{"id":"W2784757986","doi":"10.1103/physrevlett.120.213601","title":"Tomography and Purification of the Temporal-Mode Structure of Quantum Light","year":2018,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Laser-Matter Interactions and Applications","field":"Physics and Astronomy","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Leibniz-Gemeinschaft; Gottfried Wilhelm Leibniz Universität Hannover; Deutsche Forschungsgemeinschaft","keywords":"Quantum; Photon; Physics; Quantum optics; Broadband; Parametric statistics; Quantum state; Mode (computer interface); Computer science; Quantum imaging; Quantum tomography; Quantum information; Pulse (music); Optics; Quantum network; Quantum mechanics; Mathematics","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":[0.00002226936,0.00007759195,0.000166751,0.00001543838,0.00005230918,0.000007205626,0.0001339051,0.000003938077,0.0000667815],"category_scores_gemma":[0.000002114281,0.00004812624,0.0001172311,0.0002020638,0.000116745,0.00006215662,0.00002950285,0.00006842668,0.000005728386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000281344,"about_ca_system_score_gemma":0.000006781722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006875749,"about_ca_topic_score_gemma":0.000001225173,"domain_scores_codex":[0.9995124,0.00002949763,0.0001777776,0.0001219021,0.00008804208,0.00007041096],"domain_scores_gemma":[0.9994147,0.00002569574,0.0001846772,0.0002994764,0.00005221169,0.00002318293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000004174713,0.0002343595,0.01530246,0.0004471795,0.0000966295,2.386813e-8,0.0002682875,0.000005152287,0.9185499,0.04317634,0.01740049,0.004515016],"study_design_scores_gemma":[0.0005133643,0.0001164714,0.05910579,0.002936325,0.0005227061,0.000001926843,0.0001029018,0.001820478,0.7461264,0.02596364,0.1621964,0.0005936494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901791,0.0001569652,0.001067344,0.007941728,0.00004703043,0.0002627222,0.00007104547,0.000005424779,0.0002686948],"genre_scores_gemma":[0.9988152,0.00002042619,0.0001042596,0.0008692885,0.0001523759,0.00001642772,0.00001060497,0.000005982009,0.000005409961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1724235,"threshold_uncertainty_score":0.1962531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008722045405816403,"score_gpt":0.2859415858677034,"score_spread":0.277219540461887,"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."}}