{"id":"W3142599207","doi":"10.1038/s41534-021-00396-0","title":"Reprogrammable and high-precision holographic optical addressing of trapped ions for scalable quantum control","year":2021,"lang":"en","type":"article","venue":"npj Quantum Information","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Army Research Laboratory; Army Research Office; Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Canada First Research Excellence Fund; Innovation, Science and Economic Development Canada","keywords":"Qubit; Ion; Holography; Quantum computer; Quantum; Scaling; Fourier transform; Trapped ion quantum computer; Crosstalk; Quantum information; Scalability; Optics; Materials science; Physics; Computer science; Optoelectronics; Quantum error correction; Quantum mechanics; Mathematics","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":[0.0001640654,0.0001840571,0.0001459218,0.0001728406,0.000183878,0.0003659277,0.0004444691,0.0002262678,0.001289909],"category_scores_gemma":[0.0003222749,0.0001214464,0.00008585996,0.0001738361,0.0004485596,0.0004484032,0.0005487807,0.0003480125,0.0002819314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002745256,"about_ca_system_score_gemma":0.0002703734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003258444,"about_ca_topic_score_gemma":0.000697428,"domain_scores_codex":[0.9999198,0.000009182636,0.000005323409,0.00001291159,0.0000414037,0.00001143902],"domain_scores_gemma":[0.9997618,0.00005387541,0.00006414511,0.00007545841,0.00002855329,0.0000161508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005509386,0.0000418963,0.0002870983,0.00003194386,0.000004686472,0.00008824804,0.0001122986,0.002936955,0.9700855,0.006119007,0.0003841433,0.01985317],"study_design_scores_gemma":[0.00001482662,0.0001042235,0.0004170385,0.000005732035,0.000003459041,0.0001241695,0.00004188233,0.03536843,0.9600586,0.0007368559,0.003112589,0.00001220842],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8566285,0.0003140894,0.1332091,0.0002722827,0.00008086406,0.00005763073,0.0001029407,0.0009350764,0.00839948],"genre_scores_gemma":[0.9028314,0.0001052729,0.09423254,0.0000511386,0.00001164401,0.00003171237,0.00004317363,0.00004910818,0.002644059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001289909,"threshold_uncertainty_score":0.004315138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01944382149630659,"score_gpt":0.2583641631890106,"score_spread":0.238920341692704,"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."}}