N-qudit SLOCC equivalent W states are determined by their bipartite reduced density matrices with tree form
N-qudit SLOCC equivalent W states are determined by their bipartite reduced density matrices with tree form
复制标题
N-qudit SLOCC 等效 W 状态由树形二分约化密度矩阵确定
DOI:
10.1007/s11128-020-02918-9
复制
发表时间:
2020-11
期刊:
影响因子:
--
通讯作者:
Fei Gao
中科院分区:
文献类型:
--
作者:
Xia Wu;Hengyue Jia;D;an Li;Fei Gao
It has been proved that N-qudit (i.e., d-level subsystems) generalized W states are determined by their bipartite reduced density matrices. In this paper, we prove that only (N-1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(N-1)$$\end{document} of the bipartite reduced density matrices are sufficient. Furthermore, we find that N-qudit W states preserve their determinability under stochastic local operation and classical communication (SLOCC). That is, all multipartite pure states that are SLOCC equivalent to N-qudit W states can be uniquely determined (among pure, mixed states) by their (N-1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(N-1)$$\end{document} of the bipartite reduced density matrices, if the (N-1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(N-1)$$\end{document} pairs of qudits constitute a tree graph on N vertices, where each pair of qudits represents an edge.
登录
查看更多内容
影响因子:
2.9
作者:
P. Parashar;S. Rana
通讯作者:
P. Parashar;S. Rana
影响因子:
2.9
作者:
H. S. Tonchev;N. Vitanov
通讯作者:
H. S. Tonchev;N. Vitanov
影响因子:
2.9
作者:
Wang, Yu-kun;Wen, Qiao-yan;Qin, Su-juan;Gao, Fei
通讯作者:
Gao, Fei
影响因子:
8.6
作者:
Xin, Tao;Lu, Dawei;Laflamme, Raymond
通讯作者:
Laflamme, Raymond
影响因子:
16.6
作者:
Cramer, Marcus;Plenio, Martin B.;Liu, Yi-Kai
通讯作者:
Liu, Yi-Kai