{"id":"W4312108358","doi":"10.48550/arxiv.2212.11144","title":"QuOCS: The Quantum Optimal Control Suite","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Diamond and Carbon-based Materials Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Center for Integrated Quantum Science and Technology; QuantERA; Women's College Research Institute; Deutsche Forschungsgemeinschaft; European Commission; Bundesministerium für Bildung und Forschung; Baden-Württemberg Stiftung","keywords":"Toolbox; Computer science; Suite; Qubit; Software; Quantum; Quantum computer; Optimal control; Computational science; Quantum technology; Focus (optics); License; Theoretical computer science; Computer engineering; Mathematical optimization; Open quantum system; Physics; Mathematics; Programming language; Operating system; Quantum mechanics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00128381,0.0003629679,0.0004578237,0.0001609831,0.000497974,0.0003261519,0.002125366,0.0002043715,0.004968998],"category_scores_gemma":[0.00009080174,0.000310156,0.0002821478,0.0002963215,0.0003763654,0.0001548706,0.001980952,0.000705755,0.0004532168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002608784,"about_ca_system_score_gemma":0.0004628317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008651572,"about_ca_topic_score_gemma":0.00003589834,"domain_scores_codex":[0.9969764,0.0007413934,0.0002687094,0.001030305,0.0002893702,0.0006938024],"domain_scores_gemma":[0.9978437,0.0003289705,0.0002464051,0.001250549,0.0001342122,0.0001961832],"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":[0.001464483,0.0004705691,0.002220933,0.0003985009,0.0002235243,0.001698068,0.0004731197,0.7654756,0.1050734,0.115192,0.007176997,0.0001327925],"study_design_scores_gemma":[0.01412917,0.001908749,0.007243162,0.0005506393,0.001961122,0.00006250445,0.007630861,0.7231513,0.06701205,0.07528047,0.09335183,0.007718106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905552,0.0001620722,0.002849217,0.0002429108,0.001649911,0.00063347,0.0004697421,0.0002826636,0.003154798],"genre_scores_gemma":[0.9970194,0.0001294051,0.00002566811,0.0002218197,0.0002212455,0.0000146124,0.00004757076,0.00004336463,0.002276974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08617483,"threshold_uncertainty_score":0.999935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05834906737163335,"score_gpt":0.2055553498766376,"score_spread":0.1472062825050043,"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."}}