{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001293129,0.0001048001,0.000135288,0.0001189685,0.0001475604,0.00002234476,0.0006780986,0.00003956184,0.00001495963],"category_scores_gemma":[0.00002543921,0.0001037519,0.00006425863,0.0006272523,0.0001455227,0.000152141,0.0003059627,0.0001613011,0.00003200803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001600017,"about_ca_system_score_gemma":0.00003233562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006379338,"about_ca_topic_score_gemma":0.000006878587,"domain_scores_codex":[0.9991869,0.0000707696,0.0001098557,0.0003521582,0.00005637755,0.0002239554],"domain_scores_gemma":[0.9992688,0.00008905342,0.0001054353,0.0003391573,0.0001220746,0.00007548297],"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":[0.00003229972,0.0003135174,0.008340803,0.00003323392,0.00006795157,0.0001485166,0.001969677,0.5846421,0.0007763089,0.3858242,0.0002806784,0.01757069],"study_design_scores_gemma":[0.0002142703,0.0002578097,0.002551261,0.00002157212,0.000005491905,0.000004917767,0.00008375267,0.9851034,0.0004943328,0.01000536,0.001133905,0.0001239429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5534938,0.000009888236,0.446068,0.00004687849,0.00009920511,0.00002171775,0.000001371242,0.00009272647,0.0001664382],"genre_scores_gemma":[0.9954447,0.00001549889,0.004011752,0.00004969865,0.00007526054,2.193297e-8,0.000002466666,0.000006287531,0.0003943821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4420562,"threshold_uncertainty_score":0.4230879,"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."}}