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[1]韦 仙.基于矩阵填充技术重构低秩密度矩阵[J].武汉工程大学学报,2015,37(02):72-76.[doi:10. 3969/j. issn. 1674-2869. 2015. 02. 016]
 Reconstructing low-rank density matrix via matrix completion[J].Journal of Wuhan Institute of Technology,2015,37(02):72-76.[doi:10. 3969/j. issn. 1674-2869. 2015. 02. 016]
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基于矩阵填充技术重构低秩密度矩阵(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
37
期数:
2015年02期
页码:
72-76
栏目:
机电与信息工程
出版日期:
2015-02-28

文章信息/Info

Title:
Reconstructing low-rank density matrix via matrix completion
文章编号:
1674 - 2869(2015)02 - 0072 - 05
作者:
韦 仙
太原工业学院理学系,山西 太原 030008
Author(s):
WEI Xian
Faculty of Science, Taiyuan Institute of Technology, Shanxi 030008, China
关键词:
矩阵填充密度矩阵低秩量子态层析
Keywords:
matrix completion density matrix low-rank quantum state tomography
分类号:
O413.1
DOI:
10. 3969/j. issn. 1674-2869. 2015. 02. 016
文献标志码:
A
摘要:
从有限的信息中重构低秩或者近似低秩矩阵的问题日益受到人们的关注,解决这个问题的技术称为矩阵填充. 对于一个希尔伯特空间下纯态或者近似纯态的量子体系(也就是低熵状态),其密度矩阵是低秩的,且迹为1. 将矩阵填充理论应用于重构泡利测量下未知密度矩阵中,用Matlab软件程序进行数值模拟,采用奇异值阈值算法,将软阈值法则用在未知态密度矩阵的奇异值上,通过计算机编程,进行阈值迭代,直至达到截止标准,能够大大提高运行速率. 由于以泡利矩阵为基的张量积结构便于在实验中获得,以重构泡利测量下的未知密度矩阵为例,采集了部分数据,分析了矩阵的重构结果. 通过对重构误差、运行时间、采样率方面的研究,得出密度矩阵能够通过矩阵填充技术完整重构的结论.
Abstract:
The problem of reconstructing low-rank or approximately low-rank matrix from the limited information is getting people's attention and solving this problem is well known as matrix completion. For the pure or nearly pure quantum state (ie. low entropy state) in a Hilbert space, the density matrix is low-rank and has trace 1. This paper is concerned with applying matrix completion theory to the unknown density matrix recovery which is from Pauli measurements. The singular value thresholding (SVT) algorithm was utilized to numerical simulation by Matlab software programs. And its soft-thresholding rule was used to singular values of the unknown state density matrix. The threshold iteration was conducted by SVT algorithm through computer programming until a stopping criteria was reached, which could greatly improve the run rate. We took the density matrix from Pauli measurements for example because of the convenience on getting the tensor product structure based on Pauli matrices in experiment. The effect of matrix reconstruction was studied in the case of sampling a small number of entries from the matrix. We conclude that the density matrix can be reconstructed successfully by studying the aspects of reconstruction error, run-time and sampling rate.

参考文献/References:

[1] MATTEO Paris, JAROSLAV Rehacek. Quantum state estimation[M]. Berlin: Springer Science & Business Media, 2004:1-8.[2] 戴宏毅.约化密度矩阵及其在量子信息处理中的应用[J].大学物理, 2010,29(2):31-33.DAI Hong-yi. Reduced density matrix and its application in quantum information processing[J]. College Physics, 2010,29(2):31-33.(in Chinese)[3] DONOHO D L. Compressed sensing [J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.[4] 胡端平,唐超.一致矩阵的特征性质[J].武汉工程大学学报,2009,31(5):93-94.HU Duan-ping, TANG Chao. The character of consistent matrix[J]. Journal of Wuhan Institute of Technology, 2009,31(5):93-94.(in Chinese)[5] 杨建华,孙霞林.协方差矩阵在非负二次型估计中的可容许性[J].武汉工程大学学报,2007,29(1):75-77.YANG Jian-hua, SUN Xia-lin. Compatibility of non-negative quadractic estimation[J]. Journal of Wuhan Institute of Technology, 2007,29(1):75-77.(in Chinese)[6] EMMANUEL J Candès, TERENCE Tao. The power of convex relaxation: Near-optimal matrix completion[J]. IEEE Transactions on Information Theory, 2010,56(5):2053-2080.[7] CAI Jian-feng, EMMANUEL J Candes, SHEN Zuowei. A sngular value thresholding algorithm for matrix completion[J]. Siam Journal of Optimization, 2010, 20(4):1956-1982.[8] DAVE Gross. Recovering low-rank matrices from few coefficients in any basis[J]. IEEE Transactions on Information Theory, 2011, 57(3):1548-1566.

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备注/Memo

备注/Memo:
收稿日期:2014-11-24基金项目:太原工业学院院级青年科学基金(2014LQ05)作者简介:韦 仙(1988-),女,山西晋城人,助理实验师,硕士. 研究方向:理论物理.
更新日期/Last Update: 2015-03-21