{"id":"W2893036903","doi":"10.1109/dsd.2018.00005","title":"Optimization of Circuits for IBM's Five-Qubit Quantum Computers","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Quantum computer; IBM; Controlled NOT gate; Qubit; Computer science; Electronic circuit; Quantum circuit; Fidelity; Quantum gate; Set (abstract data type); Computer engineering; Quantum; Electrical engineering; Quantum error correction; Physics; Engineering; Quantum mechanics; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004289944,0.0003668355,0.0005514543,0.0002604474,0.0001422452,0.0002118875,0.002070621,0.0002820879,0.00001293121],"category_scores_gemma":[0.00006493095,0.0003317443,0.0003007753,0.0002562173,0.0001071675,0.0001041157,0.001836105,0.0003137489,0.000006102378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000389042,"about_ca_system_score_gemma":0.0002253774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005655521,"about_ca_topic_score_gemma":0.00000197195,"domain_scores_codex":[0.9976469,0.00008043253,0.0005732266,0.0009412526,0.0003549989,0.0004031436],"domain_scores_gemma":[0.9975342,0.0002878788,0.0004902374,0.001123108,0.0004478314,0.000116749],"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":[0.000004172969,0.00007610508,0.00001302338,0.0002682265,0.0000701652,0.000002153983,0.0006402577,0.9531587,0.00002017592,0.01360388,0.004762054,0.02738111],"study_design_scores_gemma":[0.000333803,0.0002139505,0.00008740653,0.0002482168,0.00001612709,0.000008521174,0.000006010117,0.9845357,0.0003790649,0.01324867,0.0005454784,0.0003770746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00432502,0.00009233336,0.9902285,0.0007065188,0.003104615,0.0006862584,0.00003453521,0.0003621123,0.0004600826],"genre_scores_gemma":[0.1123554,0.0000169695,0.8864023,0.0003071764,0.0006012737,0.0000349566,0.00006528656,0.00003783028,0.0001788394],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1080304,"threshold_uncertainty_score":0.9999135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831536029599826,"score_gpt":0.254833830983043,"score_spread":0.2365184706870448,"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."}}