{"id":"https://openalex.org/W7216059062","doi":"https://doi.org/10.48550/arxiv.2610.01574","title":"Adversarial Robustness in Fake Quantum Simulators","display_name":"Adversarial Robustness in Fake Quantum Simulators","publication_year":2026,"publication_date":"2026-10-01","ids":{"openalex":"https://openalex.org/W7216059062","doi":"https://doi.org/10.48550/arxiv.2610.01574"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.01574","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.01574","pdf_url":"https://arxiv.org/pdf/2610.01574","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":"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/2610.01574","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115003680","display_name":"Marc Mau\u00dfner","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mau\u00dfner, Marc","raw_affiliation_strings":["Qseidon GmbH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qseidon GmbH","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5118641790","display_name":"Volker Reers","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reers, Volker","raw_affiliation_strings":["Qseidon GmbH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qseidon GmbH","institution_ids":[]}]}],"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":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":0.6470000147819519,"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":0.6470000147819519,"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":0.34689998626708984,"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/T10020","display_name":"Quantum Information and Cryptography","score":0.0010000000474974513,"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/adversarial-robustness","display_name":"adversarial robustness","score":0.9229999780654907},{"id":"https://openalex.org/keywords/quantum-machine-learning","display_name":"quantum machine learning","score":0.8859999775886536},{"id":"https://openalex.org/keywords/projected-gradient-descent-attacks","display_name":"projected gradient descent attacks","score":0.8600000143051147},{"id":"https://openalex.org/keywords/adversarial-retraining","display_name":"adversarial retraining","score":0.9980000257492065},{"id":"https://openalex.org/keywords/qiskit-aer","display_name":"Qiskit Aer","score":0.9359999895095825},{"id":"https://openalex.org/keywords/scalability","display_name":"scalability","score":0.49300000071525574},{"id":"https://openalex.org/keywords/quantum-classifiers","display_name":"quantum classifiers","score":0.48100000619888306},{"id":"https://openalex.org/keywords/noise-robustness","display_name":"noise robustness","score":0.42399999499320984}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8222000002861023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7567999958992004},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7023000121116638},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6535000205039978},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5967000126838684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47999998927116394},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.46860000491142273},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43939998745918274},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4124000072479248},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.35850000381469727},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.34060001373291016},{"id":"https://openalex.org/C134765980","wikidata":"https://www.wikidata.org/wiki/Q879126","display_name":"Bitwise operation","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.3118000030517578},{"id":"https://openalex.org/C2780909371","wikidata":"https://www.wikidata.org/wiki/Q4801092","display_name":"Artificial noise","level":4,"score":0.3043999969959259},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27390000224113464},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25440001487731934}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.01574","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.01574","pdf_url":"https://arxiv.org/pdf/2610.01574","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.01574","doi":"https://doi.org/10.48550/arxiv.2610.01574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.01574","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:2610.01574","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.01574","pdf_url":"https://arxiv.org/pdf/2610.01574","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320317153","display_name":"DeepMind","ror":"https://ror.org/00971b260"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7216059062.pdf","grobid_xml":"https://content.openalex.org/works/W7216059062.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2901859177","https://openalex.org/W4401692535","https://openalex.org/W6912284476"],"related_works":["https://openalex.org/W7087485688","https://openalex.org/W7106304233","https://openalex.org/W7153098979","https://openalex.org/W4406059442","https://openalex.org/W4402397238","https://openalex.org/W7152673209","https://openalex.org/W3157186308","https://openalex.org/W4410358458","https://openalex.org/W7165839606","https://openalex.org/W7154104078"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"the":[3,27,42,61],"performance":[4],"scalability":[5],"and":[6,39,50,64,75],"adversarial":[7,51],"robustness":[8,89],"of":[9,30,44],"Quantum":[10],"Machine":[11],"Learning":[12],"(QML)":[13],"models":[14],"deployed":[15],"on":[16],"noise-model-based":[17],"fake":[18],"simulators.":[19],"We":[20],"conduct":[21],"a":[22],"dual-phased":[23],"study,":[24],"first":[25],"benchmarking":[26],"computational":[28],"throughput":[29],"Qiskit's":[31],"Aer":[32],"simulation":[33],"engine":[34],"across":[35],"varying":[36],"hardware":[37],"architectures,":[38],"second,":[40],"evaluating":[41],"effectiveness":[43],"Projected":[45],"Gradient":[46],"Descent":[47],"(PGD)":[48],"attacks":[49],"retraining":[52,80],"strategies":[53],"under":[54,93],"realistic":[55,94],"noise":[56,95],"conditions.":[57,96],"Our":[58],"results":[59],"quantify":[60],"runtime":[62],"tradeoffs":[63],"scaling":[65],"behavior":[66],"for":[67,85,90],"medium-scale":[68],"simulations":[69],"(projected":[70],"up":[71],"to":[72],"8":[73],"qubits)":[74],"demonstrate":[76],"that":[77],"high":[78],"adversarial-to-benign":[79],"ratios":[81],"(50/50)":[82],"are":[83],"essential":[84],"achieving":[86],"practical":[87],"model":[88],"4-qubit":[91],"classifiers":[92]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-03T00:00:00"}
