{"id":"https://openalex.org/W4405431847","doi":"https://doi.org/10.1088/2632-2153/ad9fd1","title":"Refinable modeling for unbinned SMEFT analyses","display_name":"Refinable modeling for unbinned SMEFT analyses","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4405431847","doi":"https://doi.org/10.1088/2632-2153/ad9fd1"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/ad9fd1","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad9fd1","pdf_url":null,"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":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1088/2632-2153/ad9fd1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Robert Sch\u00f6fbeck","orcid":"https://orcid.org/0000-0002-2332-8784"},"institutions":[{"id":"https://openalex.org/I138211613","display_name":"Austrian Academy of Sciences","ror":"https://ror.org/03anc3s24","country_code":"AT","type":"government","lineage":["https://openalex.org/I138211613"]},{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Robert Sch\u00f6fbeck","raw_affiliation_strings":["Technische Universit\u00e4t Wien, Karlsplatz 13, 1040 Vienna","Institute for High Energy Physics, Austrian Academy of Sciences, Dominikanerbastei 16, 1010 Vienna, Austria"],"raw_orcid":"https://orcid.org/0000-0002-2332-8784","affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Wien, Karlsplatz 13, 1040 Vienna","institution_ids":["https://openalex.org/I145847075"]},{"raw_affiliation_string":"Institute for High Energy Physics, Austrian Academy of Sciences, Dominikanerbastei 16, 1010 Vienna, Austria","institution_ids":["https://openalex.org/I138211613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I138211613","https://openalex.org/I145847075"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":3.0595,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93769296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"6","issue":"1","first_page":"015007","last_page":"015007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10048","display_name":"Particle physics theoretical and experimental studies","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"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/T10048","display_name":"Particle physics theoretical and experimental studies","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"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/T11263","display_name":"Electromagnetic Simulation and Numerical Methods","score":0.90420001745224,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10739","display_name":"Electromagnetic Scattering and Analysis","score":0.902899980545044,"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/computer-science","display_name":"Computer science","score":0.3881400525569916},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.38166555762290955},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.3528045415878296},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.2572978734970093},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2542635202407837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3881400525569916},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.38166555762290955},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3528045415878296},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2572978734970093},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2542635202407837}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1088/2632-2153/ad9fd1","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad9fd1","pdf_url":null,"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:doaj.org/article:a86b6d1800004c6faf5b44d42b09bf6c","is_oa":true,"landing_page_url":"https://doaj.org/article/a86b6d1800004c6faf5b44d42b09bf6c","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":"Machine Learning: Science and Technology, Vol 6, Iss 1, p 015007 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/ad9fd1","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad9fd1","pdf_url":null,"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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":100,"referenced_works":["https://openalex.org/W93830287","https://openalex.org/W362526619","https://openalex.org/W632087424","https://openalex.org/W1537132919","https://openalex.org/W1965888463","https://openalex.org/W1975211291","https://openalex.org/W1975846771","https://openalex.org/W1978047112","https://openalex.org/W1987435915","https://openalex.org/W1991302676","https://openalex.org/W1992364697","https://openalex.org/W2016966976","https://openalex.org/W2017958417","https://openalex.org/W2018213750","https://openalex.org/W2019149276","https://openalex.org/W2019841176","https://openalex.org/W2020084508","https://openalex.org/W2044160967","https://openalex.org/W2057766171","https://openalex.org/W2100507804","https://openalex.org/W2110999179","https://openalex.org/W2125102738","https://openalex.org/W2128158076","https://openalex.org/W2137284081","https://openalex.org/W2156247879","https://openalex.org/W2156379501","https://openalex.org/W2157014333","https://openalex.org/W2164169895","https://openalex.org/W2165037242","https://openalex.org/W2182495628","https://openalex.org/W2184278756","https://openalex.org/W2194121477","https://openalex.org/W2201035149","https://openalex.org/W2467464714","https://openalex.org/W2599043313","https://openalex.org/W2604487509","https://openalex.org/W2621084749","https://openalex.org/W2624881227","https://openalex.org/W2730968276","https://openalex.org/W2798398359","https://openalex.org/W2799038815","https://openalex.org/W2807858310","https://openalex.org/W2895846750","https://openalex.org/W2946775087","https://openalex.org/W2950368925","https://openalex.org/W2950853342","https://openalex.org/W2962762178","https://openalex.org/W2969792851","https://openalex.org/W2993330478","https://openalex.org/W2999655151","https://openalex.org/W3006943238","https://openalex.org/W3035751413","https://openalex.org/W3035965352","https://openalex.org/W3093489024","https://openalex.org/W3099061352","https://openalex.org/W3099878876","https://openalex.org/W3101501459","https://openalex.org/W3102134862","https://openalex.org/W3106311915","https://openalex.org/W3115718118","https://openalex.org/W3122853355","https://openalex.org/W3153097845","https://openalex.org/W3162060232","https://openalex.org/W3170196853","https://openalex.org/W3178960719","https://openalex.org/W3183439224","https://openalex.org/W3200924559","https://openalex.org/W4221104935","https://openalex.org/W4282004305","https://openalex.org/W4290056518","https://openalex.org/W4293352142","https://openalex.org/W4308242209","https://openalex.org/W4312051506","https://openalex.org/W4312292931","https://openalex.org/W4318239044","https://openalex.org/W4323349777","https://openalex.org/W4327584080","https://openalex.org/W4378627722","https://openalex.org/W4385067633","https://openalex.org/W4385775260","https://openalex.org/W4390091566","https://openalex.org/W4392231918","https://openalex.org/W4392951883","https://openalex.org/W4394749943","https://openalex.org/W4394774618","https://openalex.org/W4394905311","https://openalex.org/W4398781580","https://openalex.org/W4400914077","https://openalex.org/W6612301713","https://openalex.org/W6620232636","https://openalex.org/W6632353429","https://openalex.org/W6735525128","https://openalex.org/W6779920328","https://openalex.org/W6801154860","https://openalex.org/W6803920545","https://openalex.org/W6838336989","https://openalex.org/W6846396315","https://openalex.org/W6847727485","https://openalex.org/W6848856019","https://openalex.org/W6860475044"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Abstract":[0],"We":[1,84,108],"present":[2],"methods":[3],"to":[4,33,61,102],"estimate":[5],"systematic":[6,95],"uncertainties":[7],"in":[8,21,123],"unbinned":[9,63,79],"large":[10],"hadron":[11],"collider":[12],"(LHC)":[13],"data":[14],"analyses,":[15],"focusing":[16],"on":[17],"constraining":[18],"Wilson":[19],"coefficients":[20],"the":[22,41,49,62,75,82],"standard":[23,42],"model":[24],"effective":[25],"field":[26],"theory":[27],"(SMEFT).":[28],"Our":[29],"approach":[30,111],"also":[31,85],"applies":[32],"broader":[34],"parametric":[35],"models":[36],"of":[37,48,94,116],"non-resonant":[38],"phenomena":[39],"beyond":[40],"model.":[43],"By":[44],"using":[45],"machine-learned":[46],"surrogates":[47],"likelihood":[50],"ratio,":[51],"we":[52],"extend":[53],"well-established":[54],"procedures":[55],"from":[56],"binned":[57],"Poisson":[58],"counting":[59],"experiments":[60],"case.":[64],"This":[65],"framework":[66],"handles":[67],"various":[68],"theoretical,":[69],"modeling,":[70],"and":[71],"experimental":[72],"uncertainties,":[73],"laying":[74],"foundation":[76],"for":[77,105],"future":[78],"analyses":[80],"at":[81],"LHC.":[83],"introduce":[86],"a":[87,98],"tree-boosting":[88],"algorithm":[89],"that":[90],"learns":[91],"precise":[92],"parametrizations":[93],"effects,":[96],"providing":[97],"robust,":[99],"flexible":[100],"alternative":[101],"neural":[103],"networks":[104],"modeling":[106],"systematics.":[107],"demonstrate":[109],"this":[110],"with":[112],"an":[113],"SMEFT":[114],"analysis":[115],"highly":[117],"energetic":[118],"top":[119],"quark":[120],"pair":[121],"production":[122],"proton\u2013proton":[124],"collisions.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2024-12-17T00:00:00"}