{"id":"https://openalex.org/W7138308782","doi":"https://doi.org/10.1109/access.2026.3674830","title":"Efficient Optimization of Variational Quantum Algorithms via Gradient-Free Parameter Prediction","display_name":"Efficient Optimization of Variational Quantum Algorithms via Gradient-Free Parameter Prediction","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7138308782","doi":"https://doi.org/10.1109/access.2026.3674830"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3674830","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3674830","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3674830","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013754781","display_name":"Satwik Kundu","orcid":"https://orcid.org/0000-0002-2140-6486"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Satwik Kundu","raw_affiliation_strings":["School of EECS, The Pennsylvania State University, University Park, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2140-6486","affiliations":[{"raw_affiliation_string":"School of EECS, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050944647","display_name":"Debarshi Kundu","orcid":"https://orcid.org/0009-0000-3912-3831"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debarshi Kundu","raw_affiliation_strings":["School of EECS, The Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of EECS, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121534257","display_name":"Swaroop Ghosh","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Swaroop Ghosh","raw_affiliation_strings":["School of EECS, The Pennsylvania State University, University Park, PA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8753-490X","affiliations":[{"raw_affiliation_string":"School of EECS, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013754781"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50455675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"42485","last_page":"42499"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.944100022315979,"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":0.944100022315979,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.016100000590085983,"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":0.004699999932199717,"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/quantum","display_name":"Quantum","score":0.46799999475479126},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.39750000834465027},{"id":"https://openalex.org/keywords/quantum-computer","display_name":"Quantum computer","score":0.3871999979019165},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.3483999967575073},{"id":"https://openalex.org/keywords/quantum-algorithm","display_name":"Quantum algorithm","score":0.3301999866962433},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.32659998536109924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5964999794960022},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5343999862670898},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.46799999475479126},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.39750000834465027},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.3871999979019165},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3564000129699707},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.3301999866962433},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2816999852657318},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C192122513","wikidata":"https://www.wikidata.org/wiki/Q2835770","display_name":"Quantum phase estimation algorithm","level":5,"score":0.2587999999523163}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3674830","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3674830","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a03466862c3f484a878e0264691db921","is_oa":true,"landing_page_url":"https://doaj.org/article/a03466862c3f484a878e0264691db921","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":"IEEE Access, Vol 14, Pp 42485-42499 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3674830","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3674830","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3263384860","display_name":null,"funder_award_id":"2129675","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5551914454","display_name":null,"funder_award_id":"2113839","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6765727964","display_name":null,"funder_award_id":"2040667","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7383289970","display_name":null,"funder_award_id":"1821766","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8396843534","display_name":null,"funder_award_id":"2210963","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"exponential":[1],"runtime":[2],"of":[3,29,68,102,116,174,203,225],"quantum":[4,20],"simulators":[5],"on":[6,106,167],"classical":[7],"machines,":[8],"along":[9],"with":[10,18,139],"long":[11],"queue":[12],"times":[13],"and":[14,46,93,100,132,142,157,180,216],"high":[15],"costs":[16],"associated":[17],"real":[19],"devices,":[21],"presents":[22],"significant":[23],"challenges":[24],"for":[25,86,152,160,178,182],"the":[26,36,66,75,201,223],"efficient":[27],"optimization":[28,209],"Variational":[30,37],"Quantum":[31,38,41,47],"Algorithms":[32],"(VQAs)":[33],"such":[34],"as":[35],"Eigensolver":[39],"(VQE),":[40],"Approximate":[42],"Optimization":[43],"Algorithm":[44],"(QAOA),":[45],"Neural":[48],"Networks":[49],"(QNNs).":[50],"To":[51],"address":[52],"these":[53],"limitations,":[54],"we":[55,109],"propose":[56],"a":[57,114,172],"novel":[58],"approach,":[59],"DyPP":[60,112,169,206],"(Dynamic":[61],"Parameter":[62],"Prediction),":[63],"which":[64],"accelerates":[65],"convergence":[67],"VQAs":[69],"by":[70],"leveraging":[71],"regular":[72],"trends":[73],"in":[74,150,158,200],"parameter":[76],"weights":[77],"to":[78,119,129,136,171,176,185,191,213],"update":[79],"parameters":[80],"efficiently.":[81],"We":[82,145],"introduce":[83],"two":[84],"techniques":[85],"optimal":[87],"prediction":[88],"performance:":[89],"Naive":[90],"Prediction":[91,95],"(NaP)":[92],"Adaptive":[94],"(AdaP).":[96],"Through":[97],"extensive":[98],"experimentation":[99],"training":[101,121],"multiple":[103],"QNN":[104],"models":[105],"various":[107],"datasets,":[108],"demonstrate":[110],"that":[111],"achieves":[113],"speedup":[115,173,215],"approximately":[117],"2.25\u00d7compared":[118],"standard":[120],"methods,":[122],"while":[123,188],"also":[124],"providing":[125],"improved":[126],"accuracy":[127],"(up":[128,135],"2.3%":[130],"higher)":[131],"lower":[133],"loss":[134],"6.1%":[137],"reduction)":[138],"minimal":[140],"storage":[141],"computational":[143],"overhead.":[144],"further":[146],"evaluate":[147],"DyPP\u2019s":[148],"effectiveness":[149],"VQE":[151,179],"molecular":[153],"ground-state":[154],"energy":[155],"estimation":[156],"QAOA":[159,183],"graph":[161],"MaxCut.":[162],"Our":[163],"results":[164],"show":[165],"that,":[166],"average,":[168],"leads":[170],"up":[175,190,212],"3.1\u00d7":[177],"2.91\u00d7":[181],"compared":[184],"traditional":[186],"optimization,":[187],"requiring":[189,217],"3.3\u00d7":[192],"fewer":[193,219],"shots":[194],"(i.e.,":[195],"repeated":[196],"circuit":[197],"executions).":[198],"Even":[199],"presence":[202],"hardware":[204],"noise,":[205],"outperforms":[207],"existing":[208],"techniques,":[210],"delivering":[211],"3.33\u00d7":[214],"2.5\u00d7":[218],"shots,":[220],"thereby":[221],"enhancing":[222],"efficiency":[224],"VQAs.":[226]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-03-18T00:00:00"}
