{"id":"W2952301357","doi":"10.48550/arxiv.0810.2780","title":"Universal quantum computation in a hidden basis","year":2008,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Mitacs; Government of Canada; Canadian Institute for Advanced Research","keywords":"Invariant (physics); Bounded function; Quantum computer; Qubit; Mathematics; Quantum; Quantum state; Discrete mathematics; Basis (linear algebra); Quantum algorithm; Quantum mechanics; Mathematical physics; Physics; Mathematical analysis","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002031445,0.0003834597,0.0004263406,0.0006435683,0.0001797096,0.0001053356,0.001761221,0.0003083019,0.000006034285],"category_scores_gemma":[0.00002249141,0.0004556611,0.0002248978,0.001069252,0.0001214447,0.0002565193,0.002064933,0.0009526942,0.00005214185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002871812,"about_ca_system_score_gemma":0.0003289591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005707557,"about_ca_topic_score_gemma":0.00005350158,"domain_scores_codex":[0.9975807,0.0002523259,0.0002606888,0.001290174,0.0001447035,0.0004713906],"domain_scores_gemma":[0.9984926,0.000165294,0.0002547797,0.0008090601,0.0001112393,0.0001670428],"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":[0.00001627734,0.0001048167,0.001180785,0.00003855147,0.00003662817,0.001505768,0.0008144835,0.9677448,0.000005528456,0.02251564,0.0002862419,0.005750534],"study_design_scores_gemma":[0.0005790097,0.00005630938,0.003737834,0.0001267889,0.00001423402,0.00002630421,0.00005346171,0.9707934,0.00001404915,0.0239362,0.000184432,0.0004779815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5254815,0.00004011517,0.4727094,0.0001727189,0.0004944907,0.0001727136,0.000007225835,0.0002663373,0.0006555018],"genre_scores_gemma":[0.9888907,0.0001608073,0.01054654,0.00007971907,0.00008984504,4.110222e-7,0.00001785561,0.0000213996,0.0001927163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4634092,"threshold_uncertainty_score":0.9997895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04249667185003747,"score_gpt":0.1881049257764523,"score_spread":0.1456082539264149,"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."}}