{"id":"https://openalex.org/W7213409739","doi":"https://doi.org/10.48550/arxiv.2609.17150","title":"Observational Indistinguishability and Integrity Blind Regions in Hybrid Quantum-Classical Workflows","display_name":"Observational Indistinguishability and Integrity Blind Regions in Hybrid Quantum-Classical Workflows","publication_year":2026,"publication_date":"2026-09-15","ids":{"openalex":"https://openalex.org/W7213409739","doi":"https://doi.org/10.48550/arxiv.2609.17150"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.17150","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.17150","pdf_url":"https://arxiv.org/pdf/2609.17150","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,"listed_in":[],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.17150","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140720486","display_name":"Roberto Fern\u00e1ndez-Barrios","orcid":"https://orcid.org/0009-0003-5312-2634","observed_orcids":["https://orcid.org/0009-0003-5312-2634"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fern\u00e1ndez-Barrios, Roberto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008372294","display_name":"Iker Pastor-L\u00f3pez","orcid":"https://orcid.org/0000-0002-3068-6248","observed_orcids":["https://orcid.org/0000-0002-3068-6248"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pastor-L\u00f3pez, Iker","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093255811","display_name":"Amaia Pikatza-Huerga","orcid":"https://orcid.org/0009-0003-9080-6242","observed_orcids":["https://orcid.org/0009-0003-9080-6242"]},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pikatza-Huerga, Amaia","raw_affiliation_strings":["Faculty of Engineering , Univer- sity of Deusto , Avda. de las Universidades 24 , 48007 Bilbao , Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering , Univer- sity of Deusto , Avda. de las Universidades 24 , 48007 Bilbao , Spain","institution_ids":["https://openalex.org/I136040515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003633944","display_name":"Pablo G. Bringas","orcid":"https://orcid.org/0000-0003-3594-9534","observed_orcids":["https://orcid.org/0000-0003-3594-9534"]},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Bringas, Pablo Garc\u00eda","raw_affiliation_strings":["Faculty of Engineering , Univer- sity of Deusto , Avda. de las Universidades 24 , 48007 Bilbao , Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering , Univer- sity of Deusto , Avda. de las Universidades 24 , 48007 Bilbao , Spain","institution_ids":["https://openalex.org/I136040515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.7182999849319458,"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":0.7182999849319458,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.08609999716281891,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.024000000208616257,"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/conformal-prediction","display_name":"conformal prediction","score":0.6359999775886536},{"id":"https://openalex.org/keywords/exchangeability","display_name":"exchangeability","score":0.6909999847412109}],"concepts":[{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.7580999732017517},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6869999766349792},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.6564000248908997},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.6553000211715698},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.5411999821662903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5360000133514404},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.49900001287460327},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.4717000126838684},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39399999380111694},{"id":"https://openalex.org/C40422974","wikidata":"https://www.wikidata.org/wiki/Q741248","display_name":"Assertion","level":2,"score":0.37779998779296875},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34200000762939453},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3402999937534332},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C2778058735","wikidata":"https://www.wikidata.org/wiki/Q4692253","display_name":"Aggregate data","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32260000705718994},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C80478641","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential analysis","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2596000134944916},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2549999952316284},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.17150","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.17150","pdf_url":"https://arxiv.org/pdf/2609.17150","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,"listed_in":[],"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":"doi:10.48550/arxiv.2609.17150","doi":"https://doi.org/10.48550/arxiv.2609.17150","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.17150","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.17150","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.17150","pdf_url":"https://arxiv.org/pdf/2609.17150","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,"listed_in":[],"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"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3480869486","display_name":null,"funder_award_id":"13039","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G5080475149","display_name":null,"funder_award_id":"10.13039","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G6033112984","display_name":null,"funder_award_id":"MICIU/AEI/10","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G7084143925","display_name":null,"funder_award_id":"AEI/10","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"}],"funders":[{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320335598","display_name":"Agencia Estatal de Investigaci\u00f3n","ror":"https://ror.org/003x0zc53"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7213409739.pdf","grobid_xml":"https://content.openalex.org/works/W7213409739.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W3108983691","https://openalex.org/W3146670357","https://openalex.org/W4396986598","https://openalex.org/W7139979229","https://openalex.org/W7154990388","https://openalex.org/W7158848168","https://openalex.org/W7161189302","https://openalex.org/W7162446075","https://openalex.org/W7172541607","https://openalex.org/W7202195358","https://openalex.org/W7207677962","https://openalex.org/W7211894454"],"related_works":["https://openalex.org/W7161189302","https://openalex.org/W7124567873","https://openalex.org/W4410885234","https://openalex.org/W2783238335","https://openalex.org/W6885039882","https://openalex.org/W6949297697","https://openalex.org/W7167912969","https://openalex.org/W2955758032","https://openalex.org/W7167731538","https://openalex.org/W7212227009"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,26],"claim-relative":[3],"evidence/reference":[4],"framework":[5],"for":[6,32,37,45],"hybrid":[7],"quantum-classical":[8],"workflow":[9],"integrity.":[10],"Observational":[11],"indistinguishability":[12],"yields":[13,99],"structural":[14],"blind":[15],"regions,":[16],"distinct":[17],"from":[18],"finite-batch":[19],"statistical":[20,72],"misses.":[21],"Within":[22],"the":[23,74,85,91,94,119],"declared":[24],"lattice,":[25],"trusted":[27],"same-batch":[28],"scalar":[29],"$R_0$":[30],"suffices":[31],"conclusion":[33,40,143],"integrity,":[34,41],"aggregate":[35,38],"$M_0$":[36],"plus":[39],"and":[42,88,101,149,156],"item-aligned":[43],"binding":[44],"item":[46],"identity.":[47],"In":[48],"3,600":[49],"label":[50,82],"interventions,":[51],"feature/prediction":[52],"views":[53],"realize":[54],"exact":[55],"label-path":[56],"invariance;":[57],"all":[58],"764":[59],"geometry-aligned":[60,75],"aggregate-blind":[61],"rows":[62],"equal":[63],"their":[64],"paired-clean":[65],"responses,":[66],"giving":[67],"zero":[68],"attack-only":[69],"increment.":[70],"For":[71],"response,":[73],"construction":[76],"detects":[77],"343/2,700":[78],"conclusion-changing":[79],"($\u03c4\\to":[80],"0^+$)":[81],"interventions":[83],"with":[84,90],"conformal":[86,106],"rule":[87],"1,183/2,700":[89],"uncorrected":[92],"union;":[93],"original":[95],"frozen":[96],"same-item":[97],"geometry":[98],"11/2,617":[100],"43/2,617,":[102],"respectively.":[103],"The":[104,123,160],"executed":[105],"clean":[107],"false-action":[108],"rates":[109],"are":[110],"0.048--0.059":[111],"descriptively;":[112],"its":[113],"finite-sample":[114],"guarantee":[115],"requires":[116],"exchangeability,":[117],"which":[118],"overlapping-draw":[120],"design":[121,163],"violates.":[122],"cluster-preserving":[124],"adaptive":[125],"stress":[126],"test":[127],"(Gate":[128],"A)":[129],"reduces":[130],"response":[131],"versus":[132],"matched":[133],"controls":[134],"in":[135],"25--40":[136],"of":[137],"40":[138],"environment/split":[139],"cells":[140],"while":[141],"retaining":[142],"changes.":[144],"A":[145],"bounded":[146],"165-design-cell":[147],"ideal-statevector":[148],"finite-shot-emulation":[150],"branch":[151],"directly":[152],"instantiates":[153],"semantic,":[154],"estimated":[155],"observed":[157],"kernel":[158],"transitions.":[159],"fixed":[161],"equal-weight":[162],"estimates":[164],"neither":[165],"deployment":[166],"prevalence":[167],"nor":[168],"QPU,":[169],"provider":[170],"or":[171],"deployed-service":[172],"assurance.":[173]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-17T00:00:00"}
