{"id":"W3108732296","doi":"10.1145/3593593","title":"Rigidity of Superdense Coding","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Quantum Computing","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; Kavli Institute for Theoretical Physics, University of California, Santa Barbara; National Science Foundation","keywords":"Superdense coding; Communication source; Computer science; Quantum entanglement; Coding (social sciences); Unitary state; Randomness; Theoretical computer science; Qubit; Quantum; Discrete mathematics; Mathematics; Physics; Quantum mechanics; Computer network; Quantum channel","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":[0.0004961605,0.0001431153,0.0001930307,0.0005179197,0.0003545627,0.00008167205,0.0008871744,0.00006066281,0.00003550857],"category_scores_gemma":[0.00004211001,0.0001427148,0.000174993,0.001748854,0.00006042615,0.0003715824,0.00003538328,0.0002118891,0.0002579791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001888441,"about_ca_system_score_gemma":0.00004031113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001745904,"about_ca_topic_score_gemma":0.000001672184,"domain_scores_codex":[0.9985902,0.00006738106,0.0004280636,0.0002453159,0.0003503708,0.0003186991],"domain_scores_gemma":[0.9984825,0.0004594616,0.0001181313,0.0007538267,0.00009852603,0.00008753],"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":[0.00004859981,0.0004808955,0.0007030494,0.0003050064,0.0002082217,0.00005236954,0.01105595,0.05741002,0.004028318,0.5810638,0.00278672,0.341857],"study_design_scores_gemma":[0.0004470281,0.000138954,0.003030395,0.00008355472,0.00001028863,0.00002468122,0.0004874574,0.9771077,0.008137739,0.009557115,0.0007189453,0.0002561586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2700272,0.000007000242,0.7279474,0.0004847228,0.0005104074,0.00008294007,0.000004320965,0.000559739,0.0003762317],"genre_scores_gemma":[0.9882619,0.00002428425,0.01148648,0.0001743819,0.00002046507,0.00000348892,0.00000298368,0.000009134421,0.00001680991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9196976,"threshold_uncertainty_score":0.5819741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03306623313664293,"score_gpt":0.2745214806680112,"score_spread":0.2414552475313683,"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."}}