{"id":"W1556973100","doi":"10.3390/e17074547","title":"Noiseless Linear Amplifiers in Entanglement-Based Continuous-Variable Quantum Key Distribution","year":2015,"lang":"en","type":"article","venue":"Entropy","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Fund for Distinguished Young Scholars; National Key Research and Development Program of China; Engineering and Physical Sciences Research Council; State Key Laboratory of Information Photonics and Optical Communications; Leverhulme Trust","keywords":"Quantum entanglement; Quantum key distribution; Computer science; Squashed entanglement; Continuous variable; Key (lock); Transmission (telecommunications); Topology (electrical circuits); Protocol (science); Quantum; Quantum mechanics; Mathematics; Physics; Telecommunications; Mathematical optimization; Computer security","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":[0.00129104,0.0005761146,0.000404705,0.0004637588,0.0004047094,0.0008224036,0.001306401,0.0007202949,0.001445554],"category_scores_gemma":[0.004018024,0.0002535054,0.0002583397,0.0005392318,0.002072347,0.002247632,0.001185836,0.00091748,0.0003378575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007216656,"about_ca_system_score_gemma":0.0004525319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000497281,"about_ca_topic_score_gemma":0.0004164304,"domain_scores_codex":[0.9990054,0.0004160629,0.00003336026,0.0001214428,0.0003286357,0.00009510472],"domain_scores_gemma":[0.9974044,0.001831162,0.0002372607,0.0002339814,0.0002211051,0.00007205261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008837598,0.0003160047,0.001644833,0.0003936696,0.0001198648,0.0004404026,0.0005339117,0.4292424,0.1767277,0.3114921,0.000872265,0.07733301],"study_design_scores_gemma":[0.00006213441,0.0002579079,0.000149798,0.00001961458,0.00003607034,0.00007985546,0.00002216333,0.9401857,0.03769416,0.02013311,0.001324165,0.00003537031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1329535,0.0007480432,0.860613,0.0003871172,0.00007934721,0.00007784709,0.00002532213,0.0004032324,0.004712593],"genre_scores_gemma":[0.949105,0.0002356884,0.04921297,0.0000896416,0.0000349702,0.00005967712,0.00001152012,0.0000215529,0.00122911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001445554,"threshold_uncertainty_score":0.006827712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01638727909396116,"score_gpt":0.2414393429294273,"score_spread":0.2250520638354662,"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."}}