{"id":"W2258238025","doi":"10.1103/physrevlett.115.110401","title":"Optimal Feedback Scheme and Universal Time Scaling for Hamiltonian Parameter Estimation","year":2015,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"Research Grants Council, University Grants Committee","keywords":"Intuition; Hamiltonian (control theory); Scaling; Estimation theory; Computer science; Statistical physics; Applied mathematics; Physics; Control theory (sociology); Mathematics; Mathematical optimization; Algorithm; Artificial intelligence","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":[0.0002086754,0.0001146635,0.0001975684,0.00004479001,0.00005490686,0.0001026851,0.0002437101,0.000009196089,0.000002449669],"category_scores_gemma":[0.00006603447,0.0000986263,0.0001001743,0.0002207295,0.00005678754,0.0007423263,0.00006901883,0.00006907804,0.0001144273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002117883,"about_ca_system_score_gemma":0.00001924155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001906475,"about_ca_topic_score_gemma":4.050998e-8,"domain_scores_codex":[0.9992565,0.00003299358,0.000163883,0.0001815234,0.0001867476,0.0001783585],"domain_scores_gemma":[0.9994323,0.00007526183,0.00008428664,0.0002121751,0.00005507399,0.0001408956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001124174,0.0006894346,0.0003325641,0.004863577,0.0002658924,0.00001693118,0.006277304,0.01185196,0.008736782,0.3186183,0.1957743,0.4524605],"study_design_scores_gemma":[0.000361493,0.00005059162,0.0001160256,0.0002346059,0.00001819725,0.000004096095,0.000005951563,0.9876606,0.00008117639,0.0008374461,0.0104599,0.0001699064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1771969,0.0007038965,0.8114828,0.009839162,0.0000645665,0.0004309775,0.000003060459,0.0001235472,0.0001550524],"genre_scores_gemma":[0.2660043,0.0003000726,0.6922555,0.04114066,0.0001466185,0.00007983435,0.0000343522,0.00002242752,0.0000162195],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9758086,"threshold_uncertainty_score":0.4021864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02204734134589702,"score_gpt":0.2770810391958727,"score_spread":0.2550336978499757,"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."}}