{"id":"W4409012448","doi":"10.1103/physrevresearch.7.013331","title":"Universal algorithm for transforming Hamiltonian eigenvalues","year":2025,"lang":"en","type":"article","venue":"Physical Review Research","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Perimeter Institute","funders":"Japan Society for the Promotion of Science; Ministry of Colleges and Universities; Ministry of Education, Culture, Sports, Science and Technology; International Business Machines Corporation","keywords":"Eigenvalues and eigenvectors; Algorithm; Hamiltonian (control theory); Mathematics; Computer science; Physics; Mathematical optimization; Quantum mechanics","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":[0.0005097825,0.0006412538,0.000475468,0.0004555417,0.0004804154,0.000638791,0.0008905584,0.0005091112,0.007819203],"category_scores_gemma":[0.002634675,0.0003088111,0.0005234026,0.0003464253,0.000671592,0.0008786873,0.001166889,0.0008291091,0.001771621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005973054,"about_ca_system_score_gemma":0.001202322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008163587,"about_ca_topic_score_gemma":0.001273425,"domain_scores_codex":[0.999517,0.00009571862,0.00003485315,0.0001461439,0.0001388686,0.00006740597],"domain_scores_gemma":[0.9990294,0.0004944305,0.00007176089,0.0002321227,0.0001450647,0.00002715838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003629227,0.0002816949,0.002876886,0.0003881669,0.0000839072,0.0002750443,0.0004910298,0.1212557,0.05624355,0.1245665,0.01256748,0.6806071],"study_design_scores_gemma":[0.0000990705,0.0001093088,0.0005346041,0.00003659091,0.00003276374,0.0002046951,0.00007480723,0.8469967,0.07502055,0.06002282,0.01681872,0.00004935128],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01478912,0.00003579345,0.9731285,0.00006689176,0.00002370351,0.00006267954,0.00007888513,0.009256439,0.002558062],"genre_scores_gemma":[0.2610836,0.00006179631,0.7326496,0.0001393636,0.00001937216,0.00033743,0.0003162796,0.001961411,0.003431256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007819203,"threshold_uncertainty_score":0.02615786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05588916434120532,"score_gpt":0.4608325819771099,"score_spread":0.4049434176359046,"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."}}