{"id":"W2775563604","doi":"10.1103/physrevlett.121.010501","title":"Quantum Algorithm for Spectral Measurement with a Lower Gate Count","year":2018,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Canadian Institute for Advanced Research","funders":"National Center of Competence in Research Affective Sciences - Emotions in Individual Behaviour and Social Processes; Natural Sciences and Engineering Research Council of Canada; Institute for Quantum Information and Matter, California Institute of Technology; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Simons Foundation","keywords":"Hamiltonian (control theory); Unitary state; Qubit; Algorithm; Computer science; Gate count; Lattice (music); Operator (biology); Quantum computer; Unitary operator; Ground state; Quantum algorithm; Quantum; Quantum mechanics; Topology (electrical circuits); Physics; Mathematics; 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":[0.0006637514,0.0005924405,0.0007117501,0.0008295773,0.0008395555,0.001663688,0.001671812,0.001273944,0.01484145],"category_scores_gemma":[0.003534118,0.0003044028,0.0006705003,0.0008111479,0.001077855,0.002577506,0.002226386,0.002022053,0.00374761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009781134,"about_ca_system_score_gemma":0.001847743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001116905,"about_ca_topic_score_gemma":0.002204925,"domain_scores_codex":[0.9988004,0.0002815479,0.00008197451,0.0001992227,0.0004975264,0.000139341],"domain_scores_gemma":[0.9983719,0.0006047596,0.00007605271,0.0006715141,0.0002084235,0.00006741175],"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":[0.0003549041,0.0002815813,0.0004650574,0.0002070992,0.00005804295,0.0001228182,0.0001632142,0.05681403,0.02581727,0.5871797,0.01121885,0.3173174],"study_design_scores_gemma":[0.0001380647,0.00009292345,0.0001486285,0.00003286607,0.00002187347,0.0001118396,0.00003571582,0.7297112,0.01213344,0.2430838,0.01445497,0.00003462551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007036299,0.0001086419,0.9825733,0.000511638,0.0001283973,0.0001226212,0.00009373445,0.00142809,0.007997239],"genre_scores_gemma":[0.1527446,0.0001061996,0.8394742,0.0003556038,0.00009842246,0.000419792,0.0002550101,0.0002464398,0.006299795],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01484145,"threshold_uncertainty_score":0.04964954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917141360005648,"score_gpt":0.2653781742452574,"score_spread":0.2462067606452009,"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."}}