{"id":"https://openalex.org/W4414904152","doi":"https://doi.org/10.1088/2632-2153/ae107c","title":"Learning phases with quantum Monte Carlo simulation cell","display_name":"Learning phases with quantum Monte Carlo simulation cell","publication_year":2025,"publication_date":"2025-10-07","ids":{"openalex":"https://openalex.org/W4414904152","doi":"https://doi.org/10.1088/2632-2153/ae107c"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/ae107c","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ae107c","pdf_url":null,"source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1088/2632-2153/ae107c","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076905862","display_name":"Amrita Ghosh","orcid":"https://orcid.org/0000-0003-1417-0492"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]},{"id":"https://openalex.org/I4210119858","display_name":"National Center for Theoretical Sciences","ror":"https://ror.org/02mfp0b67","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210119858"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Amrita Ghosh","raw_affiliation_strings":["Center for Theory and Computation, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan Province, 300044, TAIWAN"],"raw_orcid":"https://orcid.org/0000-0003-1417-0492","affiliations":[{"raw_affiliation_string":"Center for Theory and Computation, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan Province, 300044, TAIWAN","institution_ids":["https://openalex.org/I25846049","https://openalex.org/I4210119858"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013884812","display_name":"Mugdha Sarkar","orcid":"https://orcid.org/0000-0002-3494-7249"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Mugdha Sarkar","raw_affiliation_strings":["Physics, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei City, 10617, TAIWAN"],"raw_orcid":"https://orcid.org/0000-0002-3494-7249","affiliations":[{"raw_affiliation_string":"Physics, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei City, 10617, TAIWAN","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016871377","display_name":"Ying-Jer Kao","orcid":"https://orcid.org/0000-0002-3329-6018"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Ying-Jer Kao","raw_affiliation_strings":["Physics, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei City, Taipei City, 10617, TAIWAN"],"raw_orcid":"https://orcid.org/0000-0002-3329-6018","affiliations":[{"raw_affiliation_string":"Physics, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei City, Taipei City, 10617, TAIWAN","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037153888","display_name":"Pochung Chen","orcid":"https://orcid.org/0000-0002-8092-7177"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Pochung Chen","raw_affiliation_strings":["Department of Physics, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan Province, 300044, TAIWAN"],"raw_orcid":"https://orcid.org/0000-0002-8092-7177","affiliations":[{"raw_affiliation_string":"Department of Physics, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan Province, 300044, TAIWAN","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013884812","https://openalex.org/A5016871377","https://openalex.org/A5037153888","https://openalex.org/A5076905862"],"corresponding_institution_ids":["https://openalex.org/I16733864","https://openalex.org/I25846049","https://openalex.org/I4210119858"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":2.0204,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90091868,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"6","issue":"4","first_page":"045017","last_page":"045017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8198999762535095,"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/T10320","display_name":"Neural Networks and Applications","score":0.8198999762535095,"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/interpretability","display_name":"Interpretability","score":0.8956999778747559},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5324000120162964},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5109000205993652},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4706000089645386},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4334000051021576},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.38370001316070557},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3614000082015991},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.34459999203681946}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8956999778747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.593500018119812},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5324000120162964},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.4936000108718872},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4706000089645386},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4334000051021576},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4196000099182129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41920000314712524},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.38370001316070557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3614000082015991},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C16016025","wikidata":"https://www.wikidata.org/wiki/Q3861408","display_name":"Quantum Monte Carlo","level":3,"score":0.33889999985694885},{"id":"https://openalex.org/C2778926657","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum system","level":3,"score":0.33180001378059387},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32030001282691956},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C42704618","wikidata":"https://www.wikidata.org/wiki/Q910917","display_name":"Spin (aerodynamics)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2842000126838684},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C15706264","wikidata":"https://www.wikidata.org/wiki/Q230883","display_name":"Quantum state","level":3,"score":0.27790001034736633},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2632-2153/ae107c","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ae107c","pdf_url":null,"source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2503.23098","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.23098","pdf_url":"https://arxiv.org/pdf/2503.23098","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:c504fca242b74fc7a3cd44736998cb08","is_oa":true,"landing_page_url":"https://doaj.org/article/c504fca242b74fc7a3cd44736998cb08","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":"Machine Learning: Science and Technology, Vol 6, Iss 4, p 045017 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/ae107c","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ae107c","pdf_url":null,"source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1247606989","display_name":null,"funder_award_id":"113-2112-M-002-033-MY3","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G5617203904","display_name":null,"funder_award_id":"112-2639-M-002-006-ASP","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G796364119","display_name":null,"funder_award_id":"113H0001L9","funder_id":"https://openalex.org/F4320323092","funder_display_name":"National Tsing Hua University"}],"funders":[{"id":"https://openalex.org/F4320323092","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1787224781","https://openalex.org/W1990455780","https://openalex.org/W1992040324","https://openalex.org/W2004352277","https://openalex.org/W2032480840","https://openalex.org/W2069693887","https://openalex.org/W2072703702","https://openalex.org/W2073511410","https://openalex.org/W2331494357","https://openalex.org/W2337082154","https://openalex.org/W2414456771","https://openalex.org/W2516533688","https://openalex.org/W2520014252","https://openalex.org/W2528710350","https://openalex.org/W2531147647","https://openalex.org/W2608461474","https://openalex.org/W2615003501","https://openalex.org/W2623750799","https://openalex.org/W2748390680","https://openalex.org/W2765597272","https://openalex.org/W2795407028","https://openalex.org/W2806077230","https://openalex.org/W2996496795","https://openalex.org/W2999329857","https://openalex.org/W3003976047","https://openalex.org/W3012938368","https://openalex.org/W3015369740","https://openalex.org/W3029316972","https://openalex.org/W3095662067","https://openalex.org/W3157035322","https://openalex.org/W4308562547","https://openalex.org/W4389135182","https://openalex.org/W4403714849","https://openalex.org/W4404167686"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"We":[1,75],"propose":[2],"the":[3,6,35,44,55,78,127,139,149,169,180,187],"use":[4],"of":[5,30,80,120,130,142,151],"\u2018spin-opstring\u2019,":[7],"derived":[8],"from":[9,179],"Stochastic":[10],"Series":[11],"Expansion":[12],"quantum":[13,91,132,199],"Monte":[14],"Carlo":[15],"(QMC)":[16],"simulations":[17],"as":[18,98,100,189],"machine":[19],"learning":[20,85],"(ML)":[21],"input":[22,181,194],"data.":[23,182],"It":[24],"offers":[25],"a":[26,68,117,131,190],"compact,":[27],"memory-efficient":[28],"representation":[29],"QMC":[31],"simulation":[32],"cells,":[33],"combining":[34],"initial":[36],"state":[37],"with":[38],"an":[39,145],"operator":[40],"string":[41],"that":[42,102,168],"encodes":[43],"state\u2019s":[45],"evolution":[46],"through":[47],"imaginary":[48],"time.":[49],"Using":[50,154],"supervised":[51],"ML,":[52],"we":[53,115,136,166],"demonstrate":[54,77],"input\u2019s":[56],"effectiveness":[57],"in":[58,67,83,126,198],"capturing":[59],"both":[60],"conventional":[61,123],"and":[62,66,93,162,173,192],"topological":[63],"phase":[64,133],"transitions,":[65],"regression":[69],"task":[70],"to":[71,111],"predict":[72],"non-local":[73],"observables.":[74],"also":[76],"capability":[79],"spin-opstring":[81,121,143,188],"data":[82],"transfer":[84],"by":[86],"training":[87],"models":[88,103,171],"on":[89,96,105,175],"one":[90],"system":[92,107],"successfully":[94],"predicting":[95],"another,":[97],"well":[99,110],"showing":[101],"trained":[104],"smaller":[106],"sizes":[108],"generalize":[109],"larger":[112],"ones.":[113],"Importantly,":[114],"illustrate":[116],"clear":[118],"advantage":[119],"over":[122],"spin":[124],"configurations":[125],"accurate":[128],"prediction":[129],"transition.":[134],"Finally,":[135],"show":[137,167],"how":[138],"inherent":[140],"structure":[141],"provides":[144],"elegant":[146],"framework":[147],"for":[148,196],"interpretability":[150,157],"ML":[152,170,197],"predictions.":[153],"two":[155],"state-of-the-art":[156],"techniques,":[158],"Layer-wise":[159],"Relevance":[160],"Propagation":[161],"SHapley":[163],"Additive":[164],"exPlanations,":[165],"learn":[172],"rely":[174],"physically":[176],"meaningful":[177],"features":[178],"Together,":[183],"these":[184],"findings":[185],"establish":[186],"broadly-applicable":[191],"interpretable":[193],"format":[195],"many-body":[200],"physics.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-11T08:15:01.531666","created_date":"2025-10-10T00:00:00"}