{"id":"W2473578726","doi":"10.1038/ncomms11925","title":"Loss-tolerant state engineering for quantum-enhanced metrology via the reverse Hong–Ou–Mandel effect","year":2016,"lang":"en","type":"article","venue":"Nature Communications","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education and Science of the Russian Federation; Canadian Institute for Advanced Research","keywords":"Quantum metrology; Physics; Quantum state; Photon; Metrology; Quantum optics; Quantum information science; Coherent states; Homodyne detection; Spontaneous parametric down-conversion; State (computer science); Quantum; Measure (data warehouse); Fidelity; Quantum sensor; Computer science; Quantum mechanics; Quantum entanglement; Quantum network; Telecommunications; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006271275,0.000152007,0.0001683518,0.0001650776,0.0003566927,0.00007623882,0.002636063,0.0001406564,0.000005435135],"category_scores_gemma":[0.0001925726,0.0000865383,0.0001578728,0.0004999602,0.0001166016,0.0004643413,0.0003338576,0.0004182687,0.00004493737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003234623,"about_ca_system_score_gemma":0.00003159314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004192282,"about_ca_topic_score_gemma":0.0000289598,"domain_scores_codex":[0.998985,0.0001296576,0.0002795253,0.0001749101,0.0001630893,0.0002678127],"domain_scores_gemma":[0.9960177,0.001366345,0.0001427101,0.002223931,0.0001837813,0.00006551756],"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":[0.00005370656,0.00008838053,0.0003541494,0.00003972344,0.0001621822,7.874646e-7,0.001119756,0.0002468382,0.01246674,0.9273018,0.007727107,0.05043881],"study_design_scores_gemma":[0.003845553,0.0005182902,0.008803944,0.0001411738,0.00007740477,0.00004314818,0.00004177339,0.5017408,0.01628804,0.02148214,0.4461415,0.0008761931],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008837258,0.0009776192,0.9724681,0.01623885,0.0004137548,0.0004741978,0.00001896887,0.000240188,0.0003310661],"genre_scores_gemma":[0.9824678,0.0002714822,0.01581946,0.001171184,0.00002370283,0.0001886384,0.00000994103,0.00001064012,0.00003720802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9736305,"threshold_uncertainty_score":0.4898505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009689668649562999,"score_gpt":0.2638712514596744,"score_spread":0.2541815828101114,"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."}}