{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001478435,0.0007640229,0.0008603648,0.0009006158,0.0005533806,0.001403013,0.002256946,0.001227613,0.004120441],"category_scores_gemma":[0.0120347,0.0005255082,0.0007060031,0.0006323433,0.001330163,0.002465628,0.001821822,0.001466327,0.0005197884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001949076,"about_ca_system_score_gemma":0.001883755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002293942,"about_ca_topic_score_gemma":0.002863659,"domain_scores_codex":[0.9984791,0.0004880249,0.00008249467,0.0003314702,0.000439812,0.000179151],"domain_scores_gemma":[0.993836,0.003982785,0.0005105145,0.00103377,0.0004474294,0.000189434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007628837,0.0001642602,0.006783737,0.0001823901,0.0001099073,0.0001400638,0.0002137756,0.747586,0.01313847,0.1057564,0.001993805,0.1231684],"study_design_scores_gemma":[0.00002439209,0.00002204155,0.0002367449,0.000004180587,0.000003555213,0.00001282738,0.000009788269,0.9776111,0.004394159,0.01749025,0.00018332,0.000007702944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1366691,0.00007527456,0.8575215,0.0002419992,0.00002877916,0.00009819789,0.0001637261,0.003043811,0.002157641],"genre_scores_gemma":[0.7165186,0.00004478913,0.281404,0.00009138238,0.00002467641,0.0001936638,0.0003748916,0.000311419,0.001036587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004120441,"threshold_uncertainty_score":0.01414156,"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."}}