{"id":"https://openalex.org/W7146976123","doi":"https://doi.org/10.1109/access.2026.3679418","title":"Noncommutative Quantum Dynamics for Feature Representation Learning","display_name":"Noncommutative Quantum Dynamics for Feature Representation Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7146976123","doi":"https://doi.org/10.1109/access.2026.3679418"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3679418","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3679418","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3679418","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119772604","display_name":"Hirokazu SHIMAUCHI","orcid":null},"institutions":[{"id":"https://openalex.org/I84400586","display_name":"Future University Hakodate","ror":"https://ror.org/05szw2z23","country_code":"JP","type":"education","lineage":["https://openalex.org/I84400586"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hirokazu Shimauchi","raw_affiliation_strings":["Future University Hakodate, Hakodate, Hokkaido, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9160-5667","affiliations":[{"raw_affiliation_string":"Future University Hakodate, Hakodate, Hokkaido, Japan","institution_ids":["https://openalex.org/I84400586"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5119772604"],"corresponding_institution_ids":["https://openalex.org/I84400586"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64976456,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"53529","last_page":"53571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.4034999907016754,"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"}},"topics":[{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.4034999907016754,"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/T11804","display_name":"Quantum many-body systems","score":0.3828999996185303,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.05860000103712082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6104000210762024},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.5947999954223633},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5473999977111816},{"id":"https://openalex.org/keywords/hidden-variable-theory","display_name":"Hidden variable theory","score":0.4505999982357025},{"id":"https://openalex.org/keywords/noncommutative-geometry","display_name":"Noncommutative geometry","score":0.4242999851703644},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4147999882698059},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4124999940395355},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.398499995470047},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.36230000853538513}],"concepts":[{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6104000210762024},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.5947999954223633},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5473999977111816},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5271999835968018},{"id":"https://openalex.org/C137002209","wikidata":"https://www.wikidata.org/wiki/Q898521","display_name":"Hidden variable theory","level":3,"score":0.4505999982357025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4260999858379364},{"id":"https://openalex.org/C68797384","wikidata":"https://www.wikidata.org/wiki/Q2746792","display_name":"Noncommutative geometry","level":2,"score":0.4242999851703644},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40540000796318054},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39410001039505005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3626999855041504},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3589000105857849},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.3370000123977661},{"id":"https://openalex.org/C203087015","wikidata":"https://www.wikidata.org/wiki/Q378201","display_name":"Qubit","level":3,"score":0.32839998602867126},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.31279999017715454},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.2736000120639801},{"id":"https://openalex.org/C2779094486","wikidata":"https://www.wikidata.org/wiki/Q18811578","display_name":"Quantum machine learning","level":4,"score":0.2736000120639801},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C110340908","wikidata":"https://www.wikidata.org/wiki/Q131594","display_name":"Pauli exclusion principle","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2531000077724457},{"id":"https://openalex.org/C79379906","wikidata":"https://www.wikidata.org/wiki/Q3174497","display_name":"Dynamical systems theory","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3679418","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3679418","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ca0133908bdf429ebacd751cd317793e","is_oa":true,"landing_page_url":"https://doaj.org/article/ca0133908bdf429ebacd751cd317793e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 53529-53571 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3679418","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3679418","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,151],"propose":[1],"an":[2,169],"explicit":[3,94],"feature":[4,146],"representation":[5],"for":[6],"supervised":[7],"learning":[8],"derived":[9],"from":[10,210],"short":[11],"quantum":[12,143],"dynamical":[13],"trajectories":[14],"composed":[15],"of":[16,46,57,61,120,227],"generally":[17],"noncommuting":[18],"operations,":[19],"conceptually":[20],"inspired":[21],"by":[22,53],"reservoir":[23],"computing":[24],"in":[25],"that":[26],"fixed,":[27],"untrained":[28],"dynamics":[29],"are":[30,51,76,102,126],"coupled":[31],"to":[32,78,185,206],"a":[33,40,44,58,112,117,211],"simple":[34],"trained":[35,90],"readout.":[36],"For":[37],"each":[38],"input,":[39],"fixed-depth":[41],"circuit":[42,74],"generates":[43],"sequence":[45],"prefix":[47],"states,":[48],"and":[49,63,111,125,135,162,178,203,221],"features":[50,134,235],"formed":[52],"concatenating":[54],"expectation":[55],"values":[56],"predetermined":[59],"set":[60],"single-":[62],"two-qubit":[64],"Pauli":[65],"observables":[66],"recorded":[67],"across":[68],"depths;":[69],"multiple":[70],"randomized":[71],"but":[72],"fixed":[73,177],"instantiations":[75],"aggregated":[77],"improve":[79],"stability.":[80],"A":[81,165],"classical":[82,129],"<italic":[83],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[84],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">l</i>2-":[85],"regularized":[86],"logistic-regression":[87],"readout":[88],"is":[89,231],"on":[91,116],"the":[92,196,208,216,225,228,233],"resulting":[93],"features.":[95],"To":[96],"isolate":[97],"representational":[98],"effects,":[99],"all":[100],"methods":[101],"evaluated":[103],"under":[104,176],"identical":[105],"preprocessing,":[106],"repeated":[107],"stratified":[108],"holdout":[109],"splits,":[110],"unified":[113],"model-selection":[114],"protocol":[115],"controlled":[118,154],"subset":[119],"11":[121],"tabular":[122],"classification":[123],"datasets,":[124],"compared":[127],"against":[128],"baselines,":[130,144],"including":[131],"random":[132],"Fourier":[133],"second-degree":[136],"polynomial":[137],"expansions,":[138],"as":[139,141],"well":[140],"reservoir-style":[142],"with":[145,173],"dimensionality":[147],"matched":[148],"when":[149],"feasible.":[150],"further":[152],"examine":[153],"variants":[155],"targeting":[156],"commutativity,":[157],"entangling":[158,229],"structure,":[159],"history":[160,222],"concatenation,":[161,223],"observable":[163],"choice.":[164],"staged":[166],"evaluation":[167],"contrasts":[168],"idealized":[170],"exact-expectation":[171],"regime":[172],"finite-shot":[174,242],"estimation":[175],"larger":[179],"measurement":[180],"budgets,":[181],"thereby":[182],"assessing":[183],"sensitivity":[184],"sampling":[186],"noise":[187],"after":[188],"re-tuning":[189],"regularization.":[190],"Beyond":[191],"predictive":[192],"performance,":[193],"we":[194],"analyze":[195],"induced":[197],"geometry":[198],"via":[199],"empirical":[200],"kernel":[201,239],"spectra":[202],"effective-dimension":[204],"diagnostics":[205],"contextualize":[207],"representations":[209],"regularization-aware":[212],"capacity":[213],"perspective.":[214],"Empirically,":[215],"strongest":[217],"support":[218],"concerns":[219],"noncommutativity":[220],"whereas":[224],"contribution":[226],"block":[230],"mixed;":[232],"trajectory-based":[234],"induce":[236],"empirically":[237],"distinct":[238],"geometries,":[240],"while":[241],"robustness":[243],"remains":[244],"strongly":[245],"task-and":[246],"configuration-dependent.":[247]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-04-02T00:00:00"}