{"id":"W2902397160","doi":"10.1139/cjp-2018-0452","title":"Additive composition formulation of the iterative Grover algorithm","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Redeemer University","funders":"Japan Society for the Promotion of Science","keywords":"Superposition principle; Algorithm; Physics; Rotation (mathematics); Search algorithm; Phase (matter); Operator (biology); Mathematics; Quantum mechanics; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001029823,0.00007010801,0.0001077792,0.00005541952,0.0001822398,0.00005414807,0.0004036753,0.00002440916,0.000005330673],"category_scores_gemma":[0.00001209613,0.00004900242,0.00008945735,0.0002800978,0.00009214191,0.0002550418,0.00002736527,0.0001473802,0.00000224382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005428522,"about_ca_system_score_gemma":0.0003906777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002161004,"about_ca_topic_score_gemma":0.0001811326,"domain_scores_codex":[0.9994015,0.00005398835,0.0001781182,0.00007537241,0.0001548443,0.0001361471],"domain_scores_gemma":[0.9990087,0.00004468557,0.0002687015,0.0001510206,0.000411115,0.0001157522],"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":[0.000005343532,0.00004059716,0.0003680537,0.000009077723,0.00009272901,0.00002189522,0.01369968,0.003251015,0.001614587,0.0677327,0.003190669,0.9099737],"study_design_scores_gemma":[0.0005769558,0.0005954138,0.01981468,0.0002925409,0.0000254858,0.0001472958,0.00006636139,0.8627809,0.04992111,0.06205717,0.003483205,0.0002389222],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1008815,0.00003053723,0.8972995,0.0004766239,0.0008842223,0.0000628121,0.00002944668,0.000004402071,0.0003309733],"genre_scores_gemma":[0.9739139,4.191934e-7,0.02521424,0.0002057764,0.0006481928,1.977021e-7,0.000001116636,0.00000415329,0.00001198196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9097347,"threshold_uncertainty_score":0.1998261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007626706953568936,"score_gpt":0.2130652140179394,"score_spread":0.2054385070643705,"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."}}