{"id":"W3204444058","doi":"10.1038/s41566-021-00877-w","title":"Turbulence-resilient pilot-assisted self-coherent free-space optical communications using automatic optoelectronic mixing of many modes","year":2021,"lang":"en","type":"article","venue":"Nature Photonics","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Defense Security Cooperation Agency; Office of Naval Research; Multidisciplinary University Research Initiative; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Physics; Free-space optical communication; Optics; Optical communication; Quadrature amplitude modulation; Gaussian beam; Multiplexing; Gaussian; Turbulence; Amplitude; Beam (structure); Telecommunications; Computer science; Bit error rate; Quantum mechanics; Decoding methods","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001976573,0.0002868376,0.0004399717,0.0001492876,0.0001564217,0.00006407833,0.001729025,0.0004682553,0.00003195504],"category_scores_gemma":[0.0003569816,0.0003003734,0.0001322057,0.0007753145,0.0001633956,0.0001411249,0.0008701407,0.001721376,0.00000739756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005240666,"about_ca_system_score_gemma":0.0001854985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009613037,"about_ca_topic_score_gemma":0.00005339738,"domain_scores_codex":[0.9982471,0.00009376671,0.0005350822,0.0002778449,0.0003859494,0.0004602169],"domain_scores_gemma":[0.9959096,0.0004079644,0.0001169996,0.003210878,0.0002628696,0.00009168901],"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":[0.00002990789,0.001905508,0.0001875091,0.00127051,0.0009700519,0.00002510479,0.000622495,0.06962348,0.5895223,0.3214461,0.0006439659,0.01375302],"study_design_scores_gemma":[0.0003342345,0.0000471013,0.0002117211,0.0001898971,0.00006748694,0.0000243642,0.0001885789,0.7605816,0.2362613,0.001201101,0.0006404888,0.0002521294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9243638,0.05610129,0.007890872,0.001618573,0.0002360487,0.0006374395,0.00004111034,0.00257807,0.006532803],"genre_scores_gemma":[0.7553821,0.002298719,0.2421684,0.00002721532,0.000005812052,0.00003870894,0.00001910156,0.00004742902,0.00001258563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6909581,"threshold_uncertainty_score":0.9999449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767023288563724,"score_gpt":0.2663029042502818,"score_spread":0.2486326713646446,"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."}}