{"id":"W3179964333","doi":"10.21468/scipostphyscore.7.2.016","title":"Stochastic series expansion quantum Monte Carlo for Rydberg arrays","year":2024,"lang":"en","type":"article","venue":"SciPost Physics Core","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Shared Hierarchical Academic Research Computing Network; Ministry of Colleges and Universities; Canada Research Chairs; Institut Périmètre de physique théorique; Compute Canada","keywords":"Series (stratigraphy); Rydberg formula; Monte Carlo method; Statistical physics; Quantum Monte Carlo; Quantum; Quantum defect; Physics; Mathematics; Quantum mechanics; Statistics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001278793,0.000335476,0.0006286564,0.0004436494,0.0005859799,0.00049771,0.001157594,0.0006206962,0.001485161],"category_scores_gemma":[0.003215521,0.0003175018,0.0003748021,0.0004855576,0.001281297,0.0008322369,0.0007427449,0.0009278791,0.0002413782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001299369,"about_ca_system_score_gemma":0.001215237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004465793,"about_ca_topic_score_gemma":0.00565887,"domain_scores_codex":[0.9995199,0.0002048106,0.00001473866,0.00004331969,0.0001708217,0.00004629441],"domain_scores_gemma":[0.9987347,0.0007789774,0.0000857186,0.0001575083,0.0001696505,0.00007350959],"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":[0.00005573477,0.00004401052,0.0004617291,0.00002809003,0.00002064009,0.00005148173,0.00004569087,0.8112326,0.003105578,0.1768127,0.000633161,0.007508615],"study_design_scores_gemma":[0.000003690842,0.00000272653,0.00001841199,7.613949e-7,7.889569e-7,0.000001670115,0.000001151743,0.9929697,0.000243843,0.006632302,0.0001232296,0.000001674086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08695398,0.0001925634,0.9066208,0.0003128359,0.0000467664,0.00006776224,0.00009237688,0.0005290473,0.005183878],"genre_scores_gemma":[0.7360929,0.0001848027,0.2587258,0.0001779352,0.00006436285,0.0002712107,0.0002068254,0.0002907304,0.003985411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004465793,"threshold_uncertainty_score":0.009427607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02752362495310944,"score_gpt":0.2853337605458706,"score_spread":0.2578101355927612,"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."}}