{"id":"W4377121328","doi":"10.48550/arxiv.2305.10310","title":"QRAM: A Survey and Critique","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Clarendon Fund; University of Oxford","keywords":"Scalability; Computer science; Qubit; Argument (complex analysis); Quantum; Quantum computer; Random access; State (computer science); Theoretical computer science; Algorithm; Physics; Quantum mechanics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005309017,0.0002768002,0.0002982417,0.0002343689,0.0001752647,0.0002167981,0.00136627,0.0002352272,0.000003304247],"category_scores_gemma":[0.0001127622,0.0003077308,0.0001069131,0.0005509722,0.0001015521,0.0001164111,0.003543945,0.0007038891,0.00004820788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004303362,"about_ca_system_score_gemma":0.0001364022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00082434,"about_ca_topic_score_gemma":0.0002104398,"domain_scores_codex":[0.9979862,0.0002763064,0.0001463251,0.001164175,0.00007549729,0.0003514796],"domain_scores_gemma":[0.9982017,0.0004712282,0.0001144909,0.0009241759,0.0001137212,0.0001747168],"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":[0.00003505901,0.0001589354,0.04702445,0.0003707252,0.0002563563,0.002685032,0.001179925,0.7833358,0.00001367448,0.1526728,0.004776272,0.007490931],"study_design_scores_gemma":[0.0001680807,0.00003413517,0.04389343,0.00007559475,0.000009265586,0.000007459217,0.00001014445,0.8994136,0.00000767343,0.05581253,0.0002167745,0.0003512774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4510313,0.00005653434,0.5470724,0.0003164987,0.0006425941,0.0001396967,0.00002799113,0.0005442172,0.0001687295],"genre_scores_gemma":[0.9956625,0.0001373267,0.002795954,0.000148374,0.00006684191,4.306494e-7,0.00001609704,0.00002234481,0.00115011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5446312,"threshold_uncertainty_score":0.9999375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08066532993175275,"score_gpt":0.2106777055279482,"score_spread":0.1300123755961955,"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."}}