{"id":"https://openalex.org/W4416874430","doi":"https://doi.org/10.1109/qce65121.2025.00200","title":"Learning to Program Quantum Measurements for Machine Learning","display_name":"Learning to Program Quantum Measurements for Machine Learning","publication_year":2025,"publication_date":"2025-08-30","ids":{"openalex":"https://openalex.org/W4416874430","doi":"https://doi.org/10.1109/qce65121.2025.00200"},"language":null,"primary_location":{"id":"doi:10.1109/qce65121.2025.00200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qce65121.2025.00200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Quantum Computing and Engineering (QCE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021414038","display_name":"Samuel Yen-Chi Chen","orcid":"https://orcid.org/0000-0003-0114-4826"},"institutions":[{"id":"https://openalex.org/I166794780","display_name":"Wells Fargo (United States)","ror":"https://ror.org/037r2ff59","country_code":"US","type":"company","lineage":["https://openalex.org/I166794780"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samuel Yen-Chi Chen","raw_affiliation_strings":["Wells Fargo,New York,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wells Fargo,New York,NY,USA","institution_ids":["https://openalex.org/I166794780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034788095","display_name":"H. Eric Tseng","orcid":"https://orcid.org/0000-0001-9544-4226"},"institutions":[{"id":"https://openalex.org/I200870766","display_name":"Brookhaven National Laboratory","ror":"https://ror.org/02ex6cf31","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I200870766","https://openalex.org/I39565521","https://openalex.org/I4210142672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huan-Hsin Tseng","raw_affiliation_strings":["Brookhaven National Laboratory,AI Department,Upton,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brookhaven National Laboratory,AI Department,Upton,NY,USA","institution_ids":["https://openalex.org/I200870766"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100652782","display_name":"Hsin-Yi Lin","orcid":"https://orcid.org/0000-0001-5731-2353"},"institutions":[{"id":"https://openalex.org/I12524447","display_name":"Seton Hall University","ror":"https://ror.org/007tn5k56","country_code":"US","type":"education","lineage":["https://openalex.org/I12524447"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsin-Yi Lin","raw_affiliation_strings":["Seton Hall University,Department of Mathematics and Computer Science,South Orange,NJ,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seton Hall University,Department of Mathematics and Computer Science,South Orange,NJ,USA","institution_ids":["https://openalex.org/I12524447"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048176207","display_name":"Shinjae Yoo","orcid":"https://orcid.org/0000-0003-4378-6448"},"institutions":[{"id":"https://openalex.org/I200870766","display_name":"Brookhaven National Laboratory","ror":"https://ror.org/02ex6cf31","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I200870766","https://openalex.org/I39565521","https://openalex.org/I4210142672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shinjae Yoo","raw_affiliation_strings":["Brookhaven National Laboratory,AI Department,Upton,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brookhaven National Laboratory,AI Department,Upton,NY,USA","institution_ids":["https://openalex.org/I200870766"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17866324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1826","last_page":"1836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9693999886512756,"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":0.9693999886512756,"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":0.010499999858438969,"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":0.007799999788403511,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.8019000291824341},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.6621999740600586},{"id":"https://openalex.org/keywords/quantum-machine-learning","display_name":"Quantum machine learning","score":0.5803999900817871},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5698999762535095},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5321999788284302},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5235000252723694},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4894999861717224},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3944000005722046},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.39149999618530273}],"concepts":[{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.8019000291824341},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.6621999740600586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6151000261306763},{"id":"https://openalex.org/C2779094486","wikidata":"https://www.wikidata.org/wiki/Q18811578","display_name":"Quantum machine learning","level":4,"score":0.5803999900817871},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5698999762535095},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5235000252723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49779999256134033},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4345000088214874},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.39149999618530273},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.3714999854564667},{"id":"https://openalex.org/C124148022","wikidata":"https://www.wikidata.org/wiki/Q2122210","display_name":"Quantum circuit","level":5,"score":0.36010000109672546},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C2778926657","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum system","level":3,"score":0.3504999876022339},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.349700003862381},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.33739998936653137},{"id":"https://openalex.org/C58849907","wikidata":"https://www.wikidata.org/wiki/Q2118982","display_name":"Quantum gate","level":4,"score":0.329800009727478},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32580000162124634},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3084999918937683},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C94940","wikidata":"https://www.wikidata.org/wiki/Q652941","display_name":"Hermitian matrix","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C89143813","wikidata":"https://www.wikidata.org/wiki/Q17105423","display_name":"Quantum sensor","level":5,"score":0.2597000002861023},{"id":"https://openalex.org/C11255438","wikidata":"https://www.wikidata.org/wiki/Q7269085","display_name":"Quantum process","level":4,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/qce65121.2025.00200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qce65121.2025.00200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Quantum Computing and Engineering (QCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2053186076","https://openalex.org/W2089217417","https://openalex.org/W2097308346","https://openalex.org/W2161685427","https://openalex.org/W2766447205","https://openalex.org/W2790388700","https://openalex.org/W2796293949","https://openalex.org/W2990961515","https://openalex.org/W3045093737","https://openalex.org/W3082455048","https://openalex.org/W3092829287","https://openalex.org/W3093944484","https://openalex.org/W3111162498","https://openalex.org/W3116184205","https://openalex.org/W3141755656","https://openalex.org/W3173431334","https://openalex.org/W3196514226","https://openalex.org/W3207377511","https://openalex.org/W4213212652","https://openalex.org/W4221167764","https://openalex.org/W4372259985","https://openalex.org/W4372267505","https://openalex.org/W4372349431","https://openalex.org/W4382203069","https://openalex.org/W4385261005","https://openalex.org/W4389607983","https://openalex.org/W4392909937","https://openalex.org/W4401954443","https://openalex.org/W4402351602","https://openalex.org/W4406261273","https://openalex.org/W4406261916","https://openalex.org/W4406262044","https://openalex.org/W4406262067","https://openalex.org/W4406266084","https://openalex.org/W4406276699","https://openalex.org/W4406355331","https://openalex.org/W4408355722","https://openalex.org/W4410770879","https://openalex.org/W4410771607","https://openalex.org/W4412956029"],"related_works":[],"abstract_inverted_index":{"The":[0,32],"rapid":[1],"advancements":[2],"in":[3,162],"quantum":[4,19,63,113,142,147,186],"computing":[5],"(QC)":[6],"and":[7,61,139],"machine":[8,20],"learning":[9,21,124],"(ML)":[10],"have":[11],"sparked":[12],"significant":[13],"interest,":[14],"driving":[15],"extensive":[16],"exploration":[17],"of":[18,29,34,49,56,66,73,98,111,129,212],"(QML)":[22],"algorithms":[23],"to":[24,45,134,160,192],"address":[25],"a":[26,42,112],"wide":[27],"range":[28],"complex":[30],"challenges.":[31],"development":[33],"high-performance":[35],"QML":[36,74,84,213],"models":[37,85],"requires":[38],"expert-level":[39],"expertise,":[40],"presenting":[41],"key":[43],"challenge":[44],"the":[46,54,71,77,95,99,109,115,130,136,140,146,154,158,167,177,209],"widespread":[47],"adoption":[48],"QML.":[50],"Critical":[51],"obstacles":[52],"include":[53],"design":[55],"effective":[57],"data":[58,169],"encoding":[59],"strategies":[60],"parameterized":[62,137],"circuits,":[64,187],"both":[65],"which":[67],"are":[68,150],"vital":[69],"for":[70],"performance":[72,199],"models.":[75,214],"Furthermore,":[76],"measurement":[78,88],"process":[79],"is":[80],"often":[81],"neglected-most":[82],"existing":[83,193],"employ":[86],"predefined":[87],"schemes":[89],"that":[90,107,176],"may":[91],"not":[92],"align":[93],"with":[94],"specific":[96],"requirements":[97],"targeted":[100],"problem.":[101],"We":[102],"propose":[103],"an":[104,121],"innovative":[105],"framework":[106],"renders":[108],"observable":[110,148],"system-specifically,":[114],"Hermitian":[116],"matrix-trainable.":[117],"This":[118],"approach":[119],"employs":[120],"end-to-end":[122],"differentiable":[123],"framework,":[125],"enabling":[126],"simultaneous":[127],"optimization":[128],"neural":[131,155],"network":[132],"used":[133],"program":[135],"observables":[138,159,182],"standard":[141],"circuit":[143],"parameters.":[144],"Notably,":[145,195],"parameters":[149],"dynamically":[151,183],"programmed":[152],"by":[153],"network,":[156],"allowing":[157],"adapt":[161],"real":[163],"time":[164],"based":[165],"on":[166],"input":[168],"stream.":[170],"Through":[171],"numerical":[172],"simulations,":[173],"we":[174],"demonstrate":[175],"proposed":[178],"method":[179],"effectively":[180],"programs":[181],"within":[184],"variational":[185],"achieving":[188],"superior":[189],"results":[190],"compared":[191],"approaches.":[194],"it":[196],"delivers":[197],"enhanced":[198],"metrics,":[200],"such":[201],"as":[202],"higher":[203],"classification":[204],"accuracy,":[205],"thereby":[206],"significantly":[207],"improving":[208],"overall":[210],"effectiveness":[211]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-01T00:00:00"}
