{"id":"https://openalex.org/W7134288201","doi":"https://doi.org/10.48550/arxiv.2603.06440","title":"Toward Generative Quantum Utility via Correlation-Complexity Map","display_name":"Toward Generative Quantum Utility via Correlation-Complexity Map","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134288201","doi":"https://doi.org/10.48550/arxiv.2603.06440"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06440","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128453381","display_name":"Chen-Yu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Chen-Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025464539","display_name":"Leonardo Placidi","orcid":"https://orcid.org/0000-0001-7693-7631"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Placidi, Leonardo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042008618","display_name":"Eric Brunner","orcid":"https://orcid.org/0000-0001-7631-6528"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brunner, Eric","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128427225","display_name":"Enrico Rinaldi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rinaldi, Enrico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5128453381"],"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/T11804","display_name":"Quantum many-body systems","score":0.3912999927997589,"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"}},"topics":[{"id":"https://openalex.org/T11804","display_name":"Quantum many-body systems","score":0.3912999927997589,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.3343999981880188,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.07680000364780426,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/generative-model","display_name":"Generative model","score":0.4747999906539917},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46140000224113464},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.45500001311302185},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.3939000070095062},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.37950000166893005},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.37400001287460327},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.3555999994277954}],"concepts":[{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4747999906539917},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46140000224113464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45879998803138733},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.45500001311302185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4366999864578247},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3847000002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38359999656677246},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3828999996185303},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.3555999994277954},{"id":"https://openalex.org/C96442724","wikidata":"https://www.wikidata.org/wiki/Q242188","display_name":"Invertible matrix","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.26170000433921814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2517000138759613},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06440","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06440","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06440","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:doi:10.48550/arxiv.2603.06440","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"We":[0,29,69],"study":[1],"a":[2,11,25,32,71,74,129,159,172,178,183,190,202],"practical":[3],"question":[4],"in":[5,201,228],"generative":[6,27,67,164,218],"quantum":[7,26,35,40,66,163,217],"machine":[8],"learning:":[9],"given":[10],"classical":[12,57,149,199],"dataset,":[13],"can":[14,124,131,212],"we":[15,123,154,170],"determine,":[16],"before":[17],"training,":[18],"whether":[19],"it":[20],"is":[21],"well":[22,128],"suited":[23],"to":[24,50,53,63,223],"model?":[28],"focus":[30],"on":[31],"class":[33],"of":[34,108,148],"circuits":[36,60],"known":[37],"as":[38,158],"instantaneous":[39],"polynomial-time":[41],"(IQP)":[42],"circuits,":[43,101],"whose":[44],"output":[45],"distributions":[46],"are":[47,61,220],"widely":[48],"believed":[49],"be":[51,114,132,224],"difficult":[52],"sample":[54],"from":[55,78,82],"using":[56],"methods.":[58],"These":[59,206],"used":[62],"build":[64],"our":[65,135],"models.":[68,119,150],"introduce":[70],"Correlation-Complexity":[72],"Map,":[73],"simple":[75,117],"diagnostic":[76],"built":[77],"two":[79],"quantities":[80],"computed":[81],"data":[83,157,229],"samples.":[84],"The":[85],"first":[86],"measures":[87],"how":[88,106,127,140],"closely":[89],"the":[90,103,109],"dataset's":[91,110],"spectral":[92],"correlation":[93,112],"patterns":[94],"resemble":[95],"those":[96],"naturally":[97],"produced":[98],"by":[99,116,134,167,186],"IQP":[100,180],"while":[102],"second":[104],"quantifies":[105],"much":[107],"structural":[111],"cannot":[113],"captured":[115],"pairwise":[118],"In":[120],"other":[121],"words,":[122],"estimate":[125],"beforehand":[126],"dataset":[130],"approximated":[133],"model":[136],"family":[137],"and":[138,188,194,230],"also":[139],"complex":[141],"its":[142],"correlations":[143],"are,":[144],"indicating":[145],"possible":[146],"failures":[147],"Applying":[151],"this":[152,168],"framework,":[153],"identify":[155],"turbulence":[156],"promising":[160],"target":[161],"for":[162],"modeling.":[165],"Guided":[166],"analysis,":[169],"use":[171],"latent-parameter":[173],"adaptation":[174],"scheme":[175],"that":[176,209],"reuses":[177],"compact":[179],"circuit":[181],"over":[182],"temporal":[184],"sequence":[185],"learning":[187],"interpolating":[189],"low-dimensional":[191],"latent":[192],"trajectory,":[193],"observe":[195],"competitive":[196],"performance":[197],"against":[198],"baselines":[200],"low-data,":[203],"low-parameter":[204],"regime.":[205],"results":[207],"suggest":[208],"dataset-level":[210],"diagnostics":[211],"help":[213],"prioritize":[214],"problems":[215],"where":[216],"models":[219],"most":[221],"likely":[222],"useful,":[225],"with":[226],"improvements":[227],"parameter":[231],"efficiency.":[232]},"counts_by_year":[],"updated_date":"2026-05-07T06:04:25.777469","created_date":"2026-03-10T00:00:00"}