{"id":"W3128583303","doi":"10.1103/prxquantum.3.020361","title":"Fast Estimation of Outcome Probabilities for Quantum Circuits","year":2022,"lang":"en","type":"article","venue":"PRX Quantum","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Army Research Office; Innovation, Science and Economic Development Canada; Institut Périmètre de physique théorique; Natural Sciences and Engineering Research Council of Canada; Fundacja na rzecz Nauki Polskiej; Government of Canada; Australian Research Council; Ministry of Colleges and Universities","keywords":"Qubit; Quantum circuit; Quantum computer; Algorithm; Mathematics; Quantum gate; Rotation (mathematics); Electronic circuit; Computer science; Discrete mathematics; Quantum; Quantum error correction; Quantum mechanics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0007924023,0.0001845046,0.0003159165,0.0001752086,0.0004270187,0.00006942395,0.0009996496,0.00003525249,0.00001635227],"category_scores_gemma":[0.0001640852,0.0001763142,0.0001687035,0.0004247679,0.00006504246,0.000176843,0.0004884839,0.0002198205,0.000004708137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000590149,"about_ca_system_score_gemma":0.00009752806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003462133,"about_ca_topic_score_gemma":0.000001811192,"domain_scores_codex":[0.998054,0.000129113,0.0005268636,0.0004568385,0.0004487352,0.000384431],"domain_scores_gemma":[0.9986607,0.0003315401,0.0002711205,0.0005716223,0.00009537834,0.00006959153],"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":[0.00001568367,0.0002792216,0.0008892954,0.0003366224,0.00003481136,0.000005204178,0.00419267,0.2652032,0.0003833245,0.6322876,0.000701345,0.09567101],"study_design_scores_gemma":[0.0003369295,0.0004138394,0.0009867401,0.00001457161,0.000007395972,0.00002606783,0.000108627,0.9065028,0.0002236588,0.08978853,0.001389257,0.0002015192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2783515,0.0001268431,0.7183327,0.001208413,0.001027858,0.0005616428,0.00004987561,0.0002477656,0.0000934351],"genre_scores_gemma":[0.9728729,9.767673e-7,0.026636,0.0001354759,0.00006119474,0.0001516911,0.00001437975,0.0000193102,0.0001081031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6945214,"threshold_uncertainty_score":0.7189887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02544168142698658,"score_gpt":0.2672365872888874,"score_spread":0.2417949058619009,"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."}}