{"id":"W3038572776","doi":"10.22331/q-2020-11-17-364","title":"Operational, gauge-free quantum tomography","year":2020,"lang":"en","type":"article","venue":"Quantum","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; TRIUMF","funders":"Pacific Northwest National Laboratory; National Nuclear Security Administration; Office of Science; Government of Canada; Advanced Scientific Computing Research; Sandia National Laboratories; Laboratory Directed Research and Development; U.S. Department of Energy","keywords":"Tomography; Computer science; Benchmarking; Set (abstract data type); Parameterized complexity; Ambiguity; Representation (politics); Gauge (firearms); Observable; Algorithm; Process (computing); Computer engineering; Theoretical computer science; Physics; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000201358,0.0002593881,0.0002633556,0.0001167569,0.0002973519,0.000322757,0.002090764,0.00007952587,0.00004931163],"category_scores_gemma":[0.0001344794,0.0002274122,0.0001832145,0.0009185069,0.00007336568,0.0003142729,0.0006495736,0.0003352907,0.0002006956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001221819,"about_ca_system_score_gemma":0.00009841364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003212638,"about_ca_topic_score_gemma":0.000001934412,"domain_scores_codex":[0.9979241,0.00009892534,0.0003389316,0.0006830529,0.0004945543,0.0004604147],"domain_scores_gemma":[0.9985356,0.0001176093,0.00009425048,0.0008406088,0.0000969296,0.000315005],"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":[0.00001585857,0.0001116107,0.0004765911,0.00004201914,0.00005149105,0.0001037296,0.001794881,0.001978563,0.001310919,0.916773,0.06564678,0.01169458],"study_design_scores_gemma":[0.0005558797,0.0002808707,0.00120188,0.00002136163,0.000005562686,0.00002822969,0.00002512657,0.9220741,0.0005139346,0.03252745,0.042412,0.0003535691],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1949125,0.001031883,0.7288299,0.07029403,0.001449801,0.0003547825,0.00004143396,0.001452314,0.001633416],"genre_scores_gemma":[0.9550714,0.0000192552,0.036387,0.007769042,0.0006531638,0.00001340573,0.00001329341,0.00002960482,0.000043806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9200956,"threshold_uncertainty_score":0.9273601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01639338014628364,"score_gpt":0.2289598460008861,"score_spread":0.2125664658546025,"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."}}