{"id":"W3042949392","doi":"10.1103/physreva.102.062607","title":"Loss-tolerant quantum key distribution with mixed signal states","year":2020,"lang":"en","type":"article","venue":"Physical review. A/Physical review, A","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Quantum Research Center; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Huawei Technologies; Ministry of Education - Singapore; Ontario Research Foundation; National Research Foundation Singapore; Royal Bank of Canada; Cummings Foundation; National Science Foundation","keywords":"Quantum key distribution; Computer science; Qubit; Key (lock); SIGNAL (programming language); Theoretical computer science; Quantum; Quantum mechanics; Physics; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001810925,0.0004268185,0.00050749,0.0004329417,0.0003737628,0.001582984,0.0009358547,0.0006351452,0.002536578],"category_scores_gemma":[0.003718307,0.0003918899,0.0004730048,0.0005147299,0.001982266,0.002586067,0.001938058,0.001465786,0.0006311971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008418438,"about_ca_system_score_gemma":0.000640411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001446362,"about_ca_topic_score_gemma":0.0001236968,"domain_scores_codex":[0.9988376,0.0004744672,0.00004615854,0.0001194066,0.0004269112,0.00009547785],"domain_scores_gemma":[0.9987395,0.0006894713,0.0001669633,0.00024804,0.0001102816,0.0000457641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000121771,0.00004171876,0.0002130986,0.00009536605,0.00001901232,0.0000805521,0.00006933133,0.04794217,0.01062281,0.9282444,0.0006284784,0.01192127],"study_design_scores_gemma":[0.00006826742,0.0001419137,0.0001620075,0.00004509667,0.00001649852,0.0001255487,0.00003617229,0.515463,0.0199752,0.4592681,0.004658494,0.00003965511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06652909,0.0005162229,0.9153997,0.0008136458,0.00006986369,0.00006791244,0.0001095692,0.0002207899,0.01627319],"genre_scores_gemma":[0.8768187,0.0007068812,0.117648,0.0002526075,0.00005897987,0.0001654078,0.00008905075,0.00008160502,0.004178705],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002536578,"threshold_uncertainty_score":0.009577215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465401791407804,"score_gpt":0.2998931336183681,"score_spread":0.28523911570429,"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."}}