{"id":"W1904238065","doi":"10.1103/physreva.92.052323","title":"Searching for quantum speedup in quasistatic quantum annealers","year":2015,"lang":"en","type":"article","venue":"Physical Review A","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":161,"is_retracted":false,"has_abstract":true,"ca_institutions":"D-Wave Systems (Canada); Simon Fraser University","funders":"","keywords":"Speedup; Quantum annealing; Quasistatic process; Physics; Statistical physics; Quantum; Quantum Monte Carlo; Quantum algorithm; Quantum computer; Monte Carlo method; Qubit; Hamiltonian (control theory); Quantum mechanics; Computer science; Parallel computing; Mathematics; Mathematical optimization; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001367926,0.0002216061,0.0006435166,0.0004046658,0.001098912,0.00152282,0.0009449174,0.001096419,0.005091495],"category_scores_gemma":[0.005834363,0.0004248595,0.0004634399,0.000311052,0.002408435,0.003390905,0.001083061,0.00122018,0.000337837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009271835,"about_ca_system_score_gemma":0.0006290547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006036774,"about_ca_topic_score_gemma":0.0008652053,"domain_scores_codex":[0.9996628,0.00008769547,0.00001319653,0.00007029052,0.00007634097,0.00008966935],"domain_scores_gemma":[0.9975695,0.001445735,0.0002543923,0.0004220795,0.0001531244,0.0001551714],"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":[0.000223376,0.0001248858,0.00201885,0.0001024091,0.00004437774,0.0002349681,0.0003107981,0.08121059,0.01140426,0.8915409,0.001031602,0.01175297],"study_design_scores_gemma":[0.0000797265,0.0001577391,0.001166501,0.00001971486,0.00002206251,0.0001261011,0.0001230994,0.4574845,0.005728775,0.5321502,0.002914015,0.00002741885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8538651,0.0007031322,0.1202292,0.002710389,0.00009734459,0.00005595198,0.00004409629,0.0002726638,0.02202201],"genre_scores_gemma":[0.9813887,0.0001905202,0.01557318,0.0001261254,0.00002795714,0.00004011457,0.00001892032,0.00004427554,0.002590237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005091495,"threshold_uncertainty_score":0.01703274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04924061468170257,"score_gpt":0.3501909471162513,"score_spread":0.3009503324345487,"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."}}