{"id":"W3047757000","doi":"10.1103/physrevlett.125.240405","title":"Symmetry Breaking and Error Correction in Open Quantum Systems","year":2020,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Advanced Scientific Computing Research; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Multidisciplinary University Research Initiative; Air Force Office of Scientific Research; National Institute of Standards and Technology; U.S. Department of Energy; National Science Foundation","keywords":"Symmetry (geometry); Quantum; Explicit symmetry breaking; Physics; Symmetry breaking; Quantum mechanics; Theoretical physics; Spontaneous symmetry breaking; Mathematics; Geometry","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":[0.0001818775,0.00009901939,0.0002598392,0.00004105581,0.00004281136,0.0002122591,0.0005038726,0.000006529603,0.000001951788],"category_scores_gemma":[0.00004023247,0.00008366651,0.0000533991,0.0006620958,0.00002182777,0.0008057281,0.0002131442,0.0001351601,0.00005439954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001385814,"about_ca_system_score_gemma":0.000009993118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005879897,"about_ca_topic_score_gemma":7.725918e-7,"domain_scores_codex":[0.9991644,0.00008842075,0.0002294642,0.0002132178,0.0001612545,0.0001432344],"domain_scores_gemma":[0.999556,0.00005943321,0.000103616,0.0001730462,0.00001588829,0.00009200937],"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":[0.0000311615,0.0003649664,0.004412113,0.008258622,0.0000877735,0.00005280197,0.005261106,0.0007602191,0.003964321,0.6750898,0.1351431,0.1665741],"study_design_scores_gemma":[0.0003577897,0.00009120808,0.002827932,0.001802963,0.00001408997,0.00001524521,0.00007324586,0.9643094,0.00003389177,0.0002558586,0.0299113,0.0003070757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4881402,0.01473405,0.3549197,0.1331479,0.001873031,0.003176155,0.000005099151,0.0005037864,0.003500008],"genre_scores_gemma":[0.9609805,0.0005319525,0.0002106048,0.03818023,0.00005511716,0.00003465543,0.000001699838,0.000004592974,6.965787e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9635492,"threshold_uncertainty_score":0.3411821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03349519478763083,"score_gpt":0.3021552850788862,"score_spread":0.2686600902912553,"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."}}