{"id":"W2138674143","doi":"10.1109/tit.2011.2165149","title":"High Performance Single-Error-Correcting Quantum Codes for Amplitude Damping","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo","funders":"","keywords":"Dimension (graph theory); Code word; Decoding methods; Block code; Amplitude; Algorithm; Construct (python library); Quantum; Block (permutation group theory); Computer science; Discrete mathematics; Mathematics; Combinatorics; Physics; Quantum mechanics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006659342,0.0002061225,0.0001812429,0.0002913362,0.0006449084,0.0001654592,0.0005419032,0.0000832501,0.0000219772],"category_scores_gemma":[0.00001819075,0.0001890576,0.0001147744,0.0003144133,0.00005719878,0.001476889,0.00000577907,0.000266228,0.00006652146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005668479,"about_ca_system_score_gemma":0.00004380394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002164405,"about_ca_topic_score_gemma":0.000001837243,"domain_scores_codex":[0.9987149,0.00006842954,0.0004434455,0.0002110857,0.0002114295,0.0003506739],"domain_scores_gemma":[0.9988544,0.0003095705,0.0002082409,0.0004110424,0.0001352063,0.00008153774],"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":[0.0001356095,0.000149326,0.000004757376,0.0001038153,0.00005358697,5.759043e-7,0.01603185,0.1520538,0.0001623146,0.03457319,0.0000422157,0.796689],"study_design_scores_gemma":[0.0005875478,0.0004775592,0.0001637168,0.0001239718,0.00001753012,0.00004764415,0.00048727,0.9392555,0.04671038,0.01124665,0.0004951587,0.0003871215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1191284,0.000005863389,0.8779785,0.00005847358,0.001716043,0.0002507354,0.00001397623,0.0004426072,0.0004053814],"genre_scores_gemma":[0.9349479,0.000003805826,0.06441501,0.0004723918,0.00004744353,0.00005704287,0.00000524638,0.00001204784,0.00003913276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8158195,"threshold_uncertainty_score":0.7709545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02439391026629164,"score_gpt":0.2311883811895065,"score_spread":0.2067944709232149,"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."}}