{"id":"W4226083025","doi":"10.48550/arxiv.2202.08380","title":"The platypus of the quantum channel zoo","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Army Research Office; Multidisciplinary University Research Initiative; National Science Foundation","keywords":"Quantum channel; Channel (broadcasting); Qutrit; Quantum; Variety (cybernetics); Qubit; Quantum information; Computer science; Classical capacity; Amplitude damping channel; Information flow; Conjecture; Topology (electrical circuits); Physics; Mathematics; Theoretical physics; Theoretical computer science; Quantum mechanics; Pure mathematics; Quantum network; Telecommunications; Combinatorics; Artificial intelligence; Philosophy","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":[0.000429938,0.000253459,0.0002480947,0.00009540141,0.0008598156,0.00009507009,0.005224967,0.0001220059,0.00001125062],"category_scores_gemma":[0.00004299268,0.0001731704,0.0003514695,0.0007267945,0.0002059584,0.00006510709,0.007854844,0.001094069,0.000007287023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008959437,"about_ca_system_score_gemma":0.0002449555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001574614,"about_ca_topic_score_gemma":0.00002110519,"domain_scores_codex":[0.9982214,0.0002986372,0.0002110104,0.0007264395,0.0001841193,0.0003583684],"domain_scores_gemma":[0.9971676,0.0003160452,0.0003942336,0.00196635,0.00008243599,0.00007329232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001172074,0.00004286866,0.0002297728,0.00002723977,0.00006510921,0.00004569425,0.0005398534,0.8095946,0.000006401055,0.1879354,0.0004416709,0.001059626],"study_design_scores_gemma":[0.0001518053,0.00003972361,0.00129396,0.00003974664,0.00002093444,0.000006843815,0.00009301985,0.9105855,0.00004052275,0.08466269,0.002858091,0.0002071861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7469373,0.0004719725,0.2421422,0.00169643,0.006014526,0.000583121,0.0000383287,0.0002869179,0.001829141],"genre_scores_gemma":[0.9982503,0.00008720433,0.0002122292,0.00008760334,0.00008327738,9.467514e-7,0.000002034076,0.00001431535,0.001262099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2513129,"threshold_uncertainty_score":0.97905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03733223417230856,"score_gpt":0.1748285517745969,"score_spread":0.1374963176022883,"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."}}