{"id":"https://openalex.org/W7120109751","doi":"https://doi.org/10.48550/arxiv.2601.04732","title":"The Role of Quantum in Hybrid Quantum-Classical Neural Networks: An Empirical Assessment","display_name":"The Role of Quantum in Hybrid Quantum-Classical Neural Networks: An Empirical Assessment","publication_year":2026,"publication_date":"2026-01-08","ids":{"openalex":"https://openalex.org/W7120109751","doi":"https://doi.org/10.48550/arxiv.2601.04732"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2601.04732","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.04732","pdf_url":"https://arxiv.org/pdf/2601.04732","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2601.04732","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115426437","display_name":"Dominik Freinberger","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210140024","display_name":"RISC Software (Austria)","ror":"https://ror.org/0533vxh11","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210140024"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Freinberger, Dominik","raw_affiliation_strings":["Research Unit Medical Informatics , RISC Software GmbH , Softwarepark 32a , Hagenberg , 4232 , Upper Austria , Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Unit Medical Informatics , RISC Software GmbH , Softwarepark 32a , Hagenberg , 4232 , Upper Austria , Austria","institution_ids":["https://openalex.org/I4210140024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028987288","display_name":"Philipp Moser","orcid":"https://orcid.org/0000-0002-9717-6197","observed_orcids":["https://orcid.org/0000-0002-9717-6197"]},"institutions":[{"id":"https://openalex.org/I4210140024","display_name":"RISC Software (Austria)","ror":"https://ror.org/0533vxh11","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210140024"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Moser, Philipp","raw_affiliation_strings":["Research Unit Medical Informatics , RISC Software GmbH , Softwarepark 32a , Hagenberg , 4232 , Upper Austria , Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Unit Medical Informatics , RISC Software GmbH , Softwarepark 32a , Hagenberg , 4232 , Upper Austria , Austria","institution_ids":["https://openalex.org/I4210140024"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210140024"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"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":1.0,"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":1.0,"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":0.0,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.0,"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/hybrid-quantum-classical-neural-networks","display_name":"hybrid quantum-classical neural networks","score":0.9959999918937683},{"id":"https://openalex.org/keywords/quantum-machine-learning","display_name":"quantum machine learning","score":0.972000002861023},{"id":"https://openalex.org/keywords/quantum-neural-networks","display_name":"quantum neural networks","score":0.5659999847412109},{"id":"https://openalex.org/keywords/quantum-entanglement","display_name":"quantum entanglement","score":0.5680000185966492},{"id":"https://openalex.org/keywords/circuit-size","display_name":"circuit size","score":0.8299999833106995},{"id":"https://openalex.org/keywords/medical-image-classification","display_name":"medical image classification","score":0.7319999933242798},{"id":"https://openalex.org/keywords/biomedical-signal-classification","display_name":"biomedical signal classification","score":0.8140000104904175},{"id":"https://openalex.org/keywords/binary-classification","display_name":"binary classification","score":0.578000009059906},{"id":"https://openalex.org/keywords/quantum-advantage","display_name":"quantum advantage","score":0.3100000023841858}],"concepts":[{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.6891999840736389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6032999753952026},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4375},{"id":"https://openalex.org/C2779094486","wikidata":"https://www.wikidata.org/wiki/Q18811578","display_name":"Quantum machine learning","level":4,"score":0.4287000000476837},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C186468114","wikidata":"https://www.wikidata.org/wiki/Q836478","display_name":"Quantum network","level":4,"score":0.34200000762939453},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.33059999346733093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32710000872612},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31439998745918274},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C2778926657","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum system","level":3,"score":0.3043000102043152},{"id":"https://openalex.org/C15706264","wikidata":"https://www.wikidata.org/wiki/Q230883","display_name":"Quantum state","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C169699857","wikidata":"https://www.wikidata.org/wiki/Q2122243","display_name":"Quantum information","level":3,"score":0.2793999910354614},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.26409998536109924},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26089999079704285},{"id":"https://openalex.org/C190463098","wikidata":"https://www.wikidata.org/wiki/Q2081419","display_name":"Quantum technology","level":4,"score":0.2606000006198883},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C5320026","wikidata":"https://www.wikidata.org/wiki/Q2122216","display_name":"Quantum information science","level":4,"score":0.257999986410141},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2601.04732","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.04732","pdf_url":"https://arxiv.org/pdf/2601.04732","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2601.04732","doi":"https://doi.org/10.48550/arxiv.2601.04732","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.04732","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2601.04732","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.04732","pdf_url":"https://arxiv.org/pdf/2601.04732","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7120109751.pdf","grobid_xml":"https://content.openalex.org/works/W7120109751.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2095409369","https://openalex.org/W2790388700","https://openalex.org/W2794444783","https://openalex.org/W2896712926","https://openalex.org/W2954939433","https://openalex.org/W2968611999","https://openalex.org/W2970971581","https://openalex.org/W2995742898","https://openalex.org/W2998932335","https://openalex.org/W3075559820","https://openalex.org/W3097610849","https://openalex.org/W3136233239","https://openalex.org/W4220710689","https://openalex.org/W4229459353","https://openalex.org/W4280496556","https://openalex.org/W4296126438","https://openalex.org/W4312261998","https://openalex.org/W4376983366","https://openalex.org/W4381163518","https://openalex.org/W4392305906","https://openalex.org/W4392761808","https://openalex.org/W4392781618","https://openalex.org/W4401698596","https://openalex.org/W4402824346","https://openalex.org/W4407154363"],"related_works":["https://openalex.org/W7164017666","https://openalex.org/W7172427074","https://openalex.org/W7168923075","https://openalex.org/W7117475745","https://openalex.org/W4392305906","https://openalex.org/W4408982605","https://openalex.org/W7140082788","https://openalex.org/W7202176855","https://openalex.org/W4312080395","https://openalex.org/W4327773897"],"abstract_inverted_index":{"Quantum":[0],"machine":[1],"learning":[2],"has":[3],"emerged":[4],"as":[5,107,109,128],"a":[6,39,79,90],"promising":[7],"application":[8],"domain":[9],"for":[10,187,193],"near-term":[11,197],"quantum":[12,24,49,70,125,183],"hardware,":[13],"particularly":[14],"through":[15,78],"hybrid":[16,28,73,145,194],"quantum-classical":[17,74],"models":[18,146,195],"that":[19,141],"leverage":[20],"both":[21],"classical":[22,123,152,168],"and":[23,33,111,124,132,185,190],"processing.":[25],"Although":[26],"numerous":[27],"architectures":[29,77,96],"have":[30],"been":[31],"proposed":[32],"demonstrated":[34],"successfully":[35],"on":[36,66,97],"benchmark":[37],"tasks,":[38],"significant":[40],"open":[41],"question":[42],"remains":[43],"regarding":[44],"the":[45,52,67,119,162,178,181],"specific":[46],"contribution":[47],"of":[48,55,69,92,180],"components":[50,165,184],"to":[51,63,122,150],"overall":[53],"performance":[54,148,158],"these":[56],"models.":[57],"In":[58,114],"this":[59,136],"work,":[60],"we":[61,117,139],"aim":[62],"shed":[64],"light":[65],"impact":[68],"processing":[71,169],"within":[72],"neural":[75],"network":[76],"rigorous":[80],"statistical":[81],"study":[82],"under":[83],"ideal,":[84],"noise-free":[85],"simulation.":[86],"We":[87],"systematically":[88],"assess":[89],"selection":[91],"commonly":[93],"used":[94],"HQNN":[95],"three":[98],"binary":[99],"medical":[100,104],"classification":[101],"tasks":[102],"covering":[103],"signal":[105],"data":[106],"well":[108],"planar":[110],"volumetric":[112],"images.":[113],"doing":[115],"so,":[116],"examine":[118],"influence":[120],"attributable":[121],"aspects":[126],"such":[127],"encoding":[129],"schemes,":[130],"entanglement,":[131],"circuit":[133],"size.":[134],"Within":[135],"experimental":[137],"setting,":[138],"find":[140],"in":[142,155,196],"best-case":[143],"scenarios,":[144],"show":[147],"comparable":[149],"their":[151],"counterparts.":[153],"However,":[154],"most":[156],"cases,":[157],"metrics":[159],"deteriorate":[160],"when":[161],"investigated":[163],"QNN":[164],"replace":[166],"matched":[167],"layers.":[170],"Our":[171],"multi-modal":[172],"analysis":[173],"provides":[174],"empirical":[175],"insights":[176],"into":[177],"contributions":[179],"tested":[182],"advocates":[186],"cautious":[188],"claims":[189],"design":[191],"choices":[192],"applications.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-01-10T00:00:00"}