{"id":"https://openalex.org/W7139927139","doi":"https://doi.org/10.48550/arxiv.2603.18554","title":"End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibration","display_name":"End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibration","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7139927139","doi":"https://doi.org/10.48550/arxiv.2603.18554"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.18554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.18554","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.18554","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130230035","display_name":"Xue Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yang, Xue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130225970","display_name":"Rigui Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Rigui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126589573","display_name":"Shizheng Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Shizheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046561636","display_name":"Dax Enshan Koh","orcid":"https://orcid.org/0000-0002-8968-591X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koh, Dax Enshan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044933432","display_name":"Siong Thye Goh","orcid":"https://orcid.org/0000-0001-7563-0961"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goh, Siong Thye","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130250963","display_name":"Yaochong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yaochong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130231692","display_name":"Hongyu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hongyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126634134","display_name":"Fuhui Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Fuhui","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5130230035"],"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.8485000133514404,"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":0.8485000133514404,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.042100001126527786,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11804","display_name":"Quantum many-body systems","score":0.035100001841783524,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5710999965667725},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.541700005531311},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5001999735832214},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.4918999969959259},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.47540000081062317},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46889999508857727},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4652999937534332},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41499999165534973}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6154999732971191},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5710999965667725},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.541700005531311},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.4918999969959259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4844000041484833},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46889999508857727},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43630000948905945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4253000020980835},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C203087015","wikidata":"https://www.wikidata.org/wiki/Q378201","display_name":"Qubit","level":3,"score":0.414900004863739},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.41119998693466187},{"id":"https://openalex.org/C2777967070","wikidata":"https://www.wikidata.org/wiki/Q18208114","display_name":"Intensity mapping","level":4,"score":0.4041999876499176},{"id":"https://openalex.org/C15706264","wikidata":"https://www.wikidata.org/wiki/Q230883","display_name":"Quantum state","level":3,"score":0.3125999867916107},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C111996192","wikidata":"https://www.wikidata.org/wiki/Q7269075","display_name":"Quantum noise","level":3,"score":0.2833000123500824},{"id":"https://openalex.org/C93038891","wikidata":"https://www.wikidata.org/wiki/Q1061524","display_name":"Intensity (physics)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C2778926657","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum system","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2624000012874603},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.2531999945640564},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.250900000333786},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.18554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.18554","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":"doi:10.48550/arxiv.2603.18554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.18554","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":false,"raw_source_name":null,"raw_type":"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":{"Quantum":[0],"Generative":[1],"Adversarial":[2],"Networks":[3],"(QGANs)":[4],"offer":[5],"a":[6,64,100,110,119],"promising":[7],"path":[8],"for":[9,20,105],"learning":[10],"data":[11],"distributions":[12],"on":[13,28,126],"near-term":[14],"quantum":[15,38,67,91],"devices.":[16],"However,":[17],"existing":[18],"QGANs":[19],"image":[21,46,62,138],"synthesis":[22,139],"avoid":[23],"direct":[24,75],"full-image":[25],"generation,":[26],"relying":[27],"classical":[29],"post-processing":[30],"or":[31],"patch-based":[32],"methods.":[33],"These":[34],"approaches":[35],"dilute":[36],"the":[37,79,86,94,148],"generator's":[39],"role":[40],"and":[41,84,93,109,128,136],"struggle":[42],"to":[43,115,118],"capture":[44],"global":[45],"semantics.":[47],"To":[48],"address":[49],"this,":[50],"we":[51],"propose":[52],"ReQGAN,":[53],"an":[54,59],"end-to-end":[55],"framework":[56],"that":[57,131],"synthesizes":[58],"entire":[60],"N=2^D-pixel":[61],"using":[63],"single":[65],"D-qubit":[66],"circuit.":[68],"ReQGAN":[69,132],"overcomes":[70],"two":[71],"fundamental":[72],"bottlenecks":[73],"hindering":[74],"pixel":[76,123],"generation:":[77],"(1)":[78],"rigid":[80],"classical-to-quantum":[81],"noise":[82],"interface":[83],"(2)":[85],"output":[87],"mismatch":[88],"between":[89],"normalized":[90],"statistics":[92],"desired":[95],"pixel-intensity":[96],"space.":[97],"We":[98],"introduce":[99],"learnable":[101],"Neural":[102],"Noise":[103],"Encoder":[104],"adaptive":[106],"state":[107],"preparation":[108],"differentiable":[111],"Intensity":[112],"Calibration":[113],"module":[114],"map":[116],"measurements":[117],"stable,":[120],"visually":[121],"meaningful":[122],"domain.":[124],"Experiments":[125],"MNIST":[127],"Fashion-MNIST":[129],"demonstrate":[130],"achieves":[133],"stable":[134],"training":[135],"effective":[137],"under":[140],"stringent":[141],"qubit":[142],"budgets,":[143],"with":[144],"ablation":[145],"studies":[146],"verifying":[147],"contribution":[149],"of":[150],"each":[151],"component.":[152]},"counts_by_year":[],"updated_date":"2026-03-21T06:36:02.116451","created_date":"2026-03-21T00:00:00"}