{"id":"W2899524259","doi":"10.1145/3290344","title":"Quantitative robustness analysis of quantum programs","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wind Energy Technologies Office; Office of Science; Canadian Institute for Advanced Research; Advanced Scientific Computing Research; U.S. Department of Energy","keywords":"Robustness (evolution); Quantum computer; Quantum; Quantum logic; Computation; Quantum algorithm; Quantum error correction; Property (philosophy)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005496415,0.0002057443,0.0004680959,0.0003364976,0.00008198898,0.0001191052,0.003497669,0.00006989751,0.000003781076],"category_scores_gemma":[0.0004460448,0.000131808,0.0003441065,0.002593851,0.0001201122,0.0001666746,0.001091024,0.0002270839,0.000002671709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001719691,"about_ca_system_score_gemma":0.00002534899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004811366,"about_ca_topic_score_gemma":0.000002170723,"domain_scores_codex":[0.9982888,0.0000201441,0.0003633226,0.00045121,0.0005373238,0.0003392001],"domain_scores_gemma":[0.9981079,0.0001759268,0.0005456127,0.0008205533,0.0002976924,0.00005233935],"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":[0.0001297633,0.001203701,0.08633053,0.0009357152,0.002494388,0.000004470066,0.01450421,0.02132463,0.01409717,0.3233751,0.0001974551,0.5354029],"study_design_scores_gemma":[0.0006346708,0.001752783,0.02417737,0.0006614357,0.000483651,0.00001131037,0.002962409,0.9390508,0.02575436,0.003309732,0.0005937705,0.0006076994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995248,0.0001989193,0.002649587,0.0009298214,0.0001514219,0.000424124,0.000002574226,0.0001532128,0.0002423181],"genre_scores_gemma":[0.8857912,0.000003033524,0.1140485,0.00003187022,0.00001739247,0.00001387095,0.000001649476,0.00001328551,0.00007918622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9177262,"threshold_uncertainty_score":0.6499597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01364223519066183,"score_gpt":0.2654272453488792,"score_spread":0.2517850101582174,"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."}}