{"id":"https://openalex.org/W7138894318","doi":"https://doi.org/10.48550/arxiv.2603.16946","title":"Automatic Termination Strategy of Inelastic Neutron-scattering Measurement Using Bayesian Optimization for Bin-width Selection","display_name":"Automatic Termination Strategy of Inelastic Neutron-scattering Measurement Using Bayesian Optimization for Bin-width Selection","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7138894318","doi":"https://doi.org/10.48550/arxiv.2603.16946"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.16946","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16946","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,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.16946","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047778829","display_name":"Kensuke Muto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muto, Kensuke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068335003","display_name":"Hirotaka Sakamoto","orcid":"https://orcid.org/0000-0002-6224-4591"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sakamoto, Hirotaka","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050911583","display_name":"Kenji Nagata","orcid":"https://orcid.org/0000-0001-9894-4461"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nagata, Kenji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008100767","display_name":"T. Arima","orcid":"https://orcid.org/0000-0002-6959-0454"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arima, Taka-hisa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103124754","display_name":"Masato Okada","orcid":"https://orcid.org/0000-0002-9040-8784"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Okada, Masato","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T11949","display_name":"Nuclear Physics and Applications","score":0.6514000296592712,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11949","display_name":"Nuclear Physics and Applications","score":0.6514000296592712,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"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/T10597","display_name":"Nuclear reactor physics and engineering","score":0.07880000025033951,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11216","display_name":"Radiation Detection and Scintillator Technologies","score":0.07320000231266022,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"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/bin","display_name":"Bin","score":0.7705000042915344},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.7570000290870667},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5548999905586243},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.41019999980926514},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.3801000118255615},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.37689998745918274},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.3549000024795532}],"concepts":[{"id":"https://openalex.org/C156273044","wikidata":"https://www.wikidata.org/wiki/Q4913766","display_name":"Bin","level":2,"score":0.7705000042915344},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.7570000290870667},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5548999905586243},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5440999865531921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5349000096321106},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4381999969482422},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3801000118255615},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.37689998745918274},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3244999945163727},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3010999858379364},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25929999351501465},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.16946","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16946","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,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.16946","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16946","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,"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Currently,":[0],"an":[1,53,80,186],"excessive":[2,161],"amount":[3],"of":[4,21,45,132,163,185],"event":[5],"data":[6,141],"is":[7,57,89,103],"being":[8],"obtained":[9],"in":[10,189],"four-dimensional":[11],"inelastic":[12,32,121,165],"neutron-scattering":[13,33,122],"experiments.":[14,192],"A":[15],"method":[16,63],"for":[17,140,168],"automatic":[18,54],"bin-width":[19,87],"optimization":[20,88,93,176],"multidimensional":[22],"histograms":[23],"has":[24],"been":[25],"developed":[26],"and":[27,156],"recently":[28],"validated":[29],"on":[30,74],"real":[31,120],"data.":[34],"However,":[35],"measuring":[36],"beyond":[37],"the":[38,83,86,97,106,113,124,130,136,148,152,164,169,179],"equipment":[39],"resolution":[40],"leads":[41],"to":[42,64,76,94,143,182],"inefficient":[43],"use":[44],"valuable":[46],"beam":[47],"time.":[48],"To":[49],"improve":[50],"experimental":[51],"efficiency,":[52],"termination":[55],"strategy":[56],"essential.":[58],"We":[59],"propose":[60],"a":[61,66],"Bayesian-optimization-based":[62],"compute":[65,96],"stopping":[67],"criterion":[68],"that":[69,174],"can":[70,177],"support":[71],"online":[72],"decisions":[73],"whether":[75],"continue":[77],"or":[78],"terminate":[79],"experiment.":[81],"In":[82,116],"proposed":[84],"method,":[85],"performed":[90],"using":[91,119],"Bayesian":[92,175],"efficiently":[95],"optimal":[98,107,125,137],"bin":[99,108,126,138],"widths.":[100],"The":[101],"experiment":[102],"terminated":[104],"when":[105],"widths":[109,127,139],"become":[110],"smaller":[111],"than":[112],"target":[114],"resolutions.":[115],"numerical":[117,191],"experiments":[118,167],"data,":[123],"decrease":[128],"as":[129],"number":[131],"events":[133],"increases.":[134],"Even":[135],"downsampled":[142],"1/5":[144],"are":[145],"comparable":[146],"with":[147],"resolutions":[149],"limited":[150],"by":[151],"sample":[153],"size,":[154],"choppers,":[155],"so":[157],"on.":[158],"This":[159],"implies":[160],"measurement":[162],"neutron":[166],"moment.":[170],"Moreover,":[171],"we":[172],"found":[173],"reduce":[178],"search":[180,188],"cost":[181],"approximately":[183],"10%":[184],"exhaustive":[187],"our":[190]},"counts_by_year":[],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2026-03-20T00:00:00"}