{"id":"W4395444109","doi":"10.48550/arxiv.2404.14493","title":"On verifiable quantum advantage with peaked circuit sampling","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kavli Institute for Theoretical Physics, University of California, Santa Barbara; University of Toronto; U.S. Department of Energy; U.S. Department of Defense; Office of Science; National Science Foundation","keywords":"Verifiable secret sharing; Sampling (signal processing); Computer science; Quantum; Physics; Quantum mechanics; Telecommunications; Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002581802,0.0004951495,0.000815711,0.0005860369,0.0005595178,0.001435085,0.001660157,0.001241936,0.004814622],"category_scores_gemma":[0.01381023,0.0004625123,0.0006523668,0.0004672739,0.003404663,0.003459793,0.001757307,0.002281981,0.0002722156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002115755,"about_ca_system_score_gemma":0.001101144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001003666,"about_ca_topic_score_gemma":0.0007205936,"domain_scores_codex":[0.9982178,0.0007952267,0.00004327601,0.0002035861,0.0004714192,0.0002686729],"domain_scores_gemma":[0.9921078,0.006320706,0.0003872725,0.0007623133,0.0002396174,0.0001821691],"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":[0.0003381438,0.00009240344,0.0008920574,0.0001047411,0.00003210377,0.0001730426,0.0001158015,0.1984481,0.01064748,0.7781218,0.0008339711,0.0102003],"study_design_scores_gemma":[0.00005151801,0.00007764185,0.0001673466,0.00001657289,0.00001012731,0.00005044375,0.00001709338,0.8142092,0.004404718,0.1804195,0.0005546409,0.00002129171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3133323,0.0005906845,0.6659292,0.001220089,0.00007914456,0.000182454,0.0002140523,0.001136852,0.01731537],"genre_scores_gemma":[0.9593112,0.0001279853,0.03860339,0.0001842976,0.0000196455,0.00009130828,0.00006269239,0.00008615445,0.001513231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004814622,"threshold_uncertainty_score":0.01610655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0659768341863672,"score_gpt":0.191679732223094,"score_spread":0.1257028980367269,"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."}}