{"id":"W4385958524","doi":"10.48550/arxiv.2308.01068","title":"Neural network encoded variational quantum algorithms","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Parameterized complexity; Artificial neural network; Hamiltonian (control theory); Computer science; Quantum computer; Quantum; Quantum circuit; Ansatz; Ground state; Quantum machine learning; Algorithm; Quantum algorithm; Bethe ansatz; Artificial intelligence; Mathematical optimization; Quantum network; Mathematics; Quantum mechanics; Physics","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":[0.001023093,0.000574497,0.0008354863,0.0004100151,0.0004661861,0.0008842562,0.001999562,0.001347145,0.003083705],"category_scores_gemma":[0.003719563,0.0004157737,0.000526449,0.0005258582,0.001301326,0.001364468,0.001574679,0.001644048,0.0004134452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001111982,"about_ca_system_score_gemma":0.001244559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003147915,"about_ca_topic_score_gemma":0.004094095,"domain_scores_codex":[0.9995467,0.0001936101,0.00001948636,0.00006613546,0.0001221592,0.00005183344],"domain_scores_gemma":[0.9991789,0.0004666076,0.00004990825,0.0001471238,0.0001167656,0.00004067977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002840839,0.00002382045,0.0003077201,0.00005189287,0.00002683196,0.00002869932,0.00004141271,0.7997232,0.001088982,0.1787024,0.001044246,0.01893247],"study_design_scores_gemma":[0.000003297469,0.000003689242,0.00001396545,0.00000239901,8.882351e-7,0.000002810173,0.00000214389,0.9720142,0.000124736,0.02749173,0.0003381782,0.00000205253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01008822,0.0001691732,0.9845268,0.0002780665,0.0000461046,0.00004050126,0.00007955242,0.0002362297,0.00453531],"genre_scores_gemma":[0.5133835,0.0003169623,0.4777649,0.0004171082,0.00008925678,0.0003669029,0.0003421409,0.0002937359,0.007025663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003147915,"threshold_uncertainty_score":0.01031601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06197315344912986,"score_gpt":0.1979388471108701,"score_spread":0.1359656936617403,"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."}}