{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006134756,0.0001885069,0.0007486867,0.00002653412,0.00007227503,0.00007886389,0.0006270259,0.000007922063,0.000005807523],"category_scores_gemma":[0.0000911656,0.0001310565,0.0004748513,0.0002145232,0.00003629145,0.0001425976,0.0001469763,0.0001253526,0.00006600044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001440513,"about_ca_system_score_gemma":0.00001435314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005886988,"about_ca_topic_score_gemma":2.304639e-7,"domain_scores_codex":[0.9985961,0.0001766941,0.0002481743,0.0004486261,0.0002241907,0.0003062007],"domain_scores_gemma":[0.998026,0.0012929,0.0001503946,0.000427556,0.00003419239,0.00006898191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001340288,0.0006661993,0.000326731,0.01572502,0.0008114153,0.00003248623,0.002479878,0.01843918,0.02532237,0.05221628,0.03194852,0.8506916],"study_design_scores_gemma":[0.008339739,0.00004167439,0.00007199828,0.001564003,0.00004399136,0.000003061546,4.791606e-7,0.959761,0.0002420962,0.0004890188,0.02914485,0.0002981066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3044386,0.02753928,0.6238492,0.03580884,0.001681545,0.005047464,0.000006995381,0.0005942122,0.001033984],"genre_scores_gemma":[0.8571318,0.002190255,0.07444592,0.06481509,0.001053161,0.0002758131,0.00001181847,0.00003968667,0.00003648625],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9413218,"threshold_uncertainty_score":0.534433,"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."}}