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We compute analytically the joint probability density of eigenvalues and the level spacing statistics for an ensemble of random matrices with interesting features. It is invariant under the standard symmetry groups (orthogonal and unitary)…

Statistical Mechanics · Physics 2015-07-21 Zdzisław Burda , Giacomo Livan , Pierpaolo Vivo

Covariance matrices are fundamental to the analysis and forecast of economic, physical and biological systems. Although the eigenvalues $\{\lambda_i\}$ and eigenvectors $\{{\bf u}_i\}$ of a covariance matrix are central to such endeavors,…

Statistics Theory · Mathematics 2018-03-02 Dane Taylor , Juan G. Restrepo , Francois G. Meyer

We study the statistical properties of eigenvalues of the Hessian matrix ${\cal H}$ (matrix of second derivatives of the potential energy) for a classical atomic liquid, and compare these properties with predictions for random matrix models…

Statistical Mechanics · Physics 2016-08-31 Srikanth Sastry , Nivedita Deo , Silvio Franz

Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq 3$, and denote the eigenvalues as $\lambda_1=d/\sqrt{d-1}\geq \lambda_2\geq\lambda_3\cdots\geq \lambda_N$. We prove that the…

Probability · Mathematics 2024-05-21 Jiaoyang Huang , Theo McKenzie , Horng-Tzer Yau

We consider an ensemble of random density matrices distributed according to the Bures measure. The corresponding joint probability density of eigenvalues is described by the fixed trace Bures-Hall ensemble of random matrices which, in turn,…

Mathematical Physics · Physics 2019-07-12 Ayana Sarkar , Santosh Kumar

We extend to additional probability measures and scenarios, certain of the recent results of Krattenthaler and Slater (quant-ph/9612043), whose original motivation was to obtain quantum analogs of seminal work on universal data compression…

Quantum Physics · Physics 2007-05-23 Paul B. Slater

We consider random matrices of the form $H = W + \lambda V$, $\lambda\in\mathbb{R}^+$, where $W$ is a real symmetric or complex Hermitian Wigner matrix of size $N$ and $V$ is a real bounded diagonal random matrix of size $N$ with i.i.d.\…

Probability · Mathematics 2014-01-15 Ji Oon Lee , Kevin Schnelli

We describe an algorithm to compute the extremal eigenvalues and corresponding eigenvectors of a symmetric matrix by solving a sequence of Quadratic Binary Optimization problems. This algorithm is robust across many different classes of…

Emerging Technologies · Computer Science 2022-10-12 Benjamin Krakoff , Susan M. Mniszewski , Christian F. A. Negre

Higher dimensional quantum systems (qudits) present a potentially more efficient means, compared to qubits, for implementing various information theoretic tasks. One of the ubiquitous resources in such explorations is entanglement.…

Quantum Physics · Physics 2022-10-06 Debadrita Ghosh , Thomas Jennewein , Urbasi Sinha

Let $m,n>1$ be integers and $\mathbb{P}_{n,m}$ be the point set of the projective $(n-1)$-space (defined by [2]) over the ring $\mathbb{Z}_m$of integers modulo $m$. Let $A_{n,m}=(a_{uv})$ be the matrix with rows and columns being labeled by…

Discrete Mathematics · Computer Science 2013-04-01 Liang Feng Zhang

We consider two-dimensional (2D) "artificial atoms" confined by an axially symmetric potential $V(\rho)$. Such configurations arise in circular quantum dots and other systems effectively restricted to a 2D layer. Using the semiclassical…

Mesoscale and Nanoscale Physics · Physics 2014-07-28 Yu. N. Ovchinnikov , Avik Halder , Vitaly V. Kresin

We consider a semiparametric mixture of two univariate density functions where one of them is known while the weight and the other function are unknown. Such mixtures have a history of application to the problem of detecting differentially…

Statistics Theory · Mathematics 2017-08-01 Zhou Shen , Michael Levine , Zuofeng Shang

The nonlocal properties of arbitrary dimensional bipartite quantum systems are investigated. A complete set of invariants under local unitary transformations is presented. These invariants give rise to both sufficient and necessary…

Quantum Physics · Physics 2012-07-12 Chunqin Zhou , Tinggui Zhang , Shao-Ming Fei , Naihuan Jing , Xianqing Li-Jost

We compute the exact and limiting smallest eigenvalue distributions for two classes of $\beta$-Jacobi ensembles not covered by previous studies. In the general $\beta$ case, these distributions are given by multivariate hypergeometric…

Probability · Mathematics 2011-08-16 Ioana Dumitriu

For finite-dimensional bipartite quantum systems, we find the exact size of the largest balls, in spectral $l_p$ norms for $1 \le p \le \infty$, of separable (unentangled) matrices around the identity matrix. This implies a simple and…

Quantum Physics · Physics 2009-11-07 Leonid Gurvits , Howard Barnum

We investigate optimal separable approximations (decompositions) of states rho of bipartite quantum systems A and B of arbitrary dimensions MxN following the lines of Ref. [M. Lewenstein and A. Sanpera, Phys. Rev. Lett. 80, 2261 (1998)].…

Quantum Physics · Physics 2016-09-08 S. Karnas , M. Lewenstein

Let $A$ and $B$ be independent, central Wishart matrices in $p$ variables with common covariance and having $m$ and $n$ degrees of freedom, respectively. The distribution of the largest eigenvalue of $(A+B)^{-1}B$ has numerous applications…

Statistics Theory · Mathematics 2009-01-21 Iain M. Johnstone

It is well known that the joint probability density of the eigenvalues of Gaussian ensembles of random matrices may be interpreted as a Coulomb gas. We review these classical results for hermitian and complex random matrices, with special…

Statistical Mechanics · Physics 2007-05-23 P. Leboeuf

Under the name prime decomposition (pd), a unique decomposition of an arbitrary $N$-dimensional density matrix $\rho$ into a sum of seperable density matrices with dimensions given by the coprime factors of $N$ is introduced. For a class of…

Quantum Physics · Physics 2011-07-19 D. Ellinas , E. G. Floratos

The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions, thus has been widely adopted in numerous statistical…

Machine Learning · Statistics 2022-05-17 Yuxin Dong , Tieliang Gong , Shujian Yu , Chen Li
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