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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1,803.01367 | Wafer-scale fabrication and room-temperature experiments on
graphene-based gates for quantum computation | We have fabricated at wafer scale graphene-based configurations suitable for
implementing at room temperature one-qubit quantum gates and a modified
Deutsch-Jozsa algorithm. Our measurements confirmed the (quasi-)ballistic
nature of charge carrier propagation through both types of devices, which have
dimensions smaller than the room-temperature mean-free-path in graphene. As
such, both graphene-based configurations were found to be suitable for quantum
computation. These results are encouraging for demonstrating a miniaturized,
room-temperature quantum computer based on graphene.
| cond-mat.mes-hall quant-ph | we have fabricated at wafer scale graphenebased configurations suitable for implementing at room temperature onequbit quantum gates and a modified deutschjozsa algorithm our measurements confirmed the quasiballistic nature of charge carrier propagation through both types of devices which have dimensions smaller than the roomtemperature meanfreepath in graphene as such both graphenebased configurations were found to be suitable for quantum computation these results are encouraging for demonstrating a miniaturized roomtemperature quantum computer based on graphene | [['we', 'have', 'fabricated', 'at', 'wafer', 'scale', 'graphenebased', 'configurations', 'suitable', 'for', 'implementing', 'at', 'room', 'temperature', 'onequbit', 'quantum', 'gates', 'and', 'a', 'modified', 'deutschjozsa', 'algorithm', 'our', 'measurements', 'confirmed', 'the', 'quasiballistic', 'nature', 'of', 'charge', 'carrier', 'propagation', 'through', 'both', 'types', 'of', 'devices', 'which', 'have', 'dimensions', 'smaller', 'than', 'the', 'roomtemperature', 'meanfreepath', 'in', 'graphene', 'as', 'such', 'both', 'graphenebased', 'configurations', 'were', 'found', 'to', 'be', 'suitable', 'for', 'quantum', 'computation', 'these', 'results', 'are', 'encouraging', 'for', 'demonstrating', 'a', 'miniaturized', 'roomtemperature', 'quantum', 'computer', 'based', 'on', 'graphene']] | [-0.12895353078036695, 0.19181518563119745, -0.027789666890040844, -0.06091359586178048, 0.019418005504318187, -0.26487252559525437, 0.052738624395223685, 0.4728225717018988, -0.20194092523810026, -0.3240053126387097, 0.050764464951007046, -0.2669643047391563, -0.1393225437684639, 0.3431989284534309, 0.035064258210351563, 0.14916642329882127, 0.03874688362702727, -0.10781664160910893, -0.07181583356263267, -0.24008141802875577, 0.19328819440577077, 0.07010695319528364, 0.33968003345905123, 0.09716213757889597, 0.09283797846276413, -0.04154220624902361, 0.09196581626688508, 0.021310301208113495, -0.11717092730356632, 0.04924615117645747, 0.296784994494472, -0.08929750970816491, 0.22368575798070714, -0.4948726346168818, -0.24189250744923294, -0.007072748314287211, 0.11458759591442759, 0.198875484608957, -0.11998766097649177, -0.3052394041992925, 0.16473990807158723, -0.10346294558179137, -0.07413919228172351, -0.13270883658598806, 0.0009255745020267126, -0.02543018164264189, -0.20975922971863198, 0.03267967851354262, -0.006528373926443778, 0.07977913549748829, -0.009237814837605756, -0.15362273043373953, 0.01969467368719445, 0.05937196093460394, -0.10740465578478384, -0.04630623762244107, 0.2836245232941331, -0.09453965433105524, -0.19952486670651548, 0.35616652994743875, -0.0018706867147655528, -0.1508661882536536, 0.16265351378132362, -0.10169246891077696, -0.07296292327747152, 0.07677431358968385, 0.12102517476808783, 0.12389190866913949, -0.14707405774577245, 0.06244973626815261, 0.03317094979354659, 0.16438521328067557, 0.10859308121851771, 0.1788273436344556, 0.2613366158125368, 0.2068585076847592, 0.03643978103315709, 0.11884796891418109, -0.10283789910514511, -0.06533261590536583, -0.22569371912175337, -0.22322960909317574, -0.2537155415283868, 0.09585122799349798, -0.10892028750429351, -0.16287664490172993, 0.3944856358213803, 0.20522103761322796, 0.11133685355653634, 0.01528083294082584, 0.29026534332818277, 0.11573542318955013, 0.13543514494243003, 0.03071616030285588, 0.23623081307065347, 0.12180272140225547, 0.12838104455354246, -0.23572011724919886, 0.03435489534073182, -0.03365695363577657] |
1,803.01368 | Finite Length Analysis of Irregular Repetition Slotted ALOHA in the
Waterfall Region | A finite length analysis is introduced for irregular repetition slotted ALOHA
(IRSA) that enables to accurately estimate its performance in the
moderate-to-high packet loss probability regime, i.e., in the so-called
waterfall region. The analysis is tailored to the collision channel model,
which enables mapping the description of the successive interference
cancellation process onto the iterative erasure decoding of low-density
parity-check codes. The analysis provides accurate estimates of the packet loss
probability of IRSA in the waterfall region as demonstrated by Monte Carlo
simulations.
| cs.IT math.IT | a finite length analysis is introduced for irregular repetition slotted aloha irsa that enables to accurately estimate its performance in the moderatetohigh packet loss probability regime ie in the socalled waterfall region the analysis is tailored to the collision channel model which enables mapping the description of the successive interference cancellation process onto the iterative erasure decoding of lowdensity paritycheck codes the analysis provides accurate estimates of the packet loss probability of irsa in the waterfall region as demonstrated by monte carlo simulations | [['a', 'finite', 'length', 'analysis', 'is', 'introduced', 'for', 'irregular', 'repetition', 'slotted', 'aloha', 'irsa', 'that', 'enables', 'to', 'accurately', 'estimate', 'its', 'performance', 'in', 'the', 'moderatetohigh', 'packet', 'loss', 'probability', 'regime', 'ie', 'in', 'the', 'socalled', 'waterfall', 'region', 'the', 'analysis', 'is', 'tailored', 'to', 'the', 'collision', 'channel', 'model', 'which', 'enables', 'mapping', 'the', 'description', 'of', 'the', 'successive', 'interference', 'cancellation', 'process', 'onto', 'the', 'iterative', 'erasure', 'decoding', 'of', 'lowdensity', 'paritycheck', 'codes', 'the', 'analysis', 'provides', 'accurate', 'estimates', 'of', 'the', 'packet', 'loss', 'probability', 'of', 'irsa', 'in', 'the', 'waterfall', 'region', 'as', 'demonstrated', 'by', 'monte', 'carlo', 'simulations']] | [-0.21062080120017013, 0.04337143701191217, -0.1247048346011574, 0.10552647564057784, 0.016379745088023954, -0.19765202735876103, 0.10116075420280896, 0.3975901352802673, -0.2545457712643926, -0.24273934419524956, 0.07243261988560883, -0.22020379516733699, -0.14732526558947873, 0.15501737992660738, -0.0880959728916445, 0.11104757892997397, 0.10423859796228718, 0.012646270354828203, -0.11505746160891939, -0.22653274341340524, 0.22463415278099388, 0.26013259936393385, 0.35710065972329263, -0.010819244588422308, 0.06922312899554395, 0.07509607354919594, -0.05451095452060901, -0.12049262950488601, -0.14789154810639146, 0.054945640894303836, 0.26103858147882464, 0.1585063860998545, 0.2640382044286613, -0.37177911161792926, -0.3149683531373739, 0.02402248273109905, 0.211294383842902, 0.12935280762135937, -0.06289841512958687, -0.26502680901931713, 0.12474986191569681, -0.2362712677343782, -0.02969124515439911, 0.04780688930684364, -0.10023852543209691, 0.04966112621218325, -0.3507018484882113, 0.02130771265926221, 0.022849945721766317, -0.005250041824709399, 0.023647339923408287, -0.057623300791145804, 0.041115110055599584, 0.0899957187027749, -0.019520090668846527, 0.04415900775803679, 0.10086665130276458, -0.0687611664095557, -0.07701163737843912, 0.33329603678816144, -0.05377352182439203, -0.14782115722815675, 0.14915166583812672, -0.10634080202217741, -0.018152086670140188, 0.2645761262715222, 0.2270020111744483, 0.09538192196513515, -0.14924348038004107, 0.050937930481081986, 0.018896799119391357, 0.1505938554407064, 0.09405329998537719, 0.10483206427622452, 0.11639445983378374, 0.18246377422193805, 0.04852800337802506, 0.17799089885743177, -0.18317013762958617, -0.1982062110475388, -0.25869243320481605, -0.08739125807275182, -0.19702853285988053, -0.01732307052974735, -0.1323859307477363, -0.17637446218630276, 0.3770629681242877, 0.1355903428384518, 0.14426572343716063, 0.11076545257665531, 0.3766412910169372, 0.09738107937730354, 0.06705142362940922, 0.12849478876913886, 0.16155023970472884, 0.16014655184488832, 0.04689750713739805, -0.2642470107705568, 0.10995248936296227, 0.10448817624878812] |
1,803.01369 | Competing dynamics of single phosphorus dopant in graphene with electron
irradiation | Atomic-level structural changes in materials are important but challenging to
study. Here, we demonstrate the dynamics and the possibility of manipulating a
phosphorus dopant atom in graphene using scanning transmission electron
microscopy (STEM). The mechanisms of various processes are explored and
compared with those of other dopant species by first-principles calculations.
This work paves the way for designing a more precise and optimized protocol for
atomic engineering.
| cond-mat.mtrl-sci physics.atom-ph | atomiclevel structural changes in materials are important but challenging to study here we demonstrate the dynamics and the possibility of manipulating a phosphorus dopant atom in graphene using scanning transmission electron microscopy stem the mechanisms of various processes are explored and compared with those of other dopant species by firstprinciples calculations this work paves the way for designing a more precise and optimized protocol for atomic engineering | [['atomiclevel', 'structural', 'changes', 'in', 'materials', 'are', 'important', 'but', 'challenging', 'to', 'study', 'here', 'we', 'demonstrate', 'the', 'dynamics', 'and', 'the', 'possibility', 'of', 'manipulating', 'a', 'phosphorus', 'dopant', 'atom', 'in', 'graphene', 'using', 'scanning', 'transmission', 'electron', 'microscopy', 'stem', 'the', 'mechanisms', 'of', 'various', 'processes', 'are', 'explored', 'and', 'compared', 'with', 'those', 'of', 'other', 'dopant', 'species', 'by', 'firstprinciples', 'calculations', 'this', 'work', 'paves', 'the', 'way', 'for', 'designing', 'a', 'more', 'precise', 'and', 'optimized', 'protocol', 'for', 'atomic', 'engineering']] | [-0.10038614497040468, 0.16231272453720222, -0.0338642512406431, 0.03080501399565933, 0.0114420272701823, -0.20185828518900853, 0.10887220984502043, 0.46902833634348057, -0.26372572667062727, -0.33517860915901054, -0.023444610171770647, -0.29853763293697316, -0.19889228621414348, 0.23606700501265698, 0.02251353407445461, 0.10457791724422974, 0.021336335758331108, -0.13977800541098662, -0.07119608155465615, -0.1794649817244108, 0.2746779883085792, 0.10921711027761226, 0.33183496736629464, 0.08805511764653806, 0.040380394294746776, 0.03104290594138316, 0.00509166367935823, 0.02275808407827767, -0.15558123696289622, 0.19449700873074516, 0.2812978025424162, 0.0014918715442850518, 0.2598686167108479, -0.5513545924158239, -0.27039142833230323, -0.032885799198341906, 0.15347482602167598, 0.21404401963548875, -0.14667057588374166, -0.2360102131462364, 0.037542942647280086, -0.10549283212523407, -0.12340867703558127, -0.157565144307689, -0.01972126193455796, 0.023526569498258074, -0.20274226194414408, 0.04261566125857296, -0.021376476220008152, 0.11766879139161832, -0.10998352381067156, -0.09243628318741251, -0.020149213312291053, 0.09738476172353683, -0.02212232258170843, -0.01666939751516138, 0.25023746605156294, -0.11894901062765006, -0.13888494692631623, 0.4368328834647563, 0.012353263260212853, -0.12327196749288645, 0.20351506882249865, -0.15027808056755074, -0.11151660269876915, 0.08596271888783841, 0.10173935159596044, 0.157943107354552, -0.20767621256744684, 0.03512558782796389, 0.022235426976633912, 0.14187921933940986, 0.09662485692594479, 0.11965671419374534, 0.18956858973338533, 0.25020457036904437, 0.03970338522331483, 0.10109700405806887, -0.08752751165528351, -0.024019280973293665, -0.14034111184109724, -0.21457999488755838, -0.16073088605068067, 0.0504933595796352, -0.03887887854314124, -0.12089015824247652, 0.40211912528820226, 0.18789741175280494, 0.15445487387478352, -0.09861374970303098, 0.3108810683166775, 0.050140268968612844, 0.039254074513133785, -0.06757647453793394, 0.22773221249122227, 0.13151158338565547, 0.0769125449318272, -0.2577546016215833, 0.1337901194572949, -0.045873569741622724] |
1,803.0137 | A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization
with Nonsmooth Regularization | We propose a communication- and computation-efficient distributed
optimization algorithm using second-order information for solving ERM problems
with a nonsmooth regularization term. Current second-order and quasi-Newton
methods for this problem either do not work well in the distributed setting or
work only for specific regularizers. Our algorithm uses successive quadratic
approximations, and we describe how to maintain an approximation of the Hessian
and solve subproblems efficiently in a distributed manner. The proposed method
enjoys global linear convergence for a broad range of non-strongly convex
problems that includes the most commonly used ERMs, thus requiring lower
communication complexity. It also converges on non-convex problems, so has the
potential to be used on applications such as deep learning. Initial
computational results on convex problems demonstrate that our method
significantly improves on communication cost and running time over the current
state-of-the-art methods.
| math.OC cs.LG stat.ML | we propose a communication and computationefficient distributed optimization algorithm using secondorder information for solving erm problems with a nonsmooth regularization term current secondorder and quasinewton methods for this problem either do not work well in the distributed setting or work only for specific regularizers our algorithm uses successive quadratic approximations and we describe how to maintain an approximation of the hessian and solve subproblems efficiently in a distributed manner the proposed method enjoys global linear convergence for a broad range of nonstrongly convex problems that includes the most commonly used erms thus requiring lower communication complexity it also converges on nonconvex problems so has the potential to be used on applications such as deep learning initial computational results on convex problems demonstrate that our method significantly improves on communication cost and running time over the current stateoftheart methods | [['we', 'propose', 'a', 'communication', 'and', 'computationefficient', 'distributed', 'optimization', 'algorithm', 'using', 'secondorder', 'information', 'for', 'solving', 'erm', 'problems', 'with', 'a', 'nonsmooth', 'regularization', 'term', 'current', 'secondorder', 'and', 'quasinewton', 'methods', 'for', 'this', 'problem', 'either', 'do', 'not', 'work', 'well', 'in', 'the', 'distributed', 'setting', 'or', 'work', 'only', 'for', 'specific', 'regularizers', 'our', 'algorithm', 'uses', 'successive', 'quadratic', 'approximations', 'and', 'we', 'describe', 'how', 'to', 'maintain', 'an', 'approximation', 'of', 'the', 'hessian', 'and', 'solve', 'subproblems', 'efficiently', 'in', 'a', 'distributed', 'manner', 'the', 'proposed', 'method', 'enjoys', 'global', 'linear', 'convergence', 'for', 'a', 'broad', 'range', 'of', 'nonstrongly', 'convex', 'problems', 'that', 'includes', 'the', 'most', 'commonly', 'used', 'erms', 'thus', 'requiring', 'lower', 'communication', 'complexity', 'it', 'also', 'converges', 'on', 'nonconvex', 'problems', 'so', 'has', 'the', 'potential', 'to', 'be', 'used', 'on', 'applications', 'such', 'as', 'deep', 'learning', 'initial', 'computational', 'results', 'on', 'convex', 'problems', 'demonstrate', 'that', 'our', 'method', 'significantly', 'improves', 'on', 'communication', 'cost', 'and', 'running', 'time', 'over', 'the', 'current', 'stateoftheart', 'methods']] | [-0.047442923526050174, -0.051807932413003466, -0.07351752385105667, 0.06152635724266883, -0.10082411878080903, -0.19231324761674023, 0.042157034396423376, 0.419253450366196, -0.3378143473368044, -0.3122773334954231, 0.13024314748548457, -0.22957029346160698, -0.1897443076140126, 0.24026101218128199, -0.12302205837466687, 0.14555433160790743, 0.09537398095742083, -0.015057800921436021, -0.11775650284160266, -0.33098682669409807, 0.259679262740605, 0.007463979016630101, 0.26457982123289525, 0.070743962670204, 0.1395542638281873, 0.004704281788967226, 0.02003249257994458, 0.04985976104449103, -0.07095796487429533, 0.14545883987338512, 0.31639677378942893, 0.21210813904316098, 0.38152333899684576, -0.4283376791905882, -0.22851190363070456, 0.13499787977122216, 0.17470855479621314, 0.09257571389763683, -0.05831142614993766, -0.22010402635171794, 0.07280873006928469, -0.11865118409817417, -0.017399838356220203, -0.15671895918996492, -0.09406669048990622, 0.02974883378803919, -0.34270100556718913, 0.07243267534805994, 0.047033331330791385, -0.003880556114355399, -0.07228909966036462, -0.1411055848053049, 0.1009593535757934, 0.04929701600770425, 0.04016722832381239, 0.06425451165642185, 0.11350670068160347, -0.1029784355314273, -0.1471725667901067, 0.37317950887254614, -0.04975515652778626, -0.25882945675740315, 0.2086172950187482, 0.012929726808763824, -0.16022385818634075, 0.11631969329428629, 0.270203075941949, 0.21985632122116353, -0.13299362595611508, 0.12389559050865026, -0.015429550059733616, 0.1572371906047498, 0.015888238942378834, 0.005190606320536682, 0.0616779942014862, 0.18526201013583635, 0.2105451076699799, 0.11585358430148926, -0.02946885920549824, -0.14377300241165727, -0.24668665737777518, -0.09634376203209377, -0.21972796927287203, -0.051914320849417876, -0.11148078437247971, -0.16490371193925757, 0.3817203783335677, 0.16621956655570472, 0.14947515649154133, 0.16508516223183362, 0.37313512871311844, 0.12822166214396746, 0.07827377319209398, 0.17534325091654193, 0.21099042296207146, 0.07570440739906137, 0.1335362121623104, -0.2274422212065184, 0.08226274165824271, 0.07966387981508413] |
1,803.01371 | Minimizers of the p-oscillation functional | We define a family of functionals, called p-oscillation functionals, that can
be interpreted as discrete versions of the classical total variation functional
for p=1 and of the p-Dirichlet functionals for p>1. We introduce the notion of
minimizers and prove existence of solutions to the Dirichlet problem. Finally
we provide a description of Class A minimizers (i.e. minimizers under compact
perturbations) in dimension 1.
| math.AP | we define a family of functionals called poscillation functionals that can be interpreted as discrete versions of the classical total variation functional for p1 and of the pdirichlet functionals for p1 we introduce the notion of minimizers and prove existence of solutions to the dirichlet problem finally we provide a description of class a minimizers ie minimizers under compact perturbations in dimension 1 | [['we', 'define', 'a', 'family', 'of', 'functionals', 'called', 'poscillation', 'functionals', 'that', 'can', 'be', 'interpreted', 'as', 'discrete', 'versions', 'of', 'the', 'classical', 'total', 'variation', 'functional', 'for', 'p1', 'and', 'of', 'the', 'pdirichlet', 'functionals', 'for', 'p1', 'we', 'introduce', 'the', 'notion', 'of', 'minimizers', 'and', 'prove', 'existence', 'of', 'solutions', 'to', 'the', 'dirichlet', 'problem', 'finally', 'we', 'provide', 'a', 'description', 'of', 'class', 'a', 'minimizers', 'ie', 'minimizers', 'under', 'compact', 'perturbations', 'in', 'dimension', '1']] | [-0.1461381081551794, 0.03855071439888449, -0.12369875812662705, 0.1601571578292116, -0.017772052729983005, -0.06990596657288412, 0.009599189484311689, 0.30012339837248286, -0.3246215274933005, -0.2367476588115096, 0.11035628138004892, -0.2770323886145507, -0.14843107579696563, 0.1393146864739397, -0.11966539354762062, 0.07608870777391619, 0.033578005807113745, 0.042645238426743046, -0.10597406005892422, -0.2037597668860408, 0.36850938855880694, -0.0904625818854378, 0.20667924071031232, 0.04969929965614762, 0.10712442147515473, 0.023328727877308286, 0.06405982483298547, 0.07465739662368451, -0.24067916204430437, 0.1761087286117066, 0.25082513785450683, 0.09839250109038286, 0.34025078909772055, -0.39443882795110824, -0.22985278271258838, 0.2087930351375572, 0.06644636240596283, 0.03151071105798286, -0.014733830204932019, -0.2454434551914493, 0.16763211409711548, -0.12268693096965792, -0.18799622131947188, -0.14362810231414774, 0.013419878180889834, 0.12296483439070383, -0.30464002764182946, 0.114720041397959, 0.0875957106210051, 0.03445757542466445, -0.20843955450841495, -0.09746564186794023, -0.007955016226567808, 0.008909628131321722, 0.05872636358253658, -0.0018936979974950514, 0.0657450435110443, -0.08464936650688609, -0.12609446231245755, 0.36557056103934416, -0.11690698531475069, -0.29370244072690127, 0.14097974006266845, -0.07278988762728629, -0.19302002963940462, 0.05213473909234087, 0.16223880231771018, 0.19390583597123623, -0.1001456858169648, 0.173951709475894, -0.06263569538151065, 0.11122151247916683, 0.08397960356406627, 0.08984623536197169, 0.09765176087497704, 0.10793616303483085, 0.2266587694926608, 0.20208811332404072, -0.06733971778040511, -0.09232400051288066, -0.4051366811317782, -0.17933008797286498, -0.14327116292570868, 0.10032307542860508, -0.06255011979608811, -0.2484666117497029, 0.39380667890392, 0.05565288166737094, 0.157806076274644, 0.15949597550676234, 0.11609238065824273, 0.1392178388571577, 0.01858663048234678, 0.08801137631939303, 0.1422782211391736, 0.1214009065090889, -0.004122899124218571, -0.1283122458375029, 0.015948393952942664, 0.17524555239886527] |
1,803.01372 | Optimal Transmit Antenna Selection for Massive MIMO Wiretap Channels | In this paper, we study the impacts of transmit antenna selection on the
secrecy performance of massive MIMO systems. We consider a wiretap setting in
which a fixed number of transmit antennas are selected and then confidential
messages are transmitted over them to a multi-antenna legitimate receiver while
being overheard by a multi-antenna eavesdropper. For this setup, we derive an
accurate approximation of the instantaneous secrecy rate. Using this
approximation, it is shown that in some wiretap settings under antenna
selection the growth in the number of active antennas enhances the secrecy
performance of the system up to some optimal number and degrades it when this
optimal number is surpassed. This observation demonstrates that antenna
selection in some massive MIMO settings not only reduces the RF-complexity, but
also enhances the secrecy performance. We then consider various scenarios and
derive the optimal number of active antennas analytically using our
large-system approximation. Numerical investigations show an accurate match
between simulations and the analytic results.
| cs.IT math.IT | in this paper we study the impacts of transmit antenna selection on the secrecy performance of massive mimo systems we consider a wiretap setting in which a fixed number of transmit antennas are selected and then confidential messages are transmitted over them to a multiantenna legitimate receiver while being overheard by a multiantenna eavesdropper for this setup we derive an accurate approximation of the instantaneous secrecy rate using this approximation it is shown that in some wiretap settings under antenna selection the growth in the number of active antennas enhances the secrecy performance of the system up to some optimal number and degrades it when this optimal number is surpassed this observation demonstrates that antenna selection in some massive mimo settings not only reduces the rfcomplexity but also enhances the secrecy performance we then consider various scenarios and derive the optimal number of active antennas analytically using our largesystem approximation numerical investigations show an accurate match between simulations and the analytic results | [['in', 'this', 'paper', 'we', 'study', 'the', 'impacts', 'of', 'transmit', 'antenna', 'selection', 'on', 'the', 'secrecy', 'performance', 'of', 'massive', 'mimo', 'systems', 'we', 'consider', 'a', 'wiretap', 'setting', 'in', 'which', 'a', 'fixed', 'number', 'of', 'transmit', 'antennas', 'are', 'selected', 'and', 'then', 'confidential', 'messages', 'are', 'transmitted', 'over', 'them', 'to', 'a', 'multiantenna', 'legitimate', 'receiver', 'while', 'being', 'overheard', 'by', 'a', 'multiantenna', 'eavesdropper', 'for', 'this', 'setup', 'we', 'derive', 'an', 'accurate', 'approximation', 'of', 'the', 'instantaneous', 'secrecy', 'rate', 'using', 'this', 'approximation', 'it', 'is', 'shown', 'that', 'in', 'some', 'wiretap', 'settings', 'under', 'antenna', 'selection', 'the', 'growth', 'in', 'the', 'number', 'of', 'active', 'antennas', 'enhances', 'the', 'secrecy', 'performance', 'of', 'the', 'system', 'up', 'to', 'some', 'optimal', 'number', 'and', 'degrades', 'it', 'when', 'this', 'optimal', 'number', 'is', 'surpassed', 'this', 'observation', 'demonstrates', 'that', 'antenna', 'selection', 'in', 'some', 'massive', 'mimo', 'settings', 'not', 'only', 'reduces', 'the', 'rfcomplexity', 'but', 'also', 'enhances', 'the', 'secrecy', 'performance', 'we', 'then', 'consider', 'various', 'scenarios', 'and', 'derive', 'the', 'optimal', 'number', 'of', 'active', 'antennas', 'analytically', 'using', 'our', 'largesystem', 'approximation', 'numerical', 'investigations', 'show', 'an', 'accurate', 'match', 'between', 'simulations', 'and', 'the', 'analytic', 'results']] | [-0.27367561149919684, 0.017035825924127203, 0.007846911702259088, 0.024007976541646332, -0.04799230119219211, -0.253406765445331, 0.14163041232156648, 0.37749804132962944, -0.2129504310950223, -0.2653424241465091, 0.08484049642064759, -0.2795824165833988, -0.19241162829882938, 0.15597610288000677, -0.11219618143513799, 0.03939451784596859, 0.0342588806481756, 0.06295281648204697, -0.02392258305091089, -0.3373021801824417, 0.2881650044575598, 0.14000516860274437, 0.3465212789927552, -0.008274331532582571, 0.07406933036960524, 0.036807360749887184, 0.0034323865687905775, -0.03822824425339975, -0.1110919722515614, 0.05052212492962469, 0.3367655473318595, 0.1985239673910352, 0.2846672980770193, -0.37150793173062946, -0.2569831614325076, 0.0805703641726049, 0.19380322398393657, 0.10850566737195706, -0.08121675110700896, -0.2528038407606935, 0.12269574565594488, -0.22717013212124226, -0.036193403171053455, 0.01149311568013128, -0.11528712765164213, 0.06565709371711875, -0.3848860857600093, -0.01697847880527268, -0.012275208592598822, 0.0385654260645862, -0.03664416298241481, -0.11192566482296334, 0.06669377850334125, 0.1635583361417104, 0.07199681591016459, -0.046306315400597445, 0.09781214724478807, -0.10700190002184913, -0.048604285953663263, 0.3323778532916841, 0.016347651109731767, -0.28605980670976416, 0.1523744163022917, -0.1520841801524691, -0.10259727243173086, 0.18664469525942373, 0.27390078268370327, 0.10028895434498052, -0.15659360384561746, 0.03900725972108589, -0.07399063524042751, 0.2023044512154431, 0.0990711563639774, 0.13823169864783133, 0.13280597586546922, 0.17997816357226973, 0.13351011921847125, 0.19399208097609427, -0.10843836248835785, -0.10460145100390676, -0.25135103172197204, -0.11930708804783659, -0.23376706739266714, 0.03469295074660576, -0.13367802015596275, -0.03529783998336499, 0.31068412396182987, 0.19291323032460095, 0.10239696623412547, 0.13680119702612614, 0.4304482683677364, 0.09389424422916806, 0.01005228232005956, 0.1476345964661443, 0.26011199458487144, 0.13075756615410086, 0.06336196067665394, -0.23963316670190657, 0.05013211486849612, -0.0434504064693932] |
1,803.01373 | A Successive Optimization Approach to Pilot Design for Multi-Cell
Massive MIMO Systems | In this letter, we introduce a novel pilot design approach that minimizes the
total mean square errors of the minimum mean square error estimators of all
base stations (BSs) subject to the transmit power constraints of individual
users in the network, while tackling the pilot contamination in multi-cell
Massive MIMO systems. First, we decompose the original non-convex problem into
distributed optimization sub-problems at individual BSs, where each BS can
optimize its own pilot signals given the knowledge of pilot signals from the
remaining BSs. We then introduce a successive optimization approach to
transform each optimization sub-problem into a linear matrix inequality (LMI)
form, which is convex and can be solved by available optimization packages.
Simulation results confirm the fast convergence of the proposed approach and
prevails a benchmark scheme in terms of providing higher accuracy.
| cs.IT math.IT | in this letter we introduce a novel pilot design approach that minimizes the total mean square errors of the minimum mean square error estimators of all base stations bss subject to the transmit power constraints of individual users in the network while tackling the pilot contamination in multicell massive mimo systems first we decompose the original nonconvex problem into distributed optimization subproblems at individual bss where each bs can optimize its own pilot signals given the knowledge of pilot signals from the remaining bss we then introduce a successive optimization approach to transform each optimization subproblem into a linear matrix inequality lmi form which is convex and can be solved by available optimization packages simulation results confirm the fast convergence of the proposed approach and prevails a benchmark scheme in terms of providing higher accuracy | [['in', 'this', 'letter', 'we', 'introduce', 'a', 'novel', 'pilot', 'design', 'approach', 'that', 'minimizes', 'the', 'total', 'mean', 'square', 'errors', 'of', 'the', 'minimum', 'mean', 'square', 'error', 'estimators', 'of', 'all', 'base', 'stations', 'bss', 'subject', 'to', 'the', 'transmit', 'power', 'constraints', 'of', 'individual', 'users', 'in', 'the', 'network', 'while', 'tackling', 'the', 'pilot', 'contamination', 'in', 'multicell', 'massive', 'mimo', 'systems', 'first', 'we', 'decompose', 'the', 'original', 'nonconvex', 'problem', 'into', 'distributed', 'optimization', 'subproblems', 'at', 'individual', 'bss', 'where', 'each', 'bs', 'can', 'optimize', 'its', 'own', 'pilot', 'signals', 'given', 'the', 'knowledge', 'of', 'pilot', 'signals', 'from', 'the', 'remaining', 'bss', 'we', 'then', 'introduce', 'a', 'successive', 'optimization', 'approach', 'to', 'transform', 'each', 'optimization', 'subproblem', 'into', 'a', 'linear', 'matrix', 'inequality', 'lmi', 'form', 'which', 'is', 'convex', 'and', 'can', 'be', 'solved', 'by', 'available', 'optimization', 'packages', 'simulation', 'results', 'confirm', 'the', 'fast', 'convergence', 'of', 'the', 'proposed', 'approach', 'and', 'prevails', 'a', 'benchmark', 'scheme', 'in', 'terms', 'of', 'providing', 'higher', 'accuracy']] | [-0.17990481620309529, -0.04101992254835312, -0.06573740519686705, 0.029671438400530152, -0.08568101403458665, -0.1942250039049045, 0.13020372215520454, 0.35345947732631533, -0.3120062335980711, -0.3123606705900144, 0.09362801199571955, -0.24833496807970934, -0.18514090991682478, 0.10422307081796504, -0.1103679439018446, 0.0648006217308446, 0.09436518218609746, 0.004140949207875464, -0.09765363875431594, -0.3136104298652046, 0.22647236176611235, 0.07439302671010847, 0.297479560814315, -0.04672312372778025, 0.11574873536549232, 0.019008064152741873, -0.04391205565296803, -0.0005597755235309403, -0.05610198922033844, 0.1094014134525356, 0.3290401660061131, 0.2540707947410367, 0.38028796093745365, -0.4235468878583224, -0.19367075126480174, 0.10974081490809719, 0.19536696479966242, 0.04556977809320584, -0.03299459431458403, -0.25874257534742356, 0.11793276613440226, -0.17139895808779532, -0.031075240619894532, 0.012418177646274368, -0.10945316990492521, 0.05559709207974029, -0.37383728311569603, 0.06705572671705375, -0.01160845133924374, -0.0018270906319634783, -0.1005069171535541, -0.20179871280367176, 0.043138643837085475, 0.13973069680958158, 0.04144623577336056, -0.0002222548325166658, 0.12189618453590406, -0.03855967633253722, -0.08942822880375456, 0.3757578145436667, 0.005460132623988169, -0.2636004816878725, 0.08877969747409224, -0.0869424244561405, -0.12456979175374187, 0.18105670035713248, 0.3071898577389894, 0.11763529201486596, -0.21595778981982558, 0.03868819235013453, -0.03358257492590282, 0.1739661052712041, 0.04035023819068791, 0.04506089004981159, 0.17142205749879832, 0.19208008319320571, 0.18112905995092457, 0.18203458398390837, -0.10803448368312309, -0.10126324856515836, -0.2658915433506654, -0.10470347552111856, -0.2416969924673645, -0.015599803028076335, -0.10335716123291705, -0.06429862219288393, 0.3838198435778193, 0.11367827406135836, 0.10661978682641078, 0.13261219185725268, 0.40514091007687425, 0.12613096102658244, 0.06893221961325724, 0.11438887520106854, 0.1730666468427646, 0.11815545914384226, 0.07754940273481663, -0.26161460427877803, 0.0022768908749437994, 0.03300914091782437] |
1,803.01374 | A numerical method to solve a phaseless coefficient inverse problem from
a single measurement of experimental data | We propose in this paper a globally numerical method to solve a phaseless
coefficient inverse problem: how to reconstruct the spatially distributed
refractive index of scatterers from the intensity (modulus square) of the full
complex valued wave field at an array of light detectors located on a
measurement board. The propagation of the wave field is governed by the 3D
Helmholtz equation. Our method consists of two stages. On the first stage, we
use asymptotic analysis to obtain an upper estimate for the modulus of the
scattered wave field. This estimate allows us to approximately reconstruct the
wave field at the measurement board using an inversion formula. This reduces
the phaseless inverse scattering problem to the phased one. At the second
stage, we apply a recently developed globally convergent numerical method to
reconstruct the desired refractive index from the total wave obtained at the
first stage. Unlike the optimization approach, the two-stage method described
above is global in the sense that it does not require a good initial guess of
the true solution. We test our numerical method on both computationally
simulated and experimental data. Although experimental data are noisy, our
method produces quite accurate numerical results.
| math.AP | we propose in this paper a globally numerical method to solve a phaseless coefficient inverse problem how to reconstruct the spatially distributed refractive index of scatterers from the intensity modulus square of the full complex valued wave field at an array of light detectors located on a measurement board the propagation of the wave field is governed by the 3d helmholtz equation our method consists of two stages on the first stage we use asymptotic analysis to obtain an upper estimate for the modulus of the scattered wave field this estimate allows us to approximately reconstruct the wave field at the measurement board using an inversion formula this reduces the phaseless inverse scattering problem to the phased one at the second stage we apply a recently developed globally convergent numerical method to reconstruct the desired refractive index from the total wave obtained at the first stage unlike the optimization approach the twostage method described above is global in the sense that it does not require a good initial guess of the true solution we test our numerical method on both computationally simulated and experimental data although experimental data are noisy our method produces quite accurate numerical results | [['we', 'propose', 'in', 'this', 'paper', 'a', 'globally', 'numerical', 'method', 'to', 'solve', 'a', 'phaseless', 'coefficient', 'inverse', 'problem', 'how', 'to', 'reconstruct', 'the', 'spatially', 'distributed', 'refractive', 'index', 'of', 'scatterers', 'from', 'the', 'intensity', 'modulus', 'square', 'of', 'the', 'full', 'complex', 'valued', 'wave', 'field', 'at', 'an', 'array', 'of', 'light', 'detectors', 'located', 'on', 'a', 'measurement', 'board', 'the', 'propagation', 'of', 'the', 'wave', 'field', 'is', 'governed', 'by', 'the', '3d', 'helmholtz', 'equation', 'our', 'method', 'consists', 'of', 'two', 'stages', 'on', 'the', 'first', 'stage', 'we', 'use', 'asymptotic', 'analysis', 'to', 'obtain', 'an', 'upper', 'estimate', 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1,803.01375 | Tunability of electronic and optical properties of the Ba-Zr-S system
via dimensional reduction | Transition metal sulfide perovskites offer lower band gaps and greater
tunability than oxides, along with other desirable properties for applications.
Here we explore dimensional reduction as a tuning strategy using the
Ruddlesden-Popper phases in the Ba-Zr-S system as a model. The three
dimensional perovskite BaZrS$_3$ is a direct band semiconductor, with a band
gap of 1.5 eV suitable for solar photovoltaic application. However, the three
known members of the Ruddlesden-Popper series, are all indirect gap materials,
and additionally have lower fundamental band gaps. This is accompanied in the
case of by a band structure that is more favorable for carrier transport for
oriented samples. The layered Ruddlesden-Popper compounds, show significantly
anisotropic optical properties, as may be expected. The optical spectra show
tails at low energy, which may complicate experimental characterization of
these materials.
| cond-mat.mtrl-sci | transition metal sulfide perovskites offer lower band gaps and greater tunability than oxides along with other desirable properties for applications here we explore dimensional reduction as a tuning strategy using the ruddlesdenpopper phases in the bazrs system as a model the three dimensional perovskite bazrs_3 is a direct band semiconductor with a band gap of 15 ev suitable for solar photovoltaic application however the three known members of the ruddlesdenpopper series are all indirect gap materials and additionally have lower fundamental band gaps this is accompanied in the case of by a band structure that is more favorable for carrier transport for oriented samples the layered ruddlesdenpopper compounds show significantly anisotropic optical properties as may be expected the optical spectra show tails at low energy which may complicate experimental characterization of these materials | [['transition', 'metal', 'sulfide', 'perovskites', 'offer', 'lower', 'band', 'gaps', 'and', 'greater', 'tunability', 'than', 'oxides', 'along', 'with', 'other', 'desirable', 'properties', 'for', 'applications', 'here', 'we', 'explore', 'dimensional', 'reduction', 'as', 'a', 'tuning', 'strategy', 'using', 'the', 'ruddlesdenpopper', 'phases', 'in', 'the', 'bazrs', 'system', 'as', 'a', 'model', 'the', 'three', 'dimensional', 'perovskite', 'bazrs_3', 'is', 'a', 'direct', 'band', 'semiconductor', 'with', 'a', 'band', 'gap', 'of', '15', 'ev', 'suitable', 'for', 'solar', 'photovoltaic', 'application', 'however', 'the', 'three', 'known', 'members', 'of', 'the', 'ruddlesdenpopper', 'series', 'are', 'all', 'indirect', 'gap', 'materials', 'and', 'additionally', 'have', 'lower', 'fundamental', 'band', 'gaps', 'this', 'is', 'accompanied', 'in', 'the', 'case', 'of', 'by', 'a', 'band', 'structure', 'that', 'is', 'more', 'favorable', 'for', 'carrier', 'transport', 'for', 'oriented', 'samples', 'the', 'layered', 'ruddlesdenpopper', 'compounds', 'show', 'significantly', 'anisotropic', 'optical', 'properties', 'as', 'may', 'be', 'expected', 'the', 'optical', 'spectra', 'show', 'tails', 'at', 'low', 'energy', 'which', 'may', 'complicate', 'experimental', 'characterization', 'of', 'these', 'materials']] | [-0.1324319397445896, 0.15115883089566448, -0.0014527796390857405, 0.029251209931192165, -0.03358832999658664, -0.1532509362659211, 0.11143338588556943, 0.4690304604707328, -0.26131664813702343, -0.33853087717852065, 0.06473426137809137, -0.3057269298094716, -0.1745531200253554, 0.23498378638782402, 0.014932638741603107, 0.005982032571812622, 0.02195127489123465, -0.1118027233955884, -0.1356897777611148, -0.15997215037461626, 0.26624361747690967, 0.04529294043153752, 0.28790239524451716, 0.048554098631703214, -0.013882909805464153, -0.04820557576355361, 0.12539723095349, 0.014410648509177542, -0.14700964096613017, 0.13817005790414588, 0.28903180688356567, -0.10070382409110551, 0.22207203211852897, -0.40255836984640314, -0.2737243160648087, 0.017257469861753968, 0.13233929958180277, 0.06755111541666574, -0.11423247201310005, -0.20424274870066528, 0.09529972957306762, -0.1647122679562628, -0.11038798816103972, -0.08418372633888294, -0.01832959908309556, 0.005318897483934371, -0.24214644668817534, 0.06507443485937955, 0.024680197164274126, 0.0816871924983437, -0.13006564701075546, -0.21739506700435185, -0.07490405567587559, 0.057269539133083955, 0.018965855712703792, -0.037868389374583616, 0.12073858257184047, -0.12143441400535579, -0.12830216625264582, 0.4355355607690503, -0.02680056219983167, -0.043757820082472934, 0.2098497426428811, -0.1660928059182039, -0.09253205551289534, 0.1821618249554557, 0.12422318992610196, 0.10516966331949215, -0.1115014511662649, 0.07790362479574872, -0.013314013582661407, 0.17400043097303342, 0.029859759571130268, 0.16697495200809886, 0.2520687726863041, 0.23233756964727667, 0.08396065344799396, 0.11815310978350223, -0.09172711771813342, 0.020936755922032903, -0.16905451259568674, -0.2454053852991521, -0.20798096937777916, 0.03886474804779006, -0.0930987143029729, -0.21251084584429974, 0.4339221043739724, 0.10277193173666606, 0.14929379775181753, -0.03986602306333975, 0.2258996512947021, 0.10538938828790205, 0.0916979730107914, 0.006315612436791185, 0.27163776783059346, 0.09067482260439744, 0.09057162104899646, -0.1749668773867986, 0.09471509309897896, -0.008611066048282361] |
1,803.01376 | Homotopy Theory of linear coalgebras | We study extensively the homotopy theory of coalgebras. By coalgebras, we
mean the full theory of coalgebras: with counits and not necessarily locally
conilpotent. For example $\mathcal E_\infty$-coalgebras, $\mathcal
A_\infty$-coalgebras, $\mathcal L_\infty$-coalgebras etc. To do so, we define
the category of complete curved algebras -- where the notion of
quasi-isomorphims does not make sense -- and endow it with a model category
structure, equivalent to that of the category of coalgebras.
| math.AT math.CT math.KT | we study extensively the homotopy theory of coalgebras by coalgebras we mean the full theory of coalgebras with counits and not necessarily locally conilpotent for example mathcal e_inftycoalgebras mathcal a_inftycoalgebras mathcal l_inftycoalgebras etc to do so we define the category of complete curved algebras where the notion of quasiisomorphims does not make sense and endow it with a model category structure equivalent to that of the category of coalgebras | [['we', 'study', 'extensively', 'the', 'homotopy', 'theory', 'of', 'coalgebras', 'by', 'coalgebras', 'we', 'mean', 'the', 'full', 'theory', 'of', 'coalgebras', 'with', 'counits', 'and', 'not', 'necessarily', 'locally', 'conilpotent', 'for', 'example', 'mathcal', 'e_inftycoalgebras', 'mathcal', 'a_inftycoalgebras', 'mathcal', 'l_inftycoalgebras', 'etc', 'to', 'do', 'so', 'we', 'define', 'the', 'category', 'of', 'complete', 'curved', 'algebras', 'where', 'the', 'notion', 'of', 'quasiisomorphims', 'does', 'not', 'make', 'sense', 'and', 'endow', 'it', 'with', 'a', 'model', 'category', 'structure', 'equivalent', 'to', 'that', 'of', 'the', 'category', 'of', 'coalgebras']] | [-0.08696848391131921, 0.06287284010569706, -0.05661516268314286, 0.09498283058179147, -0.12606999201163877, -0.15045234258286655, -0.04451977824580602, 0.4319511270432761, -0.4132470470768484, -0.1711289581179506, 0.06423282601419046, -0.19152417468527952, -0.162675371492338, 0.09907626466310555, -0.21618552583580217, -0.07927056610810035, 0.08224344284584124, 0.16085906166611522, -0.097875416038953, -0.2284934641193655, 0.4520628099527323, 0.014130133743023951, 0.24492673369400797, 0.038377494683531535, 0.12369348012461243, 0.0321046418623265, -0.00479527334259315, 0.08642576938269264, -0.22085258726501983, 0.11728883066891947, 0.3082927539944649, 0.11271438436498019, 0.22609787741429033, -0.37778330465891596, -0.07012072872991364, 0.19800313761119137, 0.13649207175793973, 0.037153544440639744, 0.053109931972964354, -0.29084740318075725, 0.13561414750857334, -0.2628269783277629, -0.0705778169318695, -0.07828547215710084, 0.08678316905614779, -0.008159538861505236, -0.23384824262977805, -0.07542994123121555, 0.11505052314676119, 0.09950801375971148, -0.11130190162326802, -0.003537768441619295, -0.16072985674184043, 0.077894312588879, -0.09445774542682832, 0.01225655318844612, 0.1221738269263314, -0.08731888918290762, -0.1557559774267826, 0.38598481684245844, -0.06703811645804142, -0.23976178884957777, 0.12787071706120376, -0.18239526964978062, -0.1601924801132444, 0.0765155019859473, 0.027564031721064537, 0.20617288970529582, -0.047257556736109436, 0.22822965485234323, -0.12242266950268073, 0.07287049437449737, 0.008451177569275553, 0.09336624892823624, 0.13915975793144864, 0.11655911944355025, 0.007385515089316124, 0.09776138782388333, 0.07059470427956319, -0.10951857826192722, -0.3739735370671207, -0.1791647543255804, 0.004858865220960455, 0.13621830701110108, -0.016599095226741734, -0.256164745039617, 0.3314092378414264, 0.17661732604557817, 0.16320521460676735, 0.17937919081922507, 0.19512364607318444, 0.017403373960405588, 0.11074832057806128, 0.035661195926932676, 0.17008949366793263, 0.26411014214285056, 0.006422506927540808, -0.04944841689289068, -0.013870302898188433, 0.2156632530756972] |
1,803.01377 | Sets of universal sequences for the symmetric group and analogous
semigroups | A universal sequence for a group or semigroup $S$ is a sequence of words
$w_1, w_2, \ldots$ such that for any sequence $s_1, s_2, \ldots\in S$, the
equations $w_n = s_n$, $n\in \mathbb{N}$, can be solved simultaneously in $S$.
For example, Galvin showed that the sequence
$(a^{-1}(a^nba^{-n})b^{-1}(a^nb^{-1}a^{-n})ba)_{n\in\mathbb{N}}$ is universal
for the symmetric group Sym$(X)$ when $X$ is infinite, and Sierpi\'nski showed
that $(a ^ 2 b ^ 3 (abab ^ 3) ^ {n + 1} ab ^ 2 ab ^ 3)_{n\in \mathbb{N}}$ is
universal for the monoid $X ^ X$ of functions from the infinite set $X$ to
itself.
In this paper, we show that under some conditions, the set of universal
sequences for the symmetric group on an infinite set $X$ is independent of the
cardinality of $X$. More precisely, we show that if $Y$ is any set such that
$|Y| \geq |X|$, then every universal sequence for Sym$(X)$ is also universal
for Sym$(Y)$. If $|X| > 2 ^ {\aleph_0}$, then the converse also holds. It is
shown that an analogue of this theorem holds in the context of inverse
semigroups, where the role of the symmetric group is played by the symmetric
inverse monoid. In the general context of semigroups, the full transformation
monoid $X ^ X$ is the natural analogue of the symmetric group and the symmetric
inverse monoid. If $X$ and $Y$ are arbitrary infinite sets, then it is an open
question as to whether or not every sequence that is universal for $X ^ X$ is
also universal for $Y ^ Y$. However, we obtain a sufficient condition for a
sequence to be universal for $X ^ X$ which does not depend on the cardinality
of $X$. A large class of sequences satisfy this condition, and hence are
universal for $X ^ X$ for every infinite set $X$.
| math.GR | a universal sequence for a group or semigroup s is a sequence of words w_1 w_2 ldots such that for any sequence s_1 s_2 ldotsin s the equations w_n s_n nin mathbbn can be solved simultaneously in s for example galvin showed that the sequence a1anbanb1anb1anba_ninmathbbn is universal for the symmetric group symx when x is infinite and sierpinski showed that a 2 b 3 abab 3 n 1 ab 2 ab 3_nin mathbbn is universal for the monoid x x of functions from the infinite set x to itself in this paper we show that under some conditions the set of universal sequences for the symmetric group on an infinite set x is independent of the cardinality of x more precisely we show that if y is any set such that y geq x then every universal sequence for symx is also universal for symy if x 2 aleph_0 then the converse also holds it is shown that an analogue of this theorem holds in the context of inverse semigroups where the role of the symmetric group is played by the symmetric inverse monoid in the general context of semigroups the full transformation monoid x x is the natural analogue of the symmetric group and the symmetric inverse monoid if x and y are arbitrary infinite sets then it is an open question as to whether or not every sequence that is universal for x x is also universal for y y however we obtain a sufficient condition for a sequence to be universal for x x which does not depend on the cardinality of x a large class of sequences satisfy this condition and hence are universal for x x for every infinite set x | [['a', 'universal', 'sequence', 'for', 'a', 'group', 'or', 'semigroup', 's', 'is', 'a', 'sequence', 'of', 'words', 'w_1', 'w_2', 'ldots', 'such', 'that', 'for', 'any', 'sequence', 's_1', 's_2', 'ldotsin', 's', 'the', 'equations', 'w_n', 's_n', 'nin', 'mathbbn', 'can', 'be', 'solved', 'simultaneously', 'in', 's', 'for', 'example', 'galvin', 'showed', 'that', 'the', 'sequence', 'a1anbanb1anb1anba_ninmathbbn', 'is', 'universal', 'for', 'the', 'symmetric', 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1,803.01378 | Localization under Topological Uncertainty for Lane Identification of
Autonomous Vehicles | Autonomous vehicles (AVs) require accurate metric and topological location
estimates for safe, effective navigation and decision-making. Although many
high-definition (HD) roadmaps exist, they are not always accurate since public
roads are dynamic, shaped unpredictably by both human activity and nature.
Thus, AVs must be able to handle situations in which the topology specified by
the map does not agree with reality. We present the Variable Structure Multiple
Hidden Markov Model (VSM-HMM) as a framework for localizing in the presence of
topological uncertainty, and demonstrate its effectiveness on an AV where lane
membership is modeled as a topological localization process. VSM-HMMs use a
dynamic set of HMMs to simultaneously reason about location within a set of
most likely current topologies and therefore may also be applied to topological
structure estimation as well as AV lane estimation. In addition, we present an
extension to the Earth Mover's Distance which allows uncertainty to be taken
into account when computing the distance between belief distributions on
simplices of arbitrary relative sizes.
| cs.RO cs.AI | autonomous vehicles avs require accurate metric and topological location estimates for safe effective navigation and decisionmaking although many highdefinition hd roadmaps exist they are not always accurate since public roads are dynamic shaped unpredictably by both human activity and nature thus avs must be able to handle situations in which the topology specified by the map does not agree with reality we present the variable structure multiple hidden markov model vsmhmm as a framework for localizing in the presence of topological uncertainty and demonstrate its effectiveness on an av where lane membership is modeled as a topological localization process vsmhmms use a dynamic set of hmms to simultaneously reason about location within a set of most likely current topologies and therefore may also be applied to topological structure estimation as well as av lane estimation in addition we present an extension to the earth movers distance which allows uncertainty to be taken into account when computing the distance between belief distributions on simplices of arbitrary relative sizes | [['autonomous', 'vehicles', 'avs', 'require', 'accurate', 'metric', 'and', 'topological', 'location', 'estimates', 'for', 'safe', 'effective', 'navigation', 'and', 'decisionmaking', 'although', 'many', 'highdefinition', 'hd', 'roadmaps', 'exist', 'they', 'are', 'not', 'always', 'accurate', 'since', 'public', 'roads', 'are', 'dynamic', 'shaped', 'unpredictably', 'by', 'both', 'human', 'activity', 'and', 'nature', 'thus', 'avs', 'must', 'be', 'able', 'to', 'handle', 'situations', 'in', 'which', 'the', 'topology', 'specified', 'by', 'the', 'map', 'does', 'not', 'agree', 'with', 'reality', 'we', 'present', 'the', 'variable', 'structure', 'multiple', 'hidden', 'markov', 'model', 'vsmhmm', 'as', 'a', 'framework', 'for', 'localizing', 'in', 'the', 'presence', 'of', 'topological', 'uncertainty', 'and', 'demonstrate', 'its', 'effectiveness', 'on', 'an', 'av', 'where', 'lane', 'membership', 'is', 'modeled', 'as', 'a', 'topological', 'localization', 'process', 'vsmhmms', 'use', 'a', 'dynamic', 'set', 'of', 'hmms', 'to', 'simultaneously', 'reason', 'about', 'location', 'within', 'a', 'set', 'of', 'most', 'likely', 'current', 'topologies', 'and', 'therefore', 'may', 'also', 'be', 'applied', 'to', 'topological', 'structure', 'estimation', 'as', 'well', 'as', 'av', 'lane', 'estimation', 'in', 'addition', 'we', 'present', 'an', 'extension', 'to', 'the', 'earth', 'movers', 'distance', 'which', 'allows', 'uncertainty', 'to', 'be', 'taken', 'into', 'account', 'when', 'computing', 'the', 'distance', 'between', 'belief', 'distributions', 'on', 'simplices', 'of', 'arbitrary', 'relative', 'sizes']] | [-0.09756962858196912, 0.08810715722784428, -0.0760456882134983, 0.08380142932473973, -0.10754954527894205, -0.152167130237671, 0.06246948709259882, 0.4397009701665604, -0.2702645655022934, -0.34239041497084227, 0.12962464969393545, -0.21984049900387287, -0.1511572982410364, 0.16822942404048236, -0.13882293831557035, 0.05554574013186732, 0.04364044176569829, 0.053979974082022, -0.005138617063604408, -0.19639241633033663, 0.26878315727649765, 0.024482598677842003, 0.26145767137888026, 0.046622849423014985, 0.07770976923462568, 0.031376695534157936, -0.010061073294756088, 0.059206423716563164, -0.054113325710888165, 0.1378629127940671, 0.30155573312588263, 0.13455625936868743, 0.24733846719292077, -0.4169230026404627, -0.2493790788576007, 0.11668069718377383, 0.1600688236433956, 0.0645335148370853, 0.0039364786868011864, -0.3686221823717157, 0.09829647731261723, -0.18901409873259112, -0.10241829355981089, -0.09399115950094931, 0.050554005626701946, 0.008053992745099646, -0.270676342714719, 0.012732555740160134, 0.026238779122032804, 0.06070013049086838, -0.0829398005576381, -0.057623454532586035, -0.03682133367313354, 0.21417238211319217, 0.01522616976854448, 0.032841982219763324, 0.14425415221926277, -0.14116861804981123, -0.12081706517686447, 0.4123145528913786, -0.006803791419687596, -0.2334098659737995, 0.21008430554277518, -0.07682990500505901, -0.11711602425202727, 0.09780040570026771, 0.20970293277253707, 0.1080272565765137, -0.1749819121857096, 0.02956377312463398, -0.011903433944804198, 0.1703050306518421, 0.03264883986504918, 0.042434160147394956, 0.2467940108370826, 0.14495662762642358, 0.1372198016181673, 0.06758523545524275, -0.10836334273106221, -0.13311142973799373, -0.2648011317734155, -0.12079869830737483, -0.15896222657439382, 0.005408994836739801, -0.0891114769640174, -0.16984751250764185, 0.3299052124786558, 0.21430143802708973, 0.22851105739334315, 0.055363932570837666, 0.31789900101721286, 0.06488300525163526, 0.07278820729504029, 0.12049909156154502, 0.18456944492830768, 0.06264045693149621, 0.07091477530246432, -0.15804316885028544, 0.16598329243786408, 0.04890172003881272] |
1,803.01379 | AdS$_4$/CFT$_3$ for Unprotected Operators | We consider the four-point function of the lowest scalar in the stress-energy
tensor multiplet in $\mathcal{N}=8$ ABJ(M) theory \cite{Aharony:2008ug,
Aharony:2008gk}. At large central charge $c_T\sim N^{3/2}$, this correlator is
given by the corresponding holographic correlation function in 11d supergravity
on $AdS_4\times S^7$. We use Mellin space techniques to compute the leading
$1/c_T$ correction to anomalous dimensions and OPE coefficients of operators
that appear in this holographic correlator. For half and quarter-BPS operators,
we find exact agreement with previously computed localization results. For the
other BPS and non-BPS operators, our results match the $\mathcal{N}=8$
numerical bootstrap for ABJ(M) at large $c_T$, which provides a precise check
of unprotected observables in AdS/CFT.
| hep-th | we consider the fourpoint function of the lowest scalar in the stressenergy tensor multiplet in mathcaln8 abjm theory citeaharony2008ug aharony2008gk at large central charge c_tsim n32 this correlator is given by the corresponding holographic correlation function in 11d supergravity on ads_4times s7 we use mellin space techniques to compute the leading 1c_t correction to anomalous dimensions and ope coefficients of operators that appear in this holographic correlator for half and quarterbps operators we find exact agreement with previously computed localization results for the other bps and nonbps operators our results match the mathcaln8 numerical bootstrap for abjm at large c_t which provides a precise check of unprotected observables in adscft | [['we', 'consider', 'the', 'fourpoint', 'function', 'of', 'the', 'lowest', 'scalar', 'in', 'the', 'stressenergy', 'tensor', 'multiplet', 'in', 'mathcaln8', 'abjm', 'theory', 'citeaharony2008ug', 'aharony2008gk', 'at', 'large', 'central', 'charge', 'c_tsim', 'n32', 'this', 'correlator', 'is', 'given', 'by', 'the', 'corresponding', 'holographic', 'correlation', 'function', 'in', '11d', 'supergravity', 'on', 'ads_4times', 's7', 'we', 'use', 'mellin', 'space', 'techniques', 'to', 'compute', 'the', 'leading', '1c_t', 'correction', 'to', 'anomalous', 'dimensions', 'and', 'ope', 'coefficients', 'of', 'operators', 'that', 'appear', 'in', 'this', 'holographic', 'correlator', 'for', 'half', 'and', 'quarterbps', 'operators', 'we', 'find', 'exact', 'agreement', 'with', 'previously', 'computed', 'localization', 'results', 'for', 'the', 'other', 'bps', 'and', 'nonbps', 'operators', 'our', 'results', 'match', 'the', 'mathcaln8', 'numerical', 'bootstrap', 'for', 'abjm', 'at', 'large', 'c_t', 'which', 'provides', 'a', 'precise', 'check', 'of', 'unprotected', 'observables', 'in', 'adscft']] | [-0.12705607757517048, 0.1055217910599719, -0.03286390385221479, 0.14252443084787614, -0.03308557888782882, -0.14027293958209175, -0.049144350169094735, 0.28719686081562684, -0.07574951565244568, -0.23144982923876564, 0.0967685568688947, -0.3506722731498193, -0.1716594540970927, 0.10106789302201678, -0.006426579257438205, 0.1003431846334968, -0.006754559719548473, 0.059401053741996016, -0.17569190861639689, -0.24569379786284254, 0.3403452067275725, -0.0007404049963883634, 0.2772981916677277, 0.0989597291281482, 0.07688687059518723, 0.034959945414777635, -0.04744678987481166, -0.03163370067052727, -0.15102811587595805, 0.13486729807633344, 0.2722308278445677, 0.04810974577042046, 0.057953693152774335, -0.45521974549540933, -0.14526914054185222, 0.0601065906757524, 0.2001012702085921, 0.1438485959375646, 0.03716817815713409, -0.23673452604737766, 0.06772607616104959, -0.1979414953911712, -0.19576029643363688, -0.1412436158027289, 0.037862583943247305, -0.1414628172258161, -0.3107191115587001, 0.14509691998257107, -0.09788136072632558, -0.002714421881257363, -0.058161306054384077, -0.11346992338762645, -0.059105689066268924, 0.12423639784496769, 0.12119899297524069, 0.09863972594908807, 0.10816079383509515, -0.19603367950679418, -0.15724905846774456, 0.2536523763775685, -0.10584210365887661, -0.22952297773598782, 0.10877214960165252, -0.22392331811880586, -0.2217017103794892, 0.06421110443419444, 0.07802831867867906, 0.18519347925922494, -0.11191149801015854, 0.21124204981661365, -0.0355802839973344, 0.12780467712733332, 0.11606727452632391, 0.08418616324267515, 0.22193782587693828, 0.03644670723752944, 0.024870561224404054, 0.1849336473250384, -0.010307746185956276, -0.0967826718499638, -0.4379673972022983, -0.121697266139134, -0.16995237298520668, 0.07875068850358422, -0.22071121296505467, -0.19022419382730182, 0.3699557127668259, 0.15307901033534194, 0.18856635916470726, 0.12276684964308515, 0.20927775897226245, 0.1614909850309146, 0.15230708061893172, 0.08807860563052292, 0.2638458982582274, 0.15213329688303243, 0.1398304500221714, -0.274304535423344, -0.16123347955740513, 0.24525392698651216] |
1,803.0138 | Traveling Wave Solutions to a Neural Field Model With Oscillatory
Synaptic Coupling Types | In this paper, we investigate the existence, uniqueness, and spectral
stability of traveling waves arising from a single threshold neural field model
with one spatial dimension, a Heaviside firing rate function, axonal
propagation delay, and biologically motivated oscillatory coupling types.
Neuronal tracing studies show that long-ranged excitatory connections form
stripe-like patterns throughout the mammalian cortex; thus, we aim to
generalize the notions of pure excitation, lateral inhibition, and lateral
excitation by allowing coupling types to spatially oscillate between excitation
and inhibition. In turn, we hope to analyze traveling fronts and pulses with
novel shapes. With fronts as our main focus, we exploit Heaviside firing rate
functions in order to establish existence and utilize speed index functions
with at most one critical point as a tool for showing uniqueness of wave speed.
We are able to construct Evans functions, the so-called stability index
functions, in order to provide positive spectral stability results. Finally, we
show that by incorporating slow linear feedback, we can compute fast pulses
numerically with phase space dynamics that are similar to their corresponding
singular homoclinical orbits; hence, our work answers open problems and
provides insight into new ones.
| math.DS | in this paper we investigate the existence uniqueness and spectral stability of traveling waves arising from a single threshold neural field model with one spatial dimension a heaviside firing rate function axonal propagation delay and biologically motivated oscillatory coupling types neuronal tracing studies show that longranged excitatory connections form stripelike patterns throughout the mammalian cortex thus we aim to generalize the notions of pure excitation lateral inhibition and lateral excitation by allowing coupling types to spatially oscillate between excitation and inhibition in turn we hope to analyze traveling fronts and pulses with novel shapes with fronts as our main focus we exploit heaviside firing rate functions in order to establish existence and utilize speed index functions with at most one critical point as a tool for showing uniqueness of wave speed we are able to construct evans functions the socalled stability index functions in order to provide positive spectral stability results finally we show that by incorporating slow linear feedback we can compute fast pulses numerically with phase space dynamics that are similar to their corresponding singular homoclinical orbits hence our work answers open problems and provides insight into new ones | [['in', 'this', 'paper', 'we', 'investigate', 'the', 'existence', 'uniqueness', 'and', 'spectral', 'stability', 'of', 'traveling', 'waves', 'arising', 'from', 'a', 'single', 'threshold', 'neural', 'field', 'model', 'with', 'one', 'spatial', 'dimension', 'a', 'heaviside', 'firing', 'rate', 'function', 'axonal', 'propagation', 'delay', 'and', 'biologically', 'motivated', 'oscillatory', 'coupling', 'types', 'neuronal', 'tracing', 'studies', 'show', 'that', 'longranged', 'excitatory', 'connections', 'form', 'stripelike', 'patterns', 'throughout', 'the', 'mammalian', 'cortex', 'thus', 'we', 'aim', 'to', 'generalize', 'the', 'notions', 'of', 'pure', 'excitation', 'lateral', 'inhibition', 'and', 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1,803.01381 | Generalized Information Ratio | Alpha-based performance evaluation may fail to capture correlated residuals
due to model errors. This paper proposes using the Generalized Information
Ratio (GIR) to measure performance under misspecified benchmarks. Motivated by
the theoretical link between abnormal returns and residual covariance matrix,
GIR is derived as alphas scaled by the inverse square root of residual
covariance matrix. GIR nests alphas and Information Ratio as special cases,
depending on the amount of information used in the residual covariance matrix.
We show that GIR is robust to various degrees of model misspecification and
produces stable out-of-sample returns. Incorporating residual correlations
leads to substantial gains that alleviate model error concerns of active
management.
| q-fin.PM stat.ME | alphabased performance evaluation may fail to capture correlated residuals due to model errors this paper proposes using the generalized information ratio gir to measure performance under misspecified benchmarks motivated by the theoretical link between abnormal returns and residual covariance matrix gir is derived as alphas scaled by the inverse square root of residual covariance matrix gir nests alphas and information ratio as special cases depending on the amount of information used in the residual covariance matrix we show that gir is robust to various degrees of model misspecification and produces stable outofsample returns incorporating residual correlations leads to substantial gains that alleviate model error concerns of active management | [['alphabased', 'performance', 'evaluation', 'may', 'fail', 'to', 'capture', 'correlated', 'residuals', 'due', 'to', 'model', 'errors', 'this', 'paper', 'proposes', 'using', 'the', 'generalized', 'information', 'ratio', 'gir', 'to', 'measure', 'performance', 'under', 'misspecified', 'benchmarks', 'motivated', 'by', 'the', 'theoretical', 'link', 'between', 'abnormal', 'returns', 'and', 'residual', 'covariance', 'matrix', 'gir', 'is', 'derived', 'as', 'alphas', 'scaled', 'by', 'the', 'inverse', 'square', 'root', 'of', 'residual', 'covariance', 'matrix', 'gir', 'nests', 'alphas', 'and', 'information', 'ratio', 'as', 'special', 'cases', 'depending', 'on', 'the', 'amount', 'of', 'information', 'used', 'in', 'the', 'residual', 'covariance', 'matrix', 'we', 'show', 'that', 'gir', 'is', 'robust', 'to', 'various', 'degrees', 'of', 'model', 'misspecification', 'and', 'produces', 'stable', 'outofsample', 'returns', 'incorporating', 'residual', 'correlations', 'leads', 'to', 'substantial', 'gains', 'that', 'alleviate', 'model', 'error', 'concerns', 'of', 'active', 'management']] | [-0.051891630593066417, 0.04361267369111172, -0.047069410612392754, 0.1376563209826903, -0.05496200017148146, -0.1602129901724833, 0.055486897894836684, 0.3845619051889689, -0.29459055054812106, -0.2959857867713759, 0.11984195554935097, -0.2918478768530164, -0.18424014716637666, 0.13278020068753027, -0.18003102386784223, 0.0644556284468207, 0.0710917377922063, 0.003990363726323402, -0.13414157647639513, -0.25756429738572073, 0.2628732869418821, 0.15324090338738947, 0.34678645828669824, 0.020930091142805328, 0.12344133477933981, 0.00776964738421763, -0.07472550844842638, 0.02793881635913446, -0.056995384714860445, 0.1231191371183808, 0.249828928104964, 0.13991107195788235, 0.2760695979102618, -0.3769813157893993, -0.18988492800336745, 0.16926963365835104, 0.1050045100252006, 0.021602142791919136, 0.011169418721692637, -0.261701792564795, 0.0818225438879044, -0.18556973523960482, -0.08100595454150741, -0.11951773787451977, -0.024249933698835473, -0.012057440583939079, -0.36520970948212955, 0.17574827944540797, 0.06138322046630223, 0.04572066861739451, 0.021402011394793925, -0.20997618496875037, 0.03244911993021594, 0.14424919850555146, 0.12967013901517796, -0.03928812561207451, 0.15532042807468247, -0.09441490177737756, -0.07403024412363905, 0.3452806885837129, -0.07442321580256922, -0.241804530714742, 0.07633241353323683, -0.06520131724472675, -0.08371129582843019, 0.12908420973798018, 0.2355803274118376, -0.01886107121956431, -0.15775897318531792, 0.03892857574747824, -0.018436117891084264, 0.22043820680981432, 0.00793627145079275, 0.030146399292991392, 0.13708703144436218, 0.1421151678767745, 0.07793050083327452, 0.14723875673263576, -0.13994649209726723, -0.1382982964515341, -0.26269825365549576, -0.08101141599386379, -0.18378144297619453, 0.031005031200712203, -0.15838464546942743, -0.1628690516722768, 0.3704549464509236, 0.19848435772776915, 0.18330149407739993, 0.09041923529002815, 0.29558735592635693, 0.08782844534963025, 0.05517705997031212, 0.07060994676969669, 0.19184361584053408, 0.15292792869473082, 0.01745158178662812, -0.23098016977827582, 0.15927731708722637, 0.0404148023808375] |
1,803.01382 | Oxygen vacancies and hydrogen doping in LaAlO3/SrTiO3 heterostructures:
electronic properties and impact on surface and interface reconstruction | We investigate the effect of oxygen vacancies and hydrogen dopants at the
surface and inside slabs of LaAlO3, SrTiO3, and LaAlO3/SrTiO3 heterostructures
on the electronic properties by means of electronic structure calculations as
based on density functional theory. Depending on the concentration, the
presence of these defects in LaAlO3 slab can suppress the surface conductivity.
In contrast, in insulating SrTiO3 slabs already very small concentrations of
oxygen vacancies or hydrogen dopant atoms induce a finite occupation of the
conduction band. Surface defects in insulating LaAlO3/SrTiO3 heterostructure
slabs with three LaAlO3 overlayers lead to the emergence of interface
conductivity. Calculated defect formation energies reveal strong preference of
hydrogen dopant atoms for surface sites for all structures and concentrations
considered. Strong decrease of the defect formation energy of hydrogen adatoms
with increasing thickness of the LaAlO3 overlayer and crossover from positive
to negative values, taken together with the metallic conductivity induced by
hydrogen adatoms, seamlessly explains the semiconductor-metal transition
observed for these heterostructures as a function of the overlayer thickness.
Moreover, we show that the potential drop and concomitant shift of (layer
resolved) band edges is suppressed for the metallic configuration. Finally,
magnetism with stable local moments, which form atomically thin magnetic layers
at the interface, is generated by oxygen vacancies either at the surface or the
interface, or by hydrogen atoms buried at the interface. In particular, oxygen
vacancies in the TiO2 interface layer cause drastic downshift of the 3d e_g
states of the Ti atoms neighboring the vacancies, giving rise to strongly
localized magnetic moments, which add to the two-dimensional background
magnetization.
| cond-mat.str-el cond-mat.mtrl-sci | we investigate the effect of oxygen vacancies and hydrogen dopants at the surface and inside slabs of laalo3 srtio3 and laalo3srtio3 heterostructures on the electronic properties by means of electronic structure calculations as based on density functional theory depending on the concentration the presence of these defects in laalo3 slab can suppress the surface conductivity in contrast in insulating srtio3 slabs already very small concentrations of oxygen vacancies or hydrogen dopant atoms induce a finite occupation of the conduction band surface defects in insulating laalo3srtio3 heterostructure slabs with three laalo3 overlayers lead to the emergence of interface conductivity calculated defect formation energies reveal strong preference of hydrogen dopant atoms for surface sites for all structures and concentrations considered strong decrease of the defect formation energy of hydrogen adatoms with increasing thickness of the laalo3 overlayer and crossover from positive to negative values taken together with the metallic conductivity induced by hydrogen adatoms seamlessly explains the semiconductormetal transition observed for these heterostructures as a function of the overlayer thickness moreover we show that the potential drop and concomitant shift of layer resolved band edges is suppressed for the metallic configuration finally magnetism with stable local moments which form atomically thin magnetic layers at the interface is generated by oxygen vacancies either at the surface or the interface or by hydrogen atoms buried at the interface in particular oxygen vacancies in the tio2 interface layer cause drastic downshift of the 3d e_g states of the ti atoms neighboring the vacancies giving rise to strongly localized magnetic moments which add to the twodimensional background magnetization | [['we', 'investigate', 'the', 'effect', 'of', 'oxygen', 'vacancies', 'and', 'hydrogen', 'dopants', 'at', 'the', 'surface', 'and', 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1,803.01383 | Algebraic construction of higher order difference approximations for
fractional derivatives and applications | A generalization of the Gr\"{u}nwald difference approximation for fractional
derivatives in terms of a real sequence and its generating function is
presented. Properties of the generating function are derived for consistency
and order of accuracy for the approximation corresponding to the generator.
Using this generalization, some higher order Gr\"{u}nwald type approximations
are constructed and tested for numerical stability by using steady state
fractional differential problems. These higher order approximations are used in
Crank-Nicolson type numerical schemes to approximate the solution of space
fractional diffusion equations. Stability and convergence of these numerical
schemes are analyzed and are supported by numerical examples.
| math.NA | a generalization of the grunwald difference approximation for fractional derivatives in terms of a real sequence and its generating function is presented properties of the generating function are derived for consistency and order of accuracy for the approximation corresponding to the generator using this generalization some higher order grunwald type approximations are constructed and tested for numerical stability by using steady state fractional differential problems these higher order approximations are used in cranknicolson type numerical schemes to approximate the solution of space fractional diffusion equations stability and convergence of these numerical schemes are analyzed and are supported by numerical examples | [['a', 'generalization', 'of', 'the', 'grunwald', 'difference', 'approximation', 'for', 'fractional', 'derivatives', 'in', 'terms', 'of', 'a', 'real', 'sequence', 'and', 'its', 'generating', 'function', 'is', 'presented', 'properties', 'of', 'the', 'generating', 'function', 'are', 'derived', 'for', 'consistency', 'and', 'order', 'of', 'accuracy', 'for', 'the', 'approximation', 'corresponding', 'to', 'the', 'generator', 'using', 'this', 'generalization', 'some', 'higher', 'order', 'grunwald', 'type', 'approximations', 'are', 'constructed', 'and', 'tested', 'for', 'numerical', 'stability', 'by', 'using', 'steady', 'state', 'fractional', 'differential', 'problems', 'these', 'higher', 'order', 'approximations', 'are', 'used', 'in', 'cranknicolson', 'type', 'numerical', 'schemes', 'to', 'approximate', 'the', 'solution', 'of', 'space', 'fractional', 'diffusion', 'equations', 'stability', 'and', 'convergence', 'of', 'these', 'numerical', 'schemes', 'are', 'analyzed', 'and', 'are', 'supported', 'by', 'numerical', 'examples']] | [-0.09598518686834723, -0.009771372635150329, -0.04776767497882247, 0.11444378336658702, -0.04612826883327216, -0.06028593151364475, 0.005155603076564148, 0.35903691992163655, -0.267871007937938, -0.28862716030329466, 0.1881321972119622, -0.26638826112262903, -0.13373440252617003, 0.24323004003614188, -0.030231811127159745, 0.14636724956857505, 0.03099840203067288, -0.00962818855419755, -0.14661233772523702, -0.2846649187593721, 0.322618572358042, -0.002906971937045455, 0.23448521153302862, -0.020094047472812234, 0.12265057237818837, -0.10042786144651472, -0.06043539866805077, 0.042349008265591695, -0.15749056315049528, 0.15018027886282653, 0.219001710168086, 0.04096019486896694, 0.28675604954361916, -0.39352782391011715, -0.2006668429262936, 0.06945193869178183, 0.13121641732286662, 0.06582817945629359, -0.069385433671996, -0.29722168849781155, 0.1606699076341465, -0.17679502257495186, -0.16400733722373842, -0.18435912675224245, -0.013109356863424182, 0.15106644735205918, -0.32371371367946267, 0.12089248197386042, 0.0145242639654316, 0.039475587940833064, -0.0762085909920279, -0.1479810152668506, -0.008500472959131002, 0.08518332168576308, 0.004793061199598015, -0.035771680292673406, -0.003483046181499958, -0.10607056271051989, -0.15492342081852256, 0.3694503189437091, -0.08455027667689137, -0.3311199524253607, 0.15378941723844036, -0.1088779806997627, -0.06352391889318824, 0.14545332950074225, 0.15707711804658175, 0.17405858820304274, -0.10259943522512913, 0.0679796698008431, 0.03410472830757499, 0.10019789931364358, 0.1033112675556913, 0.026779844211414456, 0.05122660513035953, 0.13091720374301075, 0.06087305140681565, 0.11899956645909697, -0.02563909490592778, -0.18750854549114593, -0.3669811951636802, -0.155020320257172, -0.17931759528815747, -0.008684574915096164, -0.12756620244515943, -0.1522029248997569, 0.3900713391369209, 0.11331083001219668, 0.11032685283571482, 0.09366770525462925, 0.27695165161509067, 0.2704161722958088, -0.03512991816387512, 0.043119080374017356, 0.1753285975722247, 0.19177075682906433, 0.08103834885172546, -0.2278399596066447, 0.0804271215479821, 0.20660100350156427] |
1,803.01384 | Data Curation with Deep Learning [Vision] | Data curation - the process of discovering, integrating, and cleaning data -
is one of the oldest, hardest, yet inevitable data management problems. Despite
decades of efforts from both researchers and practitioners, it is still one of
the most time consuming and least enjoyable work of data scientists. In most
organizations, data curation plays an important role so as to fully unlock the
value of big data. Unfortunately, the current solutions are not keeping up with
the ever-changing data ecosystem, because they often require substantially high
human cost. Meanwhile, deep learning is making strides in achieving remarkable
successes in multiple areas, such as image recognition, natural language
processing, and speech recognition. In this vision paper, we explore how some
of the fundamental innovations in deep learning could be leveraged to improve
existing data curation solutions and to help build new ones. In particular, we
provide a thorough overview of the current deep learning landscape, and
identify interesting research opportunities and dispel common myths. We hope
that the synthesis of these important domains will unleash a series of research
activities that will lead to significantly improved solutions for many data
curation tasks.
| cs.DB | data curation the process of discovering integrating and cleaning data is one of the oldest hardest yet inevitable data management problems despite decades of efforts from both researchers and practitioners it is still one of the most time consuming and least enjoyable work of data scientists in most organizations data curation plays an important role so as to fully unlock the value of big data unfortunately the current solutions are not keeping up with the everchanging data ecosystem because they often require substantially high human cost meanwhile deep learning is making strides in achieving remarkable successes in multiple areas such as image recognition natural language processing and speech recognition in this vision paper we explore how some of the fundamental innovations in deep learning could be leveraged to improve existing data curation solutions and to help build new ones in particular we provide a thorough overview of the current deep learning landscape and identify interesting research opportunities and dispel common myths we hope that the synthesis of these important domains will unleash a series of research activities that will lead to significantly improved solutions for many data curation tasks | [['data', 'curation', 'the', 'process', 'of', 'discovering', 'integrating', 'and', 'cleaning', 'data', 'is', 'one', 'of', 'the', 'oldest', 'hardest', 'yet', 'inevitable', 'data', 'management', 'problems', 'despite', 'decades', 'of', 'efforts', 'from', 'both', 'researchers', 'and', 'practitioners', 'it', 'is', 'still', 'one', 'of', 'the', 'most', 'time', 'consuming', 'and', 'least', 'enjoyable', 'work', 'of', 'data', 'scientists', 'in', 'most', 'organizations', 'data', 'curation', 'plays', 'an', 'important', 'role', 'so', 'as', 'to', 'fully', 'unlock', 'the', 'value', 'of', 'big', 'data', 'unfortunately', 'the', 'current', 'solutions', 'are', 'not', 'keeping', 'up', 'with', 'the', 'everchanging', 'data', 'ecosystem', 'because', 'they', 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1,803.01385 | Vertex operator algebras generated by Ising vectors of $\sigma$-type | We prove the uniqueness of the simple vertex operator algebra of OZ-type
generated by Ising vectors of $\sigma$-type. We also prove that the simplicity
can be omitted if the Griess algebra is isomorphic to the Matsuo algebra
associated with the root system of type $A_n$.
| math.QA | we prove the uniqueness of the simple vertex operator algebra of oztype generated by ising vectors of sigmatype we also prove that the simplicity can be omitted if the griess algebra is isomorphic to the matsuo algebra associated with the root system of type a_n | [['we', 'prove', 'the', 'uniqueness', 'of', 'the', 'simple', 'vertex', 'operator', 'algebra', 'of', 'oztype', 'generated', 'by', 'ising', 'vectors', 'of', 'sigmatype', 'we', 'also', 'prove', 'that', 'the', 'simplicity', 'can', 'be', 'omitted', 'if', 'the', 'griess', 'algebra', 'is', 'isomorphic', 'to', 'the', 'matsuo', 'algebra', 'associated', 'with', 'the', 'root', 'system', 'of', 'type', 'a_n']] | [-0.15596914384514093, 0.09381806820800359, -0.04290385161187838, 0.04285009427985642, -0.14726239419542253, -0.15302140814045825, -0.06860813248733227, 0.34156582258980384, -0.41946181146935985, -0.12268601222471757, 0.14703112944367935, -0.2762414835901423, -0.16041059146465902, 0.13499795907939022, -0.12675031477754767, -0.07205812754215334, 0.12624803206629373, 0.16198596249821343, -0.0889800726806491, -0.2657722467133267, 0.3940634151751345, -0.028383648179111664, 0.202556606403298, 0.04476540404456583, 0.15423130329740656, 0.03835186000849882, 0.03327947575598955, -0.006572237915613435, -0.12974599990758923, 0.07219694483369081, 0.2284746429755945, 0.11551396253476427, 0.21585392670716497, -0.36827850358730013, -0.04144317233427004, 0.2099286772480065, 0.18903788617304104, 0.010870771609585394, -0.02321347836616703, -0.25740930188277905, 0.17319887821477922, -0.2508831690065563, -0.19165205320512707, -0.04662107574768015, 0.048206812321123754, 0.01588890102522617, -0.26670705573633313, 0.06569119723214746, 0.13045594527978788, 0.09991495865820484, -0.06978830248540775, -0.11071476496660827, -0.13793492403452878, 0.05448314858685163, -0.04952065412230282, 0.04332352424336767, 0.08222193285738202, -0.07861369977366518, -0.19966458084739067, 0.3381536881524054, 0.02833206725666638, -0.2553988339548761, 0.10318885557353497, -0.22336578672878782, -0.16004702298563311, 0.04399949703788893, 0.04095965187827295, 0.06415437548209658, -0.06792789621447975, 0.2023073386993598, -0.1421789545989172, 0.05018999029628255, 0.013208156451582909, -0.0164231499762867, 0.07891194992275401, 0.06873626719144257, 0.04229566116224636, 0.1946121328510344, 0.0723490271153754, -0.005490816325287928, -0.3744308774105527, -0.15378408292202617, -0.18887044025839053, 0.14429301156831736, -0.1441004426345568, -0.17090542885390195, 0.4182975453917276, 0.18319970927074214, 0.16445605484345419, 0.0774340090045536, 0.15867790393531322, 0.17271179191514172, 0.14594370029358703, 0.07682374262631955, 0.130809226941148, 0.2507032230972651, -0.0013817894664085047, -0.20597501563183454, -0.002135980831967159, 0.26448076709427615] |
1,803.01386 | A Most Interesting, but Revoked Draft for Hilbert and Bernays'
"Grundlagen der Mathematik" that never found its way into any publication,
and 2 CV of Gisbert Hasenjaeger | In 1934, in Bernays preface to the 1st edn. of the 1st vol. of
Hilbert-Bernays "Grundlagen der Mathematik", a nearly completed draft of the
the finally two-volume monograph is mentioned, which had to be revoked because
of the completely changed situation in the area of proof theory after Herbrand
and Goedels revolutionary results. Nothing at all seems to be known about this
draft and its whereabouts. A third of a century later, Bernays preface to the
2nd edn. (1968) of the 1st vol. of Hilbert-Bernays mentions joint work of
Hasenjaeger and Bernays on the second edition. Bernays states there that it
became obvious that the integration of the many new results in the area of
proof theory would have required a complete reorganization of the book, i.e.
that the inclusion of the intermediately found new results in the area of proof
theory turned out to be unobtainable by a revision, but would have required a
complete reorganization of the entire textbook. We document that - even after
the need for a complete reorganization had become obvious - this joint work
went on to a considerable extent. Moreover, we document when Hasenjaeger stayed
in Zurich to assist Bernays in the completion of the 2nd edn. In May 2017, we
identified an incorrectly filed text in Bernays scientific legacy at the
archive of the ETH Zurich as a candidate for the beginning of the revoked draft
for the 1st edn. or of a revoked draft for the 2nd edn. In a partial
presentation and careful investigation of this text we gather only some minor
evidence that this text is the beginning of the nearly completed draft of the
1st edn., but ample evidence that this text is part of the work of Hasenjaeger
and Bernays on the 2nd edn. We provide some evidence that this work has covered
a complete reorganization of the entire 1st vol., including a completely new
version of its last chapter on the iota.
| math.HO math.LO | in 1934 in bernays preface to the 1st edn of the 1st vol of hilbertbernays grundlagen der mathematik a nearly completed draft of the the finally twovolume monograph is mentioned which had to be revoked because of the completely changed situation in the area of proof theory after herbrand and goedels revolutionary results nothing at all seems to be known about this draft and its whereabouts a third of a century later bernays preface to the 2nd edn 1968 of the 1st vol of hilbertbernays mentions joint work of hasenjaeger and bernays on the second edition bernays states there that it became obvious that the integration of the many new results in the area of proof theory would have required a complete reorganization of the book ie that the inclusion of the intermediately found new results in the area of proof theory turned out to be unobtainable by a revision but would have required a complete reorganization of the entire textbook we document that even after the need for a complete reorganization had become obvious this joint work went on to a considerable extent moreover we document when hasenjaeger stayed in zurich to assist bernays in the completion of the 2nd edn in may 2017 we identified an incorrectly filed text in bernays scientific legacy at the archive of the eth zurich as a candidate for the beginning of the revoked draft for the 1st edn or of a revoked draft for the 2nd edn in a partial presentation and careful investigation of this text we gather only some minor evidence that this text is the beginning of the nearly completed draft of the 1st edn but ample evidence that this text is part of the work of hasenjaeger and bernays on the 2nd edn we provide some evidence that this work has covered a complete reorganization of the entire 1st vol including a completely new version of its last chapter on the iota | [['in', '1934', 'in', 'bernays', 'preface', 'to', 'the', '1st', 'edn', 'of', 'the', '1st', 'vol', 'of', 'hilbertbernays', 'grundlagen', 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1,803.01387 | Robust Abstractions for Control Synthesis: Robustness Equals
Realizability for Linear-Time Properties | We define robust abstractions for synthesizing provably correct and robust
controllers for (possibly infinite) uncertain transition systems. It is shown
that robust abstractions are sound in the sense that they preserve robust
satisfaction of linear-time properties. We then focus on discrete-time control
systems modelled by nonlinear difference equations with inputs and define
concrete robust abstractions for them. While most abstraction techniques in the
literature for nonlinear systems focus on constructing sound abstractions, we
present computational procedures for constructing both sound and approximately
complete robust abstractions for general nonlinear control systems without
stability assumptions. Such procedures are approximately complete in the sense
that, given a concrete discrete-time control system and an arbitrarily small
perturbation of this system, there exists a finite transition system that
robustly abstracts the concrete system and is abstracted by the slightly
perturbed system simultaneously. A direct consequence of this result is that
robust control synthesis for discrete-time nonlinear systems and linear-time
specifications is robustly decidable. More specifically, if there exists a
robust control strategy that realizes a given linear-time specification, we can
algorithmically construct a (potentially less) robust control strategy that
realizes the same specification. The theoretical results are illustrated with a
simple motion planning example.
| cs.SY | we define robust abstractions for synthesizing provably correct and robust controllers for possibly infinite uncertain transition systems it is shown that robust abstractions are sound in the sense that they preserve robust satisfaction of lineartime properties we then focus on discretetime control systems modelled by nonlinear difference equations with inputs and define concrete robust abstractions for them while most abstraction techniques in the literature for nonlinear systems focus on constructing sound abstractions we present computational procedures for constructing both sound and approximately complete robust abstractions for general nonlinear control systems without stability assumptions such procedures are approximately complete in the sense that given a concrete discretetime control system and an arbitrarily small perturbation of this system there exists a finite transition system that robustly abstracts the concrete system and is abstracted by the slightly perturbed system simultaneously a direct consequence of this result is that robust control synthesis for discretetime nonlinear systems and lineartime specifications is robustly decidable more specifically if there exists a robust control strategy that realizes a given lineartime specification we can algorithmically construct a potentially less robust control strategy that realizes the same specification the theoretical results are illustrated with a simple motion planning example | [['we', 'define', 'robust', 'abstractions', 'for', 'synthesizing', 'provably', 'correct', 'and', 'robust', 'controllers', 'for', 'possibly', 'infinite', 'uncertain', 'transition', 'systems', 'it', 'is', 'shown', 'that', 'robust', 'abstractions', 'are', 'sound', 'in', 'the', 'sense', 'that', 'they', 'preserve', 'robust', 'satisfaction', 'of', 'lineartime', 'properties', 'we', 'then', 'focus', 'on', 'discretetime', 'control', 'systems', 'modelled', 'by', 'nonlinear', 'difference', 'equations', 'with', 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1,803.01388 | Lefschetz properties of monomial ideals with almost linear resolution | We study the WLP and SLP of artinian monomial ideals in
$S=\mathbb{K}[x_1,\dots ,x_n]$ via studying their minimal free resolutions. We
study the Lefschetz properties of such ideals where the minimal free resolution
of $S/I$ is linear for at least $n-2$ steps. We give an affirmative answer to a
conjecture of Eisenbud, Huneke and Ulrich for artinian monomial ideals with
almost linear resolutions.
| math.AC | we study the wlp and slp of artinian monomial ideals in smathbbkx_1dots x_n via studying their minimal free resolutions we study the lefschetz properties of such ideals where the minimal free resolution of si is linear for at least n2 steps we give an affirmative answer to a conjecture of eisenbud huneke and ulrich for artinian monomial ideals with almost linear resolutions | [['we', 'study', 'the', 'wlp', 'and', 'slp', 'of', 'artinian', 'monomial', 'ideals', 'in', 'smathbbkx_1dots', 'x_n', 'via', 'studying', 'their', 'minimal', 'free', 'resolutions', 'we', 'study', 'the', 'lefschetz', 'properties', 'of', 'such', 'ideals', 'where', 'the', 'minimal', 'free', 'resolution', 'of', 'si', 'is', 'linear', 'for', 'at', 'least', 'n2', 'steps', 'we', 'give', 'an', 'affirmative', 'answer', 'to', 'a', 'conjecture', 'of', 'eisenbud', 'huneke', 'and', 'ulrich', 'for', 'artinian', 'monomial', 'ideals', 'with', 'almost', 'linear', 'resolutions']] | [-0.17590152763868452, -0.008748694939193407, -0.011243755723059665, 0.08728945680672577, -0.021583179080645082, -0.2591176103479916, -0.11642665522875356, 0.34840297382935637, -0.3924849004041953, -0.17298166530176265, 0.11153231260221695, -0.28020094362179154, -0.0363604181778205, 0.11649566996445665, -0.15642079303315917, 0.034006783402845506, 0.04353010223903617, -0.012070102006441256, -0.0608092997620096, -0.420732569865516, 0.3713293351294076, 0.09486044152471863, 0.14923555428375962, 0.10030540546066448, 0.15324914614196683, 0.02339388444622765, -0.023635222660530298, 0.007124768173108335, -0.2936244666820667, 0.13901216777224765, 0.38166174799448155, 0.12835787048899247, 0.22656940607751003, -0.4188832022845134, -0.0184836641343341, 0.22355132711837528, 0.1252098202201553, -0.002364290202586133, 0.020846810985784062, -0.1164177021271259, 0.1748564023005425, -0.1547457021279413, -0.2049274270224278, -0.08382361690651198, 0.06797054380972366, -0.00951135936422182, -0.3033799777746384, -0.02889473064512503, 0.17908881226035414, 0.3004227791012066, -0.014733584536636462, -0.06568173061079177, -0.0717495435345002, -0.03293477912570854, -0.041948820959928, -0.09183141076173938, 0.023855789946239502, -0.14892838190721927, -0.19315278155301682, 0.3259055379808682, -0.04486028612285974, -0.18473963464656082, 0.10952886248190628, -0.2058653301544121, -0.1315126005697568, 0.11397204948894557, -0.030830180180854486, 0.1930787114666958, 0.020871432944674227, 0.22173693415624868, -0.21742741690307368, 0.035895083733208356, 0.21440440138466046, 0.03537680986184688, 0.15806775990888844, 0.09809621243325413, 0.10811146531925826, 0.13379622568361094, 0.03182115066857612, 0.07654861490562802, -0.3562022004826147, -0.23839438095933102, -0.08637941168376902, 0.20733728493395887, -0.09924653419780118, -0.1589913704875307, 0.4725533347637927, 0.11807288678332431, 0.17598897365273022, 0.158500029919211, 0.21906571768102098, 0.01120021618658402, -0.029082984178800318, 0.05244434944766223, 0.06687353551387787, 0.26192848924852785, -0.0503443905350859, -0.14246728453693575, -0.032578084114022916, 0.25402347366401895] |
1,803.01389 | Comparing Asset Pricing Models: Distance-based Metrics and Bayesian
Interpretations | In light of the power problems of statistical tests and undisciplined use of
alpha-based statistics to compare models, this paper proposes a unified set of
distance-based performance metrics, derived as the square root of the sum of
squared alphas and squared standard errors. The Bayesian investor views model
performance as the shortest distance between his dogmatic belief (model-implied
distribution) and complete skepticism (data-based distribution) in the model,
and favors models that produce low dispersion of alphas with high explanatory
power. In this view, the momentum factor is a crucial addition to the
five-factor model of Fama and French (2015), alleviating his prior concern of
model mispricing by -8% to 8% per annum. The distance metrics complement the
frequentist p-values with a diagnostic tool to guard against bad models.
| q-fin.PM q-fin.ST | in light of the power problems of statistical tests and undisciplined use of alphabased statistics to compare models this paper proposes a unified set of distancebased performance metrics derived as the square root of the sum of squared alphas and squared standard errors the bayesian investor views model performance as the shortest distance between his dogmatic belief modelimplied distribution and complete skepticism databased distribution in the model and favors models that produce low dispersion of alphas with high explanatory power in this view the momentum factor is a crucial addition to the fivefactor model of fama and french 2015 alleviating his prior concern of model mispricing by 8 to 8 per annum the distance metrics complement the frequentist pvalues with a diagnostic tool to guard against bad models | [['in', 'light', 'of', 'the', 'power', 'problems', 'of', 'statistical', 'tests', 'and', 'undisciplined', 'use', 'of', 'alphabased', 'statistics', 'to', 'compare', 'models', 'this', 'paper', 'proposes', 'a', 'unified', 'set', 'of', 'distancebased', 'performance', 'metrics', 'derived', 'as', 'the', 'square', 'root', 'of', 'the', 'sum', 'of', 'squared', 'alphas', 'and', 'squared', 'standard', 'errors', 'the', 'bayesian', 'investor', 'views', 'model', 'performance', 'as', 'the', 'shortest', 'distance', 'between', 'his', 'dogmatic', 'belief', 'modelimplied', 'distribution', 'and', 'complete', 'skepticism', 'databased', 'distribution', 'in', 'the', 'model', 'and', 'favors', 'models', 'that', 'produce', 'low', 'dispersion', 'of', 'alphas', 'with', 'high', 'explanatory', 'power', 'in', 'this', 'view', 'the', 'momentum', 'factor', 'is', 'a', 'crucial', 'addition', 'to', 'the', 'fivefactor', 'model', 'of', 'fama', 'and', 'french', '2015', 'alleviating', 'his', 'prior', 'concern', 'of', 'model', 'mispricing', 'by', '8', 'to', '8', 'per', 'annum', 'the', 'distance', 'metrics', 'complement', 'the', 'frequentist', 'pvalues', 'with', 'a', 'diagnostic', 'tool', 'to', 'guard', 'against', 'bad', 'models']] | [-0.05105428391238895, 0.021011692301304206, -0.09062445372724393, 0.11314477633380544, -0.06145744074290017, -0.1605453336552724, 0.10734777179946316, 0.34128914033539415, -0.24623797387324683, -0.3572220592209556, 0.05274641845012304, -0.3158035332476354, -0.1076959586577622, 0.1589653517246085, -0.13384815130206779, 0.06476035128222911, 0.0561869058879019, 0.016672663562967788, -0.0470540233517403, -0.2678106990386182, 0.2630253586932782, 0.14918887824934768, 0.33399512162652073, 0.02410136148889043, 0.11697517971207541, 0.011286839439467651, -0.06116549004378956, 0.009415175983000283, -0.1137413434122481, 0.14665078253697927, 0.22322022460611773, 0.20047160238760897, 0.32421158204280487, -0.33376218470690705, -0.18395935865779092, 0.14065612907572758, 0.07399672306120747, 0.023236170200279026, 0.03310567386976377, -0.22851118614794466, 0.05809065508546205, -0.2123430290224588, -0.11204486852878426, -0.03090708175908745, -0.005384122468824462, 0.027476361795057226, -0.2755916630010502, 0.12698891396106288, 0.023392371327330276, 0.09126896031318217, -0.007441160751242689, -0.17537532333929942, 0.017899076346175994, 0.12281107569964031, 0.11374453128330175, 0.04713855843668378, 0.08314618438951613, -0.14011257083620876, -0.1500402152406301, 0.37572084968418296, -0.06120165809118152, -0.20030394609372212, 0.12178569775272718, -0.08926061801722376, -0.07914518393891475, 0.07169464814355671, 0.21426513310573173, 0.0684121972031059, -0.1528806471573849, 0.038898732787956976, -0.002930696058182383, 0.17315100310150328, 0.04377716941040332, -0.01190944373475637, 0.20269368709556349, 0.15493133143928842, 0.017711970513305208, 0.10523583176802462, -0.11902940659088268, -0.11541068458592328, -0.3103854572987111, -0.12507766221217284, -0.14216199831479764, 0.015437451231579377, -0.14878867023867853, -0.1798911452088065, 0.39216805477516625, 0.17622767804982506, 0.1867763840072737, 0.12224057811774372, 0.32019654351953913, 0.059169564085511134, 0.034775665210808375, 0.07480479671443835, 0.22101449174623145, 0.10183983066441916, 0.06400655581722198, -0.13321691979910796, 0.08285185275874357, 0.03418039841995406] |
1,803.0139 | Comparing Downward Fragments of the Relational Calculus with Transitive
Closure on Trees | Motivated by the continuing interest in the tree data model, we study the
expressive power of downward navigational query languages on trees and chains.
Basic navigational queries are built from the identity relation and edge
relations using composition and union. We study the effects on relative
expressiveness when we add transitive closure, projections, coprojections,
intersection, and difference; this for boolean queries and path queries on
labeled and unlabeled structures. In all cases, we present the complete Hasse
diagram. In particular, we establish, for each query language fragment that we
study on trees, whether it is closed under difference and intersection.
| cs.DB | motivated by the continuing interest in the tree data model we study the expressive power of downward navigational query languages on trees and chains basic navigational queries are built from the identity relation and edge relations using composition and union we study the effects on relative expressiveness when we add transitive closure projections coprojections intersection and difference this for boolean queries and path queries on labeled and unlabeled structures in all cases we present the complete hasse diagram in particular we establish for each query language fragment that we study on trees whether it is closed under difference and intersection | [['motivated', 'by', 'the', 'continuing', 'interest', 'in', 'the', 'tree', 'data', 'model', 'we', 'study', 'the', 'expressive', 'power', 'of', 'downward', 'navigational', 'query', 'languages', 'on', 'trees', 'and', 'chains', 'basic', 'navigational', 'queries', 'are', 'built', 'from', 'the', 'identity', 'relation', 'and', 'edge', 'relations', 'using', 'composition', 'and', 'union', 'we', 'study', 'the', 'effects', 'on', 'relative', 'expressiveness', 'when', 'we', 'add', 'transitive', 'closure', 'projections', 'coprojections', 'intersection', 'and', 'difference', 'this', 'for', 'boolean', 'queries', 'and', 'path', 'queries', 'on', 'labeled', 'and', 'unlabeled', 'structures', 'in', 'all', 'cases', 'we', 'present', 'the', 'complete', 'hasse', 'diagram', 'in', 'particular', 'we', 'establish', 'for', 'each', 'query', 'language', 'fragment', 'that', 'we', 'study', 'on', 'trees', 'whether', 'it', 'is', 'closed', 'under', 'difference', 'and', 'intersection']] | [-0.11831004440965545, 0.07132825031500271, -0.010165872804895795, 0.13738694009982577, -0.13567191580159946, -0.08660478742247579, 0.16922128462289093, 0.41975556246258994, -0.3362030920553764, -0.2683975442942947, 0.0813872497963879, -0.3394626367536157, -0.11795268091608328, 0.16949751876962532, -0.1057180478684416, 0.025039906801674703, 0.10518782205804429, 0.07249780849205574, -0.042567351600155234, -0.26867581038462995, 0.37703760757553156, -0.03854395093565637, 0.2445334606342996, 0.03422944543288193, 0.055489381338996495, 0.05627111857639381, -0.04350681147641606, 0.10139661157079147, -0.18031486333384605, 0.13968632345304194, 0.2952045050492002, 0.2644966850903901, 0.17172457761309964, -0.41959029024071764, -0.098376711975134, 0.1212749899778929, 0.1005128519280315, 0.046814840184371785, -0.004848331926188272, -0.2671334447357992, 0.09554893041800971, -0.15716586239410169, 0.007181826560297097, -0.09263573078476268, 0.07956313450980668, 0.045424603050424145, -0.21599708031745382, -0.047660486744434544, 0.13487823216535322, 0.14937373307166676, -0.021944450313281832, -0.059644729623364076, -0.003824159766387458, 0.13225223017166218, -0.016943649801594966, 0.01779300946921035, 0.06460540794362926, -0.07519372266416222, -0.18528764926819036, 0.37361424428533124, -0.02186395347852147, -0.19764342677374983, 0.1738994641986798, -0.15103665363005916, -0.20820649971037802, 0.05005389245960749, 0.17504770022751104, 0.10543034688071018, -0.12202542537021935, 0.145617840023161, -0.07993126592852852, 0.1529876205957297, 0.14675420446020335, -0.015280834309794385, 0.20303612787753045, 0.20029120855127472, 0.05344550234778323, 0.19694068503914156, 0.005383340119751114, -0.0727532321935275, -0.26422980001591373, -0.1369839652507293, -0.12811524453079046, -0.04858428336717565, -0.14522152614554584, -0.20492657226971303, 0.38370178463031546, 0.1816627135914233, 0.16903958656834533, 0.1739442886389566, 0.28702883488225817, 0.06244017014449293, 0.06128710185676211, 0.1273080717320695, 0.060816296341598526, 0.11262984991760341, 0.044668222001443304, -0.1626187295892812, 0.12696028402489093, 0.13008498581069888] |
1,803.01391 | Boundary Value Problems for the Helmholtz Equation for a Half-plane with
a Lipschitz Inclusion | This paper considers to the problems of diffraction of electromagnetic waves
on a half-plane, which has a finite inclusion in the form of a Lipschitz curve.
The diffraction problem formulated as boundary value problem for Helmholtz
equations and boundary conditions Dirichlet or Neumann on the boundary, as well
as the radiation conditions at infinity. We carry out research on these
problems in generalized Sobolev spaces. We use the operators of potential type,
that by their properties are analogs of the classical potentials of single and
double layers. We proved the solvability of the boundary value problems of
Dirichlet and Neumann. We have obtained solutions of boundary value problems in
the form of operators of potential type. Boundary problems are reduced to
integral equations of the second kind.
| math-ph math.MP | this paper considers to the problems of diffraction of electromagnetic waves on a halfplane which has a finite inclusion in the form of a lipschitz curve the diffraction problem formulated as boundary value problem for helmholtz equations and boundary conditions dirichlet or neumann on the boundary as well as the radiation conditions at infinity we carry out research on these problems in generalized sobolev spaces we use the operators of potential type that by their properties are analogs of the classical potentials of single and double layers we proved the solvability of the boundary value problems of dirichlet and neumann we have obtained solutions of boundary value problems in the form of operators of potential type boundary problems are reduced to integral equations of the second kind | [['this', 'paper', 'considers', 'to', 'the', 'problems', 'of', 'diffraction', 'of', 'electromagnetic', 'waves', 'on', 'a', 'halfplane', 'which', 'has', 'a', 'finite', 'inclusion', 'in', 'the', 'form', 'of', 'a', 'lipschitz', 'curve', 'the', 'diffraction', 'problem', 'formulated', 'as', 'boundary', 'value', 'problem', 'for', 'helmholtz', 'equations', 'and', 'boundary', 'conditions', 'dirichlet', 'or', 'neumann', 'on', 'the', 'boundary', 'as', 'well', 'as', 'the', 'radiation', 'conditions', 'at', 'infinity', 'we', 'carry', 'out', 'research', 'on', 'these', 'problems', 'in', 'generalized', 'sobolev', 'spaces', 'we', 'use', 'the', 'operators', 'of', 'potential', 'type', 'that', 'by', 'their', 'properties', 'are', 'analogs', 'of', 'the', 'classical', 'potentials', 'of', 'single', 'and', 'double', 'layers', 'we', 'proved', 'the', 'solvability', 'of', 'the', 'boundary', 'value', 'problems', 'of', 'dirichlet', 'and', 'neumann', 'we', 'have', 'obtained', 'solutions', 'of', 'boundary', 'value', 'problems', 'in', 'the', 'form', 'of', 'operators', 'of', 'potential', 'type', 'boundary', 'problems', 'are', 'reduced', 'to', 'integral', 'equations', 'of', 'the', 'second', 'kind']] | [-0.13712185807526112, 0.0472932982031168, -0.06322287336563853, 0.04174610172988715, -0.11738767438223512, -0.0897558664235719, 0.009133266535308946, 0.31204601122418374, -0.32150994640166364, -0.22471431236508793, 0.1962562648260482, -0.2991837887973415, -0.11200582870194234, 0.21490151663017495, -0.06758754393159169, 0.14010158279456023, 0.08863589271360378, 0.06801318047260206, -0.11120483769639213, -0.22088782259219097, 0.4379668202339195, -0.04505169367890688, 0.22618707685225356, 0.08671560698357506, 0.08585007967084543, -0.0219387352488583, 0.039214852926005996, 0.04164965114167591, -0.16390641610071432, 0.1102430180510814, 0.2346837032755001, 0.0501365431338754, 0.3093989779036052, -0.47293639760904427, -0.255883832374133, 0.11179029225100448, 0.1069077574024637, 0.02717181819025427, -0.004718573818049269, -0.27258001316309444, 0.06870803081771491, -0.06903390159764451, -0.18936405507261006, -0.005621024260781412, -0.033173186752182525, 0.031201345085232392, -0.30320902964041574, 0.11705042805346683, 0.04451231841148266, 0.0445145855485425, -0.1997674967484974, -0.11683259174726375, 0.008549774995103008, 0.0759542611937266, 0.03214377764333773, -0.03334346701075712, 0.04862601888333044, -0.16045131489055187, -0.10108382718300256, 0.37308673613418747, -0.026189445752621165, -0.2766377975298898, 0.1590354367228973, -0.1340811363582712, -0.09812882696837553, 0.06981495885530442, 0.16090180126832812, 0.18298828761701977, -0.14300429878947069, 0.15461873539446624, -0.049121025471222095, 0.08121041331704207, 0.14117193915037893, -0.01085240805272277, 0.13736260173416984, 0.09006003301414683, 0.12731331296624454, 0.19851052636412655, -0.023018040718129417, -0.08783119617673517, -0.3656618270847037, -0.15280483188070942, -0.15738209213064178, 0.05765353927139457, -0.09243666000094074, -0.25652347474292975, 0.3538756628784784, 0.10689335743718832, 0.15076708785390233, 0.02896339692061723, 0.2032715835650708, 0.19901266409630528, 0.0534982479298414, 0.03562774439525651, 0.19430209374363264, 0.18734938436642465, 0.1575050621264152, -0.21564064491709775, 0.000642168588613666, 0.16488847756157005] |
1,803.01392 | Facile and fast growth of high mobility nanoribbons of ZrTe$_5$ | Recently, ZrTe$_5$ has received a lot of attention as it exhibits various
topological phases, such as weak and strong topological insulators, a Dirac
semimetal, and a quantum spin Hall insulator in the monolayer limit. While most
of studies have been focused on the three-dimensional bulk material, it is
highly desired to obtain nanostructured materials due to their advantages in
device applications. We report the synthesis and characterizations of ZrTe$_5$
nanoribbons. Via a silicon-assisted chemical vapor transport method, long
nanoribbons with thickness as thin as 20 nm can be grown. The growth rate is
over an order of magnitude faster than the previous method for growth of bulk
crystals. Moreover, transport studies show that nanoribbons are of low
unintentional doping and high carrier mobility, over 30,000 cm$^2$/Vs, which
enable reliable determination of the Berry phase of $\pi$ in the $ac$ plane
from quantum oscillations. Our method holds great potential in growth of high
quality ultra-thin nanostructures of ZrTe$_5$.
| cond-mat.mtrl-sci | recently zrte_5 has received a lot of attention as it exhibits various topological phases such as weak and strong topological insulators a dirac semimetal and a quantum spin hall insulator in the monolayer limit while most of studies have been focused on the threedimensional bulk material it is highly desired to obtain nanostructured materials due to their advantages in device applications we report the synthesis and characterizations of zrte_5 nanoribbons via a siliconassisted chemical vapor transport method long nanoribbons with thickness as thin as 20 nm can be grown the growth rate is over an order of magnitude faster than the previous method for growth of bulk crystals moreover transport studies show that nanoribbons are of low unintentional doping and high carrier mobility over 30000 cm2vs which enable reliable determination of the berry phase of pi in the ac plane from quantum oscillations our method holds great potential in growth of high quality ultrathin nanostructures of zrte_5 | [['recently', 'zrte_5', 'has', 'received', 'a', 'lot', 'of', 'attention', 'as', 'it', 'exhibits', 'various', 'topological', 'phases', 'such', 'as', 'weak', 'and', 'strong', 'topological', 'insulators', 'a', 'dirac', 'semimetal', 'and', 'a', 'quantum', 'spin', 'hall', 'insulator', 'in', 'the', 'monolayer', 'limit', 'while', 'most', 'of', 'studies', 'have', 'been', 'focused', 'on', 'the', 'threedimensional', 'bulk', 'material', 'it', 'is', 'highly', 'desired', 'to', 'obtain', 'nanostructured', 'materials', 'due', 'to', 'their', 'advantages', 'in', 'device', 'applications', 'we', 'report', 'the', 'synthesis', 'and', 'characterizations', 'of', 'zrte_5', 'nanoribbons', 'via', 'a', 'siliconassisted', 'chemical', 'vapor', 'transport', 'method', 'long', 'nanoribbons', 'with', 'thickness', 'as', 'thin', 'as', '20', 'nm', 'can', 'be', 'grown', 'the', 'growth', 'rate', 'is', 'over', 'an', 'order', 'of', 'magnitude', 'faster', 'than', 'the', 'previous', 'method', 'for', 'growth', 'of', 'bulk', 'crystals', 'moreover', 'transport', 'studies', 'show', 'that', 'nanoribbons', 'are', 'of', 'low', 'unintentional', 'doping', 'and', 'high', 'carrier', 'mobility', 'over', '30000', 'cm2vs', 'which', 'enable', 'reliable', 'determination', 'of', 'the', 'berry', 'phase', 'of', 'pi', 'in', 'the', 'ac', 'plane', 'from', 'quantum', 'oscillations', 'our', 'method', 'holds', 'great', 'potential', 'in', 'growth', 'of', 'high', 'quality', 'ultrathin', 'nanostructures', 'of', 'zrte_5']] | [-0.14893428237440112, 0.14992149382053938, -0.045149867673619434, -0.06719105143117933, -0.042610528017692745, -0.16475698970353755, 0.0808618968167605, 0.43698839148661744, -0.2340773320704615, -0.3107410974096125, 0.05263727949559092, -0.3166849030516086, -0.15562667810501388, 0.26141848143351337, -0.013632003122415299, 0.11995085445307314, -0.016518066368567254, -0.09448521334277944, -0.11042633008074541, -0.2388599660883371, 0.2134200102255608, 0.01591962243233306, 0.3758723096122058, 0.1133337121976253, 0.03807404616292423, -0.03186666275248102, 0.11542443759464778, 0.041818560913014106, -0.1530213541666457, 0.06862455623363181, 0.24172144236926657, -0.10693031032301056, 0.2405028845368622, -0.45845427351573914, -0.2895563501978102, -0.010142119517788673, 0.14484872271826205, 0.16236113486826445, -0.14148418719728048, -0.2660228146526676, 0.14365298927982506, -0.16516432297439912, -0.06584929877545875, -0.0999835370741307, 0.015067496498187002, -0.031208389033473886, -0.18596900708395808, 0.06932748810355313, 0.022594466142786238, 0.0981436560925944, -0.0537232927342232, -0.13616634393707874, -0.10477238129869175, 0.09078325658367994, 0.0600582752824546, 0.032912397073605694, 0.17281756629176342, -0.14923119664084739, -0.1242990339442025, 0.40860521469193584, -0.059617554473124286, -0.0921109253152584, 0.1899113638463836, -0.18778626386604932, -0.051803857732850775, 0.18639986222096455, 0.14296123808703554, 0.15098022724477908, -0.11936897844768679, 0.08930711713876988, -0.015454813711142216, 0.15615058051219258, 0.07782933734900628, 0.14764711831827673, 0.26266972854351384, 0.23365298696220493, 0.09133670002801153, 0.11698470854436238, -0.09514737921283366, 0.015901469585235015, -0.14488747954750672, -0.24442236086365599, -0.23927691059846742, 0.1257797205232633, -0.07653918759322738, -0.22437884180973738, 0.42560947221071005, 0.15276953491952439, 0.16559579687413928, -0.057195679110755474, 0.25294958435906434, 0.09609078964030442, 0.0908984638353547, -0.012832054163878545, 0.24326461603124747, 0.1874652844376098, 0.14392018737430007, -0.21432109858739215, 0.10367966183156778, -0.008938623178833857] |
1,803.01393 | $\mathbb{R}$-complex Finsler spaces with infinite series $(\alpha,
\beta)$-metric | In the present paper, the notion of $\mathbb{R}$-complex Finsler space with
Infinite Series ($\alpha, \beta$)- metric $\dfrac{\beta^2}{\beta - \alpha}$ is
defined. The Fundamental metric fields $g_{ij}$, $g_{i\bar{j}}$, their
determinants and the inverse of these tensor fields are obtained. Also some
properties of these spaces are studied.
| math.DG | in the present paper the notion of mathbbrcomplex finsler space with infinite series alpha beta metric dfracbeta2beta alpha is defined the fundamental metric fields g_ij g_ibarj their determinants and the inverse of these tensor fields are obtained also some properties of these spaces are studied | [['in', 'the', 'present', 'paper', 'the', 'notion', 'of', 'mathbbrcomplex', 'finsler', 'space', 'with', 'infinite', 'series', 'alpha', 'beta', 'metric', 'dfracbeta2beta', 'alpha', 'is', 'defined', 'the', 'fundamental', 'metric', 'fields', 'g_ij', 'g_ibarj', 'their', 'determinants', 'and', 'the', 'inverse', 'of', 'these', 'tensor', 'fields', 'are', 'obtained', 'also', 'some', 'properties', 'of', 'these', 'spaces', 'are', 'studied']] | [-0.1867274312479865, 0.1922735864008289, -0.024103552812621706, 0.11460569735139697, -0.07175852868351199, -0.06585447862744331, -0.08071947634674698, 0.4181314442484152, -0.30922023118251846, -0.24010080298674957, 0.11687744587072216, -0.267858491035267, -0.21051621672120832, 0.17968716046639852, -0.01278820097269047, 0.06103208390552373, -0.032265310730075554, 0.10956494289539045, -0.1212802161462605, -0.27378332011756445, 0.4586287722035888, 0.03392663360795095, 0.20940196826787932, -0.004128397974584784, 0.09420441286194892, -0.05440448384199824, -0.10606302247781839, 0.07968744392703575, -0.2014776658976362, 0.16999541453662373, 0.21882318590013755, 0.12854175828397274, 0.2411170420902116, -0.3159994041724574, -0.19984782790942562, 0.14442667169939905, 0.09614076618371266, -0.06534941574292523, -0.007848182803995553, -0.29822064381802366, 0.0736310923738139, -0.10762068735701698, -0.1364454318813625, -0.10727592759455244, 0.027975448429407107, 0.0632331698600735, -0.21740399622580125, 0.042947704210140124, 0.06970318254371662, 0.06738172968228658, -0.11368057486556825, -0.16639125941409952, 0.024502431524784436, 0.1316514223082257, 0.10952377285520058, 0.01919079228259978, 0.08998537742133651, -0.08727859935191061, -0.08820911519052017, 0.3568838530974019, -0.042668173577459084, -0.26548799012033714, 0.10242143521706264, -0.18701011348249658, -0.1418888739620646, 0.05205962364561856, 0.12892055928352333, 0.18002672231800498, -0.10045233544050938, 0.22348522655305542, -0.021929694395068856, 0.042612060926677214, 0.09655439330353624, 0.08831397220048876, 0.1157310503047137, 0.0386195071041584, 0.02271098160140571, 0.12815348733039128, 0.009046205408161595, -0.07438572973339996, -0.35733474649134134, -0.20416089242679022, -0.1418698338924774, 0.07469061830834973, -0.18810975983970343, -0.24759458987751887, 0.35087130182156606, 0.038933181846957834, 0.15357473916290992, 0.0954524052684151, 0.17431427392044238, 0.1314207044030939, -0.0004876164020970464, 0.032758241663465186, 0.24046246303104063, 0.2311990712547586, 0.08116418176463672, -0.13409946976406945, -0.016728918389638976, 0.1477206662696387] |
1,803.01394 | The ICO Phenomenon and Its Relationships with Ethereum Smart Contract
Environment | Initial Coin Offerings (ICO) are public offers of new cryptocurrencies in
exchange of existing ones, aimed to finance projects in the blockchain
development arena. In the last 8 months of 2017, the total amount gathered by
ICOs exceeded 4 billion US$, and overcame the venture capital funnelled toward
high tech initiatives in the same period. A high percentage of ICOS is managed
through Smart Contracts running on Ethereum blockchain, and in particular to
ERC-20 Token Standard Contract. In this work we examine 1388 ICOs, published on
December 31, 2017 on icobench.com Web site, gathering information relevant to
the assessment of their quality and software development management, including
data on their development teams. We also study, at the same date, the financial
data of 450 ICO tokens available on coinmarketcap.com Web site, among which 355
tokens are managed on Ethereum blochain. We define success criteria for the
ICOs, based on the funds actually gathered, and on the behavior of the price of
the related tokens, finding the factors that most likely influence the ICO
success likeliness.
| cs.CY | initial coin offerings ico are public offers of new cryptocurrencies in exchange of existing ones aimed to finance projects in the blockchain development arena in the last 8 months of 2017 the total amount gathered by icos exceeded 4 billion us and overcame the venture capital funnelled toward high tech initiatives in the same period a high percentage of icos is managed through smart contracts running on ethereum blockchain and in particular to erc20 token standard contract in this work we examine 1388 icos published on december 31 2017 on icobenchcom web site gathering information relevant to the assessment of their quality and software development management including data on their development teams we also study at the same date the financial data of 450 ico tokens available on coinmarketcapcom web site among which 355 tokens are managed on ethereum blochain we define success criteria for the icos based on the funds actually gathered and on the behavior of the price of the related tokens finding the factors that most likely influence the ico success likeliness | [['initial', 'coin', 'offerings', 'ico', 'are', 'public', 'offers', 'of', 'new', 'cryptocurrencies', 'in', 'exchange', 'of', 'existing', 'ones', 'aimed', 'to', 'finance', 'projects', 'in', 'the', 'blockchain', 'development', 'arena', 'in', 'the', 'last', '8', 'months', 'of', '2017', 'the', 'total', 'amount', 'gathered', 'by', 'icos', 'exceeded', '4', 'billion', 'us', 'and', 'overcame', 'the', 'venture', 'capital', 'funnelled', 'toward', 'high', 'tech', 'initiatives', 'in', 'the', 'same', 'period', 'a', 'high', 'percentage', 'of', 'icos', 'is', 'managed', 'through', 'smart', 'contracts', 'running', 'on', 'ethereum', 'blockchain', 'and', 'in', 'particular', 'to', 'erc20', 'token', 'standard', 'contract', 'in', 'this', 'work', 'we', 'examine', '1388', 'icos', 'published', 'on', 'december', '31', '2017', 'on', 'icobenchcom', 'web', 'site', 'gathering', 'information', 'relevant', 'to', 'the', 'assessment', 'of', 'their', 'quality', 'and', 'software', 'development', 'management', 'including', 'data', 'on', 'their', 'development', 'teams', 'we', 'also', 'study', 'at', 'the', 'same', 'date', 'the', 'financial', 'data', 'of', '450', 'ico', 'tokens', 'available', 'on', 'coinmarketcapcom', 'web', 'site', 'among', 'which', '355', 'tokens', 'are', 'managed', 'on', 'ethereum', 'blochain', 'we', 'define', 'success', 'criteria', 'for', 'the', 'icos', 'based', 'on', 'the', 'funds', 'actually', 'gathered', 'and', 'on', 'the', 'behavior', 'of', 'the', 'price', 'of', 'the', 'related', 'tokens', 'finding', 'the', 'factors', 'that', 'most', 'likely', 'influence', 'the', 'ico', 'success', 'likeliness']] | [-0.10421474061115797, 0.04588985600140552, -0.042770827830725805, 0.050376132774968135, -0.11080468643651625, -0.10754849235825024, 0.13672358924956168, 0.37432249756746516, -0.19026146328339333, -0.3760706729977798, 0.1698087073800284, -0.3580278577634978, -0.04756233733022845, 0.1975969821725685, -0.11825061128691358, 0.0055216856599991145, 0.06508389207112147, 0.021175332921408226, 0.05618112317833313, -0.3799120502791443, 0.25728364957518185, 0.09126926155565956, 0.3557310571946843, 0.07964852571942259, 0.09119606445960397, -0.011924481476240163, -0.10383369155085326, -0.07957175869337652, -0.1355280530178154, 0.16321989977299128, 0.28539292589046583, 0.21034746620056846, 0.36103391765107856, -0.43259605434235876, -0.08264226315280444, 0.06387819316194848, 0.06472031676161731, 0.04365030638156134, -0.03331234540010607, -0.313054388812689, 0.04583161287645939, -0.24650627201379732, -0.09736782949834759, -0.007160903127907321, 0.05750975260229478, 0.016753235594288252, -0.16600876639131457, -0.0024733932590353044, -0.03320691505782739, 0.11987200748110406, -0.031128865509662172, -0.12182905055517547, -0.05789074858076611, 0.18532314857056495, 0.06505228681246165, -0.020608922275261097, 0.1532766251306342, -0.12752460829404638, -0.172589884811016, 0.3724761759905621, -0.02499838750660528, -0.05220089588523436, 0.16056587864955493, -0.09285827291328026, -0.19321151230786748, 0.06298925421677183, 0.2554253215555015, 0.03997746022650972, -0.19503445433301114, 0.022721040429449967, -0.009904472452458428, 0.1938948523304642, 0.10057199464536944, -0.0005745594606323298, 0.21276698297574617, 0.17937278870065415, 0.06006335478877042, 0.07178448405127626, -0.0505295816678987, -0.14543020043543778, -0.22067925883836093, -0.1345885424931577, -0.14422787051664146, 0.046766748421062, -0.07579871182306941, -0.09603259636313914, 0.3879669369144235, 0.20052260434699007, 0.1004998789352993, 0.002155216768800909, 0.27415314134681423, -0.00017433981600672354, 0.11495323065112241, 0.11105511284454964, 0.20950186590198427, -0.05339130101221895, 0.23080189777592328, -0.11644259671244749, 0.15197547512713733, -0.006680840826701633] |
1,803.01395 | Quantification of GR effects in muon g-2, EDM and other spin precession
experiments | Recently, Morishima, Futamase and Shimizu published a series of manuscripts,
putting forward arguments, based on a post-Newtonian approximative calculation,
that there can be a sizable general relativistic (GR) correction in the
experimental determination of the muon magnetic moment based on spin
precession, i.e., in muon g-2 experiments. In response, other authors argued
that the effect must be much smaller than claimed. Further authors argued that
the effect exactly cancels. Also, the known formulae for de Sitter and
Lense-Thirring effect do not apply due to the non-geodesic motion. All this
indicates that it is difficult to estimate from first principles the influence
of GR corrections in the problem of spin propagation. Therefore, in this paper
we present a full general relativistic calculation in order to quantify this
effect. The main methodology is the purely differential geometrical tool of
Fermi-Walker transport over a Schwarzschild background. Also the Larmor
precession due to the propagation in the electromagnetic field of the
experimental apparatus is included. For the muon g-2 experiments the GR
correction turns out to be very small, well below the present sensitivity.
However, in other similar storage ring experimental settings, such as electric
dipole moment (EDM) search experiments, where the so-called frozen spin method
is used, GR gives a well detectable effect, and should be corrected for. All
frozen spin scenarios are affected which intend to reach a sensitivity of 0.1
microradians/second for the spin precession in the vertical plane.
| gr-qc hep-ph hep-th | recently morishima futamase and shimizu published a series of manuscripts putting forward arguments based on a postnewtonian approximative calculation that there can be a sizable general relativistic gr correction in the experimental determination of the muon magnetic moment based on spin precession ie in muon g2 experiments in response other authors argued that the effect must be much smaller than claimed further authors argued that the effect exactly cancels also the known formulae for de sitter and lensethirring effect do not apply due to the nongeodesic motion all this indicates that it is difficult to estimate from first principles the influence of gr corrections in the problem of spin propagation therefore in this paper we present a full general relativistic calculation in order to quantify this effect the main methodology is the purely differential geometrical tool of fermiwalker transport over a schwarzschild background also the larmor precession due to the propagation in the electromagnetic field of the experimental apparatus is included for the muon g2 experiments the gr correction turns out to be very small well below the present sensitivity however in other similar storage ring experimental settings such as electric dipole moment edm search experiments where the socalled frozen spin method is used gr gives a well detectable effect and should be corrected for all frozen spin scenarios are affected which intend to reach a sensitivity of 01 microradianssecond for the spin precession in the vertical plane | [['recently', 'morishima', 'futamase', 'and', 'shimizu', 'published', 'a', 'series', 'of', 'manuscripts', 'putting', 'forward', 'arguments', 'based', 'on', 'a', 'postnewtonian', 'approximative', 'calculation', 'that', 'there', 'can', 'be', 'a', 'sizable', 'general', 'relativistic', 'gr', 'correction', 'in', 'the', 'experimental', 'determination', 'of', 'the', 'muon', 'magnetic', 'moment', 'based', 'on', 'spin', 'precession', 'ie', 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1,803.01396 | On the distribution of totients 2 mod. 4 | In this paper we study the distribution of totients $2$ mod. $4$. We prove
that the asymptotic magnitude of such totients with multiplicity two is half of
that of prime numbers. As a corollary we obtain that the relative asymptotic
density of the number of those totients with multiplicity four over the number
of totients with multiplicity two is zero. We also obtain that the set of
totients which have, a bigger than one, power of a prime in their pre-images
and multiplicity $k$ has relative asymptotic density over the number of all
totients of multiplicity $k$ equals to zero. A result on the distribution of
consecutive pairs of totients $2$ mod. $4$, which relates to cousin primes, is
also provide.
| math.NT | in this paper we study the distribution of totients 2 mod 4 we prove that the asymptotic magnitude of such totients with multiplicity two is half of that of prime numbers as a corollary we obtain that the relative asymptotic density of the number of those totients with multiplicity four over the number of totients with multiplicity two is zero we also obtain that the set of totients which have a bigger than one power of a prime in their preimages and multiplicity k has relative asymptotic density over the number of all totients of multiplicity k equals to zero a result on the distribution of consecutive pairs of totients 2 mod 4 which relates to cousin primes is also provide | [['in', 'this', 'paper', 'we', 'study', 'the', 'distribution', 'of', 'totients', '2', 'mod', '4', 'we', 'prove', 'that', 'the', 'asymptotic', 'magnitude', 'of', 'such', 'totients', 'with', 'multiplicity', 'two', 'is', 'half', 'of', 'that', 'of', 'prime', 'numbers', 'as', 'a', 'corollary', 'we', 'obtain', 'that', 'the', 'relative', 'asymptotic', 'density', 'of', 'the', 'number', 'of', 'those', 'totients', 'with', 'multiplicity', 'four', 'over', 'the', 'number', 'of', 'totients', 'with', 'multiplicity', 'two', 'is', 'zero', 'we', 'also', 'obtain', 'that', 'the', 'set', 'of', 'totients', 'which', 'have', 'a', 'bigger', 'than', 'one', 'power', 'of', 'a', 'prime', 'in', 'their', 'preimages', 'and', 'multiplicity', 'k', 'has', 'relative', 'asymptotic', 'density', 'over', 'the', 'number', 'of', 'all', 'totients', 'of', 'multiplicity', 'k', 'equals', 'to', 'zero', 'a', 'result', 'on', 'the', 'distribution', 'of', 'consecutive', 'pairs', 'of', 'totients', '2', 'mod', '4', 'which', 'relates', 'to', 'cousin', 'primes', 'is', 'also', 'provide']] | [-0.2066830329227546, 0.11040144052725932, -0.13660782666430493, 0.02703516779675279, 0.024249710146460896, -0.06812001439196265, -0.006232448829499589, 0.27673818950718343, -0.20964512061558602, -0.3435837413561492, 0.04780608812955108, -0.31277743649999956, -0.07728443325551088, 0.18731040922032038, -0.050335385948265636, 0.009547886865844658, 0.02127662701301338, 0.17484143941133082, -0.05555969239732112, -0.31420156544397687, 0.3686337505798202, -0.04599851683890524, 0.18282646985824627, 0.018864206338593783, 0.06575204950780415, 0.03418139100444218, 0.003754899459929506, 0.030441088093952698, -0.15692889913728977, 0.12299511889919393, 0.21730136181697374, 0.10917594612283586, 0.2644215898726844, -0.3239223374869705, -0.09839900010380863, 0.2134305138779758, 0.16476316936314106, 0.008748223364337787, 0.02796052624798603, -0.13146433585192546, 0.22993966664595544, -0.2066782612453623, -0.16844243108687446, -0.027318469941431334, 0.08650110889041474, 0.10013224253592597, -0.2598484333927843, 0.05815905362919881, 0.09993308092035018, 0.12717637516296476, -0.02455762749507038, -0.21038202195205102, -0.03614218138381531, 0.10966466171359104, 0.09721067633425956, 0.012355957809481616, 0.02513956360149482, -0.12446745444851165, -0.11332133811829258, 0.31153678085870484, -0.04590590991340058, -0.1566950451921333, 0.17485290603358145, -0.24133763361860774, -0.12808954170019912, 0.17181132678404326, 0.1253136292346253, 0.13298659374521785, -0.022178341276666597, 0.07140198493066575, -0.12665995368387642, 0.15021294258411758, 0.13509976279667832, 0.05385410047544182, 0.1413025524975224, 0.10857951541023314, 0.11579404104970518, 0.1488142294639891, -0.12631602634383318, -0.00040493872279324375, -0.33187269951286147, -0.22359856785359708, -0.1970552300874621, 0.1305832459922295, -0.11339396144797899, -0.14181329324564412, 0.41374754853361895, 0.12633670808762804, 0.26139031016568015, 0.12255691954565873, 0.2431080397064528, 0.10428037625472426, 0.01968875941281661, 0.07548717144214787, 0.14999838456634648, 0.1540526467844967, -0.0031941674384173037, -0.1691969141849001, -0.004049320909202345, 0.10142244106497277] |
1,803.01397 | Universal bounds for the Hardy--Littlewood inequalities on multilinear
forms | The Hardy--Littlewood inequalities for multilinear forms on sequence spaces
state that for all positive integers $m,n\geq2$ and all $m$-linear forms
$T:\ell_{p_{1}}^{n}\times\cdots\times\ell_{p_{m}}^{n}\rightarrow\mathbb{K}$
($\mathbb{K}=\mathbb{R}$ or $\mathbb{C}$) there are constants $C_{m}\geq1$ (not
depending on $n$) such that \[ \left( \sum_{j_{1},\ldots,j_{m}=1}^{n}\left\vert
T(e_{j_{1}},\ldots,e_{j_{m}})\right\vert ^{\rho}\right) ^{\frac{1}{\rho}}\leq
C_{m}\sup_{\left\Vert x_{1}\right\Vert ,\dots,\left\Vert x_{m}\right\Vert \leq
1}\left\vert T(x_{1},\dots,x_{m})\right\vert, \] where
$\rho=\frac{2m}{m+1-2\left( \frac{1}{p_{1}}+\cdots+\frac{1}{p_{m}}\right) }$ if
$0\leq\frac{1}{p_{1}}+\cdots+\frac{1}{p_{m}}\leq\frac{1}{2}$ or
$\rho=\frac{1}{1-\left( \frac{1}{p_{1}}+\cdots+\frac{1}{p_{m}}\right)}$ if
$\frac{1}{2}\leq\frac{1}{p_{1}}+\cdots+\frac{1}{p_{m}}<1$. Good estimates for
the Hardy-Littlewood constants are, in general, associated to applications in
Mathematics and even in Physics, but the exact behavior of these constants is
still unknown. In this note we give some new contributions to the behavior of
the constants in the case
$\frac{1}{2}\leq\frac{1}{p_{1}}+\cdots+\frac{1}{p_{m}}<1$. As a consequence of
our main result, we present a generalization and a simplified proof of a result
due to Aron et al. on certain Hardy--Littlewood type inequalities.
| math.FA | the hardylittlewood inequalities for multilinear forms on sequence spaces state that for all positive integers mngeq2 and all mlinear forms tell_p_1ntimescdotstimesell_p_mnrightarrowmathbbk mathbbkmathbbr or mathbbc there are constants c_mgeq1 not depending on n such that left sum_j_1ldotsj_m1nleftvert te_j_1ldotse_j_mrightvert rhoright frac1rholeq c_msup_leftvert x_1rightvert dotsleftvert x_mrightvert leq 1leftvert tx_1dotsx_mrightvert where rhofrac2mm12left frac1p_1cdotsfrac1p_mright if 0leqfrac1p_1cdotsfrac1p_mleqfrac12 or rhofrac11left frac1p_1cdotsfrac1p_mright if frac12leqfrac1p_1cdotsfrac1p_m1 good estimates for the hardylittlewood constants are in general associated to applications in mathematics and even in physics but the exact behavior of these constants is still unknown in this note we give some new contributions to the behavior of the constants in the case frac12leqfrac1p_1cdotsfrac1p_m1 as a consequence of our main result we present a generalization and a simplified proof of a result due to aron et al on certain hardylittlewood type inequalities | [['the', 'hardylittlewood', 'inequalities', 'for', 'multilinear', 'forms', 'on', 'sequence', 'spaces', 'state', 'that', 'for', 'all', 'positive', 'integers', 'mngeq2', 'and', 'all', 'mlinear', 'forms', 'tell_p_1ntimescdotstimesell_p_mnrightarrowmathbbk', 'mathbbkmathbbr', 'or', 'mathbbc', 'there', 'are', 'constants', 'c_mgeq1', 'not', 'depending', 'on', 'n', 'such', 'that', 'left', 'sum_j_1ldotsj_m1nleftvert', 'te_j_1ldotse_j_mrightvert', 'rhoright', 'frac1rholeq', 'c_msup_leftvert', 'x_1rightvert', 'dotsleftvert', 'x_mrightvert', 'leq', '1leftvert', 'tx_1dotsx_mrightvert', 'where', 'rhofrac2mm12left', 'frac1p_1cdotsfrac1p_mright', 'if', '0leqfrac1p_1cdotsfrac1p_mleqfrac12', 'or', 'rhofrac11left', 'frac1p_1cdotsfrac1p_mright', 'if', 'frac12leqfrac1p_1cdotsfrac1p_m1', 'good', 'estimates', 'for', 'the', 'hardylittlewood', 'constants', 'are', 'in', 'general', 'associated', 'to', 'applications', 'in', 'mathematics', 'and', 'even', 'in', 'physics', 'but', 'the', 'exact', 'behavior', 'of', 'these', 'constants', 'is', 'still', 'unknown', 'in', 'this', 'note', 'we', 'give', 'some', 'new', 'contributions', 'to', 'the', 'behavior', 'of', 'the', 'constants', 'in', 'the', 'case', 'frac12leqfrac1p_1cdotsfrac1p_m1', 'as', 'a', 'consequence', 'of', 'our', 'main', 'result', 'we', 'present', 'a', 'generalization', 'and', 'a', 'simplified', 'proof', 'of', 'a', 'result', 'due', 'to', 'aron', 'et', 'al', 'on', 'certain', 'hardylittlewood', 'type', 'inequalities']] | [-0.11512042823885274, 0.10005894028749485, -0.03123130877544214, 0.08352031797036394, -0.0905258419654995, -0.13341714643982347, 0.03251536365762051, 0.31975629205840667, -0.2846931197537898, -0.2335420729978396, 0.14691521749970177, -0.28483047431989295, -0.17454834326237506, 0.2708517502246609, -0.0977103616496934, -0.005031317576287767, 0.018452545997124533, 0.06650280115102325, -0.05756853620504944, -0.299701255867845, 0.34330481297529497, -0.06424481596227165, 0.15492809649246433, 0.10074315209629701, 0.05451176100335008, 0.016311449972023297, 0.03530167897760465, -0.04777033076629982, -0.21064511947986683, 0.12544766512777036, 0.26018872618809474, 0.10647545493551874, 0.2750870196971002, -0.3685610318673892, -0.12505456184766986, 0.1809246237809258, 0.14536806679674769, 0.038286944482106344, -0.07159599807713316, -0.24560780987470737, 0.08981295688463761, -0.08792571415012988, -0.15311078446590015, -0.10337347202086905, 0.06355014436685287, 0.04669274683404076, -0.3335743558525972, 0.09983632827244766, 0.12344422915673538, 0.05213658649724518, -0.1014827148305034, -0.18258821528702807, 0.05901611931747883, 0.0858011983360189, 0.050450583171049085, 0.029372779882160593, 0.020909888795702845, -0.0955545978750698, -0.11263286320886969, 0.3363646161700557, -0.05807782832096826, -0.23770400685434406, 0.16130410245124688, -0.1721318003109044, -0.20484313028151388, 0.02568957492707062, 0.10810334435538263, 0.15080594833597313, -0.07514422185937161, 0.1537242766563059, -0.11293882255752881, 0.1421126258844795, 0.12687372651186074, 0.07558079942198773, 0.08302028468395227, 0.03217688739836753, 0.09747754841170332, 0.06880701533812392, 0.04227476915803965, -0.05700273654499167, -0.36380033364502695, -0.18241635569358697, -0.19320016770690746, 0.12545675327301314, -0.09173961443501957, -0.18548878476963387, 0.3474834530219973, 0.0901000556024211, 0.19839423206878137, 0.09967872545727201, 0.20421300646807025, 0.08041659008862602, 0.05377481398298531, 0.07165969902783767, 0.19732668868036363, 0.14683512293708487, 0.05355195285383243, -0.12355055035456915, 0.08872034159061071, 0.1544116999207249] |
1,803.01398 | Hirzebruch Functional Equation: Classification of Solutions | The Hirzebruch functional equation is \[
\sum_{i = 1}^{n} \prod_{j \ne i} { 1 \over f(z_j - z_i)} = c \] with constant
$c$ and initial conditions $f(0)=0, f'(0)=1$. In this paper we find all
solutions of the Hirzebruch functional equation for $n \leqslant 6$ in the
class of meromorphic functions and in the class of series. Previously, such
results were known only for $n \leqslant 4$.
The Todd function is the function determining the two-parametric Todd genus
(i.e. the $\chi_{a,b}$-genus). It gives a solution to the Hirzebruch functional
equation for any $n$. The elliptic function of level $N$ is the function
determining the elliptic genus of level $N$. It gives a solution to the
Hirzebruch functional equation for $n$ divisible by $N$.
A series corresponding to a meromorphic function $f$ with parameters in $U
\subset \mathbb{C}^k$ is a series with parameters in the Zariski closure of $U$
in $\mathbb{C}^k$, such that for parameters in $U$ it coincides with the series
expansion at zero of $f$. The main results are:
Any series solution of the Hirzebruch functional equation for $n = 5$
corresponds to the Todd function or to the elliptic function of level $5$.
Any series solution of the Hirzebruch functional equation for $n = 6$
corresponds to the Todd function or to the elliptic function of level $2$, $3$
or $6$.
This gives a complete classification of complex genera that are fiber
multiplicative with respect to $\mathbb{C}P^{n-1}$ for $n \leqslant 6$.
| math.AT | the hirzebruch functional equation is sum_i 1n prod_j ne i 1 over fz_j z_i c with constant c and initial conditions f00 f01 in this paper we find all solutions of the hirzebruch functional equation for n leqslant 6 in the class of meromorphic functions and in the class of series previously such results were known only for n leqslant 4 the todd function is the function determining the twoparametric todd genus ie the chi_abgenus it gives a solution to the hirzebruch functional equation for any n the elliptic function of level n is the function determining the elliptic genus of level n it gives a solution to the hirzebruch functional equation for n divisible by n a series corresponding to a meromorphic function f with parameters in u subset mathbbck is a series with parameters in the zariski closure of u in mathbbck such that for parameters in u it coincides with the series expansion at zero of f the main results are any series solution of the hirzebruch functional equation for n 5 corresponds to the todd function or to the elliptic function of level 5 any series solution of the hirzebruch functional equation for n 6 corresponds to the todd function or to the elliptic function of level 2 3 or 6 this gives a complete classification of complex genera that are fiber multiplicative with respect to mathbbcpn1 for n leqslant 6 | [['the', 'hirzebruch', 'functional', 'equation', 'is', 'sum_i', '1n', 'prod_j', 'ne', 'i', '1', 'over', 'fz_j', 'z_i', 'c', 'with', 'constant', 'c', 'and', 'initial', 'conditions', 'f00', 'f01', 'in', 'this', 'paper', 'we', 'find', 'all', 'solutions', 'of', 'the', 'hirzebruch', 'functional', 'equation', 'for', 'n', 'leqslant', '6', 'in', 'the', 'class', 'of', 'meromorphic', 'functions', 'and', 'in', 'the', 'class', 'of', 'series', 'previously', 'such', 'results', 'were', 'known', 'only', 'for', 'n', 'leqslant', '4', 'the', 'todd', 'function', 'is', 'the', 'function', 'determining', 'the', 'twoparametric', 'todd', 'genus', 'ie', 'the', 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1,803.01399 | Ancient Solutions to Curve Shortening with Finite Total Curvature | We construct ancient solutions to Curve Shortening in the plane whose total
curvature is uniformly bounded by gluing together an arbitrary chain of given
Grim Reapers along their common asymptotes.
| math.DG | we construct ancient solutions to curve shortening in the plane whose total curvature is uniformly bounded by gluing together an arbitrary chain of given grim reapers along their common asymptotes | [['we', 'construct', 'ancient', 'solutions', 'to', 'curve', 'shortening', 'in', 'the', 'plane', 'whose', 'total', 'curvature', 'is', 'uniformly', 'bounded', 'by', 'gluing', 'together', 'an', 'arbitrary', 'chain', 'of', 'given', 'grim', 'reapers', 'along', 'their', 'common', 'asymptotes']] | [-0.22469083822021882, 0.1290381256689822, -0.07935187841455142, 0.022181164011514435, -0.11575774028897286, -0.14893827283134062, -0.052964943007100376, 0.3923295047134161, -0.33298353031277655, -0.17397231453408799, 0.16705401949196433, -0.32484695240855216, -0.034918150817975405, 0.18917686122780045, -0.13608728628605604, 0.04551109926154216, 0.03210547752678394, 0.0830923513819774, -0.07142312470823527, -0.25049281592170397, 0.3443082952251037, -0.019597286482652028, 0.2120175242734452, -0.014441905387987694, 0.14621699918061495, 0.009479303301001588, -0.003959289689858755, 0.0032535452395677567, -0.24143849691996971, 0.17817012031252186, 0.2165482223033905, 0.09940185608963172, 0.17740635437270005, -0.410979519225657, -0.16157180681669464, 0.1756514921784401, 0.19426578317458432, 0.09694457072764635, -0.01711409892110775, -0.2368222736530394, 0.09735238210608561, -0.05760254468768835, -0.2755860937293619, 0.015867928400014837, 0.06135636971642574, 0.12356849002341429, -0.12266772321114937, 0.004377919621765614, 0.06507102842442691, 0.07067663262908658, -0.07474529274040834, -0.06452285932997863, -0.13552473690360783, 0.09916274670201043, 0.058821735942425825, 0.13748804214410484, 0.037537969664360085, 0.007542964505652587, -0.045163728389889, 0.2716213744133711, -0.11660746382549406, -0.24921074956655503, 0.09062086312721172, -0.07018076043265561, -0.0369777524843812, 0.2070760177448392, 0.1280182846666624, 0.1642488669604063, -0.1447213030575464, 0.10460629025474191, -0.02018998945131898, 0.13147118526200455, 0.16840579466273387, -0.087004387875398, 0.24355766735970974, 0.026109408183644215, 0.16791138037418327, 0.20775278327055274, 0.022809377297138174, -0.17426278615991275, -0.33803162624438604, -0.14007472473507127, -0.12982993304807072, 0.09098471629743775, -0.17780249409067134, -0.26286414824426174, 0.3475209812323252, -0.035137341541091396, 0.23847950499815246, 0.09895844611649712, 0.22810868689169486, 0.067686642271777, 0.028900014712902097, 0.15072865536203608, 0.11268917943816632, 0.12994540014769881, 0.03290267259192963, -0.1773558384273201, 0.0385012315120548, 0.12172804923563187] |
1,803.014 | Concatenated Power Mean Word Embeddings as Universal Cross-Lingual
Sentence Representations | Average word embeddings are a common baseline for more sophisticated sentence
embedding techniques. However, they typically fall short of the performances of
more complex models such as InferSent. Here, we generalize the concept of
average word embeddings to power mean word embeddings. We show that the
concatenation of different types of power mean word embeddings considerably
closes the gap to state-of-the-art methods monolingually and substantially
outperforms these more complex techniques cross-lingually. In addition, our
proposed method outperforms different recently proposed baselines such as SIF
and Sent2Vec by a solid margin, thus constituting a much harder-to-beat
monolingual baseline. Our data and code are publicly available.
| cs.CL | average word embeddings are a common baseline for more sophisticated sentence embedding techniques however they typically fall short of the performances of more complex models such as infersent here we generalize the concept of average word embeddings to power mean word embeddings we show that the concatenation of different types of power mean word embeddings considerably closes the gap to stateoftheart methods monolingually and substantially outperforms these more complex techniques crosslingually in addition our proposed method outperforms different recently proposed baselines such as sif and sent2vec by a solid margin thus constituting a much hardertobeat monolingual baseline our data and code are publicly available | [['average', 'word', 'embeddings', 'are', 'a', 'common', 'baseline', 'for', 'more', 'sophisticated', 'sentence', 'embedding', 'techniques', 'however', 'they', 'typically', 'fall', 'short', 'of', 'the', 'performances', 'of', 'more', 'complex', 'models', 'such', 'as', 'infersent', 'here', 'we', 'generalize', 'the', 'concept', 'of', 'average', 'word', 'embeddings', 'to', 'power', 'mean', 'word', 'embeddings', 'we', 'show', 'that', 'the', 'concatenation', 'of', 'different', 'types', 'of', 'power', 'mean', 'word', 'embeddings', 'considerably', 'closes', 'the', 'gap', 'to', 'stateoftheart', 'methods', 'monolingually', 'and', 'substantially', 'outperforms', 'these', 'more', 'complex', 'techniques', 'crosslingually', 'in', 'addition', 'our', 'proposed', 'method', 'outperforms', 'different', 'recently', 'proposed', 'baselines', 'such', 'as', 'sif', 'and', 'sent2vec', 'by', 'a', 'solid', 'margin', 'thus', 'constituting', 'a', 'much', 'hardertobeat', 'monolingual', 'baseline', 'our', 'data', 'and', 'code', 'are', 'publicly', 'available']] | [-0.02522044228412464, 0.0459875524003348, -0.047663515347770406, 0.1326367575720459, -0.11706715843920569, -0.1504561876091491, 0.04552951300498641, 0.47951831654148197, -0.2762364072197352, -0.31649276187408315, 0.05106834528710042, -0.31135448285839656, -0.12720677028500557, 0.28035110438206384, -0.10601343876609887, 0.06707348214299644, 0.16308683473436, 0.05857918856358065, -0.1468402904636923, -0.31893575642691946, 0.28762533769544973, 0.05358935400642437, 0.3551016296531318, 0.004209857764066133, 0.10130104573231045, -0.05428238272287168, -0.06408148330582071, 0.02382816452967021, -0.07088644354350161, 0.18906873528330218, 0.3178305785386505, 0.19158019180617575, 0.26475114719851794, -0.3718978869412275, -0.26799238070809434, 0.0838752081888972, 0.14986720145001864, 0.11691519038896393, 0.0063374363863897215, -0.3163792190042514, 0.10436926729687789, -0.22540788283996574, 0.07207987644230422, -0.14286428828863879, 0.007200208139940373, 0.060495497897330636, -0.22872181430242014, 0.04757229900620516, 0.1563832839471695, 0.06250749329032684, -0.028810834756247627, -0.2098277875457357, 0.032672533503218186, 0.14179150108700095, 0.05226502182341895, 0.07199959069472349, 0.08853127832696275, -0.147716190476079, -0.1781461235063458, 0.36123720692127076, -0.10901579365712925, -0.2303625292334597, 0.22850410213006786, -0.025311264132592572, -0.1141876934132385, 0.07901869558738274, 0.17830384368058835, 0.11113283622250394, -0.10357271288566798, -0.014599460861487404, -0.06525032004359567, 0.21431296760017432, 0.10650548613765864, 0.02779442843194436, 0.1252449093910965, 0.24339672563217798, 0.02241992506478886, 0.09447824148895237, -0.09753160156847601, -0.06992995327799717, -0.16337310257412999, -0.09751419704949972, -0.15183188222366775, -0.03416121470316955, -0.14239439033652831, -0.13199403853092379, 0.4189321833834486, 0.20963266535291394, 0.1568327112693014, 0.17058371761655525, 0.33776933417736904, -0.005296823668103774, 0.13980918755366023, 0.1244119023452106, 0.1710498000165104, -0.019671109904257075, 0.05556659487265985, -0.12610925781739496, 0.05431324315655217, 0.05737225876813664] |
1,803.01401 | A Primal-Dual Algorithm with Line Search for General Convex-Concave
Saddle Point Problems | In this paper, we propose a primal-dual algorithm with a novel momentum term
using the partial gradients of the coupling function that can be viewed as a
generalization of the method proposed by Chambolle and Pock in 2016 to solve
saddle point problems defined by a convex-concave function $\mathcal
L(x,y)=f(x)+\Phi(x,y)-h(y)$ with a general coupling term $\Phi(x,y)$ that is
not assumed to be bilinear. Assuming $\nabla_x\Phi(\cdot,y)$ is Lipschitz for
any fixed $y$, and $\nabla_y\Phi(\cdot,\cdot)$ is Lipschitz, we show that the
iterate sequence converges to a saddle point; and for any $(x,y)$, we derive
error bounds in terms of $\mathcal L(\bar{x}_k,y)-\mathcal L(x,\bar{y}_k)$ for
the ergodic sequence $\{\bar{x}_k,\bar{y}_k\}$. In particular, we show
$\mathcal O(1/k)$ rate when the problem is merely convex in $x$. Furthermore,
assuming $\Phi(x,\cdot)$ is linear for each fixed $x$ and $f$ is strongly
convex, we obtain the ergodic convergence rate of $\mathcal O(1/k^2)$ -- we are
not aware of another single-loop method in the related literature achieving the
same rate when $\Phi$ is not bilinear. Finally, we propose a backtracking
technique which does not require the knowledge of Lipschitz constants while
ensuring the same convergence results. We also consider convex optimization
problems with nonlinear functional constraints and we show that using the
backtracking scheme, the optimal convergence rate can be achieved even when the
dual domain is unbounded. We tested our method against other state-of-the-art
first-order algorithms and interior-point methods for solving quadratically
constrained quadratic problems with synthetic data, the kernel matrix learning,
and regression with fairness constraints arising in machine learning.
| math.OC | in this paper we propose a primaldual algorithm with a novel momentum term using the partial gradients of the coupling function that can be viewed as a generalization of the method proposed by chambolle and pock in 2016 to solve saddle point problems defined by a convexconcave function mathcal lxyfxphixyhy with a general coupling term phixy that is not assumed to be bilinear assuming nabla_xphicdoty is lipschitz for any fixed y and nabla_yphicdotcdot is lipschitz we show that the iterate sequence converges to a saddle point and for any xy we derive error bounds in terms of mathcal lbarx_kymathcal lxbary_k for the ergodic sequence barx_kbary_k in particular we show mathcal o1k rate when the problem is merely convex in x furthermore assuming phixcdot is linear for each fixed x and f is strongly convex we obtain the ergodic convergence rate of mathcal o1k2 we are not aware of another singleloop method in the related literature achieving the same rate when phi is not bilinear finally we propose a backtracking technique which does not require the knowledge of lipschitz constants while ensuring the same convergence results we also consider convex optimization problems with nonlinear functional constraints and we show that using the backtracking scheme the optimal convergence rate can be achieved even when the dual domain is unbounded we tested our method against other stateoftheart firstorder algorithms and interiorpoint methods for solving quadratically constrained quadratic problems with synthetic data the kernel matrix learning and regression with fairness constraints arising in machine learning | [['in', 'this', 'paper', 'we', 'propose', 'a', 'primaldual', 'algorithm', 'with', 'a', 'novel', 'momentum', 'term', 'using', 'the', 'partial', 'gradients', 'of', 'the', 'coupling', 'function', 'that', 'can', 'be', 'viewed', 'as', 'a', 'generalization', 'of', 'the', 'method', 'proposed', 'by', 'chambolle', 'and', 'pock', 'in', '2016', 'to', 'solve', 'saddle', 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1,803.01402 | An Note on Why Geographically Weighted Regression Overcomes
Multidimensional-Kernel-Based Varying-Coefficient Model | It is widely known that geographically weighted regression(GWR) is
essentially same as varying-coefficient model. In the former research about
varying-coefficient model, scholars tend to use multidimensional-kernel-based
locally weighted estimation(MLWE) so that information of both distance and
direction is considered. However, when we construct the local weight matrix of
geographically weighted estimation, distance among the locations in the
neighbor is the only factor controlling the value of entries of weight matrix.
In other word, estimation of GWR is distance-kernel-based. Thus, in this paper,
under stationary and limited dependent data with multidimensional subscripts,
we analyze the local mean squared properties of without any assumption of the
form of coefficient functions and compare it with MLWE. According to the
theoretical and simulation results, geographically-weighted locally linear
estimation(GWLE) is asymptotically more efficient than MLWE. Furthermore, a
relationship between optimal bandwith selection and design of scale parameters
is also obtained.
| econ.EM | it is widely known that geographically weighted regressiongwr is essentially same as varyingcoefficient model in the former research about varyingcoefficient model scholars tend to use multidimensionalkernelbased locally weighted estimationmlwe so that information of both distance and direction is considered however when we construct the local weight matrix of geographically weighted estimation distance among the locations in the neighbor is the only factor controlling the value of entries of weight matrix in other word estimation of gwr is distancekernelbased thus in this paper under stationary and limited dependent data with multidimensional subscripts we analyze the local mean squared properties of without any assumption of the form of coefficient functions and compare it with mlwe according to the theoretical and simulation results geographicallyweighted locally linear estimationgwle is asymptotically more efficient than mlwe furthermore a relationship between optimal bandwith selection and design of scale parameters is also obtained | [['it', 'is', 'widely', 'known', 'that', 'geographically', 'weighted', 'regressiongwr', 'is', 'essentially', 'same', 'as', 'varyingcoefficient', 'model', 'in', 'the', 'former', 'research', 'about', 'varyingcoefficient', 'model', 'scholars', 'tend', 'to', 'use', 'multidimensionalkernelbased', 'locally', 'weighted', 'estimationmlwe', 'so', 'that', 'information', 'of', 'both', 'distance', 'and', 'direction', 'is', 'considered', 'however', 'when', 'we', 'construct', 'the', 'local', 'weight', 'matrix', 'of', 'geographically', 'weighted', 'estimation', 'distance', 'among', 'the', 'locations', 'in', 'the', 'neighbor', 'is', 'the', 'only', 'factor', 'controlling', 'the', 'value', 'of', 'entries', 'of', 'weight', 'matrix', 'in', 'other', 'word', 'estimation', 'of', 'gwr', 'is', 'distancekernelbased', 'thus', 'in', 'this', 'paper', 'under', 'stationary', 'and', 'limited', 'dependent', 'data', 'with', 'multidimensional', 'subscripts', 'we', 'analyze', 'the', 'local', 'mean', 'squared', 'properties', 'of', 'without', 'any', 'assumption', 'of', 'the', 'form', 'of', 'coefficient', 'functions', 'and', 'compare', 'it', 'with', 'mlwe', 'according', 'to', 'the', 'theoretical', 'and', 'simulation', 'results', 'geographicallyweighted', 'locally', 'linear', 'estimationgwle', 'is', 'asymptotically', 'more', 'efficient', 'than', 'mlwe', 'furthermore', 'a', 'relationship', 'between', 'optimal', 'bandwith', 'selection', 'and', 'design', 'of', 'scale', 'parameters', 'is', 'also', 'obtained']] | [-0.0708790352639409, 0.09562067182591852, -0.05006949737477694, 0.06936506343747142, -0.09288910699899505, -0.13955192746642134, 0.05860331713776002, 0.4266991535895062, -0.2991852312532328, -0.28124267316973994, 0.11566673127431286, -0.28506554984725524, -0.16487363533517957, 0.16875876151501154, -0.05791793091317816, 0.0466636706850607, 0.039893951661286564, 0.08659453420852223, -0.09074748205273823, -0.2620453502588572, 0.32081222153663036, 0.09614859805884261, 0.3194632079710599, -0.0038626062829067837, 0.09073406694045658, 0.03439950360066808, -0.07126018654701238, 0.027516643528137815, -0.10983816281109318, 0.1409697678572342, 0.25233248980158435, 0.13265877795901937, 0.3053771025589565, -0.36796859693951417, -0.1933342387192767, 0.15796728309220123, 0.12693587727300878, 0.06312577213996845, 0.010713047660563487, -0.21727991246883452, 0.12131468881682976, -0.1330016666624345, -0.09799857948478448, -0.03551831698881285, 0.026341595182222496, 0.048153960570139834, -0.3104078790009783, 0.11279988041241912, 0.032289452633283436, 0.022141663126484322, -0.06493365327848026, -0.1453494298795279, -0.0002717295029356967, 0.14426785351493546, 0.05859210658274645, 0.02497215291576963, 0.08941348519747275, -0.12550311862749394, -0.062405105122793326, 0.3649602319134304, -0.0528077750028507, -0.2609804647254085, 0.1475685451393879, -0.12007541643849907, -0.08269417437344083, 0.056961571928589555, 0.17008795013037734, 0.12207577726293872, -0.17592058760289486, 0.06705025356920627, -0.06594497952644245, 0.17853390500901173, 0.044295076890950545, 0.03876773863487, 0.12115372971624788, 0.1367637687991543, 0.136797932353904, 0.12013123198930704, -0.07621663239832124, -0.12439800543459065, -0.2628126547257178, -0.12003221025649649, -0.22326261850998458, 0.008208989430844348, -0.14046927362994416, -0.17939023527972753, 0.3731097761511014, 0.14963582293368385, 0.21053929399549418, 0.10236627058921395, 0.2718446605913613, 0.10278628910568807, 0.06659896233302616, 0.12626094557174963, 0.19700945520188903, 0.12642222343107862, 0.03261228517737974, -0.16575378742932348, 0.12644899439408247, 0.04954191685287132] |
1,803.01403 | Exploring Novel Game Spaces with Fluidic Games | With the growing integration of smartphones into our daily lives, and their
increased ease of use, mobile games have become highly popular across all
demographics. People listen to music, play games or read the news while in
transit or bridging gap times. While mobile gaming is gaining popularity,
mobile expression of creativity is still in its early stages. We present here a
new type of mobile app -- fluidic games -- and illustrate our iterative
approach to their design. This new type of app seamlessly integrates
exploration of the design space into the actual user experience of playing the
game, and aims to enrich the user experience. To better illustrate the game
domain and our approach, we discuss one specific fluidic game, which is
available as a commercial product. We also briefly discuss open challenges such
as player support and how generative techniques can aid the exploration of the
game space further.
| cs.AI | with the growing integration of smartphones into our daily lives and their increased ease of use mobile games have become highly popular across all demographics people listen to music play games or read the news while in transit or bridging gap times while mobile gaming is gaining popularity mobile expression of creativity is still in its early stages we present here a new type of mobile app fluidic games and illustrate our iterative approach to their design this new type of app seamlessly integrates exploration of the design space into the actual user experience of playing the game and aims to enrich the user experience to better illustrate the game domain and our approach we discuss one specific fluidic game which is available as a commercial product we also briefly discuss open challenges such as player support and how generative techniques can aid the exploration of the game space further | [['with', 'the', 'growing', 'integration', 'of', 'smartphones', 'into', 'our', 'daily', 'lives', 'and', 'their', 'increased', 'ease', 'of', 'use', 'mobile', 'games', 'have', 'become', 'highly', 'popular', 'across', 'all', 'demographics', 'people', 'listen', 'to', 'music', 'play', 'games', 'or', 'read', 'the', 'news', 'while', 'in', 'transit', 'or', 'bridging', 'gap', 'times', 'while', 'mobile', 'gaming', 'is', 'gaining', 'popularity', 'mobile', 'expression', 'of', 'creativity', 'is', 'still', 'in', 'its', 'early', 'stages', 'we', 'present', 'here', 'a', 'new', 'type', 'of', 'mobile', 'app', 'fluidic', 'games', 'and', 'illustrate', 'our', 'iterative', 'approach', 'to', 'their', 'design', 'this', 'new', 'type', 'of', 'app', 'seamlessly', 'integrates', 'exploration', 'of', 'the', 'design', 'space', 'into', 'the', 'actual', 'user', 'experience', 'of', 'playing', 'the', 'game', 'and', 'aims', 'to', 'enrich', 'the', 'user', 'experience', 'to', 'better', 'illustrate', 'the', 'game', 'domain', 'and', 'our', 'approach', 'we', 'discuss', 'one', 'specific', 'fluidic', 'game', 'which', 'is', 'available', 'as', 'a', 'commercial', 'product', 'we', 'also', 'briefly', 'discuss', 'open', 'challenges', 'such', 'as', 'player', 'support', 'and', 'how', 'generative', 'techniques', 'can', 'aid', 'the', 'exploration', 'of', 'the', 'game', 'space', 'further']] | [-0.07931132379298408, 0.05207931886194274, -0.08684780701606845, 0.06805286969523877, -0.1490035344970723, -0.2006981330892692, 0.09298802691356589, 0.43009517949831205, -0.2511421764673044, -0.3448451114197572, 0.1059977124646927, -0.28813591375947, -0.20719120465529461, 0.1609104168935058, -0.1412071370705962, -0.010661640561884268, 0.09523765041492879, 0.04647515509277582, 0.02277226165868342, -0.2935905379972731, 0.3066075561195612, 0.041500691069910924, 0.2864462547857935, 0.07270046036690474, 0.06481335904061174, 0.009288901013011735, -0.07850016480001311, -0.02094088233114841, -0.09488203490133552, 0.16809999124961905, 0.3314625026658177, 0.24588571985252203, 0.4076582583474616, -0.47687050556143123, -0.17157179394892105, 0.04912019668651434, 0.18586407251811277, 0.0659716810604247, -0.08612634465175992, -0.3510887949665387, 0.0897862788491572, -0.25027655242631835, -0.08393027432883779, -0.06902309775352478, -0.0006602328767379125, 0.02993412423413247, -0.22776462525129318, -0.0816295354597969, 0.0032257626267770925, 0.06904860547743738, -0.03853649786479461, -0.11985962036376198, 0.010314296907745301, 0.2599890473453949, 0.06040076986886561, -0.010096946666017174, 0.186717390101403, -0.17415415202733128, -0.16910610199905932, 0.3799458989997705, 0.001816921488692363, -0.13132421612739564, 0.2053773823628823, -0.04289428097506364, -0.09302181004857024, 0.06223113365471363, 0.25312353822092215, 0.08830471097957343, -0.13039389234191429, 0.021552110770329213, 0.005372645392393073, 0.16624657456064595, 0.017683854797699797, 0.052625034572556614, 0.23126662615065774, 0.2632371281956633, 0.08450770152267069, 0.10106941121630371, -0.007684753173186134, -0.151191594125703, -0.1994175277518419, -0.21712834964195887, -0.131092761150018, 0.006523904561569604, -0.09597178456325006, -0.14593974461235726, 0.3840649593062699, 0.2059256385314317, 0.10063652027398348, 0.06418778929451946, 0.34399878663321337, 0.026332888855443645, 0.07403337722023329, 0.07159462131404629, 0.14698390858015045, -0.009188479178895552, 0.2534118579979986, -0.16412004818130904, 0.09031012063845992, -0.003388314135372639] |
1,803.01404 | Fractalized Metals | The classification of gapped phases of non-interacting fermions hinges on the
tenfold symmetries and on the spatial dimension. The notion of dimension leads
to a well defined demarcation between bulk and edge. Here we explore the nature
of topological phases in systems where the distinction between bulk and edge is
nebulous, of which fractal lattices are canonical examples. Our key finding is
that in homogeneous fractal lattices (where every site is equally coordinated),
there are no gapped topological phases. What appears instead is a novel
metallic state -- the fractalized metal -- whose low energy states arrange
hierarchically on the structure of the fractal that hosts them. We study the
properties (such as chiral transport) of this metal and demonstrate its
robustness to disorder. Further, by studying a variety of fractal models we
establish that the homogeneity of the fractal is a key condition for the
realization of such fractalized metallic states.
| cond-mat.dis-nn cond-mat.mes-hall | the classification of gapped phases of noninteracting fermions hinges on the tenfold symmetries and on the spatial dimension the notion of dimension leads to a well defined demarcation between bulk and edge here we explore the nature of topological phases in systems where the distinction between bulk and edge is nebulous of which fractal lattices are canonical examples our key finding is that in homogeneous fractal lattices where every site is equally coordinated there are no gapped topological phases what appears instead is a novel metallic state the fractalized metal whose low energy states arrange hierarchically on the structure of the fractal that hosts them we study the properties such as chiral transport of this metal and demonstrate its robustness to disorder further by studying a variety of fractal models we establish that the homogeneity of the fractal is a key condition for the realization of such fractalized metallic states | [['the', 'classification', 'of', 'gapped', 'phases', 'of', 'noninteracting', 'fermions', 'hinges', 'on', 'the', 'tenfold', 'symmetries', 'and', 'on', 'the', 'spatial', 'dimension', 'the', 'notion', 'of', 'dimension', 'leads', 'to', 'a', 'well', 'defined', 'demarcation', 'between', 'bulk', 'and', 'edge', 'here', 'we', 'explore', 'the', 'nature', 'of', 'topological', 'phases', 'in', 'systems', 'where', 'the', 'distinction', 'between', 'bulk', 'and', 'edge', 'is', 'nebulous', 'of', 'which', 'fractal', 'lattices', 'are', 'canonical', 'examples', 'our', 'key', 'finding', 'is', 'that', 'in', 'homogeneous', 'fractal', 'lattices', 'where', 'every', 'site', 'is', 'equally', 'coordinated', 'there', 'are', 'no', 'gapped', 'topological', 'phases', 'what', 'appears', 'instead', 'is', 'a', 'novel', 'metallic', 'state', 'the', 'fractalized', 'metal', 'whose', 'low', 'energy', 'states', 'arrange', 'hierarchically', 'on', 'the', 'structure', 'of', 'the', 'fractal', 'that', 'hosts', 'them', 'we', 'study', 'the', 'properties', 'such', 'as', 'chiral', 'transport', 'of', 'this', 'metal', 'and', 'demonstrate', 'its', 'robustness', 'to', 'disorder', 'further', 'by', 'studying', 'a', 'variety', 'of', 'fractal', 'models', 'we', 'establish', 'that', 'the', 'homogeneity', 'of', 'the', 'fractal', 'is', 'a', 'key', 'condition', 'for', 'the', 'realization', 'of', 'such', 'fractalized', 'metallic', 'states']] | [-0.16949470704421402, 0.20075015909659366, -0.07719182206628224, 0.039552852779161186, -0.021188566531054675, -0.13307432675578942, 0.06468586898874491, 0.3565531115233898, -0.260681638220946, -0.25164160147309306, 0.0672569271006311, -0.2873975944022338, -0.19445861383263643, 0.12010676438609759, -0.017909199989711244, 0.015029471626524658, -0.034395968671888114, -0.00209565049658219, -0.0900708737395083, -0.22262289623885104, 0.3715699413387726, -0.011840840734851856, 0.3361580411515509, 0.06470971869459996, 0.0357864140594999, -0.03696173861778031, 0.03620910227919618, 0.03061538469667236, -0.13926576068542393, 0.11581172636632497, 0.2281499254869656, 0.0045705823716707525, 0.19874139453129222, -0.405721453591832, -0.227148896252426, 0.08230800190009177, 0.12727483832044528, 0.09164838541531935, -0.04569751553159828, -0.2892739152691017, 0.09147802004503319, -0.10707465128352245, -0.16374218936728235, -0.09031821470988992, 0.022961419690400362, -0.024331080975825897, -0.19460759700314761, 0.08202796844765543, 0.09974586555346225, 0.07464773627463728, -0.061745881060293564, -0.058970854667325816, -0.10192763220053166, 0.12580112072483948, -0.004893891121416042, -0.01565451974204431, 0.08669981310415703, -0.1490178417880088, -0.1366341656446457, 0.4085179478613039, 0.003924124708864838, -0.1727202840335667, 0.27407971120749913, -0.13616611332351264, -0.12056515336657564, 0.09168606858079632, 0.1284870592628916, 0.07185638331342488, -0.09314815112117988, 0.07966859111892215, -0.08524535852173964, 0.15640416427127396, 0.015306896683759987, 0.10451273616713783, 0.24302871886252736, 0.21690372941394648, 0.08758450588521859, 0.16596346478598814, -0.06946800014644396, -0.09157435872902472, -0.27087024111223096, -0.22687378072490294, -0.25258679864462463, 0.06106907582841813, -0.10003741207183339, -0.23270917816087602, 0.42569986059019965, 0.10489568946960692, 0.22735627430180708, -0.01841708897224938, 0.22919015309462945, 0.07441927974422773, 0.05466190981989105, 0.057253218713837366, 0.20188576607499273, 0.13435589718477178, 0.025159441564852992, -0.20163644070737063, 0.046563826277075955, 0.07952381280561288] |
1,803.01405 | Three-forms, dualities and membranes in four-dimensional supergravity | We consider four-dimensional $\mathcal{N}=1$ supergravity models of a kind
appearing in string flux compactifications. It has been recently shown that, by
using double three-form multiplets instead of ordinary chiral multiplets, one
can promote to dynamical variables (part of) the quantized numbers appearing in
the flux-induced superpotential. We show that double three-form multiplets
naturally transform under symplectic dualities associated with the special
K\"ahler structure that characterizes their scalar sector. Furthermore, we
discuss how to couple membranes which carry arbitrary `electric-magnetic'
charges. The complete action is supersymmetric, kappa-symmetric and duality
covariant. As an application, we derive the flow equations for BPS domain walls
sourced by membranes and give simple analytic examples of their solution.
| hep-th | we consider fourdimensional mathcaln1 supergravity models of a kind appearing in string flux compactifications it has been recently shown that by using double threeform multiplets instead of ordinary chiral multiplets one can promote to dynamical variables part of the quantized numbers appearing in the fluxinduced superpotential we show that double threeform multiplets naturally transform under symplectic dualities associated with the special kahler structure that characterizes their scalar sector furthermore we discuss how to couple membranes which carry arbitrary electricmagnetic charges the complete action is supersymmetric kappasymmetric and duality covariant as an application we derive the flow equations for bps domain walls sourced by membranes and give simple analytic examples of their solution | [['we', 'consider', 'fourdimensional', 'mathcaln1', 'supergravity', 'models', 'of', 'a', 'kind', 'appearing', 'in', 'string', 'flux', 'compactifications', 'it', 'has', 'been', 'recently', 'shown', 'that', 'by', 'using', 'double', 'threeform', 'multiplets', 'instead', 'of', 'ordinary', 'chiral', 'multiplets', 'one', 'can', 'promote', 'to', 'dynamical', 'variables', 'part', 'of', 'the', 'quantized', 'numbers', 'appearing', 'in', 'the', 'fluxinduced', 'superpotential', 'we', 'show', 'that', 'double', 'threeform', 'multiplets', 'naturally', 'transform', 'under', 'symplectic', 'dualities', 'associated', 'with', 'the', 'special', 'kahler', 'structure', 'that', 'characterizes', 'their', 'scalar', 'sector', 'furthermore', 'we', 'discuss', 'how', 'to', 'couple', 'membranes', 'which', 'carry', 'arbitrary', 'electricmagnetic', 'charges', 'the', 'complete', 'action', 'is', 'supersymmetric', 'kappasymmetric', 'and', 'duality', 'covariant', 'as', 'an', 'application', 'we', 'derive', 'the', 'flow', 'equations', 'for', 'bps', 'domain', 'walls', 'sourced', 'by', 'membranes', 'and', 'give', 'simple', 'analytic', 'examples', 'of', 'their', 'solution']] | [-0.16655921622441383, 0.16443209704877, -0.05540727110513087, 0.12772994370087482, -0.1492205522954464, -0.15956358053725644, -0.05124715230028544, 0.3364666155934434, -0.17661303032946307, -0.2575431194023362, 0.07858670645925615, -0.23464027979935054, -0.23647669259142795, 0.08898527926274775, -0.10479156257185553, -0.005229909588316721, -0.02064742912521719, 0.06009363948708467, -0.09438133233717443, -0.2795267247752885, 0.3681145083059424, -0.05068942892830819, 0.2567575506608201, 0.03269485024741568, 0.1310023439249822, -0.031068845034626844, 0.003732993034645915, -0.020988816823644032, -0.11260943425226547, 0.12743749954721093, 0.22504023002215945, 0.05876729232217518, 0.06275940335971038, -0.503423059209516, -0.23913312601923412, 0.11765087557224822, 0.19413007465170398, 0.13647614841361896, -0.033296774383675905, -0.2667788334323892, 0.0686491961667863, -0.193197767368734, -0.18052342945260794, -0.17562710697088083, 0.010645182869796242, -0.06938749444504667, -0.23719793997848423, 0.0715884223879714, 0.004677117823770719, 0.024048472621611187, -0.08209747110127605, -0.0765230761296282, -0.10775566756326173, 0.054270722951124686, 0.15331559484288196, 0.02000757527587536, 0.13544742385939962, -0.18948703781435533, -0.1700137584048207, 0.3388794421875251, -0.08682100242211684, -0.28329981706338003, 0.0917554893614059, -0.08452794445163038, -0.17778427034915825, 0.09540310701101719, 0.08676434995972418, 0.1839860563881562, -0.1330485209811221, 0.23824989258407317, -0.05934472158384908, 0.1043176991339091, 0.12875622493447736, 0.03478699008701369, 0.2755525327707541, 0.054938746310654096, 0.047331394677062884, 0.18617699712714447, 0.016445115033483098, -0.14484417268873326, -0.4287332808931491, -0.13566959488006042, -0.08053136970348922, 0.15678836089292808, -0.09272929855563104, -0.17996612279421242, 0.39498272652937366, 0.046932341668122844, 0.159800153109245, 0.04651559276576985, 0.16783750938650752, 0.09951777748626357, 0.10207588683780548, -0.002619664703420962, 0.22430745645293168, 0.22392022965816846, 0.10074951487955072, -0.22369967661714846, -0.19647068214336677, 0.19682322584724585] |
1,803.01406 | On Andrews' partitions with parts separated by parity | In this paper, we present a generalization of one of the theorems in [G. E.
Andrews, Partitions with parts separated by parity, \textit{Annals of
Combinatorics} \textbf{23}(2019), 241 - 248], and give its bijective proof.
Further variations of related partition functions are studied resulting in a
number of interesting identities.
| math.NT | in this paper we present a generalization of one of the theorems in g e andrews partitions with parts separated by parity textitannals of combinatorics textbf232019 241 248 and give its bijective proof further variations of related partition functions are studied resulting in a number of interesting identities | [['in', 'this', 'paper', 'we', 'present', 'a', 'generalization', 'of', 'one', 'of', 'the', 'theorems', 'in', 'g', 'e', 'andrews', 'partitions', 'with', 'parts', 'separated', 'by', 'parity', 'textitannals', 'of', 'combinatorics', 'textbf232019', '241', '248', 'and', 'give', 'its', 'bijective', 'proof', 'further', 'variations', 'of', 'related', 'partition', 'functions', 'are', 'studied', 'resulting', 'in', 'a', 'number', 'of', 'interesting', 'identities']] | [-0.18181362381184715, 0.10168348986189812, -0.11564362837183896, 0.05632519619488765, -0.05687104574526134, -0.11910488803709007, 0.07491021198169935, 0.26932269219390076, -0.2663588271192882, -0.34297474157874996, 0.06798993752834023, -0.2739929958125171, -0.1810943013785974, 0.17082973314530175, -0.11602190535758501, -0.0352648032801327, 0.022188901253368542, 0.004983981139957905, -0.07229717020147844, -0.2788666289947603, 0.30631019940356846, -0.0558195544163818, 0.16699686286586296, 0.08190562713729299, 0.053292118448197194, 0.03595809101977426, -0.1104598043628199, 0.013511419539218363, -0.15857855692688053, 0.16614580818492433, 0.2911186617515657, 0.12353562561633147, 0.24270859136975007, -0.36702417898113315, -0.05168583494125177, 0.11620488012735934, 0.13685901365850284, -0.009381200105923674, -0.06164796101739225, -0.25811604734348215, 0.07852018272261256, -0.1411564825102687, -0.12623872009672873, -0.03254206052920579, 0.11149429511177637, 0.04293792613822481, -0.22148486429258532, 0.06273579550907016, 0.11695352869624596, 0.09485715771576075, 0.004511823267777167, -0.1909928227491353, 0.005047815867051806, 0.08900854368086743, 0.0321181811918707, 0.05632174850198562, 0.018558704709310248, -0.11169612251282872, -0.17391557955061612, 0.3289589308323744, 0.03567484616423431, -0.19846439940611954, 0.1397047004783931, -0.11608150031964254, -0.2270374658578278, 0.1033239882014206, 0.10927068652666133, 0.15693847476707204, -0.09851695044452081, 0.11530131519564589, -0.14483601009187227, 0.08715994324049224, 0.1743115710357771, 0.0590514371212086, 0.1870338557207066, 0.05767867570419027, 0.03542453595234648, 0.2726186536576437, 0.004978624536939289, -0.025059446611482163, -0.34649451101279777, -0.1312112579851047, -0.17838372500694316, 0.08456525725879423, -0.09766457265251792, -0.17641957699442687, 0.45597139175009466, 0.10453712840503811, 0.2176958696167592, 0.09469003110881084, 0.1994608008991117, 0.11187733466858449, 0.03343347853818989, 0.003288373351097107, 0.1340034651549776, 0.2484809077678896, 0.061243464002314875, -0.1154982956030163, -0.002579854062312971, 0.16872218974015635] |
1,803.01407 | Self-consistent modeling of anisotropic interfaces and missing
orientations: Derivation from phase-field crystal | Highly anisotropic interfaces play an important role in the development of
material microstructure. Using the diffusive atomistic phase-field crystal
(PFC) formalism, we determine the capability of the model to quantitatively
describe these interfaces. Specifically, we coarse grain the PFC model to
attain both its complex amplitude formulation and its corresponding phase-field
limit. Using this latter formulation, in one-dimensional calculations, we
determine the surface energy and the properties of the Wulff shape. We find
that the model can yield Wulff shapes with missing orientations, the transition
to missing orientations, and facet formation. We show that the corresponding
phase-field limit of the complex amplitude model yields a self-consistent
description of highly anisotropic surface properties that are a function of the
surface orientation with respect to the underlying crystal lattice. The
phase-field model is also capable of describing missing orientations on
equilibrium shapes of crystals and naturally includes a regularizing
contribution. We demonstrate, in two dimensions, how the resultant model can be
used to study growth of crystals with varying degrees of anisotropy in the
phase-field limit.
| cond-mat.mtrl-sci | highly anisotropic interfaces play an important role in the development of material microstructure using the diffusive atomistic phasefield crystal pfc formalism we determine the capability of the model to quantitatively describe these interfaces specifically we coarse grain the pfc model to attain both its complex amplitude formulation and its corresponding phasefield limit using this latter formulation in onedimensional calculations we determine the surface energy and the properties of the wulff shape we find that the model can yield wulff shapes with missing orientations the transition to missing orientations and facet formation we show that the corresponding phasefield limit of the complex amplitude model yields a selfconsistent description of highly anisotropic surface properties that are a function of the surface orientation with respect to the underlying crystal lattice the phasefield model is also capable of describing missing orientations on equilibrium shapes of crystals and naturally includes a regularizing contribution we demonstrate in two dimensions how the resultant model can be used to study growth of crystals with varying degrees of anisotropy in the phasefield limit | [['highly', 'anisotropic', 'interfaces', 'play', 'an', 'important', 'role', 'in', 'the', 'development', 'of', 'material', 'microstructure', 'using', 'the', 'diffusive', 'atomistic', 'phasefield', 'crystal', 'pfc', 'formalism', 'we', 'determine', 'the', 'capability', 'of', 'the', 'model', 'to', 'quantitatively', 'describe', 'these', 'interfaces', 'specifically', 'we', 'coarse', 'grain', 'the', 'pfc', 'model', 'to', 'attain', 'both', 'its', 'complex', 'amplitude', 'formulation', 'and', 'its', 'corresponding', 'phasefield', 'limit', 'using', 'this', 'latter', 'formulation', 'in', 'onedimensional', 'calculations', 'we', 'determine', 'the', 'surface', 'energy', 'and', 'the', 'properties', 'of', 'the', 'wulff', 'shape', 'we', 'find', 'that', 'the', 'model', 'can', 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1,803.01408 | Unobstructedness of Galois deformation rings associated to RACSDC
automorphic representations | Let $F$ be a CM field and let $(\overline{r}_{\pi,\lambda})_{\lambda}$ be the
compatible system of residual $\mathcal{G}_n$-valued representations of
$\operatorname{Gal}_{F}$ attached to a RACSDC automorphic representation $\pi$
of $\operatorname{GL}_n(\mathbb{A})$, as studied by Clozel, Harris and Taylor
and others. Under mild assumptions, we prove that the fixed-determinant
universal deformation rings attached to $\overline{r}_{\pi,\lambda}$ are
unobstructed for all places $\lambda$ in a subset of Dirichlet density $1$,
continuing the investigations of Mazur, Weston and Gamzon. During the proof, we
develop a general framework for proving unobstructedness (which could be useful
for other applications in future) and an $R=T$-theorem, relating the universal
crystalline deformation ring of $\overline{r}_{\pi,\lambda}$ and a certain
unitary fixed-type Hecke algebra.
| math.NT | let f be a cm field and let overliner_pilambda_lambda be the compatible system of residual mathcalg_nvalued representations of operatornamegal_f attached to a racsdc automorphic representation pi of operatornamegl_nmathbba as studied by clozel harris and taylor and others under mild assumptions we prove that the fixeddeterminant universal deformation rings attached to overliner_pilambda are unobstructed for all places lambda in a subset of dirichlet density 1 continuing the investigations of mazur weston and gamzon during the proof we develop a general framework for proving unobstructedness which could be useful for other applications in future and an rttheorem relating the universal crystalline deformation ring of overliner_pilambda and a certain unitary fixedtype hecke algebra | [['let', 'f', 'be', 'a', 'cm', 'field', 'and', 'let', 'overliner_pilambda_lambda', 'be', 'the', 'compatible', 'system', 'of', 'residual', 'mathcalg_nvalued', 'representations', 'of', 'operatornamegal_f', 'attached', 'to', 'a', 'racsdc', 'automorphic', 'representation', 'pi', 'of', 'operatornamegl_nmathbba', 'as', 'studied', 'by', 'clozel', 'harris', 'and', 'taylor', 'and', 'others', 'under', 'mild', 'assumptions', 'we', 'prove', 'that', 'the', 'fixeddeterminant', 'universal', 'deformation', 'rings', 'attached', 'to', 'overliner_pilambda', 'are', 'unobstructed', 'for', 'all', 'places', 'lambda', 'in', 'a', 'subset', 'of', 'dirichlet', 'density', '1', 'continuing', 'the', 'investigations', 'of', 'mazur', 'weston', 'and', 'gamzon', 'during', 'the', 'proof', 'we', 'develop', 'a', 'general', 'framework', 'for', 'proving', 'unobstructedness', 'which', 'could', 'be', 'useful', 'for', 'other', 'applications', 'in', 'future', 'and', 'an', 'rttheorem', 'relating', 'the', 'universal', 'crystalline', 'deformation', 'ring', 'of', 'overliner_pilambda', 'and', 'a', 'certain', 'unitary', 'fixedtype', 'hecke', 'algebra']] | [-0.16202439070030145, 0.07360126645991584, -0.1540460267311169, 0.020585463504598597, -0.08624948036734655, -0.1674131575285109, -0.015862157314926423, 0.291972119135387, -0.3055062863806432, -0.20316534066535155, 0.12575084217729968, -0.197150101584166, -0.13172598783811085, 0.24517066809678018, -0.12534638887478244, 0.008007091620579512, 0.042083438204817775, 0.08669991285958788, -0.08385021515388155, -0.24380383437800437, 0.3555351957170801, 0.027074211004256, 0.21906239121700777, 0.03671694032535089, 0.06599268777945051, 0.03825130703802587, 0.008217991927093026, -0.010777930987791883, -0.15832943755510379, 0.160504624605947, 0.2989736321579778, 0.05087870973011836, 0.2354048950705828, -0.4215395368560396, -0.1489524363605964, 0.16650086807820833, 0.12253394551255335, 0.00359848853214785, -0.004359506931969652, -0.30590156579126765, 0.15734571488186097, -0.17653895754395335, -0.17093139536434201, -0.11106658090997223, 0.09732949064992782, 0.03111118567528937, -0.31672666648948433, 0.002612951380962675, 0.11437913099470821, 0.12186662712125014, -0.0923340604029069, -0.12275086089996903, 0.004947545693604031, 0.06979975776483464, -0.003126483260080068, 0.0653524988500232, 0.12829059836774537, -0.12831578380295963, -0.07070454210983683, 0.3401886442807889, -0.06990970096155776, -0.16320980726412, 0.14908652067786515, -0.15618462196899333, -0.16895213428263864, 0.0781774219276026, 0.10394428546700363, 0.10859100571410223, -0.07140801292891154, 0.17916768229674698, -0.10538398742798076, 0.07074971261288444, 0.12886406511839743, -0.04312995746625926, 0.21333036144649742, 0.08065352175911569, 0.05520243914074716, 0.11663400437953327, 0.002295518388049771, -0.00862068195375755, -0.365082676868152, -0.20143022849177472, -0.12100683748040048, 0.1288608692614644, -0.06570368905868051, -0.13490356982807922, 0.38300750491143476, 0.08166064900543654, 0.2182732234906518, 0.08544494092024656, 0.16567274135998403, 0.10050462979842166, 0.08502038519340333, 0.057398776260364534, 0.12098492465612262, 0.21620901490825067, -0.004930637127748041, -0.13702261996822376, 0.007256815395778929, 0.11854710076192412] |
1,803.01409 | Holomorphic anomaly equations for the formal quintic | We define a formal Gromov-Witten theory of the quintic 3-fold via
localization on CP4. Our main result is a direct geometric proof of holomorphic
anomaly equations for the formal quintic in precisely the same form as
predicted by B-model physics for the true Gromov-Witten theory of the quintic
3-fold. The results suggest that the formal quintic and the true quintic
theories should be related by transformations which respect the holomorphic
anomaly equations. Such a relationship has been recently found by Q. Chen, S.
Guo, F. Janda, and Y. Ruan via the geometry of new moduli spaces.
| math.AG | we define a formal gromovwitten theory of the quintic 3fold via localization on cp4 our main result is a direct geometric proof of holomorphic anomaly equations for the formal quintic in precisely the same form as predicted by bmodel physics for the true gromovwitten theory of the quintic 3fold the results suggest that the formal quintic and the true quintic theories should be related by transformations which respect the holomorphic anomaly equations such a relationship has been recently found by q chen s guo f janda and y ruan via the geometry of new moduli spaces | [['we', 'define', 'a', 'formal', 'gromovwitten', 'theory', 'of', 'the', 'quintic', '3fold', 'via', 'localization', 'on', 'cp4', 'our', 'main', 'result', 'is', 'a', 'direct', 'geometric', 'proof', 'of', 'holomorphic', 'anomaly', 'equations', 'for', 'the', 'formal', 'quintic', 'in', 'precisely', 'the', 'same', 'form', 'as', 'predicted', 'by', 'bmodel', 'physics', 'for', 'the', 'true', 'gromovwitten', 'theory', 'of', 'the', 'quintic', '3fold', 'the', 'results', 'suggest', 'that', 'the', 'formal', 'quintic', 'and', 'the', 'true', 'quintic', 'theories', 'should', 'be', 'related', 'by', 'transformations', 'which', 'respect', 'the', 'holomorphic', 'anomaly', 'equations', 'such', 'a', 'relationship', 'has', 'been', 'recently', 'found', 'by', 'q', 'chen', 's', 'guo', 'f', 'janda', 'and', 'y', 'ruan', 'via', 'the', 'geometry', 'of', 'new', 'moduli', 'spaces']] | [-0.17701053631026298, -0.007831307533100093, -0.0992869878912946, 0.12523667239414257, -0.10478581986778106, -0.15253306846231376, 0.0035621102979348507, 0.21669565994913378, -0.29337463529858115, -0.25474742136248096, 0.06909974424706888, -0.24424785557979098, -0.2592173549249613, 0.19946590758142216, -0.12978798123367596, 0.06556504569016397, -0.030368119737734862, 0.015651148724524926, -0.12913513402600074, -0.34851007942294626, 0.4104302210713892, -0.039201583596877754, 0.22466655897248225, 0.10598877141334621, 0.08759535816473847, 0.018483053424764268, -0.017205388357979245, -0.03798810934919553, -0.1458035014103037, 0.14302004012157946, 0.30542664423895377, 0.053846108487050515, 0.16105002437446578, -0.3888204149649634, -0.21313862001989037, 0.1073328334581068, 0.11068400421451467, 0.07619075879362451, -0.03469717091866187, -0.31249682611087337, 0.1022943730707387, -0.126778175792424, -0.20180305766310389, -0.12152581999544054, 0.05603661983332131, 0.04329188327634862, -0.20095473589996496, 0.039247703600267414, 0.08995080102855961, 0.10598579529323615, -0.0375989652966382, -0.0692954613235391, -0.1504643901292487, -0.01333331915763362, 0.041979064779297914, 0.1470360922103282, 0.03318203965318389, -0.12667954138305504, -0.13368209237038778, 0.36516312839618575, -0.09598311574275915, -0.21620899271025942, 0.0959355044227171, -0.11857944139531658, -0.1720376519151614, 0.12611652600753587, 0.060440630855737254, 0.16726616263622418, -0.05512070867310589, 0.21753942561796671, -0.07917117528995732, 0.09573307008637737, 0.10381400501015985, -0.0631780880066799, 0.190828804380241, 0.0693606063578045, 0.025688928784802556, 0.07880985826219937, 0.0030195338040357456, -0.07750374811863973, -0.388071089827766, -0.2010514528277175, -0.10617569489598584, 0.14250828801838603, -0.1175567927245235, -0.09993412548404497, 0.39434165701338014, 0.028632570271535467, 0.18483282109567276, 0.10057013815912796, 0.21800682983060446, 0.1261843974595346, 0.04244002700337054, -0.03738262701760201, 0.21866156476608012, 0.22364044760615798, 0.032457007682144955, -0.16398749429693757, 0.018552876591760043, 0.23867578599310946] |
1,803.0141 | Translating solitons in Riemannian products | In this paper we study solitons invariant with respect to the flow generated
by a complete Killing vector field in a ambient Riemannian manifold. A special
case occurs when the ambient manifold is the Riemannian product $(\mathbb{R}
\times P, {\rm d}t^2+g_0)$ and the Killing field is $X=\partial_t$. Similarly
to what happens in the Euclidean setting, we call them translating solitons. We
see that a translating soliton in $\mathbb{R} \times P$ can be seen as a
minimal submanifold for a weighted volume functional. Moreover we show that
this kind of solitons appear in a natural way in the context of a monotonicity
formula for the mean curvature flow in $\mathbb{R} \times P$. When $g_0$ is
rotationally invariant and its sectional curvature is non-positive, we are able
to characterize all the rotationally invariant translating solitons.
Furthermore, we use these families of new examples as barriers to deduce
several non-existence results.
| math.DG | in this paper we study solitons invariant with respect to the flow generated by a complete killing vector field in a ambient riemannian manifold a special case occurs when the ambient manifold is the riemannian product mathbbr times p rm dt2g_0 and the killing field is xpartial_t similarly to what happens in the euclidean setting we call them translating solitons we see that a translating soliton in mathbbr times p can be seen as a minimal submanifold for a weighted volume functional moreover we show that this kind of solitons appear in a natural way in the context of a monotonicity formula for the mean curvature flow in mathbbr times p when g_0 is rotationally invariant and its sectional curvature is nonpositive we are able to characterize all the rotationally invariant translating solitons furthermore we use these families of new examples as barriers to deduce several nonexistence results | [['in', 'this', 'paper', 'we', 'study', 'solitons', 'invariant', 'with', 'respect', 'to', 'the', 'flow', 'generated', 'by', 'a', 'complete', 'killing', 'vector', 'field', 'in', 'a', 'ambient', 'riemannian', 'manifold', 'a', 'special', 'case', 'occurs', 'when', 'the', 'ambient', 'manifold', 'is', 'the', 'riemannian', 'product', 'mathbbr', 'times', 'p', 'rm', 'dt2g_0', 'and', 'the', 'killing', 'field', 'is', 'xpartial_t', 'similarly', 'to', 'what', 'happens', 'in', 'the', 'euclidean', 'setting', 'we', 'call', 'them', 'translating', 'solitons', 'we', 'see', 'that', 'a', 'translating', 'soliton', 'in', 'mathbbr', 'times', 'p', 'can', 'be', 'seen', 'as', 'a', 'minimal', 'submanifold', 'for', 'a', 'weighted', 'volume', 'functional', 'moreover', 'we', 'show', 'that', 'this', 'kind', 'of', 'solitons', 'appear', 'in', 'a', 'natural', 'way', 'in', 'the', 'context', 'of', 'a', 'monotonicity', 'formula', 'for', 'the', 'mean', 'curvature', 'flow', 'in', 'mathbbr', 'times', 'p', 'when', 'g_0', 'is', 'rotationally', 'invariant', 'and', 'its', 'sectional', 'curvature', 'is', 'nonpositive', 'we', 'are', 'able', 'to', 'characterize', 'all', 'the', 'rotationally', 'invariant', 'translating', 'solitons', 'furthermore', 'we', 'use', 'these', 'families', 'of', 'new', 'examples', 'as', 'barriers', 'to', 'deduce', 'several', 'nonexistence', 'results']] | [-0.19576767913690984, 0.1204491918619518, -0.08550183492878528, 0.10951277016732229, -0.07988236301374456, -0.11990555636393391, -0.05389322659992676, 0.419716315308892, -0.2507256769343145, -0.19697968775210328, 0.11465463205599481, -0.27240720950226516, -0.16163598941894222, 0.16203360425384894, -0.11432323746753167, 0.020813880251857694, 0.04953508231268992, 0.13330107232019917, -0.1011422519916541, -0.23564561015658386, 0.412404865919523, -0.07112381624198225, 0.22423407875722248, 0.06315047203878911, 0.0959637232080153, -0.04530735936475127, 0.04731840825972964, 0.04481422318439063, -0.226378026071235, 0.10380471871419465, 0.221692852248527, 0.08235552406244695, 0.23064906783051126, -0.387371521902411, -0.21553278865120437, 0.2069661175857668, 0.15172787413099934, 0.07683592281393604, -0.03545011904139282, -0.3056393241468332, 0.12300697897165401, -0.08665667533434367, -0.16913262030033216, -0.09785013360430626, 0.05152123942747967, -0.011025246680867283, -0.23007686602666158, 0.05154424476475544, 0.13302799191785186, 0.05066923705912004, -0.09524693829884548, -0.05115334667849086, -0.04943583657237867, 0.05755212088952747, 0.08003053942548545, 0.09284691290438736, 0.11862142612098729, -0.0708357590403765, -0.08507000135053715, 0.3873990257844737, -0.15974442575331013, -0.28476939381942257, 0.11105623645771755, -0.13735941947080604, -0.1042085238859976, 0.11057577639808623, 0.17835559852162938, 0.18426401038615875, -0.0850088960813655, 0.11956518017670956, -0.08629315620773051, 0.08559358632192016, 0.12848529864536368, -0.031313610409884014, 0.13408398004376318, 0.09199814528724408, 0.15304766351050914, 0.14919278583503712, -0.030720149452538127, -0.09267082957436062, -0.36521162124420836, -0.2305099717676257, -0.13687791867454357, 0.16066717898651753, -0.09553603213005349, -0.12108616164745126, 0.36760555867309846, 0.03169078301408724, 0.23073849642381378, 0.09783648719934568, 0.23251194788672488, 0.09056636496695805, 0.04614219598612455, 0.10873337708132928, 0.16575417529204733, 0.1750298114501463, 0.0767106562725281, -0.11153841628980096, -0.06569634051594807, 0.06717500332360195] |
1,803.01411 | Topological Sachdev-Ye-Kitaev Model | In this letter we construct a large-N exactly solvable model to study the
interplay between interaction and topology, by connecting Sacheve-Ye-Kitaev
(SYK) model with constant hopping. The hopping forms a band structure that can
exhibit both topological trivial and nontrivial phases. Starting from a
topologically trivial insulator with zero Hall conductance, we show that
interaction can drive a phase transition to topological nontrivial insulator
with quantized non-zero Hall conductance, and a single gapless Dirac fermion
emerges when the interaction is fine tuned to the critical point. The finite
temperature effect is also considered and we show that the topological phase
with stronger interaction is less stable against temperature. Our model
provides a concrete example to illustrate interacting topological phases and
phase transition, and can shed light on similar problems in physical systems.
| cond-mat.str-el cond-mat.mes-hall cond-mat.quant-gas | in this letter we construct a largen exactly solvable model to study the interplay between interaction and topology by connecting sacheveyekitaev syk model with constant hopping the hopping forms a band structure that can exhibit both topological trivial and nontrivial phases starting from a topologically trivial insulator with zero hall conductance we show that interaction can drive a phase transition to topological nontrivial insulator with quantized nonzero hall conductance and a single gapless dirac fermion emerges when the interaction is fine tuned to the critical point the finite temperature effect is also considered and we show that the topological phase with stronger interaction is less stable against temperature our model provides a concrete example to illustrate interacting topological phases and phase transition and can shed light on similar problems in physical systems | [['in', 'this', 'letter', 'we', 'construct', 'a', 'largen', 'exactly', 'solvable', 'model', 'to', 'study', 'the', 'interplay', 'between', 'interaction', 'and', 'topology', 'by', 'connecting', 'sacheveyekitaev', 'syk', 'model', 'with', 'constant', 'hopping', 'the', 'hopping', 'forms', 'a', 'band', 'structure', 'that', 'can', 'exhibit', 'both', 'topological', 'trivial', 'and', 'nontrivial', 'phases', 'starting', 'from', 'a', 'topologically', 'trivial', 'insulator', 'with', 'zero', 'hall', 'conductance', 'we', 'show', 'that', 'interaction', 'can', 'drive', 'a', 'phase', 'transition', 'to', 'topological', 'nontrivial', 'insulator', 'with', 'quantized', 'nonzero', 'hall', 'conductance', 'and', 'a', 'single', 'gapless', 'dirac', 'fermion', 'emerges', 'when', 'the', 'interaction', 'is', 'fine', 'tuned', 'to', 'the', 'critical', 'point', 'the', 'finite', 'temperature', 'effect', 'is', 'also', 'considered', 'and', 'we', 'show', 'that', 'the', 'topological', 'phase', 'with', 'stronger', 'interaction', 'is', 'less', 'stable', 'against', 'temperature', 'our', 'model', 'provides', 'a', 'concrete', 'example', 'to', 'illustrate', 'interacting', 'topological', 'phases', 'and', 'phase', 'transition', 'and', 'can', 'shed', 'light', 'on', 'similar', 'problems', 'in', 'physical', 'systems']] | [-0.22599702485915246, 0.26953616571961014, -0.09319321520427484, 0.0405325049779712, -0.07773550690101985, -0.2563536461186773, 0.0880539252721342, 0.3645416775874737, -0.2797681339767598, -0.26781072987968685, 0.003161443438281426, -0.3156689027331428, -0.23730107805983142, 0.13237899524970193, 0.028421336095353574, -0.0028310253903383515, -0.027417621056314644, 0.0018413436442670475, -0.13846190460026264, -0.19021833822920292, 0.32848114065314066, -0.0450410595179699, 0.28107629972332304, 0.10146476915959297, 0.024866904338238804, -0.04860984179091761, 0.1369177782694802, 0.06083730040544658, -0.1322777410781963, -0.00611133081483022, 0.23025155893370566, -0.11933505652251987, 0.13844784774518934, -0.41247890910972623, -0.23244530836632118, 0.06841917622137729, 0.12906434602736858, 0.1398178950264936, -0.09188522238245247, -0.3176638299300698, 0.06010465042750913, -0.1790357303755884, -0.11346392295472608, -0.12352236337561644, -0.0030043382012775836, -0.09521101470787846, -0.23866457114118783, 0.06604808186983356, 0.03176140345682795, 0.04848321891115522, -0.05673558044936935, -0.04743158122353995, -0.11938690939271211, 0.10782361157769017, 0.01908688747967444, 0.032943740151182725, 0.09130379703706344, -0.13592859115611533, -0.1409428774962159, 0.39045335132742426, -0.09046954071888601, -0.14149610320006617, 0.2314781081571265, -0.1570607406722172, -0.08019845484123203, 0.13982128566273183, 0.0992633723227293, 0.052943580325351645, -0.05154986867762459, 0.12095219736211428, -0.0249767356431325, 0.17820352977181728, -0.034937927350117505, 0.042683781881795356, 0.27938346819994786, 0.1711716300048972, 0.07636662607813496, 0.20539937107219497, -0.044396814561399225, -0.14290383111379812, -0.283633116355436, -0.15394365408756408, -0.22904583857970612, 0.09855860108260833, -0.07845377092687804, -0.22324362813800802, 0.4524615198260045, 0.19518764617227247, 0.22114213808943545, -0.0021903092034502337, 0.2535100994962232, 0.15278446012201455, 0.010996333947263032, 0.03836278047924506, 0.22443106815304237, 0.13819433090220143, 0.06046184304504449, -0.26211027554876193, 0.014210976422088975, 0.07866581052342672] |
1,803.01412 | A real-time decision support system for bridge management based on the
rules generalized by CART decision tree and SMO algorithms | Under dynamic conditions on bridges, we need a real-time management. To this
end, this paper presents a rule-based decision support system in which the
necessary rules are extracted from simulation results made by Aimsun traffic
micro-simulation software. Then, these rules are generalized by the aid of
fuzzy rule generation algorithms. Then, they are trained by a set of supervised
and the unsupervised learning algorithms to get an ability to make decision in
real cases. As a pilot case study, Nasr Bridge in Tehran is simulated in Aimsun
and WEKA data mining software is used to execute the learning algorithms. Based
on this experiment, the accuracy of the supervised algorithms to generalize the
rules is greater than 80%. In addition, CART decision tree and sequential
minimal optimization (SMO) provides 100% accuracy for normal data and these
algorithms are so reliable for crisis management on bridge. This means that, it
is possible to use such machine learning methods to manage bridges in the
real-time conditions.
| cs.AI | under dynamic conditions on bridges we need a realtime management to this end this paper presents a rulebased decision support system in which the necessary rules are extracted from simulation results made by aimsun traffic microsimulation software then these rules are generalized by the aid of fuzzy rule generation algorithms then they are trained by a set of supervised and the unsupervised learning algorithms to get an ability to make decision in real cases as a pilot case study nasr bridge in tehran is simulated in aimsun and weka data mining software is used to execute the learning algorithms based on this experiment the accuracy of the supervised algorithms to generalize the rules is greater than 80 in addition cart decision tree and sequential minimal optimization smo provides 100 accuracy for normal data and these algorithms are so reliable for crisis management on bridge this means that it is possible to use such machine learning methods to manage bridges in the realtime conditions | [['under', 'dynamic', 'conditions', 'on', 'bridges', 'we', 'need', 'a', 'realtime', 'management', 'to', 'this', 'end', 'this', 'paper', 'presents', 'a', 'rulebased', 'decision', 'support', 'system', 'in', 'which', 'the', 'necessary', 'rules', 'are', 'extracted', 'from', 'simulation', 'results', 'made', 'by', 'aimsun', 'traffic', 'microsimulation', 'software', 'then', 'these', 'rules', 'are', 'generalized', 'by', 'the', 'aid', 'of', 'fuzzy', 'rule', 'generation', 'algorithms', 'then', 'they', 'are', 'trained', 'by', 'a', 'set', 'of', 'supervised', 'and', 'the', 'unsupervised', 'learning', 'algorithms', 'to', 'get', 'an', 'ability', 'to', 'make', 'decision', 'in', 'real', 'cases', 'as', 'a', 'pilot', 'case', 'study', 'nasr', 'bridge', 'in', 'tehran', 'is', 'simulated', 'in', 'aimsun', 'and', 'weka', 'data', 'mining', 'software', 'is', 'used', 'to', 'execute', 'the', 'learning', 'algorithms', 'based', 'on', 'this', 'experiment', 'the', 'accuracy', 'of', 'the', 'supervised', 'algorithms', 'to', 'generalize', 'the', 'rules', 'is', 'greater', 'than', '80', 'in', 'addition', 'cart', 'decision', 'tree', 'and', 'sequential', 'minimal', 'optimization', 'smo', 'provides', '100', 'accuracy', 'for', 'normal', 'data', 'and', 'these', 'algorithms', 'are', 'so', 'reliable', 'for', 'crisis', 'management', 'on', 'bridge', 'this', 'means', 'that', 'it', 'is', 'possible', 'to', 'use', 'such', 'machine', 'learning', 'methods', 'to', 'manage', 'bridges', 'in', 'the', 'realtime', 'conditions']] | [-0.045071331855013934, 0.030844161799123963, -0.09900974838257384, 0.09966776376030197, -0.14240366010783823, -0.16128272507225444, 0.11469725060828052, 0.4498826104353405, -0.2510678027128012, -0.3176972849831625, 0.14379063723901675, -0.25577029708110116, -0.16427526796990835, 0.22075151230717088, -0.12713604416709645, 0.11038488149428682, 0.1174467339586078, 0.04296674570668649, -0.01706952731192192, -0.2866072750813185, 0.2752374998390949, 0.0471162295927425, 0.3360431373827845, 0.01957764485643811, 0.07823983264481363, 0.005750633866445481, -0.05365508552812086, -0.006689527250485415, -0.09404792038294768, 0.14631196283992448, 0.3613884612557941, 0.22530786600535266, 0.32876455767845814, -0.41676392535424783, -0.15137974610780738, 0.10964275693429486, 0.11637434359936992, 0.0748155427321026, 0.00744578572621489, -0.2877551739266931, 0.11960984984315658, -0.16706579403403254, -0.05956341492217834, -0.14658514617662305, -0.053579351834758565, 0.004835176853173087, -0.295197236145978, -0.008694397739814652, 0.0346714478054661, 0.07664457740022178, -0.021261998509382544, -0.09370360399119304, 0.05070805732600757, 0.12942310101266927, 0.01502572960631659, 0.028259705499305954, 0.14244702005308219, -0.128199781452597, -0.20209300044946876, 0.36167252771099284, -0.013270536573775872, -0.20471760884507278, 0.213036541886302, 0.020321313908860727, -0.17195121815108175, 0.10141249878069192, 0.23234660192707016, 0.09198024215182415, -0.21919233498786309, 0.02078750042496192, -0.010076779395090473, 0.14710349307332668, 0.03931041942920787, -0.08265976936047885, 0.15333072195633776, 0.2533685746859828, 0.06362947205330126, 0.14533184785995792, -0.059051795951176454, -0.10968330912499123, -0.224500821134864, -0.12892269891932423, -0.1439475904653089, -0.028706654083509385, -0.07066834438770747, -0.14354924498085916, 0.3292872057656295, 0.2269823758325831, 0.14797049776370283, 0.09484468908206291, 0.36054049705817975, 0.049689781033677514, 0.09767137121043505, 0.11477644063326661, 0.18106270508206468, 0.041831563573981996, 0.14886560969831752, -0.16893119931055312, 0.08906747025231962, 0.025084410817290948] |
1,803.01413 | Egocentric Basketball Motion Planning from a Single First-Person Image | We present a model that uses a single first-person image to generate an
egocentric basketball motion sequence in the form of a 12D camera configuration
trajectory, which encodes a player's 3D location and 3D head orientation
throughout the sequence. To do this, we first introduce a future convolutional
neural network (CNN) that predicts an initial sequence of 12D camera
configurations, aiming to capture how real players move during a one-on-one
basketball game. We also introduce a goal verifier network, which is trained to
verify that a given camera configuration is consistent with the final goals of
real one-on-one basketball players. Next, we propose an inverse synthesis
procedure to synthesize a refined sequence of 12D camera configurations that
(1) sufficiently matches the initial configurations predicted by the future
CNN, while (2) maximizing the output of the goal verifier network. Finally, by
following the trajectory resulting from the refined camera configuration
sequence, we obtain the complete 12D motion sequence.
Our model generates realistic basketball motion sequences that capture the
goals of real players, outperforming standard deep learning approaches such as
recurrent neural networks (RNNs), long short-term memory networks (LSTMs), and
generative adversarial networks (GANs).
| cs.CV | we present a model that uses a single firstperson image to generate an egocentric basketball motion sequence in the form of a 12d camera configuration trajectory which encodes a players 3d location and 3d head orientation throughout the sequence to do this we first introduce a future convolutional neural network cnn that predicts an initial sequence of 12d camera configurations aiming to capture how real players move during a oneonone basketball game we also introduce a goal verifier network which is trained to verify that a given camera configuration is consistent with the final goals of real oneonone basketball players next we propose an inverse synthesis procedure to synthesize a refined sequence of 12d camera configurations that 1 sufficiently matches the initial configurations predicted by the future cnn while 2 maximizing the output of the goal verifier network finally by following the trajectory resulting from the refined camera configuration sequence we obtain the complete 12d motion sequence our model generates realistic basketball motion sequences that capture the goals of real players outperforming standard deep learning approaches such as recurrent neural networks rnns long shortterm memory networks lstms and generative adversarial networks gans | [['we', 'present', 'a', 'model', 'that', 'uses', 'a', 'single', 'firstperson', 'image', 'to', 'generate', 'an', 'egocentric', 'basketball', 'motion', 'sequence', 'in', 'the', 'form', 'of', 'a', '12d', 'camera', 'configuration', 'trajectory', 'which', 'encodes', 'a', 'players', '3d', 'location', 'and', '3d', 'head', 'orientation', 'throughout', 'the', 'sequence', 'to', 'do', 'this', 'we', 'first', 'introduce', 'a', 'future', 'convolutional', 'neural', 'network', 'cnn', 'that', 'predicts', 'an', 'initial', 'sequence', 'of', '12d', 'camera', 'configurations', 'aiming', 'to', 'capture', 'how', 'real', 'players', 'move', 'during', 'a', 'oneonone', 'basketball', 'game', 'we', 'also', 'introduce', 'a', 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'recurrent', 'neural', 'networks', 'rnns', 'long', 'shortterm', 'memory', 'networks', 'lstms', 'and', 'generative', 'adversarial', 'networks', 'gans']] | [-0.08457786312465032, 0.028804913879487987, -0.09927718334680928, 0.08340067083008762, -0.09251697062669943, -0.20255675053825448, 0.009781683937035268, 0.48016348041710444, -0.27295759690605337, -0.31835382237234927, 0.015129393419556436, -0.24215874483343214, -0.21203838848305168, 0.11191607645317465, -0.1726830125238242, 0.0746724461047658, 0.1949261477013048, 0.05860028864481137, 0.02107266570844028, -0.27040925320943643, 0.30908055812809226, 0.008895450571041389, 0.26843847962057527, -0.10570519673152982, 0.1805797140332288, 0.018689692418168608, 0.02144220346720734, -0.016160091971566242, -0.08302759029603142, 0.12952675228007138, 0.2424341223522788, 0.21350211315044967, 0.3297422399336938, -0.4425320511654718, -0.18448012001075162, 0.1095907557476797, 0.11612366314875544, 0.12135868646146264, -0.0038433403521291134, 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1,803.01414 | Product formulas for weight two newforms | For a weight two newform $f$ attached to an elliptic curve $E$ defined over
rational numbers we write $f=q\prod_{n=1}^\infty (1-q^n)^{g_n}, \ g_n\in\Z$ and
we observe that for some special elliptic curves $g_n$ is an increasing
sequence of positive integers.
| math.NT math.CV | for a weight two newform f attached to an elliptic curve e defined over rational numbers we write fqprod_n1infty 1qng_n g_ninz and we observe that for some special elliptic curves g_n is an increasing sequence of positive integers | [['for', 'a', 'weight', 'two', 'newform', 'f', 'attached', 'to', 'an', 'elliptic', 'curve', 'e', 'defined', 'over', 'rational', 'numbers', 'we', 'write', 'fqprod_n1infty', '1qng_n', 'g_ninz', 'and', 'we', 'observe', 'that', 'for', 'some', 'special', 'elliptic', 'curves', 'g_n', 'is', 'an', 'increasing', 'sequence', 'of', 'positive', 'integers']] | [-0.30231245258556944, 0.09656788845895789, -0.12022785229076233, 0.02166200409576829, -0.10419774470584733, -0.2089415362636958, -0.03848294300758945, 0.3531504115455651, -0.37002989649772644, -0.207604953540223, -0.002588965238205024, -0.3418979712961508, -0.11631893946656159, 0.31266625661935127, -0.12786508625639337, 0.027941097681676703, 0.027664216035710915, 0.13884646728900926, -0.06258941842908305, -0.33709172553249767, 0.3774323617773397, -0.09971009950552667, 0.1085736494511366, 0.01932971283261265, 0.09047012451503958, 0.04546777301334909, 0.058511563496930256, -0.0750758174274649, -0.18631379885836005, 0.1082749909854361, 0.3302630745938846, 0.03554708957672119, 0.25686990565487317, -0.3543820993708713, -0.10063120805259262, 0.29005605136709556, 0.14482210161430495, -0.08592321228768145, -0.033396770512419086, -0.11285281404852868, 0.13314015628503903, -0.15419363646568465, -0.2016316707911236, -0.06985791509172747, 0.14806783506646753, 0.09286738458488669, -0.33522864367280686, -0.08736921173653432, 0.07187664188178522, 0.20487520111990826, -0.03093218889885715, -0.18931393721806153, -0.0373485675613795, 0.06477285772562028, 0.008754707174375653, 0.10904765337639089, 0.006756721942552498, -0.12109659198738103, -0.06391567768795149, 0.2805861375693764, -0.12457334393901484, -0.22187552079558373, 0.019775941222906112, -0.14906571009861572, -0.1469162853700774, 0.16156044223545385, 0.1327572161464819, 0.17051053068467548, 0.01925242817295449, 0.11232136115265479, -0.0931318559609021, 0.13323890842896488, 0.1628654882045729, -0.09840206964872777, 0.17740438460106298, -0.04261623828538826, 0.0659892874104636, 0.14079107389718826, 0.014045067397611482, -0.010560754939381566, -0.3473835444876126, -0.19558125037167753, -0.15467534586787224, 0.21003290779356446, -0.09030476104692622, -0.19486347053732192, 0.39613584615290165, 0.00014511442610195706, 0.25805227188393476, 0.15820542228009019, 0.1348877170256206, 0.19594730420836382, 0.010157619203839983, 0.04371495921430843, -0.006420761302745502, 0.14610567068947214, -0.03433309670072049, -0.16630324153229595, -0.05339245727934342, 0.12487608843616077] |
1,803.01415 | Invariant, anti-invariant and slant submanifolds of a metallic Riemannian manifold | Properties of invariant, anti-invariant and slant isometrically immersed submanifolds of metallic Riemannian manifolds are given with a special view towards the induced $\Sigma$-structure. Examples of such metallic manifolds are also given. | math.DG | properties of invariant antiinvariant and slant isometrically immersed submanifolds of metallic riemannian manifolds are given with a special view towards the induced sigmastructure examples of such metallic manifolds are also given | [['properties', 'of', 'invariant', 'antiinvariant', 'and', 'slant', 'isometrically', 'immersed', 'submanifolds', 'of', 'metallic', 'riemannian', 'manifolds', 'are', 'given', 'with', 'a', 'special', 'view', 'towards', 'the', 'induced', 'sigmastructure', 'examples', 'of', 'such', 'metallic', 'manifolds', 'are', 'also', 'given']] | [-0.22064265366643668, 0.14130407944321632, 0.010220116873582204, 0.0899589772336185, -0.11933521589574715, -0.20029636470911402, -0.14227127429718772, 0.4711290488640467, -0.22281869687139988, -0.21641961994270484, 0.10630785391355554, -0.38689895496548465, -0.22071477688538532, 0.1813904481784751, -0.20992809668902435, 0.04366660181597884, 0.10538123180158436, 0.05447796777977298, -0.21040594189738235, -0.24341977934042613, 0.5131662413477898, -0.03039462628463904, 0.1795895435536901, 0.11192676140926779, 0.1430048513536652, -0.06745969210751354, 0.08361429890307287, 0.09288350212736987, -0.2263671721952657, 0.09586705093582472, 0.27785407228705783, -0.0334596823900938, 0.11022176903982957, -0.37485181403656803, -0.1813396737910807, 0.180155259432892, 0.09737845569228133, -0.03871362420419852, -0.08263483286524813, -0.42814004719257354, 0.0100005976545314, 0.02043660239626964, -0.2425039286414782, -0.1527314310427755, -0.02144537940621376, -0.00024573101351658505, -0.14218100688109794, -0.015425491155474447, 0.20341342153648537, 0.16157291885465383, -0.11229547914117574, -0.11411371122424802, -0.14058543536812068, 0.10303566668493053, -0.005787799631555875, 0.060126315848901865, 0.20798743789394697, 0.02752920047690471, -0.04346047503252824, 0.39627180993556976, -0.051781210613747436, -0.36107311186691127, 0.0782423888022701, -0.08632989196727674, -0.14259960564474264, 0.1534771699186725, 0.16355998077585052, 0.20621220152825118, -0.11603233041241764, 0.11571498848303842, -0.05617870030303796, -0.09117802046239376, 0.10175655176863074, 0.06564755141735076, 0.19899919430414836, 0.1532249073497951, 0.13889058977365493, 0.19650669309000174, -0.007317854805539052, -0.04444562556842963, -0.3715023192266623, -0.26628565732389686, -0.11387067261772851, 0.21614598085482914, -0.1359050494148202, -0.2727781026313702, 0.3527009092271328, -0.11768518999839822, 0.17760220860751966, 0.07071020752191544, 0.22340913203855356, -0.09409791436046362, -0.017907291588683923, 0.11494378323356311, 0.20748821894327799, 0.2762026439110438, -0.03163886228576303, 0.005425353969136874, -0.09843253131645421, 0.11437426383296649] |
1,803.01416 | Machine learning determination of atomic dynamics at grain boundaries | In polycrystalline materials, grain boundaries are sites of enhanced atomic
motion, but the complexity of the atomic structures within a grain boundary
network makes it difficult to link the structure and atomic dynamics. Here we
use a machine learning technique to establish a connection between local
structure and dynamics of these materials. Following previous work on bulk
glassy materials, we define a purely structural quantity, softness, that
captures the propensity of an atom to rearrange. This approach correctly
identifies crystalline regions, stacking faults, and twin boundaries as having
low likelihood of atomic rearrangements, while finding a large variability
within high-energy grain boundaries. As has been found in glasses [9,19,26],
the probability that atoms of a given softness will rearrange is nearly
Arrhenius. This indicates a well-defined energy barrier as well as a
well-defined prefactor for the Arrhenius form for atoms of a given softness.
The decrease in the prefactor for low-softness atoms indicates that variations
in entropy exhibit a dominant influence on the atomic dynamics in grain
boundaries.
| cond-mat.mtrl-sci | in polycrystalline materials grain boundaries are sites of enhanced atomic motion but the complexity of the atomic structures within a grain boundary network makes it difficult to link the structure and atomic dynamics here we use a machine learning technique to establish a connection between local structure and dynamics of these materials following previous work on bulk glassy materials we define a purely structural quantity softness that captures the propensity of an atom to rearrange this approach correctly identifies crystalline regions stacking faults and twin boundaries as having low likelihood of atomic rearrangements while finding a large variability within highenergy grain boundaries as has been found in glasses 91926 the probability that atoms of a given softness will rearrange is nearly arrhenius this indicates a welldefined energy barrier as well as a welldefined prefactor for the arrhenius form for atoms of a given softness the decrease in the prefactor for lowsoftness atoms indicates that variations in entropy exhibit a dominant influence on the atomic dynamics in grain boundaries | [['in', 'polycrystalline', 'materials', 'grain', 'boundaries', 'are', 'sites', 'of', 'enhanced', 'atomic', 'motion', 'but', 'the', 'complexity', 'of', 'the', 'atomic', 'structures', 'within', 'a', 'grain', 'boundary', 'network', 'makes', 'it', 'difficult', 'to', 'link', 'the', 'structure', 'and', 'atomic', 'dynamics', 'here', 'we', 'use', 'a', 'machine', 'learning', 'technique', 'to', 'establish', 'a', 'connection', 'between', 'local', 'structure', 'and', 'dynamics', 'of', 'these', 'materials', 'following', 'previous', 'work', 'on', 'bulk', 'glassy', 'materials', 'we', 'define', 'a', 'purely', 'structural', 'quantity', 'softness', 'that', 'captures', 'the', 'propensity', 'of', 'an', 'atom', 'to', 'rearrange', 'this', 'approach', 'correctly', 'identifies', 'crystalline', 'regions', 'stacking', 'faults', 'and', 'twin', 'boundaries', 'as', 'having', 'low', 'likelihood', 'of', 'atomic', 'rearrangements', 'while', 'finding', 'a', 'large', 'variability', 'within', 'highenergy', 'grain', 'boundaries', 'as', 'has', 'been', 'found', 'in', 'glasses', '91926', 'the', 'probability', 'that', 'atoms', 'of', 'a', 'given', 'softness', 'will', 'rearrange', 'is', 'nearly', 'arrhenius', 'this', 'indicates', 'a', 'welldefined', 'energy', 'barrier', 'as', 'well', 'as', 'a', 'welldefined', 'prefactor', 'for', 'the', 'arrhenius', 'form', 'for', 'atoms', 'of', 'a', 'given', 'softness', 'the', 'decrease', 'in', 'the', 'prefactor', 'for', 'lowsoftness', 'atoms', 'indicates', 'that', 'variations', 'in', 'entropy', 'exhibit', 'a', 'dominant', 'influence', 'on', 'the', 'atomic', 'dynamics', 'in', 'grain', 'boundaries']] | [-0.10281582459009916, 0.18978275672449316, -0.10595578233806227, 0.055103087049775096, -0.02640847021485205, -0.11754121065898213, 0.10111314302566879, 0.413297466889113, -0.29001214834554734, -0.3123162631335819, -0.006021895039475294, -0.26782719242737857, -0.14655228525269107, 0.1180425899432314, -0.033348628005408824, 0.04342248820571486, 0.012844545614743928, -0.016702078201969763, -0.05031801960821414, -0.1900408444507884, 0.26977396282384136, 0.07093825133260853, 0.3053819258016964, 0.05900546263981454, 0.052215610513697844, -0.027305746770291003, 0.05699959483477259, 0.058667274300025746, -0.15452062554338014, 0.1301130860224666, 0.24764336099078554, -0.012116971282109975, 0.2313332207874579, -0.45968374077922214, -0.2443431267907988, 0.04713222570717335, 0.14110271242296624, 0.12713703980749894, -0.03382455926070625, -0.21232998397892822, 0.017515483904841863, -0.11820146167639665, -0.1343314325503871, -0.08097382219129069, 0.06949066341865785, 0.03231154031135577, -0.2230418433141086, 0.1121829645819739, 0.0697553271579718, 0.09852927406792512, -0.11372961758769781, -0.07366307704949272, -0.038676579303002195, 0.09711438348282597, 0.03782153576696124, 0.011341533445178749, 0.2154239587496944, -0.13758660223325267, -0.07894005122856644, 0.4064995314881295, -0.020410844727494604, -0.14022443611397892, 0.2237554250987704, -0.13178171467839064, -0.14209181249621297, 0.1779120185936684, 0.12444519213523471, 0.07630266108923776, -0.14014382404763207, 0.058989540069234354, -0.010638406008766395, 0.2055676464565812, 0.09019539779516406, 0.03829322804691281, 0.2114678576761511, 0.21456360199605812, 0.0542978798520255, 0.16926490273438172, -0.10837900956875149, -0.09356637214572576, -0.24533746938477688, -0.20736283472945502, -0.22574791193989938, 0.0319166918798255, -0.09928735820438872, -0.24291113941946965, 0.34486875143236745, 0.10433720275871232, 0.2417685808390825, -0.0026171656379833106, 0.20441969229022744, 0.04748587076507598, 0.09102984380902733, 0.023412475953558963, 0.21663787379068974, 0.11300200286940365, 0.08127254653515707, -0.2368726611142967, 0.14621160049855844, 0.03553803683353399] |
1,803.01417 | Efficient and Accurate MRI Super-Resolution using a Generative
Adversarial Network and 3D Multi-Level Densely Connected Network | High-resolution (HR) magnetic resonance images (MRI) provide detailed
anatomical information important for clinical application and quantitative
image analysis. However, HR MRI conventionally comes at the cost of longer scan
time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent
studies have shown that single image super-resolution (SISR), a technique to
recover HR details from one single low-resolution (LR) input image, could
provide high-quality image details with the help of advanced deep convolutional
neural networks (CNN). However, deep neural networks consume memory heavily and
run slowly, especially in 3D settings. In this paper, we propose a novel 3D
neural network design, namely a multi-level densely connected super-resolution
network (mDCSRN) with generative adversarial network (GAN)-guided training. The
mDCSRN quickly trains and inferences and the GAN promotes realistic output
hardly distinguishable from original HR images. Our results from experiments on
a dataset with 1,113 subjects show that our new architecture beats other
popular deep learning methods in recovering 4x resolution-downgraded im-ages
and runs 6x faster.
| cs.CV eess.IV | highresolution hr magnetic resonance images mri provide detailed anatomical information important for clinical application and quantitative image analysis however hr mri conventionally comes at the cost of longer scan time smaller spatial coverage and lower signaltonoise ratio snr recent studies have shown that single image superresolution sisr a technique to recover hr details from one single lowresolution lr input image could provide highquality image details with the help of advanced deep convolutional neural networks cnn however deep neural networks consume memory heavily and run slowly especially in 3d settings in this paper we propose a novel 3d neural network design namely a multilevel densely connected superresolution network mdcsrn with generative adversarial network ganguided training the mdcsrn quickly trains and inferences and the gan promotes realistic output hardly distinguishable from original hr images our results from experiments on a dataset with 1113 subjects show that our new architecture beats other popular deep learning methods in recovering 4x resolutiondowngraded images and runs 6x faster | [['highresolution', 'hr', 'magnetic', 'resonance', 'images', 'mri', 'provide', 'detailed', 'anatomical', 'information', 'important', 'for', 'clinical', 'application', 'and', 'quantitative', 'image', 'analysis', 'however', 'hr', 'mri', 'conventionally', 'comes', 'at', 'the', 'cost', 'of', 'longer', 'scan', 'time', 'smaller', 'spatial', 'coverage', 'and', 'lower', 'signaltonoise', 'ratio', 'snr', 'recent', 'studies', 'have', 'shown', 'that', 'single', 'image', 'superresolution', 'sisr', 'a', 'technique', 'to', 'recover', 'hr', 'details', 'from', 'one', 'single', 'lowresolution', 'lr', 'input', 'image', 'could', 'provide', 'highquality', 'image', 'details', 'with', 'the', 'help', 'of', 'advanced', 'deep', 'convolutional', 'neural', 'networks', 'cnn', 'however', 'deep', 'neural', 'networks', 'consume', 'memory', 'heavily', 'and', 'run', 'slowly', 'especially', 'in', '3d', 'settings', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', '3d', 'neural', 'network', 'design', 'namely', 'a', 'multilevel', 'densely', 'connected', 'superresolution', 'network', 'mdcsrn', 'with', 'generative', 'adversarial', 'network', 'ganguided', 'training', 'the', 'mdcsrn', 'quickly', 'trains', 'and', 'inferences', 'and', 'the', 'gan', 'promotes', 'realistic', 'output', 'hardly', 'distinguishable', 'from', 'original', 'hr', 'images', 'our', 'results', 'from', 'experiments', 'on', 'a', 'dataset', 'with', '1113', 'subjects', 'show', 'that', 'our', 'new', 'architecture', 'beats', 'other', 'popular', 'deep', 'learning', 'methods', 'in', 'recovering', '4x', 'resolutiondowngraded', 'images', 'and', 'runs', '6x', 'faster']] | [-0.012698739639607175, -0.02655461474168527, -0.026744865597213938, 0.07776567625409417, -0.09707228268667631, -0.24288503864199465, -0.006145961870751756, 0.49330353390283976, -0.2432940017455552, -0.35857446591923886, 0.07011653324721759, -0.2438515482376082, -0.2112527087513546, 0.19450645784322831, -0.16072435967647766, 0.09518625038046731, 0.2306600894736232, 0.02104416254891637, -0.05512792866896614, -0.2741046808866336, 0.24201733955031826, 0.07219626275985354, 0.3765965489658845, -0.061275997500471725, 0.09998164510890795, -0.03763462308517221, -0.02331184214452588, -0.046342515436007016, -0.07032905767505614, 0.15544145357282244, 0.3240628706474046, 0.21532844406879756, 0.3085907143481736, -0.5016586079344719, -0.27742928727986765, 0.046921990399213534, 0.18945198090668897, 0.10269236020873525, -0.061737182394666246, -0.3443953988843751, 0.07808266862448823, -0.09813243563023, 0.0770897198484288, -0.13301270230838297, -0.052960766707045984, -0.04652887259069043, -0.31683871213087367, 0.07717726790623244, 0.04486328580628939, 0.09852296270760177, -0.055984088165915415, -0.12094323973088891, 0.016514036651182024, 0.14637094530383055, -0.03126874779530836, 0.12745918237082543, 0.1621208698754022, -0.23255538076156443, -0.09433439303678755, 0.27843943319307, -0.03847982488790692, -0.1255966586142239, 0.20215344207974362, -0.08262603472375983, -0.13593623808089975, 0.1720460702111072, 0.2329187232211138, 0.12745576976987097, -0.1379086312298557, -0.026873177217313714, -0.03649565214703826, 0.25309913658796324, 0.06552530066412283, 0.031369741324518065, 0.17185413900208718, 0.30034539008717925, -0.013553734772980119, 0.1486759723441917, -0.2666670272354835, -0.024949807619905878, -0.12429964488749451, -0.07120056131182687, -0.1957726196814741, 0.01870012165804665, -0.1494568076710102, -0.12308917142715323, 0.4204778156974176, 0.23152308066705643, 0.22788866091507806, 0.11849663348844912, 0.4111677144382951, -0.02209941347724982, 0.1586991939527908, 0.0632671060724349, 0.18598949709977908, 0.017232602411275343, 0.200208490941367, -0.12742353384412494, 0.041503748945638394, 0.008405351731336759] |
1,803.01418 | Complexity and (un)decidability of fragments of $\langle
\omega^{\omega^\lambda}; \times \rangle$ | We specify the frontier of decidability for fragments of the first-order
theory of ordinal multiplication. We give a NEXPTIME lower bound for the
complexity of the existential fragment of $\langle \omega^{\omega^\lambda};
\times, \omega, \omega+1, \omega^2+1 \rangle$ for every ordinal $\lambda$.
Moreover, we prove (by reduction from Hilbert Tenth Problem) that the
$\exists^*\forall^{6}$-fragment of $\langle \omega^{\omega^\lambda}; \times
\rangle$ is undecidable for every ordinal $\lambda$.
| cs.LO math.LO | we specify the frontier of decidability for fragments of the firstorder theory of ordinal multiplication we give a nexptime lower bound for the complexity of the existential fragment of langle omegaomegalambda times omega omega1 omega21 rangle for every ordinal lambda moreover we prove by reduction from hilbert tenth problem that the existsforall6fragment of langle omegaomegalambda times rangle is undecidable for every ordinal lambda | [['we', 'specify', 'the', 'frontier', 'of', 'decidability', 'for', 'fragments', 'of', 'the', 'firstorder', 'theory', 'of', 'ordinal', 'multiplication', 'we', 'give', 'a', 'nexptime', 'lower', 'bound', 'for', 'the', 'complexity', 'of', 'the', 'existential', 'fragment', 'of', 'langle', 'omegaomegalambda', 'times', 'omega', 'omega1', 'omega21', 'rangle', 'for', 'every', 'ordinal', 'lambda', 'moreover', 'we', 'prove', 'by', 'reduction', 'from', 'hilbert', 'tenth', 'problem', 'that', 'the', 'existsforall6fragment', 'of', 'langle', 'omegaomegalambda', 'times', 'rangle', 'is', 'undecidable', 'for', 'every', 'ordinal', 'lambda']] | [-0.1476408422536527, 0.18431473568392295, -0.06250288904023667, 0.1292104090350525, -0.030459937639534473, -0.12224038956531634, 0.04729732083505951, 0.31685005814457934, -0.33784905013938743, -0.1870717060752213, 0.030426718985351424, -0.30739431421170593, -0.012860810291022063, 0.16980267290297585, -0.013360404859607418, 0.02516242532680432, 0.004672634477416674, 0.1541464183217613, -0.06122293994994834, -0.27428923416882756, 0.31037319629297905, -0.07843899132373432, 0.1371622486350437, 0.06483714183947692, 0.12939874110743405, 0.03203653361027439, 0.06471172102416554, 0.02736650804678599, -0.2243396532106999, 0.11441995304388304, 0.30743355080485346, 0.26917745608758803, 0.32069088201969864, -0.3592154683341505, -0.04599829073995352, 0.15566414232210565, 0.1517085651634261, 0.007735427313794692, 0.05445970800550034, -0.24584192605689167, 0.15977416858077048, -0.17602319400854563, -0.05941690281033516, -0.05139844190174093, 0.18427873911956946, -0.011141667080422243, -0.3105581355591615, 0.11008333275870731, 0.14808745061357817, 0.08170990408398211, -0.10348196742512906, -0.17595853083766996, 0.04187150737270713, 0.02395274896019449, -0.022005269788981725, 0.07908773458718012, 0.02945743877401886, -0.12056025212320189, -0.124085957929492, 0.3954506375826895, -0.068740241585571, -0.13536303093036015, 0.013998241563482831, -0.17942817877628842, -0.1971158320006604, 0.11682281165073315, 0.05796255516664436, 0.16574446762291092, 0.015409928482646744, 0.22116288770145426, -0.1568743315874599, 0.28909917433435717, 0.13817407097667456, 0.0557228248178338, 0.05539986807852983, 0.15575516546765963, 0.1348761793691665, 0.16816585225363573, 0.028842029608010005, -0.029393143656974038, -0.37468975950032474, -0.15266781911583774, -0.060685061787565546, 0.08346249889970446, -0.1469084323849529, -0.16563920713961125, 0.2734781333206532, 0.1344062052667141, 0.15658154636621474, 0.25137828214404484, 0.24509850442409514, 0.1889342197217047, 0.010773850698024034, 0.06815056757380565, 0.07701353658922017, 0.13102218464094526, -0.014237911688784759, -0.21119771524099634, 0.09154832060448825, 0.15229940116405488] |
1,803.01419 | Image space projection for low-rank signal estimation: Modified
Gauss-Newton method | The paper is devoted to the solution of a weighted nonlinear least-squares
problem for low-rank signal estimation, which is related to Hankel structured
low-rank approximation problems. A modified weighted Gauss-Newton method, which
uses projecting on the image space of the signal, is proposed to solve this
problem. The advantage of the proposed method is the possibility of its
numerically stable and fast implementation. For a weight matrix, which
corresponds to an autoregressive process of order $p$, the computational cost
of iterations is $O(N r^2 + N p^2 + r N \log N)$, where $N$ is the time series
length, $r$ is the rank of the approximating time series. For developing the
method, some useful properties of the space of time series of rank $r$ are
studied. The method is compared with state-of-the-art methods based on the
variable projection approach in terms of numerical stability, accuracy and
computational cost.
| math.NA cs.NA | the paper is devoted to the solution of a weighted nonlinear leastsquares problem for lowrank signal estimation which is related to hankel structured lowrank approximation problems a modified weighted gaussnewton method which uses projecting on the image space of the signal is proposed to solve this problem the advantage of the proposed method is the possibility of its numerically stable and fast implementation for a weight matrix which corresponds to an autoregressive process of order p the computational cost of iterations is on r2 n p2 r n log n where n is the time series length r is the rank of the approximating time series for developing the method some useful properties of the space of time series of rank r are studied the method is compared with stateoftheart methods based on the variable projection approach in terms of numerical stability accuracy and computational cost | [['the', 'paper', 'is', 'devoted', 'to', 'the', 'solution', 'of', 'a', 'weighted', 'nonlinear', 'leastsquares', 'problem', 'for', 'lowrank', 'signal', 'estimation', 'which', 'is', 'related', 'to', 'hankel', 'structured', 'lowrank', 'approximation', 'problems', 'a', 'modified', 'weighted', 'gaussnewton', 'method', 'which', 'uses', 'projecting', 'on', 'the', 'image', 'space', 'of', 'the', 'signal', 'is', 'proposed', 'to', 'solve', 'this', 'problem', 'the', 'advantage', 'of', 'the', 'proposed', 'method', 'is', 'the', 'possibility', 'of', 'its', 'numerically', 'stable', 'and', 'fast', 'implementation', 'for', 'a', 'weight', 'matrix', 'which', 'corresponds', 'to', 'an', 'autoregressive', 'process', 'of', 'order', 'p', 'the', 'computational', 'cost', 'of', 'iterations', 'is', 'on', 'r2', 'n', 'p2', 'r', 'n', 'log', 'n', 'where', 'n', 'is', 'the', 'time', 'series', 'length', 'r', 'is', 'the', 'rank', 'of', 'the', 'approximating', 'time', 'series', 'for', 'developing', 'the', 'method', 'some', 'useful', 'properties', 'of', 'the', 'space', 'of', 'time', 'series', 'of', 'rank', 'r', 'are', 'studied', 'the', 'method', 'is', 'compared', 'with', 'stateoftheart', 'methods', 'based', 'on', 'the', 'variable', 'projection', 'approach', 'in', 'terms', 'of', 'numerical', 'stability', 'accuracy', 'and', 'computational', 'cost']] | [-0.10318773185630163, -0.018255969231102252, -0.079639225579441, 0.022167289807054645, -0.05995452292710032, -0.13119928688703947, 0.004259697510063495, 0.3645681565219205, -0.31128037570376105, -0.2645681098116281, 0.1423548032323932, -0.25506186020905025, -0.15401372878034025, 0.1927240897713178, -0.05712214709029929, 0.13371444732063986, 0.052164370425313404, 0.07623969961263954, -0.10733304423206702, -0.32790657595973716, 0.28087973541082584, 0.07134700463829588, 0.24137430480196562, -0.022123001908169012, 0.1269263348204071, -0.010857367851414194, -0.04262167289023836, 0.0033411741530210135, -0.06102117452744956, 0.15705368655083113, 0.25619734803291216, 0.1574977524929412, 0.3489496170587787, -0.38156835201725825, -0.1771107197751942, 0.13010154767536036, 0.13263385162301272, 0.04177505033782824, 0.0022385581276915356, -0.24191995307624545, 0.09516202843722517, -0.11677382473693523, -0.09484135613247292, -0.09732985818816017, 0.01983130389141965, -0.0065923940568958245, -0.3559905313057442, 0.08164109368744778, 0.04548210301396616, 0.0008278743185307065, -0.0332607169913077, -0.15438341517447915, 0.07269743222054349, 0.05548524393138718, 0.048766612726517264, 0.050844119700654215, 0.055511199636384845, -0.07245100987915665, -0.07128150778988453, 0.382142999094643, -0.06082314027757193, -0.2386600334557692, 0.11742672468184762, -0.07683631813485328, -0.1106215351714102, 0.17709840416002456, 0.20870860144559752, 0.19383458360074382, -0.07758638741965214, 0.1533167418849986, -0.04927180525336466, 0.17640296748698983, 0.039286763085154434, -0.009442031504713918, 0.0725447832357955, 0.22301890344787764, 0.11833116513946451, 0.13221695165035047, -0.09676322615099434, -0.06856124567135863, -0.2793197610913074, -0.16175894643266187, -0.25730319596724965, -0.025988129973858083, -0.15365195779543694, -0.1679930068322853, 0.42182526860564745, 0.1249380249447151, 0.18880285315649353, 0.1168473160096878, 0.3296566457066634, 0.15107509539756056, -0.006426263075522849, 0.07937262553525515, 0.13124179325249102, 0.15120722821272578, 0.07439909406522231, -0.2550586482401529, 0.06981783519337138, 0.18696367171471812] |
1,803.0142 | Detecting Correlations with Little Memory and Communication | We study the problem of identifying correlations in multivariate data, under
information constraints: Either on the amount of memory that can be used by the
algorithm, or the amount of communication when the data is distributed across
several machines. We prove a tight trade-off between the memory/communication
complexity and the sample complexity, implying (for example) that to detect
pairwise correlations with optimal sample complexity, the number of required
memory/communication bits is at least quadratic in the dimension. Our results
substantially improve those of Shamir [2014], which studied a similar question
in a much more restricted setting. To the best of our knowledge, these are the
first provable sample/memory/communication trade-offs for a practical
estimation problem, using standard distributions, and in the natural regime
where the memory/communication budget is larger than the size of a single data
point. To derive our theorems, we prove a new information-theoretic result,
which may be relevant for studying other information-constrained learning
problems.
| cs.LG stat.ML | we study the problem of identifying correlations in multivariate data under information constraints either on the amount of memory that can be used by the algorithm or the amount of communication when the data is distributed across several machines we prove a tight tradeoff between the memorycommunication complexity and the sample complexity implying for example that to detect pairwise correlations with optimal sample complexity the number of required memorycommunication bits is at least quadratic in the dimension our results substantially improve those of shamir 2014 which studied a similar question in a much more restricted setting to the best of our knowledge these are the first provable samplememorycommunication tradeoffs for a practical estimation problem using standard distributions and in the natural regime where the memorycommunication budget is larger than the size of a single data point to derive our theorems we prove a new informationtheoretic result which may be relevant for studying other informationconstrained learning problems | [['we', 'study', 'the', 'problem', 'of', 'identifying', 'correlations', 'in', 'multivariate', 'data', 'under', 'information', 'constraints', 'either', 'on', 'the', 'amount', 'of', 'memory', 'that', 'can', 'be', 'used', 'by', 'the', 'algorithm', 'or', 'the', 'amount', 'of', 'communication', 'when', 'the', 'data', 'is', 'distributed', 'across', 'several', 'machines', 'we', 'prove', 'a', 'tight', 'tradeoff', 'between', 'the', 'memorycommunication', 'complexity', 'and', 'the', 'sample', 'complexity', 'implying', 'for', 'example', 'that', 'to', 'detect', 'pairwise', 'correlations', 'with', 'optimal', 'sample', 'complexity', 'the', 'number', 'of', 'required', 'memorycommunication', 'bits', 'is', 'at', 'least', 'quadratic', 'in', 'the', 'dimension', 'our', 'results', 'substantially', 'improve', 'those', 'of', 'shamir', '2014', 'which', 'studied', 'a', 'similar', 'question', 'in', 'a', 'much', 'more', 'restricted', 'setting', 'to', 'the', 'best', 'of', 'our', 'knowledge', 'these', 'are', 'the', 'first', 'provable', 'samplememorycommunication', 'tradeoffs', 'for', 'a', 'practical', 'estimation', 'problem', 'using', 'standard', 'distributions', 'and', 'in', 'the', 'natural', 'regime', 'where', 'the', 'memorycommunication', 'budget', 'is', 'larger', 'than', 'the', 'size', 'of', 'a', 'single', 'data', 'point', 'to', 'derive', 'our', 'theorems', 'we', 'prove', 'a', 'new', 'informationtheoretic', 'result', 'which', 'may', 'be', 'relevant', 'for', 'studying', 'other', 'informationconstrained', 'learning', 'problems']] | [-0.10077625137036517, 0.05743835860743157, -0.07235655065085138, 0.09920230736512871, -0.05990248401198656, -0.13826860951319817, 0.10322806457838704, 0.32463500834400616, -0.29618007764070026, -0.3629320392204869, 0.11427532350869789, -0.2697839757637872, -0.10839160225061219, 0.23792761585284625, -0.10078900884236058, 0.07702705467780752, 0.055956023444812146, 0.043657823282504275, -0.05415998851549962, -0.30459965462646177, 0.29432437418163904, 0.05485912957078507, 0.28078820840605806, 0.02605445308182689, 0.06720202241859008, -0.006015863539951463, -0.013299155800092605, 0.03179629795974301, -0.1201169249726527, 0.14309965475582548, 0.2849562662773796, 0.17313614152822523, 0.3150237780394814, -0.3973719995494203, -0.20344818176160898, 0.15700585814793744, 0.1290340457562237, 0.11052699975759513, -0.032239754983287815, -0.24424543382690078, 0.0895406933899428, -0.10420583459518609, -0.05461989000980412, -0.04422827976184987, -0.004907048541691996, -0.0003903327825208825, -0.313977771515267, 0.05010299749612328, 0.08356568948215534, 0.040529162502817566, -0.022300121091276166, -0.11084672383092825, 0.04148549786168, 0.12521040004005865, 0.02782860814533647, 0.0228047123306521, 0.0742361149570394, -0.12459236326056623, -0.12272312752602081, 0.36520731682108054, -0.022223516031367435, -0.204531184726605, 0.18890600959439913, -0.12017752926255906, -0.16365206952116662, 0.10058201959416752, 0.2086554100436549, 0.11890320825660902, -0.14708063866494359, 0.059343409056835356, -0.0733340568810461, 0.1958711264424041, 0.041053402787374876, 0.08362031172239973, 0.11404781463713716, 0.17445132665846858, 0.1007917960865363, 0.17449442609100632, -0.06260322513689677, -0.10156180864320166, -0.2512583995568416, -0.15610591745935382, -0.21538022023535544, 0.009190415666859237, -0.14365260609737296, -0.09733340381494453, 0.34812939400153775, 0.16590175946137958, 0.21022841503182726, 0.1252131374851395, 0.30509513192209264, 0.09292877628693297, 0.059978224135815134, 0.13864735782506965, 0.22431251553277815, 0.07246361554660384, 0.049273006852355694, -0.19249240057843348, 0.10639228746895829, 0.017441566172806965] |
1,803.01421 | XDFT: an efficient first-principles method for neutral excitations in
molecules | State-of-the-art methods for calculating neutral excitation energies are
typically demanding and limited to single electron-hole pairs and their
composite plasmons. Here we introduce excitonic density-functional theory
(XDFT) a computationally light, generally applicable, first-principles
technique for calculating neutral excitations based on generalized constrained
DFT. In order to simulate an M-particle excited state of an N-electron system,
XDFT automatically optimizes a constraining potential to confine N-M electrons
within the ground-state Kohn-Sham valence subspace. We demonstrate the efficacy
of XDFT by calculating the lowest single-particle singlet and triplet
excitation energies of the well-known Thiel molecular test set, with results
which are in excellent agreement with time-dependent DFT. Furthermore, going
beyond the capability of adiabatic time-dependent DFT, we show that XDFT can
successfully capture double excitations. Overall our method makes optical gaps,
excition bindings and oscillator strengths readily accessible at a
computational cost comparable to that of standard DFT. As such, XDFT appears as
an ideal candidate to work within high-throughput discovery frameworks and
within linear-scaling methods for large systems.
| physics.chem-ph cond-mat.mtrl-sci physics.atm-clus physics.comp-ph quant-ph | stateoftheart methods for calculating neutral excitation energies are typically demanding and limited to single electronhole pairs and their composite plasmons here we introduce excitonic densityfunctional theory xdft a computationally light generally applicable firstprinciples technique for calculating neutral excitations based on generalized constrained dft in order to simulate an mparticle excited state of an nelectron system xdft automatically optimizes a constraining potential to confine nm electrons within the groundstate kohnsham valence subspace we demonstrate the efficacy of xdft by calculating the lowest singleparticle singlet and triplet excitation energies of the wellknown thiel molecular test set with results which are in excellent agreement with timedependent dft furthermore going beyond the capability of adiabatic timedependent dft we show that xdft can successfully capture double excitations overall our method makes optical gaps excition bindings and oscillator strengths readily accessible at a computational cost comparable to that of standard dft as such xdft appears as an ideal candidate to work within highthroughput discovery frameworks and within linearscaling methods for large systems | [['stateoftheart', 'methods', 'for', 'calculating', 'neutral', 'excitation', 'energies', 'are', 'typically', 'demanding', 'and', 'limited', 'to', 'single', 'electronhole', 'pairs', 'and', 'their', 'composite', 'plasmons', 'here', 'we', 'introduce', 'excitonic', 'densityfunctional', 'theory', 'xdft', 'a', 'computationally', 'light', 'generally', 'applicable', 'firstprinciples', 'technique', 'for', 'calculating', 'neutral', 'excitations', 'based', 'on', 'generalized', 'constrained', 'dft', 'in', 'order', 'to', 'simulate', 'an', 'mparticle', 'excited', 'state', 'of', 'an', 'nelectron', 'system', 'xdft', 'automatically', 'optimizes', 'a', 'constraining', 'potential', 'to', 'confine', 'nm', 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'methods', 'for', 'large', 'systems']] | [-0.04290893354385822, 0.1191792147852451, -0.039759665911004556, 0.10828127893086253, -0.0045489365373827875, -0.16636600544261015, 0.08267512721225552, 0.4097453948132784, -0.2362084226424705, -0.30893763119399725, -0.0491398738694366, -0.2855011969860868, -0.10740146734218775, 0.1721324200702674, 0.04165689127536558, 0.08791316824078739, 0.06524826248501797, -0.03839580616100231, -0.10625650404836051, -0.17124638197724765, 0.2362322031628307, 0.08647015116791835, 0.28077520707100406, 0.09974047615675323, 0.02942462253429175, 0.03669663422308997, 0.06349730420105877, -0.01208120236083506, -0.11260326377002884, 0.17561509474236742, 0.2917759060040565, 0.02303356475320207, 0.2636082468397287, -0.4720067137919636, -0.19458980048748564, 0.020450819715722858, 0.16840233685482428, 0.17644015320433662, -0.03686172278746626, -0.27744869278612017, 0.06087739661291062, -0.19565918363479293, -0.1380398986729266, -0.20319459189253042, 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1,803.01422 | DAGs with NO TEARS: Continuous Optimization for Structure Learning | Estimating the structure of directed acyclic graphs (DAGs, also known as
Bayesian networks) is a challenging problem since the search space of DAGs is
combinatorial and scales superexponentially with the number of nodes. Existing
approaches rely on various local heuristics for enforcing the acyclicity
constraint. In this paper, we introduce a fundamentally different strategy: We
formulate the structure learning problem as a purely \emph{continuous}
optimization problem over real matrices that avoids this combinatorial
constraint entirely. This is achieved by a novel characterization of acyclicity
that is not only smooth but also exact. The resulting problem can be
efficiently solved by standard numerical algorithms, which also makes
implementation effortless. The proposed method outperforms existing ones,
without imposing any structural assumptions on the graph such as bounded
treewidth or in-degree. Code implementing the proposed algorithm is open-source
and publicly available at https://github.com/xunzheng/notears.
| stat.ML cs.AI cs.LG stat.ME | estimating the structure of directed acyclic graphs dags also known as bayesian networks is a challenging problem since the search space of dags is combinatorial and scales superexponentially with the number of nodes existing approaches rely on various local heuristics for enforcing the acyclicity constraint in this paper we introduce a fundamentally different strategy we formulate the structure learning problem as a purely emphcontinuous optimization problem over real matrices that avoids this combinatorial constraint entirely this is achieved by a novel characterization of acyclicity that is not only smooth but also exact the resulting problem can be efficiently solved by standard numerical algorithms which also makes implementation effortless the proposed method outperforms existing ones without imposing any structural assumptions on the graph such as bounded treewidth or indegree code implementing the proposed algorithm is opensource and publicly available at httpsgithubcomxunzhengnotears | [['estimating', 'the', 'structure', 'of', 'directed', 'acyclic', 'graphs', 'dags', 'also', 'known', 'as', 'bayesian', 'networks', 'is', 'a', 'challenging', 'problem', 'since', 'the', 'search', 'space', 'of', 'dags', 'is', 'combinatorial', 'and', 'scales', 'superexponentially', 'with', 'the', 'number', 'of', 'nodes', 'existing', 'approaches', 'rely', 'on', 'various', 'local', 'heuristics', 'for', 'enforcing', 'the', 'acyclicity', 'constraint', 'in', 'this', 'paper', 'we', 'introduce', 'a', 'fundamentally', 'different', 'strategy', 'we', 'formulate', 'the', 'structure', 'learning', 'problem', 'as', 'a', 'purely', 'emphcontinuous', 'optimization', 'problem', 'over', 'real', 'matrices', 'that', 'avoids', 'this', 'combinatorial', 'constraint', 'entirely', 'this', 'is', 'achieved', 'by', 'a', 'novel', 'characterization', 'of', 'acyclicity', 'that', 'is', 'not', 'only', 'smooth', 'but', 'also', 'exact', 'the', 'resulting', 'problem', 'can', 'be', 'efficiently', 'solved', 'by', 'standard', 'numerical', 'algorithms', 'which', 'also', 'makes', 'implementation', 'effortless', 'the', 'proposed', 'method', 'outperforms', 'existing', 'ones', 'without', 'imposing', 'any', 'structural', 'assumptions', 'on', 'the', 'graph', 'such', 'as', 'bounded', 'treewidth', 'or', 'indegree', 'code', 'implementing', 'the', 'proposed', 'algorithm', 'is', 'opensource', 'and', 'publicly', 'available', 'at', 'httpsgithubcomxunzhengnotears']] | [-0.12259834335209038, 0.01924782913687418, -0.06175524139904129, 0.0838993135856451, -0.17685549779252396, -0.18599506098736854, 0.047693132882244325, 0.4194968989748749, -0.3407916349338756, -0.35521174982364334, 0.13133670668295255, -0.1814623427503615, -0.18982311675371938, 0.17201552575909726, -0.08930515485527597, 0.08157822321480636, 0.14089594766658417, 0.02434718238002212, -0.06765477793957458, -0.26925403259048847, 0.3250460236018403, 0.04118681206575615, 0.27151776249888987, 0.07121293140883497, 0.11729291538379603, 0.019223798759844448, -0.025906044794682066, 0.09301015952071878, -0.10390900278167896, 0.12536583107849247, 0.2756428992067524, 0.23398944939546984, 0.2814551524168028, -0.4083753331018304, -0.22232231430260452, 0.1752290594728208, 0.15056325628743808, 0.1143308889276596, -0.012401452837444895, -0.26177744846121015, 0.11365850815187684, -0.13258891860894162, -0.022901680288675556, -0.08086577812276727, -0.027457447136289996, -0.007987175337809453, -0.29597339668669637, 0.03235405064192132, 0.07400865781141057, 0.04358509713247847, -0.016259510993032897, -0.15030281573346407, 0.02752704022405334, 0.06989943467100694, 0.002398945593858044, 0.029583634508827287, 0.10626248403941449, -0.11744276747415713, -0.18920413682089865, 0.3728731934570794, 0.022702670759997136, -0.24810373797516921, 0.16728947532410138, 0.01444379651664401, -0.1923060377577333, 0.11124907240686978, 0.14999219970844632, 0.18822318279660114, -0.15683051090262054, 0.13766147502071538, -0.10185545778049411, 0.15095535517006897, 0.058579566761208096, 0.008273475594892294, 0.09758147365319804, 0.1941698650048925, 0.14831658332816344, 0.15913641272136178, -0.008695358742135678, -0.07702586544583813, -0.2452136408906135, -0.0756897592888609, -0.23046534644480018, -0.007785258089295226, -0.13746502661466994, -0.20067846127065475, 0.38493720718438357, 0.17043076777703417, 0.1562035260923046, 0.1611629243079144, 0.367082489352077, 0.06793389277509246, 0.07634339401860246, 0.14847615399069602, 0.1572854392944078, 0.07357832401649182, 0.0691415115767125, -0.16742892652287705, 0.14870701864087058, 0.10792412097335931] |
1,803.01423 | The Navarro Conjecture for the alternating groups | Recently Navarro proposed a strengthening of the unsolved McKay conjecture
using Galois automorphisms. We prove that the Navarro conjecture holds for the
alternating groups when the prime p is odd.
| math.RT math.CO math.GR | recently navarro proposed a strengthening of the unsolved mckay conjecture using galois automorphisms we prove that the navarro conjecture holds for the alternating groups when the prime p is odd | [['recently', 'navarro', 'proposed', 'a', 'strengthening', 'of', 'the', 'unsolved', 'mckay', 'conjecture', 'using', 'galois', 'automorphisms', 'we', 'prove', 'that', 'the', 'navarro', 'conjecture', 'holds', 'for', 'the', 'alternating', 'groups', 'when', 'the', 'prime', 'p', 'is', 'odd']] | [-0.24931303126116594, 0.07079719246054689, -0.18982916502282024, 0.11313013051403686, -0.11477213172862927, -0.23005350640354058, -0.03247639977683624, 0.23565852077056965, -0.2746240591009458, -0.3450555408373475, 0.0022201326830933493, -0.2014947770629078, -0.1435559160502938, 0.21294226634005706, -0.20825733694558343, -0.014622905594296753, 0.02902666727701823, 0.05313556517163912, -0.034484526289937395, -0.48916418248166643, 0.3475143338243167, -0.05197409450386961, 0.2046410714586576, 0.100550087261945, 0.047820531918356814, 0.13412983934395015, 0.03502539196051657, -0.04504136474182208, -0.14859109098057768, 0.07839673677808605, 0.30745071355098236, 0.09013378237529347, 0.26487048268318175, -0.3222333948438366, -0.2012495199373613, 0.26654365432138244, 0.12444037782649199, 0.011899205483496189, -0.14162072319692623, -0.23819042593240738, 0.21092151856670777, -0.17655069716274738, -0.23904349664226174, -0.005164739054938157, 0.14739925600588322, 0.0004353067527214686, -0.27155809067189696, 0.0653771609494773, 0.22208737389494976, 0.14444346021239957, -0.07104800864278028, -0.16220309638107816, -0.030097516160458325, 0.017417740974148426, 0.011844872582393388, -0.002134120980432878, -0.046217673318460585, -0.08016848359256983, -0.1454606139101088, 0.32501072411735854, -0.020812802870447438, -0.07338788695633411, 0.034435414150357245, -0.12130447037828465, -0.2925047955165307, 0.06442669710765282, -0.06220848535497983, 0.11732594127145907, 0.09750403026652445, 0.249708275248607, -0.3498957556982835, 0.03878248482942581, 0.22845399550472698, -0.20457891348438959, 0.11009370130486787, 0.06891115782006334, 0.06806828410675128, 0.1638989212612311, -0.0042547081907590234, 0.08213498713448644, -0.2522598502536615, -0.18403149272004762, -0.13631710388387244, 0.0975831247245272, -0.09870704063214361, -0.08645586847172429, 0.3185500239332517, 0.08440769299243887, 0.07200701609253883, 0.2027682431973517, 0.24134537745267154, 0.04164861926692538, -0.009013121326764425, 0.12924659679216954, 0.11402239377299944, 0.4022612661123276, -0.12469682122270266, -0.17583336831691365, 0.006662743523096045, 0.26271030721254646] |
1,803.01424 | Two more, bright, z > 6 quasars from VST ATLAS and WISE | Recently, Carnall et al. discovered two bright high redshift quasars using
the combination of the VST ATLAS and WISE surveys. The technique involved using
the 3-D colour plane i-z:z-W1:W1-W2 with the WISE W1 (3.4 micron) and W2 (4.5
micron) bands taking the place of the usual NIR J band to help decrease stellar
dwarf contamination. Here we report on our continued search for 5.7<z<6.4
quasars over an ~2x larger area of ~3577 sq. deg. of the Southern Hemisphere.
We have found two further z>6 quasars, VST-ATLAS J158.6938-14.4211 at z=6.07
and J332.8017-32.1036 at z=6.32 with magnitudes of z_AB=19.4 and 19.7 mag
respectively. J158.6938-14.4211 was confirmed by Keck LRIS observations and
J332.8017-32.1036 was confirmed by ESO NTT EFOSC-2 observations. Here we
present VLT X-shooter Visible and NIR spectra for the four ATLAS quasars. We
have further independently rediscovered two z>5.7 quasars previously found by
the VIKING/KiDS and PanSTARRS surveys. This means that in ATLAS we have now
discovered a total of six quasars in our target 5.7<z<6.4 redshift range.
Making approximate corrections for incompleteness, we find that our quasar
space density agrees with the SDSS results of Jiang et al. at M_1450A~-27mag.
Preliminary virial mass estimates based on the CIV and MIII emission lines give
black hole masses in the range M_BH~1-6x10e9 M_solar for the four ATLAS
quasars.
| astro-ph.GA astro-ph.CO | recently carnall et al discovered two bright high redshift quasars using the combination of the vst atlas and wise surveys the technique involved using the 3d colour plane izzw1w1w2 with the wise w1 34 micron and w2 45 micron bands taking the place of the usual nir j band to help decrease stellar dwarf contamination here we report on our continued search for 57z64 quasars over an 2x larger area of 3577 sq deg of the southern hemisphere we have found two further z6 quasars vstatlas j1586938144211 at z607 and j3328017321036 at z632 with magnitudes of z_ab194 and 197 mag respectively j1586938144211 was confirmed by keck lris observations and j3328017321036 was confirmed by eso ntt efosc2 observations here we present vlt xshooter visible and nir spectra for the four atlas quasars we have further independently rediscovered two z57 quasars previously found by the vikingkids and panstarrs surveys this means that in atlas we have now discovered a total of six quasars in our target 57z64 redshift range making approximate corrections for incompleteness we find that our quasar space density agrees with the sdss results of jiang et al at m_1450a27mag preliminary virial mass estimates based on the civ and miii emission lines give black hole masses in the range m_bh16x10e9 m_solar for the four atlas quasars | [['recently', 'carnall', 'et', 'al', 'discovered', 'two', 'bright', 'high', 'redshift', 'quasars', 'using', 'the', 'combination', 'of', 'the', 'vst', 'atlas', 'and', 'wise', 'surveys', 'the', 'technique', 'involved', 'using', 'the', '3d', 'colour', 'plane', 'izzw1w1w2', 'with', 'the', 'wise', 'w1', '34', 'micron', 'and', 'w2', '45', 'micron', 'bands', 'taking', 'the', 'place', 'of', 'the', 'usual', 'nir', 'j', 'band', 'to', 'help', 'decrease', 'stellar', 'dwarf', 'contamination', 'here', 'we', 'report', 'on', 'our', 'continued', 'search', 'for', '57z64', 'quasars', 'over', 'an', '2x', 'larger', 'area', 'of', '3577', 'sq', 'deg', 'of', 'the', 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1,803.01425 | On the Effectiveness of Simple Success-Based Parameter Selection
Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark
Problems | Despite significant empirical and theoretically supported evidence that
non-static parameter choices can be strongly beneficial in evolutionary
computation, the question how to best adjust parameter values plays only a
marginal role in contemporary research on discrete black-box optimization. This
has led to the unsatisfactory situation in which feedback-free parameter
selection rules such as the cooling schedule of Simulated Annealing are
predominant in state-of-the-art heuristics, while, at the same time, we
understand very well that such time-dependent selection rules can only perform
worse than adjustment rules that do take into account the evolution of the
optimization process. A number of adaptive and self-adaptive parameter control
strategies have been proposed in the literature, but did not (yet) make their
way to a broader public. A key obstacle seems to lie in their rather complex
update rules.
The purpose of our work is to demonstrate that high-performing online
parameter selection rules do not have to be very complicated. More precisely,
we experiment with a multiplicative, comparison-based update rule to adjust the
mutation probability of a (1+1)~Evolutionary Algorithm. We show that this
simple self-adjusting rule outperforms the best static unary unbiased black-box
algorithm on LeadingOnes, achieving an almost optimal speedup of about~$18\%$.
| cs.NE | despite significant empirical and theoretically supported evidence that nonstatic parameter choices can be strongly beneficial in evolutionary computation the question how to best adjust parameter values plays only a marginal role in contemporary research on discrete blackbox optimization this has led to the unsatisfactory situation in which feedbackfree parameter selection rules such as the cooling schedule of simulated annealing are predominant in stateoftheart heuristics while at the same time we understand very well that such timedependent selection rules can only perform worse than adjustment rules that do take into account the evolution of the optimization process a number of adaptive and selfadaptive parameter control strategies have been proposed in the literature but did not yet make their way to a broader public a key obstacle seems to lie in their rather complex update rules the purpose of our work is to demonstrate that highperforming online parameter selection rules do not have to be very complicated more precisely we experiment with a multiplicative comparisonbased update rule to adjust the mutation probability of a 11evolutionary algorithm we show that this simple selfadjusting rule outperforms the best static unary unbiased blackbox algorithm on leadingones achieving an almost optimal speedup of about18 | [['despite', 'significant', 'empirical', 'and', 'theoretically', 'supported', 'evidence', 'that', 'nonstatic', 'parameter', 'choices', 'can', 'be', 'strongly', 'beneficial', 'in', 'evolutionary', 'computation', 'the', 'question', 'how', 'to', 'best', 'adjust', 'parameter', 'values', 'plays', 'only', 'a', 'marginal', 'role', 'in', 'contemporary', 'research', 'on', 'discrete', 'blackbox', 'optimization', 'this', 'has', 'led', 'to', 'the', 'unsatisfactory', 'situation', 'in', 'which', 'feedbackfree', 'parameter', 'selection', 'rules', 'such', 'as', 'the', 'cooling', 'schedule', 'of', 'simulated', 'annealing', 'are', 'predominant', 'in', 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1,803.01426 | Brake wear (nano)particle characterization and toxicity on airway
epithelial cells in vitro | Particulate air pollution results from different sources, among which those
related to road traffic have a significant impact on human health.
Combustion-derived particles emitted by thermal engines have been incriminated
and are now better controlled. In contrast, non-exhaust emission sources
related to car wear and degradation processes are not yet regulated. Here we
report on brake wear particles (BWP) harvested in two test facilities operating
in France, providing samples from different braking systems and driving/testing
conditions. Using a combination of light scattering, X-ray fluorescence,
optical and electron microscopy, the particle size and elemental composition
are revealed. The BWP are shown to be in the nano- to micrometer range and to
have a low carbonaceous content (6%), iron and copper being the main components
(> 40%). To evaluate the toxicity potential of its nano-sized fraction, brake
wear nanoparticles are isolated by sonication, filtration and
ultra-centrifugation techniques, leading to stable colloidal dispersions. A
significant outcome of this study is that the nano-sized fraction represents
26% by mass of the initial BWP. Human bronchial epithelial cells (Calu-3) are
used as relevant target cells to investigate their cytotoxicity. We observe a
clear short-term loss of viability associated to reactive oxygen species
generation, but with limited pro-inflammatory effects. On an actual
cell-deposited mass-dose basis, the cytotoxicity of the nanosized fraction is
similar to that of BWP, suggesting that the cytotoxicity is particle size
independent. To conclude, brake wear dust contains substantial amount of
metallic nanoparticles exhibiting toxicity for lung cells, and should warrant
further consideration.
| physics.app-ph physics.bio-ph | particulate air pollution results from different sources among which those related to road traffic have a significant impact on human health combustionderived particles emitted by thermal engines have been incriminated and are now better controlled in contrast nonexhaust emission sources related to car wear and degradation processes are not yet regulated here we report on brake wear particles bwp harvested in two test facilities operating in france providing samples from different braking systems and drivingtesting conditions using a combination of light scattering xray fluorescence optical and electron microscopy the particle size and elemental composition are revealed the bwp are shown to be in the nano to micrometer range and to have a low carbonaceous content 6 iron and copper being the main components 40 to evaluate the toxicity potential of its nanosized fraction brake wear nanoparticles are isolated by sonication filtration and ultracentrifugation techniques leading to stable colloidal dispersions a significant outcome of this study is that the nanosized fraction represents 26 by mass of the initial bwp human bronchial epithelial cells calu3 are used as relevant target cells to investigate their cytotoxicity we observe a clear shortterm loss of viability associated to reactive oxygen species generation but with limited proinflammatory effects on an actual celldeposited massdose basis the cytotoxicity of the nanosized fraction is similar to that of bwp suggesting that the cytotoxicity is particle size independent to conclude brake wear dust contains substantial amount of metallic nanoparticles exhibiting toxicity for lung cells and should warrant further consideration | [['particulate', 'air', 'pollution', 'results', 'from', 'different', 'sources', 'among', 'which', 'those', 'related', 'to', 'road', 'traffic', 'have', 'a', 'significant', 'impact', 'on', 'human', 'health', 'combustionderived', 'particles', 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1,803.01427 | Lie-Poisson integrators | In this paper, we discuss the geometric integration of hamiltonian systems on
Poisson manifolds, in particular, in the case, when the Poisson structure is
induced by a Lie algebra, that is, it is a Lie-Poisson structure.
A Hamiltonian system on a Poisson manifold $(P, \Pi)$ is a smooth manifold
$P$ equipped with a bivector field $\Pi$ satisfying $[\Pi, \Pi]=0$ (Jacobi
identity), inducing the Poisson bracket on $C^{\infty}(P)$, $\{f, g\}\equiv
\Pi(df, dg)$ where $f, g\in C^{\infty}(P)$. For any $f\in C^{\infty}(P)$ the
Hamiltonian vector field is defined by $X_f(g)=\{g, f\}$. The Hamiltonian
vector fields $X_f$ generate an integrable generalized distribution on $P$ and
the leaves of this foliation are symplectic. The flow of any hamiltonian vector
field preserves the Poisson structure, it fixes each leaf and the hamiltonian
itself is a first integral.
It is important to characterize numerical methods preserving some of these
fundamental properties of the hamiltonian flow on Poisson manifolds (geometric
integrators). We discuss the difficulties of deriving these Poisson methods
using standard techniques and we present some modern approaches to the problem.
| math.NA math-ph math.DG math.MP math.SG | in this paper we discuss the geometric integration of hamiltonian systems on poisson manifolds in particular in the case when the poisson structure is induced by a lie algebra that is it is a liepoisson structure a hamiltonian system on a poisson manifold p pi is a smooth manifold p equipped with a bivector field pi satisfying pi pi0 jacobi identity inducing the poisson bracket on cinftyp f gequiv pidf dg where f gin cinftyp for any fin cinftyp the hamiltonian vector field is defined by x_fgg f the hamiltonian vector fields x_f generate an integrable generalized distribution on p and the leaves of this foliation are symplectic the flow of any hamiltonian vector field preserves the poisson structure it fixes each leaf and the hamiltonian itself is a first integral it is important to characterize numerical methods preserving some of these fundamental properties of the hamiltonian flow on poisson manifolds geometric integrators we discuss the difficulties of deriving these poisson methods using standard techniques and we present some modern approaches to the problem | [['in', 'this', 'paper', 'we', 'discuss', 'the', 'geometric', 'integration', 'of', 'hamiltonian', 'systems', 'on', 'poisson', 'manifolds', 'in', 'particular', 'in', 'the', 'case', 'when', 'the', 'poisson', 'structure', 'is', 'induced', 'by', 'a', 'lie', 'algebra', 'that', 'is', 'it', 'is', 'a', 'liepoisson', 'structure', 'a', 'hamiltonian', 'system', 'on', 'a', 'poisson', 'manifold', 'p', 'pi', 'is', 'a', 'smooth', 'manifold', 'p', 'equipped', 'with', 'a', 'bivector', 'field', 'pi', 'satisfying', 'pi', 'pi0', 'jacobi', 'identity', 'inducing', 'the', 'poisson', 'bracket', 'on', 'cinftyp', 'f', 'gequiv', 'pidf', 'dg', 'where', 'f', 'gin', 'cinftyp', 'for', 'any', 'fin', 'cinftyp', 'the', 'hamiltonian', 'vector', 'field', 'is', 'defined', 'by', 'x_fgg', 'f', 'the', 'hamiltonian', 'vector', 'fields', 'x_f', 'generate', 'an', 'integrable', 'generalized', 'distribution', 'on', 'p', 'and', 'the', 'leaves', 'of', 'this', 'foliation', 'are', 'symplectic', 'the', 'flow', 'of', 'any', 'hamiltonian', 'vector', 'field', 'preserves', 'the', 'poisson', 'structure', 'it', 'fixes', 'each', 'leaf', 'and', 'the', 'hamiltonian', 'itself', 'is', 'a', 'first', 'integral', 'it', 'is', 'important', 'to', 'characterize', 'numerical', 'methods', 'preserving', 'some', 'of', 'these', 'fundamental', 'properties', 'of', 'the', 'hamiltonian', 'flow', 'on', 'poisson', 'manifolds', 'geometric', 'integrators', 'we', 'discuss', 'the', 'difficulties', 'of', 'deriving', 'these', 'poisson', 'methods', 'using', 'standard', 'techniques', 'and', 'we', 'present', 'some', 'modern', 'approaches', 'to', 'the', 'problem']] | [-0.2259076422156203, 0.08709126010039336, -0.09847439501873152, 0.048675561668946904, -0.11991790361799906, -0.13556328948944546, -0.0503796000110776, 0.36087696527152563, -0.3398254464575371, -0.19312797326778688, 0.04208944371406011, -0.2444176633983071, -0.19305726636720952, 0.16617778321690208, -0.08889579130769816, 0.040987616915561714, 0.09165632027894431, 0.13198207702005801, -0.12204926536236768, -0.21504147339011218, 0.4182685403543156, 0.0036678878193840297, 0.21006602047790968, -0.022366206948158093, 0.16437695240842173, 0.018043742175376434, 0.019981687451268784, -0.022026138162229557, -0.1528474826470703, 0.09421334043077496, 0.2229893998213134, 0.05773824871636841, 0.21460636306505346, -0.3583455035831173, -0.18136839334972116, 0.13535079766988084, 0.09688883537134199, 0.022126486665720858, 0.005999473594318599, -0.29960570408459103, 0.11439084188016348, -0.11220867086884154, -0.14544478623023213, -0.09941790065035051, 0.02197882110661784, 0.009125614615609371, -0.25515150716007134, 0.01296946924818723, 0.12320515572778383, 0.09360865977874329, -0.06382478425566238, -0.11814473627533136, -0.053721723236078614, 0.04521791231334561, -0.011596379053053382, 0.10732599618833859, 0.12674700894100635, -0.06779781568674967, -0.1013636295440022, 0.41433583972109267, -0.04154461452826792, -0.33038294012996716, 0.094885099389547, -0.1089937127531008, -0.2036337257758173, 0.11619485772572198, 0.1066088060750951, 0.1269562559305192, -0.1214242787534394, 0.24141537194136195, -0.03969454325107468, 0.05033371697564414, 0.05090640454693849, -0.05978866897287865, 0.12076449378252808, 0.11562935736024925, 0.13706135184796484, 0.07171456511186566, -0.04035937955581345, -0.10802650399679362, -0.3484975097235292, -0.18269048218729061, -0.16128774017886108, 0.15184995907542922, -0.11674894180650035, -0.17192149011764762, 0.382726032990789, 0.07009665817455497, 0.19928675928954467, 0.04141918499547945, 0.2703091894698784, 0.1785062347044004, 0.029284441004355632, 0.08762601268380274, 0.10455202228196106, 0.23284420719489368, 0.045192943904873766, -0.17162225799172098, -0.032522184885618664, 0.12834231269296778] |
1,803.01428 | Effective-energy universality approach describing total multiplicity
centrality dependence in heavy-ion collisions | The recently proposed participant dissipating effective-energy approach is
applied to describe the dependence on centrality of the multiplicity of charged
particles measured in heavy-ion collisions at the collision energies up to the
highest LHC energy of 5 TeV. The effective-energy approach relates multihadron
production in different types of collisions, by combining, under the proper
collision energy scaling, the constituent quark picture with Landau
relativistic hydrodynamics. The measurements are shown to be well described in
terms of the centrality-dependent effective energy of participants and an
explanation of the differences in the measurements at RHIC and LHC are given by
means of the recently introduced hypothesis of the energy-balanced limiting
fragmentation scaling. A similarity between the centrality data and the data
from most central collisions is proposed pointing to the central character of
participant interactions independent of centrality. The findings complement our
recent investigations of the similar midrapidity pseudorapidity density
measurements extending the description to the full pseudorapidity range in view
of the considered similarity of multihadron production in nucleon interactions
and heavy-ion collisions.
| hep-ph hep-ex nucl-ex nucl-th | the recently proposed participant dissipating effectiveenergy approach is applied to describe the dependence on centrality of the multiplicity of charged particles measured in heavyion collisions at the collision energies up to the highest lhc energy of 5 tev the effectiveenergy approach relates multihadron production in different types of collisions by combining under the proper collision energy scaling the constituent quark picture with landau relativistic hydrodynamics the measurements are shown to be well described in terms of the centralitydependent effective energy of participants and an explanation of the differences in the measurements at rhic and lhc are given by means of the recently introduced hypothesis of the energybalanced limiting fragmentation scaling a similarity between the centrality data and the data from most central collisions is proposed pointing to the central character of participant interactions independent of centrality the findings complement our recent investigations of the similar midrapidity pseudorapidity density measurements extending the description to the full pseudorapidity range in view of the considered similarity of multihadron production in nucleon interactions and heavyion collisions | [['the', 'recently', 'proposed', 'participant', 'dissipating', 'effectiveenergy', 'approach', 'is', 'applied', 'to', 'describe', 'the', 'dependence', 'on', 'centrality', 'of', 'the', 'multiplicity', 'of', 'charged', 'particles', 'measured', 'in', 'heavyion', 'collisions', 'at', 'the', 'collision', 'energies', 'up', 'to', 'the', 'highest', 'lhc', 'energy', 'of', '5', 'tev', 'the', 'effectiveenergy', 'approach', 'relates', 'multihadron', 'production', 'in', 'different', 'types', 'of', 'collisions', 'by', 'combining', 'under', 'the', 'proper', 'collision', 'energy', 'scaling', 'the', 'constituent', 'quark', 'picture', 'with', 'landau', 'relativistic', 'hydrodynamics', 'the', 'measurements', 'are', 'shown', 'to', 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'interactions', 'and', 'heavyion', 'collisions']] | [-0.07717173473471586, 0.17908126329483673, -0.1741871362623791, 0.09838176121106805, 0.021642004876115988, -0.0530548625203326, -0.05023057136662998, 0.30802450186118135, -0.204578901920603, -0.33237045291854544, -0.08479790408353777, -0.35530992134387585, 0.053843565260839846, 0.13775075235685638, 0.04199274401397033, 0.1066651793344347, 0.10975022932926062, 0.04887017606335237, -0.03359072372523071, -0.2033157234464577, 0.31909572801059977, 0.15349019977783915, 0.26724971041928025, 0.1786979614891691, 0.07242165110953867, 0.08321562404392374, -0.06911044069877176, 0.040984383762575856, -0.1339424687064101, 0.10396753121416581, 0.28302671456794787, 0.0547519766249363, 0.18798806503425938, -0.34689145663016757, -0.16178868494272708, 0.0853356292287191, 0.12200665943118809, 0.06668014776741349, -0.06072422411891112, -0.27838302997677306, 0.10274361355804167, -0.2525568265193088, -0.13859291426596493, -0.041940376388929716, 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1,803.01429 | Classification of the Horndeski cosmologies via Noether Symmetries | Adopting Noether point symmetries, we classify and integrate dynamical
systems coming from Horndeski cosmologies. The method is particularly effective
both to select the form of Horndeski models and to derive exact cosmological
solutions. Starting from the Lagrangians selected by the Noether symmetries, it
is possible to derive several modified theories of gravity like $f(R)$ gravity,
Brans-Dicke gravity, string inspired gravity and so on. In any case, exact
solutions are found out.
| gr-qc astro-ph.CO hep-th | adopting noether point symmetries we classify and integrate dynamical systems coming from horndeski cosmologies the method is particularly effective both to select the form of horndeski models and to derive exact cosmological solutions starting from the lagrangians selected by the noether symmetries it is possible to derive several modified theories of gravity like fr gravity bransdicke gravity string inspired gravity and so on in any case exact solutions are found out | [['adopting', 'noether', 'point', 'symmetries', 'we', 'classify', 'and', 'integrate', 'dynamical', 'systems', 'coming', 'from', 'horndeski', 'cosmologies', 'the', 'method', 'is', 'particularly', 'effective', 'both', 'to', 'select', 'the', 'form', 'of', 'horndeski', 'models', 'and', 'to', 'derive', 'exact', 'cosmological', 'solutions', 'starting', 'from', 'the', 'lagrangians', 'selected', 'by', 'the', 'noether', 'symmetries', 'it', 'is', 'possible', 'to', 'derive', 'several', 'modified', 'theories', 'of', 'gravity', 'like', 'fr', 'gravity', 'bransdicke', 'gravity', 'string', 'inspired', 'gravity', 'and', 'so', 'on', 'in', 'any', 'case', 'exact', 'solutions', 'are', 'found', 'out']] | [-0.14529857314913205, 0.03102466722451885, -0.1252545734054186, 0.1759101402335866, -0.1766548763540849, -0.2318392156665935, -0.03204715589035145, 0.24797117910806982, -0.20216827159485137, -0.31269407033605473, 0.055479649078874836, -0.2891531831742277, -0.15626840804978995, 0.11934625476100286, -0.036025446485465684, 0.01521561513851646, -0.06839867614039129, 0.051158853517976444, -0.11640063369020322, -0.2474096380698849, 0.3774294770309623, 0.05345170716689506, 0.21471845262854453, -0.09672422871701944, 0.11709177022485036, -0.09477714668880675, -0.04814192089973621, 0.058807602939261516, -0.19888351270010773, 0.04253483886345172, 0.2334149677434409, 0.1397862750708952, 0.1524228093437326, -0.4234515205025673, -0.3091502249057234, 0.07758814143672796, 0.14596441196618784, 0.25104312459662764, -0.046311304650374384, -0.3241622345226909, 0.05174555948896097, -0.18941571810086008, -0.13840050080423832, -0.13853475561654063, 0.016271334902291566, -0.04873850012958889, -0.21498954456142136, 0.07425838694571596, -0.048925110357436415, -0.038045216325513075, -0.11414361564101468, -0.09386888539917032, -0.05579082056565184, 0.03802493206736907, 0.1646304862232695, 0.026544865520841534, 0.1379383798741119, -0.1644624099200985, -0.09582654279197605, 0.4775887350355026, -0.08832912104250207, -0.2604804185914322, 0.1739121809680487, -0.09776744811179143, -0.19839147809551846, 0.024490962565784723, 0.08921646235615645, 0.19120405844911198, -0.219759526721556, 0.2166799588537198, 0.06037998106330633, 0.0828085196631613, 0.13329108239768048, 0.011325360357787617, 0.3296917878143804, 0.037735540085327875, 0.0362006823571635, 0.0899881842598634, 0.008012480630447537, -0.14551798187435644, -0.3769581313572929, -0.0791260671972389, -0.0963414149083407, 0.08445766000536231, -0.15734978802571842, -0.13776897323567053, 0.33926465325910127, 0.20666806670036955, 0.035797464628507136, 0.12682123040504964, 0.15691857879430476, 0.09887625628583868, 0.0759527856930041, 0.08434143821171051, 0.3201944803897764, 0.14731697045909373, 0.06429145922785966, -0.2168626567598065, -0.1417800746136673, 0.14081691724287582] |
1,803.0143 | On Rigid Origami I: Piecewise-planar Paper with Straight-line Creases | We develop a theoretical framework for rigid origami, and show how this
framework can be used to connect rigid origami and results from cognate areas,
such as the rigidity theory, graph theory, linkage folding and computer
science. First, we give definitions on important concepts in rigid origami,
then focus on how to describe the configuration space of a creased paper. The
shape and 0-connectedness of the configuration space are analyzed using
algebraic, geometric and numeric methods, where the key results from each
method are gathered and reviewed.
| math.MG | we develop a theoretical framework for rigid origami and show how this framework can be used to connect rigid origami and results from cognate areas such as the rigidity theory graph theory linkage folding and computer science first we give definitions on important concepts in rigid origami then focus on how to describe the configuration space of a creased paper the shape and 0connectedness of the configuration space are analyzed using algebraic geometric and numeric methods where the key results from each method are gathered and reviewed | [['we', 'develop', 'a', 'theoretical', 'framework', 'for', 'rigid', 'origami', 'and', 'show', 'how', 'this', 'framework', 'can', 'be', 'used', 'to', 'connect', 'rigid', 'origami', 'and', 'results', 'from', 'cognate', 'areas', 'such', 'as', 'the', 'rigidity', 'theory', 'graph', 'theory', 'linkage', 'folding', 'and', 'computer', 'science', 'first', 'we', 'give', 'definitions', 'on', 'important', 'concepts', 'in', 'rigid', 'origami', 'then', 'focus', 'on', 'how', 'to', 'describe', 'the', 'configuration', 'space', 'of', 'a', 'creased', 'paper', 'the', 'shape', 'and', '0connectedness', 'of', 'the', 'configuration', 'space', 'are', 'analyzed', 'using', 'algebraic', 'geometric', 'and', 'numeric', 'methods', 'where', 'the', 'key', 'results', 'from', 'each', 'method', 'are', 'gathered', 'and', 'reviewed']] | [-0.04065888373960936, 0.0685923253835807, -0.10597658123777703, 0.07096820002351346, -0.09400501616060906, -0.11685296833558484, -0.004281628742911528, 0.3995755749732949, -0.3102405025233883, -0.31257797447358104, 0.09587989608231975, -0.20881006194191964, -0.2890001524911197, 0.20317580139394417, -0.13139873973722027, 0.04891267705838694, 0.07797088859018025, 0.03712444891070211, -0.03555360895603202, -0.202963030582015, 0.33184450900528667, 0.002304445648955744, 0.2658081682355598, 0.05479303514720266, 0.08491484460632079, 0.042923131513647565, -0.03459566181287343, 0.07898536653645055, -0.2612959708162952, 0.23530432393471168, 0.28958232218648716, 0.16785033740276514, 0.21580386131482068, -0.48314443811081176, -0.18015018641017377, 0.025499125948002518, 0.11021957150660455, 0.12727949198681948, -0.034475544768082365, -0.276551814067589, 0.09404545787960118, -0.15082173467597512, -0.10957972644719967, -0.137453107683118, 0.003585972947739931, 0.05364286210821118, -0.14718773535474441, -0.01822106575939891, 0.04553600729897965, 0.08590891344342814, -0.07506889883472129, -0.0998178041163767, -0.008591616699515386, 0.16633823095160255, 0.01620110775192463, 0.04172102407129958, 0.14937243769811684, -0.06858647610115018, -0.1597956473191897, 0.4144076454604781, 0.023590595374793508, -0.24140626625266187, 0.1907914881432039, -0.05966489358133702, -0.1923174556712945, 0.04634219818466971, 0.1952450390428651, 0.12292362770693767, -0.09856204720495572, 0.10290952905238238, -0.017024037024807617, 0.11650682738873848, 0.05132907124095445, -0.033223887965039806, 0.20685291096438155, 0.18900971997767513, 0.05478834408486998, 0.1551254123468277, -0.05240233153169758, -0.12113732160177342, -0.324136377247267, -0.13878602149549785, -0.16145906893964207, 0.003574511263692795, -0.06030796495771176, -0.16199185305036778, 0.391540628608836, 0.1407822272934894, 0.19889933894236766, 0.02996186860891189, 0.2972804000709466, -0.009021970125315927, 0.009683920035333655, 0.025082438761844884, 0.19880412191932284, 0.1370683867311062, 0.04482147376984358, -0.11923554196390648, -0.0009163828393401102, 0.10958621608699824] |
1,803.01431 | Design of a Low Voltage Analog-to-Digital Converter using Voltage
Controlled Stochastic Switching of Low Barrier Nanomagnets | The inherent stochasticity in many nano-scale devices makes them prospective
candidates for low-power computations. Such devices have been demonstrated to
exhibit probabilistic switching between two stable states to achieve stochastic
behavior. Recently, superparamagnetic nanomagnets (having low energy barrier EB
$\sim$ 1kT) have shown promise of achieving stochastic switching at GHz rates,
with very low currents. On the other hand, voltage-controlled switching of
nanomagnets through the Magneto-electric (ME) effect has shown further
improvements in energy efficiency. In this simulation paper, we first analyze
the stochastic switching characteristics of such super-paramagnetic nanomagnets
in a voltage-controlled spintronic device. We study the influence of external
bias on the switching behavior. Subsequently, we show that our proposed device
leverages the voltage controlled stochasticity in performing low-voltage 8-bit
analog to digital conversions. This eliminates the need for comparators, unlike
the Complementary Metal-Oxide Semiconductor (CMOS)-based flash
Analog-to-Digital converters (ADC). This device allows for a simple and compact
design which can potentially be applied in implementing sensors which desire
low voltage conversions.
| cs.ET | the inherent stochasticity in many nanoscale devices makes them prospective candidates for lowpower computations such devices have been demonstrated to exhibit probabilistic switching between two stable states to achieve stochastic behavior recently superparamagnetic nanomagnets having low energy barrier eb sim 1kt have shown promise of achieving stochastic switching at ghz rates with very low currents on the other hand voltagecontrolled switching of nanomagnets through the magnetoelectric me effect has shown further improvements in energy efficiency in this simulation paper we first analyze the stochastic switching characteristics of such superparamagnetic nanomagnets in a voltagecontrolled spintronic device we study the influence of external bias on the switching behavior subsequently we show that our proposed device leverages the voltage controlled stochasticity in performing lowvoltage 8bit analog to digital conversions this eliminates the need for comparators unlike the complementary metaloxide semiconductor cmosbased flash analogtodigital converters adc this device allows for a simple and compact design which can potentially be applied in implementing sensors which desire low voltage conversions | [['the', 'inherent', 'stochasticity', 'in', 'many', 'nanoscale', 'devices', 'makes', 'them', 'prospective', 'candidates', 'for', 'lowpower', 'computations', 'such', 'devices', 'have', 'been', 'demonstrated', 'to', 'exhibit', 'probabilistic', 'switching', 'between', 'two', 'stable', 'states', 'to', 'achieve', 'stochastic', 'behavior', 'recently', 'superparamagnetic', 'nanomagnets', 'having', 'low', 'energy', 'barrier', 'eb', 'sim', '1kt', 'have', 'shown', 'promise', 'of', 'achieving', 'stochastic', 'switching', 'at', 'ghz', 'rates', 'with', 'very', 'low', 'currents', 'on', 'the', 'other', 'hand', 'voltagecontrolled', 'switching', 'of', 'nanomagnets', 'through', 'the', 'magnetoelectric', 'me', 'effect', 'has', 'shown', 'further', 'improvements', 'in', 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1,803.01432 | Gersten weight structures for motivic homotopy categories; retracts of
cohomology of function fields, motivic dimensions, and coniveau spectral
sequences | For any cohomology theory $H$ that can be factorized through (the
Morel-Voevodsky's triangulated motivic homotopy category) $SH^{S^1}(k)$ we
establish the $SH^{S^1}(k)$-functoriality of coniveau spectral sequences for
$H$. We also prove: for any affine essentially smooth semi-local $S$ the Cousin
complex for $H^*(S)$ splits; if $H$ also factorizes through $SH^+(k)$ or
$DM(k)$, then this is also true for any primitive $S$. Moreover, the cohomology
of such an $S$ is a direct summand of the cohomology of any its open dense
subscheme. This is a vast generalization of the results of a previous paper.
In order to prove these results we consider certain triangulated categories
of motivic pro-spectra, and introduce Gersten weight structures for them. We
study in detail the notions of cohomological dimensions of scheme associated to
various categories of motivic pro-spectra; they are defined in terms of the
corresponding weight structures and count the number of non-zero Nisnevich
cohomology for sheaves in the hearts of orthogonal "homotopy" $t$-structures.
| math.AG math.KT | for any cohomology theory h that can be factorized through the morelvoevodskys triangulated motivic homotopy category shs1k we establish the shs1kfunctoriality of coniveau spectral sequences for h we also prove for any affine essentially smooth semilocal s the cousin complex for hs splits if h also factorizes through shk or dmk then this is also true for any primitive s moreover the cohomology of such an s is a direct summand of the cohomology of any its open dense subscheme this is a vast generalization of the results of a previous paper in order to prove these results we consider certain triangulated categories of motivic prospectra and introduce gersten weight structures for them we study in detail the notions of cohomological dimensions of scheme associated to various categories of motivic prospectra they are defined in terms of the corresponding weight structures and count the number of nonzero nisnevich cohomology for sheaves in the hearts of orthogonal homotopy tstructures | [['for', 'any', 'cohomology', 'theory', 'h', 'that', 'can', 'be', 'factorized', 'through', 'the', 'morelvoevodskys', 'triangulated', 'motivic', 'homotopy', 'category', 'shs1k', 'we', 'establish', 'the', 'shs1kfunctoriality', 'of', 'coniveau', 'spectral', 'sequences', 'for', 'h', 'we', 'also', 'prove', 'for', 'any', 'affine', 'essentially', 'smooth', 'semilocal', 's', 'the', 'cousin', 'complex', 'for', 'hs', 'splits', 'if', 'h', 'also', 'factorizes', 'through', 'shk', 'or', 'dmk', 'then', 'this', 'is', 'also', 'true', 'for', 'any', 'primitive', 's', 'moreover', 'the', 'cohomology', 'of', 'such', 'an', 's', 'is', 'a', 'direct', 'summand', 'of', 'the', 'cohomology', 'of', 'any', 'its', 'open', 'dense', 'subscheme', 'this', 'is', 'a', 'vast', 'generalization', 'of', 'the', 'results', 'of', 'a', 'previous', 'paper', 'in', 'order', 'to', 'prove', 'these', 'results', 'we', 'consider', 'certain', 'triangulated', 'categories', 'of', 'motivic', 'prospectra', 'and', 'introduce', 'gersten', 'weight', 'structures', 'for', 'them', 'we', 'study', 'in', 'detail', 'the', 'notions', 'of', 'cohomological', 'dimensions', 'of', 'scheme', 'associated', 'to', 'various', 'categories', 'of', 'motivic', 'prospectra', 'they', 'are', 'defined', 'in', 'terms', 'of', 'the', 'corresponding', 'weight', 'structures', 'and', 'count', 'the', 'number', 'of', 'nonzero', 'nisnevich', 'cohomology', 'for', 'sheaves', 'in', 'the', 'hearts', 'of', 'orthogonal', 'homotopy', 'tstructures']] | [-0.19203589351859707, 0.05902695274348028, -0.09562777572920403, 0.09020680133984663, -0.04718605214909006, -0.1170549677977434, -0.011891797638665408, 0.35876256620021874, -0.3822723947322139, -0.1825581825015923, 0.07324166350773363, -0.18083570447439948, -0.14403209222916466, 0.16484833027994356, -0.1903362644579596, -0.04423718043723896, 0.08401242393749551, 0.11977085689058861, -0.06575916444461864, -0.2941541101735754, 0.4485750422747328, -0.05329780498943411, 0.2071067687736034, 0.07520012071397968, 0.074471999413501, -0.0065272759231261145, -0.01928772754334391, -0.013496442662122158, -0.16777929463462035, 0.17173216059857693, 0.34456141890050507, 0.06922923258613221, 0.19341736941043144, -0.3634564727067183, -0.11621281953725535, 0.19608395983082935, 0.12928341632822338, 0.028408463881649554, 0.014801399325593732, -0.26936057158626425, 0.19385393342236057, -0.20632037988159424, -0.11741399398007883, -0.09445896479062355, 0.07899816407828042, 0.04138871687255465, -0.2501343756776828, -0.01930920389620438, 0.0698899562852696, 0.1148442773344122, -0.12107511772550285, -0.08010994537900655, -0.0973352896331702, 0.09363244272595367, -0.030800041356810536, 0.030020798955005236, 0.07930345856286107, -0.13537602308982363, -0.14438066579914915, 0.36000166076402634, -0.048431751638418064, -0.2001217272884857, 0.14464413637940127, -0.1341346651315689, -0.19672331912181854, 0.14260679127302212, -0.00021696903217488373, 0.18584109857702294, 0.012773140918654509, 0.19911816665971388, -0.12883457647433552, 0.07740561591792637, 0.11707924838694266, 0.04930833729210859, 0.1278017756989683, 0.07111631311738911, 0.061407125901239805, 0.1410592476358243, -0.035981172497812595, -0.02848551865034283, -0.3571098624274899, -0.263376009862464, -0.10657048543604712, 0.14239190010956895, -0.10090963263251186, -0.19925262232740912, 0.406926410564572, 0.07709550270392822, 0.20282796856899482, 0.15257037700249407, 0.24143555171441478, 0.05994675476820423, 0.04449470521649346, 0.013814732539825715, 0.11798802465021324, 0.21105084515725955, -0.03105443883060406, -0.09209833691980188, -0.022771672128911655, 0.22883907691814387] |
1,803.01433 | A continuation method for tensor complementarity problems | We introduce a Kojima-Megiddo-Mizuno type continuation method for solving
tensor complementarity problems. We show that there exists a bounded
continuation trajectory when the tensor is strictly semi-positive and any limit
point tracing the trajectory gives a solution of the tensor complementarity
problem. Moreover, when the tensor is strong strictly semi-positive, tracing
the trajectory will converge to the unique solution. Some numerical results are
given to illustrate the effectiveness of the method.
| math.OC | we introduce a kojimamegiddomizuno type continuation method for solving tensor complementarity problems we show that there exists a bounded continuation trajectory when the tensor is strictly semipositive and any limit point tracing the trajectory gives a solution of the tensor complementarity problem moreover when the tensor is strong strictly semipositive tracing the trajectory will converge to the unique solution some numerical results are given to illustrate the effectiveness of the method | [['we', 'introduce', 'a', 'kojimamegiddomizuno', 'type', 'continuation', 'method', 'for', 'solving', 'tensor', 'complementarity', 'problems', 'we', 'show', 'that', 'there', 'exists', 'a', 'bounded', 'continuation', 'trajectory', 'when', 'the', 'tensor', 'is', 'strictly', 'semipositive', 'and', 'any', 'limit', 'point', 'tracing', 'the', 'trajectory', 'gives', 'a', 'solution', 'of', 'the', 'tensor', 'complementarity', 'problem', 'moreover', 'when', 'the', 'tensor', 'is', 'strong', 'strictly', 'semipositive', 'tracing', 'the', 'trajectory', 'will', 'converge', 'to', 'the', 'unique', 'solution', 'some', 'numerical', 'results', 'are', 'given', 'to', 'illustrate', 'the', 'effectiveness', 'of', 'the', 'method']] | [-0.16316410824656485, 0.007501403608226351, -0.09523813660655703, 0.025662091470855686, -0.11689299972993987, -0.16844338839208442, -0.031186503052179303, 0.3584791396212365, -0.3279898766694324, -0.15874570134494986, 0.1474920804204885, -0.3180428689079625, -0.20534446195898845, 0.16804264967462845, -0.02717591456935874, 0.06642757620928542, 0.16592322424320238, 0.04634661943252597, -0.12449759384284594, -0.18235427189751396, 0.38898519591561387, 0.009818000027111598, 0.26148527433563556, 0.12377515605517796, 0.15358086467853616, -0.04367545627589737, 0.005896902177482843, 0.10384616536487426, -0.10141496019755973, 0.1135348440164567, 0.25437424517170126, 0.2411064290840711, 0.3162307090791208, -0.34967911301979, -0.1720829304174653, 0.17615574349516205, 0.11557938430591354, 0.09324141493000622, -0.07925664432612912, -0.26928128294114556, 0.15621530702337622, -0.1104428090687309, -0.183037478919141, -0.13626641242631843, -0.02373951668185847, -0.012910011410713195, -0.2954696093153741, 0.039500062992530206, 0.05841741484722921, -0.02456705514341593, -0.11677930186768727, -0.0868156352479543, 0.016764031244175776, 0.07426135342185651, 0.07962117310879487, 0.0717039475749646, 0.0928484939970076, -0.091340535985572, -0.10828246429030385, 0.37742630067680566, -0.0738491847046784, -0.32218658240245923, 0.14092032865488102, -0.1205824539065361, -0.09761401523303773, 0.12735639471294624, 0.07285399575983839, 0.1905633702075907, -0.07184918748555771, 0.1387755951037564, -0.0844520122744143, 0.13273502516635094, 0.05064615997751909, -0.04768735683257026, 0.15606503783326064, 0.12239334646479359, 0.18499291375545518, 0.15050496829207988, -0.009652396318103586, -0.14078628133450236, -0.36378033225025447, -0.1688453772770507, -0.18596051074564457, 0.08757255460202162, -0.13490673255021518, -0.18242084405251913, 0.37457328102817494, 0.14935233364480416, 0.1616722343256697, 0.14351468115845428, 0.3083983648219146, 0.15856233768697295, -0.01102416151136692, 0.10348732066340745, 0.2613044617917954, 0.15174687931846295, 0.08303629889685128, -0.20119620228984525, 0.036404740344733, 0.15374809489647825] |
1,803.01434 | Dynamical analysis of the circumprimary planet in the eccentric binary
system HD59686 | We present a detailed orbital and stability analysis of the HD~59686
binary-star planet system. HD~59686 is a single-lined moderately close ($a_{B}
= 13.6\,$AU) eccentric ($e_{B} = 0.73$) binary, where the primary is an evolved
K giant with mass $M = 1.9 M_{\odot}$ and the secondary is a star with a
minimum mass of $m_{B} = 0.53 M_{\odot}$. Additionally, on the basis of precise
radial velocity (RV) data a Jovian planet with a minimum mass of $m_p = 7
M_{\mathrm{Jup}}$, orbiting the primary on a nearly circular S-type orbit with
$e_p = 0.05$ and $a_p = 1.09\,$AU, has recently been announced. We investigate
large sets of orbital fits consistent with HD 59686's radial velocity data by
applying bootstrap and systematic grid-search techniques coupled with
self-consistent dynamical fitting. We perform long-term dynamical integrations
of these fits to constrain the permitted orbital configurations. We find that
if the binary and the planet in this system have prograde and aligned coplanar
orbits, there are narrow regions of stable orbital solutions locked in a
secular apsidal alignment with the angle between the periapses, $\Delta
\omega$, librating about $0^\circ$. We also test a large number of mutually
inclined dynamical models in an attempt to constrain the three-dimensional
orbital architecture. We find that for nearly coplanar and retrograde orbits
with mutual inclination $145^\circ \lesssim \Delta i \leq 180^\circ$, the
system is fully stable for a large range of orbital solutions.
| astro-ph.EP | we present a detailed orbital and stability analysis of the hd59686 binarystar planet system hd59686 is a singlelined moderately close a_b 136au eccentric e_b 073 binary where the primary is an evolved k giant with mass m 19 m_odot and the secondary is a star with a minimum mass of m_b 053 m_odot additionally on the basis of precise radial velocity rv data a jovian planet with a minimum mass of m_p 7 m_mathrmjup orbiting the primary on a nearly circular stype orbit with e_p 005 and a_p 109au has recently been announced we investigate large sets of orbital fits consistent with hd 59686s radial velocity data by applying bootstrap and systematic gridsearch techniques coupled with selfconsistent dynamical fitting we perform longterm dynamical integrations of these fits to constrain the permitted orbital configurations we find that if the binary and the planet in this system have prograde and aligned coplanar orbits there are narrow regions of stable orbital solutions locked in a secular apsidal alignment with the angle between the periapses delta omega librating about 0circ we also test a large number of mutually inclined dynamical models in an attempt to constrain the threedimensional orbital architecture we find that for nearly coplanar and retrograde orbits with mutual inclination 145circ lesssim delta i leq 180circ the system is fully stable for a large range of orbital solutions | [['we', 'present', 'a', 'detailed', 'orbital', 'and', 'stability', 'analysis', 'of', 'the', 'hd59686', 'binarystar', 'planet', 'system', 'hd59686', 'is', 'a', 'singlelined', 'moderately', 'close', 'a_b', '136au', 'eccentric', 'e_b', '073', 'binary', 'where', 'the', 'primary', 'is', 'an', 'evolved', 'k', 'giant', 'with', 'mass', 'm', '19', 'm_odot', 'and', 'the', 'secondary', 'is', 'a', 'star', 'with', 'a', 'minimum', 'mass', 'of', 'm_b', '053', 'm_odot', 'additionally', 'on', 'the', 'basis', 'of', 'precise', 'radial', 'velocity', 'rv', 'data', 'a', 'jovian', 'planet', 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1,803.01435 | Primitive values of quadratic polynomials in a finite field | We prove that for all $q>211$, there always exists a primitive root $g$ in
the finite field $\mathbb{F}_{q}$ such that $Q(g)$ is also a primitive root,
where $Q(x)= ax^2 + bx + c$ is a quadratic polynomial with $a, b, c\in
\mathbb{F}_{q}$ such that $b^{2} - 4ac \neq 0$.
| math.NT | we prove that for all q211 there always exists a primitive root g in the finite field mathbbf_q such that qg is also a primitive root where qx ax2 bx c is a quadratic polynomial with a b cin mathbbf_q such that b2 4ac neq 0 | [['we', 'prove', 'that', 'for', 'all', 'q211', 'there', 'always', 'exists', 'a', 'primitive', 'root', 'g', 'in', 'the', 'finite', 'field', 'mathbbf_q', 'such', 'that', 'qg', 'is', 'also', 'a', 'primitive', 'root', 'where', 'qx', 'ax2', 'bx', 'c', 'is', 'a', 'quadratic', 'polynomial', 'with', 'a', 'b', 'cin', 'mathbbf_q', 'such', 'that', 'b2', '4ac', 'neq', '0']] | [-0.27555142016046574, 0.15070105290247335, -0.0389367978192038, -0.006977540125242538, -0.0609648815718376, -0.2574277004847924, -0.04639079293443097, 0.3195664023359617, -0.39481804139084287, -0.07361598597425553, 0.025199423572565945, -0.3022898213730918, -0.15300154745475286, 0.17235728945686585, -0.021718896304567654, -0.017511566686961386, -0.010972490306529734, 0.198460536946853, -0.05929182985694044, -0.2577084315733777, 0.2830081452512079, -0.15355842800603972, 0.08642103256036839, 0.04463690229588085, 0.12552544507715438, -0.03611361946289738, 0.1405190530543526, 0.030380156222316955, -0.17321010864996222, -0.08387796845701005, 0.33132297802302574, 0.14236546232778993, 0.3031775900731898, -0.2679731500024597, -0.14228315158850616, 0.2906291912206345, 0.17985915146354173, -0.05621105958190229, -0.085089961038385, -0.10203696025742424, 0.2556544621914832, -0.17405116639824378, -0.14163997953550683, 0.008478254969749187, 0.19760656389149112, 0.025020224766598806, -0.41437885434263283, -0.002420229511982244, 0.12747345827519893, 0.18657859872198768, 0.007364529226389196, -0.2619330005306337, -0.01430849176314142, 0.009870143048465252, -0.06554845452515615, 0.22270174219997393, -0.01606968780979514, -0.08932930500143105, -0.02618909674282703, 0.4198461756110191, -0.10760208090974224, -0.23437090694076484, 0.060081820283085105, -0.18990547619760037, -0.1924730493583613, 0.09295940697710547, 0.06534630215416352, 0.12786404349737698, 0.007829316560592917, 0.30069702979591156, -0.17534677847805952, 0.13146990163044797, 0.04537827972736624, -0.056982839635262884, 0.10582951795465002, -0.021986294822353456, 0.05870054931276374, 0.069227953420745, -0.002785212836331791, 0.02559849482236637, -0.42948300341765083, -0.1913608855800703, -0.1879299943878626, 0.20763015027623624, -0.1588739350748559, -0.2000608688136304, 0.30468168084820113, 0.09326450169189937, 0.14537085067066882, 0.11473035560920834, 0.193654764472093, 0.10568030356532998, 0.08177152442513033, 0.16155396637817224, 0.06620417369736566, 0.12060973587342434, -0.03392148270375199, -0.18312966755280893, 0.00234348661162787, 0.11555314641445875] |
1,803.01436 | Gradient Bounds for Kolmogorov Type Diffusions | We study gradient bounds and other functional inequalities for the diffusion
semigroup generated by Kolmogorov type operators. The focus is on two different
methods: coupling techniques and generalized $\Gamma$-calculus techniques. The
advantages and drawbacks of each of these methods are discussed.
| math.PR math.AP math.DG | we study gradient bounds and other functional inequalities for the diffusion semigroup generated by kolmogorov type operators the focus is on two different methods coupling techniques and generalized gammacalculus techniques the advantages and drawbacks of each of these methods are discussed | [['we', 'study', 'gradient', 'bounds', 'and', 'other', 'functional', 'inequalities', 'for', 'the', 'diffusion', 'semigroup', 'generated', 'by', 'kolmogorov', 'type', 'operators', 'the', 'focus', 'is', 'on', 'two', 'different', 'methods', 'coupling', 'techniques', 'and', 'generalized', 'gammacalculus', 'techniques', 'the', 'advantages', 'and', 'drawbacks', 'of', 'each', 'of', 'these', 'methods', 'are', 'discussed']] | [-0.06041744032238678, 0.08264970413704471, -0.05691109983841094, 0.14076294589549213, -0.07796421579494164, -0.19182353373616934, -0.009844460229321225, 0.3638244400300631, -0.335570338023145, -0.21666439397760281, 0.1598429778795235, -0.3247889487481699, -0.16457287301650134, 0.27388069149470184, -0.050855094964457, 0.0836661760127399, 0.04742379704626595, -0.00370719429196381, -0.14708406503153285, -0.2561911514892084, 0.4094579784971912, -0.05246745160406047, 0.3256207139730999, 0.06914818474296026, 0.10492440878708915, -0.06008502674039181, -0.1141134432130834, 0.036733485417576824, -0.19878308075230297, 0.20750742741269854, 0.204961423557706, 0.1409644951430581, 0.3312610113629844, -0.45463956951549866, -0.23612828623140003, 0.07605417037564444, 0.10858347969947428, 0.059007460228735355, -0.047538413907537554, -0.28504303988160157, 0.07585789112192465, -0.14152122815934623, -0.08276841719066952, -0.11010449120729435, -0.048017413468986025, 0.13470875857420628, -0.2506686769789312, 0.06563945684763717, 0.09147165947389312, 0.050592890012123415, -0.0478741694468914, -0.193606250351522, 0.056085450381676595, 0.07584409395278227, 0.07605060691400091, -0.08650047358738758, 0.11761641539860426, -0.07691091079855474, -0.22055730606406565, 0.27914889025070316, -0.08862872596648408, -0.2620551110040851, 0.20714167569105219, -0.05681658235219557, -0.16793004029271444, 0.02971320787853584, 0.12332786609441405, 0.1665771236506904, -0.14986925433594278, 0.14588921679121375, 0.05266328689801257, 0.05202329340504437, 0.020119494406460988, 0.07326951364009845, 0.026951124505480616, 0.09955852069869274, 0.07169932690335483, 0.0846933671401064, -0.059604105988244824, -0.11091147190550478, -0.266643477830945, -0.1302498847973056, -0.167331983312601, -0.053634865959061355, -0.13549580172779005, -0.12524824602836063, 0.39313322700923536, 0.13621355838528493, 0.12844104110831167, 0.04187287615112415, 0.30962869753243355, 0.15974428211679545, 0.055697071615879126, 0.04765764993002138, 0.1921652944633601, 0.19143284153670254, 0.07663131202003215, -0.21088746806220493, 0.04673970611084525, 0.21796621005732295] |
1,803.01437 | The radius of a typical-mass neutron star and chiral effective field
theory | We calculate neutron star masses and radii from equations of state based on
recent high-quality chiral nucleon-nucleon potentials up to fifth order of the
chiral expansion and the leading chiral three- nucleon force. Our focus is on
the radius of a 1.4 M_{Sun} neutron star, for which we report predictions that
are consistent with the most recent constraints. We also show the full M(R)
relations up to their respective maximum masses. Beyond the densities for which
microscopic predictions are derived from chiral forces, the equations of state
are obtained via polytropic continuations. However, the radius of a 1.4 M_{Sun}
neutron star is nearly insensitive to the high-density extrapolation.
| nucl-th | we calculate neutron star masses and radii from equations of state based on recent highquality chiral nucleonnucleon potentials up to fifth order of the chiral expansion and the leading chiral three nucleon force our focus is on the radius of a 14 m_sun neutron star for which we report predictions that are consistent with the most recent constraints we also show the full mr relations up to their respective maximum masses beyond the densities for which microscopic predictions are derived from chiral forces the equations of state are obtained via polytropic continuations however the radius of a 14 m_sun neutron star is nearly insensitive to the highdensity extrapolation | [['we', 'calculate', 'neutron', 'star', 'masses', 'and', 'radii', 'from', 'equations', 'of', 'state', 'based', 'on', 'recent', 'highquality', 'chiral', 'nucleonnucleon', 'potentials', 'up', 'to', 'fifth', 'order', 'of', 'the', 'chiral', 'expansion', 'and', 'the', 'leading', 'chiral', 'three', 'nucleon', 'force', 'our', 'focus', 'is', 'on', 'the', 'radius', 'of', 'a', '14', 'm_sun', 'neutron', 'star', 'for', 'which', 'we', 'report', 'predictions', 'that', 'are', 'consistent', 'with', 'the', 'most', 'recent', 'constraints', 'we', 'also', 'show', 'the', 'full', 'mr', 'relations', 'up', 'to', 'their', 'respective', 'maximum', 'masses', 'beyond', 'the', 'densities', 'for', 'which', 'microscopic', 'predictions', 'are', 'derived', 'from', 'chiral', 'forces', 'the', 'equations', 'of', 'state', 'are', 'obtained', 'via', 'polytropic', 'continuations', 'however', 'the', 'radius', 'of', 'a', '14', 'm_sun', 'neutron', 'star', 'is', 'nearly', 'insensitive', 'to', 'the', 'highdensity', 'extrapolation']] | [-0.08962577645218482, 0.17229547464564718, -0.07877161202917772, 0.03889617930744188, -0.09312944660929066, -0.029094529510648164, 0.03618954548922678, 0.3335797930377777, -0.14239500504077618, -0.31997126183058655, 0.060131881097159175, -0.32840988350411254, -0.03332635823257819, 0.19418410594678587, 0.04646575935314306, 0.06841582627816091, 0.038419195504738365, 0.08296787439569554, -0.1484446964481052, -0.2118132317997084, 0.3635574762442115, -0.004762580635509005, 0.20583861955889948, 0.08620537633800672, 0.051807696211013804, -0.06362546745394529, -0.003469738695356581, -0.0354233480024117, -0.19801111848135877, 0.09349450018877785, 0.17032917550144097, 0.04530328972679046, 0.1333143805947017, -0.4457537220204594, -0.17390315790005303, 0.010816709207439865, 0.11372009794016506, 0.13741012526615695, -0.05504359354273657, -0.26822851478398124, 0.110868317782189, -0.24813575767567037, -0.17509176358753056, -0.09092341566078917, 0.03435177980335774, 0.06019509284373338, -0.2792352453150131, 0.1378381946250792, -0.004741468807440941, -0.0002442745716069584, -0.12750470937721226, -0.1693458153469557, -0.0422369181825262, 0.07915179046836716, 0.06031615741031365, 0.07061957291982791, 0.15116610237035072, -0.1790895399991078, -0.05740653471460704, 0.4139470149659448, -0.03847838144564001, -0.08223600813222152, 0.1722258936389591, -0.18343505321967382, -0.13119607676613937, 0.1344076842845728, 0.15658327674976102, 0.16392456508981046, -0.1936878687357185, 0.01068845051405434, -0.001663815309897203, 0.20306446935757305, 0.0812211410375312, 0.004682065957846741, 0.30387102618503076, 0.1524098113446531, 0.006164386506295866, 0.042203144079798624, -0.1361644993863862, -0.11802115714763878, -0.29390600543141504, -0.025959475733408774, -0.14907988119456503, 0.06040006218892005, -0.13858152138628713, -0.09966525978719194, 0.3193108995652033, 0.13581086080348878, 0.22793875574306757, 0.0801934162003885, 0.2844236074360432, 0.11282698084552842, 0.10798208420466701, 0.07493317732587457, 0.3427338877485858, 0.24601454774124754, 0.0644367946251468, -0.2693966821362092, -0.02010632304828269, 0.0652976772678947] |
1,803.01438 | High-Precision Measurement of Sine and Pulse Reference Signals using
Software-Defined Radio | This paper addresses simultaneous, high-precision measurement and analysis of
generic reference signals by using inexpensive commercial off-the-shelf
Software Defined Radio hardware. Sine reference signals are digitally
down-converted to baseband for the analysis of phase deviations. Hereby, we
compare the precision of the fixed-point hardware Digital Signal Processing
chain with a custom Single Instruction Multiple Data (SIMD) x86 floating-point
implementation. Pulse reference signals are analyzed by a software trigger that
precisely locates the time where the slope passes a certain threshold. The
measurement system is implemented and verified using the Universal Software
Radio Peripheral (USRP) N210 by Ettus Research LLC. Applying standard 10 MHz
and 1 PPS reference signals for testing, a measurement precision (standard
deviation) of 0.36 ps and 16.6 ps is obtained, respectively. In connection with
standard PC hardware, the system allows long-term acquisition and storage of
measurement data over several weeks. A comparison is given to the Dual Mixer
Time Difference (DMTD) and Time Interval Counter (TIC), which are
state-of-the-art measurement methods for sine and pulse signal analysis,
respectively. Furthermore, we show that our proposed USRP-based approach
outperforms measurements with a high-grade Digital Sampling Oscilloscope.
| eess.SP | this paper addresses simultaneous highprecision measurement and analysis of generic reference signals by using inexpensive commercial offtheshelf software defined radio hardware sine reference signals are digitally downconverted to baseband for the analysis of phase deviations hereby we compare the precision of the fixedpoint hardware digital signal processing chain with a custom single instruction multiple data simd x86 floatingpoint implementation pulse reference signals are analyzed by a software trigger that precisely locates the time where the slope passes a certain threshold the measurement system is implemented and verified using the universal software radio peripheral usrp n210 by ettus research llc applying standard 10 mhz and 1 pps reference signals for testing a measurement precision standard deviation of 036 ps and 166 ps is obtained respectively in connection with standard pc hardware the system allows longterm acquisition and storage of measurement data over several weeks a comparison is given to the dual mixer time difference dmtd and time interval counter tic which are stateoftheart measurement methods for sine and pulse signal analysis respectively furthermore we show that our proposed usrpbased approach outperforms measurements with a highgrade digital sampling oscilloscope | [['this', 'paper', 'addresses', 'simultaneous', 'highprecision', 'measurement', 'and', 'analysis', 'of', 'generic', 'reference', 'signals', 'by', 'using', 'inexpensive', 'commercial', 'offtheshelf', 'software', 'defined', 'radio', 'hardware', 'sine', 'reference', 'signals', 'are', 'digitally', 'downconverted', 'to', 'baseband', 'for', 'the', 'analysis', 'of', 'phase', 'deviations', 'hereby', 'we', 'compare', 'the', 'precision', 'of', 'the', 'fixedpoint', 'hardware', 'digital', 'signal', 'processing', 'chain', 'with', 'a', 'custom', 'single', 'instruction', 'multiple', 'data', 'simd', 'x86', 'floatingpoint', 'implementation', 'pulse', 'reference', 'signals', 'are', 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1,803.01439 | An Investigation of the Bound State Solutions of the Klein-Gordon
Equation for the Generalized Woods-Saxon Potential in Spin Symmetry and
Pseudo-spin Symmetry Limits | Recently, scattering of a Klein-Gordon particle in the presence of mixed
scalar-vector generalized symmetric Woods-Saxon potential was investigated for
the spin symmetric and the pseudo-spin symmetric limits in one spatial
dimension. In this manuscript, the bound state solutions of the Klein-Gordon
equation with mixed scalar-vector generalized symmetric Woods-Saxon potential
are examined analytically within the framework of spin and pseudo-spin symmetry
limits. We prove that the occurrence of bound state energy spectrum exists only
in the spin symmetric limit, while in the pseudo-spin symmetric limit, the
bound state spectrum does not exist. Besides the theoretical proof, the
Newton-Raphson numerical methods are used to calculate the bound state energy
spectra of a neutral Kaon particle, confined in a generalized symmetric
Woods-Saxon potential, energy well constituted with repulsive or attractive
surface interactions, for the spin and pseudo-spin symmetric limits,
respectively. Numerical results are consistent with the non-existence of the
bound state energy spectrum in the pseudo-spin symmetric limit.
| nucl-th | recently scattering of a kleingordon particle in the presence of mixed scalarvector generalized symmetric woodssaxon potential was investigated for the spin symmetric and the pseudospin symmetric limits in one spatial dimension in this manuscript the bound state solutions of the kleingordon equation with mixed scalarvector generalized symmetric woodssaxon potential are examined analytically within the framework of spin and pseudospin symmetry limits we prove that the occurrence of bound state energy spectrum exists only in the spin symmetric limit while in the pseudospin symmetric limit the bound state spectrum does not exist besides the theoretical proof the newtonraphson numerical methods are used to calculate the bound state energy spectra of a neutral kaon particle confined in a generalized symmetric woodssaxon potential energy well constituted with repulsive or attractive surface interactions for the spin and pseudospin symmetric limits respectively numerical results are consistent with the nonexistence of the bound state energy spectrum in the pseudospin symmetric limit | [['recently', 'scattering', 'of', 'a', 'kleingordon', 'particle', 'in', 'the', 'presence', 'of', 'mixed', 'scalarvector', 'generalized', 'symmetric', 'woodssaxon', 'potential', 'was', 'investigated', 'for', 'the', 'spin', 'symmetric', 'and', 'the', 'pseudospin', 'symmetric', 'limits', 'in', 'one', 'spatial', 'dimension', 'in', 'this', 'manuscript', 'the', 'bound', 'state', 'solutions', 'of', 'the', 'kleingordon', 'equation', 'with', 'mixed', 'scalarvector', 'generalized', 'symmetric', 'woodssaxon', 'potential', 'are', 'examined', 'analytically', 'within', 'the', 'framework', 'of', 'spin', 'and', 'pseudospin', 'symmetry', 'limits', 'we', 'prove', 'that', 'the', 'occurrence', 'of', 'bound', 'state', 'energy', 'spectrum', 'exists', 'only', 'in', 'the', 'spin', 'symmetric', 'limit', 'while', 'in', 'the', 'pseudospin', 'symmetric', 'limit', 'the', 'bound', 'state', 'spectrum', 'does', 'not', 'exist', 'besides', 'the', 'theoretical', 'proof', 'the', 'newtonraphson', 'numerical', 'methods', 'are', 'used', 'to', 'calculate', 'the', 'bound', 'state', 'energy', 'spectra', 'of', 'a', 'neutral', 'kaon', 'particle', 'confined', 'in', 'a', 'generalized', 'symmetric', 'woodssaxon', 'potential', 'energy', 'well', 'constituted', 'with', 'repulsive', 'or', 'attractive', 'surface', 'interactions', 'for', 'the', 'spin', 'and', 'pseudospin', 'symmetric', 'limits', 'respectively', 'numerical', 'results', 'are', 'consistent', 'with', 'the', 'nonexistence', 'of', 'the', 'bound', 'state', 'energy', 'spectrum', 'in', 'the', 'pseudospin', 'symmetric', 'limit']] | [-0.13703713691943595, 0.17452146898834936, -0.06712116464078727, 0.08961399385870825, -0.02897609768795871, -0.18137556930643417, -0.017663171343625553, 0.3101890127384855, -0.1917902274417781, -0.24906653221696615, 0.037204037619484286, -0.2762092339618492, -0.08360595089203167, 0.1183580226760598, 0.07284391049686219, 0.04516303533455357, 0.017003846829456666, 0.06820582758274771, -0.1083563577218522, -0.17548072104822965, 0.3331764595643167, 0.0012493270697192319, 0.2875202556951873, 0.12533369861926222, 0.05382869867007098, 0.04693525158049118, 0.07325879022659314, -0.051253564232179236, -0.13511235787436524, 0.07951586660102851, 0.20733023610026124, -0.009001345061997493, 0.15522989187269443, -0.4223283984570674, -0.19009867478312265, 0.15850441082110328, 0.1648488951756829, 0.1506456537067049, -0.08242792424505517, -0.34090093971500474, 0.006358976914517341, -0.22830373281312566, -0.26002423304824096, -0.07669686659749958, 0.00568080622883093, 0.032757676078472284, -0.26325107601681547, 0.17535622907021353, 0.08459552010566357, -0.014595394110637566, -0.16536757174218375, -0.17597028516953991, -0.08978077274176383, 0.007791854577108977, 0.04225215876196613, -0.030134738480011303, 0.06583938452700573, -0.12795946534400085, -0.11978422749727484, 0.36108582759756713, -0.09227232305152762, -0.28449048189626586, 0.11124070298767859, -0.13762964783837237, -0.07198316592182363, 0.1245226618743712, 0.14829107066616415, 0.12332932583146518, -0.12562573633847698, 0.16893426967491845, -0.07070560173371866, 0.14175514783334708, 0.08612796447480157, 0.06642571380662342, 0.20687887486551076, 0.11111893985540636, 0.0699242105286929, 0.13150542332910964, -0.08665603297131677, -0.21040070991842977, -0.2913641472617465, -0.10708246169228768, -0.2622866221282992, 0.05413285788278201, -0.07593262437402436, -0.1395810234720909, 0.4153484247684959, 0.03889592506832654, 0.09958492928755379, 0.02033034301693401, 0.2575260454075291, 0.16502378823295716, 0.01111874378196174, 0.07638953810918235, 0.29941778246673845, 0.2016536427181094, 0.05848898271909885, -0.2566991783855032, -0.03871834907500494, 0.05839012134219369] |
1,803.0144 | Hierarchical Modeling and Shrinkage for User Session Length Prediction
in Media Streaming | An important metric of users' satisfaction and engagement within on-line
streaming services is the user session length, i.e. the amount of time they
spend on a service continuously without interruption. Being able to predict
this value directly benefits the recommendation and ad pacing contexts in music
and video streaming services. Recent research has shown that predicting the
exact amount of time spent is highly nontrivial due to many external factors
for which a user can end a session, and the lack of predictive covariates. Most
of the other related literature on duration based user engagement has focused
on dwell time for websites, for search and display ads, mainly for post-click
satisfaction prediction or ad ranking.
In this work we present a novel framework inspired by hierarchical Bayesian
modeling to predict, at the moment of login, the amount of time a user will
spend in the streaming service. The time spent by a user on a platform depends
upon user-specific latent variables which are learned via hierarchical
shrinkage. Our framework enjoys theoretical guarantees and naturally
incorporates flexible parametric/nonparametric models on the covariates,
including models robust to outliers. Our proposal is found to outperform
state-of- the-art estimators in terms of efficiency and predictive performance
on real world public and private datasets.
| stat.ML cs.LG | an important metric of users satisfaction and engagement within online streaming services is the user session length ie the amount of time they spend on a service continuously without interruption being able to predict this value directly benefits the recommendation and ad pacing contexts in music and video streaming services recent research has shown that predicting the exact amount of time spent is highly nontrivial due to many external factors for which a user can end a session and the lack of predictive covariates most of the other related literature on duration based user engagement has focused on dwell time for websites for search and display ads mainly for postclick satisfaction prediction or ad ranking in this work we present a novel framework inspired by hierarchical bayesian modeling to predict at the moment of login the amount of time a user will spend in the streaming service the time spent by a user on a platform depends upon userspecific latent variables which are learned via hierarchical shrinkage our framework enjoys theoretical guarantees and naturally incorporates flexible parametricnonparametric models on the covariates including models robust to outliers our proposal is found to outperform stateof theart estimators in terms of efficiency and predictive performance on real world public and private datasets | [['an', 'important', 'metric', 'of', 'users', 'satisfaction', 'and', 'engagement', 'within', 'online', 'streaming', 'services', 'is', 'the', 'user', 'session', 'length', 'ie', 'the', 'amount', 'of', 'time', 'they', 'spend', 'on', 'a', 'service', 'continuously', 'without', 'interruption', 'being', 'able', 'to', 'predict', 'this', 'value', 'directly', 'benefits', 'the', 'recommendation', 'and', 'ad', 'pacing', 'contexts', 'in', 'music', 'and', 'video', 'streaming', 'services', 'recent', 'research', 'has', 'shown', 'that', 'predicting', 'the', 'exact', 'amount', 'of', 'time', 'spent', 'is', 'highly', 'nontrivial', 'due', 'to', 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1,803.01441 | On Antipodes Of Hom-Hopf algebras | In the recent definition of Hom-Hopf algebras the antipode S is the relative
Hominverse of the identity map with respect to the convolution product. We
observe that some fundamental properties of the antipode of Hopf algebras and
Hom-Hopf algebras, with the original definition, do not hold generally in the
new setting. We show that the antipode is a relative Hom-anti algebra and a
relative anti-coalgebra morphism. It is also relative Hom-unital, and relative
Hom-counital. Furthermore if the twisting maps of multiplications and
comultiplications are invertible then S is an anti-algebra and an
anti-coalgebra map. We show that any Hom-bialgebra map between two Hom-Hopf
algebras is a relative Hom-morphism of Hom-Hopf alegbras. Specially if the
corresponding twisting maps are all invertible then it is a Hom-Hopf algebra
map. If the Hom-Hopf algebra is commutative or cocommutative we observe that
S^2 is equal to the identity map in some sense. At the end we study the images
of primitive and group-like elements under the antipode.
| math.RA | in the recent definition of homhopf algebras the antipode s is the relative hominverse of the identity map with respect to the convolution product we observe that some fundamental properties of the antipode of hopf algebras and homhopf algebras with the original definition do not hold generally in the new setting we show that the antipode is a relative homanti algebra and a relative anticoalgebra morphism it is also relative homunital and relative homcounital furthermore if the twisting maps of multiplications and comultiplications are invertible then s is an antialgebra and an anticoalgebra map we show that any hombialgebra map between two homhopf algebras is a relative hommorphism of homhopf alegbras specially if the corresponding twisting maps are all invertible then it is a homhopf algebra map if the homhopf algebra is commutative or cocommutative we observe that s2 is equal to the identity map in some sense at the end we study the images of primitive and grouplike elements under the antipode | [['in', 'the', 'recent', 'definition', 'of', 'homhopf', 'algebras', 'the', 'antipode', 's', 'is', 'the', 'relative', 'hominverse', 'of', 'the', 'identity', 'map', 'with', 'respect', 'to', 'the', 'convolution', 'product', 'we', 'observe', 'that', 'some', 'fundamental', 'properties', 'of', 'the', 'antipode', 'of', 'hopf', 'algebras', 'and', 'homhopf', 'algebras', 'with', 'the', 'original', 'definition', 'do', 'not', 'hold', 'generally', 'in', 'the', 'new', 'setting', 'we', 'show', 'that', 'the', 'antipode', 'is', 'a', 'relative', 'homanti', 'algebra', 'and', 'a', 'relative', 'anticoalgebra', 'morphism', 'it', 'is', 'also', 'relative', 'homunital', 'and', 'relative', 'homcounital', 'furthermore', 'if', 'the', 'twisting', 'maps', 'of', 'multiplications', 'and', 'comultiplications', 'are', 'invertible', 'then', 's', 'is', 'an', 'antialgebra', 'and', 'an', 'anticoalgebra', 'map', 'we', 'show', 'that', 'any', 'hombialgebra', 'map', 'between', 'two', 'homhopf', 'algebras', 'is', 'a', 'relative', 'hommorphism', 'of', 'homhopf', 'alegbras', 'specially', 'if', 'the', 'corresponding', 'twisting', 'maps', 'are', 'all', 'invertible', 'then', 'it', 'is', 'a', 'homhopf', 'algebra', 'map', 'if', 'the', 'homhopf', 'algebra', 'is', 'commutative', 'or', 'cocommutative', 'we', 'observe', 'that', 's2', 'is', 'equal', 'to', 'the', 'identity', 'map', 'in', 'some', 'sense', 'at', 'the', 'end', 'we', 'study', 'the', 'images', 'of', 'primitive', 'and', 'grouplike', 'elements', 'under', 'the', 'antipode']] | [-0.1522039292199958, 0.06372257713622774, -0.060961829672657675, 0.06751538051833068, -0.09835088228386256, -0.15297010066888986, -0.047085929893317724, 0.4295076624280022, -0.44306192151721446, -0.15061264298743599, 0.11958702958203972, -0.2669682150286051, -0.1915771533840246, 0.16601914946635765, -0.1768995644644864, -0.09222819100569693, 0.0957823606898948, 0.1497251187541312, -0.15780521494847152, -0.22091582519783368, 0.41190307654680747, 0.014489975127000962, 0.22222474160333794, 0.022527406936616548, 0.1295383306640771, -0.03462668032115025, -0.02671536166341074, -0.006046121857399421, -0.1549039780622303, 0.09688276017625486, 0.22140280274794466, 0.10102116297930479, 0.1846153243692712, -0.31505649486977244, -0.0139317445336811, 0.1975239719113996, 0.11090087881011347, 0.023825972124693857, -0.0005965185411755116, -0.26537743196372066, 0.1297008155274295, -0.23488086612835046, -0.04721805664500402, -0.07321501084633412, 0.10751327951363618, -0.0014757000706008365, -0.2874842680990696, 0.006120743617347832, 0.1303299104838985, 0.11442806108464157, -0.0754897364355143, -0.03504939442200045, -0.11421481085821025, 0.11626177807038109, -0.08308005453117433, 0.07390577982239906, 0.14993110451426717, -0.10134492562332702, -0.10496960723276941, 0.3500319668121876, -0.040877176478745475, -0.21639581168851546, 0.13165014645407697, -0.21406961326081786, -0.1465038340478655, 0.07209739615359614, -0.01809706257716302, 0.10117978002996214, -0.056610778110822844, 0.18859050988685339, -0.159340041467259, 0.07830738701046475, 0.09519718232895097, 0.0013385874174174763, 0.13090249737424234, 0.041788277968448855, 0.10974684789806845, 0.13550890801294196, -0.006963174811173831, -0.005172840915169687, -0.3538262868119824, -0.23294295620233302, -0.06140115584862689, 0.09300135647016201, -0.08863293665419933, -0.15749938809463093, 0.3890778670267713, 0.17068713500329682, 0.2014053589093589, 0.09066234037520424, 0.23452677810865064, 0.09234969496967331, 0.11925497423489428, 0.04621257321728814, 0.15985074306034572, 0.27724607726258615, 0.011599274859913895, -0.12512886623942082, -0.024535213211821692, 0.19222515935318604] |
1,803.01442 | Stochastic Activation Pruning for Robust Adversarial Defense | Neural networks are known to be vulnerable to adversarial examples. Carefully
chosen perturbations to real images, while imperceptible to humans, induce
misclassification and threaten the reliability of deep learning systems in the
wild. To guard against adversarial examples, we take inspiration from game
theory and cast the problem as a minimax zero-sum game between the adversary
and the model. In general, for such games, the optimal strategy for both
players requires a stochastic policy, also known as a mixed strategy. In this
light, we propose Stochastic Activation Pruning (SAP), a mixed strategy for
adversarial defense. SAP prunes a random subset of activations (preferentially
pruning those with smaller magnitude) and scales up the survivors to
compensate. We can apply SAP to pretrained networks, including adversarially
trained models, without fine-tuning, providing robustness against adversarial
examples. Experiments demonstrate that SAP confers robustness against attacks,
increasing accuracy and preserving calibration.
| cs.LG stat.ML | neural networks are known to be vulnerable to adversarial examples carefully chosen perturbations to real images while imperceptible to humans induce misclassification and threaten the reliability of deep learning systems in the wild to guard against adversarial examples we take inspiration from game theory and cast the problem as a minimax zerosum game between the adversary and the model in general for such games the optimal strategy for both players requires a stochastic policy also known as a mixed strategy in this light we propose stochastic activation pruning sap a mixed strategy for adversarial defense sap prunes a random subset of activations preferentially pruning those with smaller magnitude and scales up the survivors to compensate we can apply sap to pretrained networks including adversarially trained models without finetuning providing robustness against adversarial examples experiments demonstrate that sap confers robustness against attacks increasing accuracy and preserving calibration | [['neural', 'networks', 'are', 'known', 'to', 'be', 'vulnerable', 'to', 'adversarial', 'examples', 'carefully', 'chosen', 'perturbations', 'to', 'real', 'images', 'while', 'imperceptible', 'to', 'humans', 'induce', 'misclassification', 'and', 'threaten', 'the', 'reliability', 'of', 'deep', 'learning', 'systems', 'in', 'the', 'wild', 'to', 'guard', 'against', 'adversarial', 'examples', 'we', 'take', 'inspiration', 'from', 'game', 'theory', 'and', 'cast', 'the', 'problem', 'as', 'a', 'minimax', 'zerosum', 'game', 'between', 'the', 'adversary', 'and', 'the', 'model', 'in', 'general', 'for', 'such', 'games', 'the', 'optimal', 'strategy', 'for', 'both', 'players', 'requires', 'a', 'stochastic', 'policy', 'also', 'known', 'as', 'a', 'mixed', 'strategy', 'in', 'this', 'light', 'we', 'propose', 'stochastic', 'activation', 'pruning', 'sap', 'a', 'mixed', 'strategy', 'for', 'adversarial', 'defense', 'sap', 'prunes', 'a', 'random', 'subset', 'of', 'activations', 'preferentially', 'pruning', 'those', 'with', 'smaller', 'magnitude', 'and', 'scales', 'up', 'the', 'survivors', 'to', 'compensate', 'we', 'can', 'apply', 'sap', 'to', 'pretrained', 'networks', 'including', 'adversarially', 'trained', 'models', 'without', 'finetuning', 'providing', 'robustness', 'against', 'adversarial', 'examples', 'experiments', 'demonstrate', 'that', 'sap', 'confers', 'robustness', 'against', 'attacks', 'increasing', 'accuracy', 'and', 'preserving', 'calibration']] | [-0.042668646743699704, 0.03467781789447755, -0.04174891727727723, 0.13424815402337517, -0.09831032779527037, -0.2709120132973137, 0.1122946134359378, 0.4271824124862427, -0.28934046273336633, -0.3238642270491803, 0.08918447173854387, -0.29357161252178915, -0.24400249307286248, 0.13060221547653184, -0.22097459331805475, 0.10954993132068074, 0.08277286464118794, -0.0022671341876920365, 0.04004930750922278, -0.343840755869105, 0.2923709634812676, 0.05717670885755916, 0.26640847766746395, -0.023330674592839325, 0.13852631666518953, -0.049717616283475125, 0.023925945545508438, 0.03497915222526413, -0.04059404756401208, 0.07364979626735264, 0.3105998750413899, 0.1896991577630939, 0.40541467382429064, -0.445681908793033, -0.23235689706172258, 0.17646323317464135, 0.10073476889663478, 0.18471683983927056, -0.06321916221449636, -0.3567260384427269, 0.158779757869213, -0.1762763117854675, -0.027240232015921646, -0.15910920410812512, -0.05838861954813083, -0.007221124960629473, -0.33176383025918715, -0.03799017256923971, 0.06790534992973808, 0.039940783530728864, -0.033903978737900416, -0.11901810420405962, -0.03880510535346319, 0.1457319562610443, 0.057414887577442016, 0.012270436038531056, 0.17731557178872395, -0.1709841778230764, -0.16778216573524557, 0.33110888502624347, -0.06687483422088195, -0.20533506514198363, 0.1676277799901795, 0.05184539709533628, -0.11417087150916252, 0.11438661815649638, 0.27981952683719463, 0.1282148452073795, -0.10422281478531659, -0.01453090462497155, -0.0021840511719147635, 0.1527331661471255, 0.08259941630818154, -0.003183414588270913, 0.11183885542104939, 0.22165338257455255, 0.11600063119421726, 0.19198174048326783, -0.0971663189822272, -0.13656856807918377, -0.22649641389869254, -0.029840835323876203, -0.14194028784380588, 0.004922028575056673, -0.131564359741476, -0.15986983410931155, 0.36762791834388897, 0.2360385927157987, 0.17635486000664022, 0.1850538472341986, 0.36148239617963157, -0.009867280748774847, 0.10538055700862346, 0.11588582622081883, 0.2056697343527148, 0.03422239192519082, 0.0857063580849782, -0.1750414137942206, 0.16476193375005196, 0.03410935204249666] |
1,803.01443 | Entanglement in finite quantum systems under twisted boundary conditions | In a recent publication, we have discussed the effects of boundary conditions
in finite quantum systems and their connection with symmetries. Focusing on the
one-dimensional Hubbard Hamiltonian under twisted boundary conditions, we have
shown that properties, such as the ground-state and gap energies, converge
faster to the thermodynamical limit ($L \rightarrow \infty$) if a special
torsion $\Theta^*$ is adjusted to ensure particle-hole symmetry. Complementary
to the previous research, the present paper extends our analysis to a key
quantity for understanding correlations in many-body systems: the entanglement.
Specifically, we investigate the average single-site entanglement $\langle S_j
\rangle$ as a function of the coupling $U/t$ in Hubbard chains with up to $L=8$
sites and further examine the dependence of the per-site ground-state
$\epsilon_0$ on the torsion $\Theta$ in different coupling regimes. We discuss
the scaling of $\epsilon_0$ and $\langle S_j \rangle$ under $\Theta^*$ and
analyse their convergence to Bethe Ansatz solution of the infinite Hubbard
Hamiltonian. Additionally, we describe the exact diagonalization procedure used
in our numerical calculations and show analytical calculations for the
case-study of a trimer.
| cond-mat.str-el | in a recent publication we have discussed the effects of boundary conditions in finite quantum systems and their connection with symmetries focusing on the onedimensional hubbard hamiltonian under twisted boundary conditions we have shown that properties such as the groundstate and gap energies converge faster to the thermodynamical limit l rightarrow infty if a special torsion theta is adjusted to ensure particlehole symmetry complementary to the previous research the present paper extends our analysis to a key quantity for understanding correlations in manybody systems the entanglement specifically we investigate the average singlesite entanglement langle s_j rangle as a function of the coupling ut in hubbard chains with up to l8 sites and further examine the dependence of the persite groundstate epsilon_0 on the torsion theta in different coupling regimes we discuss the scaling of epsilon_0 and langle s_j rangle under theta and analyse their convergence to bethe ansatz solution of the infinite hubbard hamiltonian additionally we describe the exact diagonalization procedure used in our numerical calculations and show analytical calculations for the casestudy of a trimer | [['in', 'a', 'recent', 'publication', 'we', 'have', 'discussed', 'the', 'effects', 'of', 'boundary', 'conditions', 'in', 'finite', 'quantum', 'systems', 'and', 'their', 'connection', 'with', 'symmetries', 'focusing', 'on', 'the', 'onedimensional', 'hubbard', 'hamiltonian', 'under', 'twisted', 'boundary', 'conditions', 'we', 'have', 'shown', 'that', 'properties', 'such', 'as', 'the', 'groundstate', 'and', 'gap', 'energies', 'converge', 'faster', 'to', 'the', 'thermodynamical', 'limit', 'l', 'rightarrow', 'infty', 'if', 'a', 'special', 'torsion', 'theta', 'is', 'adjusted', 'to', 'ensure', 'particlehole', 'symmetry', 'complementary', 'to', 'the', 'previous', 'research', 'the', 'present', 'paper', 'extends', 'our', 'analysis', 'to', 'a', 'key', 'quantity', 'for', 'understanding', 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1,803.01444 | Stellar and AGN feedback in isolated early-type galaxies: the role in
regulating star formation and ISM properties | Understanding how galaxies maintain the inefficiency of star formation with
physically self-consistent models is a central problem for galaxy evolution.
Although numerous theoretical models have been proposed in recent decades, the
debate still exists. By means of high-resolution two-dimensional hydrodynamical
simulations, we study the three feedback effects (the stellar wind heating, SNe
feedback, and AGN feedback) in suppressing star formation activities on the
evolution of early-type galaxies with different stellar masses. AGN feedback
models are updated based on \citet{Yuan2018}. The gas sources comes exclusively
from the mass losses of dying low-mass stars for most of our models. We find
that SNe feedback can keep star formation at a significantly low level for low
mass elliptical galaxies for a cosmological evolution time. For the high mass
galaxies, AGN feedback can efficiently offset the radiative cooling and thus
regulate the star formation activities. Such a suppression of star formation is
extremely efficient in the inner region of the galaxies. AGB heating cannot
account for this suppression for low and high mass galaxies. The X-ray
temperature $T_{\rm X}$ and luminosity $L_{\rm X}$ of hot plasma can be in
agreement with the observed data with the inclusion of effective feedback
processes. These results thus suggest that we can use $T_{\rm X}$ and $L_{\rm
X}$ to probe the role of different feedback processes. The inclusion of
additional gas sources can make the mass scale between SNe and AGN feedback
dominating in suppressing star formation decrease to an observationally
inferred value of a few $10^{10}~M_{\odot}$.
| astro-ph.HE astro-ph.GA | understanding how galaxies maintain the inefficiency of star formation with physically selfconsistent models is a central problem for galaxy evolution although numerous theoretical models have been proposed in recent decades the debate still exists by means of highresolution twodimensional hydrodynamical simulations we study the three feedback effects the stellar wind heating sne feedback and agn feedback in suppressing star formation activities on the evolution of earlytype galaxies with different stellar masses agn feedback models are updated based on citetyuan2018 the gas sources comes exclusively from the mass losses of dying lowmass stars for most of our models we find that sne feedback can keep star formation at a significantly low level for low mass elliptical galaxies for a cosmological evolution time for the high mass galaxies agn feedback can efficiently offset the radiative cooling and thus regulate the star formation activities such a suppression of star formation is extremely efficient in the inner region of the galaxies agb heating cannot account for this suppression for low and high mass galaxies the xray temperature t_rm x and luminosity l_rm x of hot plasma can be in agreement with the observed data with the inclusion of effective feedback processes these results thus suggest that we can use t_rm x and l_rm x to probe the role of different feedback processes the inclusion of additional gas sources can make the mass scale between sne and agn feedback dominating in suppressing star formation decrease to an observationally inferred value of a few 1010m_odot | [['understanding', 'how', 'galaxies', 'maintain', 'the', 'inefficiency', 'of', 'star', 'formation', 'with', 'physically', 'selfconsistent', 'models', 'is', 'a', 'central', 'problem', 'for', 'galaxy', 'evolution', 'although', 'numerous', 'theoretical', 'models', 'have', 'been', 'proposed', 'in', 'recent', 'decades', 'the', 'debate', 'still', 'exists', 'by', 'means', 'of', 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1,803.01445 | Universal (and Existential) Nulls | Incomplete Information research is quite mature when it comes to so called
{\em existential nulls}, where an existential null is a value stored in the
database, representing an unknown object. For some reason {\em universal
nulls}, that is, values representing {\em all} possible objects, have received
almost no attention. We remedy the situation in this paper, by showing that a
suitable finite representation mechanism, called {\em Star Cylinders}, handling
universal nulls can be developed based on the {\em Cylindric Set Algebra} of
Henkin, Monk and Tarski. We provide a finitary version of the cylindric set
algebra, called {\em Cylindric Star Algebra}, and show that our star-cylinders
are closed under this algebra. Moreover, we show that any {\em First Order
Relational Calculus} query over databases containing universal nulls can be
translated into an equivalent expression in our cylindric star-algebra, and
vice versa, in time polynomial in the size of the database.
The representation mechanism is then extended to {\em Naive Star Cylinders},
which are star-cylinders allowing existential nulls in addition to universal
nulls. For positive queries (with universal quantification), the well known
naive evaluation technique can still be applied on the existential nulls,
thereby allowing polynomial time evaluation of certain answers on databases
containing both universal and existential nulls. If precise answers are
required, certain answer evaluation with universal and existential nulls
remains in coNP. Note that the problem is coNP-hard, already for positive
existential queries and databases with only existential nulls. If inequalities
$\neg(x_i\approx x_j)$ are allowed, reasoning over existential databases is
known to be $\Pi^p_2$-complete, and it remains in $\Pi^p_2$ when universal
nulls and full first order queries are allowed.
| cs.DB | incomplete information research is quite mature when it comes to so called em existential nulls where an existential null is a value stored in the database representing an unknown object for some reason em universal nulls that is values representing em all possible objects have received almost no attention we remedy the situation in this paper by showing that a suitable finite representation mechanism called em star cylinders handling universal nulls can be developed based on the em cylindric set algebra of henkin monk and tarski we provide a finitary version of the cylindric set algebra called em cylindric star algebra and show that our starcylinders are closed under this algebra moreover we show that any em first order relational calculus query over databases containing universal nulls can be translated into an equivalent expression in our cylindric staralgebra and vice versa in time polynomial in the size of the database the representation mechanism is then extended to em naive star cylinders which are starcylinders allowing existential nulls in addition to universal nulls for positive queries with universal quantification the well known naive evaluation technique can still be applied on the existential nulls thereby allowing polynomial time evaluation of certain answers on databases containing both universal and existential nulls if precise answers are required certain answer evaluation with universal and existential nulls remains in conp note that the problem is conphard already for positive existential queries and databases with only existential nulls if inequalities negx_iapprox x_j are allowed reasoning over existential databases is known to be pip_2complete and it remains in pip_2 when universal nulls and full first order queries are allowed | [['incomplete', 'information', 'research', 'is', 'quite', 'mature', 'when', 'it', 'comes', 'to', 'so', 'called', 'em', 'existential', 'nulls', 'where', 'an', 'existential', 'null', 'is', 'a', 'value', 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1,803.01446 | Learning to Sequence Robot Behaviors for Visual Navigation | Recent literature in the robotics community has focused on learning robot
behaviors that abstract out lower-level details of robot control. To fully
leverage the efficacy of such behaviors, it is necessary to select and sequence
them to achieve a given task. In this paper, we present an approach to both
learn and sequence robot behaviors, applied to the problem of visual navigation
of mobile robots. We construct a layered representation of control policies
composed of low- level behaviors and a meta-level policy. The low-level
behaviors enable the robot to locomote in a particular environment while
avoiding obstacles, and the meta-level policy actively selects the low-level
behavior most appropriate for the current situation based purely on visual
feedback. We demonstrate the effectiveness of our method on three simulated
robot navigation tasks: a legged hexapod robot which must successfully traverse
varying terrain, a wheeled robot which must navigate a maze-like course while
avoiding obstacles, and finally a wheeled robot navigating in the presence of
dynamic obstacles. We show that by learning control policies in a layered
manner, we gain the ability to successfully traverse new compound environments
composed of distinct sub-environments, and outperform both the low-level
behaviors in their respective sub-environments, as well as a hand-crafted
selection of low-level policies on these compound environments.
| cs.RO | recent literature in the robotics community has focused on learning robot behaviors that abstract out lowerlevel details of robot control to fully leverage the efficacy of such behaviors it is necessary to select and sequence them to achieve a given task in this paper we present an approach to both learn and sequence robot behaviors applied to the problem of visual navigation of mobile robots we construct a layered representation of control policies composed of low level behaviors and a metalevel policy the lowlevel behaviors enable the robot to locomote in a particular environment while avoiding obstacles and the metalevel policy actively selects the lowlevel behavior most appropriate for the current situation based purely on visual feedback we demonstrate the effectiveness of our method on three simulated robot navigation tasks a legged hexapod robot which must successfully traverse varying terrain a wheeled robot which must navigate a mazelike course while avoiding obstacles and finally a wheeled robot navigating in the presence of dynamic obstacles we show that by learning control policies in a layered manner we gain the ability to successfully traverse new compound environments composed of distinct subenvironments and outperform both the lowlevel behaviors in their respective subenvironments as well as a handcrafted selection of lowlevel policies on these compound environments | [['recent', 'literature', 'in', 'the', 'robotics', 'community', 'has', 'focused', 'on', 'learning', 'robot', 'behaviors', 'that', 'abstract', 'out', 'lowerlevel', 'details', 'of', 'robot', 'control', 'to', 'fully', 'leverage', 'the', 'efficacy', 'of', 'such', 'behaviors', 'it', 'is', 'necessary', 'to', 'select', 'and', 'sequence', 'them', 'to', 'achieve', 'a', 'given', 'task', 'in', 'this', 'paper', 'we', 'present', 'an', 'approach', 'to', 'both', 'learn', 'and', 'sequence', 'robot', 'behaviors', 'applied', 'to', 'the', 'problem', 'of', 'visual', 'navigation', 'of', 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1,803.01447 | Blending Mathematical and Physical Negative-ness | Expressing physics problems in the form of a mathematical model is one of the
most important stages in the problem-solving process. Particularly in algebraic
symbolization, understanding the meanings of signs and being able to manipulate
them becomes a challenging task for students, especially when more than two
elements in the mathematical expression could carry a negative sign. We use
Conceptual Blending theory to investigate how students attribute emergent
meaning to the signs and how they articulate different signs in their algebraic
symbolization. The data for this research is drawn from oral exams of students
enrolled in upper-division physics. The results shed light on students'
understanding of algebraic symbols and their competence in formulating and
manipulating them.
| physics.ed-ph | expressing physics problems in the form of a mathematical model is one of the most important stages in the problemsolving process particularly in algebraic symbolization understanding the meanings of signs and being able to manipulate them becomes a challenging task for students especially when more than two elements in the mathematical expression could carry a negative sign we use conceptual blending theory to investigate how students attribute emergent meaning to the signs and how they articulate different signs in their algebraic symbolization the data for this research is drawn from oral exams of students enrolled in upperdivision physics the results shed light on students understanding of algebraic symbols and their competence in formulating and manipulating them | [['expressing', 'physics', 'problems', 'in', 'the', 'form', 'of', 'a', 'mathematical', 'model', 'is', 'one', 'of', 'the', 'most', 'important', 'stages', 'in', 'the', 'problemsolving', 'process', 'particularly', 'in', 'algebraic', 'symbolization', 'understanding', 'the', 'meanings', 'of', 'signs', 'and', 'being', 'able', 'to', 'manipulate', 'them', 'becomes', 'a', 'challenging', 'task', 'for', 'students', 'especially', 'when', 'more', 'than', 'two', 'elements', 'in', 'the', 'mathematical', 'expression', 'could', 'carry', 'a', 'negative', 'sign', 'we', 'use', 'conceptual', 'blending', 'theory', 'to', 'investigate', 'how', 'students', 'attribute', 'emergent', 'meaning', 'to', 'the', 'signs', 'and', 'how', 'they', 'articulate', 'different', 'signs', 'in', 'their', 'algebraic', 'symbolization', 'the', 'data', 'for', 'this', 'research', 'is', 'drawn', 'from', 'oral', 'exams', 'of', 'students', 'enrolled', 'in', 'upperdivision', 'physics', 'the', 'results', 'shed', 'light', 'on', 'students', 'understanding', 'of', 'algebraic', 'symbols', 'and', 'their', 'competence', 'in', 'formulating', 'and', 'manipulating', 'them']] | [-0.04645481218628039, 0.09473973048192545, -0.14068415268035284, 0.1370692637038262, -0.18865800692483076, -0.17584571771821456, 0.06036249843751209, 0.3613611211486418, -0.2571690268543597, -0.35699268251432686, 0.0492795946022319, -0.28192120941821486, -0.19859754927616952, 0.19631300979607, -0.09772489413394239, -0.024573212275723125, 0.04311738848979264, 0.047286506870697284, -0.05059589961531636, -0.2688131319752348, 0.32072584325415565, 0.029941885475197744, 0.2736449920540226, 0.05079571437090635, 0.06632706991111828, -0.010019780196859661, -0.08459017065715985, -0.03074957474018447, -0.0546325791222224, 0.17909093739480936, 0.4106307137307936, 0.18831801732825437, 0.352484814638015, -0.47591208801444235, -0.14242795134838349, 0.06111644985051906, 0.12004787013424432, 0.1085198845730388, -0.05620994547280134, -0.2774646450155254, 0.03476973640298921, -0.11445447100840252, -0.10020936203439086, -0.07533155843326501, 0.037251794151353386, -0.06412437225788317, -0.16739821603826793, 0.0035952600602317474, 0.0801490656369173, 0.1575536715460877, -0.058611219744840314, -0.14717645367210055, 0.038337403539054356, 0.22031183549577313, 0.07757477567140776, -0.0143673666592302, 0.12984299476274513, -0.24771920657226945, -0.13602633223515645, 0.4273477603906187, 0.040022594445652995, -0.21243331658429113, 0.21637563137859428, -0.1365471760042871, -0.13492927075150937, 0.04090551178348411, 0.22256358574016083, 0.09040393048078464, -0.14914155027948034, 0.018843091050853376, 0.01639020422088175, 0.1512383403836605, 0.06834629862890418, 0.005960983356685731, 0.2571589643585271, 0.1430695700952944, -0.05692176813468466, 0.0888646172825247, 0.019188593327898757, -0.1133045089342792, -0.2529080922169418, -0.18705254351792472, -0.10535196626181553, 0.043757217861952837, -0.04170384001867958, -0.1237778246707829, 0.4289567835111139, 0.21454284029434725, 0.14597267038586073, -0.007524902386398151, 0.2651147737713723, 0.08083770787423669, 0.039273846131781566, 0.020616536168682646, 0.1825501699650917, 0.11326784178100784, 0.1544788984455377, -0.18497211754057108, 0.1356510629552288, 0.018297474518225623] |
1,803.01448 | Tree dimension in verification of constrained Horn clauses | In this paper, we show how the notion of tree dimension can be used in the
verification of constrained Horn clauses (CHCs). The dimension of a tree is a
numerical measure of its branching complexity and the concept here applies to
Horn clause derivation trees. Derivation trees of dimension zero correspond to
derivations using linear CHCs, while trees of higher dimension arise from
derivations using non-linear CHCs. We show how to instrument CHCs predicates
with an extra argument for the dimension, allowing a CHC verifier to reason
about bounds on the dimension of derivations. Given a set of CHCs $P$, we
define a transformation of $P$ yielding a dimension bounded set of CHCs
$P^{\leq{k}}$. The set of derivations for $P^{\leq{k}}$ consists of the
derivations for $P$ that have dimension at most $k$. We also show how to
construct a set of clauses denoted $P^{>{k}}$ whose derivations have dimension
exceeding $k$. We then present algorithms using these constructions to
decompose a CHC verification problem. One variation of this decomposition
considers derivations of successively increasing dimension. The paper includes
descriptions of implementations and experimental results. Under consideration
for publication in Theory and Practice of Logic Programming (TPLP).
| cs.LO | in this paper we show how the notion of tree dimension can be used in the verification of constrained horn clauses chcs the dimension of a tree is a numerical measure of its branching complexity and the concept here applies to horn clause derivation trees derivation trees of dimension zero correspond to derivations using linear chcs while trees of higher dimension arise from derivations using nonlinear chcs we show how to instrument chcs predicates with an extra argument for the dimension allowing a chc verifier to reason about bounds on the dimension of derivations given a set of chcs p we define a transformation of p yielding a dimension bounded set of chcs pleqk the set of derivations for pleqk consists of the derivations for p that have dimension at most k we also show how to construct a set of clauses denoted pk whose derivations have dimension exceeding k we then present algorithms using these constructions to decompose a chc verification problem one variation of this decomposition considers derivations of successively increasing dimension the paper includes descriptions of implementations and experimental results under consideration for publication in theory and practice of logic programming tplp | [['in', 'this', 'paper', 'we', 'show', 'how', 'the', 'notion', 'of', 'tree', 'dimension', 'can', 'be', 'used', 'in', 'the', 'verification', 'of', 'constrained', 'horn', 'clauses', 'chcs', 'the', 'dimension', 'of', 'a', 'tree', 'is', 'a', 'numerical', 'measure', 'of', 'its', 'branching', 'complexity', 'and', 'the', 'concept', 'here', 'applies', 'to', 'horn', 'clause', 'derivation', 'trees', 'derivation', 'trees', 'of', 'dimension', 'zero', 'correspond', 'to', 'derivations', 'using', 'linear', 'chcs', 'while', 'trees', 'of', 'higher', 'dimension', 'arise', 'from', 'derivations', 'using', 'nonlinear', 'chcs', 'we', 'show', 'how', 'to', 'instrument', 'chcs', 'predicates', 'with', 'an', 'extra', 'argument', 'for', 'the', 'dimension', 'allowing', 'a', 'chc', 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1,803.01449 | Deep Continuous Clustering | Clustering high-dimensional datasets is hard because interpoint distances
become less informative in high-dimensional spaces. We present a clustering
algorithm that performs nonlinear dimensionality reduction and clustering
jointly. The data is embedded into a lower-dimensional space by a deep
autoencoder. The autoencoder is optimized as part of the clustering process.
The resulting network produces clustered data. The presented approach does not
rely on prior knowledge of the number of ground-truth clusters. Joint nonlinear
dimensionality reduction and clustering are formulated as optimization of a
global continuous objective. We thus avoid discrete reconfigurations of the
objective that characterize prior clustering algorithms. Experiments on
datasets from multiple domains demonstrate that the presented algorithm
outperforms state-of-the-art clustering schemes, including recent methods that
use deep networks.
| cs.LG cs.CV | clustering highdimensional datasets is hard because interpoint distances become less informative in highdimensional spaces we present a clustering algorithm that performs nonlinear dimensionality reduction and clustering jointly the data is embedded into a lowerdimensional space by a deep autoencoder the autoencoder is optimized as part of the clustering process the resulting network produces clustered data the presented approach does not rely on prior knowledge of the number of groundtruth clusters joint nonlinear dimensionality reduction and clustering are formulated as optimization of a global continuous objective we thus avoid discrete reconfigurations of the objective that characterize prior clustering algorithms experiments on datasets from multiple domains demonstrate that the presented algorithm outperforms stateoftheart clustering schemes including recent methods that use deep networks | [['clustering', 'highdimensional', 'datasets', 'is', 'hard', 'because', 'interpoint', 'distances', 'become', 'less', 'informative', 'in', 'highdimensional', 'spaces', 'we', 'present', 'a', 'clustering', 'algorithm', 'that', 'performs', 'nonlinear', 'dimensionality', 'reduction', 'and', 'clustering', 'jointly', 'the', 'data', 'is', 'embedded', 'into', 'a', 'lowerdimensional', 'space', 'by', 'a', 'deep', 'autoencoder', 'the', 'autoencoder', 'is', 'optimized', 'as', 'part', 'of', 'the', 'clustering', 'process', 'the', 'resulting', 'network', 'produces', 'clustered', 'data', 'the', 'presented', 'approach', 'does', 'not', 'rely', 'on', 'prior', 'knowledge', 'of', 'the', 'number', 'of', 'groundtruth', 'clusters', 'joint', 'nonlinear', 'dimensionality', 'reduction', 'and', 'clustering', 'are', 'formulated', 'as', 'optimization', 'of', 'a', 'global', 'continuous', 'objective', 'we', 'thus', 'avoid', 'discrete', 'reconfigurations', 'of', 'the', 'objective', 'that', 'characterize', 'prior', 'clustering', 'algorithms', 'experiments', 'on', 'datasets', 'from', 'multiple', 'domains', 'demonstrate', 'that', 'the', 'presented', 'algorithm', 'outperforms', 'stateoftheart', 'clustering', 'schemes', 'including', 'recent', 'methods', 'that', 'use', 'deep', 'networks']] | [-0.07524339068525782, -0.04316786755031596, -0.11452452742572253, 0.11904097666418541, -0.11942821918637492, -0.13868891744253536, -0.0005983656058864047, 0.45821420329933366, -0.28019158785852294, -0.3198488807072863, 0.10181409733971426, -0.25353903201563904, -0.21170630955602973, 0.16746518960765874, -0.09514930003788322, 0.09549368204704176, 0.15932504596033445, 0.002564176583352188, -0.07355285489563054, -0.3210327532423738, 0.33223611215556353, 0.05069415246786472, 0.3745376156604228, -0.07025829277311763, 0.13710583470916995, 0.033621264109388, -0.09359248109685722, 0.054815975036035525, -0.03941648168765823, 0.17618590079800925, 0.3167270343905936, 0.24413208030940345, 0.3500328688125592, -0.3835194727871567, -0.27873560558073224, 0.13050733289370933, 0.16685754067342107, 0.09787857666209068, -0.017147132403139646, -0.3064490417328974, 0.04525623465500151, -0.09658664999490914, 0.028579501640827707, -0.1838063478625069, -0.05750096875320499, 0.011387340802078446, -0.2999036505701952, 0.12462699167857257, 0.07388221418126098, -0.021904305547165374, -0.06371429044520482, -0.1432896334018248, 0.003994350030552596, 0.08512547254795208, -0.0009227555422209358, 0.05405728803792347, 0.1376893507714461, -0.1263692249970821, -0.15386886384609777, 0.34400039141376815, -0.024021654203534127, -0.21202547407398623, 0.20615027935709804, -0.002765974763315171, -0.19007252099302907, 0.15511829521662246, 0.2711965653472968, 0.14016223108628764, -0.13087099477803957, 0.06992894664387374, -0.04278988814136634, 0.19729587982874364, 0.008231455497055624, -0.0009679553875078758, 0.10562870693587077, 0.2827065641235095, 0.11686600926332176, 0.13141018176587144, -0.14266418297532557, -0.08061228602067179, -0.19896907835548822, -0.04621258749975823, -0.2851962340103152, -0.05354168531666801, -0.1648172707527313, -0.17744983403633038, 0.34354237558242556, 0.17702530086001692, 0.26296159185003487, 0.09853761022677646, 0.3710803595992426, 0.0036132771036742877, 0.09233253867908692, 0.09088385870757823, 0.17183768783385556, 0.04644090361543931, 0.08530569968279451, -0.17919028711233598, 0.08099624206176183, 0.05952268744974087] |
1,803.0145 | An Implementation of Adaptive Mesh Refinement for Shallow Water
Equations | An implementation of adaptive mesh refinement algorithms is presented for use
with multilayer shallow water equations. Currently, adaptive mesh refinement is
implemented with a single layer shallow water model in the GeoClaw framework.
This implementation, also in the GeoClaw framework, is for multilayer models,
which have been implemented in GeoClaw previously. Until now, however, these
models were too computationally expensive to run on large domains while
resolving detail in coastal regions.
| math.NA | an implementation of adaptive mesh refinement algorithms is presented for use with multilayer shallow water equations currently adaptive mesh refinement is implemented with a single layer shallow water model in the geoclaw framework this implementation also in the geoclaw framework is for multilayer models which have been implemented in geoclaw previously until now however these models were too computationally expensive to run on large domains while resolving detail in coastal regions | [['an', 'implementation', 'of', 'adaptive', 'mesh', 'refinement', 'algorithms', 'is', 'presented', 'for', 'use', 'with', 'multilayer', 'shallow', 'water', 'equations', 'currently', 'adaptive', 'mesh', 'refinement', 'is', 'implemented', 'with', 'a', 'single', 'layer', 'shallow', 'water', 'model', 'in', 'the', 'geoclaw', 'framework', 'this', 'implementation', 'also', 'in', 'the', 'geoclaw', 'framework', 'is', 'for', 'multilayer', 'models', 'which', 'have', 'been', 'implemented', 'in', 'geoclaw', 'previously', 'until', 'now', 'however', 'these', 'models', 'were', 'too', 'computationally', 'expensive', 'to', 'run', 'on', 'large', 'domains', 'while', 'resolving', 'detail', 'in', 'coastal', 'regions']] | [-0.024392701495228937, 0.005531454618083982, -0.0402692239600378, 0.058645409600756745, -0.054388505511615476, -0.1981741468369646, -0.027697878010885815, 0.4541286162402428, -0.23561836653192278, -0.34813049983915306, 0.17102180706651907, -0.1877809204817028, -0.14504414201963325, 0.18010852076309983, -0.06298597003530029, 0.14018928932524483, 0.12316703652097306, -0.08913000330696223, -0.019820659681269243, -0.2879503042187909, 0.25212294808392166, 0.12989480293710048, 0.2922300755925162, 0.02324315350056744, 0.0939836928089687, -0.07629144786279911, -0.04352187971309037, 0.03882108621535377, -0.10858332059464194, 0.07785340415602418, 0.3003936416292637, 0.08460385911494599, 0.29966522486959124, -0.5071783575531043, -0.27636228132546997, -0.005908959656691467, 0.16937399429964348, 0.13504869332307504, -0.0734070620227369, -0.2285372866579974, 0.0988843817408131, -0.179107247851789, -0.10133640550759057, -0.08972490854351453, -0.007488088025613098, 0.007917169472497796, -0.2695261830805053, 0.009788437965768717, 0.0012308499893881905, 0.0917512751905851, -0.018399204035669987, -0.12707779083637075, 0.0036682145027312593, 0.07290335509165281, -0.0655051358716405, 0.03041513282543337, 0.07244149938514324, -0.12678053769492872, -0.075948282997583, 0.36079802374604725, -0.0338084628857987, -0.261057666384838, 0.22393465881616298, -0.023860725731602018, -0.1797972175843594, 0.15036329814613286, 0.2011130071494361, 0.15675404273026006, -0.18455974370713385, 0.08696885228576795, -0.03759592081564413, 0.196805422128716, 0.054920771106762786, -0.06234690222994123, 0.1600381121249266, 0.30166230723261833, 0.04028955086554125, 0.11537651245442915, -0.11536129140032744, -0.13942394235079558, -0.20805325151853998, -0.12570413821508034, -0.13163414797876818, -0.10591930524826469, -0.03852422883025777, -0.19917275983525415, 0.3144020096097194, 0.1681013302024926, 0.09298785446657681, 0.05119363987378933, 0.34840589711888575, 0.06594476366127042, 0.16491950201001807, 0.12585880217129286, 0.2318695108635797, 0.047961454756531706, 0.16836479215384265, -0.14301021320378066, 0.10736007548370202, 0.09383631227406818] |
1,803.01451 | Near-optimal planning using approximate dynamic programming to enhance
post-hazard community resilience management | The lack of a comprehensive decision-making approach at the community level
is an important problem that warrants immediate attention. Network-level
decision-making algorithms need to solve large-scale optimization problems that
pose computational challenges. The complexity of the optimization problems
increases when various sources of uncertainty are considered. This research
introduces a sequential discrete optimization approach, as a decision-making
framework at the community level for recovery management. The proposed
mathematical approach leverages approximate dynamic programming along with
heuristics for the determination of recovery actions. Our methodology overcomes
the curse of dimensionality and manages multi-state, large-scale infrastructure
systems following disasters. We also provide computational results showing that
our methodology not only incorporates recovery policies of responsible public
and private entities within the community but also substantially enhances the
performance of their underlying strategies with limited resources. The
methodology can be implemented efficiently to identify near-optimal recovery
decisions following a severe earthquake based on multiple objectives for an
electrical power network of a testbed community coarsely modeled after Gilroy,
California, United States. The proposed optimization method supports
risk-informed community decision makers within chaotic post-hazard
circumstances.
| math.OC cs.CE cs.SY | the lack of a comprehensive decisionmaking approach at the community level is an important problem that warrants immediate attention networklevel decisionmaking algorithms need to solve largescale optimization problems that pose computational challenges the complexity of the optimization problems increases when various sources of uncertainty are considered this research introduces a sequential discrete optimization approach as a decisionmaking framework at the community level for recovery management the proposed mathematical approach leverages approximate dynamic programming along with heuristics for the determination of recovery actions our methodology overcomes the curse of dimensionality and manages multistate largescale infrastructure systems following disasters we also provide computational results showing that our methodology not only incorporates recovery policies of responsible public and private entities within the community but also substantially enhances the performance of their underlying strategies with limited resources the methodology can be implemented efficiently to identify nearoptimal recovery decisions following a severe earthquake based on multiple objectives for an electrical power network of a testbed community coarsely modeled after gilroy california united states the proposed optimization method supports riskinformed community decision makers within chaotic posthazard circumstances | [['the', 'lack', 'of', 'a', 'comprehensive', 'decisionmaking', 'approach', 'at', 'the', 'community', 'level', 'is', 'an', 'important', 'problem', 'that', 'warrants', 'immediate', 'attention', 'networklevel', 'decisionmaking', 'algorithms', 'need', 'to', 'solve', 'largescale', 'optimization', 'problems', 'that', 'pose', 'computational', 'challenges', 'the', 'complexity', 'of', 'the', 'optimization', 'problems', 'increases', 'when', 'various', 'sources', 'of', 'uncertainty', 'are', 'considered', 'this', 'research', 'introduces', 'a', 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1,803.01452 | The when and where of water in the history of the universe | It is undeniable that life as we know it depends on liquid water. It is
difficult to imagine any biochemical machinery that does not require water. On
Earth, life adapts to the most diverse environments and, once established, it
is very resilient. Considering that water is a common compound in the Universe,
it seems possible (maybe even likely) that one day we will find life elsewhere
in the universe. In this study, we review the main aspects of water as an
essential compound for life: when it appeared since the Big Bang, and where it
spread throughout the diverse cosmic sites. Then, we describe the strong
relation between water and life, as we know it.
| astro-ph.EP | it is undeniable that life as we know it depends on liquid water it is difficult to imagine any biochemical machinery that does not require water on earth life adapts to the most diverse environments and once established it is very resilient considering that water is a common compound in the universe it seems possible maybe even likely that one day we will find life elsewhere in the universe in this study we review the main aspects of water as an essential compound for life when it appeared since the big bang and where it spread throughout the diverse cosmic sites then we describe the strong relation between water and life as we know it | [['it', 'is', 'undeniable', 'that', 'life', 'as', 'we', 'know', 'it', 'depends', 'on', 'liquid', 'water', 'it', 'is', 'difficult', 'to', 'imagine', 'any', 'biochemical', 'machinery', 'that', 'does', 'not', 'require', 'water', 'on', 'earth', 'life', 'adapts', 'to', 'the', 'most', 'diverse', 'environments', 'and', 'once', 'established', 'it', 'is', 'very', 'resilient', 'considering', 'that', 'water', 'is', 'a', 'common', 'compound', 'in', 'the', 'universe', 'it', 'seems', 'possible', 'maybe', 'even', 'likely', 'that', 'one', 'day', 'we', 'will', 'find', 'life', 'elsewhere', 'in', 'the', 'universe', 'in', 'this', 'study', 'we', 'review', 'the', 'main', 'aspects', 'of', 'water', 'as', 'an', 'essential', 'compound', 'for', 'life', 'when', 'it', 'appeared', 'since', 'the', 'big', 'bang', 'and', 'where', 'it', 'spread', 'throughout', 'the', 'diverse', 'cosmic', 'sites', 'then', 'we', 'describe', 'the', 'strong', 'relation', 'between', 'water', 'and', 'life', 'as', 'we', 'know', 'it']] | [-0.06740938300347847, 0.1503651640227358, -0.07659650445794282, 0.15414976313123074, -0.08458873245298215, -0.11797452047872155, 0.042655597978180436, 0.3866995233637483, -0.25024320370740377, -0.2902408600582377, 0.1491681991033661, -0.2570847016921186, -0.22017904496144342, 0.1988111674623645, -0.09309613230921653, -0.0634594749811146, 0.055725210637825984, 0.08244948382286922, 0.030541683459634206, -0.288154514050921, 0.29116803581785894, 0.09130250925765089, 0.24771428758521444, 0.10177160399439542, 0.07341830264776945, -0.04694148099211895, -0.012902863578789907, -0.04667709122371414, -0.11245522873359733, 0.021415292944268163, 0.3115761550386315, 0.20539219567309255, 0.2710795259670071, -0.46034937261239345, -0.2302282267300736, 0.1487352841594459, 0.13071095326348492, 0.12890786802720117, -0.03986294102936011, -0.18474908159316883, 0.06372364604562197, -0.1356402221945641, -0.15124876265130613, -0.050177252620620574, 0.07197149114116379, -0.04131006364654952, -0.14400566779886897, 0.01780715201292997, 0.049120253906079124, 0.003033810667693615, -0.06623553267437154, -0.10800274577720657, -0.022622231345461763, 0.15770801581042496, 0.09759173487191615, 0.016644888533198315, 0.17484641454546995, -0.10106601415242514, 0.021623419056666773, 0.47220922458269027, -0.04610433559459837, -0.11149318661900116, 0.2648458353486722, -0.17965556989403683, -0.19899974647585464, 0.10643427551359586, 0.10598325897311872, 0.09834995302979065, -0.16872487839820047, 0.03213233159622177, -0.05103056957216366, 0.19401727944774472, 0.06855158404366153, -0.003584108906595603, 0.25120691180877064, 0.2194751525560961, 0.09250256528510996, 0.037519343992513, -0.044807168756328196, -0.11946327750338241, -0.25129210944894864, -0.22112331902203353, -0.21153930972795934, 0.0855796162627445, -0.014253596612884986, -0.1815069826643752, 0.326841451484791, 0.1933021110361037, 0.12215177599228691, -0.025286070393074466, 0.2852072838774842, 0.018487345335154753, 0.08467993052757304, 0.07477392332385416, 0.24733293437115525, 0.060041127191937486, 0.17084210309321465, -0.1482587210753042, 0.17350662542183115, -0.048217990368847614] |
1,803.01453 | Nonlinear Orbital Stability for Planar Vortex Patches | In this paper, we prove nonlinear orbital stability for steady vortex patches
that maximize the kinetic energy among isovortical rearrangements in a planar
bounded domain. As a result, nonlinear stability for an isolated vortex patch
is proved. The proof is based on conservation of energy and vorticity, which is
an analogue of the classical Liapunov function method.
| math.AP | in this paper we prove nonlinear orbital stability for steady vortex patches that maximize the kinetic energy among isovortical rearrangements in a planar bounded domain as a result nonlinear stability for an isolated vortex patch is proved the proof is based on conservation of energy and vorticity which is an analogue of the classical liapunov function method | [['in', 'this', 'paper', 'we', 'prove', 'nonlinear', 'orbital', 'stability', 'for', 'steady', 'vortex', 'patches', 'that', 'maximize', 'the', 'kinetic', 'energy', 'among', 'isovortical', 'rearrangements', 'in', 'a', 'planar', 'bounded', 'domain', 'as', 'a', 'result', 'nonlinear', 'stability', 'for', 'an', 'isolated', 'vortex', 'patch', 'is', 'proved', 'the', 'proof', 'is', 'based', 'on', 'conservation', 'of', 'energy', 'and', 'vorticity', 'which', 'is', 'an', 'analogue', 'of', 'the', 'classical', 'liapunov', 'function', 'method']] | [-0.1657116198748873, 0.07185887424898203, -0.11308548922993635, 0.06559870718455497, -0.056580250159624895, -0.05501395857713202, -0.046183987093778946, 0.28580241815366764, -0.29530462799103635, -0.24014002983376645, 0.08495122591940392, -0.22005075678686825, -0.14150298922731167, 0.1783630073217577, -0.060348873614872754, 0.06754585165987935, 0.04480443698795218, 0.030254961975866503, -0.01186860993651575, -0.1994147923031593, 0.33770314466796425, 0.014006374975699083, 0.31646126371465233, 0.07811544897655646, 0.13946866634579605, -0.007757267914712429, 0.02284805544472316, 0.0400729263119661, -0.19232330409661363, 0.0824833731983968, 0.19957024502780354, 0.02949110832343107, 0.30146506629688175, -0.42495042664047916, -0.19588328527874851, 0.11889980698265788, 0.15698678794790777, 0.1299465510099636, -0.056812952877136697, -0.22215652505033895, 0.10407342622873553, -0.11131155262946298, -0.19172339520433493, -0.05841921791107508, 0.05446111002381433, 0.10843830050802544, -0.30353631350424204, 0.13090903846252905, 0.16145760566404646, 0.06505281443854696, -0.13739193717769363, -0.0312631994796296, -0.09765445457346607, 0.026442809041646684, 0.029811747033116325, 0.03960917511824192, 0.08703431393951178, -0.1293765356674333, -0.10923598277006756, 0.3257060271377365, -0.037527643846707384, -0.2589709339826776, 0.1397961508360152, -0.07002968319871447, -0.09572602043810644, 0.14353866997714104, 0.1497056698671689, 0.15269571988794364, -0.13292896474727936, 0.07816432382842003, -0.0856249305141861, 0.18078373871711, 0.11572129197680113, 0.03293042800699671, 0.19151096947883306, 0.19281853556126488, 0.19714120716640823, 0.1818041875631663, -0.0650545320138662, -0.125256400008016, -0.32407442715607193, -0.19526981274809754, -0.2634867215692474, 0.05805555403869795, -0.05403556961442646, -0.2098851048698028, 0.3943820455879496, 0.0515090944929653, 0.1396415020623081, 0.07528397115968626, 0.2819732382828206, 0.16130339501123353, -0.0036108222169180713, 0.08695955630882006, 0.25758144468591926, 0.14804353381470337, 0.13508100684307384, -0.2435528420549082, -0.003015966987923572, 0.17334528827070658] |
1,803.01454 | Fast Best Subset Selection: Coordinate Descent and Local Combinatorial
Optimization Algorithms | The $L_0$-regularized least squares problem (a.k.a. best subsets) is central
to sparse statistical learning and has attracted significant attention across
the wider statistics, machine learning, and optimization communities. Recent
work has shown that modern mixed integer optimization (MIO) solvers can be used
to address small to moderate instances of this problem. In spite of the
usefulness of $L_0$-based estimators and generic MIO solvers, there is a steep
computational price to pay when compared to popular sparse learning algorithms
(e.g., based on $L_1$ regularization). In this paper, we aim to push the
frontiers of computation for a family of $L_0$-regularized problems with
additional convex penalties. We propose a new hierarchy of necessary optimality
conditions for these problems. We develop fast algorithms, based on coordinate
descent and local combinatorial optimization, that are guaranteed to converge
to solutions satisfying these optimality conditions. From a statistical
viewpoint, an interesting story emerges. When the signal strength is high, our
combinatorial optimization algorithms have an edge in challenging statistical
settings. When the signal is lower, pure $L_0$ benefits from additional convex
regularization. We empirically demonstrate that our family of $L_0$-based
estimators can outperform the state-of-the-art sparse learning algorithms in
terms of a combination of prediction, estimation, and variable selection
metrics under various regimes (e.g., different signal strengths, feature
correlations, number of samples and features). Our new open-source sparse
learning toolkit L0Learn (available on CRAN and Github) reaches up to a
three-fold speedup (with $p$ up to $10^6$) when compared to competing toolkits
such as glmnet and ncvreg.
| stat.CO math.OC stat.ML | the l_0regularized least squares problem aka best subsets is central to sparse statistical learning and has attracted significant attention across the wider statistics machine learning and optimization communities recent work has shown that modern mixed integer optimization mio solvers can be used to address small to moderate instances of this problem in spite of the usefulness of l_0based estimators and generic mio solvers there is a steep computational price to pay when compared to popular sparse learning algorithms eg based on l_1 regularization in this paper we aim to push the frontiers of computation for a family of l_0regularized problems with additional convex penalties we propose a new hierarchy of necessary optimality conditions for these problems we develop fast algorithms based on coordinate descent and local combinatorial optimization that are guaranteed to converge to solutions satisfying these optimality conditions from a statistical viewpoint an interesting story emerges when the signal strength is high our combinatorial optimization algorithms have an edge in challenging statistical settings when the signal is lower pure l_0 benefits from additional convex regularization we empirically demonstrate that our family of l_0based estimators can outperform the stateoftheart sparse learning algorithms in terms of a combination of prediction estimation and variable selection metrics under various regimes eg different signal strengths feature correlations number of samples and features our new opensource sparse learning toolkit l0learn available on cran and github reaches up to a threefold speedup with p up to 106 when compared to competing toolkits such as glmnet and ncvreg | [['the', 'l_0regularized', 'least', 'squares', 'problem', 'aka', 'best', 'subsets', 'is', 'central', 'to', 'sparse', 'statistical', 'learning', 'and', 'has', 'attracted', 'significant', 'attention', 'across', 'the', 'wider', 'statistics', 'machine', 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1,803.01455 | Testing the Cubic Galileon Gravity model by the Milky Way rotation curve
and SPARC data | Recently, the Cubic Galileon Gravity (CGG) model has been suggested as an
alternative gravity theory to General Relativity. The model consists of an
extra field potential term which can serve as the `fifth-force'. In this
article, we examine the possibility whether this extra force term can explain
the missing mass problem in galaxies without the help of dark matter. By using
the Milky Way rotation curve and the Spitzer Photomery & Accurate Rotation
Curves (SPARC) data, we show that this CGG model can satisfactorily explain the
shapes of these rotation curves without dark matter. The CGG model can be
regarded as a new alternative theory to challenge the existing dark matter
paradigm.
| astro-ph.GA | recently the cubic galileon gravity cgg model has been suggested as an alternative gravity theory to general relativity the model consists of an extra field potential term which can serve as the fifthforce in this article we examine the possibility whether this extra force term can explain the missing mass problem in galaxies without the help of dark matter by using the milky way rotation curve and the spitzer photomery accurate rotation curves sparc data we show that this cgg model can satisfactorily explain the shapes of these rotation curves without dark matter the cgg model can be regarded as a new alternative theory to challenge the existing dark matter paradigm | [['recently', 'the', 'cubic', 'galileon', 'gravity', 'cgg', 'model', 'has', 'been', 'suggested', 'as', 'an', 'alternative', 'gravity', 'theory', 'to', 'general', 'relativity', 'the', 'model', 'consists', 'of', 'an', 'extra', 'field', 'potential', 'term', 'which', 'can', 'serve', 'as', 'the', 'fifthforce', 'in', 'this', 'article', 'we', 'examine', 'the', 'possibility', 'whether', 'this', 'extra', 'force', 'term', 'can', 'explain', 'the', 'missing', 'mass', 'problem', 'in', 'galaxies', 'without', 'the', 'help', 'of', 'dark', 'matter', 'by', 'using', 'the', 'milky', 'way', 'rotation', 'curve', 'and', 'the', 'spitzer', 'photomery', 'accurate', 'rotation', 'curves', 'sparc', 'data', 'we', 'show', 'that', 'this', 'cgg', 'model', 'can', 'satisfactorily', 'explain', 'the', 'shapes', 'of', 'these', 'rotation', 'curves', 'without', 'dark', 'matter', 'the', 'cgg', 'model', 'can', 'be', 'regarded', 'as', 'a', 'new', 'alternative', 'theory', 'to', 'challenge', 'the', 'existing', 'dark', 'matter', 'paradigm']] | [-0.11223146275151522, 0.08040099230579058, -0.17635406808800658, 0.16448710747168993, -0.1665172553705898, -0.1324658068785952, -0.014678356553089212, 0.32337466569363393, -0.26404029189354994, -0.4044099940918386, 0.019695662603374908, -0.2133652885021134, -0.14643260699442842, 0.16997908918525684, -0.08806708487682044, 0.045653695064935496, -0.03494371123273264, 0.004591850513084368, -0.012013195478357375, -0.2833241915044544, 0.29461938657120545, 0.07175498545508494, 0.20536487257446756, 0.0030667417132380333, 0.07211528153857216, -0.044057858701456676, -0.009669031228192827, 0.0012612427584826947, -0.1391357194783764, 0.07548804260176521, 0.184669183912179, 0.12208547727416523, 0.1802164928712459, -0.4516493933783336, -0.32189546703567345, 0.167910901050676, 0.17079458087682725, 0.16094368589851496, -0.09577570305290548, -0.26830531814643604, 0.029025113150816073, -0.2344100894914432, -0.1990053737747737, -0.08788943951949477, -0.017892184086270968, -0.0506041840036315, -0.2127346588637341, 0.09248011265881359, 0.019942718073302373, -0.0037743653170764445, -0.06957464448641985, -0.08079986821817742, -0.01609351052902639, 0.026797607579183848, 0.09140402848662978, 0.08093111058538356, 0.10634971945969895, -0.15330876609395175, -0.10583101595243948, 0.4376674218611284, -0.14468780280175533, -0.15578067828186745, 0.14250357758931137, -0.08324161927977747, -0.1371192345734347, 0.05572340747510845, 0.1368076498112218, 0.0793636807827914, -0.1834538191980259, 0.1370679120231547, -0.07198745687492192, 0.17737940832633864, 0.019665786090560935, -0.01307498261237263, 0.34514024210247124, 0.14137028989974748, 0.020583587419241666, 0.07372805108422074, -0.09992001772942868, -0.0543159498790787, -0.3323821451091631, -0.14744267876098588, -0.11331117824566635, 0.021497375196353957, -0.10152657559890278, -0.09521024639040909, 0.3535371365533634, 0.1293964946642518, 0.18861294815486127, 0.030534048946785994, 0.33628587596626447, 0.067783033920833, 0.08893637386235324, 0.028244794029424983, 0.3116181054237214, 0.11394011844161221, 0.06684276326559484, -0.2309428766031157, 0.033237702716988594, 0.03469697624360296] |
1,803.01456 | Loop effects on the Higgs decay widths in extended Higgs models | In order to identify the Higgs sector using future precision data, we
calculate the partial decay widths of the discovered Higgs boson with the mass
of 125 GeV into fermion pairs and gauge-boson pairs with one-loop electroweak
and one-loop QCD corrections in various extended Higgs models, such as the
Higgs singlet model and four types of two Higgs doublet models. In the
tree-level analysis, the patterns of deviations from the standard model
predictions in the partial decay widths for various decay modes are distinctive
for each model, due to the mixing of the Higgs boson with other neutral
scalars. Our present analysis shows that even with a full set of radiative
corrections we can discriminate these extended Higgs models via the partial
decay widths as long as any of the deviations is detected at future precision
measurements. Furthermore, we quantitatively show that in each model the
magnitude of the deviations can provide important information on the mass scale
of extra Higgs bosons under the theoretical constraints from perturbative
unitary and vacuum stability, which can be obtained without discovery of the
additional Higgs bosons.
| hep-ph | in order to identify the higgs sector using future precision data we calculate the partial decay widths of the discovered higgs boson with the mass of 125 gev into fermion pairs and gaugeboson pairs with oneloop electroweak and oneloop qcd corrections in various extended higgs models such as the higgs singlet model and four types of two higgs doublet models in the treelevel analysis the patterns of deviations from the standard model predictions in the partial decay widths for various decay modes are distinctive for each model due to the mixing of the higgs boson with other neutral scalars our present analysis shows that even with a full set of radiative corrections we can discriminate these extended higgs models via the partial decay widths as long as any of the deviations is detected at future precision measurements furthermore we quantitatively show that in each model the magnitude of the deviations can provide important information on the mass scale of extra higgs bosons under the theoretical constraints from perturbative unitary and vacuum stability which can be obtained without discovery of the additional higgs bosons | [['in', 'order', 'to', 'identify', 'the', 'higgs', 'sector', 'using', 'future', 'precision', 'data', 'we', 'calculate', 'the', 'partial', 'decay', 'widths', 'of', 'the', 'discovered', 'higgs', 'boson', 'with', 'the', 'mass', 'of', '125', 'gev', 'into', 'fermion', 'pairs', 'and', 'gaugeboson', 'pairs', 'with', 'oneloop', 'electroweak', 'and', 'oneloop', 'qcd', 'corrections', 'in', 'various', 'extended', 'higgs', 'models', 'such', 'as', 'the', 'higgs', 'singlet', 'model', 'and', 'four', 'types', 'of', 'two', 'higgs', 'doublet', 'models', 'in', 'the', 'treelevel', 'analysis', 'the', 'patterns', 'of', 'deviations', 'from', 'the', 'standard', 'model', 'predictions', 'in', 'the', 'partial', 'decay', 'widths', 'for', 'various', 'decay', 'modes', 'are', 'distinctive', 'for', 'each', 'model', 'due', 'to', 'the', 'mixing', 'of', 'the', 'higgs', 'boson', 'with', 'other', 'neutral', 'scalars', 'our', 'present', 'analysis', 'shows', 'that', 'even', 'with', 'a', 'full', 'set', 'of', 'radiative', 'corrections', 'we', 'can', 'discriminate', 'these', 'extended', 'higgs', 'models', 'via', 'the', 'partial', 'decay', 'widths', 'as', 'long', 'as', 'any', 'of', 'the', 'deviations', 'is', 'detected', 'at', 'future', 'precision', 'measurements', 'furthermore', 'we', 'quantitatively', 'show', 'that', 'in', 'each', 'model', 'the', 'magnitude', 'of', 'the', 'deviations', 'can', 'provide', 'important', 'information', 'on', 'the', 'mass', 'scale', 'of', 'extra', 'higgs', 'bosons', 'under', 'the', 'theoretical', 'constraints', 'from', 'perturbative', 'unitary', 'and', 'vacuum', 'stability', 'which', 'can', 'be', 'obtained', 'without', 'discovery', 'of', 'the', 'additional', 'higgs', 'bosons']] | [-0.0614034252297235, 0.2155776172011195, -0.04606042725741456, 0.16889086447444954, -0.050924341866105304, -0.18758586069309444, 0.021315113861429317, 0.3171716364599316, -0.2236862231397116, -0.2945198928326613, 0.05110071282363064, -0.2982621298431129, -0.01829138616242451, 0.14270930280247346, 0.0930276672404178, 0.10253691332748088, 0.08642459933549329, 0.02753659252149226, -0.0788249587881903, -0.2650096455176712, 0.31639798599310587, -0.005084946324102214, 0.19176093824818485, 0.08009165499958622, 0.04311518935051548, 0.002278369962100367, -0.03639223104688884, -0.0806410619581902, -0.12185495660286919, 0.10673189706988429, 0.13713411799432182, 0.0683019164150652, 0.13266721455370142, -0.33419376939453715, -0.16503902902327927, 0.15669603472260016, 0.17286790570987215, 0.15357096196989442, -0.04133467958245141, -0.35969162813789857, 0.10726202435758413, -0.1885014031377565, -0.09807232565811423, -0.09414732003523434, -0.08432998115583602, -0.09499667533495225, -0.3469324568362876, 0.08230426032388777, -0.06689582641943882, 0.03069979887865382, -0.00926027801829324, -0.16194174365430583, -0.10612722141973552, 0.0546078182186911, 0.17577982978523796, -0.02693773758320311, 0.14085951134501423, -0.2159020145903367, -0.20079645589935527, 0.42045408295457315, -0.1768786409135674, -0.16283026640430662, 0.16356415874350186, -0.182619549904039, -0.1399485686732853, 0.15126559031424952, 0.20259823308127825, 0.03501520082710789, -0.15336751797404446, 0.15193895139741645, -0.026936829820417806, 0.1722950048393524, 0.03372215267647404, 0.09328745883161742, 0.2732578265783504, 0.14810189076500838, -0.021639908821693535, 0.07830074382659628, -0.09063605946244398, -0.08571604689420328, -0.4404814080309754, -0.13967875314779743, -0.013954654535726528, 0.0440939774983588, -0.09085818606284396, -0.1120592252519287, 0.4173758506744367, 0.1595551714764226, 0.26144102935124536, 0.04389708173204254, 0.294751412557092, 0.11199369777989246, 0.1277325294932218, -0.00024431439299808176, 0.33625128489659456, 0.14868957199196997, 0.08455044072111204, -0.23618643146639312, -0.005351995311351747, 0.0744722537757432] |
1,803.01457 | Less Is More: Picking Informative Frames for Video Captioning | In video captioning task, the best practice has been achieved by
attention-based models which associate salient visual components with sentences
in the video. However, existing study follows a common procedure which includes
a frame-level appearance modeling and motion modeling on equal interval frame
sampling, which may bring about redundant visual information, sensitivity to
content noise and unnecessary computation cost.
We propose a plug-and-play PickNet to perform informative frame picking in
video captioning. Based on a standard Encoder-Decoder framework, we develop a
reinforcement-learning-based procedure to train the network sequentially, where
the reward of each frame picking action is designed by maximizing visual
diversity and minimizing textual discrepancy. If the candidate is rewarded, it
will be selected and the corresponding latent representation of Encoder-Decoder
will be updated for future trials. This procedure goes on until the end of the
video sequence. Consequently, a compact frame subset can be selected to
represent the visual information and perform video captioning without
performance degradation. Experiment results shows that our model can use 6-8
frames to achieve competitive performance across popular benchmarks.
| cs.CV | in video captioning task the best practice has been achieved by attentionbased models which associate salient visual components with sentences in the video however existing study follows a common procedure which includes a framelevel appearance modeling and motion modeling on equal interval frame sampling which may bring about redundant visual information sensitivity to content noise and unnecessary computation cost we propose a plugandplay picknet to perform informative frame picking in video captioning based on a standard encoderdecoder framework we develop a reinforcementlearningbased procedure to train the network sequentially where the reward of each frame picking action is designed by maximizing visual diversity and minimizing textual discrepancy if the candidate is rewarded it will be selected and the corresponding latent representation of encoderdecoder will be updated for future trials this procedure goes on until the end of the video sequence consequently a compact frame subset can be selected to represent the visual information and perform video captioning without performance degradation experiment results shows that our model can use 68 frames to achieve competitive performance across popular benchmarks | [['in', 'video', 'captioning', 'task', 'the', 'best', 'practice', 'has', 'been', 'achieved', 'by', 'attentionbased', 'models', 'which', 'associate', 'salient', 'visual', 'components', 'with', 'sentences', 'in', 'the', 'video', 'however', 'existing', 'study', 'follows', 'a', 'common', 'procedure', 'which', 'includes', 'a', 'framelevel', 'appearance', 'modeling', 'and', 'motion', 'modeling', 'on', 'equal', 'interval', 'frame', 'sampling', 'which', 'may', 'bring', 'about', 'redundant', 'visual', 'information', 'sensitivity', 'to', 'content', 'noise', 'and', 'unnecessary', 'computation', 'cost', 'we', 'propose', 'a', 'plugandplay', 'picknet', 'to', 'perform', 'informative', 'frame', 'picking', 'in', 'video', 'captioning', 'based', 'on', 'a', 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1,803.01458 | Contact process under renewals I | Motivated by questions regarding long range percolation, we investigate a
non-Markovian analogue of the Harris contact process in $\mathbb{Z}^d$: an
individual is attached to each site $x \in \mathbb{Z}^d$, and it can be
infected or healthy; the infection propagates to healthy neighbors just as in
the usual contact process, according to independent exponential times with a
fixed rate $\lambda$; nevertheless, the possible recovery times for an
individual are given by the points of a renewal process with heavy tail; the
renewal processes are assumed to be independent for different sites. We show
that the resulting processes have a critical value equal to zero.
| math.PR | motivated by questions regarding long range percolation we investigate a nonmarkovian analogue of the harris contact process in mathbbzd an individual is attached to each site x in mathbbzd and it can be infected or healthy the infection propagates to healthy neighbors just as in the usual contact process according to independent exponential times with a fixed rate lambda nevertheless the possible recovery times for an individual are given by the points of a renewal process with heavy tail the renewal processes are assumed to be independent for different sites we show that the resulting processes have a critical value equal to zero | [['motivated', 'by', 'questions', 'regarding', 'long', 'range', 'percolation', 'we', 'investigate', 'a', 'nonmarkovian', 'analogue', 'of', 'the', 'harris', 'contact', 'process', 'in', 'mathbbzd', 'an', 'individual', 'is', 'attached', 'to', 'each', 'site', 'x', 'in', 'mathbbzd', 'and', 'it', 'can', 'be', 'infected', 'or', 'healthy', 'the', 'infection', 'propagates', 'to', 'healthy', 'neighbors', 'just', 'as', 'in', 'the', 'usual', 'contact', 'process', 'according', 'to', 'independent', 'exponential', 'times', 'with', 'a', 'fixed', 'rate', 'lambda', 'nevertheless', 'the', 'possible', 'recovery', 'times', 'for', 'an', 'individual', 'are', 'given', 'by', 'the', 'points', 'of', 'a', 'renewal', 'process', 'with', 'heavy', 'tail', 'the', 'renewal', 'processes', 'are', 'assumed', 'to', 'be', 'independent', 'for', 'different', 'sites', 'we', 'show', 'that', 'the', 'resulting', 'processes', 'have', 'a', 'critical', 'value', 'equal', 'to', 'zero']] | [-0.08599882194709069, 0.19732141045619533, -0.051694876717819464, 0.046516488808883524, -0.014454975337676198, -0.18730585051935564, 0.1131276541651742, 0.3779633395663164, -0.28300258594122035, -0.2034980377308952, 0.12977470182791098, -0.2982397268896977, -0.09726227094979903, 0.12223935345847847, -0.06429905157753275, 0.0102272942409064, 0.02626574543096776, 0.12235367501796522, 0.017278344010441447, -0.28637555393489816, 0.30081122922846704, 0.05806965833457494, 0.23619352646954178, 0.014272954323989095, 0.09514629139194211, 0.04587695492630445, 0.0019829053865763747, -0.01613160083360023, -0.15572689689993371, 0.02032211255799251, 0.22163108117354002, 0.06294340791858312, 0.29696506048435145, -0.43651324203147474, -0.21645824486633888, 0.15328142481394907, 0.1508775437883671, 0.08876752403555709, 0.028818771763008486, -0.2906346473372677, 0.10613830788151442, -0.12696809207034992, -0.17063817833957162, 0.043130885565526855, 0.08252988370063091, 0.06375712824497119, -0.31888425342955634, 0.07994281403715858, 0.04982662488914375, 0.027834868804524536, -0.01640175756754227, -0.1038011173328873, -0.016235295755481258, 0.19791026998682001, 0.09224377191558851, 0.05208601977097467, 0.18258805257421964, -0.10854722950163917, -0.13345939634838005, 0.329688740188925, -0.05486065893461114, -0.17800649326041484, 0.22574079467110264, -0.1619950178332482, -0.11132203183561853, 0.158378214647686, 0.13421821487543073, 0.09264043926541667, -0.2032667587068185, 0.05207096529362759, -0.01307918921732389, 0.11880983185312412, 0.06780490864212942, -0.033569931943258906, 0.1956405476079259, 0.1786607243504954, 0.08600667873804357, 0.1199056531813502, -0.03876652470925479, -0.12281345388031502, -0.28551079289427084, -0.13673723581726255, -0.17793544619208546, 0.15145942718197491, -0.13901091286970768, -0.16912153541354588, 0.34194032436471833, 0.14026971298125257, 0.25903670443674026, 0.060296521151384105, 0.17915909276208253, 0.15042907120411295, 0.027587957946963393, 0.06204921326245966, 0.12273045572298534, 0.10378820879059364, 0.042685884037461964, -0.1446840767206136, 0.13958653169277224, 0.0374330610027808] |
1,803.01459 | Qualitative Measures of Equity in Small Groups | We investigate the utility of two qualitative measures of equity. Our data
are videos of groups of first-generation and Deaf or hard-of-hearing students
in a pre-matriculation university program designed to help them persist in STEM
fields by developing their metacognitive practices. We analyze video data of
students in small groups trying to accomplish various tasks. We analyze how
groups engage with proposed ideas (inchargeness) and create a space of open
sharing (civility). By capturing different aspects of each group, these
measures combine to help our understanding of what an equitable group could
look like.
| physics.ed-ph | we investigate the utility of two qualitative measures of equity our data are videos of groups of firstgeneration and deaf or hardofhearing students in a prematriculation university program designed to help them persist in stem fields by developing their metacognitive practices we analyze video data of students in small groups trying to accomplish various tasks we analyze how groups engage with proposed ideas inchargeness and create a space of open sharing civility by capturing different aspects of each group these measures combine to help our understanding of what an equitable group could look like | [['we', 'investigate', 'the', 'utility', 'of', 'two', 'qualitative', 'measures', 'of', 'equity', 'our', 'data', 'are', 'videos', 'of', 'groups', 'of', 'firstgeneration', 'and', 'deaf', 'or', 'hardofhearing', 'students', 'in', 'a', 'prematriculation', 'university', 'program', 'designed', 'to', 'help', 'them', 'persist', 'in', 'stem', 'fields', 'by', 'developing', 'their', 'metacognitive', 'practices', 'we', 'analyze', 'video', 'data', 'of', 'students', 'in', 'small', 'groups', 'trying', 'to', 'accomplish', 'various', 'tasks', 'we', 'analyze', 'how', 'groups', 'engage', 'with', 'proposed', 'ideas', 'inchargeness', 'and', 'create', 'a', 'space', 'of', 'open', 'sharing', 'civility', 'by', 'capturing', 'different', 'aspects', 'of', 'each', 'group', 'these', 'measures', 'combine', 'to', 'help', 'our', 'understanding', 'of', 'what', 'an', 'equitable', 'group', 'could', 'look', 'like']] | [-0.08747663245691607, 0.08710721193751346, -0.14459700176699294, 0.1420325035125845, -0.14312956862462065, -0.1521154794945485, 0.07688413521342834, 0.4333324619879325, -0.26972935732661024, -0.3753206920965264, 0.08736760613844834, -0.2859761552316033, -0.14956548457654814, 0.1720669701281521, -0.14921113510564382, -0.021085482245932024, 0.05849162945394508, 0.02874679191865855, -0.021715500128145018, -0.3156324666562594, 0.37682491790813705, 0.03837256288776795, 0.29615685061241187, 0.0031762700424426134, 0.06134072722763651, -0.004045525713849606, -0.11218109727940626, -0.0031987357111777077, -0.11763073416530258, 0.19273455489116412, 0.3862351171258423, 0.21726335518889958, 0.39739814069535995, -0.4640215783276492, -0.16411502708991368, 0.09368915597183837, 0.08561535585257742, 0.056631309911608696, -0.06690924200746748, -0.34028457589447497, 0.05942529298804907, -0.17021287969417043, -0.10554718603897426, -0.13177536430044307, -0.053692687773663136, 0.03567041834402415, -0.178190040629771, -0.04697156161483791, 0.0077286840377685925, 0.11763692484754655, -0.03663892780637575, -0.10101886799352036, 0.035357370303892015, 0.30190231365720843, 0.06408149331109599, -0.023963334395860632, 0.1369207992270175, -0.17562483408384852, -0.20057848919596938, 0.4261796560138464, -0.005687001513110267, -0.13750033104378317, 0.23322436454085013, -0.15946016767476168, -0.15662495580294894, 0.0410823210918655, 0.25971259561677773, 0.05555408337515676, -0.1659086603102171, -0.00960585221570606, -0.035820204361031456, 0.12862278658042972, 0.04756440447332958, 0.004482437007957035, 0.20312514435499907, 0.16123028989467356, 0.003055776511448332, 0.10545957409453371, 0.013150429531298061, -0.05910383217140204, -0.21540530828319282, -0.1828629553524984, -0.07698471792714877, -0.012642187035332124, -0.04181545825849753, -0.08516169628904512, 0.43323808713402184, 0.20846031408550011, 0.13141478788521554, 0.044179333891305655, 0.23039128319877716, -0.012655589778700637, 0.08571671748585585, 0.06557827763155931, 0.11784846277959231, 0.0519237850779771, 0.1220648021540708, -0.16917649800371792, 0.030054870196100737, -0.006986879691895511] |
1,803.0146 | Contact process under renewals II | We continue the study of renewal contact processes initiated in a companion
paper, where we showed that if the tail of the interarrival distribution $\mu$
is heavier than $t^{-\alpha}$ for some $\alpha <1$ (plus auxiliary regularity
conditions) then the critical value vanishes. In this paper we show that if
$\mu$ has decreasing hazard rate and tail bounded by $t^{-\alpha}$ with $\alpha
>1$, then the critical value is positive in the one-dimensional case. A more
robust and much simpler argument shows that the critical value is positive in
any dimension whenever the interarrival distribution has a finite second
moment.
| math.PR | we continue the study of renewal contact processes initiated in a companion paper where we showed that if the tail of the interarrival distribution mu is heavier than talpha for some alpha 1 plus auxiliary regularity conditions then the critical value vanishes in this paper we show that if mu has decreasing hazard rate and tail bounded by talpha with alpha 1 then the critical value is positive in the onedimensional case a more robust and much simpler argument shows that the critical value is positive in any dimension whenever the interarrival distribution has a finite second moment | [['we', 'continue', 'the', 'study', 'of', 'renewal', 'contact', 'processes', 'initiated', 'in', 'a', 'companion', 'paper', 'where', 'we', 'showed', 'that', 'if', 'the', 'tail', 'of', 'the', 'interarrival', 'distribution', 'mu', 'is', 'heavier', 'than', 'talpha', 'for', 'some', 'alpha', '1', 'plus', 'auxiliary', 'regularity', 'conditions', 'then', 'the', 'critical', 'value', 'vanishes', 'in', 'this', 'paper', 'we', 'show', 'that', 'if', 'mu', 'has', 'decreasing', 'hazard', 'rate', 'and', 'tail', 'bounded', 'by', 'talpha', 'with', 'alpha', '1', 'then', 'the', 'critical', 'value', 'is', 'positive', 'in', 'the', 'onedimensional', 'case', 'a', 'more', 'robust', 'and', 'much', 'simpler', 'argument', 'shows', 'that', 'the', 'critical', 'value', 'is', 'positive', 'in', 'any', 'dimension', 'whenever', 'the', 'interarrival', 'distribution', 'has', 'a', 'finite', 'second', 'moment']] | [-0.12940687083102267, 0.18948361445788522, -0.09307248260331702, 0.06793960292909142, -0.028508846902250484, -0.16817661992996474, 0.04587828214529769, 0.3507864752081128, -0.2346781884339087, -0.17724955910626722, 0.10715255178321077, -0.3203251729434242, -0.13359889741369277, 0.1558765818421938, -0.06018164104839065, 0.04496330982169174, 0.005044931614752479, 0.11448427858021186, -0.05848140791486189, -0.2356664668008381, 0.36257651541382074, 0.02332388677121121, 0.2079494303301433, 0.08169716830384366, 0.037213408768329084, 0.001477780435788172, 0.029612196276762655, -0.0070238386290337965, -0.20879020091324121, 0.028802353955273117, 0.15139960857792473, 0.10240936517116747, 0.343312960726266, -0.32943145096378057, -0.1977162961943113, 0.19425849493935096, 0.15501447339371152, -0.0036423016073448317, -0.0356353202732862, -0.21231736099271445, 0.1546575212043387, -0.1782632214088487, -0.18224689185296242, 0.007464930139558047, 0.13268108161318362, 0.03151551388650752, -0.35289214739613994, 0.11208581064390588, 0.12121602624882849, 0.03533185284694049, -0.05678122761844638, -0.15076377085999262, 0.005793731355545472, 0.0807413472235678, 0.12443446735043687, 0.06491368149445222, 0.10453628277767221, -0.11618359978738411, -0.03853481618820557, 0.3165474936546644, -0.11935685781541647, -0.19146866277240368, 0.13796644874050148, -0.24531128132069596, -0.15952127664445007, 0.13014299426303835, 0.11526885555524911, 0.1322695119496511, -0.10855293059151391, 0.1247667866385998, -0.029686714750619566, 0.20582847831009327, 0.07592121815803099, -0.03702610298725111, 0.10101591990975549, 0.14377932949941985, 0.17691873297171326, 0.13354741446483803, -0.07337130896024863, -0.075175227863448, -0.32682130611216537, -0.1785223880706697, -0.21164203358918657, 0.13522725539966202, -0.11553595410345113, -0.12501614630146293, 0.3422452347894788, 0.15123286604767247, 0.22469665269528952, 0.15727342307277747, 0.24920702077524395, 0.210582623125187, -0.02378387062107118, 0.10761713915580541, 0.14545556751456426, 0.07601148925236978, 0.11062025521378203, -0.15221426938927723, 0.14228524986122335, 0.05392209654813514] |
1,803.01461 | Fermi surfaces in Kondo insulators | We report magnetic quantum oscillations measured using torque magnetisation
in the Kondo insulator YbB$_{12}$ and discuss the potential origin of the
underlying Fermi surface. Observed quantum oscillations as well as
complementary quantities such as a finite linear specific heat capacity in
YbB$_{12}$ exhibit similarities with the Kondo insulator SmB$_6$, yet also
crucial differences. Small heavy Fermi sections are observed in YbB$_{12}$ with
similarities to the neighbouring heavy fermion semimetallic Fermi surface, in
contrast to large light Fermi surface sections in SmB$_6$ which are more
similar to the conduction electron Fermi surface. A rich spectrum of
theoretical models is suggested to explain the origin across different Kondo
insulating families of a bulk Fermi surface potentially from novel itinerant
quasiparticles that couple to magnetic fields, yet do not couple to weak DC
electric fields.
| cond-mat.str-el | we report magnetic quantum oscillations measured using torque magnetisation in the kondo insulator ybb_12 and discuss the potential origin of the underlying fermi surface observed quantum oscillations as well as complementary quantities such as a finite linear specific heat capacity in ybb_12 exhibit similarities with the kondo insulator smb_6 yet also crucial differences small heavy fermi sections are observed in ybb_12 with similarities to the neighbouring heavy fermion semimetallic fermi surface in contrast to large light fermi surface sections in smb_6 which are more similar to the conduction electron fermi surface a rich spectrum of theoretical models is suggested to explain the origin across different kondo insulating families of a bulk fermi surface potentially from novel itinerant quasiparticles that couple to magnetic fields yet do not couple to weak dc electric fields | [['we', 'report', 'magnetic', 'quantum', 'oscillations', 'measured', 'using', 'torque', 'magnetisation', 'in', 'the', 'kondo', 'insulator', 'ybb_12', 'and', 'discuss', 'the', 'potential', 'origin', 'of', 'the', 'underlying', 'fermi', 'surface', 'observed', 'quantum', 'oscillations', 'as', 'well', 'as', 'complementary', 'quantities', 'such', 'as', 'a', 'finite', 'linear', 'specific', 'heat', 'capacity', 'in', 'ybb_12', 'exhibit', 'similarities', 'with', 'the', 'kondo', 'insulator', 'smb_6', 'yet', 'also', 'crucial', 'differences', 'small', 'heavy', 'fermi', 'sections', 'are', 'observed', 'in', 'ybb_12', 'with', 'similarities', 'to', 'the', 'neighbouring', 'heavy', 'fermion', 'semimetallic', 'fermi', 'surface', 'in', 'contrast', 'to', 'large', 'light', 'fermi', 'surface', 'sections', 'in', 'smb_6', 'which', 'are', 'more', 'similar', 'to', 'the', 'conduction', 'electron', 'fermi', 'surface', 'a', 'rich', 'spectrum', 'of', 'theoretical', 'models', 'is', 'suggested', 'to', 'explain', 'the', 'origin', 'across', 'different', 'kondo', 'insulating', 'families', 'of', 'a', 'bulk', 'fermi', 'surface', 'potentially', 'from', 'novel', 'itinerant', 'quasiparticles', 'that', 'couple', 'to', 'magnetic', 'fields', 'yet', 'do', 'not', 'couple', 'to', 'weak', 'dc', 'electric', 'fields']] | [-0.16241157747307708, 0.24886808947088535, -0.06386717451228337, 0.1413431712470342, -0.08846549492922019, -0.2067520181599045, 0.08311944909986448, 0.3579113636867877, -0.2702684577300467, -0.3227173015545828, -0.06986791396841661, -0.36002724808923, -0.11713130990657108, 0.21722387228333956, -0.003115972602796374, 0.033689013975107984, -0.04845666998263561, -0.037445157589955314, -0.1346463922562896, -0.20819054957422795, 0.30224195398587844, 0.017336691876125493, 0.30540042583633104, 0.13285037511113015, 0.0034246184275781907, -0.062924629913389, 0.1349474542640206, 0.041536900213087036, -0.09957073352300293, 0.02949604620296282, 0.2865880848622978, -0.16933601225415865, 0.1491400124081834, -0.4634468132263106, -0.2503359753662318, 0.020309048764774518, 0.11453476147002992, 0.12624529816093855, -0.10090446762732233, -0.28881590380192257, -0.014852744029750202, -0.14969979460919136, -0.12221451988443732, -0.13317497093653816, -0.038705826267797616, -0.02381775186707576, -0.12910880649746326, 0.12384390844906165, 0.023777577739427656, 0.10774297124677987, -0.10555537885661717, -0.1301651244849023, -0.10571999718950158, 0.058042728546724626, 0.1092296780605631, 0.04214876097147212, 0.16937152338637548, -0.12284430704841559, -0.100752084057383, 0.354341332885352, -0.10919305401021671, -0.09919468459503894, 0.23387203732448997, -0.258129423741731, -0.08030413691779938, 0.18104501889143704, 0.1371236463795261, 0.03229675099084323, -0.15182740500930583, 0.09453163826159046, -0.053106628746415176, 0.1231526927175847, -0.008787810058107205, 0.11582798494209508, 0.3497184380522054, 0.17600088354304194, 0.02589774379951202, 0.09012814594880734, -0.17164654376436816, -0.047140914655756205, -0.25121145952443563, -0.1585300784473392, -0.2409260575271522, 0.06533026119712193, 0.010557824551858974, -0.24300751823819045, 0.4103740294689708, 0.13195494334683067, 0.23766047096543128, -0.11262392953402454, 0.22985835707301952, 0.08186329500908456, 0.0929861819639689, 0.08511168881192464, 0.24094000697633336, 0.18031170562784554, 0.10320809153331952, -0.3143548134901335, 0.04486916851998434, 0.008116215254024913] |
1,803.01462 | Optimal Status Updating for an Energy Harvesting Sensor with a Noisy
Channel | Consider an energy harvesting sensor continuously monitors a system and sends
time-stamped status update to a destination. The destination keeps track of the
system status through the received updates. Under the energy causality
constraint at the sensor, our objective is to design an optimal online status
updating policy to minimize the long-term average Age of Information (AoI) at
the destination. We focus on the scenario where the the channel between the
source and the destination is noisy, and each transmitted update may fail
independently with a constant probability. We assume there is no channel state
information or transmission feedback available to the sensor. We prove that
within a broadly defined class of online policies, the best-effort uniform
updating policy, which was shown to be optimal when the channel is perfect, is
still optimal in the presence of update failures. Our proof relies on tools
from Martingale processes, and the construction of a sequence of virtual
policies.
| cs.NI cs.IT math.IT | consider an energy harvesting sensor continuously monitors a system and sends timestamped status update to a destination the destination keeps track of the system status through the received updates under the energy causality constraint at the sensor our objective is to design an optimal online status updating policy to minimize the longterm average age of information aoi at the destination we focus on the scenario where the the channel between the source and the destination is noisy and each transmitted update may fail independently with a constant probability we assume there is no channel state information or transmission feedback available to the sensor we prove that within a broadly defined class of online policies the besteffort uniform updating policy which was shown to be optimal when the channel is perfect is still optimal in the presence of update failures our proof relies on tools from martingale processes and the construction of a sequence of virtual policies | [['consider', 'an', 'energy', 'harvesting', 'sensor', 'continuously', 'monitors', 'a', 'system', 'and', 'sends', 'timestamped', 'status', 'update', 'to', 'a', 'destination', 'the', 'destination', 'keeps', 'track', 'of', 'the', 'system', 'status', 'through', 'the', 'received', 'updates', 'under', 'the', 'energy', 'causality', 'constraint', 'at', 'the', 'sensor', 'our', 'objective', 'is', 'to', 'design', 'an', 'optimal', 'online', 'status', 'updating', 'policy', 'to', 'minimize', 'the', 'longterm', 'average', 'age', 'of', 'information', 'aoi', 'at', 'the', 'destination', 'we', 'focus', 'on', 'the', 'scenario', 'where', 'the', 'the', 'channel', 'between', 'the', 'source', 'and', 'the', 'destination', 'is', 'noisy', 'and', 'each', 'transmitted', 'update', 'may', 'fail', 'independently', 'with', 'a', 'constant', 'probability', 'we', 'assume', 'there', 'is', 'no', 'channel', 'state', 'information', 'or', 'transmission', 'feedback', 'available', 'to', 'the', 'sensor', 'we', 'prove', 'that', 'within', 'a', 'broadly', 'defined', 'class', 'of', 'online', 'policies', 'the', 'besteffort', 'uniform', 'updating', 'policy', 'which', 'was', 'shown', 'to', 'be', 'optimal', 'when', 'the', 'channel', 'is', 'perfect', 'is', 'still', 'optimal', 'in', 'the', 'presence', 'of', 'update', 'failures', 'our', 'proof', 'relies', 'on', 'tools', 'from', 'martingale', 'processes', 'and', 'the', 'construction', 'of', 'a', 'sequence', 'of', 'virtual', 'policies']] | [-0.18176553242478688, 0.06405348666120493, -0.06930303587040935, 0.016044022011696003, -0.10998565542440002, -0.21433180015092382, 0.1565152058528605, 0.4185158787235522, -0.3216543378165135, -0.2738762320726752, 0.14453109761906, -0.2800935388614352, -0.10216675607117419, 0.11508447003329937, -0.142179517823164, 0.05507210187389342, 0.08122065392298958, 0.14246504376970756, -0.00806143916158292, -0.26159036930393764, 0.29785456921523196, 0.11921988415549724, 0.31703920762102383, 0.026160097168683887, 0.15844831697699518, 0.07644568820101902, -0.050019607931459084, -0.056198656504514076, -0.09968311340759474, 0.04030669047922576, 0.2822084117782278, 0.22194768352141508, 0.2970583015658821, -0.4046844396238717, -0.19163625931366532, 0.11871121099624687, 0.10112231034182538, 0.10002295290439342, -0.03387700841696455, -0.2796469343802295, 0.10779117897469312, -0.17426911479038282, -0.04364021480656587, 0.07223462836387065, -0.04096148787543942, 0.0654146687352295, -0.34247553280483073, -0.013452638292876191, -0.02724064583442389, 0.0017459592580472906, -0.10201098375434342, -0.08300024872938266, -0.02545708854897664, 0.2057210598150283, 0.038375034930560596, 0.05040839615797337, 0.17072377112717965, -0.10159365562960887, -0.12671852517180526, 0.3182885183069186, -0.008765007428920422, -0.20605126342986926, 0.1290962176933998, -0.05428575732124349, -0.10417210006226714, 0.13045814460238966, 0.2087100405866901, 0.08305727088382134, -0.20240761180759412, 0.024646687164651945, -0.018884959388882495, 0.2052441883059099, 0.008452479757416325, 0.05379283559159376, 0.16769096575593814, 0.17437785840145528, 0.1762068586920997, 0.12310466345754834, -0.06812350545078516, -0.13487972126294595, -0.3006848184338126, -0.11263627454042226, -0.2029572408838505, 0.03332700982886868, -0.06945932799172648, -0.10116848966703028, 0.3633718654417839, 0.15901688353430168, 0.1627783159746263, 0.09436157088240203, 0.36443638266661227, 0.08911170441961776, 0.011084967160012381, 0.18925934969089353, 0.19987477068431103, 0.07139876927174509, 0.15244324815471488, -0.21422654047059134, 0.18601390577327365, 0.0015868347478457368] |
1,803.01463 | Motivic cohomology of fat points in Milnor range | We introduce a new algebraic-cycle model for the motivic cohomology theory of
truncated polynomials $k[t]/(t^m)$ in one variable. This approach uses ideas
from the deformation theory and non-archimedean analysis, and is distinct from
the approaches via cycles with modulus. We compute the groups in the Milnor
range when the base field is of characteristic $0$, and prove that they give
the Milnor $K$-groups of $k[t]/(t^m)$, whose relative part is the sum of the
absolute K\"ahler differential forms.
| math.AG math.KT | we introduce a new algebraiccycle model for the motivic cohomology theory of truncated polynomials kttm in one variable this approach uses ideas from the deformation theory and nonarchimedean analysis and is distinct from the approaches via cycles with modulus we compute the groups in the milnor range when the base field is of characteristic 0 and prove that they give the milnor kgroups of kttm whose relative part is the sum of the absolute kahler differential forms | [['we', 'introduce', 'a', 'new', 'algebraiccycle', 'model', 'for', 'the', 'motivic', 'cohomology', 'theory', 'of', 'truncated', 'polynomials', 'kttm', 'in', 'one', 'variable', 'this', 'approach', 'uses', 'ideas', 'from', 'the', 'deformation', 'theory', 'and', 'nonarchimedean', 'analysis', 'and', 'is', 'distinct', 'from', 'the', 'approaches', 'via', 'cycles', 'with', 'modulus', 'we', 'compute', 'the', 'groups', 'in', 'the', 'milnor', 'range', 'when', 'the', 'base', 'field', 'is', 'of', 'characteristic', '0', 'and', 'prove', 'that', 'they', 'give', 'the', 'milnor', 'kgroups', 'of', 'kttm', 'whose', 'relative', 'part', 'is', 'the', 'sum', 'of', 'the', 'absolute', 'kahler', 'differential', 'forms']] | [-0.171192113549222, 0.054637106185829315, -0.1757343963191316, 0.04098546788461406, -0.05699774074191983, -0.09443461931486791, -0.0020836714696063586, 0.28247767325641737, -0.3569450165975738, -0.24074778142007622, 0.08285163663566818, -0.23226676628345977, -0.19742462742519942, 0.179495399185406, -0.12758925014704064, -0.04620621589994108, 0.008380289107712137, 0.11375677999033518, -0.06413251798241273, -0.2727216271324889, 0.4248740103699871, -0.040430276742758786, 0.21716557682894572, 0.045294312005107466, 0.10921702489753984, 0.004878141451627016, -0.047166101722600495, -0.04004270340177558, -0.1608981954574316, 0.1622288163021408, 0.2878646524371328, 0.06352624265363792, 0.2314199375844485, -0.38117098380698244, -0.12242177311909964, 0.17518387030105334, 0.09641509444918483, 0.051351076844651754, 0.03837599525404339, -0.23802168299821583, 0.13173532091408363, -0.15764977074089787, -0.1531029353327294, -0.10016943560913205, 0.034648387436440366, 0.06714411921849525, -0.23639721463660937, 0.03777665743679815, 0.029881493487836624, 0.15431257000041976, -0.10687121265328715, -0.1242221689820793, -0.0030802620096585234, 0.0965108350725574, 0.05095949162559181, 0.034962810292789664, 0.12242882088380488, -0.11482201117355176, -0.11611342440183098, 0.371042708488735, -0.09893005372912346, -0.1767537126166595, 0.11289715955688341, -0.14828687521150788, -0.13515121027877605, 0.13287665513721672, 0.08101038901588402, 0.20067003386321705, -0.00467135233437246, 0.15574637730999194, -0.05598257633077132, 0.09560942910359921, 0.07096643626337519, -0.012596360174939036, 0.15199228421457717, 0.07525471192344117, 0.07229566628843345, 0.1323674613408543, -0.03687849241258526, -0.0875278811562001, -0.3636845432322573, -0.20176118992998995, -0.1326828409187697, 0.12076370358448224, -0.14131852806914705, -0.18543459895708775, 0.44276926072465406, 0.08435299679183879, 0.1873212157358491, 0.15769877206735514, 0.28810346579632246, 0.1220561811146704, 0.0949072098922664, 0.022439256096510467, 0.1922317805410539, 0.24213983523785262, 0.03527123659748484, -0.1237443418720284, -0.026523438021163078, 0.20672722359666149] |
1,803.01464 | The hydrogen identity for Laplacians | For any finite simple graph G, the hydrogen identity H=L-L^(-1) holds, where
H=(d+d^*)^2 is the sign-less Hodge Laplacian defined by sign-less incidence
matrix d and where L is the connection Laplacian. Any spectral information
about L directly leads to estimates for the Hodge Laplacian H=(d+d^*)^2 and
allows to estimate the spectrum of the Kirchhoff Laplacian H_0=d^* d. The
hydrogen identity implies that the random walk u(n) = L^n u with integer n
solves the one-dimensional Jacobi equation Delta u=H^2 with (Delta
u)(n)=u(n+2)-2 u(n)+u(n-2). Every solution is represented by such a reversible
path integral. Over a finite field, we get a reversible cellular automaton. By
taking products of complexes such processes can be defined over any lattice
Z^r. Since L^2 and L^(-2) are isospectral, by a theorem of Kirby, the matrix
L^2 is always similar to a symplectic matrix if the graph has an even number of
simplices. The hydrogen relation is robust: any Schr\"odinger operator K close
to H with the same support can still can be written as $K=L-L^{-1}$ where both
L(x,y) and L^-1(x,y) are zero if x and y do not intersect.
| math.SP cs.DM | for any finite simple graph g the hydrogen identity hll1 holds where hdd2 is the signless hodge laplacian defined by signless incidence matrix d and where l is the connection laplacian any spectral information about l directly leads to estimates for the hodge laplacian hdd2 and allows to estimate the spectrum of the kirchhoff laplacian h_0d d the hydrogen identity implies that the random walk un ln u with integer n solves the onedimensional jacobi equation delta uh2 with delta unun22 unun2 every solution is represented by such a reversible path integral over a finite field we get a reversible cellular automaton by taking products of complexes such processes can be defined over any lattice zr since l2 and l2 are isospectral by a theorem of kirby the matrix l2 is always similar to a symplectic matrix if the graph has an even number of simplices the hydrogen relation is robust any schrodinger operator k close to h with the same support can still can be written as kll1 where both lxy and l1xy are zero if x and y do not intersect | [['for', 'any', 'finite', 'simple', 'graph', 'g', 'the', 'hydrogen', 'identity', 'hll1', 'holds', 'where', 'hdd2', 'is', 'the', 'signless', 'hodge', 'laplacian', 'defined', 'by', 'signless', 'incidence', 'matrix', 'd', 'and', 'where', 'l', 'is', 'the', 'connection', 'laplacian', 'any', 'spectral', 'information', 'about', 'l', 'directly', 'leads', 'to', 'estimates', 'for', 'the', 'hodge', 'laplacian', 'hdd2', 'and', 'allows', 'to', 'estimate', 'the', 'spectrum', 'of', 'the', 'kirchhoff', 'laplacian', 'h_0d', 'd', 'the', 'hydrogen', 'identity', 'implies', 'that', 'the', 'random', 'walk', 'un', 'ln', 'u', 'with', 'integer', 'n', 'solves', 'the', 'onedimensional', 'jacobi', 'equation', 'delta', 'uh2', 'with', 'delta', 'unun22', 'unun2', 'every', 'solution', 'is', 'represented', 'by', 'such', 'a', 'reversible', 'path', 'integral', 'over', 'a', 'finite', 'field', 'we', 'get', 'a', 'reversible', 'cellular', 'automaton', 'by', 'taking', 'products', 'of', 'complexes', 'such', 'processes', 'can', 'be', 'defined', 'over', 'any', 'lattice', 'zr', 'since', 'l2', 'and', 'l2', 'are', 'isospectral', 'by', 'a', 'theorem', 'of', 'kirby', 'the', 'matrix', 'l2', 'is', 'always', 'similar', 'to', 'a', 'symplectic', 'matrix', 'if', 'the', 'graph', 'has', 'an', 'even', 'number', 'of', 'simplices', 'the', 'hydrogen', 'relation', 'is', 'robust', 'any', 'schrodinger', 'operator', 'k', 'close', 'to', 'h', 'with', 'the', 'same', 'support', 'can', 'still', 'can', 'be', 'written', 'as', 'kll1', 'where', 'both', 'lxy', 'and', 'l1xy', 'are', 'zero', 'if', 'x', 'and', 'y', 'do', 'not', 'intersect']] | [-0.15138071536404657, 0.14711996199722224, -0.05181295568499164, 0.04647481876798503, -0.1012415819065857, -0.18830694629948333, 0.003551272959157359, 0.3611586260270666, -0.3259179753526537, -0.22484060198952316, 0.1097448189314243, -0.30855240585126675, -0.13109540032912098, 0.10722242473076965, -0.089636834356828, 0.02192263412821789, 0.08808680046191016, 0.11839654833734543, -0.0699501770326275, -0.20653885015483617, 0.32479062338296155, -0.030331005864850755, 0.1644402956431308, 0.07273922766564117, 0.06419948011567943, 0.02476518335540525, -0.0021179513013604183, 0.009993832957909697, -0.12031265350994792, 0.08328046726621158, 0.2613827315402556, 0.09421329915957441, 0.23182175972033292, -0.3959374787897435, -0.18380244031273338, 0.21932917630130594, 0.1498540683665355, 0.011464825614397838, 0.04029472469979241, -0.24237082026031037, 0.13356574430839496, -0.1091346036277669, -0.14409176411374408, -0.02935985348912337, 0.0815331058779107, 0.027833067488576158, -0.31465765078742564, 0.04416253983006093, 0.09936057591601805, 0.030712849529333074, -0.014772568689460802, -0.1627161733314014, -0.09360808050471613, 0.0815767591835042, -0.062445166156976484, 0.07294741368241375, 0.06744852245339478, -0.027208247084424576, -0.08043884109991434, 0.39308710881265474, -0.10252767071704677, -0.23695278423309157, 0.0796465336964254, -0.16348237283686598, -0.09831276240187105, 0.11297015984283379, 0.04778543311377606, 0.12094903857955201, -0.08577045925829391, 0.21043979860041873, -0.09878568176910366, 0.12792112859113497, 0.11117659975372424, 0.005687413454076953, 0.11292393472885207, 0.07722566975148352, 0.1445232616077357, 0.06594718796523838, -0.007921208548147908, -0.021137829801194708, -0.29595913636347343, -0.18262301467422565, -0.25144335262170486, 0.16402455886162154, -0.1789687820838398, -0.19762838565855584, 0.3382422333472112, 0.02523118774512444, 0.21111954473731617, 0.0884443864713169, 0.20933333936277035, 0.16914840278001397, 0.05961474212873244, 0.12868512179358566, 0.0858943537777205, 0.2453195668098157, 0.04954137416577644, -0.18633555982589975, 0.031074754141048867, 0.18282761781434106] |
1,803.01465 | Query and Output: Generating Words by Querying Distributed Word
Representations for Paraphrase Generation | Most recent approaches use the sequence-to-sequence model for paraphrase
generation. The existing sequence-to-sequence model tends to memorize the words
and the patterns in the training dataset instead of learning the meaning of the
words. Therefore, the generated sentences are often grammatically correct but
semantically improper. In this work, we introduce a novel model based on the
encoder-decoder framework, called Word Embedding Attention Network (WEAN). Our
proposed model generates the words by querying distributed word representations
(i.e. neural word embeddings), hoping to capturing the meaning of the according
words. Following previous work, we evaluate our model on two
paraphrase-oriented tasks, namely text simplification and short text
abstractive summarization. Experimental results show that our model outperforms
the sequence-to-sequence baseline by the BLEU score of 6.3 and 5.5 on two
English text simplification datasets, and the ROUGE-2 F1 score of 5.7 on a
Chinese summarization dataset. Moreover, our model achieves state-of-the-art
performances on these three benchmark datasets.
| cs.CL cs.LG | most recent approaches use the sequencetosequence model for paraphrase generation the existing sequencetosequence model tends to memorize the words and the patterns in the training dataset instead of learning the meaning of the words therefore the generated sentences are often grammatically correct but semantically improper in this work we introduce a novel model based on the encoderdecoder framework called word embedding attention network wean our proposed model generates the words by querying distributed word representations ie neural word embeddings hoping to capturing the meaning of the according words following previous work we evaluate our model on two paraphraseoriented tasks namely text simplification and short text abstractive summarization experimental results show that our model outperforms the sequencetosequence baseline by the bleu score of 63 and 55 on two english text simplification datasets and the rouge2 f1 score of 57 on a chinese summarization dataset moreover our model achieves stateoftheart performances on these three benchmark datasets | [['most', 'recent', 'approaches', 'use', 'the', 'sequencetosequence', 'model', 'for', 'paraphrase', 'generation', 'the', 'existing', 'sequencetosequence', 'model', 'tends', 'to', 'memorize', 'the', 'words', 'and', 'the', 'patterns', 'in', 'the', 'training', 'dataset', 'instead', 'of', 'learning', 'the', 'meaning', 'of', 'the', 'words', 'therefore', 'the', 'generated', 'sentences', 'are', 'often', 'grammatically', 'correct', 'but', 'semantically', 'improper', 'in', 'this', 'work', 'we', 'introduce', 'a', 'novel', 'model', 'based', 'on', 'the', 'encoderdecoder', 'framework', 'called', 'word', 'embedding', 'attention', 'network', 'wean', 'our', 'proposed', 'model', 'generates', 'the', 'words', 'by', 'querying', 'distributed', 'word', 'representations', 'ie', 'neural', 'word', 'embeddings', 'hoping', 'to', 'capturing', 'the', 'meaning', 'of', 'the', 'according', 'words', 'following', 'previous', 'work', 'we', 'evaluate', 'our', 'model', 'on', 'two', 'paraphraseoriented', 'tasks', 'namely', 'text', 'simplification', 'and', 'short', 'text', 'abstractive', 'summarization', 'experimental', 'results', 'show', 'that', 'our', 'model', 'outperforms', 'the', 'sequencetosequence', 'baseline', 'by', 'the', 'bleu', 'score', 'of', '63', 'and', '55', 'on', 'two', 'english', 'text', 'simplification', 'datasets', 'and', 'the', 'rouge2', 'f1', 'score', 'of', '57', 'on', 'a', 'chinese', 'summarization', 'dataset', 'moreover', 'our', 'model', 'achieves', 'stateoftheart', 'performances', 'on', 'these', 'three', 'benchmark', 'datasets']] | [-0.021990533852275757, -0.012598282078550639, -0.025913155366556327, 0.09953138930952839, -0.15793077763488614, -0.15396918870484164, 0.0759948376737731, 0.4522191625774691, -0.2559455837112374, -0.324702405174704, -0.017165344306512884, -0.36123761934179227, -0.15407908345437854, 0.20978988040741042, -0.13632270174735153, 0.06229752258131109, 0.18587666719931326, 0.10880868588145332, -0.023312289947506015, -0.3569204441170625, 0.2992186851264897, 0.008439897213400783, 0.41758934591014524, -0.004090179364491058, 0.15593395017602138, -0.08411702066108487, -0.07009902695809662, -0.08198232336455571, -0.04351304238686058, 0.20056509283236473, 0.30981217724834814, 0.2209204094067804, 0.30162258258573466, -0.34167415024957765, -0.22191819481208527, 0.043338361269745385, 0.13041209800978418, 0.12004340487539211, -0.0019957468129608684, -0.3841037154258964, 0.08220452022865893, -0.2066179844183161, 0.16295528596138434, -0.13950487863698263, 0.004830294052417709, -0.01484267084053595, -0.26718167098557677, 0.02623998697258924, 0.1991712680258053, 0.058173446490208766, -0.056495022505834255, -0.15238412219026176, 0.06262422011442188, 0.12559871051435997, 0.07717822812264785, 0.13519139180425555, 0.09111338808045395, -0.17745622999825028, -0.20572177496643762, 0.39422678258760196, -0.1110492345952049, -0.2555966066306849, 0.17536752669404546, 0.019654591172614966, -0.16936430177271464, 0.018839055684542184, 0.20389242399649352, 0.09368537240784224, -0.1548705817580125, -0.009292526490753517, -0.12009268950082753, 0.252725459410086, 0.11500036762108241, -0.04182501732506544, 0.17680212995343791, 0.2997937964054903, -0.0954764646012336, 0.11092177668960128, -0.11889940166790773, -0.07804283901044216, -0.19241902460711763, -0.07989613125468359, -0.15872423947133174, -0.05813243841495071, -0.13829531079107638, -0.15728192917365386, 0.47008567786236344, 0.3204637236501041, 0.1919365889227361, 0.18449056748374315, 0.30801799783856904, -0.04581616482219512, 0.0905139520519266, 0.09667914436584779, 0.10208871517342662, -0.06982316535370621, 0.1106665576811984, -0.13675226615496763, 0.106317754998025, 0.12236836006693345] |
1,803.01466 | Learning how to Prove: From the Coq Proof Assistant to Textbook Style | We have developed an alternative approach to teaching computer science
students how to prove. First, students are taught how to prove theorems with
the Coq proof assistant. In a second, more difficult, step students will
transfer their acquired skills to the area of textbook proofs. In this article
we present a realisation of the second step.
Proofs in Coq have a high degree of formality while textbook proofs have only
a medium one. Therefore our key idea is to reduce the degree of formality from
the level of Coq to textbook proofs in several small steps. For that purpose we
introduce three proof styles between Coq and textbook proofs, called line by
line comments, weakened line by line comments, and structure faithful proofs.
While this article is mostly conceptional we also report on experiences with
putting our approach into practise.
| cs.LO cs.SY | we have developed an alternative approach to teaching computer science students how to prove first students are taught how to prove theorems with the coq proof assistant in a second more difficult step students will transfer their acquired skills to the area of textbook proofs in this article we present a realisation of the second step proofs in coq have a high degree of formality while textbook proofs have only a medium one therefore our key idea is to reduce the degree of formality from the level of coq to textbook proofs in several small steps for that purpose we introduce three proof styles between coq and textbook proofs called line by line comments weakened line by line comments and structure faithful proofs while this article is mostly conceptional we also report on experiences with putting our approach into practise | [['we', 'have', 'developed', 'an', 'alternative', 'approach', 'to', 'teaching', 'computer', 'science', 'students', 'how', 'to', 'prove', 'first', 'students', 'are', 'taught', 'how', 'to', 'prove', 'theorems', 'with', 'the', 'coq', 'proof', 'assistant', 'in', 'a', 'second', 'more', 'difficult', 'step', 'students', 'will', 'transfer', 'their', 'acquired', 'skills', 'to', 'the', 'area', 'of', 'textbook', 'proofs', 'in', 'this', 'article', 'we', 'present', 'a', 'realisation', 'of', 'the', 'second', 'step', 'proofs', 'in', 'coq', 'have', 'a', 'high', 'degree', 'of', 'formality', 'while', 'textbook', 'proofs', 'have', 'only', 'a', 'medium', 'one', 'therefore', 'our', 'key', 'idea', 'is', 'to', 'reduce', 'the', 'degree', 'of', 'formality', 'from', 'the', 'level', 'of', 'coq', 'to', 'textbook', 'proofs', 'in', 'several', 'small', 'steps', 'for', 'that', 'purpose', 'we', 'introduce', 'three', 'proof', 'styles', 'between', 'coq', 'and', 'textbook', 'proofs', 'called', 'line', 'by', 'line', 'comments', 'weakened', 'line', 'by', 'line', 'comments', 'and', 'structure', 'faithful', 'proofs', 'while', 'this', 'article', 'is', 'mostly', 'conceptional', 'we', 'also', 'report', 'on', 'experiences', 'with', 'putting', 'our', 'approach', 'into', 'practise']] | [-0.046359253776193196, 0.030385353496967582, -0.1532793118319075, 0.0634017525174256, -0.18327392785410795, -0.19513023905456067, 0.05821696365019306, 0.3828435220506175, -0.22053810825039233, -0.33189385550628814, 0.0779190338981737, -0.23974257030391266, -0.1506099735810754, 0.21801885749612535, -0.14207131458512906, -0.00986552840497877, 0.08625825334872518, -0.007128933331530009, -0.020944883539674004, -0.30977445270400494, 0.3489023346270967, 0.022151971289089748, 0.23553406475111843, 0.11427635003679565, 0.07059123044767018, 0.0073305693721132615, -0.06121561171021313, -0.05154061997309327, -0.13129141249753176, 0.1912648953830025, 0.35328991204234106, 0.1567938618494996, 0.3568379734659434, -0.4412778843194246, -0.08077023610572463, -0.0003342555586381682, 0.1375158174412458, 0.14992476495348717, -0.04729683346283439, -0.30139079348051123, 0.09102407449723354, -0.1570816533425906, -0.12670228285216062, -0.09633723651724202, 0.02126534423857395, -0.014677246321558155, -0.12171679197552814, -0.05327872133867848, 0.19435934295844554, 0.18274365312286786, 0.03610527050082705, -0.13218711799542818, 0.039675489354080384, 0.12214219400193542, 0.05277908567139613, -0.0011586723705737053, 0.12731771391616867, -0.11248709591039058, -0.16229355702442783, 0.3595250067168048, -0.008715015156277721, -0.161107065196016, 0.1832606273329085, -0.09659106185260628, -0.1811614767980895, 0.0611782600171864, 0.15700594785490207, 0.13367598812827575, -0.13522433848328155, 0.05876808830653317, -0.021190479331250702, 0.22990486879633473, 0.09086903874828879, -0.013953479209781757, 0.1518526027045612, 0.12004347277273025, 0.012422543614437537, 0.13826170631551316, 0.04181652988939147, -0.10059967285820416, -0.3357471734584708, -0.23389479333002652, -0.16307190278811115, 0.04501293668789523, 0.007533852095158571, -0.12879122780037244, 0.3794324906958666, 0.20290170002595653, 0.11495930710474828, 0.11537348434628386, 0.3244930429916297, 0.06869900231415937, 0.05944753196589383, 0.032965541168648214, 0.19289409044265216, 0.12972171080764383, 0.2052022381486105, -0.060837306766188703, 0.0727334327862731, 0.1454019891896418] |
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