{"id":"W4214797950","doi":"10.1007/s00220-023-04653-5","title":"The Tensor Harish-Chandra–Itzykson–Zuber Integral II: Detecting Entanglement in Large Quantum Systems","year":2023,"lang":"en","type":"article","venue":"Communications in Mathematical Physics","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"Japan Society for the Promotion of Science; European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Quantum entanglement; Scaling; Context (archaeology); Tensor (intrinsic definition); Quantum; Generalization; Domain (mathematical analysis); Mathematics; Multipartite entanglement; Multipartite; Pure mathematics; Physics; Theoretical physics; Algebra over a field; Statistical physics; Squashed entanglement; Quantum mechanics; Mathematical analysis; Geometry","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":[0.001505134,0.0001548836,0.0002215623,0.0001753459,0.0006961999,0.0002897078,0.002377257,0.00006012773,0.000005967035],"category_scores_gemma":[0.0002252231,0.0001162969,0.00009743734,0.001885335,0.0001384135,0.0004415539,0.001400012,0.0004561995,0.0003098172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008296433,"about_ca_system_score_gemma":0.00003678095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001578441,"about_ca_topic_score_gemma":0.00004393922,"domain_scores_codex":[0.9981593,0.0002178382,0.0006869396,0.0001775259,0.0003277564,0.0004306067],"domain_scores_gemma":[0.9967047,0.0009196359,0.0001610165,0.00206688,0.00008914556,0.00005862609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001488955,0.0001816021,0.0002881741,0.00003220962,0.000009644093,8.600082e-7,0.004243546,0.00008279007,0.00001749993,0.9908372,0.0005263936,0.003778622],"study_design_scores_gemma":[0.0002948915,0.000023926,0.0005052718,0.000138055,0.00000338068,0.000002680215,0.003153437,0.7908565,0.00003426291,0.2008239,0.004018958,0.0001446344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1089486,0.0008168257,0.8527945,0.009373506,0.0007957473,0.002176139,0.00002496014,0.001102968,0.02396673],"genre_scores_gemma":[0.9932353,0.0001726726,0.006031346,0.0001133781,0.00002026378,0.0003106632,0.00001225857,0.00001329342,0.00009076512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8842868,"threshold_uncertainty_score":0.5354677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05324919612132943,"score_gpt":0.3184183425715146,"score_spread":0.2651691464501852,"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."}}