{"id":"W4385802095","doi":"10.1145/3588983.3596680","title":"Efficient QAOA Optimization using Directed Restarts and Graph Lookup","year":2023,"lang":"en","type":"article","venue":"","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Research Council Canada; Pacific Northwest National Laboratory; Office of Science; Battelle; U.S. Department of Energy","keywords":"Computer science; Scalability; Parameterized complexity; Random graph; Theoretical computer science; Algorithm; Graph; Enhanced Data Rates for GSM Evolution; Mathematical optimization; Mathematics; Artificial intelligence; Database","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":[0.0006158439,0.0007702319,0.001076482,0.0006829454,0.0007141696,0.001208372,0.001477336,0.0009700559,0.005891409],"category_scores_gemma":[0.003335965,0.000471047,0.0007045714,0.0007321576,0.0009630105,0.001196998,0.001208784,0.001032987,0.001209395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008772709,"about_ca_system_score_gemma":0.001447202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004720074,"about_ca_topic_score_gemma":0.009139809,"domain_scores_codex":[0.9995427,0.0001448051,0.00002306135,0.00009172151,0.0001234343,0.00007417563],"domain_scores_gemma":[0.9988574,0.0006578182,0.00006640745,0.000231226,0.0001330359,0.00005411233],"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":[0.0002187479,0.00008920235,0.0006007614,0.0001401586,0.00006751583,0.0001556481,0.00009606692,0.8525333,0.005205753,0.05270421,0.005915826,0.08227279],"study_design_scores_gemma":[0.00001606205,0.00002033366,0.00005263432,0.000005190374,0.000005709167,0.00001509383,0.00001611771,0.9838406,0.001065352,0.01403818,0.0009176364,0.000007005538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03667888,0.0004555438,0.9453146,0.0003527057,0.0001134672,0.0001038496,0.0001705815,0.003409381,0.01340087],"genre_scores_gemma":[0.6287615,0.0001704399,0.3648327,0.0003123277,0.00003224708,0.0002594463,0.0003483383,0.0007364862,0.004546582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005891409,"threshold_uncertainty_score":0.01970875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350811794924672,"score_gpt":0.2350153909846498,"score_spread":0.2215072730354031,"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."}}