{"id":"https://openalex.org/W7224818470","doi":"https://doi.org/10.48550/arxiv.2610.39847","title":"Digital-Analog Quantum Neural Network with Long-Range Interactions","display_name":"Digital-Analog Quantum Neural Network with Long-Range Interactions","publication_year":2026,"publication_date":"2026-10-29","ids":{"openalex":"https://openalex.org/W7224818470","doi":"https://doi.org/10.48550/arxiv.2610.39847"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.39847","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.39847","pdf_url":"https://arxiv.org/pdf/2610.39847","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.39847","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005014252","display_name":"Zongyuan Ge","orcid":"https://orcid.org/0000-0002-5880-8673","observed_orcids":["https://orcid.org/0000-0002-5880-8673","https://orcid.org/0000-0001-6192-8601"]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I4405259049","display_name":"Shanghai Qi Zhi Institute","ror":"https://ror.org/01n14yn69","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4405259049"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Ge, Zongyuan","raw_affiliation_strings":["Department of Physics , National University of Singapore , Singapore 117551 , Singapore","Shanghai Qi Zhi Institute , Shanghai 200232 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics , National University of Singapore , Singapore 117551 , Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Shanghai Qi Zhi Institute , Shanghai 200232 , China","institution_ids":["https://openalex.org/I4405259049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134375545","display_name":"Daili Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405259049","display_name":"Shanghai Qi Zhi Institute","ror":"https://ror.org/01n14yn69","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4405259049"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Daili","raw_affiliation_strings":["School of Physics and Key Laboratory of Quantum State Construction and Manipulation","Shanghai Qi Zhi Institute , Shanghai 200232 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Key Laboratory of Quantum State Construction and Manipulation","institution_ids":[]},{"raw_affiliation_string":"Shanghai Qi Zhi Institute , Shanghai 200232 , China","institution_ids":["https://openalex.org/I4405259049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102014223","display_name":"Zewen Zhang","orcid":"https://orcid.org/0000-0003-2258-613X","observed_orcids":["https://orcid.org/0000-0003-2258-613X"]},"institutions":[{"id":"https://openalex.org/I4405259049","display_name":"Shanghai Qi Zhi Institute","ror":"https://ror.org/01n14yn69","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4405259049"]},{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Zewen","raw_affiliation_strings":["(Ministry of Education) , Renmin University of China , Beijing 100872 , China","Shanghai Qi Zhi Institute , Shanghai 200232 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"(Ministry of Education) , Renmin University of China , Beijing 100872 , China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Shanghai Qi Zhi Institute , Shanghai 200232 , China","institution_ids":["https://openalex.org/I4405259049"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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/long-range-interactions","display_name":"long-range interactions","score":0.9819999933242798},{"id":"https://openalex.org/keywords/power-law-interactions","display_name":"power-law interactions","score":0.7509999871253967},{"id":"https://openalex.org/keywords/ising-model","display_name":"Ising model","score":0.9610000252723694},{"id":"https://openalex.org/keywords/variational-quantum-algorithms","display_name":"variational quantum algorithms","score":0.8209999799728394},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.800000011920929},{"id":"https://openalex.org/keywords/transverse-field","display_name":"transverse field","score":0.7139999866485596},{"id":"https://openalex.org/keywords/nonlocal-coupling","display_name":"nonlocal coupling","score":0.703000009059906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6184999942779541},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.6000000238418579},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5877000093460083},{"id":"https://openalex.org/C51329190","wikidata":"https://www.wikidata.org/wiki/Q1076349","display_name":"Ising model","level":2,"score":0.5728999972343445},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5536999702453613},{"id":"https://openalex.org/C130979935","wikidata":"https://www.wikidata.org/wiki/Q568954","display_name":"Ansatz","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4462999999523163},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.39809998869895935},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.3978999853134155},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34450000524520874},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.3303000032901764},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.31130000948905945},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.302700012922287},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C2778926657","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum system","level":3,"score":0.2921000123023987},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.28459998965263367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28380000591278076},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C80891386","wikidata":"https://www.wikidata.org/wiki/Q7269084","display_name":"Quantum phases","level":4,"score":0.2685000002384186},{"id":"https://openalex.org/C2779094486","wikidata":"https://www.wikidata.org/wiki/Q18811578","display_name":"Quantum machine learning","level":4,"score":0.2639999985694885}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.39847","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.39847","pdf_url":"https://arxiv.org/pdf/2610.39847","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.39847","doi":"https://doi.org/10.48550/arxiv.2610.39847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.39847","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:2610.39847","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.39847","pdf_url":"https://arxiv.org/pdf/2610.39847","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":"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/W7224818470.pdf","grobid_xml":"https://content.openalex.org/works/W7224818470.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7156063838","https://openalex.org/W3110421208","https://openalex.org/W2904720022","https://openalex.org/W3145169319","https://openalex.org/W4416344473","https://openalex.org/W6889956278","https://openalex.org/W7117548288","https://openalex.org/W2946576068","https://openalex.org/W4384615827","https://openalex.org/W2976134173"],"abstract_inverted_index":{"Protocols":[0],"combining":[1],"single-qubit":[2],"digital":[3],"operations":[4],"with":[5,60,124],"analog":[6,55],"quantum":[7,25,31,202],"evolutions":[8],"bypass":[9],"large":[10],"numbers":[11],"of":[12,49,83,104,120],"two-qubit":[13],"entangling":[14],"gates,":[15],"offering":[16],"a":[17,36,194],"promising":[18],"approach":[19],"to":[20,65,133],"variational":[21],"algorithms":[22],"and":[23,68,75,87,102,111,153],"hybrid":[24,51],"simulation.":[26],"Focusing":[27],"on":[28,94],"the":[29,47,54,81,84,90,96,100,105,118,134,139,149,162,174,183],"digital-analog":[30,201],"neural":[32],"network":[33],"(DA-QNN)":[34],"as":[35,193],"representative":[37],"framework,":[38],"this":[39,69],"work":[40],"demonstrates":[41],"that":[42,180],"incorporating":[43],"long-range":[44,115,163,190],"interactions":[45,62],"enhances":[46],"efficiency":[48],"such":[50],"algorithms.":[52],"Within":[53],"blocks,":[56],"an":[57],"Ising":[58],"model":[59],"power-law":[61],"is":[63,71],"employed":[64],"generate":[66],"entanglement,":[67],"protocol":[70],"benchmarked":[72],"across":[73,138],"supervised":[74,108],"unsupervised":[76,158],"learning":[77],"tasks.":[78],"Beyond":[79],"discussing":[80],"effects":[82],"transverse":[85],"field":[86],"evolution":[88,130],"time,":[89],"primary":[91],"analysis":[92],"focuses":[93],"how":[95],"interaction":[97],"range":[98],"governs":[99],"expressibility":[101],"trainability":[103],"ansatz.":[106],"For":[107],"image":[109],"classification":[110],"many-body":[112],"phase":[113,159,185],"detection,":[114,160],"ansatzes":[116,176],"match":[117],"performance":[119],"their":[121],"short-range":[122,169],"counterparts":[123],"fewer":[125],"DA-QNN":[126],"layers":[127],"or":[128],"shorter":[129],"times,":[131],"owing":[132],"rapid":[135],"information":[136],"propagation":[137],"system":[140],"enabled":[141],"by":[142],"nonlocal":[143],"couplings.":[144],"This":[145],"resource":[146,196],"reduction":[147],"alleviates":[148],"classical":[150],"optimization":[151],"overhead":[152],"eases":[154],"experimental":[155],"implementation.":[156],"In":[157],"although":[161],"ansatz":[164],"does":[165],"not":[166],"outperform":[167],"its":[168],"counterpart":[170],"in":[171],"every":[172],"regime,":[173],"two":[175],"provide":[177],"complementary":[178],"signatures":[179],"jointly":[181],"reconstruct":[182],"complete":[184],"diagram.":[186],"These":[187],"findings":[188],"establish":[189],"interacting":[191],"platforms":[192],"compelling":[195],"for":[197],"advancing":[198],"practical,":[199],"large-scale":[200],"computing.":[203]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-10-31T00:00:00"}