{"id":"https://openalex.org/W4402589817","doi":"https://doi.org/10.1088/2632-2153/ad7cc1","title":"Benchmarking of quantum fidelity kernels for Gaussian process regression","display_name":"Benchmarking of quantum fidelity kernels for Gaussian process regression","publication_year":2024,"publication_date":"2024-09-01","ids":{"openalex":"https://openalex.org/W4402589817","doi":"https://doi.org/10.1088/2632-2153/ad7cc1"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/ad7cc1","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad7cc1","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad7cc1/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad7cc1/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104084334","display_name":"Xuyang Guo","orcid":"https://orcid.org/0009-0007-4962-3515"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Xuyang Guo","raw_affiliation_strings":["Department of Chemistry, University of British Columbia, Vancouver, B.C. V6T 1Z1, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Chemistry, University of British Columbia, Vancouver, B.C. V6T 1Z1, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008029440","display_name":"Jun Dai","orcid":"https://orcid.org/0000-0002-2732-7316"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jun Dai","raw_affiliation_strings":["Department of Chemistry, University of British Columbia, Vancouver, B.C. V6T 1Z1, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Chemistry, University of British Columbia, Vancouver, B.C. V6T 1Z1, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087205640","display_name":"Roman V. Krems","orcid":"https://orcid.org/0000-0002-9918-211X"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Roman V Krems","raw_affiliation_strings":["Stewart Blusson Quantum Matter Institute, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada"],"affiliations":[{"raw_affiliation_string":"Stewart Blusson Quantum Matter Institute, University of British Columbia, Vancouver, B.C. V6T 1Z4, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5104084334"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":0.3512,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66499903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"5","issue":"3","first_page":"035081","last_page":"035081"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9739999771118164,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9739999771118164,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9467999935150146,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.8110613822937012},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.7342246770858765},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6044905781745911},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5689891576766968},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5387275218963623},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5291270017623901},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46752098202705383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4467867612838745},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3458203673362732},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32377439737319946},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2899024486541748},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24056509137153625},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.153395414352417},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.09736120700836182},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.0827169120311737},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08125045895576477},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.058245688676834106}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8110613822937012},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.7342246770858765},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6044905781745911},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5689891576766968},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5387275218963623},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5291270017623901},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46752098202705383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4467867612838745},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3458203673362732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32377439737319946},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2899024486541748},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24056509137153625},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.153395414352417},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.09736120700836182},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0827169120311737},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08125045895576477},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.058245688676834106},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2632-2153/ad7cc1","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad7cc1","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad7cc1/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2407.15961","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.15961","pdf_url":"https://arxiv.org/pdf/2407.15961","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:e48ccf428aee4c598aacb148ed477dfe","is_oa":true,"landing_page_url":"https://doaj.org/article/e48ccf428aee4c598aacb148ed477dfe","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 5, Iss 3, p 035081 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/ad7cc1","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad7cc1","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad7cc1/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2165548363","display_name":null,"funder_award_id":"Canada","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G8284766523","display_name":null,"funder_award_id":"(NSERC)","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320321487","display_name":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402589817.pdf","grobid_xml":"https://content.openalex.org/works/W4402589817.grobid-xml"},"referenced_works_count":110,"referenced_works":["https://openalex.org/W1998217267","https://openalex.org/W2114112946","https://openalex.org/W2117980155","https://openalex.org/W2168175751","https://openalex.org/W2207520826","https://openalex.org/W2412592673","https://openalex.org/W2489886790","https://openalex.org/W2494686247","https://openalex.org/W2527658566","https://openalex.org/W2560696273","https://openalex.org/W2594860211","https://openalex.org/W2790441086","https://openalex.org/W2792946961","https://openalex.org/W2798434869","https://openalex.org/W2808979145","https://openalex.org/W2906538035","https://openalex.org/W2952619856","https://openalex.org/W2999629616","https://openalex.org/W3001801734","https://openalex.org/W3005709073","https://openalex.org/W3007306537","https://openalex.org/W3023876973","https://openalex.org/W3024243470","https://openalex.org/W3036307007","https://openalex.org/W3036744022","https://openalex.org/W3043562389","https://openalex.org/W3075454079","https://openalex.org/W3086641254","https://openalex.org/W3090365491","https://openalex.org/W3092496008","https://openalex.org/W3104395828","https://openalex.org/W3111467040","https://openalex.org/W3121074625","https://openalex.org/W3121778920","https://openalex.org/W3123403316","https://openalex.org/W3147993824","https://openalex.org/W3158182757","https://openalex.org/W3165351650","https://openalex.org/W3169581362","https://openalex.org/W3169665891","https://openalex.org/W3198579014","https://openalex.org/W3198799154","https://openalex.org/W3208667952","https://openalex.org/W3211629182","https://openalex.org/W3213257350","https://openalex.org/W3214211083","https://openalex.org/W4210600166","https://openalex.org/W4221165036","https://openalex.org/W4223588155","https://openalex.org/W4226048270","https://openalex.org/W4280568025","https://openalex.org/W4281287768","https://openalex.org/W4288081075","https://openalex.org/W4289334409","https://openalex.org/W4313593847","https://openalex.org/W4313830797","https://openalex.org/W4318975179","https://openalex.org/W4319166667","https://openalex.org/W4321125021","https://openalex.org/W4361212435","https://openalex.org/W4362013221","https://openalex.org/W4367180862","https://openalex.org/W4378194280","https://openalex.org/W4383898636","https://openalex.org/W4385406777","https://openalex.org/W4385443553","https://openalex.org/W4386523533","https://openalex.org/W4387899421","https://openalex.org/W4389526726","https://openalex.org/W4391141387","https://openalex.org/W4391349502","https://openalex.org/W4391612726","https://openalex.org/W4398521005","https://openalex.org/W4399991957","https://openalex.org/W6631190155","https://openalex.org/W6632974064","https://openalex.org/W6638780994","https://openalex.org/W6679226052","https://openalex.org/W6681609451","https://openalex.org/W6681765526","https://openalex.org/W6745256532","https://openalex.org/W6753275298","https://openalex.org/W6755964158","https://openalex.org/W6758352740","https://openalex.org/W6765443743","https://openalex.org/W6771396984","https://openalex.org/W6773142731","https://openalex.org/W6773665884","https://openalex.org/W6776033166","https://openalex.org/W6779403110","https://openalex.org/W6785846972","https://openalex.org/W6788172518","https://openalex.org/W6794232156","https://openalex.org/W6795610815","https://openalex.org/W6797611524","https://openalex.org/W6798987241","https://openalex.org/W6799085204","https://openalex.org/W6803654554","https://openalex.org/W6803956798","https://openalex.org/W6808653556","https://openalex.org/W6841081014","https://openalex.org/W6842469858","https://openalex.org/W6846024199","https://openalex.org/W6850847842","https://openalex.org/W6853010227","https://openalex.org/W6855421628","https://openalex.org/W6856271122","https://openalex.org/W6857796349","https://openalex.org/W6859237795","https://openalex.org/W6894219385"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655","https://openalex.org/W2115519811"],"abstract_inverted_index":{"Abstract":[0],"Quantum":[1],"computing":[2],"algorithms":[3],"have":[4],"been":[5],"shown":[6,111],"to":[7,40,75,83,112,138,207],"produce":[8],"performant":[9],"quantum":[10,22,35,55,80,85,98,120,125,131,214],"kernels":[11,23,50,56,86,132,201,215,226],"for":[12,24,57,87,148,172,181,189,202,227],"machine-learning":[13],"classification":[14],"problems.":[15,229],"Here,":[16],"we":[17],"examine":[18],"the":[19,42,48,52,71,77,94,97,103,106,156,208,218],"performance":[20,104],"of":[21,27,34,47,70,79,96,105,142,155,164,199],"regression":[25,205,228],"problems":[26],"practical":[28],"interest.":[29],"For":[30],"an":[31,64,68],"unbiased":[32],"benchmarking":[33],"kernels,":[36,108],"it":[37],"is":[38,110,168],"necessary":[39],"construct":[41],"most":[43,53],"optimal":[44,54],"functional":[45],"form":[46],"classical":[49,200,225],"and":[51,109,185],"each":[58],"given":[59],"data":[60],"set.":[61],"We":[62,128,193],"develop":[63],"algorithm":[65,92],"that":[66,130,195,213],"uses":[67],"analog":[69],"Bayesian":[72],"information":[73],"criterion":[74],"optimize":[76],"sequence":[78],"gates":[81,121],"used":[82,137],"estimate":[84],"Gaussian":[88,203],"process":[89,204],"models.":[90],"The":[91,151],"increases":[93],"complexity":[95],"circuits":[99],"incrementally,":[100],"while":[101],"improving":[102],"resulting":[107],"yield":[113],"much":[114],"higher":[115],"model":[116],"accuracy":[117],"with":[118,160],"fewer":[119],"than":[122],"a":[123,161,196],"fixed":[124],"circuit":[126],"ansatz.":[127],"demonstrate":[129],"thus":[133],"obtained":[134,159],"can":[135,216],"be":[136],"build":[139],"accurate":[140],"models":[141],"global":[143],"potential":[144],"energy":[145,166],"surfaces":[146],"(PES)":[147],"polyatomic":[149],"molecules.":[150],"average":[152],"interpolation":[153],"error":[154],"six-dimensional":[157],"PES":[158],"random":[162],"distribution":[163],"2000":[165],"points":[167],"16":[169],"cm":[170,179,187],"\u22121":[171,180,188],"H":[173,182],"3":[174],"O":[175],"+":[176],",":[177],"15":[178],"2":[183,191],"CO":[184],"88":[186],"HNO":[190],".":[192],"show":[194],"compositional":[197],"optimization":[198],"converges":[206],"same":[209],"errors.":[210],"This":[211],"indicates":[212],"achieve":[217],"same,":[219],"though":[220],"not":[221],"better,":[222],"expressivity":[223],"as":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
