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We reconsider density matrices of graphs as defined in [quant-ph/0406165]. The density matrix of a graph is the combinatorial laplacian of the graph normalized to have unit trace. We describe a simple combinatorial condition (the "degree…

Recently normalized Laplacian matrices of graphs are studied as density matrices in quantum mechanics. Separability and entanglement of density matrices are important properties as they determine the nonclassical behavior in quantum…

Quantum Physics · Physics 2017-02-28 Chai Wah Wu

Density matrices of graphs are combinatorial laplacians normalized to have trace one (Braunstein \emph{et al.} \emph{Phys. Rev. A,} \textbf{73}:1, 012320 (2006)). If the vertices of a graph are arranged as an array, then its density matrix…

Computational Complexity · Computer Science 2008-07-03 Roland Hildebrand , Stefano Mancini , Simone Severini

Recently, Braunstein et al. [1] introduced normalized Laplacian matrices of graphs as density matrices in quantum mechanics and studied the relationships between quantum physical properties and graph theoretical properties of the underlying…

Quantum Physics · Physics 2011-11-15 Chai Wah Wu

Normalized Laplacian matrices of graphs have recently been studied in the context of quantum mechanics as density matrices of quantum systems. Of particular interest is the relationship between quantum physical properties of the density…

Mathematical Physics · Physics 2011-11-15 Chai Wah Wu

The Peres-Horodecki criterion of positivity under partial transpose is studied in the context of separability of bipartite continuous variable states. The partial transpose operation admits, in the continuous case, a geometric…

Quantum Physics · Physics 2009-10-31 R. Simon

The density matrix of a graph is the combinatorial laplacian matrix of a graph normalized to have unit trace. In this paper we generalize the entanglement properties of mixed density matrices from combinatorial laplacian matrices of graphs…

Quantum Physics · Physics 2011-04-20 Zhen Wang , Zhixi Wang

A new layers method is presented for multipartite separability of density matrices from simple graphs. Full separability of tripartite states is studied for graphs on degree symmetric premise. The models are generalized to multipartite…

Quantum Physics · Physics 2018-09-18 Hui Zhao , Jing Yun Zhao , Naihuan Jing

In light of recent interest in Hadamard diagonalisable graphs (graphs whose Laplacian matrix is diagonalisable by a Hadamard matrix), we generalise this notion from real to complex Hadamard matrices. We give some basic properties and…

Combinatorics · Mathematics 2020-07-21 Ada Chan , Shaun Fallat , Steve Kirkland , Jephian C. -H. Lin , Shahla Nasserasr , Sarah Plosker

We study entanglement properties of mixed density matrices obtained from combinatorial Laplacians. This is done by introducing the notion of the density matrix of a graph. We characterize the graphs with pure density matrices and show that…

Quantum Physics · Physics 2007-05-23 Samuel L. Braunstein , Sibasish Ghosh , Simone Severini

In this article we consider resistance matrix of a connected graph. For unweighted graph we study some necessary and sufficient conditions for resistance regular graphs. Also we find some relationship between Laplacian matrix and resistance…

Combinatorics · Mathematics 2018-03-28 Deepak Sarma

We give necessary and sufficient conditions under which a density matrix acting on a two-fold tensor product space is separable. Our conditions are given in terms of quantum conditional information transmission.

Quantum Physics · Physics 2016-09-08 Robert R. Tucci

In this paper we give a method to associate a graph with an arbitrary density matrix referred to a standard orthonormal basis in the Hilbert space of a finite dimensional quantum system. We study the related issues like classification of…

Quantum Physics · Physics 2007-08-28 Ali Saif M. Hassan , Pramod Joag

Representing graphs as quantum states is becoming an increasingly important approach to study entanglement of mixed states, alternate to the standard linear algebraic density matrix-based approach of study. In this paper, we propose a…

Quantum Physics · Physics 2017-03-24 Bibhas Adhikari , Subhashish Banerjee , Satyabrata Adhikari , Atul Kumar

We consider nonnegative r-potent matrices with finite dimensions and study their decomposability. We derive the precise conditions under which an r-potent matrix is decomposable. We further determine a general structure for the r-potent…

Functional Analysis · Mathematics 2015-04-20 Rashmi Sehgal Thukral , Alka Marwaha

Explicit separable density matrices, for mixed two qubits states, are derived by the use of Hilbert Schmidt decompositions and Peres Horodecki criterion. A strongly separable two qubits mixed state is defined by multiplications of two…

Quantum Physics · Physics 2015-10-01 Y. Ben-Aryeh

In a series of papers with Kossakowski, the first author has examined properties of densities for which the positive partial transpositrionm (PPT) property can be readily checked. These densities were also investigated from a different…

Quantum Physics · Physics 2009-11-13 Dariusz Chruscinski , Arthur O. Pittenger

The question of when zeros (i.e., sparsity) in a positive definite matrix $A$ are preserved in its Cholesky decomposition, and vice versa, was addressed by Paulsen et al. in the Journal of Functional Analysis (85, pp151-178). In particular,…

Combinatorics · Mathematics 2012-03-26 Kshitij Khare , Bala Rajaratnam

A general separability condition on the second moment (covariance matrix) for continuous variable two-party systems is derived by an analysis analogous to the derivation of the Kennard's uncertainty relation without referring to the…

Quantum Physics · Physics 2015-05-13 Kazuo Fujikawa

The eigenvalues of the Laplacian matrix for a class of directed graphs with both positive and negative weights are studied. First, a class of directed signed graphs is investigated in which one pair of nodes (either connected or not) is…

Optimization and Control · Mathematics 2017-05-15 Saeed Ahmadizadeh , Iman Shames , Samuel Martin , Dragan Nesic
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