{"id":"W2080711848","doi":"10.1364/icqi.2001.pa39","title":"Empirical Determination of Bang-Bang Controls","year":2001,"lang":"en","type":"article","venue":"Optical Fiber Communication Conference and International Conference on Quantum Information","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Quantum decoherence; Bang–bang control; Set (abstract data type); Computer science; Quantum computer; Big Bang (financial markets); Quantum; Algorithm; Mathematics; Physics; Optimal control; Quantum mechanics; Mathematical optimization; Finance","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":[0.0004360582,0.0002116459,0.0002561611,0.0002783178,0.0001803505,0.0004407828,0.001148583,0.0001327619,0.0001957201],"category_scores_gemma":[0.0002177296,0.0001894394,0.00007501621,0.0002368185,0.0001772698,0.001709624,0.0003353328,0.0003352527,0.0001054447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004251738,"about_ca_system_score_gemma":0.0001119163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002092337,"about_ca_topic_score_gemma":0.000004773225,"domain_scores_codex":[0.9982734,0.000124177,0.000669464,0.0002368065,0.000466792,0.0002293176],"domain_scores_gemma":[0.9977924,0.0003186192,0.000352875,0.000620013,0.0007951409,0.0001209882],"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":[0.00004828573,0.00007826984,0.0002065719,0.00001243048,0.00001647875,9.135073e-7,0.0008362067,0.00009242447,0.0002149649,0.6871469,0.0001072496,0.3112393],"study_design_scores_gemma":[0.0006363843,0.0002405885,0.003734432,0.000146581,0.000008056017,0.00003676674,0.0001540624,0.9563711,0.0003166519,0.02952916,0.008583886,0.0002422851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1271925,0.00007822708,0.7593225,0.02414723,0.0003614796,0.0004801574,0.00002674249,0.0002303362,0.08816078],"genre_scores_gemma":[0.9778488,0.0003351378,0.02086985,0.0006278456,0.00003280326,0.00002548348,0.00008719089,0.000005875713,0.0001670572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9562787,"threshold_uncertainty_score":0.7725116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04705630212697417,"score_gpt":0.314661143690371,"score_spread":0.2676048415633968,"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."}}