{"id":"W2884175209","doi":"10.1103/physrevlett.123.030503","title":"Direct Randomized Benchmarking for Multiqubit Devices","year":2019,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Intelligence Advanced Research Projects Activity; Office of the Director of National Intelligence; U.S. Department of Energy","keywords":"Qubit; Computer science; Benchmarking; Quantum computer; Topology (electrical circuits); Quantum; Quantum mechanics; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002953066,0.0005554638,0.0009099559,0.0004935857,0.0008666042,0.00150858,0.002202056,0.001103855,0.0058901],"category_scores_gemma":[0.01171859,0.0003976109,0.0003623297,0.0006028679,0.001592683,0.002006391,0.002316984,0.002121316,0.001034349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001329,"about_ca_system_score_gemma":0.000911487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003363082,"about_ca_topic_score_gemma":0.0005038852,"domain_scores_codex":[0.9965515,0.001404733,0.0002013081,0.0004762237,0.001096784,0.0002694437],"domain_scores_gemma":[0.9954603,0.001914727,0.0004058552,0.001629994,0.0004140084,0.000175002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005730435,0.000349118,0.002311836,0.0008691162,0.0001003923,0.0003633578,0.0003563825,0.1735251,0.08781002,0.613561,0.01157549,0.1086052],"study_design_scores_gemma":[0.00009492558,0.0004629837,0.0006108565,0.0001285708,0.00002439216,0.0001769541,0.00008786585,0.7343808,0.1086481,0.134903,0.02037052,0.0001110639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1007076,0.0009226529,0.8702057,0.0008411813,0.0005237271,0.000420828,0.0004174784,0.005254835,0.02070611],"genre_scores_gemma":[0.7723752,0.0002936173,0.2191287,0.0005666421,0.00006374942,0.001147104,0.0003432428,0.001130907,0.004950926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0058901,"threshold_uncertainty_score":0.01970434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009240767773537082,"score_gpt":0.2710381899377006,"score_spread":0.2617974221641635,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}