{"id":"W4406261887","doi":"10.1109/qce60285.2024.10429","title":"Denoising Wavelength-Multiplexed Time-Bin Correlated Photons for Quantum Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Quantum optics and atomic interactions","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Photon; Bin; Computer science; Multiplexing; Wavelength; Physics; Noise reduction; Quantum; Optoelectronics; Optics; Telecommunications; Quantum mechanics; Algorithm; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002468965,0.0003103204,0.0002229982,0.0001863254,0.0001739215,0.0003889012,0.0003945613,0.0003078458,0.001362407],"category_scores_gemma":[0.0004261021,0.00009683429,0.00008103786,0.0002462155,0.0005289902,0.000625437,0.0005776681,0.0004440317,0.0002218217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003335795,"about_ca_system_score_gemma":0.0001752506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002091942,"about_ca_topic_score_gemma":0.0005253925,"domain_scores_codex":[0.9998286,0.00003002012,0.000004689698,0.00002987361,0.00008500125,0.00002190936],"domain_scores_gemma":[0.9997837,0.0000767953,0.00006151263,0.00003035568,0.00002634756,0.00002137531],"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":[0.0001471656,0.00007420585,0.000482277,0.0001033482,0.00001780832,0.0001451728,0.0001181037,0.01619759,0.9169024,0.03629183,0.000542184,0.02897792],"study_design_scores_gemma":[0.00001168411,0.0001228976,0.0004306488,0.00001164746,0.000008029248,0.0001354631,0.00003296836,0.250643,0.7364489,0.006151474,0.005975335,0.00002803044],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5413663,0.001125802,0.445925,0.0003309106,0.0001672866,0.00005351275,0.00009722777,0.000699196,0.01023473],"genre_scores_gemma":[0.9079003,0.0004390641,0.08835749,0.0001102104,0.00002241354,0.00003407256,0.00005161064,0.00006192746,0.003022955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001362407,"threshold_uncertainty_score":0.004557729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008331165692328536,"score_gpt":0.2571567706148889,"score_spread":0.2488256049225604,"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."}}