{"id":"W1763515295","doi":"10.1103/physreva.95.022309","title":"Classical simulation of quantum error correction in a Fibonacci anyon code","year":2017,"lang":"en","type":"article","venue":"Physical review. A/Physical review, A","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"Army Research Office; Australian Research Council; European Research Council; Government of Canada","keywords":"Fibonacci number; Anyon; Code (set theory); Quantum; Computer science; Parallel computing; Physics; Quantum mechanics; Mathematics; Programming language; Discrete mathematics; Topological quantum computer","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00067171,0.0004506551,0.001584234,0.00007650009,0.0002504425,0.0001077098,0.001695861,0.00005765984,0.000005888096],"category_scores_gemma":[0.001881714,0.0003513022,0.0006858248,0.0006007946,0.0001950355,0.0005282967,0.0006093686,0.0007146618,0.0001024622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007587934,"about_ca_system_score_gemma":0.0001133739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004368463,"about_ca_topic_score_gemma":0.00001330432,"domain_scores_codex":[0.9964844,0.0004302351,0.0008191252,0.0009164392,0.0007993798,0.0005504304],"domain_scores_gemma":[0.9960921,0.0007826489,0.0008778268,0.001809179,0.0002054822,0.0002328022],"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":[0.00005293554,0.003409243,0.001041733,0.01271228,0.00008831293,0.00005643644,0.0004536739,0.01125086,0.007620725,0.04586795,0.004538289,0.9129075],"study_design_scores_gemma":[0.0002954086,0.0002591513,0.006065223,0.01227956,0.00006828868,0.000005928541,0.00000128154,0.9536995,0.0008993712,0.01833989,0.007702971,0.0003834589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6920295,0.03670198,0.2514777,0.01310223,0.001702199,0.003210515,0.00003067334,0.0003946533,0.001350539],"genre_scores_gemma":[0.9877959,0.01002318,0.0008031777,0.0007799341,0.000458493,0.00006828296,0.000008823468,0.00003012145,0.0000320735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9424486,"threshold_uncertainty_score":0.9998939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02849846784863923,"score_gpt":0.3888720086599162,"score_spread":0.3603735408112769,"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."}}