{"id":"https://openalex.org/W3045342273","doi":"https://doi.org/10.22331/q-2021-06-07-469","title":"Efficient Bayesian phase estimation using mixed priors","display_name":"Efficient Bayesian phase estimation using mixed priors","publication_year":2021,"publication_date":"2021-06-07","ids":{"openalex":"https://openalex.org/W3045342273","doi":"https://doi.org/10.22331/q-2021-06-07-469","mag":"3045342273"},"language":"en","primary_location":{"id":"doi:10.22331/q-2021-06-07-469","is_oa":true,"landing_page_url":"https://doi.org/10.22331/q-2021-06-07-469","pdf_url":"https://quantum-journal.org/papers/q-2021-06-07-469/pdf/","source":{"id":"https://openalex.org/S4210226432","display_name":"Quantum","issn_l":"2521-327X","issn":["2521-327X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317900","host_organization_name":"Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften","host_organization_lineage":["https://openalex.org/P4310317900"],"host_organization_lineage_names":["Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Quantum","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://quantum-journal.org/papers/q-2021-06-07-469/pdf/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ewout van den Berg","orcid":"https://orcid.org/0000-0002-0991-3397"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ewout van den Berg","raw_affiliation_strings":["IBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":{"value":200,"currency":"EUR","value_usd":215},"apc_paid":{"value":200,"currency":"EUR","value_usd":215},"fwci":0.4103,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.50238663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"5","issue":null,"first_page":"469","last_page":"469"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.10809999704360962,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.10809999704360962,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11177","display_name":"Spectroscopy and Quantum Chemical Studies","score":0.09030000120401382,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.07769999653100967,"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/truncation","display_name":"Truncation (statistics)","score":0.6216999888420105},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5777999758720398},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.5551000237464905},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5288000106811523},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48919999599456787},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.47099998593330383},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.3885999917984009},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.38029998540878296},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.3772999942302704}],"concepts":[{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.6216999888420105},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6008999943733215},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5777999758720398},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.5551000237464905},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.536300003528595},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5249000191688538},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48919999599456787},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.47099998593330383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42250001430511475},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.38029998540878296},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.3772999942302704},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.35690000653266907},{"id":"https://openalex.org/C207864730","wikidata":"https://www.wikidata.org/wiki/Q179467","display_name":"Fourier series","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.3425999879837036},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3303999900817871},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C40343088","wikidata":"https://www.wikidata.org/wiki/Q3059012","display_name":"Recursive Bayesian estimation","level":3,"score":0.30480000376701355},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C104942944","wikidata":"https://www.wikidata.org/wiki/Q3434686","display_name":"Truncation error","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C26004113","wikidata":"https://www.wikidata.org/wiki/Q3711784","display_name":"Conjugate prior","level":4,"score":0.26460000872612},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.257099986076355}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.22331/q-2021-06-07-469","is_oa":true,"landing_page_url":"https://doi.org/10.22331/q-2021-06-07-469","pdf_url":"https://quantum-journal.org/papers/q-2021-06-07-469/pdf/","source":{"id":"https://openalex.org/S4210226432","display_name":"Quantum","issn_l":"2521-327X","issn":["2521-327X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317900","host_organization_name":"Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften","host_organization_lineage":["https://openalex.org/P4310317900"],"host_organization_lineage_names":["Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Quantum","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2007.11629","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.11629","pdf_url":"https://arxiv.org/pdf/2007.11629","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:0c5f03430c7a4aa3b471c1ff3b18658b","is_oa":true,"landing_page_url":"https://doaj.org/article/0c5f03430c7a4aa3b471c1ff3b18658b","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Quantum, Vol 5, p 469 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.22331/q-2021-06-07-469","is_oa":true,"landing_page_url":"https://doi.org/10.22331/q-2021-06-07-469","pdf_url":"https://quantum-journal.org/papers/q-2021-06-07-469/pdf/","source":{"id":"https://openalex.org/S4210226432","display_name":"Quantum","issn_l":"2521-327X","issn":["2521-327X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317900","host_organization_name":"Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften","host_organization_lineage":["https://openalex.org/P4310317900"],"host_organization_lineage_names":["Verein zur F\u00f6rderung des Open Access Publizierens in den Quantenwissenschaften"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Quantum","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3045342273.pdf","grobid_xml":"https://content.openalex.org/works/W3045342273.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1531371725","https://openalex.org/W2023789062","https://openalex.org/W2038710373","https://openalex.org/W2046481556","https://openalex.org/W2052891002","https://openalex.org/W2056231850","https://openalex.org/W2109741106","https://openalex.org/W2180180824","https://openalex.org/W2282673650","https://openalex.org/W2496808384","https://openalex.org/W2904801124","https://openalex.org/W2950567220","https://openalex.org/W2963751607","https://openalex.org/W2990012674","https://openalex.org/W3016128111","https://openalex.org/W3023478445","https://openalex.org/W4301014524"],"related_works":[],"abstract_inverted_index":{"We":[0,79,123],"describe":[1],"an":[2],"efficient":[3],"implementation":[4],"of":[5,13,21,31,48,62,68,144,153],"Bayesian":[6,121],"quantum":[7],"phase":[8,33],"estimation":[9],"in":[10,51,85,114,126],"the":[11,25,32,46,63,69,74,83,103,129,141,145,160,181,190,195],"presence":[12],"noise":[14],"and":[15,39,94,111],"multiple":[16],"eigenstates.":[17],"The":[18,42],"main":[19],"contribution":[20],"this":[22],"work":[23],"is":[24,108],"dynamic":[26],"switching":[27],"between":[28],"different":[29],"representations":[30],"distributions,":[34],"namely":[35],"truncated":[36,91],"Fourier":[37,92],"series":[38],"normal":[40,87],"distributions.":[41],"Fourier-series":[43],"representation":[44,107],"has":[45],"advantage":[47],"being":[49],"exact":[50],"many":[52,127],"cases,":[53,128],"but":[54],"suffers":[55],"from":[56],"increasing":[57],"complexity":[58,143,192],"with":[59,89,116,150],"each":[60],"update":[61,130],"prior.":[64],"This":[65,106,163],"necessitates":[66],"truncation":[67],"series,":[70,93],"which":[71,172],"eventually":[72],"causes":[73],"distribution":[75],"to":[76,97,100,102,158],"become":[77],"unstable.":[78],"derive":[80],"bounds":[81],"on":[82],"error":[84],"representing":[86],"distributions":[88],"a":[90,151,168,176],"use":[95],"these":[96],"decide":[98],"when":[99,148],"switch":[101],"normal-distribution":[104],"representation.":[105],"much":[109],"simpler,":[110],"was":[112],"proposed":[113],"conjunction":[115],"rejection":[117],"filtering":[118],"for":[119],"approximate":[120],"updates.":[122,146],"show":[124],"that,":[125],"can":[131,164],"be":[132,165],"done":[133],"exactly":[134],"using":[135,175],"analytic":[136],"expressions,":[137],"thereby":[138],"greatly":[139,188],"reducing":[140],"time":[142],"Finally,":[147],"dealing":[149],"superposition":[152],"several":[154],"eigenstates,":[155],"we":[156,173,187],"need":[157],"estimate":[159],"relative":[161],"weights.":[162],"formulated":[166],"as":[167],"convex":[169],"optimization":[170],"problem,":[171],"solve":[174],"gradient-projection":[177],"algorithm.":[178],"By":[179],"updating":[180],"weights":[182],"at":[183],"exponentially":[184],"scaled":[185],"iterations":[186],"reduce":[189],"computational":[191],"without":[193],"affecting":[194],"overall":[196],"accuracy.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2020-07-29T00:00:00"}
