{"id":"W3139445264","doi":"10.1103/prxquantum.3.020323","title":"Real-Time Evolution for Ultracompact Hamiltonian Eigenstates on Quantum Hardware","year":2022,"lang":"en","type":"article","venue":"PRX Quantum","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Air Force Research Laboratory; Chemical Sciences, Geosciences, and Biosciences Division; Advanced Scientific Computing Research; Basic Energy Sciences; National Aeronautics and Space Administration; Office of Science; Ames Research Center; U.S. Department of Energy","keywords":"Hamiltonian (control theory); Unitary transformation; Eigenvalues and eigenvectors; Ising model; Excited state; Quantum; Quantum phase estimation algorithm; Statistical physics; Physics; Algorithm; Computer science; Applied mathematics; Quantum mechanics; Quantum computer; Mathematics; Mathematical optimization; Quantum simulator","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007882672,0.0003634144,0.0003884735,0.000299314,0.001337792,0.0002037254,0.001385535,0.0000630751,0.00005843977],"category_scores_gemma":[0.00009676114,0.0003444272,0.0002722469,0.0006296784,0.0000613901,0.0002051303,0.0003898638,0.0004516963,0.0001052045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002586088,"about_ca_system_score_gemma":0.0002062486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001383468,"about_ca_topic_score_gemma":0.000003723176,"domain_scores_codex":[0.9969162,0.0002626558,0.0004381285,0.0008997354,0.0006513573,0.000831904],"domain_scores_gemma":[0.9980605,0.0004953779,0.000248297,0.0008882373,0.0001068831,0.0002007678],"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":[0.0004110181,0.001439087,0.0007843314,0.0001893283,0.000235537,0.0002143799,0.00595119,0.2191977,0.03087161,0.6526837,0.05117512,0.03684701],"study_design_scores_gemma":[0.0005802045,0.001177877,0.003724043,0.00003318126,0.00001203484,0.00008025273,0.0000803826,0.9468244,0.0005198293,0.03408841,0.01239307,0.0004863186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7366188,0.0002978717,0.2506196,0.004921752,0.002989317,0.001370724,0.0003261163,0.001801256,0.001054491],"genre_scores_gemma":[0.983791,0.00001251357,0.01483807,0.0003325549,0.0002833974,0.000139623,0.00006660551,0.00005837121,0.0004778626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7276267,"threshold_uncertainty_score":0.9999623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01188107317108784,"score_gpt":0.2446101803161353,"score_spread":0.2327291071450475,"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."}}