{"id":"W2943747723","doi":"10.1002/andp.201900022","title":"Direct Observation of Dissipation in Dynamical Search Algorithm using Transmon Qubits","year":2019,"lang":"en","type":"article","venue":"Annalen der Physik","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Transmon; Dissipation; Qubit; Quantum decoherence; Physics; Noise (video); Charge qubit; Energy (signal processing); Quantum computer; Quantum; Subspace topology; Algorithm; Statistical physics; Quantum mechanics; Phase qubit; Computer science","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":[0.000171874,0.00007956057,0.0001313828,0.0001700892,0.00002605532,0.0000356656,0.0002421709,0.00004149717,0.00001218636],"category_scores_gemma":[0.000002971232,0.00007648415,0.00006733054,0.0007080749,0.00001932972,0.001025771,0.00003079261,0.00007884673,0.00002199332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001867602,"about_ca_system_score_gemma":0.00003644915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000953301,"about_ca_topic_score_gemma":0.000008000045,"domain_scores_codex":[0.9991165,0.00005481367,0.0002358753,0.0001548706,0.0002806311,0.0001572439],"domain_scores_gemma":[0.9995659,0.00003046336,0.00006600926,0.0002280631,0.00007604304,0.00003352702],"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":[0.00007262059,0.0009483402,0.1030265,0.0005273985,0.0001199099,0.000005751194,0.0207556,0.01854616,0.05894062,0.07575862,0.0001683618,0.7211302],"study_design_scores_gemma":[0.0002540674,0.00004258103,0.135723,0.00004079394,0.000002294753,7.432906e-7,0.00004923149,0.8550518,0.007835804,0.0008230897,0.00007674809,0.00009981739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8047478,0.00002533624,0.1941867,0.0001173788,0.00007269441,0.0001360384,0.00000240994,0.00003060896,0.0006809782],"genre_scores_gemma":[0.9913663,0.000008839409,0.008475014,0.00009672366,0.00001165301,0.000003511018,0.00001403973,0.000004579614,0.00001931422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8365057,"threshold_uncertainty_score":0.3118933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02746065945632982,"score_gpt":0.2757309268647616,"score_spread":0.2482702674084318,"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."}}