id float64 706 1.8k | title stringlengths 1 343 | abstract stringlengths 6 6.09k | categories stringlengths 5 125 | processed_abstract stringlengths 2 5.96k | tokenized_abstract stringlengths 8 8.74k | centroid stringlengths 2.1k 2.17k |
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1,802.0736 | Comparison of the Magnetic properties of Mn3Fe2Si3O12 as a crystalline
garnet and as a glass | The crystalline garnet Mn3Fe2Si3O12 and an amorphous phase of the same
nominal composition are synthesized at high pressure. The magnetic properties
of the two forms are reported. Both phases order antiferromagnetically. The
crystalline phase exhibits a Curie-Weiss theta of -47.2 K, with a sharp
ordering transition at 12 K. The glassy phase exhibits a larger
antiferromagnetic Curie-Weiss theta, of -83.0 K, with a broad ordering
transition observed at 2.5 K. Both phases can be classified as magnetically
frustrated, although the amorphous phase shows a much higher degree of
frustration. The amorphous phase exhibits spin-glass behavior and is determined
to have an actual composition of Mn3Fe2Si3O13.
| cond-mat.mtrl-sci | the crystalline garnet mn3fe2si3o12 and an amorphous phase of the same nominal composition are synthesized at high pressure the magnetic properties of the two forms are reported both phases order antiferromagnetically the crystalline phase exhibits a curieweiss theta of 472 k with a sharp ordering transition at 12 k the glassy phase exhibits a larger antiferromagnetic curieweiss theta of 830 k with a broad ordering transition observed at 25 k both phases can be classified as magnetically frustrated although the amorphous phase shows a much higher degree of frustration the amorphous phase exhibits spinglass behavior and is determined to have an actual composition of mn3fe2si3o13 | [['the', 'crystalline', 'garnet', 'mn3fe2si3o12', 'and', 'an', 'amorphous', 'phase', 'of', 'the', 'same', 'nominal', 'composition', 'are', 'synthesized', 'at', 'high', 'pressure', 'the', 'magnetic', 'properties', 'of', 'the', 'two', 'forms', 'are', 'reported', 'both', 'phases', 'order', 'antiferromagnetically', 'the', 'crystalline', 'phase', 'exhibits', 'a', 'curieweiss', 'theta', 'of', '472', 'k', 'with', 'a', 'sharp', 'ordering', 'transition', 'at', '12', 'k', 'the', 'glassy', 'phase', 'exhibits', 'a', 'larger', 'antiferromagnetic', 'curieweiss', 'theta', 'of', '830', 'k', 'with', 'a', 'broad', 'ordering', 'transition', 'observed', 'at', '25', 'k', 'both', 'phases', 'can', 'be', 'classified', 'as', 'magnetically', 'frustrated', 'although', 'the', 'amorphous', 'phase', 'shows', 'a', 'much', 'higher', 'degree', 'of', 'frustration', 'the', 'amorphous', 'phase', 'exhibits', 'spinglass', 'behavior', 'and', 'is', 'determined', 'to', 'have', 'an', 'actual', 'composition', 'of', 'mn3fe2si3o13']] | [-0.20376257862877642, 0.31891129036842014, -0.07416459931133007, -0.04596534306612951, -0.028175068187337476, -0.14492693763606032, 0.06691048149634334, 0.39793645684580203, -0.24948204631546458, -0.3467072806167371, 0.040211255899494855, -0.3447370760287475, -0.07473902718742713, 0.08278299376223851, 0.10053714038126026, -0.02145270382967389, -0.14304972119466627, 0.03783016170384091, -0.19439977450856885, -0.21138153823761685, 0.20558202326370095, -0.023083544860693438, 0.2731956787479734, 0.009468316209041377, 0.04332672650428507, -0.10007399141571476, 0.2074264602609051, 0.036392452267622485, -0.1706925913063104, -0.011073218712818276, 0.2735004875542216, -0.08342493578646946, 0.12758154620968024, -0.34013011627514095, -0.21061161658681424, 0.05625769789375871, 0.07351601810999286, 0.05079737108526299, -0.039236743039297826, -0.26262563345863404, 0.08090458238877139, -0.10810886474806042, -0.12341111270966261, -0.08820950903577134, -0.029966858125210386, -0.01604724893554394, -0.2728601705680773, 0.12452148584630883, 0.14061241060748553, 0.2065517897943704, -0.0904580020996769, -0.2092934685365921, -0.10175408339308738, 0.048731442572530904, 0.006525646449853349, 0.07481930848975096, 0.1334949117153883, -0.09752690911437702, -0.09311358462476614, 0.40193381797504224, -0.04963701526358615, 0.05787442754688492, 0.20038491722594187, -0.2232565906995713, -0.09318035615843187, 0.29920211714891337, 0.07474261461259815, 0.10006750351071213, -0.09132280296564681, 0.046738554799287284, 0.014952709509548053, 0.2523365597448592, 0.0214693301054423, 0.02898746076293145, 0.24579162389781434, 0.19928624100748052, 0.01413605717300139, 0.23653713721687028, -0.10756650231145684, -0.09104056584250941, -0.18491406801599755, -0.15757947087794252, -0.2211095976204729, 0.038573380989176266, -0.18408763748610582, -0.209191039059926, 0.36069542748256794, 0.09108852908168964, 0.24205812230226992, -0.03943143376529, 0.15791071326589412, 0.07158460109991935, 0.012335137352211744, 0.029955633264939184, 0.2507366683126147, 0.18821724159733474, 0.1750818395137208, -0.22454194867196808, 0.14660259569063783, -0.008552510006516014] |
1,802.07361 | Fault Detection Effectiveness of Source Test Case Generation Strategies
for Metamorphic Testing | Metamorphic testing is a well known approach to tackle the oracle problem in
software testing. This technique requires the use of source test cases that
serve as seeds for the generation of follow-up test cases. Systematic design of
test cases is crucial for the test quality. Thus, source test case generation
strategy can make a big impact on the fault detection effectiveness of
metamorphic testing. Most of the previous studies on metamorphic testing have
used either random test data or existing test cases as source test cases. There
has been limited research done on systematic source test case generation for
metamorphic testing. This paper provides a comprehensive evaluation on the
impact of source test case generation techniques on the fault finding
effectiveness of metamorphic testing. We evaluated the effectiveness of line
coverage, branch coverage, weak mutation and random test generation strategies
for source test case generation. The experiments are conducted with 77 methods
from 4 open source code repositories. Our results show that by systematically
creating source test cases, we can significantly increase the fault finding
effectiveness of metamorphic testing. Further, in this paper we introduce a
simple metamorphic testing tool called "METtester" that we use to conduct
metamorphic testing on these methods.
| cs.SE | metamorphic testing is a well known approach to tackle the oracle problem in software testing this technique requires the use of source test cases that serve as seeds for the generation of followup test cases systematic design of test cases is crucial for the test quality thus source test case generation strategy can make a big impact on the fault detection effectiveness of metamorphic testing most of the previous studies on metamorphic testing have used either random test data or existing test cases as source test cases there has been limited research done on systematic source test case generation for metamorphic testing this paper provides a comprehensive evaluation on the impact of source test case generation techniques on the fault finding effectiveness of metamorphic testing we evaluated the effectiveness of line coverage branch coverage weak mutation and random test generation strategies for source test case generation the experiments are conducted with 77 methods from 4 open source code repositories our results show that by systematically creating source test cases we can significantly increase the fault finding effectiveness of metamorphic testing further in this paper we introduce a simple metamorphic testing tool called mettester that we use to conduct metamorphic testing on these methods | [['metamorphic', 'testing', 'is', 'a', 'well', 'known', 'approach', 'to', 'tackle', 'the', 'oracle', 'problem', 'in', 'software', 'testing', 'this', 'technique', 'requires', 'the', 'use', 'of', 'source', 'test', 'cases', 'that', 'serve', 'as', 'seeds', 'for', 'the', 'generation', 'of', 'followup', 'test', 'cases', 'systematic', 'design', 'of', 'test', 'cases', 'is', 'crucial', 'for', 'the', 'test', 'quality', 'thus', 'source', 'test', 'case', 'generation', 'strategy', 'can', 'make', 'a', 'big', 'impact', 'on', 'the', 'fault', 'detection', 'effectiveness', 'of', 'metamorphic', 'testing', 'most', 'of', 'the', 'previous', 'studies', 'on', 'metamorphic', 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1,802.07362 | Statistical Software for Psychology: Comparing Development Practices
Between CRAN and Other Communities | Different communities rely heavily on software, but use quite different
software development practices. {\bf Objective}: We wanted to measure the state
of the practice in the area of statistical software for psychology to
understand how it compares to best practices. {\bf Method}: We compared and
ranked 30 software tools with respect to adherence to best software engineering
practices on items that could be measured by end-users. {\bf Results} We found
that R packages use quite good practices, that while commercial packages were
quite usable, many aspects of their development is too opaque to be measures,
and that research projects vary a lot in their practices. {\bf Conclusion} We
recommend that more organizations adopt practices similar to those used by CRAN
to facilitate success, even for small teams. We also recommend close coupling
of source code and documentation, to improve verifiability.
| cs.SE | different communities rely heavily on software but use quite different software development practices bf objective we wanted to measure the state of the practice in the area of statistical software for psychology to understand how it compares to best practices bf method we compared and ranked 30 software tools with respect to adherence to best software engineering practices on items that could be measured by endusers bf results we found that r packages use quite good practices that while commercial packages were quite usable many aspects of their development is too opaque to be measures and that research projects vary a lot in their practices bf conclusion we recommend that more organizations adopt practices similar to those used by cran to facilitate success even for small teams we also recommend close coupling of source code and documentation to improve verifiability | [['different', 'communities', 'rely', 'heavily', 'on', 'software', 'but', 'use', 'quite', 'different', 'software', 'development', 'practices', 'bf', 'objective', 'we', 'wanted', 'to', 'measure', 'the', 'state', 'of', 'the', 'practice', 'in', 'the', 'area', 'of', 'statistical', 'software', 'for', 'psychology', 'to', 'understand', 'how', 'it', 'compares', 'to', 'best', 'practices', 'bf', 'method', 'we', 'compared', 'and', 'ranked', '30', 'software', 'tools', 'with', 'respect', 'to', 'adherence', 'to', 'best', 'software', 'engineering', 'practices', 'on', 'items', 'that', 'could', 'be', 'measured', 'by', 'endusers', 'bf', 'results', 'we', 'found', 'that', 'r', 'packages', 'use', 'quite', 'good', 'practices', 'that', 'while', 'commercial', 'packages', 'were', 'quite', 'usable', 'many', 'aspects', 'of', 'their', 'development', 'is', 'too', 'opaque', 'to', 'be', 'measures', 'and', 'that', 'research', 'projects', 'vary', 'a', 'lot', 'in', 'their', 'practices', 'bf', 'conclusion', 'we', 'recommend', 'that', 'more', 'organizations', 'adopt', 'practices', 'similar', 'to', 'those', 'used', 'by', 'cran', 'to', 'facilitate', 'success', 'even', 'for', 'small', 'teams', 'we', 'also', 'recommend', 'close', 'coupling', 'of', 'source', 'code', 'and', 'documentation', 'to', 'improve', 'verifiability']] | [-0.03770054603269923, -0.0006637809166152562, -0.06653040761261114, 0.08615692098974251, -0.16535686123949875, -0.18776466815314571, 0.0734676986134478, 0.480932961085013, -0.21387141532530743, -0.36395658206602094, 0.08256604200661448, -0.2773708445585466, -0.12449603519510544, 0.24149517478820468, -0.1502953744559948, 0.05028672769466149, 0.09154833293536545, -0.024793188267254403, -0.0404093360727919, -0.3217117509804666, 0.25131782263384334, 0.11728053030424884, 0.3733670384223972, 0.04617908291319119, -0.05222702342434786, -0.06422987465879747, -0.06942585171865566, -0.021496340772137044, -0.13836078843664187, 0.15699465916758137, 0.4230407756221082, 0.26793679940913406, 0.3374524661872004, -0.4100546594775681, -0.11408800966372447, 0.02750280324502715, 0.11950307050220935, 0.02857776079825791, 0.019858361073420382, -0.29068014236566214, 0.08569232032833887, -0.2325277055447389, -0.10349209494223552, -0.13699647251383534, 0.000645951510939215, 0.023908036863680798, -0.21741915242746473, -0.04381999755132711, -0.01757195950984689, 0.10306376547752215, 0.006544050725642592, -0.1741049373788493, -0.0041700420235948905, 0.19385031747099543, 0.1138586112813625, 0.07173840213633542, 0.19628097788164658, -0.13095357061496804, -0.12126119346025267, 0.4121907815736319, -0.02289349498626377, -0.19584807403319116, 0.2411617659032345, -0.06896216772895838, -0.16768578855387334, 0.0665533771804933, 0.20591387002329742, 0.04132244201110942, -0.21324218860162156, 0.0390653041112403, 0.04774064181256108, 0.2161420227128214, 0.06276771633087525, -0.0143332302154574, 0.178775796483803, 0.12483270899974741, 0.036673817207754054, 0.05667999735284996, 0.0406622106442228, -0.08283762183397941, -0.20913437401426824, -0.12390638782110597, -0.15609164146839508, 0.013047657231800259, -0.023403469748882345, -0.15642527058454497, 0.36896739383061816, 0.26017004349934203, 0.055499844712072186, 0.01509002698585391, 0.2754067181210433, -0.028627562409799013, 0.1089702918185919, 0.12414439393074385, 0.20463701055850833, 0.01033662793093494, 0.15908020297896916, -0.10811927017556237, 0.13714331766656998, -0.07671391213745145] |
1,802.07363 | Mean Field Approximations to a Queueing System with Threshold-Based
Workload Control Scheme | In this paper, motivated by considerations of server utilization and energy
consumptions in cloud computing, we investigate a homogeneous queueing system
with a threshold-based workload control scheme. In this system, a virtual
machine will be turned off when there are no tasks in its buffer upon the
completion of a service by the machine, and turned on when the number of tasks
in its buffer reaches a pre-set threshold value. Due to complexity of this
system, we propose approximations to system performance measures by mean field
limits. An iterative algorithm is suggested for the solution to the mean field
limit equations. In addition, numerical and simulation results are presented to
justify the proposed approximation method and to provide a numerical analysis
on the impact of the system performances by system parameters.
| math.PR | in this paper motivated by considerations of server utilization and energy consumptions in cloud computing we investigate a homogeneous queueing system with a thresholdbased workload control scheme in this system a virtual machine will be turned off when there are no tasks in its buffer upon the completion of a service by the machine and turned on when the number of tasks in its buffer reaches a preset threshold value due to complexity of this system we propose approximations to system performance measures by mean field limits an iterative algorithm is suggested for the solution to the mean field limit equations in addition numerical and simulation results are presented to justify the proposed approximation method and to provide a numerical analysis on the impact of the system performances by system parameters | [['in', 'this', 'paper', 'motivated', 'by', 'considerations', 'of', 'server', 'utilization', 'and', 'energy', 'consumptions', 'in', 'cloud', 'computing', 'we', 'investigate', 'a', 'homogeneous', 'queueing', 'system', 'with', 'a', 'thresholdbased', 'workload', 'control', 'scheme', 'in', 'this', 'system', 'a', 'virtual', 'machine', 'will', 'be', 'turned', 'off', 'when', 'there', 'are', 'no', 'tasks', 'in', 'its', 'buffer', 'upon', 'the', 'completion', 'of', 'a', 'service', 'by', 'the', 'machine', 'and', 'turned', 'on', 'when', 'the', 'number', 'of', 'tasks', 'in', 'its', 'buffer', 'reaches', 'a', 'preset', 'threshold', 'value', 'due', 'to', 'complexity', 'of', 'this', 'system', 'we', 'propose', 'approximations', 'to', 'system', 'performance', 'measures', 'by', 'mean', 'field', 'limits', 'an', 'iterative', 'algorithm', 'is', 'suggested', 'for', 'the', 'solution', 'to', 'the', 'mean', 'field', 'limit', 'equations', 'in', 'addition', 'numerical', 'and', 'simulation', 'results', 'are', 'presented', 'to', 'justify', 'the', 'proposed', 'approximation', 'method', 'and', 'to', 'provide', 'a', 'numerical', 'analysis', 'on', 'the', 'impact', 'of', 'the', 'system', 'performances', 'by', 'system', 'parameters']] | [-0.1593515406867475, 0.018274463029895584, -0.1008479929820613, 0.008722391578489702, -0.0027932980673686237, -0.13531780178224995, 0.152552361448139, 0.3852846058554777, -0.258838590890354, -0.33138845043384846, 0.1300671131755332, -0.23982834703473815, -0.1280388067128094, 0.22587190553517514, -0.11621424675926224, 0.09769953040935753, 0.09602038797972198, 0.053754792803096876, -0.04302975218138792, -0.2900466624263475, 0.3041105117606184, 0.09676517973625536, 0.31332092155979674, 0.06433336352680646, 0.0948264699665659, -0.020236622311089556, 0.011527963416323861, 0.024853726806303926, -0.10399325633819663, 0.08634301576983781, 0.23554295304281112, 0.14916259079517527, 0.32880839536265105, -0.42291671678935755, -0.19104656827358799, 0.07880248539620754, 0.1391945537108615, 0.07300198716573587, -0.03838149433287273, -0.26729792137523645, 0.10879520826638882, -0.2027563861169575, -0.09974027199684891, -0.08460084504611393, -0.006204366888353274, 0.04207564849861478, -0.28007719340158327, -0.01595359910030686, 0.01668475278678087, 0.038884360648919154, -0.07613814274695141, -0.08741827093185643, 0.05657304944968178, 0.10172760827361983, 0.06769041158614382, 0.011349319800279523, 0.15101203153563933, -0.15948082429342655, -0.11702730291956709, 0.39828927377381057, -0.05773815908291526, -0.23319876267937303, 0.15906480260420847, -0.054835624527186155, -0.10260766395189949, 0.13506163750910236, 0.23493890679007723, 0.08101866122349415, -0.16769815561337617, 0.0750369859862902, -0.0009356540599340246, 0.17782324124554186, 0.011465105498280689, -0.001926389498856516, 0.15090795336397833, 0.23048645566139397, 0.09070168911898864, 0.16813084471505135, -0.04113243231443219, -0.11418745549793803, -0.2494242276697782, -0.13940246644223692, -0.18085160181423976, 0.009408112354078934, -0.06483720055601794, -0.12439966671353647, 0.35141030685426394, 0.18540025663825163, 0.16839752184717652, 0.07740970073402895, 0.3631818150347881, 0.17542776348467432, 0.021839207162696668, 0.13559536494399982, 0.2118728640844747, 0.08103440254606761, 0.15187955163561434, -0.2399197119600957, 0.052166384856309034, 0.05576622397247844] |
1,802.07364 | Controlling stability and transport of magnetic microswimmers by an
external field | We investigate the hydrodynamic stability and transport of magnetic
microswimmers in an external field using a kinetic theory framework. Combining
linear stability analysis and nonlinear 3D continuum simulations, we show that
for sufficiently large activity and magnetic field strengths, a homogeneous
polar steady state is unstable for both puller and pusher swimmers. This
instability is caused by the amplification of anisotropic hydrodynamic
interactions due to the external alignment and leads to a partial
depolarization and a reduction of the average transport speed of the swimmers
in the field direction. Notably, at higher field strengths a reentrant
hydrodynamic stability emerges where the homogeneous polar state becomes stable
and a transport efficiency identical to that of active particles without
hydrodynamic interactions is restored.
| cond-mat.soft cond-mat.stat-mech nlin.PS | we investigate the hydrodynamic stability and transport of magnetic microswimmers in an external field using a kinetic theory framework combining linear stability analysis and nonlinear 3d continuum simulations we show that for sufficiently large activity and magnetic field strengths a homogeneous polar steady state is unstable for both puller and pusher swimmers this instability is caused by the amplification of anisotropic hydrodynamic interactions due to the external alignment and leads to a partial depolarization and a reduction of the average transport speed of the swimmers in the field direction notably at higher field strengths a reentrant hydrodynamic stability emerges where the homogeneous polar state becomes stable and a transport efficiency identical to that of active particles without hydrodynamic interactions is restored | [['we', 'investigate', 'the', 'hydrodynamic', 'stability', 'and', 'transport', 'of', 'magnetic', 'microswimmers', 'in', 'an', 'external', 'field', 'using', 'a', 'kinetic', 'theory', 'framework', 'combining', 'linear', 'stability', 'analysis', 'and', 'nonlinear', '3d', 'continuum', 'simulations', 'we', 'show', 'that', 'for', 'sufficiently', 'large', 'activity', 'and', 'magnetic', 'field', 'strengths', 'a', 'homogeneous', 'polar', 'steady', 'state', 'is', 'unstable', 'for', 'both', 'puller', 'and', 'pusher', 'swimmers', 'this', 'instability', 'is', 'caused', 'by', 'the', 'amplification', 'of', 'anisotropic', 'hydrodynamic', 'interactions', 'due', 'to', 'the', 'external', 'alignment', 'and', 'leads', 'to', 'a', 'partial', 'depolarization', 'and', 'a', 'reduction', 'of', 'the', 'average', 'transport', 'speed', 'of', 'the', 'swimmers', 'in', 'the', 'field', 'direction', 'notably', 'at', 'higher', 'field', 'strengths', 'a', 'reentrant', 'hydrodynamic', 'stability', 'emerges', 'where', 'the', 'homogeneous', 'polar', 'state', 'becomes', 'stable', 'and', 'a', 'transport', 'efficiency', 'identical', 'to', 'that', 'of', 'active', 'particles', 'without', 'hydrodynamic', 'interactions', 'is', 'restored']] | [-0.2215448910378166, 0.2017575899680955, -0.057992574567367776, 0.041235345796766604, -0.027506193854222614, -0.11455637004903772, -0.018838288147033245, 0.344293409619819, -0.284279403569223, -0.2761597652252848, 0.04964230215650298, -0.20845466243749686, -0.1297384115659501, 0.13556270210133972, 0.03550710184268715, 0.0032722938359399474, 0.01739857394309822, -0.01811684415606428, -0.018650204751425047, -0.14461209855142457, 0.27118988586050913, 0.08386692446310165, 0.31215632460580384, 0.028145585609369042, 0.12113706783722501, -0.005429873824088781, 0.046756072042987123, 0.12665027977556206, -0.125392117080195, 0.05642796490603119, 0.16921181166890917, -0.0339688133017337, 0.23060420779742238, -0.47238104801224773, -0.24426332504819492, 0.04878479645641382, 0.1697681113954418, 0.1903477681431273, -0.08834045010446648, -0.2411568243756952, 0.05931715803482562, -0.14468658993728767, -0.15648569691395156, -0.09163084636973448, 0.02739698714422724, 0.06249812676394281, -0.3202295241384836, 0.13057638054294127, 0.10206838601176466, 0.12515592057265587, -0.12304887103594163, -0.02911538264737272, -0.059072760922818886, 0.09896454821275316, 0.0710323324238435, 0.041522692900520464, 0.19282224226342745, -0.23503068532055812, -0.06460252348025722, 0.38330400493842637, -0.09360647185086003, -0.20374347796386555, 0.263833844206827, -0.14297456386275897, -0.033191974861701286, 0.20619728300751242, 0.21328379791076027, 0.10843550973025358, -0.0860320187735656, 0.048134178531737154, -0.0018374752484200414, 0.15824593549925248, 0.029519738814185473, -0.032523264681289264, 0.2254020961671144, 0.18035212745659115, 0.04283982255950201, 0.14874957428767907, -0.11967791154911388, -0.13311168604938328, -0.25176776676200147, -0.13690258685714943, -0.11943793360698075, 0.07228362484938997, -0.10008171354148687, -0.1583717311424596, 0.3690885020158261, 0.15146148623898625, 0.15465094653258393, 0.013035733322035675, 0.304159517576995, 0.09641736828190975, 0.008187906279744318, 0.09055454046888785, 0.33108173009038955, 0.19950392730880437, 0.1298956260131287, -0.31840364228210544, 0.013931582235415612, 0.052254405934825415] |
1,802.07365 | Lorentz-violating contributions to the nuclear Schiff moment and nuclear
EDM | In the context of an atom endowed with nuclear electric dipole moment (EDM),
we consider the effects on the Schiff moment of $CPT$-even Lorentz-violating
(LV) terms that modify the Coulomb potential. First, we study the modifications
on the Schiff moment when the nucleus interacts with the electronic cloud by
means of a Coulomb potential altered only by the $P$-even LV components. Next,
by supposing the existence of an additional intrinsic LV EDM generated by other
LV sources, we assess the corrections to the Schiff moment when the interaction
nucleus-electrons runs mediated by a Coulomb potential modified by both the
$P$-odd and $P$-even LV components. We then use known estimates and EDM
measurements to discuss upper bounds on the new Schiff moment components and
the possibility of an intrisic nuclear EDM component ascribed to LV effects.
| hep-ph hep-th nucl-th | in the context of an atom endowed with nuclear electric dipole moment edm we consider the effects on the schiff moment of cpteven lorentzviolating lv terms that modify the coulomb potential first we study the modifications on the schiff moment when the nucleus interacts with the electronic cloud by means of a coulomb potential altered only by the peven lv components next by supposing the existence of an additional intrinsic lv edm generated by other lv sources we assess the corrections to the schiff moment when the interaction nucleuselectrons runs mediated by a coulomb potential modified by both the podd and peven lv components we then use known estimates and edm measurements to discuss upper bounds on the new schiff moment components and the possibility of an intrisic nuclear edm component ascribed to lv effects | [['in', 'the', 'context', 'of', 'an', 'atom', 'endowed', 'with', 'nuclear', 'electric', 'dipole', 'moment', 'edm', 'we', 'consider', 'the', 'effects', 'on', 'the', 'schiff', 'moment', 'of', 'cpteven', 'lorentzviolating', 'lv', 'terms', 'that', 'modify', 'the', 'coulomb', 'potential', 'first', 'we', 'study', 'the', 'modifications', 'on', 'the', 'schiff', 'moment', 'when', 'the', 'nucleus', 'interacts', 'with', 'the', 'electronic', 'cloud', 'by', 'means', 'of', 'a', 'coulomb', 'potential', 'altered', 'only', 'by', 'the', 'peven', 'lv', 'components', 'next', 'by', 'supposing', 'the', 'existence', 'of', 'an', 'additional', 'intrinsic', 'lv', 'edm', 'generated', 'by', 'other', 'lv', 'sources', 'we', 'assess', 'the', 'corrections', 'to', 'the', 'schiff', 'moment', 'when', 'the', 'interaction', 'nucleuselectrons', 'runs', 'mediated', 'by', 'a', 'coulomb', 'potential', 'modified', 'by', 'both', 'the', 'podd', 'and', 'peven', 'lv', 'components', 'we', 'then', 'use', 'known', 'estimates', 'and', 'edm', 'measurements', 'to', 'discuss', 'upper', 'bounds', 'on', 'the', 'new', 'schiff', 'moment', 'components', 'and', 'the', 'possibility', 'of', 'an', 'intrisic', 'nuclear', 'edm', 'component', 'ascribed', 'to', 'lv', 'effects']] | [-0.10261936419675606, 0.16452836469908283, 0.0363087121609237, 0.11041916633692028, -0.05715890269754315, -0.053161866657102284, 0.04918053972147363, 0.2743325247203431, -0.23988024990852755, -0.2851773909946431, 0.00962272393013309, -0.33783295196689556, -0.08022102005970873, 0.1405362419283657, 0.037147498050176385, -0.05642856184198563, -0.017126599714201666, 0.0696719545982222, -0.045109380695120944, -0.21659697716145207, 0.3265929810751452, 0.055251813618772065, 0.1987760747407577, 0.13179772528356035, 0.07692856256460855, 0.05172794831763786, 0.004412076269179138, 0.03268173451660507, -0.07652897836924782, 0.1438752678917971, 0.07333124227128547, 0.027829954835044135, 0.15830885389917043, -0.4738947081365692, -0.11647216748418425, 0.12840389759269363, 0.07208067253092999, 0.08594167677324209, -0.10031578063864066, -0.35476025801200645, 0.008871054940347893, -0.21990695529019655, -0.15446056032886923, -0.12405628981346738, 0.06079351668134888, 0.04488493058545543, -0.35090905318815097, 0.07924160038454653, 0.058784827834982144, 0.011888987886669016, -0.09400395274426399, -0.18269750796981268, 0.041158036898765994, 0.04892733059832201, 0.09717590090342616, 0.06486014233478136, 0.18734788011981926, -0.17188170306912776, -0.12220208066751931, 0.40244227094547963, -0.12959291767884992, -0.18200142981150924, 0.10437430915207283, -0.17005984288807124, -0.1264878064254994, 0.05929323408488574, 0.1744385366467064, 0.08120275236694004, -0.20325444598874223, 0.17009549680966954, 0.03061496820161814, 0.146994662116657, 0.03297433795741023, 0.0015236391831856611, 0.21324830627722194, 0.09244077008759687, 0.0546134172197811, 0.10300483777745516, -0.1714994684052862, -0.02497225341303691, -0.3402429418221338, -0.09281609793464694, -0.17988789838099323, 0.03518888545083577, -0.06829617665127118, -0.08758472935722293, 0.3780966822365073, 0.14030553815789076, 0.1365616640350573, -0.08537459291462134, 0.32041657918980765, 0.11694188558395757, 0.11571878505481491, 0.012604759599485281, 0.33857367510573744, 0.1846552924843811, 0.015213729612140068, -0.36312818528959223, 0.0795140007246675, 0.12786282259109083] |
1,802.07366 | Free complete Wasserstein algebras | We present an algebraic account of the Wasserstein distances $W_p$ on
complete metric spaces, for $p \geq 1$. This is part of a program of a
quantitative algebraic theory of effects in programming languages. In
particular, we give axioms, parametric in $p$, for algebras over metric spaces
equipped with probabilistic choice operations. The axioms say that the
operations form a barycentric algebra and that the metric satisfies a property
typical of the Wasserstein distance $W_p$. We show that the free complete such
algebra over a complete metric space is that of the Radon probability measures
with finite moments of order $p$, equipped with the Wasserstein distance as
metric and with the usual binary convex sums as operations.
| cs.LO | we present an algebraic account of the wasserstein distances w_p on complete metric spaces for p geq 1 this is part of a program of a quantitative algebraic theory of effects in programming languages in particular we give axioms parametric in p for algebras over metric spaces equipped with probabilistic choice operations the axioms say that the operations form a barycentric algebra and that the metric satisfies a property typical of the wasserstein distance w_p we show that the free complete such algebra over a complete metric space is that of the radon probability measures with finite moments of order p equipped with the wasserstein distance as metric and with the usual binary convex sums as operations | [['we', 'present', 'an', 'algebraic', 'account', 'of', 'the', 'wasserstein', 'distances', 'w_p', 'on', 'complete', 'metric', 'spaces', 'for', 'p', 'geq', '1', 'this', 'is', 'part', 'of', 'a', 'program', 'of', 'a', 'quantitative', 'algebraic', 'theory', 'of', 'effects', 'in', 'programming', 'languages', 'in', 'particular', 'we', 'give', 'axioms', 'parametric', 'in', 'p', 'for', 'algebras', 'over', 'metric', 'spaces', 'equipped', 'with', 'probabilistic', 'choice', 'operations', 'the', 'axioms', 'say', 'that', 'the', 'operations', 'form', 'a', 'barycentric', 'algebra', 'and', 'that', 'the', 'metric', 'satisfies', 'a', 'property', 'typical', 'of', 'the', 'wasserstein', 'distance', 'w_p', 'we', 'show', 'that', 'the', 'free', 'complete', 'such', 'algebra', 'over', 'a', 'complete', 'metric', 'space', 'is', 'that', 'of', 'the', 'radon', 'probability', 'measures', 'with', 'finite', 'moments', 'of', 'order', 'p', 'equipped', 'with', 'the', 'wasserstein', 'distance', 'as', 'metric', 'and', 'with', 'the', 'usual', 'binary', 'convex', 'sums', 'as', 'operations']] | [-0.1509369403306936, 0.06553524231419273, -0.1299099801864443, 0.12025587293060704, -0.07619472761821543, -0.09627287759660529, 0.027636959568724737, 0.3601785679208513, -0.3430058030236481, -0.20548008853628333, 0.05859642192566147, -0.28942756512417245, -0.12477681362348744, 0.18148380663627997, -0.14498604357672426, 0.029277350021223735, 0.07129912944231978, 0.12129638473001811, -0.16737329443263957, -0.23134958097197783, 0.41391024807404375, -0.005044887632402217, 0.20467966246920136, -0.00040066860711727385, 0.17049418779042286, 0.0542277103711843, 0.008152640814709866, 0.08423551418355857, -0.1840695176668103, 0.1327523154576715, 0.2686735148358549, 0.19011832346630275, 0.27878020859809005, -0.3693632753486307, -0.15236721922142002, 0.16491851681031477, 0.024397966409655303, -0.02223168229326033, 0.004140182178364032, -0.27668831036645025, 0.08574008712003756, -0.16622900544132432, -0.09108492855328876, -0.07571338186374842, 0.08767026428801891, 0.026459151457071815, -0.3024306351111995, -0.010563060935809571, 0.12481345540374263, 0.11811914400826408, -0.06906659845620967, -0.09478016646427667, -0.005256313122172131, 0.061940959805988856, -0.013048700466911253, 0.10965432485756584, 0.0643743281551183, -0.0017008536587803601, -0.16314558059267667, 0.3768257842688726, -0.06557233624645852, -0.2580609490386505, 0.10926307001525265, -0.1761690983787561, -0.14029985629658923, 0.05816328840760084, 0.15716879402534065, 0.15790445529497588, -0.0814707362268152, 0.19677006169799396, -0.05783818863107401, 0.10761031405761456, 0.07670167753170444, 0.08706783904877101, 0.09883379159320115, 0.12386351993952233, 0.1444921838438027, 0.13852646158068863, -0.017553795139010772, -0.06651084188224636, -0.3786642321775484, -0.19418740660971046, -0.16175773212861302, 0.09298236058372208, -0.19733929375368647, -0.20208542286139777, 0.3220528981839426, 0.059764287474318445, 0.16680591337932035, 0.17914477247012478, 0.259922706338967, 0.07256330670510283, 0.07473651086115557, 0.07455293788041314, 0.12870144781021753, 0.18016547518264917, 0.01614135805453755, -0.11557553259210072, 0.04130175605050137, 0.1543109647762508] |
1,802.07367 | Strain Fields in Repulsive Colloidal Crystals | The concept of a local linear elastic strain field is commonly used in the
metallurgical research community to approximate the collective effect of atomic
displacements around crystalline defects. Here we show that the elastic strain
field approximation is a useful tool in colloidal systems. For colloidal
crystals with repulsive particle interaction potentials, given similar
mechanical properties, sharper potentials lead to: 1) free energies of
deformation dominated by entropy, 2) lower variance in strain field
fluctuations, 3) increased tension-compression asymmetry near dislocation core
regions, and 4) smaller windows of applicability of the linear elastic
approximation. We show that the window of linear behavior for entropic
colloidal crystals is broadened for pressures at which the inter-particle
separation sufficiently exceeds the range of steep repulsive interactions.
| cond-mat.soft | the concept of a local linear elastic strain field is commonly used in the metallurgical research community to approximate the collective effect of atomic displacements around crystalline defects here we show that the elastic strain field approximation is a useful tool in colloidal systems for colloidal crystals with repulsive particle interaction potentials given similar mechanical properties sharper potentials lead to 1 free energies of deformation dominated by entropy 2 lower variance in strain field fluctuations 3 increased tensioncompression asymmetry near dislocation core regions and 4 smaller windows of applicability of the linear elastic approximation we show that the window of linear behavior for entropic colloidal crystals is broadened for pressures at which the interparticle separation sufficiently exceeds the range of steep repulsive interactions | [['the', 'concept', 'of', 'a', 'local', 'linear', 'elastic', 'strain', 'field', 'is', 'commonly', 'used', 'in', 'the', 'metallurgical', 'research', 'community', 'to', 'approximate', 'the', 'collective', 'effect', 'of', 'atomic', 'displacements', 'around', 'crystalline', 'defects', 'here', 'we', 'show', 'that', 'the', 'elastic', 'strain', 'field', 'approximation', 'is', 'a', 'useful', 'tool', 'in', 'colloidal', 'systems', 'for', 'colloidal', 'crystals', 'with', 'repulsive', 'particle', 'interaction', 'potentials', 'given', 'similar', 'mechanical', 'properties', 'sharper', 'potentials', 'lead', 'to', '1', 'free', 'energies', 'of', 'deformation', 'dominated', 'by', 'entropy', '2', 'lower', 'variance', 'in', 'strain', 'field', 'fluctuations', '3', 'increased', 'tensioncompression', 'asymmetry', 'near', 'dislocation', 'core', 'regions', 'and', '4', 'smaller', 'windows', 'of', 'applicability', 'of', 'the', 'linear', 'elastic', 'approximation', 'we', 'show', 'that', 'the', 'window', 'of', 'linear', 'behavior', 'for', 'entropic', 'colloidal', 'crystals', 'is', 'broadened', 'for', 'pressures', 'at', 'which', 'the', 'interparticle', 'separation', 'sufficiently', 'exceeds', 'the', 'range', 'of', 'steep', 'repulsive', 'interactions']] | [-0.1178998996284071, 0.23847126601097302, -0.09081352330466005, 0.04826231985977601, -0.018658464297470524, -0.1365376413171369, -0.011736939594005727, 0.3807578752862244, -0.2988801194407894, -0.27323415110690324, -0.008314005734315672, -0.28102473582602977, -0.12423876678851259, 0.14848080331107555, 0.04402702180592994, 0.0713931822967602, -0.017126256471302937, -0.02339408306662387, -0.04395647486955745, -0.18085141785866846, 0.2582112447154231, 0.06423725032747336, 0.31064623978076034, 0.11024841105913728, 0.04738106446840414, 0.051821513238696125, 0.09376924816988469, 0.09778699675968629, -0.19660402287038636, 0.09495059957318916, 0.2516996360320515, -0.0568938356051903, 0.2631558412534556, -0.44508498725367757, -0.2216501478702057, 0.09852480758890146, 0.14110609505143834, 0.13587218165166706, -0.05892905320004916, -0.24147352101129851, 0.053173822290226214, -0.12877270003886726, -0.17244252168414434, -0.07724546102856142, 0.07020221471055828, 0.06268536755095834, -0.2512758013951342, 0.1718065003841752, 0.06610563262962033, 0.10974292541907085, -0.13818040643856536, -0.10606286240499316, -0.004999838354883761, 0.018006890398881783, 0.053151593927854325, 0.018411950795055646, 0.2708584487332198, -0.16192642216971978, -0.05151915520702193, 0.39754246364582363, -0.05108648600299063, -0.13374832532429173, 0.18632222391755843, -0.12934492567432967, -0.07985838574009031, 0.22829339329751466, 0.1948436991637194, 0.06525554567408877, -0.10779187115802755, 0.07049834901964806, 0.05745672305754378, 0.19412593306534418, 0.10498813561701435, 0.015630951942497393, 0.20768795601410292, 0.18034616296039516, 0.07446752672227538, 0.14885670359708308, -0.0946534577817694, -0.07868089694984076, -0.2723797053473479, -0.12689839676401116, -0.21780405939950387, 0.007459112047495811, -0.15045843228716232, -0.19126839221008424, 0.33372728323669937, 0.09751574668987859, 0.1332375689076517, 0.03005324084807672, 0.19593589292551444, 0.07844768229841702, 0.08390531348200833, 0.011155729655297549, 0.31914732272062846, 0.16989253589133846, 0.09512889251203799, -0.240229232403321, 0.027371763104073157, 0.01599678231925681] |
1,802.07368 | Gaussian Random Number Generator: Implemented in FPGA for Quantum Key
Distribution | Quantum Key Distribution is the process of using quantum communication to
establish a shared key between two parties. It has been demonstrated the
unconditional security and effective communication of quantum communication
system can be guaranteed by an excellent Gaussian random number generator with
high speed and an extended random period. In this paper, we propose to
construct the Gaussian random number generator using Field-Programmable Gate
Array (FPGA) which is able to process large data in high speed. We also compare
three algorithms ofGRNgeneration: Box-Muller algorithm, polarization decision
algorithm, and central limit algorithm. We demonstrate that the polarization
decision algorithm implemented inFPGArequires less computing resources and also
produces a high-quality Gaussian random number, through the null hypothesis
test.
| eess.SP | quantum key distribution is the process of using quantum communication to establish a shared key between two parties it has been demonstrated the unconditional security and effective communication of quantum communication system can be guaranteed by an excellent gaussian random number generator with high speed and an extended random period in this paper we propose to construct the gaussian random number generator using fieldprogrammable gate array fpga which is able to process large data in high speed we also compare three algorithms ofgrngeneration boxmuller algorithm polarization decision algorithm and central limit algorithm we demonstrate that the polarization decision algorithm implemented infpgarequires less computing resources and also produces a highquality gaussian random number through the null hypothesis test | [['quantum', 'key', 'distribution', 'is', 'the', 'process', 'of', 'using', 'quantum', 'communication', 'to', 'establish', 'a', 'shared', 'key', 'between', 'two', 'parties', 'it', 'has', 'been', 'demonstrated', 'the', 'unconditional', 'security', 'and', 'effective', 'communication', 'of', 'quantum', 'communication', 'system', 'can', 'be', 'guaranteed', 'by', 'an', 'excellent', 'gaussian', 'random', 'number', 'generator', 'with', 'high', 'speed', 'and', 'an', 'extended', 'random', 'period', 'in', 'this', 'paper', 'we', 'propose', 'to', 'construct', 'the', 'gaussian', 'random', 'number', 'generator', 'using', 'fieldprogrammable', 'gate', 'array', 'fpga', 'which', 'is', 'able', 'to', 'process', 'large', 'data', 'in', 'high', 'speed', 'we', 'also', 'compare', 'three', 'algorithms', 'ofgrngeneration', 'boxmuller', 'algorithm', 'polarization', 'decision', 'algorithm', 'and', 'central', 'limit', 'algorithm', 'we', 'demonstrate', 'that', 'the', 'polarization', 'decision', 'algorithm', 'implemented', 'infpgarequires', 'less', 'computing', 'resources', 'and', 'also', 'produces', 'a', 'highquality', 'gaussian', 'random', 'number', 'through', 'the', 'null', 'hypothesis', 'test']] | [-0.15011732589615429, 0.10263531871529741, -0.08216711943564207, 0.04402961280091246, -0.03532704181321289, -0.2281438619789222, 0.07606978062843985, 0.43903010701355727, -0.2592708555495609, -0.3288895705309899, 0.0921252468864069, -0.19354251038445078, -0.16068451827310998, 0.22681979520813278, -0.08924379821299859, 0.16013075308469327, 0.06512432424098497, 0.011000204205755953, 0.01790938659080142, -0.30131666777331545, 0.23020400519928205, 0.10065542253078488, 0.3470537665826471, -0.017560711393699698, 0.1394424903905019, 0.039719178444584426, -0.01376191489120095, -0.028550468563385632, -0.04577847327663735, 0.10801187305427763, 0.24125653985158904, 0.1839131206901663, 0.30506602417191736, -0.42213473491694614, -0.14336863910860342, 0.1302860795641723, 0.1512054484742491, 0.1256950121241338, -0.05389317943836036, -0.28418633898963097, 0.10128259932440098, -0.20717391509400762, -0.08955003579309129, -0.09795746862402428, -0.03261485571122688, 0.019525821814718455, -0.30447868109559234, -0.022490647914768805, 0.010580477069901383, 0.043378620902481284, 0.04782834195167474, -0.05732398908079157, 0.0441983450771026, 0.1136187846812865, -0.0345292194427558, 0.051737263418086196, 0.12365859947774721, -0.0671044375990396, -0.19359752701838379, 0.3063335167689492, -0.0676494582819388, -0.19878074159926695, 0.17188136584084968, -0.09367848842850197, -0.13685406581296222, 0.1148894928800671, 0.23057915048430797, 0.0523471408078204, -0.17535993990528842, 0.07550026859237773, -0.020290731689285326, 0.2095410708844176, 0.052115286866445905, 0.05735057077077015, 0.16213167588955357, 0.16150172356030215, 0.08613958239109944, 0.19090345729365135, -0.10799159156968412, -0.1339401647893955, -0.2637497100047767, -0.17820280870402475, -0.2625871601595503, 0.027576995851553005, -0.1491682256283441, -0.1454275716551701, 0.34947105474446133, 0.20997434484053645, 0.14187109238751558, 0.09386841636252306, 0.35570321073755623, 0.11805301264900228, 0.03396663845924195, 0.16846258513953374, 0.15204766805121755, 0.14654678137284582, 0.07315269257144436, -0.16808523925264243, 0.10192517276205447, 0.010550040281985118] |
1,802.07369 | On the Statistical Challenges of Echo State Networks and Some Potential
Remedies | Echo state networks are powerful recurrent neural networks. However, they are
often unstable and shaky, making the process of finding an good ESN for a
specific dataset quite hard. Obtaining a superb accuracy by using the Echo
State Network is a challenging task. We create, develop and implement a family
of predictably optimal robust and stable ensemble of Echo State Networks via
regularizing the training and perturbing the input. Furthermore, several
distributions of weights have been tried based on the shape to see if the shape
of the distribution has the impact for reducing the error. We found ESN can
track in short term for most dataset, but it collapses in the long run.
Short-term tracking with large size reservoir enables ESN to perform strikingly
with superior prediction. Based on this scenario, we go a further step to
aggregate many of ESNs into an ensemble to lower the variance and stabilize the
system by stochastic replications and bootstrapping of input data.
| stat.ML cs.LG | echo state networks are powerful recurrent neural networks however they are often unstable and shaky making the process of finding an good esn for a specific dataset quite hard obtaining a superb accuracy by using the echo state network is a challenging task we create develop and implement a family of predictably optimal robust and stable ensemble of echo state networks via regularizing the training and perturbing the input furthermore several distributions of weights have been tried based on the shape to see if the shape of the distribution has the impact for reducing the error we found esn can track in short term for most dataset but it collapses in the long run shortterm tracking with large size reservoir enables esn to perform strikingly with superior prediction based on this scenario we go a further step to aggregate many of esns into an ensemble to lower the variance and stabilize the system by stochastic replications and bootstrapping of input data | [['echo', 'state', 'networks', 'are', 'powerful', 'recurrent', 'neural', 'networks', 'however', 'they', 'are', 'often', 'unstable', 'and', 'shaky', 'making', 'the', 'process', 'of', 'finding', 'an', 'good', 'esn', 'for', 'a', 'specific', 'dataset', 'quite', 'hard', 'obtaining', 'a', 'superb', 'accuracy', 'by', 'using', 'the', 'echo', 'state', 'network', 'is', 'a', 'challenging', 'task', 'we', 'create', 'develop', 'and', 'implement', 'a', 'family', 'of', 'predictably', 'optimal', 'robust', 'and', 'stable', 'ensemble', 'of', 'echo', 'state', 'networks', 'via', 'regularizing', 'the', 'training', 'and', 'perturbing', 'the', 'input', 'furthermore', 'several', 'distributions', 'of', 'weights', 'have', 'been', 'tried', 'based', 'on', 'the', 'shape', 'to', 'see', 'if', 'the', 'shape', 'of', 'the', 'distribution', 'has', 'the', 'impact', 'for', 'reducing', 'the', 'error', 'we', 'found', 'esn', 'can', 'track', 'in', 'short', 'term', 'for', 'most', 'dataset', 'but', 'it', 'collapses', 'in', 'the', 'long', 'run', 'shortterm', 'tracking', 'with', 'large', 'size', 'reservoir', 'enables', 'esn', 'to', 'perform', 'strikingly', 'with', 'superior', 'prediction', 'based', 'on', 'this', 'scenario', 'we', 'go', 'a', 'further', 'step', 'to', 'aggregate', 'many', 'of', 'esns', 'into', 'an', 'ensemble', 'to', 'lower', 'the', 'variance', 'and', 'stabilize', 'the', 'system', 'by', 'stochastic', 'replications', 'and', 'bootstrapping', 'of', 'input', 'data']] | [-0.07070512331513144, 0.059434554081371126, -0.11284036038483938, 0.0875435218360892, -0.05696090608141067, -0.18363641376855858, 0.03762759129670073, 0.43639432092093117, -0.2690284629287314, -0.3243141779173542, 0.12688578999751704, -0.2535269232958509, -0.15035225482084874, 0.19415867968421915, -0.06771064872176659, 0.10707229182416261, 0.130041401920065, 0.059507737102519186, -0.03661938171373877, -0.2752599392826698, 0.2946351087660824, 0.1008263633337728, 0.32155953045726193, -0.0159824598459122, 0.11601680096420344, -0.01756299230102334, 0.00182889264094302, -0.015338311321102083, -0.03683113494543764, 0.12793680430846924, 0.21624768852915685, 0.17307482860976633, 0.3037121556988507, -0.44771065859714093, -0.21259161639779298, 0.13793292638458174, 0.16022980746488458, 0.1336350522108191, -0.016039099454082932, -0.2832588144326409, 0.08611444988062386, -0.17412184135733833, -0.060082818858718835, -0.14636317766972917, 0.03383985534310341, 0.02018293337997697, -0.2791526562397611, 0.03523237248723574, 0.07446498030605755, 0.007442831420426413, -0.02615513847359913, -0.11007306343797733, 0.010604373295791447, 0.18156092128895732, 0.03040092324484458, 0.03987831408909944, 0.12425260719848993, -0.1569988584790888, -0.0945395825876166, 0.3161392127006801, -0.0709927371624996, -0.1883195958805982, 0.1880236331298253, -0.064515899022266, -0.12563786571787566, 0.12476902514383752, 0.2079073947229602, 0.10697119099938351, -0.14769618061330655, -0.013918533544518887, -0.020833356158449227, 0.20734380611351558, 0.017474127687536967, 0.026878664165558813, 0.17388703473930403, 0.2722430317113118, 0.05703366936657358, 0.16593118137477533, -0.13562108139270304, -0.11314905114668589, -0.19999439935113147, -0.10084762520255139, -0.21538269778811922, 0.04568842637803845, -0.08693709197509832, -0.17245330241861642, 0.4093177706199866, 0.1847863631173484, 0.24131395394757668, 0.09855881847603165, 0.28631780764539233, 0.0723766157901065, 0.08798082165061409, 0.1005062702764838, 0.222522608473064, 0.05697689040835877, 0.11284040975578198, -0.19699403896251033, 0.11614326725609786, 0.014888085155011738] |
1,802.0737 | SufiSent - Universal Sentence Representations Using Suffix Encodings | Computing universal distributed representations of sentences is a fundamental
task in natural language processing. We propose a method to learn such
representations by encoding the suffixes of word sequences in a sentence and
training on the Stanford Natural Language Inference (SNLI) dataset. We
demonstrate the effectiveness of our approach by evaluating it on the SentEval
benchmark, improving on existing approaches on several transfer tasks.
| cs.CL cs.AI | computing universal distributed representations of sentences is a fundamental task in natural language processing we propose a method to learn such representations by encoding the suffixes of word sequences in a sentence and training on the stanford natural language inference snli dataset we demonstrate the effectiveness of our approach by evaluating it on the senteval benchmark improving on existing approaches on several transfer tasks | [['computing', 'universal', 'distributed', 'representations', 'of', 'sentences', 'is', 'a', 'fundamental', 'task', 'in', 'natural', 'language', 'processing', 'we', 'propose', 'a', 'method', 'to', 'learn', 'such', 'representations', 'by', 'encoding', 'the', 'suffixes', 'of', 'word', 'sequences', 'in', 'a', 'sentence', 'and', 'training', 'on', 'the', 'stanford', 'natural', 'language', 'inference', 'snli', 'dataset', 'we', 'demonstrate', 'the', 'effectiveness', 'of', 'our', 'approach', 'by', 'evaluating', 'it', 'on', 'the', 'senteval', 'benchmark', 'improving', 'on', 'existing', 'approaches', 'on', 'several', 'transfer', 'tasks']] | [-0.0423013065046689, -0.03639245954400394, -0.04895384169140016, 0.09220667310182762, -0.1275680250764708, -0.11743425561871845, 0.07210839601611951, 0.4508121318940539, -0.2975091368862195, -0.34907018931698985, 0.03289879802832729, -0.27282729919534177, -0.16950532459304668, 0.2779615214676596, -0.14332356154045556, 0.11059277380991261, 0.17509151570266113, 0.1156178870878648, -0.05963391471595969, -0.3127998292911798, 0.3227564613061986, -0.0036550039731082506, 0.3883433121955022, 0.013502746973244939, 0.1843012970421114, -0.04515002528205514, -0.04237792786079808, -0.098333258589264, -0.02360022012362606, 0.248648243239586, 0.3504006210132502, 0.3011822599073639, 0.3278776432198356, -0.35035934633924626, -0.1958705769648077, 0.04845552128972486, 0.11422944780497346, 0.13193844689521939, -0.03230606893339427, -0.3689069521642523, 0.10106144480960211, -0.14509381202515215, 0.18397698024637066, -0.18468739627860487, 0.03520768649468664, -0.052965048656915314, -0.25011466695650597, -0.0015259080100804567, 0.15830204752273858, 0.11847253519954393, -0.02587877533005667, -0.11706031601352151, 0.08456270728856907, 0.1470649558250443, 0.01604813285121054, 0.0617231209835154, 0.13896857321378775, -0.18330099856393645, -0.23642462387215346, 0.41344980655412655, -0.07545820952145732, -0.2606912807241315, 0.213702753855614, 0.001026036679832032, -0.19204140346846543, -0.009592290793079883, 0.2358935427510005, 0.13792459190881345, -0.1306722370936768, 0.08505813679494167, -0.09555737300252076, 0.19618718266065116, 0.1284984645753866, -0.044783247663872316, 0.1887690549774561, 0.3214442250027787, -0.036139051044301596, 0.15414996744993914, -0.053849166390136816, -0.04680550658667926, -0.20691118339891545, -0.12887727999623166, -0.21825461436674232, -0.048199534096056595, -0.12028091225488424, -0.14519046539794545, 0.42206263809930533, 0.26961129280971363, 0.19395209242065903, 0.16777539628674276, 0.3478443516942207, 0.01960090630200284, 0.12119339606397261, 0.10385279578531481, 0.03252217317640316, -0.011861885745020118, 0.10103567324404139, -0.20103853086038725, 0.06089266259004944, 0.10037711061886512] |
1,802.07371 | Gravitational Wave Opacity from Gauge Field Dark Energy | We show that astrophysical gravitational waves can undergo an anomalous
modulation when propagating through cosmic gauge field dark energy. A
sufficiently strong effect, dependent on the gauge field energy density, would
appear as a redshift-dependent opacity, thereby impacting the use of
gravitational wave standard sirens to constrain the expansion history of the
Universe. We investigate a particular model of cosmic gauge field dark energy
and show that at early times it behaves like dark radiation, whereas a novel
interaction causes it to drive cosmic acceleration at late times. Joint
constraints on the cosmological scenario due to type 1a supernovae, baryon
acoustic oscillations, and cosmic microwave background data are presented. In
view of these constraints, we show that standard siren luminosity distances in
the redshift range 0.5 < z < 1.5 would systematically dim by up to 1%, which
may be distinguishable by third-generation gravitational wave detectors.
| gr-qc astro-ph.CO | we show that astrophysical gravitational waves can undergo an anomalous modulation when propagating through cosmic gauge field dark energy a sufficiently strong effect dependent on the gauge field energy density would appear as a redshiftdependent opacity thereby impacting the use of gravitational wave standard sirens to constrain the expansion history of the universe we investigate a particular model of cosmic gauge field dark energy and show that at early times it behaves like dark radiation whereas a novel interaction causes it to drive cosmic acceleration at late times joint constraints on the cosmological scenario due to type 1a supernovae baryon acoustic oscillations and cosmic microwave background data are presented in view of these constraints we show that standard siren luminosity distances in the redshift range 05 z 15 would systematically dim by up to 1 which may be distinguishable by thirdgeneration gravitational wave detectors | [['we', 'show', 'that', 'astrophysical', 'gravitational', 'waves', 'can', 'undergo', 'an', 'anomalous', 'modulation', 'when', 'propagating', 'through', 'cosmic', 'gauge', 'field', 'dark', 'energy', 'a', 'sufficiently', 'strong', 'effect', 'dependent', 'on', 'the', 'gauge', 'field', 'energy', 'density', 'would', 'appear', 'as', 'a', 'redshiftdependent', 'opacity', 'thereby', 'impacting', 'the', 'use', 'of', 'gravitational', 'wave', 'standard', 'sirens', 'to', 'constrain', 'the', 'expansion', 'history', 'of', 'the', 'universe', 'we', 'investigate', 'a', 'particular', 'model', 'of', 'cosmic', 'gauge', 'field', 'dark', 'energy', 'and', 'show', 'that', 'at', 'early', 'times', 'it', 'behaves', 'like', 'dark', 'radiation', 'whereas', 'a', 'novel', 'interaction', 'causes', 'it', 'to', 'drive', 'cosmic', 'acceleration', 'at', 'late', 'times', 'joint', 'constraints', 'on', 'the', 'cosmological', 'scenario', 'due', 'to', 'type', '1a', 'supernovae', 'baryon', 'acoustic', 'oscillations', 'and', 'cosmic', 'microwave', 'background', 'data', 'are', 'presented', 'in', 'view', 'of', 'these', 'constraints', 'we', 'show', 'that', 'standard', 'siren', 'luminosity', 'distances', 'in', 'the', 'redshift', 'range', '05', 'z', '15', 'would', 'systematically', 'dim', 'by', 'up', 'to', '1', 'which', 'may', 'be', 'distinguishable', 'by', 'thirdgeneration', 'gravitational', 'wave', 'detectors']] | [-0.13795907587821907, 0.22632543432630176, -0.06663640203057891, 0.16063508027744117, -0.1252583876096954, -0.0723573322692472, -0.02713833612506278, 0.34097986872721875, -0.22656386485970062, -0.34465432579680866, 0.03277550565124127, -0.27487469461306724, -0.03729128713570794, 0.20052516543041243, 0.060262223645774306, -0.041272080846182585, 0.019338377232391697, -0.004416120141589393, -0.04132625169657129, -0.23826031785251367, 0.31098006352436236, 0.14194510496680676, 0.24663569885241385, 0.013257863945909776, 0.10596873251051875, -0.03877985974314571, -0.069624260789068, -0.008385965722684179, -0.14839690498456548, -0.03803359065204859, 0.18791296135208946, 0.13976041342054182, 0.18479504759792084, -0.44643185435820165, -0.2829825655919396, 0.15188693189217398, 0.1731257518598189, 0.14255075549509558, -0.07387207805732032, -0.29307676896051915, 0.024820455969852953, -0.1945356382348109, -0.1359032751667352, 0.014307129030284058, -0.0043905925130174085, 0.013009077216136374, -0.24650298205152568, 0.13793274416174325, -0.03452766590635292, -0.07121374455164187, -0.06675146223602092, -0.0360367978638452, -0.01278669393246269, -0.02374190427528649, 0.10918791572637726, 0.10507491775853042, 0.19410728947776887, -0.16964628553250805, -0.06317556688251595, 0.4247205363224364, -0.1732002394290046, -0.07659881496025871, 0.1932976564696421, -0.19277299558355784, -0.13709142935436425, 0.14539977084981123, 0.19493774270166694, 0.028409739052424103, -0.14517004049604212, 0.10174131122039398, 0.0868447514167201, 0.18658539025636856, 0.1096460248712295, 0.07039097365567512, 0.3529005532165886, 0.11815428420474443, 0.04224738678021822, 0.022580221031805396, -0.13444654303020798, 0.037961648330868535, -0.3335291934070281, -0.09010990414956016, -0.14783810124370372, 0.12174962210439036, -0.136785758128705, -0.138591478462331, 0.34088963190960286, 0.1593809654918409, 0.1603928582141331, 0.035761687297458086, 0.2813447644132086, 0.06922713524383856, 0.05302506123805668, 0.04470535593281966, 0.35627694610351074, 0.11522419332403741, 0.118335237755673, -0.22376739458801845, -0.027680492287698952, 0.0054906634888741085] |
1,802.07372 | Stochastic Variance-Reduced Cubic Regularization for Nonconvex
Optimization | Cubic regularization (CR) is an optimization method with emerging popularity
due to its capability to escape saddle points and converge to second-order
stationary solutions for nonconvex optimization. However, CR encounters a high
sample complexity issue for finite-sum problems with a large data size.
%Various inexact variants of CR have been proposed to improve the sample
complexity. In this paper, we propose a stochastic variance-reduced
cubic-regularization (SVRC) method under random sampling, and study its
convergence guarantee as well as sample complexity. We show that the iteration
complexity of SVRC for achieving a second-order stationary solution within
$\epsilon$ accuracy is $O(\epsilon^{-3/2})$, which matches the state-of-art
result on CR types of methods. Moreover, our proposed variance reduction scheme
significantly reduces the per-iteration sample complexity. The resulting total
Hessian sample complexity of our SVRC is ${\Oc}(N^{2/3} \epsilon^{-3/2})$,
which outperforms the state-of-art result by a factor of $O(N^{2/15})$. We also
study our SVRC under random sampling without replacement scheme, which yields a
lower per-iteration sample complexity, and hence justifies its practical
applicability.
| math.OC cs.LG stat.ML | cubic regularization cr is an optimization method with emerging popularity due to its capability to escape saddle points and converge to secondorder stationary solutions for nonconvex optimization however cr encounters a high sample complexity issue for finitesum problems with a large data size various inexact variants of cr have been proposed to improve the sample complexity in this paper we propose a stochastic variancereduced cubicregularization svrc method under random sampling and study its convergence guarantee as well as sample complexity we show that the iteration complexity of svrc for achieving a secondorder stationary solution within epsilon accuracy is oepsilon32 which matches the stateofart result on cr types of methods moreover our proposed variance reduction scheme significantly reduces the periteration sample complexity the resulting total hessian sample complexity of our svrc is ocn23 epsilon32 which outperforms the stateofart result by a factor of on215 we also study our svrc under random sampling without replacement scheme which yields a lower periteration sample complexity and hence justifies its practical applicability | [['cubic', 'regularization', 'cr', 'is', 'an', 'optimization', 'method', 'with', 'emerging', 'popularity', 'due', 'to', 'its', 'capability', 'to', 'escape', 'saddle', 'points', 'and', 'converge', 'to', 'secondorder', 'stationary', 'solutions', 'for', 'nonconvex', 'optimization', 'however', 'cr', 'encounters', 'a', 'high', 'sample', 'complexity', 'issue', 'for', 'finitesum', 'problems', 'with', 'a', 'large', 'data', 'size', 'various', 'inexact', 'variants', 'of', 'cr', 'have', 'been', 'proposed', 'to', 'improve', 'the', 'sample', 'complexity', 'in', 'this', 'paper', 'we', 'propose', 'a', 'stochastic', 'variancereduced', 'cubicregularization', 'svrc', 'method', 'under', 'random', 'sampling', 'and', 'study', 'its', 'convergence', 'guarantee', 'as', 'well', 'as', 'sample', 'complexity', 'we', 'show', 'that', 'the', 'iteration', 'complexity', 'of', 'svrc', 'for', 'achieving', 'a', 'secondorder', 'stationary', 'solution', 'within', 'epsilon', 'accuracy', 'is', 'oepsilon32', 'which', 'matches', 'the', 'stateofart', 'result', 'on', 'cr', 'types', 'of', 'methods', 'moreover', 'our', 'proposed', 'variance', 'reduction', 'scheme', 'significantly', 'reduces', 'the', 'periteration', 'sample', 'complexity', 'the', 'resulting', 'total', 'hessian', 'sample', 'complexity', 'of', 'our', 'svrc', 'is', 'ocn23', 'epsilon32', 'which', 'outperforms', 'the', 'stateofart', 'result', 'by', 'a', 'factor', 'of', 'on215', 'we', 'also', 'study', 'our', 'svrc', 'under', 'random', 'sampling', 'without', 'replacement', 'scheme', 'which', 'yields', 'a', 'lower', 'periteration', 'sample', 'complexity', 'and', 'hence', 'justifies', 'its', 'practical', 'applicability']] | [-0.07760229198511963, -0.03752477750210191, -0.061052607210557455, 0.06545400173863306, -0.05813940305535386, -0.13515602687385114, 0.10651220614764918, 0.3786825357039073, -0.2638043039705513, -0.3373730376521807, 0.10340059983541212, -0.24895859680638263, -0.14195844929284848, 0.20284006400488136, -0.13034961866243266, 0.10924079966420455, 0.08981063935860265, -0.021797548846069086, -0.12253158509861906, -0.3361331324942024, 0.24611444129443885, 0.09552224030116255, 0.33868970154222416, 0.00500302578013095, 0.12324000796638201, -0.03525913782451847, 0.03596278202291237, 0.07724545721394839, -0.09118728223598382, 0.11049853016838158, 0.24407645589785604, 0.18170388103831878, 0.35233170796958047, -0.34512801704512663, -0.21275213203696738, 0.11565802416128175, 0.16600388622535364, 0.11534170792849803, -0.09265587644200068, -0.2233731286591714, 0.13144080190374174, -0.1245934504500261, -0.10913989591559894, -0.12078461253720267, -0.05319292901549488, 0.04221261409253291, -0.3092061142016929, 0.07333628469691243, 0.07844840014415862, 0.008994762116344646, -0.035973019522427374, -0.15042968574775065, 0.05152892161135153, 0.04175099510083361, 0.0855772181771832, 0.04512877695875742, 0.10236890817582096, -0.07003659066579464, -0.12896218471706095, 0.3617844280571018, -0.04862497368026752, -0.206087111279641, 0.20626034788793043, -0.06787296783508415, -0.15294416701398428, 0.20795563155523977, 0.23331293848747098, 0.15628263248249935, -0.11071186625432768, 0.13788081819039666, -0.008937983313666248, 0.16079833290380677, 0.03829174079483647, 0.047550585333338835, 0.010935496585727556, 0.20742963083661956, 0.18293361818537163, 0.14760549355613453, -0.09232226450943172, -0.12229220144643743, -0.21686805717692506, -0.14036948482006242, -0.22428029201635183, 0.027980598816988854, -0.17828877698944204, -0.17679496533691702, 0.35918099885655064, 0.16143966304484708, 0.1792111782095872, 0.16821410543520982, 0.34278388076075694, 0.13513836490413425, 0.012964925734417104, 0.1460385402840585, 0.1805063447597005, 0.10995596608362819, 0.08642161091812318, -0.27487757846020255, 0.0998689200581483, 0.11131226767149822] |
1,802.07373 | Polynomial convolutions in max-plus algebra | Recently, in a work that grew out of their exploration of interlacing
polynomials, Marcus, Spielman and Srivastava and then Marcus studied certain
combinatorial polynomial convolutions. These convolutions preserve
real-rootedness and capture expectations of characteristic polynomials of
unitarily invariant random matrices, thus providing a link to free probability.
We explore analogues of these types of convolutions in the setting of max-plus
algebra. In this setting the max-permanent replaces the determinant, the
maximum is the analogue of the expected value and real-rootedness is replaced
by full canonical form. Our results resemble those of Marcus et al., however,
in contrast to the classical setting we obtain an exact and simple description
of all roots.
| math.RA | recently in a work that grew out of their exploration of interlacing polynomials marcus spielman and srivastava and then marcus studied certain combinatorial polynomial convolutions these convolutions preserve realrootedness and capture expectations of characteristic polynomials of unitarily invariant random matrices thus providing a link to free probability we explore analogues of these types of convolutions in the setting of maxplus algebra in this setting the maxpermanent replaces the determinant the maximum is the analogue of the expected value and realrootedness is replaced by full canonical form our results resemble those of marcus et al however in contrast to the classical setting we obtain an exact and simple description of all roots | [['recently', 'in', 'a', 'work', 'that', 'grew', 'out', 'of', 'their', 'exploration', 'of', 'interlacing', 'polynomials', 'marcus', 'spielman', 'and', 'srivastava', 'and', 'then', 'marcus', 'studied', 'certain', 'combinatorial', 'polynomial', 'convolutions', 'these', 'convolutions', 'preserve', 'realrootedness', 'and', 'capture', 'expectations', 'of', 'characteristic', 'polynomials', 'of', 'unitarily', 'invariant', 'random', 'matrices', 'thus', 'providing', 'a', 'link', 'to', 'free', 'probability', 'we', 'explore', 'analogues', 'of', 'these', 'types', 'of', 'convolutions', 'in', 'the', 'setting', 'of', 'maxplus', 'algebra', 'in', 'this', 'setting', 'the', 'maxpermanent', 'replaces', 'the', 'determinant', 'the', 'maximum', 'is', 'the', 'analogue', 'of', 'the', 'expected', 'value', 'and', 'realrootedness', 'is', 'replaced', 'by', 'full', 'canonical', 'form', 'our', 'results', 'resemble', 'those', 'of', 'marcus', 'et', 'al', 'however', 'in', 'contrast', 'to', 'the', 'classical', 'setting', 'we', 'obtain', 'an', 'exact', 'and', 'simple', 'description', 'of', 'all', 'roots']] | [-0.1140220153346573, 0.06961902788197304, -0.07978029555471783, 0.08806221673624928, -0.07390226839872246, -0.09151131283407184, 0.013011336963708427, 0.29239119023761967, -0.3101280850569972, -0.26010139229792084, 0.08043495500566099, -0.25156432566317644, -0.2114615453237837, 0.16988194864878262, -0.13460634376176378, 0.07600576734932309, 0.025958015071228146, 0.010690574153241787, -0.1163636942679163, -0.30225693812085824, 0.3209747098301622, 0.06178604714911092, 0.2275316723029722, -0.011597995578565381, 0.07628581487912346, 0.046306173761629245, -0.07598948309367354, -0.021874646304852582, -0.14775475910686178, 0.14350304503882813, 0.22983188518238337, 0.1152929694391787, 0.2386280906513672, -0.42046163369986145, -0.14529639002443714, 0.1309868540593677, 0.12465634430991486, 0.053391981757753955, -0.0036103845404630358, -0.2573361032007431, 0.0848334335953537, -0.16567584198730237, -0.13159152263436805, -0.08817146185319871, 0.021279640732841058, 0.055769286648666656, -0.3063243767288937, 0.058950058150697836, 0.153188881426203, 0.07003321882591329, -0.024985629942437464, -0.1449398962569169, 0.034772543103264816, 0.0808966053141789, -0.014723572901196101, -0.0050009004729376595, 0.04898011106151071, -0.10216561503158035, -0.14447560217443176, 0.33018752379681576, 0.0022961218788457864, -0.19644844489256766, 0.17350062385243786, -0.17710959415205502, -0.16250283052636819, 0.10245852009816603, 0.10593027055305852, 0.1364998867904598, -0.09969088795002211, 0.15008394773149947, -0.13927133072336967, 0.04439691973596134, 0.17080245009538803, 0.022241152176072566, 0.11279964080419053, 0.024242616567591375, 0.023720114470713517, 0.14375860768327997, 0.04258212692908604, -0.17145074347764339, -0.2538600233552808, -0.20952885139214975, -0.20481423153647815, 0.10471371226541867, -0.11155042699472026, -0.173095640049062, 0.39087126072792505, 0.1369017686604903, 0.2276329940692945, 0.1580682331611487, 0.1991558802483434, 0.15331746642160313, 0.03992117326918312, 0.06232015526108047, 0.14405209655471315, 0.2404081464215944, 0.07494584659791806, -0.15015105077234858, 0.05443591552532532, 0.18514777493176304] |
1,802.07374 | On the scaling of polynomial features for representation matching | In many neural models, new features as polynomial functions of existing ones
are used to augment representations. Using the natural language inference task
as an example, we investigate the use of scaled polynomials of degree 2 and
above as matching features. We find that scaling degree 2 features has the
highest impact on performance, reducing classification error by 5% in the best
models.
| cs.CL cs.AI | in many neural models new features as polynomial functions of existing ones are used to augment representations using the natural language inference task as an example we investigate the use of scaled polynomials of degree 2 and above as matching features we find that scaling degree 2 features has the highest impact on performance reducing classification error by 5 in the best models | [['in', 'many', 'neural', 'models', 'new', 'features', 'as', 'polynomial', 'functions', 'of', 'existing', 'ones', 'are', 'used', 'to', 'augment', 'representations', 'using', 'the', 'natural', 'language', 'inference', 'task', 'as', 'an', 'example', 'we', 'investigate', 'the', 'use', 'of', 'scaled', 'polynomials', 'of', 'degree', '2', 'and', 'above', 'as', 'matching', 'features', 'we', 'find', 'that', 'scaling', 'degree', '2', 'features', 'has', 'the', 'highest', 'impact', 'on', 'performance', 'reducing', 'classification', 'error', 'by', '5', 'in', 'the', 'best', 'models']] | [-0.04185941414759746, 0.00489985175076909, -0.030652488478355937, 0.1064044722237639, -0.07040003864538102, -0.12862658117424755, -0.0038669825797634466, 0.3915155983663031, -0.29481265785556937, -0.36161436213712606, 0.09356386178646177, -0.2900047131060135, -0.19666644321044996, 0.22529667553802332, -0.07573948719997019, 0.0878365005676945, 0.04591783626921593, 0.07226160616569575, -0.09711641914743398, -0.2917836950057083, 0.3089133049509237, 0.07184683045165406, 0.2760311681185923, 0.006506500043167126, 0.11120513785955688, -0.044742601051453564, -0.006636917539354827, -0.03923212834412143, -0.0886312005714567, 0.1346199019028554, 0.26916849412107635, 0.1942269825967886, 0.27000891097584767, -0.3699597438560828, -0.21871148664799947, 0.13158179971847742, 0.17386965099574317, 0.08939481754269865, 0.011455582430778396, -0.2295140041747973, 0.10869633656970802, -0.1685822435090178, -0.06655577235367327, -0.13607156454097658, -0.00643026250015412, 0.05317689688314521, -0.24668026098885412, 0.03994868068201911, 0.092184708143274, 0.1298157485305435, -0.027001545856898977, -0.18152563751394313, 0.014613690209530648, 0.16157782391186745, -0.006783547219894235, 0.04556558732061632, 0.09353772469515366, -0.24224358476284477, -0.1973845837785611, 0.3638988753396367, -0.11001881447044157, -0.24275634363515392, 0.20717900780044377, -0.06556956735365684, -0.1778575747037336, 0.0662344232393754, 0.2266202469666799, 0.09783224532351134, -0.10496068428019209, 0.044418563000998265, -0.040249146328913785, 0.19006413045997125, 0.09112254303273937, 0.018677002713379878, 0.14166958747239458, 0.2027197080176501, 0.01603141508992791, 0.15556390230203904, -0.08940036715717897, -0.014063758531674034, -0.2481893179938197, -0.11358704026197157, -0.1793932123072741, -0.03320082533173263, -0.15022968643484452, -0.10579760206885458, 0.4406739915351546, 0.20030841515177772, 0.2505293916097827, 0.12991960228435576, 0.2582126437198548, 0.11163860450993987, 0.11909060763372552, 0.0952101684949686, 0.17368729200421107, 0.058788278454264244, 0.03841412987648731, -0.13016578334841936, 0.09662117269481459, 0.07669925382952132] |
1,802.07375 | Periodicity in Data Streams with Wildcards | We investigate the problem of detecting periodic trends within a string $S$
of length $n$, arriving in the streaming model, containing at most $k$ wildcard
characters, where $k=o(n)$. A wildcard character is a special character that
can be assigned any other character. We say $S$ has wildcard-period $p$ if
there exists an assignment to each of the wildcard characters so that in the
resulting stream the length $n-p$ prefix equals the length $n-p$ suffix. We
present a two-pass streaming algorithm that computes wildcard-periods of $S$
using $\mathcal{O}(k^3\,\mathsf{polylog}\,n)$ bits of space, while we also show
that this problem cannot be solved in sublinear space in one pass. We then give
a one-pass randomized streaming algorithm that computes all wildcard-periods
$p$ of $S$ with $p<\frac{n}{2}$ and no wildcard characters appearing in the
last $p$ symbols of $S$, using $\mathcal{O}(k^3\mathsf{polylog}\, n)$ space.
| cs.DS | we investigate the problem of detecting periodic trends within a string s of length n arriving in the streaming model containing at most k wildcard characters where kon a wildcard character is a special character that can be assigned any other character we say s has wildcardperiod p if there exists an assignment to each of the wildcard characters so that in the resulting stream the length np prefix equals the length np suffix we present a twopass streaming algorithm that computes wildcardperiods of s using mathcalok3mathsfpolylogn bits of space while we also show that this problem cannot be solved in sublinear space in one pass we then give a onepass randomized streaming algorithm that computes all wildcardperiods p of s with pfracn2 and no wildcard characters appearing in the last p symbols of s using mathcalok3mathsfpolylog n space | [['we', 'investigate', 'the', 'problem', 'of', 'detecting', 'periodic', 'trends', 'within', 'a', 'string', 's', 'of', 'length', 'n', 'arriving', 'in', 'the', 'streaming', 'model', 'containing', 'at', 'most', 'k', 'wildcard', 'characters', 'where', 'kon', 'a', 'wildcard', 'character', 'is', 'a', 'special', 'character', 'that', 'can', 'be', 'assigned', 'any', 'other', 'character', 'we', 'say', 's', 'has', 'wildcardperiod', 'p', 'if', 'there', 'exists', 'an', 'assignment', 'to', 'each', 'of', 'the', 'wildcard', 'characters', 'so', 'that', 'in', 'the', 'resulting', 'stream', 'the', 'length', 'np', 'prefix', 'equals', 'the', 'length', 'np', 'suffix', 'we', 'present', 'a', 'twopass', 'streaming', 'algorithm', 'that', 'computes', 'wildcardperiods', 'of', 's', 'using', 'mathcalok3mathsfpolylogn', 'bits', 'of', 'space', 'while', 'we', 'also', 'show', 'that', 'this', 'problem', 'can', 'not', 'be', 'solved', 'in', 'sublinear', 'space', 'in', 'one', 'pass', 'we', 'then', 'give', 'a', 'onepass', 'randomized', 'streaming', 'algorithm', 'that', 'computes', 'all', 'wildcardperiods', 'p', 'of', 's', 'with', 'pfracn2', 'and', 'no', 'wildcard', 'characters', 'appearing', 'in', 'the', 'last', 'p', 'symbols', 'of', 's', 'using', 'mathcalok3mathsfpolylog', 'n', 'space']] | [-0.2087921285242946, 0.14985333551777769, -0.0714420111677437, 0.034577079362632636, -0.07639291532924054, -0.19593436847337417, 0.07888919135762586, 0.3547451555797899, -0.3457138620429086, -0.25348238420771885, 0.036471732863638966, -0.30266194605199553, -0.11954805582278856, 0.16466627362425681, -0.046936775862963666, -0.00968063334606726, 0.0646017491782981, 0.145501834505962, -0.043172109411615464, -0.3012648210860789, 0.2535864897106809, -0.03873452397270335, 0.18303049376441372, -0.025720068520900828, 0.07238952349871397, 0.05303468702843896, 0.0016238725985641832, 0.01860621411081714, -0.11418851146919662, 0.07450471374344218, 0.29472541824474724, 0.20222270748302065, 0.23990585104545095, -0.40648706298735404, -0.1538841223102753, 0.16845711633494054, 0.1617985042674398, 0.08894115267493935, -0.027300353658696017, -0.18137904693958937, 0.20112680836528954, -0.11855749858853717, -0.04327367365498234, 0.01975731930040099, 0.1439128525555134, -0.039075796685992155, -0.2888873376314425, -0.012240638275397942, 0.08914869769165913, 0.02445751839765796, -0.031263986350623545, -0.13443522970019667, 0.042732443036166606, 0.0949060845464744, 0.02368399932445889, 0.09485892742630785, 0.01846426174182583, -0.07577223583961043, -0.15340438008791318, 0.4037925515944759, -0.09286497453986495, -0.2003438412444666, 0.09244813577754905, -0.12289032651525404, -0.15301355307714806, 0.15180038156212067, 0.13575695875204272, 0.14606992936244717, -0.04267928329882798, 0.18050260219196962, -0.15572920133170015, 0.22479879687005586, 0.1526635817648774, 0.017708196245237357, 0.11221828703527097, 0.11051319980200518, 0.06582449246887807, 0.14733159796170958, -0.08660161676989109, 0.009242225667522117, -0.3286889659999697, -0.16638834173618644, -0.19951450406418492, 0.01452925385469657, -0.09622388759065265, -0.1870798309299129, 0.3520956554795029, 0.14021523921164097, 0.23892081922644542, 0.0766247515566647, 0.23145407104985444, 0.09579973388808193, 0.06270378769064942, 0.18669662860532601, 0.05654543379701122, 0.013280493741061676, 0.0008931061546145766, -0.18961200009065646, 0.10511893575873088, 0.12641374936189365] |
1,802.07376 | Core Emergence in a Massive Infrared Dark Cloud: A Comparison Between
Mid-IR Extinction and 1.3 mm Emission | Stars are born from dense cores in molecular clouds. Observationally, it is
crucial to capture the formation of cores in order to understand the necessary
conditions and rate of the star formation process. The {\it Atacama Large
Mm/sub-mm Array} (ALMA) is extremely powerful for identifying dense gas
structures, including cores, at mm wavelengths via their dust continuum
emission. Here we use ALMA to carry out a survey of dense gas and cores in the
central region of the massive ($\sim10^5\:M_\odot$) Infrared Dark Cloud (IRDC)
G28.37+0.07. The observation consists of a mosaic of 86 pointings of the
12m-array and produces an unprecedented view of the densest structures of this
IRDC. In this first paper about this data set, we focus on a comparison between
the 1.3 mm continuum emission and a mid-infrared (MIR) extinction map of the
IRDC. This allows estimation of the "dense gas" detection probability function
(DPF), i.e., as a function of the local mass surface density, $\Sigma$, for
various choices of thresholds of mm continuum emission to define "dense gas".
We then estimate the dense gas mass fraction, $f_{\rm dg}$, in the central
region of the IRDC and, via extrapolation with the DPF and the known $\Sigma$
probability distribution function, to the larger-scale surrounding regions,
finding values of about 5\% to 15\% for the fiducial choice of threshold. We
argue that this observed dense gas is a good tracer of the protostellar core
population and, in this context, estimate a star formation efficiency per
free-fall time in the central IRDC region of $\epsilon_{\rm ff}\sim$10\%, with
approximately a factor of two systematic uncertainties.
| astro-ph.GA | stars are born from dense cores in molecular clouds observationally it is crucial to capture the formation of cores in order to understand the necessary conditions and rate of the star formation process the it atacama large mmsubmm array alma is extremely powerful for identifying dense gas structures including cores at mm wavelengths via their dust continuum emission here we use alma to carry out a survey of dense gas and cores in the central region of the massive sim105m_odot infrared dark cloud irdc g2837007 the observation consists of a mosaic of 86 pointings of the 12marray and produces an unprecedented view of the densest structures of this irdc in this first paper about this data set we focus on a comparison between the 13 mm continuum emission and a midinfrared mir extinction map of the irdc this allows estimation of the dense gas detection probability function dpf ie as a function of the local mass surface density sigma for various choices of thresholds of mm continuum emission to define dense gas we then estimate the dense gas mass fraction f_rm dg in the central region of the irdc and via extrapolation with the dpf and the known sigma probability distribution function to the largerscale surrounding regions finding values of about 5 to 15 for the fiducial choice of threshold we argue that this observed dense gas is a good tracer of the protostellar core population and in this context estimate a star formation efficiency per freefall time in the central irdc region of epsilon_rm ffsim10 with approximately a factor of two systematic uncertainties | [['stars', 'are', 'born', 'from', 'dense', 'cores', 'in', 'molecular', 'clouds', 'observationally', 'it', 'is', 'crucial', 'to', 'capture', 'the', 'formation', 'of', 'cores', 'in', 'order', 'to', 'understand', 'the', 'necessary', 'conditions', 'and', 'rate', 'of', 'the', 'star', 'formation', 'process', 'the', 'it', 'atacama', 'large', 'mmsubmm', 'array', 'alma', 'is', 'extremely', 'powerful', 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1,802.07377 | C*-Algebras for partial product systems over N | We define partial product systems over N. They generalise product systems
over N and Fell bundles over Z. We define Toeplitz C*-algebras and relative
Cuntz-Pimsner algebras for them and show that the section C*-algebra of a Fell
bundle over Z is a relative Cuntz-Pimsner algebra. We describe the
gauge-invariant ideals in the Toeplitz C*-algebra.
| math.OA | we define partial product systems over n they generalise product systems over n and fell bundles over z we define toeplitz calgebras and relative cuntzpimsner algebras for them and show that the section calgebra of a fell bundle over z is a relative cuntzpimsner algebra we describe the gaugeinvariant ideals in the toeplitz calgebra | [['we', 'define', 'partial', 'product', 'systems', 'over', 'n', 'they', 'generalise', 'product', 'systems', 'over', 'n', 'and', 'fell', 'bundles', 'over', 'z', 'we', 'define', 'toeplitz', 'calgebras', 'and', 'relative', 'cuntzpimsner', 'algebras', 'for', 'them', 'and', 'show', 'that', 'the', 'section', 'calgebra', 'of', 'a', 'fell', 'bundle', 'over', 'z', 'is', 'a', 'relative', 'cuntzpimsner', 'algebra', 'we', 'describe', 'the', 'gaugeinvariant', 'ideals', 'in', 'the', 'toeplitz', 'calgebra']] | [-0.18765623222484631, 0.09877176754741447, -0.034198970499413985, 0.051841522060351926, -0.03955266548803559, -0.09882683484573607, -0.04531447713573774, 0.44511954872696485, -0.395492358788572, -0.11250299560251059, 0.09147112943982291, -0.2698171095991576, -0.08813835945221837, 0.1489809781519903, -0.20172562595042917, -0.05024658729908643, 0.11019021470996516, 0.15631358425512357, -0.1964101261282512, -0.29855412879691423, 0.49283361469429954, -0.02646670814310373, 0.1476148422807455, 0.008055491062502066, 0.12259812762581364, 0.04174729183971606, -0.05711016778109802, -0.03276771136249105, -0.16214641118575754, 0.08002479855592053, 0.3492624616181409, 0.1398621355700824, 0.2130663739517331, -0.31841774074429713, -0.02871041670786562, 0.22727797358055357, 0.15000071062671919, -0.09645710137017348, 0.0709627201884157, -0.3028777540592408, 0.04821692592533374, -0.4097713635009886, -0.007581598401345589, -0.13150775363599812, 0.1230470785457227, -0.04309321705389906, -0.2591992753851055, -0.03300405422191101, 0.09593385008850384, 0.1286528990474633, -0.1110346981289762, -0.06506836626471744, -0.11888347876568635, 0.04273309477570432, -0.09176884266047704, -0.048285510739164976, 0.22850801494765888, 0.006583388515368656, -0.18192358994511543, 0.31785363531498995, -0.07139064530255618, -0.19975091085803728, 0.11684632556581939, -0.24831824230582075, -0.1740904962643981, 0.1248857334808067, 0.0989679561720954, 0.15856165917055612, 0.06666784214407757, 0.2348870905083863, -0.18920575972232553, 0.05691273772606143, 0.035188774056560186, 0.026025057054573187, 0.11864395398232672, 0.049625678574321444, 0.10868961169142966, 0.10082234704384098, 0.1182020616203469, -0.024321331763295113, -0.33453005207357583, -0.2719764887544982, 0.0027083403223918546, 0.22212181793939736, -0.09816302193293167, -0.14516971564498143, 0.37686880909044435, 0.12335923127830029, 0.2588036663968254, 0.17846185473414758, 0.16784786183766467, 0.053653332232325164, 0.10728392001517394, 0.07577387563435843, 0.09443555949945692, 0.40667341946175806, 0.02170964645187336, -0.05640420408195092, -0.09436304152391299, 0.25350132832924527] |
1,802.07378 | Perturbation theories behind thermal mode spectroscopy for high-accuracy
measurement of thermal diffusivity of solids | Thermal mode spectroscopy (TMS) has been recently proposed for accurately
measuring thermal diffusivity of solids from a temperature decay rate of a
specific thermal mode selected by three- dimensional (anti)nodal information
[Phys. Rev. Lett., 117, 195901 (2016)]. In this paper, we find out the
following advantages of TMS by use of perturbation analyses. First, TMS is
applicable to the measurement of high thermal diffusivity with a small size
specimen. Second, it is less affected by thermally resistive films on a
specimen in the sense that the resistance at the interface does not affect the
first-order correction of thermal diffusivity. Third, it can perform doubly
accurate measurement of the thermal diffusivity specified at a thermal
equilibrium state even if the diffusivity depends on temperature in the sense
that the measurement can be performed within tiny temperature difference from
the given state and that the decay rate of the slowest decaying mode is not
affected by the dependence.
| cond-mat.mtrl-sci | thermal mode spectroscopy tms has been recently proposed for accurately measuring thermal diffusivity of solids from a temperature decay rate of a specific thermal mode selected by three dimensional antinodal information phys rev lett 117 195901 2016 in this paper we find out the following advantages of tms by use of perturbation analyses first tms is applicable to the measurement of high thermal diffusivity with a small size specimen second it is less affected by thermally resistive films on a specimen in the sense that the resistance at the interface does not affect the firstorder correction of thermal diffusivity third it can perform doubly accurate measurement of the thermal diffusivity specified at a thermal equilibrium state even if the diffusivity depends on temperature in the sense that the measurement can be performed within tiny temperature difference from the given state and that the decay rate of the slowest decaying mode is not affected by the dependence | [['thermal', 'mode', 'spectroscopy', 'tms', 'has', 'been', 'recently', 'proposed', 'for', 'accurately', 'measuring', 'thermal', 'diffusivity', 'of', 'solids', 'from', 'a', 'temperature', 'decay', 'rate', 'of', 'a', 'specific', 'thermal', 'mode', 'selected', 'by', 'three', 'dimensional', 'antinodal', 'information', 'phys', 'rev', 'lett', '117', '195901', '2016', 'in', 'this', 'paper', 'we', 'find', 'out', 'the', 'following', 'advantages', 'of', 'tms', 'by', 'use', 'of', 'perturbation', 'analyses', 'first', 'tms', 'is', 'applicable', 'to', 'the', 'measurement', 'of', 'high', 'thermal', 'diffusivity', 'with', 'a', 'small', 'size', 'specimen', 'second', 'it', 'is', 'less', 'affected', 'by', 'thermally', 'resistive', 'films', 'on', 'a', 'specimen', 'in', 'the', 'sense', 'that', 'the', 'resistance', 'at', 'the', 'interface', 'does', 'not', 'affect', 'the', 'firstorder', 'correction', 'of', 'thermal', 'diffusivity', 'third', 'it', 'can', 'perform', 'doubly', 'accurate', 'measurement', 'of', 'the', 'thermal', 'diffusivity', 'specified', 'at', 'a', 'thermal', 'equilibrium', 'state', 'even', 'if', 'the', 'diffusivity', 'depends', 'on', 'temperature', 'in', 'the', 'sense', 'that', 'the', 'measurement', 'can', 'be', 'performed', 'within', 'tiny', 'temperature', 'difference', 'from', 'the', 'given', 'state', 'and', 'that', 'the', 'decay', 'rate', 'of', 'the', 'slowest', 'decaying', 'mode', 'is', 'not', 'affected', 'by', 'the', 'dependence']] | [-0.08605475013311474, 0.2062482758386371, -0.07806765359157744, -0.04722662924308306, -0.03608640422447561, -0.12931541116752973, 0.08165015431362778, 0.31995573681062806, -0.24654484812755328, -0.2956690263743393, 0.05280447918966484, -0.29316918458789587, -0.06557017359404992, 0.1912951602552755, -0.026739596056405645, 0.03290773348178332, 0.04175685112698911, 0.022221267942745142, -0.029662847438325677, -0.2073741303801608, 0.2609059398737139, 0.11478716560090199, 0.3265365297213579, 0.08281591586105955, 0.05993328673335222, -0.02541842551764626, 0.0011953196685331373, 0.07217618762754285, -0.15185530293796873, -0.01796947117560567, 0.1964141315099998, -0.003782609082871857, 0.24161014222996668, -0.41470098052508175, -0.21029480260152084, 0.09310979843259048, 0.1274453170182637, 0.11824808682491167, -0.01938574926670975, -0.23289901218287504, 0.061612536412818976, -0.13456173716948774, -0.09791223234004484, -0.11206194567971696, 0.05709983963214864, -0.036517237742932945, -0.2660082731073579, 0.1942567728065814, 0.035486419718020044, 0.05241024085225012, -0.043169469645736404, -0.09979181623874375, -0.06598340103534074, 0.06508155905295354, 0.024868552822273415, 0.02025520203497786, 0.21171878608098874, -0.08135112710745791, -0.0581991917719372, 0.33383383334447175, -0.11213600638961324, -0.15323710520393574, 0.17681939927532744, -0.1881315969885924, -0.07917790644420072, 0.19259416949577057, 0.13306033287573463, 0.14894796853873116, -0.16691268274847132, 0.047154878968752034, 0.004836406176671004, 0.21501390841485074, 0.08245765849446449, 0.020741552936856467, 0.19890134780703542, 0.1906581151117093, -0.0027684150711418344, 0.11235579558669063, -0.1292618139891718, -0.05803715153920982, -0.2717646816327499, -0.16644386866774324, -0.242185070216902, 0.061838950593366276, -0.03835786362049895, -0.1495822129281572, 0.38424360272116387, 0.1685525730744979, 0.18833915605388868, -0.010965027191186657, 0.3039088470932956, 0.1377323313186375, 0.06165525414652597, 0.10723598224098961, 0.324162144528087, 0.15507437566963908, 0.1430808189145934, -0.3028500140497225, 0.13434713010270244, 0.013245419130469553] |
1,802.07379 | Scalable Label Propagation for Multi-relational Learning on the Tensor
Product of Graphs | Multi-relational learning on knowledge graphs infers high-order relations
among the entities across the graphs. This learning task can be solved by label
propagation on the tensor product of the knowledge graphs to learn the
high-order relations as a tensor. In this paper, we generalize a widely used
label propagation model to the normalized tensor product graph, and propose an
optimization formulation and a scalable Low-rank Tensor-based Label Propagation
algorithm (LowrankTLP) to infer multi-relations for two learning tasks,
hyperlink prediction and multiple graph alignment. The optimization formulation
minimizes the upper bound of the noisy tensor estimation error for multiple
graph alignment, by learning with a subset of the eigen-pairs in the spectrum
of the normalized tensor product graph. We also provide a data-dependent
transductive Rademacher bound for binary hyperlink prediction. We accelerate
LowrankTLP with parallel tensor computation which enables label propagation on
a tensor product of 100 graphs each of size 1000 in less than half hour in the
simulation. LowrankTLP was also applied to predicting the author-paper-venue
hyperlinks in publication records, alignment of segmented regions across up to
26 CT-scan images and alignment of protein-protein interaction networks across
multiple species. The experiments demonstrate that LowrankTLP indeed well
approximates the original label propagation with better scalability and
accuracy.
| cs.LG | multirelational learning on knowledge graphs infers highorder relations among the entities across the graphs this learning task can be solved by label propagation on the tensor product of the knowledge graphs to learn the highorder relations as a tensor in this paper we generalize a widely used label propagation model to the normalized tensor product graph and propose an optimization formulation and a scalable lowrank tensorbased label propagation algorithm lowranktlp to infer multirelations for two learning tasks hyperlink prediction and multiple graph alignment the optimization formulation minimizes the upper bound of the noisy tensor estimation error for multiple graph alignment by learning with a subset of the eigenpairs in the spectrum of the normalized tensor product graph we also provide a datadependent transductive rademacher bound for binary hyperlink prediction we accelerate lowranktlp with parallel tensor computation which enables label propagation on a tensor product of 100 graphs each of size 1000 in less than half hour in the simulation lowranktlp was also applied to predicting the authorpapervenue hyperlinks in publication records alignment of segmented regions across up to 26 ctscan images and alignment of proteinprotein interaction networks across multiple species the experiments demonstrate that lowranktlp indeed well approximates the original label propagation with better scalability and accuracy | [['multirelational', 'learning', 'on', 'knowledge', 'graphs', 'infers', 'highorder', 'relations', 'among', 'the', 'entities', 'across', 'the', 'graphs', 'this', 'learning', 'task', 'can', 'be', 'solved', 'by', 'label', 'propagation', 'on', 'the', 'tensor', 'product', 'of', 'the', 'knowledge', 'graphs', 'to', 'learn', 'the', 'highorder', 'relations', 'as', 'a', 'tensor', 'in', 'this', 'paper', 'we', 'generalize', 'a', 'widely', 'used', 'label', 'propagation', 'model', 'to', 'the', 'normalized', 'tensor', 'product', 'graph', 'and', 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1,802.0738 | Fast Nonconvex Deconvolution of Calcium Imaging Data | Calcium imaging data promises to transform the field of neuroscience by
making it possible to record from large populations of neurons simultaneously.
However, determining the exact moment in time at which a neuron spikes, from a
calcium imaging data set, amounts to a non-trivial deconvolution problem which
is of critical importance for downstream analyses. While a number of
formulations have been proposed for this task in the recent literature, in this
paper we focus on a formulation recently proposed in Jewell and Witten (2017)
which has shown initial promising results. However, this proposal is slow to
run on fluorescence traces of hundreds of thousands of timesteps.
Here we develop a much faster online algorithm for solving the optimization
problem of Jewell and Witten (2017) that can be used to deconvolve a
fluorescence trace of 100,000 timesteps in less than a second. Furthermore,
this algorithm overcomes a technical challenge of Jewell and Witten (2017) by
avoiding the occurrence of so-called "negative" spikes. We demonstrate that
this algorithm has superior performance relative to existing methods for spike
deconvolution on calcium imaging datasets that were recently released as part
of the spikefinder challenge (http://spikefinder.codeneuro.org/).
Our C++ implementation, along with R and python wrappers, is publicly
available on Github at https://github.com/jewellsean/FastLZeroSpikeInference.
| stat.ME q-bio.NC stat.AP | calcium imaging data promises to transform the field of neuroscience by making it possible to record from large populations of neurons simultaneously however determining the exact moment in time at which a neuron spikes from a calcium imaging data set amounts to a nontrivial deconvolution problem which is of critical importance for downstream analyses while a number of formulations have been proposed for this task in the recent literature in this paper we focus on a formulation recently proposed in jewell and witten 2017 which has shown initial promising results however this proposal is slow to run on fluorescence traces of hundreds of thousands of timesteps here we develop a much faster online algorithm for solving the optimization problem of jewell and witten 2017 that can be used to deconvolve a fluorescence trace of 100000 timesteps in less than a second furthermore this algorithm overcomes a technical challenge of jewell and witten 2017 by avoiding the occurrence of socalled negative spikes we demonstrate that this algorithm has superior performance relative to existing methods for spike deconvolution on calcium imaging datasets that were recently released as part of the spikefinder challenge httpspikefindercodeneuroorg our c implementation along with r and python wrappers is publicly available on github at httpsgithubcomjewellseanfastlzerospikeinference | [['calcium', 'imaging', 'data', 'promises', 'to', 'transform', 'the', 'field', 'of', 'neuroscience', 'by', 'making', 'it', 'possible', 'to', 'record', 'from', 'large', 'populations', 'of', 'neurons', 'simultaneously', 'however', 'determining', 'the', 'exact', 'moment', 'in', 'time', 'at', 'which', 'a', 'neuron', 'spikes', 'from', 'a', 'calcium', 'imaging', 'data', 'set', 'amounts', 'to', 'a', 'nontrivial', 'deconvolution', 'problem', 'which', 'is', 'of', 'critical', 'importance', 'for', 'downstream', 'analyses', 'while', 'a', 'number', 'of', 'formulations', 'have', 'been', 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1,802.07381 | How to Subvert Backdoored Encryption: Security Against Adversaries that
Decrypt All Ciphertexts | We study secure and undetectable communication in a world where governments
can read all encrypted communications of citizens. We consider a world where
the only permitted communication method is via a government-mandated encryption
scheme, using government-mandated keys. Citizens caught trying to communicate
otherwise (e.g., by encrypting strings which do not appear to be natural
language plaintexts) will be arrested. The one guarantee we suppose is that the
government-mandated encryption scheme is semantically secure against outsiders:
a perhaps advantageous feature to secure communication against foreign
entities. But what good is semantic security against an adversary that has the
power to decrypt?
Even in this pessimistic scenario, we show citizens can communicate securely
and undetectably. Informally, there is a protocol between Alice and Bob where
they exchange ciphertexts that look innocuous even to someone who knows the
secret keys and thus sees the corresponding plaintexts. And yet, in the end,
Alice will have transmitted her secret message to Bob. Our security definition
requires indistinguishability between unmodified use of the mandated encryption
scheme, and conversations using the mandated encryption scheme in a modified
way for subliminal communication.
Our topics may be thought to fall broadly within the realm of steganography:
the science of hiding secret communication in innocent-looking messages, or
cover objects. However, we deal with the non-standard setting of adversarial
cover object distributions (i.e., a stronger-than-usual adversary). We leverage
that our cover objects are ciphertexts of a secure encryption scheme to bypass
impossibility results which we show for broader classes of steganographic
schemes. We give several constructions of subliminal communication schemes
based on any key exchange protocol with random messages (e.g., Diffie-Hellman).
| cs.CR | we study secure and undetectable communication in a world where governments can read all encrypted communications of citizens we consider a world where the only permitted communication method is via a governmentmandated encryption scheme using governmentmandated keys citizens caught trying to communicate otherwise eg by encrypting strings which do not appear to be natural language plaintexts will be arrested the one guarantee we suppose is that the governmentmandated encryption scheme is semantically secure against outsiders a perhaps advantageous feature to secure communication against foreign entities but what good is semantic security against an adversary that has the power to decrypt even in this pessimistic scenario we show citizens can communicate securely and undetectably informally there is a protocol between alice and bob where they exchange ciphertexts that look innocuous even to someone who knows the secret keys and thus sees the corresponding plaintexts and yet in the end alice will have transmitted her secret message to bob our security definition requires indistinguishability between unmodified use of the mandated encryption scheme and conversations using the mandated encryption scheme in a modified way for subliminal communication our topics may be thought to fall broadly within the realm of steganography the science of hiding secret communication in innocentlooking messages or cover objects however we deal with the nonstandard setting of adversarial cover object distributions ie a strongerthanusual adversary we leverage that our cover objects are ciphertexts of a secure encryption scheme to bypass impossibility results which we show for broader classes of steganographic schemes we give several constructions of subliminal communication schemes based on any key exchange protocol with random messages eg diffiehellman | [['we', 'study', 'secure', 'and', 'undetectable', 'communication', 'in', 'a', 'world', 'where', 'governments', 'can', 'read', 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1,802.07382 | Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic
Regression, Sigmoid and more | Coreset (or core-set) is a small weighted \emph{subset} $Q$ of an input set
$P$ with respect to a given \emph{monotonic} function
$f:\mathbb{R}\to\mathbb{R}$ that \emph{provably} approximates its fitting loss
$\sum_{p\in P}f(p\cdot x)$ to \emph{any} given $x\in\mathbb{R}^d$. Using $Q$ we
can obtain approximation of $x^*$ that minimizes this loss, by running
\emph{existing} optimization algorithms on $Q$. In this work we provide: (i) A
lower bound which proves that there are sets with no coresets smaller than
$n=|P|$ for general monotonic loss functions. (ii) A proof that, under a
natural assumption that holds e.g. for logistic regression and the sigmoid
activation functions, a small coreset exists for \emph{any} input $P$. (iii) A
generic coreset construction algorithm that computes such a small coreset $Q$
in $O(nd+n\log n)$ time, and (iv) Experimental results which demonstrate that
our coresets are effective and are much smaller in practice than predicted in
theory.
| cs.LG cs.DS | coreset or coreset is a small weighted emphsubset q of an input set p with respect to a given emphmonotonic function fmathbbrtomathbbr that emphprovably approximates its fitting loss sum_pin pfpcdot x to emphany given xinmathbbrd using q we can obtain approximation of x that minimizes this loss by running emphexisting optimization algorithms on q in this work we provide i a lower bound which proves that there are sets with no coresets smaller than np for general monotonic loss functions ii a proof that under a natural assumption that holds eg for logistic regression and the sigmoid activation functions a small coreset exists for emphany input p iii a generic coreset construction algorithm that computes such a small coreset q in ondnlog n time and iv experimental results which demonstrate that our coresets are effective and are much smaller in practice than predicted in theory | [['coreset', 'or', 'coreset', 'is', 'a', 'small', 'weighted', 'emphsubset', 'q', 'of', 'an', 'input', 'set', 'p', 'with', 'respect', 'to', 'a', 'given', 'emphmonotonic', 'function', 'fmathbbrtomathbbr', 'that', 'emphprovably', 'approximates', 'its', 'fitting', 'loss', 'sum_pin', 'pfpcdot', 'x', 'to', 'emphany', 'given', 'xinmathbbrd', 'using', 'q', 'we', 'can', 'obtain', 'approximation', 'of', 'x', 'that', 'minimizes', 'this', 'loss', 'by', 'running', 'emphexisting', 'optimization', 'algorithms', 'on', 'q', 'in', 'this', 'work', 'we', 'provide', 'i', 'a', 'lower', 'bound', 'which', 'proves', 'that', 'there', 'are', 'sets', 'with', 'no', 'coresets', 'smaller', 'than', 'np', 'for', 'general', 'monotonic', 'loss', 'functions', 'ii', 'a', 'proof', 'that', 'under', 'a', 'natural', 'assumption', 'that', 'holds', 'eg', 'for', 'logistic', 'regression', 'and', 'the', 'sigmoid', 'activation', 'functions', 'a', 'small', 'coreset', 'exists', 'for', 'emphany', 'input', 'p', 'iii', 'a', 'generic', 'coreset', 'construction', 'algorithm', 'that', 'computes', 'such', 'a', 'small', 'coreset', 'q', 'in', 'ondnlog', 'n', 'time', 'and', 'iv', 'experimental', 'results', 'which', 'demonstrate', 'that', 'our', 'coresets', 'are', 'effective', 'and', 'are', 'much', 'smaller', 'in', 'practice', 'than', 'predicted', 'in', 'theory']] | [-0.10893406477221783, 0.07646999173190408, -0.0838256628658781, 0.11493752387117806, -0.04332715526540229, -0.2101494254319803, 0.08945803326333325, 0.38974721824208686, -0.24804064039312673, -0.28685503498467796, 0.03624986645481582, -0.2565562888147666, -0.16898029695714142, 0.2156595546010789, -0.09414318665954555, 0.09261322761217053, 0.08693875317917542, 0.03007634508061051, -0.10287421672185552, -0.27899197805408676, 0.29086737332086193, -0.014285797053446056, 0.23307856615031705, 0.014690818940041626, 0.10957368539567007, 0.022408636653439163, 0.03455897813649676, 0.04303924573572181, -0.12962869213618866, 0.1313710709912405, 0.2408291835829959, 0.21233893046155572, 0.30351877657709814, -0.35023712711606886, -0.17544274219845962, 0.15831345362681234, 0.12440272111886144, 0.06667674328481236, -0.04763538925000301, -0.15954130950733914, 0.16715022571820845, -0.12751915961741767, -0.06587036337921436, -0.09153438216002645, 0.09597570330056474, 0.016080968531099617, -0.4070404209394721, 0.030009664917746162, 0.11648766445458358, 0.0166825661714377, -0.055974156986294536, -0.1976476164182965, 0.03323444401752864, 0.0048983622398491656, -0.00470825557676243, 0.14687468691114733, 0.08963162079453468, -0.09229029918086207, -0.09095205388243265, 0.3522105155816526, -0.08065162513983859, -0.23295479067370084, 0.12298906104414599, -0.10834476103055034, -0.11894925136171969, 0.11993894279531553, 0.16872137339607357, 0.14606867525363276, -0.054216266381851536, 0.13589133641142595, -0.10843362441907327, 0.1909236737315589, 0.08865987095017488, 0.008075996053963239, 0.06704764708988897, 0.15071893979445206, 0.13909168216459294, 0.13105149168673083, -0.01865338633688999, -0.044069818756047714, -0.36884291762327576, -0.08882957849554975, -0.23431648900864502, 0.06423031655140221, -0.16468624589960207, -0.21117634418361048, 0.31224335863499353, 0.1093140735475888, 0.27012174384972304, 0.18369668635130193, 0.2955637319229794, 0.13606856670240947, 0.06928869607983858, 0.1449973173670682, 0.13868201625242776, 0.03628171204939379, -0.0013416270421593324, -0.131550550305595, 0.1257881080427914, 0.08229014278944344] |
1,802.07383 | Artinian algebras and Jordan type | The Jordan type of an element $\ell$ of the maximal ideal of an Artinian
k-algebra A acting on an A-module M of k-dimension n, is the partition of n
given by the Jordan block decomposition of the multiplication map $m_\ell$ on
M. In general the Jordan type has more information than whether the pair
$(\ell,M)$ is strong or weak Lefschetz. We develop basic properties of the
Jordan type and their loci for modules over graded or local Artinian algebras.
We as well study the relation of generic Jordan type of $A$ to the Hilbert
function of $A$. We introduce and study a finer invariant, the Jordan degree
type.
In our last sections we give an overview of topics such as the Jordan types
for Nagata idealizations, for modular tensor products, and for free extensions,
including examples and some new results. We as well propose open problems.
| math.AC | the jordan type of an element ell of the maximal ideal of an artinian kalgebra a acting on an amodule m of kdimension n is the partition of n given by the jordan block decomposition of the multiplication map m_ell on m in general the jordan type has more information than whether the pair ellm is strong or weak lefschetz we develop basic properties of the jordan type and their loci for modules over graded or local artinian algebras we as well study the relation of generic jordan type of a to the hilbert function of a we introduce and study a finer invariant the jordan degree type in our last sections we give an overview of topics such as the jordan types for nagata idealizations for modular tensor products and for free extensions including examples and some new results we as well propose open problems | [['the', 'jordan', 'type', 'of', 'an', 'element', 'ell', 'of', 'the', 'maximal', 'ideal', 'of', 'an', 'artinian', 'kalgebra', 'a', 'acting', 'on', 'an', 'amodule', 'm', 'of', 'kdimension', 'n', 'is', 'the', 'partition', 'of', 'n', 'given', 'by', 'the', 'jordan', 'block', 'decomposition', 'of', 'the', 'multiplication', 'map', 'm_ell', 'on', 'm', 'in', 'general', 'the', 'jordan', 'type', 'has', 'more', 'information', 'than', 'whether', 'the', 'pair', 'ellm', 'is', 'strong', 'or', 'weak', 'lefschetz', 'we', 'develop', 'basic', 'properties', 'of', 'the', 'jordan', 'type', 'and', 'their', 'loci', 'for', 'modules', 'over', 'graded', 'or', 'local', 'artinian', 'algebras', 'we', 'as', 'well', 'study', 'the', 'relation', 'of', 'generic', 'jordan', 'type', 'of', 'a', 'to', 'the', 'hilbert', 'function', 'of', 'a', 'we', 'introduce', 'and', 'study', 'a', 'finer', 'invariant', 'the', 'jordan', 'degree', 'type', 'in', 'our', 'last', 'sections', 'we', 'give', 'an', 'overview', 'of', 'topics', 'such', 'as', 'the', 'jordan', 'types', 'for', 'nagata', 'idealizations', 'for', 'modular', 'tensor', 'products', 'and', 'for', 'free', 'extensions', 'including', 'examples', 'and', 'some', 'new', 'results', 'we', 'as', 'well', 'propose', 'open', 'problems']] | [-0.15968048708491053, 0.030911465896666688, -0.03523882577348858, 0.054144757316600886, -0.08077763659841292, -0.16872558415522926, -0.04236901084866936, 0.3228127123622147, -0.34084909641477346, -0.18618230700926625, 0.11085736511230519, -0.24079413316999992, -0.14413725052105442, 0.20354696207086567, -0.09318322694401117, -0.02421685189889004, 0.02985168975931018, 0.12922670525077679, -0.11704158931906807, -0.27945074391605534, 0.4194402385898547, 0.009438211996146566, 0.1925665347722091, 0.04573683267497547, 0.10150136360707246, 0.05420919999716268, -0.04612604865153665, 0.00296226977562047, -0.18192949290833857, 0.12210644295675144, 0.25170056995846435, 0.14876395287087876, 0.23471455643438313, -0.39983498042270743, -0.10171619297183845, 0.19163275822001982, 0.13851042600884422, 0.017846428761091274, -0.036985120486188204, -0.22748678611680764, 0.11867475479263939, -0.1892985603031551, -0.13115067881921127, -0.0564497986869019, 0.09724082705829522, 0.014490873999782035, -0.27376463255934314, 0.025204344796118876, 0.11908387055792782, 0.1383753720454055, -0.06692477485024664, -0.10128043287621862, -0.022335599962787778, 0.07970924202148637, -0.057887254349810825, -0.0044874051555493615, 0.09524832605001556, -0.0985089231008179, -0.1417130370088534, 0.3577403163231195, -0.06401809919571698, -0.21802735997185316, 0.17170416505063232, -0.11426314299492395, -0.12632106420622297, 0.02932368034228989, 0.09654022857215103, 0.14603110049749177, -0.07677716370161673, 0.1866888394403871, -0.12944332128773406, 0.06264739704863742, 0.09186173072850255, 0.04505577215754223, 0.1682269618693382, 0.12726045055442478, 0.05533227165969574, 0.1316006181280014, 0.011391003389702472, 0.007944300263635304, -0.39341851357013397, -0.2357050301060591, -0.11482810985603153, 0.13084070371744566, -0.13156937739982474, -0.1969118216393949, 0.46577798977991797, 0.04426446819856559, 0.2166237844930075, 0.09261787845434187, 0.2160166305591901, 0.03856535192917114, 0.09782999849157434, 0.04788616389572008, 0.1347585004566585, 0.21452175415669605, 0.009841516912972224, -0.12267970436967093, -0.03274048052485777, 0.19442484665929965] |
1,802.07384 | Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic
Corrections | We present a new algorithm to generate minimal, stable, and symbolic
corrections to an input that will cause a neural network with ReLU activations
to change its output. We argue that such a correction is a useful way to
provide feedback to a user when the network's output is different from a
desired output. Our algorithm generates such a correction by solving a series
of linear constraint satisfaction problems. The technique is evaluated on three
neural network models: one predicting whether an applicant will pay a mortgage,
one predicting whether a first-order theorem can be proved efficiently by a
solver using certain heuristics, and the final one judging whether a drawing is
an accurate rendition of a canonical drawing of a cat.
| cs.LG cs.AI stat.ML | we present a new algorithm to generate minimal stable and symbolic corrections to an input that will cause a neural network with relu activations to change its output we argue that such a correction is a useful way to provide feedback to a user when the networks output is different from a desired output our algorithm generates such a correction by solving a series of linear constraint satisfaction problems the technique is evaluated on three neural network models one predicting whether an applicant will pay a mortgage one predicting whether a firstorder theorem can be proved efficiently by a solver using certain heuristics and the final one judging whether a drawing is an accurate rendition of a canonical drawing of a cat | [['we', 'present', 'a', 'new', 'algorithm', 'to', 'generate', 'minimal', 'stable', 'and', 'symbolic', 'corrections', 'to', 'an', 'input', 'that', 'will', 'cause', 'a', 'neural', 'network', 'with', 'relu', 'activations', 'to', 'change', 'its', 'output', 'we', 'argue', 'that', 'such', 'a', 'correction', 'is', 'a', 'useful', 'way', 'to', 'provide', 'feedback', 'to', 'a', 'user', 'when', 'the', 'networks', 'output', 'is', 'different', 'from', 'a', 'desired', 'output', 'our', 'algorithm', 'generates', 'such', 'a', 'correction', 'by', 'solving', 'a', 'series', 'of', 'linear', 'constraint', 'satisfaction', 'problems', 'the', 'technique', 'is', 'evaluated', 'on', 'three', 'neural', 'network', 'models', 'one', 'predicting', 'whether', 'an', 'applicant', 'will', 'pay', 'a', 'mortgage', 'one', 'predicting', 'whether', 'a', 'firstorder', 'theorem', 'can', 'be', 'proved', 'efficiently', 'by', 'a', 'solver', 'using', 'certain', 'heuristics', 'and', 'the', 'final', 'one', 'judging', 'whether', 'a', 'drawing', 'is', 'an', 'accurate', 'rendition', 'of', 'a', 'canonical', 'drawing', 'of', 'a', 'cat']] | [-0.07533130189308469, 0.03436330517266827, -0.1354056366520827, 0.10441670820620827, -0.12111351755065997, -0.22572810763538984, 0.06714824189958697, 0.3803035557750979, -0.307725915723465, -0.299694751450395, 0.09189359366618952, -0.2541759494371468, -0.19712968558439467, 0.20958629263885564, -0.09613787235318087, 0.07647306931569607, 0.11248895851131833, 0.06714905311804853, -0.07348155353187782, -0.26165636546802934, 0.2778843980832178, 0.052429017171904936, 0.2481903596418589, 0.015142472728048681, 0.1457899670979222, -0.04762558996179771, 0.018103334048885058, 0.04346489312306627, -0.05272683372769264, 0.13994700766596027, 0.2601933789159017, 0.21558131249697848, 0.37487074724001596, -0.4040315506643936, -0.20634992674115252, 0.1200726779834291, 0.08166734186443882, 0.16355347325720015, -0.030461043429553327, -0.24696508132123587, 0.11895572117586586, -0.16873312126997797, -0.05012422466467394, -0.08725583933477031, -0.009573012972097904, -0.014926549032724489, -0.3505087004073697, -0.04681599450767132, 0.07155770968923013, 0.010464536365823911, -0.003947887685127007, -0.0639052740870746, -0.013908409155699134, 0.15271590580160874, -0.034598268683022654, 0.09060577743640932, 0.11592536768017214, -0.16689587385941404, -0.14845871657217075, 0.38861582371726877, -0.04680638709945268, -0.2452062621262291, 0.12400909499875958, -0.028989508122083594, -0.1488336947895434, 0.10795005529615112, 0.2077876508281734, 0.11369048938017766, -0.14128251638529216, -0.011993195161773999, -0.06023264435486349, 0.2294902135618031, 0.04017840065520074, -0.05378606028618199, 0.219201203634138, 0.20130596647886406, 0.07742881507719637, 0.1666191295619489, -0.04424135593366313, -0.02885297051970618, -0.2659791439702948, -0.12106037855262346, -0.16436431450066996, 0.049610750337482475, -0.09227888241050514, -0.2001843569937666, 0.4164145888959164, 0.15758896769467193, 0.20818887042171766, 0.10241170823345053, 0.3271744742333034, 0.14165924076605435, 0.06707029049971798, 0.08678664077745109, 0.17751049441590783, 0.06511982322334632, 0.08181670489797338, -0.17105973084632795, 0.1060177774863226, 0.0896613906694912] |
1,802.07385 | Universal Growth in Production Economies | We consider a simple variant of the von Neumann model of an expanding
economy, in which multiple producers make goods according to their production
function. The players trade their goods at the market and then use the bundles
acquired for the production in the next round. We study a simple decentralized
dynamic---known as proportional response---in which players update their bids
proportionally to how useful the investments were in the past round.
We show this dynamic leads to growth of the economy in the long term
(whenever growth is possible) but also creates unbounded inequality, i.e. very
rich and very poor players emerge. We analyze several other phenomena, such as
how the relation of a player with others influences its development and the
Gini index of the system.
One of the key technical findings is that the players learn a global feature
of the network (the optimal cycle) in a decentralized way, while interacting
locally with their direct neighbors. We obtain this by studying the volume in
the resulting dynamical system and showing that the volume of each cycle
expands or contracts by a constant factor in each round.
| cs.GT | we consider a simple variant of the von neumann model of an expanding economy in which multiple producers make goods according to their production function the players trade their goods at the market and then use the bundles acquired for the production in the next round we study a simple decentralized dynamicknown as proportional responsein which players update their bids proportionally to how useful the investments were in the past round we show this dynamic leads to growth of the economy in the long term whenever growth is possible but also creates unbounded inequality ie very rich and very poor players emerge we analyze several other phenomena such as how the relation of a player with others influences its development and the gini index of the system one of the key technical findings is that the players learn a global feature of the network the optimal cycle in a decentralized way while interacting locally with their direct neighbors we obtain this by studying the volume in the resulting dynamical system and showing that the volume of each cycle expands or contracts by a constant factor in each round | [['we', 'consider', 'a', 'simple', 'variant', 'of', 'the', 'von', 'neumann', 'model', 'of', 'an', 'expanding', 'economy', 'in', 'which', 'multiple', 'producers', 'make', 'goods', 'according', 'to', 'their', 'production', 'function', 'the', 'players', 'trade', 'their', 'goods', 'at', 'the', 'market', 'and', 'then', 'use', 'the', 'bundles', 'acquired', 'for', 'the', 'production', 'in', 'the', 'next', 'round', 'we', 'study', 'a', 'simple', 'decentralized', 'dynamicknown', 'as', 'proportional', 'responsein', 'which', 'players', 'update', 'their', 'bids', 'proportionally', 'to', 'how', 'useful', 'the', 'investments', 'were', 'in', 'the', 'past', 'round', 'we', 'show', 'this', 'dynamic', 'leads', 'to', 'growth', 'of', 'the', 'economy', 'in', 'the', 'long', 'term', 'whenever', 'growth', 'is', 'possible', 'but', 'also', 'creates', 'unbounded', 'inequality', 'ie', 'very', 'rich', 'and', 'very', 'poor', 'players', 'emerge', 'we', 'analyze', 'several', 'other', 'phenomena', 'such', 'as', 'how', 'the', 'relation', 'of', 'a', 'player', 'with', 'others', 'influences', 'its', 'development', 'and', 'the', 'gini', 'index', 'of', 'the', 'system', 'one', 'of', 'the', 'key', 'technical', 'findings', 'is', 'that', 'the', 'players', 'learn', 'a', 'global', 'feature', 'of', 'the', 'network', 'the', 'optimal', 'cycle', 'in', 'a', 'decentralized', 'way', 'while', 'interacting', 'locally', 'with', 'their', 'direct', 'neighbors', 'we', 'obtain', 'this', 'by', 'studying', 'the', 'volume', 'in', 'the', 'resulting', 'dynamical', 'system', 'and', 'showing', 'that', 'the', 'volume', 'of', 'each', 'cycle', 'expands', 'or', 'contracts', 'by', 'a', 'constant', 'factor', 'in', 'each', 'round']] | [-0.11467451224809573, 0.09911101186932478, -0.09690707345162669, 0.057332406296164436, -0.06900810232005453, -0.16429936494590636, 0.10819115631735474, 0.3666102700673985, -0.3176877859088602, -0.2624078480707061, 0.1263287164657677, -0.2834306444712384, -0.14725672876993093, 0.12815963296984542, -0.09475348178755431, -0.022973520486297645, 0.037953349426814345, 0.06812996477118984, 0.02625218012854607, -0.31367663981177674, 0.3263979642451691, 0.054978510627763405, 0.26830791104810253, 0.030929392912194775, 0.10398933079258929, 0.012270258008552495, -0.04511269604253973, 0.043011438890423824, -0.13588669923954375, 0.13983124743656367, 0.23367540858515728, 0.15563081180857075, 0.3530624797417512, -0.44230969031892153, -0.1483258800944113, 0.13920257282843915, 0.10408121171677785, 0.06568916059721584, -0.022577021914404086, -0.22297457740792342, 0.04604553249138858, -0.22452210917347862, -0.12289096255065693, -0.049251818581314014, 0.009257947728137976, 0.04536203019413596, -0.25767270013845217, 0.024501095769234673, 0.0372160851684091, 0.012970833911470348, -0.05440856536014146, -0.05741507582421545, -0.05360336877876312, 0.20444224552396606, 0.07511868085386732, -0.00695324450936569, 0.14416126465494994, -0.16894790387126588, -0.1324192890021149, 0.3871518626849177, -0.06001929950246948, -0.15477275875677424, 0.17854938677622265, -0.14439422460222837, -0.11759168709007402, 0.05711713601003892, 0.18446868423889493, 0.087623858426307, -0.12999256437404022, 0.03502893729651126, -0.05957344061975438, 0.15608207782560218, 0.05800738603237175, 0.03355571046792051, 0.18337204922691627, 0.17539119793687977, 0.14136112732211908, 0.13985969349510358, -0.002875577828969546, -0.14638345989039397, -0.27088043112990007, -0.17929095372567655, -0.1384394461193913, 0.053189808729365066, -0.14064862509649273, -0.15407713308095775, 0.4007525052124214, 0.09806811123064929, 0.20640092143402133, 0.07372719353479233, 0.2959553642168401, 0.08591463853309672, 0.06456844039982365, 0.09511102313083165, 0.2300938586704433, 0.04622674631755999, 0.14750775213350834, -0.2023672292369508, 0.12077466931234124, 0.026655756923500248] |
1,802.07386 | Subspace Methods for 3-Parameter Eigenvalue Problems | We propose subspace methods for 3-parameter eigenvalue problems. Such
problems arise when separation of variables is applied to separable boundary
value problems; a particular example is the Helmholtz equation in ellipsoidal
and paraboloidal coordinates. While several subspace methods for 2-parameter
eigenvalue problems exist, their extensions to three parameter setting seem to
be challenging. An inherent difficulty is that, while for 2-parameter
eigenvalue problems we can exploit a relation to Sylvester equations to obtain
a fast Arnoldi type method, such a relation does not seem to exist when there
are three or more parameters. Instead, we introduce a subspace iteration method
with projections onto generalized Krylov subspaces that are constructed from
scratch at every iteration using certain Ritz vectors as the initial vectors.
Another possibility is a Jacobi--Davidson type method for three or more
parameters, which we generalize from its 2-parameter counterpart. For both
approaches, we introduce a selection criterion for deflation that is based on
the angles between left and right eigenvectors. The Jacobi--Davidson approach
is devised to locate eigenvalues close to a prescribed target, yet it often
also performs well when eigenvalues are sought based on the proximity of one of
the components to a prescribed target. The subspace iteration method is devised
specifically for the latter task. The proposed approaches are suitable
especially for problems where the computation of several eigenvalues is
required with high accuracy. Matlab implementations of both methods have been
made available in the package MultiParEig.
| math.NA | we propose subspace methods for 3parameter eigenvalue problems such problems arise when separation of variables is applied to separable boundary value problems a particular example is the helmholtz equation in ellipsoidal and paraboloidal coordinates while several subspace methods for 2parameter eigenvalue problems exist their extensions to three parameter setting seem to be challenging an inherent difficulty is that while for 2parameter eigenvalue problems we can exploit a relation to sylvester equations to obtain a fast arnoldi type method such a relation does not seem to exist when there are three or more parameters instead we introduce a subspace iteration method with projections onto generalized krylov subspaces that are constructed from scratch at every iteration using certain ritz vectors as the initial vectors another possibility is a jacobidavidson type method for three or more parameters which we generalize from its 2parameter counterpart for both approaches we introduce a selection criterion for deflation that is based on the angles between left and right eigenvectors the jacobidavidson approach is devised to locate eigenvalues close to a prescribed target yet it often also performs well when eigenvalues are sought based on the proximity of one of the components to a prescribed target the subspace iteration method is devised specifically for the latter task the proposed approaches are suitable especially for problems where the computation of several eigenvalues is required with high accuracy matlab implementations of both methods have been made available in the package multipareig | [['we', 'propose', 'subspace', 'methods', 'for', '3parameter', 'eigenvalue', 'problems', 'such', 'problems', 'arise', 'when', 'separation', 'of', 'variables', 'is', 'applied', 'to', 'separable', 'boundary', 'value', 'problems', 'a', 'particular', 'example', 'is', 'the', 'helmholtz', 'equation', 'in', 'ellipsoidal', 'and', 'paraboloidal', 'coordinates', 'while', 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1,802.07387 | Dynamics of Viscous Entrapped Saturated Zones in Partially Wetted Porous
Media | As a typical multiphase fluid flow process, drainage in porous media is of
fundamental interest in nature and industrial applications. During drainage
processes in unsaturated soils and porous media in general, saturated clusters,
in which a liquid phase fully occupies the pore space between solid grains,
affect the relative permeability and effective stress of the system. In this
study, we experimentally studied drainage processes in unsaturated granular
media as a model porous system. The distribution of saturated clusters is
analysed by an optical imaging method under different drainage conditions, in
which pore-scale information from Voronoi and Delaunay tessellation was used to
characterise the topology of saturated cluster distributions. By employing
statistical analyses, the observed spatial and temporal information of
multiphase flow and fluid entrapment in porous media are described. The results
indicate that the distributions of both the crystallised cell size and pore
size are positively correlated to the spatial and temporal distribution of
saturated cluster sizes. The saturated cluster size is found to follow a
lognormal distribution, in which the generalised Bond number correlates
negatively to the scale parameter and positively to the shape parameter. These
findings can be used to connect pore-scale behaviour with overall
hydro-mechanical characteristics in partially saturated porous media, using
both the degree of saturation and generalised Bond number.
| cond-mat.soft | as a typical multiphase fluid flow process drainage in porous media is of fundamental interest in nature and industrial applications during drainage processes in unsaturated soils and porous media in general saturated clusters in which a liquid phase fully occupies the pore space between solid grains affect the relative permeability and effective stress of the system in this study we experimentally studied drainage processes in unsaturated granular media as a model porous system the distribution of saturated clusters is analysed by an optical imaging method under different drainage conditions in which porescale information from voronoi and delaunay tessellation was used to characterise the topology of saturated cluster distributions by employing statistical analyses the observed spatial and temporal information of multiphase flow and fluid entrapment in porous media are described the results indicate that the distributions of both the crystallised cell size and pore size are positively correlated to the spatial and temporal distribution of saturated cluster sizes the saturated cluster size is found to follow a lognormal distribution in which the generalised bond number correlates negatively to the scale parameter and positively to the shape parameter these findings can be used to connect porescale behaviour with overall hydromechanical characteristics in partially saturated porous media using both the degree of saturation and generalised bond number | [['as', 'a', 'typical', 'multiphase', 'fluid', 'flow', 'process', 'drainage', 'in', 'porous', 'media', 'is', 'of', 'fundamental', 'interest', 'in', 'nature', 'and', 'industrial', 'applications', 'during', 'drainage', 'processes', 'in', 'unsaturated', 'soils', 'and', 'porous', 'media', 'in', 'general', 'saturated', 'clusters', 'in', 'which', 'a', 'liquid', 'phase', 'fully', 'occupies', 'the', 'pore', 'space', 'between', 'solid', 'grains', 'affect', 'the', 'relative', 'permeability', 'and', 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1,802.07388 | Canonical heights on hyper-K\"ahler varieties and the
Kawaguchi-Silverman conjecture | The Kawaguchi--Silverman conjecture predicts that if $f\colon X
\dashrightarrow X$ is a dominant rational-self map of a projective variety over
$\overline{\mathbb{Q}}$, and $P$ is a $\overline{\mathbb{Q}}$-point of $X$ with
Zariski-dense orbit, then the dynamical and arithmetic degrees of $f$ coincide:
$\lambda_1(f) = \alpha_f(P)$. We prove this conjecture in several
higher-dimensional settings, including all endomorphisms of non-uniruled smooth
projective threefolds with degree larger than $1$, and all endomorphisms of
hyper-K\"ahler varieties in any dimension. In the latter case, we construct a
canonical height function associated to any automorphism $f\colon X \to X$ of a
hyper-K\"ahler variety defined over $\overline{\mathbb{Q}}$.
| math.AG math.DS math.NT | the kawaguchisilverman conjecture predicts that if fcolon x dashrightarrow x is a dominant rationalself map of a projective variety over overlinemathbbq and p is a overlinemathbbqpoint of x with zariskidense orbit then the dynamical and arithmetic degrees of f coincide lambda_1f alpha_fp we prove this conjecture in several higherdimensional settings including all endomorphisms of nonuniruled smooth projective threefolds with degree larger than 1 and all endomorphisms of hyperkahler varieties in any dimension in the latter case we construct a canonical height function associated to any automorphism fcolon x to x of a hyperkahler variety defined over overlinemathbbq | [['the', 'kawaguchisilverman', 'conjecture', 'predicts', 'that', 'if', 'fcolon', 'x', 'dashrightarrow', 'x', 'is', 'a', 'dominant', 'rationalself', 'map', 'of', 'a', 'projective', 'variety', 'over', 'overlinemathbbq', 'and', 'p', 'is', 'a', 'overlinemathbbqpoint', 'of', 'x', 'with', 'zariskidense', 'orbit', 'then', 'the', 'dynamical', 'and', 'arithmetic', 'degrees', 'of', 'f', 'coincide', 'lambda_1f', 'alpha_fp', 'we', 'prove', 'this', 'conjecture', 'in', 'several', 'higherdimensional', 'settings', 'including', 'all', 'endomorphisms', 'of', 'nonuniruled', 'smooth', 'projective', 'threefolds', 'with', 'degree', 'larger', 'than', '1', 'and', 'all', 'endomorphisms', 'of', 'hyperkahler', 'varieties', 'in', 'any', 'dimension', 'in', 'the', 'latter', 'case', 'we', 'construct', 'a', 'canonical', 'height', 'function', 'associated', 'to', 'any', 'automorphism', 'fcolon', 'x', 'to', 'x', 'of', 'a', 'hyperkahler', 'variety', 'defined', 'over', 'overlinemathbbq']] | [-0.24283121221084544, 0.055754884483015285, -0.06116547420660549, 0.04886370453057177, -0.028829501877400153, -0.17472954535425858, -0.020311133010917283, 0.3463689876284371, -0.31281516308638646, -0.15548369132893833, 0.04763357052604291, -0.2483070929227595, -0.1270453794760273, 0.23748456494526027, -0.16149500386908333, -0.020077137355791762, -0.00010275063253542844, 0.0808488492051417, -0.17091341909427354, -0.3595454511455597, 0.4197370805480379, -0.11820595836306506, 0.15700620288980452, 0.04210607344136039, 0.17919193214162232, 0.030589064072936455, 0.06947226087225879, -0.006162385515710141, -0.1575020378771482, 0.08793594484326449, 0.3180098401139827, 0.11043076639241994, 0.1685049291279048, -0.2796984023632521, -0.19326899166496353, 0.3181483457459414, 0.09404693075277387, -0.04259553261378661, 0.03664702436381436, -0.23356087613068124, 0.13965425264084727, -0.1610859599649631, -0.18956081324474924, -0.06682388456736474, 0.10664530719650235, 0.02923261648740005, -0.26125944033265114, -0.04761615543170495, 0.1305940153477887, 0.18399600589528997, -0.018091581150037336, -0.09121603602444396, -0.15496351260771143, -0.0008431616588495672, -0.022021625711126848, 0.18200871114064246, 0.08876685124693161, -0.060333086546768055, -0.09287612459701584, 0.3588628966430638, -0.07253336015933297, -0.22291079523200366, 0.11761097443547655, -0.22868290533648528, -0.1688998370540348, 0.19505336310001128, 0.10074825648297654, 0.21905785290266763, 0.047121750364238595, 0.24346048423854455, -0.16037177794830912, 0.12801269628107548, 0.12601691816358807, -0.03865962551332059, 0.11339850006303057, 0.066336031980872, 0.10906356150665855, 0.09443283256420747, 0.002183633484317862, -0.004579556245400763, -0.37842568172577845, -0.20235578634558207, -0.07842758309561759, 0.2640457108537567, -0.12393268771878904, -0.1391472766433466, 0.3563379095470969, 0.038046314683247436, 0.23191713383223148, 0.11851563093628972, 0.1873009220914955, -0.024968256331742444, 0.026601020444897896, 0.05716767398382914, 0.06171958941094419, 0.22737117418078112, -0.09377389485660464, -0.07412612349032721, -0.01932947944968622, 0.17089328663720887] |
1,802.07389 | 3LC: Lightweight and Effective Traffic Compression for Distributed
Machine Learning | The performance and efficiency of distributed machine learning (ML) depends
significantly on how long it takes for nodes to exchange state changes.
Overly-aggressive attempts to reduce communication often sacrifice final model
accuracy and necessitate additional ML techniques to compensate for this loss,
limiting their generality. Some attempts to reduce communication incur high
computation overhead, which makes their performance benefits visible only over
slow networks.
We present 3LC, a lossy compression scheme for state change traffic that
strikes balance between multiple goals: traffic reduction, accuracy,
computation overhead, and generality. It combines three new
techniques---3-value quantization with sparsity multiplication, quartic
encoding, and zero-run encoding---to leverage strengths of quantization and
sparsification techniques and avoid their drawbacks. It achieves a data
compression ratio of up to 39--107X, almost the same test accuracy of trained
models, and high compression speed. Distributed ML frameworks can employ 3LC
without modifications to existing ML algorithms. Our experiments show that 3LC
reduces wall-clock training time of ResNet-110--based image classifiers for
CIFAR-10 on a 10-GPU cluster by up to 16--23X compared to TensorFlow's baseline
design.
| cs.LG cs.DC stat.ML | the performance and efficiency of distributed machine learning ml depends significantly on how long it takes for nodes to exchange state changes overlyaggressive attempts to reduce communication often sacrifice final model accuracy and necessitate additional ml techniques to compensate for this loss limiting their generality some attempts to reduce communication incur high computation overhead which makes their performance benefits visible only over slow networks we present 3lc a lossy compression scheme for state change traffic that strikes balance between multiple goals traffic reduction accuracy computation overhead and generality it combines three new techniques3value quantization with sparsity multiplication quartic encoding and zerorun encodingto leverage strengths of quantization and sparsification techniques and avoid their drawbacks it achieves a data compression ratio of up to 39107x almost the same test accuracy of trained models and high compression speed distributed ml frameworks can employ 3lc without modifications to existing ml algorithms our experiments show that 3lc reduces wallclock training time of resnet110based image classifiers for cifar10 on a 10gpu cluster by up to 1623x compared to tensorflows baseline design | [['the', 'performance', 'and', 'efficiency', 'of', 'distributed', 'machine', 'learning', 'ml', 'depends', 'significantly', 'on', 'how', 'long', 'it', 'takes', 'for', 'nodes', 'to', 'exchange', 'state', 'changes', 'overlyaggressive', 'attempts', 'to', 'reduce', 'communication', 'often', 'sacrifice', 'final', 'model', 'accuracy', 'and', 'necessitate', 'additional', 'ml', 'techniques', 'to', 'compensate', 'for', 'this', 'loss', 'limiting', 'their', 'generality', 'some', 'attempts', 'to', 'reduce', 'communication', 'incur', 'high', 'computation', 'overhead', 'which', 'makes', 'their', 'performance', 'benefits', 'visible', 'only', 'over', 'slow', 'networks', 'we', 'present', '3lc', 'a', 'lossy', 'compression', 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1,802.0739 | Quantum contextuality implies a logic that does not obey the principle
of bivalence | In the paper, a value assignment for projection operators relating to a
quantum system is equated with assignment of truth-values to the propositions
associated with these operators. In consequence, the Kochen-Specker theorem
(its localized variant, to be exact) can be treated as the statement that a
logic of those projection operators does not obey the principle of bivalence.
This implies that such a logic has a gappy (partial) semantics or many-valued
semantics.
| quant-ph | in the paper a value assignment for projection operators relating to a quantum system is equated with assignment of truthvalues to the propositions associated with these operators in consequence the kochenspecker theorem its localized variant to be exact can be treated as the statement that a logic of those projection operators does not obey the principle of bivalence this implies that such a logic has a gappy partial semantics or manyvalued semantics | [['in', 'the', 'paper', 'a', 'value', 'assignment', 'for', 'projection', 'operators', 'relating', 'to', 'a', 'quantum', 'system', 'is', 'equated', 'with', 'assignment', 'of', 'truthvalues', 'to', 'the', 'propositions', 'associated', 'with', 'these', 'operators', 'in', 'consequence', 'the', 'kochenspecker', 'theorem', 'its', 'localized', 'variant', 'to', 'be', 'exact', 'can', 'be', 'treated', 'as', 'the', 'statement', 'that', 'a', 'logic', 'of', 'those', 'projection', 'operators', 'does', 'not', 'obey', 'the', 'principle', 'of', 'bivalence', 'this', 'implies', 'that', 'such', 'a', 'logic', 'has', 'a', 'gappy', 'partial', 'semantics', 'or', 'manyvalued', 'semantics']] | [-0.1255045301384396, 0.07116571614622241, -0.13186239472512776, 0.10081439706522764, -0.1356259873751292, -0.1586280753577335, 0.07573747239479821, 0.31089581838912433, -0.31248213244705564, -0.24870956407135558, 0.12746219767399858, -0.26072467395311427, -0.09754821877059941, 0.13538649760044386, -0.1607239347585063, 0.04923725417837785, 0.041235538367699415, 0.09116142141445177, -0.08656868082471192, -0.16227509812193197, 0.3225295550396873, -0.0341110225045769, 0.20910360219487403, 0.04769336863036086, 0.09150725283608255, 0.026438138871324353, 0.04354061361583364, 0.08210895444588256, -0.028702939806559396, 0.1184385781072908, 0.32087889727618957, 0.20476523826235077, 0.2922055122132103, -0.41144103104145163, -0.13330806213909657, 0.13771276741236863, 0.08451603411877942, 0.11344167246069345, 0.052335988038167774, -0.31461988870675367, 0.08458435081411153, -0.1849514802355164, -0.13021605495466954, -0.08567686777354942, 0.022468876792117953, -0.01468639194758402, -0.2750132723724366, 0.05281490434814865, 0.18960403030117354, 0.049940811932578474, -0.07734756135646927, -0.06306180566833872, -0.018465084599382762, 0.051478904772213556, -0.019126517274546333, 0.04513208240193004, 0.09350749225510906, -0.0544691396482651, -0.22203965276841903, 0.3686455006892275, -0.03321589354567954, -0.27014904632233083, 0.13221049145148653, -0.09863147320639756, -0.17312481019568318, 0.04374771578133934, 0.058905598332381084, 0.11338606939858033, -0.13709102596153067, 0.09340200784047031, -0.12261436348004888, 0.1835138908225215, 0.09783927753515956, 0.1291315407983752, 0.1840351118783777, 0.10230567804925765, 0.08876424007596345, 0.10944708868434343, 0.055310473957635824, -0.11862128414213657, -0.3565517411851842, -0.19545597624285924, -0.16443251248953553, 0.0749005787238275, -0.03431799893223797, -0.21060720269775224, 0.3556664323097923, 0.15274967822349733, 0.16968678679162016, 0.10051151167135686, 0.24074543515841165, 0.21483418710057675, 0.15057371808345327, 0.00443199220009976, 0.15787262236699462, 0.1835603709073944, 0.09087210474535823, -0.155863888154272, 0.109625377077868, 0.15042200537734768] |
1,802.07391 | Glassy, Gardner-like Phenomenology in Minimally Polydisperse Crystalline
Systems | We report on a non-equilibrium phase of matter, the minimally disordered
crystal phase, which we find exists between the maximally amorphous glasses and
the ideal crystal. Even though these near crystals appear highly ordered, they
display glassy and jamming features akin to those observed in amorphous solids.
Structurally, they exhibit a power-law scaling in their probability
distribution of weak forces and small interparticle gaps as well as a flat
density of vibrational states. Dynamically, they display anomalous aging above
a characteristic pressure. Quantitatively this disordered crystal phase has
much in common with the Gardner-like phase seen in maximally disordered solids.
Near crystals should be amenable to experimental realizations in
commercially-available particulate systems and are to be indispensable in
verifying the theory of amorphous materials.
| cond-mat.soft cond-mat.mtrl-sci | we report on a nonequilibrium phase of matter the minimally disordered crystal phase which we find exists between the maximally amorphous glasses and the ideal crystal even though these near crystals appear highly ordered they display glassy and jamming features akin to those observed in amorphous solids structurally they exhibit a powerlaw scaling in their probability distribution of weak forces and small interparticle gaps as well as a flat density of vibrational states dynamically they display anomalous aging above a characteristic pressure quantitatively this disordered crystal phase has much in common with the gardnerlike phase seen in maximally disordered solids near crystals should be amenable to experimental realizations in commerciallyavailable particulate systems and are to be indispensable in verifying the theory of amorphous materials | [['we', 'report', 'on', 'a', 'nonequilibrium', 'phase', 'of', 'matter', 'the', 'minimally', 'disordered', 'crystal', 'phase', 'which', 'we', 'find', 'exists', 'between', 'the', 'maximally', 'amorphous', 'glasses', 'and', 'the', 'ideal', 'crystal', 'even', 'though', 'these', 'near', 'crystals', 'appear', 'highly', 'ordered', 'they', 'display', 'glassy', 'and', 'jamming', 'features', 'akin', 'to', 'those', 'observed', 'in', 'amorphous', 'solids', 'structurally', 'they', 'exhibit', 'a', 'powerlaw', 'scaling', 'in', 'their', 'probability', 'distribution', 'of', 'weak', 'forces', 'and', 'small', 'interparticle', 'gaps', 'as', 'well', 'as', 'a', 'flat', 'density', 'of', 'vibrational', 'states', 'dynamically', 'they', 'display', 'anomalous', 'aging', 'above', 'a', 'characteristic', 'pressure', 'quantitatively', 'this', 'disordered', 'crystal', 'phase', 'has', 'much', 'in', 'common', 'with', 'the', 'gardnerlike', 'phase', 'seen', 'in', 'maximally', 'disordered', 'solids', 'near', 'crystals', 'should', 'be', 'amenable', 'to', 'experimental', 'realizations', 'in', 'commerciallyavailable', 'particulate', 'systems', 'and', 'are', 'to', 'be', 'indispensable', 'in', 'verifying', 'the', 'theory', 'of', 'amorphous', 'materials']] | [-0.12657633489300688, 0.3177173891430342, -0.13759658873323502, 0.02694966096707385, 0.013841164663691468, -0.16455703571711372, 0.03778378214077585, 0.43442894413128375, -0.25626994521126184, -0.2637917471063376, 0.05228640470933926, -0.30722638176436107, -0.18861358152225433, 0.12478563112274903, -0.00015583651247282884, 0.0859586856994263, -0.04749873851433518, -0.02958697289591882, -0.08089470067600969, -0.17820940871639707, 0.2440425657773224, -0.002186538681872492, 0.3097923808708424, 0.020573801504887218, 0.00695737817407987, -0.03059174239680898, 0.09367212008806021, 0.06961724767461419, -0.1515221551999571, 0.028935534362321554, 0.33418291827145113, -0.0850395359746294, 0.15343618326313127, -0.4837284872868681, -0.24265445510944827, 0.11866721281085194, 0.10724580518871062, 0.13071661416301125, -0.06852157451818144, -0.26291527550258653, 0.05413057935439292, -0.13606998635402964, -0.15517451786776867, -0.13391165578419842, 0.0038675372318432827, 0.026034618788436662, -0.1898761727710868, 0.14452595555041803, 0.06612062640204208, 0.07788601209507967, -0.09813222306878949, -0.07899562564178757, -0.06377436670595855, 0.04371181764920068, -0.0028528903830584472, -0.014809454556524269, 0.21105511323738146, -0.17418819993575355, -0.06588763122284043, 0.44951530685269736, 0.005252578825788285, -0.10274317571741899, 0.26409819964470904, -0.17953592848517302, -0.10962565557470894, 0.2019816549510006, 0.13006980153703607, 0.07886943822287447, -0.10007791749648447, 0.010152108051125111, -0.02628038373559986, 0.2059734773924347, 0.03425729410662278, 0.11221492990881689, 0.28252149601959115, 0.17518129620731362, 0.0006632946916227419, 0.17726783506207622, -0.035743640200045654, -0.09964122693622257, -0.20883352021550441, -0.17059170863992437, -0.22572190043463455, 0.04809298997231342, -0.08586366580396028, -0.2580847571711851, 0.3232506531010556, 0.09011624286678142, 0.16497436071920202, -0.009527044989167698, 0.1586200227323026, 0.05056305159057483, 0.060965968026189, 0.047376995667724346, 0.29421333447704473, 0.13033584685526728, 0.11347891679942244, -0.18592389509445284, 0.08121376751890838, -0.02812716802695721] |
1,802.07392 | Chromospheric heating due to cancellation of quiet Sun internetwork
fields | The heating of the solar chromosphere remains one of the most important
questions in solar physics. Our current understanding is that small-scale
internetwork (IN) magnetic fields play an important role as a heating agent.
Indeed, cancellations of IN magnetic elements in the photosphere can produce
transient brightenings in the chromosphere and transition region. These bright
structures might be the signature of energy release and plasma heating,
probably driven by magnetic reconnection of IN field lines. Although single
events are not expected to release large amounts of energy, their global
contribution to the chromosphere may be significant due to their ubiquitous
presence in quiet Sun regions. In this paper we study cancellations of IN
elements and analyze their impact on the energetics and dynamics of the quiet
Sun atmosphere. We use high resolution, multiwavelength, coordinated
observations obtained with the Interface Region Imaging Spectrograph (IRIS) and
the Swedish 1-m Solar Telescope (SST) to identify cancellations of IN magnetic
flux patches and follow their evolution. We find that, on average, these events
live for ~3 minutes in the photosphere and ~12 minutes in the chromosphere
and/or transition region. Employing multi-line inversions of the Mg II h & k
lines we show that cancellations produce clear signatures of heating in the
upper atmospheric layers. However, at the resolution and sensitivity accessible
to the SST, their number density still seems to be one order of magnitude too
low to explain the global chromospheric heating.
| astro-ph.SR | the heating of the solar chromosphere remains one of the most important questions in solar physics our current understanding is that smallscale internetwork in magnetic fields play an important role as a heating agent indeed cancellations of in magnetic elements in the photosphere can produce transient brightenings in the chromosphere and transition region these bright structures might be the signature of energy release and plasma heating probably driven by magnetic reconnection of in field lines although single events are not expected to release large amounts of energy their global contribution to the chromosphere may be significant due to their ubiquitous presence in quiet sun regions in this paper we study cancellations of in elements and analyze their impact on the energetics and dynamics of the quiet sun atmosphere we use high resolution multiwavelength coordinated observations obtained with the interface region imaging spectrograph iris and the swedish 1m solar telescope sst to identify cancellations of in magnetic flux patches and follow their evolution we find that on average these events live for 3 minutes in the photosphere and 12 minutes in the chromosphere andor transition region employing multiline inversions of the mg ii h k lines we show that cancellations produce clear signatures of heating in the upper atmospheric layers however at the resolution and sensitivity accessible to the sst their number density still seems to be one order of magnitude too low to explain the global chromospheric heating | [['the', 'heating', 'of', 'the', 'solar', 'chromosphere', 'remains', 'one', 'of', 'the', 'most', 'important', 'questions', 'in', 'solar', 'physics', 'our', 'current', 'understanding', 'is', 'that', 'smallscale', 'internetwork', 'in', 'magnetic', 'fields', 'play', 'an', 'important', 'role', 'as', 'a', 'heating', 'agent', 'indeed', 'cancellations', 'of', 'in', 'magnetic', 'elements', 'in', 'the', 'photosphere', 'can', 'produce', 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0.053792603397076685] |
1,802.07393 | A lateral-type spin-photodiode based on Fe/x-AlOx/p-InGaAs junctions
with a refracting-facet side window | A lateral-type spin-photodiode having a refracting facet on a side edge of
the device is proposed and demonstrated at room temperature. The light shed
horizontally on the side of the device is refracted and introduced directly
into a thin InGaAs active layer under the spin-detecting Fe contact in which
spin-polarized carriers are generated and injected into the Fe contact through
a crystalline AlOx tunnel barrier. Experiments have been carried out with a
circular polarization spectrometry set up, through which helicity-dependent
photocurrent component, dI, is obtained with the conversion efficiency F ~ 0.4
%, where F is the ratio between dI and total photocurrent Iph. This value is
the highest reported so far for pure lateral-type spin-photodiodes. It is
discussed through analysis with a model consisting of drift-diffusion and
quantum tunneling equations that a factor that limits the F value is unoccupied
spin-polarized density-of-states of Fe in energy region into which
spin-polarized electrons in a semiconductor are injected.
| physics.app-ph | a lateraltype spinphotodiode having a refracting facet on a side edge of the device is proposed and demonstrated at room temperature the light shed horizontally on the side of the device is refracted and introduced directly into a thin ingaas active layer under the spindetecting fe contact in which spinpolarized carriers are generated and injected into the fe contact through a crystalline alox tunnel barrier experiments have been carried out with a circular polarization spectrometry set up through which helicitydependent photocurrent component di is obtained with the conversion efficiency f 04 where f is the ratio between di and total photocurrent iph this value is the highest reported so far for pure lateraltype spinphotodiodes it is discussed through analysis with a model consisting of driftdiffusion and quantum tunneling equations that a factor that limits the f value is unoccupied spinpolarized densityofstates of fe in energy region into which spinpolarized electrons in a semiconductor are injected | [['a', 'lateraltype', 'spinphotodiode', 'having', 'a', 'refracting', 'facet', 'on', 'a', 'side', 'edge', 'of', 'the', 'device', 'is', 'proposed', 'and', 'demonstrated', 'at', 'room', 'temperature', 'the', 'light', 'shed', 'horizontally', 'on', 'the', 'side', 'of', 'the', 'device', 'is', 'refracted', 'and', 'introduced', 'directly', 'into', 'a', 'thin', 'ingaas', 'active', 'layer', 'under', 'the', 'spindetecting', 'fe', 'contact', 'in', 'which', 'spinpolarized', 'carriers', 'are', 'generated', 'and', 'injected', 'into', 'the', 'fe', 'contact', 'through', 'a', 'crystalline', 'alox', 'tunnel', 'barrier', 'experiments', 'have', 'been', 'carried', 'out', 'with', 'a', 'circular', 'polarization', 'spectrometry', 'set', 'up', 'through', 'which', 'helicitydependent', 'photocurrent', 'component', 'di', 'is', 'obtained', 'with', 'the', 'conversion', 'efficiency', 'f', '04', 'where', 'f', 'is', 'the', 'ratio', 'between', 'di', 'and', 'total', 'photocurrent', 'iph', 'this', 'value', 'is', 'the', 'highest', 'reported', 'so', 'far', 'for', 'pure', 'lateraltype', 'spinphotodiodes', 'it', 'is', 'discussed', 'through', 'analysis', 'with', 'a', 'model', 'consisting', 'of', 'driftdiffusion', 'and', 'quantum', 'tunneling', 'equations', 'that', 'a', 'factor', 'that', 'limits', 'the', 'f', 'value', 'is', 'unoccupied', 'spinpolarized', 'densityofstates', 'of', 'fe', 'in', 'energy', 'region', 'into', 'which', 'spinpolarized', 'electrons', 'in', 'a', 'semiconductor', 'are', 'injected']] | [-0.11863525930216144, 0.15255095363796786, -0.051599782585215415, -0.04570430324958196, -0.006451521445629432, -0.18790287204625966, 0.07911705443678473, 0.4031232815039785, -0.25538183618827087, -0.2948272294658971, 0.009028120650327764, -0.33828863007090004, -0.05511064184400694, 0.22564048273948414, 0.04917006209583824, 0.0071237229552168985, 0.01638324843186542, -0.05262827092634612, -0.030472056060955908, -0.18750176436610913, 0.26853957371387976, 0.05503132600125881, 0.3171484365593642, 0.11052711527085385, 0.11883675765956898, -0.013355456303351707, 0.07136420522798098, 0.028314422739449105, -0.10124755661529075, 0.07510606734247535, 0.22142365531334163, -0.05588787612597164, 0.219611399659985, -0.44356545981473144, -0.20738577656945717, -0.0031844268577467453, 0.11155215790495276, 0.05399258138296366, -0.1037030732672735, -0.273988251549829, 0.07696457602708649, -0.11924756926753999, -0.06417407582538497, 0.02009778499823848, 0.007338690528597094, -0.0009248460080829988, -0.26541514745430933, 0.04054045157451918, 0.042696910274619436, 0.028847997005581612, -0.027745660578243826, -0.1304925945036015, -0.111912294562085, 0.04495921541360746, 0.0057648455158893115, 0.04086466653174475, 0.2114247135989564, -0.08500544863521722, -0.07938711960052483, 0.32043362283347004, -0.08426780079025775, -0.15620722637609824, 0.11974915112123678, -0.19251922765550644, -0.0163068187202474, 0.19384577833606223, 0.10082190575715351, 0.13577509825393608, -0.15947269169478923, 0.09899478814201614, -0.045801916874265054, 0.17260806615874907, 0.08859014346748345, 0.026378240146043123, 0.27866920049142974, 0.1984779804540602, 0.06364570698841769, 0.1304030783664386, -0.1602721514247701, -0.033922860696819906, -0.2337613669024952, -0.20441059452346771, -0.19492474856624062, 0.10764854118966277, -0.0016792653258514627, -0.1451260502324562, 0.4013334303408077, 0.08196293889226294, 0.18081644735004948, -0.06177865327289941, 0.32434713688072453, 0.15665647692798015, 0.07910020317496291, 0.044908107233870974, 0.25197299992616634, 0.16160613389403902, 0.10102917494317042, -0.22551928727434165, 0.08532155979743325, -0.004719848951361583] |
1,802.07394 | The "quantum" Turan problem for operator systems | Let V be a linear subspace of M_n(C) which contains the identity matrix and
is stable under Hermitian transpose. A "quantum k-clique" for V is a rank k
orthogonal projection P in M_n(C) for which dim(PVP) = k^2, and a "quantum
k-anticlique" is a rank k orthogonal projection for which dim(PVP) = 1. We give
upper and lower bounds both for the largest dimension of V which would ensure
the existence of a quantum k-anticlique, and for the smallest dimension of V
which would ensure the existence of a quantum k-clique.
| math.OA math.CO math.FA math.RA quant-ph | let v be a linear subspace of m_nc which contains the identity matrix and is stable under hermitian transpose a quantum kclique for v is a rank k orthogonal projection p in m_nc for which dimpvp k2 and a quantum kanticlique is a rank k orthogonal projection for which dimpvp 1 we give upper and lower bounds both for the largest dimension of v which would ensure the existence of a quantum kanticlique and for the smallest dimension of v which would ensure the existence of a quantum kclique | [['let', 'v', 'be', 'a', 'linear', 'subspace', 'of', 'm_nc', 'which', 'contains', 'the', 'identity', 'matrix', 'and', 'is', 'stable', 'under', 'hermitian', 'transpose', 'a', 'quantum', 'kclique', 'for', 'v', 'is', 'a', 'rank', 'k', 'orthogonal', 'projection', 'p', 'in', 'm_nc', 'for', 'which', 'dimpvp', 'k2', 'and', 'a', 'quantum', 'kanticlique', 'is', 'a', 'rank', 'k', 'orthogonal', 'projection', 'for', 'which', 'dimpvp', '1', 'we', 'give', 'upper', 'and', 'lower', 'bounds', 'both', 'for', 'the', 'largest', 'dimension', 'of', 'v', 'which', 'would', 'ensure', 'the', 'existence', 'of', 'a', 'quantum', 'kanticlique', 'and', 'for', 'the', 'smallest', 'dimension', 'of', 'v', 'which', 'would', 'ensure', 'the', 'existence', 'of', 'a', 'quantum', 'kclique']] | [-0.18047741335955844, 0.14580168522795361, -0.07038916474550791, -0.015473276014097205, -0.053186354687672924, -0.21942200924366198, 0.05284980169615184, 0.2776250298531062, -0.26176259585324374, -0.19411474898800082, 0.11540490204612885, -0.27233962277913915, -0.11156864407547247, 0.16165749354009656, -0.01706642420941043, 0.04030725304736493, 0.03668362614109941, 0.16080118012453976, -0.11406771643836608, -0.2834289691186157, 0.28785446286201477, -0.032260842294828306, 0.18357939660634803, 0.041494928136462585, 0.10976403476884482, 0.0068596803219239605, 0.03912486845691656, 0.022887082901601304, -0.1343970323709407, 0.11925811411802197, 0.30095734626011944, 0.17304995973412504, 0.2590595199351852, -0.2858729034705066, -0.12289597957405722, 0.20962268065918108, 0.09691439606998672, 0.029344028802642107, -0.010938003145415208, -0.24885969322667212, 0.19572483286818212, -0.1042947814446585, -0.13208449863405208, -0.050905587047274256, 0.13813231493903047, -0.06677882533905835, -0.38325714337072153, 0.013587133613704094, 0.12412493740176332, 0.048661214253669816, -0.008064117724204371, -0.18740383519566264, 0.003331462006973124, 0.06522022722149803, -0.10648879695458915, 0.05608706568212559, 0.036083984108449055, -0.07806776056899796, -0.10573892656649495, 0.39474894398630694, -0.06554500529563975, -0.18508770865998392, 0.13527523400797242, -0.13348761286543703, -0.10634720228858635, 0.11691124575619383, 0.14753075122790432, 0.09441591798255605, -0.05469620958420223, 0.201113027523154, -0.13526217020705514, 0.14555739938955883, 0.06802536196064675, 0.05226949427341079, 0.13654668901072836, 0.035484821086042916, 0.23114064529580974, 0.10125915615032588, -0.06530251228999903, -0.0029919935690089204, -0.32703989628573943, -0.21992034683453626, -0.20836039681801166, 0.15182502709072213, -0.13101558841633792, -0.1715471601400032, 0.3999285555722984, 0.038644907492930175, 0.23776810519911093, 0.06681449840450124, 0.2409700806648738, 0.13228984302225597, 0.04382219970568843, 0.13470761127363162, 0.1340453866655114, 0.24183975531580462, -0.03479725377227383, -0.1971432283338716, 0.030276052900001234, 0.1416252051672802] |
1,802.07395 | A Mixed Mimetic Spectral Element Model of the Rotating Shallow Water
Equations on the Cubed Sphere | In a previous article [J. Comp. Phys. $\mathbf{357}$ (2018) 282-304], the
mixed mimetic spectral element method was used to solve the rotating shallow
water equations in an idealized geometry. Here the method is extended to a
smoothly varying, non-affine, cubed sphere geometry. The differential operators
are encoded topologically via incidence matrices due to the use of spectral
element edge functions to construct tensor product solution spaces in
$H(\mathrm{rot})$, $H(\mathrm{div})$ and $L_2$. These incidence matrices
commute with respect to the metric terms in order to ensure that the mimetic
properties are preserved independent of the geometry. This ensures conservation
of mass, vorticity and energy for the rotating shallow water equations using
inexact quadrature on the cubed sphere. The spectral convergence of errors are
similarly preserved on the cubed sphere, with the generalized Piola
transformation used to construct the metric terms for the physical field
quantities.
| math.NA | in a previous article j comp phys mathbf357 2018 282304 the mixed mimetic spectral element method was used to solve the rotating shallow water equations in an idealized geometry here the method is extended to a smoothly varying nonaffine cubed sphere geometry the differential operators are encoded topologically via incidence matrices due to the use of spectral element edge functions to construct tensor product solution spaces in hmathrmrot hmathrmdiv and l_2 these incidence matrices commute with respect to the metric terms in order to ensure that the mimetic properties are preserved independent of the geometry this ensures conservation of mass vorticity and energy for the rotating shallow water equations using inexact quadrature on the cubed sphere the spectral convergence of errors are similarly preserved on the cubed sphere with the generalized piola transformation used to construct the metric terms for the physical field quantities | [['in', 'a', 'previous', 'article', 'j', 'comp', 'phys', 'mathbf357', '2018', '282304', 'the', 'mixed', 'mimetic', 'spectral', 'element', 'method', 'was', 'used', 'to', 'solve', 'the', 'rotating', 'shallow', 'water', 'equations', 'in', 'an', 'idealized', 'geometry', 'here', 'the', 'method', 'is', 'extended', 'to', 'a', 'smoothly', 'varying', 'nonaffine', 'cubed', 'sphere', 'geometry', 'the', 'differential', 'operators', 'are', 'encoded', 'topologically', 'via', 'incidence', 'matrices', 'due', 'to', 'the', 'use', 'of', 'spectral', 'element', 'edge', 'functions', 'to', 'construct', 'tensor', 'product', 'solution', 'spaces', 'in', 'hmathrmrot', 'hmathrmdiv', 'and', 'l_2', 'these', 'incidence', 'matrices', 'commute', 'with', 'respect', 'to', 'the', 'metric', 'terms', 'in', 'order', 'to', 'ensure', 'that', 'the', 'mimetic', 'properties', 'are', 'preserved', 'independent', 'of', 'the', 'geometry', 'this', 'ensures', 'conservation', 'of', 'mass', 'vorticity', 'and', 'energy', 'for', 'the', 'rotating', 'shallow', 'water', 'equations', 'using', 'inexact', 'quadrature', 'on', 'the', 'cubed', 'sphere', 'the', 'spectral', 'convergence', 'of', 'errors', 'are', 'similarly', 'preserved', 'on', 'the', 'cubed', 'sphere', 'with', 'the', 'generalized', 'piola', 'transformation', 'used', 'to', 'construct', 'the', 'metric', 'terms', 'for', 'the', 'physical', 'field', 'quantities']] | [-0.1039716045154219, 0.07750097475378322, -0.06247450139188598, 0.0569285729450854, -0.06351216745245805, -0.08247076990809424, -0.04388014774056191, 0.3569654351272059, -0.2875693772542984, -0.262439940777419, 0.11852578349173704, -0.2583127671865918, -0.13642976327852102, 0.1338435878006226, -0.10611703128435035, 0.07044676590895822, 0.029126482675552158, 0.013604558634419813, -0.14586293497717284, -0.23205698828761143, 0.3446784957397914, 0.05356835397802531, 0.26452533505359127, 0.006924940603421935, 0.1072428633363138, -0.011376843492150412, -0.05396015297106289, 0.03837418941457274, -0.14385640822502277, 0.11364916576485806, 0.24267392547913424, 0.055969115741687565, 0.18989711026297817, -0.41964827999736826, -0.1956193797382797, 0.10366840955160611, 0.10243622379060438, 0.05918281775707683, -0.001932851053734726, -0.25837946105220005, 0.06712805627059218, -0.1508125098593903, -0.17940265730565005, -0.07872271857633922, -0.000656670691769121, 0.04277600818610889, -0.27485548330682286, 0.08832804442734556, 0.040341307098666825, 0.025256462144196457, -0.07657919445484612, -0.09721800553156658, -0.04713369998420384, 0.07251295128322029, 0.022343985632339372, 0.030608727590095065, 0.10576316529178185, -0.03144997303334481, -0.0481329346075654, 0.388739250124769, -0.09139544147823059, -0.32010313539587437, 0.15614487730125162, -0.11108501402806517, -0.06341833521195865, 0.1314756373498351, 0.17526236869450923, 0.15365271137842368, -0.11833141372846241, 0.12311532573876836, -0.03428408076180845, 0.15750623778407033, 0.12046408902602733, 0.014753473232374758, 0.16396620388122948, 0.06287119212619802, 0.09269252858712529, 0.12393552303278707, -0.05950230544314106, -0.12215552828233385, -0.30445607960329835, -0.17605085143116006, -0.18096993867710814, 0.028778804814548673, -0.12183553727772185, -0.2127383547300037, 0.3774131418648341, 0.08812230476673613, 0.1352856682868615, 0.037150425704341405, 0.2520398296488462, 0.13501254295441487, 0.06883422457423154, 0.08849058496428931, 0.24315049395242588, 0.24410449252926236, 0.11762253954636713, -0.23459877137504254, -0.040906433699692185, 0.17252630851370224] |
1,802.07396 | Galois representations and ordinary reduction | We provide conditions on the p-adic Galois representation of a smooth proper
variety over a complete nonarchimedean extension of Q_p to have (potentially)
good ordinary reduction.
| math.AG math.NT | we provide conditions on the padic galois representation of a smooth proper variety over a complete nonarchimedean extension of q_p to have potentially good ordinary reduction | [['we', 'provide', 'conditions', 'on', 'the', 'padic', 'galois', 'representation', 'of', 'a', 'smooth', 'proper', 'variety', 'over', 'a', 'complete', 'nonarchimedean', 'extension', 'of', 'q_p', 'to', 'have', 'potentially', 'good', 'ordinary', 'reduction']] | [-0.2047399036013163, -0.06706812042886248, -0.2679152919266086, 0.06645021981631334, -0.20846827341637647, -0.025967110700618763, -0.005364966471321308, 0.32391351099627524, -0.3287988147483422, -0.24208731720080742, 0.03880050273325581, -0.1504280581497229, -0.08198787507493623, 0.32934639796328086, -0.20859974628994957, -0.021400554463840447, 0.01891473766702872, 0.15901741825263555, -0.10712442942894995, -0.3725493567494246, 0.32003752514719963, -0.09733593012564458, 0.22156181648516884, 0.010808430504626952, 0.15451256898590005, 0.06987701958188644, -0.005156343516248923, -0.01805925325383074, -0.14526296763394314, 0.117734916221637, 0.4315029696489756, 0.0507265894423024, 0.27054211862671834, -0.42246798923812234, -0.23001037212088704, 0.31474388390779495, 0.08957829804589543, 0.016839642435885392, -0.04870673735142471, -0.2785101898301106, 0.17307598392765683, -0.20268113209077945, -0.1474740372146838, -0.19556154110110724, 0.0579037547398072, 0.01535167029270759, -0.2903492391969149, -0.04414293284599598, 0.07087866317194241, 0.31672070974197525, -0.10429803339334634, -0.10191766702784942, 0.02550420379982545, 0.009192439834945478, -0.07510882372466418, 0.1298630317637267, 0.07902396995072755, -0.10724428267433093, -0.0766446074614158, 0.36311703060682005, -0.18704283817742878, -0.19401719134587508, 0.19029615977062628, -0.13647172754057324, -0.1183217907181153, 0.2027805976283092, 0.1685711070895195, 0.12698738398746803, 0.005056252309049551, 0.17698631947860122, -0.19945242098317698, 0.03621081721324187, 0.05837050288055952, 0.03578471528509489, 0.17359249284849143, 0.08953682472929358, 0.13377279008273035, 0.07558288289090762, 0.04417946849627277, -0.05626447036719093, -0.4017674900018252, -0.16302760497022134, -0.02287241916816968, 0.1406404720619321, -0.163037178464807, -0.2049256984072809, 0.43376216980127186, 0.08265976668693699, 0.17344989133282349, 0.13889263208525685, 0.212423161102029, 0.08192633941339758, 0.06498546103158823, -0.03950891795998009, 0.053674011276318476, 0.24633658183022186, -0.0893695684051356, -0.1442926651171337, -0.055286190839699254, 0.11894155393999356] |
1,802.07397 | PTL-separability and closures for WQOs on words | We introduce a flexible class of well-quasi-orderings (WQOs) on words that
generalizes the ordering of (not necessarily contiguous) subwords. Each such
WQO induces a class of piecewise testable languages (PTLs) as Boolean
combinations of upward closed sets. In this way, a range of regular language
classes arises as PTLs. Moreover, each of the WQOs guarantees regularity of all
downward closed sets. We consider two problems. First, we study which (perhaps
non-regular) language classes permit a decision procedure to decide whether two
given languages are separable by a PTL with respect to a given WQO. Second, we
want to effectively compute downward closures with respect to these WQOs. Our
first main result that for each of the WQOs, under mild assumptions, both
problems reduce to the simultaneous unboundedness problem (SUP) and are thus
solvable for many powerful system classes. In the second main result, we apply
the framework to show decidability of separability of regular languages by
$\mathcal{B}\Sigma_1[<, \mathsf{mod}]$, a fragment of first-order logic with
modular predicates.
| cs.FL | we introduce a flexible class of wellquasiorderings wqos on words that generalizes the ordering of not necessarily contiguous subwords each such wqo induces a class of piecewise testable languages ptls as boolean combinations of upward closed sets in this way a range of regular language classes arises as ptls moreover each of the wqos guarantees regularity of all downward closed sets we consider two problems first we study which perhaps nonregular language classes permit a decision procedure to decide whether two given languages are separable by a ptl with respect to a given wqo second we want to effectively compute downward closures with respect to these wqos our first main result that for each of the wqos under mild assumptions both problems reduce to the simultaneous unboundedness problem sup and are thus solvable for many powerful system classes in the second main result we apply the framework to show decidability of separability of regular languages by mathcalbsigma_1 mathsfmod a fragment of firstorder logic with modular predicates | [['we', 'introduce', 'a', 'flexible', 'class', 'of', 'wellquasiorderings', 'wqos', 'on', 'words', 'that', 'generalizes', 'the', 'ordering', 'of', 'not', 'necessarily', 'contiguous', 'subwords', 'each', 'such', 'wqo', 'induces', 'a', 'class', 'of', 'piecewise', 'testable', 'languages', 'ptls', 'as', 'boolean', 'combinations', 'of', 'upward', 'closed', 'sets', 'in', 'this', 'way', 'a', 'range', 'of', 'regular', 'language', 'classes', 'arises', 'as', 'ptls', 'moreover', 'each', 'of', 'the', 'wqos', 'guarantees', 'regularity', 'of', 'all', 'downward', 'closed', 'sets', 'we', 'consider', 'two', 'problems', 'first', 'we', 'study', 'which', 'perhaps', 'nonregular', 'language', 'classes', 'permit', 'a', 'decision', 'procedure', 'to', 'decide', 'whether', 'two', 'given', 'languages', 'are', 'separable', 'by', 'a', 'ptl', 'with', 'respect', 'to', 'a', 'given', 'wqo', 'second', 'we', 'want', 'to', 'effectively', 'compute', 'downward', 'closures', 'with', 'respect', 'to', 'these', 'wqos', 'our', 'first', 'main', 'result', 'that', 'for', 'each', 'of', 'the', 'wqos', 'under', 'mild', 'assumptions', 'both', 'problems', 'reduce', 'to', 'the', 'simultaneous', 'unboundedness', 'problem', 'sup', 'and', 'are', 'thus', 'solvable', 'for', 'many', 'powerful', 'system', 'classes', 'in', 'the', 'second', 'main', 'result', 'we', 'apply', 'the', 'framework', 'to', 'show', 'decidability', 'of', 'separability', 'of', 'regular', 'languages', 'by', 'mathcalbsigma_1', 'mathsfmod', 'a', 'fragment', 'of', 'firstorder', 'logic', 'with', 'modular', 'predicates']] | [-0.11062607899549659, 0.07522648095187766, -0.021065823840161348, 0.11284159215233278, -0.13464068334814114, -0.15278054581506662, 0.061047337489363585, 0.3727145241113541, -0.34556735047271453, -0.25045767784431966, 0.08170811637781883, -0.2270559416566458, -0.10887629419844022, 0.20889133538362387, -0.11389298590452031, 0.047939964219421885, 0.07881926071404675, 0.06675281663415206, -0.08545569162729576, -0.2576925874699229, 0.3702522844053161, -0.0788289061172601, 0.20498767576789784, 0.021902001116145976, 0.10126415129612994, 0.005773295891287242, 0.017457667209299994, 0.07414177305821076, -0.1183120562608913, 0.14170908343182004, 0.3168235416696579, 0.21131392009268848, 0.3064002669013945, -0.3781647805561438, -0.14316494665741, 0.1489547017076409, 0.06954625067962218, 0.07861951989823102, 0.03388452193308852, -0.24844231743388523, 0.13478293445932873, -0.16535289493464164, -0.0926554863654468, -0.07258155940094801, 0.03422994693787194, 0.05659954351758194, -0.27299669243533303, -0.009851511429857325, 0.18798589228094056, 0.0514410372862237, -0.06417690111427671, -0.07728184616684707, 0.010509136487890817, 0.10068110009519898, 0.02593069337811436, 0.018676531966775656, 0.05284410610473082, -0.06285712891545744, -0.16612994577017048, 0.38452777230625623, -0.0461271570544161, -0.2249985312997007, 0.21617294298657388, -0.12750779810350066, -0.22749041481932372, 0.10023298040377321, 0.1413798204358713, 0.1331114891203649, -0.13771200753219517, 0.11974699613508871, -0.11577592408974413, 0.17758864129284097, 0.14036450448250512, 0.027486022452559367, 0.1701893354018713, 0.13965327301878988, 0.12256165097408675, 0.19720549609535087, 0.03182036177697879, -0.052265835284215204, -0.3392452837232454, -0.1397246442574226, -0.08872029110487481, -0.007189437413475344, -0.07345129523408689, -0.23862911906829218, 0.4028366543697538, 0.1379836748043696, 0.15800978285892878, 0.17715616654791513, 0.2344955873940094, 0.08568656801197241, 0.05562552327094714, 0.08691812325326473, 0.09161587167864689, 0.12483958534631924, 0.007061047548497164, -0.16083779126257683, 0.1027756249618337, 0.10686372996762072] |
1,802.07398 | Investigating Rumor News Using Agreement-Aware Search | Recent years have witnessed a widespread increase of rumor news generated by
humans and machines. Therefore, tools for investigating rumor news have become
an urgent necessity. One useful function of such tools is to see ways a
specific topic or event is represented by presenting different points of view
from multiple sources.
In this paper, we propose Maester, a novel agreement-aware search framework
for investigating rumor news. Given an investigative question, Maester will
retrieve related articles to that question, assign and display top articles
from agree, disagree, and discuss categories to users. Splitting the results
into these three categories provides the user a holistic view towards the
investigative question. We build Maester based on the following two key
observations: (1) relatedness can commonly be determined by keywords and
entities occurring in both questions and articles, and (2) the level of
agreement between the investigative question and the related news article can
often be decided by a few key sentences. Accordingly, we use gradient boosting
tree models with keyword/entity matching features for relatedness detection,
and leverage recurrent neural network to infer the level of agreement. Our
experiments on the Fake News Challenge (FNC) dataset demonstrate up to an order
of magnitude improvement of Maester over the original FNC winning solution, for
agreement-aware search.
| cs.IR | recent years have witnessed a widespread increase of rumor news generated by humans and machines therefore tools for investigating rumor news have become an urgent necessity one useful function of such tools is to see ways a specific topic or event is represented by presenting different points of view from multiple sources in this paper we propose maester a novel agreementaware search framework for investigating rumor news given an investigative question maester will retrieve related articles to that question assign and display top articles from agree disagree and discuss categories to users splitting the results into these three categories provides the user a holistic view towards the investigative question we build maester based on the following two key observations 1 relatedness can commonly be determined by keywords and entities occurring in both questions and articles and 2 the level of agreement between the investigative question and the related news article can often be decided by a few key sentences accordingly we use gradient boosting tree models with keywordentity matching features for relatedness detection and leverage recurrent neural network to infer the level of agreement our experiments on the fake news challenge fnc dataset demonstrate up to an order of magnitude improvement of maester over the original fnc winning solution for agreementaware search | [['recent', 'years', 'have', 'witnessed', 'a', 'widespread', 'increase', 'of', 'rumor', 'news', 'generated', 'by', 'humans', 'and', 'machines', 'therefore', 'tools', 'for', 'investigating', 'rumor', 'news', 'have', 'become', 'an', 'urgent', 'necessity', 'one', 'useful', 'function', 'of', 'such', 'tools', 'is', 'to', 'see', 'ways', 'a', 'specific', 'topic', 'or', 'event', 'is', 'represented', 'by', 'presenting', 'different', 'points', 'of', 'view', 'from', 'multiple', 'sources', 'in', 'this', 'paper', 'we', 'propose', 'maester', 'a', 'novel', 'agreementaware', 'search', 'framework', 'for', 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'matching', 'features', 'for', 'relatedness', 'detection', 'and', 'leverage', 'recurrent', 'neural', 'network', 'to', 'infer', 'the', 'level', 'of', 'agreement', 'our', 'experiments', 'on', 'the', 'fake', 'news', 'challenge', 'fnc', 'dataset', 'demonstrate', 'up', 'to', 'an', 'order', 'of', 'magnitude', 'improvement', 'of', 'maester', 'over', 'the', 'original', 'fnc', 'winning', 'solution', 'for', 'agreementaware', 'search']] | [-0.0676216095592381, 0.038831634110195724, -0.04857627120042781, 0.10644919614020165, -0.12134971024923062, -0.15170944594047323, 0.08532634134455606, 0.3997421409025717, -0.2635945389802015, -0.34892638422477473, 0.06949083079387874, -0.34475360202500555, -0.15732461129511266, 0.19689813100857634, -0.09641398146611413, 0.012780266571077005, 0.09645255137475554, 0.048068504105433466, -0.0042571827711350325, -0.306077090023491, 0.35774193852348923, 0.05180104617385915, 0.2937230280952519, 0.07050186692643465, 0.0920422112827666, -0.017524427322127174, 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1,802.07399 | Arbitrary helicity control of circularly polarized light from
lateral-type spin-polarized light-emitting diodes at room temperature | We demonstrate arbitrary helicity control of circularly polarized light (CPL)
emitted at room temperature from the cleaved side-facet of a lateral-type
spin-polarized light-emitting diode (spin-LED) with two ferromagnetic
electrodes in an anti-parallel magnetization configuration. Driving alternate
currents through the two electrodes results in polarization switching of CPL
with frequencies up to 100 kHz. Furthermore, tuning the current density ratio
in the two electrodes enables manipulation of the degree of circular
polarization. These results demonstrate arbitrary electrical control of
polarization with high speed, which is required for the practical use of
lateral-type spin-LEDs as monolithic CPL light sources.
| physics.optics physics.app-ph | we demonstrate arbitrary helicity control of circularly polarized light cpl emitted at room temperature from the cleaved sidefacet of a lateraltype spinpolarized lightemitting diode spinled with two ferromagnetic electrodes in an antiparallel magnetization configuration driving alternate currents through the two electrodes results in polarization switching of cpl with frequencies up to 100 khz furthermore tuning the current density ratio in the two electrodes enables manipulation of the degree of circular polarization these results demonstrate arbitrary electrical control of polarization with high speed which is required for the practical use of lateraltype spinleds as monolithic cpl light sources | [['we', 'demonstrate', 'arbitrary', 'helicity', 'control', 'of', 'circularly', 'polarized', 'light', 'cpl', 'emitted', 'at', 'room', 'temperature', 'from', 'the', 'cleaved', 'sidefacet', 'of', 'a', 'lateraltype', 'spinpolarized', 'lightemitting', 'diode', 'spinled', 'with', 'two', 'ferromagnetic', 'electrodes', 'in', 'an', 'antiparallel', 'magnetization', 'configuration', 'driving', 'alternate', 'currents', 'through', 'the', 'two', 'electrodes', 'results', 'in', 'polarization', 'switching', 'of', 'cpl', 'with', 'frequencies', 'up', 'to', '100', 'khz', 'furthermore', 'tuning', 'the', 'current', 'density', 'ratio', 'in', 'the', 'two', 'electrodes', 'enables', 'manipulation', 'of', 'the', 'degree', 'of', 'circular', 'polarization', 'these', 'results', 'demonstrate', 'arbitrary', 'electrical', 'control', 'of', 'polarization', 'with', 'high', 'speed', 'which', 'is', 'required', 'for', 'the', 'practical', 'use', 'of', 'lateraltype', 'spinleds', 'as', 'monolithic', 'cpl', 'light', 'sources']] | [-0.1631274308213809, 0.19188960740226926, 0.00053580114520931, -0.07283827871075725, -0.051381347429317735, -0.20119728068918144, 0.06491002625261899, 0.4845347903125609, -0.23660330879404987, -0.3225439435336739, -0.0338446038828503, -0.2636717660643626, -0.017447088490977574, 0.27032973179787706, 0.030108060940013576, 0.0331775477049329, -0.03919717223470798, -0.09370068813829373, -0.04426555636988875, -0.16484909481975288, 0.22412849348256714, 0.0063001457989836735, 0.37410090431027737, 0.07666022261158408, 0.15209369842583934, 0.005719343093611921, 0.09402523226162884, -0.023296040738690255, -0.046252871606460154, 0.08131751337835642, 0.24132443750083135, -0.03253318496475307, 0.14242862029883932, -0.4730685987160541, -0.16502132090196633, 0.027809514382776495, 0.08661220278978969, 0.1345632171954397, -0.07498546492812845, -0.22145612289508185, 0.04080492562691992, -0.11364439343636452, -0.15787710111180786, -0.04173368637566455, -0.037330218918214086, 0.07836157632846152, -0.2595180280441127, 0.03595904789108317, 0.018934640936398257, 0.049115040864611124, -0.06939694373674381, -0.11682538950117305, -0.08143872700748034, 0.022213307466396753, 0.009013147430475025, 0.05495151584424699, 0.20601673107012175, -0.1291349447783432, -0.1791644649298784, 0.2692923292246026, -0.1000404290825827, -0.13320638957278183, 0.12134294613497332, -0.20129931548823757, -0.002583026187494397, 0.13874638792306845, 0.12336318589223083, 0.1390721485707521, -0.13620243906552787, 0.025766000588191673, 0.051581345521602394, 0.19722450277913595, 0.1716138415019183, 0.044052071132076286, 0.29212263321581605, 0.1908159178662269, 0.06055552276181212, 0.15795215187730113, -0.15140681211293364, -0.007574622912216, -0.24167194172817594, -0.14562097356732315, -0.15085255187780908, 0.11381851762416773, -0.1303221962346773, -0.12290499701036121, 0.4577183411844696, 0.1578764385873607, 0.14254069973443015, -0.021955969926542213, 0.39033534738700837, 0.07957990971408435, 0.02425457076121044, 0.04274408045845727, 0.29859856295903836, 0.1916388283522489, 0.12793355339575405, -0.27845047987648286, 0.03578792613310119, -0.11959363198063026] |
1,802.074 | Direct Learning to Rank and Rerank | Learning-to-rank techniques have proven to be extremely useful for
prioritization problems, where we rank items in order of their estimated
probabilities, and dedicate our limited resources to the top-ranked items. This
work exposes a serious problem with the state of learning-to-rank algorithms,
which is that they are based on convex proxies that lead to poor
approximations. We then discuss the possibility of "exact" reranking algorithms
based on mathematical programming. We prove that a relaxed version of the
"exact" problem has the same optimal solution, and provide an empirical
analysis.
| stat.ML cs.IR cs.LG | learningtorank techniques have proven to be extremely useful for prioritization problems where we rank items in order of their estimated probabilities and dedicate our limited resources to the topranked items this work exposes a serious problem with the state of learningtorank algorithms which is that they are based on convex proxies that lead to poor approximations we then discuss the possibility of exact reranking algorithms based on mathematical programming we prove that a relaxed version of the exact problem has the same optimal solution and provide an empirical analysis | [['learningtorank', 'techniques', 'have', 'proven', 'to', 'be', 'extremely', 'useful', 'for', 'prioritization', 'problems', 'where', 'we', 'rank', 'items', 'in', 'order', 'of', 'their', 'estimated', 'probabilities', 'and', 'dedicate', 'our', 'limited', 'resources', 'to', 'the', 'topranked', 'items', 'this', 'work', 'exposes', 'a', 'serious', 'problem', 'with', 'the', 'state', 'of', 'learningtorank', 'algorithms', 'which', 'is', 'that', 'they', 'are', 'based', 'on', 'convex', 'proxies', 'that', 'lead', 'to', 'poor', 'approximations', 'we', 'then', 'discuss', 'the', 'possibility', 'of', 'exact', 'reranking', 'algorithms', 'based', 'on', 'mathematical', 'programming', 'we', 'prove', 'that', 'a', 'relaxed', 'version', 'of', 'the', 'exact', 'problem', 'has', 'the', 'same', 'optimal', 'solution', 'and', 'provide', 'an', 'empirical', 'analysis']] | [-0.04281329255802243, -0.023712067523274018, -0.12071823471047904, 0.1313899357102058, -0.12650225347619545, -0.17045448591744297, 0.1321248230942933, 0.3920101766275723, -0.2666397075106003, -0.3080948871152287, 0.1466164263998671, -0.2645141786916621, -0.1568186270345128, 0.18747112072292674, -0.12707170599213477, 0.08130320405399197, 0.1049524806596841, 0.03479058012723389, -0.0707002663291635, -0.3267838918300492, 0.2974295297041117, 0.05578364941469404, 0.2964872922957613, 0.08356524225366249, 0.10917665076892027, -0.026629862569146946, -0.02203752179473136, 0.05649850665057978, -0.12802345561394352, 0.1821668360439872, 0.3349854875816388, 0.20972231325295784, 0.35897172606560623, -0.4299847956621245, -0.1446446706907133, 0.12115428139772161, 0.13959642326501145, 0.1236057680746373, -0.05680778173185634, -0.276050007138192, 0.13154664841804947, -0.1595383617409578, -0.05395918302865845, -0.11220187687032511, -0.01655088289081004, 0.01017068699002266, -0.29294485156162736, 0.02997987863628633, 0.03446123331165192, 0.013955782418756673, -0.07053607896891202, -0.16247804683183184, 0.08825676181102486, 0.11761770323128178, 0.08380277212866152, -0.0026795118262342523, 0.07844608027320892, -0.10990843148326522, -0.16465200424675694, 0.38190013214192364, 0.0070738759705420125, -0.23348552417637927, 0.19096460187117034, -0.0247819781031334, -0.1890591274203963, 0.07613367550048894, 0.2160537932820231, 0.1582530872700762, -0.14569600304102084, 0.06415701626009947, -0.09075062510588866, 0.17792666939432533, 0.027432652713542574, 0.030282787732738122, 0.14805780734155286, 0.1637049467627252, 0.11947951259436819, 0.13568466536967566, -0.008943114958159375, -0.0729820118547323, -0.21638533201466284, -0.12333060846287297, -0.18305433603275692, 0.009219887510747806, -0.0849034672421848, -0.18928098451382783, 0.3591678516541639, 0.22557944598283325, 0.16415431690559293, 0.1016678091863254, 0.3098436387444145, 0.13637564269161334, 0.035267864495222824, 0.11470692460896091, 0.20810954472745946, 0.06278404726102697, 0.06805336742211929, -0.17712221929693617, 0.12468462438437711, 0.07500328581905767] |
1,802.07401 | A Study into the similarity in generator and discriminator in GAN
architecture | One popular generative model that has high-quality results is the Generative
Adversarial Networks(GAN). This type of architecture consists of two separate
networks that play against each other. The generator creates an output from the
input noise that is given to it. The discriminator has the task of determining
if the input to it is real or fake. This takes place constantly eventually
leads to the generator modeling the target distribution. This paper includes a
study into the actual weights learned by the network and a study into the
similarity of the discriminator and generator networks. The paper also tries to
leverage the similarity between these networks and shows that indeed both the
networks may have a similar structure with experimental evidence with a novel
shared architecture.
| cs.LG stat.ML | one popular generative model that has highquality results is the generative adversarial networksgan this type of architecture consists of two separate networks that play against each other the generator creates an output from the input noise that is given to it the discriminator has the task of determining if the input to it is real or fake this takes place constantly eventually leads to the generator modeling the target distribution this paper includes a study into the actual weights learned by the network and a study into the similarity of the discriminator and generator networks the paper also tries to leverage the similarity between these networks and shows that indeed both the networks may have a similar structure with experimental evidence with a novel shared architecture | [['one', 'popular', 'generative', 'model', 'that', 'has', 'highquality', 'results', 'is', 'the', 'generative', 'adversarial', 'networksgan', 'this', 'type', 'of', 'architecture', 'consists', 'of', 'two', 'separate', 'networks', 'that', 'play', 'against', 'each', 'other', 'the', 'generator', 'creates', 'an', 'output', 'from', 'the', 'input', 'noise', 'that', 'is', 'given', 'to', 'it', 'the', 'discriminator', 'has', 'the', 'task', 'of', 'determining', 'if', 'the', 'input', 'to', 'it', 'is', 'real', 'or', 'fake', 'this', 'takes', 'place', 'constantly', 'eventually', 'leads', 'to', 'the', 'generator', 'modeling', 'the', 'target', 'distribution', 'this', 'paper', 'includes', 'a', 'study', 'into', 'the', 'actual', 'weights', 'learned', 'by', 'the', 'network', 'and', 'a', 'study', 'into', 'the', 'similarity', 'of', 'the', 'discriminator', 'and', 'generator', 'networks', 'the', 'paper', 'also', 'tries', 'to', 'leverage', 'the', 'similarity', 'between', 'these', 'networks', 'and', 'shows', 'that', 'indeed', 'both', 'the', 'networks', 'may', 'have', 'a', 'similar', 'structure', 'with', 'experimental', 'evidence', 'with', 'a', 'novel', 'shared', 'architecture']] | [-0.07183707046881319, 0.030066486858879218, -0.08642077568918466, 0.050628489077091214, -0.08715045095607639, -0.16611017560213803, -0.00042599283996969464, 0.4223242536485195, -0.27935065603256226, -0.31109156524483117, 0.030563758507370947, -0.2886141850948334, -0.22581353628076614, 0.16038419892266392, -0.09205755996704101, 0.021758586034178733, 0.11465160364584881, 0.08015812263824046, -0.018782148906961085, -0.23954263596143574, 0.3755097395479679, 0.06220651368796826, 0.33986110842972994, -0.012481736686080694, 0.14341287190816365, -0.032660789212211966, -0.01991825099289417, -0.015449596689082683, -0.037073785624699665, 0.1602558769080788, 0.22168322567641735, 0.1971570406705141, 0.33327254115231336, -0.41621609053760766, -0.22500495633482934, 0.13875709982216358, 0.0836937942057848, 0.11933927424997091, -0.04922810359392315, -0.29773725468292833, 0.13256634952500462, -0.16035187548398971, 0.004650179613381624, -0.07597365127503872, -0.01215259287506342, 0.0035244061704725028, -0.29728992419550193, -0.037847444514045495, 0.1240296452306211, -0.04437824138998985, -0.028756738213822245, -0.07274716790765524, -0.04790048089250922, 0.20787246287427844, 0.0378256877521053, 0.07303944878093899, 0.0844786457568407, -0.150420362630859, -0.11257942825555801, 0.3568506666868925, -0.031071504026651382, -0.19854052631556987, 0.18456456530094148, -0.05191763132438064, -0.12874883621744812, 0.09258278973400592, 0.21448158532381056, 0.04574907812476158, -0.16079645545827226, 0.009213344226125627, -0.07229810420051216, 0.18937612611055374, -0.003013455778360367, -0.011372883662581443, 0.20189383368939162, 0.2323769806176424, 0.032319569919258356, 0.19968915372574703, -0.12254658088996075, -0.08342891491111368, -0.27188242704421284, -0.12015497582405806, -0.19225434123538435, 0.01936460737907328, -0.09550876477605198, -0.1676794182509184, 0.4542446388378739, 0.19681995906773955, 0.2698089464604855, 0.0691138304695487, 0.34483452067524195, 0.07738051740266383, 0.12361454875022172, 0.0878370506982319, 0.188510867677629, 0.06029589646868408, 0.10834099180437624, -0.16098358842916788, 0.15218606949970126, 0.03285943176597357] |
1,802.07402 | Microwave device characterisation using a widefield diamond microscope | Devices relying on microwave circuitry form a cornerstone of many classical
and emerging quantum technologies. A capability to provide in-situ, noninvasive
and direct imaging of the microwave fields above such devices would be a
powerful tool for their function and failure analysis. In this work, we build
on recent achievements in magnetometry using ensembles of nitrogen vacancy
centres in diamond, to present a widefield microwave microscope with few-micron
resolution over a millimeter-scale field of view, 130nT/sqrt-Hz microwave
amplitude sensitivity, a dynamic range of 48 dB, and sub-ms temporal
resolution. We use our microscope to image the microwave field a few microns
above a range of microwave circuitry components, and to characterise a novel
atom chip design. Our results open the way to high-throughput characterisation
and debugging of complex, multi-component microwave devices, including
real-time exploration of device operation.
| quant-ph cond-mat.mes-hall physics.app-ph | devices relying on microwave circuitry form a cornerstone of many classical and emerging quantum technologies a capability to provide insitu noninvasive and direct imaging of the microwave fields above such devices would be a powerful tool for their function and failure analysis in this work we build on recent achievements in magnetometry using ensembles of nitrogen vacancy centres in diamond to present a widefield microwave microscope with fewmicron resolution over a millimeterscale field of view 130ntsqrthz microwave amplitude sensitivity a dynamic range of 48 db and subms temporal resolution we use our microscope to image the microwave field a few microns above a range of microwave circuitry components and to characterise a novel atom chip design our results open the way to highthroughput characterisation and debugging of complex multicomponent microwave devices including realtime exploration of device operation | [['devices', 'relying', 'on', 'microwave', 'circuitry', 'form', 'a', 'cornerstone', 'of', 'many', 'classical', 'and', 'emerging', 'quantum', 'technologies', 'a', 'capability', 'to', 'provide', 'insitu', 'noninvasive', 'and', 'direct', 'imaging', 'of', 'the', 'microwave', 'fields', 'above', 'such', 'devices', 'would', 'be', 'a', 'powerful', 'tool', 'for', 'their', 'function', 'and', 'failure', 'analysis', 'in', 'this', 'work', 'we', 'build', 'on', 'recent', 'achievements', 'in', 'magnetometry', 'using', 'ensembles', 'of', 'nitrogen', 'vacancy', 'centres', 'in', 'diamond', 'to', 'present', 'a', 'widefield', 'microwave', 'microscope', 'with', 'fewmicron', 'resolution', 'over', 'a', 'millimeterscale', 'field', 'of', 'view', '130ntsqrthz', 'microwave', 'amplitude', 'sensitivity', 'a', 'dynamic', 'range', 'of', '48', 'db', 'and', 'subms', 'temporal', 'resolution', 'we', 'use', 'our', 'microscope', 'to', 'image', 'the', 'microwave', 'field', 'a', 'few', 'microns', 'above', 'a', 'range', 'of', 'microwave', 'circuitry', 'components', 'and', 'to', 'characterise', 'a', 'novel', 'atom', 'chip', 'design', 'our', 'results', 'open', 'the', 'way', 'to', 'highthroughput', 'characterisation', 'and', 'debugging', 'of', 'complex', 'multicomponent', 'microwave', 'devices', 'including', 'realtime', 'exploration', 'of', 'device', 'operation']] | [-0.11784762581673396, 0.09898290517936831, -0.02928678468314876, -0.04289818276575876, -0.07344296667724848, -0.13222336118034198, 0.07595500552869293, 0.4304523369954789, -0.23565427164944328, -0.3532060517224154, 0.08282992222024511, -0.2562957266174421, -0.12430332734605626, 0.3137336355250548, -0.03813311284038184, 0.09315267092247001, 0.04500255151459201, -0.07671624530420933, -0.00757214061655652, -0.15985545150589828, 0.20179808475351071, 0.11417033158581677, 0.3482487475643318, 0.04693635649677804, 0.13075612788944616, 0.02532407342497369, -0.0014765062951482832, -0.0032854599397550747, -0.1081576658616541, 0.1738664657528074, 0.30451288726694387, 0.13033384591108188, 0.23997962499133257, -0.4767256090828382, -0.2638083910843467, 0.06808218464806594, 0.12190236607977353, 0.11737565946874812, -0.10158194285331239, -0.2770186927587287, 0.07719390721895787, -0.14134346018887728, -0.13242391517922122, -0.10553318528485868, -0.04353883653803838, 0.010433812043629587, -0.22413223845582894, 0.015063781797995461, 0.0056768003174939245, 0.13969456401708372, -0.039374509121711636, -0.027900272432495567, 0.08670479990199537, 0.09777022999033387, -0.13338879291789935, 0.06732206210932311, 0.2431985887575566, -0.1394978401127874, -0.16200809509438627, 0.30669138687388864, -0.0666193849996061, -0.057713544420788396, 0.2118417479471057, -0.15281520382781952, -0.10851200744646657, 0.08545153089525069, 0.16815977042150573, 0.09705788398723063, -0.200279196142219, 0.06758744695638169, 0.0764510014833992, 0.2339346458483145, 0.09672981434713994, 0.13694022506858936, 0.27072446893298013, 0.24269611495273077, 0.07674001523045103, 0.13712558419844273, -0.14749768647872022, 0.015372276994372335, -0.23768337629072073, -0.16692415384151152, -0.1577869712816798, 0.11159561162297477, -0.059630805549472025, -0.18807824699701192, 0.3774696358339176, 0.18792891334048953, 0.1577154366463861, -0.03572745322633315, 0.40288558286642107, 0.01249280888142119, 0.12964489590205416, -0.052452485987861806, 0.22316126192933605, 0.2017515763616436, 0.16617530531178037, -0.18643063008922206, -0.050121068799532674, -0.056927019127589816] |
1,802.07403 | Stability conditions for restrictions of vector bundles on projective
surfaces | Using Bridgeland stability conditions we give sufficient criteria for a
stable vector bundle on a surface to remain stable when restricted to a curve.
We give a stronger criterion when the vector bundle is a general vector bundle
on the plane. As an application, we compute the cohomology of such bundles for
curves that lie in the plane or on Hirzebruch surfaces.
| math.AG | using bridgeland stability conditions we give sufficient criteria for a stable vector bundle on a surface to remain stable when restricted to a curve we give a stronger criterion when the vector bundle is a general vector bundle on the plane as an application we compute the cohomology of such bundles for curves that lie in the plane or on hirzebruch surfaces | [['using', 'bridgeland', 'stability', 'conditions', 'we', 'give', 'sufficient', 'criteria', 'for', 'a', 'stable', 'vector', 'bundle', 'on', 'a', 'surface', 'to', 'remain', 'stable', 'when', 'restricted', 'to', 'a', 'curve', 'we', 'give', 'a', 'stronger', 'criterion', 'when', 'the', 'vector', 'bundle', 'is', 'a', 'general', 'vector', 'bundle', 'on', 'the', 'plane', 'as', 'an', 'application', 'we', 'compute', 'the', 'cohomology', 'of', 'such', 'bundles', 'for', 'curves', 'that', 'lie', 'in', 'the', 'plane', 'or', 'on', 'hirzebruch', 'surfaces']] | [-0.22645801570146315, 0.04020119332750666, -0.11155416726345016, 0.1068129620999248, -0.14150798930260802, -0.1540336862521907, 0.05833881756951732, 0.39849735964690486, -0.262497027254393, -0.17570085622250073, 0.1597325928911056, -0.16158173361703032, -0.17203285652137693, 0.24507418965485187, -0.14641965504345153, 0.007205857654973384, 0.0497494048153561, 0.10705571409104572, -0.10136973178539906, -0.2925683411435344, 0.4408173825471632, -0.018705071798796134, 0.28259653350218167, 0.06983369873506168, 0.12164883178857347, 0.055737467632899364, 0.09603117939250003, -0.010778018273413181, -0.1926577456504146, 0.12082030589602166, 0.2266340084306355, 0.07603921117110839, 0.1557950266006012, -0.3946814289196364, -0.16607373434629652, 0.21061733458191156, 0.061739623711834994, 0.048584155543076414, -0.013777434365868929, -0.23027668109223728, 0.1437858489432162, -0.057805615462242596, -0.18844035404524015, -0.11718095233663917, 0.07269634090123638, 0.018049919301824223, -0.231870885915874, -0.036576923223272446, 0.069352418800155, 0.160131728712229, -0.15944205660132632, -0.047985478227342206, -0.12613320705150405, 0.006546891783551884, -0.009140429736655806, 0.06056161150486479, 0.12086683910550369, -0.11018588084487184, -0.07496949223681323, 0.40173197856112836, -0.12742262216465128, -0.2933022793863089, 0.12725203595454654, -0.08087515769406192, -0.1109264143291981, 0.14578143258639162, 0.19361636913832156, 0.22263397292924986, 0.01812584067445113, 0.07379819895891894, -0.11448975832712266, 0.0649167482831305, 0.05525256211178437, -0.05858892658556391, 0.19231771837803535, 0.09761807121967356, 0.14715238268517197, 0.12807613491238426, -0.07038732887350864, -0.06096668529414361, -0.3933337052022257, -0.2723195630936853, -0.05523147228579488, 0.12311048148530385, -0.06857459374793595, -0.20309530469333573, 0.4202825153667119, 0.023766679028349537, 0.2990497579275172, 0.10144069192991141, 0.26145244434085346, 0.08255369828416846, 0.035907088303335305, 0.03170435437782397, 0.24610989540815353, 0.20751484824464686, -0.008689358792898635, -0.07514952286146581, -0.019986031494373755, 0.16778668287330337] |
1,802.07404 | Where and how is entropy generated in solar energy conversion systems? | The hotness of the sun and the coldness of the outer space are inexhaustible
thermodynamic resources for human beings. From a thermodynamic point of view,
any energy conversion systems that receive energy from the sun and/or dissipate
energy to the universe are heat engines with photons as the "working fluid" and
can be analyzed using the concept of entropy. While entropy analysis provides a
particularly convenient way to understand the efficiency limits, it is
typically taught in the context of thermodynamic cycles among quasi-equilibrium
states and its generalization to solar energy conversion systems running in a
continuous and non-equilibrium fashion is not straightforward. In this
educational article, we present a few examples to illustrate how the concept of
photon entropy, combined with the radiative transfer equation, can be used to
analyze the local entropy generation processes and the efficiency limits of
different solar energy conversion systems. We provide explicit calculations for
the local and total entropy generation rates for simple emitters and absorbers,
as well as photovoltaic cells, which can be readily reproduced by students. We
further discuss the connection between the entropy generation and the device
efficiency, particularly the exact spectral matching condition that is shared
by infinite-junction photovoltaic cells and reversible thermoelectric materials
to approach their theoretical efficiency limit.
| physics.app-ph | the hotness of the sun and the coldness of the outer space are inexhaustible thermodynamic resources for human beings from a thermodynamic point of view any energy conversion systems that receive energy from the sun andor dissipate energy to the universe are heat engines with photons as the working fluid and can be analyzed using the concept of entropy while entropy analysis provides a particularly convenient way to understand the efficiency limits it is typically taught in the context of thermodynamic cycles among quasiequilibrium states and its generalization to solar energy conversion systems running in a continuous and nonequilibrium fashion is not straightforward in this educational article we present a few examples to illustrate how the concept of photon entropy combined with the radiative transfer equation can be used to analyze the local entropy generation processes and the efficiency limits of different solar energy conversion systems we provide explicit calculations for the local and total entropy generation rates for simple emitters and absorbers as well as photovoltaic cells which can be readily reproduced by students we further discuss the connection between the entropy generation and the device efficiency particularly the exact spectral matching condition that is shared by infinitejunction photovoltaic cells and reversible thermoelectric materials to approach their theoretical efficiency limit | [['the', 'hotness', 'of', 'the', 'sun', 'and', 'the', 'coldness', 'of', 'the', 'outer', 'space', 'are', 'inexhaustible', 'thermodynamic', 'resources', 'for', 'human', 'beings', 'from', 'a', 'thermodynamic', 'point', 'of', 'view', 'any', 'energy', 'conversion', 'systems', 'that', 'receive', 'energy', 'from', 'the', 'sun', 'andor', 'dissipate', 'energy', 'to', 'the', 'universe', 'are', 'heat', 'engines', 'with', 'photons', 'as', 'the', 'working', 'fluid', 'and', 'can', 'be', 'analyzed', 'using', 'the', 'concept', 'of', 'entropy', 'while', 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1,802.07405 | Extracting the multi-timescale activity patterns of online financial
markets | Online financial markets can be represented as complex systems where trading
dynamics can be captured and characterized at different resolutions and time
scales. In this work, we develop a methodology based on non-negative tensor
factorization (NTF) aimed at extracting and revealing the multi-timescale
trading dynamics governing online financial systems. We demonstrate the
advantage of our strategy first using synthetic data, and then on real-world
data capturing all interbank transactions (over a million) occurred in an
Italian online financial market (e-MID) between 2001 and 2015. Our results
demonstrate how NTF can uncover hidden activity patterns that characterize
groups of banks exhibiting different trading strategies (normal vs. early vs.
flash trading, etc.). We further illustrate how our methodology can reveal
"crisis modalities" in trading triggered by endogenous and exogenous system
shocks: as an example, we reveal and characterize trading anomalies in the
midst of the 2008 financial crisis.
| q-fin.TR | online financial markets can be represented as complex systems where trading dynamics can be captured and characterized at different resolutions and time scales in this work we develop a methodology based on nonnegative tensor factorization ntf aimed at extracting and revealing the multitimescale trading dynamics governing online financial systems we demonstrate the advantage of our strategy first using synthetic data and then on realworld data capturing all interbank transactions over a million occurred in an italian online financial market emid between 2001 and 2015 our results demonstrate how ntf can uncover hidden activity patterns that characterize groups of banks exhibiting different trading strategies normal vs early vs flash trading etc we further illustrate how our methodology can reveal crisis modalities in trading triggered by endogenous and exogenous system shocks as an example we reveal and characterize trading anomalies in the midst of the 2008 financial crisis | [['online', 'financial', 'markets', 'can', 'be', 'represented', 'as', 'complex', 'systems', 'where', 'trading', 'dynamics', 'can', 'be', 'captured', 'and', 'characterized', 'at', 'different', 'resolutions', 'and', 'time', 'scales', 'in', 'this', 'work', 'we', 'develop', 'a', 'methodology', 'based', 'on', 'nonnegative', 'tensor', 'factorization', 'ntf', 'aimed', 'at', 'extracting', 'and', 'revealing', 'the', 'multitimescale', 'trading', 'dynamics', 'governing', 'online', 'financial', 'systems', 'we', 'demonstrate', 'the', 'advantage', 'of', 'our', 'strategy', 'first', 'using', 'synthetic', 'data', 'and', 'then', 'on', 'realworld', 'data', 'capturing', 'all', 'interbank', 'transactions', 'over', 'a', 'million', 'occurred', 'in', 'an', 'italian', 'online', 'financial', 'market', 'emid', 'between', '2001', 'and', '2015', 'our', 'results', 'demonstrate', 'how', 'ntf', 'can', 'uncover', 'hidden', 'activity', 'patterns', 'that', 'characterize', 'groups', 'of', 'banks', 'exhibiting', 'different', 'trading', 'strategies', 'normal', 'vs', 'early', 'vs', 'flash', 'trading', 'etc', 'we', 'further', 'illustrate', 'how', 'our', 'methodology', 'can', 'reveal', 'crisis', 'modalities', 'in', 'trading', 'triggered', 'by', 'endogenous', 'and', 'exogenous', 'system', 'shocks', 'as', 'an', 'example', 'we', 'reveal', 'and', 'characterize', 'trading', 'anomalies', 'in', 'the', 'midst', 'of', 'the', '2008', 'financial', 'crisis']] | [-0.0860084254037085, 0.07208450521643063, -0.13494394935846124, 0.11119317572981706, -0.07678554975746633, -0.1071527440783453, 0.0737111544258867, 0.4151522501791215, -0.29023082023295127, -0.31642723455387234, 0.17692622100003064, -0.2937688369061543, -0.2394145345506705, 0.18562573330374818, -0.10545443712689033, -0.04255267438376705, 0.041496465617331536, -0.0622231773250698, 0.05412307315767577, -0.28572835285112513, 0.27049702288557403, 0.05613138498451357, 0.3086959348277074, 0.042591015936660086, 0.1434634611907986, -0.0014168057249450724, -0.11371296933813863, 0.013371578077243462, -0.07528666385365945, 0.11481036457762582, 0.3523364258875866, 0.16544501628002714, 0.338536987803583, -0.4960769682114765, -0.1845237829161119, 0.11961994903825529, 0.07465900805753285, 0.028546199454504945, 0.014174884508925248, -0.308483450067523, 0.018625031193488673, -0.25096290315539665, -0.05745249577919149, -0.16941887315455187, 0.019910997306060507, 0.010710476494190118, -0.2762785901838582, 0.071334210725195, 0.0022401646710932255, 0.11645558418080926, -0.06389234555336608, -0.056573526456964854, -0.04013591971127189, 0.16169683167340923, 0.08333287010035535, -0.12017763081351168, 0.159448195759754, -0.08922183805636501, -0.22595788715152096, 0.3460615748214242, -0.05335597245960356, -0.06826816115860049, 0.16668896976864755, -0.11169791992511345, -0.1523702277623321, 0.07265794504280776, 0.264635828733508, 0.04103413541571633, -0.1765216312798582, 0.0005050241769361628, -0.030293934551156955, 0.20410789766553025, 0.0901729252336113, -0.03998540393603098, 0.1860504179893138, 0.24041300283566322, 0.03361329750404279, 0.13835754829190977, -0.0716220097686483, -0.1542789487149056, -0.2297502606979584, -0.06924188934419662, -0.1528994417757319, 0.023362303615152222, -0.15783658144887527, -0.09262444199962312, 0.4042653326608547, 0.15410167455341514, 0.15730049241093397, 0.0384992941901445, 0.24721505432644833, 0.05098393059109197, -0.011619026035912437, 0.1426002107072647, 0.14635061683696982, -0.04025724987907667, 0.19472129292361923, -0.19235029068061035, 0.1564270300018818, -0.021586438551647207] |
1,802.07406 | Differential Bandpass Filters Based on Dumbbell-Shaped Defected Ground
Resonators | This letter presents a dumbbell-shaped defected ground resonator and its
application in the design of differential filters. The operation principle of
the dumbbell-shaped resonator (DSR) coupled to differential microstrip lines is
studied through a circuit model analysis. The proposed circuit model is
validated through the comparison with the electromagnetic simulation results.
It is shown that the bandpass configuration of microstripline- coupled DSR can
be used to design higher order bandpass filters. The design procedure is
explained by developing a thirdorder filter prototype. The designed filter
shows more than 57 dB common mode rejection within the differential passband.
| eess.SP | this letter presents a dumbbellshaped defected ground resonator and its application in the design of differential filters the operation principle of the dumbbellshaped resonator dsr coupled to differential microstrip lines is studied through a circuit model analysis the proposed circuit model is validated through the comparison with the electromagnetic simulation results it is shown that the bandpass configuration of microstripline coupled dsr can be used to design higher order bandpass filters the design procedure is explained by developing a thirdorder filter prototype the designed filter shows more than 57 db common mode rejection within the differential passband | [['this', 'letter', 'presents', 'a', 'dumbbellshaped', 'defected', 'ground', 'resonator', 'and', 'its', 'application', 'in', 'the', 'design', 'of', 'differential', 'filters', 'the', 'operation', 'principle', 'of', 'the', 'dumbbellshaped', 'resonator', 'dsr', 'coupled', 'to', 'differential', 'microstrip', 'lines', 'is', 'studied', 'through', 'a', 'circuit', 'model', 'analysis', 'the', 'proposed', 'circuit', 'model', 'is', 'validated', 'through', 'the', 'comparison', 'with', 'the', 'electromagnetic', 'simulation', 'results', 'it', 'is', 'shown', 'that', 'the', 'bandpass', 'configuration', 'of', 'microstripline', 'coupled', 'dsr', 'can', 'be', 'used', 'to', 'design', 'higher', 'order', 'bandpass', 'filters', 'the', 'design', 'procedure', 'is', 'explained', 'by', 'developing', 'a', 'thirdorder', 'filter', 'prototype', 'the', 'designed', 'filter', 'shows', 'more', 'than', '57', 'db', 'common', 'mode', 'rejection', 'within', 'the', 'differential', 'passband']] | [-0.14072464122772985, 0.00585599247001342, -0.04466006200287741, -0.0248280250930621, -0.07389516930681528, -0.22176859930119255, -0.002210566829217924, 0.4538968559738594, -0.19508765998402053, -0.3200321141438386, 0.07189747742881288, -0.24427822097348645, -0.18360467850153825, 0.21520275952409684, -0.05295678854622331, 0.08989038795998473, 0.0800688417686015, -0.022196580723081668, -0.008477516546749423, -0.1670883695448547, 0.2081419843796295, 0.13088190422114945, 0.3460137271010269, -0.06525756607369818, 0.13373805819674559, -0.006542096982023573, -0.021161313624764533, 0.04079248892028153, -0.10544904212255245, 0.07768883424590237, 0.2663058333924597, 0.07065661375161222, 0.2476949661768512, -0.37089077942073345, -0.18040454842764692, -0.006203554286237461, 0.11623226034157362, 0.08164098453659986, -0.011934477514026268, -0.2936403625404712, 0.0775747126863655, -0.1925853391648414, -0.105350165507881, -0.021538538531851524, -0.07809401136467752, -0.01818655703466424, -0.2685492317643516, -0.03913266254173707, 0.042565079957976475, 0.02913783014435129, 0.01815269255564193, -0.08536975059811909, -0.037386343411179544, 0.011452985865054364, -0.07843499139224938, -0.03157899305032393, 0.18342889147359379, -0.055714505237344766, -0.12360976043051665, 0.37924014377532544, -0.1028086349661234, -0.19196958023665914, 0.10009920796302636, -0.08017109808291203, 0.0022267236220698382, 0.20626981801247782, 0.13879422546057127, 0.1025176310489319, -0.21287654152082414, 0.026920963750225634, 0.010109161911292252, 0.26393508448831965, 0.06002279231324792, 0.03223705953515144, 0.15777636542868292, 0.24729343741704932, 0.04531364042141484, 0.20005925594692206, -0.13433264818320953, -0.08312476887943741, -0.3058483787649071, -0.1334148817359633, -0.12271493469147712, -0.013404829291982058, -0.05081433492332226, -0.13583707230582057, 0.42569454317701233, 0.16194046498996387, 0.09194778745571516, -0.01913024935410502, 0.34565410632448096, 0.18320602205217115, 0.12345159570830538, 0.010729280745697007, 0.3146107267857212, 0.20260203358736464, 0.1301114615148951, -0.23983675068647592, -0.00343217632790893, 0.020904684266478745] |
1,802.07407 | Third-Party Data Providers Ruin Simple Mechanisms | Motivated by the growing prominence of third-party data providers in online
marketplaces, this paper studies the impact of the presence of third-party data
providers on mechanism design. When no data provider is present, it has been
shown that simple mechanisms are "good enough" -- they can achieve a constant
fraction of the revenue of optimal mechanisms. The results in this paper
demonstrate that this is no longer true in the presence of a third-party data
provider who can provide the bidder with a signal that is correlated with the
item type. Specifically, even with a single seller, a single bidder, and a
single item of uncertain type for sale, the strategies of pricing each
item-type separately (the analog of item pricing for multi-item auctions) and
bundling all item-types under a single price (the analog of grand bundling) can
both simultaneously be a logarithmic factor worse than the optimal revenue.
Further, in the presence of a data provider, item-type partitioning
mechanisms---a more general class of mechanisms which divide item-types into
disjoint groups and offer prices for each group---still cannot achieve within a
$\log \log$ factor of the optimal revenue. Thus, our results highlight that the
presence of a data-provider forces the use of more complicated mechanisms in
order to achieve a constant fraction of the optimal revenue.
| cs.GT | motivated by the growing prominence of thirdparty data providers in online marketplaces this paper studies the impact of the presence of thirdparty data providers on mechanism design when no data provider is present it has been shown that simple mechanisms are good enough they can achieve a constant fraction of the revenue of optimal mechanisms the results in this paper demonstrate that this is no longer true in the presence of a thirdparty data provider who can provide the bidder with a signal that is correlated with the item type specifically even with a single seller a single bidder and a single item of uncertain type for sale the strategies of pricing each itemtype separately the analog of item pricing for multiitem auctions and bundling all itemtypes under a single price the analog of grand bundling can both simultaneously be a logarithmic factor worse than the optimal revenue further in the presence of a data provider itemtype partitioning mechanismsa more general class of mechanisms which divide itemtypes into disjoint groups and offer prices for each groupstill cannot achieve within a log log factor of the optimal revenue thus our results highlight that the presence of a dataprovider forces the use of more complicated mechanisms in order to achieve a constant fraction of the optimal revenue | [['motivated', 'by', 'the', 'growing', 'prominence', 'of', 'thirdparty', 'data', 'providers', 'in', 'online', 'marketplaces', 'this', 'paper', 'studies', 'the', 'impact', 'of', 'the', 'presence', 'of', 'thirdparty', 'data', 'providers', 'on', 'mechanism', 'design', 'when', 'no', 'data', 'provider', 'is', 'present', 'it', 'has', 'been', 'shown', 'that', 'simple', 'mechanisms', 'are', 'good', 'enough', 'they', 'can', 'achieve', 'a', 'constant', 'fraction', 'of', 'the', 'revenue', 'of', 'optimal', 'mechanisms', 'the', 'results', 'in', 'this', 'paper', 'demonstrate', 'that', 'this', 'is', 'no', 'longer', 'true', 'in', 'the', 'presence', 'of', 'a', 'thirdparty', 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1,802.07408 | Physics and Human-Based Information Fusion for Improved Resident Space
Object Tracking | Maintaining a catalog of Resident Space Objects (RSOs) can be cast in a
typical Bayesian multi-object estimation problem, where the various sources of
uncertainty in the problem - the orbital mechanics, the kinematic states of the
identified objects, the data sources, etc. - are modeled as random variables
with associated probability distributions. In the context of Space Situational
Awareness, however, the information available to a space analyst on many
uncertain components is scarce, preventing their appropriate modeling with a
random variable and thus their exploitation in a RSO tracking algorithm. A
typical example are human-based data sources such as Two-Line Elements (TLEs),
which are publicly available but lack any statistical description of their
accuracy. In this paper, we propose the first exploitation of uncertain
variables in a RSO tracking problem, allowing for a representation of the
uncertain components reflecting the information available to the space analyst,
however scarce, and nothing more. In particular, we show that a human-based
data source and a physics-based data source can be embedded in a unified and
rigorous Bayesian estimator in order to track a RSO. We illustrate this concept
on a scenario where real TLEs queried from the U.S. Strategic Command are fused
with realistically simulated radar observations in order to track a Low-Earth
Orbit satellite.
| stat.AP | maintaining a catalog of resident space objects rsos can be cast in a typical bayesian multiobject estimation problem where the various sources of uncertainty in the problem the orbital mechanics the kinematic states of the identified objects the data sources etc are modeled as random variables with associated probability distributions in the context of space situational awareness however the information available to a space analyst on many uncertain components is scarce preventing their appropriate modeling with a random variable and thus their exploitation in a rso tracking algorithm a typical example are humanbased data sources such as twoline elements tles which are publicly available but lack any statistical description of their accuracy in this paper we propose the first exploitation of uncertain variables in a rso tracking problem allowing for a representation of the uncertain components reflecting the information available to the space analyst however scarce and nothing more in particular we show that a humanbased data source and a physicsbased data source can be embedded in a unified and rigorous bayesian estimator in order to track a rso we illustrate this concept on a scenario where real tles queried from the us strategic command are fused with realistically simulated radar observations in order to track a lowearth orbit satellite | [['maintaining', 'a', 'catalog', 'of', 'resident', 'space', 'objects', 'rsos', 'can', 'be', 'cast', 'in', 'a', 'typical', 'bayesian', 'multiobject', 'estimation', 'problem', 'where', 'the', 'various', 'sources', 'of', 'uncertainty', 'in', 'the', 'problem', 'the', 'orbital', 'mechanics', 'the', 'kinematic', 'states', 'of', 'the', 'identified', 'objects', 'the', 'data', 'sources', 'etc', 'are', 'modeled', 'as', 'random', 'variables', 'with', 'associated', 'probability', 'distributions', 'in', 'the', 'context', 'of', 'space', 'situational', 'awareness', 'however', 'the', 'information', 'available', 'to', 'a', 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1,802.07409 | Metastable state en route to traveling-wave synchronization state | The Kuramoto model with mixed signs of couplings is known to produce a
traveling-wave synchronized state. Here, we consider an abrupt synchronization
transition from the incoherent state to the traveling-wave state through a
long-lasting metastable state with large fluctuations. Our explanation of the
metastability is that the dynamic flow remains within a limited region of phase
space and circulates through a few active states bounded by saddle and stable
fixed points. This complex flow generates a long-lasting critical behavior, a
signature of a hybrid phase transition. We show that the long-lasting period
can be controlled by varying the density of inhibitory/excitatory interactions.
We discuss a potential application of this transition behavior to the recovery
process of human consciousness.
| cond-mat.stat-mech cond-mat.dis-nn nlin.CD physics.bio-ph | the kuramoto model with mixed signs of couplings is known to produce a travelingwave synchronized state here we consider an abrupt synchronization transition from the incoherent state to the travelingwave state through a longlasting metastable state with large fluctuations our explanation of the metastability is that the dynamic flow remains within a limited region of phase space and circulates through a few active states bounded by saddle and stable fixed points this complex flow generates a longlasting critical behavior a signature of a hybrid phase transition we show that the longlasting period can be controlled by varying the density of inhibitoryexcitatory interactions we discuss a potential application of this transition behavior to the recovery process of human consciousness | [['the', 'kuramoto', 'model', 'with', 'mixed', 'signs', 'of', 'couplings', 'is', 'known', 'to', 'produce', 'a', 'travelingwave', 'synchronized', 'state', 'here', 'we', 'consider', 'an', 'abrupt', 'synchronization', 'transition', 'from', 'the', 'incoherent', 'state', 'to', 'the', 'travelingwave', 'state', 'through', 'a', 'longlasting', 'metastable', 'state', 'with', 'large', 'fluctuations', 'our', 'explanation', 'of', 'the', 'metastability', 'is', 'that', 'the', 'dynamic', 'flow', 'remains', 'within', 'a', 'limited', 'region', 'of', 'phase', 'space', 'and', 'circulates', 'through', 'a', 'few', 'active', 'states', 'bounded', 'by', 'saddle', 'and', 'stable', 'fixed', 'points', 'this', 'complex', 'flow', 'generates', 'a', 'longlasting', 'critical', 'behavior', 'a', 'signature', 'of', 'a', 'hybrid', 'phase', 'transition', 'we', 'show', 'that', 'the', 'longlasting', 'period', 'can', 'be', 'controlled', 'by', 'varying', 'the', 'density', 'of', 'inhibitoryexcitatory', 'interactions', 'we', 'discuss', 'a', 'potential', 'application', 'of', 'this', 'transition', 'behavior', 'to', 'the', 'recovery', 'process', 'of', 'human', 'consciousness']] | [-0.19940938819515502, 0.2294896891138613, -0.09227692794648662, 0.024954103807338746, -0.03441576034785643, -0.12063174860520383, 0.09896666634733141, 0.3471833993207221, -0.2970202934170552, -0.2534366299998078, 0.11617904594089142, -0.25712309165273683, -0.18203252224819894, 0.11461143116506164, -0.0290989203092946, 0.03244546006859864, 0.047297769810183576, 0.04173307939653553, -0.048551925385994364, -0.11694336038722136, 0.32124319882724056, -0.007015788690897368, 0.2663085133318742, 0.017939624169908495, 0.09497693478192945, -0.05266021402805286, 0.10919249838615681, 0.007392976930023613, -0.10839789214613552, 0.057778623262893854, 0.23310433003767314, 0.07032228824761459, 0.27523947781804253, -0.4280303859988512, -0.2562236377685252, 0.14616736559240714, 0.1434792745384877, 0.13913456869501054, -0.08746478261457662, -0.3330600445663904, 0.04461238026851788, -0.16170379281107147, -0.1447743265924115, -0.09382149420868037, 0.02127954806595788, 0.00835502060067098, -0.26845902554154144, 0.10044894329966757, 0.04695114798417662, 0.046720463328726466, -0.08610252769056202, 0.008451556558010437, -0.030073799924940754, 0.12793787471334434, 0.010570432822825783, 0.031671012530766304, 0.13418777224260492, -0.15833892020933582, -0.10615584920841206, 0.32705149019010743, -0.09348967952936911, -0.11431834937499488, 0.19930165641057163, -0.1372848987121577, -0.06322111410751813, 0.20480061044632378, 0.15813431640646924, 0.11700309852485434, -0.09826357811057972, -0.00037824746193679964, -0.0009700890079977275, 0.20089906717303319, 0.007010896700055544, 0.0006767174355306868, 0.22535820987462302, 0.22736077505495336, 0.06934965264951905, 0.18344268891703874, -0.0803074985979346, -0.18819348000668748, -0.30519409427198313, -0.09815356871744586, -0.1573149222796497, 0.06443998100575439, -0.06021181114340572, -0.19182193624171412, 0.43918366058161323, 0.1200880345541163, 0.24985118794365455, -0.009410422409774136, 0.25941906964516864, 0.11367638022895366, -0.004475162171544625, 0.06300367033740474, 0.27804919631788666, 0.09653341189279395, 0.11516383919328199, -0.2556405690423671, 0.0988652774772086, 0.009100213872196776] |
1,802.0741 | Reduced Transmission in Multi-Server Coded Caching | Coded caching has been widely used in the wireless network for shifting the
some transmissions during the peak traffic times to the off-peak traffic times.
Multi-server coded caching, which can share responsibility for the total amount
of transmission in the wireless network during the peak traffic times by means
of the collaboration among these servers, can be seen everywhere in our life.
The three servers setting (two data servers and one parity check server) is
used in practice, e.g. redundant array of independent disks-4. In this
scenario, there are total $N$ files which are equally stored in two data
servers respectively and $K$ users each of which has the memory size of $M$
files. Each server connects to users by an independently channel. During the
off-peak traffic times, two data servers place some parts of each files in each
user's cache. In that time, servers do not know users' requests in future.
During the peak traffic times each user just requests one file from $N$ files.
Luo et al. in 2016 proposed the first coded caching scheme for this setting. In
this paper, we proposed some method that further reduces the amount of
transmission in each channel when $\frac{KM}{N}$ is odd. This method also
improves the transmission rate for systems with general multiply servers.
| cs.IT math.IT | coded caching has been widely used in the wireless network for shifting the some transmissions during the peak traffic times to the offpeak traffic times multiserver coded caching which can share responsibility for the total amount of transmission in the wireless network during the peak traffic times by means of the collaboration among these servers can be seen everywhere in our life the three servers setting two data servers and one parity check server is used in practice eg redundant array of independent disks4 in this scenario there are total n files which are equally stored in two data servers respectively and k users each of which has the memory size of m files each server connects to users by an independently channel during the offpeak traffic times two data servers place some parts of each files in each users cache in that time servers do not know users requests in future during the peak traffic times each user just requests one file from n files luo et al in 2016 proposed the first coded caching scheme for this setting in this paper we proposed some method that further reduces the amount of transmission in each channel when frackmn is odd this method also improves the transmission rate for systems with general multiply servers | [['coded', 'caching', 'has', 'been', 'widely', 'used', 'in', 'the', 'wireless', 'network', 'for', 'shifting', 'the', 'some', 'transmissions', 'during', 'the', 'peak', 'traffic', 'times', 'to', 'the', 'offpeak', 'traffic', 'times', 'multiserver', 'coded', 'caching', 'which', 'can', 'share', 'responsibility', 'for', 'the', 'total', 'amount', 'of', 'transmission', 'in', 'the', 'wireless', 'network', 'during', 'the', 'peak', 'traffic', 'times', 'by', 'means', 'of', 'the', 'collaboration', 'among', 'these', 'servers', 'can', 'be', 'seen', 'everywhere', 'in', 'our', 'life', 'the', 'three', 'servers', 'setting', 'two', 'data', 'servers', 'and', 'one', 'parity', 'check', 'server', 'is', 'used', 'in', 'practice', 'eg', 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1,802.07411 | Design of Chern Insulating Phases in Honeycomb Lattices | The search for robust examples of the magnetic version of topological
insulators, referred to as quantum anomalous Hall insulators or simply Chern
insulators, so far lacks success. Our groups have explored two distinct
possibilities based on multiorbital 3d oxide honeycomb lattices. Each has a
Chern insulating phase near the ground state, but materials parameters were not
appropriate to produce a viable Chern insulator. Further exploration of one of
these classes, by substituting open shell 3d with 4d and 5d counterparts, has
led to realistic prediction of Chern insulating ground states. Here we recount
the design process, discussing the many energy scales that are active in
participating (or resisting) the desired Chern insulator phase.
| cond-mat.mtrl-sci cond-mat.str-el | the search for robust examples of the magnetic version of topological insulators referred to as quantum anomalous hall insulators or simply chern insulators so far lacks success our groups have explored two distinct possibilities based on multiorbital 3d oxide honeycomb lattices each has a chern insulating phase near the ground state but materials parameters were not appropriate to produce a viable chern insulator further exploration of one of these classes by substituting open shell 3d with 4d and 5d counterparts has led to realistic prediction of chern insulating ground states here we recount the design process discussing the many energy scales that are active in participating or resisting the desired chern insulator phase | [['the', 'search', 'for', 'robust', 'examples', 'of', 'the', 'magnetic', 'version', 'of', 'topological', 'insulators', 'referred', 'to', 'as', 'quantum', 'anomalous', 'hall', 'insulators', 'or', 'simply', 'chern', 'insulators', 'so', 'far', 'lacks', 'success', 'our', 'groups', 'have', 'explored', 'two', 'distinct', 'possibilities', 'based', 'on', 'multiorbital', '3d', 'oxide', 'honeycomb', 'lattices', 'each', 'has', 'a', 'chern', 'insulating', 'phase', 'near', 'the', 'ground', 'state', 'but', 'materials', 'parameters', 'were', 'not', 'appropriate', 'to', 'produce', 'a', 'viable', 'chern', 'insulator', 'further', 'exploration', 'of', 'one', 'of', 'these', 'classes', 'by', 'substituting', 'open', 'shell', '3d', 'with', '4d', 'and', '5d', 'counterparts', 'has', 'led', 'to', 'realistic', 'prediction', 'of', 'chern', 'insulating', 'ground', 'states', 'here', 'we', 'recount', 'the', 'design', 'process', 'discussing', 'the', 'many', 'energy', 'scales', 'that', 'are', 'active', 'in', 'participating', 'or', 'resisting', 'the', 'desired', 'chern', 'insulator', 'phase']] | [-0.17276268871707132, 0.22744680154837865, -0.003816749263900967, 0.06005907441400606, -0.09587387112523038, -0.24867136832903577, 0.080311472526395, 0.402744463438877, -0.20478121818463624, -0.3202766648501949, 0.05955761392802758, -0.30588980432830554, -0.18025882099961152, 0.13756399818663115, -0.01577130283550483, 0.0888962804348068, -0.031320885598527644, -0.06977040674207749, -0.1315172932180782, -0.2495115868483497, 0.3340510955508963, -0.03872826070405246, 0.2918120482895293, 0.030194609805084434, 0.03447380110176396, -0.07219627147926269, 0.13234346983459802, 0.030844774150775862, -0.14709800498724135, 0.09797404976551363, 0.2971123689291092, -0.08375885464926869, 0.19191113867656848, -0.4725213321832429, -0.2328334837344236, 0.030356762246682052, 0.09033905942017724, 0.15623463155388567, -0.09887843793031421, -0.3796124310702481, 0.040945676641654126, -0.19139597878535897, -0.09861944672297192, -0.1670817346847822, 0.011964240680094313, -0.07250094566642579, -0.1712985248716993, -0.0037728570962110453, 0.04003687337271671, 0.09447742706016365, -0.09920542286832577, -0.14259430245224353, -0.10528904027140708, 0.12293825517573385, 0.05368649662009737, 0.02635049477911892, 0.11209860119342277, -0.17156813411553085, -0.19451206272665775, 0.4131969331673025, 0.0136409639669335, -0.14541122040389914, 0.20322655288057517, -0.11927332818318587, -0.10230322061436234, 0.17193641820180733, 0.08262909004728483, 0.10140987174107438, -0.03450809331380029, 0.09215055781455743, -0.05074389854990012, 0.15271935121061495, -0.05013024594132022, 0.11881656653404368, 0.30577855771489904, 0.18041597223898345, 0.06899271624531614, 0.16215848368468933, -0.099578531951421, -0.069907826767097, -0.2360386155644613, -0.25558854424213345, -0.2936280189860876, 0.09044238435018466, -0.001891700245838703, -0.22176409278073209, 0.4597872957191636, 0.1493234847398244, 0.13862935224531497, -0.05678550997930291, 0.24138572297792518, 0.07395082880718122, 0.06659264402233261, 0.01695110431287141, 0.2612391142050975, 0.09629234831071401, 0.07804165165294456, -0.17614463504931305, 0.06162992644791318, 0.10623696711804487] |
1,802.07412 | Density-aware Single Image De-raining using a Multi-stream Dense Network | Single image rain streak removal is an extremely challenging problem due to
the presence of non-uniform rain densities in images. We present a novel
density-aware multi-stream densely connected convolutional neural network-based
algorithm, called DID-MDN, for joint rain density estimation and de-raining.
The proposed method enables the network itself to automatically determine the
rain-density information and then efficiently remove the corresponding
rain-streaks guided by the estimated rain-density label. To better characterize
rain-streaks with different scales and shapes, a multi-stream densely connected
de-raining network is proposed which efficiently leverages features from
different scales. Furthermore, a new dataset containing images with
rain-density labels is created and used to train the proposed density-aware
network. Extensive experiments on synthetic and real datasets demonstrate that
the proposed method achieves significant improvements over the recent
state-of-the-art methods. In addition, an ablation study is performed to
demonstrate the improvements obtained by different modules in the proposed
method. Code can be found at: https://github.com/hezhangsprinter
| cs.CV | single image rain streak removal is an extremely challenging problem due to the presence of nonuniform rain densities in images we present a novel densityaware multistream densely connected convolutional neural networkbased algorithm called didmdn for joint rain density estimation and deraining the proposed method enables the network itself to automatically determine the raindensity information and then efficiently remove the corresponding rainstreaks guided by the estimated raindensity label to better characterize rainstreaks with different scales and shapes a multistream densely connected deraining network is proposed which efficiently leverages features from different scales furthermore a new dataset containing images with raindensity labels is created and used to train the proposed densityaware network extensive experiments on synthetic and real datasets demonstrate that the proposed method achieves significant improvements over the recent stateoftheart methods in addition an ablation study is performed to demonstrate the improvements obtained by different modules in the proposed method code can be found at httpsgithubcomhezhangsprinter | [['single', 'image', 'rain', 'streak', 'removal', 'is', 'an', 'extremely', 'challenging', 'problem', 'due', 'to', 'the', 'presence', 'of', 'nonuniform', 'rain', 'densities', 'in', 'images', 'we', 'present', 'a', 'novel', 'densityaware', 'multistream', 'densely', 'connected', 'convolutional', 'neural', 'networkbased', 'algorithm', 'called', 'didmdn', 'for', 'joint', 'rain', 'density', 'estimation', 'and', 'deraining', 'the', 'proposed', 'method', 'enables', 'the', 'network', 'itself', 'to', 'automatically', 'determine', 'the', 'raindensity', 'information', 'and', 'then', 'efficiently', 'remove', 'the', 'corresponding', 'rainstreaks', 'guided', 'by', 'the', 'estimated', 'raindensity', 'label', 'to', 'better', 'characterize', 'rainstreaks', 'with', 'different', 'scales', 'and', 'shapes', 'a', 'multistream', 'densely', 'connected', 'deraining', 'network', 'is', 'proposed', 'which', 'efficiently', 'leverages', 'features', 'from', 'different', 'scales', 'furthermore', 'a', 'new', 'dataset', 'containing', 'images', 'with', 'raindensity', 'labels', 'is', 'created', 'and', 'used', 'to', 'train', 'the', 'proposed', 'densityaware', 'network', 'extensive', 'experiments', 'on', 'synthetic', 'and', 'real', 'datasets', 'demonstrate', 'that', 'the', 'proposed', 'method', 'achieves', 'significant', 'improvements', 'over', 'the', 'recent', 'stateoftheart', 'methods', 'in', 'addition', 'an', 'ablation', 'study', 'is', 'performed', 'to', 'demonstrate', 'the', 'improvements', 'obtained', 'by', 'different', 'modules', 'in', 'the', 'proposed', 'method', 'code', 'can', 'be', 'found', 'at', 'httpsgithubcomhezhangsprinter']] | [-0.03117034825636378, 0.018585529654123974, -0.06751450738607863, 0.05077023751154128, -0.06556776504251449, -0.12537365326706587, -0.01575957413525412, 0.44819536091747625, -0.26956420078313625, -0.33436923699903914, 0.06280016925968109, -0.2518225847652145, -0.21039472379739962, 0.19292236947655386, -0.13379115746447853, 0.07377539392031145, 0.15442825065852672, 0.024704615053647728, -0.04447947744146184, -0.27467280410205813, 0.28398291849732105, 0.06905194264197466, 0.3787701045242108, 0.051309882888412164, 0.16067391754511526, -0.05187605275449897, -0.06645442525174444, 0.03231934421570984, -0.045244228216795496, 0.15047236361002148, 0.2541871442234302, 0.16629502355894135, 0.27535464655717506, -0.43508107721610784, -0.25934919139451734, 0.07760684474164413, 0.1519254454551569, 0.09169082648702517, -0.04547013944772748, -0.3635812586575162, 0.13452633621256335, -0.15460091202178958, 0.007776154019547249, -0.12762134255585716, -0.04636706450034931, -0.01749844202890481, -0.323387184715982, 0.03780062642904133, -0.0034097442932250403, 0.0014447673677399852, -0.0339911024944455, -0.08363207638129787, -0.005702422867876058, 0.14798628383474363, -0.021410009409818385, 0.053624625345905085, 0.1317912969902596, -0.1311954831403187, -0.11800324046692136, 0.32006303949610276, -0.08974808949240623, -0.18927877151340344, 0.1934605378541925, -0.03619288065428146, -0.11832497012344938, 0.17981382019915224, 0.23112285238526323, 0.14533917709661562, -0.14878098281964758, -0.027593529584218013, -0.07094670856581527, 0.18121968687578938, 0.06081235487838854, -0.04169820868744959, 0.1687871476793601, 0.2336323302105264, 0.038272859638228136, 0.19066084189313082, -0.22030051558370664, -0.018390947353289604, -0.17124662158122056, -0.06438978450537167, -0.21057375900301278, -0.07791922867505087, -0.09701672837195623, -0.1296119437510379, 0.4444161633248715, 0.2453427980288717, 0.23000306209695398, 0.0740525391009131, 0.36853244047295425, 0.01099356282441542, 0.1434843033043138, 0.11942193737509203, 0.13757848712536536, 0.04362955589830461, 0.07304209575712912, -0.19261239985235376, 0.055110668108396814, 0.04532708346332405] |
1,802.07413 | Dysprosium-doped ZBLAN fiber laser tunable from 2.8 {\mu}m to 3.4
{\mu}m, pumped at 1.7 {\mu}m | We demonstrate a mid-infrared dysprosium-doped fluoride fiber laser with a
continuously tunable output range of 573 nm, pumped by a 1.7 {\mu}m Raman fiber
laser. To the best of our knowledge, this represents the largest tuning range
achieved to date from any rare-earth-doped fiber laser and, critically, spans
the 2.8-3.4 {\mu}m spectral region, which contains absorption resonances of
many important functional groups and is uncovered by other rare-earth ions.
Output powers up to 170 mW are achieved, with 21% slope efficiency. We also
discuss the relative merits of the 1.7 {\mu}m pump scheme, including possible
pump excited-state absorption.
| physics.optics | we demonstrate a midinfrared dysprosiumdoped fluoride fiber laser with a continuously tunable output range of 573 nm pumped by a 17 mum raman fiber laser to the best of our knowledge this represents the largest tuning range achieved to date from any rareearthdoped fiber laser and critically spans the 2834 mum spectral region which contains absorption resonances of many important functional groups and is uncovered by other rareearth ions output powers up to 170 mw are achieved with 21 slope efficiency we also discuss the relative merits of the 17 mum pump scheme including possible pump excitedstate absorption | [['we', 'demonstrate', 'a', 'midinfrared', 'dysprosiumdoped', 'fluoride', 'fiber', 'laser', 'with', 'a', 'continuously', 'tunable', 'output', 'range', 'of', '573', 'nm', 'pumped', 'by', 'a', '17', 'mum', 'raman', 'fiber', 'laser', 'to', 'the', 'best', 'of', 'our', 'knowledge', 'this', 'represents', 'the', 'largest', 'tuning', 'range', 'achieved', 'to', 'date', 'from', 'any', 'rareearthdoped', 'fiber', 'laser', 'and', 'critically', 'spans', 'the', '2834', 'mum', 'spectral', 'region', 'which', 'contains', 'absorption', 'resonances', 'of', 'many', 'important', 'functional', 'groups', 'and', 'is', 'uncovered', 'by', 'other', 'rareearth', 'ions', 'output', 'powers', 'up', 'to', '170', 'mw', 'are', 'achieved', 'with', '21', 'slope', 'efficiency', 'we', 'also', 'discuss', 'the', 'relative', 'merits', 'of', 'the', '17', 'mum', 'pump', 'scheme', 'including', 'possible', 'pump', 'excitedstate', 'absorption']] | [-0.08086643561872901, 0.12592862330897406, 0.00870398858239, -0.08168298453662773, -0.010661166503417249, -0.15430373829618402, 0.09434143237161394, 0.5256025868525006, -0.2107161260970241, -0.3348250591899363, 0.0140353325393279, -0.2875262583149787, -0.030842453179576873, 0.25386488317911116, -0.02534043772546432, 0.046732562051982646, -0.002303850732515661, -0.09422194242135298, 0.02852679163690333, -0.17900952190393582, 0.22451382431698183, 0.05108103297688827, 0.2809888907822267, 0.03830044163980198, 0.1251451856390174, -0.0590458746586109, 0.00043498308454849283, -0.1046035829551366, -0.16245180265787912, 0.13702883968980298, 0.2824542978968547, -0.002162055891691422, 0.2690105277389212, -0.26609456240750695, -0.2331601121386855, 0.054544316110562305, 0.12991226454056343, 0.08316533459345715, -0.024424428101248886, -0.25429375667115484, 0.07455666095246466, -0.14589423913394614, -0.1299196189502254, -0.010117757951422614, 0.017419492255668252, 0.08094492678207402, -0.23463693268749178, -0.02154105674144004, 0.0036627715623525343, 0.13187920797274125, -0.03945810935811653, -0.13262227254596595, -0.0692411181683253, 0.03821957088788325, -0.0602888452644669, 0.027444020196099348, 0.25017986372018197, -0.07855585719695153, -0.07378242745501351, 0.3761021553595759, -0.13937583754352312, 0.015271888047988926, 0.14069447473014648, -0.18425908567840044, -0.017857876919894194, 0.2683297368621796, 0.06713667644035755, 0.11136068718754971, -0.08998475737907753, 0.016491150373013273, 0.026595389753180956, 0.3340167753512458, 0.1787203562265376, 0.1550980485899716, 0.19120333055794544, 0.18368839312876975, 0.011489783845514022, 0.1618777445751499, -0.17413179242178056, 0.006173319299111371, -0.25375393625082715, -0.1024020935114169, -0.15388390835260554, 0.08371685263320651, -0.11253938535483772, -0.053225361302552024, 0.4310209149084864, 0.1229525849422706, 0.15107683884930245, -0.029937193202738632, 0.27847963129645403, 0.08117687508430597, 0.09812938242352434, 0.017251763407293022, 0.33578387838408197, 0.1739653974352167, 0.09989362851745087, -0.22918963604559173, -0.04410451782240095, -0.04353640196198712] |
1,802.07414 | Tunable Lifshitz Transitions and Multiband Transport in Tetralayer
Graphene | As the Fermi level and band structure of two-dimensional materials are
readily tunable, they constitute an ideal platform for exploring Lifshitz
transition, a change in the topology of a material's Fermi surface. Using
tetralayer graphene that host two intersecting massive Dirac bands, we
demonstrate multiple Lifshitz transitions and multiband transport, which
manifest as non-monotonic dependence of conductivity on charge density n and
out-of-plane electric fieldD, anomalous quantum Hall sequences and Landau level
crossings that evolve with n, D and B.
| cond-mat.mes-hall | as the fermi level and band structure of twodimensional materials are readily tunable they constitute an ideal platform for exploring lifshitz transition a change in the topology of a materials fermi surface using tetralayer graphene that host two intersecting massive dirac bands we demonstrate multiple lifshitz transitions and multiband transport which manifest as nonmonotonic dependence of conductivity on charge density n and outofplane electric fieldd anomalous quantum hall sequences and landau level crossings that evolve with n d and b | [['as', 'the', 'fermi', 'level', 'and', 'band', 'structure', 'of', 'twodimensional', 'materials', 'are', 'readily', 'tunable', 'they', 'constitute', 'an', 'ideal', 'platform', 'for', 'exploring', 'lifshitz', 'transition', 'a', 'change', 'in', 'the', 'topology', 'of', 'a', 'materials', 'fermi', 'surface', 'using', 'tetralayer', 'graphene', 'that', 'host', 'two', 'intersecting', 'massive', 'dirac', 'bands', 'we', 'demonstrate', 'multiple', 'lifshitz', 'transitions', 'and', 'multiband', 'transport', 'which', 'manifest', 'as', 'nonmonotonic', 'dependence', 'of', 'conductivity', 'on', 'charge', 'density', 'n', 'and', 'outofplane', 'electric', 'fieldd', 'anomalous', 'quantum', 'hall', 'sequences', 'and', 'landau', 'level', 'crossings', 'that', 'evolve', 'with', 'n', 'd', 'and', 'b']] | [-0.22262646764799765, 0.2317965570573851, -0.03812418599860578, 0.0280480023497079, -0.04540962883848933, -0.22716583226088294, 0.09359915393899797, 0.3704380885804001, -0.24314604321188188, -0.32209139369145223, -0.043642452612955455, -0.3351064119723779, -0.20012973551343702, 0.16420492360109015, 0.08230165394518195, 0.024522969847002737, -0.041609212011983025, -0.09641088418591814, -0.10346003313094991, -0.18256410386389757, 0.3091602162104336, -0.004179978644463552, 0.32843596929141994, 0.058777576082539335, 0.01506921617149175, 0.012333095639566832, 0.13150442672799093, 0.07216388805286039, -0.11573404419221886, 0.05484690807193895, 0.264596440873545, -0.14868343905162631, 0.14963615143117553, -0.4257039397695585, -0.21024688142882306, -0.032981894830760514, 0.15088952656340185, 0.10166840785023862, -0.058135918702611915, -0.30031189491052795, 0.003589070696808115, -0.14438817965432624, -0.14745745248355774, -0.10776736829105671, 0.04110054832682768, -0.0419006212909199, -0.20689814551689226, 0.08248544051724521, 0.0270003909952467, 0.10654811766087019, -0.09651319599191693, -0.13482758773364056, -0.14260227883328933, 0.08542916469888974, 0.015544996162157364, 0.03796690871977377, 0.1838169423391736, -0.14231929805459856, -0.13642017757873745, 0.38482358877228784, -0.07143666710751721, -0.12012009569031151, 0.21153810540732892, -0.22284637459353368, -0.0964459150003953, 0.1692443760111928, 0.14568547458871256, 0.04954704187244554, -0.09361821642997262, 0.1412728526180056, -0.025753448718769736, 0.1057548285933518, 0.06645081225263921, 0.13265928115601403, 0.3451675363356554, 0.15777111073507916, 0.048440112932762014, 0.08344872209797555, -0.13950918381886346, 0.02556495800838346, -0.2661726940843229, -0.2174999298162381, -0.25274601250981227, 0.11209472884789487, -0.05808156609879306, -0.2528823814767448, 0.39816144615694693, 0.09124962294097, 0.2026951716906285, -0.040208297898061574, 0.17811331860839, 0.13304027883612987, 0.05030304563594275, 0.09587929805127691, 0.18670796527810207, 0.10052375880635897, 0.05865538976732877, -0.27562238170788916, -0.026419814953085364, 0.005896059433705633] |
1,802.07415 | Stationary distribution of a 2-island 2-allele Wright-Fisher diffusion
model with slow mutation and migration rates | The stationary distribution of the diffusion limit of the 2-island, 2-allele
Wright-Fisher with small but otherwise arbitrary mutation and migration rates
is investigated. Following a method developed by Burden and Tang (2016, 2017)
for approximating the forward Kolmogorov equation, the stationary distribution
is obtained to leading order as a set of line densities on the edges of the
sample space, corresponding to states for which one island is bi-allelic and
the other island is non-segregating, and a set of point masses at the corners
of the sample space, corresponding to states for which both islands are
simultaneously non-segregating. Analytic results for the corner probabilities
and line densities are verified independently using the backward generator and
for the corner probabilities using the coalescent.
| q-bio.PE | the stationary distribution of the diffusion limit of the 2island 2allele wrightfisher with small but otherwise arbitrary mutation and migration rates is investigated following a method developed by burden and tang 2016 2017 for approximating the forward kolmogorov equation the stationary distribution is obtained to leading order as a set of line densities on the edges of the sample space corresponding to states for which one island is biallelic and the other island is nonsegregating and a set of point masses at the corners of the sample space corresponding to states for which both islands are simultaneously nonsegregating analytic results for the corner probabilities and line densities are verified independently using the backward generator and for the corner probabilities using the coalescent | [['the', 'stationary', 'distribution', 'of', 'the', 'diffusion', 'limit', 'of', 'the', '2island', '2allele', 'wrightfisher', 'with', 'small', 'but', 'otherwise', 'arbitrary', 'mutation', 'and', 'migration', 'rates', 'is', 'investigated', 'following', 'a', 'method', 'developed', 'by', 'burden', 'and', 'tang', '2016', '2017', 'for', 'approximating', 'the', 'forward', 'kolmogorov', 'equation', 'the', 'stationary', 'distribution', 'is', 'obtained', 'to', 'leading', 'order', 'as', 'a', 'set', 'of', 'line', 'densities', 'on', 'the', 'edges', 'of', 'the', 'sample', 'space', 'corresponding', 'to', 'states', 'for', 'which', 'one', 'island', 'is', 'biallelic', 'and', 'the', 'other', 'island', 'is', 'nonsegregating', 'and', 'a', 'set', 'of', 'point', 'masses', 'at', 'the', 'corners', 'of', 'the', 'sample', 'space', 'corresponding', 'to', 'states', 'for', 'which', 'both', 'islands', 'are', 'simultaneously', 'nonsegregating', 'analytic', 'results', 'for', 'the', 'corner', 'probabilities', 'and', 'line', 'densities', 'are', 'verified', 'independently', 'using', 'the', 'backward', 'generator', 'and', 'for', 'the', 'corner', 'probabilities', 'using', 'the', 'coalescent']] | [-0.05571784769223693, 0.10793593549363625, -0.05634622162130351, 0.08060221946992291, -0.01632238905876875, -0.10569225728007343, 0.09942749328135202, 0.3291235240952422, -0.22120671098430952, -0.2839699073539426, 0.13261174803289275, -0.29674668348549554, -0.05546766489666576, 0.17722460133954882, -0.007491632391853879, 0.08655231450490343, 0.06564201462315396, 0.01655937801891317, -0.003388303006067872, -0.21436006869965543, 0.3492002372571733, 0.048433719677026, 0.2959898438304663, -0.013623715083425244, 0.12044030327039461, -0.016205359149413803, -0.006028997100656852, 0.014479219843148409, -0.13053006511181592, 0.11045250265839665, 0.21246947588321444, 0.07253450408267478, 0.24054436295603712, -0.39646627289803293, -0.16902557690627873, 0.06340004395072658, 0.13053973744196506, 0.13596773815709942, -0.014091183180183483, -0.30789435492867295, 0.0905305129631112, -0.11656846805320432, -0.15301428224969035, 0.0018064703171451887, 0.06829922937710459, 0.05410690079443157, -0.3195902907813434, 0.06350996559485793, 0.04905619984686685, 0.011387970593447486, -0.022795245767338202, -0.1386911525100004, -0.09041072437539696, 0.14141733865253628, 0.028934966792197276, 0.0024011725792661308, 0.1107918034462879, -0.08980323122426247, -0.10797521484394869, 0.3121020844516655, -0.03352717571833637, -0.19636732197056214, 0.2043474824478229, -0.19654248257478077, -0.07415598828811198, 0.17702541126248736, 0.1539112962258514, 0.1296435745569397, -0.14216099718275169, 0.09086775205117495, -0.030367788959605, 0.07757707104829023, 0.08944719634018838, -0.028690565975072482, 0.16376409544221435, 0.13990810013686616, 0.08396051911792407, 0.09810259726024621, -0.15657490613909128, -0.1408440971824651, -0.29579746793800343, -0.15914010362466796, -0.21002272820333018, 0.006882962617479885, -0.07295894971587889, -0.17033541313139722, 0.3722573331712435, 0.08955932195143153, 0.25644810903274146, 0.09525955783513686, 0.21634279019199312, 0.17825385298856417, 0.007769395411014557, 0.10585550519948204, 0.1546770131390076, 0.1223901949376644, 0.0718018323299475, -0.21839985103967288, 0.09427439221569027, 0.10811023934123416] |
1,802.07416 | Angle constrained path to cluster multiple manifolds | In this paper, we propose a method to cluster multiple intersected manifolds.
The algorithm chooses several landmark nodes randomly and then checks whether
there is an angle constrained path between each landmark node and every other
node in the neighborhood graph. When the points lie on different manifolds with
intersection they should not be connected using a smooth path, thus the angle
constraint is used to prevent connecting points from one cluster to another
one. The resulting algorithm is implemented as a simple variation of Dijkstras
algorithm used in Isomap. However, Isomap was specifically designed for
dimensionality reduction in the single-manifold setting, and in particular,
can-not handle intersections. Our method is simpler than the previous proposals
in the literature and performs comparably to the best methods, both on
simulated and some real datasets.
| cs.CV | in this paper we propose a method to cluster multiple intersected manifolds the algorithm chooses several landmark nodes randomly and then checks whether there is an angle constrained path between each landmark node and every other node in the neighborhood graph when the points lie on different manifolds with intersection they should not be connected using a smooth path thus the angle constraint is used to prevent connecting points from one cluster to another one the resulting algorithm is implemented as a simple variation of dijkstras algorithm used in isomap however isomap was specifically designed for dimensionality reduction in the singlemanifold setting and in particular cannot handle intersections our method is simpler than the previous proposals in the literature and performs comparably to the best methods both on simulated and some real datasets | [['in', 'this', 'paper', 'we', 'propose', 'a', 'method', 'to', 'cluster', 'multiple', 'intersected', 'manifolds', 'the', 'algorithm', 'chooses', 'several', 'landmark', 'nodes', 'randomly', 'and', 'then', 'checks', 'whether', 'there', 'is', 'an', 'angle', 'constrained', 'path', 'between', 'each', 'landmark', 'node', 'and', 'every', 'other', 'node', 'in', 'the', 'neighborhood', 'graph', 'when', 'the', 'points', 'lie', 'on', 'different', 'manifolds', 'with', 'intersection', 'they', 'should', 'not', 'be', 'connected', 'using', 'a', 'smooth', 'path', 'thus', 'the', 'angle', 'constraint', 'is', 'used', 'to', 'prevent', 'connecting', 'points', 'from', 'one', 'cluster', 'to', 'another', 'one', 'the', 'resulting', 'algorithm', 'is', 'implemented', 'as', 'a', 'simple', 'variation', 'of', 'dijkstras', 'algorithm', 'used', 'in', 'isomap', 'however', 'isomap', 'was', 'specifically', 'designed', 'for', 'dimensionality', 'reduction', 'in', 'the', 'singlemanifold', 'setting', 'and', 'in', 'particular', 'can', 'not', 'handle', 'intersections', 'our', 'method', 'is', 'simpler', 'than', 'the', 'previous', 'proposals', 'in', 'the', 'literature', 'and', 'performs', 'comparably', 'to', 'the', 'best', 'methods', 'both', 'on', 'simulated', 'and', 'some', 'real', 'datasets']] | [-0.09212363234185961, 0.007719734952191704, -0.09289555440642941, 0.057239180197070506, -0.11560342383376364, -0.204261891700244, 0.06977924839471843, 0.4318795139665034, -0.2810129290029629, -0.2941115114893486, 0.10700169555780326, -0.2837698787256186, -0.17691082501811767, 0.2110829759222358, -0.12670994782125328, 0.051320824904172724, 0.09380157446530439, 0.08356964044662109, -0.04496797487342125, -0.30304452825321143, 0.3159482218290387, 0.0318090460235392, 0.2596786251680842, 0.009149887460047629, 0.10234367127144542, 0.009867735648416538, -0.015138943308665515, 0.08859722462218644, -0.06589596932788672, 0.0988977043889463, 0.2709930163457184, 0.15227526668876187, 0.26582925152311576, -0.41680598692901594, -0.1782558614165703, 0.15234234112439982, 0.15939186015791856, 0.10922292726378934, 0.018582569006065936, -0.26025075519652063, 0.10816019642820109, -0.09823076865712264, -0.08528712353279898, -0.0531991614535305, -0.016270206344605825, -0.01454163534278328, -0.25866309956494554, -0.004746244831094102, 0.019368092140266253, 0.019664247930327904, -0.02126041890222774, -0.10139421239119968, -0.02265932345450091, 0.14123806157501226, -0.0004387838312480321, 0.10078486689686109, 0.1158924315523516, -0.06016267618727384, -0.1664833710268279, 0.3909584797550438, -0.0007862371220748607, -0.24351963458353404, 0.20775803651855285, -0.06095954945394352, -0.17161690302318267, 0.09818098137030072, 0.1596528996692609, 0.1615812334878398, -0.13390787589286, 0.053441649457047095, -0.056675938590527025, 0.13400739630156044, 0.06580044396235538, -0.0525853892132586, 0.13567911803258892, 0.16176458319419745, 0.142541060891826, 0.11126096778047104, -0.13119057799105657, -0.07513152336208288, -0.253375885685395, -0.1113106740235504, -0.22033702661352816, -0.03383225620070076, -0.12443202685288053, -0.15409901639474416, 0.387218845076859, 0.1512699013266629, 0.25161851650284633, 0.06551711624071224, 0.34219113403736656, 0.054863911202010604, 0.0839883170347772, 0.1499042239113113, 0.16422383553707284, 0.06681107589279983, 0.04911196157475239, -0.14720255737331933, 0.07482382522916782, 0.10281668696552515] |
1,802.07417 | Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient
Algorithms | Mixture-of-Experts (MoE) is a widely popular model for ensemble learning and
is a basic building block of highly successful modern neural networks as well
as a component in Gated Recurrent Units (GRU) and Attention networks. However,
present algorithms for learning MoE including the EM algorithm, and gradient
descent are known to get stuck in local optima. From a theoretical viewpoint,
finding an efficient and provably consistent algorithm to learn the parameters
remains a long standing open problem for more than two decades. In this paper,
we introduce the first algorithm that learns the true parameters of a MoE model
for a wide class of non-linearities with global consistency guarantees. While
existing algorithms jointly or iteratively estimate the expert parameters and
the gating paramters in the MoE, we propose a novel algorithm that breaks the
deadlock and can directly estimate the expert parameters by sensing its echo in
a carefully designed cross-moment tensor between the inputs and the output.
Once the experts are known, the recovery of gating parameters still requires an
EM algorithm; however, we show that the EM algorithm for this simplified
problem, unlike the joint EM algorithm, converges to the true parameters. We
empirically validate our algorithm on both the synthetic and real data sets in
a variety of settings, and show superior performance to standard baselines.
| cs.LG | mixtureofexperts moe is a widely popular model for ensemble learning and is a basic building block of highly successful modern neural networks as well as a component in gated recurrent units gru and attention networks however present algorithms for learning moe including the em algorithm and gradient descent are known to get stuck in local optima from a theoretical viewpoint finding an efficient and provably consistent algorithm to learn the parameters remains a long standing open problem for more than two decades in this paper we introduce the first algorithm that learns the true parameters of a moe model for a wide class of nonlinearities with global consistency guarantees while existing algorithms jointly or iteratively estimate the expert parameters and the gating paramters in the moe we propose a novel algorithm that breaks the deadlock and can directly estimate the expert parameters by sensing its echo in a carefully designed crossmoment tensor between the inputs and the output once the experts are known the recovery of gating parameters still requires an em algorithm however we show that the em algorithm for this simplified problem unlike the joint em algorithm converges to the true parameters we empirically validate our algorithm on both the synthetic and real data sets in a variety of settings and show superior performance to standard baselines | [['mixtureofexperts', 'moe', 'is', 'a', 'widely', 'popular', 'model', 'for', 'ensemble', 'learning', 'and', 'is', 'a', 'basic', 'building', 'block', 'of', 'highly', 'successful', 'modern', 'neural', 'networks', 'as', 'well', 'as', 'a', 'component', 'in', 'gated', 'recurrent', 'units', 'gru', 'and', 'attention', 'networks', 'however', 'present', 'algorithms', 'for', 'learning', 'moe', 'including', 'the', 'em', 'algorithm', 'and', 'gradient', 'descent', 'are', 'known', 'to', 'get', 'stuck', 'in', 'local', 'optima', 'from', 'a', 'theoretical', 'viewpoint', 'finding', 'an', 'efficient', 'and', 'provably', 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1,802.07418 | Limits for Partial Maxima of Gaussian Random Vectors | We obtain almost sure limit theorems for partial maxima of norms of a
sequence of Banach-valued Gaussian random variables.
| math.PR | we obtain almost sure limit theorems for partial maxima of norms of a sequence of banachvalued gaussian random variables | [['we', 'obtain', 'almost', 'sure', 'limit', 'theorems', 'for', 'partial', 'maxima', 'of', 'norms', 'of', 'a', 'sequence', 'of', 'banachvalued', 'gaussian', 'random', 'variables']] | [-0.12956351806458674, 0.10514006033343704, -0.14347497417934632, 0.14308583559958557, 0.05490426988782067, -0.05573095489097269, 0.14198650675213062, 0.36830900413425344, -0.2749853706673572, -0.11608362491977842, 0.20223439036329327, -0.28133089232601616, -0.12395267443437326, 0.14424759776968704, -0.10221015884982128, 0.15128273348397525, 0.04970728101110772, 0.08177443319245388, -0.09980974363555249, -0.318816181909489, 0.32520516785351855, -0.09439331449960407, 0.20474028959870338, -0.07934051036442581, 0.16196669932258756, 0.1464881372245911, -0.0892086649607671, -0.07657570784029208, -0.13604213655191033, 0.0951681305458279, 0.2260825902615723, 0.09438743423302903, 0.34443523440706103, -0.35988197943783906, -0.13073506626594616, 0.20788551587611437, 0.14953401140672595, 0.00843432369200807, 0.06859491549824413, -0.2694099502343881, 0.10928090686272633, -0.025538277977734412, -0.24386233601130938, -0.11590254914603736, -0.007269721821342644, 0.16888444821693396, -0.46777537170993655, 0.15233658724709562, 0.24145474488307772, 0.08379985040396844, -0.06561956829146336, -0.16488311890708773, 0.037333470499633176, 0.12952252259281904, 0.0999642850733117, -0.04638217404288681, 0.10527373999847393, -0.03927154172407953, -0.14311745716258883, 0.23193821779109144, -0.1631286846669881, -0.1742392509783569, 0.08237426414301521, -0.16125546787914477, -0.21065095248387047, 0.09131861331039354, 0.1727537188286844, 0.14751847132452225, -0.19905334985569903, 0.12334546427193441, -0.12037141954428271, 0.10584910537459348, 0.20199718341035278, 0.16107818925459133, 0.08471691569215373, 0.03301532361901512, 0.23534529979683852, 0.14351845748330416, -0.0015078209291555379, -0.11668197251856327, -0.3225310354640609, -0.12267226912081242, -0.17511402541085294, 0.14327889014231532, -0.25649794898957845, -0.3411183855251262, 0.3208157445157045, 0.08701205508489358, 0.18465249632534228, 0.2171254827101764, 0.16975379715624608, 0.18996444310208685, -0.07211081134645562, 0.057192655917453136, 0.12635438212830769, 0.34153732088835614, 0.06423260305861109, 0.01851252486046992, 0.0535168542257069, 0.18934540828003696] |
1,802.07419 | Approximate low-weight check codes and circuit lower bounds for noisy
ground states | The No Low-Energy Trivial States (NLTS) conjecture of Freedman and Hastings
(Quantum Information and Computation 2014), which asserts the existence of
local Hamiltonians whose low energy states cannot be generated by constant
depth quantum circuits, identifies a fundamental obstacle to resolving the
quantum PCP conjecture. Progress towards the NLTS conjecture was made by Eldar
and Harrow (Foundations of Computer Science 2017), who proved a closely related
theorem called No Low-Error Trivial States (NLETS). In this paper, we give a
much simpler proof of the NLETS theorem, and use the same technique to
establish superpolynomial circuit size lower bounds for noisy ground states of
local Hamiltonians (assuming $\mathsf{QCMA} \neq \mathsf{QMA}$), resolving an
open question of Eldar and Harrow. We discuss the new light our results cast on
the relationship between NLTS and NLETS.
Finally, our techniques imply the existence of $\textit{approximate quantum
low-weight check (qLWC) codes}$ with linear rate, linear distance, and constant
weight checks. These codes are similar to quantum LDPC codes except (1) each
particle may participate in a large number of checks, and (2) errors only need
to be corrected up to fidelity $1 - 1/\mathsf{poly}(n)$. This stands in
contrast to the best-known stabilizer LDPC codes due to Freedman, Meyer, and
Luo which achieve a distance of $O(\sqrt{n \log n})$.
The principal technique used in our results is to leverage the Feynman-Kitaev
clock construction to approximately embed a subspace of states defined by a
circuit as the ground space of a local Hamiltonian.
| quant-ph | the no lowenergy trivial states nlts conjecture of freedman and hastings quantum information and computation 2014 which asserts the existence of local hamiltonians whose low energy states cannot be generated by constant depth quantum circuits identifies a fundamental obstacle to resolving the quantum pcp conjecture progress towards the nlts conjecture was made by eldar and harrow foundations of computer science 2017 who proved a closely related theorem called no lowerror trivial states nlets in this paper we give a much simpler proof of the nlets theorem and use the same technique to establish superpolynomial circuit size lower bounds for noisy ground states of local hamiltonians assuming mathsfqcma neq mathsfqma resolving an open question of eldar and harrow we discuss the new light our results cast on the relationship between nlts and nlets finally our techniques imply the existence of textitapproximate quantum lowweight check qlwc codes with linear rate linear distance and constant weight checks these codes are similar to quantum ldpc codes except 1 each particle may participate in a large number of checks and 2 errors only need to be corrected up to fidelity 1 1mathsfpolyn this stands in contrast to the bestknown stabilizer ldpc codes due to freedman meyer and luo which achieve a distance of osqrtn log n the principal technique used in our results is to leverage the feynmankitaev clock construction to approximately embed a subspace of states defined by a circuit as the ground space of a local hamiltonian | [['the', 'no', 'lowenergy', 'trivial', 'states', 'nlts', 'conjecture', 'of', 'freedman', 'and', 'hastings', 'quantum', 'information', 'and', 'computation', '2014', 'which', 'asserts', 'the', 'existence', 'of', 'local', 'hamiltonians', 'whose', 'low', 'energy', 'states', 'can', 'not', 'be', 'generated', 'by', 'constant', 'depth', 'quantum', 'circuits', 'identifies', 'a', 'fundamental', 'obstacle', 'to', 'resolving', 'the', 'quantum', 'pcp', 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1,802.0742 | Sequence-based Multi-lingual Low Resource Speech Recognition | Techniques for multi-lingual and cross-lingual speech recognition can help in
low resource scenarios, to bootstrap systems and enable analysis of new
languages and domains. End-to-end approaches, in particular sequence-based
techniques, are attractive because of their simplicity and elegance. While it
is possible to integrate traditional multi-lingual bottleneck feature
extractors as front-ends, we show that end-to-end multi-lingual training of
sequence models is effective on context independent models trained using
Connectionist Temporal Classification (CTC) loss. We show that our model
improves performance on Babel languages by over 6% absolute in terms of
word/phoneme error rate when compared to mono-lingual systems built in the same
setting for these languages. We also show that the trained model can be adapted
cross-lingually to an unseen language using just 25% of the target data. We
show that training on multiple languages is important for very low resource
cross-lingual target scenarios, but not for multi-lingual testing scenarios.
Here, it appears beneficial to include large well prepared datasets.
| cs.CL cs.SD eess.AS | techniques for multilingual and crosslingual speech recognition can help in low resource scenarios to bootstrap systems and enable analysis of new languages and domains endtoend approaches in particular sequencebased techniques are attractive because of their simplicity and elegance while it is possible to integrate traditional multilingual bottleneck feature extractors as frontends we show that endtoend multilingual training of sequence models is effective on context independent models trained using connectionist temporal classification ctc loss we show that our model improves performance on babel languages by over 6 absolute in terms of wordphoneme error rate when compared to monolingual systems built in the same setting for these languages we also show that the trained model can be adapted crosslingually to an unseen language using just 25 of the target data we show that training on multiple languages is important for very low resource crosslingual target scenarios but not for multilingual testing scenarios here it appears beneficial to include large well prepared datasets | [['techniques', 'for', 'multilingual', 'and', 'crosslingual', 'speech', 'recognition', 'can', 'help', 'in', 'low', 'resource', 'scenarios', 'to', 'bootstrap', 'systems', 'and', 'enable', 'analysis', 'of', 'new', 'languages', 'and', 'domains', 'endtoend', 'approaches', 'in', 'particular', 'sequencebased', 'techniques', 'are', 'attractive', 'because', 'of', 'their', 'simplicity', 'and', 'elegance', 'while', 'it', 'is', 'possible', 'to', 'integrate', 'traditional', 'multilingual', 'bottleneck', 'feature', 'extractors', 'as', 'frontends', 'we', 'show', 'that', 'endtoend', 'multilingual', 'training', 'of', 'sequence', 'models', 'is', 'effective', 'on', 'context', 'independent', 'models', 'trained', 'using', 'connectionist', 'temporal', 'classification', 'ctc', 'loss', 'we', 'show', 'that', 'our', 'model', 'improves', 'performance', 'on', 'babel', 'languages', 'by', 'over', '6', 'absolute', 'in', 'terms', 'of', 'wordphoneme', 'error', 'rate', 'when', 'compared', 'to', 'monolingual', 'systems', 'built', 'in', 'the', 'same', 'setting', 'for', 'these', 'languages', 'we', 'also', 'show', 'that', 'the', 'trained', 'model', 'can', 'be', 'adapted', 'crosslingually', 'to', 'an', 'unseen', 'language', 'using', 'just', '25', 'of', 'the', 'target', 'data', 'we', 'show', 'that', 'training', 'on', 'multiple', 'languages', 'is', 'important', 'for', 'very', 'low', 'resource', 'crosslingual', 'target', 'scenarios', 'but', 'not', 'for', 'multilingual', 'testing', 'scenarios', 'here', 'it', 'appears', 'beneficial', 'to', 'include', 'large', 'well', 'prepared', 'datasets']] | [-0.04403787450396321, 0.002547529014358268, -0.03143426245839903, 0.13638324250610628, -0.10095321638919648, -0.21908959845350412, 0.05456191323237763, 0.4792873276948179, -0.26280989788425796, -0.3374445238051813, 0.0644933278935979, -0.23612503083598502, -0.14364753385900325, 0.2681353042318058, -0.16527333755760729, 0.073933054069965, 0.1749686728577194, 0.05226938978405728, -0.06578187011116413, -0.3199655433923428, 0.30633398075148743, 0.03917997798724276, 0.3783704751294176, 0.03807737087280308, 0.11045076641179628, -0.04027243058706792, -0.005131581401358704, -0.04173003745107156, -0.022723285398049187, 0.15355358927059662, 0.3825361021908689, 0.2419177616946674, 0.2624286436622248, -0.38223786380891717, -0.23021196713963957, 0.07270157426220816, 0.18342357541510612, 0.1388906402442547, 0.0024374737909485427, -0.33823362301007126, 0.09653089911553939, -0.20524291736557027, 0.059736019067770846, -0.167905504832578, -0.008354703362726566, -0.005462705307426341, -0.2769810821730702, 0.05883469603078604, 0.13408680674371035, 0.0990726875094404, -0.05682745742986459, -0.11858898997394685, 0.023106857879473915, 0.17024783651383282, 0.05579448580952748, 0.046510688975195655, 0.1017278578928994, -0.16128606591139388, -0.1679913127595711, 0.3721489384418951, -0.0954760662514318, -0.241923010404333, 0.28723534647047333, -0.01743490320671373, -0.16963638685081364, 0.029700438595968503, 0.25069631876075443, 0.10306484167136064, -0.1738938948117766, 0.04693889312933744, -0.0008621571011513284, 0.25019294736063424, 0.07897109998999245, 0.013805199262199912, 0.17521381439017308, 0.27035863802082977, -0.002110952933160764, 0.14127004002411295, -0.07171167657452887, -0.04981234072855492, -0.19450254048075843, -0.10744011756501295, -0.1797718436035486, -0.053741469293881836, -0.08678329911093234, -0.12321180176376453, 0.3386221255216771, 0.23347767593877963, 0.13911605775122, 0.1502678592091883, 0.3117786003452427, 0.013612681982230465, 0.15906157095641274, 0.09061760546452126, 0.16490254076798125, -0.034027963848901714, 0.13107712900796142, -0.13833352855887007, 0.0796284988396596, 0.008247901612318724] |
1,802.07421 | Conditional Adversarial Synthesis of 3D Facial Action Units | Employing deep learning-based approaches for fine-grained facial expression
analysis, such as those involving the estimation of Action Unit (AU)
intensities, is difficult due to the lack of a large-scale dataset of real
faces with sufficiently diverse AU labels for training. In this paper, we
consider how AU-level facial image synthesis can be used to substantially
augment such a dataset. We propose an AU synthesis framework that combines the
well-known 3D Morphable Model (3DMM), which intrinsically disentangles
expression parameters from other face attributes, with models that
adversarially generate 3DMM expression parameters conditioned on given target
AU labels, in contrast to the more conventional approach of generating facial
images directly. In this way, we are able to synthesize new combinations of
expression parameters and facial images from desired AU labels. Extensive
quantitative and qualitative results on the benchmark DISFA dataset demonstrate
the effectiveness of our method on 3DMM facial expression parameter synthesis
and data augmentation for deep learning-based AU intensity estimation.
| cs.CV | employing deep learningbased approaches for finegrained facial expression analysis such as those involving the estimation of action unit au intensities is difficult due to the lack of a largescale dataset of real faces with sufficiently diverse au labels for training in this paper we consider how aulevel facial image synthesis can be used to substantially augment such a dataset we propose an au synthesis framework that combines the wellknown 3d morphable model 3dmm which intrinsically disentangles expression parameters from other face attributes with models that adversarially generate 3dmm expression parameters conditioned on given target au labels in contrast to the more conventional approach of generating facial images directly in this way we are able to synthesize new combinations of expression parameters and facial images from desired au labels extensive quantitative and qualitative results on the benchmark disfa dataset demonstrate the effectiveness of our method on 3dmm facial expression parameter synthesis and data augmentation for deep learningbased au intensity estimation | [['employing', 'deep', 'learningbased', 'approaches', 'for', 'finegrained', 'facial', 'expression', 'analysis', 'such', 'as', 'those', 'involving', 'the', 'estimation', 'of', 'action', 'unit', 'au', 'intensities', 'is', 'difficult', 'due', 'to', 'the', 'lack', 'of', 'a', 'largescale', 'dataset', 'of', 'real', 'faces', 'with', 'sufficiently', 'diverse', 'au', 'labels', 'for', 'training', 'in', 'this', 'paper', 'we', 'consider', 'how', 'aulevel', 'facial', 'image', 'synthesis', 'can', 'be', 'used', 'to', 'substantially', 'augment', 'such', 'a', 'dataset', 'we', 'propose', 'an', 'au', 'synthesis', 'framework', 'that', 'combines', 'the', 'wellknown', '3d', 'morphable', 'model', '3dmm', 'which', 'intrinsically', 'disentangles', 'expression', 'parameters', 'from', 'other', 'face', 'attributes', 'with', 'models', 'that', 'adversarially', 'generate', '3dmm', 'expression', 'parameters', 'conditioned', 'on', 'given', 'target', 'au', 'labels', 'in', 'contrast', 'to', 'the', 'more', 'conventional', 'approach', 'of', 'generating', 'facial', 'images', 'directly', 'in', 'this', 'way', 'we', 'are', 'able', 'to', 'synthesize', 'new', 'combinations', 'of', 'expression', 'parameters', 'and', 'facial', 'images', 'from', 'desired', 'au', 'labels', 'extensive', 'quantitative', 'and', 'qualitative', 'results', 'on', 'the', 'benchmark', 'disfa', 'dataset', 'demonstrate', 'the', 'effectiveness', 'of', 'our', 'method', 'on', '3dmm', 'facial', 'expression', 'parameter', 'synthesis', 'and', 'data', 'augmentation', 'for', 'deep', 'learningbased', 'au', 'intensity', 'estimation']] | [0.024567903423994262, -0.061760102786898134, -0.037175349285531366, 0.036915816063845315, -0.09832748748020187, -0.1822588274939151, -0.01162789665277505, 0.46073562621221514, -0.2498022712342724, -0.3757613301630827, 0.04254401203825527, -0.2932637784423018, -0.21367460511671968, 0.19604605250797363, -0.176449954521524, 0.10627189332831509, 0.15473803317489668, 0.017823276227145586, -0.05575865720265362, -0.19029645519655292, 0.2982910000601241, 0.002800691277127642, 0.3110588689193224, 0.0017468671836076846, 0.13325287526417406, -0.02666771727515741, -0.00648144225418992, -0.016659540474957116, -0.09182222939475478, 0.22295037185024658, 0.3107094233040744, 0.21523244152600063, 0.22145552559213452, -0.4284707513531741, -0.21284923889921814, 0.027369400218152738, 0.14072359049555705, 0.14875786699269178, -0.060940807013749584, -0.3621753117753358, 0.08431266750654064, -0.14898273844678614, -0.0041569500433611154, -0.15864961378606438, -0.003365624912637227, -0.05584342572860172, -0.35633344274961765, 0.06780354396581556, 0.049097255206463526, 0.12359820167192176, -0.11589698583518356, -0.14053474441376998, -0.007282459594108919, 0.19387177844779402, 0.03530720193926363, 0.05660972359024365, 0.16244843269144243, -0.18504162706822286, -0.09573292287502767, 0.3579667657495865, -0.07193121579888312, -0.24078430507663282, 0.21758048878864775, -0.07241290955379888, -0.13617949142515706, 0.13141282707971486, 0.24150771669132776, 0.1845190941350228, -0.16732053917278594, 0.011032608663736948, -0.07721886411898687, 0.2280352782116189, 0.049935320006164755, -0.029908760160478894, 0.2006718191094225, 0.20936883789121727, -0.011888011691714578, 0.15956181625922541, -0.23141382537823454, -0.01761125628188064, -0.19323003058884694, -0.05809075408320449, -0.20579674571186682, -0.01760181736516401, -0.13318520140676846, -0.16871849899740207, 0.4121025021120175, 0.2814399515001598, 0.25791202422785514, 0.1127376247063291, 0.36155362170236777, 0.02336676511324093, 0.11766669093749096, 0.014827597626968276, 0.13579005949034156, -0.015629132749819304, 0.057406955039057926, -0.17157397290125867, 0.11209385839285023, 0.067193226785623] |
1,802.07422 | Blockchain: Data Malls, Coin Economies and Keyless Payments | We discuss several uses of blockchain (and, more generally, distributed
ledger) technologies outside of cryptocurrencies with a pragmatic view. We
mostly focus on three areas: the role of coin economies for what we refer to as
data malls (specialized data marketplaces); data provenance (a historical
record of data and its origins); and what we term keyless payments (made
without having to know other users' cryptographic keys). We also discuss voting
and other areas, and give a sizable list of academic and nonacademic
references.
| q-fin.GN cs.CR q-fin.EC | we discuss several uses of blockchain and more generally distributed ledger technologies outside of cryptocurrencies with a pragmatic view we mostly focus on three areas the role of coin economies for what we refer to as data malls specialized data marketplaces data provenance a historical record of data and its origins and what we term keyless payments made without having to know other users cryptographic keys we also discuss voting and other areas and give a sizable list of academic and nonacademic references | [['we', 'discuss', 'several', 'uses', 'of', 'blockchain', 'and', 'more', 'generally', 'distributed', 'ledger', 'technologies', 'outside', 'of', 'cryptocurrencies', 'with', 'a', 'pragmatic', 'view', 'we', 'mostly', 'focus', 'on', 'three', 'areas', 'the', 'role', 'of', 'coin', 'economies', 'for', 'what', 'we', 'refer', 'to', 'as', 'data', 'malls', 'specialized', 'data', 'marketplaces', 'data', 'provenance', 'a', 'historical', 'record', 'of', 'data', 'and', 'its', 'origins', 'and', 'what', 'we', 'term', 'keyless', 'payments', 'made', 'without', 'having', 'to', 'know', 'other', 'users', 'cryptographic', 'keys', 'we', 'also', 'discuss', 'voting', 'and', 'other', 'areas', 'and', 'give', 'a', 'sizable', 'list', 'of', 'academic', 'and', 'nonacademic', 'references']] | [-0.14323624623350306, 0.03160350683358419, -0.05509417000260339, 0.12848000818616653, -0.17039823151720934, -0.19766187693654413, 0.1500872449433229, 0.4006879952433239, -0.2676446250000273, -0.31676588209376794, 0.1758822210929749, -0.35872752703053046, -0.10560844262433519, 0.20381644291870565, -0.16717328295582928, -0.005764477628883513, 0.03707063555049833, 0.05415305443646678, 0.01722698737250035, -0.31957534164560575, 0.332180995854594, 0.034855681120878064, 0.2794714204950191, 0.06180048768418415, 0.05722579132787973, 0.0004866083534097815, -0.10572303814465651, -0.047543833750378656, -0.13695463716579848, 0.14500480549163128, 0.3363400448607393, 0.26681309578805623, 0.33392935134021634, -0.46918298986302803, -0.09761265184202916, 0.09031823996723776, 0.09264878622685413, 0.0972921205852854, -0.08746925918669411, -0.29696704918541106, 0.02440667004010315, -0.25878303170383693, -0.09329018471425915, -0.09465252291635577, 0.022846736597368515, 0.03225876672013876, -0.1982419195259551, -0.03222365269236861, -0.00019568548795868116, 0.13237983685166363, -0.003107743695411966, -0.15558168369468794, 0.007526902986847493, 0.19219574938718992, 0.07867392401648574, -0.04799888911095997, 0.1633186251295349, -0.14433563843997846, -0.18324907037642707, 0.40574485943259964, 0.03196150867024041, -0.11797890220824854, 0.14524802390530886, -0.07367332493437521, -0.17766273091512128, -0.006444953090275626, 0.20362167901931758, 0.03155440816947495, -0.18757414684283086, 0.0010837271026930358, -0.0503262948659978, 0.16022112953311102, 0.06028295227562089, 0.10884782062641468, 0.19398706725024314, 0.1441310589168086, 0.08545760274023177, 0.09378859178718539, -0.05530431757523981, -0.1495642065553062, -0.22634772922989566, -0.1519152303226292, -0.13276422575834285, 0.01989201616484627, -0.07643618475518145, -0.17704232678333498, 0.36530614793525046, 0.21847777066651328, 0.1360271456314767, 0.016166264536308057, 0.31884493773062544, -0.061603404201443744, 0.12651916467640772, 0.10257038380389652, 0.14295448496354274, -0.007920430504705712, 0.23318969106570964, -0.04283016699321388, 0.1282947345816317, -0.04674156034836568] |
1,802.07423 | Calabi-Yau algebras and the shifted noncommutative symplectic structure | In this paper we show that for a Koszul Calabi-Yau algebra, there is a
shifted bi-symplectic structure in the sense of
Crawley-Boevey-Etingof-Ginzburg, on the cobar construction of its co-unitalized
Koszul dual coalgebra, and hence its DG representation schemes, in the sense of
Berest-Khachatryan-Ramadoss, have a shifted symplectic structure in the sense
of Pantev-To\"en-Vaqui\'e-Vezzosi.
| math.RA | in this paper we show that for a koszul calabiyau algebra there is a shifted bisymplectic structure in the sense of crawleyboeveyetingofginzburg on the cobar construction of its counitalized koszul dual coalgebra and hence its dg representation schemes in the sense of berestkhachatryanramadoss have a shifted symplectic structure in the sense of pantevtoenvaquievezzosi | [['in', 'this', 'paper', 'we', 'show', 'that', 'for', 'a', 'koszul', 'calabiyau', 'algebra', 'there', 'is', 'a', 'shifted', 'bisymplectic', 'structure', 'in', 'the', 'sense', 'of', 'crawleyboeveyetingofginzburg', 'on', 'the', 'cobar', 'construction', 'of', 'its', 'counitalized', 'koszul', 'dual', 'coalgebra', 'and', 'hence', 'its', 'dg', 'representation', 'schemes', 'in', 'the', 'sense', 'of', 'berestkhachatryanramadoss', 'have', 'a', 'shifted', 'symplectic', 'structure', 'in', 'the', 'sense', 'of', 'pantevtoenvaquievezzosi']] | [-0.16857329208403826, -0.022426038086414336, -0.13618159551173448, 0.06488149512559176, -0.0973765478655696, -0.10057217418216169, -0.019378389751072974, 0.4001073598861694, -0.403532828502357, -0.1457731518894434, 0.09393337937537581, -0.13896541394293307, -0.2249400826357305, 0.14209383441135287, -0.21903829196467994, -0.10118339307839051, 0.1186408825032413, 0.11420655677095055, -0.1384885719185695, -0.24308728418312966, 0.4484742472320795, 0.04475201128982007, 0.24504016120918096, 0.01749798746779561, 0.15544142551720141, -0.044227493200451135, -0.026848541926592587, -0.006689230054616928, -0.12533406464921426, 0.18415655182674529, 0.31603734962642194, 0.04484708475880325, 0.19816984818316996, -0.34989433201029896, -0.05735526617092546, 0.1179959225282073, 0.1648140262067318, 0.03461942620575428, -0.03790687094675377, -0.24379267010837793, 0.13496381274424493, -0.23166243137791753, -0.10103657754138112, -0.05732685956172645, 0.06605715819634497, -0.007890801280736923, -0.22386982026742772, -0.018359654545783997, 0.12591284822672605, 0.10573097819462418, -0.05377857439685613, -0.06132791412994266, -0.11928978376090527, 0.014300092542544007, -0.05118835857603699, 0.05782229822129011, 0.07052701425738633, -0.14884542684536428, -0.15329604637576266, 0.38076536286622287, -0.0335282957367599, -0.25977917958050967, 0.11304659781977534, -0.18228590092621744, -0.19923547465354205, 0.08743580602109433, 0.012813953068107366, 0.18625829562544824, 0.009642489475663752, 0.2438356415729504, -0.11251741550862789, 0.03996604420244694, 0.11175213281065226, 0.07314972137100995, 0.13077804536558688, 0.1402167726168409, 0.11203544969204814, 0.09840176872909069, 0.021134989713318647, -0.08712878853082656, -0.32807797282934187, -0.22548587050812785, -0.09918147753924131, 0.10490203501656652, -0.07715260583878263, -0.19294628620147705, 0.4095715832710266, 0.10832465803250671, 0.18262582002207636, 0.10748316908255219, 0.2124803490936756, 0.08686574140563608, 0.10595387499779463, 0.05578907043673098, 0.16971045836806298, 0.25952590657398106, 0.09511711577884853, -0.1457640101481229, -0.017096185726113617, 0.20955736238509418] |
1,802.07424 | On the vibron-polaron damping in quasi 1D macromolecular chains | The properties of the intramolecular vibrational excitation (vibron) in a
quasi 1D macromolecular structure are studied. It is supposed that due to the
vibron interaction with optical phonon modes, a vibron might form partially
dressed small polaron states. The properties of these states are investigated
in dependence on the basic system parameters and temperature of a thermal bath.
We also investigate the process of damping of the polaron amplitude as a
function of temperature and vibron-phonon coupling strength. Two different
regimes of the polaron damping are found and discussed.
| cond-mat.mes-hall cond-mat.soft cond-mat.stat-mech hep-th | the properties of the intramolecular vibrational excitation vibron in a quasi 1d macromolecular structure are studied it is supposed that due to the vibron interaction with optical phonon modes a vibron might form partially dressed small polaron states the properties of these states are investigated in dependence on the basic system parameters and temperature of a thermal bath we also investigate the process of damping of the polaron amplitude as a function of temperature and vibronphonon coupling strength two different regimes of the polaron damping are found and discussed | [['the', 'properties', 'of', 'the', 'intramolecular', 'vibrational', 'excitation', 'vibron', 'in', 'a', 'quasi', '1d', 'macromolecular', 'structure', 'are', 'studied', 'it', 'is', 'supposed', 'that', 'due', 'to', 'the', 'vibron', 'interaction', 'with', 'optical', 'phonon', 'modes', 'a', 'vibron', 'might', 'form', 'partially', 'dressed', 'small', 'polaron', 'states', 'the', 'properties', 'of', 'these', 'states', 'are', 'investigated', 'in', 'dependence', 'on', 'the', 'basic', 'system', 'parameters', 'and', 'temperature', 'of', 'a', 'thermal', 'bath', 'we', 'also', 'investigate', 'the', 'process', 'of', 'damping', 'of', 'the', 'polaron', 'amplitude', 'as', 'a', 'function', 'of', 'temperature', 'and', 'vibronphonon', 'coupling', 'strength', 'two', 'different', 'regimes', 'of', 'the', 'polaron', 'damping', 'are', 'found', 'and', 'discussed']] | [-0.1830023617086032, 0.2577475960355964, -0.05463554722706923, 0.07661351494519632, -0.011602624424136756, -0.12669223563724688, 0.04321161250510577, 0.38166073106982734, -0.27023260048433634, -0.21960190386417205, 0.00605031808058658, -0.25632171698040174, -0.11821236597960082, 0.1600822378996383, 0.09500420289218761, 0.017752685691386962, 0.02369908690112486, 0.005364920548948176, -0.0029974987630973036, -0.1531164857135102, 0.32423981699799553, 0.05525762352862217, 0.2840858646616172, 0.11200121840922518, 0.06412649317906144, -0.0148123673534837, 0.09224130981340167, -0.017358611023911598, -0.16849463534833448, 0.05121992536417596, 0.21700327057624236, -0.07390070269721445, 0.2299522284465434, -0.4142418182088753, -0.21764682334837285, -0.0015107428215527803, 0.16227858891093244, 0.18373910673688626, 0.005918883764331512, -0.24016755176812746, -0.034078318144330814, -0.15155288339540196, -0.13441393401845242, -0.10016086363767306, 0.0389432477649678, 0.05555108383172349, -0.2267111173779913, 0.13067353587680014, 0.04080486170466194, 0.03823105500111084, -0.11893059342074093, -0.11597153789682962, -0.09675770620763134, 0.08369461886501045, 0.04724626643079584, -0.05872250469715408, 0.19982794649752506, -0.13629268914502993, -0.042323238399465765, 0.37639583977922964, -0.09752712046905432, -0.16686035078437475, 0.24843390335150983, -0.1588946614215632, -0.06628575144215289, 0.16130536295515432, 0.11051384769537057, 0.09982690578745154, -0.17121543501977274, 0.07921840086006403, 0.02696255331838064, 0.17754893017189807, 0.05409130070023657, 0.15705778490061337, 0.19192462597628324, 0.1653773901680631, -0.04410734885696615, 0.19365037432636312, -0.07990026355229235, -0.09973630607860644, -0.23558153896435594, -0.08963974213667131, -0.2152787819295452, 0.04169106967171675, -0.051060760361855334, -0.19860704923362543, 0.45118269328226784, 0.08772793191935072, 0.21399311014706807, -0.02403668820690573, 0.21998081785323245, 0.17751714756602444, 0.05196968132755562, 0.0054395333419062115, 0.28858401113597865, 0.22012109574443253, 0.057364500582929745, -0.38758107995237695, 0.03800803129404281, 0.021956931885980656] |
1,802.07425 | Inapproximability of Matrix $p\rightarrow q$ Norms | We study the problem of computing the $p\rightarrow q$ norm of a matrix $A
\in R^{m \times n}$, defined as \[ \|A\|_{p\rightarrow q} ~:=~ \max_{x \,\in\,
R^n \setminus \{0\}} \frac{\|Ax\|_q}{\|x\|_p} \] This problem generalizes the
spectral norm of a matrix ($p=q=2$) and the Grothendieck problem ($p=\infty$,
$q=1$), and has been widely studied in various regimes. When $p \geq q$, the
problem exhibits a dichotomy: constant factor approximation algorithms are
known if $2 \in [q,p]$, and the problem is hard to approximate within almost
polynomial factors when $2 \notin [q,p]$.
The regime when $p < q$, known as \emph{hypercontractive norms}, is
particularly significant for various applications but much less well
understood. The case with $p = 2$ and $q > 2$ was studied by [Barak et al,
STOC'12] who gave sub-exponential algorithms for a promise version of the
problem (which captures small-set expansion) and also proved hardness of
approximation results based on the Exponential Time Hypothesis. However, no
NP-hardness of approximation is known for these problems for any $p < q$.
We study the hardness of approximating matrix norms in both the above cases
and prove the following results:
- We show that for any $1< p < q < \infty$ with $2 \notin [p,q]$,
$\|A\|_{p\rightarrow q}$ is hard to approximate within
$2^{O(\log^{1-\epsilon}\!n)}$ assuming $NP \not\subseteq
BPTIME(2^{\log^{O(1)}\!n})$. This suggests that, similar to the case of $p \geq
q$, the hypercontractive setting may be qualitatively different when $2$ does
not lie between $p$ and $q$.
- For all $p \geq q$ with $2 \in [q,p]$, we show $\|A\|_{p\rightarrow q}$ is
hard to approximate within any factor than $1/(\gamma_{p^*} \cdot \gamma_q)$,
where for any $r$, $\gamma_r$ denotes the $r^{th}$ norm of a gaussian, and
$p^*$ is the dual norm of $p$.
| cs.CC | we study the problem of computing the prightarrow q norm of a matrix a in rm times n defined as a_prightarrow q max_x in rn setminus 0 fracax_qx_p this problem generalizes the spectral norm of a matrix pq2 and the grothendieck problem pinfty q1 and has been widely studied in various regimes when p geq q the problem exhibits a dichotomy constant factor approximation algorithms are known if 2 in qp and the problem is hard to approximate within almost polynomial factors when 2 notin qp the regime when p q known as emphhypercontractive norms is particularly significant for various applications but much less well understood the case with p 2 and q 2 was studied by barak et al stoc12 who gave subexponential algorithms for a promise version of the problem which captures smallset expansion and also proved hardness of approximation results based on the exponential time hypothesis however no nphardness of approximation is known for these problems for any p q we study the hardness of approximating matrix norms in both the above cases and prove the following results we show that for any 1 p q infty with 2 notin pq a_prightarrow q is hard to approximate within 2olog1epsilonn assuming np notsubseteq bptime2logo1n this suggests that similar to the case of p geq q the hypercontractive setting may be qualitatively different when 2 does not lie between p and q for all p geq q with 2 in qp we show a_prightarrow q is hard to approximate within any factor than 1gamma_p cdot gamma_q where for any r gamma_r denotes the rth norm of a gaussian and p is the dual norm of p | [['we', 'study', 'the', 'problem', 'of', 'computing', 'the', 'prightarrow', 'q', 'norm', 'of', 'a', 'matrix', 'a', 'in', 'rm', 'times', 'n', 'defined', 'as', 'a_prightarrow', 'q', 'max_x', 'in', 'rn', 'setminus', '0', 'fracax_qx_p', 'this', 'problem', 'generalizes', 'the', 'spectral', 'norm', 'of', 'a', 'matrix', 'pq2', 'and', 'the', 'grothendieck', 'problem', 'pinfty', 'q1', 'and', 'has', 'been', 'widely', 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1,802.07426 | Generalization in Machine Learning via Analytical Learning Theory | This paper introduces a novel measure-theoretic theory for machine learning
that does not require statistical assumptions. Based on this theory, a new
regularization method in deep learning is derived and shown to outperform
previous methods in CIFAR-10, CIFAR-100, and SVHN. Moreover, the proposed
theory provides a theoretical basis for a family of practically successful
regularization methods in deep learning. We discuss several consequences of our
results on one-shot learning, representation learning, deep learning, and
curriculum learning. Unlike statistical learning theory, the proposed learning
theory analyzes each problem instance individually via measure theory, rather
than a set of problem instances via statistics. As a result, it provides
different types of results and insights when compared to statistical learning
theory.
| stat.ML cs.AI cs.LG cs.NE | this paper introduces a novel measuretheoretic theory for machine learning that does not require statistical assumptions based on this theory a new regularization method in deep learning is derived and shown to outperform previous methods in cifar10 cifar100 and svhn moreover the proposed theory provides a theoretical basis for a family of practically successful regularization methods in deep learning we discuss several consequences of our results on oneshot learning representation learning deep learning and curriculum learning unlike statistical learning theory the proposed learning theory analyzes each problem instance individually via measure theory rather than a set of problem instances via statistics as a result it provides different types of results and insights when compared to statistical learning theory | [['this', 'paper', 'introduces', 'a', 'novel', 'measuretheoretic', 'theory', 'for', 'machine', 'learning', 'that', 'does', 'not', 'require', 'statistical', 'assumptions', 'based', 'on', 'this', 'theory', 'a', 'new', 'regularization', 'method', 'in', 'deep', 'learning', 'is', 'derived', 'and', 'shown', 'to', 'outperform', 'previous', 'methods', 'in', 'cifar10', 'cifar100', 'and', 'svhn', 'moreover', 'the', 'proposed', 'theory', 'provides', 'a', 'theoretical', 'basis', 'for', 'a', 'family', 'of', 'practically', 'successful', 'regularization', 'methods', 'in', 'deep', 'learning', 'we', 'discuss', 'several', 'consequences', 'of', 'our', 'results', 'on', 'oneshot', 'learning', 'representation', 'learning', 'deep', 'learning', 'and', 'curriculum', 'learning', 'unlike', 'statistical', 'learning', 'theory', 'the', 'proposed', 'learning', 'theory', 'analyzes', 'each', 'problem', 'instance', 'individually', 'via', 'measure', 'theory', 'rather', 'than', 'a', 'set', 'of', 'problem', 'instances', 'via', 'statistics', 'as', 'a', 'result', 'it', 'provides', 'different', 'types', 'of', 'results', 'and', 'insights', 'when', 'compared', 'to', 'statistical', 'learning', 'theory']] | [0.03141027646656227, -0.021000531601711666, -0.1635113092498475, 0.09282754272739482, -0.12340494605191683, -0.20364222366962645, 0.057029300872473265, 0.3974259578922795, -0.2742342562809334, -0.30917406064789676, 0.03349154645486309, -0.23673896208184503, -0.25363309799014766, 0.257565118396118, -0.1693576229262655, 0.09274856333415639, 0.12397988886627669, 0.05310463427439711, -0.12285976930150479, -0.29455002462807095, 0.31267785822767447, 0.012006921363428187, 0.39303879621359755, 0.046771271300296915, 0.13884617242630634, 0.012671654085013069, -0.011270993491792577, 0.012475491273493143, -0.11316506814644958, 0.22040416247613917, 0.33635388229484275, 0.2454041227208987, 0.4171188382463435, -0.38462596161732987, -0.27814819022886833, 0.0937391523157357, 0.12121156412887119, 0.140842814393089, -0.07173331542201024, -0.3092113484675854, 0.07725181416963559, -0.18309109670630955, 0.02530647521854331, -0.2083880390845618, -0.0733328855880615, -0.053275797259599224, -0.3034675742649489, 0.021324870478503913, 0.09880093136265622, 0.09729025295888216, -0.0795528159705701, -0.16701667225067268, 0.11309865250062766, 0.07252180870643114, 0.051722598899455775, 0.04778966826181543, 0.13539689411882752, -0.17787918233030509, -0.198155747192825, 0.3266630863422583, -0.07393718193054803, -0.21074335376526845, 0.2133016343133808, 0.018211380878494957, -0.22937348201255298, 0.04489709960959726, 0.2259825228760808, 0.15745435086457785, -0.14728513567462284, 0.07094137411035786, -0.07690592106999987, 0.1434431512824307, 0.001902568899884315, 0.009281268256511224, 0.11638403136156879, 0.26912967073612737, 0.029552002259830044, 0.09050245468220594, -0.08230432049347625, -0.1377221810378892, -0.2510138710771324, -0.06891956558782544, -0.2024821732745711, -0.012731206307253776, -0.11330633749149471, -0.15674016894688791, 0.3543675585918255, 0.22971755781574016, 0.1662645223866201, 0.1479056419536345, 0.3256377143690647, 0.04857398689661858, 0.06673833552818997, 0.11046609178607715, 0.235174152589703, 0.10533779278650122, 0.09584567421589489, -0.14762091901453245, 0.05411952083448927, 0.09681723882854616] |
1,802.07427 | Active Learning with Partial Feedback | While many active learning papers assume that the learner can simply ask for
a label and receive it, real annotation often presents a mismatch between the
form of a label (say, one among many classes), and the form of an annotation
(typically yes/no binary feedback). To annotate examples corpora for multiclass
classification, we might need to ask multiple yes/no questions, exploiting a
label hierarchy if one is available. To address this more realistic setting, we
propose active learning with partial feedback (ALPF), where the learner must
actively choose both which example to label and which binary question to ask.
At each step, the learner selects an example, asking if it belongs to a chosen
(possibly composite) class. Each answer eliminates some classes, leaving the
learner with a partial label. The learner may then either ask more questions
about the same example (until an exact label is uncovered) or move on
immediately, leaving the first example partially labeled. Active learning with
partial labels requires (i) a sampling strategy to choose (example, class)
pairs, and (ii) learning from partial labels between rounds. Experiments on
Tiny ImageNet demonstrate that our most effective method improves 26%
(relative) in top-1 classification accuracy compared to i.i.d. baselines and
standard active learners given 30% of the annotation budget that would be
required (naively) to annotate the dataset. Moreover, ALPF-learners fully
annotate TinyImageNet at 42% lower cost. Surprisingly, we observe that
accounting for per-example annotation costs can alter the conventional wisdom
that active learners should solicit labels for hard examples.
| cs.LG | while many active learning papers assume that the learner can simply ask for a label and receive it real annotation often presents a mismatch between the form of a label say one among many classes and the form of an annotation typically yesno binary feedback to annotate examples corpora for multiclass classification we might need to ask multiple yesno questions exploiting a label hierarchy if one is available to address this more realistic setting we propose active learning with partial feedback alpf where the learner must actively choose both which example to label and which binary question to ask at each step the learner selects an example asking if it belongs to a chosen possibly composite class each answer eliminates some classes leaving the learner with a partial label the learner may then either ask more questions about the same example until an exact label is uncovered or move on immediately leaving the first example partially labeled active learning with partial labels requires i a sampling strategy to choose example class pairs and ii learning from partial labels between rounds experiments on tiny imagenet demonstrate that our most effective method improves 26 relative in top1 classification accuracy compared to iid baselines and standard active learners given 30 of the annotation budget that would be required naively to annotate the dataset moreover alpflearners fully annotate tinyimagenet at 42 lower cost surprisingly we observe that accounting for perexample annotation costs can alter the conventional wisdom that active learners should solicit labels for hard examples | [['while', 'many', 'active', 'learning', 'papers', 'assume', 'that', 'the', 'learner', 'can', 'simply', 'ask', 'for', 'a', 'label', 'and', 'receive', 'it', 'real', 'annotation', 'often', 'presents', 'a', 'mismatch', 'between', 'the', 'form', 'of', 'a', 'label', 'say', 'one', 'among', 'many', 'classes', 'and', 'the', 'form', 'of', 'an', 'annotation', 'typically', 'yesno', 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1,802.07428 | Writing and Erasing of Temporal Kerr Cavity Solitons via Intensity
Modulation of the Cavity Driving Field | We experimentally and numerically study the use of intensity modulation for
the controlled addressing of temporal Kerr cavity solitons. Using a coherently
driven fiber ring resonator, we demonstrate that a single temporally broad
intensity modulation pulse applied on the cavity driving field permits
systematic and efficient writing and erasing of ultrashort cavity solitons. We
use numerical simulations based on the mean-field Lugiato-Lefever model to
investigate the addressing dynamics, and present a simple physical description
of the underlying physics.
| physics.optics | we experimentally and numerically study the use of intensity modulation for the controlled addressing of temporal kerr cavity solitons using a coherently driven fiber ring resonator we demonstrate that a single temporally broad intensity modulation pulse applied on the cavity driving field permits systematic and efficient writing and erasing of ultrashort cavity solitons we use numerical simulations based on the meanfield lugiatolefever model to investigate the addressing dynamics and present a simple physical description of the underlying physics | [['we', 'experimentally', 'and', 'numerically', 'study', 'the', 'use', 'of', 'intensity', 'modulation', 'for', 'the', 'controlled', 'addressing', 'of', 'temporal', 'kerr', 'cavity', 'solitons', 'using', 'a', 'coherently', 'driven', 'fiber', 'ring', 'resonator', 'we', 'demonstrate', 'that', 'a', 'single', 'temporally', 'broad', 'intensity', 'modulation', 'pulse', 'applied', 'on', 'the', 'cavity', 'driving', 'field', 'permits', 'systematic', 'and', 'efficient', 'writing', 'and', 'erasing', 'of', 'ultrashort', 'cavity', 'solitons', 'we', 'use', 'numerical', 'simulations', 'based', 'on', 'the', 'meanfield', 'lugiatolefever', 'model', 'to', 'investigate', 'the', 'addressing', 'dynamics', 'and', 'present', 'a', 'simple', 'physical', 'description', 'of', 'the', 'underlying', 'physics']] | [-0.17915712892621136, 0.10607722786386521, -0.07840570142397131, 0.031192121609376792, -0.07213397863774727, -0.15945324664099667, 0.037439840130854204, 0.4879718369637162, -0.25608425783829236, -0.2250712941854428, 0.05247958298199452, -0.17731322353789344, -0.13161574434250212, 0.25060899341061044, 0.011469666307302525, 0.056251109625475526, 0.024042444061846115, -0.05770221706002186, 0.009392510720480902, -0.12532874519148698, 0.2995776572169211, 0.05960555334026233, 0.31365163718612915, 0.013031055350811819, 0.15823948766606358, 0.038655311693079196, -0.008170060885067169, -0.03261123586875888, -0.18192773431478715, 0.12055076402015029, 0.17556546188783473, 0.034705258798427306, 0.2629279494643785, -0.48422995277752096, -0.26528474741066116, 0.024100925021160107, 0.18390210645082286, 0.19909908210572141, -0.12147057198961146, -0.307651115127672, -0.0032265370663924096, -0.1421565544576599, -0.14247393051090723, -0.1277356535130634, -0.007634580641304358, 0.08328740124423535, -0.23558066741754422, 0.025136109238538224, 0.043404873162030407, 0.09137283283500718, -0.03726194770887303, 0.0713172769651581, 0.025582389738888312, 0.04633702176700657, -0.06557483470980795, -0.030432751244053435, 0.17823947597748768, -0.1203240950544102, -0.1262363326879075, 0.3724118188644449, -0.14626942468711582, -0.15982589135185266, 0.1454869529011492, -0.14851476840125635, 0.003976207727996202, 0.1203422972586197, 0.19687862762620148, 0.1293367909697386, -0.1086526267373791, 0.0074297069983843425, -0.0077269203148973295, 0.29600298712746453, 0.12575459375213355, 0.06332428579648527, 0.2295769473346762, 0.23511263857094142, -0.027404865733189628, 0.19375100593345287, -0.11447026266847761, -0.1371189177645227, -0.2867873835449035, -0.05693577621908238, -0.1467133573232553, 0.05569152833702855, -0.06473911133854507, -0.12230511930568191, 0.4946314894522612, 0.18371538996983033, 0.13317929160518524, -0.03301674491749742, 0.32091613148506254, 0.15540857648384424, 0.00460751333202307, 0.020116415477763765, 0.26833193284722096, 0.1825326404725321, 0.09549371128042157, -0.32373359391035944, -0.05872667042347483, 0.011610815635858437] |
1,802.07429 | PABO: Mitigating Congestion via Packet Bounce in Data Center Networks | In today's data center, a diverse mix of throughput-sensitive long flows and
delay-sensitive short flows are commonly presented in shallow-buffered
switches. Long flows could potentially block the transmission of
delay-sensitive short flows, leading to degraded performance. Congestion can
also be caused by the synchronization of multiple TCP connections for short
flows, as typically seen in the partition/aggregate traffic pattern. While
multiple end-to-end transport-layer solutions have been proposed, none of them
have tackled the real challenge: reliable transmission in the network. In this
paper, we fill this gap by presenting PABO -- a novel link-layer design that
can mitigate congestion by temporarily bouncing packets to upstream switches.
PABO's design fulfills the following goals: i) providing per-flow based flow
control on the link layer, ii) handling transient congestion without the
intervention of end devices, and iii) gradually back propagating the congestion
signal to the source when the network is not capable to handle the
congestion.Experiment results show that PABO can provide prominent advantage of
mitigating transient congestions and can achieve significant gain on end-to-end
delay.
| cs.NI | in todays data center a diverse mix of throughputsensitive long flows and delaysensitive short flows are commonly presented in shallowbuffered switches long flows could potentially block the transmission of delaysensitive short flows leading to degraded performance congestion can also be caused by the synchronization of multiple tcp connections for short flows as typically seen in the partitionaggregate traffic pattern while multiple endtoend transportlayer solutions have been proposed none of them have tackled the real challenge reliable transmission in the network in this paper we fill this gap by presenting pabo a novel linklayer design that can mitigate congestion by temporarily bouncing packets to upstream switches pabos design fulfills the following goals i providing perflow based flow control on the link layer ii handling transient congestion without the intervention of end devices and iii gradually back propagating the congestion signal to the source when the network is not capable to handle the congestionexperiment results show that pabo can provide prominent advantage of mitigating transient congestions and can achieve significant gain on endtoend delay | [['in', 'todays', 'data', 'center', 'a', 'diverse', 'mix', 'of', 'throughputsensitive', 'long', 'flows', 'and', 'delaysensitive', 'short', 'flows', 'are', 'commonly', 'presented', 'in', 'shallowbuffered', 'switches', 'long', 'flows', 'could', 'potentially', 'block', 'the', 'transmission', 'of', 'delaysensitive', 'short', 'flows', 'leading', 'to', 'degraded', 'performance', 'congestion', 'can', 'also', 'be', 'caused', 'by', 'the', 'synchronization', 'of', 'multiple', 'tcp', 'connections', 'for', 'short', 'flows', 'as', 'typically', 'seen', 'in', 'the', 'partitionaggregate', 'traffic', 'pattern', 'while', 'multiple', 'endtoend', 'transportlayer', 'solutions', 'have', 'been', 'proposed', 'none', 'of', 'them', 'have', 'tackled', 'the', 'real', 'challenge', 'reliable', 'transmission', 'in', 'the', 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1,802.0743 | Extreme conditions in the molecular gas of lensed star-forming galaxies
at z~3 | Atomic Carbon can be an efficient tracer of the molecular gas mass, and when
combined to the detection of high-J and low-J CO lines it yields also a
sensitive probe of the power sources in the molecular gas of high redshift
galaxies. The recently installed SEPIA5 receiver at the focus of the APEX
telescope has opened up a new window at frequencies 159 - 211 GHz allowing the
exploration of the Atomic Carbon in high-z galaxies, at previously inaccessible
frequencies from the ground. We have targeted three gravitationally lensed
galaxies at redshift of about 3 and conducted a comparative study of the
observed high-J CO/CI ~ratios with well-studied nearby galaxies. Atomic Carbon
(CI(2-1)) was detected in one of the three targets and marginally in a second,
while in all three targets the $J=7\to6$ CO line is detected. The
CO(7-6)/CI(2-1), CO(7-6)/CO(1-0) line ratios and the CO(7-6)/(far-IR continuum)
luminosity ratio are compared to those of nearby objects. A large excitation
status in the ISM of these high-z objects is seen, unless differential lensing
unevenly boosts the CO line fluxes from the warm and dense gas more than the
CO(1-0), CI(2-1), tracing a more widely distributed cold gas phase. We provide
estimates of total molecular gas masses derived from the atomic Carbon and the
Carbon monoxide CO(1-0), which within the uncertainties turn out to be equal.
| astro-ph.GA astro-ph.CO | atomic carbon can be an efficient tracer of the molecular gas mass and when combined to the detection of highj and lowj co lines it yields also a sensitive probe of the power sources in the molecular gas of high redshift galaxies the recently installed sepia5 receiver at the focus of the apex telescope has opened up a new window at frequencies 159 211 ghz allowing the exploration of the atomic carbon in highz galaxies at previously inaccessible frequencies from the ground we have targeted three gravitationally lensed galaxies at redshift of about 3 and conducted a comparative study of the observed highj coci ratios with wellstudied nearby galaxies atomic carbon ci21 was detected in one of the three targets and marginally in a second while in all three targets the j7to6 co line is detected the co76ci21 co76co10 line ratios and the co76farir continuum luminosity ratio are compared to those of nearby objects a large excitation status in the ism of these highz objects is seen unless differential lensing unevenly boosts the co line fluxes from the warm and dense gas more than the co10 ci21 tracing a more widely distributed cold gas phase we provide estimates of total molecular gas masses derived from the atomic carbon and the carbon monoxide co10 which within the uncertainties turn out to be equal | [['atomic', 'carbon', 'can', 'be', 'an', 'efficient', 'tracer', 'of', 'the', 'molecular', 'gas', 'mass', 'and', 'when', 'combined', 'to', 'the', 'detection', 'of', 'highj', 'and', 'lowj', 'co', 'lines', 'it', 'yields', 'also', 'a', 'sensitive', 'probe', 'of', 'the', 'power', 'sources', 'in', 'the', 'molecular', 'gas', 'of', 'high', 'redshift', 'galaxies', 'the', 'recently', 'installed', 'sepia5', 'receiver', 'at', 'the', 'focus', 'of', 'the', 'apex', 'telescope', 'has', 'opened', 'up', 'a', 'new', 'window', 'at', 'frequencies', '159', '211', 'ghz', 'allowing', 'the', 'exploration', 'of', 'the', 'atomic', 'carbon', 'in', 'highz', 'galaxies', 'at', 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1,802.07431 | Monitoring spin coherence of single nitrogen-vacancy centers in
nanodiamonds during pH changes in aqueous buffer solutions | We report on sensing stability of nanodiamond (ND) quantum sensors in various
pH aqueous buffer solutions for the two detection schemes of quantum
decoherence spectroscopy and thermometry. The electron spin properties of
single nitrogen-vacancy (NV) centers in 25-nm-sized NDs have been characterized
by a spin-measurement compatible perfusion (SMCP) chamber where observing the
same individual NDs in different buffer solutions is possible. With this
system, we have determined the stability of the NV quantum sensors during the
pH change from 4 to 11 as the fluctuations of +- 12% and +- 0.2 MHz for the
spin coherence time ($T_2$) and the resonance frequency ($\omega_0$) of their
mean values, which are comparable to the instrumental error of the measurement
system. Here, we discuss the importance of characterizing the sensing stability
during pH changes and how the present observations affect ND-based NV quantum
sensing.
| cond-mat.mes-hall quant-ph | we report on sensing stability of nanodiamond nd quantum sensors in various ph aqueous buffer solutions for the two detection schemes of quantum decoherence spectroscopy and thermometry the electron spin properties of single nitrogenvacancy nv centers in 25nmsized nds have been characterized by a spinmeasurement compatible perfusion smcp chamber where observing the same individual nds in different buffer solutions is possible with this system we have determined the stability of the nv quantum sensors during the ph change from 4 to 11 as the fluctuations of 12 and 02 mhz for the spin coherence time t_2 and the resonance frequency omega_0 of their mean values which are comparable to the instrumental error of the measurement system here we discuss the importance of characterizing the sensing stability during ph changes and how the present observations affect ndbased nv quantum sensing | [['we', 'report', 'on', 'sensing', 'stability', 'of', 'nanodiamond', 'nd', 'quantum', 'sensors', 'in', 'various', 'ph', 'aqueous', 'buffer', 'solutions', 'for', 'the', 'two', 'detection', 'schemes', 'of', 'quantum', 'decoherence', 'spectroscopy', 'and', 'thermometry', 'the', 'electron', 'spin', 'properties', 'of', 'single', 'nitrogenvacancy', 'nv', 'centers', 'in', '25nmsized', 'nds', 'have', 'been', 'characterized', 'by', 'a', 'spinmeasurement', 'compatible', 'perfusion', 'smcp', 'chamber', 'where', 'observing', 'the', 'same', 'individual', 'nds', 'in', 'different', 'buffer', 'solutions', 'is', 'possible', 'with', 'this', 'system', 'we', 'have', 'determined', 'the', 'stability', 'of', 'the', 'nv', 'quantum', 'sensors', 'during', 'the', 'ph', 'change', 'from', '4', 'to', '11', 'as', 'the', 'fluctuations', 'of', '12', 'and', '02', 'mhz', 'for', 'the', 'spin', 'coherence', 'time', 't_2', 'and', 'the', 'resonance', 'frequency', 'omega_0', 'of', 'their', 'mean', 'values', 'which', 'are', 'comparable', 'to', 'the', 'instrumental', 'error', 'of', 'the', 'measurement', 'system', 'here', 'we', 'discuss', 'the', 'importance', 'of', 'characterizing', 'the', 'sensing', 'stability', 'during', 'ph', 'changes', 'and', 'how', 'the', 'present', 'observations', 'affect', 'ndbased', 'nv', 'quantum', 'sensing']] | [-0.1134205861543951, 0.17702250507231937, -0.009231734674179206, -0.040372237855446164, 0.0819368337920058, -0.14842430516112134, 0.06037295428036719, 0.42099278635025894, -0.24649759843931907, -0.29963189921253464, 0.1302426577567796, -0.3068572634994222, -0.05342157406011855, 0.18088653609734437, -0.05214686115292737, 0.09802415269101124, 0.022374740281706527, 0.04325276191761024, -0.05774351515268472, -0.18985441666993783, 0.22369627206565906, 0.05505345729485589, 0.3137417388969461, 0.05963587318292146, 0.13274787134664257, 0.007040026853027597, 0.05013805914697421, -0.01821288930330371, -0.14212524371534369, 0.10660351328786512, 0.26468789339555004, 0.07507213911748607, 0.2289683943763919, -0.42938801763837575, -0.21211249584903138, 0.08262867216160182, 0.13763592806542768, 0.14891232185432837, -0.07524947414300438, -0.30664647412724305, 0.07723626575473505, -0.12529159163211534, -0.097399954871023, -0.04012866322304646, 0.0008970750291852186, 0.04790800532162951, -0.19205260893370765, 0.09611668004688338, 0.021218611923365913, 0.11232515923461339, -0.1296444444434486, -0.09816626016642001, 0.011411152367928766, 0.13550796887257824, -0.022596374658840526, -0.02339590957014818, 0.27138788902275535, -0.10947395836676124, -0.13023701484865732, 0.33809447204218296, -0.06356340388080826, -0.12584147959617034, 0.17361296584530578, -0.1828446671278318, -0.10129406153781842, 0.11490886827529728, 0.12711271806110214, 0.12856671746045242, -0.15900613290995333, 0.05943726520495911, 0.04887145428525719, 0.20308890793622084, 0.09632739656176555, 0.1399324832783237, 0.18489008688836964, 0.16522433183896934, 0.08023642484492956, 0.11225446348629185, -0.17384814487151584, -0.04852581497861317, -0.21254071635602, -0.17703974506151557, -0.1849964359081792, 0.09768617042020833, -0.09546010498676354, -0.09475292670574502, 0.4139439207875598, 0.1666602876910899, 0.17921201888315488, -0.04733860459651145, 0.2723337533156367, 0.08655642468845948, 0.05263885964102445, -0.027714171518238573, 0.26968454315333906, 0.17283103508487288, 0.12453364556906812, -0.3616704360673707, 0.043748741265875794, -0.04466946056982788] |
1,802.07432 | Enhanced global signal of neutral hydrogen due to excess radiation at
cosmic dawn | We revisit the global 21cm signal calculation incorporating a possible radio
background at early times, and find that the global 21cm signal shows a much
stronger absorption feature, which could enhance detection prospects for future
21 cm experiments. In light of recent reports of a possible low-frequency
excess radio background, we propose that detailed 21 cm calculations should
include a possible early radio background.
| astro-ph.CO | we revisit the global 21cm signal calculation incorporating a possible radio background at early times and find that the global 21cm signal shows a much stronger absorption feature which could enhance detection prospects for future 21 cm experiments in light of recent reports of a possible lowfrequency excess radio background we propose that detailed 21 cm calculations should include a possible early radio background | [['we', 'revisit', 'the', 'global', '21cm', 'signal', 'calculation', 'incorporating', 'a', 'possible', 'radio', 'background', 'at', 'early', 'times', 'and', 'find', 'that', 'the', 'global', '21cm', 'signal', 'shows', 'a', 'much', 'stronger', 'absorption', 'feature', 'which', 'could', 'enhance', 'detection', 'prospects', 'for', 'future', '21', 'cm', 'experiments', 'in', 'light', 'of', 'recent', 'reports', 'of', 'a', 'possible', 'lowfrequency', 'excess', 'radio', 'background', 'we', 'propose', 'that', 'detailed', '21', 'cm', 'calculations', 'should', 'include', 'a', 'possible', 'early', 'radio', 'background']] | [-0.1181583465076983, 0.07130368610160076, -0.03397913397202501, 0.07852283896500012, -0.10844856343464926, -0.09296214977803174, 0.03433725718059577, 0.398926546680741, -0.1380586056111497, -0.28311211922118673, 0.10773087292000127, -0.29897265848558163, -0.14358416536924778, 0.17578114643038134, 0.0626499661084381, 0.0015755648928461596, 0.03317765425708785, -0.06182750393054448, -0.08116674575558136, -0.17921029248827836, 0.19813183063524775, 0.21681846241699532, 0.2876789726433344, 0.08366640485473908, 0.04630507045658305, -0.04602867904759478, -0.20718100311933085, -0.014646994110080414, -0.0602567435569199, 0.06456584340776317, 0.26730272793065524, 0.2028117160371039, 0.1521607627873891, -0.4459377844905248, -0.3083364014601102, 0.18164175890706247, 0.15991237090929644, 0.16476848576530756, -0.09593455112189986, -0.29369153486914, 0.09493366074730147, -0.16611641793861054, -0.14014497238531476, 0.020479670256463578, 0.04720414421899477, -0.05956727468583267, -0.24482521721802186, 0.10476511773231323, 0.014932292826415505, 0.04432765058561472, -0.05981740154675208, -0.12743237771792337, 0.041000459481438156, 0.025846705815638416, 0.006893067737109959, 0.06650159605851513, 0.2070388520587585, -0.14653944788733497, -0.13696472182346042, 0.38276470702840015, -0.17996416056121234, 0.014344379218528047, 0.1925039746274706, -0.21102712251013145, -0.22559367975918576, 0.18361008938518353, 0.1953875719300413, 0.03189195503364317, -0.11881615540551138, 0.018552189793808793, 0.004103409795789048, 0.23812012441339903, 0.042926649937726324, 0.0846105979726417, 0.3427576928952476, 0.1519413535716012, 0.07437462799134664, 0.10859231202630326, -0.2278260258044611, 0.07757879362634412, -0.2978899840381928, -0.06995476772135589, -0.06794334402729874, 0.14332056581042707, -0.08500446764787739, -0.05024763641995378, 0.4191752522601746, 0.19928613933734596, 0.1857127810358179, 0.030972471375207533, 0.3444013697153423, 0.07119411620078608, 0.019856952218106017, 0.03227304838219425, 0.3624357550870627, 0.07615307410014793, 0.14745250256964937, -0.18051474563981174, -0.010977647221807274, -0.04855289715487743] |
1,802.07433 | Static-Memory-Hard Functions and Nonlinear Space-Time Tradeoffs via
Pebbling | Pebble games were originally formulated to study time-space tradeoffs in
computation, modeled by games played on directed acyclic graphs (DAGs). Close
connections between pebbling and cryptography have been known for decades. A
series of recent research starting with (Alwen and Serbinenko, STOC 2015) has
deepened our understanding of the notion of memory-hardness in cryptography ---
a useful property of hash functions for deterring large-scale password-cracking
attacks --- and has shown memory-hardness to have intricate connections with
the theory of graph pebbling.
In this work, we improve upon two main limitations of existing models of
memory-hardness. First, existing measures of memory-hardness only account for
dynamic (i.e., runtime) memory usage, and do not consider static memory usage.
We propose a new definition of static-memory-hard function (SHF) which takes
into account static memory usage and allows the formalization of larger memory
requirements for efficient functions, than in the dynamic setting (where memory
usage is inherently bounded by runtime). We then give two SHF constructions
based on pebbling; to prove static-memory-hardness, we define a new pebble game
("black-magic pebble game"), and new graph constructions with optimal
complexity under our proposed measure.
Secondly, existing memory-hardness models implicitly consider linear
tradeoffs between the costs of time and space. We propose a new model to
capture nonlinear time-space trade-offs and prove that nonlinear tradeoffs can
in fact cause adversaries to employ different strategies from linear tradeoffs.
Finally, as an additional contribution of independent interest, we present
the first asymptotically tight graph construction that achieves the best
possible space complexity up to $\log{\log{n}}$-factors for an existing
memory-hardness measure called cumulative complexity in the sequential pebbling
model.
| cs.CR cs.CC | pebble games were originally formulated to study timespace tradeoffs in computation modeled by games played on directed acyclic graphs dags close connections between pebbling and cryptography have been known for decades a series of recent research starting with alwen and serbinenko stoc 2015 has deepened our understanding of the notion of memoryhardness in cryptography a useful property of hash functions for deterring largescale passwordcracking attacks and has shown memoryhardness to have intricate connections with the theory of graph pebbling in this work we improve upon two main limitations of existing models of memoryhardness first existing measures of memoryhardness only account for dynamic ie runtime memory usage and do not consider static memory usage we propose a new definition of staticmemoryhard function shf which takes into account static memory usage and allows the formalization of larger memory requirements for efficient functions than in the dynamic setting where memory usage is inherently bounded by runtime we then give two shf constructions based on pebbling to prove staticmemoryhardness we define a new pebble game blackmagic pebble game and new graph constructions with optimal complexity under our proposed measure secondly existing memoryhardness models implicitly consider linear tradeoffs between the costs of time and space we propose a new model to capture nonlinear timespace tradeoffs and prove that nonlinear tradeoffs can in fact cause adversaries to employ different strategies from linear tradeoffs finally as an additional contribution of independent interest we present the first asymptotically tight graph construction that achieves the best possible space complexity up to loglognfactors for an existing memoryhardness measure called cumulative complexity in the sequential pebbling model | [['pebble', 'games', 'were', 'originally', 'formulated', 'to', 'study', 'timespace', 'tradeoffs', 'in', 'computation', 'modeled', 'by', 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1,802.07434 | Nonparametric Bayesian Sparse Graph Linear Dynamical Systems | A nonparametric Bayesian sparse graph linear dynamical system (SGLDS) is
proposed to model sequentially observed multivariate data. SGLDS uses the
Bernoulli-Poisson link together with a gamma process to generate an infinite
dimensional sparse random graph to model state transitions. Depending on the
sparsity pattern of the corresponding row and column of the graph affinity
matrix, a latent state of SGLDS can be categorized as either a non-dynamic
state or a dynamic one. A normal-gamma construction is used to shrink the
energy captured by the non-dynamic states, while the dynamic states can be
further categorized into live, absorbing, or noise-injection states, which
capture different types of dynamical components of the underlying time series.
The state-of-the-art performance of SGLDS is demonstrated with experiments on
both synthetic and real data.
| stat.ML stat.ME | a nonparametric bayesian sparse graph linear dynamical system sglds is proposed to model sequentially observed multivariate data sglds uses the bernoullipoisson link together with a gamma process to generate an infinite dimensional sparse random graph to model state transitions depending on the sparsity pattern of the corresponding row and column of the graph affinity matrix a latent state of sglds can be categorized as either a nondynamic state or a dynamic one a normalgamma construction is used to shrink the energy captured by the nondynamic states while the dynamic states can be further categorized into live absorbing or noiseinjection states which capture different types of dynamical components of the underlying time series the stateoftheart performance of sglds is demonstrated with experiments on both synthetic and real data | [['a', 'nonparametric', 'bayesian', 'sparse', 'graph', 'linear', 'dynamical', 'system', 'sglds', 'is', 'proposed', 'to', 'model', 'sequentially', 'observed', 'multivariate', 'data', 'sglds', 'uses', 'the', 'bernoullipoisson', 'link', 'together', 'with', 'a', 'gamma', 'process', 'to', 'generate', 'an', 'infinite', 'dimensional', 'sparse', 'random', 'graph', 'to', 'model', 'state', 'transitions', 'depending', 'on', 'the', 'sparsity', 'pattern', 'of', 'the', 'corresponding', 'row', 'and', 'column', 'of', 'the', 'graph', 'affinity', 'matrix', 'a', 'latent', 'state', 'of', 'sglds', 'can', 'be', 'categorized', 'as', 'either', 'a', 'nondynamic', 'state', 'or', 'a', 'dynamic', 'one', 'a', 'normalgamma', 'construction', 'is', 'used', 'to', 'shrink', 'the', 'energy', 'captured', 'by', 'the', 'nondynamic', 'states', 'while', 'the', 'dynamic', 'states', 'can', 'be', 'further', 'categorized', 'into', 'live', 'absorbing', 'or', 'noiseinjection', 'states', 'which', 'capture', 'different', 'types', 'of', 'dynamical', 'components', 'of', 'the', 'underlying', 'time', 'series', 'the', 'stateoftheart', 'performance', 'of', 'sglds', 'is', 'demonstrated', 'with', 'experiments', 'on', 'both', 'synthetic', 'and', 'real', 'data']] | [-0.07346480157167658, 0.12433617421085341, -0.0909396995914968, 0.045595698349715115, -0.08960036858989615, -0.1634872057676814, 0.048250904438767846, 0.3822502325193619, -0.3101180713095768, -0.28432137424522264, 0.1261836896232498, -0.2607077627816773, -0.1180163846079876, 0.11905855711505521, -0.03032925042991094, 0.07882871458262909, 0.07189838358340418, 0.07328323411799263, -0.04971634138991514, -0.2256847245022416, 0.30334700080639443, 0.022863933655220693, 0.2847550848982935, -0.034029212153304046, 0.12280931273717287, 0.011980358349878019, -0.02552194829560875, 0.040550016552415184, -0.03288119112134097, 0.10232808365620394, 0.2734434330674607, 0.1569270837949369, 0.24436573852880264, -0.4324972370096783, -0.24861812965342167, 0.11058350389742652, 0.09660777385075262, 0.05354393687278883, 0.011300856592206974, -0.34739715619174044, 0.05494461881040823, -0.16769636686392655, -0.047884713511870014, -0.09622647563604213, -0.03556974990088053, 0.004718941496135154, -0.33023821802692505, 0.06820628371669024, 0.056876845584034656, 0.0042485382085240735, -0.0443816143583037, -0.12543851672030076, -0.04893674989282264, 0.12324171259405282, -0.00499944001075071, 0.006511755476478399, 0.11964920853946621, -0.09566429020374267, -0.16778009787465878, 0.33910429017163635, -0.05818454093688468, -0.19714876628062855, 0.20957806548763683, -0.0689453345276122, -0.1187429705939043, 0.1495844959446383, 0.22348059415010604, 0.059722909007192126, -0.12167942551089318, 0.045544874082561436, -0.05856796008659395, 0.203424961225489, 0.01905318501581416, -0.020475043148887675, 0.17447349269449067, 0.18123439884942583, 0.053784445277816256, 0.14545035371226883, -0.09386735670195204, -0.09882664141853846, -0.21153523891020243, -0.1197431946164602, -0.23076179603437388, 9.884711127640225e-05, -0.13825022833186704, -0.20110802523293128, 0.44642565205810575, 0.08735234414797467, 0.25042125884091526, 0.03767988907895601, 0.287450163427183, 0.11482877939789167, 0.04639238991048627, 0.0681382247547465, 0.1179795088429796, 0.12186992587338341, 0.039854342277403774, -0.18076726546012392, 0.1107250007408429, 0.0592952410353157] |
1,802.07435 | Playing with Repetitions in Data Words Using Energy Games | We introduce two-player games which build words over infinite alphabets, and
we study the problem of checking the existence of winning strategies. These
games are played by two players, who take turns in choosing valuations for
variables ranging over an infinite data domain, thus generating
multi-attributed data words. The winner of the game is specified by formulas in
the Logic of Repeating Values, which can reason about repetitions of data
values in infinite data words. We prove that it is undecidable to check if one
of the players has a winning strategy, even in very restrictive settings.
However, we prove that if one of the players is restricted to choose valuations
ranging over the Boolean domain, the games are effectively equivalent to
single-sided games on vector addition systems with states (in which one of the
players can change control states but cannot change counter values), known to
be decidable and effectively equivalent to energy games.
Previous works have shown that the satisfiability problem for various
variants of the logic of repeating values is equivalent to the reachability and
coverability problems in vector addition systems. Our results raise this
connection to the level of games, augmenting further the associations between
logics on data words and counter systems.
| cs.LO | we introduce twoplayer games which build words over infinite alphabets and we study the problem of checking the existence of winning strategies these games are played by two players who take turns in choosing valuations for variables ranging over an infinite data domain thus generating multiattributed data words the winner of the game is specified by formulas in the logic of repeating values which can reason about repetitions of data values in infinite data words we prove that it is undecidable to check if one of the players has a winning strategy even in very restrictive settings however we prove that if one of the players is restricted to choose valuations ranging over the boolean domain the games are effectively equivalent to singlesided games on vector addition systems with states in which one of the players can change control states but cannot change counter values known to be decidable and effectively equivalent to energy games previous works have shown that the satisfiability problem for various variants of the logic of repeating values is equivalent to the reachability and coverability problems in vector addition systems our results raise this connection to the level of games augmenting further the associations between logics on data words and counter systems | [['we', 'introduce', 'twoplayer', 'games', 'which', 'build', 'words', 'over', 'infinite', 'alphabets', 'and', 'we', 'study', 'the', 'problem', 'of', 'checking', 'the', 'existence', 'of', 'winning', 'strategies', 'these', 'games', 'are', 'played', 'by', 'two', 'players', 'who', 'take', 'turns', 'in', 'choosing', 'valuations', 'for', 'variables', 'ranging', 'over', 'an', 'infinite', 'data', 'domain', 'thus', 'generating', 'multiattributed', 'data', 'words', 'the', 'winner', 'of', 'the', 'game', 'is', 'specified', 'by', 'formulas', 'in', 'the', 'logic', 'of', 'repeating', 'values', 'which', 'can', 'reason', 'about', 'repetitions', 'of', 'data', 'values', 'in', 'infinite', 'data', 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1,802.07436 | Time-resolved optical emission spectroscopic studies of picosecond laser
produced Cr plasma | Time-resolved optical emission spectroscopic measurements of a plasma
generated by irradiating a Cr target using 60 picosecond (ps) and 300 ps laser
pulses is carried out to investigate the variation in the linewidth
($\delta\lambda$) of emission from neutrals and ions for increasing ambient
pressures. Measurements ranging from 10$^{-6}$ Torr to 10$^2$ Torr show a
distinctly different variation in the $\delta\lambda$ of neutrals (Cr I)
compared to that of singly ionized Cr (Cr II), for both irradiations.
$\delta\lambda$ increases monotonously with pressure for Cr II, but an
oscillation is evident at intermediate pressures for Cr I. This oscillation
does not depend on the laser pulse widths used. In spite of the differences in
the plasma formation mechanisms, it is experimentally found that there is an
optimum intermediate background pressure for which $\delta\lambda$ of neutrals
drops to a minimum. Importantly, these results underline the fact that for
intermediate pressures, the usual practice of calculating the plasma number
density from the $\delta\lambda$ of neutrals needs to be judiciously done, to
avoid reaching inaccurate conclusions.
| physics.plasm-ph | timeresolved optical emission spectroscopic measurements of a plasma generated by irradiating a cr target using 60 picosecond ps and 300 ps laser pulses is carried out to investigate the variation in the linewidth deltalambda of emission from neutrals and ions for increasing ambient pressures measurements ranging from 106 torr to 102 torr show a distinctly different variation in the deltalambda of neutrals cr i compared to that of singly ionized cr cr ii for both irradiations deltalambda increases monotonously with pressure for cr ii but an oscillation is evident at intermediate pressures for cr i this oscillation does not depend on the laser pulse widths used in spite of the differences in the plasma formation mechanisms it is experimentally found that there is an optimum intermediate background pressure for which deltalambda of neutrals drops to a minimum importantly these results underline the fact that for intermediate pressures the usual practice of calculating the plasma number density from the deltalambda of neutrals needs to be judiciously done to avoid reaching inaccurate conclusions | [['timeresolved', 'optical', 'emission', 'spectroscopic', 'measurements', 'of', 'a', 'plasma', 'generated', 'by', 'irradiating', 'a', 'cr', 'target', 'using', '60', 'picosecond', 'ps', 'and', '300', 'ps', 'laser', 'pulses', 'is', 'carried', 'out', 'to', 'investigate', 'the', 'variation', 'in', 'the', 'linewidth', 'deltalambda', 'of', 'emission', 'from', 'neutrals', 'and', 'ions', 'for', 'increasing', 'ambient', 'pressures', 'measurements', 'ranging', 'from', '106', 'torr', 'to', '102', 'torr', 'show', 'a', 'distinctly', 'different', 'variation', 'in', 'the', 'deltalambda', 'of', 'neutrals', 'cr', 'i', 'compared', 'to', 'that', 'of', 'singly', 'ionized', 'cr', 'cr', 'ii', 'for', 'both', 'irradiations', 'deltalambda', 'increases', 'monotonously', 'with', 'pressure', 'for', 'cr', 'ii', 'but', 'an', 'oscillation', 'is', 'evident', 'at', 'intermediate', 'pressures', 'for', 'cr', 'i', 'this', 'oscillation', 'does', 'not', 'depend', 'on', 'the', 'laser', 'pulse', 'widths', 'used', 'in', 'spite', 'of', 'the', 'differences', 'in', 'the', 'plasma', 'formation', 'mechanisms', 'it', 'is', 'experimentally', 'found', 'that', 'there', 'is', 'an', 'optimum', 'intermediate', 'background', 'pressure', 'for', 'which', 'deltalambda', 'of', 'neutrals', 'drops', 'to', 'a', 'minimum', 'importantly', 'these', 'results', 'underline', 'the', 'fact', 'that', 'for', 'intermediate', 'pressures', 'the', 'usual', 'practice', 'of', 'calculating', 'the', 'plasma', 'number', 'density', 'from', 'the', 'deltalambda', 'of', 'neutrals', 'needs', 'to', 'be', 'judiciously', 'done', 'to', 'avoid', 'reaching', 'inaccurate', 'conclusions']] | [-0.0757095143825295, 0.21685272668864802, -0.00040734462625189135, 0.0412711649336607, 0.03424162096861336, -0.1483551009356627, 0.05657292773255436, 0.43750314672248797, -0.24363848561154167, -0.3147717050293036, 0.006439115678515742, -0.30973858673435944, 0.03321426132781028, 0.19060524587372416, 0.018993979210663064, -0.03550077301357486, 0.02638021765728835, -0.038161923504320155, -0.06833635089368892, -0.161224274727249, 0.2671585261211758, 0.1307054769509194, 0.2745288435631154, 0.10432443428751931, 0.06403512725189917, -0.08189988778141594, -0.01128499657841541, 0.0300513638873797, -0.1270851687111974, 0.03789483905601048, 0.2499143683463226, 0.08083013811540839, 0.22245153937793788, -0.4111332034376281, -0.2570586556743024, 0.03499065852745801, 0.163280255411757, 0.09691657871620632, -0.06853037442241343, -0.2151520420233474, 0.09023407023476317, -0.13065764272778857, -0.12470712046219276, 0.01895662666331127, 0.05119744297225921, 0.057459812078281845, -0.30237063518262397, 0.08248776287842564, 0.012013474608668022, 0.09211319579323482, -0.09972002677914239, -0.12432224061734952, -0.05014446616133305, 0.03518648789405866, 0.06631257785456963, 0.039186351545895746, 0.22214152787305547, -0.06983194643854877, 0.004015583931659049, 0.38481826642364786, -0.09910788081793322, -0.05666577903695448, 0.1914523319730655, -0.20508628591148956, -0.0658644417633387, 0.2666269566844032, 0.11736828531410916, 0.1018070049191776, -0.10221766151095692, 0.011222132630727924, 0.020960502023536342, 0.24057176676497125, 0.14464004943419617, 0.01856886485744028, 0.16275032367952147, 0.10648698123833655, 0.04481368236943578, 0.07127745298339239, -0.1395440473594316, 0.013485157764271685, -0.24637259299031525, -0.13418437893181082, -0.1366120235645893, 0.092757795971484, -0.05338082955969765, -0.10571827490035204, 0.35995611843070263, 0.14655723101976845, 0.19419207140988512, -0.04322320226598967, 0.28538819441669866, 0.09209617663430845, 0.02269093177079806, 0.078783031190849, 0.30292023716178557, 0.1739277000721457, 0.1610244322481037, -0.28906316216013866, 0.05500314002094126, -0.05483074476316092] |
1,802.07437 | Binary Constrained Deep Hashing Network for Image Retrieval without
Manual Annotation | Learning compact binary codes for image retrieval task using deep neural
networks has attracted increasing attention recently. However, training deep
hashing networks for the task is challenging due to the binary constraints on
the hash codes, the similarity preserving property, and the requirement for a
vast amount of labelled images. To the best of our knowledge, none of the
existing methods has tackled all of these challenges completely in a unified
framework. In this work, we propose a novel end-to-end deep learning approach
for the task, in which the network is trained to produce binary codes directly
from image pixels without the need of manual annotation. In particular, to deal
with the non-smoothness of binary constraints, we propose a novel pairwise
constrained loss function, which simultaneously encodes the distances between
pairs of hash codes, and the binary quantization error. In order to train the
network with the proposed loss function, we propose an efficient parameter
learning algorithm. In addition, to provide similar / dissimilar training
images to train the network, we exploit 3D models reconstructed from unlabelled
images for automatic generation of enormous training image pairs. The extensive
experiments on image retrieval benchmark datasets demonstrate the improvements
of the proposed method over the state-of-the-art compact representation methods
on the image retrieval problem.
| cs.CV | learning compact binary codes for image retrieval task using deep neural networks has attracted increasing attention recently however training deep hashing networks for the task is challenging due to the binary constraints on the hash codes the similarity preserving property and the requirement for a vast amount of labelled images to the best of our knowledge none of the existing methods has tackled all of these challenges completely in a unified framework in this work we propose a novel endtoend deep learning approach for the task in which the network is trained to produce binary codes directly from image pixels without the need of manual annotation in particular to deal with the nonsmoothness of binary constraints we propose a novel pairwise constrained loss function which simultaneously encodes the distances between pairs of hash codes and the binary quantization error in order to train the network with the proposed loss function we propose an efficient parameter learning algorithm in addition to provide similar dissimilar training images to train the network we exploit 3d models reconstructed from unlabelled images for automatic generation of enormous training image pairs the extensive experiments on image retrieval benchmark datasets demonstrate the improvements of the proposed method over the stateoftheart compact representation methods on the image retrieval problem | [['learning', 'compact', 'binary', 'codes', 'for', 'image', 'retrieval', 'task', 'using', 'deep', 'neural', 'networks', 'has', 'attracted', 'increasing', 'attention', 'recently', 'however', 'training', 'deep', 'hashing', 'networks', 'for', 'the', 'task', 'is', 'challenging', 'due', 'to', 'the', 'binary', 'constraints', 'on', 'the', 'hash', 'codes', 'the', 'similarity', 'preserving', 'property', 'and', 'the', 'requirement', 'for', 'a', 'vast', 'amount', 'of', 'labelled', 'images', 'to', 'the', 'best', 'of', 'our', 'knowledge', 'none', 'of', 'the', 'existing', 'methods', 'has', 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1,802.07438 | Magnetic fields in multiple bright-rimmed clouds in different directions
of H$~$II region IC1396 - II | Bright-rimmed clouds form on the edges of H II regions affected by the high
energy radiation from a central ionizing source. The UV radiation from the
ionizing source results in compression and ionization causing either cloud
disruption or further star formation. In this work, we present R-band
polarization measurements towards four bright-rimmed clouds, IC1396A, BRC 37,
BRC 38, and BRC 39, located in the different directions of the H II region,
Sh2-131, in order to map magnetic fields (B-fields) in the plane of the sky.
These BRCs are illuminated by the O star HD206267 and present a range of
projected on sky geometries. This provides an opportunity to understand the
magnetized evolution of BRCs. The B-field geometries of the clouds deduced from
the polarization data, after correction for foreground ISM contamination, are
seen to be connected to the ambient B-fields on the large scale. They seem to
play an important role in shaping the cloud IC1396A and BRC 37. BRCs 38 and 39
show a broader and snubber head morphology possibly due to the B-fields being
aligned with incoming radiation as explained in the simulations. A good general
agreement is noted on comparing our observational results with the simulations
supporting the importance of B-fields in BRC evolution. This work is the first
step towards systematic mapping the B-fields morphology in multiple BRCs in an
expanding H II region, extending the work presented by Soam et al. (2017b).
| astro-ph.GA | brightrimmed clouds form on the edges of h ii regions affected by the high energy radiation from a central ionizing source the uv radiation from the ionizing source results in compression and ionization causing either cloud disruption or further star formation in this work we present rband polarization measurements towards four brightrimmed clouds ic1396a brc 37 brc 38 and brc 39 located in the different directions of the h ii region sh2131 in order to map magnetic fields bfields in the plane of the sky these brcs are illuminated by the o star hd206267 and present a range of projected on sky geometries this provides an opportunity to understand the magnetized evolution of brcs the bfield geometries of the clouds deduced from the polarization data after correction for foreground ism contamination are seen to be connected to the ambient bfields on the large scale they seem to play an important role in shaping the cloud ic1396a and brc 37 brcs 38 and 39 show a broader and snubber head morphology possibly due to the bfields being aligned with incoming radiation as explained in the simulations a good general agreement is noted on comparing our observational results with the simulations supporting the importance of bfields in brc evolution this work is the first step towards systematic mapping the bfields morphology in multiple brcs in an expanding h ii region extending the work presented by soam et al 2017b | [['brightrimmed', 'clouds', 'form', 'on', 'the', 'edges', 'of', 'h', 'ii', 'regions', 'affected', 'by', 'the', 'high', 'energy', 'radiation', 'from', 'a', 'central', 'ionizing', 'source', 'the', 'uv', 'radiation', 'from', 'the', 'ionizing', 'source', 'results', 'in', 'compression', 'and', 'ionization', 'causing', 'either', 'cloud', 'disruption', 'or', 'further', 'star', 'formation', 'in', 'this', 'work', 'we', 'present', 'rband', 'polarization', 'measurements', 'towards', 'four', 'brightrimmed', 'clouds', 'ic1396a', 'brc', '37', 'brc', '38', 'and', 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1,802.07439 | Constant Factor Approximation Algorithm for Weighted Flow Time on a
Single Machine in Pseudo-polynomial time | In the weighted flow-time problem on a single machine, we are given a set of
n jobs, where each job has a processing requirement p_j, release date r_j and
weight w_j. The goal is to find a preemptive schedule which minimizes the sum
of weighted flow-time of jobs, where the flow-time of a job is the difference
between its completion time and its released date. We give the first
pseudo-polynomial time constant approximation algorithm for this problem. The
running time of our algorithm is polynomial in n, the number of jobs, and P,
which is the ratio of the largest to the smallest processing requirement of a
job. Our algorithm relies on a novel reduction of this problem to a
generalization of the multi-cut problem on trees, which we call the Demand
Multi-Cut problem. Even though we do not give a constant factor approximation
algorithm for the Demand Multi-Cut problem on trees, we show that the specific
instances of Demand Multi-Cut obtained by reduction from weighted flow-time
problem instances have more structure in them, and we are able to employ
techniques based on dynamic programming. Our dynamic programming algorithm
relies on showing that there are near optimal solutions which have nice
smoothness properties, and we exploit these properties to reduce the size of DP
table.
| cs.DS | in the weighted flowtime problem on a single machine we are given a set of n jobs where each job has a processing requirement p_j release date r_j and weight w_j the goal is to find a preemptive schedule which minimizes the sum of weighted flowtime of jobs where the flowtime of a job is the difference between its completion time and its released date we give the first pseudopolynomial time constant approximation algorithm for this problem the running time of our algorithm is polynomial in n the number of jobs and p which is the ratio of the largest to the smallest processing requirement of a job our algorithm relies on a novel reduction of this problem to a generalization of the multicut problem on trees which we call the demand multicut problem even though we do not give a constant factor approximation algorithm for the demand multicut problem on trees we show that the specific instances of demand multicut obtained by reduction from weighted flowtime problem instances have more structure in them and we are able to employ techniques based on dynamic programming our dynamic programming algorithm relies on showing that there are near optimal solutions which have nice smoothness properties and we exploit these properties to reduce the size of dp table | [['in', 'the', 'weighted', 'flowtime', 'problem', 'on', 'a', 'single', 'machine', 'we', 'are', 'given', 'a', 'set', 'of', 'n', 'jobs', 'where', 'each', 'job', 'has', 'a', 'processing', 'requirement', 'p_j', 'release', 'date', 'r_j', 'and', 'weight', 'w_j', 'the', 'goal', 'is', 'to', 'find', 'a', 'preemptive', 'schedule', 'which', 'minimizes', 'the', 'sum', 'of', 'weighted', 'flowtime', 'of', 'jobs', 'where', 'the', 'flowtime', 'of', 'a', 'job', 'is', 'the', 'difference', 'between', 'its', 'completion', 'time', 'and', 'its', 'released', 'date', 'we', 'give', 'the', 'first', 'pseudopolynomial', 'time', 'constant', 'approximation', 'algorithm', 'for', 'this', 'problem', 'the', 'running', 'time', 'of', 'our', 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1,802.0744 | Max-size popular matchings and extensions | We consider the max-size popular matching problem in a roommates instance G =
(V,E) with strict preference lists. A matching M is popular if there is no
matching M' in G such that the vertices that prefer M' to M outnumber those
that prefer M to M'. We show it is NP-hard to compute a max-size popular
matching in G. This is in contrast to the tractability of this problem in
bipartite graphs where a max-size popular matching can be computed in linear
time. We define a subclass of max-size popular matchings called strongly
dominant matchings and show a linear time algorithm to solve the strongly
dominant matching problem in a roommates instance.
We consider a generalization of the max-size popular matching problem in
bipartite graphs: this is the max-weight popular matching problem where there
is also an edge weight function w and we seek a popular matching of largest
weight. We show this is an NP-hard problem and this is so even when w(e) is
either 1 or 2 for every edge e. We also show an algorithm with running time
O*(2^{n/4}) to find a max-weight popular matching matching in G = (A U B,E)$ on
n vertices.
| cs.DS | we consider the maxsize popular matching problem in a roommates instance g ve with strict preference lists a matching m is popular if there is no matching m in g such that the vertices that prefer m to m outnumber those that prefer m to m we show it is nphard to compute a maxsize popular matching in g this is in contrast to the tractability of this problem in bipartite graphs where a maxsize popular matching can be computed in linear time we define a subclass of maxsize popular matchings called strongly dominant matchings and show a linear time algorithm to solve the strongly dominant matching problem in a roommates instance we consider a generalization of the maxsize popular matching problem in bipartite graphs this is the maxweight popular matching problem where there is also an edge weight function w and we seek a popular matching of largest weight we show this is an nphard problem and this is so even when we is either 1 or 2 for every edge e we also show an algorithm with running time o2n4 to find a maxweight popular matching matching in g a u be on n vertices | [['we', 'consider', 'the', 'maxsize', 'popular', 'matching', 'problem', 'in', 'a', 'roommates', 'instance', 'g', 've', 'with', 'strict', 'preference', 'lists', 'a', 'matching', 'm', 'is', 'popular', 'if', 'there', 'is', 'no', 'matching', 'm', 'in', 'g', 'such', 'that', 'the', 'vertices', 'that', 'prefer', 'm', 'to', 'm', 'outnumber', 'those', 'that', 'prefer', 'm', 'to', 'm', 'we', 'show', 'it', 'is', 'nphard', 'to', 'compute', 'a', 'maxsize', 'popular', 'matching', 'in', 'g', 'this', 'is', 'in', 'contrast', 'to', 'the', 'tractability', 'of', 'this', 'problem', 'in', 'bipartite', 'graphs', 'where', 'a', 'maxsize', 'popular', 'matching', 'can', 'be', 'computed', 'in', 'linear', 'time', 'we', 'define', 'a', 'subclass', 'of', 'maxsize', 'popular', 'matchings', 'called', 'strongly', 'dominant', 'matchings', 'and', 'show', 'a', 'linear', 'time', 'algorithm', 'to', 'solve', 'the', 'strongly', 'dominant', 'matching', 'problem', 'in', 'a', 'roommates', 'instance', 'we', 'consider', 'a', 'generalization', 'of', 'the', 'maxsize', 'popular', 'matching', 'problem', 'in', 'bipartite', 'graphs', 'this', 'is', 'the', 'maxweight', 'popular', 'matching', 'problem', 'where', 'there', 'is', 'also', 'an', 'edge', 'weight', 'function', 'w', 'and', 'we', 'seek', 'a', 'popular', 'matching', 'of', 'largest', 'weight', 'we', 'show', 'this', 'is', 'an', 'nphard', 'problem', 'and', 'this', 'is', 'so', 'even', 'when', 'we', 'is', 'either', '1', 'or', '2', 'for', 'every', 'edge', 'e', 'we', 'also', 'show', 'an', 'algorithm', 'with', 'running', 'time', 'o2n4', 'to', 'find', 'a', 'maxweight', 'popular', 'matching', 'matching', 'in', 'g', 'a', 'u', 'be', 'on', 'n', 'vertices']] | [-0.1597284505517236, 0.05989823140034648, -0.049576225364344376, 0.08068262546696714, -0.11384508286503517, -0.17926662011889902, 0.036086273496630156, 0.43712791070568985, -0.29123641602070954, -0.3315106148306791, 0.09261208266518575, -0.30363998019850347, -0.17306638606185765, 0.09160298734624411, -0.10038484285968512, 0.01825622664647813, 0.10864566061598471, 0.11410959764634292, 0.010252585979698576, -0.27753054744181066, 0.2895062265061977, -0.024553319178096156, 0.22408182944672247, 0.053628703461118456, 0.06953698739664733, 0.05339282049045799, 0.016233882264040298, 0.09154869494681969, -0.14849459150504543, 0.07431294596612188, 0.29234730425352223, 0.1693385942569617, 0.2932115384202621, -0.34429250541423817, -0.11992156559242134, 0.2370959410874107, 0.10910974644883276, 0.06174658516393549, -0.029205811164474238, -0.1573412738064408, 0.1468411221991525, -0.11786767529314242, -0.02893558127313928, 0.02891725524409017, 0.10813471261260625, -0.06095090077310649, -0.352451805186075, -0.0035310543327223567, 0.051469782001556365, -0.04943778849675776, 0.04578989609274635, -0.1517074427562695, 0.020700822574875984, 0.06708642120457131, -0.032142789777649595, 0.093169751799273, -0.008285979501877056, -0.14953716569473768, -0.157321125330394, 0.4420704129081087, -0.10007441418982929, -0.17987216040633883, 0.15206478558348369, -0.06263439358698988, -0.19309093332069402, 0.06186198124805049, 0.14425688946789822, 0.22363970442651415, -0.09742027081392272, 0.1195643411770222, -0.1879496895931224, 0.14358589918882148, 0.11045893174856145, -0.035541510441680885, 0.13578503522170982, 0.18714642499072412, 0.20973729250980966, 0.1668987489662365, 0.011738736333732073, 0.0017403917774784989, -0.2021344739820827, -0.10786601948506921, -0.21354726013174366, 0.01602346880768005, -0.12822599625807352, -0.2110826498474264, 0.3607763904832341, 0.1306964436824892, 0.21387907972814618, 0.0986116053938374, 0.2695319065150479, 0.12551005364532777, 0.031245411131684643, 0.22102420192642072, 0.14631829293844228, 0.07421031087603855, -0.004610366180898423, -0.1803236880090305, 0.05097956929342859, 0.08494090796141002] |
1,802.07441 | Nucleon radius effects on neutron stars in quark mean field model | We study the effects of free space nucleon radius on nuclear matter and
neutron stars within the framework of quark mean field model. The nucleon
radius is treated self-consistently with this model, where quark confinement is
adjusted to fit different values of nucleon radius. Corrections due to
center-of-mass motion, quark-pion coupling, and one gluon exchange are included
to obtain the nucleon mass in vacuum. The meson coupling constants that
describe the behavior of many-body nucleonic system are newly-constructed by
reproducing the empirical saturation properties of nuclear matter, including
the recent determinations of symmetry energy parameters. Our results show that
the nucleon radius in free space have negligible effects on nuclear matter
equation of state and neutron star mass-radius relations, which is different
from the conclusion drawn in previous studies. We further explore that the
sensitivity of star radius on the nucleon radius found in earlier publications
is actually from the symmetry energy and its slope.
| nucl-th astro-ph.HE astro-ph.SR | we study the effects of free space nucleon radius on nuclear matter and neutron stars within the framework of quark mean field model the nucleon radius is treated selfconsistently with this model where quark confinement is adjusted to fit different values of nucleon radius corrections due to centerofmass motion quarkpion coupling and one gluon exchange are included to obtain the nucleon mass in vacuum the meson coupling constants that describe the behavior of manybody nucleonic system are newlyconstructed by reproducing the empirical saturation properties of nuclear matter including the recent determinations of symmetry energy parameters our results show that the nucleon radius in free space have negligible effects on nuclear matter equation of state and neutron star massradius relations which is different from the conclusion drawn in previous studies we further explore that the sensitivity of star radius on the nucleon radius found in earlier publications is actually from the symmetry energy and its slope | [['we', 'study', 'the', 'effects', 'of', 'free', 'space', 'nucleon', 'radius', 'on', 'nuclear', 'matter', 'and', 'neutron', 'stars', 'within', 'the', 'framework', 'of', 'quark', 'mean', 'field', 'model', 'the', 'nucleon', 'radius', 'is', 'treated', 'selfconsistently', 'with', 'this', 'model', 'where', 'quark', 'confinement', 'is', 'adjusted', 'to', 'fit', 'different', 'values', 'of', 'nucleon', 'radius', 'corrections', 'due', 'to', 'centerofmass', 'motion', 'quarkpion', 'coupling', 'and', 'one', 'gluon', 'exchange', 'are', 'included', 'to', 'obtain', 'the', 'nucleon', 'mass', 'in', 'vacuum', 'the', 'meson', 'coupling', 'constants', 'that', 'describe', 'the', 'behavior', 'of', 'manybody', 'nucleonic', 'system', 'are', 'newlyconstructed', 'by', 'reproducing', 'the', 'empirical', 'saturation', 'properties', 'of', 'nuclear', 'matter', 'including', 'the', 'recent', 'determinations', 'of', 'symmetry', 'energy', 'parameters', 'our', 'results', 'show', 'that', 'the', 'nucleon', 'radius', 'in', 'free', 'space', 'have', 'negligible', 'effects', 'on', 'nuclear', 'matter', 'equation', 'of', 'state', 'and', 'neutron', 'star', 'massradius', 'relations', 'which', 'is', 'different', 'from', 'the', 'conclusion', 'drawn', 'in', 'previous', 'studies', 'we', 'further', 'explore', 'that', 'the', 'sensitivity', 'of', 'star', 'radius', 'on', 'the', 'nucleon', 'radius', 'found', 'in', 'earlier', 'publications', 'is', 'actually', 'from', 'the', 'symmetry', 'energy', 'and', 'its', 'slope']] | [-0.053485458811009, 0.2135388417860433, -0.1242310878309992, 0.10949246122336556, -0.06762516653585819, -0.02245664123385664, 0.02663546431689493, 0.34751975584414696, -0.16805799090934376, -0.31507559139882363, -0.029250861046415184, -0.29947702837807516, -0.006552716152321908, 0.1270530054976623, 0.034310038242068505, 0.03803025733636347, 0.06004424152535296, 0.08069867758651174, -0.09000079534617403, -0.2000930561195879, 0.3843716327761931, 0.038459602184593676, 0.1997072845291827, 0.13815685419230572, 0.032976689828079074, 0.012143560296164885, -0.020624647677064904, -0.032469243118013705, -0.19906447366280894, 0.048567166461819605, 0.18110986766630724, 0.04879000605658568, 0.16527368347010304, -0.4008176262099897, -0.21880817244940948, 0.07138341499732867, 0.11386482437261411, 0.09836709924387715, -0.04448069403053171, -0.27598338969232095, 0.03332367281038915, -0.24433338661347667, -0.17945578008469554, -0.09859878498339845, 0.026457683053764235, 0.03195199906645763, -0.25344606649671353, 0.1343459911862268, -0.010600717406299325, -0.004933468636966521, -0.1250517167969637, -0.22560284599406463, -0.03432555493538178, 0.05943825485695514, 0.13102089715070062, 0.08608570415676842, 0.2036232817097522, -0.18499094769809274, -0.03859158891944155, 0.40901255523485525, -0.026557182447023448, -0.15276701644723933, 0.09350921673580043, -0.20994617444793542, -0.10621272809202632, 0.0988933204733316, 0.181470608218543, 0.08749480431358661, -0.1751003017889396, 0.10766361203615464, -0.0402134112886063, 0.21937462988970502, 0.06073674008009895, 0.06751935990121696, 0.24323372479167676, 0.1696742063508399, -0.02177393269244461, 0.04657072740036153, -0.10354569836579744, -0.1410036030105285, -0.3280972539116779, -0.04325182070775378, -0.1672005840201652, 0.0294508938136841, -0.12208109315927891, -0.08527361846739245, 0.3679421823396678, 0.09339417961572537, 0.19367431861408535, -0.018855554153091245, 0.291328063541122, 0.10197516763507719, 0.10654961866657099, 0.07548101896719608, 0.3363053279658479, 0.2386157422131228, 0.07858283192279839, -0.33690310751778946, -0.0021770531544461845, 0.06234360012796617] |
1,802.07442 | Learning to Play with Intrinsically-Motivated Self-Aware Agents | Infants are experts at playing, with an amazing ability to generate novel
structured behaviors in unstructured environments that lack clear extrinsic
reward signals. We seek to mathematically formalize these abilities using a
neural network that implements curiosity-driven intrinsic motivation. Using a
simple but ecologically naturalistic simulated environment in which an agent
can move and interact with objects it sees, we propose a "world-model" network
that learns to predict the dynamic consequences of the agent's actions.
Simultaneously, we train a separate explicit "self-model" that allows the agent
to track the error map of its own world-model, and then uses the self-model to
adversarially challenge the developing world-model. We demonstrate that this
policy causes the agent to explore novel and informative interactions with its
environment, leading to the generation of a spectrum of complex behaviors,
including ego-motion prediction, object attention, and object gathering.
Moreover, the world-model that the agent learns supports improved performance
on object dynamics prediction, detection, localization and recognition tasks.
Taken together, our results are initial steps toward creating flexible
autonomous agents that self-supervise in complex novel physical environments.
| cs.LG cs.AI cs.CV stat.ML | infants are experts at playing with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals we seek to mathematically formalize these abilities using a neural network that implements curiositydriven intrinsic motivation using a simple but ecologically naturalistic simulated environment in which an agent can move and interact with objects it sees we propose a worldmodel network that learns to predict the dynamic consequences of the agents actions simultaneously we train a separate explicit selfmodel that allows the agent to track the error map of its own worldmodel and then uses the selfmodel to adversarially challenge the developing worldmodel we demonstrate that this policy causes the agent to explore novel and informative interactions with its environment leading to the generation of a spectrum of complex behaviors including egomotion prediction object attention and object gathering moreover the worldmodel that the agent learns supports improved performance on object dynamics prediction detection localization and recognition tasks taken together our results are initial steps toward creating flexible autonomous agents that selfsupervise in complex novel physical environments | [['infants', 'are', 'experts', 'at', 'playing', 'with', 'an', 'amazing', 'ability', 'to', 'generate', 'novel', 'structured', 'behaviors', 'in', 'unstructured', 'environments', 'that', 'lack', 'clear', 'extrinsic', 'reward', 'signals', 'we', 'seek', 'to', 'mathematically', 'formalize', 'these', 'abilities', 'using', 'a', 'neural', 'network', 'that', 'implements', 'curiositydriven', 'intrinsic', 'motivation', 'using', 'a', 'simple', 'but', 'ecologically', 'naturalistic', 'simulated', 'environment', 'in', 'which', 'an', 'agent', 'can', 'move', 'and', 'interact', 'with', 'objects', 'it', 'sees', 'we', 'propose', 'a', 'worldmodel', 'network', 'that', 'learns', 'to', 'predict', 'the', 'dynamic', 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1,802.07443 | Space Elevator Propulsion with Mechanical Waves | The current preferred envisioned method for transmitting power to a space
elevator climber is a laser/photovoltaic (PV) system. In this, a ground-based
laser beam would transmit megawatts of optical power through the atmosphere to
an arrangement of PV panels mounted on the ascending climber. Although this
technique has been successfully demonstrated in small models, this method will
likely suffer from serious shortcomings in a realistic full-scale system,
including poor conversion efficiency, obscuration by clouds, and mechanical
fragility of the panels. Worse, the PV method provides no means of regenerative
energy recovery. Furthermore, the laser would need to operate continuously at
multi-megawatt levels for as long as 14 days (the time for the climber to reach
geosynchronous altitudes). No such laser has ever been demonstrated.
This paper presents a radical alternative method for propelling a space
elevator car: by using the cable to transmit power in the form of transverse
mechanical waves propagated on the cable. A ground-based mechanical driving
oscillator would excite the waves. Traveling at hypersonic speeds, the waves
encounter the climber. This mechanical power is then extracted by an engine in
the climber to propel the climber upward. The oscillator may be manifested by a
pair of opposing pistons contacting the cable on opposite sides of the cable,
near the anchor point. Most importantly, existing engines can easily provide
the required amount of power to send a 10 metric-ton car from the ground to
geosynchronous altitudes.
| physics.pop-ph | the current preferred envisioned method for transmitting power to a space elevator climber is a laserphotovoltaic pv system in this a groundbased laser beam would transmit megawatts of optical power through the atmosphere to an arrangement of pv panels mounted on the ascending climber although this technique has been successfully demonstrated in small models this method will likely suffer from serious shortcomings in a realistic fullscale system including poor conversion efficiency obscuration by clouds and mechanical fragility of the panels worse the pv method provides no means of regenerative energy recovery furthermore the laser would need to operate continuously at multimegawatt levels for as long as 14 days the time for the climber to reach geosynchronous altitudes no such laser has ever been demonstrated this paper presents a radical alternative method for propelling a space elevator car by using the cable to transmit power in the form of transverse mechanical waves propagated on the cable a groundbased mechanical driving oscillator would excite the waves traveling at hypersonic speeds the waves encounter the climber this mechanical power is then extracted by an engine in the climber to propel the climber upward the oscillator may be manifested by a pair of opposing pistons contacting the cable on opposite sides of the cable near the anchor point most importantly existing engines can easily provide the required amount of power to send a 10 metricton car from the ground to geosynchronous altitudes | [['the', 'current', 'preferred', 'envisioned', 'method', 'for', 'transmitting', 'power', 'to', 'a', 'space', 'elevator', 'climber', 'is', 'a', 'laserphotovoltaic', 'pv', 'system', 'in', 'this', 'a', 'groundbased', 'laser', 'beam', 'would', 'transmit', 'megawatts', 'of', 'optical', 'power', 'through', 'the', 'atmosphere', 'to', 'an', 'arrangement', 'of', 'pv', 'panels', 'mounted', 'on', 'the', 'ascending', 'climber', 'although', 'this', 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1,802.07444 | Scaling-up Split-Merge MCMC with Locality Sensitive Sampling (LSS) | Split-Merge MCMC (Monte Carlo Markov Chain) is one of the essential and
popular variants of MCMC for problems when an MCMC state consists of an unknown
number of components. It is well known that state-of-the-art methods for
split-merge MCMC do not scale well. Strategies for rapid mixing requires smart
and informative proposals to reduce the rejection rate. However, all known
smart proposals involve expensive operations to suggest informative
transitions. As a result, the cost of each iteration is prohibitive for massive
scale datasets. It is further known that uninformative but computationally
efficient proposals, such as random split-merge, leads to extremely slow
convergence. This tradeoff between mixing time and per update cost seems hard
to get around.
In this paper, we show a sweet spot. We leverage some unique properties of
weighted MinHash, which is a popular LSH, to design a novel class of
split-merge proposals which are significantly more informative than random
sampling but at the same time efficient to compute. Overall, we obtain a
superior tradeoff between convergence and per update cost. As a direct
consequence, our proposals are around 6X faster than the state-of-the-art
sampling methods on two large real datasets KDDCUP and PubMed with several
millions of entities and thousands of clusters.
| cs.LG cs.AI cs.DS stat.ME stat.ML | splitmerge mcmc monte carlo markov chain is one of the essential and popular variants of mcmc for problems when an mcmc state consists of an unknown number of components it is well known that stateoftheart methods for splitmerge mcmc do not scale well strategies for rapid mixing requires smart and informative proposals to reduce the rejection rate however all known smart proposals involve expensive operations to suggest informative transitions as a result the cost of each iteration is prohibitive for massive scale datasets it is further known that uninformative but computationally efficient proposals such as random splitmerge leads to extremely slow convergence this tradeoff between mixing time and per update cost seems hard to get around in this paper we show a sweet spot we leverage some unique properties of weighted minhash which is a popular lsh to design a novel class of splitmerge proposals which are significantly more informative than random sampling but at the same time efficient to compute overall we obtain a superior tradeoff between convergence and per update cost as a direct consequence our proposals are around 6x faster than the stateoftheart sampling methods on two large real datasets kddcup and pubmed with several millions of entities and thousands of clusters | [['splitmerge', 'mcmc', 'monte', 'carlo', 'markov', 'chain', 'is', 'one', 'of', 'the', 'essential', 'and', 'popular', 'variants', 'of', 'mcmc', 'for', 'problems', 'when', 'an', 'mcmc', 'state', 'consists', 'of', 'an', 'unknown', 'number', 'of', 'components', 'it', 'is', 'well', 'known', 'that', 'stateoftheart', 'methods', 'for', 'splitmerge', 'mcmc', 'do', 'not', 'scale', 'well', 'strategies', 'for', 'rapid', 'mixing', 'requires', 'smart', 'and', 'informative', 'proposals', 'to', 'reduce', 'the', 'rejection', 'rate', 'however', 'all', 'known', 'smart', 'proposals', 'involve', 'expensive', 'operations', 'to', 'suggest', 'informative', 'transitions', 'as', 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1,802.07445 | A compactness result for non-local unregularized gradient flow lines | We prove an abstract compactness result for gradient flow lines of a
non-local unregularized gradient flow equation on a scale Hilbert space. This
is the first step towards Floer theory on scale Hilbert spaces.
| math.FA math.SG | we prove an abstract compactness result for gradient flow lines of a nonlocal unregularized gradient flow equation on a scale hilbert space this is the first step towards floer theory on scale hilbert spaces | [['we', 'prove', 'an', 'abstract', 'compactness', 'result', 'for', 'gradient', 'flow', 'lines', 'of', 'a', 'nonlocal', 'unregularized', 'gradient', 'flow', 'equation', 'on', 'a', 'scale', 'hilbert', 'space', 'this', 'is', 'the', 'first', 'step', 'towards', 'floer', 'theory', 'on', 'scale', 'hilbert', 'spaces']] | [-0.1413769040886751, 0.0543245123600868, -0.183808274950613, 0.12522513764526913, -0.09866652161102085, -0.0565601072191973, -0.07247379519771237, 0.3785876500803758, -0.3754633250920212, -0.18324173669166424, 0.13177723742966704, -0.22196177324718414, -0.09904493711313561, 0.14984880234388745, -0.1320600682467343, 0.06486450461670756, 0.07800449803471565, 0.013784908086938016, -0.10348321535788915, -0.22870884830241694, 0.4688409941736609, -0.01929888597634785, 0.23504335696206374, 0.07378111867343679, 0.16221029040239313, -0.04321114008095773, 0.0031524179914199256, 0.0010951081528807716, -0.15863319426117575, 0.17448769053718186, 0.2286943310378667, 0.014747078701689401, 0.3659626911668217, -0.41113674207864437, -0.27244636723223853, 0.1033001910922501, 0.15615590623415568, 0.09756249197594383, -0.033547782599378156, -0.30157056724762216, 0.0026870885973467548, -0.08302051349378683, -0.14756103021585765, -0.12780805157757746, 0.017221217043697834, -0.05158287029275123, -0.24092770592473886, 0.06988438988542732, 0.07681179819080759, 0.11948304245358005, -0.0977195775245919, -0.034066086046068984, -0.02032514146583922, 0.02622897892861682, -0.020331606467473593, 0.12267161153859514, 0.15939996770911796, -0.09816654899623245, -0.06290890092906706, 0.32585700371247883, -0.14470329713281793, -0.26165047452292023, 0.08926062710473642, -0.06224517554373426, -0.20779297476196112, 0.08342141230754993, 0.16255683239604182, 0.22648333703332088, -0.03519229941508349, 0.14553958418614724, -0.098715620005832, 0.14970056811238036, 0.0231247411986046, -0.010347861146061298, 0.03743002418538227, 0.16099569528801916, 0.28939318120041313, 0.10393787753555979, -0.018131246009622428, -0.1672328267544371, -0.4057160142590018, -0.23796140742214286, -0.17623055085320682, 0.10698501147357199, -0.1672424367930302, -0.20355616214082523, 0.3375752876540098, 0.08530390843310777, 0.22983450322028467, 0.1768918142051381, 0.29412717646097436, 0.1424060977228424, 0.03154230057535803, 0.096791582140962, 0.1897584919762962, 0.16679145439582713, 0.1788756945718299, -0.18461103032014387, -0.025052521244266674, 0.3443929653833894] |
1,802.07446 | Distributed Compression of Graphical Data | In contrast to time series, graphical data is data indexed by the vertices
and edges of a graph. Modern applications such as the internet, social
networks, genomics and proteomics generate graphical data, often at large
scale. The large scale argues for the need to compress such data for storage
and subsequent processing. Since this data might have several components
available in different locations, it is also important to study distributed
compression of graphical data. In this paper, we derive a rate region for this
problem which is a counterpart of the Slepian-Wolf theorem. We characterize the
rate region when the statistical description of the distributed graphical data
can be modeled as being one of two types - as a member of a sequence of marked
sparse Erdos-Renyi ensembles or as a member of a sequence of marked
configuration model ensembles. Our results are in terms of a generalization of
the notion of entropy introduced by Bordenave and Caputo in the study of local
weak limits of sparse graphs. Furthermore, we give a generalization of this
result for Erdos-Renyi and configuration model ensembles with more than two
sources.
| cs.IT math.IT | in contrast to time series graphical data is data indexed by the vertices and edges of a graph modern applications such as the internet social networks genomics and proteomics generate graphical data often at large scale the large scale argues for the need to compress such data for storage and subsequent processing since this data might have several components available in different locations it is also important to study distributed compression of graphical data in this paper we derive a rate region for this problem which is a counterpart of the slepianwolf theorem we characterize the rate region when the statistical description of the distributed graphical data can be modeled as being one of two types as a member of a sequence of marked sparse erdosrenyi ensembles or as a member of a sequence of marked configuration model ensembles our results are in terms of a generalization of the notion of entropy introduced by bordenave and caputo in the study of local weak limits of sparse graphs furthermore we give a generalization of this result for erdosrenyi and configuration model ensembles with more than two sources | [['in', 'contrast', 'to', 'time', 'series', 'graphical', 'data', 'is', 'data', 'indexed', 'by', 'the', 'vertices', 'and', 'edges', 'of', 'a', 'graph', 'modern', 'applications', 'such', 'as', 'the', 'internet', 'social', 'networks', 'genomics', 'and', 'proteomics', 'generate', 'graphical', 'data', 'often', 'at', 'large', 'scale', 'the', 'large', 'scale', 'argues', 'for', 'the', 'need', 'to', 'compress', 'such', 'data', 'for', 'storage', 'and', 'subsequent', 'processing', 'since', 'this', 'data', 'might', 'have', 'several', 'components', 'available', 'in', 'different', 'locations', 'it', 'is', 'also', 'important', 'to', 'study', 'distributed', 'compression', 'of', 'graphical', 'data', 'in', 'this', 'paper', 'we', 'derive', 'a', 'rate', 'region', 'for', 'this', 'problem', 'which', 'is', 'a', 'counterpart', 'of', 'the', 'slepianwolf', 'theorem', 'we', 'characterize', 'the', 'rate', 'region', 'when', 'the', 'statistical', 'description', 'of', 'the', 'distributed', 'graphical', 'data', 'can', 'be', 'modeled', 'as', 'being', 'one', 'of', 'two', 'types', 'as', 'a', 'member', 'of', 'a', 'sequence', 'of', 'marked', 'sparse', 'erdosrenyi', 'ensembles', 'or', 'as', 'a', 'member', 'of', 'a', 'sequence', 'of', 'marked', 'configuration', 'model', 'ensembles', 'our', 'results', 'are', 'in', 'terms', 'of', 'a', 'generalization', 'of', 'the', 'notion', 'of', 'entropy', 'introduced', 'by', 'bordenave', 'and', 'caputo', 'in', 'the', 'study', 'of', 'local', 'weak', 'limits', 'of', 'sparse', 'graphs', 'furthermore', 'we', 'give', 'a', 'generalization', 'of', 'this', 'result', 'for', 'erdosrenyi', 'and', 'configuration', 'model', 'ensembles', 'with', 'more', 'than', 'two', 'sources']] | [-0.10888411203506954, 0.0716194253106932, -0.059663763066994085, 0.06935552024640523, -0.04733126859245722, -0.11429248229470304, 0.04314041668636805, 0.3667935624027685, -0.2938430072571982, -0.3281184071324445, 0.1346125021916113, -0.27489105102315703, -0.14479021623577942, 0.18417723803600716, -0.08248221362792006, 0.04570742991818015, 0.09594259681918668, 0.0610501090908343, -0.015182845700912112, -0.22967386039888352, 0.316777752092739, 0.056634072790182725, 0.27727506436427596, 0.0007640358901792957, 0.06238369196412399, 0.0038642633677540366, -0.05512389066530221, 0.02705661891659181, -0.09526364637353528, 0.15500276161405327, 0.2869876833702688, 0.16663033451123904, 0.2898376091904137, -0.39762391166521177, -0.23038402439523187, 0.1422803085021955, 0.12697169959284765, 0.10683203829009266, -0.02803706179189268, -0.25967314112330636, 0.10864079719589602, -0.1664653066032496, -0.08662683173753721, -0.051177886692726965, 0.020566617148698018, 0.04027118453454297, -0.301635058316332, 0.06538132577242645, 0.08487126664558967, 0.08119195626165482, 0.0018629023795246437, -0.090069320566091, 0.01800173322509934, 0.12174261182684937, 0.020458870367096958, 0.0252950173109189, 0.08456327650015072, -0.14068917235107942, -0.13728032025298284, 0.3806071387383566, -0.050949412900394314, -0.16720220525824134, 0.1813973908091054, -0.09310682817056815, -0.19967789168629835, 0.07779438123958166, 0.20700533216148215, 0.11705699682946727, -0.18182922882612818, 0.05111727328133589, -0.06176997546947772, 0.13760469785593551, 0.06659119719168752, 0.048225964850155255, 0.1729443016191644, 0.19264187815133482, 0.06570080914048783, 0.18042870727179933, -0.08411798545444805, -0.10155027642125083, -0.2611933585797106, -0.15103512444603506, -0.23040857132253867, 0.014272821741679343, -0.14976852431463675, -0.19993475856358356, 0.37600934859527957, 0.13287442200566812, 0.23602590793042735, 0.07467246657019601, 0.2714322091015156, 0.06014814042118228, 0.07709183936728345, 0.0877969978259556, 0.13973548936767763, 0.12105718623816726, 0.11049112556402081, -0.10639488570747636, 0.06919593391163896, 0.03980074344723616] |
1,802.07447 | Load Balanced GANs for Multi-view Face Image Synthesis | Multi-view face synthesis from a single image is an ill-posed problem and
often suffers from serious appearance distortion. Producing photo-realistic and
identity preserving multi-view results is still a not well defined synthesis
problem. This paper proposes Load Balanced Generative Adversarial Networks
(LB-GAN) to precisely rotate the yaw angle of an input face image to any
specified angle. LB-GAN decomposes the challenging synthesis problem into two
well constrained subtasks that correspond to a face normalizer and a face
editor respectively. The normalizer first frontalizes an input image, and then
the editor rotates the frontalized image to a desired pose guided by a remote
code. In order to generate photo-realistic local details, the normalizer and
the editor are trained in a two-stage manner and regulated by a conditional
self-cycle loss and an attention based L2 loss. Exhaustive experiments on
controlled and uncontrolled environments demonstrate that the proposed method
not only improves the visual realism of multi-view synthetic images, but also
preserves identity information well.
| cs.CV | multiview face synthesis from a single image is an illposed problem and often suffers from serious appearance distortion producing photorealistic and identity preserving multiview results is still a not well defined synthesis problem this paper proposes load balanced generative adversarial networks lbgan to precisely rotate the yaw angle of an input face image to any specified angle lbgan decomposes the challenging synthesis problem into two well constrained subtasks that correspond to a face normalizer and a face editor respectively the normalizer first frontalizes an input image and then the editor rotates the frontalized image to a desired pose guided by a remote code in order to generate photorealistic local details the normalizer and the editor are trained in a twostage manner and regulated by a conditional selfcycle loss and an attention based l2 loss exhaustive experiments on controlled and uncontrolled environments demonstrate that the proposed method not only improves the visual realism of multiview synthetic images but also preserves identity information well | [['multiview', 'face', 'synthesis', 'from', 'a', 'single', 'image', 'is', 'an', 'illposed', 'problem', 'and', 'often', 'suffers', 'from', 'serious', 'appearance', 'distortion', 'producing', 'photorealistic', 'and', 'identity', 'preserving', 'multiview', 'results', 'is', 'still', 'a', 'not', 'well', 'defined', 'synthesis', 'problem', 'this', 'paper', 'proposes', 'load', 'balanced', 'generative', 'adversarial', 'networks', 'lbgan', 'to', 'precisely', 'rotate', 'the', 'yaw', 'angle', 'of', 'an', 'input', 'face', 'image', 'to', 'any', 'specified', 'angle', 'lbgan', 'decomposes', 'the', 'challenging', 'synthesis', 'problem', 'into', 'two', 'well', 'constrained', 'subtasks', 'that', 'correspond', 'to', 'a', 'face', 'normalizer', 'and', 'a', 'face', 'editor', 'respectively', 'the', 'normalizer', 'first', 'frontalizes', 'an', 'input', 'image', 'and', 'then', 'the', 'editor', 'rotates', 'the', 'frontalized', 'image', 'to', 'a', 'desired', 'pose', 'guided', 'by', 'a', 'remote', 'code', 'in', 'order', 'to', 'generate', 'photorealistic', 'local', 'details', 'the', 'normalizer', 'and', 'the', 'editor', 'are', 'trained', 'in', 'a', 'twostage', 'manner', 'and', 'regulated', 'by', 'a', 'conditional', 'selfcycle', 'loss', 'and', 'an', 'attention', 'based', 'l2', 'loss', 'exhaustive', 'experiments', 'on', 'controlled', 'and', 'uncontrolled', 'environments', 'demonstrate', 'that', 'the', 'proposed', 'method', 'not', 'only', 'improves', 'the', 'visual', 'realism', 'of', 'multiview', 'synthetic', 'images', 'but', 'also', 'preserves', 'identity', 'information', 'well']] | [-0.05465987041633859, -0.01064261111771228, -0.03131686444776336, 0.05698332696625538, -0.12307042383022984, -0.1947284852507483, -0.0026776588137285146, 0.4538915436007554, -0.33140205631999275, -0.3377768051047232, 0.09870949208506537, -0.2531704794338468, -0.1896189970474195, 0.14638138389954627, -0.2343850364566698, 0.10487620593520187, 0.12561049471503194, 0.016058186913510384, -0.0726188978733262, -0.24183075463611492, 0.28326861573607204, 0.029265735899628716, 0.324608649003402, 0.008540561452177884, 0.18712570110948967, -0.004405395863625616, -0.01762362727633813, -0.004907358657344704, -0.008553963589730313, 0.14042175517239183, 0.25957287537947865, 0.22794193473559454, 0.27031331365821953, -0.4196626165103686, -0.1692516617963232, 0.0704028336047578, 0.1267413010959266, 0.11322711619012105, -0.08424402890016643, -0.35694525296110186, 0.07441593322584618, -0.1344554355505064, 0.0026076617532798762, -0.08354537416532447, -0.034155470840013996, -0.0848858664127552, -0.32921465711455933, 0.01877891902846455, 0.11235540613010407, 0.08368846856034066, -0.0622457741476784, -0.0629934332793272, -0.04280338490446676, 0.19322830310557038, -0.0014544550780371964, 0.10281936172616986, 0.1686290573178425, -0.18657670413177826, -0.10219725182271103, 0.4145625910332686, -0.014101580637094529, -0.24528013665635798, 0.14573109157153558, -0.030179618801803716, -0.11669210320238402, 0.13454545248016903, 0.19647140639813476, 0.12852783466960432, -0.14620014226736053, 0.02871474728306543, -0.079191644033535, 0.22214119616362465, 0.06956840732246873, -0.028074995231449226, 0.1884821316181635, 0.17899042169881774, 0.06303694806521452, 0.17840848029208004, -0.1068321047453917, -0.0024101660480793517, -0.22079316382900563, -0.08885421733153819, -0.19936494394264456, -0.00879520842421629, -0.06661521019104609, -0.16810326978948875, 0.41318956181359817, 0.1905648056436124, 0.25110163656652823, 0.07818507338296386, 0.41533071466403293, 0.0368499859793206, 0.08708063165857634, 0.07747088850746993, 0.13801692378901748, 0.02528705454469788, 0.0842983348300987, -0.17713295481214889, 0.09215170654757067, 0.07709958388977035] |
1,802.07448 | The asymptotic expansion of the regular discretization error of It\^o
integrals | We study a Edgeworth-type refinement of the central limit theorem for the
discretizacion error of It\^o integrals. Towards this end, we introduce a new
approach, based on the anticipating It\^o formula. This alternative technique
allows us to compute explicitly the terms of the corresponding expansion
formula.
| math.PR | we study a edgeworthtype refinement of the central limit theorem for the discretizacion error of ito integrals towards this end we introduce a new approach based on the anticipating ito formula this alternative technique allows us to compute explicitly the terms of the corresponding expansion formula | [['we', 'study', 'a', 'edgeworthtype', 'refinement', 'of', 'the', 'central', 'limit', 'theorem', 'for', 'the', 'discretizacion', 'error', 'of', 'ito', 'integrals', 'towards', 'this', 'end', 'we', 'introduce', 'a', 'new', 'approach', 'based', 'on', 'the', 'anticipating', 'ito', 'formula', 'this', 'alternative', 'technique', 'allows', 'us', 'to', 'compute', 'explicitly', 'the', 'terms', 'of', 'the', 'corresponding', 'expansion', 'formula']] | [-0.08724385776246588, -0.02850658820890304, -0.19742480429510276, 0.09414106674181918, -0.09793114454175035, -0.052416860920170116, 0.14696005094382497, 0.2930396651228269, -0.23488389444020058, -0.259495634585619, 0.08930263281282451, -0.1983510360176701, -0.19200255448619524, 0.22113865713278452, -0.12387432757002696, 0.03343606096588903, 0.028833968885656862, -0.0012018728794323075, -0.11428784045080344, -0.19287049192417827, 0.31575788386269577, 0.04531231555673811, 0.25751063782307837, 0.058126621093187066, 0.17222272145251433, 0.07202531051977228, -0.0884067579689953, -0.05428171760092179, -0.2254594503177537, 0.2702770432224497, 0.20682595575021373, 0.037801183845537406, 0.29545919278429617, -0.40704984364824165, -0.11392706620196501, 0.06603438835591077, 0.1288510190322995, 0.13605998541849354, 0.006595058270937038, -0.23253693940738837, 0.07328331874062617, -0.2582216649833653, -0.23115679887123405, -0.10847379792895583, -0.013789612510138088, 0.0022492746874276134, -0.2921481070212192, 0.06762850506024229, 0.11791256533728706, 0.001795068672961659, -0.04674941634422996, -0.07507348074060348, 0.10413364813559585, 0.11693704665328065, 0.024680106714367867, -0.015921527825088964, 0.08229404723064768, -0.055270910087145034, -0.13549762635310697, 0.27816263188918433, -0.12352016368725648, -0.20806984355052313, 0.10848770458768639, -0.12408649216716489, -0.1544035161534945, 0.10627791817403502, 0.15366525194711156, 0.21248220437102847, -0.19417719112502205, 0.12027832062708008, -0.005371777796083026, 0.06303385833485259, 0.10635836432791418, 0.014363177907135751, 0.1481975390886267, 0.1382253804968463, 0.08828707662307554, 0.23373316907220418, -0.09293436314393248, -0.10904483025272688, -0.37457420287860765, -0.27114904721577965, -0.13572408408961362, 0.0889615655462775, -0.1479355567548838, -0.2088028308004141, 0.3482340024577247, 0.2292271073597173, 0.16760141292793884, 0.1269946007989347, 0.27322662414775956, 0.2499293208329214, 0.03904840095589558, 0.0047981614764365885, 0.14000941993047794, 0.16888097284568682, 0.1283669323246512, -0.19322044969432883, 0.05822607646178868, 0.23548171119764447] |
1,802.07449 | An iterated graph construction and periodic orbits of Hamiltonian delay
equations | According to the Arnold conjectures and Floer's proofs, there are non-trivial
lower bounds for the number of periodic solutions of Hamiltonian differential
equations on a closed symplectic manifold whose symplectic form vanishes on
spheres. We use an iterated graph construction and Lagrangian Floer homology to
show that these lower bounds also hold for certain Hamiltonian delay equations.
| math.DS math.SG | according to the arnold conjectures and floers proofs there are nontrivial lower bounds for the number of periodic solutions of hamiltonian differential equations on a closed symplectic manifold whose symplectic form vanishes on spheres we use an iterated graph construction and lagrangian floer homology to show that these lower bounds also hold for certain hamiltonian delay equations | [['according', 'to', 'the', 'arnold', 'conjectures', 'and', 'floers', 'proofs', 'there', 'are', 'nontrivial', 'lower', 'bounds', 'for', 'the', 'number', 'of', 'periodic', 'solutions', 'of', 'hamiltonian', 'differential', 'equations', 'on', 'a', 'closed', 'symplectic', 'manifold', 'whose', 'symplectic', 'form', 'vanishes', 'on', 'spheres', 'we', 'use', 'an', 'iterated', 'graph', 'construction', 'and', 'lagrangian', 'floer', 'homology', 'to', 'show', 'that', 'these', 'lower', 'bounds', 'also', 'hold', 'for', 'certain', 'hamiltonian', 'delay', 'equations']] | [-0.24601667133678698, 0.0764174152008899, -0.0913698053673694, 0.1277356008149422, -0.12508691540151312, -0.19105546049397895, -0.0021295208144900307, 0.27650280662795956, -0.2516073886991331, -0.288571909523422, 0.0934922945146498, -0.25367046338751126, -0.2191193609890577, 0.23191867441984645, -0.14817631154794964, 0.06975088413322769, 0.10336885525714279, 0.08349573875270914, -0.12005868599456, -0.2995026064817099, 0.398225227861028, -0.07721204145631769, 0.1575325854620978, 0.10888421140088324, 0.12532996791496612, -0.045401957482426314, 0.016320199350287255, -0.02648384240979284, -0.2703111057212881, 0.10088231359820879, 0.2501073732906789, 0.036992261562038935, 0.15002214076945133, -0.4687402654243143, -0.100029599031315, 0.1328206724699652, 0.16143296415975783, 0.06142385661798088, 2.394343334201135e-05, -0.3085175028822401, 0.09297402236577973, -0.11568508682805195, -0.172167028594566, -0.13856362458318472, 0.03339025848790219, 0.0494396163379414, -0.17963147384375988, -0.03556474197396535, 0.13889837248675657, 0.08589142155751847, -0.08423712139687779, -0.10247043686052948, -0.048052050475553984, 0.07500324785513313, 0.030122153085182634, -0.0002722983460938721, 0.09072611769334528, -0.0630658421861498, -0.1132558988766712, 0.32859146938120065, -0.08952525855254448, -0.33373721339331386, 0.10359979775150127, -0.06716327615931891, -0.25000609812865915, 0.19114763402429066, 0.10751886934597503, 0.13719712335028147, -0.06281588172638103, 0.1825997715697444, -0.10883425150001258, 0.06337257749155949, 0.14139914234054454, 0.007658061759317653, 0.06580662289470957, 0.009734159997223239, 0.21496497932004563, 0.0757117943282713, 0.045394847733213714, -0.21136601703862348, -0.33198513123288487, -0.18069685048376732, -0.1573506805294177, 0.15284182314287154, -0.18518794228255406, -0.23659992623633067, 0.33923442453848557, 0.046244605411693715, 0.1399138438384653, 0.2111822223094733, 0.25215338274281013, 0.1605817078635211, 0.01817626865548, 0.10803918203894507, 0.1406863220403657, 0.24665188009589256, 0.0017000298064790275, -0.14908718646160865, -0.047808945918325005, 0.2778700601734352] |
1,802.0745 | Umbilical Cord Blood Banking and its Therapeutic Uses | Umbilical cord blood (UBC) can be viewed as the most promising source of stem
cells, in which collection cost is minimal and its benefits are immense. The
cord blood is used to treat malignant and nonmalignant diseases; this is due to
its progenitor characteristics know as stem cells.Its properties of being,
immunologically immature and high plasticity has made it superior to other
sources of stem cells. The stem cells collected from cord blood have neutral
differentiation capabilities which allow medical professionals to produce
functional neural cells from these stem cells.Cord Blood Banking (CBB) is the
storing of the umbilical cord blood which is collected immediately after the
delivery of the baby. Great care and concern are needed for proper storage of
these progenitor cells, hence cord blood banks come into the play, they are of
3 types which are: public, private and direct donation banks.Clinical trials
are still at its very early stages having abundances to still be uncovered but
results were obtained have demonstrated high potential and more scope towards
effective development therapies and treatments for rare disorders.
| q-bio.CB q-bio.TO | umbilical cord blood ubc can be viewed as the most promising source of stem cells in which collection cost is minimal and its benefits are immense the cord blood is used to treat malignant and nonmalignant diseases this is due to its progenitor characteristics know as stem cellsits properties of being immunologically immature and high plasticity has made it superior to other sources of stem cells the stem cells collected from cord blood have neutral differentiation capabilities which allow medical professionals to produce functional neural cells from these stem cellscord blood banking cbb is the storing of the umbilical cord blood which is collected immediately after the delivery of the baby great care and concern are needed for proper storage of these progenitor cells hence cord blood banks come into the play they are of 3 types which are public private and direct donation banksclinical trials are still at its very early stages having abundances to still be uncovered but results were obtained have demonstrated high potential and more scope towards effective development therapies and treatments for rare disorders | [['umbilical', 'cord', 'blood', 'ubc', 'can', 'be', 'viewed', 'as', 'the', 'most', 'promising', 'source', 'of', 'stem', 'cells', 'in', 'which', 'collection', 'cost', 'is', 'minimal', 'and', 'its', 'benefits', 'are', 'immense', 'the', 'cord', 'blood', 'is', 'used', 'to', 'treat', 'malignant', 'and', 'nonmalignant', 'diseases', 'this', 'is', 'due', 'to', 'its', 'progenitor', 'characteristics', 'know', 'as', 'stem', 'cellsits', 'properties', 'of', 'being', 'immunologically', 'immature', 'and', 'high', 'plasticity', 'has', 'made', 'it', 'superior', 'to', 'other', 'sources', 'of', 'stem', 'cells', 'the', 'stem', 'cells', 'collected', 'from', 'cord', 'blood', 'have', 'neutral', 'differentiation', 'capabilities', 'which', 'allow', 'medical', 'professionals', 'to', 'produce', 'functional', 'neural', 'cells', 'from', 'these', 'stem', 'cellscord', 'blood', 'banking', 'cbb', 'is', 'the', 'storing', 'of', 'the', 'umbilical', 'cord', 'blood', 'which', 'is', 'collected', 'immediately', 'after', 'the', 'delivery', 'of', 'the', 'baby', 'great', 'care', 'and', 'concern', 'are', 'needed', 'for', 'proper', 'storage', 'of', 'these', 'progenitor', 'cells', 'hence', 'cord', 'blood', 'banks', 'come', 'into', 'the', 'play', 'they', 'are', 'of', '3', 'types', 'which', 'are', 'public', 'private', 'and', 'direct', 'donation', 'banksclinical', 'trials', 'are', 'still', 'at', 'its', 'very', 'early', 'stages', 'having', 'abundances', 'to', 'still', 'be', 'uncovered', 'but', 'results', 'were', 'obtained', 'have', 'demonstrated', 'high', 'potential', 'and', 'more', 'scope', 'towards', 'effective', 'development', 'therapies', 'and', 'treatments', 'for', 'rare', 'disorders']] | [-0.018003951115216212, 0.12220451204815287, -0.03900639898810451, 0.06233909320375956, -0.0877930830756668, -0.16538516950359652, 0.0417180553393502, 0.3888351722456388, -0.20977467906182443, -0.2661411878801697, 0.15690530768717342, -0.34149788560303435, -0.17051723901055416, 0.21851512982869858, -0.19830998826460638, -0.009046606389099245, 0.11981548473175446, 0.01964778105850035, 0.09525906453828528, -0.29601994512565644, 0.20688301254300645, 0.01693257770569868, 0.3152948550533355, 0.04976791454828344, 0.07523617502936925, -0.08097274929274466, -0.06471628971319826, 0.0015316019099290397, -0.06150999285984488, 0.1369397725439657, 0.3426614736884155, 0.19730771816631948, 0.34008203428873623, -0.5129606393483382, -0.25813072397828696, 0.09884784760817472, 0.15798796743778934, 0.07879739111310548, -0.07769512398797153, -0.25374592772938986, 0.133192880269648, -0.15744177939433773, -0.12379502809860489, -0.06696977754406609, -0.001937045324170454, 0.01719403312422814, -0.2093302929087341, 0.11407767976445692, -0.018159742980391125, 0.10967144921133612, -0.06446125586345178, -0.17127299841641533, -0.10363189462011425, 0.27196759047166613, 0.07199063470298742, 0.02440747378965501, 0.22846358416890408, -0.17294059677806217, -0.04326626991017044, 0.3687228314123455, 0.09617154870846373, -0.15676080258774824, 0.24348697663464752, -0.1198931994771225, -0.08881663749343716, 0.17352373653821732, 0.15797853136874354, 0.041637807690263304, -0.21415262079773872, -0.05057047156118311, 0.06353242442392829, 0.09890012618019352, 0.1256434377282858, 0.023633090482855387, 0.22361290859143165, 0.1952914685534779, -0.027220404069918335, 0.07573304358580076, -0.08973206179110672, -0.020800444420522333, -0.18888933243513087, -0.18281193721420344, -0.08815302966765805, 0.055348796959316875, -0.054719888311410614, -0.18073847801761903, 0.3608989488989623, 0.078925230945143, 0.11493722175576047, 0.0031820618367584593, 0.26882685241501103, -0.004917235257876614, 0.16517551220286722, -0.015638458010719412, 0.18809448098181747, 0.08621961470461512, 0.13812517783265899, -0.19957442008705006, 0.14231848749808373, -0.004373543356037276] |
1,802.07451 | A two-class queueing system with constant retrial policy and general
class dependent service times | A single server retrial queueing system with two-classes of orbiting
customers, and general class dependent service times is considered. If an
arriving customer finds the server unavailable, it enters a virtual queue,
called the orbit, according to its type. The customers from the orbits retry
independently to access the server according to the constant retrial policy. We
derive the generating function of the stationary distribution of the number of
orbiting customers at service completion epochs in terms of the solution of a
Riemann boundary value problem. For the symmetrical system we also derived
explicit expressions for the expected delay in an orbit without solving a
boundary value problem. A simple numerical example is obtained to illustrate
the system's performance.
| math.PR | a single server retrial queueing system with twoclasses of orbiting customers and general class dependent service times is considered if an arriving customer finds the server unavailable it enters a virtual queue called the orbit according to its type the customers from the orbits retry independently to access the server according to the constant retrial policy we derive the generating function of the stationary distribution of the number of orbiting customers at service completion epochs in terms of the solution of a riemann boundary value problem for the symmetrical system we also derived explicit expressions for the expected delay in an orbit without solving a boundary value problem a simple numerical example is obtained to illustrate the systems performance | [['a', 'single', 'server', 'retrial', 'queueing', 'system', 'with', 'twoclasses', 'of', 'orbiting', 'customers', 'and', 'general', 'class', 'dependent', 'service', 'times', 'is', 'considered', 'if', 'an', 'arriving', 'customer', 'finds', 'the', 'server', 'unavailable', 'it', 'enters', 'a', 'virtual', 'queue', 'called', 'the', 'orbit', 'according', 'to', 'its', 'type', 'the', 'customers', 'from', 'the', 'orbits', 'retry', 'independently', 'to', 'access', 'the', 'server', 'according', 'to', 'the', 'constant', 'retrial', 'policy', 'we', 'derive', 'the', 'generating', 'function', 'of', 'the', 'stationary', 'distribution', 'of', 'the', 'number', 'of', 'orbiting', 'customers', 'at', 'service', 'completion', 'epochs', 'in', 'terms', 'of', 'the', 'solution', 'of', 'a', 'riemann', 'boundary', 'value', 'problem', 'for', 'the', 'symmetrical', 'system', 'we', 'also', 'derived', 'explicit', 'expressions', 'for', 'the', 'expected', 'delay', 'in', 'an', 'orbit', 'without', 'solving', 'a', 'boundary', 'value', 'problem', 'a', 'simple', 'numerical', 'example', 'is', 'obtained', 'to', 'illustrate', 'the', 'systems', 'performance']] | [-0.21629272696382107, 0.02845156639877965, -0.0855813346756231, 0.038854943754683645, -0.0885852547205922, -0.1998601872865267, 0.15511408783182376, 0.3295644120305401, -0.26571316732007605, -0.2740603741101858, 0.11643522275228273, -0.2876449311973856, -0.059913544301256665, 0.17387153447151749, -0.1289282391403465, 0.07468736835240833, 0.09178727155183482, 0.13287126320754686, -0.03194116237729851, -0.27815004609360855, 0.31084998207119835, 0.027542720141844088, 0.24800248322186663, -0.0017229714587393427, 0.11731783320986423, 0.037802656756385285, 0.026329407798118515, -0.0517494174557153, -0.12739556236094757, 0.041816782715002526, 0.23825364186185874, 0.14686271488400443, 0.2694906045119239, -0.4014305366719721, -0.14190310468709394, 0.07798037143862423, 0.11623503772948846, 0.04756288584556524, -0.026488128384309157, -0.30217569847317305, 0.09358622685873083, -0.24550739669107965, -0.17128233356448283, 0.061773882212289494, 0.053883977066099396, 0.037530937181206564, -0.32629287573939364, -0.02726809846011319, -0.030507391154327813, -0.009412123888198818, -0.12787688129186287, -0.07661657506979595, 0.0037097352275139643, 0.18309678493347412, 0.1135868910316597, -0.0038820869610214433, 0.1472532824816636, -0.09972247728655319, -0.08365501189494834, 0.4255709581765808, -0.05214818370207643, -0.19337827580816605, 0.14033736510617079, -0.07367132710559028, -0.13609811560382398, 0.1348929556337099, 0.1932439340920258, 0.115489740535116, -0.21965185586488298, 0.0534909156326228, -0.05698861929631064, 0.13965566658234896, 0.09013220391572774, -0.006471244831072527, 0.20019721818360023, 0.18235139317513138, 0.13496941224351025, 0.14709650847215613, -0.03742524913801741, -0.13555868922443198, -0.2772075506161992, -0.15411723209271097, -0.20325166709768047, 0.06409523251442974, -0.14126788813827712, -0.17243299274822743, 0.37015652763774665, 0.10742997466547399, 0.149592058825064, 0.15363960621385453, 0.30610188585119086, 0.19428721630648405, 0.008747239017999973, 0.17961901242007353, 0.10973814670622599, 0.03557421874299943, 0.14738338736488538, -0.2090873603842088, 0.12834413952248938, 0.07183672886873994] |
1,802.07452 | Spatial Morphing Kernel Regression For Feature Interpolation | In recent years, geotagged social media has become popular as a novel source
for geographic knowledge discovery. Ground-level images and videos provide a
different perspective than overhead imagery and can be applied to a range of
applications such as land use mapping, activity detection, pollution mapping,
etc. The sparse and uneven distribution of this data presents a problem,
however, for generating dense maps. We therefore investigate the problem of
spatially interpolating the high-dimensional features extracted from sparse
social media to enable dense labeling using standard classifiers. Further, we
show how prior knowledge about region boundaries can be used to improve the
interpolation through spatial morphing kernel regression. We show that an
interpolate-then-classify framework can produce dense maps from sparse
observations but that care must be taken in choosing the interpolation method.
We also show that the spatial morphing kernel improves the results.
| cs.CV | in recent years geotagged social media has become popular as a novel source for geographic knowledge discovery groundlevel images and videos provide a different perspective than overhead imagery and can be applied to a range of applications such as land use mapping activity detection pollution mapping etc the sparse and uneven distribution of this data presents a problem however for generating dense maps we therefore investigate the problem of spatially interpolating the highdimensional features extracted from sparse social media to enable dense labeling using standard classifiers further we show how prior knowledge about region boundaries can be used to improve the interpolation through spatial morphing kernel regression we show that an interpolatethenclassify framework can produce dense maps from sparse observations but that care must be taken in choosing the interpolation method we also show that the spatial morphing kernel improves the results | [['in', 'recent', 'years', 'geotagged', 'social', 'media', 'has', 'become', 'popular', 'as', 'a', 'novel', 'source', 'for', 'geographic', 'knowledge', 'discovery', 'groundlevel', 'images', 'and', 'videos', 'provide', 'a', 'different', 'perspective', 'than', 'overhead', 'imagery', 'and', 'can', 'be', 'applied', 'to', 'a', 'range', 'of', 'applications', 'such', 'as', 'land', 'use', 'mapping', 'activity', 'detection', 'pollution', 'mapping', 'etc', 'the', 'sparse', 'and', 'uneven', 'distribution', 'of', 'this', 'data', 'presents', 'a', 'problem', 'however', 'for', 'generating', 'dense', 'maps', 'we', 'therefore', 'investigate', 'the', 'problem', 'of', 'spatially', 'interpolating', 'the', 'highdimensional', 'features', 'extracted', 'from', 'sparse', 'social', 'media', 'to', 'enable', 'dense', 'labeling', 'using', 'standard', 'classifiers', 'further', 'we', 'show', 'how', 'prior', 'knowledge', 'about', 'region', 'boundaries', 'can', 'be', 'used', 'to', 'improve', 'the', 'interpolation', 'through', 'spatial', 'morphing', 'kernel', 'regression', 'we', 'show', 'that', 'an', 'interpolatethenclassify', 'framework', 'can', 'produce', 'dense', 'maps', 'from', 'sparse', 'observations', 'but', 'that', 'care', 'must', 'be', 'taken', 'in', 'choosing', 'the', 'interpolation', 'method', 'we', 'also', 'show', 'that', 'the', 'spatial', 'morphing', 'kernel', 'improves', 'the', 'results']] | [-0.026228950940178217, 0.024677035607771573, -0.09818033162002446, 0.08587281156004348, -0.12544296294820648, -0.10413936902735885, 0.039926962362245674, 0.47213007340617213, -0.3101966103492635, -0.3096697708981521, 0.1401256430392147, -0.27863002095886685, -0.20792331252616983, 0.19684745450933458, -0.12497993892389812, 0.06105192789827731, 0.12313625957579055, -0.006470274980838827, -0.06234121820493106, -0.2174371411208169, 0.30779658517872927, 0.028276084856202838, 0.3088724445551634, 0.056177837457111544, 0.10818121562536859, 0.00845852401437806, -0.09939145423630451, 0.01927033273489974, -0.0538873331701686, 0.17027976978999557, 0.3306496001248321, 0.22720333612656077, 0.29064763427203427, -0.4375732241607938, -0.32412725380549195, 0.12174845214417958, 0.1679235366140063, 0.10112983297147121, -0.07842606628406132, -0.3406709864246824, 0.06461796652631345, -0.15104006671310397, -0.056430185806494976, -0.13055951819434788, -0.032480643021028675, -0.0019840715834474627, -0.31666659814114057, 0.0554789506963616, 0.021480409558102858, 0.07133374472498788, -0.04578357196003463, -0.08035223721691691, 0.03135271953643425, 0.21529082755445905, 0.005572388529883209, 0.05075243875674956, 0.12859380640855705, -0.16502487689507664, -0.07428464510128008, 0.3860212845252232, -0.07046894247840566, -0.19244468913179102, 0.2035556022566578, -0.06925382867045965, -0.15656103892582104, 0.11015611583802928, 0.26449250032240196, 0.10136603096938454, -0.15759072973762792, 0.014219390386500864, -0.07739388605857149, 0.20207996615076582, 0.08570936158405128, 0.004905468847021355, 0.1763979207843225, 0.18247922608985545, 0.08581122275316387, 0.14139124498032166, -0.1631943561163143, -0.03536541202165028, -0.19118519807696766, -0.10525616585996979, -0.20576758158280917, -0.01048127342187238, -0.1431396413320578, -0.12808277084762956, 0.3742104408641656, 0.22277999359533085, 0.2382667052926139, 0.03927766535668931, 0.3102575791008929, 0.04366949997373348, 0.096977065277702, 0.09066804134821956, 0.1491272238195471, 0.023950674147852895, 0.12677476819644265, -0.10167488386418591, 0.07213549603004643, 0.03409406347266326] |
1,802.07453 | Hamiltonian delay equations -- examples and a lower bound for the number
of periodic solutions | We describe a variational approach to a notion of Hamiltonian delay
equations. Our delay Hamiltonians are of product form. We consider several
examples. For closed symplectically aspherical symplectic manifolds
$(M,\omega)$ we prove that for generic delay Hamiltonians the number of
1-periodic solutions of the Hamiltonian delay equation is at least the sum of
the Betti numbers of $M$, extending the proof of the Arnold conjecture to the
case with delay.
| math.DS math.SG | we describe a variational approach to a notion of hamiltonian delay equations our delay hamiltonians are of product form we consider several examples for closed symplectically aspherical symplectic manifolds momega we prove that for generic delay hamiltonians the number of 1periodic solutions of the hamiltonian delay equation is at least the sum of the betti numbers of m extending the proof of the arnold conjecture to the case with delay | [['we', 'describe', 'a', 'variational', 'approach', 'to', 'a', 'notion', 'of', 'hamiltonian', 'delay', 'equations', 'our', 'delay', 'hamiltonians', 'are', 'of', 'product', 'form', 'we', 'consider', 'several', 'examples', 'for', 'closed', 'symplectically', 'aspherical', 'symplectic', 'manifolds', 'momega', 'we', 'prove', 'that', 'for', 'generic', 'delay', 'hamiltonians', 'the', 'number', 'of', '1periodic', 'solutions', 'of', 'the', 'hamiltonian', 'delay', 'equation', 'is', 'at', 'least', 'the', 'sum', 'of', 'the', 'betti', 'numbers', 'of', 'm', 'extending', 'the', 'proof', 'of', 'the', 'arnold', 'conjecture', 'to', 'the', 'case', 'with', 'delay']] | [-0.2935320829174348, 0.06841453764853733, -0.04512461500375398, 0.05980463511077687, -0.0683297867753676, -0.1588771265133151, -0.0016364084157560552, 0.312203670998237, -0.26658186140869344, -0.2639871832881389, 0.04315681230343346, -0.2748559766814911, -0.16698346166605396, 0.2171085889284898, -0.10576144124248198, 0.052667983900755645, 0.12397501567445163, 0.07688572662217276, -0.11169073015917093, -0.2874235206982121, 0.4111296257802418, -0.07628950808596398, 0.13523730271429354, 0.060933466984092126, 0.14211361576536938, -0.03778485882628177, 0.05205548259296588, -0.005297306189978761, -0.18091679288159607, 0.0964008211091693, 0.219924948337887, 0.09960372204160584, 0.21518105694225856, -0.4069566815160215, -0.19590822699413235, 0.14265241105375545, 0.10590783005713351, 0.09641303211184485, 0.027467615180648865, -0.29915401800868235, 0.055919588021268805, -0.1706135755645976, -0.24099661385906593, -0.06412171418113367, 0.03827895241390381, 0.062278389491673025, -0.21619358169181005, 0.02821688491052815, 0.09921489372583372, 0.024750832348529782, -0.07427236538579954, -0.07674763013076569, -0.02942671167298353, 0.046880583551579286, 0.026387204427737742, -0.027759191639987486, 0.028900614879759295, -0.038407867115789224, -0.08328626580935504, 0.3791658579771008, -0.06383784701382475, -0.2663275192890848, 0.07298661423847079, -0.09351998689318342, -0.1781327098541494, 0.15451468072299446, 0.13912308742292226, 0.18024093150161208, -0.08856287121307105, 0.13903744166184748, -0.0776978041444506, 0.07907139870471187, 0.10235019111007984, 0.008875739235164864, 0.04857061802010451, 0.11632387100918484, 0.15478488081800088, 0.11679314201963799, 0.009031487369377698, -0.139574231037737, -0.3523079404341323, -0.23335146025887557, -0.17175932004715183, 0.19246867167364273, -0.1317133125716022, -0.16836996799600976, 0.39586496229083945, 0.04932322911252933, 0.1637930203561804, 0.20626267536676357, 0.2624928826599249, 0.1636947238293942, 0.00038670773085738933, 0.09068600532066609, 0.15263315432904553, 0.23547870721668004, 0.026658710138872267, -0.1949196353255372, -0.03960599476870682, 0.20863241172794786] |
1,802.07454 | Narrowband Bandpass Frequency Selective Surface with Miniaturized
Elements | This article presents a bandpass frequency selective surface (FSS) with a
narrowband frequency response. The designed FSS is made of miniaturized
elements unit cell. The operation principle of the FSS is explained by using an
equivalent circuit model, where the passband bandwidth can be controlled by the
values of the circuit elements corresponding to the geometrical dimensions of
the unit cell. The compatibility of the presented structure in designing higher
order narrowband filtering responses is verified by designing a second-order
bandpass FSS with 8:5% fractional bandwidth with a center frequency of 2:7 GHz.
| eess.SP | this article presents a bandpass frequency selective surface fss with a narrowband frequency response the designed fss is made of miniaturized elements unit cell the operation principle of the fss is explained by using an equivalent circuit model where the passband bandwidth can be controlled by the values of the circuit elements corresponding to the geometrical dimensions of the unit cell the compatibility of the presented structure in designing higher order narrowband filtering responses is verified by designing a secondorder bandpass fss with 85 fractional bandwidth with a center frequency of 27 ghz | [['this', 'article', 'presents', 'a', 'bandpass', 'frequency', 'selective', 'surface', 'fss', 'with', 'a', 'narrowband', 'frequency', 'response', 'the', 'designed', 'fss', 'is', 'made', 'of', 'miniaturized', 'elements', 'unit', 'cell', 'the', 'operation', 'principle', 'of', 'the', 'fss', 'is', 'explained', 'by', 'using', 'an', 'equivalent', 'circuit', 'model', 'where', 'the', 'passband', 'bandwidth', 'can', 'be', 'controlled', 'by', 'the', 'values', 'of', 'the', 'circuit', 'elements', 'corresponding', 'to', 'the', 'geometrical', 'dimensions', 'of', 'the', 'unit', 'cell', 'the', 'compatibility', 'of', 'the', 'presented', 'structure', 'in', 'designing', 'higher', 'order', 'narrowband', 'filtering', 'responses', 'is', 'verified', 'by', 'designing', 'a', 'secondorder', 'bandpass', 'fss', 'with', '85', 'fractional', 'bandwidth', 'with', 'a', 'center', 'frequency', 'of', '27', 'ghz']] | [-0.1618192103736463, 0.10412692549023202, 0.019450078064936302, -0.05788235401550698, -0.05166880394862865, -0.16874264828580363, 0.10720192015130994, 0.43560639876992474, -0.2468931077308552, -0.28952785325486974, 0.10973306886866808, -0.20789925844198273, -0.1294447662664317, 0.22111148236730005, -0.07537076990771037, 0.06646383956956592, 0.0034495088708667103, -0.04835942769998945, -0.055178108775327285, -0.16832144108290473, 0.25608659273774553, 0.09033344719078272, 0.32494307806094486, -0.018844657938086217, 0.0918278522008369, -0.017441701604634204, 0.006442888389511775, 0.03813821583565685, -0.08707642618138643, 0.14295228100031293, 0.28641982749855566, 0.021462211831002144, 0.2740003179223026, -0.3714877552282746, -0.21753070569567143, 0.017034102588020746, 0.08111227381103221, 0.039519818019001715, -0.021961198919402656, -0.26088610136260587, 0.0939674357012395, -0.14299186443289122, -0.14048307606830232, 0.02701553148567997, -0.02671195605709668, 0.03459039416104075, -0.28007170198527814, 0.01784412413635241, 0.04404643343220795, 0.0852967846627918, -0.04139953841685608, -0.09393015449806567, 0.011294015502977756, 0.09491807064141637, -0.0863680454879819, -0.004457786614175445, 0.14369079345456695, -0.05095917486425449, -0.12198499605179794, 0.3881186134161888, -0.04502244573712389, -0.18221892971640594, 0.10104168317110468, -0.14823804879360783, 0.011151528827125026, 0.18251828148320157, 0.12303812700694286, 0.0425209010680837, -0.17174304919805558, 0.07776784243923361, 0.016562236362807854, 0.2983250462760528, 0.10543325291045251, 0.07841331418102948, 0.19662017147407257, 0.18091915744126483, 0.06574127393566893, 0.14558244410086102, -0.15619735646071614, -0.012130160024890336, -0.2793383859598669, -0.13335024281555125, -0.1900226206528724, 0.03300128124093497, -0.07606783040088191, -0.13279791437690297, 0.45915811026208503, 0.08153164687676616, 0.17255596752448749, 0.022483227914699946, 0.2929783358128481, 0.2074839214353712, 0.14696394958563389, 0.016847663473898686, 0.23805911004823702, 0.13584214227364189, 0.09572134353220463, -0.25128461530191765, -0.02074342145914993, 0.030403520696626236] |
1,802.07455 | Asymptotic efficiency of restart and checkpointing | Many tasks are subject to failure before completion. Two of the most common
failure recovery strategies are restart and checkpointing. Under restart, once
a failure occurs, it is restarted from the beginning. Under checkpointing, the
task is resumed from the preceding checkpoint after the failure. We study
asymptotic efficiency of restart for an infinite sequence of tasks, whose sizes
form a stationary sequence. We define asymptotic efficiency as the limit of the
ratio of the total time to completion in the absence of failures over the total
time to completion when failures take place. Whether the asymptotic efficiency
is positive or not depends on the comparison of the tail of the distributions
of the task size and the random variables governing failures. Our framework
allows for variations in the failure rates and dependencies between task sizes.
We also study a similar notion of asymptotic efficiency for checkpointing when
the task is infinite a.s. and the inter-checkpoint times are i.i.d.. Moreover,
in checkpointing, when the failures are exponentially distributed, we prove the
existence of an infinite sequence of universal checkpoints, which are always
used whenever the system starts from any checkpoint that precedes them.
| math.PR cs.PF | many tasks are subject to failure before completion two of the most common failure recovery strategies are restart and checkpointing under restart once a failure occurs it is restarted from the beginning under checkpointing the task is resumed from the preceding checkpoint after the failure we study asymptotic efficiency of restart for an infinite sequence of tasks whose sizes form a stationary sequence we define asymptotic efficiency as the limit of the ratio of the total time to completion in the absence of failures over the total time to completion when failures take place whether the asymptotic efficiency is positive or not depends on the comparison of the tail of the distributions of the task size and the random variables governing failures our framework allows for variations in the failure rates and dependencies between task sizes we also study a similar notion of asymptotic efficiency for checkpointing when the task is infinite as and the intercheckpoint times are iid moreover in checkpointing when the failures are exponentially distributed we prove the existence of an infinite sequence of universal checkpoints which are always used whenever the system starts from any checkpoint that precedes them | [['many', 'tasks', 'are', 'subject', 'to', 'failure', 'before', 'completion', 'two', 'of', 'the', 'most', 'common', 'failure', 'recovery', 'strategies', 'are', 'restart', 'and', 'checkpointing', 'under', 'restart', 'once', 'a', 'failure', 'occurs', 'it', 'is', 'restarted', 'from', 'the', 'beginning', 'under', 'checkpointing', 'the', 'task', 'is', 'resumed', 'from', 'the', 'preceding', 'checkpoint', 'after', 'the', 'failure', 'we', 'study', 'asymptotic', 'efficiency', 'of', 'restart', 'for', 'an', 'infinite', 'sequence', 'of', 'tasks', 'whose', 'sizes', 'form', 'a', 'stationary', 'sequence', 'we', 'define', 'asymptotic', 'efficiency', 'as', 'the', 'limit', 'of', 'the', 'ratio', 'of', 'the', 'total', 'time', 'to', 'completion', 'in', 'the', 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1,802.07456 | Communication Using Eigenvalues of Higher Multiplicity of the Nonlinear
Fourier Transform | A generalized Nonlinear Fourier Transform (GNFT), which includes eigenvalues
of higher multiplicity, is considered for information transmission over fiber
optic channels. Numerical algorithms are developed to compute the direct and
inverse GNFTs. For closely-spaced eigenvalues, examples suggest that the GNFT
is more robust than the NFT to the practical impairments of truncation,
discretization, attenuation and noise. Communication using a soliton with one
double eigenvalue is numerically demonstrated, and its information rates are
compared to solitons with one and two simple eigenvalues.
| cs.IT math.AP math.IT | a generalized nonlinear fourier transform gnft which includes eigenvalues of higher multiplicity is considered for information transmission over fiber optic channels numerical algorithms are developed to compute the direct and inverse gnfts for closelyspaced eigenvalues examples suggest that the gnft is more robust than the nft to the practical impairments of truncation discretization attenuation and noise communication using a soliton with one double eigenvalue is numerically demonstrated and its information rates are compared to solitons with one and two simple eigenvalues | [['a', 'generalized', 'nonlinear', 'fourier', 'transform', 'gnft', 'which', 'includes', 'eigenvalues', 'of', 'higher', 'multiplicity', 'is', 'considered', 'for', 'information', 'transmission', 'over', 'fiber', 'optic', 'channels', 'numerical', 'algorithms', 'are', 'developed', 'to', 'compute', 'the', 'direct', 'and', 'inverse', 'gnfts', 'for', 'closelyspaced', 'eigenvalues', 'examples', 'suggest', 'that', 'the', 'gnft', 'is', 'more', 'robust', 'than', 'the', 'nft', 'to', 'the', 'practical', 'impairments', 'of', 'truncation', 'discretization', 'attenuation', 'and', 'noise', 'communication', 'using', 'a', 'soliton', 'with', 'one', 'double', 'eigenvalue', 'is', 'numerically', 'demonstrated', 'and', 'its', 'information', 'rates', 'are', 'compared', 'to', 'solitons', 'with', 'one', 'and', 'two', 'simple', 'eigenvalues']] | [-0.1389210935583553, 0.04726953014062765, -0.07797008045972922, 0.08278948074738042, -0.08765610578493813, -0.20595131124942923, -0.05121764094413569, 0.4218541939193622, -0.2457466770011263, -0.20803698104543564, 0.15729851039269796, -0.3008064442099287, -0.16977612122606772, 0.26312139586438066, -0.054339154169727594, 0.1082937216904098, 0.08616562730047661, 0.05327966042722647, -0.0666702404522743, -0.20658210096641993, 0.2910433540072961, 0.038410368762038745, 0.27131842168119663, 0.023152911528133046, 0.10210308574665433, -0.006076718647725498, -0.05947078994284265, -0.05776324420450972, -0.1102449844016892, 0.12522571219298512, 0.280005093326625, 0.046378597223128266, 0.2593227471344364, -0.38374481672564376, -0.2346457871250235, 0.10999758300395349, 0.1838730828335079, 0.11357586544741374, -0.045802439877335045, -0.2731359691078512, 0.11500565433883682, -0.1462611419459184, -0.11041931527404067, -0.0878923853727965, 0.0009473251680342051, 0.030631675599859312, -0.31732061357261276, 0.09425675816451892, 0.012860784363837387, 0.020500248254766353, -0.0032579008361491827, -0.13255520100490406, -0.016737579135224223, 0.07960310211787239, 0.0151999824328157, -0.11478332432213789, 0.0907678256253115, -0.08702314516099599, -0.11944849740785475, 0.3646080769144763, -0.01797357582855068, -0.25165427217068964, 0.15862272531450847, -0.11564550003132378, -0.01838353579529585, 0.19986642802802798, 0.16382926979508156, 0.10253057294549087, -0.10887589597722325, -0.0019105188459014664, 0.04226478479671268, 0.15882618142626223, 0.10007355580679499, 0.07364269636738567, 0.10259770028269252, 0.144355246068862, 0.09948466969534564, 0.13025323731394914, -0.10066959074435708, -0.12304173920972225, -0.2510411551204295, -0.14023648576142314, -0.21966314182067528, 0.00693663712650633, -0.11103042342606037, -0.147085816002427, 0.41328001698144734, 0.08121015241321845, 0.16270447806574595, 0.08786622814696808, 0.3721106855724102, 0.19936327101328435, 0.07007921554554158, 0.08418158352828752, 0.22683861984525067, 0.22298026089675915, 0.05781127049629457, -0.22827052347994864, -0.036763244905532934, 0.06246130041873608] |
1,802.07457 | The Security of the United Kingdom Electricity Imports under Conditions
of High European Demand | Energy policy in Europe has been driven by the three goals of security of
supply, economic competitiveness and environmental sustainability, referred to
as the energy trilemma. Although there are clear conflicts within the trilemma,
member countries have acted to facilitate a fully integrated European
electricity market. Interconnection and cross-border electricity trade has been
a fundamental part of such market liberalisation. However, it has been
suggested that consumers are exposed to a higher price volatility as a
consequence of interconnection. Furthermore, during times of energy shortages
and high demand, issues of national sovereignty take precedence over
cooperation. In this article, the unique and somewhat peculiar conditions of
early 2017 within France, Germany and the United Kingdom have been studied to
understand how the existing integration arrangements address the energy
trilemma. It is concluded that the dominant interests are economic and national
security; issues of environmental sustainability are neglected or overridden.
Although the optimisation of European electricity generation to achieve a lower
overall carbon emission is possible, such a goal is far from being realised.
Furthermore, it is apparent that the United Kingdom, and other countries,
cannot rely upon imports from other countries during periods of high demand
and/or limited supply.
| econ.EM q-fin.GN | energy policy in europe has been driven by the three goals of security of supply economic competitiveness and environmental sustainability referred to as the energy trilemma although there are clear conflicts within the trilemma member countries have acted to facilitate a fully integrated european electricity market interconnection and crossborder electricity trade has been a fundamental part of such market liberalisation however it has been suggested that consumers are exposed to a higher price volatility as a consequence of interconnection furthermore during times of energy shortages and high demand issues of national sovereignty take precedence over cooperation in this article the unique and somewhat peculiar conditions of early 2017 within france germany and the united kingdom have been studied to understand how the existing integration arrangements address the energy trilemma it is concluded that the dominant interests are economic and national security issues of environmental sustainability are neglected or overridden although the optimisation of european electricity generation to achieve a lower overall carbon emission is possible such a goal is far from being realised furthermore it is apparent that the united kingdom and other countries cannot rely upon imports from other countries during periods of high demand andor limited supply | [['energy', 'policy', 'in', 'europe', 'has', 'been', 'driven', 'by', 'the', 'three', 'goals', 'of', 'security', 'of', 'supply', 'economic', 'competitiveness', 'and', 'environmental', 'sustainability', 'referred', 'to', 'as', 'the', 'energy', 'trilemma', 'although', 'there', 'are', 'clear', 'conflicts', 'within', 'the', 'trilemma', 'member', 'countries', 'have', 'acted', 'to', 'facilitate', 'a', 'fully', 'integrated', 'european', 'electricity', 'market', 'interconnection', 'and', 'crossborder', 'electricity', 'trade', 'has', 'been', 'a', 'fundamental', 'part', 'of', 'such', 'market', 'liberalisation', 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1,802.07458 | Non-Asymptotic Bounds and a General Formula for the Rate-Distortion
Region of the Successive Refinement Problem | In the successive refinement problem, a fixed-length sequence emitted from an
information source is encoded into two codewords by two encoders in order to
give two reconstructions of the sequence. One of two reconstructions is
obtained by one of two codewords, and the other reconstruction is obtained by
all two codewords. For this coding problem, we give non-asymptotic inner and
outer bounds on pairs of numbers of codewords of two encoders such that each
probability that a distortion exceeds a given distortion level is less than a
given probability level. We also give a general formula for the rate-distortion
region for general sources, where the rate-distortion region is the set of rate
pairs of two encoders such that each maximum value of possible distortions is
less than a given distortion level.
| cs.IT math.IT | in the successive refinement problem a fixedlength sequence emitted from an information source is encoded into two codewords by two encoders in order to give two reconstructions of the sequence one of two reconstructions is obtained by one of two codewords and the other reconstruction is obtained by all two codewords for this coding problem we give nonasymptotic inner and outer bounds on pairs of numbers of codewords of two encoders such that each probability that a distortion exceeds a given distortion level is less than a given probability level we also give a general formula for the ratedistortion region for general sources where the ratedistortion region is the set of rate pairs of two encoders such that each maximum value of possible distortions is less than a given distortion level | [['in', 'the', 'successive', 'refinement', 'problem', 'a', 'fixedlength', 'sequence', 'emitted', 'from', 'an', 'information', 'source', 'is', 'encoded', 'into', 'two', 'codewords', 'by', 'two', 'encoders', 'in', 'order', 'to', 'give', 'two', 'reconstructions', 'of', 'the', 'sequence', 'one', 'of', 'two', 'reconstructions', 'is', 'obtained', 'by', 'one', 'of', 'two', 'codewords', 'and', 'the', 'other', 'reconstruction', 'is', 'obtained', 'by', 'all', 'two', 'codewords', 'for', 'this', 'coding', 'problem', 'we', 'give', 'nonasymptotic', 'inner', 'and', 'outer', 'bounds', 'on', 'pairs', 'of', 'numbers', 'of', 'codewords', 'of', 'two', 'encoders', 'such', 'that', 'each', 'probability', 'that', 'a', 'distortion', 'exceeds', 'a', 'given', 'distortion', 'level', 'is', 'less', 'than', 'a', 'given', 'probability', 'level', 'we', 'also', 'give', 'a', 'general', 'formula', 'for', 'the', 'ratedistortion', 'region', 'for', 'general', 'sources', 'where', 'the', 'ratedistortion', 'region', 'is', 'the', 'set', 'of', 'rate', 'pairs', 'of', 'two', 'encoders', 'such', 'that', 'each', 'maximum', 'value', 'of', 'possible', 'distortions', 'is', 'less', 'than', 'a', 'given', 'distortion', 'level']] | [-0.17669201940866827, 0.09123108670471382, -0.04724944921437907, 0.0891582932434745, -0.012055317302525953, -0.16853025293276283, 0.0659326842456402, 0.3580053418817866, -0.298225057887212, -0.2533556126513099, 0.10060008171099799, -0.30557853558975206, -0.11031841099233801, 0.20976262044815616, -0.07650223893037009, 0.022262480801312635, 0.04574252088653734, 0.1104073116470498, -0.09545576362915068, -0.2893891407191071, 0.3522761523908445, 0.056332908286393146, 0.24731079496812958, -0.010352852391718908, 0.12150973415016446, -0.002637664190287353, 0.014988494418447709, -0.011013198615485475, -0.12056673661789472, 0.14776089111918883, 0.2617230443266142, 0.19965419582382754, 0.261560388499487, -0.3543856163288801, -0.2203844782331148, 0.08679918914976466, 0.1259918991282568, 0.12127503133841029, -0.06138823025429778, -0.22230254739295435, 0.12537762313327602, -0.12696160683906033, 0.02537844753788628, 0.05670089634577033, -0.02647075867493644, 0.00010928661271019746, -0.3416894891455713, 0.045876414082963946, 0.07846658570222727, 0.018814280947300654, -0.0429828898049891, -0.14815379809126086, 0.00638431090131075, 0.1631128337475976, 0.019397828553781936, 0.08808802905246324, 0.0491875336300635, -0.10343686484052793, -0.11845384825390713, 0.35248198906201444, -0.016482396950840396, -0.2437436337518783, 0.12086790755661275, -0.15697693577718758, -0.10023655430662609, 0.19599063558688828, 0.14482408051755818, 0.11361187470380131, -0.15009429362666515, -0.01476970804901438, -0.05701189972318083, 0.20200444356972025, 0.13768857211329555, 0.10403099584389648, 0.19262839919169442, 0.11924953685845924, 0.115131531191549, 0.21842681230818994, -0.1193849959869279, -0.057168445267753665, -0.3195806336198144, -0.10523453561006156, -0.22457337460946292, -0.019049441214394933, -0.1469144393716146, -0.11687474400169422, 0.395885196094977, 0.08689512481614378, 0.2480258478868383, 0.12016080091671862, 0.3311940627954616, 0.09176764111418921, 0.012663489093876067, 0.10678840938329924, 0.17486184886976622, 0.10944509904348214, -0.0636362162816786, -0.1208919397935641, 0.08166712701306429, 0.13364227185601668] |
1,802.07459 | Matching Article Pairs with Graphical Decomposition and Convolutions | Identifying the relationship between two articles, e.g., whether two articles
published from different sources describe the same breaking news, is critical
to many document understanding tasks. Existing approaches for modeling and
matching sentence pairs do not perform well in matching longer documents, which
embody more complex interactions between the enclosed entities than a sentence
does. To model article pairs, we propose the Concept Interaction Graph to
represent an article as a graph of concepts. We then match a pair of articles
by comparing the sentences that enclose the same concept vertex through a
series of encoding techniques, and aggregate the matching signals through a
graph convolutional network. To facilitate the evaluation of long article
matching, we have created two datasets, each consisting of about 30K pairs of
breaking news articles covering diverse topics in the open domain. Extensive
evaluations of the proposed methods on the two datasets demonstrate significant
improvements over a wide range of state-of-the-art methods for natural language
matching.
| cs.CL cs.IR | identifying the relationship between two articles eg whether two articles published from different sources describe the same breaking news is critical to many document understanding tasks existing approaches for modeling and matching sentence pairs do not perform well in matching longer documents which embody more complex interactions between the enclosed entities than a sentence does to model article pairs we propose the concept interaction graph to represent an article as a graph of concepts we then match a pair of articles by comparing the sentences that enclose the same concept vertex through a series of encoding techniques and aggregate the matching signals through a graph convolutional network to facilitate the evaluation of long article matching we have created two datasets each consisting of about 30k pairs of breaking news articles covering diverse topics in the open domain extensive evaluations of the proposed methods on the two datasets demonstrate significant improvements over a wide range of stateoftheart methods for natural language matching | [['identifying', 'the', 'relationship', 'between', 'two', 'articles', 'eg', 'whether', 'two', 'articles', 'published', 'from', 'different', 'sources', 'describe', 'the', 'same', 'breaking', 'news', 'is', 'critical', 'to', 'many', 'document', 'understanding', 'tasks', 'existing', 'approaches', 'for', 'modeling', 'and', 'matching', 'sentence', 'pairs', 'do', 'not', 'perform', 'well', 'in', 'matching', 'longer', 'documents', 'which', 'embody', 'more', 'complex', 'interactions', 'between', 'the', 'enclosed', 'entities', 'than', 'a', 'sentence', 'does', 'to', 'model', 'article', 'pairs', 'we', 'propose', 'the', 'concept', 'interaction', 'graph', 'to', 'represent', 'an', 'article', 'as', 'a', 'graph', 'of', 'concepts', 'we', 'then', 'match', 'a', 'pair', 'of', 'articles', 'by', 'comparing', 'the', 'sentences', 'that', 'enclose', 'the', 'same', 'concept', 'vertex', 'through', 'a', 'series', 'of', 'encoding', 'techniques', 'and', 'aggregate', 'the', 'matching', 'signals', 'through', 'a', 'graph', 'convolutional', 'network', 'to', 'facilitate', 'the', 'evaluation', 'of', 'long', 'article', 'matching', 'we', 'have', 'created', 'two', 'datasets', 'each', 'consisting', 'of', 'about', '30k', 'pairs', 'of', 'breaking', 'news', 'articles', 'covering', 'diverse', 'topics', 'in', 'the', 'open', 'domain', 'extensive', 'evaluations', 'of', 'the', 'proposed', 'methods', 'on', 'the', 'two', 'datasets', 'demonstrate', 'significant', 'improvements', 'over', 'a', 'wide', 'range', 'of', 'stateoftheart', 'methods', 'for', 'natural', 'language', 'matching']] | [-0.10477383201435694, 0.02613739664342778, -0.047782194358513615, 0.09812479142912357, -0.13742952489999835, -0.09451874644460839, 0.054641293302490755, 0.43394747776737125, -0.24529936848358708, -0.37147925771564616, 0.031158141243728513, -0.34919699134814164, -0.1366016344335046, 0.18967816441374838, -0.050729940243366155, 0.019850379923323853, 0.12559133862081615, 0.06064692705143706, -0.07532962907527961, -0.280612219175467, 0.3371378784348008, -0.014801408106357045, 0.3489350540598172, 0.06911445070659707, 0.11002087189312677, -0.010906255812679204, -0.11131697813604281, 0.012280184973261945, -0.104750078392979, 0.16317909292772598, 0.32986957377425874, 0.20025171523896387, 0.3041902545041272, -0.400591777591324, -0.20407347845040863, 0.09727904040030903, 0.13997302444025178, 0.1066503474651185, 0.0030271258975794217, -0.3121752675379748, 0.0766517392870166, -0.18203920063487491, 0.04995297899134226, -0.06309628086482748, 0.03485425367014286, 0.013816123417584422, -0.23492917546536773, 0.01369096067378309, 0.07813395794136854, 0.08991691425604664, 0.007688157179433367, -0.09294069575609333, 0.03443322309165591, 0.1850804549725784, 0.04462476864078238, 0.057569546602602745, 0.11339908384180032, -0.16998257306664719, -0.2123385956554286, 0.38852051922021813, -0.06364557902830846, -0.1795371443622345, 0.21846559166514912, -0.047364284833951026, -0.14193672920802827, 0.0892115955368286, 0.20340450959835457, 0.10843292899123937, -0.19442695933423057, -0.018720900070830392, -0.08890207790948959, 0.20815221986065255, 0.12742983311362657, 0.021112078377797692, 0.22969346042282834, 0.2084589742401742, 0.01331765162114991, 0.12615406199688126, -0.024507621817692272, -0.07959026499667281, -0.253972919734111, -0.1102813973340281, -0.1855470681641112, -0.05210720651097211, -0.0848466405868805, -0.18098166085431144, 0.4513414975267297, 0.20512838611344558, 0.21351114998322837, 0.05192712786887998, 0.29002407914958894, -0.022241134767027236, 0.09028859689805703, 0.0759102059181155, 0.1165670567482814, 0.029577039903816507, 0.10431268319461541, -0.115060319489892, 0.04817710764509458, 0.05407063301322947] |
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