{"id":"https://openalex.org/W4415251321","doi":"https://doi.org/10.48550/arxiv.2509.18483","title":"Physics-informed time series analysis with Kolmogorov-Arnold Networks under Ehrenfest constraints","display_name":"Physics-informed time series analysis with Kolmogorov-Arnold Networks under Ehrenfest constraints","publication_year":2025,"publication_date":"2025-09-23","ids":{"openalex":"https://openalex.org/W4415251321","doi":"https://doi.org/10.48550/arxiv.2509.18483"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2509.18483","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.18483","pdf_url":"https://arxiv.org/pdf/2509.18483","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.18483","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068208870","display_name":"Abhijit Sen","orcid":"https://orcid.org/0000-0003-2783-1763"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sen, Abhijit","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000840321","display_name":"I. V. Lukin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lukin, Illya V.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067092118","display_name":"K. C. Jacobs","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jacobs, Kurt","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067373405","display_name":"L. Kaplan","orcid":"https://orcid.org/0000-0002-7256-3203"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaplan, Lev","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005166495","display_name":"Andrii Sotnikov","orcid":"https://orcid.org/0000-0002-3632-4790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sotnikov, Andrii G.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5076308400","display_name":"Denys I. Bondar","orcid":"https://orcid.org/0000-0002-3626-4804"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bondar, Denys I.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5068208870"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12261","display_name":"Statistical Mechanics and Entropy","score":0.9653000235557556,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12261","display_name":"Statistical Mechanics and Entropy","score":0.9653000235557556,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9569000005722046,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9458000063896179,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.5893999934196472},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5058000087738037},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4350999891757965},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.41260001063346863},{"id":"https://openalex.org/keywords/dynamical-systems-theory","display_name":"Dynamical systems theory","score":0.40470001101493835},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.3846000134944916},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.3840000033378601},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.3763999938964844},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.35910001397132874}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6650000214576721},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.5893999934196472},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4350999891757965},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42179998755455017},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C79379906","wikidata":"https://www.wikidata.org/wiki/Q3174497","display_name":"Dynamical systems theory","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.3840000033378601},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3634999990463257},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3440000116825104},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2856999933719635},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2743000090122223},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C122527463","wikidata":"https://www.wikidata.org/wiki/Q578430","display_name":"Quantum decoherence","level":3,"score":0.26409998536109924},{"id":"https://openalex.org/C48753275","wikidata":"https://www.wikidata.org/wiki/Q11216","display_name":"Numerical analysis","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C15184713","wikidata":"https://www.wikidata.org/wiki/Q7269042","display_name":"Quantum dynamics","level":3,"score":0.25589999556541443}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2509.18483","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.18483","pdf_url":"https://arxiv.org/pdf/2509.18483","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.18483","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.18483","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.18483","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.18483","pdf_url":"https://arxiv.org/pdf/2509.18483","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"prediction":[1],"of":[2,10,60,133,148],"quantum":[3,23,48,61],"dynamical":[4],"responses":[5],"lies":[6],"at":[7],"the":[8,56,66,115,134,146,159],"heart":[9],"modern":[11],"physics.":[12],"Yet,":[13],"modeling":[14],"these":[15],"time-dependent":[16],"behaviors":[17],"remains":[18],"a":[19,51,70,100,150,177],"formidable":[20],"challenge":[21],"because":[22],"systems":[24,62],"evolve":[25],"in":[26,45,69],"high-dimensional":[27],"Hilbert":[28],"spaces,":[29],"often":[30,81],"rendering":[31],"traditional":[32],"numerical":[33],"methods":[34],"computationally":[35],"prohibitive.":[36],"While":[37],"large":[38],"language":[39],"models":[40],"have":[41],"achieved":[42],"remarkable":[43],"success":[44],"sequential":[46],"prediction,":[47],"dynamics":[49],"presents":[50],"fundamentally":[52,101],"different":[53],"challenge:":[54],"forecasting":[55],"entire":[57],"temporal":[58,155],"evolution":[59],"rather":[63],"than":[64],"merely":[65],"next":[67],"element":[68],"sequence.":[71],"Existing":[72],"neural":[73],"architectures":[74],"such":[75],"as":[76],"recurrent":[77],"and":[78,86,188],"convolutional":[79],"networks":[80],"require":[82],"vast":[83],"training":[84,126],"datasets":[85],"suffer":[87],"from":[88],"spurious":[89],"oscillations":[90],"that":[91,113,153,173],"compromise":[92],"physical":[93,189],"interpretability.":[94],"In":[95],"this":[96],"work,":[97],"we":[98],"introduce":[99,145],"new":[102],"approach:":[103],"Kolmogorov":[104],"Arnold":[105],"Networks":[106,141],"(KANs)":[107],"augmented":[108],"with":[109,123],"physics-informed":[110,174],"loss":[111],"functions":[112],"enforce":[114],"Ehrenfest":[116],"theorems.":[117],"Our":[118,170],"method":[119],"achieves":[120],"superior":[121],"accuracy":[122],"significantly":[124],"less":[125],"data:":[127],"it":[128,163],"requires":[129],"only":[130],"5.4":[131],"percent":[132],"samples":[135],"(200)":[136],"compared":[137],"to":[138],"Temporal":[139],"Convolution":[140],"(3,700).":[142],"We":[143],"further":[144],"Chain":[147],"KANs,":[149],"novel":[151],"architecture":[152],"embeds":[154],"causality":[156],"directly":[157],"into":[158],"model":[160],"design,":[161],"making":[162],"particularly":[164],"well-suited":[165],"for":[166],"time":[167],"series":[168],"modeling.":[169],"results":[171],"demonstrate":[172],"KANs":[175],"offer":[176],"compelling":[178],"advantage":[179],"over":[180],"conventional":[181],"black-box":[182],"models,":[183],"maintaining":[184],"both":[185],"mathematical":[186],"rigor":[187],"consistency":[190],"while":[191],"dramatically":[192],"reducing":[193],"data":[194],"requirements.":[195]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-16T00:00:00"}