{"id":"W3098074752","doi":"10.1137/1.9781611973105.106","title":"Nested Quantum Walks with Quantum Data Structures","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Quantum walk; Quantum; Theoretical computer science; Computer science; Graph; Upper and lower bounds; Logarithm; Simple (philosophy); Quantum algorithm; Random walk; Mathematics; Discrete mathematics; Physics; Quantum mechanics","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":[0.001570165,0.0005901856,0.001010467,0.001435228,0.002104063,0.002782391,0.002660432,0.001856579,0.008382435],"category_scores_gemma":[0.008381697,0.0008021543,0.001300097,0.001634491,0.003622494,0.009088116,0.004209549,0.003562066,0.00134348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709695,"about_ca_system_score_gemma":0.001553169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001882087,"about_ca_topic_score_gemma":0.002829847,"domain_scores_codex":[0.9982371,0.0005049289,0.00009373956,0.000366163,0.0005380447,0.0002600368],"domain_scores_gemma":[0.9945017,0.002498269,0.0003247401,0.001885288,0.0004564755,0.0003335278],"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":[0.00001799269,0.0000274356,0.0001173392,0.00002419325,0.000005522741,0.00003298551,0.00007232856,0.009944931,0.0009485298,0.9813485,0.0005709545,0.006889263],"study_design_scores_gemma":[0.00001274029,0.00002039692,0.00004087296,0.0000104804,0.00000527424,0.00003478878,0.00002279296,0.1350253,0.001056918,0.8604176,0.00333786,0.00001500176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02271101,0.0001652133,0.9653301,0.000688419,0.00008814124,0.00007698953,0.0001215439,0.000384857,0.01043377],"genre_scores_gemma":[0.4264925,0.000333594,0.5624941,0.000537314,0.0001577964,0.0003529795,0.0002382648,0.0003264586,0.009067053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008382435,"threshold_uncertainty_score":0.02804208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03116897440204137,"score_gpt":0.2632554257835967,"score_spread":0.2320864513815554,"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."}}