{"id":"W4321444449","doi":"10.22331/q-2023-02-21-929","title":"Efficient color code decoders in <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mi>d</mml:mi><mml:mo>&amp;#x2265;</mml:mo><mml:mn>2</mml:mn></mml:math> dimensions from toric code decoders","year":2023,"lang":"en","type":"article","venue":"Quantum","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Government of Canada; Institut Périmètre de physique théorique; Industry Canada; Simons Foundation","keywords":"Decoding methods; Code (set theory); Computer science; Approx; Algorithm; Lattice (music); Square (algebra); Mathematics; Physics; Geometry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000780495,0.0009705158,0.0006384085,0.0005403401,0.0005774838,0.00125167,0.0009064983,0.0009378917,0.006579616],"category_scores_gemma":[0.00416468,0.0003629797,0.0004619012,0.0005016096,0.001008558,0.001801581,0.001624723,0.001547116,0.002392258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342205,"about_ca_system_score_gemma":0.002284015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003216434,"about_ca_topic_score_gemma":0.005175413,"domain_scores_codex":[0.9988589,0.0001535508,0.00005530191,0.0001273532,0.0006265174,0.0001783418],"domain_scores_gemma":[0.9985253,0.0005331031,0.0001462418,0.0003391214,0.0003731363,0.00008297966],"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":[0.0009596006,0.0002105593,0.002919143,0.00039445,0.0001113908,0.0005659967,0.0004561059,0.3127306,0.09554084,0.4252304,0.01354354,0.1473373],"study_design_scores_gemma":[0.0000701715,0.0001319721,0.0004505843,0.00004031294,0.0000293131,0.0002826854,0.00006100584,0.8322384,0.1292687,0.03075302,0.006608513,0.00006530307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1084714,0.0002325199,0.8590426,0.0004203857,0.0001082663,0.0001930504,0.0005378835,0.004016629,0.02697733],"genre_scores_gemma":[0.5671747,0.0002810663,0.4154779,0.0002455182,0.00004226923,0.0002189062,0.001095738,0.0006271483,0.01483669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006579616,"threshold_uncertainty_score":0.02201098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02051097418491303,"score_gpt":0.2495002887244011,"score_spread":0.2289893145394881,"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."}}