{"id":"W2046440776","doi":"10.1103/physrevlett.88.207902","title":"Creating Decoherence-Free Subspaces Using Strong and Fast Pulses","year":2002,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Quantum decoherence; Decoherence-free subspaces; Quantum computer; Computation; Physics; Linear subspace; Scalability; Quantum; Quantum mechanics; Computer science; Quantum error correction; Statistical physics; Algorithm; Mathematics; Pure mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001131839,0.0001795358,0.0003012674,0.00003205798,0.0001810673,0.0001510693,0.0005899027,0.0000074132,0.000008786398],"category_scores_gemma":[0.00007223254,0.0001413799,0.00008987716,0.0002739064,0.00007058035,0.0002280066,0.0003344669,0.0001848809,0.00001197601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001544756,"about_ca_system_score_gemma":0.000005512083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002238759,"about_ca_topic_score_gemma":0.000001175709,"domain_scores_codex":[0.9988109,0.00008681507,0.0001698476,0.0003845524,0.0002365581,0.0003113555],"domain_scores_gemma":[0.9991473,0.000173573,0.0001020359,0.0004537935,0.00001972355,0.0001035677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001655295,0.0002345662,0.001672419,0.001742741,0.00009375942,0.00008938418,0.002636736,0.007798052,0.0117632,0.006433056,0.004846493,0.962688],"study_design_scores_gemma":[0.0001158279,0.00003266596,0.0004914067,0.001154315,0.00002048336,0.00002819817,0.000004769844,0.9967315,0.0000919117,0.0003431879,0.0007611651,0.0002245235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8742662,0.01747154,0.0959747,0.01132825,0.0001344065,0.0002680936,0.000002720376,0.000177301,0.0003767749],"genre_scores_gemma":[0.9407426,0.001289856,0.05124701,0.006289384,0.0003921983,0.000009268642,6.852368e-7,0.00001798045,0.00001104071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9889335,"threshold_uncertainty_score":0.5765304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0266396085938247,"score_gpt":0.2758922985308619,"score_spread":0.2492526899370373,"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."}}