{"id":"W2079853850","doi":"10.1103/physrevlett.113.020501","title":"Discriminating Single-Photon States Unambiguously in High Dimensions","year":2014,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Nondeterministic algorithm; Word error rate; Photon; Quantum; Quantum state; Dimension (graph theory); Physics; Quantum cryptography; Quantum error correction; Quantum mechanics; Qubit; Range (aeronautics); State (computer science); Quantum information; Statistical physics; Computer science; Algorithm; Mathematics; Speech recognition","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":[0.0002433194,0.0001350511,0.0002592949,0.00007919099,0.00006110963,0.00007115149,0.0004050726,0.000006365598,0.000005228723],"category_scores_gemma":[0.0000626188,0.0001077724,0.0001125889,0.0005222205,0.00004292159,0.0004648853,0.0001061062,0.0001447122,0.0000990019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002383327,"about_ca_system_score_gemma":0.000005819165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004844339,"about_ca_topic_score_gemma":0.00000410952,"domain_scores_codex":[0.9988776,0.0001162719,0.0002799527,0.0002167368,0.0002534371,0.0002560152],"domain_scores_gemma":[0.9992827,0.0001411073,0.0001094407,0.0003621267,0.00002581836,0.00007884121],"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":[0.000005697396,0.001101133,0.001124423,0.002531888,0.00003905244,0.00001878028,0.003316473,0.001108723,0.02515365,0.7328159,0.01605692,0.2167274],"study_design_scores_gemma":[0.001804029,0.0005636815,0.02036458,0.00864184,0.00009745816,0.00001942245,0.00009014359,0.8136266,0.004282749,0.07148889,0.07682563,0.002194997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8683248,0.0005562518,0.1106647,0.0191727,0.0001580436,0.0003050814,0.000001396346,0.0001748134,0.000642231],"genre_scores_gemma":[0.9505482,0.0003131118,0.002840465,0.04622463,0.00003039992,0.0000280933,0.000007303102,0.000006634098,0.000001159499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8125179,"threshold_uncertainty_score":0.4394831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416073087059052,"score_gpt":0.2579031858834142,"score_spread":0.2437424550128236,"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."}}