{"id":"W2964229111","doi":"10.48550/arxiv.1802.09025","title":"Online Learning of Quantum States","year":2018,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Dimension (graph theory); Learnability; Quantum decoherence; Qubit; Quantum state; State (computer science); Convex optimization; Mathematics; Weak measurement; Quantum; Measure (data warehouse); Discrete mathematics; Computer science; Algorithm; Regular polygon; Combinatorics; Artificial intelligence; Physics; Quantum mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003850364,0.001343188,0.002283074,0.0006032711,0.001149509,0.001846545,0.003931419,0.002554981,0.005777334],"category_scores_gemma":[0.03125389,0.0008736828,0.00110788,0.0008712449,0.003265234,0.006425596,0.003708479,0.005173394,0.0008323697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002702017,"about_ca_system_score_gemma":0.00234812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003064748,"about_ca_topic_score_gemma":0.003596377,"domain_scores_codex":[0.9965976,0.001347862,0.000129655,0.0009103901,0.0005266754,0.0004879477],"domain_scores_gemma":[0.9768753,0.01728174,0.001098824,0.003151574,0.0008214602,0.0007710871],"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":[0.001540791,0.0005378817,0.004048197,0.0003334636,0.0001651909,0.00024968,0.0002645841,0.7597172,0.001674052,0.1369723,0.008702689,0.08579389],"study_design_scores_gemma":[0.00004213125,0.0000503359,0.000201111,0.00001181885,0.00001049093,0.00001836393,0.00001239518,0.9269137,0.0006759004,0.07173479,0.0003181009,0.00001085539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1344933,0.0007070492,0.8467561,0.003721311,0.0002508963,0.0002357957,0.000860163,0.002202122,0.01077326],"genre_scores_gemma":[0.9221259,0.0001979356,0.07033136,0.0007017003,0.0001852179,0.0002525535,0.0009091469,0.0001674998,0.005128758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005777334,"threshold_uncertainty_score":0.02036297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03005286238573474,"score_gpt":0.1860936531163934,"score_spread":0.1560407907306587,"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."}}