{"id":"W2306477081","doi":"10.1103/physrevlett.118.080501","title":"Quantum Machine Learning over Infinite Dimensions","year":2017,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Xanadu Quantum Technologies (Canada)","funders":"Croucher Foundation; U.S. Department of Energy","keywords":"Quantum machine learning; Computer science; Subroutine; Quantum computer; Quantum algorithm; Quantum; Speedup; Quantum information; Quantum sort; Blueprint; Theoretical computer science; Quantum Turing machine; Quantum simulator; Photonics; Field (mathematics); Algorithm; Quantum mechanics; Physics; Mathematics; Parallel computing; Programming language","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":[0.001501148,0.000395499,0.0006206707,0.0006045523,0.0008778119,0.0017994,0.0008465415,0.0009750424,0.003190594],"category_scores_gemma":[0.007360064,0.0003495509,0.000370355,0.0006161119,0.002795042,0.004705169,0.001666763,0.002565269,0.0004957885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001410086,"about_ca_system_score_gemma":0.001101133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001296469,"about_ca_topic_score_gemma":0.000974632,"domain_scores_codex":[0.9990766,0.0004098333,0.00004344281,0.0001145077,0.0002655326,0.00008992344],"domain_scores_gemma":[0.9969633,0.002172242,0.0001162752,0.0004245545,0.0002274016,0.00009632002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002219821,0.00001533947,0.0001323904,0.0000643915,0.000008043556,0.00003510256,0.00005650609,0.03048161,0.0007701229,0.9546155,0.001537221,0.01226171],"study_design_scores_gemma":[0.000009610856,0.00000860262,0.00006902133,0.00001888515,0.000002151631,0.00001641023,0.00001239317,0.2414351,0.0005168976,0.7554185,0.002483066,0.000009291942],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0822376,0.006460447,0.8486889,0.007177012,0.0005663089,0.00006916604,0.0002190212,0.0008329914,0.05374863],"genre_scores_gemma":[0.8525349,0.003287335,0.1357315,0.000581226,0.0004820647,0.0001562591,0.0001256852,0.0001394349,0.006961446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003190594,"threshold_uncertainty_score":0.01067364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176649778114673,"score_gpt":0.2967564698724735,"score_spread":0.2749899720913268,"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."}}