{"id":"W1973967102","doi":"10.1364/oe.18.013679","title":"Acceleration of FDTD mode solver by high-performance computing techniques","year":2010,"lang":"en","type":"article","venue":"Optics Express","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"McMaster University; Shandong University","keywords":"Finite-difference time-domain method; Solver; Computer science; Computational science; CUDA; Parallel computing; Graphics processing unit; Mode (computer interface); Finite difference method; Optics; Algorithm; Physics; Mathematics; Mathematical analysis","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":[0.0003581439,0.000515998,0.0004515245,0.0004294596,0.0003471857,0.0004861557,0.0007930158,0.0006082118,0.002932526],"category_scores_gemma":[0.001207755,0.0002704459,0.0003532368,0.0004481063,0.0002515444,0.0006322279,0.0004052567,0.000671161,0.0008522803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003423437,"about_ca_system_score_gemma":0.0009128359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001736677,"about_ca_topic_score_gemma":0.001603397,"domain_scores_codex":[0.9997554,0.00004111691,0.00001403436,0.00002667279,0.0001410306,0.000021684],"domain_scores_gemma":[0.9993955,0.0002859156,0.00003638987,0.00008263435,0.0001824891,0.0000171275],"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":[0.0001712088,0.0001360009,0.002257498,0.0004897026,0.00006248499,0.0006470751,0.0003974086,0.4148897,0.2414775,0.05133646,0.009861374,0.2782735],"study_design_scores_gemma":[0.00001592983,0.00001950431,0.0001612238,0.000006511095,0.000003976283,0.0001160143,0.000009642986,0.9745223,0.01854378,0.001255316,0.005336092,0.000009789303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01142589,0.00007224709,0.9840901,0.00005941802,0.00005045262,0.00003821771,0.00006373388,0.001175975,0.003023917],"genre_scores_gemma":[0.1080554,0.000149562,0.8889797,0.0000335155,0.00001951135,0.0001608511,0.0001647182,0.0001654422,0.002271294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002932526,"threshold_uncertainty_score":0.009810269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008788666041882073,"score_gpt":0.2628725508780276,"score_spread":0.2540838848361456,"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."}}