{"id":"W2963307420","doi":"10.1103/physreve.101.023316","title":"Computational hardness of spin-glass problems with tile-planted solutions","year":2020,"lang":"en","type":"article","venue":"Physical review. E","topic":"Theoretical and Computational Physics","field":"Physics and Astronomy","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"D-Wave Systems (Canada)","funders":"Intelligence Advanced Research Projects Activity; European Commission; Office of the Director of National Intelligence; University of Texas at Austin; Texas A and M University","keywords":"Quantum annealing; Simulated annealing; Ground state; Annealing (glass); Spin glass; Population; A priori and a posteriori; Materials science; Statistical physics; Monte Carlo method; Computer science; Condensed matter physics; Mathematics; Physics; Algorithm; Quantum; Quantum computer; Quantum mechanics; Composite material; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003959657,0.0001455031,0.0003459055,0.000008755491,0.00005984124,0.00001214094,0.000151701,0.000008183405,0.0001190512],"category_scores_gemma":[0.00000770007,0.0001083066,0.000138343,0.0002759595,0.0001361448,0.00008055077,0.00005493641,0.0001340601,0.0001311202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005821642,"about_ca_system_score_gemma":0.00006453581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006786913,"about_ca_topic_score_gemma":7.928116e-8,"domain_scores_codex":[0.9990821,0.00004371428,0.0002213013,0.0002111355,0.0002691451,0.0001725875],"domain_scores_gemma":[0.9994,0.00009624879,0.0001231519,0.00009837442,0.0001559655,0.0001262811],"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":[0.00001910349,0.0003360011,0.000363345,0.0003816671,0.00008629107,4.849788e-7,0.0001123805,0.007372866,0.0003404306,0.9842921,0.00110237,0.005592959],"study_design_scores_gemma":[0.001046719,0.0004092407,0.002135275,0.001443269,0.0002761283,0.000001451983,0.00005230427,0.1410115,0.000988152,0.8461442,0.005950633,0.0005411503],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2547843,0.001283194,0.701994,0.01188211,0.0001399238,0.001760565,0.0007394496,0.0001899428,0.02722649],"genre_scores_gemma":[0.9985399,0.000009240757,0.0005077882,0.0004371666,0.0002669061,0.00003450629,0.0001778595,0.00001364984,0.00001298326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7437556,"threshold_uncertainty_score":0.4416614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01967273993409568,"score_gpt":0.2827723773357624,"score_spread":0.2630996374016667,"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."}}