{"id":"W2888807544","doi":"10.1103/physreva.98.020102","title":"Ramsey interferometry in correlated quantum noise environments","year":2018,"lang":"en","type":"article","venue":"Physical review. A/Physical review, A","topic":"Cold Atom Physics and Bose-Einstein Condensates","field":"Physics and Astronomy","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Office; Fonds de recherche du Québec – Nature et technologies","keywords":"Quantum entanglement; Noise (video); Statistical physics; Physics; Interferometry; Observable; Quantum; Quantum metrology; Scaling; Amplitude; Gaussian noise; Gaussian; Quantum noise; Uncorrelated; Quantum mechanics; Quantum discord; Computer science; Statistics; Algorithm; Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001751556,0.00060873,0.0005317912,0.0005048874,0.0004001798,0.0007633902,0.0008001297,0.0005043427,0.0004885012],"category_scores_gemma":[0.005302944,0.0002541443,0.0001846336,0.0004446456,0.001958425,0.001928032,0.00181004,0.0006407984,0.0001125936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005893031,"about_ca_system_score_gemma":0.0004298874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006137521,"about_ca_topic_score_gemma":0.0008447933,"domain_scores_codex":[0.9987947,0.0004220703,0.00003195086,0.0002630253,0.0003711357,0.0001171422],"domain_scores_gemma":[0.9960078,0.002232369,0.0009049724,0.0004948541,0.0002416208,0.0001183838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005455545,0.0002924036,0.009644972,0.0002113335,0.0002044291,0.0007688058,0.000379543,0.303815,0.3511503,0.3093232,0.000657071,0.02300725],"study_design_scores_gemma":[0.00002748766,0.0003034707,0.002983403,0.00002142308,0.0000351206,0.0001725705,0.00008061656,0.824949,0.1150134,0.05546224,0.0008879445,0.00006334441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.775123,0.000593006,0.2171277,0.0003303893,0.00003765895,0.00004870253,0.0001325205,0.00013723,0.00646986],"genre_scores_gemma":[0.9875417,0.0002031499,0.01175874,0.00004055167,0.00001381418,0.00002139602,0.00004021166,0.00000984009,0.0003707689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001751556,"threshold_uncertainty_score":0.009263217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01325855534067189,"score_gpt":0.336458989386134,"score_spread":0.3232004340454621,"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."}}