was injected into the katrin source section and a condensed kr83m source was deployed in the transport section in this paper we describe the technical details of the apparatus and the configuration for each measurement and give first results on source and system performance we have successfully achieved transmission from all four sources established system stability and characterized many aspects of the apparatus | [['the', 'karlsruhe', 'tritium', 'neutrino', 'katrin', 'experiment', 'is', 'a', 'largescale', 'effort', 'to', 'probe', 'the', 'absolute', 'neutrino', 'mass', 'scale', 'with', 'a', 'sensitivity', 'of', '02', 'ev', '90', 'confidence', 'level', 'via', 'a', 'precise', 'measurement', 'of', 'the', 'endpoint', 'spectrum', 'of', 'tritium', 'beta', 'decay', 'this', 'work', 'documents', 'several', 'katrin', 'commissioning', 'milestones', 'the', 'complete', 'assembly', 'of', 'the', 'experimental', 'beamline', 'the', 'successful', 'transmission', 'of', 'electrons', 'from', 'three', 'sources', 'through', 'the', 'beamline', 'to', 'the', 'primary', 'detector', 'and', 'tests', 'of', 'ion', 'transport', 'and', 'retention', 'in', 'the', 'first', 'light', 'commissioning', 'campaign', 'of', 'autumn', '2016', 'photoelectrons', 'were', 'generated', 'at', 'the', 'rear', 'wall', 'and', 'ions', 'were', 'created', 'by', 'a', 'dedicated', 'ion', 'source', 'attached', 'to', 'the', 'rear', 'section', 'in', 'july', '2017', 'gaseous', 'kr83m', 'was', 'injected', 'into', 'the', 'katrin', 'source', 'section', 'and', 'a', 'condensed', 'kr83m', 'source', 'was', 'deployed', 'in', 'the', 'transport', 'section', 'in', 'this', 'paper', 'we', 'describe', 'the', 'technical', 'details', 'of', 'the', 'apparatus', 'and', 'the', 'configuration', 'for', 'each', 'measurement', 'and', 'give', 'first', 'results', 'on', 'source', 'and', 'system', 'performance', 'we', 'have', 'successfully', 'achieved', 'transmission', 'from', 'all', 'four', 'sources', 'established', 'system', 'stability', 'and', 'characterized', 'many', 'aspects', 'of', 'the', 'apparatus']] | [-0.06648959848436874, 0.1693966029730333, -0.06992288317726275, 0.02394780786477874, 0.003128382932329767, -0.12424859095081893, 0.02892254947665754, 0.3524955629349448, -0.18561866950666056, -0.3694332908015958, 0.09978153706977663, -0.3414416572706487, 0.023850906488680563, 0.2264809207652349, 0.0006574472672370977, 0.10245013376156431, 0.13034082171074007, -0.01149799503916658, -0.020023133859531087, -0.2514323276653074, 0.2565084520922324, 0.20270617824957468, 0.2769766060640862, 0.10633674201144036, 0.1354007970008371, -0.02297705003374451, -0.05460198444390783, -0.09694047822335432, -0.11785782895289189, 0.07024518843215002, 0.2617626316332039, 0.11422654371410824, 0.1822686494351094, -0.41588882362296764, -0.14525937755337678, 0.043665105912856064, 0.0809963462782244, 0.03416418101500482, -0.09910235505586296, -0.318762336077905, 0.02489169563036845, -0.19449598223599063, -0.13963071598812157, 0.05194667503535531, -0.0354808651094953, 0.01621856172360018, -0.22582399776898499, 0.002062064569800832, -0.015992378133760636, 0.06640450586226422, -0.062317620042364956, -0.13181764615813357, 0.04487778967365536, 0.13486486402351064, 0.02979288820236878, 0.01931075476394928, 0.1962916620460144, -0.08425716267151455, -0.07388578152803835, 0.35448134415999577, -0.05026626111675585, -0.07625242952409006, 0.12929723370647014, -0.20984274534736003, -0.12230722744256085, 0.17304573388943492, 0.19453584152100564, 0.07822831713480788, -0.22433719354096887, 0.034965674796271634, 0.011010494291630769, 0.21611316349015736, 0.12081066531340354, -0.01430520667629533, 0.24166405381943468, 0.23298705115286245, 0.04146031867597674, 0.09162241877696266, -0.18377002008189666, 0.010675604030121725, -0.3542760396132592, -0.16010693103876397, -0.10940084857175798, 0.0375070653363066, 0.05317836333415471, -0.07875750863858293, 0.4495983305698542, 0.11501870486820333, 0.1386916554630409, -0.06854139742858405, 0.330017639925097, 0.01804858049767655, 0.02320315523971912, 0.004130687705392755, 0.29936949134436114, 0.13693650117695438, 0.17024346039803742, -0.22372379058343053, 0.0456599032582152, 0.03271265791155138] |
1,802.04168 | Collective Classification of Spam Campaigners on Twitter: A Hierarchical
Meta-Path Based Approach | Cybercriminals have leveraged the popularity of a large user base available
on Online Social Networks to spread spam campaigns by propagating phishing
URLs, attaching malicious contents, etc. However, another kind of spam attacks
using phone numbers has recently become prevalent on OSNs, where spammers
advertise phone numbers to attract users' attention and convince them to make a
call to these phone numbers. The dynamics of phone number based spam is
different from URL-based spam due to an inherent trust associated with a phone
number. While previous work has proposed strategies to mitigate URL-based spam
attacks, phone number based spam attacks have received less attention. In this
paper, we aim to detect spammers that use phone numbers to promote campaigns on
Twitter. To this end, we collected information about 3,370 campaigns spread by
670,251 users. We model the Twitter dataset as a heterogeneous network by
leveraging various interconnections between different types of nodes present in
the dataset. In particular, we make the following contributions: (i) We propose
a simple yet effective metric, called Hierarchical Meta-Path Score (HMPS) to
measure the proximity of an unknown user to the other known pool of spammers.
(ii) We design a feedback-based active learning strategy and show that it
significantly outperforms three state-of-the-art baselines for the task of spam
detection. Our method achieves 6.9% and 67.3% higher F1-score and AUC,
respectively compared to the best baseline method. (iii) To overcome the
problem of less training instances for supervised learning, we show that our
proposed feedback strategy achieves 25.6% and 46% higher F1-score and AUC
respectively than other oversampling strategies. Finally, we perform a case
study to show how our method is capable of detecting those users as spammers
who have not been suspended by Twitter (and other baselines) yet.
| cs.SI | cybercriminals have leveraged the popularity of a large user base available on online social networks to spread spam campaigns by propagating phishing urls attaching malicious contents etc however another kind of spam attacks using phone numbers has recently become prevalent on osns where spammers advertise phone numbers to attract users attention and convince them to make a call to these phone numbers the dynamics of phone number based spam is different from urlbased spam due to an inherent trust associated with a phone number while previous work has proposed strategies to mitigate urlbased spam attacks phone number based spam attacks have received less attention in this paper we aim to detect spammers that use phone numbers to promote campaigns on twitter to this end we collected information about 3370 campaigns spread by 670251 users we model the twitter dataset as a heterogeneous network by leveraging various interconnections between different types of nodes present in the dataset in particular we make the following contributions i we propose a simple yet effective metric called hierarchical metapath score hmps to measure the proximity of an unknown user to the other known pool of spammers ii we design a feedbackbased active learning strategy and show that it significantly outperforms three stateoftheart baselines for the task of spam detection our method achieves 69 and 673 higher f1score and auc respectively compared to the best baseline method iii to overcome the problem of less training instances for supervised learning we show that our proposed feedback strategy achieves 256 and 46 higher f1score and auc respectively than other oversampling strategies finally we perform a case study to show how our method is capable of detecting those users as spammers who have not been suspended by twitter and other baselines yet | [['cybercriminals', 'have', 'leveraged', 'the', 'popularity', 'of', 'a', 'large', 'user', 'base', 'available', 'on', 'online', 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1,802.04169 | Geometrical meaning of winding number and its characterization of
topological phases in one-dimensional chiral non-Hermitian systems | We unveil the geometrical meaning of winding number and utilize it to
characterize the topological phases in one-dimensional chiral non-Hermitian
systems. While chiral symmetry ensures the winding number of Hermitian systems
being integers, it can take half integers for non-Hermitian systems. We give a
geometrical interpretation of the half integers by demonstrating that the
winding number $\nu$ of a non-Hermitian system is equal to half of the
summation of two winding numbers $\nu_1$ and $\nu_2$ associated with two
exceptional points respectively. The winding numbers $\nu_1$ and $\nu_2$
represent the times of real part of the Hamiltonian in momentum space
encircling the exceptional points and can only take integers. We further find
that the difference of $\nu_1$ and $\nu_2$ is related to the second winding
number or energy vorticity. By applying our scheme to a non-Hermitian
Su-Schrieffer-Heeger model and an extended version of it, we show that the
topologically different phases can be well characterized by winding numbers.
Furthermore, we demonstrate that the existence of left and right zero-mode edge
states is closely related to the winding number $\nu_1$ and $\nu_2$.
| cond-mat.mes-hall | we unveil the geometrical meaning of winding number and utilize it to characterize the topological phases in onedimensional chiral nonhermitian systems while chiral symmetry ensures the winding number of hermitian systems being integers it can take half integers for nonhermitian systems we give a geometrical interpretation of the half integers by demonstrating that the winding number nu of a nonhermitian system is equal to half of the summation of two winding numbers nu_1 and nu_2 associated with two exceptional points respectively the winding numbers nu_1 and nu_2 represent the times of real part of the hamiltonian in momentum space encircling the exceptional points and can only take integers we further find that the difference of nu_1 and nu_2 is related to the second winding number or energy vorticity by applying our scheme to a nonhermitian suschriefferheeger model and an extended version of it we show that the topologically different phases can be well characterized by winding numbers furthermore we demonstrate that the existence of left and right zeromode edge states is closely related to the winding number nu_1 and nu_2 | [['we', 'unveil', 'the', 'geometrical', 'meaning', 'of', 'winding', 'number', 'and', 'utilize', 'it', 'to', 'characterize', 'the', 'topological', 'phases', 'in', 'onedimensional', 'chiral', 'nonhermitian', 'systems', 'while', 'chiral', 'symmetry', 'ensures', 'the', 'winding', 'number', 'of', 'hermitian', 'systems', 'being', 'integers', 'it', 'can', 'take', 'half', 'integers', 'for', 'nonhermitian', 'systems', 'we', 'give', 'a', 'geometrical', 'interpretation', 'of', 'the', 'half', 'integers', 'by', 'demonstrating', 'that', 'the', 'winding', 'number', 'nu', 'of', 'a', 'nonhermitian', 'system', 'is', 'equal', 'to', 'half', 'of', 'the', 'summation', 'of', 'two', 'winding', 'numbers', 'nu_1', 'and', 'nu_2', 'associated', 'with', 'two', 'exceptional', 'points', 'respectively', 'the', 'winding', 'numbers', 'nu_1', 'and', 'nu_2', 'represent', 'the', 'times', 'of', 'real', 'part', 'of', 'the', 'hamiltonian', 'in', 'momentum', 'space', 'encircling', 'the', 'exceptional', 'points', 'and', 'can', 'only', 'take', 'integers', 'we', 'further', 'find', 'that', 'the', 'difference', 'of', 'nu_1', 'and', 'nu_2', 'is', 'related', 'to', 'the', 'second', 'winding', 'number', 'or', 'energy', 'vorticity', 'by', 'applying', 'our', 'scheme', 'to', 'a', 'nonhermitian', 'suschriefferheeger', 'model', 'and', 'an', 'extended', 'version', 'of', 'it', 'we', 'show', 'that', 'the', 'topologically', 'different', 'phases', 'can', 'be', 'well', 'characterized', 'by', 'winding', 'numbers', 'furthermore', 'we', 'demonstrate', 'that', 'the', 'existence', 'of', 'left', 'and', 'right', 'zeromode', 'edge', 'states', 'is', 'closely', 'related', 'to', 'the', 'winding', 'number', 'nu_1', 'and', 'nu_2']] | [-0.254089498343981, 0.24289464268699199, -0.03957548040384103, 0.04960711476224888, -0.0400467495744427, -0.1527605888356144, 0.04640514386378022, 0.30219363525716797, -0.24100406306744035, -0.28751594023779037, 0.0613734631294695, -0.2778112604981288, -0.1628891263014844, 0.1461259561176929, -0.025334463155983637, 0.02828670252735416, 0.003861580413973166, 0.04356039223235308, -0.05154692537875639, -0.22381362521813974, 0.32261208702499666, -0.06898820445251962, 0.20744681479150637, 0.014763672600707246, 0.03773161310236901, -0.03377916229785317, 0.05043194760380882, -0.018697019277897197, -0.11491623889321798, 0.06142871130432468, 0.18452595355661794, 0.03320372774420927, 0.18274732722072964, -0.4045944523687164, -0.12167145733773295, 0.14797814153652225, 0.19107694587049384, 0.05738579115907972, 0.025168970410919023, -0.3085724926553667, 0.091596111913936, -0.13359454734923526, -0.1891672292827732, -0.099807590401421, 0.05501116610442599, -0.007073703284388304, -0.2470072008928077, 0.05655108956723577, 0.03321460346859466, 0.04989652000626342, -0.00727457718506533, -0.1368376240645173, -0.0986410375425799, 0.08733294687570176, 0.06325484323703373, -0.022156656199755768, 0.06376611741013928, -0.07043231956841838, -0.15116856733026604, 0.3908683778200712, -0.00015980930378039677, -0.2375033745723259, 0.13507619006041852, -0.1673763771025632, -0.0973241104485674, 0.16193691635918286, 0.058676338821856515, 0.09871875031644271, -0.008709719673626952, 0.08441790600772947, -0.08430985437395672, 0.1558070475188692, 0.087734826734393, 0.07944390212133941, 0.25652956450358033, 0.04640403977310699, 0.08752158810643272, 0.1626396812828413, -0.08658221138919342, -0.1254228905153771, -0.31327176926036676, -0.20070181301885492, -0.2781077410133245, 0.09657355192151347, -0.06378318333364506, -0.15285787398719952, 0.4748818859581459, 0.12487759811984789, 0.24151873726190792, 0.03970972046954557, 0.24718202236884584, 0.1596486911623894, 0.04703713477227009, 0.0627995182113308, 0.1699811349157244, 0.14480567624042223, 0.04572914556031012, -0.24606640450801934, -0.06494642974705332, 0.11716244339735972] |
1,802.0417 | Design of Experiments for Model Discrimination Hybridising Analytical
and Data-Driven Approaches | Healthcare companies must submit pharmaceutical drugs or medical devices to
regulatory bodies before marketing new technology. Regulatory bodies frequently
require transparent and interpretable computational modelling to justify a new
healthcare technology, but researchers may have several competing models for a
biological system and too little data to discriminate between the models. In
design of experiments for model discrimination, the goal is to design maximally
informative physical experiments in order to discriminate between rival
predictive models. Prior work has focused either on analytical approaches,
which cannot manage all functions, or on data-driven approaches, which may have
computational difficulties or lack interpretable marginal predictive
distributions. We develop a methodology introducing Gaussian process surrogates
in lieu of the original mechanistic models. We thereby extend existing design
and model discrimination methods developed for analytical models to cases of
non-analytical models in a computationally efficient manner.
| stat.AP stat.ML | healthcare companies must submit pharmaceutical drugs or medical devices to regulatory bodies before marketing new technology regulatory bodies frequently require transparent and interpretable computational modelling to justify a new healthcare technology but researchers may have several competing models for a biological system and too little data to discriminate between the models in design of experiments for model discrimination the goal is to design maximally informative physical experiments in order to discriminate between rival predictive models prior work has focused either on analytical approaches which cannot manage all functions or on datadriven approaches which may have computational difficulties or lack interpretable marginal predictive distributions we develop a methodology introducing gaussian process surrogates in lieu of the original mechanistic models we thereby extend existing design and model discrimination methods developed for analytical models to cases of nonanalytical models in a computationally efficient manner | [['healthcare', 'companies', 'must', 'submit', 'pharmaceutical', 'drugs', 'or', 'medical', 'devices', 'to', 'regulatory', 'bodies', 'before', 'marketing', 'new', 'technology', 'regulatory', 'bodies', 'frequently', 'require', 'transparent', 'and', 'interpretable', 'computational', 'modelling', 'to', 'justify', 'a', 'new', 'healthcare', 'technology', 'but', 'researchers', 'may', 'have', 'several', 'competing', 'models', 'for', 'a', 'biological', 'system', 'and', 'too', 'little', 'data', 'to', 'discriminate', 'between', 'the', 'models', 'in', 'design', 'of', 'experiments', 'for', 'model', 'discrimination', 'the', 'goal', 'is', 'to', 'design', 'maximally', 'informative', 'physical', 'experiments', 'in', 'order', 'to', 'discriminate', 'between', 'rival', 'predictive', 'models', 'prior', 'work', 'has', 'focused', 'either', 'on', 'analytical', 'approaches', 'which', 'can', 'not', 'manage', 'all', 'functions', 'or', 'on', 'datadriven', 'approaches', 'which', 'may', 'have', 'computational', 'difficulties', 'or', 'lack', 'interpretable', 'marginal', 'predictive', 'distributions', 'we', 'develop', 'a', 'methodology', 'introducing', 'gaussian', 'process', 'surrogates', 'in', 'lieu', 'of', 'the', 'original', 'mechanistic', 'models', 'we', 'thereby', 'extend', 'existing', 'design', 'and', 'model', 'discrimination', 'methods', 'developed', 'for', 'analytical', 'models', 'to', 'cases', 'of', 'nonanalytical', 'models', 'in', 'a', 'computationally', 'efficient', 'manner']] | [-0.0011688797655974475, 0.037500081170665125, -0.08482095259438518, 0.12630660152421705, -0.15218244511699697, -0.23310861239721342, 0.08019808026581583, 0.43839031460524447, -0.21358020773032863, -0.339492935595483, 0.0912025639859871, -0.2784826255232935, -0.17514086273846438, 0.20834181858325035, -0.13647849394113454, 0.10637535462418282, 0.06386765603527007, -0.03305859493360606, -0.02493824376593488, -0.24568377940220312, 0.23247441918339948, 0.06860200076652559, 0.3285031112789793, 0.021639948786223228, 0.060061734058225236, -0.052614513891224395, -0.05642436424694122, -0.042192637599737924, -0.12529884017085735, 0.20303888336597928, 0.37435264558842674, 0.23097634207273662, 0.36699937687675194, -0.4981420287947682, -0.29523033890742023, 0.15994608361916748, 0.1497558569904535, 0.10772866611926436, -0.02120004392218363, -0.24820632512458193, 0.03084284122246252, -0.22556449983983864, -0.0842066864518106, -0.20705419793252794, -0.01927614550132462, -0.023343947847229495, -0.3148052560749241, 0.04938989863927725, 0.022814275088152702, 0.056838875308527916, -0.0534858161672289, -0.14596808187148705, 0.022361487058371727, 0.1471575948321195, 0.06489491481706992, -0.03280250169500761, 0.154288095012176, -0.1757612388866337, -0.17849294226255896, 0.33844031479445774, 0.035557300033552806, -0.2628945907279456, 0.26640332514964515, -0.04544518628603661, -0.14623205587890944, 0.07812802443398871, 0.2533925580037889, 0.06802365955122759, -0.23527635823489285, 0.019018860576054553, 0.0679498036510088, 0.1739830916524458, 0.02090505456870002, -0.027190325952226847, 0.23858688442482495, 0.21068451001471183, 0.026744080626268044, 0.0737070858111264, -0.00040047905985003625, -0.11486058208015813, -0.20737988944493338, -0.09867811715230346, -0.11569001461120165, 0.001868439589165525, -0.07015845870804517, -0.17793817948742646, 0.3566564297775777, 0.2147616083523862, 0.11541995991834662, 0.03896189867322084, 0.3463644003954677, 0.0034498167425085803, 0.09061090027196923, 0.02053206331345817, 0.19746430766847456, 0.03167126667489049, 0.11975569243241153, -0.10745943204498141, 0.1829737448375377, -0.030242738230350678] |
1,802.04171 | On the BV formalism of open superstring field theory in the large
Hilbert space | We construct several BV master actions for open superstring field theory in
the large Hilbert space. First, we show that a naive use of the conventional BV
approach breaks down at the third order of the antifield number expansion,
although it enables us to define a simple "string antibracket" taking the
Darboux form as space-time antibrackets. This fact implies that in the large
Hilbert space, "string fields-antifields" should be reassembled to obtain
master actions in a simple manner. We determine the assembly of the string
antifields on the basis of Berkovits' constrained BV approach, and give
solutions to the master equation defined by Dirac antibrackets on the
constrained string field-antifield space. It is expected that partially
gauge-fixing enables us to relate superstring field theories based on the large
and small Hilbert spaces directly: Reassembling string fields-antifields is
rather natural from this point of view. Finally, inspired by these results, we
revisit the conventional BV approach and construct a BV master action based on
the minimal set of string fields-antifields.
| hep-th | we construct several bv master actions for open superstring field theory in the large hilbert space first we show that a naive use of the conventional bv approach breaks down at the third order of the antifield number expansion although it enables us to define a simple string antibracket taking the darboux form as spacetime antibrackets this fact implies that in the large hilbert space string fieldsantifields should be reassembled to obtain master actions in a simple manner we determine the assembly of the string antifields on the basis of berkovits constrained bv approach and give solutions to the master equation defined by dirac antibrackets on the constrained string fieldantifield space it is expected that partially gaugefixing enables us to relate superstring field theories based on the large and small hilbert spaces directly reassembling string fieldsantifields is rather natural from this point of view finally inspired by these results we revisit the conventional bv approach and construct a bv master action based on the minimal set of string fieldsantifields | [['we', 'construct', 'several', 'bv', 'master', 'actions', 'for', 'open', 'superstring', 'field', 'theory', 'in', 'the', 'large', 'hilbert', 'space', 'first', 'we', 'show', 'that', 'a', 'naive', 'use', 'of', 'the', 'conventional', 'bv', 'approach', 'breaks', 'down', 'at', 'the', 'third', 'order', 'of', 'the', 'antifield', 'number', 'expansion', 'although', 'it', 'enables', 'us', 'to', 'define', 'a', 'simple', 'string', 'antibracket', 'taking', 'the', 'darboux', 'form', 'as', 'spacetime', 'antibrackets', 'this', 'fact', 'implies', 'that', 'in', 'the', 'large', 'hilbert', 'space', 'string', 'fieldsantifields', 'should', 'be', 'reassembled', 'to', 'obtain', 'master', 'actions', 'in', 'a', 'simple', 'manner', 'we', 'determine', 'the', 'assembly', 'of', 'the', 'string', 'antifields', 'on', 'the', 'basis', 'of', 'berkovits', 'constrained', 'bv', 'approach', 'and', 'give', 'solutions', 'to', 'the', 'master', 'equation', 'defined', 'by', 'dirac', 'antibrackets', 'on', 'the', 'constrained', 'string', 'fieldantifield', 'space', 'it', 'is', 'expected', 'that', 'partially', 'gaugefixing', 'enables', 'us', 'to', 'relate', 'superstring', 'field', 'theories', 'based', 'on', 'the', 'large', 'and', 'small', 'hilbert', 'spaces', 'directly', 'reassembling', 'string', 'fieldsantifields', 'is', 'rather', 'natural', 'from', 'this', 'point', 'of', 'view', 'finally', 'inspired', 'by', 'these', 'results', 'we', 'revisit', 'the', 'conventional', 'bv', 'approach', 'and', 'construct', 'a', 'bv', 'master', 'action', 'based', 'on', 'the', 'minimal', 'set', 'of', 'string', 'fieldsantifields']] | [-0.11084952816841077, 0.11207572160668935, -0.1293764177505919, 0.12208393558077293, -0.13789108445173537, -0.09682379742896945, 0.0726137675734832, 0.3182863363329343, -0.2658990147143338, -0.25357443336176977, 0.07489704818825772, -0.19678110298121998, -0.1741598123497159, 0.16453370754469251, -0.12802209634989634, 0.0037076703752198163, 0.032262022611161574, 0.06859396899824399, -0.11372337757455482, -0.2846057630259786, 0.3749572567878699, -0.02707598679946989, 0.2613338718642674, -0.028186440179895984, 0.1444736274907134, 0.0490217496428815, -0.03241083142674837, 0.01840558982769044, -0.1250954653162178, 0.16088550068719104, 0.2079578064955198, 0.12965837400957678, 0.19681184255001727, -0.4377639266116732, -0.18563169727829346, 0.06988731999716243, 0.1414341439187152, 0.14873927130264689, 0.021444641016478812, -0.2768410499780797, 0.05588731356516216, -0.1485763561371824, -0.13924778444064262, -0.12791346422997277, 0.009902541332784488, -0.06984738866073911, -0.22002045431080655, 0.013491387100140813, -0.020740606050563635, 0.01453049270403103, -0.0683438993946335, -0.055184194648682454, -0.025454334194149227, 0.08748898779995432, 0.020951954973034956, 0.12380707121492755, 0.08971538656865131, -0.09734039343190903, -0.11143403023222362, 0.39243985338345966, -0.09379109853986077, -0.2232917439765655, 0.12146335298790646, -0.12178601138569282, -0.17031180895258777, 0.09429674366896851, 0.09211705409447778, 0.1461277742974857, -0.17906355374002245, 0.22011598063536925, -0.03978842170633508, 0.11089139295340317, 0.07705943331056268, 0.05259083773797521, 0.17438389099142432, 0.12755583603205103, 0.04836347527228869, 0.11985550388850867, -0.021715721068628263, -0.13892934540494692, -0.3858656189762629, -0.1421209428453895, -0.12742313270087866, 0.11699736080016698, -0.09736125749791077, -0.18594835808958043, 0.3485608794306234, 0.15990891394938325, 0.18365332263813922, 0.1017470775590934, 0.20706723243984554, 0.14882884028695934, 0.08249031305147787, 0.06098019148735605, 0.17931296511624867, 0.1359201493960965, 0.07786193426378821, -0.22719922456642358, -0.09780714432185394, 0.1996328988933616] |
1,802.04172 | Coded Distributed Computing with Node Cooperation Substantially
Increases Speedup Factors | This work explores a distributed computing setting where $K$ nodes are
assigned fractions (subtasks) of a computational task in order to perform the
computation in parallel. In this setting, a well-known main bottleneck has been
the inter-node communication cost required to parallelize the task, because
unlike the computational cost which could keep decreasing as $K$ increases, the
communication cost remains approximately constant, thus bounding the total
speedup gains associated to having more computing nodes. This bottleneck was
substantially ameliorated by the recent introduction of coded MapReduce
techniques which allowed each node --- at the computational cost of having to
preprocess approximately $t$ times more subtasks --- to reduce its
communication cost by approximately $t$ times. In reality though, the
associated speed up gains were severely limited by the requirement that larger
$t$ and $K$ necessitated that the original task be divided into an extremely
large number of subtasks. In this work we show how node cooperation, along with
a novel assignment of tasks, can help to dramatically ameliorate this
limitation. The result applies to wired as well as wireless distributed
computing, and it is based on the idea of having groups of nodes compute
identical parallelization (mapping) tasks and then employing a here-proposed
novel D2D coded caching algorithm.
| cs.IT math.IT | this work explores a distributed computing setting where k nodes are assigned fractions subtasks of a computational task in order to perform the computation in parallel in this setting a wellknown main bottleneck has been the internode communication cost required to parallelize the task because unlike the computational cost which could keep decreasing as k increases the communication cost remains approximately constant thus bounding the total speedup gains associated to having more computing nodes this bottleneck was substantially ameliorated by the recent introduction of coded mapreduce techniques which allowed each node at the computational cost of having to preprocess approximately t times more subtasks to reduce its communication cost by approximately t times in reality though the associated speed up gains were severely limited by the requirement that larger t and k necessitated that the original task be divided into an extremely large number of subtasks in this work we show how node cooperation along with a novel assignment of tasks can help to dramatically ameliorate this limitation the result applies to wired as well as wireless distributed computing and it is based on the idea of having groups of nodes compute identical parallelization mapping tasks and then employing a hereproposed novel d2d coded caching algorithm | [['this', 'work', 'explores', 'a', 'distributed', 'computing', 'setting', 'where', 'k', 'nodes', 'are', 'assigned', 'fractions', 'subtasks', 'of', 'a', 'computational', 'task', 'in', 'order', 'to', 'perform', 'the', 'computation', 'in', 'parallel', 'in', 'this', 'setting', 'a', 'wellknown', 'main', 'bottleneck', 'has', 'been', 'the', 'internode', 'communication', 'cost', 'required', 'to', 'parallelize', 'the', 'task', 'because', 'unlike', 'the', 'computational', 'cost', 'which', 'could', 'keep', 'decreasing', 'as', 'k', 'increases', 'the', 'communication', 'cost', 'remains', 'approximately', 'constant', 'thus', 'bounding', 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1,802.04173 | Topological Photonics | Topological photonics is a rapidly emerging field of research in which
geometrical and topological ideas are exploited to design and control the
behavior of light. Drawing inspiration from the discovery of the quantum Hall
effects and topological insulators in condensed matter, recent advances have
shown how to engineer analogous effects also for photons, leading to remarkable
phenomena such as the robust unidirectional propagation of light, which hold
great promise for applications. Thanks to the flexibility and diversity of
photonics systems, this field is also opening up new opportunities to realize
exotic topological models and to probe and exploit topological effects in new
ways. This article reviews experimental and theoretical developments in
topological photonics across a wide range of experimental platforms, including
photonic crystals, waveguides, metamaterials, cavities, optomechanics, silicon
photonics, and circuit QED. A discussion of how changing the dimensionality and
symmetries of photonics systems has allowed for the realization of different
topological phases is offered, and progress in understanding the interplay of
topology with non-Hermitian effects, such as dissipation, is reviewed. As an
exciting perspective, topological photonics can be combined with optical
nonlinearities, leading toward new collective phenomena and novel strongly
correlated states of light, such as an analog of the fractional quantum Hall
effect.
| physics.optics cond-mat.mes-hall cond-mat.quant-gas quant-ph | topological photonics is a rapidly emerging field of research in which geometrical and topological ideas are exploited to design and control the behavior of light drawing inspiration from the discovery of the quantum hall effects and topological insulators in condensed matter recent advances have shown how to engineer analogous effects also for photons leading to remarkable phenomena such as the robust unidirectional propagation of light which hold great promise for applications thanks to the flexibility and diversity of photonics systems this field is also opening up new opportunities to realize exotic topological models and to probe and exploit topological effects in new ways this article reviews experimental and theoretical developments in topological photonics across a wide range of experimental platforms including photonic crystals waveguides metamaterials cavities optomechanics silicon photonics and circuit qed a discussion of how changing the dimensionality and symmetries of photonics systems has allowed for the realization of different topological phases is offered and progress in understanding the interplay of topology with nonhermitian effects such as dissipation is reviewed as an exciting perspective topological photonics can be combined with optical nonlinearities leading toward new collective phenomena and novel strongly correlated states of light such as an analog of the fractional quantum hall effect | [['topological', 'photonics', 'is', 'a', 'rapidly', 'emerging', 'field', 'of', 'research', 'in', 'which', 'geometrical', 'and', 'topological', 'ideas', 'are', 'exploited', 'to', 'design', 'and', 'control', 'the', 'behavior', 'of', 'light', 'drawing', 'inspiration', 'from', 'the', 'discovery', 'of', 'the', 'quantum', 'hall', 'effects', 'and', 'topological', 'insulators', 'in', 'condensed', 'matter', 'recent', 'advances', 'have', 'shown', 'how', 'to', 'engineer', 'analogous', 'effects', 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1,802.04174 | Unbounded Software Model Checking with Incremental SAT-Solving | This paper describes a novel unbounded software model checking approach to
find errors in programs written in the C language based on incremental
SAT-solving. Instead of using the traditional assumption based API to
incremental SAT solvers we use the DimSpec format that is used in SAT based
automated planning. A DimSpec formula consists of four CNF formulas
representing the initial, goal and intermediate states and the relations
between each pair of neighboring states of a transition system. We present a
new tool called LLUMC which encodes the presence of certain errors in a C
program into a DimSpec formula, which can be solved by either an incremental
SAT-based DimSpec solver or the IC3 algorithm for invariant checking. We
evaluate the approach in the context of SAT-based model checking for both the
incremental SAT-solving and the IC3 algorithm. We show that our encoding
expands the functionality of bounded model checkers by also covering large and
infinite loops, while still maintaining a feasible time performance.
Furthermore, we demonstrate that our approach offers the opportunity to
generate runtime-optimizations by utilizing parallel SAT-solving.
| cs.SC cs.PL | this paper describes a novel unbounded software model checking approach to find errors in programs written in the c language based on incremental satsolving instead of using the traditional assumption based api to incremental sat solvers we use the dimspec format that is used in sat based automated planning a dimspec formula consists of four cnf formulas representing the initial goal and intermediate states and the relations between each pair of neighboring states of a transition system we present a new tool called llumc which encodes the presence of certain errors in a c program into a dimspec formula which can be solved by either an incremental satbased dimspec solver or the ic3 algorithm for invariant checking we evaluate the approach in the context of satbased model checking for both the incremental satsolving and the ic3 algorithm we show that our encoding expands the functionality of bounded model checkers by also covering large and infinite loops while still maintaining a feasible time performance furthermore we demonstrate that our approach offers the opportunity to generate runtimeoptimizations by utilizing parallel satsolving | [['this', 'paper', 'describes', 'a', 'novel', 'unbounded', 'software', 'model', 'checking', 'approach', 'to', 'find', 'errors', 'in', 'programs', 'written', 'in', 'the', 'c', 'language', 'based', 'on', 'incremental', 'satsolving', 'instead', 'of', 'using', 'the', 'traditional', 'assumption', 'based', 'api', 'to', 'incremental', 'sat', 'solvers', 'we', 'use', 'the', 'dimspec', 'format', 'that', 'is', 'used', 'in', 'sat', 'based', 'automated', 'planning', 'a', 'dimspec', 'formula', 'consists', 'of', 'four', 'cnf', 'formulas', 'representing', 'the', 'initial', 'goal', 'and', 'intermediate', 'states', 'and', 'the', 'relations', 'between', 'each', 'pair', 'of', 'neighboring', 'states', 'of', 'a', 'transition', 'system', 'we', 'present', 'a', 'new', 'tool', 'called', 'llumc', 'which', 'encodes', 'the', 'presence', 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0.11933867301855047, 0.12243018647164862] |
1,802.04175 | On monomial algebras having the double centraliser property | Let $A$ be a finite dimensional algebra having the double centraliser
property with respect to a minimal faithful projective-injective left module
$Af$ for some idempotent $f$. We prove that in this case $A$ is a monomial
algebra if and only if $A$ is a Nakayama algebra given by quiver and relations.
| math.RT | let a be a finite dimensional algebra having the double centraliser property with respect to a minimal faithful projectiveinjective left module af for some idempotent f we prove that in this case a is a monomial algebra if and only if a is a nakayama algebra given by quiver and relations | [['let', 'a', 'be', 'a', 'finite', 'dimensional', 'algebra', 'having', 'the', 'double', 'centraliser', 'property', 'with', 'respect', 'to', 'a', 'minimal', 'faithful', 'projectiveinjective', 'left', 'module', 'af', 'for', 'some', 'idempotent', 'f', 'we', 'prove', 'that', 'in', 'this', 'case', 'a', 'is', 'a', 'monomial', 'algebra', 'if', 'and', 'only', 'if', 'a', 'is', 'a', 'nakayama', 'algebra', 'given', 'by', 'quiver', 'and', 'relations']] | [-0.17162966514554093, 0.11216940358281136, -0.08727920062693895, 0.028276427532546222, -0.14182860201553388, -0.22801705271772602, -0.034636719371466076, 0.3583018552311057, -0.4188468142175207, -0.08646301420830081, 0.14927879271471836, -0.24748382078228043, -0.12618880182066383, 0.16172951217466855, -0.16189490455914946, -0.11509342285274875, 0.10749088388447668, 0.19743821795518493, -0.13386811049855954, -0.2462853391600006, 0.3790671168004765, -0.015410227043663753, 0.17836715666321562, 0.008953990853008102, 0.17304216940686398, 0.01758533973628016, 0.05578654641559457, 0.036113995414994216, -0.1446766921864907, 0.07623679846452147, 0.3130899616608433, 0.07918736539945445, 0.25284866966745434, -0.3164499045769666, -0.07558831444704066, 0.2670981345661715, 0.14236075715983615, -0.02681332658611092, -0.06784219006943863, -0.2041110286041729, 0.19656322361426612, -0.2938353063575193, -0.14034438837210045, -0.05099955038167536, 0.14927188296090155, -0.05682450715525478, -0.3629208180103816, -0.04196468048601174, 0.11407199240855727, 0.16928612201602436, -0.05066242566624401, -0.019194914557624097, -0.14345074976410935, 0.00426312461130175, -0.13472628526791347, 0.09495362083372824, 0.04159746820326237, -0.08534113542983131, -0.1430681290073028, 0.3560954801665217, -0.022625274921986547, -0.3060874538678749, 0.10561844654490843, -0.2298335887802144, -0.13718799167477033, 0.059153528190126606, -0.03187857223126818, 0.10229852656815566, -0.0336720016145823, 0.27810967565450234, -0.1903495671519754, 0.08086525401392695, 0.04656331425569221, -0.021498091847581023, 0.1526066621938976, 0.10095488243535453, 0.06852111042312839, 0.1393851448539827, 0.08723091250102893, 0.0691561743470968, -0.3643645215231706, -0.21777769563463972, -0.0870093733400983, 0.16189653152490363, -0.0964952810369569, -0.1807845299515654, 0.4178147095383382, 0.07435977836390592, 0.16328646448970424, 0.13182282383900648, 0.21672690013313994, 0.09007335059783038, 0.09948011363546054, 0.07006604158703018, 0.06280119585925621, 0.28565571808219686, -0.0853166047520205, -0.11754968157038093, -0.011342683880060328, 0.23539480517673142] |
1,802.04176 | Poisson processes and a log-concave Bernstein theorem | We discuss interplays between log-concave functions and log-concave
sequences. We prove a Bernstein-type theorem, which characterizes the Laplace
transform of log-concave measures on the half-line in terms of log-concavity of
the alternating Taylor coefficients. We establish concavity inequalities for
sequences inspired by the Pr\'ekopa-Leindler and the Walkup theorems. One of
our main tools is a stochastic variational formula for the Poisson average.
| math.PR math.FA | we discuss interplays between logconcave functions and logconcave sequences we prove a bernsteintype theorem which characterizes the laplace transform of logconcave measures on the halfline in terms of logconcavity of the alternating taylor coefficients we establish concavity inequalities for sequences inspired by the prekopaleindler and the walkup theorems one of our main tools is a stochastic variational formula for the poisson average | [['we', 'discuss', 'interplays', 'between', 'logconcave', 'functions', 'and', 'logconcave', 'sequences', 'we', 'prove', 'a', 'bernsteintype', 'theorem', 'which', 'characterizes', 'the', 'laplace', 'transform', 'of', 'logconcave', 'measures', 'on', 'the', 'halfline', 'in', 'terms', 'of', 'logconcavity', 'of', 'the', 'alternating', 'taylor', 'coefficients', 'we', 'establish', 'concavity', 'inequalities', 'for', 'sequences', 'inspired', 'by', 'the', 'prekopaleindler', 'and', 'the', 'walkup', 'theorems', 'one', 'of', 'our', 'main', 'tools', 'is', 'a', 'stochastic', 'variational', 'formula', 'for', 'the', 'poisson', 'average']] | [-0.11199228102040867, 0.04188062929578366, -0.13293046490552143, 0.178666930084282, -0.03472642654613141, -0.12539766906129737, 0.04641325566016378, 0.3138902908371341, -0.31988292451827754, -0.1648400640715995, 0.08350965838631495, -0.2762533785970581, -0.1951707182151656, 0.21200510474943346, -0.1530550317388148, 0.09012723732138833, 0.014928625337028455, 0.00473049771220934, -0.13308539427065802, -0.25521140052906927, 0.34692036069088406, -0.0681343385048451, 0.26134754953935985, 0.11280739594311003, 0.15863128285855055, 0.09382726522462984, -0.0730806703514029, -0.08807537862430176, -0.2125813327279062, 0.21573222756025293, 0.20864019479842916, 0.1627379537958111, 0.30969916362195243, -0.3669036883079717, -0.14592553134406766, 0.17618218829645024, 0.08007527428497034, -0.018948156343427516, -0.007350075494257673, -0.3167540349306599, 0.06972743923805895, -0.09206246680790378, -0.19279979700372823, -0.08277357564938645, -0.030714484862983227, 0.19760029642812668, -0.3600255327840005, 0.13768717244590423, 0.1953861557112466, 0.045903685114031, -0.08203911562750657, -0.1700317138325303, 0.07053277403258928, 0.01714935844704028, 0.07899819213461372, -0.00555527561734761, 0.09194078335478421, -0.036730279777980136, -0.14062739423600085, 0.24609637352067135, -0.07803315514578454, -0.2835493546219603, 0.0911526899904974, -0.1588608773139816, -0.2215922510611915, 0.04421566001650307, 0.10954159188775285, 0.17533355317409, -0.13161879375336633, 0.12846009119135898, -0.10490179539568001, 0.056500935175966834, 0.14817423012948805, 0.021740156376073436, 0.06982560440777771, 0.019161152503182812, 0.17271327241624315, 0.23055858717810723, -0.019390613512857067, -0.1409230310800335, -0.30587624068392605, -0.2205032085579249, -0.2809283881853785, 0.07652613579956515, -0.21590144157122385, -0.1992400992631672, 0.35613884066321677, 0.04408310332726086, 0.13128664230387058, 0.21016148539567966, 0.20380385876858548, 0.19073016048716981, -0.04400432342287874, 0.04558243175908443, 0.11494980087023109, 0.28981321506697927, 0.08347866387527075, -0.10218476496952315, 0.08676429692235205, 0.22658391217250498] |
1,802.04177 | Order parameters for the high-energy spectra of pulsars | From the hundreds of gamma-ray pulsars known, only a handful show non-thermal
X-ray pulsations. Instead, nine objects pulse in non-thermal X-rays but lack
counterparts at higher energies. Here, we present a physical model for the
non-thermal emission of pulsars above 1 keV. With just four physical
parameters, we fit the spectrum of the gamma/X-ray pulsars along seven orders
of magnitude. We find that all detections can be encompassed in a continuous
variation of the model parameters, and pose that their values could likely
relate to the closure mechanism operating in the accelerating region. The model
explains the appearance of sub-exponential cutoffs at high energies as a
natural consequence of synchro-curvature dominated losses, unveiling that
curvature-only emission may play a relatively minor role --if any-- in the
spectrum of most pulsars. The model also explains the flattening of the X-ray
spectra at soft energies as a result of propagating particles being subject to
synchrotron losses all along their trajectories. Using this model, we show how
observations in gamma-rays can predict the detectability of the pulsar in
X-rays, and viceversa.
| astro-ph.HE gr-qc | from the hundreds of gammaray pulsars known only a handful show nonthermal xray pulsations instead nine objects pulse in nonthermal xrays but lack counterparts at higher energies here we present a physical model for the nonthermal emission of pulsars above 1 kev with just four physical parameters we fit the spectrum of the gammaxray pulsars along seven orders of magnitude we find that all detections can be encompassed in a continuous variation of the model parameters and pose that their values could likely relate to the closure mechanism operating in the accelerating region the model explains the appearance of subexponential cutoffs at high energies as a natural consequence of synchrocurvature dominated losses unveiling that curvatureonly emission may play a relatively minor role if any in the spectrum of most pulsars the model also explains the flattening of the xray spectra at soft energies as a result of propagating particles being subject to synchrotron losses all along their trajectories using this model we show how observations in gammarays can predict the detectability of the pulsar in xrays and viceversa | [['from', 'the', 'hundreds', 'of', 'gammaray', 'pulsars', 'known', 'only', 'a', 'handful', 'show', 'nonthermal', 'xray', 'pulsations', 'instead', 'nine', 'objects', 'pulse', 'in', 'nonthermal', 'xrays', 'but', 'lack', 'counterparts', 'at', 'higher', 'energies', 'here', 'we', 'present', 'a', 'physical', 'model', 'for', 'the', 'nonthermal', 'emission', 'of', 'pulsars', 'above', '1', 'kev', 'with', 'just', 'four', 'physical', 'parameters', 'we', 'fit', 'the', 'spectrum', 'of', 'the', 'gammaxray', 'pulsars', 'along', 'seven', 'orders', 'of', 'magnitude', 'we', 'find', 'that', 'all', 'detections', 'can', 'be', 'encompassed', 'in', 'a', 'continuous', 'variation', 'of', 'the', 'model', 'parameters', 'and', 'pose', 'that', 'their', 'values', 'could', 'likely', 'relate', 'to', 'the', 'closure', 'mechanism', 'operating', 'in', 'the', 'accelerating', 'region', 'the', 'model', 'explains', 'the', 'appearance', 'of', 'subexponential', 'cutoffs', 'at', 'high', 'energies', 'as', 'a', 'natural', 'consequence', 'of', 'synchrocurvature', 'dominated', 'losses', 'unveiling', 'that', 'curvatureonly', 'emission', 'may', 'play', 'a', 'relatively', 'minor', 'role', 'if', 'any', 'in', 'the', 'spectrum', 'of', 'most', 'pulsars', 'the', 'model', 'also', 'explains', 'the', 'flattening', 'of', 'the', 'xray', 'spectra', 'at', 'soft', 'energies', 'as', 'a', 'result', 'of', 'propagating', 'particles', 'being', 'subject', 'to', 'synchrotron', 'losses', 'all', 'along', 'their', 'trajectories', 'using', 'this', 'model', 'we', 'show', 'how', 'observations', 'in', 'gammarays', 'can', 'predict', 'the', 'detectability', 'of', 'the', 'pulsar', 'in', 'xrays', 'and', 'viceversa']] | [-0.07569845308454991, 0.18895219083044068, -0.052714389308719564, 0.14806117332806168, -0.0897082099243788, -0.07069927644731719, 0.045904633460177036, 0.43287330483859876, -0.23578206931916987, -0.3587742104052992, 0.044004539497417665, -0.30024362914395747, -0.04834310791986642, 0.24069514192277724, -0.007926490208322161, -0.04146263629484509, 0.05032859332096568, -0.0225468351266289, -0.03381005123962706, -0.16072130302356302, 0.2636730372984657, 0.09461956494750907, 0.16833822049547809, 0.04627157059777002, 0.07968494969572724, -0.0633571624761121, -0.002555157492360847, -0.027897680612375676, -0.05595029801807575, 0.06480087438140507, 0.21761004235279763, 0.0995163124132445, 0.19385549333867338, -0.38973085453870604, -0.2738959235218117, 0.12164319095288609, 0.1596003040989682, 0.029307943800369562, -0.030834720193113774, -0.2147128682104755, 0.05012000231519552, -0.20354494554553665, -0.19140977272763848, 0.002076528219264106, 0.002600523610309945, 0.03194051734461202, -0.17425210067823446, 0.0983253583444564, 0.06421295730896967, 0.027444511115298432, -0.15370939608589657, -0.08148122149832694, -0.011039410775664163, 0.06684570227312923, 0.08716959243385111, -0.01337940314005913, 0.1431607515419607, -0.16285697859975032, -0.13683555485670176, 0.40466130630634095, -0.059395921037079885, -0.04665733789656795, 0.21094115669076136, -0.226981826315997, -0.19654513715298078, 0.20851442447237375, 0.13404300549635823, 0.10279047051918204, -0.13970376504848234, 0.025400370248267162, -0.006886936667622567, 0.2056151114984305, 0.08138774032836076, 0.07344138102163955, 0.28752731713913593, 0.10069228790201888, 0.00882025621831417, 0.1413756431939375, -0.19264019079411687, -0.007672233867464261, -0.30912930199529154, -0.05189045774487326, -0.13573499661765068, 0.078752642049024, -0.08712029849862453, -0.1382976754536947, 0.4281826913356781, 0.133430332589321, 0.22130393326324596, 0.03729270615530763, 0.29923150874805865, 0.12297507025443523, 0.06554852967745083, 0.11358251966967506, 0.327479019498, 0.09828415672456099, 0.07559835317802463, -0.18738866042961383, 0.09704489270119933, -0.030318139836035596] |
1,802.04178 | Dimension Reduction Using Active Manifolds | Scientists and engineers rely on accurate mathematical models to quantify the
objects of their studies, which are often high-dimensional. Unfortunately,
high-dimensional models are inherently difficult, i.e. when observations are
sparse or expensive to determine. One way to address this problem is to
approximate the original model with fewer input dimensions. Our project goal
was to recover a function f that takes n inputs and returns one output, where n
is potentially large. For any given n-tuple, we assume that we can observe a
sample of the gradient and output of the function but it is computationally
expensive to do so. This project was inspired by an approach known as Active
Subspaces, which works by linearly projecting to a linear subspace where the
function changes most on average. Our research gives mathematical developments
informing a novel algorithm for this problem. Our approach, Active Manifolds,
increases accuracy by seeking nonlinear analogues that approximate the
function. The benefits of our approach are eliminated unprincipled parameter,
choices, guaranteed accessible visualization, and improved estimation accuracy.
| cs.LG math.CA stat.ML | scientists and engineers rely on accurate mathematical models to quantify the objects of their studies which are often highdimensional unfortunately highdimensional models are inherently difficult ie when observations are sparse or expensive to determine one way to address this problem is to approximate the original model with fewer input dimensions our project goal was to recover a function f that takes n inputs and returns one output where n is potentially large for any given ntuple we assume that we can observe a sample of the gradient and output of the function but it is computationally expensive to do so this project was inspired by an approach known as active subspaces which works by linearly projecting to a linear subspace where the function changes most on average our research gives mathematical developments informing a novel algorithm for this problem our approach active manifolds increases accuracy by seeking nonlinear analogues that approximate the function the benefits of our approach are eliminated unprincipled parameter choices guaranteed accessible visualization and improved estimation accuracy | [['scientists', 'and', 'engineers', 'rely', 'on', 'accurate', 'mathematical', 'models', 'to', 'quantify', 'the', 'objects', 'of', 'their', 'studies', 'which', 'are', 'often', 'highdimensional', 'unfortunately', 'highdimensional', 'models', 'are', 'inherently', 'difficult', 'ie', 'when', 'observations', 'are', 'sparse', 'or', 'expensive', 'to', 'determine', 'one', 'way', 'to', 'address', 'this', 'problem', 'is', 'to', 'approximate', 'the', 'original', 'model', 'with', 'fewer', 'input', 'dimensions', 'our', 'project', 'goal', 'was', 'to', 'recover', 'a', 'function', 'f', 'that', 'takes', 'n', 'inputs', 'and', 'returns', 'one', 'output', 'where', 'n', 'is', 'potentially', 'large', 'for', 'any', 'given', 'ntuple', 'we', 'assume', 'that', 'we', 'can', 'observe', 'a', 'sample', 'of', 'the', 'gradient', 'and', 'output', 'of', 'the', 'function', 'but', 'it', 'is', 'computationally', 'expensive', 'to', 'do', 'so', 'this', 'project', 'was', 'inspired', 'by', 'an', 'approach', 'known', 'as', 'active', 'subspaces', 'which', 'works', 'by', 'linearly', 'projecting', 'to', 'a', 'linear', 'subspace', 'where', 'the', 'function', 'changes', 'most', 'on', 'average', 'our', 'research', 'gives', 'mathematical', 'developments', 'informing', 'a', 'novel', 'algorithm', 'for', 'this', 'problem', 'our', 'approach', 'active', 'manifolds', 'increases', 'accuracy', 'by', 'seeking', 'nonlinear', 'analogues', 'that', 'approximate', 'the', 'function', 'the', 'benefits', 'of', 'our', 'approach', 'are', 'eliminated', 'unprincipled', 'parameter', 'choices', 'guaranteed', 'accessible', 'visualization', 'and', 'improved', 'estimation', 'accuracy']] | [-0.05233621838954551, 0.06048745992670507, -0.060582316532621486, 0.07965984918683877, -0.13645331731805688, -0.16934946745853213, 0.04076309997095343, 0.3899012546602856, -0.26772532149505635, -0.34880189113900995, 0.11813076059607898, -0.26395738394930957, -0.19165938526104367, 0.19786034775418504, -0.10337462330387687, 0.09231638598105157, 0.07506877147619996, 0.011549330623272588, -0.06311820840106948, -0.29586464817471364, 0.2719972996972501, 0.06093000265057472, 0.2726861540253808, -0.034205468322205196, 0.12356478597092278, 0.0018803901312982336, -0.05649664057692622, 0.008812015235204907, -0.08558523532971295, 0.1615766953495896, 0.30532849453965727, 0.18662188981166658, 0.34499202125212725, -0.4044809526761716, -0.2202194154591245, 0.13553897287381594, 0.15997721173951182, 0.12383436213302261, 0.008739486275076428, -0.2479154076468309, 0.07822277450331432, -0.1176270481390769, -0.10518386774586842, -0.12791249610428862, 0.01753576644422377, -0.0151374984477811, -0.3218405494151418, 0.03302377007682534, 0.0413351763615056, 0.018146135910030673, -0.018520338989465552, -0.1298231278792681, 0.0184911878697355, 0.14754225344290983, 0.03483380878631793, 0.0778722367797266, 0.12683263181927887, -0.10865482151960297, -0.09085541670347619, 0.3576678764787229, -0.003848292642985197, -0.25713455018532627, 0.19816860224476412, -0.08735826450728756, -0.13800879974852945, 0.12338611966765979, 0.19623555556377945, 0.14166557941969266, -0.1265899560185704, 0.07808490478954114, -0.03988540630294558, 0.19431525583324186, 0.0025142090395092963, 0.002904579426874133, 0.16194399867672474, 0.16324774145169238, 0.09334258652593502, 0.12681039476986317, -0.02347127081901657, -0.0813689322964124, -0.23848856306045918, -0.09785895810440279, -0.2200265094117426, 0.027182134361389804, -0.06303713698563275, -0.15832961418063324, 0.35873428273480384, 0.18857090463313986, 0.2198255205691299, 0.08527819818050107, 0.35187381111523686, 0.09895829168792047, 0.05050846453557503, 0.08968705428928575, 0.20535161023521248, 0.057177182471872694, 0.05393215628231273, -0.16549028395127285, 0.1079078676411882, 0.047564493384047904] |
1,802.04179 | Planar graphs without cycles of length 4 or 5 are (11:3)-colorable | A graph G is (a:b)-colorable if there exists an assignment of b-element
subsets of {1,...,a} to vertices of G such that sets assigned to adjacent
vertices are disjoint. We show that every planar graph without cycles of length
4 or 5 is (11:3)-colorable, a weakening of recently disproved Steinberg's
conjecture. In particular, each such graph with n vertices has an independent
set of size at least 3n/11.
| math.CO | a graph g is abcolorable if there exists an assignment of belement subsets of 1a to vertices of g such that sets assigned to adjacent vertices are disjoint we show that every planar graph without cycles of length 4 or 5 is 113colorable a weakening of recently disproved steinbergs conjecture in particular each such graph with n vertices has an independent set of size at least 3n11 | [['a', 'graph', 'g', 'is', 'abcolorable', 'if', 'there', 'exists', 'an', 'assignment', 'of', 'belement', 'subsets', 'of', '1a', 'to', 'vertices', 'of', 'g', 'such', 'that', 'sets', 'assigned', 'to', 'adjacent', 'vertices', 'are', 'disjoint', 'we', 'show', 'that', 'every', 'planar', 'graph', 'without', 'cycles', 'of', 'length', '4', 'or', '5', 'is', '113colorable', 'a', 'weakening', 'of', 'recently', 'disproved', 'steinbergs', 'conjecture', 'in', 'particular', 'each', 'such', 'graph', 'with', 'n', 'vertices', 'has', 'an', 'independent', 'set', 'of', 'size', 'at', 'least', '3n11']] | [-0.20335318245703266, 0.1610374113822925, -0.013708898361535772, -0.05144794877352459, -0.0836968764455782, -0.1646249040754305, 0.04741403626071082, 0.41703908228211933, -0.26130194398796275, -0.30949295716478475, 0.05682385737808155, -0.37019923536313903, -0.1029320934432603, 0.07131289242811147, -0.09233876196519723, -0.04452957838241543, 0.14107759460984243, 0.15034444849672063, 0.050985864267521906, -0.3049965476767818, 0.3020978086103227, -0.10492308077121539, 0.14434813745578545, 0.08006937019083471, 0.1189130467495748, 0.06660315429880506, 0.042563794823806914, 0.13048471330058953, -0.1448596900207497, 0.021103351421299436, 0.24443570373668558, 0.202486347448564, 0.2985116416026676, -0.3933388081149176, -0.15115145854430184, 0.26896889892125886, 0.10983184873614282, 0.01572217135911896, 0.02839646747867976, -0.15181999025674212, 0.20558390552030195, -0.08647208291268538, -0.10463946818241052, 0.07229094646338906, 0.20820563487590305, -0.032335514720115394, -0.2957004517730739, -0.060240379741622344, 0.08595623877195138, 0.081702771604002, 0.08928325863200284, -0.18000447489912547, -0.08826222763367234, 0.12107439615970685, -0.040072043211982836, 0.1301389229409988, 0.003900447194205804, -0.06217784085680568, -0.20140775683380308, 0.35608352895175654, -0.004796485756597821, -0.13717443991955075, 0.17826351304612462, -0.13874022557149782, -0.2189930185217351, 0.13345281546196294, 0.05481016386063799, 0.09964480769214412, -0.08685112901268498, 0.12632057808398728, -0.17413252852265798, 0.17769062188675716, 0.18981647620805436, 0.00034119783150446083, 0.15202048283425115, 0.15999789783243268, 0.165245292087396, 0.14968900349996392, 0.017636415186441608, 0.11649878184118914, -0.34066383138535516, -0.07245352286623702, -0.26984666001110796, 0.10073672558757521, -0.19435477821481606, -0.2128817398278486, 0.3494449860549399, 0.06569140871971964, 0.2335069330911788, 0.04628144591928474, 0.18254848941236676, 0.06859158882561753, 0.08490204729790253, 0.20430454364903863, 0.1004474526123395, 0.13763473009402377, -0.14601238027569793, -0.12518031164146368, 0.03626620120901082, 0.1383716988983372] |
1,802.0418 | Modelling Quasi-Periodic Pulsations in Solar and Stellar Flares | Solar flare emission is detected in all EM bands and variations in flux
density of solar energetic particles. Often the EM radiation generated in solar
and stellar flares shows a pronounced oscillatory pattern, with characteristic
periods ranging from a fraction of a second to several minutes. These
oscillations are referred to as quasi-periodic pulsations (QPPs), to emphasise
that they often contain apparent amplitude and period modulation. We review the
current understanding of quasi-periodic pulsations in solar and stellar flares.
In particular, we focus on the possible physical mechanisms, with an emphasis
on the underlying physics that generates the resultant range of periodicities.
These physical mechanisms include MHD oscillations, self-oscillatory
mechanisms, oscillatory reconnection/reconnection reversal, wave-driven
reconnection, two loop coalescence, MHD flow over-stability, the equivalent
LCR-contour mechanism, and thermal-dynamical cycles. We also provide a
histogram of all QPP events published in the literature at this time. The
occurrence of QPPs puts additional constraints on the interpretation and
understanding of the fundamental processes operating in flares, e.g. magnetic
energy liberation and particle acceleration. Therefore, a full understanding of
QPPs is essential in order to work towards an integrated model of solar and
stellar flares.
| astro-ph.SR | solar flare emission is detected in all em bands and variations in flux density of solar energetic particles often the em radiation generated in solar and stellar flares shows a pronounced oscillatory pattern with characteristic periods ranging from a fraction of a second to several minutes these oscillations are referred to as quasiperiodic pulsations qpps to emphasise that they often contain apparent amplitude and period modulation we review the current understanding of quasiperiodic pulsations in solar and stellar flares in particular we focus on the possible physical mechanisms with an emphasis on the underlying physics that generates the resultant range of periodicities these physical mechanisms include mhd oscillations selfoscillatory mechanisms oscillatory reconnectionreconnection reversal wavedriven reconnection two loop coalescence mhd flow overstability the equivalent lcrcontour mechanism and thermaldynamical cycles we also provide a histogram of all qpp events published in the literature at this time the occurrence of qpps puts additional constraints on the interpretation and understanding of the fundamental processes operating in flares eg magnetic energy liberation and particle acceleration therefore a full understanding of qpps is essential in order to work towards an integrated model of solar and stellar flares | [['solar', 'flare', 'emission', 'is', 'detected', 'in', 'all', 'em', 'bands', 'and', 'variations', 'in', 'flux', 'density', 'of', 'solar', 'energetic', 'particles', 'often', 'the', 'em', 'radiation', 'generated', 'in', 'solar', 'and', 'stellar', 'flares', 'shows', 'a', 'pronounced', 'oscillatory', 'pattern', 'with', 'characteristic', 'periods', 'ranging', 'from', 'a', 'fraction', 'of', 'a', 'second', 'to', 'several', 'minutes', 'these', 'oscillations', 'are', 'referred', 'to', 'as', 'quasiperiodic', 'pulsations', 'qpps', 'to', 'emphasise', 'that', 'they', 'often', 'contain', 'apparent', 'amplitude', 'and', 'period', 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1,802.04181 | State Representation Learning for Control: An Overview | Representation learning algorithms are designed to learn abstract features
that characterize data. State representation learning (SRL) focuses on a
particular kind of representation learning where learned features are in low
dimension, evolve through time, and are influenced by actions of an agent. The
representation is learned to capture the variation in the environment generated
by the agent's actions; this kind of representation is particularly suitable
for robotics and control scenarios. In particular, the low dimension
characteristic of the representation helps to overcome the curse of
dimensionality, provides easier interpretation and utilization by humans and
can help improve performance and speed in policy learning algorithms such as
reinforcement learning.
This survey aims at covering the state-of-the-art on state representation
learning in the most recent years. It reviews different SRL methods that
involve interaction with the environment, their implementations and their
applications in robotics control tasks (simulated or real). In particular, it
highlights how generic learning objectives are differently exploited in the
reviewed algorithms. Finally, it discusses evaluation methods to assess the
representation learned and summarizes current and future lines of research.
| cs.AI cs.LG stat.ML | representation learning algorithms are designed to learn abstract features that characterize data state representation learning srl focuses on a particular kind of representation learning where learned features are in low dimension evolve through time and are influenced by actions of an agent the representation is learned to capture the variation in the environment generated by the agents actions this kind of representation is particularly suitable for robotics and control scenarios in particular the low dimension characteristic of the representation helps to overcome the curse of dimensionality provides easier interpretation and utilization by humans and can help improve performance and speed in policy learning algorithms such as reinforcement learning this survey aims at covering the stateoftheart on state representation learning in the most recent years it reviews different srl methods that involve interaction with the environment their implementations and their applications in robotics control tasks simulated or real in particular it highlights how generic learning objectives are differently exploited in the reviewed algorithms finally it discusses evaluation methods to assess the representation learned and summarizes current and future lines of research | [['representation', 'learning', 'algorithms', 'are', 'designed', 'to', 'learn', 'abstract', 'features', 'that', 'characterize', 'data', 'state', 'representation', 'learning', 'srl', 'focuses', 'on', 'a', 'particular', 'kind', 'of', 'representation', 'learning', 'where', 'learned', 'features', 'are', 'in', 'low', 'dimension', 'evolve', 'through', 'time', 'and', 'are', 'influenced', 'by', 'actions', 'of', 'an', 'agent', 'the', 'representation', 'is', 'learned', 'to', 'capture', 'the', 'variation', 'in', 'the', 'environment', 'generated', 'by', 'the', 'agents', 'actions', 'this', 'kind', 'of', 'representation', 'is', 'particularly', 'suitable', 'for', 'robotics', 'and', 'control', 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1,802.04182 | Frequency adaptive metadynamics for the calculation of rare-event
kinetics | The ability to predict accurate thermodynamic and kinetic properties in
biomolecular systems is of both scientific and practical utility. While both
remain very difficult, predictions of kinetics are particularly difficult
because rates, in contrast to free energies, depend on the route taken and are
thus not amenable to all enhanced sampling methods. It has recently been
demonstrated that it is possible to recover kinetics through so called
`infrequent metadynamics' simulations, where the simulations are biased in a
way that minimally corrupts the dynamics of moving between metastable states.
This method, however, requires the bias to be added slowly, thus hampering
applications to processes with only modest separations of timescales. Here we
present a frequency-adaptive strategy which bridges normal and infrequent
metadynamics. We show that this strategy can improve the precision and accuracy
of rate calculations at fixed computational cost, and should be able to extend
rate calculations for much slower kinetic processes.
| physics.chem-ph physics.bio-ph | the ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility while both remain very difficult predictions of kinetics are particularly difficult because rates in contrast to free energies depend on the route taken and are thus not amenable to all enhanced sampling methods it has recently been demonstrated that it is possible to recover kinetics through so called infrequent metadynamics simulations where the simulations are biased in a way that minimally corrupts the dynamics of moving between metastable states this method however requires the bias to be added slowly thus hampering applications to processes with only modest separations of timescales here we present a frequencyadaptive strategy which bridges normal and infrequent metadynamics we show that this strategy can improve the precision and accuracy of rate calculations at fixed computational cost and should be able to extend rate calculations for much slower kinetic processes | [['the', 'ability', 'to', 'predict', 'accurate', 'thermodynamic', 'and', 'kinetic', 'properties', 'in', 'biomolecular', 'systems', 'is', 'of', 'both', 'scientific', 'and', 'practical', 'utility', 'while', 'both', 'remain', 'very', 'difficult', 'predictions', 'of', 'kinetics', 'are', 'particularly', 'difficult', 'because', 'rates', 'in', 'contrast', 'to', 'free', 'energies', 'depend', 'on', 'the', 'route', 'taken', 'and', 'are', 'thus', 'not', 'amenable', 'to', 'all', 'enhanced', 'sampling', 'methods', 'it', 'has', 'recently', 'been', 'demonstrated', 'that', 'it', 'is', 'possible', 'to', 'recover', 'kinetics', 'through', 'so', 'called', 'infrequent', 'metadynamics', 'simulations', 'where', 'the', 'simulations', 'are', 'biased', 'in', 'a', 'way', 'that', 'minimally', 'corrupts', 'the', 'dynamics', 'of', 'moving', 'between', 'metastable', 'states', 'this', 'method', 'however', 'requires', 'the', 'bias', 'to', 'be', 'added', 'slowly', 'thus', 'hampering', 'applications', 'to', 'processes', 'with', 'only', 'modest', 'separations', 'of', 'timescales', 'here', 'we', 'present', 'a', 'frequencyadaptive', 'strategy', 'which', 'bridges', 'normal', 'and', 'infrequent', 'metadynamics', 'we', 'show', 'that', 'this', 'strategy', 'can', 'improve', 'the', 'precision', 'and', 'accuracy', 'of', 'rate', 'calculations', 'at', 'fixed', 'computational', 'cost', 'and', 'should', 'be', 'able', 'to', 'extend', 'rate', 'calculations', 'for', 'much', 'slower', 'kinetic', 'processes']] | [-0.04895207993316137, 0.14668105862763348, -0.08811492102825089, 0.08585709382761393, -0.07473354439547174, -0.16153162812185012, 0.10021663742314944, 0.43924830382726837, -0.27558249760949555, -0.3217507376403406, 0.08263170685764057, -0.23441828161690828, -0.13559411479228034, 0.22575913592463742, -0.05856220434968736, 0.06169766919156968, 0.10277190794690284, 0.0007905883233476159, -0.033419067926692546, -0.2552370690179384, 0.223193277399031, 0.12548611222902029, 0.26805260172730544, 0.0659378676471726, 0.08111920669468256, -0.055277699035515666, -0.009863111505050533, 0.040885025598355475, -0.12724520578676493, 0.08335139091544483, 0.26148303768085623, 0.09015481234589802, 0.2982359132205216, -0.4657830112175831, -0.23280558200701085, 0.11514437722739153, 0.1577739996576546, 0.1538857981348287, -0.05537288043021983, -0.21262932051935338, 0.1029490558708099, -0.1463272894566126, -0.09786200007140045, -0.16085715275658727, 0.01896950074267999, 0.033004261249913805, -0.2644953442743628, 0.1082501818105233, 0.008204809516060802, -0.009309725852205962, -0.01143064751946645, -0.09440190977931935, -0.037842830152725736, 0.13855700143797953, 0.059425177419595174, 0.016652744960360573, 0.150626855697876, -0.1362744499667122, -0.08177869021275777, 0.41090552791928414, -0.028394141965329845, -0.20526909142337887, 0.2862663453904332, -0.13359482571272957, -0.1299915130416684, 0.19474626707209164, 0.15279873336945962, 0.152870957949353, -0.16959345880171148, 0.045028279008905076, 0.07910292916345281, 0.18149506734431234, 0.021379237664579755, 0.04851936759575214, 0.1814694907701272, 0.18722208223262468, 0.05218900347341296, 0.07804898120037324, -0.07353337798791858, -0.1397639717139606, -0.20868246171265742, -0.1378200830457484, -0.17329513571542743, 0.03382072904594752, -0.020392712744743878, -0.1224695289513676, 0.3229830812212598, 0.22680983027838023, 0.18617553125746203, 0.08261182546208533, 0.30704421422055717, 0.08583515762838702, 0.06582252655351004, 0.05568976428310406, 0.2456887292225432, 0.10090930631927011, 0.07894719011668387, -0.2172279760213754, 0.10916633191302616, -0.020315920739798553] |
1,802.04183 | On Index Codes for Interlinked Cycle Structured Side-Information Graphs | In connection with the index code construction and the decoding algorithm for
interlinked cycle (IC) structures proposed by Thapa, Ong and Johnson in
\cite{TOJ} ("Interlinked Cycles for Index Coding: Generalizing Cycles and
Cliques", IEEE Trans. Inf. Theory, vol. 63, no. 6, Jun. 2017), it is shown in
\cite{VaR} ("Optimal Index Codes For A New Class of Interlinked Cycle
Structure", in \textit{IEEE Communication Letters,} available as early access
article in \textit{IEEE Xplore}: DOI-10.1109/LCOMM.2018.2799202) that the
decoding algorithm does not work for all IC structures. In this work, a set of
necessary and sufficient conditions on the IC structures is presented for the
decoding algorithm to work for the code construction given in \cite{TOJ}. These
conditions are shown to be satisfied for the IC structures without any cycles
consisting of only non-inner vertices.
| cs.IT math.IT | in connection with the index code construction and the decoding algorithm for interlinked cycle ic structures proposed by thapa ong and johnson in citetoj interlinked cycles for index coding generalizing cycles and cliques ieee trans inf theory vol 63 no 6 jun 2017 it is shown in citevar optimal index codes for a new class of interlinked cycle structure in textitieee communication letters available as early access article in textitieee xplore doi101109lcomm20182799202 that the decoding algorithm does not work for all ic structures in this work a set of necessary and sufficient conditions on the ic structures is presented for the decoding algorithm to work for the code construction given in citetoj these conditions are shown to be satisfied for the ic structures without any cycles consisting of only noninner vertices | [['in', 'connection', 'with', 'the', 'index', 'code', 'construction', 'and', 'the', 'decoding', 'algorithm', 'for', 'interlinked', 'cycle', 'ic', 'structures', 'proposed', 'by', 'thapa', 'ong', 'and', 'johnson', 'in', 'citetoj', 'interlinked', 'cycles', 'for', 'index', 'coding', 'generalizing', 'cycles', 'and', 'cliques', 'ieee', 'trans', 'inf', 'theory', 'vol', '63', 'no', '6', 'jun', '2017', 'it', 'is', 'shown', 'in', 'citevar', 'optimal', 'index', 'codes', 'for', 'a', 'new', 'class', 'of', 'interlinked', 'cycle', 'structure', 'in', 'textitieee', 'communication', 'letters', 'available', 'as', 'early', 'access', 'article', 'in', 'textitieee', 'xplore', 'doi101109lcomm20182799202', 'that', 'the', 'decoding', 'algorithm', 'does', 'not', 'work', 'for', 'all', 'ic', 'structures', 'in', 'this', 'work', 'a', 'set', 'of', 'necessary', 'and', 'sufficient', 'conditions', 'on', 'the', 'ic', 'structures', 'is', 'presented', 'for', 'the', 'decoding', 'algorithm', 'to', 'work', 'for', 'the', 'code', 'construction', 'given', 'in', 'citetoj', 'these', 'conditions', 'are', 'shown', 'to', 'be', 'satisfied', 'for', 'the', 'ic', 'structures', 'without', 'any', 'cycles', 'consisting', 'of', 'only', 'noninner', 'vertices']] | [-0.18312311197601727, 0.047626120309660756, -0.02380085152969879, 0.03612387072987942, -0.0298973061456015, -0.19152724280894742, 0.08268022443090867, 0.3782792212001569, -0.22309198043140488, -0.3303083736948141, 0.11950747532253043, -0.1927839961071594, -0.23319369048525498, 0.20700577473429244, -0.1397583005568526, 0.02014240516188342, 0.08340193135214706, 0.02148751825768882, 0.005657508050817556, -0.3108353619133746, 0.2413172241168346, 0.13949842966806994, 0.26112239895476486, 0.008645192771328716, 0.04324077619157189, 0.018214460618163304, -0.0714124245880773, -0.022394375978257712, -0.16310661983352903, 0.09215581435416861, 0.285005131655732, 0.18112719604217514, 0.17491809843753384, -0.38544344563975813, -0.2331351435603024, 0.09331365810399216, 0.10374861660846106, 0.0737833801700961, 0.008701075685181194, -0.19783289546484317, 0.1677774889394641, -0.16734131730682267, -0.03747524908472469, 0.038744910238824024, 0.10001532902105117, -0.003009904598116904, -0.29040412237642216, 0.006297955931142325, 0.10707977447864109, 0.10828930246607056, -0.04035792079952171, -0.13410708603016505, 0.00408375619426663, 0.0886290081333017, -0.08820132521443128, 0.035416348158990536, 0.016038159385147528, -0.0680264548543386, -0.1897079045260985, 0.34018692997555566, 0.018490452568714073, -0.1082928550510308, 0.1632637705536574, -0.04352261993564724, -0.20192992156664805, 0.14972260454302933, 0.1506127649551536, 0.08023845148456143, -0.14192322540458102, 0.11708079896478613, -0.04079015134269093, 0.15707217865645534, 0.1678558402166768, 0.029564508043071914, 0.08824105224916785, 0.08934194610388142, 0.06804166049659839, 0.10775643556954442, -0.015502211221633113, -0.06852332275639486, -0.30225527704524713, -0.15068108434871383, -0.16273692766970801, 0.04084363095217117, -0.058575991012695006, -0.15578121139152767, 0.3853612444986861, 0.08740846746725829, 0.09901399251557594, 0.05339793663647935, 0.2179610892822306, 0.00958520873584033, 0.06783856491294257, 0.23558164753320474, 0.18016021709896507, 0.1900514170149796, 0.0807609873838488, -0.13788622155360233, 0.045413844729223704, 0.131375655436551] |
1,802.04184 | Energy Measurements by Means of Transition Radiation in novel Linacs | Advanced linear accelerator design may use Optical Transition Radiation (OTR)
screens to measure beam spot size; for instance, such screens are foreseen in
plasma based accelerators (EuPRAXIA@SPARC_LAB) or Compton machines (Gamma Beam
Source@ELI-NP). Optical Transition Radiation angular distribution strongly
depends on beam energy. Since OTR screens are typically placed in several
positions along the Linac to monitor the beam envelope, one may perform a
distributed energy measurement along the machine. Furthermore, a single shot
energy measurement can be useful in plasma accelerators to measure shot to shot
energy variations after the plasma interaction. Preliminary measurements of OTR
angular distribution of about 100 MeV electrons have been performed at the
SPARC_LAB facility. In this paper, we discuss the sensitivity of this
measurement to beam divergence and others parameters, as well as the resolution
required and the needed upgrades of conventional OTR diagnostics, using as an
example the data collected at SPARC_LAB.
| physics.acc-ph | advanced linear accelerator design may use optical transition radiation otr screens to measure beam spot size for instance such screens are foreseen in plasma based accelerators eupraxiasparc_lab or compton machines gamma beam sourceelinp optical transition radiation angular distribution strongly depends on beam energy since otr screens are typically placed in several positions along the linac to monitor the beam envelope one may perform a distributed energy measurement along the machine furthermore a single shot energy measurement can be useful in plasma accelerators to measure shot to shot energy variations after the plasma interaction preliminary measurements of otr angular distribution of about 100 mev electrons have been performed at the sparc_lab facility in this paper we discuss the sensitivity of this measurement to beam divergence and others parameters as well as the resolution required and the needed upgrades of conventional otr diagnostics using as an example the data collected at sparc_lab | [['advanced', 'linear', 'accelerator', 'design', 'may', 'use', 'optical', 'transition', 'radiation', 'otr', 'screens', 'to', 'measure', 'beam', 'spot', 'size', 'for', 'instance', 'such', 'screens', 'are', 'foreseen', 'in', 'plasma', 'based', 'accelerators', 'eupraxiasparc_lab', 'or', 'compton', 'machines', 'gamma', 'beam', 'sourceelinp', 'optical', 'transition', 'radiation', 'angular', 'distribution', 'strongly', 'depends', 'on', 'beam', 'energy', 'since', 'otr', 'screens', 'are', 'typically', 'placed', 'in', 'several', 'positions', 'along', 'the', 'linac', 'to', 'monitor', 'the', 'beam', 'envelope', 'one', 'may', 'perform', 'a', 'distributed', 'energy', 'measurement', 'along', 'the', 'machine', 'furthermore', 'a', 'single', 'shot', 'energy', 'measurement', 'can', 'be', 'useful', 'in', 'plasma', 'accelerators', 'to', 'measure', 'shot', 'to', 'shot', 'energy', 'variations', 'after', 'the', 'plasma', 'interaction', 'preliminary', 'measurements', 'of', 'otr', 'angular', 'distribution', 'of', 'about', '100', 'mev', 'electrons', 'have', 'been', 'performed', 'at', 'the', 'sparc_lab', 'facility', 'in', 'this', 'paper', 'we', 'discuss', 'the', 'sensitivity', 'of', 'this', 'measurement', 'to', 'beam', 'divergence', 'and', 'others', 'parameters', 'as', 'well', 'as', 'the', 'resolution', 'required', 'and', 'the', 'needed', 'upgrades', 'of', 'conventional', 'otr', 'diagnostics', 'using', 'as', 'an', 'example', 'the', 'data', 'collected', 'at', 'sparc_lab']] | [-0.07135583059674741, 0.19096927515525236, -0.07825573102489813, 0.06661902008353164, -0.05619506322526398, -0.16166163695313587, 0.004808688299549156, 0.4579744554256033, -0.24629826228690627, -0.3528325281562221, 0.08428273812770819, -0.3166093359351308, 0.06255526758649155, 0.2466750603916136, -0.012846726117868152, 0.10738668199503582, 0.05663564727147854, -0.006929534268659233, -0.032790442752095576, -0.1291121380097364, 0.27533050873801235, 0.2123120647148798, 0.3264106257112334, 0.08018461402330622, 0.11877709019838538, 0.030254344000002906, -0.009673988068438817, -0.036903547373094016, -0.0814030358761013, 0.027857111645049896, 0.2592762731278984, 0.10279799825781424, 0.22614318619938506, -0.4483472940655763, -0.21579083560922202, 0.08889888853284737, 0.1293098633208831, 0.054002503001899925, -0.06859625551627711, -0.22526879568784278, -0.018294833411443855, -0.14743809376361985, -0.16079215593354765, -0.010196700373401977, -0.04294230334223217, 0.0880417458575544, -0.26083110233584433, 0.002744580147125377, -0.032673374558689586, 0.048218858981467536, -0.0183689074447041, -0.11472025918680549, 0.05233177536279713, 0.040619237106230936, -0.0016693071580973248, 0.0821468121881578, 0.25298113700302455, -0.12407184457531412, -0.09352323483994493, 0.35582643103529543, -0.03507926594465971, -0.11285370037009652, 0.14136312256454672, -0.20622467275883927, -0.0705755805618586, 0.16674462864612974, 0.23303667616549154, 0.07837512599766855, -0.1700182949956944, -0.024987566562200702, 0.05872295594980453, 0.19714799490851043, 0.14263670087241936, 0.06860900156187431, 0.23910912524927533, 0.20036777634261138, 0.03846270940891598, 0.13179914396953138, -0.2155034984008803, 0.00960138209489168, -0.30584931093769696, -0.10082928158949135, -0.17276400503946232, 0.04522887206077341, 0.006723874809740786, -0.08960979200326119, 0.37514296805348574, 0.1571433790756277, 0.14828425849750387, -0.07093850117303344, 0.3847259298723266, 0.09008942773540649, 0.07939171320102459, 0.03566246813760083, 0.27607387378061776, 0.10394978285110837, 0.1758365666512525, -0.21631523209542736, 0.015479554053420988, -0.04965843230598425] |
1,802.04185 | Determination of non-compactly supported electromagnetic potentials in
unbounded closed waveguide | We study the inverse problem of determining a magnetic Schr\"odinger operator
in an unbounded closed waveguide from boundary measurements. We consider this
problem with a general closed waveguide in the sense that we only require our
unbounded domain to be contained into an infinite cylinder. In this context we
prove the unique recovery of the magnetic field and the electric potential
associated with general bounded and non-compactly supported electromagnetic
potentials. By assuming that the electromagnetic potentials are known on the
neighborhood of the boundary outside a compact set, we even prove the unique
determination of the magnetic field and the electric potential from
measurements restricted to a bounded subset of the infinite boundary. Finally,
in the case of a waveguide taking the form of an infinite cylindrical domain,
we prove the recovery of the magnetic field and the electric potential from
partial data corresponding to restriction of Neumann boundary measurements to
slightly more than half of the boundary. We establish all these results by mean
of suitable complex geometric optics solutions and Carleman estimates suitably
designed for our problem stated in an unbounded domain and with bounded
electromagnetic potentials.
| math.AP | we study the inverse problem of determining a magnetic schrodinger operator in an unbounded closed waveguide from boundary measurements we consider this problem with a general closed waveguide in the sense that we only require our unbounded domain to be contained into an infinite cylinder in this context we prove the unique recovery of the magnetic field and the electric potential associated with general bounded and noncompactly supported electromagnetic potentials by assuming that the electromagnetic potentials are known on the neighborhood of the boundary outside a compact set we even prove the unique determination of the magnetic field and the electric potential from measurements restricted to a bounded subset of the infinite boundary finally in the case of a waveguide taking the form of an infinite cylindrical domain we prove the recovery of the magnetic field and the electric potential from partial data corresponding to restriction of neumann boundary measurements to slightly more than half of the boundary we establish all these results by mean of suitable complex geometric optics solutions and carleman estimates suitably designed for our problem stated in an unbounded domain and with bounded electromagnetic potentials | [['we', 'study', 'the', 'inverse', 'problem', 'of', 'determining', 'a', 'magnetic', 'schrodinger', 'operator', 'in', 'an', 'unbounded', 'closed', 'waveguide', 'from', 'boundary', 'measurements', 'we', 'consider', 'this', 'problem', 'with', 'a', 'general', 'closed', 'waveguide', 'in', 'the', 'sense', 'that', 'we', 'only', 'require', 'our', 'unbounded', 'domain', 'to', 'be', 'contained', 'into', 'an', 'infinite', 'cylinder', 'in', 'this', 'context', 'we', 'prove', 'the', 'unique', 'recovery', 'of', 'the', 'magnetic', 'field', 'and', 'the', 'electric', 'potential', 'associated', 'with', 'general', 'bounded', 'and', 'noncompactly', 'supported', 'electromagnetic', 'potentials', 'by', 'assuming', 'that', 'the', 'electromagnetic', 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1,802.04186 | Network community detection via iterative edge removal in a
flocking-like system | We present a network community-detection technique based on properties that
emerge from a nature-inspired system of aligning particles. Initially, each
vertex is assigned a random-direction unit vector. A nonlinear dynamic law is
established so that neighboring vertices try to become aligned with each other.
After some time, the system stops and edges that connect the least-aligned
pairs of vertices are removed. Then the evolution starts over without the
removed edges, and after enough number of removal rounds, each community
becomes a connected component. The proposed approach is evaluated using
widely-accepted benchmarks and real-world networks. Experimental results reveal
that the method is robust and excels on a wide variety of networks. Moreover,
for large sparse networks, the edge-removal process runs in quasilinear time,
which enables application in large-scale networks.
| cs.SI physics.soc-ph | we present a network communitydetection technique based on properties that emerge from a natureinspired system of aligning particles initially each vertex is assigned a randomdirection unit vector a nonlinear dynamic law is established so that neighboring vertices try to become aligned with each other after some time the system stops and edges that connect the leastaligned pairs of vertices are removed then the evolution starts over without the removed edges and after enough number of removal rounds each community becomes a connected component the proposed approach is evaluated using widelyaccepted benchmarks and realworld networks experimental results reveal that the method is robust and excels on a wide variety of networks moreover for large sparse networks the edgeremoval process runs in quasilinear time which enables application in largescale networks | [['we', 'present', 'a', 'network', 'communitydetection', 'technique', 'based', 'on', 'properties', 'that', 'emerge', 'from', 'a', 'natureinspired', 'system', 'of', 'aligning', 'particles', 'initially', 'each', 'vertex', 'is', 'assigned', 'a', 'randomdirection', 'unit', 'vector', 'a', 'nonlinear', 'dynamic', 'law', 'is', 'established', 'so', 'that', 'neighboring', 'vertices', 'try', 'to', 'become', 'aligned', 'with', 'each', 'other', 'after', 'some', 'time', 'the', 'system', 'stops', 'and', 'edges', 'that', 'connect', 'the', 'leastaligned', 'pairs', 'of', 'vertices', 'are', 'removed', 'then', 'the', 'evolution', 'starts', 'over', 'without', 'the', 'removed', 'edges', 'and', 'after', 'enough', 'number', 'of', 'removal', 'rounds', 'each', 'community', 'becomes', 'a', 'connected', 'component', 'the', 'proposed', 'approach', 'is', 'evaluated', 'using', 'widelyaccepted', 'benchmarks', 'and', 'realworld', 'networks', 'experimental', 'results', 'reveal', 'that', 'the', 'method', 'is', 'robust', 'and', 'excels', 'on', 'a', 'wide', 'variety', 'of', 'networks', 'moreover', 'for', 'large', 'sparse', 'networks', 'the', 'edgeremoval', 'process', 'runs', 'in', 'quasilinear', 'time', 'which', 'enables', 'application', 'in', 'largescale', 'networks']] | [-0.14275243180605957, 0.08720669690996233, -0.06260935956333566, 0.007054331122628183, -0.08260946976035599, -0.17858044545745522, 0.04608217202581641, 0.40855867430333076, -0.2736713307301008, -0.2769890516395057, 0.08502612869240578, -0.29491251796680157, -0.18198261473797203, 0.1590030410168436, -0.023123705297649847, 0.04062537271547769, 0.15452235118086324, 0.05647062636933869, 0.009943217218772867, -0.2700643832971205, 0.3027572757995313, 0.01762407548967602, 0.2715322558555429, 0.028831792716670225, 0.12448109130147757, 0.02562147774000278, -0.017663682337967664, 0.0781586157427514, -0.047615017607399286, 0.08467313238074929, 0.2235561813994157, 0.15101218002840994, 0.3244534055629056, -0.46640390685693484, -0.2059733872045213, 0.11436110943937161, 0.1286237721668747, 0.10682454926244123, -0.04053700539488785, -0.2642956155784956, 0.13328293591781748, -0.13520405460589044, -0.08521819788610607, -0.04825729989688697, 0.026321266293819024, 0.020477353168035468, -0.27831830999696644, 0.009402512697370972, 0.036398700724436545, -0.0007092960134852589, -0.012910867593889161, -0.10222427655693407, -0.038968590084522026, 0.15646348225216813, -0.0056269955200300825, 0.03842209576774392, 0.13850291712414914, -0.12548121298831982, -0.14150822476491215, 0.359765777872659, -0.03952225359472057, -0.15281773283784314, 0.20062156278992027, -0.055080000361094, -0.15686688268571858, 0.13819006255893843, 0.19755274218353114, 0.147516975822177, -0.1452679407056861, 0.04974939855241618, -0.054006075693705066, 0.17414018945167148, 0.04106426751241088, -0.008690871600809646, 0.17863619948121331, 0.20239971686286604, 0.10326858848978684, 0.1423501909337388, -0.08635289697929865, -0.10249775692849881, -0.25371519969336276, -0.09412194484126145, -0.22551260669312373, -0.0043221679626135375, -0.10723923441475462, -0.14113478720422803, 0.4172740644137338, 0.15563090819880132, 0.26282230067968837, 0.09002688981493656, 0.3067039399899132, 0.0531752750270186, 0.11549385519346267, 0.11799842655185727, 0.1692270067033237, 0.08920010487277677, 0.10418259657050417, -0.1518520840157674, 0.09122137968817096, 0.0506816231242315] |
1,802.04187 | A Domain-Decomposition Model Reduction Method for Linear
Convection-Diffusion Equations with Random Coefficients | We develop a domain-decomposition model reduction method for linear
steady-state convection-diffusion equations with random coefficients. Of
particular interest to this effort are the diffusion equations with random
diffusivities, and the convection-dominated transport equations with random
velocities. We investigate the equations with two types of random fields, i.e.,
colored noises and discrete white noises, both of which can lead to
high-dimensional parametric dependence. The motivation is to use domain
decomposition to exploit low-dimensional structures of local problems in the
sub-domains, such that the total number of expensive PDE solves can be greatly
reduced. Our objective is to develop an efficient model reduction method to
simultaneously handle high-dimensionality and irregular behaviors of the
stochastic PDEs under consideration. The advantages of our method lie in three
aspects: (i) online-offline decomposition, i.e., the online cost is independent
of the size of the triangle mesh; (ii) operator approximation for handling
non-affine and high-dimensional random fields; (iii) effective strategy to
capture irregular behaviors, e.g., sharp transitions of the PDE solution. Two
numerical examples will be provided to demonstrate the advantageous performance
of our method.
| math.NA | we develop a domaindecomposition model reduction method for linear steadystate convectiondiffusion equations with random coefficients of particular interest to this effort are the diffusion equations with random diffusivities and the convectiondominated transport equations with random velocities we investigate the equations with two types of random fields ie colored noises and discrete white noises both of which can lead to highdimensional parametric dependence the motivation is to use domain decomposition to exploit lowdimensional structures of local problems in the subdomains such that the total number of expensive pde solves can be greatly reduced our objective is to develop an efficient model reduction method to simultaneously handle highdimensionality and irregular behaviors of the stochastic pdes under consideration the advantages of our method lie in three aspects i onlineoffline decomposition ie the online cost is independent of the size of the triangle mesh ii operator approximation for handling nonaffine and highdimensional random fields iii effective strategy to capture irregular behaviors eg sharp transitions of the pde solution two numerical examples will be provided to demonstrate the advantageous performance of our method | [['we', 'develop', 'a', 'domaindecomposition', 'model', 'reduction', 'method', 'for', 'linear', 'steadystate', 'convectiondiffusion', 'equations', 'with', 'random', 'coefficients', 'of', 'particular', 'interest', 'to', 'this', 'effort', 'are', 'the', 'diffusion', 'equations', 'with', 'random', 'diffusivities', 'and', 'the', 'convectiondominated', 'transport', 'equations', 'with', 'random', 'velocities', 'we', 'investigate', 'the', 'equations', 'with', 'two', 'types', 'of', 'random', 'fields', 'ie', 'colored', 'noises', 'and', 'discrete', 'white', 'noises', 'both', 'of', 'which', 'can', 'lead', 'to', 'highdimensional', 'parametric', 'dependence', 'the', 'motivation', 'is', 'to', 'use', 'domain', 'decomposition', 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1,802.04188 | On the approximation of the probability density function of the
randomized non-autonomous complete linear differential equation | In this paper we study the randomized non-autonomous complete linear
differential equation. The diffusion coefficient and the source term in the
differential equation are assumed to be stochastic processes and the initial
condition is treated as a random variable on an underlying complete probability
space. The solution to this random differential equation is a stochastic
process. Any stochastic process is determined by its finite-dimensional joint
distributions. In this paper, the main goal is to obtain the probability
density function of the solution process (the first finite-dimensional
distribution) under mild conditions. The solution process is expressed by means
of Lebesgue integrals of the data stochastic processes, which, in general,
cannot be computed in an exact manner, therefore approximations for its
probability density function are constructed. The key tools applied to
construct the approximations are the Random Variable Transformation technique
and Karhunen-Loeve expansions. Our results can be applied to a large variety of
examples. Finally, several numerical experiments illustrate the potentiality of
our findings.
| math.PR | in this paper we study the randomized nonautonomous complete linear differential equation the diffusion coefficient and the source term in the differential equation are assumed to be stochastic processes and the initial condition is treated as a random variable on an underlying complete probability space the solution to this random differential equation is a stochastic process any stochastic process is determined by its finitedimensional joint distributions in this paper the main goal is to obtain the probability density function of the solution process the first finitedimensional distribution under mild conditions the solution process is expressed by means of lebesgue integrals of the data stochastic processes which in general cannot be computed in an exact manner therefore approximations for its probability density function are constructed the key tools applied to construct the approximations are the random variable transformation technique and karhunenloeve expansions our results can be applied to a large variety of examples finally several numerical experiments illustrate the potentiality of our findings | [['in', 'this', 'paper', 'we', 'study', 'the', 'randomized', 'nonautonomous', 'complete', 'linear', 'differential', 'equation', 'the', 'diffusion', 'coefficient', 'and', 'the', 'source', 'term', 'in', 'the', 'differential', 'equation', 'are', 'assumed', 'to', 'be', 'stochastic', 'processes', 'and', 'the', 'initial', 'condition', 'is', 'treated', 'as', 'a', 'random', 'variable', 'on', 'an', 'underlying', 'complete', 'probability', 'space', 'the', 'solution', 'to', 'this', 'random', 'differential', 'equation', 'is', 'a', 'stochastic', 'process', 'any', 'stochastic', 'process', 'is', 'determined', 'by', 'its', 'finitedimensional', 'joint', 'distributions', 'in', 'this', 'paper', 'the', 'main', 'goal', 'is', 'to', 'obtain', 'the', 'probability', 'density', 'function', 'of', 'the', 'solution', 'process', 'the', 'first', 'finitedimensional', 'distribution', 'under', 'mild', 'conditions', 'the', 'solution', 'process', 'is', 'expressed', 'by', 'means', 'of', 'lebesgue', 'integrals', 'of', 'the', 'data', 'stochastic', 'processes', 'which', 'in', 'general', 'can', 'not', 'be', 'computed', 'in', 'an', 'exact', 'manner', 'therefore', 'approximations', 'for', 'its', 'probability', 'density', 'function', 'are', 'constructed', 'the', 'key', 'tools', 'applied', 'to', 'construct', 'the', 'approximations', 'are', 'the', 'random', 'variable', 'transformation', 'technique', 'and', 'karhunenloeve', 'expansions', 'our', 'results', 'can', 'be', 'applied', 'to', 'a', 'large', 'variety', 'of', 'examples', 'finally', 'several', 'numerical', 'experiments', 'illustrate', 'the', 'potentiality', 'of', 'our', 'findings']] | [-0.09227808410293949, 0.053961537805695854, -0.11699462291767444, 0.08256845185526916, -0.0728803724721874, -0.0717563266006007, 0.02142377013334879, 0.34775094262844214, -0.33991352720128976, -0.2299835630435428, 0.135937715042811, -0.24420298268572868, -0.1826347833316476, 0.19287723261131648, -0.08022155263175491, 0.11199499160962671, 0.0638327486584523, 0.02379061772482344, -0.051835126177824896, -0.26820140790788494, 0.34813947828223735, 0.044143084499505034, 0.255922633734606, -0.00393903445048212, 0.14037983082420552, -0.009187352940714433, -0.056704432227358825, -0.0022495282284324086, -0.14431209606832704, 0.06790230895729701, 0.25924772328120066, 0.13054936694872618, 0.29513704200543783, -0.4105692710184658, -0.20800828611466782, 0.11222874270137856, 0.12188909356082372, 0.11635653340854779, -0.03295242349671463, -0.28902655003443817, 0.07759387840865398, -0.1421571618883065, -0.17913636950307463, -0.10740972586844597, -0.01208473633449136, 0.07596300426260653, -0.3543566089192051, 0.07210533861134703, 0.06704682197730326, -0.007343627256769801, -0.07275513672138467, -0.08324776151420354, 0.005715544075573698, 0.09188388963372796, 0.026300557041283628, 0.034300166526466516, 0.1077409801501895, -0.08111704409013908, -0.11735088624163, 0.3429755250876198, -0.10259803723896699, -0.3079224615763127, 0.1389217100438642, -0.14386541640923067, -0.12834741770678365, 0.13969203788341464, 0.18238657959194088, 0.17757148224506183, -0.23553357705862427, 0.11112833772593127, -0.024213939695190523, 0.11810335279885177, 0.007098648304325397, -0.024661100707716807, 0.10509513576794988, 0.13388638672607442, 0.07907270460726659, 0.13154584080755047, -0.023114619632337265, -0.15152959894400342, -0.3427630508649934, -0.1509400074637318, -0.20458250086857405, 0.05841304228558602, -0.1331869895400178, -0.1709547614945853, 0.3610201762686341, 0.12452410028796027, 0.20471984845089033, 0.05946551358250136, 0.2726543231615854, 0.2601436454484216, -0.021779308512669765, 0.029196002546332183, 0.14452306657709593, 0.1782205497383203, 0.07923354933244045, -0.17701006473072067, 0.12621998504958362, 0.08494920983762005] |
1,802.04189 | Multi-Round Influence Maximization | In this paper, we study the Multi-Round Influence Maximization (MRIM)
problem, where influence propagates in multiple rounds independently from
possibly different seed sets, and the goal is to select seeds for each round to
maximize the expected number of nodes that are activated in at least one round.
MRIM problem models the viral marketing scenarios in which advertisers conduct
multiple rounds of viral marketing to promote one product. We consider two
different settings: 1) the non-adaptive MRIM, where the advertiser needs to
determine the seed sets for all rounds at the very beginning, and 2) the
adaptive MRIM, where the advertiser can select seed sets adaptively based on
the propagation results in the previous rounds. For the non-adaptive setting,
we design two algorithms that exhibit an interesting tradeoff between
efficiency and effectiveness: a cross-round greedy algorithm that selects seeds
at a global level and achieves $1/2 - \varepsilon$ approximation ratio, and a
within-round greedy algorithm that selects seeds round by round and achieves
$1-e^{-(1-1/e)}-\varepsilon \approx 0.46 - \varepsilon$ approximation ratio but
saves running time by a factor related to the number of rounds. For the
adaptive setting, we design an adaptive algorithm that guarantees
$1-e^{-(1-1/e)}-\varepsilon$ approximation to the adaptive optimal solution. In
all cases, we further design scalable algorithms based on the reverse influence
sampling approach and achieve near-linear running time. We conduct experiments
on several real-world networks and demonstrate that our algorithms are
effective for the MRIM task.
| cs.SI | in this paper we study the multiround influence maximization mrim problem where influence propagates in multiple rounds independently from possibly different seed sets and the goal is to select seeds for each round to maximize the expected number of nodes that are activated in at least one round mrim problem models the viral marketing scenarios in which advertisers conduct multiple rounds of viral marketing to promote one product we consider two different settings 1 the nonadaptive mrim where the advertiser needs to determine the seed sets for all rounds at the very beginning and 2 the adaptive mrim where the advertiser can select seed sets adaptively based on the propagation results in the previous rounds for the nonadaptive setting we design two algorithms that exhibit an interesting tradeoff between efficiency and effectiveness a crossround greedy algorithm that selects seeds at a global level and achieves 12 varepsilon approximation ratio and a withinround greedy algorithm that selects seeds round by round and achieves 1e11evarepsilon approx 046 varepsilon approximation ratio but saves running time by a factor related to the number of rounds for the adaptive setting we design an adaptive algorithm that guarantees 1e11evarepsilon approximation to the adaptive optimal solution in all cases we further design scalable algorithms based on the reverse influence sampling approach and achieve nearlinear running time we conduct experiments on several realworld networks and demonstrate that our algorithms are effective for the mrim task | [['in', 'this', 'paper', 'we', 'study', 'the', 'multiround', 'influence', 'maximization', 'mrim', 'problem', 'where', 'influence', 'propagates', 'in', 'multiple', 'rounds', 'independently', 'from', 'possibly', 'different', 'seed', 'sets', 'and', 'the', 'goal', 'is', 'to', 'select', 'seeds', 'for', 'each', 'round', 'to', 'maximize', 'the', 'expected', 'number', 'of', 'nodes', 'that', 'are', 'activated', 'in', 'at', 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'withinround', 'greedy', 'algorithm', 'that', 'selects', 'seeds', 'round', 'by', 'round', 'and', 'achieves', '1e11evarepsilon', 'approx', '046', 'varepsilon', 'approximation', 'ratio', 'but', 'saves', 'running', 'time', 'by', 'a', 'factor', 'related', 'to', 'the', 'number', 'of', 'rounds', 'for', 'the', 'adaptive', 'setting', 'we', 'design', 'an', 'adaptive', 'algorithm', 'that', 'guarantees', '1e11evarepsilon', 'approximation', 'to', 'the', 'adaptive', 'optimal', 'solution', 'in', 'all', 'cases', 'we', 'further', 'design', 'scalable', 'algorithms', 'based', 'on', 'the', 'reverse', 'influence', 'sampling', 'approach', 'and', 'achieve', 'nearlinear', 'running', 'time', 'we', 'conduct', 'experiments', 'on', 'several', 'realworld', 'networks', 'and', 'demonstrate', 'that', 'our', 'algorithms', 'are', 'effective', 'for', 'the', 'mrim', 'task']] | [-0.1270859092503962, 0.04607271960381391, -0.02781919322437267, 0.03626396558387405, -0.06727849985692698, -0.20520251759032163, 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0.07455622776743233] |
1,802.0419 | On the approximation of the probability density function of the
randomized heat equation | In this paper we study the randomized heat equation with homogeneous boundary
conditions. The diffusion coeffcient is assumed to be a random variable and the
initial condition is treated as a stochastic process. The solution of this
randomized partial differential equation problem is a stochastic process, which
is given by a random series obtained via the classical method of separation of
variables. Any stochastic process is determined by its finite-dimensional joint
distributions. In this paper, the goal is to obtain approximations to the
probability density function of the solution (the first finite-dimensional
distributions) under mild conditions. Since the solution is expressed as a
random series, we perform approximations of its probability density function.
We use two approaches: broadly speaking, first, dealing with the random Fourier
coefficients of the random series, and second, taking advantage of the
Karhunen-Loeve expansion of the initial condition stochastic process. Finally,
several numerical examples illustrating the potentiality of our findings with
regard to both approaches are presented.
| math.PR | in this paper we study the randomized heat equation with homogeneous boundary conditions the diffusion coeffcient is assumed to be a random variable and the initial condition is treated as a stochastic process the solution of this randomized partial differential equation problem is a stochastic process which is given by a random series obtained via the classical method of separation of variables any stochastic process is determined by its finitedimensional joint distributions in this paper the goal is to obtain approximations to the probability density function of the solution the first finitedimensional distributions under mild conditions since the solution is expressed as a random series we perform approximations of its probability density function we use two approaches broadly speaking first dealing with the random fourier coefficients of the random series and second taking advantage of the karhunenloeve expansion of the initial condition stochastic process finally several numerical examples illustrating the potentiality of our findings with regard to both approaches are presented | [['in', 'this', 'paper', 'we', 'study', 'the', 'randomized', 'heat', 'equation', 'with', 'homogeneous', 'boundary', 'conditions', 'the', 'diffusion', 'coeffcient', 'is', 'assumed', 'to', 'be', 'a', 'random', 'variable', 'and', 'the', 'initial', 'condition', 'is', 'treated', 'as', 'a', 'stochastic', 'process', 'the', 'solution', 'of', 'this', 'randomized', 'partial', 'differential', 'equation', 'problem', 'is', 'a', 'stochastic', 'process', 'which', 'is', 'given', 'by', 'a', 'random', 'series', 'obtained', 'via', 'the', 'classical', 'method', 'of', 'separation', 'of', 'variables', 'any', 'stochastic', 'process', 'is', 'determined', 'by', 'its', 'finitedimensional', 'joint', 'distributions', 'in', 'this', 'paper', 'the', 'goal', 'is', 'to', 'obtain', 'approximations', 'to', 'the', 'probability', 'density', 'function', 'of', 'the', 'solution', 'the', 'first', 'finitedimensional', 'distributions', 'under', 'mild', 'conditions', 'since', 'the', 'solution', 'is', 'expressed', 'as', 'a', 'random', 'series', 'we', 'perform', 'approximations', 'of', 'its', 'probability', 'density', 'function', 'we', 'use', 'two', 'approaches', 'broadly', 'speaking', 'first', 'dealing', 'with', 'the', 'random', 'fourier', 'coefficients', 'of', 'the', 'random', 'series', 'and', 'second', 'taking', 'advantage', 'of', 'the', 'karhunenloeve', 'expansion', 'of', 'the', 'initial', 'condition', 'stochastic', 'process', 'finally', 'several', 'numerical', 'examples', 'illustrating', 'the', 'potentiality', 'of', 'our', 'findings', 'with', 'regard', 'to', 'both', 'approaches', 'are', 'presented']] | [-0.11308640195635257, 0.062249235560111006, -0.12240159773030636, 0.041009265730117365, -0.06282336146119542, -0.08358864033426974, 0.0341728068902649, 0.35228799400932115, -0.31698500836464744, -0.22770647128453905, 0.1385663612073241, -0.23382393379481684, -0.17251054700232626, 0.1749545931700409, -0.060669694259265286, 0.11289877165813919, 0.07145621927212113, 0.03119736694678757, -0.07451676875815628, -0.2746381325392712, 0.3451465818082324, 0.03416763168617921, 0.2512969343448694, -0.021547760333220898, 0.14723854022019583, -0.0038746924584974413, -0.06299246840398781, 0.020818819346843483, -0.13234106638549786, 0.08279979630642403, 0.21670217211618556, 0.12387215761722338, 0.33702910052300056, -0.409328327700785, -0.20833661656549074, 0.09955429411941549, 0.10736871781608565, 0.1036082406301248, -0.01913024987215581, -0.26948154073277986, 0.08218278183445613, -0.143238900070258, -0.14693376924611212, -0.06650003010511213, -0.019906045128562436, 0.07674979111534017, -0.36406939352648504, 0.10279311656211473, 0.07467630741284778, -0.0023440975820217627, -0.07644682479530619, -0.1009545200460978, 0.034131022486893564, 0.0835519681138027, 0.05708918869220623, 0.013610525805827068, 0.09307843557217661, -0.09079432036721882, -0.10621127619853486, 0.35529149986546116, -0.08424787097415302, -0.2804213212143199, 0.152853854856691, -0.15254987834704034, -0.1298806862645314, 0.11945369602499172, 0.14744730031707828, 0.16655683096047053, -0.20004383107843976, 0.09221134227425762, -0.03284659495024786, 0.10450811984208383, 0.037420375420139255, -0.0263377156582956, 0.09801012257357007, 0.15358332377968367, 0.08136529816525716, 0.16327468992098124, -0.036607050326774304, -0.14256319388897615, -0.33929409261399546, -0.15328097746776914, -0.23026877656428618, 0.052474799493663245, -0.12758336090323694, -0.1966317645823641, 0.36987443680741955, 0.12769693273708213, 0.22416509604602128, 0.0807205867145199, 0.2938630672790665, 0.2355374133247616, -0.05295580379688036, 0.03533973767832847, 0.12604401983690927, 0.19274155285516, 0.10518842996300562, -0.1778663006129961, 0.11632344499808846, 0.0953759527287984] |
1,802.04191 | Massive Dirac fermions from holography | We provide a framework to compute the dynamics of massive Dirac fermions
using holography. To this end we consider two bulk Dirac fermions that are
coupled via a Yukawa interaction and propagate on a gravitational background in
which a mass deformation is introduced. Moreover, we discuss the incorporation
of this approach in semiholography. The resulting undoped fermionic spectral
functions indeed show that the Yukawa coupling induces a gap in the holographic
spectrum, whereas the semiholographic extension is in general gapped but
additionally contains a quantum critical point at which the effective fermion
mass vanishes and a topological phase transition occurs. Furthermore, when
introducing doping, the fermionic spectral functions show a quantum phase
transition between a gapped material and a Fermi liquid.
| hep-th cond-mat.str-el | we provide a framework to compute the dynamics of massive dirac fermions using holography to this end we consider two bulk dirac fermions that are coupled via a yukawa interaction and propagate on a gravitational background in which a mass deformation is introduced moreover we discuss the incorporation of this approach in semiholography the resulting undoped fermionic spectral functions indeed show that the yukawa coupling induces a gap in the holographic spectrum whereas the semiholographic extension is in general gapped but additionally contains a quantum critical point at which the effective fermion mass vanishes and a topological phase transition occurs furthermore when introducing doping the fermionic spectral functions show a quantum phase transition between a gapped material and a fermi liquid | [['we', 'provide', 'a', 'framework', 'to', 'compute', 'the', 'dynamics', 'of', 'massive', 'dirac', 'fermions', 'using', 'holography', 'to', 'this', 'end', 'we', 'consider', 'two', 'bulk', 'dirac', 'fermions', 'that', 'are', 'coupled', 'via', 'a', 'yukawa', 'interaction', 'and', 'propagate', 'on', 'a', 'gravitational', 'background', 'in', 'which', 'a', 'mass', 'deformation', 'is', 'introduced', 'moreover', 'we', 'discuss', 'the', 'incorporation', 'of', 'this', 'approach', 'in', 'semiholography', 'the', 'resulting', 'undoped', 'fermionic', 'spectral', 'functions', 'indeed', 'show', 'that', 'the', 'yukawa', 'coupling', 'induces', 'a', 'gap', 'in', 'the', 'holographic', 'spectrum', 'whereas', 'the', 'semiholographic', 'extension', 'is', 'in', 'general', 'gapped', 'but', 'additionally', 'contains', 'a', 'quantum', 'critical', 'point', 'at', 'which', 'the', 'effective', 'fermion', 'mass', 'vanishes', 'and', 'a', 'topological', 'phase', 'transition', 'occurs', 'furthermore', 'when', 'introducing', 'doping', 'the', 'fermionic', 'spectral', 'functions', 'show', 'a', 'quantum', 'phase', 'transition', 'between', 'a', 'gapped', 'material', 'and', 'a', 'fermi', 'liquid']] | [-0.1782798099404678, 0.24685055826654012, -0.10086684543562453, 0.0688993673048113, -0.043282973760939085, -0.16848143125491694, 0.06642929785923402, 0.32968157509049356, -0.20445549372614416, -0.24389151204377413, 0.002946610042963885, -0.30075898528684025, -0.19049596244831038, 0.09787201360714706, 0.0377076705629083, -0.006933144957581458, -0.003945170097391714, 0.0238795937291512, -0.18560910911861161, -0.1858262375539769, 0.35786215071220046, -0.02027332966893234, 0.2726225292017637, 0.10847944380284465, 0.06575690552376764, 0.0019210251894864168, 0.08081324923829722, 0.006046741096349048, -0.131204804202204, 0.06320519072834925, 0.22451655407030183, -0.041313372948784226, 0.1762105244373487, -0.36995604239434987, -0.24083519563048092, 0.05763162047051909, 0.14243655719155493, 0.14439654002959015, -0.11828500894186941, -0.28453935294850796, 0.0298587704723901, -0.1996418421757061, -0.13571553131226788, -0.06821806692472113, -0.0668617852401635, -0.10194328836812869, -0.27186215808230246, 0.09253567587156118, 0.03592259583086514, 0.0068835272378680755, -0.04428476408943688, -0.0363581276542992, -0.06239772881650604, 0.05063778148845708, 0.04530191335327777, 0.032180260584982155, 0.12645900302974522, -0.1528211127298457, -0.0701197781022792, 0.40659431468172014, -0.10667713314741234, -0.18781473484536834, 0.18861246175201965, -0.140660587582768, -0.11729842605654242, 0.12728914271362804, 0.12306150060901341, 0.09363264095207507, -0.13845336719568577, 0.1697640959235978, -0.025084220531034814, 0.15841283389171854, 0.03753717297838216, 0.06599537910333611, 0.29395598815061336, 0.16587290044754652, 0.0720173405937481, 0.1646047283949192, -0.083750101265282, -0.10994795875716185, -0.31422107107937336, -0.2065252756684526, -0.21785666673513485, 0.06836097931666377, -0.0709796429402243, -0.21161793135029594, 0.441534765218654, 0.15417521091154968, 0.2081900579269883, 0.017292678081007165, 0.2357015323532699, 0.1466028654581313, 0.06594071501080902, 0.06690191619929449, 0.2709543525726219, 0.12038454169615302, 0.08411399589097204, -0.25982839805227975, -0.08130909395327192, 0.0992159063173535] |
1,802.04192 | Generalized gap acceptance models for unsignalized intersections | This paper contributes to the modeling and analysis of unsignalized
intersections. In classical gap acceptance models vehicles on the minor road
accept any gap greater than the CRITICAL gap, and reject gaps below this
threshold, where the gap is the time between two subsequent vehicles on the
major road. The main contribution of this paper is to develop a series of
generalizations of existing models, thus increasing the model's practical
applicability significantly. First, we incorporate {driver impatience behavior}
while allowing for a realistic merging behavior; we do so by distinguishing
between the critical gap and the merging time, thus allowing MULTIPLE vehicles
to use a sufficiently large gap. Incorporating this feature is particularly
challenging in models with driver impatience. Secondly, we allow for multiple
classes of gap acceptance behavior, enabling us to distinguish between
different driver types and/or different vehicle types. Thirdly, we use the
novel M$^X$/SM2/1 queueing model, which has batch arrivals, dependent service
times, and a different service-time distribution for vehicles arriving in an
empty queue on the minor road (where `service time' refers to the time required
to find a sufficiently large gap). This setup facilitates the analysis of the
service-time distribution of an arbitrary vehicle on the minor road and of the
queue length on the minor road. In particular, we can compute the MEAN service
time, thus enabling the evaluation of the capacity for the minor road vehicles.
| math.PR | this paper contributes to the modeling and analysis of unsignalized intersections in classical gap acceptance models vehicles on the minor road accept any gap greater than the critical gap and reject gaps below this threshold where the gap is the time between two subsequent vehicles on the major road the main contribution of this paper is to develop a series of generalizations of existing models thus increasing the models practical applicability significantly first we incorporate driver impatience behavior while allowing for a realistic merging behavior we do so by distinguishing between the critical gap and the merging time thus allowing multiple vehicles to use a sufficiently large gap incorporating this feature is particularly challenging in models with driver impatience secondly we allow for multiple classes of gap acceptance behavior enabling us to distinguish between different driver types andor different vehicle types thirdly we use the novel mxsm21 queueing model which has batch arrivals dependent service times and a different servicetime distribution for vehicles arriving in an empty queue on the minor road where service time refers to the time required to find a sufficiently large gap this setup facilitates the analysis of the servicetime distribution of an arbitrary vehicle on the minor road and of the queue length on the minor road in particular we can compute the mean service time thus enabling the evaluation of the capacity for the minor road vehicles | [['this', 'paper', 'contributes', 'to', 'the', 'modeling', 'and', 'analysis', 'of', 'unsignalized', 'intersections', 'in', 'classical', 'gap', 'acceptance', 'models', 'vehicles', 'on', 'the', 'minor', 'road', 'accept', 'any', 'gap', 'greater', 'than', 'the', 'critical', 'gap', 'and', 'reject', 'gaps', 'below', 'this', 'threshold', 'where', 'the', 'gap', 'is', 'the', 'time', 'between', 'two', 'subsequent', 'vehicles', 'on', 'the', 'major', 'road', 'the', 'main', 'contribution', 'of', 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1,802.04193 | Electric Vehicle Driver Clustering using Statistical Model and Machine
Learning | Electric Vehicle (EV) is playing a significant role in the distribution
energy management systems since the power consumption level of the EVs is much
higher than the other regular home appliances. The randomness of the EV driver
behaviors make the optimal charging or discharging scheduling even more
difficult due to the uncertain charging session parameters. To minimize the
impact of behavioral uncertainties, it is critical to develop effective methods
to predict EV load for smart EV energy management. Using the EV smart charging
infrastructures on UCLA campus and city of Santa Monica as testbeds, we have
collected real-world datasets of EV charging behaviors, based on which we
proposed an EV user modeling technique which combines statistical analysis and
machine learning approaches. Specifically, unsupervised clustering algorithm,
and multilayer perceptron are applied to historical charging record to make the
day-ahead EV parking and load prediction. Experimental results with
cross-validation show that our model can achieve good performance for charging
control scheduling and online EV load forecasting.
| cs.LG | electric vehicle ev is playing a significant role in the distribution energy management systems since the power consumption level of the evs is much higher than the other regular home appliances the randomness of the ev driver behaviors make the optimal charging or discharging scheduling even more difficult due to the uncertain charging session parameters to minimize the impact of behavioral uncertainties it is critical to develop effective methods to predict ev load for smart ev energy management using the ev smart charging infrastructures on ucla campus and city of santa monica as testbeds we have collected realworld datasets of ev charging behaviors based on which we proposed an ev user modeling technique which combines statistical analysis and machine learning approaches specifically unsupervised clustering algorithm and multilayer perceptron are applied to historical charging record to make the dayahead ev parking and load prediction experimental results with crossvalidation show that our model can achieve good performance for charging control scheduling and online ev load forecasting | [['electric', 'vehicle', 'ev', 'is', 'playing', 'a', 'significant', 'role', 'in', 'the', 'distribution', 'energy', 'management', 'systems', 'since', 'the', 'power', 'consumption', 'level', 'of', 'the', 'evs', 'is', 'much', 'higher', 'than', 'the', 'other', 'regular', 'home', 'appliances', 'the', 'randomness', 'of', 'the', 'ev', 'driver', 'behaviors', 'make', 'the', 'optimal', 'charging', 'or', 'discharging', 'scheduling', 'even', 'more', 'difficult', 'due', 'to', 'the', 'uncertain', 'charging', 'session', 'parameters', 'to', 'minimize', 'the', 'impact', 'of', 'behavioral', 'uncertainties', 'it', 'is', 'critical', 'to', 'develop', 'effective', 'methods', 'to', 'predict', 'ev', 'load', 'for', 'smart', 'ev', 'energy', 'management', 'using', 'the', 'ev', 'smart', 'charging', 'infrastructures', 'on', 'ucla', 'campus', 'and', 'city', 'of', 'santa', 'monica', 'as', 'testbeds', 'we', 'have', 'collected', 'realworld', 'datasets', 'of', 'ev', 'charging', 'behaviors', 'based', 'on', 'which', 'we', 'proposed', 'an', 'ev', 'user', 'modeling', 'technique', 'which', 'combines', 'statistical', 'analysis', 'and', 'machine', 'learning', 'approaches', 'specifically', 'unsupervised', 'clustering', 'algorithm', 'and', 'multilayer', 'perceptron', 'are', 'applied', 'to', 'historical', 'charging', 'record', 'to', 'make', 'the', 'dayahead', 'ev', 'parking', 'and', 'load', 'prediction', 'experimental', 'results', 'with', 'crossvalidation', 'show', 'that', 'our', 'model', 'can', 'achieve', 'good', 'performance', 'for', 'charging', 'control', 'scheduling', 'and', 'online', 'ev', 'load', 'forecasting']] | [-0.10381464418463932, 0.05156916850780651, -0.048285900304241604, 0.08785819571121686, -0.08780459962819316, -0.22189605076763233, 0.13852551890673434, 0.4340237469480532, -0.2293780732178697, -0.42185942316427827, 0.05577117132474441, -0.32802142932295525, -0.0846288852370912, 0.20714237192850105, -0.13913418387812448, 0.05501172752914632, 0.08743673827067562, 0.0030456137823554256, 0.03796545747758412, -0.258157964861134, 0.20504725776117994, 0.15415183449215142, 0.431308747025025, 0.11112699989604241, 0.06348989691823811, -0.019711788366094413, 0.04002024445586225, -0.01949206969939263, -0.08087192273794755, 0.15149031698465257, 0.36266987129233824, 0.10455989254718055, 0.34551261692512325, -0.4346428202783189, -0.21744514588215502, 0.09527622586508032, 0.05451558261581629, -0.011689041540216195, -0.03227288156462813, -0.2718509886493316, 0.10448125422408339, -0.22815462868524397, -0.04947547701460014, -0.07403215588206744, -0.016959689540515948, 0.06337251104755191, -0.3144104034219664, 0.026493873379921554, -0.053671316096059435, 0.06377878651681651, -0.11262536779537274, -0.1630794218600807, -0.010660082747784965, 0.16960132193166716, 0.06727618314169642, -0.052296105491688824, 0.22181122610061543, -0.09746662259851469, -0.16123282957024213, 0.4220796565570664, 0.03223915040454325, -0.10737315949234294, 0.11536111973904686, 0.008422503832063251, -0.10327218664031357, 0.09334544961840459, 0.26427396666400543, 0.08822201035644223, -0.1786927448602666, -0.012464555506040796, 0.04194821612682284, 0.20358167880316969, 0.03718701700350588, -0.0503185493246902, 0.16837545794047268, 0.2885671435037582, 0.18204152800296092, 0.040379562698767475, -0.11128439070520604, -0.12391032038324672, -0.17229869188144575, -0.08645119857349683, -0.15864677566583496, 0.06504784031024362, -0.0805759878381739, -0.12644380933843644, 0.3903074879802639, 0.26665528892346363, 0.10125289147821959, 0.05812968593729637, 0.37639578022971387, 0.1218085795038993, 0.05066180896729503, 0.12393437244281813, 0.1706381645898346, -0.03831880418697327, 0.21921639593329462, -0.22187026360685505, 0.08373189359341135, -0.016535550219620148] |
1,802.04194 | On large deviations of interface motions for statistical mechanics
models | We discuss the sharp interface limit of the action functional associated to
either the Glauber dynamics for Ising systems with Kac potentials or the
Glauber+Kawasaki process. The corresponding limiting functionals, for which we
provide explicit formulae of the mobility and transport coefficients, describe
the large deviations asymptotics with respect to the mean curvature flow.
| math-ph math.MP math.PR | we discuss the sharp interface limit of the action functional associated to either the glauber dynamics for ising systems with kac potentials or the glauberkawasaki process the corresponding limiting functionals for which we provide explicit formulae of the mobility and transport coefficients describe the large deviations asymptotics with respect to the mean curvature flow | [['we', 'discuss', 'the', 'sharp', 'interface', 'limit', 'of', 'the', 'action', 'functional', 'associated', 'to', 'either', 'the', 'glauber', 'dynamics', 'for', 'ising', 'systems', 'with', 'kac', 'potentials', 'or', 'the', 'glauberkawasaki', 'process', 'the', 'corresponding', 'limiting', 'functionals', 'for', 'which', 'we', 'provide', 'explicit', 'formulae', 'of', 'the', 'mobility', 'and', 'transport', 'coefficients', 'describe', 'the', 'large', 'deviations', 'asymptotics', 'with', 'respect', 'to', 'the', 'mean', 'curvature', 'flow']] | [-0.11567984136998793, 0.09855879005991947, -0.09775458724360983, 0.10674474872160677, -0.024792014875993976, -0.12154934658967662, -0.001586729607913854, 0.34513189984520654, -0.27100006255479353, -0.2270078934907017, 0.10410291682225915, -0.3098856208863545, -0.12371231398088331, 0.15088871028713602, -0.010412346404748704, 0.09542721439644976, 0.03863527463257031, 0.06825564130053434, -0.07502102417836212, -0.16882078445358378, 0.3200691252033103, 0.035440056259691155, 0.2505457800338572, 0.09432722599781558, 0.11738166632130742, 0.04584489545767319, 0.04179857613272824, -0.007582293691570466, -0.231044796998349, 0.16985630511881714, 0.1774073804482677, -0.045159717564875225, 0.17775535059846798, -0.44170315303611307, -0.2099207561498262, 0.10281543261459414, 0.0951396943298432, 0.1270281686513456, 0.007623665148989772, -0.27687552790948244, 0.0516269672134856, -0.14603767009838572, -0.20577830670155445, -0.09805199593516453, 0.00717886857126119, 0.09719991439707437, -0.2831424886606774, 0.1413187198933952, 0.05364662246725891, 0.0761427048084168, -0.09305374436783341, -0.11196869570006318, -0.004924905561086423, 0.15221175806649592, 0.08715770465600796, -0.036741351864722396, 0.1249186087944457, -0.1878042804112412, -0.11188546025176656, 0.3464050223383139, -0.1306736334314886, -0.24704161982210177, 0.20228771555467007, -0.18222287003794368, -0.09650005586445332, 0.11813712269419206, 0.17933369994620388, 0.09423043017433781, -0.16673093016768964, 0.1247946138324585, 0.04583827789679591, 0.06736526214781235, 0.04013406434799281, 0.005452439856697929, 0.1322277789267729, 0.07527881864247457, 0.08541136302651381, 0.1559715440039927, -0.06538912464253921, -0.17360426968771894, -0.36902488114417725, -0.16124055628612075, -0.17119109294517845, 0.09247368009637971, -0.1563235599421874, -0.22774901281479956, 0.37187150644384465, 0.15327764644269953, 0.22648474304356947, 0.14087119633287964, 0.1773367329975063, 0.21293072465736912, 0.036575120785888635, 0.09719381987486246, 0.16479330335937017, 0.17977808352630092, 0.09802035102922742, -0.2556305196628256, 0.053846921088923, 0.11939807237951823] |
1,802.04195 | Slow-roll corrections in multi-field inflation: a separate universes
approach | In view of cosmological parameters being measured to ever higher precision,
theoretical predictions must also be computed to an equally high level of
precision. In this work we investigate the impact on such predictions of
relaxing some of the simplifying assumptions often used in these computations.
In particular, we investigate the importance of slow-roll corrections in the
computation of multi-field inflation observables, such as the amplitude of the
scalar spectrum $P_\zeta$, its spectral tilt $n_s$, the tensor-to-scalar ratio
$r$ and the non-Gaussianity parameter $f_{NL}$. To this end we use the separate
universes approach and $\delta N$ formalism, which allows us to consider
slow-roll corrections to the non-Gaussianity of the primordial curvature
perturbation as well as corrections to its two-point statistics. In the context
of the $\delta N$ expansion, we divide slow-roll corrections into two
categories: those associated with calculating the correlation functions of the
field perturbations on the initial flat hypersurface and those associated with
determining the derivatives of the e-folding number with respect to the field
values on the initial flat hypersurface. Using the results of Nakamura &
Stewart '96, corrections of the first kind can be written in a compact form.
Corrections of the second kind arise from using different levels of slow-roll
approximation in solving for the super-horizon evolution, which in turn
corresponds to using different levels of slow-roll approximation in the
background equations of motion. We consider four different levels of
approximation and apply the results to a few example models. The various
approximations are also compared to exact numerical solutions.
| astro-ph.CO | in view of cosmological parameters being measured to ever higher precision theoretical predictions must also be computed to an equally high level of precision in this work we investigate the impact on such predictions of relaxing some of the simplifying assumptions often used in these computations in particular we investigate the importance of slowroll corrections in the computation of multifield inflation observables such as the amplitude of the scalar spectrum p_zeta its spectral tilt n_s the tensortoscalar ratio r and the nongaussianity parameter f_nl to this end we use the separate universes approach and delta n formalism which allows us to consider slowroll corrections to the nongaussianity of the primordial curvature perturbation as well as corrections to its twopoint statistics in the context of the delta n expansion we divide slowroll corrections into two categories those associated with calculating the correlation functions of the field perturbations on the initial flat hypersurface and those associated with determining the derivatives of the efolding number with respect to the field values on the initial flat hypersurface using the results of nakamura stewart 96 corrections of the first kind can be written in a compact form corrections of the second kind arise from using different levels of slowroll approximation in solving for the superhorizon evolution which in turn corresponds to using different levels of slowroll approximation in the background equations of motion we consider four different levels of approximation and apply the results to a few example models the various approximations are also compared to exact numerical solutions | [['in', 'view', 'of', 'cosmological', 'parameters', 'being', 'measured', 'to', 'ever', 'higher', 'precision', 'theoretical', 'predictions', 'must', 'also', 'be', 'computed', 'to', 'an', 'equally', 'high', 'level', 'of', 'precision', 'in', 'this', 'work', 'we', 'investigate', 'the', 'impact', 'on', 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1,802.04196 | Universal quantum computing and three-manifolds | A single qubit may be represented on the Bloch sphere or similarly on the
$3$-sphere $S^3$. Our goal is to dress this correspondence by converting the
language of universal quantum computing (UQC) to that of $3$-manifolds. A magic
state and the Pauli group acting on it define a model of UQC as a positive
operator-valued measure (POVM) that one recognizes to be a $3$-manifold $M^3$.
More precisely, the $d$-dimensional POVMs defined from subgroups of finite
index of the modular group $PSL(2,\mathbb{Z})$ correspond to $d$-fold $M^3$-
coverings over the trefoil knot. In this paper, one also investigates quantum
information on a few "universal" knots and links such as the figure-of-eight
knot, the Whitehead link and Borromean rings, making use of the catalog of
platonic manifolds available on the software SnapPy. Further connections
between POVMs based UQC and $M^3$'s obtained from Dehn fillings are explored.
| quant-ph math.GR math.GT | a single qubit may be represented on the bloch sphere or similarly on the 3sphere s3 our goal is to dress this correspondence by converting the language of universal quantum computing uqc to that of 3manifolds a magic state and the pauli group acting on it define a model of uqc as a positive operatorvalued measure povm that one recognizes to be a 3manifold m3 more precisely the ddimensional povms defined from subgroups of finite index of the modular group psl2mathbbz correspond to dfold m3 coverings over the trefoil knot in this paper one also investigates quantum information on a few universal knots and links such as the figureofeight knot the whitehead link and borromean rings making use of the catalog of platonic manifolds available on the software snappy further connections between povms based uqc and m3s obtained from dehn fillings are explored | [['a', 'single', 'qubit', 'may', 'be', 'represented', 'on', 'the', 'bloch', 'sphere', 'or', 'similarly', 'on', 'the', '3sphere', 's3', 'our', 'goal', 'is', 'to', 'dress', 'this', 'correspondence', 'by', 'converting', 'the', 'language', 'of', 'universal', 'quantum', 'computing', 'uqc', 'to', 'that', 'of', '3manifolds', 'a', 'magic', 'state', 'and', 'the', 'pauli', 'group', 'acting', 'on', 'it', 'define', 'a', 'model', 'of', 'uqc', 'as', 'a', 'positive', 'operatorvalued', 'measure', 'povm', 'that', 'one', 'recognizes', 'to', 'be', 'a', '3manifold', 'm3', 'more', 'precisely', 'the', 'ddimensional', 'povms', 'defined', 'from', 'subgroups', 'of', 'finite', 'index', 'of', 'the', 'modular', 'group', 'psl2mathbbz', 'correspond', 'to', 'dfold', 'm3', 'coverings', 'over', 'the', 'trefoil', 'knot', 'in', 'this', 'paper', 'one', 'also', 'investigates', 'quantum', 'information', 'on', 'a', 'few', 'universal', 'knots', 'and', 'links', 'such', 'as', 'the', 'figureofeight', 'knot', 'the', 'whitehead', 'link', 'and', 'borromean', 'rings', 'making', 'use', 'of', 'the', 'catalog', 'of', 'platonic', 'manifolds', 'available', 'on', 'the', 'software', 'snappy', 'further', 'connections', 'between', 'povms', 'based', 'uqc', 'and', 'm3s', 'obtained', 'from', 'dehn', 'fillings', 'are', 'explored']] | [-0.19925450659568675, 0.1232192370213464, -0.11503923210556379, 0.08247984847350215, -0.10045056994043786, -0.19041609459953918, 0.06161482107965601, 0.3543088668794534, -0.2567619796764184, -0.2730176529319553, 0.08883289943556659, -0.2824966110829655, -0.14720918665480495, 0.2185806292858157, -0.12044444903275454, 0.014697012191937937, 0.05920567909594287, 0.11027177095973303, -0.08235652878606965, -0.2513367585175169, 0.36680931632139985, -0.01095653924329037, 0.20038391527934715, 0.04712538301640058, 0.09620550669358482, 0.013296676843615992, -0.02546063067401284, 0.00483977887453837, -0.1503874717734736, 0.13995865628553125, 0.2790609010384529, 0.06891109653295936, 0.13707665787111004, -0.37492594923954325, -0.14352870059127992, 0.1309156693791697, 0.11646891933282955, -0.005366410237860742, 0.001208741387488301, -0.33343077588409603, 0.022797092113976035, -0.20976725037672095, -0.08818720260568262, -0.0567888037441624, 0.021713757877713524, -0.016897773005433016, -0.14914485044253117, -0.014530307595606673, 0.05864924306645859, 0.07663321666341354, -0.00741216008570957, -0.0832237578485604, -0.03335628897713667, 0.17064697673655005, -0.05686961295705132, 0.0731668642126154, 0.13221360829014045, -0.08431313861441518, -0.1663890975410236, 0.37587983116924345, -0.028029661863338905, -0.2520888335742317, 0.13712198653539653, -0.13267495981059396, -0.16867338965314774, 0.12242918017717612, 0.08539346770556006, 0.10954365670807999, -0.07498749222450114, 0.09600250385669093, -0.13797916967252438, 0.14193257537077775, 0.11157692454175672, 0.015883505946819806, 0.20615942950093455, 0.08082538949638292, 0.11573302883238017, 0.17066867585567483, -0.027868351350388638, -0.07087375821181006, -0.31536219807315646, -0.2536019485889954, -0.2062637433035208, 0.13701911487818494, -0.07763258150210474, -0.19294065436335295, 0.38876883757229036, 0.013396681303490553, 0.14602219357995408, 0.09712205182474393, 0.2524247235387329, 0.0025669145845593168, 0.0877796445392769, 0.07076624896168918, 0.1283219970398016, 0.19620761692269958, -0.035448241019067905, -0.13941850555715496, -0.02673297418099079, 0.1562075331950417] |
1,802.04197 | Regularity of the derivatives of $p$-orthotropic functions in the plane
for $1<p<2$ | We present a proof of the $C^1$ regularity of $p$-orthotropic functions in
the plane for $1<p<2$, based on the monotonicity of the derivatives. Moreover
we achieve an explicit logarithmic modulus of continuity.
| math.AP | we present a proof of the c1 regularity of porthotropic functions in the plane for 1p2 based on the monotonicity of the derivatives moreover we achieve an explicit logarithmic modulus of continuity | [['we', 'present', 'a', 'proof', 'of', 'the', 'c1', 'regularity', 'of', 'porthotropic', 'functions', 'in', 'the', 'plane', 'for', '1p2', 'based', 'on', 'the', 'monotonicity', 'of', 'the', 'derivatives', 'moreover', 'we', 'achieve', 'an', 'explicit', 'logarithmic', 'modulus', 'of', 'continuity']] | [-0.17863983678961953, -0.03490958802520312, -0.15016317325493983, 0.06647204799998191, -0.09636779526068319, -0.03112238728170914, 0.06109300126310348, 0.3357918785224038, -0.26592387643552595, -0.1790445105683419, 0.1410189088726897, -0.2537327957519841, -0.11202646239149955, 0.19614650188915192, -0.08486100932913682, 0.1036243587732315, -0.03771871676848781, 0.05358121880600529, -0.16551786036260666, -0.2772967104589747, 0.395258360091717, -0.05660021434267683, 0.2154419661589688, 0.14814236868293054, 0.15429845743722492, 0.01670336870536689, 0.0030641114609616417, -0.06400072943389175, -0.24818767796480848, 0.20794306124650663, 0.11431351448259046, 0.0595201488674408, 0.26426878968073475, -0.41020038363433653, -0.14245830956966646, 0.1266536310074791, 0.09769173083646644, 0.021767807808975057, -0.07624575798024213, -0.2184319326714162, 0.11254987973840005, -0.05913155910468871, -0.22389112244690618, -0.09435171892325725, 0.00487152494550232, 0.11696368095374876, -0.31796597016434514, 0.14530013357439348, 0.11817948856661396, 0.12473886033460017, -0.12722795189268166, -0.11275163833652774, -0.03134536576427279, 0.07255822475699167, 0.04178541925202514, 0.06544442598016993, 0.036280365270232, -0.15975246938966936, -0.08207631319941532, 0.30687018820355016, -0.11415763935374637, -0.276417164131999, 0.11567505819332455, -0.15051863829214726, -0.155635314843347, 0.06461888329396324, 0.15724585996940732, 0.1956015357657546, -0.10122200511696358, 0.1481094108744254, -0.048104733957218065, 0.16880331792297862, 0.13955693043047382, 0.08295619217378478, 0.013722628895794191, 0.11237823013817111, 0.1775021557846377, 0.20878826051710114, -0.013824396233464922, -0.04658396021583148, -0.4535971197389787, -0.23448993902533286, -0.19325158957226743, 0.0730872158817346, -0.17399063936224388, -0.23275878238341502, 0.3843983073470994, 0.11564352868064758, 0.17260924029734828, 0.1840336086048234, 0.23669338454642602, 0.1716904185652252, 0.02633078298681686, 0.07437533641894979, 0.25267837785424724, 0.12583472366414725, 0.10608518479632274, -0.15941499660332356, 0.06791012935460575, 0.1774141499772668] |
1,802.04198 | client2vec: Towards Systematic Baselines for Banking Applications | The workflow of data scientists normally involves potentially inefficient
processes such as data mining, feature engineering and model selection. Recent
research has focused on automating this workflow, partly or in its entirety, to
improve productivity. We choose the former approach and in this paper share our
experience in designing the client2vec: an internal library to rapidly build
baselines for banking applications. Client2vec uses marginalized stacked
denoising autoencoders on current account transactions data to create vector
embeddings which represent the behaviors of our clients. These representations
can then be used in, and optimized against, a variety of tasks such as client
segmentation, profiling and targeting. Here we detail how we selected the
algorithmic machinery of client2vec and the data it works on and present
experimental results on several business cases.
| stat.ML cs.LG | the workflow of data scientists normally involves potentially inefficient processes such as data mining feature engineering and model selection recent research has focused on automating this workflow partly or in its entirety to improve productivity we choose the former approach and in this paper share our experience in designing the client2vec an internal library to rapidly build baselines for banking applications client2vec uses marginalized stacked denoising autoencoders on current account transactions data to create vector embeddings which represent the behaviors of our clients these representations can then be used in and optimized against a variety of tasks such as client segmentation profiling and targeting here we detail how we selected the algorithmic machinery of client2vec and the data it works on and present experimental results on several business cases | [['the', 'workflow', 'of', 'data', 'scientists', 'normally', 'involves', 'potentially', 'inefficient', 'processes', 'such', 'as', 'data', 'mining', 'feature', 'engineering', 'and', 'model', 'selection', 'recent', 'research', 'has', 'focused', 'on', 'automating', 'this', 'workflow', 'partly', 'or', 'in', 'its', 'entirety', 'to', 'improve', 'productivity', 'we', 'choose', 'the', 'former', 'approach', 'and', 'in', 'this', 'paper', 'share', 'our', 'experience', 'in', 'designing', 'the', 'client2vec', 'an', 'internal', 'library', 'to', 'rapidly', 'build', 'baselines', 'for', 'banking', 'applications', 'client2vec', 'uses', 'marginalized', 'stacked', 'denoising', 'autoencoders', 'on', 'current', 'account', 'transactions', 'data', 'to', 'create', 'vector', 'embeddings', 'which', 'represent', 'the', 'behaviors', 'of', 'our', 'clients', 'these', 'representations', 'can', 'then', 'be', 'used', 'in', 'and', 'optimized', 'against', 'a', 'variety', 'of', 'tasks', 'such', 'as', 'client', 'segmentation', 'profiling', 'and', 'targeting', 'here', 'we', 'detail', 'how', 'we', 'selected', 'the', 'algorithmic', 'machinery', 'of', 'client2vec', 'and', 'the', 'data', 'it', 'works', 'on', 'and', 'present', 'experimental', 'results', 'on', 'several', 'business', 'cases']] | [-0.03147872120445205, 0.004637438830194901, -0.06465437302957902, 0.06135167309458461, -0.14457560045456933, -0.13929815439492926, 0.08657013083349682, 0.4375858359082147, -0.2742381196562923, -0.3556601160039851, 0.12717618841620149, -0.27779508634766403, -0.15452706611123254, 0.22369519726900283, -0.1161222677757285, 0.06606116203289811, 0.10362326702853852, -0.0037389250631018204, 0.012515470858432295, -0.29900277041750706, 0.2739442352010587, 0.05825944782357461, 0.3437823338213904, 0.043107563422184234, 0.05149623966422076, 0.01799731243802451, -0.08876393060741383, -0.04478669065571548, -0.09459407483010965, 0.1812631783848123, 0.35403565079147037, 0.24687285330724115, 0.30713052184017764, -0.455002962395029, -0.19540829029540682, 0.07670317106887467, 0.15656213821164627, 0.0869455711560526, -0.06443887548304575, -0.29979466368234897, 0.052029037230843025, -0.1843131042571554, -0.041918012057250556, -0.16906189196562582, -0.021230797212960763, 0.006351792388920521, -0.2512696320696395, -0.024199601638224696, 0.06445758181440016, 0.07533732852934635, -0.042938109585661584, -0.11935818037595744, -0.0023540231947924276, 0.1814965344297649, 0.06175931706183496, 0.03797861442688217, 0.17201829645530026, -0.14301034194135734, -0.15609441728280612, 0.3584650245805581, -0.02067581005033481, -0.20102873560070067, 0.2100299225881869, -0.008564880698948174, -0.21566874588760296, 0.0373430818232686, 0.25524567060403586, 0.08925465982797187, -0.16207924713344538, 0.03011248678838935, -0.0004611347202760305, 0.14814931997043881, 0.03174724926867038, -0.000852306849907997, 0.1850718025825629, 0.23124943233217843, 0.017096054246161826, 0.1315231602481032, -0.07295788685942806, -0.05992637065333105, -0.2117100371347466, -0.12383741461274814, -0.15680667456391073, -0.004842700315783767, -0.06168853179592271, -0.15300300441205847, 0.4052278538082921, 0.23447118839609993, 0.17982743847248858, 0.03036724747241612, 0.3663908677074567, 0.019204338536013003, 0.1292752466496629, 0.07933813033177871, 0.15073280259533678, 0.0011685696076746135, 0.16818637291850277, -0.12836958985692684, 0.10586984148844643, -0.01693284149144509] |
1,802.04199 | Integral representation of the subelliptic heat kernel on the complex
anti-de Sitter fibration | We derive an integral representation for the subelliptic heat kernel of the
complex anti-de Sitter fibration. Our proof is different from the one used in
Jing Wang \cite{Wan} since it appeals to the commutativity of the D'Alembertian
and of the Laplacian acting on the vertical variable rather than the analytic
continuation of the heat semigroup of the real hyperbolic space. Our approach
also sheds the light on the connection between the sub-Laplacian of the above
fibration and the so-called generalized Maass Laplacian, and on the role played
by the odd dimensional real hyperbolic space.
| math.CV math.AP math.PR | we derive an integral representation for the subelliptic heat kernel of the complex antide sitter fibration our proof is different from the one used in jing wang citewan since it appeals to the commutativity of the dalembertian and of the laplacian acting on the vertical variable rather than the analytic continuation of the heat semigroup of the real hyperbolic space our approach also sheds the light on the connection between the sublaplacian of the above fibration and the socalled generalized maass laplacian and on the role played by the odd dimensional real hyperbolic space | [['we', 'derive', 'an', 'integral', 'representation', 'for', 'the', 'subelliptic', 'heat', 'kernel', 'of', 'the', 'complex', 'antide', 'sitter', 'fibration', 'our', 'proof', 'is', 'different', 'from', 'the', 'one', 'used', 'in', 'jing', 'wang', 'citewan', 'since', 'it', 'appeals', 'to', 'the', 'commutativity', 'of', 'the', 'dalembertian', 'and', 'of', 'the', 'laplacian', 'acting', 'on', 'the', 'vertical', 'variable', 'rather', 'than', 'the', 'analytic', 'continuation', 'of', 'the', 'heat', 'semigroup', 'of', 'the', 'real', 'hyperbolic', 'space', 'our', 'approach', 'also', 'sheds', 'the', 'light', 'on', 'the', 'connection', 'between', 'the', 'sublaplacian', 'of', 'the', 'above', 'fibration', 'and', 'the', 'socalled', 'generalized', 'maass', 'laplacian', 'and', 'on', 'the', 'role', 'played', 'by', 'the', 'odd', 'dimensional', 'real', 'hyperbolic', 'space']] | [-0.12255403128582784, 0.06785305932565387, -0.09926037949519934, 0.10594177720893014, -0.17645205689534063, -0.06078027336988398, -0.0015316076942228822, 0.28490563929681817, -0.2615154559789125, -0.22403590550385816, 0.11801150236754449, -0.29236834389107524, -0.18511457288617728, 0.2600244840692168, -0.058040269410177585, 0.03672326026704683, 0.0076144435493055215, 0.08397786631073642, -0.082635589474712, -0.22848970348876652, 0.46530306387332176, 0.022892120718625526, 0.2404074216441762, 0.05253087027719425, 0.12298358825626232, 0.03930676478131484, -0.06638333732162112, -0.08960666912119655, -0.13838287296714963, 0.1598503237730393, 0.18447361629135828, 0.03013588232238607, 0.21842062509849028, -0.4140796846364655, -0.22227204114358912, 0.15231535977543761, 0.11005249784217887, -0.03708397193501393, -0.02090578354639752, -0.330897601882136, 0.00516030305035172, -0.08468028215030508, -0.1555423782537541, -0.05894677945843307, 0.02014366329036733, -0.017392383337581672, -0.22212075945791057, 0.06309480610853112, 0.1436706114840764, 0.06447802072450999, -0.09158322446408772, -0.09686629185252772, -0.08574706485735313, 0.09746264147582234, 0.02928712412023977, 0.03690600499600893, 0.08029110031202435, -0.05455910870706805, -0.07445646774384283, 0.3439299322224112, -0.07407534962738438, -0.28027729051167605, 0.1312885515326734, -0.1831656382594418, -0.11290244415142042, 0.08045489120707718, 0.12344748463221294, 0.16704876027921195, -0.049552672632759615, 0.18215764710311627, -0.07491540653200479, 0.07309644346335722, 0.11013732273732463, -0.015845298867232058, 0.10771088400274835, 0.124932908983801, 0.0973020118851495, 0.15273460647672094, -0.028259979152891745, -0.11453368487988189, -0.355969153925456, -0.2308455908931391, -0.21648825394610563, 0.13300380083702265, -0.18684570792695052, -0.1896150622576956, 0.4040304847682516, 0.07844001548652667, 0.1734914788575743, 0.054779490836525474, 0.257429234383087, 0.13915663658045432, 0.04854324656183161, 0.09192775974553379, 0.21267536296559278, 0.21097354060389423, 0.11411550130334593, -0.24777524798397496, -0.03784093641555838, 0.21850524507262695] |
1,802.042 | End-to-End Automatic Speech Translation of Audiobooks | We investigate end-to-end speech-to-text translation on a corpus of
audiobooks specifically augmented for this task. Previous works investigated
the extreme case where source language transcription is not available during
learning nor decoding, but we also study a midway case where source language
transcription is available at training time only. In this case, a single model
is trained to decode source speech into target text in a single pass.
Experimental results show that it is possible to train compact and efficient
end-to-end speech translation models in this setup. We also distribute the
corpus and hope that our speech translation baseline on this corpus will be
challenged in the future.
| cs.CL | we investigate endtoend speechtotext translation on a corpus of audiobooks specifically augmented for this task previous works investigated the extreme case where source language transcription is not available during learning nor decoding but we also study a midway case where source language transcription is available at training time only in this case a single model is trained to decode source speech into target text in a single pass experimental results show that it is possible to train compact and efficient endtoend speech translation models in this setup we also distribute the corpus and hope that our speech translation baseline on this corpus will be challenged in the future | [['we', 'investigate', 'endtoend', 'speechtotext', 'translation', 'on', 'a', 'corpus', 'of', 'audiobooks', 'specifically', 'augmented', 'for', 'this', 'task', 'previous', 'works', 'investigated', 'the', 'extreme', 'case', 'where', 'source', 'language', 'transcription', 'is', 'not', 'available', 'during', 'learning', 'nor', 'decoding', 'but', 'we', 'also', 'study', 'a', 'midway', 'case', 'where', 'source', 'language', 'transcription', 'is', 'available', 'at', 'training', 'time', 'only', 'in', 'this', 'case', 'a', 'single', 'model', 'is', 'trained', 'to', 'decode', 'source', 'speech', 'into', 'target', 'text', 'in', 'a', 'single', 'pass', 'experimental', 'results', 'show', 'that', 'it', 'is', 'possible', 'to', 'train', 'compact', 'and', 'efficient', 'endtoend', 'speech', 'translation', 'models', 'in', 'this', 'setup', 'we', 'also', 'distribute', 'the', 'corpus', 'and', 'hope', 'that', 'our', 'speech', 'translation', 'baseline', 'on', 'this', 'corpus', 'will', 'be', 'challenged', 'in', 'the', 'future']] | [-0.07154930477177172, 0.045220503945731454, -0.03298539416088412, 0.09673430734417504, -0.15291986560138562, -0.21012653902828418, 0.06132720761578875, 0.49330040212306714, -0.2511142233248662, -0.2648477260431887, 0.05790404984468801, -0.27546356771900143, -0.13093887289761807, 0.23398902354960296, -0.1253670028290125, 0.02820774313510844, 0.19187829666770995, 0.1290361550119188, -0.023735628045634023, -0.29410511905465414, 0.26078778856295953, 0.052765018617113434, 0.35991681850929225, 0.031002669306299475, 0.11000858014988436, -0.05635818407905323, -0.01861549844034016, -0.10732582171611418, -0.03887609217390828, 0.13243832981593354, 0.3636465912545814, 0.2250593927499183, 0.2698738635431423, -0.3888719741737953, -0.21877482562774309, 0.0765558389722611, 0.15409728237945172, 0.17005115597405368, -0.05077280893413074, -0.3340822091709857, 0.0911949825428935, -0.17577989480492692, 0.06628328743735673, -0.06656672783989322, 0.010370585067128693, -0.05935390933235693, -0.25670298585814805, 0.011938977723022819, 0.13428021503474424, 0.0853190618967077, -0.04698771623467716, -0.046487461723801166, 0.05839179726791809, 0.14715059413315934, 0.06064398127879637, 0.15240269859054092, 0.10505532390972669, -0.12709179580970495, -0.08588348086427518, 0.37745525011861764, -0.09294471087762052, -0.2632152434455714, 0.18034054303576272, -0.05389447701680991, -0.22145098233293672, 0.04707464149773673, 0.27260073040681027, 0.1012815117266857, -0.2017682101232586, 0.019689075777057075, -0.05926787160785386, 0.2807554089360767, 0.09775909743513223, -0.06485244794317556, 0.164350917701894, 0.26496066026717285, -0.045530450931336314, 0.1865006698817187, -0.11299291845945711, -0.03954184534409756, -0.27191631936390576, -0.11172532021602685, -0.20573471721986103, -0.0041197412193233265, 0.0006460415340067508, -0.09920836855114128, 0.38086730152092596, 0.21520112463514562, 0.1510748586927851, 0.1410347889716461, 0.33533606719639564, -0.007153326840596963, 0.10126885257799316, 0.09336143019296557, 0.182237114279781, -0.07556031786198555, 0.14197989917118792, -0.1508647689242261, 0.08750101882550451, 0.0019978683601409473] |
1,802.04201 | Cellular automaton models for time-correlated random walks: derivation
and analysis | Many diffusion processes in nature and society were found to be anomalous, in
the sense of being fundamentally different from conventional Brownian motion.
An important example is the migration of biological cells, which exhibits
non-trivial temporal decay of velocity autocorrelation functions. This means
that the corresponding dynamics is characterized by memory effects that slowly
decay in time. Motivated by this we construct non-Markovian lattice-gas
cellular automata models for moving agents with memory. For this purpose the
reorientation probabilities are derived from velocity autocorrelation functions
that are given a priori; in that respect our approach is `data-driven'.
Particular examples we consider are velocity correlations that decay
exponentially or as power laws, where the latter functions generate anomalous
diffusion. The computational efficiency of cellular automata combined with our
analytical results paves the way to explore the relevance of memory and
anomalous diffusion for the dynamics of interacting cell populations, like
confluent cell monolayers and cell clustering.
| cond-mat.stat-mech physics.bio-ph physics.comp-ph q-bio.CB | many diffusion processes in nature and society were found to be anomalous in the sense of being fundamentally different from conventional brownian motion an important example is the migration of biological cells which exhibits nontrivial temporal decay of velocity autocorrelation functions this means that the corresponding dynamics is characterized by memory effects that slowly decay in time motivated by this we construct nonmarkovian latticegas cellular automata models for moving agents with memory for this purpose the reorientation probabilities are derived from velocity autocorrelation functions that are given a priori in that respect our approach is datadriven particular examples we consider are velocity correlations that decay exponentially or as power laws where the latter functions generate anomalous diffusion the computational efficiency of cellular automata combined with our analytical results paves the way to explore the relevance of memory and anomalous diffusion for the dynamics of interacting cell populations like confluent cell monolayers and cell clustering | [['many', 'diffusion', 'processes', 'in', 'nature', 'and', 'society', 'were', 'found', 'to', 'be', 'anomalous', 'in', 'the', 'sense', 'of', 'being', 'fundamentally', 'different', 'from', 'conventional', 'brownian', 'motion', 'an', 'important', 'example', 'is', 'the', 'migration', 'of', 'biological', 'cells', 'which', 'exhibits', 'nontrivial', 'temporal', 'decay', 'of', 'velocity', 'autocorrelation', 'functions', 'this', 'means', 'that', 'the', 'corresponding', 'dynamics', 'is', 'characterized', 'by', 'memory', 'effects', 'that', 'slowly', 'decay', 'in', 'time', 'motivated', 'by', 'this', 'we', 'construct', 'nonmarkovian', 'latticegas', 'cellular', 'automata', 'models', 'for', 'moving', 'agents', 'with', 'memory', 'for', 'this', 'purpose', 'the', 'reorientation', 'probabilities', 'are', 'derived', 'from', 'velocity', 'autocorrelation', 'functions', 'that', 'are', 'given', 'a', 'priori', 'in', 'that', 'respect', 'our', 'approach', 'is', 'datadriven', 'particular', 'examples', 'we', 'consider', 'are', 'velocity', 'correlations', 'that', 'decay', 'exponentially', 'or', 'as', 'power', 'laws', 'where', 'the', 'latter', 'functions', 'generate', 'anomalous', 'diffusion', 'the', 'computational', 'efficiency', 'of', 'cellular', 'automata', 'combined', 'with', 'our', 'analytical', 'results', 'paves', 'the', 'way', 'to', 'explore', 'the', 'relevance', 'of', 'memory', 'and', 'anomalous', 'diffusion', 'for', 'the', 'dynamics', 'of', 'interacting', 'cell', 'populations', 'like', 'confluent', 'cell', 'monolayers', 'and', 'cell', 'clustering']] | [-0.0995858923205879, 0.17697619498934516, -0.05344708151389639, 0.06886816681997682, -0.0390699763854893, -0.149755512185806, 0.027447352269566135, 0.38084071400490677, -0.30339839203621854, -0.24320853488140304, 0.04813877939754589, -0.25834336265461977, -0.1960431864022507, 0.19005619684179834, -0.028267440174452284, 0.04892611401397493, 0.034196702637951576, 0.007066546706482768, 0.02839694485255795, -0.1980493480397098, 0.27852801849775305, 0.03183306595548691, 0.2890019617345813, -0.021673151756056233, 0.08147095847124984, -0.04775976700792936, -0.037810669781401296, 0.04038179442044589, -0.12478459766101548, 0.1045462420911758, 0.21335241794027257, 0.07300838421691548, 0.2573873654806188, -0.4507431907143879, -0.2540436766908637, 0.09202500092706269, 0.20031352656705959, 0.10454861312581516, -0.06019269275878157, -0.2773092991291461, 0.040618652766630924, -0.1583372577450347, -0.13493989084623512, -0.09996674100372505, 0.05915416975493555, 0.08826127584816514, -0.26673828028656493, 0.1417235032694608, 0.0610337670825954, 0.05855517099647747, -0.07434604765904777, -0.09656611266666902, -7.854894638158284e-05, 0.1475018222783027, 0.049632420355163805, -0.03143555811582158, 0.1692399741309187, -0.13221065975633425, -0.1655402106585211, 0.3801495329077755, -0.04132550369718342, -0.24714496470503994, 0.21954953048360087, -0.1717647573194019, -0.11512341452218205, 0.15622101790670836, 0.17991374713042146, 0.06837546485083106, -0.19227650052529166, 0.0677528362316775, -0.0079352822481328, 0.14962071850185293, 0.05367139814415487, 0.060427294872465315, 0.16642759261689113, 0.21625002247867986, 0.028797401408226436, 0.12484990896251924, -0.0625607786827128, -0.16204473395626268, -0.2605521648565864, -0.16900634368603396, -0.1710153075249551, 0.06887338007800281, -0.0921958823611411, -0.1574854853974244, 0.3719444537517167, 0.15185778642484507, 0.17183580779615645, 0.12515239366073186, 0.27072798286250177, 0.1432187168703221, 0.060136696369109024, 0.04920019916343418, 0.16634192564766612, 0.11220389242169096, 0.1285038563580095, -0.26013626623898745, 0.11797005669879061, 0.05790688462446553] |
1,802.04202 | Tying up instantons with anti-instantons | In quantizing classical mechanical systems one often sums over the classical
trajectories as in localization formulas, but also takes into account the
contributions of the "instanton gas": a set of approximate solutions of the
equations of motion. This paper attempts to alleviate some of the frustrations
of this 40+ years old approach by finding the honest solutions of equations of
motion of the complexified classical mechanical system. These ideas originate
in the Bethe/gauge correspondence. The examples include algebraic integrable
systems, from the abstract Hitchin systems to the well-studied anharmonic
oscillator. We also speculate on the applications to the black hole radiation.
We elucidate the relation between Lefschetz thimbles and the $\Omega$-deformed
$B$-model. We propose the notion of the topological renormalization group.
| hep-th | in quantizing classical mechanical systems one often sums over the classical trajectories as in localization formulas but also takes into account the contributions of the instanton gas a set of approximate solutions of the equations of motion this paper attempts to alleviate some of the frustrations of this 40 years old approach by finding the honest solutions of equations of motion of the complexified classical mechanical system these ideas originate in the bethegauge correspondence the examples include algebraic integrable systems from the abstract hitchin systems to the wellstudied anharmonic oscillator we also speculate on the applications to the black hole radiation we elucidate the relation between lefschetz thimbles and the omegadeformed bmodel we propose the notion of the topological renormalization group | [['in', 'quantizing', 'classical', 'mechanical', 'systems', 'one', 'often', 'sums', 'over', 'the', 'classical', 'trajectories', 'as', 'in', 'localization', 'formulas', 'but', 'also', 'takes', 'into', 'account', 'the', 'contributions', 'of', 'the', 'instanton', 'gas', 'a', 'set', 'of', 'approximate', 'solutions', 'of', 'the', 'equations', 'of', 'motion', 'this', 'paper', 'attempts', 'to', 'alleviate', 'some', 'of', 'the', 'frustrations', 'of', 'this', '40', 'years', 'old', 'approach', 'by', 'finding', 'the', 'honest', 'solutions', 'of', 'equations', 'of', 'motion', 'of', 'the', 'complexified', 'classical', 'mechanical', 'system', 'these', 'ideas', 'originate', 'in', 'the', 'bethegauge', 'correspondence', 'the', 'examples', 'include', 'algebraic', 'integrable', 'systems', 'from', 'the', 'abstract', 'hitchin', 'systems', 'to', 'the', 'wellstudied', 'anharmonic', 'oscillator', 'we', 'also', 'speculate', 'on', 'the', 'applications', 'to', 'the', 'black', 'hole', 'radiation', 'we', 'elucidate', 'the', 'relation', 'between', 'lefschetz', 'thimbles', 'and', 'the', 'omegadeformed', 'bmodel', 'we', 'propose', 'the', 'notion', 'of', 'the', 'topological', 'renormalization', 'group']] | [-0.16821812055591293, 0.0652510038007451, -0.11771584996445612, 0.10441310806700206, -0.0780359570952979, -0.1208868078235152, 0.04711840158686319, 0.2752564838694886, -0.3014873383982369, -0.2787406615266376, 0.07054753426447018, -0.28684474958187695, -0.1904337681398904, 0.1776812598571058, -0.10909582249190532, 0.046081718650053845, 0.03591702201342102, 0.02551396449158076, -0.11043161116848307, -0.24891682537965293, 0.36985786925724223, -0.028281873107449083, 0.22292278864043802, 0.02727155822660189, 0.13327164582288556, -0.0010521185434277146, -0.006616220948063145, -0.016693167919523952, -0.13838228665884922, 0.15778989114698547, 0.2545302426365535, 0.0686699940923078, 0.2417974427711865, -0.4467800620881733, -0.2068982776870166, 0.10130403720973875, 0.1693406231578224, 0.15305887390320644, -0.0012181068949539923, -0.30335485808597495, 0.02642030359345896, -0.18577844610684052, -0.1577531995698194, -0.06717361661043665, 0.0066243193366310816, 0.026122829903779198, -0.1311034224888941, 0.0587814154275616, 0.08876979552701977, 0.02787094638867627, -0.11206256835105682, -0.0514585538844247, -0.0010212006870934293, 0.10424484465317416, 0.09257803665866599, -0.016518621963317975, 0.13554988693530587, -0.1425379394930749, -0.13788347955300542, 0.4023617625174936, -0.0057809592295853685, -0.20410292310070646, 0.18353584023146344, -0.1301269174615029, -0.16177894990537162, 0.13450870299634854, 0.13522778036196, 0.11843333888653673, -0.13537353396508073, 0.1385399194213962, -0.044280224556703704, 0.09974798288635048, 0.056992645983484164, 0.04528019617288566, 0.22534289575866923, 0.08116082251379805, 0.007843465913733668, 0.16773164439907928, -0.020903176610735208, -0.15691973055012462, -0.31315330285117154, -0.15843234061502104, -0.11314374320055089, 0.1230934062772546, -0.10541914231401256, -0.18457540902809416, 0.39195676942640717, 0.17663170898011848, 0.1732179899045751, 0.05846302385811409, 0.2695203128363167, 0.12211371067546266, 0.05596174993205908, 0.02346823601079104, 0.23714004382265017, 0.1944382984118059, 0.08829307228169012, -0.24910894101524095, -0.06685872784284644, 0.1699223392027284] |
1,802.04203 | Kinematic Distances: A Monte Carlo Method | Distances to high mass star forming regions (HMSFRs) in the Milky Way are a
crucial constraint on the structure of the Galaxy. Only kinematic distances are
available for a majority of the HMSFRs in the Milky Way. Here we compare the
kinematic and parallax distances of 75 Galactic HMSFRs to assess the accuracy
of kinematic distances. We derive the kinematic distances using three different
methods: the traditional method using the Brand & Blitz (1993) rotation curve
(Method A), the traditional method using the Reid et al. (2014) rotation curve
and updated Solar motion parameters (Method B), and a Monte Carlo technique
(Method C). Methods B and C produce kinematic distances closest to the parallax
distances, with median differences of 13% (0.43 kpc) and 17% (0.42 kpc),
respectively. Except in the vicinity of the tangent point, the kinematic
distance uncertainties derived by Method C are smaller than those of Methods A
and B. In a large region of the Galaxy, the Method C kinematic distances
constrain both the distances and the Galactocentric positions of HMSFRs more
accurately than parallax distances. Beyond the tangent point along longitude=30
degrees, for example, the Method C kinematic distance uncertainties reach a
minimum of 10% of the parallax distance uncertainty at a distance of 14 kpc. We
develop a prescription for deriving and applying the Method C kinematic
distances and distance uncertainties. The code to generate the Method C
kinematic distances is publicly available and may be utilized through an
on-line tool.
| astro-ph.GA | distances to high mass star forming regions hmsfrs in the milky way are a crucial constraint on the structure of the galaxy only kinematic distances are available for a majority of the hmsfrs in the milky way here we compare the kinematic and parallax distances of 75 galactic hmsfrs to assess the accuracy of kinematic distances we derive the kinematic distances using three different methods the traditional method using the brand blitz 1993 rotation curve method a the traditional method using the reid et al 2014 rotation curve and updated solar motion parameters method b and a monte carlo technique method c methods b and c produce kinematic distances closest to the parallax distances with median differences of 13 043 kpc and 17 042 kpc respectively except in the vicinity of the tangent point the kinematic distance uncertainties derived by method c are smaller than those of methods a and b in a large region of the galaxy the method c kinematic distances constrain both the distances and the galactocentric positions of hmsfrs more accurately than parallax distances beyond the tangent point along longitude30 degrees for example the method c kinematic distance uncertainties reach a minimum of 10 of the parallax distance uncertainty at a distance of 14 kpc we develop a prescription for deriving and applying the method c kinematic distances and distance uncertainties the code to generate the method c kinematic distances is publicly available and may be utilized through an online tool | [['distances', 'to', 'high', 'mass', 'star', 'forming', 'regions', 'hmsfrs', 'in', 'the', 'milky', 'way', 'are', 'a', 'crucial', 'constraint', 'on', 'the', 'structure', 'of', 'the', 'galaxy', 'only', 'kinematic', 'distances', 'are', 'available', 'for', 'a', 'majority', 'of', 'the', 'hmsfrs', 'in', 'the', 'milky', 'way', 'here', 'we', 'compare', 'the', 'kinematic', 'and', 'parallax', 'distances', 'of', '75', 'galactic', 'hmsfrs', 'to', 'assess', 'the', 'accuracy', 'of', 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1,802.04204 | Fast Interactive Image Retrieval using large-scale unlabeled data | An interactive image retrieval system learns which images in the database
belong to a user's query concept, by analyzing the example images and feedback
provided by the user. The challenge is to retrieve the relevant images with
minimal user interaction. In this work, we propose to solve this problem by
posing it as a binary classification task of classifying all images in the
database as being relevant or irrelevant to the user's query concept. Our
method combines active learning with graph-based semi-supervised learning
(GSSL) to tackle this problem. Active learning reduces the number of user
interactions by querying the labels of the most informative points and GSSL
allows to use abundant unlabeled data along with the limited labeled data
provided by the user. To efficiently find the most informative point, we use an
uncertainty sampling based method that queries the label of the point nearest
to the decision boundary of the classifier. We estimate this decision boundary
using our heuristic of adaptive threshold. To utilize huge volumes of unlabeled
data we use an efficient approximation based method that reduces the complexity
of GSSL from $O(n^3)$ to $O(n)$, making GSSL scalable. We make the classifier
robust to the diversity and noisy labels associated with images in large
databases by incorporating information from multiple modalities such as visual
information extracted from deep learning based models and semantic information
extracted from the WordNet. High F1 scores within few relevance feedback rounds
in our experiments with concepts defined on AnimalWithAttributes and Imagenet
(1.2 million images) datasets indicate the effectiveness and scalability of our
approach.
| cs.LG stat.ML | an interactive image retrieval system learns which images in the database belong to a users query concept by analyzing the example images and feedback provided by the user the challenge is to retrieve the relevant images with minimal user interaction in this work we propose to solve this problem by posing it as a binary classification task of classifying all images in the database as being relevant or irrelevant to the users query concept our method combines active learning with graphbased semisupervised learning gssl to tackle this problem active learning reduces the number of user interactions by querying the labels of the most informative points and gssl allows to use abundant unlabeled data along with the limited labeled data provided by the user to efficiently find the most informative point we use an uncertainty sampling based method that queries the label of the point nearest to the decision boundary of the classifier we estimate this decision boundary using our heuristic of adaptive threshold to utilize huge volumes of unlabeled data we use an efficient approximation based method that reduces the complexity of gssl from on3 to on making gssl scalable we make the classifier robust to the diversity and noisy labels associated with images in large databases by incorporating information from multiple modalities such as visual information extracted from deep learning based models and semantic information extracted from the wordnet high f1 scores within few relevance feedback rounds in our experiments with concepts defined on animalwithattributes and imagenet 12 million images datasets indicate the effectiveness and scalability of our approach | [['an', 'interactive', 'image', 'retrieval', 'system', 'learns', 'which', 'images', 'in', 'the', 'database', 'belong', 'to', 'a', 'users', 'query', 'concept', 'by', 'analyzing', 'the', 'example', 'images', 'and', 'feedback', 'provided', 'by', 'the', 'user', 'the', 'challenge', 'is', 'to', 'retrieve', 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1,802.04205 | Efficient Hierarchical Robot Motion Planning Under Uncertainty and
Hybrid Dynamics | Noisy observations coupled with nonlinear dynamics pose one of the biggest
challenges in robot motion planning. By decomposing nonlinear dynamics into a
discrete set of local dynamics models, hybrid dynamics provide a natural way to
model nonlinear dynamics, especially in systems with sudden discontinuities in
dynamics due to factors such as contacts. We propose a hierarchical POMDP
planner that develops cost-optimized motion plans for hybrid dynamics models.
The hierarchical planner first develops a high-level motion plan to sequence
the local dynamics models to be visited and then converts it into a detailed
continuous state plan. This hierarchical planning approach results in a
decomposition of the POMDP planning problem into smaller sub-parts that can be
solved with significantly lower computational costs. The ability to sequence
the visitation of local dynamics models also provides a powerful way to
leverage the hybrid dynamics to reduce state uncertainty. We evaluate the
proposed planner on a navigation task in the simulated domain and on an
assembly task with a robotic manipulator, showing that our approach can solve
tasks having high observation noise and nonlinear dynamics effectively with
significantly lower computational costs compared to direct planning approaches.
| cs.RO cs.AI cs.SY | noisy observations coupled with nonlinear dynamics pose one of the biggest challenges in robot motion planning by decomposing nonlinear dynamics into a discrete set of local dynamics models hybrid dynamics provide a natural way to model nonlinear dynamics especially in systems with sudden discontinuities in dynamics due to factors such as contacts we propose a hierarchical pomdp planner that develops costoptimized motion plans for hybrid dynamics models the hierarchical planner first develops a highlevel motion plan to sequence the local dynamics models to be visited and then converts it into a detailed continuous state plan this hierarchical planning approach results in a decomposition of the pomdp planning problem into smaller subparts that can be solved with significantly lower computational costs the ability to sequence the visitation of local dynamics models also provides a powerful way to leverage the hybrid dynamics to reduce state uncertainty we evaluate the proposed planner on a navigation task in the simulated domain and on an assembly task with a robotic manipulator showing that our approach can solve tasks having high observation noise and nonlinear dynamics effectively with significantly lower computational costs compared to direct planning approaches | [['noisy', 'observations', 'coupled', 'with', 'nonlinear', 'dynamics', 'pose', 'one', 'of', 'the', 'biggest', 'challenges', 'in', 'robot', 'motion', 'planning', 'by', 'decomposing', 'nonlinear', 'dynamics', 'into', 'a', 'discrete', 'set', 'of', 'local', 'dynamics', 'models', 'hybrid', 'dynamics', 'provide', 'a', 'natural', 'way', 'to', 'model', 'nonlinear', 'dynamics', 'especially', 'in', 'systems', 'with', 'sudden', 'discontinuities', 'in', 'dynamics', 'due', 'to', 'factors', 'such', 'as', 'contacts', 'we', 'propose', 'a', 'hierarchical', 'pomdp', 'planner', 'that', 'develops', 'costoptimized', 'motion', 'plans', 'for', 'hybrid', 'dynamics', 'models', 'the', 'hierarchical', 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1,802.04206 | One-Bit Precoding and Constellation Range Design for Massive MIMO with
QAM Signaling | The use of low-resolution digital-to-analog converters (DACs) for transmit
precoding provides crucial energy efficiency advantage for massive
multiple-input multiple-output (MIMO) implementation. This paper formulates a
quadrature amplitude modulation (QAM) constellation range and one-bit
symbol-level precoding design problem for minimizing the average symbol error
rate (SER) in downlink massive MIMO transmission. A tight upper-bound for SER
with low-resolution DAC precoding is first derived. The derived expression
suggests that the performance degradation of one-bit precoding can be
interpreted as a decrease in the effective minimum distance of the QAM
constellation. Using the obtained SER expression, we propose a QAM
constellation range design for the single-user case. It is shown that in the
massive MIMO limit, a reasonable choice for constellation range with one-bit
precoding is that of the infinite-resolution precoding with per-symbol power
constraint, but reduced by a factor of $\sqrt{2/\pi}$ or about $0.8$. The
corresponding minimum distance reduction translates to about 2dB gap between
the performance of one-bit precoding and infinite-resolution precoding. This
paper further proposes a low-complexity heuristic algorithm for one-bit
precoder design. Finally, the proposed QAM constellation range and precoder
design are generalized to the multi-user downlink. We propose to scale the
constellation range for infinite-resolution zero-forcing (ZF) precoding with
per-symbol power constraint by the same factor of $\sqrt{2/\pi}$ for one-bit
precoding. The proposed one-bit precoding scheme is shown to be within 2dB of
infinite-resolution ZF. In term of number of antennas, one-bit precoding
requires about 50% more antennas to achieve the same performance as
infinite-resolution precoding.
| cs.IT math.IT | the use of lowresolution digitaltoanalog converters dacs for transmit precoding provides crucial energy efficiency advantage for massive multipleinput multipleoutput mimo implementation this paper formulates a quadrature amplitude modulation qam constellation range and onebit symbollevel precoding design problem for minimizing the average symbol error rate ser in downlink massive mimo transmission a tight upperbound for ser with lowresolution dac precoding is first derived the derived expression suggests that the performance degradation of onebit precoding can be interpreted as a decrease in the effective minimum distance of the qam constellation using the obtained ser expression we propose a qam constellation range design for the singleuser case it is shown that in the massive mimo limit a reasonable choice for constellation range with onebit precoding is that of the infiniteresolution precoding with persymbol power constraint but reduced by a factor of sqrt2pi or about 08 the corresponding minimum distance reduction translates to about 2db gap between the performance of onebit precoding and infiniteresolution precoding this paper further proposes a lowcomplexity heuristic algorithm for onebit precoder design finally the proposed qam constellation range and precoder design are generalized to the multiuser downlink we propose to scale the constellation range for infiniteresolution zeroforcing zf precoding with persymbol power constraint by the same factor of sqrt2pi for onebit precoding the proposed onebit precoding scheme is shown to be within 2db of infiniteresolution zf in term of number of antennas onebit precoding requires about 50 more antennas to achieve the same performance as infiniteresolution precoding | [['the', 'use', 'of', 'lowresolution', 'digitaltoanalog', 'converters', 'dacs', 'for', 'transmit', 'precoding', 'provides', 'crucial', 'energy', 'efficiency', 'advantage', 'for', 'massive', 'multipleinput', 'multipleoutput', 'mimo', 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1,802.04207 | The Excursion set approach: Stratonovich approximation and Cholesky
decomposition | The excursion set approach is a framework for estimating how the number
density of nonlinear structures in the cosmic web depends on the expansion
history of the universe and the nature of gravity. A key part of the approach
is the estimation of the first crossing distribution of a suitably chosen
barrier by random walks having correlated steps: The shape of the barrier is
determined by the physics of nonlinear collapse, and the correlations between
steps by the nature of the initial density fluctuation field. We describe
analytic and numerical methods for calculating such first up-crossing
distributions. While the exact solution can be written formally as an infinite
series, we show how to approximate it efficiently using the Stratonovich
approximation. We demonstrate its accuracy using Monte-Carlo realizations of
the walks, which we generate using a novel Cholesky-decomposition based
algorithm, which is significantly faster than the algorithm that is currently
in the literature.
| astro-ph.CO | the excursion set approach is a framework for estimating how the number density of nonlinear structures in the cosmic web depends on the expansion history of the universe and the nature of gravity a key part of the approach is the estimation of the first crossing distribution of a suitably chosen barrier by random walks having correlated steps the shape of the barrier is determined by the physics of nonlinear collapse and the correlations between steps by the nature of the initial density fluctuation field we describe analytic and numerical methods for calculating such first upcrossing distributions while the exact solution can be written formally as an infinite series we show how to approximate it efficiently using the stratonovich approximation we demonstrate its accuracy using montecarlo realizations of the walks which we generate using a novel choleskydecomposition based algorithm which is significantly faster than the algorithm that is currently in the literature | [['the', 'excursion', 'set', 'approach', 'is', 'a', 'framework', 'for', 'estimating', 'how', 'the', 'number', 'density', 'of', 'nonlinear', 'structures', 'in', 'the', 'cosmic', 'web', 'depends', 'on', 'the', 'expansion', 'history', 'of', 'the', 'universe', 'and', 'the', 'nature', 'of', 'gravity', 'a', 'key', 'part', 'of', 'the', 'approach', 'is', 'the', 'estimation', 'of', 'the', 'first', 'crossing', 'distribution', 'of', 'a', 'suitably', 'chosen', 'barrier', 'by', 'random', 'walks', 'having', 'correlated', 'steps', 'the', 'shape', 'of', 'the', 'barrier', 'is', 'determined', 'by', 'the', 'physics', 'of', 'nonlinear', 'collapse', 'and', 'the', 'correlations', 'between', 'steps', 'by', 'the', 'nature', 'of', 'the', 'initial', 'density', 'fluctuation', 'field', 'we', 'describe', 'analytic', 'and', 'numerical', 'methods', 'for', 'calculating', 'such', 'first', 'upcrossing', 'distributions', 'while', 'the', 'exact', 'solution', 'can', 'be', 'written', 'formally', 'as', 'an', 'infinite', 'series', 'we', 'show', 'how', 'to', 'approximate', 'it', 'efficiently', 'using', 'the', 'stratonovich', 'approximation', 'we', 'demonstrate', 'its', 'accuracy', 'using', 'montecarlo', 'realizations', 'of', 'the', 'walks', 'which', 'we', 'generate', 'using', 'a', 'novel', 'choleskydecomposition', 'based', 'algorithm', 'which', 'is', 'significantly', 'faster', 'than', 'the', 'algorithm', 'that', 'is', 'currently', 'in', 'the', 'literature']] | [-0.08849711609435336, 0.08524778307446769, -0.14235266335370228, 0.0768047496614768, -0.039469904574682774, -0.05737208103798083, 0.028232147099931312, 0.34941130285000965, -0.269653495401144, -0.3198492090458309, 0.09898278401048224, -0.2454020090721893, -0.15864734499505567, 0.19356999120718202, 0.006509924723785247, 0.06083047825385144, 0.026614574746333605, 0.019068098235381952, -0.06150162290158799, -0.2562149213256919, 0.31598605101447036, 0.0712091542521356, 0.26537342758892435, 0.013722092610173273, 0.12795031164458257, 0.004684851319831334, -0.02923487442459245, 0.0326833189619298, -0.1294988367126099, 0.13791812222531152, 0.17828013503843831, 0.13892821937688435, 0.2852497164573249, -0.42027479108416826, -0.19366417101789452, 0.07984203825217505, 0.16029189247483794, 0.14215813797053617, -0.036693722839985315, -0.27806039248278597, 0.06725919489680932, -0.14942578961517636, -0.11422311232752161, -0.07184690076993494, 0.013691668649241082, 0.06861314692130523, -0.2608105166821389, 0.0896685536186032, 0.03247330189738053, -0.0002896620626777213, -0.02843164756126233, -0.07762015829886625, 0.021051089416584925, 0.11719151330026274, 0.030443412833076142, 0.010991812655887265, 0.12263321211031139, -0.13385669744784778, -0.11835521640138862, 0.3800057890309971, -0.08797773606167406, -0.2067436956473247, 0.12207429456549222, -0.13612861158202913, -0.10207244280775059, 0.13004276346236418, 0.1463893424559212, 0.15446267525252227, -0.14970411920599294, 0.11313632253861203, -0.009665308083833151, 0.13720384202064909, 0.0420876648384979, -0.022268667184926618, 0.190208208913736, 0.17927461506996228, 0.06339629710534748, 0.13897388185148354, -0.07910830613583425, -0.1316946089199886, -0.3306103938949967, -0.15121222190969064, -0.2513772155272324, 0.0193629019665501, -0.11640717192147843, -0.20533742645558045, 0.42243916802848414, 0.19010360359325265, 0.20269389607826407, 0.07117271680070322, 0.30920000394670577, 0.16951250382215294, 0.02075569656683712, 0.0824589468908823, 0.1939147843197543, 0.1234840411995075, 0.05494464207934031, -0.22336191242092, 0.10950853435063598, 0.09030130321764393] |
1,802.04208 | Adversarial Audio Synthesis | Audio signals are sampled at high temporal resolutions, and learning to
synthesize audio requires capturing structure across a range of timescales.
Generative adversarial networks (GANs) have seen wide success at generating
images that are both locally and globally coherent, but they have seen little
application to audio generation. In this paper we introduce WaveGAN, a first
attempt at applying GANs to unsupervised synthesis of raw-waveform audio.
WaveGAN is capable of synthesizing one second slices of audio waveforms with
global coherence, suitable for sound effect generation. Our experiments
demonstrate that, without labels, WaveGAN learns to produce intelligible words
when trained on a small-vocabulary speech dataset, and can also synthesize
audio from other domains such as drums, bird vocalizations, and piano. We
compare WaveGAN to a method which applies GANs designed for image generation on
image-like audio feature representations, finding both approaches to be
promising.
| cs.SD cs.LG | audio signals are sampled at high temporal resolutions and learning to synthesize audio requires capturing structure across a range of timescales generative adversarial networks gans have seen wide success at generating images that are both locally and globally coherent but they have seen little application to audio generation in this paper we introduce wavegan a first attempt at applying gans to unsupervised synthesis of rawwaveform audio wavegan is capable of synthesizing one second slices of audio waveforms with global coherence suitable for sound effect generation our experiments demonstrate that without labels wavegan learns to produce intelligible words when trained on a smallvocabulary speech dataset and can also synthesize audio from other domains such as drums bird vocalizations and piano we compare wavegan to a method which applies gans designed for image generation on imagelike audio feature representations finding both approaches to be promising | [['audio', 'signals', 'are', 'sampled', 'at', 'high', 'temporal', 'resolutions', 'and', 'learning', 'to', 'synthesize', 'audio', 'requires', 'capturing', 'structure', 'across', 'a', 'range', 'of', 'timescales', 'generative', 'adversarial', 'networks', 'gans', 'have', 'seen', 'wide', 'success', 'at', 'generating', 'images', 'that', 'are', 'both', 'locally', 'and', 'globally', 'coherent', 'but', 'they', 'have', 'seen', 'little', 'application', 'to', 'audio', 'generation', 'in', 'this', 'paper', 'we', 'introduce', 'wavegan', 'a', 'first', 'attempt', 'at', 'applying', 'gans', 'to', 'unsupervised', 'synthesis', 'of', 'rawwaveform', 'audio', 'wavegan', 'is', 'capable', 'of', 'synthesizing', 'one', 'second', 'slices', 'of', 'audio', 'waveforms', 'with', 'global', 'coherence', 'suitable', 'for', 'sound', 'effect', 'generation', 'our', 'experiments', 'demonstrate', 'that', 'without', 'labels', 'wavegan', 'learns', 'to', 'produce', 'intelligible', 'words', 'when', 'trained', 'on', 'a', 'smallvocabulary', 'speech', 'dataset', 'and', 'can', 'also', 'synthesize', 'audio', 'from', 'other', 'domains', 'such', 'as', 'drums', 'bird', 'vocalizations', 'and', 'piano', 'we', 'compare', 'wavegan', 'to', 'a', 'method', 'which', 'applies', 'gans', 'designed', 'for', 'image', 'generation', 'on', 'imagelike', 'audio', 'feature', 'representations', 'finding', 'both', 'approaches', 'to', 'be', 'promising']] | [-0.011779929565741344, 0.04386448958584814, -0.06083902699133077, 0.09314721078464946, -0.13167269338345064, -0.1815930765637375, -0.052334068352125375, 0.5133176881568968, -0.26506427065832605, -0.32713635866769675, 0.0592390793393835, -0.27882422397164164, -0.16895525671990838, 0.23627601266741186, -0.14483613275315163, 0.08545598225397262, 0.11502017936477742, 0.0386267847345204, -0.041502110125886685, -0.2393644925319187, 0.2878117068201726, -0.0009107304925217907, 0.35638478608366025, -0.048042456269369906, 0.19471834769310653, -0.06615924582228805, -0.014580808880454894, -0.0694357785297201, 0.0023825212767973527, 0.16825957831939853, 0.39845876235197836, 0.2084684143972365, 0.2874973652329534, -0.40937002902810876, -0.2628391692745136, 0.0956730760026274, 0.13387892757239422, 0.16216093729867712, -0.10984917201517903, -0.37117743460421865, 0.15433443024596002, -0.13512004614338702, 0.07044738260467688, -0.17401037721214355, -0.00934550447756068, -0.0007569255531891018, -0.288329916851387, 0.029299574621568323, 0.08149388891104807, 0.07159712157667951, -0.05757907737898541, -0.05071386367789344, 0.0032311232152877124, 0.19738512194210975, 0.011640430637800419, 0.0563233428492693, 0.10848416106202409, -0.17529569175391596, -0.12675152795310032, 0.37228931494532747, -0.08911870578171831, -0.19395447822604725, 0.2261637280833848, -0.032944102479303454, -0.12691532060213334, 0.10914923267188013, 0.23926335242940178, 0.13575418029931632, -0.13134225723690746, -0.04996392755902947, -0.015801642011646314, 0.2281835192759977, 0.13411419111938078, 0.03644981017296619, 0.2115875650209652, 0.23882739109660875, 0.0042767562801910046, 0.15679490805317892, -0.14887567628744713, 0.008756965626665253, -0.18723308610860323, -0.04477702619025735, -0.19762669154607976, 0.0015738241387702895, -0.0438945281632238, -0.1416738806341953, 0.4309995232334902, 0.2451507434123427, 0.20964216310134592, 0.15316173715532613, 0.34239278867153833, -0.007189905439364783, 0.11489685392667744, 0.03878446089117028, 0.12899029784644325, -0.006640575637922008, 0.162286868034895, -0.10509702058303408, 0.0820444447982475, 0.04501083102869861] |
1,802.04209 | Angular Sizes of $\mu$Jy Radio Sources | We made two new sensitive (rms noise sigma_n ~ 1 microJy/beam) high
resolution (theta = 3.0" and theta = 0.66" FWHM) S--band (2 < nu < 4 GHz)
images covering a single JVLA primary beam (FWHM ~ 14') centered on J2000 RA =
10 46, Dec = 59 01 in the Lockman Hole. These images yielded a catalog of 792
radio sources, 97.7 +/- 0.8% of which have infrared counterparts stronger than
S ~ 2 microJy at lambda = 4.5 micron. About 91% of the radio sources found in
our previously published, comparably sensitive low resolution (theta = 8" FWHM)
image covering the same area were also detected at 0.66" resolution, so most
radio sources with S_3GHz >~ 5 microJy have angular structure phi <~ 0.66". The
ratios of peak brightness in the 0.66" and 3" images have a distribution
indicating that most microJy radio sources are quite compact, with a median
Gaussian angular diameter <phi> = 0.3" +/- 0.1" FWHM and an rms scatter
sigma_phi <~ 0.3" of individual sizes. Most of our microJy radio sources obey
the tight far-infrared/radio correlation, indicating that they are powered by
star formation. The median effective angular radius enclosing half the light
emitted by an exponential disk is <rho_e> ~ <phi>/2.43 ~ 0.12", so the median
effective radius of star-forming galaxies at redshifts z~1 is <r_e> ~ 1.0 kpc.
| astro-ph.GA | we made two new sensitive rms noise sigma_n 1 microjybeam high resolution theta 30 and theta 066 fwhm sband 2 nu 4 ghz images covering a single jvla primary beam fwhm 14 centered on j2000 ra 10 46 dec 59 01 in the lockman hole these images yielded a catalog of 792 radio sources 977 08 of which have infrared counterparts stronger than s 2 microjy at lambda 45 micron about 91 of the radio sources found in our previously published comparably sensitive low resolution theta 8 fwhm image covering the same area were also detected at 066 resolution so most radio sources with s_3ghz 5 microjy have angular structure phi 066 the ratios of peak brightness in the 066 and 3 images have a distribution indicating that most microjy radio sources are quite compact with a median gaussian angular diameter phi 03 01 fwhm and an rms scatter sigma_phi 03 of individual sizes most of our microjy radio sources obey the tight farinfraredradio correlation indicating that they are powered by star formation the median effective angular radius enclosing half the light emitted by an exponential disk is rho_e phi243 012 so the median effective radius of starforming galaxies at redshifts z1 is r_e 10 kpc | [['we', 'made', 'two', 'new', 'sensitive', 'rms', 'noise', 'sigma_n', '1', 'microjybeam', 'high', 'resolution', 'theta', '30', 'and', 'theta', '066', 'fwhm', 'sband', '2', 'nu', '4', 'ghz', 'images', 'covering', 'a', 'single', 'jvla', 'primary', 'beam', 'fwhm', '14', 'centered', 'on', 'j2000', 'ra', '10', '46', 'dec', '59', '01', 'in', 'the', 'lockman', 'hole', 'these', 'images', 'yielded', 'a', 'catalog', 'of', '792', 'radio', 'sources', '977', '08', 'of', 'which', 'have', 'infrared', 'counterparts', 'stronger', 'than', 's', '2', 'microjy', 'at', 'lambda', '45', 'micron', 'about', '91', 'of', 'the', 'radio', 'sources', 'found', 'in', 'our', 'previously', 'published', 'comparably', 'sensitive', 'low', 'resolution', 'theta', '8', 'fwhm', 'image', 'covering', 'the', 'same', 'area', 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1,802.0421 | Selective Area Grown Semiconductor-Superconductor Hybrids: A Basis for
Topological Networks | We introduce selective area grown hybrid InAs/Al nanowires based on molecular
beam epitaxy, allowing arbitrary semiconductor-superconductor networks
containing loops and branches. Transport reveals a hard induced gap and
unpoisoned 2e-periodic Coulomb blockade, with temperature dependent 1e features
in agreement with theory. Coulomb peak spacing in parallel magnetic field
displays overshoot, indicating an oscillating discrete near-zero subgap state
consistent with device length. Finally, we investigate a loop network, finding
strong spin-orbit coupling and a coherence length of several microns. These
results demonstrate the potential of this platform for scalable topological
networks among other applications.
| cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.supr-con | we introduce selective area grown hybrid inasal nanowires based on molecular beam epitaxy allowing arbitrary semiconductorsuperconductor networks containing loops and branches transport reveals a hard induced gap and unpoisoned 2eperiodic coulomb blockade with temperature dependent 1e features in agreement with theory coulomb peak spacing in parallel magnetic field displays overshoot indicating an oscillating discrete nearzero subgap state consistent with device length finally we investigate a loop network finding strong spinorbit coupling and a coherence length of several microns these results demonstrate the potential of this platform for scalable topological networks among other applications | [['we', 'introduce', 'selective', 'area', 'grown', 'hybrid', 'inasal', 'nanowires', 'based', 'on', 'molecular', 'beam', 'epitaxy', 'allowing', 'arbitrary', 'semiconductorsuperconductor', 'networks', 'containing', 'loops', 'and', 'branches', 'transport', 'reveals', 'a', 'hard', 'induced', 'gap', 'and', 'unpoisoned', '2eperiodic', 'coulomb', 'blockade', 'with', 'temperature', 'dependent', '1e', 'features', 'in', 'agreement', 'with', 'theory', 'coulomb', 'peak', 'spacing', 'in', 'parallel', 'magnetic', 'field', 'displays', 'overshoot', 'indicating', 'an', 'oscillating', 'discrete', 'nearzero', 'subgap', 'state', 'consistent', 'with', 'device', 'length', 'finally', 'we', 'investigate', 'a', 'loop', 'network', 'finding', 'strong', 'spinorbit', 'coupling', 'and', 'a', 'coherence', 'length', 'of', 'several', 'microns', 'these', 'results', 'demonstrate', 'the', 'potential', 'of', 'this', 'platform', 'for', 'scalable', 'topological', 'networks', 'among', 'other', 'applications']] | [-0.24875228081161724, 0.18514177181113273, -0.04030508625209737, 0.026704369930603603, -0.02841466422567306, -0.23285898854247417, 0.0663051261483064, 0.4779206902072158, -0.24371352965903023, -0.30768915337166225, -0.04524749345348581, -0.2595389185918738, -0.14365671227784807, 0.20570497775359242, 0.01400634074209096, 0.053424274812088064, 0.06396577496691505, -0.06108228833941014, -0.06033573385692485, -0.154692174720011, 0.270484841424901, 0.017185437396857076, 0.3513665636849549, 0.13930344844803863, 0.07456291986264936, -0.005233909221082602, 0.07904641572436642, 0.048637876083375886, -0.14747808969316437, 0.0963628415749712, 0.20137268423264765, -0.11283352537303352, 0.22776190468879498, -0.4690630055923501, -0.21927406014393733, 0.002203836935855772, 0.15539108885897565, 0.12689752860814738, -0.08713665491339508, -0.27266649193251913, 0.03970526108320843, -0.1376143037423785, -0.11280064993163409, -0.06537274779491228, -0.013961159627955489, 0.01617979809500115, -0.25904941849876195, 0.07579564704033344, -0.006610547534048395, 0.0881298392423955, -0.034720234198333776, -0.12310333464689471, -0.02293040026890357, 0.04327741812891833, -0.005544413377166442, 0.03480644039202319, 0.18017505156888586, -0.11865009435037475, -0.1633450293726207, 0.27302241033833957, -0.08111741833968351, -0.06046238825049089, 0.16156143857338262, -0.1169870590041999, -0.08886549570192785, 0.14544366986450294, 0.11360966827234496, 0.09002197563455885, -0.11867761882224484, 0.06662047706840499, 0.01607604299509979, 0.22311546267820118, 0.09246591808598327, 0.13876077364654085, 0.2730678769192942, 0.23765391877690412, 0.04920399883026814, 0.17824050868132515, -0.16191173975264816, -0.11525978270978869, -0.2281756822080554, -0.10930896795395276, -0.17794854527987217, 0.06786914191046811, -0.09476227665515541, -0.24270199938758236, 0.3937335832420301, 0.1384677261458305, 0.18002582543387846, 0.014077699292734589, 0.26944650511216856, 0.10029275491631226, 0.10525116795147567, 0.07973719102775921, 0.20403044730546357, 0.19322367944076416, 0.11327443977959616, -0.31644158852387866, 0.013828922528773546, -0.0268722164960902] |
1,802.04211 | Basic Parallel and Distributed Computing Curriculum | With the advent of multi-core processors and their fast expansion, it is
quite clear that {\em parallel computing} is now a genuine requirement in
Computer Science and Engineering (and related) curriculum. In addition to the
pervasiveness of parallel computing devices, we should take into account the
fact that there are lot of existing softwares that are implemented in the
sequential mode, and thus need to be adapted for a parallel execution.
Therefore, it is required to the programmer to be able to design parallel
programs and also to have some skills in moving from a given sequential code to
the corresponding parallel code. In this paper, we present a basic educational
scenario on how to give a consistent and efficient background in parallel
computing to ordinary computer scientists and engineers.
| cs.DC | with the advent of multicore processors and their fast expansion it is quite clear that em parallel computing is now a genuine requirement in computer science and engineering and related curriculum in addition to the pervasiveness of parallel computing devices we should take into account the fact that there are lot of existing softwares that are implemented in the sequential mode and thus need to be adapted for a parallel execution therefore it is required to the programmer to be able to design parallel programs and also to have some skills in moving from a given sequential code to the corresponding parallel code in this paper we present a basic educational scenario on how to give a consistent and efficient background in parallel computing to ordinary computer scientists and engineers | [['with', 'the', 'advent', 'of', 'multicore', 'processors', 'and', 'their', 'fast', 'expansion', 'it', 'is', 'quite', 'clear', 'that', 'em', 'parallel', 'computing', 'is', 'now', 'a', 'genuine', 'requirement', 'in', 'computer', 'science', 'and', 'engineering', 'and', 'related', 'curriculum', 'in', 'addition', 'to', 'the', 'pervasiveness', 'of', 'parallel', 'computing', 'devices', 'we', 'should', 'take', 'into', 'account', 'the', 'fact', 'that', 'there', 'are', 'lot', 'of', 'existing', 'softwares', 'that', 'are', 'implemented', 'in', 'the', 'sequential', 'mode', 'and', 'thus', 'need', 'to', 'be', 'adapted', 'for', 'a', 'parallel', 'execution', 'therefore', 'it', 'is', 'required', 'to', 'the', 'programmer', 'to', 'be', 'able', 'to', 'design', 'parallel', 'programs', 'and', 'also', 'to', 'have', 'some', 'skills', 'in', 'moving', 'from', 'a', 'given', 'sequential', 'code', 'to', 'the', 'corresponding', 'parallel', 'code', 'in', 'this', 'paper', 'we', 'present', 'a', 'basic', 'educational', 'scenario', 'on', 'how', 'to', 'give', 'a', 'consistent', 'and', 'efficient', 'background', 'in', 'parallel', 'computing', 'to', 'ordinary', 'computer', 'scientists', 'and', 'engineers']] | [-0.09478392187649241, 0.08350751219371047, -0.10724170220156129, 0.04760220070691923, -0.16069139378646818, -0.17379183248043634, 0.03305811985516741, 0.43857462217028326, -0.28828881674674517, -0.35800011127900616, 0.10921072393852788, -0.20493493711468405, -0.12606050685549586, 0.2500550688781704, -0.0833453949325933, 0.050837234929741286, 0.10092315466877502, 0.006009674360617422, -0.03137656832763101, -0.28895759174886804, 0.2373778900418144, 0.08243843050530324, 0.2779598824966412, 0.03852247051321543, 0.04408314532170502, -0.026163417043594213, -0.039339356956322895, 0.029214226048833763, -0.06567849447819754, 0.17569052214161135, 0.3369308595975431, 0.21462513574828895, 0.30386473015667154, -0.4838653480956474, -0.11818021468173426, 0.07958306848572996, 0.15626875391015066, 0.11402682746254589, -0.06416813872056082, -0.22707985762793284, 0.12493209947760288, -0.1738562770635606, -0.06453098884975099, -0.10617503329502562, 0.02407320334146229, -0.020412170009400984, -0.2253134220838547, -0.039063277728004886, 0.037820639302774975, 0.05645213158657918, 0.011035111691923633, -0.06824081527928894, 0.056075226812838365, 0.1446267012721644, 0.024008538482639077, 0.06811244179351399, 0.10049713893542783, -0.1269032094036587, -0.1440691945787806, 0.4137842423354204, 0.013449245949204151, -0.19878704891396828, 0.23110439808269104, -0.06213338115485385, -0.16522311138419005, 0.07835259732002249, 0.22648202955292968, 0.062829917210799, -0.1571077205742208, 0.0831953270365305, 0.0461737509100483, 0.158045838565494, 0.029496775736781555, -0.003849419697116201, 0.21538749891691483, 0.13987325597554445, 0.043124883429845794, 0.14236215183762116, -0.0010153657308994578, -0.13094977813307196, -0.26330231537755866, -0.228460050564116, -0.170952426234502, 0.005271900786409297, -0.014699008443970412, -0.1857381690866672, 0.35713674530673484, 0.22408136025500985, 0.11060954524347415, 0.04316615353768261, 0.3674633317412092, 0.07391187649650069, 0.16070889255855805, 0.15159251923637035, 0.18818982951925137, 0.07294570810806293, 0.17750490966539542, -0.16534760100587917, 0.06491690438169126, -0.042853316854542266] |
1,802.04212 | Beneficial impact of tunneling in nano-structured intermediate-band
solar cell | Using the non equilibrium Green functions formalism we propose a study of the
electronic excitation and collection in nano-structured intermediate-band solar
cell. We demonstrate that a thin tunnel barrier between the nano-objects and
the host material is beneficial for both current and voltage. For the current,
the confinement generated by such a thin barrier favors the intersubband
optical coupling in the nano-objects and then improves the
excitation-collection trade-off. We also show that a broadened density-of-state
in the nano-objects increases the radiative recombination and then degrades the
voltage. Using a detailed balance model we propose a broadening factor for this
Voc degradation which decreases when a tunnel barrier enhances the life-time in
the nano-objects.
| physics.app-ph | using the non equilibrium green functions formalism we propose a study of the electronic excitation and collection in nanostructured intermediateband solar cell we demonstrate that a thin tunnel barrier between the nanoobjects and the host material is beneficial for both current and voltage for the current the confinement generated by such a thin barrier favors the intersubband optical coupling in the nanoobjects and then improves the excitationcollection tradeoff we also show that a broadened densityofstate in the nanoobjects increases the radiative recombination and then degrades the voltage using a detailed balance model we propose a broadening factor for this voc degradation which decreases when a tunnel barrier enhances the lifetime in the nanoobjects | [['using', 'the', 'non', 'equilibrium', 'green', 'functions', 'formalism', 'we', 'propose', 'a', 'study', 'of', 'the', 'electronic', 'excitation', 'and', 'collection', 'in', 'nanostructured', 'intermediateband', 'solar', 'cell', 'we', 'demonstrate', 'that', 'a', 'thin', 'tunnel', 'barrier', 'between', 'the', 'nanoobjects', 'and', 'the', 'host', 'material', 'is', 'beneficial', 'for', 'both', 'current', 'and', 'voltage', 'for', 'the', 'current', 'the', 'confinement', 'generated', 'by', 'such', 'a', 'thin', 'barrier', 'favors', 'the', 'intersubband', 'optical', 'coupling', 'in', 'the', 'nanoobjects', 'and', 'then', 'improves', 'the', 'excitationcollection', 'tradeoff', 'we', 'also', 'show', 'that', 'a', 'broadened', 'densityofstate', 'in', 'the', 'nanoobjects', 'increases', 'the', 'radiative', 'recombination', 'and', 'then', 'degrades', 'the', 'voltage', 'using', 'a', 'detailed', 'balance', 'model', 'we', 'propose', 'a', 'broadening', 'factor', 'for', 'this', 'voc', 'degradation', 'which', 'decreases', 'when', 'a', 'tunnel', 'barrier', 'enhances', 'the', 'lifetime', 'in', 'the', 'nanoobjects']] | [-0.12261601907916234, 0.12087897106747343, -0.002853374121644135, 0.015071412265699888, 0.006496225169809934, -0.129827526614203, 0.12891432642936707, 0.4349806622735092, -0.26901587250176817, -0.31636225324057576, -0.012419100917343582, -0.2756527927205233, -0.1304392466123058, 0.21676819027093838, -0.021636777220659757, 0.00508355038307075, 0.05299657244800723, -0.09787875270870115, -0.045801611055919365, -0.1396553421259991, 0.285573005052616, 0.051076311134238495, 0.33279694985997466, 0.16787574240255967, 0.09704861662300703, -0.0035890892946294378, 0.08059676412293422, 0.03504318459558168, -0.1335209231657635, 0.08729452377260064, 0.18286519826506265, -0.015763145187520422, 0.26036471387903604, -0.4494413893303967, -0.20756794642823348, 0.024521217989136597, 0.16210617823526263, 0.1441992598213671, -0.10390565629027801, -0.23023193016914384, 0.047629060383769684, -0.1745644652442674, -0.07811891454288603, -0.028128950665372292, -0.000989151166452627, 0.05303704133880923, -0.2919331204580625, 0.055275218633791416, 0.052798739817392616, 0.043628398267693616, -0.0829608003238848, -0.07423045067116618, -0.05594461377976196, 0.11098624285217998, -0.009223711409764032, -0.0010961313403510889, 0.23507548459955224, -0.1628171379888954, -0.06986067624114055, 0.34498100612212773, -0.08739179824728385, -0.14195390605267935, 0.14850295954550216, -0.15384054804079433, -0.015502868047925793, 0.12184002436697483, 0.1258525592690733, 0.12820104184044925, -0.12768398838839598, 0.07424072934320845, 0.02069902016748009, 0.16950983770324715, 0.06978243349086759, 0.035942430237940116, 0.20060422791201354, 0.24892402777706074, 0.05511387717810327, 0.1872768781405674, -0.15585077386848362, -0.021621296681197628, -0.2245698927851793, -0.19066672922238986, -0.15573445744147257, 0.07632487174123526, -0.08366326142004255, -0.18264196576118202, 0.43922610131890644, 0.1542140684863885, 0.19544068418742558, 0.02157902136449203, 0.32499505291759434, 0.14147629734361544, 0.07448946195654571, 0.040675525553524494, 0.2879638055788486, 0.11852932680838942, 0.11966158314966638, -0.3159073842959645, 0.07252030902600382, -0.03589962244067075] |
1,802.04213 | Integral representations of the star product corresponding to the
$s$-ordering of the creation and annihilation operators | A new integral representation is obtained for the star product corresponding
to the $s$-ordering of the creation and annihilation operators. This parametric
ordering convention introduced by Cahill and Glauber enables one to vary the
type of ordering in a continuous way from normal order to antinormal order. Our
derivation of the corresponding integral representation is based on using
reproducing formulas for analytic and antianalytic functions. We also discuss a
different representation whose kernel is a generalized function and compare the
properties of this kernel with those of the kernels of another family of star
products which are intermediate between the $qp-$ and $pq$-quantization.
| math-ph math.MP quant-ph | a new integral representation is obtained for the star product corresponding to the sordering of the creation and annihilation operators this parametric ordering convention introduced by cahill and glauber enables one to vary the type of ordering in a continuous way from normal order to antinormal order our derivation of the corresponding integral representation is based on using reproducing formulas for analytic and antianalytic functions we also discuss a different representation whose kernel is a generalized function and compare the properties of this kernel with those of the kernels of another family of star products which are intermediate between the qp and pqquantization | [['a', 'new', 'integral', 'representation', 'is', 'obtained', 'for', 'the', 'star', 'product', 'corresponding', 'to', 'the', 'sordering', 'of', 'the', 'creation', 'and', 'annihilation', 'operators', 'this', 'parametric', 'ordering', 'convention', 'introduced', 'by', 'cahill', 'and', 'glauber', 'enables', 'one', 'to', 'vary', 'the', 'type', 'of', 'ordering', 'in', 'a', 'continuous', 'way', 'from', 'normal', 'order', 'to', 'antinormal', 'order', 'our', 'derivation', 'of', 'the', 'corresponding', 'integral', 'representation', 'is', 'based', 'on', 'using', 'reproducing', 'formulas', 'for', 'analytic', 'and', 'antianalytic', 'functions', 'we', 'also', 'discuss', 'a', 'different', 'representation', 'whose', 'kernel', 'is', 'a', 'generalized', 'function', 'and', 'compare', 'the', 'properties', 'of', 'this', 'kernel', 'with', 'those', 'of', 'the', 'kernels', 'of', 'another', 'family', 'of', 'star', 'products', 'which', 'are', 'intermediate', 'between', 'the', 'qp', 'and', 'pqquantization']] | [-0.06573231015953761, 0.09854885616505721, -0.11995339523142176, 0.07907819505988409, -0.12181659378941254, -0.03403426909653267, 0.03103758382269799, 0.36210017575707176, -0.27331220803063105, -0.24934892352707316, 0.09288982430007309, -0.2664000283521001, -0.13708007457380247, 0.20394518247593452, 0.00036193205964046133, 0.030144448336767087, 0.02359035456239587, 0.08636350199432656, -0.15599247752827142, -0.20014727179717162, 0.38950137469438045, -0.008601343052895132, 0.22584248398716497, 0.007050206515901159, 0.1241233104812258, 0.04253739373998182, -0.05635389008808254, -0.053311731375864535, -0.13008922000535497, 0.18965152405562008, 0.20144642760866496, 0.10594435615723233, 0.20842203453625782, -0.3649344474335413, -0.16602409523127987, 0.11286423085165201, 0.10297802603794354, 0.04561518180059582, 0.0025977269956141266, -0.27527751144722545, 0.0730732651934544, -0.21297847553349958, -0.11322581618194386, -0.09201554554781996, 0.013405137534004331, 0.0632940107532362, -0.3258842351191705, 0.05905847837958291, 0.07781749381453242, 0.019128656425135265, -0.08624727774116367, -0.11035437880102361, 0.008021670093962758, 0.0963919797939903, -0.01154327749200903, 0.043809868381496996, 0.05074693749619574, -0.12817644417092278, -0.10999498821536799, 0.34581127177375265, -0.06348053888546874, -0.20649496699213096, 0.19678515871185095, -0.15610740771332737, -0.10322245447389265, 0.08348829021197882, 0.11644996473528814, 0.13645518025254258, -0.16475225180977643, 0.08823302114038903, -0.02862910347031706, 0.08258954485380414, 0.07203658233571908, 0.031002897972075064, 0.1386951176763171, 0.11203900258988142, 0.0497606281412415, 0.16885480906187308, -0.039474474549717684, -0.1227362937487588, -0.3380407160424655, -0.18217012652260536, -0.16849354104055922, 0.02734365877951841, -0.10337031311928963, -0.19095966171952758, 0.4289629391698849, 0.09204279015412425, 0.24153732823779678, 0.0637721590949038, 0.23269714298197022, 0.19788192758119968, 0.09015596839126734, 0.045090342655150904, 0.14966203043661494, 0.16557721648420584, 0.05603648693125585, -0.21500756474451557, 0.054116282279120236, 0.14270569491522886] |
1,802.04214 | Classification of minimal 1-saturating sets in PG(v, 2), 2 <= v <= 6 | The classification of all the minimal 1-saturating sets in PG(v, 2) for 2 <=
v <= 5, and the classification of the smallest and of the second smallest
minimal 1-saturating sets in PG(6, 2) are presented. These results have been
found using a computer-based exhaustive search.
| math.CO | the classification of all the minimal 1saturating sets in pgv 2 for 2 v 5 and the classification of the smallest and of the second smallest minimal 1saturating sets in pg6 2 are presented these results have been found using a computerbased exhaustive search | [['the', 'classification', 'of', 'all', 'the', 'minimal', '1saturating', 'sets', 'in', 'pgv', '2', 'for', '2', 'v', '5', 'and', 'the', 'classification', 'of', 'the', 'smallest', 'and', 'of', 'the', 'second', 'smallest', 'minimal', '1saturating', 'sets', 'in', 'pg6', '2', 'are', 'presented', 'these', 'results', 'have', 'been', 'found', 'using', 'a', 'computerbased', 'exhaustive', 'search']] | [-0.1227870415463004, 0.06378477414376861, 0.029414742275379425, 0.07362848240882158, 0.014404301824004845, -0.09428877800399828, 0.016038089795687865, 0.32430847864164863, -0.20444097127332245, -0.3551714271956751, 0.17762829191701182, -0.33757970819986144, -0.1113505715742534, 0.23981537437607903, -0.02007776347183904, 0.08098626658753601, 0.05472958999750919, 0.11212697347929311, -0.06505251130045847, -0.34135969030822433, 0.3066486154877862, -0.05033330749287162, 0.21583738748720566, 0.045243349077916425, 0.06699786643865843, -0.031156138895989158, -0.1107227933744705, 0.04939365652281531, -0.1482699677283161, 0.161666254751211, 0.23428859405197897, 0.18361618063889099, 0.22522016896238162, -0.32363829068666283, -0.1403770408658094, 0.17657239217484413, 0.12065126825947055, 0.061945751742568125, -0.03157265852530335, -0.23166083817391894, 0.23459941393500844, -0.1387610459093784, -0.06673033667598353, -0.06167689165057138, 0.09487455719432165, 0.02131869293056255, -0.23119490779936314, -0.00404782465464154, 0.07989911934317545, 0.13975141898642274, -0.06699536011153616, -0.19552749893519766, -0.04408742440864444, 0.13633149501672664, -0.05818052563361477, 0.025172207331241564, 0.0013607397762148879, -0.10436710030880085, -0.19374881121654844, 0.3970665458676427, -0.009651062988437886, -0.1965824406334134, 0.19908497902716316, -0.15919549546616021, -0.12762569708663019, 0.15167934557444654, 0.12808596297318853, 0.12855969079185364, -0.12783140731368994, 0.11771535457295994, -0.09744977050049361, 0.13534930261761643, 0.07755015592285713, -0.02841760963201523, 0.11498688603209894, 0.20728770262280174, 0.057410739844145124, 0.08853663662773405, -0.12303672458023526, 0.04164984117283724, -0.34432420515736867, -0.15281450763604668, -0.1621454947460226, 0.00023404612790706546, -0.12130379840274082, -0.13150901373389157, 0.41683572576229655, 0.09797034915103468, 0.22610677553470745, 0.07231538955035598, 0.21748082504369493, 0.017262544439629067, 0.09434462850913405, 0.10071762207202441, 0.21408245443951252, 0.056945010716485424, -0.01966284076834834, -0.15779647638894032, -0.004736437029096969, 0.06915299369152202] |
1,802.04215 | Dynamics and morphology of chiral magnetic bubbles in perpendicularly
magnetized ultra-thin films | We study bubble domain wall dynamics using micromagnetic simulations in
perpendicularly magnetized ultra-thin films with disorder and
Dzyaloshinskii-Moriya interaction. Disorder is incorporated into the material
as grains with randomly distributed sizes and varying exchange constant at the
edges. As expected, magnetic bubbles expand asymmetrically along the axis of
the in-plane field under the simultaneous application of out-of-plane and
in-plane fields. Remarkably, the shape of the bubble has a ripple-like part
which causes a kink-like (steep decrease) feature in the velocity versus
in-plane field curve. We show that these ripples originate due to the
nucleation and interaction of vertical Bloch lines. Furthermore, we show that
the Dzyaloshinskii-Moriya interaction field is not constant but rather depends
on the in-plane field. We also extend the collective coordinate model for
domain wall motion to a magnetic bubble and compare it with the results of
micromagnetic simulations.
| cond-mat.mes-hall cond-mat.mtrl-sci | we study bubble domain wall dynamics using micromagnetic simulations in perpendicularly magnetized ultrathin films with disorder and dzyaloshinskiimoriya interaction disorder is incorporated into the material as grains with randomly distributed sizes and varying exchange constant at the edges as expected magnetic bubbles expand asymmetrically along the axis of the inplane field under the simultaneous application of outofplane and inplane fields remarkably the shape of the bubble has a ripplelike part which causes a kinklike steep decrease feature in the velocity versus inplane field curve we show that these ripples originate due to the nucleation and interaction of vertical bloch lines furthermore we show that the dzyaloshinskiimoriya interaction field is not constant but rather depends on the inplane field we also extend the collective coordinate model for domain wall motion to a magnetic bubble and compare it with the results of micromagnetic simulations | [['we', 'study', 'bubble', 'domain', 'wall', 'dynamics', 'using', 'micromagnetic', 'simulations', 'in', 'perpendicularly', 'magnetized', 'ultrathin', 'films', 'with', 'disorder', 'and', 'dzyaloshinskiimoriya', 'interaction', 'disorder', 'is', 'incorporated', 'into', 'the', 'material', 'as', 'grains', 'with', 'randomly', 'distributed', 'sizes', 'and', 'varying', 'exchange', 'constant', 'at', 'the', 'edges', 'as', 'expected', 'magnetic', 'bubbles', 'expand', 'asymmetrically', 'along', 'the', 'axis', 'of', 'the', 'inplane', 'field', 'under', 'the', 'simultaneous', 'application', 'of', 'outofplane', 'and', 'inplane', 'fields', 'remarkably', 'the', 'shape', 'of', 'the', 'bubble', 'has', 'a', 'ripplelike', 'part', 'which', 'causes', 'a', 'kinklike', 'steep', 'decrease', 'feature', 'in', 'the', 'velocity', 'versus', 'inplane', 'field', 'curve', 'we', 'show', 'that', 'these', 'ripples', 'originate', 'due', 'to', 'the', 'nucleation', 'and', 'interaction', 'of', 'vertical', 'bloch', 'lines', 'furthermore', 'we', 'show', 'that', 'the', 'dzyaloshinskiimoriya', 'interaction', 'field', 'is', 'not', 'constant', 'but', 'rather', 'depends', 'on', 'the', 'inplane', 'field', 'we', 'also', 'extend', 'the', 'collective', 'coordinate', 'model', 'for', 'domain', 'wall', 'motion', 'to', 'a', 'magnetic', 'bubble', 'and', 'compare', 'it', 'with', 'the', 'results', 'of', 'micromagnetic', 'simulations']] | [-0.1915209738547507, 0.1886535520357093, -0.059673772882965305, -0.021688233037859623, -0.10382998164441488, -0.0887399458860926, 0.001015272168573779, 0.4782205139037589, -0.2886456175785984, -0.2823212668102917, 0.035026545870826174, -0.2514529570930598, -0.09902583551921056, 0.1695106652398056, 0.05610313898109844, -0.06976833346653992, 0.011931114768589728, -0.05114226393126161, -0.011182377813383937, -0.18736977126567403, 0.291899489357733, 0.007507371184953922, 0.32936563727472135, 0.08903567080999213, 0.038496977749647915, 0.0023887468580628783, 0.06738040385305435, 0.0847751671008923, -0.15807115454540316, 0.032402349514624396, 0.13153729384927354, -0.10034938092330392, 0.18810270359726544, -0.5110694522064336, -0.20047934319902683, 0.016624925774522126, 0.19691218320332782, 0.163001785408148, -0.05692211703666237, -0.27293740310640613, 0.046213669558121284, -0.11833654848274998, -0.18136508507852572, -0.03782978171849964, 0.03838502138407907, 0.06269260989928382, -0.26173946081372107, 0.10340581811176659, 0.07529073052537057, 0.09106618676311665, -0.14032321151601754, -0.06533836716995903, -0.08626033774983714, 0.04870704306505988, 0.14590041454419048, 0.11076841627831348, 0.24154188626336792, -0.13714867225900607, -0.08307515871776662, 0.36005833168500956, -0.08992874895675029, -0.16306466939793507, 0.14210431631260984, -0.17633396673711463, -0.023653372800843397, 0.16972636066141053, 0.16430271366401247, 0.07329258122514198, -0.07964357696014496, 0.08396436737622397, -0.007610408571207712, 0.1675213730753019, 0.06570159391709932, -0.022461835544189096, 0.2518886912263221, 0.1385187243773851, 0.033463872510047864, 0.18740441015893658, -0.1664174745518478, -0.09263337820663418, -0.24826259537875442, -0.13157285264247215, -0.20129852939862758, 0.027574835466585797, -0.1487214226749337, -0.21831096219502286, 0.3865027633876028, 0.1639153040440517, 0.16618573874510614, -0.027069731437581474, 0.26609127388768633, 0.04483067595340889, 0.09025053047365181, 0.08865614954880635, 0.2668500178375504, 0.1772603814057271, 0.1385746513276925, -0.2786211466193724, 0.0586745898652507, -0.030132311722591624] |
1,802.04216 | Image-based Synthesis for Deep 3D Human Pose Estimation | This paper addresses the problem of 3D human pose estimation in the wild. A
significant challenge is the lack of training data, i.e., 2D images of humans
annotated with 3D poses. Such data is necessary to train state-of-the-art CNN
architectures. Here, we propose a solution to generate a large set of
photorealistic synthetic images of humans with 3D pose annotations. We
introduce an image-based synthesis engine that artificially augments a dataset
of real images with 2D human pose annotations using 3D motion capture data.
Given a candidate 3D pose, our algorithm selects for each joint an image whose
2D pose locally matches the projected 3D pose. The selected images are then
combined to generate a new synthetic image by stitching local image patches in
a kinematically constrained manner. The resulting images are used to train an
end-to-end CNN for full-body 3D pose estimation. We cluster the training data
into a large number of pose classes and tackle pose estimation as a $K$-way
classification problem. Such an approach is viable only with large training
sets such as ours. Our method outperforms most of the published works in terms
of 3D pose estimation in controlled environments (Human3.6M) and shows
promising results for real-world images (LSP). This demonstrates that CNNs
trained on artificial images generalize well to real images. Compared to data
generated from more classical rendering engines, our synthetic images do not
require any domain adaptation or fine-tuning stage.
| cs.CV | this paper addresses the problem of 3d human pose estimation in the wild a significant challenge is the lack of training data ie 2d images of humans annotated with 3d poses such data is necessary to train stateoftheart cnn architectures here we propose a solution to generate a large set of photorealistic synthetic images of humans with 3d pose annotations we introduce an imagebased synthesis engine that artificially augments a dataset of real images with 2d human pose annotations using 3d motion capture data given a candidate 3d pose our algorithm selects for each joint an image whose 2d pose locally matches the projected 3d pose the selected images are then combined to generate a new synthetic image by stitching local image patches in a kinematically constrained manner the resulting images are used to train an endtoend cnn for fullbody 3d pose estimation we cluster the training data into a large number of pose classes and tackle pose estimation as a kway classification problem such an approach is viable only with large training sets such as ours our method outperforms most of the published works in terms of 3d pose estimation in controlled environments human36m and shows promising results for realworld images lsp this demonstrates that cnns trained on artificial images generalize well to real images compared to data generated from more classical rendering engines our synthetic images do not require any domain adaptation or finetuning stage | [['this', 'paper', 'addresses', 'the', 'problem', 'of', '3d', 'human', 'pose', 'estimation', 'in', 'the', 'wild', 'a', 'significant', 'challenge', 'is', 'the', 'lack', 'of', 'training', 'data', 'ie', '2d', 'images', 'of', 'humans', 'annotated', 'with', '3d', 'poses', 'such', 'data', 'is', 'necessary', 'to', 'train', 'stateoftheart', 'cnn', 'architectures', 'here', 'we', 'propose', 'a', 'solution', 'to', 'generate', 'a', 'large', 'set', 'of', 'photorealistic', 'synthetic', 'images', 'of', 'humans', 'with', '3d', 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1,802.04217 | A Liv\v{s}ic theorem for matrix cocycles over non-uniformly hyperbolic
systems | We prove a Liv\v{s}ic-type theorem for H\"older continuous and matrix-valued
cocycles over non-uniformly hyperbolic systems. More precisely, we prove that
whenever $(f,\mu)$ is a non-uniformly hyperbolic system and $A:M \to
GL(d,\mathbb{R}) $ is an $\alpha$-H\"{o}lder continuous map satisfying $
A(f^{n-1}(p))\ldots A(p)=\text{Id}$ for every $p\in \text{Fix}(f^n)$ and $n\in
\mathbb{N}$, there exists a measurable map $P:M\to GL(d,\mathbb{R})$ satisfying
$A(x)=P(f(x))P(x)^{-1}$ for $\mu$-almost every $x\in M$. Moreover, we prove
that whenever the measure $\mu$ has local product structure the transfer map
$P$ is $\alpha$-H\"{o}lder continuous in sets with arbitrary large measure.
| math.DS | we prove a livvsictype theorem for holder continuous and matrixvalued cocycles over nonuniformly hyperbolic systems more precisely we prove that whenever fmu is a nonuniformly hyperbolic system and am to gldmathbbr is an alphaholder continuous map satisfying afn1pldots aptextid for every pin textfixfn and nin mathbbn there exists a measurable map pmto gldmathbbr satisfying axpfxpx1 for mualmost every xin m moreover we prove that whenever the measure mu has local product structure the transfer map p is alphaholder continuous in sets with arbitrary large measure | [['we', 'prove', 'a', 'livvsictype', 'theorem', 'for', 'holder', 'continuous', 'and', 'matrixvalued', 'cocycles', 'over', 'nonuniformly', 'hyperbolic', 'systems', 'more', 'precisely', 'we', 'prove', 'that', 'whenever', 'fmu', 'is', 'a', 'nonuniformly', 'hyperbolic', 'system', 'and', 'am', 'to', 'gldmathbbr', 'is', 'an', 'alphaholder', 'continuous', 'map', 'satisfying', 'afn1pldots', 'aptextid', 'for', 'every', 'pin', 'textfixfn', 'and', 'nin', 'mathbbn', 'there', 'exists', 'a', 'measurable', 'map', 'pmto', 'gldmathbbr', 'satisfying', 'axpfxpx1', 'for', 'mualmost', 'every', 'xin', 'm', 'moreover', 'we', 'prove', 'that', 'whenever', 'the', 'measure', 'mu', 'has', 'local', 'product', 'structure', 'the', 'transfer', 'map', 'p', 'is', 'alphaholder', 'continuous', 'in', 'sets', 'with', 'arbitrary', 'large', 'measure']] | [-0.1950597229602863, 0.1316359159145577, -0.05530946141225286, 0.05084217548574088, -0.002590969527955167, -0.21467823137645609, -0.008197970257606357, 0.4030219635460526, -0.35219429577700795, -0.0571544939361047, 0.10521615116886096, -0.3432209725491703, -0.14259441894828342, 0.24364201075804887, -0.12234401667956263, 0.07834861606825143, 0.06214424117933959, 0.07657544582907576, -0.09374060164554976, -0.1636598107375903, 0.37093909151153637, -0.14678414379013702, 0.17875484678661452, 0.037484692269936205, 0.22656240850919857, 0.023231206616037524, 0.01661717224633321, -0.020679930965707173, -0.21872203646435082, 0.0290517735411413, 0.2573932744562626, 0.12321162505832035, 0.30429818961965793, -0.2601175909941958, -0.19002081238431856, 0.3121714736917056, 0.058894115791190416, -0.07424590903974604, -0.04134088934315514, -0.2763024117331952, 0.21003303340403362, -0.10629389674868435, -0.16433005644357762, -0.10337260355590842, 0.1956512168981135, 0.06287802696278959, -0.41702285249266424, -0.004017297414247878, 0.16498676318442448, 0.07595740711740291, -0.09896116669406183, -0.01977446140808752, -0.08712657856522128, 0.11101129880407826, -0.07198625193850602, 0.18255610475316644, 0.061987432272871956, 0.05400061927502975, -0.05377748743630946, 0.33549879180500286, -0.1219220341212349, -0.30327982790331587, 0.12991328444331884, -0.26403861412545665, -0.2114140258054249, 0.09984039753908291, 0.08742361172335222, 0.09924726745812222, -0.07605910744823632, 0.257641454620898, -0.13650697023840622, 0.18688890974153766, 0.1109133227961138, -0.0024352249689400195, 0.08548903221962974, 0.053967522783204915, 0.27883632662706076, 0.1085340193239972, 0.0425025042030029, 0.01954727035481483, -0.3297683409415185, -0.19254519019741564, -0.17439294343348594, 0.19923198842734563, -0.10834650609704113, -0.1975082314806059, 0.2725183056900278, 0.07309238025045488, 0.16982520527672024, 0.16714475871704054, 0.1748156852365355, 0.16406394349614856, -0.013144286986789665, 0.13431300114025363, 0.03267552254255861, 0.11977234141668305, 0.03739781567564933, -0.07371584801585414, 0.010298310860525817, 0.12919072320801206] |
1,802.04218 | Antenna Selection in Full-Duplex Cooperative NOMA Systems | We investigate the problem of antenna selection (AS) in full-duplex (FD)
cooperative non-orthogonal multiple access (NOMA) systems, where a
multi-antenna FD relay assists transmission from a multi-antenna base station
(BS) to a far user, while at the same, the BS transmits to a near user.
Specifically, based on the end-to-end signal-to-interference-plus-noise ratio
at the near and far users, two AS schemes to select a single transmit antenna
at both the BS and the relay, respectively, as well as a single receive antenna
at relay are proposed. In order to study the ergodic sum rate and outage
probability of these AS schemes, we have derived closed-form expressions
assuming Rayleigh fading channels. The sum rate and outage probability of the
AS schemes are also compared with the optimum selection scheme that maximizes
the performance as well as with a random AS scheme. Our results show that the
proposed AS schemes can deliver a near-optimal performance for near and far
users, respectively.
| cs.IT math.IT | we investigate the problem of antenna selection as in fullduplex fd cooperative nonorthogonal multiple access noma systems where a multiantenna fd relay assists transmission from a multiantenna base station bs to a far user while at the same the bs transmits to a near user specifically based on the endtoend signaltointerferenceplusnoise ratio at the near and far users two as schemes to select a single transmit antenna at both the bs and the relay respectively as well as a single receive antenna at relay are proposed in order to study the ergodic sum rate and outage probability of these as schemes we have derived closedform expressions assuming rayleigh fading channels the sum rate and outage probability of the as schemes are also compared with the optimum selection scheme that maximizes the performance as well as with a random as scheme our results show that the proposed as schemes can deliver a nearoptimal performance for near and far users respectively | [['we', 'investigate', 'the', 'problem', 'of', 'antenna', 'selection', 'as', 'in', 'fullduplex', 'fd', 'cooperative', 'nonorthogonal', 'multiple', 'access', 'noma', 'systems', 'where', 'a', 'multiantenna', 'fd', 'relay', 'assists', 'transmission', 'from', 'a', 'multiantenna', 'base', 'station', 'bs', 'to', 'a', 'far', 'user', 'while', 'at', 'the', 'same', 'the', 'bs', 'transmits', 'to', 'a', 'near', 'user', 'specifically', 'based', 'on', 'the', 'endtoend', 'signaltointerferenceplusnoise', 'ratio', 'at', 'the', 'near', 'and', 'far', 'users', 'two', 'as', 'schemes', 'to', 'select', 'a', 'single', 'transmit', 'antenna', 'at', 'both', 'the', 'bs', 'and', 'the', 'relay', 'respectively', 'as', 'well', 'as', 'a', 'single', 'receive', 'antenna', 'at', 'relay', 'are', 'proposed', 'in', 'order', 'to', 'study', 'the', 'ergodic', 'sum', 'rate', 'and', 'outage', 'probability', 'of', 'these', 'as', 'schemes', 'we', 'have', 'derived', 'closedform', 'expressions', 'assuming', 'rayleigh', 'fading', 'channels', 'the', 'sum', 'rate', 'and', 'outage', 'probability', 'of', 'the', 'as', 'schemes', 'are', 'also', 'compared', 'with', 'the', 'optimum', 'selection', 'scheme', 'that', 'maximizes', 'the', 'performance', 'as', 'well', 'as', 'with', 'a', 'random', 'as', 'scheme', 'our', 'results', 'show', 'that', 'the', 'proposed', 'as', 'schemes', 'can', 'deliver', 'a', 'nearoptimal', 'performance', 'for', 'near', 'and', 'far', 'users', 'respectively']] | [-0.2437259688411119, -0.027901809980343067, -0.002181752549730382, 0.0024805978971457333, -0.04069597772234734, -0.29759267393101313, 0.2064622363387519, 0.40034044292058396, -0.2252796046998141, -0.22797649817646676, 0.05646474742471188, -0.2810530281104382, -0.1839230614128587, 0.1355107097107472, -0.06722861652133647, 0.04477185169059151, 0.01805035364755529, 0.12410749566489421, -0.035290464023772464, -0.23544492658649413, 0.2728383928894669, 0.18255344733783285, 0.38575577518006543, -0.00020632971921619379, 0.10305791366376779, 0.030580960108705285, 0.010628883709322731, -0.044670235623353684, -0.07155088332539158, -0.0071106066249322685, 0.3790381926363744, 0.18679757015018156, 0.2649606025115874, -0.35368029788464495, -0.2647798713648094, 0.039240715137841005, 0.21826174847031915, 0.056869923118091886, -0.010391101777793711, -0.2606118537438741, 0.17504050993542158, -0.2657450071229224, -0.01357290149320784, 0.0473964739790034, -0.1325878998932411, 0.1307597704192934, -0.4275322087437102, -0.03310686293363413, -0.07131855046733886, 0.011675392441545267, -0.03758447438129956, -0.17044325917080608, 0.0007101932215451632, 0.20635623069269196, 0.06516144013489192, -0.019473979073875356, 0.0929701950389353, -0.06910136651903766, -0.13363924953540296, 0.39363316912789764, -0.02340659553422329, -0.250110216965934, 0.15728702917607185, -0.11419181545622319, -0.06058071116161234, 0.18470612524879756, 0.2823225783488754, 0.09374722374790588, -0.16307499536178396, -0.02360235200499319, -0.03967032955268269, 0.113770237113437, 0.13119618106141406, 0.18093530502193753, 0.16515673392850602, 0.1637789799697088, 0.16775138985582352, 0.11131836379784504, -0.16769989378861613, -0.10048960652729531, -0.2443968558588077, -0.10666697008136965, -0.24019161642180556, 0.024483722160166164, -0.09062072774642455, -0.03248675599834829, 0.3168579599024847, 0.07910414554732237, 0.13838375637706066, 0.16520980242844788, 0.4407450055832383, 0.13208531801158316, 0.03825637780762506, 0.14206970384953627, 0.20331171830084085, 0.0817440569740515, 0.1279479652546557, -0.24967152071361132, 0.04293678712638669, -0.006103434875232619] |
1,802.04219 | On the nature of the shape coexistence and the quantum phase transition
phenomena: lead region and Zr isotopes | The goal of this contribution is to analyze the connection between shape
coexistence and quantum phase transition, two seemingly unrelated phenomena
that share common aspects, namely, the rapid change in the ground state
structure along an isotope chain or the presence of several minima at the
mean-field level. To illustrate the similarities and differences between both
phenomena, we will focus in the Pb region, in particular in Pt and Hg isotopes,
as well as in Zr isotopes.
| nucl-th | the goal of this contribution is to analyze the connection between shape coexistence and quantum phase transition two seemingly unrelated phenomena that share common aspects namely the rapid change in the ground state structure along an isotope chain or the presence of several minima at the meanfield level to illustrate the similarities and differences between both phenomena we will focus in the pb region in particular in pt and hg isotopes as well as in zr isotopes | [['the', 'goal', 'of', 'this', 'contribution', 'is', 'to', 'analyze', 'the', 'connection', 'between', 'shape', 'coexistence', 'and', 'quantum', 'phase', 'transition', 'two', 'seemingly', 'unrelated', 'phenomena', 'that', 'share', 'common', 'aspects', 'namely', 'the', 'rapid', 'change', 'in', 'the', 'ground', 'state', 'structure', 'along', 'an', 'isotope', 'chain', 'or', 'the', 'presence', 'of', 'several', 'minima', 'at', 'the', 'meanfield', 'level', 'to', 'illustrate', 'the', 'similarities', 'and', 'differences', 'between', 'both', 'phenomena', 'we', 'will', 'focus', 'in', 'the', 'pb', 'region', 'in', 'particular', 'in', 'pt', 'and', 'hg', 'isotopes', 'as', 'well', 'as', 'in', 'zr', 'isotopes']] | [-0.09777849006720564, 0.15881075686642857, -0.04742091610519723, 0.0984749635197706, 0.02123676450898895, -0.10699236844122023, 0.08688243056115295, 0.3829259907028505, -0.2893952780536243, -0.2871118380095471, 0.02264843324906882, -0.35066701753621365, -0.1372638652373299, 0.10598579468507949, -0.018044689425657345, -0.04523646388831851, 0.007717729739651277, 0.03916850203932444, -0.1373381977628723, -0.14809789285728975, 0.3265568083515028, 0.04938555826197148, 0.31321991900248186, 0.06784119858866097, 0.0013786751652958911, -0.028430770393219087, 0.07728515246084758, 0.003839380679313432, -0.09239834521388009, 0.065717290176756, 0.2759276168033868, 0.06757993896963535, 0.21277600542835698, -0.443527892328702, -0.1810305908756246, 0.11272463402952757, 0.13550401183734226, 0.10935226861121398, -0.0742403196802895, -0.24736676037359934, 0.024164002506642954, -0.14569348955750708, -0.13441208953963132, -0.04367938099955148, 0.027364536170400196, 0.04184598648654563, -0.18784176686237408, 0.04251687128290341, 0.05331201888409189, 0.09946471700662529, -0.059334648470696694, -0.14126863989785507, -0.027376704386665257, 0.14595910061646689, 0.09177266570207264, -0.022513621539261508, 0.08872562593647412, -0.11686035688639945, -0.11392631820197423, 0.4001269107079738, -0.048075985804490455, -0.1049813793536711, 0.23778321794778495, -0.172129690368938, -0.16928903491224173, 0.12341024950388577, 0.15345635569908403, 0.07318426098964818, -0.11198034941282292, 0.05520608210588455, 0.047960881071237776, 0.14588424484789758, 0.025394396916902685, 0.0790001134291388, 0.22193931391486874, 0.16493842980292225, 0.02578338986533307, 0.12327537028264109, -0.13489529214249077, -0.20520117151998468, -0.2993610025226296, -0.17145803426815706, -0.11591937945696054, -0.030622949122221438, -0.03962653450756304, -0.1448744279158592, 0.40595149624995985, 0.12268186488920226, 0.25966661797788043, -0.07866081729374051, 0.2265518103822969, 0.03797623172459834, -0.006668326616901058, 0.0033056171861924714, 0.28034708283043336, 0.17226555896922946, 0.10944624795493754, -0.27670250292988374, 0.11217532144230488, 0.035178957900104973] |
1,802.0422 | Augment and Reduce: Stochastic Inference for Large Categorical
Distributions | Categorical distributions are ubiquitous in machine learning, e.g., in
classification, language models, and recommendation systems. However, when the
number of possible outcomes is very large, using categorical distributions
becomes computationally expensive, as the complexity scales linearly with the
number of outcomes. To address this problem, we propose augment and reduce
(A&R), a method to alleviate the computational complexity. A&R uses two ideas:
latent variable augmentation and stochastic variational inference. It maximizes
a lower bound on the marginal likelihood of the data. Unlike existing methods
which are specific to softmax, A&R is more general and is amenable to other
categorical models, such as multinomial probit. On several large-scale
classification problems, we show that A&R provides a tighter bound on the
marginal likelihood and has better predictive performance than existing
approaches.
| stat.ML cs.LG | categorical distributions are ubiquitous in machine learning eg in classification language models and recommendation systems however when the number of possible outcomes is very large using categorical distributions becomes computationally expensive as the complexity scales linearly with the number of outcomes to address this problem we propose augment and reduce ar a method to alleviate the computational complexity ar uses two ideas latent variable augmentation and stochastic variational inference it maximizes a lower bound on the marginal likelihood of the data unlike existing methods which are specific to softmax ar is more general and is amenable to other categorical models such as multinomial probit on several largescale classification problems we show that ar provides a tighter bound on the marginal likelihood and has better predictive performance than existing approaches | [['categorical', 'distributions', 'are', 'ubiquitous', 'in', 'machine', 'learning', 'eg', 'in', 'classification', 'language', 'models', 'and', 'recommendation', 'systems', 'however', 'when', 'the', 'number', 'of', 'possible', 'outcomes', 'is', 'very', 'large', 'using', 'categorical', 'distributions', 'becomes', 'computationally', 'expensive', 'as', 'the', 'complexity', 'scales', 'linearly', 'with', 'the', 'number', 'of', 'outcomes', 'to', 'address', 'this', 'problem', 'we', 'propose', 'augment', 'and', 'reduce', 'ar', 'a', 'method', 'to', 'alleviate', 'the', 'computational', 'complexity', 'ar', 'uses', 'two', 'ideas', 'latent', 'variable', 'augmentation', 'and', 'stochastic', 'variational', 'inference', 'it', 'maximizes', 'a', 'lower', 'bound', 'on', 'the', 'marginal', 'likelihood', 'of', 'the', 'data', 'unlike', 'existing', 'methods', 'which', 'are', 'specific', 'to', 'softmax', 'ar', 'is', 'more', 'general', 'and', 'is', 'amenable', 'to', 'other', 'categorical', 'models', 'such', 'as', 'multinomial', 'probit', 'on', 'several', 'largescale', 'classification', 'problems', 'we', 'show', 'that', 'ar', 'provides', 'a', 'tighter', 'bound', 'on', 'the', 'marginal', 'likelihood', 'and', 'has', 'better', 'predictive', 'performance', 'than', 'existing', 'approaches']] | [-0.005936868029444428, 0.03792574077252616, -0.06076926883858766, 0.14001998072309607, -0.14341403773169994, -0.21356973020980755, 0.05726776512469663, 0.4124741509787796, -0.27716698444109095, -0.34831148367591724, 0.0927281162956262, -0.26928527132202346, -0.1510858786862719, 0.21548853648552138, -0.16205896689130586, 0.11458098451614149, 0.0917103316837041, 0.05095876239297926, -0.09532087171755284, -0.3153403948761465, 0.30352606459759, 0.0664922407460074, 0.33712967967455704, -0.02315909841798188, 0.0844003851065239, -0.008934876805734496, -0.04481806350121087, 0.0316353697517468, -0.06684373906488005, 0.17603667370899212, 0.3020509346720493, 0.24085139200567854, 0.3548051532603396, -0.4127227226001492, -0.24100031099433816, 0.12002687846209363, 0.12626347175897226, 0.07938335269469364, 0.01836410921295769, -0.23268575088460317, 0.04230301794162843, -0.19348770758324815, 0.029459028013859145, -0.14546797402174205, -0.021749171926531682, -0.01025383874535734, -0.3263257870499348, 0.08323046480587055, 0.047467298466394574, 0.05516742905168686, -0.027770761476266524, -0.17752634449555113, 0.0259407101877669, 0.056673955936896316, 0.0792464997579683, 0.005718869546991448, 0.11268660366037038, -0.1713383522610245, -0.15348015346044544, 0.34320832160842973, -0.029189351580287112, -0.24583209707408912, 0.26200714953561394, -0.04237105310425278, -0.19478104197304666, 0.11442354847446928, 0.21847263275277476, 0.13940795369684522, -0.10482954290073253, 0.0585652580426089, -0.04613504589845737, 0.15897534778269456, -0.0011017236429042825, -0.00665695619969737, 0.13037886455575684, 0.24050375287666512, 0.10093277791341723, 0.1401216830384138, -0.13715435713421292, -0.10612218006912894, -0.20273844649394354, -0.13865485985658688, -0.19206132161856967, -0.03679418356822038, -0.1238287317420152, -0.19582125886754934, 0.3356494458009626, 0.20258894731850605, 0.21379188748163191, 0.1377686381713639, 0.3382570799728928, 0.10673818035347228, 0.0455770458333021, 0.09830634061304867, 0.14754468448958252, 0.08548252637563057, 0.06626437828594516, -0.15592780269415285, 0.1432689319115652, 0.032457778645433887] |
1,802.04221 | Let's be Honest: An Optimal No-Regret Framework for Zero-Sum Games | We revisit the problem of solving two-player zero-sum games in the
decentralized setting. We propose a simple algorithmic framework that
simultaneously achieves the best rates for honest regret as well as adversarial
regret, and in addition resolves the open problem of removing the logarithmic
terms in convergence to the value of the game. We achieve this goal in three
steps. First, we provide a novel analysis of the optimistic mirror descent
(OMD), showing that it can be modified to guarantee fast convergence for both
honest regret and value of the game, when the players are playing
collaboratively. Second, we propose a new algorithm, dubbed as robust
optimistic mirror descent (ROMD), which attains optimal adversarial regret
without knowing the time horizon beforehand. Finally, we propose a simple
signaling scheme, which enables us to bridge OMD and ROMD to achieve the best
of both worlds. Numerical examples are presented to support our theoretical
claims and show that our non-adaptive ROMD algorithm can be competitive to OMD
with adaptive step-size selection.
| cs.GT | we revisit the problem of solving twoplayer zerosum games in the decentralized setting we propose a simple algorithmic framework that simultaneously achieves the best rates for honest regret as well as adversarial regret and in addition resolves the open problem of removing the logarithmic terms in convergence to the value of the game we achieve this goal in three steps first we provide a novel analysis of the optimistic mirror descent omd showing that it can be modified to guarantee fast convergence for both honest regret and value of the game when the players are playing collaboratively second we propose a new algorithm dubbed as robust optimistic mirror descent romd which attains optimal adversarial regret without knowing the time horizon beforehand finally we propose a simple signaling scheme which enables us to bridge omd and romd to achieve the best of both worlds numerical examples are presented to support our theoretical claims and show that our nonadaptive romd algorithm can be competitive to omd with adaptive stepsize selection | [['we', 'revisit', 'the', 'problem', 'of', 'solving', 'twoplayer', 'zerosum', 'games', 'in', 'the', 'decentralized', 'setting', 'we', 'propose', 'a', 'simple', 'algorithmic', 'framework', 'that', 'simultaneously', 'achieves', 'the', 'best', 'rates', 'for', 'honest', 'regret', 'as', 'well', 'as', 'adversarial', 'regret', 'and', 'in', 'addition', 'resolves', 'the', 'open', 'problem', 'of', 'removing', 'the', 'logarithmic', 'terms', 'in', 'convergence', 'to', 'the', 'value', 'of', 'the', 'game', 'we', 'achieve', 'this', 'goal', 'in', 'three', 'steps', 'first', 'we', 'provide', 'a', 'novel', 'analysis', 'of', 'the', 'optimistic', 'mirror', 'descent', 'omd', 'showing', 'that', 'it', 'can', 'be', 'modified', 'to', 'guarantee', 'fast', 'convergence', 'for', 'both', 'honest', 'regret', 'and', 'value', 'of', 'the', 'game', 'when', 'the', 'players', 'are', 'playing', 'collaboratively', 'second', 'we', 'propose', 'a', 'new', 'algorithm', 'dubbed', 'as', 'robust', 'optimistic', 'mirror', 'descent', 'romd', 'which', 'attains', 'optimal', 'adversarial', 'regret', 'without', 'knowing', 'the', 'time', 'horizon', 'beforehand', 'finally', 'we', 'propose', 'a', 'simple', 'signaling', 'scheme', 'which', 'enables', 'us', 'to', 'bridge', 'omd', 'and', 'romd', 'to', 'achieve', 'the', 'best', 'of', 'both', 'worlds', 'numerical', 'examples', 'are', 'presented', 'to', 'support', 'our', 'theoretical', 'claims', 'and', 'show', 'that', 'our', 'nonadaptive', 'romd', 'algorithm', 'can', 'be', 'competitive', 'to', 'omd', 'with', 'adaptive', 'stepsize', 'selection']] | [-0.09288489191593337, -0.019560020135637995, -0.1114124291121871, 0.11239893038665676, -0.11056046551536947, -0.21952517076750241, 0.13302466649700018, 0.4331730968607146, -0.2707461488649382, -0.34347223755460055, 0.10619482412723646, -0.21009717387191595, -0.18610063031623472, 0.14977920129950645, -0.20838695964249337, 0.08253311086446047, 0.06181591232667588, 0.026138692003726084, 0.014536890305212833, -0.33880084749294576, 0.27242807254827184, 0.09811942830925718, 0.2402020997611717, 0.0057843081553333574, 0.15111664241772987, -0.0070454945435769675, 0.04153719110070683, 0.03803025948824749, -0.10912136151104537, 0.09948156333606069, 0.2934724961551616, 0.20022206729100572, 0.374177460336969, -0.383283915463835, -0.10860594674540196, 0.13362207082987188, 0.14653663342150616, 0.14380738280929758, -0.08080538012464308, -0.2608333050260886, 0.11431114749229025, -0.14753334115587113, -0.0605507015938028, -0.14202960188655803, -0.10543700610564667, -0.0030385232807713606, -0.37979874644883066, 0.018181012279542517, 0.06139228452021988, -0.011786488594398611, -0.03411580664881816, -0.11927685554422039, 0.08719829837459006, 0.1307854808105081, 0.06143447696896536, 0.02087293194407331, 0.09669129920352827, -0.0980435871322351, -0.2225358168943785, 0.34004339502592174, -0.09490422487232579, -0.15446754513652108, 0.13807585636857853, -0.04114613065030426, -0.12542864611549748, 0.08436412259332082, 0.20724492762903018, 0.19103932805592194, -0.1148407987040541, 0.04567959535329248, -0.08843304462719798, 0.15165182732952026, 0.047057571089161296, 0.027948100142003524, 0.07271402630223227, 0.19649670988604026, 0.2003104028657877, 0.15011890235057632, -0.030548819843153024, -0.17701828075085013, -0.3060158000984562, -0.14987806033708953, -0.14053492621418887, -0.012079258588658246, -0.13824971952895534, -0.10921470893801943, 0.3505618053459979, 0.18966618038913502, 0.1947205183927768, 0.19468705707723052, 0.34428531766336945, 0.0726172544687177, 0.0003240002053124564, 0.15896199195482213, 0.26375846604683567, 0.0386766993878631, 0.07633033166591001, -0.2467839434670861, 0.11427313250966281, 0.07649838517577986] |
1,802.04222 | A Comparative Survey of LPWA Networking | Motivated by the increasing variance of suggested Internet of Things (IoT)
applications and the lack of suitability of current wireless technologies in
scalable, long range deployments, a number of diverging Low Power Wide Area
(LPWA) technologies have been developed. These technologies promise to enable a
scalable high range network on cheap low power devices, facilitating the
development of a ubiquitous IoT. This paper provides a definition of this new
LPWA paradigm, presents a systematic approach to defined suitable use cases,
and undertakes a detailed comparison of current LPWA standards, including the
primary technologies, upcoming cellular options, and remaining proprietary
solutions.
| cs.NI | motivated by the increasing variance of suggested internet of things iot applications and the lack of suitability of current wireless technologies in scalable long range deployments a number of diverging low power wide area lpwa technologies have been developed these technologies promise to enable a scalable high range network on cheap low power devices facilitating the development of a ubiquitous iot this paper provides a definition of this new lpwa paradigm presents a systematic approach to defined suitable use cases and undertakes a detailed comparison of current lpwa standards including the primary technologies upcoming cellular options and remaining proprietary solutions | [['motivated', 'by', 'the', 'increasing', 'variance', 'of', 'suggested', 'internet', 'of', 'things', 'iot', 'applications', 'and', 'the', 'lack', 'of', 'suitability', 'of', 'current', 'wireless', 'technologies', 'in', 'scalable', 'long', 'range', 'deployments', 'a', 'number', 'of', 'diverging', 'low', 'power', 'wide', 'area', 'lpwa', 'technologies', 'have', 'been', 'developed', 'these', 'technologies', 'promise', 'to', 'enable', 'a', 'scalable', 'high', 'range', 'network', 'on', 'cheap', 'low', 'power', 'devices', 'facilitating', 'the', 'development', 'of', 'a', 'ubiquitous', 'iot', 'this', 'paper', 'provides', 'a', 'definition', 'of', 'this', 'new', 'lpwa', 'paradigm', 'presents', 'a', 'systematic', 'approach', 'to', 'defined', 'suitable', 'use', 'cases', 'and', 'undertakes', 'a', 'detailed', 'comparison', 'of', 'current', 'lpwa', 'standards', 'including', 'the', 'primary', 'technologies', 'upcoming', 'cellular', 'options', 'and', 'remaining', 'proprietary', 'solutions']] | [-0.22053768231067805, 0.02603518236428499, 0.021562143065966665, -0.002122513137292117, -0.1071655461890623, -0.15681111600250006, 0.06570896821096539, 0.35009598230943084, -0.22936146668624133, -0.3245119654946029, 0.1260744089668151, -0.23504530392587186, -0.1458293513848912, 0.3007750411517918, -0.13639205502346158, 0.11185777655337006, 0.05054303165525198, -0.08925270535517484, -0.0348196981032379, -0.19705583267495969, 0.24454531135968863, 0.1049533759476617, 0.4397495912760496, 0.11370916992425918, 0.0744334631972015, -0.026762498417519966, -0.09160973307210953, -0.010463109013962822, -0.1103916284488514, 0.23298157250508666, 0.35907377030700444, 0.20802098911110078, 0.3928363574296236, -0.453230564892292, -0.26752474539913235, 0.09208653900990611, 0.1703352421708405, 0.03724539676681161, -0.1326355373871047, -0.25908792765811084, 0.11542999335681088, -0.32239845462143424, -0.1575163378029538, -0.08431083237752318, 0.04067445634893375, 0.09192112664692104, -0.20581895690411328, -0.017913351886090823, -0.06924322254722938, 0.08719866361469031, -0.0013672413369931746, -0.10470999367069453, 0.08346774004981854, 0.16370174535084517, 0.000766280610114336, -0.015623635387746616, 0.15203339295927434, -0.1717414926039055, -0.12240390682127326, 0.34762599125504495, 0.005783978598192335, -0.09451375641277991, 0.2168641351046972, -0.04253008810337633, -0.16499443310312928, 0.08195614097639918, 0.19512065100949258, 0.07230066606716719, -0.19892109921202064, 0.08318261852837168, 0.09713219681754709, 0.14262712083756923, 0.007732467586174607, 0.1347920456645079, 0.28197295814752577, 0.30533707126975057, 0.13139302433119154, 0.07595084427855908, -0.05851069955388084, -0.08297113744542002, -0.20553359783370978, -0.16252847937867046, -0.15841676915064454, 0.05840211898903362, -0.057146517601358936, -0.16899411133490502, 0.3852912242989987, 0.20055524855968543, 0.11396842778194696, 0.04744837097590789, 0.4043054087460041, 0.019626372465863823, 0.14509285322390497, 0.04781781899742782, 0.1616038477886468, 0.07884236220503225, 0.28310406290460377, -0.08979679654352367, 0.03984521141741425, -0.06268400256056339] |
1,802.04223 | SparseMAP: Differentiable Sparse Structured Inference | Structured prediction requires searching over a combinatorial number of
structures. To tackle it, we introduce SparseMAP: a new method for sparse
structured inference, and its natural loss function. SparseMAP automatically
selects only a few global structures: it is situated between MAP inference,
which picks a single structure, and marginal inference, which assigns
probability mass to all structures, including implausible ones. Importantly,
SparseMAP can be computed using only calls to a MAP oracle, making it
applicable to problems with intractable marginal inference, e.g., linear
assignment. Sparsity makes gradient backpropagation efficient regardless of the
structure, enabling us to augment deep neural networks with generic and sparse
structured hidden layers. Experiments in dependency parsing and natural
language inference reveal competitive accuracy, improved interpretability, and
the ability to capture natural language ambiguities, which is attractive for
pipeline systems.
| stat.ML cs.CL cs.LG | structured prediction requires searching over a combinatorial number of structures to tackle it we introduce sparsemap a new method for sparse structured inference and its natural loss function sparsemap automatically selects only a few global structures it is situated between map inference which picks a single structure and marginal inference which assigns probability mass to all structures including implausible ones importantly sparsemap can be computed using only calls to a map oracle making it applicable to problems with intractable marginal inference eg linear assignment sparsity makes gradient backpropagation efficient regardless of the structure enabling us to augment deep neural networks with generic and sparse structured hidden layers experiments in dependency parsing and natural language inference reveal competitive accuracy improved interpretability and the ability to capture natural language ambiguities which is attractive for pipeline systems | [['structured', 'prediction', 'requires', 'searching', 'over', 'a', 'combinatorial', 'number', 'of', 'structures', 'to', 'tackle', 'it', 'we', 'introduce', 'sparsemap', 'a', 'new', 'method', 'for', 'sparse', 'structured', 'inference', 'and', 'its', 'natural', 'loss', 'function', 'sparsemap', 'automatically', 'selects', 'only', 'a', 'few', 'global', 'structures', 'it', 'is', 'situated', 'between', 'map', 'inference', 'which', 'picks', 'a', 'single', 'structure', 'and', 'marginal', 'inference', 'which', 'assigns', 'probability', 'mass', 'to', 'all', 'structures', 'including', 'implausible', 'ones', 'importantly', 'sparsemap', 'can', 'be', 'computed', 'using', 'only', 'calls', 'to', 'a', 'map', 'oracle', 'making', 'it', 'applicable', 'to', 'problems', 'with', 'intractable', 'marginal', 'inference', 'eg', 'linear', 'assignment', 'sparsity', 'makes', 'gradient', 'backpropagation', 'efficient', 'regardless', 'of', 'the', 'structure', 'enabling', 'us', 'to', 'augment', 'deep', 'neural', 'networks', 'with', 'generic', 'and', 'sparse', 'structured', 'hidden', 'layers', 'experiments', 'in', 'dependency', 'parsing', 'and', 'natural', 'language', 'inference', 'reveal', 'competitive', 'accuracy', 'improved', 'interpretability', 'and', 'the', 'ability', 'to', 'capture', 'natural', 'language', 'ambiguities', 'which', 'is', 'attractive', 'for', 'pipeline', 'systems']] | [-0.04851424915771654, -0.002241571298313897, -0.04498149529829232, 0.1457933553167855, -0.2154289087899196, -0.2194241622476769, 0.08718541655828481, 0.44694338443536147, -0.35801514041776866, -0.3583386943870182, 0.05737197574544281, -0.19951661537165072, -0.1864703131436523, 0.15557058835263127, -0.08529669141271777, 0.10156127447635978, 0.12224483309980871, 0.02611652370924547, -0.09486224504144047, -0.23517942812254455, 0.24732931456598106, 0.0735214110812452, 0.288053186007414, -0.03865543444668735, 0.1712073145378659, 0.015274962490257709, -0.017932069272414516, 0.01067699687624934, -0.018687005130462904, 0.21161154230861967, 0.3038080769796063, 0.22214750189042248, 0.31978678293595675, -0.3920794554721953, -0.23575551949490084, 0.10617962754644286, 0.13201150878968063, 0.10955617726179284, -0.0029840563569885135, -0.28011629524043025, 0.08782232853709095, -0.1336921803972948, 0.00567150547050996, -0.2027818363458752, -0.022190707165803483, -0.04632586586191805, -0.3543765780250125, 0.05301153352796865, 0.06159884524149403, 0.017539611656163166, -0.003201082446994677, -0.11159836972278278, 0.00072409883280521, 0.12222813753716981, 0.006171870479749432, 0.06741334379080739, 0.14071272869955803, -0.17039941423120838, -0.10050075506589917, 0.36008149664154027, -0.028778626555715923, -0.23613644423095315, 0.22983349563637331, -0.017443948230747856, -0.19717480075274552, 0.14363592708789147, 0.20392584594995228, 0.11540684238972782, -0.1509339709865249, 0.06467647317218345, -0.04438261729977858, 0.21540594466704763, 0.0815488956555891, -0.0061828914452900195, 0.20625474193453122, 0.23906922058216226, 0.09266929521308795, 0.12489312778682267, -0.09557481197016522, -0.1000508335697006, -0.19060571801695805, -0.10450852149576227, -0.14643804648797265, -0.019189607405882162, -0.1208903528292752, -0.21890260988008925, 0.3752128935015913, 0.2020202162988317, 0.2333083766644626, 0.12416229974878118, 0.2962108245258456, 0.05700122543485529, 0.12162144073465866, 0.11041323518651579, 0.13399382944760926, 0.09744779430086543, 0.056379826491830674, -0.13368546777342294, 0.13802734672773018, 0.031123554299293615] |
1,802.04224 | Large deviations for functionals of some self-similar Gaussian processes | We prove large deviation principles for $\int_0^t \gamma(X_s)ds$, where $X$
is a $d$-dimensional self-similar Gaussian process and $\gamma(x)$ takes the
form of the Dirac delta function $\delta(x)$, $|x|^{-\beta}$ with $\beta\in
(0,d)$, or $\prod_{i=1}^d |x_i|^{-\beta_i}$ with $\beta_i\in(0,1)$. In
particular, large deviations are obtained for the functionals of
$d$-dimensional fractional Brownian motion, sub-fractional Brownian motion and
bi-fractional Brownian motion. As an application, the critical exponential
integrability of the functionals is discussed.
| math.PR | we prove large deviation principles for int_0t gammax_sds where x is a ddimensional selfsimilar gaussian process and gammax takes the form of the dirac delta function deltax xbeta with betain 0d or prod_i1d x_ibeta_i with beta_iin01 in particular large deviations are obtained for the functionals of ddimensional fractional brownian motion subfractional brownian motion and bifractional brownian motion as an application the critical exponential integrability of the functionals is discussed | [['we', 'prove', 'large', 'deviation', 'principles', 'for', 'int_0t', 'gammax_sds', 'where', 'x', 'is', 'a', 'ddimensional', 'selfsimilar', 'gaussian', 'process', 'and', 'gammax', 'takes', 'the', 'form', 'of', 'the', 'dirac', 'delta', 'function', 'deltax', 'xbeta', 'with', 'betain', '0d', 'or', 'prod_i1d', 'x_ibeta_i', 'with', 'beta_iin01', 'in', 'particular', 'large', 'deviations', 'are', 'obtained', 'for', 'the', 'functionals', 'of', 'ddimensional', 'fractional', 'brownian', 'motion', 'subfractional', 'brownian', 'motion', 'and', 'bifractional', 'brownian', 'motion', 'as', 'an', 'application', 'the', 'critical', 'exponential', 'integrability', 'of', 'the', 'functionals', 'is', 'discussed']] | [-0.11018170029009608, 0.16716040476339086, -0.06279659906585673, 0.05828831864933322, -0.04399040359015943, -0.14884712975331102, -0.01688269218147704, 0.3369545630518008, -0.33079350200679264, -0.157837986663887, 0.063123137152147, -0.34818043942196353, -0.14192831909608547, 0.1742081562812073, -0.08410612426020882, 0.12084850351410834, -0.000495046253711211, 0.020044386230328008, -0.02305830567792961, -0.14062368113434676, 0.24466615836277153, -0.08551072181117805, 0.1652904196755227, -0.04873697920420179, 0.17645098944900162, 0.038399572406585016, 0.03827758443852266, -0.004031306774722356, -0.2512609892045007, 0.06469131558145763, 0.13035016777840527, -0.04939375512626474, 0.27298064501673885, -0.36815607842678827, -0.17871327671949103, 0.14129142788111826, 0.12490829477566436, -0.0195335745105915, -0.009118751605097768, -0.3521054270818378, 0.051242048061932575, -0.07600522965587901, -0.22383635485488357, -0.05844250717200339, 0.13103038857154775, 0.107116203839806, -0.3664908782776558, 0.19662996286977874, 0.12560552001620331, -7.733948895651282e-05, -0.054879232655476895, -0.18621444995656158, -0.023417228776397125, 0.04550798987673426, 0.04683122584185295, 0.07985701620098994, 0.13551004848330084, -0.09043026606157197, -0.13584078889989265, 0.42415498343832564, -0.11892581955445083, -0.3243285711064483, 0.09629263990615128, -0.25908070540224964, -0.14023504714537977, 0.11866216162558306, 0.12427947098022384, 0.10949339631549788, -0.1753199825514898, 0.24340831301929994, -0.0073778736616738816, 0.056227108209647915, 0.09216168086100934, 0.006699135004909653, 0.09725405487838681, 0.15805017168167979, 0.1121323258672474, 0.117465320269041, -0.1233423744596428, -0.1710798723630212, -0.4022726809436625, -0.21507424395531416, -0.23983950219399325, 0.1887872618249138, -0.20011687124894129, -0.2125339312196681, 0.23882589658200176, 0.053351652921375003, 0.1735375221451801, 0.12226091131963061, 0.14178100705259677, 0.24102720221201185, -0.06848439237695526, 0.07041262863342788, 0.09811709211631255, 0.12835461710170476, 0.08569420316030807, -0.15125436412706744, 0.007815183937606034, 0.11801984553070118] |
1,802.04225 | Experimental Demonstration of Multiple Monoenergetic Gamma Radiography
for Effective Atomic Number Identification in Cargo Inspection | The smuggling of special nuclear materials (SNM) through international
borders could enable nuclear terrorism and constitutes a significant threat to
global security. This paper presents the experimental demonstration of a novel
radiographic technique for quantitatively reconstructing the density and type
of material present in commercial cargo containers, as a means of detecting
such threats. Unlike traditional techniques which use sources of bremsstrahlung
photons with a continuous distribution of energies, multiple monoenergetic
gamma radiography (MMGR) utilizes monoenergetic photons from nuclear reactions,
specifically the 4.4 and 15.1 MeV photons from the
$^{11}$B(d,n$\gamma$)$^{12}$C reaction. By exploiting the $Z$-dependence of the
photon interaction cross sections at these two specific energies it is possible
to simultaneously determine the areal density and the effective atomic number
as a function of location for a 2D projection of a scanned object. The
additional information gleaned from using and detecting photons of specific
energies for radiography substantially increases the resolving power between
different materials. This paper presents results from the imaging of mock cargo
materials ranging from $Z\approx5$--$92$, demonstrating accurate reconstruction
of the effective atomic number and areal density of the materials over the full
range. In particular, the system is capable of distinguishing pure materials
with $Z\gtrsim70$, such as lead and uranium --- a critical requirement of a
system designed to detect SNM. This methodology could be used to screen
commercial cargoes with high material specificity, to distinguish most benign
materials from SNM, such as uranium and plutonium.
| physics.ins-det physics.soc-ph | the smuggling of special nuclear materials snm through international borders could enable nuclear terrorism and constitutes a significant threat to global security this paper presents the experimental demonstration of a novel radiographic technique for quantitatively reconstructing the density and type of material present in commercial cargo containers as a means of detecting such threats unlike traditional techniques which use sources of bremsstrahlung photons with a continuous distribution of energies multiple monoenergetic gamma radiography mmgr utilizes monoenergetic photons from nuclear reactions specifically the 44 and 151 mev photons from the 11bdngamma12c reaction by exploiting the zdependence of the photon interaction cross sections at these two specific energies it is possible to simultaneously determine the areal density and the effective atomic number as a function of location for a 2d projection of a scanned object the additional information gleaned from using and detecting photons of specific energies for radiography substantially increases the resolving power between different materials this paper presents results from the imaging of mock cargo materials ranging from zapprox592 demonstrating accurate reconstruction of the effective atomic number and areal density of the materials over the full range in particular the system is capable of distinguishing pure materials with zgtrsim70 such as lead and uranium a critical requirement of a system designed to detect snm this methodology could be used to screen commercial cargoes with high material specificity to distinguish most benign materials from snm such as uranium and plutonium | [['the', 'smuggling', 'of', 'special', 'nuclear', 'materials', 'snm', 'through', 'international', 'borders', 'could', 'enable', 'nuclear', 'terrorism', 'and', 'constitutes', 'a', 'significant', 'threat', 'to', 'global', 'security', 'this', 'paper', 'presents', 'the', 'experimental', 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1,802.04226 | SU(2) Chern-Simons Theory Coupled to Competing Scalars | We study a spontaneously broken SU(2) Chern-Simons-Higgs model coupled though
a Higgs portal to an uncharged triplet scalar with a vacuum state competing
with the Higgs one. We find vortex-like solutions to the field equations in
different parameter space regions. Depending on the scalar coupling constants
we find a parameter region in which the competing order creates a halo about
the Chern-Simons-Higgs vortex core, together with two other regions, one where
no vortex solutions exist, the other where ordinary Chern-Simons-Higgs vortices
can be found. We derive the low-energy theory for the moduli fields on the
vortex world sheet and also discuss the connection of our results with those
found in studies of competing orders in high temperature superconductors.
| hep-th cond-mat.str-el cond-mat.supr-con | we study a spontaneously broken su2 chernsimonshiggs model coupled though a higgs portal to an uncharged triplet scalar with a vacuum state competing with the higgs one we find vortexlike solutions to the field equations in different parameter space regions depending on the scalar coupling constants we find a parameter region in which the competing order creates a halo about the chernsimonshiggs vortex core together with two other regions one where no vortex solutions exist the other where ordinary chernsimonshiggs vortices can be found we derive the lowenergy theory for the moduli fields on the vortex world sheet and also discuss the connection of our results with those found in studies of competing orders in high temperature superconductors | [['we', 'study', 'a', 'spontaneously', 'broken', 'su2', 'chernsimonshiggs', 'model', 'coupled', 'though', 'a', 'higgs', 'portal', 'to', 'an', 'uncharged', 'triplet', 'scalar', 'with', 'a', 'vacuum', 'state', 'competing', 'with', 'the', 'higgs', 'one', 'we', 'find', 'vortexlike', 'solutions', 'to', 'the', 'field', 'equations', 'in', 'different', 'parameter', 'space', 'regions', 'depending', 'on', 'the', 'scalar', 'coupling', 'constants', 'we', 'find', 'a', 'parameter', 'region', 'in', 'which', 'the', 'competing', 'order', 'creates', 'a', 'halo', 'about', 'the', 'chernsimonshiggs', 'vortex', 'core', 'together', 'with', 'two', 'other', 'regions', 'one', 'where', 'no', 'vortex', 'solutions', 'exist', 'the', 'other', 'where', 'ordinary', 'chernsimonshiggs', 'vortices', 'can', 'be', 'found', 'we', 'derive', 'the', 'lowenergy', 'theory', 'for', 'the', 'moduli', 'fields', 'on', 'the', 'vortex', 'world', 'sheet', 'and', 'also', 'discuss', 'the', 'connection', 'of', 'our', 'results', 'with', 'those', 'found', 'in', 'studies', 'of', 'competing', 'orders', 'in', 'high', 'temperature', 'superconductors']] | [-0.18237809550759018, 0.20585382582288791, -0.0303586036621956, 0.09293941514945384, -0.09630419066870365, -0.1512569756270781, -0.012463927329162735, 0.31461177655037936, -0.20387514439703486, -0.29584409889244173, 0.06702663443224915, -0.2747429215854381, -0.0965945818086581, 0.1248667008101435, 0.05279037165154616, -0.02867017204723305, -0.02890374329951355, 0.06705622413290381, -0.06562378287899419, -0.2500364215318429, 0.36757502262875186, -0.06924562494988727, 0.2977749360883135, 0.012299523609927145, 0.06707293813223399, -0.05889718374040104, 0.047545627916776335, 0.013656660713900622, -0.19440036016058618, 0.0727351109173654, 0.21445858575230053, -0.011910530914142096, 0.16723841499000536, -0.4558188730724535, -0.2230273405547743, 0.12706336533745466, 0.16899457654000213, 0.1415612622335853, -0.05539186701367972, -0.30461902790545026, 0.03447570447056254, -0.15504338972712473, -0.16312060548166224, -0.07889742459865066, -0.03983907424351516, -0.018140559868050455, -0.2828050440224677, 0.06249361135972214, -0.020893633579716908, 0.0190839802656891, -0.09979383049580126, -0.10337460146806503, -0.07944137442628142, 0.010614707604271629, 0.15416638426960177, 0.035346979210232145, 0.11301735416449354, -0.2346502846596226, -0.1349810033866946, 0.36163251892805603, -0.11132533972692218, -0.19279449241890936, 0.1935222118864057, -0.1539737509575404, -0.1131679607413204, 0.11867109165227009, 0.11594054907149935, 0.12306223995588972, -0.07489372034541379, 0.11839369729396067, -0.06806643545169826, 0.19520714471779638, 0.04602895914655873, 0.01931850695331439, 0.2647769006000737, 0.1424656136798025, 0.05464897433422127, 0.1380687556989191, -0.0694696473360251, -0.19740793607355553, -0.3221831948228054, -0.154634699704899, -0.07498976844757543, 0.006159578418453871, -0.12150440629957919, -0.17175124252562302, 0.4004599364135035, 0.13690505163759878, 0.20608549558294156, -0.04587009155992577, 0.2261540217767075, 0.0932157030102197, 0.07062959420826223, 0.07161875736655005, 0.3040923398240643, 0.12788162593260186, 0.09690905637522149, -0.23797266861627084, -0.06996740087061741, 0.06630076133740782] |
1,802.04227 | On a conjecture of Erd\H{o}s on locally sparse Steiner triple systems | A famous theorem of Kirkman says that there exists a Steiner triple system of
order $n$ if and only if $n\equiv 1,3\mod{6}$. In 1973, Erd\H{o}s conjectured
that one can find so-called `sparse' Steiner triple systems. Roughly speaking,
the aim is to have at most $j-3$ triples on every set of $j$ points, which
would be best possible. (Triple systems with this sparseness property are also
referred to as having high girth.) We prove this conjecture asymptotically by
analysing a natural generalization of the triangle removal process. Our result
also solves a problem posed by Lefmann, Phelps and R\"odl as well as Ellis and
Linial in a strong form, and answers a question of Krivelevich, Kwan, Loh, and
Sudakov. Moreover, we pose a conjecture which would generalize the Erd\H{o}s
conjecture to Steiner systems with arbitrary parameters and provide some
evidence for this.
| math.CO | a famous theorem of kirkman says that there exists a steiner triple system of order n if and only if nequiv 13mod6 in 1973 erdhos conjectured that one can find socalled sparse steiner triple systems roughly speaking the aim is to have at most j3 triples on every set of j points which would be best possible triple systems with this sparseness property are also referred to as having high girth we prove this conjecture asymptotically by analysing a natural generalization of the triangle removal process our result also solves a problem posed by lefmann phelps and rodl as well as ellis and linial in a strong form and answers a question of krivelevich kwan loh and sudakov moreover we pose a conjecture which would generalize the erdhos conjecture to steiner systems with arbitrary parameters and provide some evidence for this | [['a', 'famous', 'theorem', 'of', 'kirkman', 'says', 'that', 'there', 'exists', 'a', 'steiner', 'triple', 'system', 'of', 'order', 'n', 'if', 'and', 'only', 'if', 'nequiv', '13mod6', 'in', '1973', 'erdhos', 'conjectured', 'that', 'one', 'can', 'find', 'socalled', 'sparse', 'steiner', 'triple', 'systems', 'roughly', 'speaking', 'the', 'aim', 'is', 'to', 'have', 'at', 'most', 'j3', 'triples', 'on', 'every', 'set', 'of', 'j', 'points', 'which', 'would', 'be', 'best', 'possible', 'triple', 'systems', 'with', 'this', 'sparseness', 'property', 'are', 'also', 'referred', 'to', 'as', 'having', 'high', 'girth', 'we', 'prove', 'this', 'conjecture', 'asymptotically', 'by', 'analysing', 'a', 'natural', 'generalization', 'of', 'the', 'triangle', 'removal', 'process', 'our', 'result', 'also', 'solves', 'a', 'problem', 'posed', 'by', 'lefmann', 'phelps', 'and', 'rodl', 'as', 'well', 'as', 'ellis', 'and', 'linial', 'in', 'a', 'strong', 'form', 'and', 'answers', 'a', 'question', 'of', 'krivelevich', 'kwan', 'loh', 'and', 'sudakov', 'moreover', 'we', 'pose', 'a', 'conjecture', 'which', 'would', 'generalize', 'the', 'erdhos', 'conjecture', 'to', 'steiner', 'systems', 'with', 'arbitrary', 'parameters', 'and', 'provide', 'some', 'evidence', 'for', 'this']] | [-0.16419932545561874, 0.07606096985816424, -0.05503502092324197, 0.08093591942832583, -0.06643015997750419, -0.19855505262301967, 0.0635635399525719, 0.27857022423496736, -0.26513079685973934, -0.3423904612793454, 0.09602819047369329, -0.2986310110909731, -0.2023133166250773, 0.16772228929081134, -0.16648163781501352, 0.0571158919258908, 0.09751874072410699, 0.017654146423904293, 0.02443904716180571, -0.3395236985807839, 0.31800094070245644, -0.0007516052540657776, 0.14302110112559083, 0.14189132356716852, 0.07767359396010372, 0.05197373527335003, 0.02165944476187828, 0.024622296199335585, -0.14330017752498472, 0.081687042946578, 0.2715402712978955, 0.1802573662533957, 0.28327011199934143, -0.28729934274846786, -0.13932984137042825, 0.151134462794289, 0.1317867063950481, 0.06643532228398337, -0.011886250073855211, -0.23503673701946223, 0.14649058204709686, -0.13376589313681636, -0.17784125748689153, -0.04181768775618236, 0.09833039688279054, -0.028985525266866066, -0.2863839801733515, 0.03476781724311877, 0.19173657687331017, 0.01496836551117927, 0.010171155846079014, -0.1204089819395449, -0.013912926552711724, 0.06917045733176305, -0.020364612154038956, 0.0873119986483029, -0.019472426088343906, -0.0581499733111871, -0.19959767292270303, 0.3687104609927961, -0.026821927005325312, -0.14601227968232705, 0.15403445215696202, -0.1214557454455644, -0.2340131228615064, 0.07194006482604891, 0.07777453174515228, 0.13309282876018966, -0.08441679098510317, 0.13215458352268408, -0.1945130863093904, 0.13313034670427443, 0.2351932475942054, -0.0016085034169788872, 0.15345629549784853, 0.08321919954448406, 0.12166021042669724, 0.13185276713671296, 0.024201737306014236, -0.008394616599876567, -0.22254272213821033, -0.13857081926627351, -0.18526729868857988, 0.13906189615538875, -0.09249927055227869, -0.18910626694227436, 0.2777148466307803, 0.11538084080343002, 0.20732359618414192, 0.0881872595454167, 0.2037659519443488, 0.08645319799387445, 0.032929738889080386, 0.15517730872878538, 0.18523372094849558, 0.18397021756307888, 0.020666553036841964, -0.12105446034859467, 0.05668007514406262, 0.1784617938433907] |
1,802.04228 | Radio outburst from a massive (proto)star. When accretion turns into
ejection | Context. Recent observations of the massive young stellar object S255 NIRS 3
have revealed a large increase in both methanol maser flux density and IR
emission, which have been interpreted as the result of an accretion outburst,
possibly due to instabilities in a circumstellar disk. This indicates that this
type of accretion event could be common in young/forming early-type stars and
in their lower mass siblings, and supports the idea that accretion onto the
star may occur in a non-continuous way. Aims. As accretion and ejection are
believed to be tightly associated phenomena, we wanted to confirm the accretion
interpretation of the outburst in S255 NIRS 3 by detecting the corresponding
burst of the associated thermal jet. Methods. We monitored the radio continuum
emission from S255 NIRS 3 at four bands using the Karl G. Jansky Very Large
Array. The millimetre continuum emission was also observed with both the
Northern Extended Millimeter Array of IRAM and the Atacama Large
Millimeter/submillimeter Array. Results. We have detected an exponential
increase in the radio flux density from 6 to 45 GHz starting right after July
10, 2016, namely about 13 months after the estimated onset of the IR outburst.
This is the first ever detection of a radio burst associated with an IR
accretion outburst from a young stellar object. The flux density at all
observed centimetre bands can be reproduced with a simple expanding jet model.
At millimetre wavelengths we infer a marginal flux increase with respect to the
literature values and we show this is due to free-free emission from the radio
jet. Abridged.
| astro-ph.SR astro-ph.GA | context recent observations of the massive young stellar object s255 nirs 3 have revealed a large increase in both methanol maser flux density and ir emission which have been interpreted as the result of an accretion outburst possibly due to instabilities in a circumstellar disk this indicates that this type of accretion event could be common in youngforming earlytype stars and in their lower mass siblings and supports the idea that accretion onto the star may occur in a noncontinuous way aims as accretion and ejection are believed to be tightly associated phenomena we wanted to confirm the accretion interpretation of the outburst in s255 nirs 3 by detecting the corresponding burst of the associated thermal jet methods we monitored the radio continuum emission from s255 nirs 3 at four bands using the karl g jansky very large array the millimetre continuum emission was also observed with both the northern extended millimeter array of iram and the atacama large millimetersubmillimeter array results we have detected an exponential increase in the radio flux density from 6 to 45 ghz starting right after july 10 2016 namely about 13 months after the estimated onset of the ir outburst this is the first ever detection of a radio burst associated with an ir accretion outburst from a young stellar object the flux density at all observed centimetre bands can be reproduced with a simple expanding jet model at millimetre wavelengths we infer a marginal flux increase with respect to the literature values and we show this is due to freefree emission from the radio jet abridged | [['context', 'recent', 'observations', 'of', 'the', 'massive', 'young', 'stellar', 'object', 's255', 'nirs', '3', 'have', 'revealed', 'a', 'large', 'increase', 'in', 'both', 'methanol', 'maser', 'flux', 'density', 'and', 'ir', 'emission', 'which', 'have', 'been', 'interpreted', 'as', 'the', 'result', 'of', 'an', 'accretion', 'outburst', 'possibly', 'due', 'to', 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1,802.04229 | Easy-Plane Magnetic Strip as a Long Josephson Junction | Spin-torque-biased magnetic dynamics in an easy-plane ferromagnet (EPF) is
theoretically studied in the presence of a weak in-plane anisotropy. While this
anisotropy spoils U(1) symmetry thereby quenching the conventional spin
superfluidity, we show that the system instead realizes a close analog of a
long Josephson junction (LJJ) model. The traditional magnetic-field and
electric-current controls of the latter map respectively onto the symmetric and
antisymmetric combinations of the out-of-plane spin torques applied at the ends
of the magnetic strip. This suggests an alternative route towards realizations
of superfluid-like transport phenomena in insulating magnetic systems. We study
spin-torque-biased phase diagram, providing an analytical solution for static
multidomain phases in the EPF. We adapt an existing self-consistency method for
the LJJ to develop an approximate solution for the EPF dynamics. The LJJ-EPF
mapping allows us to envision superconducting circuit functionality at elevated
temperatures. The results apply equally to antiferromagnets with suitable
effective free energy in terms of the N\'{e}el order instead of magnetization.
| cond-mat.mes-hall cond-mat.str-el cond-mat.supr-con | spintorquebiased magnetic dynamics in an easyplane ferromagnet epf is theoretically studied in the presence of a weak inplane anisotropy while this anisotropy spoils u1 symmetry thereby quenching the conventional spin superfluidity we show that the system instead realizes a close analog of a long josephson junction ljj model the traditional magneticfield and electriccurrent controls of the latter map respectively onto the symmetric and antisymmetric combinations of the outofplane spin torques applied at the ends of the magnetic strip this suggests an alternative route towards realizations of superfluidlike transport phenomena in insulating magnetic systems we study spintorquebiased phase diagram providing an analytical solution for static multidomain phases in the epf we adapt an existing selfconsistency method for the ljj to develop an approximate solution for the epf dynamics the ljjepf mapping allows us to envision superconducting circuit functionality at elevated temperatures the results apply equally to antiferromagnets with suitable effective free energy in terms of the neel order instead of magnetization | [['spintorquebiased', 'magnetic', 'dynamics', 'in', 'an', 'easyplane', 'ferromagnet', 'epf', 'is', 'theoretically', 'studied', 'in', 'the', 'presence', 'of', 'a', 'weak', 'inplane', 'anisotropy', 'while', 'this', 'anisotropy', 'spoils', 'u1', 'symmetry', 'thereby', 'quenching', 'the', 'conventional', 'spin', 'superfluidity', 'we', 'show', 'that', 'the', 'system', 'instead', 'realizes', 'a', 'close', 'analog', 'of', 'a', 'long', 'josephson', 'junction', 'ljj', 'model', 'the', 'traditional', 'magneticfield', 'and', 'electriccurrent', 'controls', 'of', 'the', 'latter', 'map', 'respectively', 'onto', 'the', 'symmetric', 'and', 'antisymmetric', 'combinations', 'of', 'the', 'outofplane', 'spin', 'torques', 'applied', 'at', 'the', 'ends', 'of', 'the', 'magnetic', 'strip', 'this', 'suggests', 'an', 'alternative', 'route', 'towards', 'realizations', 'of', 'superfluidlike', 'transport', 'phenomena', 'in', 'insulating', 'magnetic', 'systems', 'we', 'study', 'spintorquebiased', 'phase', 'diagram', 'providing', 'an', 'analytical', 'solution', 'for', 'static', 'multidomain', 'phases', 'in', 'the', 'epf', 'we', 'adapt', 'an', 'existing', 'selfconsistency', 'method', 'for', 'the', 'ljj', 'to', 'develop', 'an', 'approximate', 'solution', 'for', 'the', 'epf', 'dynamics', 'the', 'ljjepf', 'mapping', 'allows', 'us', 'to', 'envision', 'superconducting', 'circuit', 'functionality', 'at', 'elevated', 'temperatures', 'the', 'results', 'apply', 'equally', 'to', 'antiferromagnets', 'with', 'suitable', 'effective', 'free', 'energy', 'in', 'terms', 'of', 'the', 'neel', 'order', 'instead', 'of', 'magnetization']] | [-0.21496160869682385, 0.1486911598470093, -0.04292539015981802, 0.04402872201894665, -0.06243412501540533, -0.12290994049743957, 0.04531204893954831, 0.381641563774045, -0.266167487243226, -0.27136258944975816, 0.015670149758381022, -0.24530670059421084, -0.10046946878803027, 0.19345788906660571, 0.04231600491607858, 0.0023490303228638925, -0.054201854976445765, -0.015556667647013073, -0.11287406039465765, -0.1646556490913603, 0.2603475669366278, 0.010626465402496088, 0.3469469501951318, 0.04912249425687133, 0.08344894049505282, 0.013861531815877196, 0.13211355208727726, 0.0009929475724507288, -0.16270808676713935, 0.03100215098494367, 0.22354388969600392, -0.06565510031951081, 0.16898415289273497, -0.4690699576975624, -0.18630205306586375, 0.05078380580561066, 0.16758208597452634, 0.18721240163768885, -0.043748025123955335, -0.2815826412136103, 0.030740591537231094, -0.1651716291501074, -0.18327095954987416, -0.12115499587539749, -0.020250909249921133, -0.03215131292951584, -0.28575294785154093, 0.08610458752258301, 0.09415874412508717, 0.06822428177110851, -0.09861786973515857, -0.06207113921424303, -0.037950435926200475, 0.08220780055056427, 0.04598898837227185, 0.07576808204079509, 0.12911946415103331, -0.1329082453676802, -0.12195928452631376, 0.3152021300047636, -0.05374258996215857, -0.1559966355102481, 0.16018006321825798, -0.1220186387836988, -0.08143294161292398, 0.1445936598106151, 0.10138196526629151, 0.08294552368716972, -0.1472934567915264, 0.08145229537025166, 0.01733457739242489, 0.15756369948129104, -0.00468272144111336, 0.030800865983863356, 0.28533339467801294, 0.20159959161852836, 0.09605557328923517, 0.19825907391183648, -0.10710071884414513, -0.09990070159636011, -0.2432185847988459, -0.15777326383995735, -0.18971394947403744, 0.0558120102583057, -0.09195326777174327, -0.1801157411244241, 0.40690949516501396, 0.20491453781605337, 0.16051977548961807, -0.022417638977325172, 0.29495756529793615, 0.09672117496063565, 0.04933982607641607, 0.050956222405553364, 0.24717636329305778, 0.18618809784744766, 0.1329784076883321, -0.32947142734221974, 0.04762107100349608, 0.036808312983269906] |
1,802.0423 | Adaptive robust estimation in sparse vector model | For the sparse vector model, we consider estimation of the target vector, of
its L2-norm and of the noise variance. We construct adaptive estimators and
establish the optimal rates of adaptive estimation when adaptation is
considered with respect to the triplet "noise level - noise distribution -
sparsity". We consider classes of noise distributions with polynomially and
exponentially decreasing tails as well as the case of Gaussian noise. The
obtained rates turn out to be different from the minimax non-adaptive rates
when the triplet is known. A crucial issue is the ignorance of the noise
variance. Moreover, knowing or not knowing the noise distribution can also
influence the rate. For example, the rates of estimation of the noise variance
can differ depending on whether the noise is Gaussian or sub-Gaussian without a
precise knowledge of the distribution. Estimation of noise variance in our
setting can be viewed as an adaptive variant of robust estimation of scale in
the contamination model, where instead of fixing the "nominal" distribution in
advance, we assume that it belongs to some class of distributions.
| math.ST stat.TH | for the sparse vector model we consider estimation of the target vector of its l2norm and of the noise variance we construct adaptive estimators and establish the optimal rates of adaptive estimation when adaptation is considered with respect to the triplet noise level noise distribution sparsity we consider classes of noise distributions with polynomially and exponentially decreasing tails as well as the case of gaussian noise the obtained rates turn out to be different from the minimax nonadaptive rates when the triplet is known a crucial issue is the ignorance of the noise variance moreover knowing or not knowing the noise distribution can also influence the rate for example the rates of estimation of the noise variance can differ depending on whether the noise is gaussian or subgaussian without a precise knowledge of the distribution estimation of noise variance in our setting can be viewed as an adaptive variant of robust estimation of scale in the contamination model where instead of fixing the nominal distribution in advance we assume that it belongs to some class of distributions | [['for', 'the', 'sparse', 'vector', 'model', 'we', 'consider', 'estimation', 'of', 'the', 'target', 'vector', 'of', 'its', 'l2norm', 'and', 'of', 'the', 'noise', 'variance', 'we', 'construct', 'adaptive', 'estimators', 'and', 'establish', 'the', 'optimal', 'rates', 'of', 'adaptive', 'estimation', 'when', 'adaptation', 'is', 'considered', 'with', 'respect', 'to', 'the', 'triplet', 'noise', 'level', 'noise', 'distribution', 'sparsity', 'we', 'consider', 'classes', 'of', 'noise', 'distributions', 'with', 'polynomially', 'and', 'exponentially', 'decreasing', 'tails', 'as', 'well', 'as', 'the', 'case', 'of', 'gaussian', 'noise', 'the', 'obtained', 'rates', 'turn', 'out', 'to', 'be', 'different', 'from', 'the', 'minimax', 'nonadaptive', 'rates', 'when', 'the', 'triplet', 'is', 'known', 'a', 'crucial', 'issue', 'is', 'the', 'ignorance', 'of', 'the', 'noise', 'variance', 'moreover', 'knowing', 'or', 'not', 'knowing', 'the', 'noise', 'distribution', 'can', 'also', 'influence', 'the', 'rate', 'for', 'example', 'the', 'rates', 'of', 'estimation', 'of', 'the', 'noise', 'variance', 'can', 'differ', 'depending', 'on', 'whether', 'the', 'noise', 'is', 'gaussian', 'or', 'subgaussian', 'without', 'a', 'precise', 'knowledge', 'of', 'the', 'distribution', 'estimation', 'of', 'noise', 'variance', 'in', 'our', 'setting', 'can', 'be', 'viewed', 'as', 'an', 'adaptive', 'variant', 'of', 'robust', 'estimation', 'of', 'scale', 'in', 'the', 'contamination', 'model', 'where', 'instead', 'of', 'fixing', 'the', 'nominal', 'distribution', 'in', 'advance', 'we', 'assume', 'that', 'it', 'belongs', 'to', 'some', 'class', 'of', 'distributions']] | [-0.06983287043680074, 0.09391442938429227, -0.0680238962315528, 0.10931601305557993, -0.03142982956264063, -0.15884779852888636, 0.05555319205968309, 0.37934538154036734, -0.3027036172116838, -0.29098082431572314, 0.15796116482148126, -0.22899676939488342, -0.12527771121138276, 0.15894823881802755, -0.147503516778855, 0.06591476331626744, 0.025707567478977355, 0.08188420287885909, -0.08117894884488298, -0.2683384390376866, 0.33867860384453824, 0.10051678364707084, 0.2976052330446424, -0.06720921785260241, 0.1010885960264605, 0.02127276614465304, -0.06069358043099022, -0.014081937201731539, -0.09172916455125459, 0.07320187146917491, 0.20459778661991596, 0.12917758374459157, 0.31261310130252506, -0.3378504736159565, -0.2317544541789987, 0.1895337739103016, 0.14983416864869453, 0.1219710252316153, -0.010685049126971786, -0.2724543212094781, 0.07376242955452052, -0.13527722192216549, -0.10260557953142009, -0.05449869156167921, -0.0515663755641945, 0.06429748401824532, -0.37974944758645945, 0.12363951206901164, 0.10085199560804324, 0.015180084065107976, -0.05173064267465392, -0.17174489989529473, 0.014101960022781192, 0.14999132126597373, 0.08081870973057582, 0.00043884168676953066, 0.15720483047708786, -0.16447443198833595, -0.074906386632346, 0.31804881573360055, -0.11842223682169839, -0.2786434558509602, 0.13234644173118312, -0.1579764362192439, -0.10076484847998005, 0.12779942523598628, 0.1995750096926497, 0.08691076317139096, -0.12705942761961314, 0.08113420468335444, -0.002028077906576422, 0.1846898341062084, 0.04139545825599446, 0.08159184743950175, 0.1243166414031622, 0.1534411007917281, 0.13107098820014187, 0.15443023050461743, -0.17283769908603175, -0.07791447727862051, -0.3092761790001039, -0.10066548740559673, -0.2237973602180827, 0.038033418923088265, -0.1339259018650769, -0.17743726655588313, 0.35491535526905527, 0.18565620726111245, 0.22119475168696903, 0.0994212426834524, 0.3007690671589331, 0.1472277416634547, -0.011093556667851695, 0.07370448164578716, 0.19509123431569317, 0.12404115575939248, 0.011215415059741439, -0.21156119056161768, 0.16678241422757675, -0.023986268599154585] |
1,802.04231 | Strong nonlocality variations in a spherical mean-field dynamo | To explain the large-scale magnetic field of the Sun and other bodies,
mean-field dynamo theory is commonly applied where one solves the averaged
equations for the mean magnetic field. However, the standard approach breaks
down when the scale of the turbulent eddies becomes comparable to the scale of
the variations of the mean magnetic field. Models showing sharp magnetic field
structures have therefore been regarded as unreliable. Our aim is to look for
new effects that occur when we relax the restrictions of the standard approach,
which becomes particularly important at the bottom of the convection zone where
the size of the turbulent eddies is comparable to the depth of the convection
zone itself. We approximate the underlying integro-differential equation by a
partial differential equation corresponding to a reaction-diffusion type
equation for the mean electromotive force, making an approach that is nonlocal
in space and time feasible under conditions where spherical geometry and
nonlinearity are included. In agreement with earlier findings, spatio-temporal
nonlocality lowers the excitation conditions of the dynamo. Sharp structures
are now found to be absent. However, in the surface layers the field remains
similar to before.
| astro-ph.SR | to explain the largescale magnetic field of the sun and other bodies meanfield dynamo theory is commonly applied where one solves the averaged equations for the mean magnetic field however the standard approach breaks down when the scale of the turbulent eddies becomes comparable to the scale of the variations of the mean magnetic field models showing sharp magnetic field structures have therefore been regarded as unreliable our aim is to look for new effects that occur when we relax the restrictions of the standard approach which becomes particularly important at the bottom of the convection zone where the size of the turbulent eddies is comparable to the depth of the convection zone itself we approximate the underlying integrodifferential equation by a partial differential equation corresponding to a reactiondiffusion type equation for the mean electromotive force making an approach that is nonlocal in space and time feasible under conditions where spherical geometry and nonlinearity are included in agreement with earlier findings spatiotemporal nonlocality lowers the excitation conditions of the dynamo sharp structures are now found to be absent however in the surface layers the field remains similar to before | [['to', 'explain', 'the', 'largescale', 'magnetic', 'field', 'of', 'the', 'sun', 'and', 'other', 'bodies', 'meanfield', 'dynamo', 'theory', 'is', 'commonly', 'applied', 'where', 'one', 'solves', 'the', 'averaged', 'equations', 'for', 'the', 'mean', 'magnetic', 'field', 'however', 'the', 'standard', 'approach', 'breaks', 'down', 'when', 'the', 'scale', 'of', 'the', 'turbulent', 'eddies', 'becomes', 'comparable', 'to', 'the', 'scale', 'of', 'the', 'variations', 'of', 'the', 'mean', 'magnetic', 'field', 'models', 'showing', 'sharp', 'magnetic', 'field', 'structures', 'have', 'therefore', 'been', 'regarded', 'as', 'unreliable', 'our', 'aim', 'is', 'to', 'look', 'for', 'new', 'effects', 'that', 'occur', 'when', 'we', 'relax', 'the', 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1,802.04232 | Optimization of Fire Sales and Borrowing in Systemic Risk | This paper provides a framework for modeling financial contagion in a network
subject to fire sales and price impacts, but allowing for firms to borrow to
cover their shortfall as well. We consider both uncollateralized and
collateralized loans. The main results of this work are providing sufficient
conditions for existence and uniqueness of the clearing solutions (i.e.,
payments, liquidations, and borrowing); in such a setting any clearing solution
is the Nash equilibrium of an aggregation game.
| q-fin.MF q-fin.RM | this paper provides a framework for modeling financial contagion in a network subject to fire sales and price impacts but allowing for firms to borrow to cover their shortfall as well we consider both uncollateralized and collateralized loans the main results of this work are providing sufficient conditions for existence and uniqueness of the clearing solutions ie payments liquidations and borrowing in such a setting any clearing solution is the nash equilibrium of an aggregation game | [['this', 'paper', 'provides', 'a', 'framework', 'for', 'modeling', 'financial', 'contagion', 'in', 'a', 'network', 'subject', 'to', 'fire', 'sales', 'and', 'price', 'impacts', 'but', 'allowing', 'for', 'firms', 'to', 'borrow', 'to', 'cover', 'their', 'shortfall', 'as', 'well', 'we', 'consider', 'both', 'uncollateralized', 'and', 'collateralized', 'loans', 'the', 'main', 'results', 'of', 'this', 'work', 'are', 'providing', 'sufficient', 'conditions', 'for', 'existence', 'and', 'uniqueness', 'of', 'the', 'clearing', 'solutions', 'ie', 'payments', 'liquidations', 'and', 'borrowing', 'in', 'such', 'a', 'setting', 'any', 'clearing', 'solution', 'is', 'the', 'nash', 'equilibrium', 'of', 'an', 'aggregation', 'game']] | [-0.10384625818666168, -0.02095815675822546, -0.10597416196680187, 0.11980905412469599, -0.09210329973077598, -0.13377122892875618, 0.13615932019801172, 0.3684041654127405, -0.26519562336493674, -0.25982199410760876, 0.19117109698402746, -0.28626193446842463, -0.12268577707245161, 0.12036851440605364, -0.1555358828581551, 0.02813675361195285, 0.027793279775467358, -0.04050210971189173, 0.09700408907251824, -0.2856060182216185, 0.30601562711557273, 0.056622124056478866, 0.2401847471850679, 0.10763845271675994, 0.10044833056408127, -0.01239969552491522, -0.01605704682572794, 0.0179073697608577, -0.16886909236200154, 0.14516598531535188, 0.30406650993973017, 0.19445300199042417, 0.43279238486368404, -0.44269920064528523, -0.17354627853063376, 0.18828938411867344, 0.04016341772052998, 0.07699566339387705, -0.013852927086286639, -0.24210490207923085, 0.04195141831817301, -0.2683827542993975, -0.11167670612370498, -0.08721814063794323, -0.002675940062066442, 0.05074515075140976, -0.3759234602514066, 0.0333277902590405, 0.06705445537476121, 0.03611362812501427, -0.1358732482675757, -0.08948486702712743, -0.052703926011944485, 0.19651499170025713, 0.0994891342967381, -0.08112534054089338, 0.1296121491499147, -0.1582716341853436, -0.1633918699073164, 0.39327952143197, -0.045581085282672, -0.1657076340144206, 0.17342077796102354, -0.08321317177653423, -0.10173564789492, 0.06849632558020714, 0.20586767035389417, 0.0644158816491989, -0.19320158378564214, 0.03270640938181283, -0.06225083038014801, 0.098771416625057, 0.09791620766229339, -0.0011177479510048503, 0.17131310104129002, 0.20305944858180164, 0.20624419888726583, 0.13930726104330174, 0.00687636313102159, -0.189902102770774, -0.2913085641461964, -0.1464508038939369, -0.08743941412601423, 0.07013635986827706, -0.0884066572172359, -0.20452134194783866, 0.3745428562458408, 0.18047903530532494, 0.12892578686832598, 0.15727319007151222, 0.2678180423696942, 0.10506142682693041, -0.035354669503009827, 0.1059910454542229, 0.16003170024334012, 0.01815376947572651, 0.1630045303302866, -0.1432807782992696, 0.194917955913728, 0.003578501854606561] |
1,802.04233 | Embedding Complexity In the Data Representation Instead of In the Model:
A Case Study Using Heterogeneous Medical Data | Electronic Health Records have become popular sources of data for secondary
research, but their use is hampered by the amount of effort it takes to
overcome the sparsity, irregularity, and noise that they contain. Modern
learning architectures can remove the need for expert-driven feature
engineering, but not the need for expert-driven preprocessing to abstract away
the inherent messiness of clinical data. This preprocessing effort is often the
dominant component of a typical clinical prediction project. In this work we
propose using semantic embedding methods to directly couple the raw, messy
clinical data to downstream learning architectures with truly minimal
preprocessing. We examine this step from the perspective of capturing and
encoding complex data dependencies in the data representation instead of in the
model, which has the nice benefit of allowing downstream processing to be done
with fast, lightweight, and simple models accessible to researchers without
machine learning expertise. We demonstrate with three typical clinical
prediction tasks that the highly compressed, embedded data representations
capture a large amount of useful complexity, although in some cases the
compression is not completely lossless.
| stat.AP | electronic health records have become popular sources of data for secondary research but their use is hampered by the amount of effort it takes to overcome the sparsity irregularity and noise that they contain modern learning architectures can remove the need for expertdriven feature engineering but not the need for expertdriven preprocessing to abstract away the inherent messiness of clinical data this preprocessing effort is often the dominant component of a typical clinical prediction project in this work we propose using semantic embedding methods to directly couple the raw messy clinical data to downstream learning architectures with truly minimal preprocessing we examine this step from the perspective of capturing and encoding complex data dependencies in the data representation instead of in the model which has the nice benefit of allowing downstream processing to be done with fast lightweight and simple models accessible to researchers without machine learning expertise we demonstrate with three typical clinical prediction tasks that the highly compressed embedded data representations capture a large amount of useful complexity although in some cases the compression is not completely lossless | [['electronic', 'health', 'records', 'have', 'become', 'popular', 'sources', 'of', 'data', 'for', 'secondary', 'research', 'but', 'their', 'use', 'is', 'hampered', 'by', 'the', 'amount', 'of', 'effort', 'it', 'takes', 'to', 'overcome', 'the', 'sparsity', 'irregularity', 'and', 'noise', 'that', 'they', 'contain', 'modern', 'learning', 'architectures', 'can', 'remove', 'the', 'need', 'for', 'expertdriven', 'feature', 'engineering', 'but', 'not', 'the', 'need', 'for', 'expertdriven', 'preprocessing', 'to', 'abstract', 'away', 'the', 'inherent', 'messiness', 'of', 'clinical', 'data', 'this', 'preprocessing', 'effort', 'is', 'often', 'the', 'dominant', 'component', 'of', 'a', 'typical', 'clinical', 'prediction', 'project', 'in', 'this', 'work', 'we', 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1,802.04234 | Reanalysis of nearby open clusters using Gaia DR1/TGAS and HSOY | Open clusters have long been used to gain insights into the structure,
composition, and evolution of the Galaxy. With the large amount of stellar data
available for many clusters in the Gaia era, new techniques must be developed
for analyzing open clusters, as visual inspection of cluster color-magnitude
diagrams is no longer feasible. An automatic tool will be required to analyze
large samples of open clusters. We seek to develop an automatic
isochrone-fitting procedure to consistently determine cluster membership and
the fundamental cluster parameters. Our cluster characterization pipeline first
determined cluster membership with precise astrometry, primarily from TGAS and
HSOY. With initial cluster members established, isochrones were fitted, using a
chi-squared minimization, to the cluster photometry in order to determine
cluster mean distances, ages, and reddening. Cluster membership was also
refined based on the stellar photometry. We used multiband photometry, which
includes ASCC-2.5 BV, 2MASS JHK_s, Gaia G band. We present parameter estimates
for all 24 clusters closer than 333 pc as determined by the Catalogue of Open
Cluster Data and the Milky Way Star Clusters catalog. We find that our
parameters are consistent to those in the Milky Way Star Clusters catalog. We
demonstrate that it is feasible to develop an automated pipeline that
determines cluster parameters and membership reliably. After additional
modifications, our pipeline will be able to use Gaia DR2 as input, leading to
better cluster memberships and more accurate cluster parameters for a much
larger number of clusters.
| astro-ph.SR astro-ph.GA | open clusters have long been used to gain insights into the structure composition and evolution of the galaxy with the large amount of stellar data available for many clusters in the gaia era new techniques must be developed for analyzing open clusters as visual inspection of cluster colormagnitude diagrams is no longer feasible an automatic tool will be required to analyze large samples of open clusters we seek to develop an automatic isochronefitting procedure to consistently determine cluster membership and the fundamental cluster parameters our cluster characterization pipeline first determined cluster membership with precise astrometry primarily from tgas and hsoy with initial cluster members established isochrones were fitted using a chisquared minimization to the cluster photometry in order to determine cluster mean distances ages and reddening cluster membership was also refined based on the stellar photometry we used multiband photometry which includes ascc25 bv 2mass jhk_s gaia g band we present parameter estimates for all 24 clusters closer than 333 pc as determined by the catalogue of open cluster data and the milky way star clusters catalog we find that our parameters are consistent to those in the milky way star clusters catalog we demonstrate that it is feasible to develop an automated pipeline that determines cluster parameters and membership reliably after additional modifications our pipeline will be able to use gaia dr2 as input leading to better cluster memberships and more accurate cluster parameters for a much larger number of clusters | [['open', 'clusters', 'have', 'long', 'been', 'used', 'to', 'gain', 'insights', 'into', 'the', 'structure', 'composition', 'and', 'evolution', 'of', 'the', 'galaxy', 'with', 'the', 'large', 'amount', 'of', 'stellar', 'data', 'available', 'for', 'many', 'clusters', 'in', 'the', 'gaia', 'era', 'new', 'techniques', 'must', 'be', 'developed', 'for', 'analyzing', 'open', 'clusters', 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1,802.04235 | Sparse Reject Option Classifier Using Successive Linear Programming | In this paper, we propose an approach for learning sparse reject option
classifiers using double ramp loss $L_{dr}$. We use DC programming to find the
risk minimizer. The algorithm solves a sequence of linear programs to learn the
reject option classifier. We show that the loss $L_{dr}$ is Fisher consistent.
We also show that the excess risk of loss $L_d$ is upper bounded by the excess
risk of $L_{dr}$. We derive the generalization error bounds for the proposed
approach. We show the effectiveness of the proposed approach by experimenting
it on several real world datasets. The proposed approach not only performs
comparable to the state of the art but it also successfully learns sparse
classifiers.
| cs.LG | in this paper we propose an approach for learning sparse reject option classifiers using double ramp loss l_dr we use dc programming to find the risk minimizer the algorithm solves a sequence of linear programs to learn the reject option classifier we show that the loss l_dr is fisher consistent we also show that the excess risk of loss l_d is upper bounded by the excess risk of l_dr we derive the generalization error bounds for the proposed approach we show the effectiveness of the proposed approach by experimenting it on several real world datasets the proposed approach not only performs comparable to the state of the art but it also successfully learns sparse classifiers | [['in', 'this', 'paper', 'we', 'propose', 'an', 'approach', 'for', 'learning', 'sparse', 'reject', 'option', 'classifiers', 'using', 'double', 'ramp', 'loss', 'l_dr', 'we', 'use', 'dc', 'programming', 'to', 'find', 'the', 'risk', 'minimizer', 'the', 'algorithm', 'solves', 'a', 'sequence', 'of', 'linear', 'programs', 'to', 'learn', 'the', 'reject', 'option', 'classifier', 'we', 'show', 'that', 'the', 'loss', 'l_dr', 'is', 'fisher', 'consistent', 'we', 'also', 'show', 'that', 'the', 'excess', 'risk', 'of', 'loss', 'l_d', 'is', 'upper', 'bounded', 'by', 'the', 'excess', 'risk', 'of', 'l_dr', 'we', 'derive', 'the', 'generalization', 'error', 'bounds', 'for', 'the', 'proposed', 'approach', 'we', 'show', 'the', 'effectiveness', 'of', 'the', 'proposed', 'approach', 'by', 'experimenting', 'it', 'on', 'several', 'real', 'world', 'datasets', 'the', 'proposed', 'approach', 'not', 'only', 'performs', 'comparable', 'to', 'the', 'state', 'of', 'the', 'art', 'but', 'it', 'also', 'successfully', 'learns', 'sparse', 'classifiers']] | [-0.02542871224451, -0.04190490572680416, -0.09616717884479009, 0.12993548242476485, -0.10166045023614298, -0.15958914562007007, 0.09359693699111434, 0.42560700668305484, -0.28344996601302663, -0.30515167015078276, 0.09109502507110491, -0.2864833323527937, -0.2127675418620524, 0.21405923516709743, -0.1508433114413334, 0.09766827155734696, 0.09967815015141084, 0.05571540832195593, -0.049747956451028585, -0.33789540743050367, 0.2942262668243569, 0.045312197474033936, 0.30858245932537576, 0.029130428859397123, 0.1565738184094105, -0.009439058079505744, 0.020118111391227853, -0.003929335418228141, -0.08897058237407296, 0.16643234407124313, 0.2542281971105536, 0.22565167135275577, 0.3367917784611168, -0.3401626511517426, -0.1863208030876906, 0.12190963300754842, 0.08616554691739704, 0.08347941906021847, -0.036456323776434624, -0.27328952215611935, 0.08325091196102617, -0.20205792444859347, -0.04530438554027806, -0.14448924667161445, -0.07305708402848762, -0.044463277932094494, -0.3372642693514733, 0.06838638830636426, 0.08189590720905233, -0.0036043117244211635, -0.07989137494410185, -0.14250708873505177, 0.02405338555817371, 0.06342888223817167, 0.061312892121951214, 0.02448544330571009, 0.12923491553039007, -0.10098887629928473, -0.1659030906430891, 0.2914504415558084, -0.1301047136116287, -0.20857381048895743, 0.1505744459107518, -0.0818447793064558, -0.10551249562033817, 0.12360884402878583, 0.222813342469137, 0.11453034225041452, -0.15769548278868847, 0.05017932303168851, -0.08776329300649788, 0.17659413427033502, 0.034850511031792215, -0.031376918838561876, 0.11927885806754879, 0.21248754693762115, 0.09431040755108647, 0.17526649631883787, -0.14730123926723457, -0.0628990829800782, -0.2757470604427078, -0.10803704579239307, -0.20343996530155772, -0.03728960140028705, -0.09779655323566303, -0.14352352156002662, 0.3488516343150126, 0.2570375828639321, 0.17036683614284773, 0.17932067863724155, 0.338682017588745, 0.10777175664577796, 0.06702280356997938, 0.15954351020652963, 0.22846474200487138, 0.039086421048673596, 0.05463497812414299, -0.23558843073981772, 0.11716312751092989, 0.05314978150329451] |
1,802.04236 | Buy your coffee with bitcoin: Real-world deployment of a bitcoin point
of sale terminal | In this paper we discuss existing approaches for Bitcoin payments, as
suitable for a small business for small-value transactions. We develop an
evaluation framework utilizing security, usability, deployability criteria,,
examine several existing systems, tools. Following a requirements engineering
approach, we designed, implemented a new Point of Sale (PoS) system that
satisfies an optimal set of criteria within our evaluation framework. Our open
source system, Aunja PoS, has been deployed in a real world cafe since October
2014.
| cs.CR cs.CY cs.ET cs.HC cs.SI | in this paper we discuss existing approaches for bitcoin payments as suitable for a small business for smallvalue transactions we develop an evaluation framework utilizing security usability deployability criteria examine several existing systems tools following a requirements engineering approach we designed implemented a new point of sale pos system that satisfies an optimal set of criteria within our evaluation framework our open source system aunja pos has been deployed in a real world cafe since october 2014 | [['in', 'this', 'paper', 'we', 'discuss', 'existing', 'approaches', 'for', 'bitcoin', 'payments', 'as', 'suitable', 'for', 'a', 'small', 'business', 'for', 'smallvalue', 'transactions', 'we', 'develop', 'an', 'evaluation', 'framework', 'utilizing', 'security', 'usability', 'deployability', 'criteria', 'examine', 'several', 'existing', 'systems', 'tools', 'following', 'a', 'requirements', 'engineering', 'approach', 'we', 'designed', 'implemented', 'a', 'new', 'point', 'of', 'sale', 'pos', 'system', 'that', 'satisfies', 'an', 'optimal', 'set', 'of', 'criteria', 'within', 'our', 'evaluation', 'framework', 'our', 'open', 'source', 'system', 'aunja', 'pos', 'has', 'been', 'deployed', 'in', 'a', 'real', 'world', 'cafe', 'since', 'october', '2014']] | [-0.1418701539943485, -0.08170610923269506, -0.09268536863505449, 0.0723601633201868, -0.08704633079469204, -0.1775555998626116, 0.10906930252033482, 0.40514903058187646, -0.21427939093279602, -0.31483033925637993, 0.1418710736845816, -0.24513123994448074, -0.1643788524609255, 0.23866349727675124, -0.14814088237778233, 0.11902101651618355, 0.09612297903942435, -0.022382191547780837, -0.015729712747040474, -0.3081488522492643, 0.2948758400452789, 0.02519061788916588, 0.3604487177523735, 0.08331808048349462, 0.09395892717752997, -0.014581140357461808, -0.009138406706226402, -0.006194793515054411, -0.12810887499319124, 0.13826043103625507, 0.3167486364193457, 0.2621167139977364, 0.3792531664964228, -0.38407922153802293, -0.14647307594943987, 0.050371641599524175, 0.10298205414897223, 0.04340084226752974, -0.06660535976927924, -0.31494080321863294, 0.09658835528075303, -0.27700553249298154, -0.11672628379279845, -0.10817069663225036, -0.0002199549589453167, -0.013996807763377498, -0.27714046284458355, -0.06143421475089302, 0.0359308902407065, 0.10682101994997968, -0.04658110287824744, -0.11569505425378386, 0.06672717162444697, 0.17172406145714617, 0.009509481066886923, -0.014534544480020964, 0.16592351559819163, -0.08210682610086606, -0.21500172662107567, 0.36758525689181526, -0.024536955365635407, -0.1535860165144856, 0.1711207091452946, 0.024444653572955805, -0.22415227289801756, 0.028245180155959372, 0.25471586648583117, 0.0755889965833998, -0.25652495766744804, 0.08605474631890263, -0.05536809583243571, 0.21028016052418694, 0.052947758749053865, 0.01158801241361193, 0.1715630568306599, 0.24426541046092384, 0.06758390725544335, 0.11234702128843453, -0.02991213102972037, -0.09814236800823557, -0.28205739576859695, -0.16533024726729645, -0.11999705182633509, -0.004226040511735175, -0.04309078887423599, -0.1560228129505719, 0.3703400341695861, 0.24070011221460605, 0.07648661036632563, 0.05027720394335981, 0.3514977675176373, 0.054841625124505584, 0.04046594492061367, 0.15049527510755548, 0.19428128883928844, -0.04784911506699006, 0.21353863756245883, -0.10747213740710561, 0.09461046177832606, 0.03383629078560166] |
1,802.04237 | Quantum Spectral Curve and Structure Constants in N=4 SYM: Cusps in the
Ladder Limit | We find a massive simplification in the non-perturbative expression for the
structure constant of Wilson lines with 3 cusps when expressed in terms of the
key Quantum Spectral Curve quantities, namely Q-functions. Our calculation is
done for the configuration of 3 cusps lying in the same plane with arbitrary
angles in the ladders limit. This provides strong evidence that the Quantum
Spectral Curve is not only a highly efficient tool for finding the anomalous
dimensions but also encodes correlation functions with all wrapping corrections
taken into account to all orders in the `t Hooft coupling. We also show how to
study the insertions of scalars coupled to the Wilson lines and extend our
results for the spectrum and the structure constants to this case. We discuss
an OPE expansion of two cusps in terms of these states. Our results give
additional support to the Separation of Variables strategy in solving the
planar N=4 SYM theory.
| hep-th math-ph math.MP | we find a massive simplification in the nonperturbative expression for the structure constant of wilson lines with 3 cusps when expressed in terms of the key quantum spectral curve quantities namely qfunctions our calculation is done for the configuration of 3 cusps lying in the same plane with arbitrary angles in the ladders limit this provides strong evidence that the quantum spectral curve is not only a highly efficient tool for finding the anomalous dimensions but also encodes correlation functions with all wrapping corrections taken into account to all orders in the t hooft coupling we also show how to study the insertions of scalars coupled to the wilson lines and extend our results for the spectrum and the structure constants to this case we discuss an ope expansion of two cusps in terms of these states our results give additional support to the separation of variables strategy in solving the planar n4 sym theory | [['we', 'find', 'a', 'massive', 'simplification', 'in', 'the', 'nonperturbative', 'expression', 'for', 'the', 'structure', 'constant', 'of', 'wilson', 'lines', 'with', '3', 'cusps', 'when', 'expressed', 'in', 'terms', 'of', 'the', 'key', 'quantum', 'spectral', 'curve', 'quantities', 'namely', 'qfunctions', 'our', 'calculation', 'is', 'done', 'for', 'the', 'configuration', 'of', '3', 'cusps', 'lying', 'in', 'the', 'same', 'plane', 'with', 'arbitrary', 'angles', 'in', 'the', 'ladders', 'limit', 'this', 'provides', 'strong', 'evidence', 'that', 'the', 'quantum', 'spectral', 'curve', 'is', 'not', 'only', 'a', 'highly', 'efficient', 'tool', 'for', 'finding', 'the', 'anomalous', 'dimensions', 'but', 'also', 'encodes', 'correlation', 'functions', 'with', 'all', 'wrapping', 'corrections', 'taken', 'into', 'account', 'to', 'all', 'orders', 'in', 'the', 't', 'hooft', 'coupling', 'we', 'also', 'show', 'how', 'to', 'study', 'the', 'insertions', 'of', 'scalars', 'coupled', 'to', 'the', 'wilson', 'lines', 'and', 'extend', 'our', 'results', 'for', 'the', 'spectrum', 'and', 'the', 'structure', 'constants', 'to', 'this', 'case', 'we', 'discuss', 'an', 'ope', 'expansion', 'of', 'two', 'cusps', 'in', 'terms', 'of', 'these', 'states', 'our', 'results', 'give', 'additional', 'support', 'to', 'the', 'separation', 'of', 'variables', 'strategy', 'in', 'solving', 'the', 'planar', 'n4', 'sym', 'theory']] | [-0.16489490424433062, 0.11696996444680413, -0.06861026480553611, 0.07097549727186561, -0.025226226845575916, -0.108008059342542, 0.027673172386693617, 0.347524759317598, -0.1950573727999243, -0.27107397030978914, 0.06324371369330273, -0.27760464076493535, -0.1547141972012938, 0.17371615705591056, 0.016893244111129354, 0.017250339554682855, 0.04779647692433378, 0.022750510063563142, -0.08564917697541176, -0.2576428329684742, 0.3276935903655906, -0.0035523663380093154, 0.23443567280567462, 0.11833309368080189, 0.053123815060262716, 0.032887635353742346, -0.013035409702288527, 0.01875707719835543, -0.11358444929416779, 0.15052758951844167, 0.2364172072870837, 0.0733572852467337, 0.13266478341012714, -0.40524607932856005, -0.1957849983937077, 0.05802906104814141, 0.1905433961310454, 0.11700403120729232, 0.009577752307297722, -0.22054690819143527, 0.0595638161104533, -0.13000942775078358, -0.1847653860887212, -0.10045018591767838, 0.01705835686035214, -0.049397285878958724, -0.2779015976041856, 0.0496569175644958, 0.06321368950509255, 0.038015940599143504, -0.03622193665904624, -0.119627099210817, -0.0046163187587573646, 0.15887018793596766, 0.06970540668154436, 0.03163147189714495, 0.06066463436300476, -0.17099036795027073, -0.1305689393959549, 0.3630381587952856, -0.08984008849328083, -0.20939549804034252, 0.13822228945491294, -0.19487079656232267, -0.1853036150306223, 0.11479335147014354, 0.12061017015047612, 0.13994990612169908, -0.10690515323724192, 0.13519490568733383, -0.02175415400415659, 0.16346600280000617, 0.07688053252115365, 0.04429384804961662, 0.19350155857391654, 0.054165358791848826, 0.038196118302162615, 0.16711732759666179, -0.049847895365148304, -0.11021634843801298, -0.37165509963468196, -0.16065358819980774, -0.11687504263038957, 0.052041895409779354, -0.16302220802134534, -0.20145443440565178, 0.3861604417343774, 0.11957297258439564, 0.24427596676133334, 0.06362242314573978, 0.26684483480789967, 0.15030644364249443, 0.09381682544105475, 0.09909293597504015, 0.2340619456022978, 0.15197165211242053, 0.06662962263029429, -0.24852944501645624, -0.024730528846022583, 0.116939446008614] |
1,802.04238 | Universal lower bounds on the kinetic energy of electronic systems with
noncollinear magnetism | The distribution of noncollinear magnetism in an electronic system provides
information about the kinetic energy as well as some kinetic energy densities.
Two different everywhere-positive kinetic densities related to the
Schr\"odinger--Pauli Hamiltonian are considered. For one-electron systems
described by a single Pauli spinor, the electron density, spin density and
current density completely determines these kinetic energy densities. For
many-electron systems, lower bounds on the kinetic energy densities are proved.
These results generalize a lower bound due to von Weizs\"acker, which is based
on the electron density alone and plays an important role in density functional
theory. The results have applications in extensions of density functional
theory that incorporate noncollinear spin densities and current densities.
| physics.chem-ph cond-mat.mtrl-sci | the distribution of noncollinear magnetism in an electronic system provides information about the kinetic energy as well as some kinetic energy densities two different everywherepositive kinetic densities related to the schrodingerpauli hamiltonian are considered for oneelectron systems described by a single pauli spinor the electron density spin density and current density completely determines these kinetic energy densities for manyelectron systems lower bounds on the kinetic energy densities are proved these results generalize a lower bound due to von weizsacker which is based on the electron density alone and plays an important role in density functional theory the results have applications in extensions of density functional theory that incorporate noncollinear spin densities and current densities | [['the', 'distribution', 'of', 'noncollinear', 'magnetism', 'in', 'an', 'electronic', 'system', 'provides', 'information', 'about', 'the', 'kinetic', 'energy', 'as', 'well', 'as', 'some', 'kinetic', 'energy', 'densities', 'two', 'different', 'everywherepositive', 'kinetic', 'densities', 'related', 'to', 'the', 'schrodingerpauli', 'hamiltonian', 'are', 'considered', 'for', 'oneelectron', 'systems', 'described', 'by', 'a', 'single', 'pauli', 'spinor', 'the', 'electron', 'density', 'spin', 'density', 'and', 'current', 'density', 'completely', 'determines', 'these', 'kinetic', 'energy', 'densities', 'for', 'manyelectron', 'systems', 'lower', 'bounds', 'on', 'the', 'kinetic', 'energy', 'densities', 'are', 'proved', 'these', 'results', 'generalize', 'a', 'lower', 'bound', 'due', 'to', 'von', 'weizsacker', 'which', 'is', 'based', 'on', 'the', 'electron', 'density', 'alone', 'and', 'plays', 'an', 'important', 'role', 'in', 'density', 'functional', 'theory', 'the', 'results', 'have', 'applications', 'in', 'extensions', 'of', 'density', 'functional', 'theory', 'that', 'incorporate', 'noncollinear', 'spin', 'densities', 'and', 'current', 'densities']] | [-0.12780329599086426, 0.18819590323564464, -0.06349886835560994, 0.13816296988871543, 0.016633958539274414, -0.06066555849202307, -0.027039218893835107, 0.3058529021795345, -0.19187850231486084, -0.34622131426513725, 0.0067697069535559385, -0.2717372024745013, -0.07087227607360191, 0.1694191979260835, 0.04104227592459822, 0.04391268487459263, -0.03469823947407107, 0.04805887451156381, -0.13066887110883815, -0.17646655598985014, 0.3126383610811513, 0.08281548459709218, 0.316474631610038, 0.14639688943166582, 0.07760573314107229, 0.01826333307117158, 0.0480218233985711, 0.018956436182215677, -0.1875343897313099, 0.1296888857531831, 0.2789518041144727, 0.02697128921683334, 0.24374879452408152, -0.5055564786513559, -0.2816674550500723, -0.0043172107317147, 0.07848982001135571, 0.12103119293388506, -0.056372795033524124, -0.23910183124903556, -0.01906373125575153, -0.21884412687700405, -0.1391455005912061, -0.13111812012286578, -0.001909383930125793, 0.09225851373203033, -0.25070590676690363, 0.18581477272843497, 0.03310222745011766, -0.012960784178457956, -0.11644085699000058, -0.20596906834846543, -0.09328046361338842, 0.04674015889784931, 0.004492110405859034, 0.016830107567015938, 0.17429681656783266, -0.14659109177990956, -0.0758827770689288, 0.3183059160622348, -0.0571511144918777, -0.21929558862693013, 0.19252517325103086, -0.11551883455316446, -0.13923362799944866, 0.15239613336733485, 0.10715202229773313, 0.06401976478591034, -0.16446607641513106, 0.12890729756333785, -0.002884871382019029, 0.12972748024488048, 0.034182877576522594, 0.10285879990943106, 0.23464126990432232, 0.1096320323547167, 0.13602824619789897, 0.038685503568236544, -0.08882825059684372, -0.14503592139818763, -0.2669861561956659, -0.14832955839543036, -0.2606562173933582, 0.10118157818781591, -0.041320364596347935, -0.13654988064467743, 0.3748717355187488, 0.14632899216911963, 0.15298389809502833, -0.01516651808370762, 0.27496075879090126, 0.2370293220954296, 0.01703339890140084, 0.08735579991943937, 0.1839636722963357, 0.2548434330352409, 0.06389442503254499, -0.2527613855354422, 0.01550774030651139, 0.08396147876829568] |
1,802.04239 | Plasmonic parametric resonance | We introduce the concept of Plasmonic Parametric Resonance (PPR) as a novel
way to amplify high angular momentum plasmonic modes of nanoparticles by means
of a simple uniform optical pump. In analogy with parametric resonance in
dynamical systems, PPR originates from the temporal modulation of one of the
parameters governing the evolution of the state of the system. As opposed to
conventional localized surface plasmon resonances, we show that in principle
any plasmonic mode of arbitrarily high order is accessible by PPR with a
spatially uniform optical pump. Moreover, in contradistinction with other
mechanisms of plasmonic amplification, the coherent nature of PPR lends itself
to a more straightforward experimental detection approach. The threshold
conditions for PPR are analytically derived. Schemes of experimental
realization and detection are also discussed.
| physics.optics | we introduce the concept of plasmonic parametric resonance ppr as a novel way to amplify high angular momentum plasmonic modes of nanoparticles by means of a simple uniform optical pump in analogy with parametric resonance in dynamical systems ppr originates from the temporal modulation of one of the parameters governing the evolution of the state of the system as opposed to conventional localized surface plasmon resonances we show that in principle any plasmonic mode of arbitrarily high order is accessible by ppr with a spatially uniform optical pump moreover in contradistinction with other mechanisms of plasmonic amplification the coherent nature of ppr lends itself to a more straightforward experimental detection approach the threshold conditions for ppr are analytically derived schemes of experimental realization and detection are also discussed | [['we', 'introduce', 'the', 'concept', 'of', 'plasmonic', 'parametric', 'resonance', 'ppr', 'as', 'a', 'novel', 'way', 'to', 'amplify', 'high', 'angular', 'momentum', 'plasmonic', 'modes', 'of', 'nanoparticles', 'by', 'means', 'of', 'a', 'simple', 'uniform', 'optical', 'pump', 'in', 'analogy', 'with', 'parametric', 'resonance', 'in', 'dynamical', 'systems', 'ppr', 'originates', 'from', 'the', 'temporal', 'modulation', 'of', 'one', 'of', 'the', 'parameters', 'governing', 'the', 'evolution', 'of', 'the', 'state', 'of', 'the', 'system', 'as', 'opposed', 'to', 'conventional', 'localized', 'surface', 'plasmon', 'resonances', 'we', 'show', 'that', 'in', 'principle', 'any', 'plasmonic', 'mode', 'of', 'arbitrarily', 'high', 'order', 'is', 'accessible', 'by', 'ppr', 'with', 'a', 'spatially', 'uniform', 'optical', 'pump', 'moreover', 'in', 'contradistinction', 'with', 'other', 'mechanisms', 'of', 'plasmonic', 'amplification', 'the', 'coherent', 'nature', 'of', 'ppr', 'lends', 'itself', 'to', 'a', 'more', 'straightforward', 'experimental', 'detection', 'approach', 'the', 'threshold', 'conditions', 'for', 'ppr', 'are', 'analytically', 'derived', 'schemes', 'of', 'experimental', 'realization', 'and', 'detection', 'are', 'also', 'discussed']] | [-0.1477289124688923, 0.14914908504579216, -0.07839682503890799, 0.025616479398195224, -0.09007053998175252, -0.16214633927029354, 0.0513480836089002, 0.4085173655039398, -0.2664340288101812, -0.2560526898741955, 0.02485256503587152, -0.23562014543404075, -0.16605115823404049, 0.2354265736794332, -0.004644928256766434, 0.08025745260965778, 0.02733120981247339, -0.0034292986001673853, -0.013334813473193208, -0.13323505835251126, 0.30983936808479484, 0.05116038111009402, 0.3156429733571713, 0.03151766051996674, 0.09625571749347728, 0.0065771154786489205, 0.033124992209195625, -0.02108299186147633, -0.10646782981558545, 0.14244206595321884, 0.2608484037045855, 0.056969664994539926, 0.2489843323091918, -0.4038841846777359, -0.23921943909226684, 0.05088672265083005, 0.1813129241684237, 0.18471576700358128, -0.06735171599814294, -0.2739735689392546, 0.08505508569214726, -0.13327257853234187, -0.1752931194314442, -0.09160001399231987, -0.037150195512367645, 0.0337570096107811, -0.28241633069410454, 0.08166238178068852, 0.08540976157814839, 0.07120338192908093, -0.04418255693235551, -0.04555612469539483, -0.02037489408212423, 0.035741205757403804, -0.015381786952190168, -0.024296000694448594, 0.15151092431187863, -0.14243557103418425, -0.15222319599342882, 0.372246356127107, -0.09657534925463551, -0.1862862707239401, 0.19076005991246348, -0.15090807178785326, 3.266775456722826e-05, 0.18539242252154509, 0.18252682674574316, 0.12958280833845492, -0.11189981267807525, 0.033513583686271886, -0.006112183851655573, 0.1732516782658422, 0.07749708592746174, 0.1454088111058809, 0.20643912408559117, 0.18134488433861407, 0.058520990914985305, 0.15931749467972622, -0.1105170921437093, -0.05647043714270694, -0.27337319319485687, -0.11707789981301175, -0.19990687010499641, 0.01827925499947014, -0.07493766117966061, -0.15571723306493368, 0.40880626245052554, 0.13031241597855114, 0.19886570351809496, -0.012736719656459172, 0.3348265207314398, 0.1654568878493592, 0.06706454531376949, 0.00280032911177841, 0.30000976371229626, 0.16824790516329813, 0.06368608841512469, -0.2530149884569255, 0.019031106198781345, 0.02059616396400088] |
1,802.0424 | Reinforcement Learning for Solving the Vehicle Routing Problem | We present an end-to-end framework for solving the Vehicle Routing Problem
(VRP) using reinforcement learning. In this approach, we train a single model
that finds near-optimal solutions for problem instances sampled from a given
distribution, only by observing the reward signals and following feasibility
rules. Our model represents a parameterized stochastic policy, and by applying
a policy gradient algorithm to optimize its parameters, the trained model
produces the solution as a sequence of consecutive actions in real time,
without the need to re-train for every new problem instance. On capacitated
VRP, our approach outperforms classical heuristics and Google's OR-Tools on
medium-sized instances in solution quality with comparable computation time
(after training). We demonstrate how our approach can handle problems with
split delivery and explore the effect of such deliveries on the solution
quality. Our proposed framework can be applied to other variants of the VRP
such as the stochastic VRP, and has the potential to be applied more generally
to combinatorial optimization problems.
| cs.AI cs.LG stat.ML | we present an endtoend framework for solving the vehicle routing problem vrp using reinforcement learning in this approach we train a single model that finds nearoptimal solutions for problem instances sampled from a given distribution only by observing the reward signals and following feasibility rules our model represents a parameterized stochastic policy and by applying a policy gradient algorithm to optimize its parameters the trained model produces the solution as a sequence of consecutive actions in real time without the need to retrain for every new problem instance on capacitated vrp our approach outperforms classical heuristics and googles ortools on mediumsized instances in solution quality with comparable computation time after training we demonstrate how our approach can handle problems with split delivery and explore the effect of such deliveries on the solution quality our proposed framework can be applied to other variants of the vrp such as the stochastic vrp and has the potential to be applied more generally to combinatorial optimization problems | [['we', 'present', 'an', 'endtoend', 'framework', 'for', 'solving', 'the', 'vehicle', 'routing', 'problem', 'vrp', 'using', 'reinforcement', 'learning', 'in', 'this', 'approach', 'we', 'train', 'a', 'single', 'model', 'that', 'finds', 'nearoptimal', 'solutions', 'for', 'problem', 'instances', 'sampled', 'from', 'a', 'given', 'distribution', 'only', 'by', 'observing', 'the', 'reward', 'signals', 'and', 'following', 'feasibility', 'rules', 'our', 'model', 'represents', 'a', 'parameterized', 'stochastic', 'policy', 'and', 'by', 'applying', 'a', 'policy', 'gradient', 'algorithm', 'to', 'optimize', 'its', 'parameters', 'the', 'trained', 'model', 'produces', 'the', 'solution', 'as', 'a', 'sequence', 'of', 'consecutive', 'actions', 'in', 'real', 'time', 'without', 'the', 'need', 'to', 'retrain', 'for', 'every', 'new', 'problem', 'instance', 'on', 'capacitated', 'vrp', 'our', 'approach', 'outperforms', 'classical', 'heuristics', 'and', 'googles', 'ortools', 'on', 'mediumsized', 'instances', 'in', 'solution', 'quality', 'with', 'comparable', 'computation', 'time', 'after', 'training', 'we', 'demonstrate', 'how', 'our', 'approach', 'can', 'handle', 'problems', 'with', 'split', 'delivery', 'and', 'explore', 'the', 'effect', 'of', 'such', 'deliveries', 'on', 'the', 'solution', 'quality', 'our', 'proposed', 'framework', 'can', 'be', 'applied', 'to', 'other', 'variants', 'of', 'the', 'vrp', 'such', 'as', 'the', 'stochastic', 'vrp', 'and', 'has', 'the', 'potential', 'to', 'be', 'applied', 'more', 'generally', 'to', 'combinatorial', 'optimization', 'problems']] | [-0.05590823146606013, -0.03176864821303484, -0.08384828689148181, 0.05780497998316298, -0.12366163504361374, -0.17835479058850945, 0.09685585118738786, 0.4426489743615495, -0.3111657015807881, -0.36434070641414884, 0.11237898108869379, -0.23589109088882712, -0.18101416605930387, 0.22762365967315262, -0.12165104179836644, 0.10379427075821712, 0.12076973649987414, 0.020918470118880456, -0.02964405761098745, -0.2937715236151854, 0.27606810157992906, 0.004883628212875384, 0.27388971855012595, 0.02198278245179017, 0.1477072863336767, 0.014640677371776543, 0.039444250966696515, 0.05822317679326958, -0.048153987051742335, 0.11919766414890558, 0.28309883696507043, 0.24333024052960192, 0.35007468133056363, -0.42111016707291304, -0.22018824189764225, 0.1462843686033703, 0.11310549995660542, 0.1120018520809573, -0.06121828311604685, -0.29275754875749166, 0.09562447941090706, -0.15629571607619228, -0.03788635291536253, -0.09676876305916741, -0.04679004749728858, 0.021959019282067116, -0.3242006941299965, -0.0038044543885425923, -0.008256501229651318, -0.049611125484200345, -0.10688415646304496, -0.11546350700460786, 0.05687940141266109, 0.12444384537774361, 0.048687152216708045, 0.056533231122842045, 0.10698810675105742, -0.12994758808482554, -0.19830988430092397, 0.41371612106821287, -0.05290947391857262, -0.23271579225976136, 0.12776057740053492, 0.027051809863787305, -0.14009494285036359, 0.10828682260324984, 0.2478481511902521, 0.19417159261319078, -0.15542615372173352, 0.037316900396225344, -0.05849903435703436, 0.15767194500315843, 0.03626117646191383, -0.0648220528119445, 0.1217180517683537, 0.2511371980232695, 0.12826752782359355, 0.18579751460211627, -0.0634269312329796, -0.11927451837830748, -0.22375961667193853, -0.08341393768758816, -0.17309493844774465, -0.005485762384908697, -0.1292612674653043, -0.12996015750711634, 0.4189351783219748, 0.21256003228117615, 0.17185687904829655, 0.14982956259345714, 0.3454719228567156, 0.09467044206581827, 0.057294447012131385, 0.12385892254611809, 0.15730112567301155, -0.004812994601913482, 0.12443770721670458, -0.2195657642652492, 0.11753651196068507, 0.08262439990599006] |
1,802.04241 | Chow Rings of Vector Space Matroids | The Chow ring of a matroid (or more generally, atomic latice) is an invariant
whose importance was demonstrated by Adiprasito, Huh and Katz, who used it to
resolve the long-standing Heron-Rota-Welsh conjecture. Here, we make a detailed
study of the Chow rings of uniform matroids and of matroids of finite vector
spaces. In particular, we express the Hilbert series of such matroids in terms
of permutation statistics; in the full rank case, our formula yields the
maj-exc $q$-Eulerian polynomials of Shareshian and Wachs. We also provide a
formula for the Charney-Davis quantities of such matroids, which can be
expressed in terms of either determinants or $q$-secant numbers.
| math.CO | the chow ring of a matroid or more generally atomic latice is an invariant whose importance was demonstrated by adiprasito huh and katz who used it to resolve the longstanding heronrotawelsh conjecture here we make a detailed study of the chow rings of uniform matroids and of matroids of finite vector spaces in particular we express the hilbert series of such matroids in terms of permutation statistics in the full rank case our formula yields the majexc qeulerian polynomials of shareshian and wachs we also provide a formula for the charneydavis quantities of such matroids which can be expressed in terms of either determinants or qsecant numbers | [['the', 'chow', 'ring', 'of', 'a', 'matroid', 'or', 'more', 'generally', 'atomic', 'latice', 'is', 'an', 'invariant', 'whose', 'importance', 'was', 'demonstrated', 'by', 'adiprasito', 'huh', 'and', 'katz', 'who', 'used', 'it', 'to', 'resolve', 'the', 'longstanding', 'heronrotawelsh', 'conjecture', 'here', 'we', 'make', 'a', 'detailed', 'study', 'of', 'the', 'chow', 'rings', 'of', 'uniform', 'matroids', 'and', 'of', 'matroids', 'of', 'finite', 'vector', 'spaces', 'in', 'particular', 'we', 'express', 'the', 'hilbert', 'series', 'of', 'such', 'matroids', 'in', 'terms', 'of', 'permutation', 'statistics', 'in', 'the', 'full', 'rank', 'case', 'our', 'formula', 'yields', 'the', 'majexc', 'qeulerian', 'polynomials', 'of', 'shareshian', 'and', 'wachs', 'we', 'also', 'provide', 'a', 'formula', 'for', 'the', 'charneydavis', 'quantities', 'of', 'such', 'matroids', 'which', 'can', 'be', 'expressed', 'in', 'terms', 'of', 'either', 'determinants', 'or', 'qsecant', 'numbers']] | [-0.175743089783715, 0.0678274587917951, -0.09946464480654825, 0.08893253621090913, -0.0751230306258159, -0.09500141347359334, 0.005595672215955953, 0.29438872104067176, -0.30182714770947183, -0.2477642096778644, 0.08124074640911116, -0.21141491606609808, -0.1699218212283172, 0.18795682584334697, -0.14219524117541454, 0.02594094748298327, 0.013695341812091925, 0.04820066324817682, -0.08400753563979552, -0.3474050268176056, 0.3400095248417485, 0.04563520043378785, 0.19990390222963123, 0.08510333590120786, 0.09103021919727325, 0.0525353272665511, -0.04806236555977236, 0.02136089346881601, -0.16208522254157634, 0.15603577906731517, 0.322766833947528, 0.12847554618049237, 0.20198125597089528, -0.3999185517785095, -0.09873816864343271, 0.1684554779347742, 0.12066085586058242, 0.04466459218390463, 0.020159020773107408, -0.2227460428872811, 0.07186672143815528, -0.21514306405470485, -0.1581842539965042, -0.12153955036774278, 0.06883622381858351, 0.0681394754088528, -0.28479679459262464, 0.012725055047831986, 0.12891322728024707, 0.15107031671241636, -0.026293982796016194, -0.14456938211140888, -0.013403675800544166, 0.08268103503976904, -0.0006234863085583562, 0.043414912461524915, 0.03219256988682208, -0.09789877507303442, -0.1603859394145686, 0.38139020087463515, -0.02202553598243477, -0.22301385997395431, 0.11614728158872042, -0.17677957102035483, -0.17280172592117674, 0.09245154205709696, 0.09232843210920691, 0.18945433881072815, -0.03175569112368283, 0.09780598893329236, -0.19790496412842046, 0.07742148707399056, 0.1687339571082876, 0.030676097094657875, 0.15162739197147035, 0.025381411663034842, 0.0344984359598519, 0.1802861586867255, 0.032577801797361604, -0.030020127615647478, -0.25438486927499376, -0.22793925516307353, -0.18048456855384368, 0.0988785765954249, -0.12647148344535492, -0.20153270680457352, 0.378048035325039, 0.0654149983566077, 0.14689684603363276, 0.11186257220383379, 0.21554081158801203, 0.0797199636753205, 0.051877635566606406, 0.0336983256707234, 0.15040342452654537, 0.26700780626075965, 0.01756279950163194, -0.10978052111874734, 0.060085363388948494, 0.20896269608998583] |
1,802.04242 | Hamilton $\ell$-cycles in randomly-perturbed hypergraphs | We prove that for integers $2 \leq \ell < k$ and a small constant $c$, if a
$k$-uniform hypergraph with linear minimum codegree is randomly `perturbed' by
changing non-edges to edges independently at random with probability $p \geq
O(n^{-(k-\ell)-c})$, then with high probability the resulting $k$-uniform
hypergraph contains a Hamilton $\ell$-cycle. This complements a recent
analogous result for Hamilton $1$-cycles due to Krivelevich, Kwan and Sudakov,
and a comparable theorem in the graph case due to Bohman, Frieze and Martin.
| math.CO | we prove that for integers 2 leq ell k and a small constant c if a kuniform hypergraph with linear minimum codegree is randomly perturbed by changing nonedges to edges independently at random with probability p geq onkellc then with high probability the resulting kuniform hypergraph contains a hamilton ellcycle this complements a recent analogous result for hamilton 1cycles due to krivelevich kwan and sudakov and a comparable theorem in the graph case due to bohman frieze and martin | [['we', 'prove', 'that', 'for', 'integers', '2', 'leq', 'ell', 'k', 'and', 'a', 'small', 'constant', 'c', 'if', 'a', 'kuniform', 'hypergraph', 'with', 'linear', 'minimum', 'codegree', 'is', 'randomly', 'perturbed', 'by', 'changing', 'nonedges', 'to', 'edges', 'independently', 'at', 'random', 'with', 'probability', 'p', 'geq', 'onkellc', 'then', 'with', 'high', 'probability', 'the', 'resulting', 'kuniform', 'hypergraph', 'contains', 'a', 'hamilton', 'ellcycle', 'this', 'complements', 'a', 'recent', 'analogous', 'result', 'for', 'hamilton', '1cycles', 'due', 'to', 'krivelevich', 'kwan', 'and', 'sudakov', 'and', 'a', 'comparable', 'theorem', 'in', 'the', 'graph', 'case', 'due', 'to', 'bohman', 'frieze', 'and', 'martin']] | [-0.16757320739233342, 0.18962325638933228, -0.03404116024597524, 0.006210777168281567, -0.07377263078561579, -0.23166225986101496, 0.07312139230840004, 0.2986202613504317, -0.2546409302307532, -0.3380003373425167, 0.01994731609011069, -0.34090196245755905, -0.13408174868434286, 0.04452894796402408, -0.16057847095175815, 0.05853562879089553, 0.13972957792859048, 0.05935093927650879, 0.09352882733293928, -0.29738434123133534, 0.26972425373223347, -0.006049485244334509, 0.13523362751286, 0.09760432239048757, 0.059262682313624866, 0.09777020907793672, 0.0249102344417061, 0.06949092531337953, -0.2340571685633152, 0.0499999134753568, 0.2506332684439631, 0.11285538510240328, 0.28550977147638035, -0.33283795356953466, -0.12324634071988746, 0.21187684901703435, 0.10525254706123796, 0.053870323568564624, 0.01713617623765738, -0.22880359360267624, 0.2104492199828084, -0.06320423991658175, -0.14122739741698098, 0.029894584765992105, 0.1723216891479798, 0.014084387045258131, -0.37690749341765273, -0.006831929320469499, 0.15640928448201755, 0.01635614676305499, 0.10181379540023418, -0.2270932119900886, -0.05215912376141391, -0.008816190998260982, -0.08038275059945403, 0.1481378597479003, 0.006445370602588623, -0.07770913455393523, -0.13024963097622952, 0.31918259046207637, -0.1132097206890392, -0.1092625095998534, 0.08455075667454647, -0.16917831106230807, -0.21690901172144386, 0.1480433926320611, 0.06308652372218859, 0.15472077393235686, -0.038967177200202756, 0.1774805346593404, -0.15601024830427307, 0.10157805136763133, 0.23613518681854773, 0.01348927386630422, 0.07478433990707764, 0.039703956443983585, 0.17692997574042052, 0.15666659087396395, 0.044777797224620976, 0.04938373569614039, -0.2577802646809664, -0.07367962129557362, -0.24757707169136176, 0.16003904431365812, -0.19882479945170836, -0.1515820699218565, 0.34474880076371706, 0.07255246723369242, 0.2195300641006981, 0.15397963725412503, 0.18928866144508505, 0.06811882188925758, -0.03424750731881851, 0.22690680788423961, 0.09138261505330984, 0.2711850899205997, -0.0056854964544375735, -0.14413837684939304, 0.041405085216049485, 0.1688539979274934] |
1,802.04243 | GPU implementation of algorithm SIMPLE-TS for calculation of unsteady,
viscous, compressible and heat-conductive gas flows | The recent trend of using Graphics Processing Units (GPU's) for high
performance computations is driven by the high ratio of price performance for
these units, complemented by their cost effectiveness. At first glance,
computational fluid dynamics (CFD) solvers match perfectly to GPU resources
because these solvers make intensive calculations and use relatively little
memory. Nevertheless, there are scarce results about the practical use of this
serious advantage of GPU over CPU, especially for calculations of viscous,
compressible, heat-conductive gas flows with double precision accuracy. In this
paper, two GPU algorithms according to time approximation of convective terms
were presented: explicit and implicit scheme. To decrease data transfers
between device memories and increase the arithmetic intensity of a GPU code we
minimize the number of kernels. The GPU algorithm was implemented in one kernel
for the implicit scheme and two kernels for the explicit scheme. The numerical
equations were put together using macros and optimization, data copy from
global to private memory, and data reuse were left to the compiler. Thus keeps
the code simpler with excellent maintenance. As a test case, we model the flow
past squares in a microchannel at supersonic speed. The tests show that overall
speedup of AMD Radeon R9 280X is up to 102x compared to Intel Core i5-4690 core
and up to 184x compared to Intel Core i7-920 core, while speedup of NVIDIA
Tesla M2090 is up to 11x compared to Intel Core i5-4690 core and up to 20x
compared to Intel Core i7-920 core. Memory requirements of GPU code are
improved compared to CPU one. It requires 1[GB] global memory for 5.9 million
finite volumes that are two times less compared to C++ CPU code. After all the
code is simple, portable (written in OpenCL), memory efficient and easily
modifiable moreover demonstrates excellent performance.
| cs.CE cs.MS | the recent trend of using graphics processing units gpus for high performance computations is driven by the high ratio of price performance for these units complemented by their cost effectiveness at first glance computational fluid dynamics cfd solvers match perfectly to gpu resources because these solvers make intensive calculations and use relatively little memory nevertheless there are scarce results about the practical use of this serious advantage of gpu over cpu especially for calculations of viscous compressible heatconductive gas flows with double precision accuracy in this paper two gpu algorithms according to time approximation of convective terms were presented explicit and implicit scheme to decrease data transfers between device memories and increase the arithmetic intensity of a gpu code we minimize the number of kernels the gpu algorithm was implemented in one kernel for the implicit scheme and two kernels for the explicit scheme the numerical equations were put together using macros and optimization data copy from global to private memory and data reuse were left to the compiler thus keeps the code simpler with excellent maintenance as a test case we model the flow past squares in a microchannel at supersonic speed the tests show that overall speedup of amd radeon r9 280x is up to 102x compared to intel core i54690 core and up to 184x compared to intel core i7920 core while speedup of nvidia tesla m2090 is up to 11x compared to intel core i54690 core and up to 20x compared to intel core i7920 core memory requirements of gpu code are improved compared to cpu one it requires 1gb global memory for 59 million finite volumes that are two times less compared to c cpu code after all the code is simple portable written in opencl memory efficient and easily modifiable moreover demonstrates excellent performance | [['the', 'recent', 'trend', 'of', 'using', 'graphics', 'processing', 'units', 'gpus', 'for', 'high', 'performance', 'computations', 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1,802.04244 | Uniqueness of isometric immersions with the same mean curvature | Motivated by the quasi-local mass problem in general relativity, we study the
rigidity of isometric immersions with the same mean curvature into a warped
product space. As a corollary of our main result, two star-shaped hypersurfaces
in a spatial Schwarzschild or AdS-Schwarzschild manifold with nonzero mass
differ only by a rotation if they are isometric and have the same mean
curvature. We also give similar results if the mean curvature condition is
replaced by an $\sigma_2$-curvature condition.
| math.DG gr-qc math.AP | motivated by the quasilocal mass problem in general relativity we study the rigidity of isometric immersions with the same mean curvature into a warped product space as a corollary of our main result two starshaped hypersurfaces in a spatial schwarzschild or adsschwarzschild manifold with nonzero mass differ only by a rotation if they are isometric and have the same mean curvature we also give similar results if the mean curvature condition is replaced by an sigma_2curvature condition | [['motivated', 'by', 'the', 'quasilocal', 'mass', 'problem', 'in', 'general', 'relativity', 'we', 'study', 'the', 'rigidity', 'of', 'isometric', 'immersions', 'with', 'the', 'same', 'mean', 'curvature', 'into', 'a', 'warped', 'product', 'space', 'as', 'a', 'corollary', 'of', 'our', 'main', 'result', 'two', 'starshaped', 'hypersurfaces', 'in', 'a', 'spatial', 'schwarzschild', 'or', 'adsschwarzschild', 'manifold', 'with', 'nonzero', 'mass', 'differ', 'only', 'by', 'a', 'rotation', 'if', 'they', 'are', 'isometric', 'and', 'have', 'the', 'same', 'mean', 'curvature', 'we', 'also', 'give', 'similar', 'results', 'if', 'the', 'mean', 'curvature', 'condition', 'is', 'replaced', 'by', 'an', 'sigma_2curvature', 'condition']] | [-0.15531122099075997, 0.1422351560173269, -0.0726380909055278, 0.0953476266261166, -0.07806050479895883, -0.13572388002044194, -0.09129775159194001, 0.3540695446253113, -0.2204121890925355, -0.2675093792911087, 0.11794305684395714, -0.2516445081995486, -0.13039302723421775, 0.13872017760688513, -0.1692507156086239, 0.0032487183048801084, 0.06879651934730929, 0.11775466086125219, -0.12190907769957436, -0.24389130900335776, 0.4381521814926104, -0.007837127821592542, 0.1836970780020604, 0.08373810492558767, 0.10126713997769085, -0.019579833125477876, 0.031182948270111116, 0.09574053501793449, -0.23037033692280484, 0.06812459741516474, 0.14804759955444893, 0.09356719745147683, 0.245131355141858, -0.3717348294260053, -0.21913333166414847, 0.16490212896862974, 0.13188708074052224, 0.0487126223017256, -0.07013536056552033, -0.31603816420130143, 0.06220461321123815, -0.09375821198518207, -0.17871565388080168, -0.047150531771604894, 0.00033903373979854505, -0.04307538334751961, -0.2070221235951433, 0.13169724677724146, 0.13512152660783236, 0.04497229244390672, -0.14753923861479218, -0.07945179049373156, -0.10711859988786473, 0.09127357653221237, 0.1176795227447065, 0.0777148504094402, 0.0995667465998755, -0.03317801162068333, -0.069008538680901, 0.3739235106819346, -0.13404425904578107, -0.3142812762699731, 0.07124772453801585, -0.18600892941482583, -0.1175420951376391, 0.10970170173927077, 0.13856804598267977, 0.1910247839745376, -0.10335446115244519, 0.1313782169736087, -0.07704886761433505, 0.08556306981421136, 0.13984460305640256, -0.0151011769126121, 0.20202061653367015, 0.0888758943137991, 0.1486345048201597, 0.11086833681729803, 0.0036079108582011293, -0.05954774076046495, -0.36727136189674403, -0.1969214100307519, -0.1862889425345249, 0.15898206110366367, -0.18882551493539698, -0.15369972609007707, 0.3465882278676447, -0.0031097644165932357, 0.2423308098616151, 0.14454027937797756, 0.27699820261884045, 0.05013462509536608, 0.06990778106325246, 0.13765528516892295, 0.27688629488617955, 0.19873559783067699, 0.032428530117424276, -0.12261432365744145, -0.05932339361880894, 0.12883139101715832] |
1,802.04245 | Scalarization Methods for Many-Objective Virtual Machine Placement of
Elastic Infrastructures in Overbooked Cloud Computing Data Centers Under
Uncertainty | Cloud computing datacenters provide thousands to millions of virtual machines
(VMs) on-demand in highly dynamic environments, requiring quick placement of
requested VMs into available physical machines (PMs). Due to the randomness of
customer requests, the Virtual Machine Placement (VMP) should be formulated as
an online optimization problem.
The first part of this work analyzes alternatives to solve the formulated
problem, an experimental comparison of five different online deterministic
heuristics against an offline memetic algorithm with migration of VMs was
performed, considering several experimental workloads. Simulations indicate
that First-Fit Decreasing algorithm (A4) outperforms other evaluated heuristics
on average.
This work presents a two-phase schema formulation of a VMP problem
considering the optimization of three objective functions in an IaaS
environment with elasticity and overbooking capabilities. The two-phase schema
formulation describes that the allocation of the VMs can be separated into two
sub-problems, the incremental allocation (iVMP) and the reconfiguration of a
placement (VMPr).
To analyze alternatives to solve the formulated problem, an experimental
comparison of three different objective function scalarization methods as part
of the iVMP and VMPr was performed considering several experimental workloads.
Simulations indicate that the Euclidean distance to origin outperforms other
evaluated scalarization methods on average.
In order to portray the dynamic nature of an IaaS environment a customizable
workload trace generator was developed to simulate uncertainty in the scenarios
with elasticity and overbooking of resources in VM requests.
Experimental results proved that the Euclidean distance is preferable over
the other scalarizatiom methods to improve the values of the power consumption
objective function.
| cs.DC | cloud computing datacenters provide thousands to millions of virtual machines vms ondemand in highly dynamic environments requiring quick placement of requested vms into available physical machines pms due to the randomness of customer requests the virtual machine placement vmp should be formulated as an online optimization problem the first part of this work analyzes alternatives to solve the formulated problem an experimental comparison of five different online deterministic heuristics against an offline memetic algorithm with migration of vms was performed considering several experimental workloads simulations indicate that firstfit decreasing algorithm a4 outperforms other evaluated heuristics on average this work presents a twophase schema formulation of a vmp problem considering the optimization of three objective functions in an iaas environment with elasticity and overbooking capabilities the twophase schema formulation describes that the allocation of the vms can be separated into two subproblems the incremental allocation ivmp and the reconfiguration of a placement vmpr to analyze alternatives to solve the formulated problem an experimental comparison of three different objective function scalarization methods as part of the ivmp and vmpr was performed considering several experimental workloads simulations indicate that the euclidean distance to origin outperforms other evaluated scalarization methods on average in order to portray the dynamic nature of an iaas environment a customizable workload trace generator was developed to simulate uncertainty in the scenarios with elasticity and overbooking of resources in vm requests experimental results proved that the euclidean distance is preferable over the other scalarizatiom methods to improve the values of the power consumption objective function | [['cloud', 'computing', 'datacenters', 'provide', 'thousands', 'to', 'millions', 'of', 'virtual', 'machines', 'vms', 'ondemand', 'in', 'highly', 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1,802.04246 | Structure and regularity for subsets of groups with finite VC-dimension | Suppose $G$ is a finite group and $A\subseteq G$ is such that $\{gA:g\in G\}$
has VC-dimension strictly less than $k$. We find algebraically well-structured
sets in $G$ which, up to a chosen $\epsilon>0$, describe the structure of $A$
and behave regularly with respect to translates of $A$. For the subclass of
groups with uniformly fixed finite exponent $r$, these algebraic objects are
normal subgroups with index bounded in terms of $k$, $r$, and $\epsilon$. For
arbitrary groups, we use Bohr neighborhoods of bounded rank and width inside
normal subgroups of bounded index. Our proofs are largely model theoretic, and
heavily rely on a structural analysis of compactifications of pseudofinite
groups as inverse limits of Lie groups. The introduction of Bohr neighborhoods
into the nonabelian setting uses model theoretic methods related to the work of
Breuillard, Green, and Tao and Hrushovski on approximate groups, as well as a
result of Alekseev, Glebskii, and Gordon on approximate homomorphisms.
| math.CO math.GR math.LO | suppose g is a finite group and asubseteq g is such that gagin g has vcdimension strictly less than k we find algebraically wellstructured sets in g which up to a chosen epsilon0 describe the structure of a and behave regularly with respect to translates of a for the subclass of groups with uniformly fixed finite exponent r these algebraic objects are normal subgroups with index bounded in terms of k r and epsilon for arbitrary groups we use bohr neighborhoods of bounded rank and width inside normal subgroups of bounded index our proofs are largely model theoretic and heavily rely on a structural analysis of compactifications of pseudofinite groups as inverse limits of lie groups the introduction of bohr neighborhoods into the nonabelian setting uses model theoretic methods related to the work of breuillard green and tao and hrushovski on approximate groups as well as a result of alekseev glebskii and gordon on approximate homomorphisms | [['suppose', 'g', 'is', 'a', 'finite', 'group', 'and', 'asubseteq', 'g', 'is', 'such', 'that', 'gagin', 'g', 'has', 'vcdimension', 'strictly', 'less', 'than', 'k', 'we', 'find', 'algebraically', 'wellstructured', 'sets', 'in', 'g', 'which', 'up', 'to', 'a', 'chosen', 'epsilon0', 'describe', 'the', 'structure', 'of', 'a', 'and', 'behave', 'regularly', 'with', 'respect', 'to', 'translates', 'of', 'a', 'for', 'the', 'subclass', 'of', 'groups', 'with', 'uniformly', 'fixed', 'finite', 'exponent', 'r', 'these', 'algebraic', 'objects', 'are', 'normal', 'subgroups', 'with', 'index', 'bounded', 'in', 'terms', 'of', 'k', 'r', 'and', 'epsilon', 'for', 'arbitrary', 'groups', 'we', 'use', 'bohr', 'neighborhoods', 'of', 'bounded', 'rank', 'and', 'width', 'inside', 'normal', 'subgroups', 'of', 'bounded', 'index', 'our', 'proofs', 'are', 'largely', 'model', 'theoretic', 'and', 'heavily', 'rely', 'on', 'a', 'structural', 'analysis', 'of', 'compactifications', 'of', 'pseudofinite', 'groups', 'as', 'inverse', 'limits', 'of', 'lie', 'groups', 'the', 'introduction', 'of', 'bohr', 'neighborhoods', 'into', 'the', 'nonabelian', 'setting', 'uses', 'model', 'theoretic', 'methods', 'related', 'to', 'the', 'work', 'of', 'breuillard', 'green', 'and', 'tao', 'and', 'hrushovski', 'on', 'approximate', 'groups', 'as', 'well', 'as', 'a', 'result', 'of', 'alekseev', 'glebskii', 'and', 'gordon', 'on', 'approximate', 'homomorphisms']] | [-0.1414583257861381, 0.11431497940415662, -0.100500772979304, 0.05537533148814767, -0.1067603528609215, -0.14156040047331678, 0.0809756444612905, 0.3809526986502982, -0.2704750212943544, -0.2854459843762346, 0.11404402434142524, -0.28027114281491317, -0.09692658982451328, 0.20776674983260984, -0.1139184411633276, -0.021868368287195825, -0.004415664973051904, 0.12029324033200837, -0.06463011217986947, -0.262835808302421, 0.3513179740251659, -0.06089674732224508, 0.22025526350049615, 0.02278599493786112, 0.07334989649787932, 0.006113479793821643, -0.051884353947039545, 0.055560541943973536, -0.1402595575081805, 0.14680188245369824, 0.27620022894524326, 0.0702318824894194, 0.2588855723817168, -0.33781751752649614, -0.18453563338556847, 0.16463767742592986, 0.13609135480897724, -0.008799060650756462, 0.005788125920974251, -0.29148445881346796, 0.15714496555707913, -0.15866295544751133, -0.13204343526551574, -0.05550544748881033, 0.11313520307885483, 0.04414229385869263, -0.23881590572849534, 0.020638945270571616, 0.11509400748348396, 0.12324566862170959, -0.03345696661071761, -0.14959691496952982, -0.01296511143990248, 0.09364966066348572, 0.006185771481666181, 0.038754605092471105, 0.11701657043206022, -0.06472555550674049, -0.09541925019886974, 0.3865275677964817, -0.061779324000556926, -0.19446661002184082, 0.1670201201016059, -0.13424409581454133, -0.13892176651014862, 0.08207027235388901, 0.1310716383219636, 0.17801229646085465, -0.0204752316617546, 0.23019501129346717, -0.12463617926862623, 0.129124353056193, 0.09218705146627912, 0.01696757782045026, 0.09881134650385758, 0.0915160729404684, 0.12275784232883484, 0.12133771686984057, 0.07429899272430301, -0.0014648543589131592, -0.3424055674173809, -0.11622735516881788, -0.1521859515273895, 0.1166682703391794, -0.12354054212246647, -0.23005515314765612, 0.36557906362010384, 0.04860910854919197, 0.18130330145721893, 0.13108314298676907, 0.18229381289475222, 0.05622640904190333, 0.050188587335552176, 0.11025418774239937, 0.081552616219254, 0.243064444778221, -0.05478459609031387, -0.13184241209687156, 0.00161973639185746, 0.16950008482152562] |
1,802.04247 | Some arithmetic aspects of polynomial maps | The Jacobian conjecture is a well-known open problem in affine algebraic
geometry that asks if any polynomial endomorphism of the affine space
$\mathbb{A}_{\mathbb{C}}^{n}$ ($n\geq2$) with jacobian $1$ is an automorphism.
We present a survey about some results around this conjecture and we discuss an
arithmetic aspect of this conjecture due to Essen-Lipton. We investigate some
cases of this arithmetic approach showing the close relationship between the
Jacobian Conjecture and the problem of counting $\mathbb{F}_p$-points of an
affine scheme.
| math.AG | the jacobian conjecture is a wellknown open problem in affine algebraic geometry that asks if any polynomial endomorphism of the affine space mathbba_mathbbcn ngeq2 with jacobian 1 is an automorphism we present a survey about some results around this conjecture and we discuss an arithmetic aspect of this conjecture due to essenlipton we investigate some cases of this arithmetic approach showing the close relationship between the jacobian conjecture and the problem of counting mathbbf_ppoints of an affine scheme | [['the', 'jacobian', 'conjecture', 'is', 'a', 'wellknown', 'open', 'problem', 'in', 'affine', 'algebraic', 'geometry', 'that', 'asks', 'if', 'any', 'polynomial', 'endomorphism', 'of', 'the', 'affine', 'space', 'mathbba_mathbbcn', 'ngeq2', 'with', 'jacobian', '1', 'is', 'an', 'automorphism', 'we', 'present', 'a', 'survey', 'about', 'some', 'results', 'around', 'this', 'conjecture', 'and', 'we', 'discuss', 'an', 'arithmetic', 'aspect', 'of', 'this', 'conjecture', 'due', 'to', 'essenlipton', 'we', 'investigate', 'some', 'cases', 'of', 'this', 'arithmetic', 'approach', 'showing', 'the', 'close', 'relationship', 'between', 'the', 'jacobian', 'conjecture', 'and', 'the', 'problem', 'of', 'counting', 'mathbbf_ppoints', 'of', 'an', 'affine', 'scheme']] | [-0.19113349615547218, -0.0017125558479165193, -0.10737030899250194, 0.05695293286024887, -0.08134462735860755, -0.15416511180075376, 0.005842823556648861, 0.3102066779117051, -0.379537242054204, -0.24502393254691637, 0.12160135524831467, -0.23061958899549945, -0.2297043916907186, 0.21339887900179938, -0.19288869329581135, 0.023044768549305827, 0.035865031687966335, 0.051657475825203095, -0.11143482591356396, -0.3673827728091151, 0.3963161579235212, -0.02718214873273514, 0.18202443958848322, 0.1642046889663968, 0.13957049997866547, 0.007146567682196435, -0.008017026059525577, -0.042138748534398474, -0.16528335837756458, 0.13731742748457595, 0.2839977864764239, 0.15340788086484136, 0.2654720658289367, -0.3487989882399377, -0.08689179137888316, 0.22527912234593378, 0.14837771833040997, 0.08269068701682906, -0.01778879465143147, -0.21579452482125672, 0.11930020327532762, -0.1342495460106109, -0.23889152988129736, -0.0010919037373050262, 0.048016605506602084, -0.03242162705742215, -0.21351515338756144, -0.005983577857382204, 0.12607809487044028, 0.15377897731224566, -0.08632752869131141, -0.05709531842455219, 0.04949817681489022, 0.048805826208799294, 0.013408120997299097, 0.07469560486558628, 0.019804192235154148, -0.12176694368367623, -0.12059923826324705, 0.36018807646867473, 0.037443278700505435, -0.2192257031259176, 0.0721681946888566, -0.12997109661074846, -0.2030821263569554, 0.07974999649358276, 0.0881914313159589, 0.1262283412506804, 0.006067493219712847, 0.17863673154160528, -0.19963848466776604, 0.1353170503172901, 0.09285016728857667, -0.0559120566743475, 0.13674408572382832, 0.08258376848932944, 0.09283570738013, 0.18120153345424975, -0.007469808339680496, -0.04206564373606326, -0.3370380935207083, -0.19482072557347188, -0.1168263167093851, 0.14621073539417825, -0.14201016516974624, -0.174652546203058, 0.3606636875699558, 0.13859530784630855, 0.18816372514763652, 0.1367567955381482, 0.2502484779657894, 0.09370205953325096, -0.030609642302519398, 0.10091161400965862, 0.13429377915254967, 0.22284233048068067, -0.03239115065355834, -0.1993413239741992, 0.02100198937114328, 0.17810523984218507] |
1,802.04248 | Up-, down-, strange-, charm-, and bottom-quark masses from four-flavor
lattice QCD | We calculate the up-, down-, strange-, charm-, and bottom-quark masses using
the MILC highly improved staggered-quark ensembles with four flavors of
dynamical quarks. We use ensembles at six lattice spacings ranging from
$a\approx0.15$~fm to $0.03$~fm and with both physical and unphysical values of
the two light and the strange sea-quark masses. We use a new method based on
heavy-quark effective theory (HQET) to extract quark masses from heavy-light
pseudoscalar meson masses. Combining our analysis with our separate
determination of ratios of light-quark masses we present masses of the up,
down, strange, charm, and bottom quarks. Our results for the
$\overline{\text{MS}}$-renormalized masses are $m_u(2~\text{GeV}) =
2.130(41)$~MeV, $m_d(2~\text{GeV}) = 4.675(56)$~MeV, $m_s(2~\text{GeV}) =
92.47(69)$~MeV, $m_c(3~\text{GeV}) = 983.7(5.6)$~MeV, and $m_c(m_c) =
1273(10)$~MeV, with four active flavors; and $m_b(m_b) = 4195(14)$~MeV with
five active flavors. We also obtain ratios of quark masses $m_c/m_s =
11.783(25)$, $m_b/m_s = 53.94(12)$, and $m_b/m_c = 4.578(8)$. The result for
$m_c$ matches the precision of the most precise calculation to date, and the
other masses and all quoted ratios are the most precise to date. Moreover,
these results are the first with a perturbative accuracy of $\alpha_s^4$. As
byproducts of our method, we obtain the matrix elements of HQET operators with
dimension 4 and 5: $\overline{\Lambda}_\text{MRS}=555(31)$~MeV in the minimal
renormalon-subtracted (MRS) scheme, $\mu_\pi^2 = 0.05(22)~\text{GeV}^2$, and
$\mu_G^2(m_b)=0.38(2)~\text{GeV}^2$. The MRS scheme [Phys. Rev. D97, 034503
(2018), arXiv:1712.04983 [hep-ph]] is the key new aspect of our method.
| hep-lat hep-ph | we calculate the up down strange charm and bottomquark masses using the milc highly improved staggeredquark ensembles with four flavors of dynamical quarks we use ensembles at six lattice spacings ranging from aapprox015fm to 003fm and with both physical and unphysical values of the two light and the strange seaquark masses we use a new method based on heavyquark effective theory hqet to extract quark masses from heavylight pseudoscalar meson masses combining our analysis with our separate determination of ratios of lightquark masses we present masses of the up down strange charm and bottom quarks our results for the overlinetextmsrenormalized masses are m_u2textgev 213041mev m_d2textgev 467556mev m_s2textgev 924769mev m_c3textgev 983756mev and m_cm_c 127310mev with four active flavors and m_bm_b 419514mev with five active flavors we also obtain ratios of quark masses m_cm_s 1178325 m_bm_s 539412 and m_bm_c 45788 the result for m_c matches the precision of the most precise calculation to date and the other masses and all quoted ratios are the most precise to date moreover these results are the first with a perturbative accuracy of alpha_s4 as byproducts of our method we obtain the matrix elements of hqet operators with dimension 4 and 5 overlinelambda_textmrs55531mev in the minimal renormalonsubtracted mrs scheme mu_pi2 00522textgev2 and mu_g2m_b0382textgev2 the mrs scheme phys rev d97 034503 2018 arxiv171204983 hepph is the key new aspect of our method | [['we', 'calculate', 'the', 'up', 'down', 'strange', 'charm', 'and', 'bottomquark', 'masses', 'using', 'the', 'milc', 'highly', 'improved', 'staggeredquark', 'ensembles', 'with', 'four', 'flavors', 'of', 'dynamical', 'quarks', 'we', 'use', 'ensembles', 'at', 'six', 'lattice', 'spacings', 'ranging', 'from', 'aapprox015fm', 'to', '003fm', 'and', 'with', 'both', 'physical', 'and', 'unphysical', 'values', 'of', 'the', 'two', 'light', 'and', 'the', 'strange', 'seaquark', 'masses', 'we', 'use', 'a', 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1,802.04249 | CoCoS: Fast and Accurate Distributed Triangle Counting in Graph Streams | Given a graph stream, how can we estimate the number of triangles in it using
multiple machines with limited storage? Specifically, how should edges be
processed and sampled across the machines for rapid and accurate estimation?
The count of triangles (i.e., cliques of size three) has proven useful in
numerous applications, including anomaly detection, community detection, and
link recommendation. For triangle counting in large and dynamic graphs, recent
work has focused largely on streaming algorithms and distributed algorithms but
little on their combinations for "the best of both worlds".
In this work, we propose CoCoS, a fast and accurate distributed streaming
algorithm for estimating the counts of global triangles (i.e., all triangles)
and local triangles incident to each node. Making one pass over the input
stream, COCOS carefully processes and stores the edges across multiple machines
so that the redundant use of computational and storage resources is minimized.
Compared to baselines, CoCoS is (a) Accurate: giving up to 39X smaller
estimation error, (b) Fast: up to 10.4X faster, scaling linearly with the size
of the input stream, and (c) Theoretically sound: yielding unbiased estimates.
| cs.DB cs.DC cs.DS cs.SI | given a graph stream how can we estimate the number of triangles in it using multiple machines with limited storage specifically how should edges be processed and sampled across the machines for rapid and accurate estimation the count of triangles ie cliques of size three has proven useful in numerous applications including anomaly detection community detection and link recommendation for triangle counting in large and dynamic graphs recent work has focused largely on streaming algorithms and distributed algorithms but little on their combinations for the best of both worlds in this work we propose cocos a fast and accurate distributed streaming algorithm for estimating the counts of global triangles ie all triangles and local triangles incident to each node making one pass over the input stream cocos carefully processes and stores the edges across multiple machines so that the redundant use of computational and storage resources is minimized compared to baselines cocos is a accurate giving up to 39x smaller estimation error b fast up to 104x faster scaling linearly with the size of the input stream and c theoretically sound yielding unbiased estimates | [['given', 'a', 'graph', 'stream', 'how', 'can', 'we', 'estimate', 'the', 'number', 'of', 'triangles', 'in', 'it', 'using', 'multiple', 'machines', 'with', 'limited', 'storage', 'specifically', 'how', 'should', 'edges', 'be', 'processed', 'and', 'sampled', 'across', 'the', 'machines', 'for', 'rapid', 'and', 'accurate', 'estimation', 'the', 'count', 'of', 'triangles', 'ie', 'cliques', 'of', 'size', 'three', 'has', 'proven', 'useful', 'in', 'numerous', 'applications', 'including', 'anomaly', 'detection', 'community', 'detection', 'and', 'link', 'recommendation', 'for', 'triangle', 'counting', 'in', 'large', 'and', 'dynamic', 'graphs', 'recent', 'work', 'has', 'focused', 'largely', 'on', 'streaming', 'algorithms', 'and', 'distributed', 'algorithms', 'but', 'little', 'on', 'their', 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1,802.0425 | Nonintegrability and quantum fluctuations in a quantum optical model | Integrability in quantum theory has been defined in more than one ways.
Recently, Braak suggested a new definition that a quantum system is integrable
if the number of parameters required to specify the eigenstates and the number
degrees of freedom (both discrete and continuous) are equal. It is argued that
the dependence of uncertainty product of suitable operators on the atom-field
interaction strength is distinctly different for the integrable and
nonintegrable cases. These studies indicate that uncertainty product is able to
identify nonintegrable atom-field systems in the context of the new definition.
| quant-ph | integrability in quantum theory has been defined in more than one ways recently braak suggested a new definition that a quantum system is integrable if the number of parameters required to specify the eigenstates and the number degrees of freedom both discrete and continuous are equal it is argued that the dependence of uncertainty product of suitable operators on the atomfield interaction strength is distinctly different for the integrable and nonintegrable cases these studies indicate that uncertainty product is able to identify nonintegrable atomfield systems in the context of the new definition | [['integrability', 'in', 'quantum', 'theory', 'has', 'been', 'defined', 'in', 'more', 'than', 'one', 'ways', 'recently', 'braak', 'suggested', 'a', 'new', 'definition', 'that', 'a', 'quantum', 'system', 'is', 'integrable', 'if', 'the', 'number', 'of', 'parameters', 'required', 'to', 'specify', 'the', 'eigenstates', 'and', 'the', 'number', 'degrees', 'of', 'freedom', 'both', 'discrete', 'and', 'continuous', 'are', 'equal', 'it', 'is', 'argued', 'that', 'the', 'dependence', 'of', 'uncertainty', 'product', 'of', 'suitable', 'operators', 'on', 'the', 'atomfield', 'interaction', 'strength', 'is', 'distinctly', 'different', 'for', 'the', 'integrable', 'and', 'nonintegrable', 'cases', 'these', 'studies', 'indicate', 'that', 'uncertainty', 'product', 'is', 'able', 'to', 'identify', 'nonintegrable', 'atomfield', 'systems', 'in', 'the', 'context', 'of', 'the', 'new', 'definition']] | [-0.15292581632282867, 0.17215123463867474, -0.0743472326759492, 0.09367619997963471, -0.06273955551391143, -0.17151614194533424, -0.04173514260480221, 0.31592027759989316, -0.2276232865811123, -0.26827845131249534, 0.05648350351712788, -0.2525023126002887, -0.15694957669905346, 0.21017497063249999, -0.04303553758718013, 0.06757587637327125, 0.04980853206412259, 0.06354220457749603, -0.08388273949410928, -0.2528607780518739, 0.3611168165984766, 0.0030727402747446754, 0.27271140693767887, 0.04418800696831844, 0.10271710325437396, 0.011321872267770865, 0.028457136925957773, -0.007532131231666584, -0.11476138305877849, 0.10187340467540629, 0.2205545156694311, 0.095390148352042, 0.2717413476911252, -0.3662248453752988, -0.22794348196855382, 0.11411089549580103, 0.14070560082125114, 0.10634147365192842, 0.03945463455997726, -0.2912468747741988, 0.02329022247020317, -0.20061597802028383, -0.1534920660462534, -0.10141248876512375, 0.08294662507250905, -0.006811553642720632, -0.2688736404272039, 0.058953120924896844, 0.06353740469026177, 0.041569774960289185, -0.03697887535014635, -0.08074914160280731, -0.04142830690429748, 0.09993703409766211, 0.040924600740570735, 0.0028320477905926173, 0.09534953992672103, -0.09298482131334426, -0.10743223404025902, 0.3721088412946657, -0.005715821804662245, -0.2633530144660693, 0.20840046179997126, -0.14699244411641973, -0.16855455822129126, 0.08170704436792142, 0.10338569653179983, 0.08451142176256879, -0.15334337882940535, 0.10990977974459225, -0.03233092188146775, 0.1701405708597082, 0.031226486519343503, 0.11658125887523689, 0.1721776821853026, 0.11008797919013254, 0.08192532389100803, 0.13058805357381378, -0.0014631479976030635, -0.18866332575840794, -0.2942033060218977, -0.14231063533351634, -0.19882009971036535, 0.07318386451199489, -0.07970645857684482, -0.133499002084136, 0.4138845416474278, 0.17419532230807186, 0.14651428085103954, 0.007563586713766436, 0.23120512031322427, 0.160825984177949, 0.09295370905791693, 0.037125378776260695, 0.2599077877416478, 0.16773113973297016, 0.04600277113343548, -0.21023395790151603, 0.05323185620869955, 0.0490984214550775] |
1,802.04251 | Constraining Bianchi Type I Universe With Type Ia Supernova and H(z)
Data | We use recent 36 observational Hubble data (OHD) in the redshift range
$0.07\leq z\leq 2.36$, latest \textgravedbl joint light curves\textacutedbl
(JLA) sample, comprised of 740 type Ia supernovae (SNIa) in the redshift range
$0.01\leq z \leq 1.30$, and their joint combination datasets to constrain
anisotropic Bianchi type I (BI) dark energy (DE) model. To estimate model
parameters, we apply Hamiltonian Monte Carlo technique. We also compute the
covariance matrix for BI dark energy model by considering different datasets to
compare the correlation between model parameters. To check the acceptability of
our fittings, all results are compared with those obtained from 9 year WMAP as
well as Planck (2015) collaboration. Our estimations show that at 68\%
confidence level the dark energy equation of state (EOS) parameter for OHD or
JLA datasets alone varies between quintessence and phantom regions whereas for
OHD+JLA dataset this parameter only varies in phantom region. It is also found
that the current cosmic anisotropy is of order $\sim10^{-3}$ which imply that
the OHD and JLA datasets do not put tight constraint on this parameter.
Therefore, to constraint anisotropy parameter, it is necessary to use high
redshif dataset namely cosmic microwave background (CMB). Moreover, from the
calculation of $p$-value associated with $\chi^{2}$ statistic we observed that
non of the $\omega \mbox{BI}$ and flat $\omega\mbox{CDM}$ models rule out by
OHD or JLA datasets. The deceleration parameter is obtained as $q=-0.46^{+0.89
+0.36}_{-0.41 -0.37}$, $q=-0.619^{+0.12 +0.20}_{-0.095 -0.24}$, and
$q=-0.52^{+0.080 +0.014}_{-0.046 -0.15}$ for OHD, SNIa, and OHD+SNIa data
respectively.
| astro-ph.CO | we use recent 36 observational hubble data ohd in the redshift range 007leq zleq 236 latest textgravedbl joint light curvestextacutedbl jla sample comprised of 740 type ia supernovae snia in the redshift range 001leq z leq 130 and their joint combination datasets to constrain anisotropic bianchi type i bi dark energy de model to estimate model parameters we apply hamiltonian monte carlo technique we also compute the covariance matrix for bi dark energy model by considering different datasets to compare the correlation between model parameters to check the acceptability of our fittings all results are compared with those obtained from 9 year wmap as well as planck 2015 collaboration our estimations show that at 68 confidence level the dark energy equation of state eos parameter for ohd or jla datasets alone varies between quintessence and phantom regions whereas for ohdjla dataset this parameter only varies in phantom region it is also found that the current cosmic anisotropy is of order sim103 which imply that the ohd and jla datasets do not put tight constraint on this parameter therefore to constraint anisotropy parameter it is necessary to use high redshif dataset namely cosmic microwave background cmb moreover from the calculation of pvalue associated with chi2 statistic we observed that non of the omega mboxbi and flat omegamboxcdm models rule out by ohd or jla datasets the deceleration parameter is obtained as q046089 036_041 037 q0619012 020_0095 024 and q0520080 0014_0046 015 for ohd snia and ohdsnia data respectively | [['we', 'use', 'recent', '36', 'observational', 'hubble', 'data', 'ohd', 'in', 'the', 'redshift', 'range', '007leq', 'zleq', '236', 'latest', 'textgravedbl', 'joint', 'light', 'curvestextacutedbl', 'jla', 'sample', 'comprised', 'of', '740', 'type', 'ia', 'supernovae', 'snia', 'in', 'the', 'redshift', 'range', '001leq', 'z', 'leq', '130', 'and', 'their', 'joint', 'combination', 'datasets', 'to', 'constrain', 'anisotropic', 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1,802.04252 | Automatic Phone Slip Detection System | Mobile phones are becoming increasingly advanced and the latest ones are
equipped with many diverse and powerful sensors. These sensors can be used to
study different position and orientation of the phone which can help smartphone
manufacture to track about their customers handling from the recorded log. The
inbuilt sensors such as the accelerometer and gyroscope present in our phones
are used to obtain data for acceleration and orientation of the phone in the
three axes for different phone vulnerable position. From the data obtained
appropriate features are extracted using various feature extraction techniques.
The extracted features are then given to classifier such as neural network to
classify them and decide whether the phone is in a vulnerable position to fall
or it is in a safe position .In this paper we mainly concentrated on various
case of handling the smartphone and classified by training the neural network.
| cs.CY | mobile phones are becoming increasingly advanced and the latest ones are equipped with many diverse and powerful sensors these sensors can be used to study different position and orientation of the phone which can help smartphone manufacture to track about their customers handling from the recorded log the inbuilt sensors such as the accelerometer and gyroscope present in our phones are used to obtain data for acceleration and orientation of the phone in the three axes for different phone vulnerable position from the data obtained appropriate features are extracted using various feature extraction techniques the extracted features are then given to classifier such as neural network to classify them and decide whether the phone is in a vulnerable position to fall or it is in a safe position in this paper we mainly concentrated on various case of handling the smartphone and classified by training the neural network | [['mobile', 'phones', 'are', 'becoming', 'increasingly', 'advanced', 'and', 'the', 'latest', 'ones', 'are', 'equipped', 'with', 'many', 'diverse', 'and', 'powerful', 'sensors', 'these', 'sensors', 'can', 'be', 'used', 'to', 'study', 'different', 'position', 'and', 'orientation', 'of', 'the', 'phone', 'which', 'can', 'help', 'smartphone', 'manufacture', 'to', 'track', 'about', 'their', 'customers', 'handling', 'from', 'the', 'recorded', 'log', 'the', 'inbuilt', 'sensors', 'such', 'as', 'the', 'accelerometer', 'and', 'gyroscope', 'present', 'in', 'our', 'phones', 'are', 'used', 'to', 'obtain', 'data', 'for', 'acceleration', 'and', 'orientation', 'of', 'the', 'phone', 'in', 'the', 'three', 'axes', 'for', 'different', 'phone', 'vulnerable', 'position', 'from', 'the', 'data', 'obtained', 'appropriate', 'features', 'are', 'extracted', 'using', 'various', 'feature', 'extraction', 'techniques', 'the', 'extracted', 'features', 'are', 'then', 'given', 'to', 'classifier', 'such', 'as', 'neural', 'network', 'to', 'classify', 'them', 'and', 'decide', 'whether', 'the', 'phone', 'is', 'in', 'a', 'vulnerable', 'position', 'to', 'fall', 'or', 'it', 'is', 'in', 'a', 'safe', 'position', 'in', 'this', 'paper', 'we', 'mainly', 'concentrated', 'on', 'various', 'case', 'of', 'handling', 'the', 'smartphone', 'and', 'classified', 'by', 'training', 'the', 'neural', 'network']] | [-0.08754555839491454, 0.06981611501652042, -0.03343551934419854, 0.06108737608332917, -0.11506088230620466, -0.2111056237670316, 0.008279603883164708, 0.4444636497898279, -0.2935247922731513, -0.3634379307512899, 0.1413023057291473, -0.3496749969828572, -0.12917776342412154, 0.2436937245573161, -0.13211488254278633, 0.06733290248116278, 0.058895376234038455, 0.10079861826238197, -0.00448598199826036, -0.23689875315019004, 0.28760392832997683, 0.0304342173920894, 0.32215206486934395, -0.009065571127811799, 0.08264170601064139, 0.008087789831758552, -0.05900820206875938, 0.006310107933697165, -0.03547945500562295, 0.17077440892446888, 0.3123891058274092, 0.17637340887449682, 0.23530261519969115, -0.4803524315608917, -0.1630357677876836, 0.07793744722683285, 0.13678718362250555, 0.0841858227213379, -0.0386413999312444, -0.3667606198326433, 0.14664396574182711, -0.1865471464682471, -0.08903093396125965, -0.08082116571116589, 0.024969279007809993, 0.08155079749318443, -0.2291318568954798, -0.0461185777975196, -0.020916180688308906, 0.10037330264930387, -0.047417487184567425, -0.06942017541606785, -0.017858150811563875, 0.2524158823495806, 0.04961286837272849, 0.008878903471348757, 0.21095527868365516, -0.12377417431609403, -0.08687849897526305, 0.3763264976819423, 0.011550509787756144, -0.19393603322739206, 0.21766612240792932, -0.04939865179649378, -0.1069701466854108, 0.04850156878977007, 0.2398854839250546, 0.09250737487879657, -0.19104373292695428, -0.039521800699829426, 0.03074453559364318, 0.16328354050858399, 0.07683795251461954, 0.02775649892518649, 0.21061771018178882, 0.17779791835896872, 0.031568202236116664, 0.09287835422170197, -0.16182278784489845, -0.026155371174870712, -0.21768575366208884, -0.10165229896272256, -0.18818225369732072, 0.015994208076704496, -0.08845103714495939, -0.13425504166327693, 0.3784503243121042, 0.22419206982138692, 0.2340116984198323, 0.025211183449435928, 0.3575245584235401, 0.038413352185523615, 0.14971710628093648, 0.06539284373237123, 0.18770824292300245, -0.0033067394271367105, 0.17048948712810572, -0.11479173933322592, 0.10061458066558919, 0.010707699099077365] |
1,802.04253 | Global Model Interpretation via Recursive Partitioning | In this work, we propose a simple but effective method to interpret black-box
machine learning models globally. That is, we use a compact binary tree, the
interpretation tree, to explicitly represent the most important decision rules
that are implicitly contained in the black-box machine learning models. This
tree is learned from the contribution matrix which consists of the
contributions of input variables to predicted scores for each single
prediction. To generate the interpretation tree, a unified process recursively
partitions the input variable space by maximizing the difference in the average
contribution of the split variable between the divided spaces. We demonstrate
the effectiveness of our method in diagnosing machine learning models on
multiple tasks. Also, it is useful for new knowledge discovery as such insights
are not easily identifiable when only looking at single predictions. In
general, our work makes it easier and more efficient for human beings to
understand machine learning models.
| cs.LG cs.AI stat.ML | in this work we propose a simple but effective method to interpret blackbox machine learning models globally that is we use a compact binary tree the interpretation tree to explicitly represent the most important decision rules that are implicitly contained in the blackbox machine learning models this tree is learned from the contribution matrix which consists of the contributions of input variables to predicted scores for each single prediction to generate the interpretation tree a unified process recursively partitions the input variable space by maximizing the difference in the average contribution of the split variable between the divided spaces we demonstrate the effectiveness of our method in diagnosing machine learning models on multiple tasks also it is useful for new knowledge discovery as such insights are not easily identifiable when only looking at single predictions in general our work makes it easier and more efficient for human beings to understand machine learning models | [['in', 'this', 'work', 'we', 'propose', 'a', 'simple', 'but', 'effective', 'method', 'to', 'interpret', 'blackbox', 'machine', 'learning', 'models', 'globally', 'that', 'is', 'we', 'use', 'a', 'compact', 'binary', 'tree', 'the', 'interpretation', 'tree', 'to', 'explicitly', 'represent', 'the', 'most', 'important', 'decision', 'rules', 'that', 'are', 'implicitly', 'contained', 'in', 'the', 'blackbox', 'machine', 'learning', 'models', 'this', 'tree', 'is', 'learned', 'from', 'the', 'contribution', 'matrix', 'which', 'consists', 'of', 'the', 'contributions', 'of', 'input', 'variables', 'to', 'predicted', 'scores', 'for', 'each', 'single', 'prediction', 'to', 'generate', 'the', 'interpretation', 'tree', 'a', 'unified', 'process', 'recursively', 'partitions', 'the', 'input', 'variable', 'space', 'by', 'maximizing', 'the', 'difference', 'in', 'the', 'average', 'contribution', 'of', 'the', 'split', 'variable', 'between', 'the', 'divided', 'spaces', 'we', 'demonstrate', 'the', 'effectiveness', 'of', 'our', 'method', 'in', 'diagnosing', 'machine', 'learning', 'models', 'on', 'multiple', 'tasks', 'also', 'it', 'is', 'useful', 'for', 'new', 'knowledge', 'discovery', 'as', 'such', 'insights', 'are', 'not', 'easily', 'identifiable', 'when', 'only', 'looking', 'at', 'single', 'predictions', 'in', 'general', 'our', 'work', 'makes', 'it', 'easier', 'and', 'more', 'efficient', 'for', 'human', 'beings', 'to', 'understand', 'machine', 'learning', 'models']] | [-0.01651544234748881, 0.07591055207459707, -0.0998894338499073, 0.12914879895178946, -0.15720987840999964, -0.16248618109224766, 0.07596728236116225, 0.40784840378910303, -0.3027251271775991, -0.3095053170436348, 0.0627591715984083, -0.23398829506576255, -0.19247253286177476, 0.19738635241230523, -0.08624242629332382, 0.05026173090571355, 0.09656721599144387, 0.06707815509411244, -0.03137021429921969, -0.28016426397283606, 0.3254818687690239, 0.034135641330804406, 0.3031398636148938, -0.017529855104881566, 0.11241300995126853, 0.028033206829789027, -0.0525473660296377, -0.01882239515163473, -0.04864729955852157, 0.18411348563591567, 0.3395977342495386, 0.22156122327155245, 0.3022462933939072, -0.3693534697381646, -0.22349804381724275, 0.13158329452686254, 0.14858310056083343, 0.12576161787215182, -0.0005276948210723954, -0.2604063821696293, 0.074408396427197, -0.14595289429759278, -0.036037177434860686, -0.13819522931837033, 0.002528892373483555, -0.0695752508461238, -0.29214493695683047, 0.011274242210978022, 0.08394835686601784, 0.018935695394045778, -0.049097097564026033, -0.1317127823968132, 0.018695633974096744, 0.15678893761907922, 0.022469726418338266, 0.07448846700729109, 0.1305586887779189, -0.156044217475973, -0.1628646589728115, 0.356693211206375, -0.042856213341473166, -0.23611499851697362, 0.20201922037023928, -0.057907378693640814, -0.20920728039897346, 0.10384174698075048, 0.23347635624406773, 0.13139885145690736, -0.19261602693577098, 0.015517862470671414, -0.04222479160856821, 0.16223430978910378, 0.009804217242240126, -0.0275203300791403, 0.21755999928109007, 0.22720450670321418, 0.002399365569836174, 0.14302331176008176, -0.03606242403917599, -0.09307636484751794, -0.27671733391174463, -0.1471213669017006, -0.1865846704801216, -0.023947716410499326, -0.11266085317385385, -0.16300679095929452, 0.3860301138327938, 0.2215687506710441, 0.21571179672339902, 0.10177273847835346, 0.34031380425980373, 0.09914678922744796, 0.09615602170792865, 0.10090915696829363, 0.1840280508287738, 0.058477593187145356, 0.0680815823637923, -0.1597554271544628, 0.13190461128411413, 0.061787593837377] |
1,802.04254 | Design of a hybrid plasmonic electro-optical modulator based on n doped
silicon and barium titanate | In this paper, a numerical solution for a hybrid plasmonic modulator is
presented with a six-layer structure consisting of an air superstrate, a gold
layer, a barium titanate layer, a n type silicon layer, a gold layer and an
Al2O3 nanolattice substrate. Regarding the suggested structure, the parameters
related to the phase and the absorption modulation are investigated at
different thicknesses. Here, the Pockels effect and the free carrier dispersion
effect are considered simultaneously. The dispersion equation of this structure
is analytically obtained and numerically solved by the Nelder-Mead method. The
minimum {\pi} shift length is predicted to be equal to 6.91{\mu}m and the
maximum calculated figure of merit is 10.74. Furthermore, according to our
results, it is understood that this modulator has a high ability to be utilized
in optical communication systems. Also, it could be integrated to the
microelectronic systems and it is compatible with CMOS technology.
| physics.app-ph physics.optics | in this paper a numerical solution for a hybrid plasmonic modulator is presented with a sixlayer structure consisting of an air superstrate a gold layer a barium titanate layer a n type silicon layer a gold layer and an al2o3 nanolattice substrate regarding the suggested structure the parameters related to the phase and the absorption modulation are investigated at different thicknesses here the pockels effect and the free carrier dispersion effect are considered simultaneously the dispersion equation of this structure is analytically obtained and numerically solved by the neldermead method the minimum pi shift length is predicted to be equal to 691mum and the maximum calculated figure of merit is 1074 furthermore according to our results it is understood that this modulator has a high ability to be utilized in optical communication systems also it could be integrated to the microelectronic systems and it is compatible with cmos technology | [['in', 'this', 'paper', 'a', 'numerical', 'solution', 'for', 'a', 'hybrid', 'plasmonic', 'modulator', 'is', 'presented', 'with', 'a', 'sixlayer', 'structure', 'consisting', 'of', 'an', 'air', 'superstrate', 'a', 'gold', 'layer', 'a', 'barium', 'titanate', 'layer', 'a', 'n', 'type', 'silicon', 'layer', 'a', 'gold', 'layer', 'and', 'an', 'al2o3', 'nanolattice', 'substrate', 'regarding', 'the', 'suggested', 'structure', 'the', 'parameters', 'related', 'to', 'the', 'phase', 'and', 'the', 'absorption', 'modulation', 'are', 'investigated', 'at', 'different', 'thicknesses', 'here', 'the', 'pockels', 'effect', 'and', 'the', 'free', 'carrier', 'dispersion', 'effect', 'are', 'considered', 'simultaneously', 'the', 'dispersion', 'equation', 'of', 'this', 'structure', 'is', 'analytically', 'obtained', 'and', 'numerically', 'solved', 'by', 'the', 'neldermead', 'method', 'the', 'minimum', 'pi', 'shift', 'length', 'is', 'predicted', 'to', 'be', 'equal', 'to', '691mum', 'and', 'the', 'maximum', 'calculated', 'figure', 'of', 'merit', 'is', '1074', 'furthermore', 'according', 'to', 'our', 'results', 'it', 'is', 'understood', 'that', 'this', 'modulator', 'has', 'a', 'high', 'ability', 'to', 'be', 'utilized', 'in', 'optical', 'communication', 'systems', 'also', 'it', 'could', 'be', 'integrated', 'to', 'the', 'microelectronic', 'systems', 'and', 'it', 'is', 'compatible', 'with', 'cmos', 'technology']] | [-0.11414296469474966, 0.1284730589818414, -0.06819583985614716, -0.015319113599764171, -0.04962664474481465, -0.155830708709923, 0.052761112337434864, 0.44177126638257774, -0.2989785040200159, -0.30560856504441314, 0.07208914975981807, -0.2957700299047173, -0.15969914534110324, 0.2037919148062576, -0.028282271505402704, 0.061175250495481934, 0.010155816248624359, -0.03820061987907802, -0.04179953059851746, -0.20067028541942253, 0.23987680383504847, 0.08932550059241318, 0.3249250069996846, 0.05776044469314149, 0.0911522304601464, -0.06193071777454099, 0.07509947454909215, 0.02553767412762288, -0.1375938210704909, 0.11576135667840119, 0.23289103960819743, -0.02360084406540704, 0.20591666790927332, -0.3878122992008119, -0.24333172571228667, 0.01124380001282269, 0.1352980833687832, 0.09372269581709171, -0.06856858879886253, -0.23525241564572286, 0.1271118193493552, -0.16464172472321503, -0.13501234372096085, 0.001358007181536507, 0.007664662164422004, -0.021519092315921206, -0.264603743858626, 0.009993528888829845, 0.02007885414137933, 0.022397943089615454, -0.04518970223678578, -0.12118085823651101, -0.04025322507997673, 0.0741710148553515, -0.036246011429235246, 0.013687568583771133, 0.13996551872696728, -0.07092658282301666, -0.07751275423435948, 0.37696466297918074, -0.06481499768906852, -0.20053416627736106, 0.13111238364709188, -0.1000694308643909, -0.0035791262823811456, 0.1361942170250758, 0.14725612957861173, 0.11770748254541005, -0.1780787998557915, 0.02655903111617836, -0.004074654922619261, 0.2494774938079629, 0.0961365839592307, 0.040952027177538826, 0.1911831792236331, 0.23888878231377317, 0.017514802748337388, 0.142996275379807, -0.09648378502665642, -0.01898978525974058, -0.23127745537439715, -0.1900161209994474, -0.19530002966309218, 0.028413492947112064, -0.0781226418780657, -0.15027196617557895, 0.37598661791432547, 0.11231698624229662, 0.15691467514930205, -0.026389686035218875, 0.31083916211689544, 0.1589535225561908, 0.11175245115835522, 0.026111918312774318, 0.2722451885960795, 0.17222821814829256, 0.10342409140807954, -0.24592229602323543, 0.08343193931756793, 0.006538231188519481] |
1,802.04255 | Systems of Global Governance in the Era of Human-Machine Convergence | Technology is increasingly shaping our social structures and is becoming a
driving force in altering human biology. Besides, human activities already
proved to have a significant impact on the Earth system which in turn generates
complex feedback loops between social and ecological systems. Furthermore,
since our species evolved relatively fast from small groups of hunter-gatherers
to large and technology-intensive urban agglomerations, it is not a surprise
that the major institutions of human society are no longer fit to cope with the
present complexity. In this note we draw foundational parallelisms between
neurophysiological systems and ICT-enabled social systems, discussing how
frameworks rooted in biology and physics could provide heuristic value in the
design of evolutionary systems relevant to politics and economics. In this
regard we highlight how the governance of emerging technology (i.e.
nanotechnology, biotechnology, information technology, and cognitive science),
and the one of climate change both presently confront us with a number of
connected challenges. In particular: historically high level of inequality; the
co-existence of growing multipolar cultural systems in an unprecedentedly
connected world; the unlikely reaching of the institutional agreements required
to deviate abnormal trajectories of development. We argue that wise general
solutions to such interrelated issues should embed the deep understanding of
how to elicit mutual incentives in the socio-economic subsystems of Earth
system in order to jointly concur to a global utility function (e.g. avoiding
the reach of planetary boundaries and widespread social unrest). We leave some
open questions on how techno-social systems can effectively learn and adapt
with respect to our understanding of geopolitical complexity.
| cs.CY physics.soc-ph q-bio.NC | technology is increasingly shaping our social structures and is becoming a driving force in altering human biology besides human activities already proved to have a significant impact on the earth system which in turn generates complex feedback loops between social and ecological systems furthermore since our species evolved relatively fast from small groups of huntergatherers to large and technologyintensive urban agglomerations it is not a surprise that the major institutions of human society are no longer fit to cope with the present complexity in this note we draw foundational parallelisms between neurophysiological systems and ictenabled social systems discussing how frameworks rooted in biology and physics could provide heuristic value in the design of evolutionary systems relevant to politics and economics in this regard we highlight how the governance of emerging technology ie nanotechnology biotechnology information technology and cognitive science and the one of climate change both presently confront us with a number of connected challenges in particular historically high level of inequality the coexistence of growing multipolar cultural systems in an unprecedentedly connected world the unlikely reaching of the institutional agreements required to deviate abnormal trajectories of development we argue that wise general solutions to such interrelated issues should embed the deep understanding of how to elicit mutual incentives in the socioeconomic subsystems of earth system in order to jointly concur to a global utility function eg avoiding the reach of planetary boundaries and widespread social unrest we leave some open questions on how technosocial systems can effectively learn and adapt with respect to our understanding of geopolitical complexity | [['technology', 'is', 'increasingly', 'shaping', 'our', 'social', 'structures', 'and', 'is', 'becoming', 'a', 'driving', 'force', 'in', 'altering', 'human', 'biology', 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1,802.04256 | GeoMFree3D: An Under-Development Meshfree Software Package for
Geomechanics | This paper briefly reports the GeoMFree3D, a meshfree / meshless software
package designed for analyzing the problems of large deformations and crack
propagations of rock and soil masses in geotechnics. The GeoMFree3D is
developed based on the meshfree RPIM, and accelerated by exploiting the
parallel computing on multi-core CPU and many-core GPU. The GeoMFree3D is
currently being under intensive developments. To demonstrate the correctness
and effectiveness of the GeoMFree3D, several simple verification examples are
presented in this paper. Moreover, future work on the development of the
GeoMFree3D is introduced.
| physics.comp-ph cs.CE math.NA | this paper briefly reports the geomfree3d a meshfree meshless software package designed for analyzing the problems of large deformations and crack propagations of rock and soil masses in geotechnics the geomfree3d is developed based on the meshfree rpim and accelerated by exploiting the parallel computing on multicore cpu and manycore gpu the geomfree3d is currently being under intensive developments to demonstrate the correctness and effectiveness of the geomfree3d several simple verification examples are presented in this paper moreover future work on the development of the geomfree3d is introduced | [['this', 'paper', 'briefly', 'reports', 'the', 'geomfree3d', 'a', 'meshfree', 'meshless', 'software', 'package', 'designed', 'for', 'analyzing', 'the', 'problems', 'of', 'large', 'deformations', 'and', 'crack', 'propagations', 'of', 'rock', 'and', 'soil', 'masses', 'in', 'geotechnics', 'the', 'geomfree3d', 'is', 'developed', 'based', 'on', 'the', 'meshfree', 'rpim', 'and', 'accelerated', 'by', 'exploiting', 'the', 'parallel', 'computing', 'on', 'multicore', 'cpu', 'and', 'manycore', 'gpu', 'the', 'geomfree3d', 'is', 'currently', 'being', 'under', 'intensive', 'developments', 'to', 'demonstrate', 'the', 'correctness', 'and', 'effectiveness', 'of', 'the', 'geomfree3d', 'several', 'simple', 'verification', 'examples', 'are', 'presented', 'in', 'this', 'paper', 'moreover', 'future', 'work', 'on', 'the', 'development', 'of', 'the', 'geomfree3d', 'is', 'introduced']] | [-0.11345818562184048, 0.04779057095347102, -0.03981045665500989, -0.0031052425457706112, -0.09071931775745957, -0.08965772456965994, -0.04407208778646363, 0.3815386473352826, -0.21392054202273314, -0.30674088799914473, 0.18231663310109789, -0.2126359914342851, -0.14693725080944078, 0.26782533422459004, -0.08376878315344626, 0.1381195102125233, 0.14663835927345897, -0.050271866431589735, -0.07333729623242953, -0.29367276183112934, 0.269589105317759, 0.12176964115784612, 0.31066891596500956, 0.12403474601058745, 0.10300539489185741, -0.01378487351047265, -0.07781800596912522, -0.0008298110076074683, -0.11008791189043793, 0.1961904495120655, 0.23312125299775668, 0.1622729919807509, 0.31009371803943503, -0.4591192196578134, -0.13472139259507923, 0.022649228996543085, 0.12328319540409761, 0.07105858262281778, -0.09314287390741303, -0.28343465073077484, 0.09898507663490098, -0.1763420107362922, -0.09270639488538511, -0.0895786141153685, -0.0313020922990819, 0.05763900912431783, -0.18783243562008234, 0.005861163464223229, 0.006647640435826467, 0.09208644077528355, -0.0010719713633121966, -0.12338096888324376, 0.06457831767972472, 0.03681092939967679, 0.04503891040127031, -0.006514549639812389, 0.15191093499523176, -0.07254762755338709, -0.14146136223923328, 0.42890934906033584, 0.016219071762333084, -0.21048165735420446, 0.2046961442345407, -0.021955604984446667, -0.16384871381464913, 0.04921099236018436, 0.2440549752588362, 0.12026891560661931, -0.1924209801675102, 0.10876085494068279, 0.029192516721005358, 0.12965266831181294, 0.0493680301696322, -0.07192829739759936, 0.14573738143541093, 0.26028650039590373, -0.01637758447742631, 0.15646977705317874, -0.07790199724340074, -0.11411870356519209, -0.2752305897640411, -0.2119881347211641, -0.19317014082768108, -0.06860062374116116, -0.042646373707908046, -0.1700677829577999, 0.409261989558852, 0.2026755535855976, 0.08362142287931124, 0.09325384062736533, 0.37779342869654037, 0.024149244391294414, 0.1028734014781062, 0.14090974469734138, 0.19819274787292923, 0.07638414724199317, 0.15574870935944451, -0.23967672132367138, 0.05364432941775683, 0.05519772065007453] |
1,802.04257 | A hypothesis in evolutionary biology | The classic Trivers-Willard hypothesis suggested the existence of means or
conditions able to influence or control the sex of the offspring. Here I
propose that mechanisms for the alteration of the gender of the offspring could
possibly be formulated in terms of a distributed system of messages expressing
a change in the environmental conditions. Such messages would provide the
biological organization with global and local assessments of the benefits
associated with the reproductive investments associated with either genres of
the offspring.
| cs.CY | the classic triverswillard hypothesis suggested the existence of means or conditions able to influence or control the sex of the offspring here i propose that mechanisms for the alteration of the gender of the offspring could possibly be formulated in terms of a distributed system of messages expressing a change in the environmental conditions such messages would provide the biological organization with global and local assessments of the benefits associated with the reproductive investments associated with either genres of the offspring | [['the', 'classic', 'triverswillard', 'hypothesis', 'suggested', 'the', 'existence', 'of', 'means', 'or', 'conditions', 'able', 'to', 'influence', 'or', 'control', 'the', 'sex', 'of', 'the', 'offspring', 'here', 'i', 'propose', 'that', 'mechanisms', 'for', 'the', 'alteration', 'of', 'the', 'gender', 'of', 'the', 'offspring', 'could', 'possibly', 'be', 'formulated', 'in', 'terms', 'of', 'a', 'distributed', 'system', 'of', 'messages', 'expressing', 'a', 'change', 'in', 'the', 'environmental', 'conditions', 'such', 'messages', 'would', 'provide', 'the', 'biological', 'organization', 'with', 'global', 'and', 'local', 'assessments', 'of', 'the', 'benefits', 'associated', 'with', 'the', 'reproductive', 'investments', 'associated', 'with', 'either', 'genres', 'of', 'the', 'offspring']] | [-0.1319591689177208, 0.11155383014637563, -0.08636087364873585, 0.061198400459999656, -0.06860861841612208, -0.12453421430639279, 0.09149361585473849, 0.3104533389624622, -0.2810625026381954, -0.28573122886181984, 0.11820162784733614, -0.24005823185161493, -0.1647168002896195, 0.10755434190210553, -0.11763394997673637, -0.01993028336653003, 0.03254491094223879, 0.07920578118150674, 0.01336529537357022, -0.2793818862108445, 0.3256520376365379, 0.0321427653371184, 0.26354580785918197, 0.042222996029634904, 0.11067140534704115, -0.010312166395539672, -0.054042504703695024, 0.010489468773206076, -0.0859177511126661, 0.14393373756428007, 0.24128622074760955, 0.22252531291020136, 0.34961682017662643, -0.44989623350125774, -0.19140055972254938, 0.1626936843227825, 0.13092838281788577, 0.05611387963326257, -0.03727283951090534, -0.293952921865347, 0.0682270599782099, -0.17595063436224503, -0.16292114079826409, -0.004020651733433759, -0.01488136657640154, 0.0933804574859455, -0.3187232887207812, 0.09410464423306195, 0.05627909249821563, 0.11137267584441068, -0.11995597059815478, -0.124438894445502, -0.05766250713969822, 0.1892496478502397, 0.11655282551123772, -0.05038176318285642, 0.1623957256835391, -0.17721729380665002, -0.16888800259380612, 0.3714922781786479, -0.021191395390893757, -0.20763282290728832, 0.2246720225400763, -0.10208907695257186, -0.11588320671293287, 0.08166310614273872, 0.17565991300054723, 0.05926294212034087, -0.16842935079087815, -0.025616693138691055, -0.00146440078538877, 0.14661549712404792, 0.0732115751799242, 0.07056972719613969, 0.2154057106624047, 0.15271455286369648, 0.07816981291973296, 0.09275286814146158, -0.053228460832205775, -0.08893732539734539, -0.2537739402442067, -0.175622326919786, -0.13122837939932022, 0.054739195531533086, -0.1070918490300688, -0.1771629056950778, 0.40768799240942355, 0.13153196360777925, 0.14172642130151758, 0.07124877628945044, 0.22331249083530297, 0.0865546439854819, 0.08503268448704923, 0.019344496477487278, 0.16690205779633727, 0.05317476672338851, 0.10760905882803562, -0.2543837248267215, 0.23664221367626279, -0.007978449196175293] |
1,802.04258 | On Random-Matrix Bases, Ghost Imaging and X-ray Phase Contrast
Computational Ghost Imaging | A theory of random-matrix bases is presented, including expressions for
orthogonality, completeness and the random-matrix synthesis of arbitrary
matrices. This is applied to ghost imaging as the realization of a random-basis
reconstruction, including an expression for the resulting signal-to-noise
ratio. Analysis of conventional direct imaging and ghost imaging leads to a
criterion which, when satisfied, implies reduced dose for computational ghost
imaging. We also propose an experiment for x-ray phase contrast computational
ghost imaging, which enables differential phase contrast to be achieved in an
x-ray ghost imaging context. We give a numerically robust solution to the
associated inverse problem of decoding differential phase contrast x-ray ghost
images, to yield a quantitative map of the projected thickness of the sample.
| eess.IV | a theory of randommatrix bases is presented including expressions for orthogonality completeness and the randommatrix synthesis of arbitrary matrices this is applied to ghost imaging as the realization of a randombasis reconstruction including an expression for the resulting signaltonoise ratio analysis of conventional direct imaging and ghost imaging leads to a criterion which when satisfied implies reduced dose for computational ghost imaging we also propose an experiment for xray phase contrast computational ghost imaging which enables differential phase contrast to be achieved in an xray ghost imaging context we give a numerically robust solution to the associated inverse problem of decoding differential phase contrast xray ghost images to yield a quantitative map of the projected thickness of the sample | [['a', 'theory', 'of', 'randommatrix', 'bases', 'is', 'presented', 'including', 'expressions', 'for', 'orthogonality', 'completeness', 'and', 'the', 'randommatrix', 'synthesis', 'of', 'arbitrary', 'matrices', 'this', 'is', 'applied', 'to', 'ghost', 'imaging', 'as', 'the', 'realization', 'of', 'a', 'randombasis', 'reconstruction', 'including', 'an', 'expression', 'for', 'the', 'resulting', 'signaltonoise', 'ratio', 'analysis', 'of', 'conventional', 'direct', 'imaging', 'and', 'ghost', 'imaging', 'leads', 'to', 'a', 'criterion', 'which', 'when', 'satisfied', 'implies', 'reduced', 'dose', 'for', 'computational', 'ghost', 'imaging', 'we', 'also', 'propose', 'an', 'experiment', 'for', 'xray', 'phase', 'contrast', 'computational', 'ghost', 'imaging', 'which', 'enables', 'differential', 'phase', 'contrast', 'to', 'be', 'achieved', 'in', 'an', 'xray', 'ghost', 'imaging', 'context', 'we', 'give', 'a', 'numerically', 'robust', 'solution', 'to', 'the', 'associated', 'inverse', 'problem', 'of', 'decoding', 'differential', 'phase', 'contrast', 'xray', 'ghost', 'images', 'to', 'yield', 'a', 'quantitative', 'map', 'of', 'the', 'projected', 'thickness', 'of', 'the', 'sample']] | [-0.07162704698788791, 0.047046554660976084, -0.09789338288039474, 0.08929421563763014, -0.08041089194653145, -0.10412410171150024, 0.009191927097548368, 0.36853777707191343, -0.26125833454494507, -0.3113633503829587, 0.11585388151372357, -0.2309847541658555, -0.1794620686155444, 0.19138651278256674, -0.0858061814728051, 0.08252963842034845, 0.08370334725882227, 0.003081338101271856, -0.10043327793699958, -0.19158064545787304, 0.2679897425104312, 0.07728616612316189, 0.2973763439015059, 0.017214464868213666, 0.1462424936618876, 0.05881730634995373, -0.03657507997448162, 0.04957518571103781, -0.128731093742348, 0.10163055349563611, 0.3004219115443401, 0.1493781950577336, 0.2011476614299404, -0.385742258414381, -0.1979215993285495, 0.10120751500382262, 0.17736079883751837, 0.11438914321923345, -0.09478551507690701, -0.24831676126410396, 0.05741337674938268, -0.12490975777855363, -0.13607993209931873, -0.08713246962268663, -0.0693597781612001, -0.06872120060784331, -0.3435383995174099, 0.12058515260484409, -0.005283416252804257, 0.0884397494038409, -0.11337337884815189, -0.08602312137372792, 0.04603273896658319, 0.05994510949294327, -0.028781451170443225, 0.042323316569771556, 0.07807682373292618, -0.21558784470317285, -0.09542082649087376, 0.3304306480844142, -0.01624655041062289, -0.17273461817116556, 0.18452029606579975, -0.11529285230346308, -0.09179784220019829, 0.2077436717937432, 0.10650900522862577, 0.12410452941795654, -0.14603962893541053, 0.08549683080824344, -0.01040226650834715, 0.23087212844294006, 0.11418844775249393, 0.0693713930214487, 0.14350691181212916, 0.15343225794208978, 0.07821999482368514, 0.20586832302772456, -0.17379237855123592, -0.04430530909882953, -0.2682711883305998, -0.189708318371894, -0.1540984006320379, 0.03740470395995683, -0.08818437106822523, -0.20420347093367727, 0.33967989636979745, 0.15241197925021524, 0.14376489934906111, 0.0631221493773194, 0.3415785415682121, 0.17169503420019144, 0.06953318975471212, -0.06800874829355438, 0.2477265054762553, 0.20476477016829017, 0.1100759742055404, -0.2703703385560726, -0.02843690237476317, 0.05756668627293686] |
1,802.04259 | Sphinx: A Secure Architecture Based on Binary Code Diversification and
Execution Obfuscation | Sphinx, a hardware-software co-design architecture for binary code and
runtime obfuscation. The Sphinx architecture uses binary code diversification
and self-reconfigurable processing elements to maintain application
functionality while obfuscating the binary code and architecture states to
attackers. This approach dramatically reduces an attacker's ability to exploit
information gained from one deployment to attack another deployment. Our
results show that the Sphinx is able to decouple the program's execution time,
power and memory and I/O activities from its functionality. It is also
practical in the sense that the system (both software and hardware) overheads
are minimal.
| cs.CR cs.AR | sphinx a hardwaresoftware codesign architecture for binary code and runtime obfuscation the sphinx architecture uses binary code diversification and selfreconfigurable processing elements to maintain application functionality while obfuscating the binary code and architecture states to attackers this approach dramatically reduces an attackers ability to exploit information gained from one deployment to attack another deployment our results show that the sphinx is able to decouple the programs execution time power and memory and io activities from its functionality it is also practical in the sense that the system both software and hardware overheads are minimal | [['sphinx', 'a', 'hardwaresoftware', 'codesign', 'architecture', 'for', 'binary', 'code', 'and', 'runtime', 'obfuscation', 'the', 'sphinx', 'architecture', 'uses', 'binary', 'code', 'diversification', 'and', 'selfreconfigurable', 'processing', 'elements', 'to', 'maintain', 'application', 'functionality', 'while', 'obfuscating', 'the', 'binary', 'code', 'and', 'architecture', 'states', 'to', 'attackers', 'this', 'approach', 'dramatically', 'reduces', 'an', 'attackers', 'ability', 'to', 'exploit', 'information', 'gained', 'from', 'one', 'deployment', 'to', 'attack', 'another', 'deployment', 'our', 'results', 'show', 'that', 'the', 'sphinx', 'is', 'able', 'to', 'decouple', 'the', 'programs', 'execution', 'time', 'power', 'and', 'memory', 'and', 'io', 'activities', 'from', 'its', 'functionality', 'it', 'is', 'also', 'practical', 'in', 'the', 'sense', 'that', 'the', 'system', 'both', 'software', 'and', 'hardware', 'overheads', 'are', 'minimal']] | [-0.15344819721785632, -0.003974844541671894, -0.04749701400733295, 0.03695046224140939, -0.12952576605404945, -0.21885328518940098, 0.09047213225827325, 0.39573809459429, -0.3198890481540497, -0.3543130694294071, 0.13366278234567058, -0.2430085177134544, -0.1679876733848706, 0.21754399850528608, -0.16145983841666517, 0.09445276789978999, 0.1362274107065032, -0.02963427621425387, -0.020960257140959195, -0.30988954330616175, 0.2413226572717441, 0.15120115989145447, 0.28390985554668735, 0.03562322796441297, 0.07587697389634683, -0.013413535190766003, 0.01259656433769046, -0.08031567610166174, -0.006120771254651853, 0.12668747902399505, 0.3281516819062861, 0.3149686002648099, 0.2778775137948229, -0.4415203636175299, -0.15772909631437443, 0.005637902927466054, 0.10587892322701976, 0.0958005779378235, -0.04002542962676826, -0.2709503487889417, 0.12534618880500661, -0.2890335811931204, -0.04473527555571909, -0.10905155091685184, -0.01401086964030215, -0.013273978491308801, -0.24128950320857953, -0.1429221472468232, 0.0885327409474833, 0.010412012167433475, -0.02675803523495833, -0.05071771710472023, -0.04541096080619683, 0.17752957551621218, -0.001791271415757055, 0.040022007659067736, 0.19553544130572614, -0.08734764348705636, -0.14510458113472077, 0.34963679779320955, 0.04242937942035496, -0.17357181614027062, 0.22243756377831736, -0.007771204371857358, -0.14677261847487472, 0.1369774896314645, 0.24770059890827126, 0.03867205336412534, -0.17325279322338905, 0.07906011520126993, 0.08346692641126982, 0.2870431149259527, 0.033297945859227726, 0.07295398610802566, 0.18364158359187793, 0.21401454346902182, 0.05819480330187907, 0.17676561977961994, -0.06637017755828639, -0.08732357228848528, -0.18126429606506483, -0.17927614735201636, -0.15953006340745599, -0.03083962639496523, -0.07421071508291247, -0.129073715689493, 0.38968029685635514, 0.2373109014625562, 0.07550641731359065, 0.15583086461621395, 0.4297107791805521, -0.02098311882272878, 0.18486344787054398, 0.2099089486068709, 0.12836104607645502, 0.0005048963865463404, 0.18312813671791253, -0.2513578156494793, 0.14354288978799384, -0.01916807287303295] |
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