{"id":"W1993000102","doi":"10.1103/physrevlett.111.183601","title":"Adaptive Quantum State Tomography Improves Accuracy Quadratically","year":2013,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Canadian Institute for Advanced Research","funders":"","keywords":"Quadratic growth; Quantum tomography; Reduction (mathematics); State (computer science); Qubit; Algorithm; Tomography; Quantum; Physics; Adaptation (eye); Quantum state; Simple (philosophy); Computer science; Statistical physics; Quantum mechanics; Applied mathematics; Mathematics; Optics; Geometry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001693642,0.0002500164,0.0003753008,0.0001050236,0.0001017742,0.000252346,0.0009134337,0.000009772336,0.00004213884],"category_scores_gemma":[0.00006872993,0.0001879095,0.0003729832,0.0008718615,0.0001186886,0.00196809,0.0001551882,0.000226439,0.001305545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000148055,"about_ca_system_score_gemma":0.00002697902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003466737,"about_ca_topic_score_gemma":5.715839e-7,"domain_scores_codex":[0.9982438,0.0001159481,0.0004309828,0.000335004,0.0004460555,0.0004281914],"domain_scores_gemma":[0.9985527,0.0002449764,0.0002111527,0.0006410955,0.0001256937,0.0002243837],"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":[0.00001054949,0.0007015279,0.0001541445,0.001500694,0.0002361107,0.00001319714,0.001654378,0.0000455249,0.02622804,0.5355503,0.1301711,0.3037344],"study_design_scores_gemma":[0.001639479,0.00111377,0.03061416,0.003330309,0.0001681219,0.00003000292,0.0001240897,0.7195908,0.002560391,0.1696036,0.06763247,0.003592758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2552602,0.004399703,0.681754,0.05292997,0.0004127472,0.002400455,0.000008080424,0.0008202983,0.002014509],"genre_scores_gemma":[0.8980371,0.001486077,0.006569617,0.09353352,0.0000778328,0.0002704332,0.000005155278,0.00001546344,0.000004799598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7195453,"threshold_uncertainty_score":0.9994721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0125987911538194,"score_gpt":0.2600638924650686,"score_spread":0.2474651013112492,"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."}}