{"id":"W3200537988","doi":"10.1103/physrevlett.129.050505","title":"Quantifying Nonlocality: How Outperforming Local Quantum Codes Is Expensive","year":2022,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"National Science Foundation","keywords":"Low-density parity-check code; Physics; Quantum nonlocality; Omega; Quantum; Dimension (graph theory); Code (set theory); Discrete mathematics; Quantum mechanics; Combinatorics; Decoding methods; Computer science; Quantum entanglement; Mathematics; Algorithm","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":[0.0004825258,0.0003070241,0.0005963392,0.00007018295,0.0006233998,0.0001494449,0.0012606,0.000009232854,0.00001645129],"category_scores_gemma":[0.00004629823,0.0002656566,0.0003566768,0.0006332471,0.0001158178,0.0002345399,0.001106332,0.0006661108,0.00004243509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009503384,"about_ca_system_score_gemma":0.00004719909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003669191,"about_ca_topic_score_gemma":6.560566e-7,"domain_scores_codex":[0.9972889,0.0003264176,0.0002806481,0.0007374494,0.0007937529,0.0005727971],"domain_scores_gemma":[0.9985535,0.0002804861,0.0001956349,0.0007671209,0.00004925698,0.0001539762],"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":[0.00003107294,0.0009981155,0.0003777786,0.004237938,0.0003839397,0.0008370253,0.01428493,0.04373978,0.0181374,0.03874363,0.1187329,0.7594955],"study_design_scores_gemma":[0.0001519452,0.00009900278,0.00005501189,0.0004020176,0.00002445311,0.00006167484,0.00008783067,0.9532614,0.0002940192,0.0003831445,0.04478607,0.000393473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2438822,0.007191464,0.612168,0.135047,0.0007651902,0.0005340211,0.00001669108,0.0003618096,0.00003363198],"genre_scores_gemma":[0.902528,0.0003384326,0.00474586,0.09203247,0.0002446292,0.00006703128,0.000009581983,0.00002623064,0.000007694389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9095216,"threshold_uncertainty_score":0.9999796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03146167953438782,"score_gpt":0.2916615374567209,"score_spread":0.2601998579223331,"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."}}