Pseudo-Bayesian quantum tomography with rank-adaptation

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• 作者：The Tien Mai ; ^{thetien.mai@ensae.fr} ; Pierre Alquier ^{pierre.alquier@ensae.fr}
• 关键词：Quantum statistics ; Bayesian statistics ; PAC-Bayesian bounds ; Oracle inequalities ; MCMC
• 刊名：Journal of Statistical Planning and Inference
• 出版年：2017
• 出版时间：May 2017
• 年：2017
• 卷：184
• 期：Complete
• 页码：62-76
• 全文大小：709 K
• 卷排序：184

文摘

Definition of a prior for Bayesian quantum tomography. This prior can be easily extended to any dimension. Best up-to-date estimation rates in the case of a low-rank density matrix. Good experimental results; clear improvement over the direct inversion method.