{"id":"W3184170950","doi":"10.1016/j.cpc.2021.108102","title":"Computational overhead of locality reduction in binary optimization problems","year":2021,"lang":"en","type":"preprint","venue":"Computer Physics Communications","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"QLT (Canada)","funders":"","keywords":"Quadratic unconstrained binary optimization; Quantum annealing; Locality; Binary number; Computer science; Solver; Simulated annealing; Reduction (mathematics); Mathematical optimization; Optimization problem; Population; Quantum; Quantum computer; Ising model; Theoretical computer science; Algorithm; Mathematics; Statistical physics; Physics; Quantum mechanics","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":[0.002091642,0.0006065964,0.001266847,0.0007384768,0.001194627,0.001797668,0.001637536,0.001050397,0.01035696],"category_scores_gemma":[0.01289074,0.0003738749,0.0006651934,0.001480148,0.001600969,0.003046355,0.002028418,0.002070107,0.00075686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610696,"about_ca_system_score_gemma":0.00223822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003622846,"about_ca_topic_score_gemma":0.005540482,"domain_scores_codex":[0.997578,0.001102907,0.00006837877,0.000207003,0.0006544886,0.0003891751],"domain_scores_gemma":[0.9906579,0.007372377,0.0002242267,0.001102767,0.0004536273,0.0001890758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002897853,0.0009634545,0.002336057,0.0007092642,0.0001263967,0.0003016432,0.0004662113,0.4538644,0.01075792,0.2693431,0.02872912,0.2295045],"study_design_scores_gemma":[0.0001137134,0.00005754357,0.0004597311,0.00001793639,0.00002840096,0.00004400798,0.00008988945,0.8798178,0.002618547,0.1155859,0.001154773,0.00001174757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4979468,0.002673427,0.3956769,0.01215462,0.0006865412,0.0002338812,0.0007164605,0.002809333,0.08710194],"genre_scores_gemma":[0.9176533,0.0003283731,0.07390328,0.0003802808,0.0001980354,0.0001382601,0.000339573,0.0004465823,0.00661242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01035696,"threshold_uncertainty_score":0.03464746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03319884652111329,"score_gpt":0.2789812256709334,"score_spread":0.2457823791498201,"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."}}