{"id":"W2784023939","doi":"10.22331/q-2018-08-22-85","title":"Real Randomized Benchmarking","year":2018,"lang":"en","type":"article","venue":"Quantum","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Australian Research Council; Army Research Office; Natural Sciences and Engineering Research Council of Canada; Industry Canada; Bundesministerium für Bildung und Forschung; Elitenetzwerk Bayern; University of Sydney; Government of Canada; Deutsche Forschungsgemeinschaft; Canadian Institute for Advanced Research; Deutscher Akademischer Austauschdienst; Canada First Research Excellence Fund; Government of Ontario","keywords":"Benchmarking; Computation; Group (periodic table); Protocol (science); Word error rate; Error detection and correction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.008411005,0.00107933,0.001550758,0.001425775,0.00111896,0.003163358,0.002465833,0.001724266,0.00659395],"category_scores_gemma":[0.02975083,0.0005009558,0.0008468957,0.001328495,0.004196477,0.00509932,0.003292702,0.002388663,0.001281952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002165798,"about_ca_system_score_gemma":0.002542075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005614857,"about_ca_topic_score_gemma":0.0005597851,"domain_scores_codex":[0.9861845,0.006558969,0.0008393442,0.002191208,0.003256476,0.0009694059],"domain_scores_gemma":[0.9791044,0.007140683,0.002258258,0.00785449,0.003087767,0.0005544432],"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":[0.0003221862,0.0001165944,0.001044599,0.0001900807,0.0000661037,0.000088481,0.00008538905,0.07070822,0.007863246,0.8871592,0.002956413,0.02939961],"study_design_scores_gemma":[0.00009053665,0.0004356195,0.0004689007,0.00009735515,0.00004376551,0.0002322599,0.00005958385,0.4569342,0.01943696,0.5097328,0.01235284,0.0001151462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03054089,0.0004269218,0.9472014,0.0004844983,0.0003000083,0.0002502872,0.0004077366,0.001323143,0.01906513],"genre_scores_gemma":[0.7244937,0.0003778393,0.265353,0.0007084326,0.0002571536,0.001052554,0.0007254204,0.0007857598,0.00624613],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008411005,"threshold_uncertainty_score":0.04448217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00935931314201262,"score_gpt":0.2472905738837169,"score_spread":0.2379312607417043,"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."}}