{"id":"W4413298911","doi":"10.1038/s41534-025-01084-z","title":"Further improving quantum algorithms for nonlinear differential equations via higher-order methods and rescaling","year":2025,"lang":"en","type":"article","venue":"npj Quantum Information","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"Centre of Excellence for Quantum Computation and Communication Technology, Australian Research Council; Advanced Research Projects Agency","keywords":"Nonlinear system; Algorithm; Quantum; Order (exchange); Quantum computer; Computer science; Quantum algorithm; Differential equation; Mathematics; Physics; Quantum mechanics; Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001609715,0.0005603848,0.0007845392,0.0004752231,0.0004885994,0.001020477,0.001248997,0.001083681,0.00455214],"category_scores_gemma":[0.007297532,0.0003051915,0.0006814305,0.0005471462,0.00158466,0.002378066,0.001729932,0.002784105,0.0009784969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102686,"about_ca_system_score_gemma":0.001013626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001935642,"about_ca_topic_score_gemma":0.002433475,"domain_scores_codex":[0.9993526,0.0002271332,0.00004290757,0.00007608635,0.00025992,0.0000413161],"domain_scores_gemma":[0.99695,0.001842259,0.0001992794,0.0006836375,0.0002522532,0.00007255316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008500083,0.0001225321,0.0006330998,0.0002634581,0.00004525741,0.00008989383,0.0003929143,0.3768636,0.0273758,0.5008669,0.001898685,0.09136272],"study_design_scores_gemma":[0.00001314273,0.00001549696,0.00004459452,0.00001060515,0.000002910444,0.00001203996,0.000009942604,0.9546445,0.003113916,0.03963113,0.002492494,0.00000918649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01025783,0.0001995054,0.9848685,0.0003068495,0.00008393808,0.00003317697,0.00001828779,0.0004030208,0.003828843],"genre_scores_gemma":[0.205942,0.0003801259,0.7882063,0.0002198404,0.00008347201,0.0001409241,0.00006303166,0.0004884735,0.004475799],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00455214,"threshold_uncertainty_score":0.01522839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522481597582772,"score_gpt":0.3062110477606575,"score_spread":0.2909862317848298,"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."}}