{"id":"W2949093047","doi":"10.26421/qic15.9-10-3","title":"Tensor networks and graphical calculus for open quantum systems","year":2015,"lang":"en","type":"article","venue":"Quantum Information and Computation","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Canada Excellence Research Chairs, Government of Canada; Natural Sciences and Engineering Research Council of Canada; Foundational Questions Institute; Canadian Institute for Advanced Research","keywords":"Multipartite; Quantum entanglement; Tensor (intrinsic definition); Quantum information; Bipartite graph; Mathematics; Fidelity; Quantum; Algebra over a field; Computer science; Calculus (dental); Theoretical computer science; Pure mathematics; Discrete mathematics; Quantum mechanics; Graph; Physics","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":[0.002954407,0.0009701359,0.0006661856,0.002487392,0.002134871,0.003889591,0.001364782,0.001264863,0.007501189],"category_scores_gemma":[0.005905288,0.0004467855,0.001520875,0.002259971,0.00574651,0.007620182,0.002525122,0.003070926,0.001110461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002496433,"about_ca_system_score_gemma":0.001391816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002784825,"about_ca_topic_score_gemma":0.001902919,"domain_scores_codex":[0.9976285,0.000984252,0.0001403737,0.0003443605,0.0006532422,0.0002493592],"domain_scores_gemma":[0.9975604,0.001258806,0.0002388613,0.0003227644,0.0004232119,0.0001958518],"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":[0.000001289555,0.000001712964,0.000008333044,0.000009243573,0.000001313289,0.00001109144,0.00004219795,0.0007500956,0.00007811104,0.9979302,0.0002517899,0.0009147539],"study_design_scores_gemma":[0.000002587281,0.000004096779,0.00001754646,0.00001145626,0.000002988069,0.00002408571,0.00002188595,0.008171249,0.0001138707,0.9854248,0.006198404,0.000006937875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01128071,0.001666058,0.945347,0.002008833,0.0003617524,0.00009096289,0.0003749639,0.0003265199,0.03854332],"genre_scores_gemma":[0.5495505,0.003938814,0.419108,0.001540903,0.001017425,0.0007095232,0.0005458458,0.0003817816,0.0232073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007501189,"threshold_uncertainty_score":0.02509397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02436090355698631,"score_gpt":0.2745504652321133,"score_spread":0.250189561675127,"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."}}