{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003029491,0.0009660094,0.0009712689,0.0005904973,0.0008286404,0.00115364,0.002378803,0.001244611,0.003373668],"category_scores_gemma":[0.01604238,0.0005502111,0.0003731199,0.0009300489,0.002946979,0.0030047,0.004236503,0.002582918,0.0007977855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202405,"about_ca_system_score_gemma":0.001712953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001412138,"about_ca_topic_score_gemma":0.002528311,"domain_scores_codex":[0.9958793,0.001037496,0.0001814517,0.0008355795,0.001563127,0.0005030515],"domain_scores_gemma":[0.9882084,0.006480587,0.0008000033,0.003268114,0.0009908576,0.0002521724],"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":[0.001944677,0.0005823337,0.007050752,0.0003683895,0.0001519563,0.0004794781,0.0006700492,0.2745875,0.256101,0.2330256,0.00593017,0.2191081],"study_design_scores_gemma":[0.00008292499,0.000247086,0.0008972746,0.000019223,0.00002481421,0.0001586622,0.00003531714,0.888455,0.0588211,0.04896059,0.00225044,0.00004756254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2437446,0.0006136296,0.7318376,0.002239099,0.0002110976,0.0001138768,0.0002211103,0.003255888,0.01776313],"genre_scores_gemma":[0.8849943,0.0001500006,0.1104246,0.0002825388,0.00007544272,0.00006799367,0.0001257487,0.0001852617,0.003694141],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003373668,"threshold_uncertainty_score":0.01602167,"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."}}