{"id":"W2946599934","doi":"10.1103/physreva.100.022341","title":"Simulating realistic non-Gaussian state preparation","year":2019,"lang":"en","type":"article","venue":"Physical review. A/Physical review, A","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Xanadu Quantum Technologies (Canada)","funders":"","keywords":"Gaussian; Fock space; Fock state; State (computer science); Statistical physics; Multi-mode optical fiber; Computation; Photon; Gaussian elimination; State space; Algorithm; Physics; Quantum mechanics; Computer science; Mathematics; Optics; Optical fiber; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005877422,0.0004476986,0.001182552,0.0000748757,0.0001326498,0.0001583099,0.001060277,0.00002986576,0.00004424182],"category_scores_gemma":[0.0003357708,0.0003446243,0.0007205062,0.001445131,0.00006700715,0.001327208,0.0002814432,0.0003916633,0.003497755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005910598,"about_ca_system_score_gemma":0.00009886093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001364279,"about_ca_topic_score_gemma":0.000001284416,"domain_scores_codex":[0.9966345,0.0002594265,0.0009080941,0.0006966662,0.000930844,0.0005705095],"domain_scores_gemma":[0.9970537,0.0003618679,0.0006031326,0.001420074,0.000232793,0.0003283882],"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":[0.00003615597,0.001540885,0.0005276502,0.03624187,0.0001921249,0.00001538624,0.001595392,0.0006625989,0.009818984,0.6504349,0.01767595,0.2812581],"study_design_scores_gemma":[0.0006839782,0.0006912645,0.001738805,0.01961806,0.0002242479,0.00001000463,0.000008071226,0.79594,0.001984098,0.0936582,0.08406875,0.00137451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.403317,0.04632081,0.4342028,0.0082617,0.001121412,0.01170631,0.00006363847,0.001513411,0.09349284],"genre_scores_gemma":[0.9688897,0.02279238,0.001111874,0.00667876,0.0001914288,0.0001799542,0.00004590063,0.00002927842,0.00008076622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7952774,"threshold_uncertainty_score":0.9999006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01217742924465273,"score_gpt":0.3593250339102694,"score_spread":0.3471476046656167,"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."}}