{"id":"W3179235454","doi":"10.1103/physrevapplied.19.044003","title":"Accurate Methods for the Analysis of Strong-Drive Effects in Parametric Gates","year":2023,"lang":"en","type":"article","venue":"Physical Review Applied","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Institut quantique; Université de Sherbrooke","funders":"Army Research Office","keywords":"Transmon; Floquet theory; Quantum gate; Qubit; Computer science; Computation; Parametric statistics; Quantum computer; Spurious relationship; Controlled NOT gate; Physics; Quantum; Topology (electrical circuits); Electronic engineering; Algorithm; Quantum mechanics; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009014723,0.0001396943,0.0006350061,0.0002197736,0.0000573754,0.00002962855,0.0007530955,0.0000168476,6.478488e-7],"category_scores_gemma":[0.0002847222,0.00008282807,0.0003095653,0.007209158,0.00003909247,0.00003042448,0.0002334679,0.0001420198,0.000009270526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001086674,"about_ca_system_score_gemma":0.0000197533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006965297,"about_ca_topic_score_gemma":8.741913e-7,"domain_scores_codex":[0.9988278,0.0001462133,0.0002583597,0.0003397937,0.0001647827,0.000263075],"domain_scores_gemma":[0.9932964,0.005969347,0.0001539471,0.0005037926,0.00003395872,0.0000425456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002635239,0.00005885939,0.00001310655,0.0005415152,0.0002479621,6.669707e-7,0.0001653027,0.0451686,0.0003967169,0.08773325,0.00007288875,0.8655985],"study_design_scores_gemma":[0.0001157805,0.00002849253,0.004331812,0.0001169892,0.0002651409,9.499403e-8,0.000002643145,0.9796011,0.0005595166,0.01432609,0.0005559537,0.00009631988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01187709,0.004301717,0.9819919,0.0006676028,0.00006950674,0.0009286974,0.000003206914,0.00009045175,0.00006980187],"genre_scores_gemma":[0.9181594,0.001255981,0.07979979,0.000318491,0.00006411198,0.0003758578,0.000008679663,0.00001213284,0.000005502131],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9344326,"threshold_uncertainty_score":0.3463762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02764744537916712,"score_gpt":0.3897343576918962,"score_spread":0.362086912312729,"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."}}