{"id":"W4383045339","doi":"10.48550/arxiv.2306.17230","title":"Superselection Rules, Quantum Error Correction, and Quantum Chromodynamics","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Brookhaven National Laboratory; Institute for Quantum Information and Matter, California Institute of Technology; Office of Science; Fonds Wetenschappelijk Onderzoek; Advanced Scientific Computing Research; National Research Foundation; Natural Sciences and Engineering Research Council of Canada; Vlaamse regering; U.S. Department of Energy; National Science Foundation","keywords":"Superselection; Quantum; Physics; Quantum error correction; Quantum field theory; Theoretical physics; Quantum mechanics; Quantum algorithm; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001003022,0.0002359758,0.0004084416,0.0007455088,0.001276446,0.001731722,0.0008289231,0.001033449,0.002623066],"category_scores_gemma":[0.003382825,0.0001482966,0.0003600919,0.0006333083,0.004350696,0.002710215,0.001041273,0.001461623,0.0003163862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008481571,"about_ca_system_score_gemma":0.0007138185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001177597,"about_ca_topic_score_gemma":0.0008319003,"domain_scores_codex":[0.9992635,0.0002027923,0.00003099833,0.00008788285,0.0002619187,0.0001529095],"domain_scores_gemma":[0.9973666,0.00122616,0.0003402328,0.0006596268,0.0002932298,0.0001141418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008177997,0.000008082381,0.0002540725,0.000008900902,0.000002295111,0.00004109437,0.00006927777,0.002880326,0.000779395,0.9938644,0.0001828634,0.001901218],"study_design_scores_gemma":[0.000004551167,0.00001487141,0.0001522783,0.000005176379,0.000002895045,0.00005662832,0.0000583455,0.02590925,0.002409773,0.9704579,0.0009184167,0.000009925031],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6753782,0.001239939,0.2252908,0.004308521,0.0002723785,0.00004837733,0.0001240293,0.000201865,0.09313587],"genre_scores_gemma":[0.9856996,0.0002817957,0.01150402,0.0001422202,0.00005249734,0.00001761443,0.00002406602,0.00002556625,0.00225258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002623066,"threshold_uncertainty_score":0.008774996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04657545105018478,"score_gpt":0.1937089216711387,"score_spread":0.1471334706209539,"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."}}