{"id":"W2981617422","doi":"10.1021/acs.jctc.9b01084","title":"Iterative Qubit Coupled Cluster Approach with Efficient Screening of Generators","year":2020,"lang":"en","type":"preprint","venue":"Journal of Chemical Theory and Computation","topic":"Advanced Thermodynamics and Statistical Mechanics","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto; OTI Lumionics (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Hamiltonian (control theory); Coupled cluster; Ansatz; Ground state; Qubit; Canonical transformation; Quantum; Cluster expansion; Quantum mechanics; Mathematics; Statistical physics; Physics; Applied mathematics; Molecule; Mathematical optimization","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":[0.0006124834,0.0004499796,0.0007532624,0.0005319346,0.0007796217,0.0006818423,0.001502505,0.0009149554,0.003918652],"category_scores_gemma":[0.001405525,0.0003163488,0.0005710198,0.0007245733,0.0008109562,0.0005775542,0.001069211,0.001110974,0.0006472268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001185764,"about_ca_system_score_gemma":0.001667625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006101511,"about_ca_topic_score_gemma":0.01073054,"domain_scores_codex":[0.9995925,0.0001647617,0.000009801625,0.00004163742,0.0001397748,0.00005160921],"domain_scores_gemma":[0.999377,0.0002753033,0.00003484857,0.0001416317,0.000125082,0.00004614195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001448925,0.0001419878,0.0006275858,0.0001026036,0.0001068841,0.0001739931,0.0001343291,0.7191223,0.006369113,0.250362,0.002796424,0.01991796],"study_design_scores_gemma":[0.00001456734,0.00001089881,0.00004292782,0.000001612566,0.000003703273,0.000006966587,0.000005549588,0.9878472,0.0005656972,0.01100915,0.0004861523,0.000005621831],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1436918,0.000307505,0.8206326,0.0007653926,0.0001894133,0.0003522309,0.0003840216,0.0008444883,0.03283252],"genre_scores_gemma":[0.7062454,0.0001107069,0.2822999,0.0001881206,0.00003801103,0.0005216097,0.0002208917,0.0002143113,0.01016116],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006101511,"threshold_uncertainty_score":0.01310921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01159284964020339,"score_gpt":0.2575650795285779,"score_spread":0.2459722298883745,"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."}}