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A variational formulation for the calculation of interacting fermion systems based on the density-matrix functional theory is presented. Our formalism provides for a natural integration of explicit many-particle effects into standard…

Strongly Correlated Electrons · Physics 2013-05-29 Peter E. Bloechl , Christian F. J. Walther , Thomas Pruschke

Quantifying the eigenvalue spectra of large random matrices allows one to understand the factors that contribute to the stability of dynamical systems with many interacting components. This work explores the effect that the interaction…

Disordered Systems and Neural Networks · Physics 2022-12-08 Joseph W. Baron

We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of adjacency matrix of various model networks, namely, random,…

Statistical Mechanics · Physics 2009-11-13 Sarika Jalan , Jayendra N. Bandyopadhyay

Our interest is in the scaled joint distribution associated with $k$-increasing subsequences for random involutions with a prescribed number of fixed points. We proceed by specifying in terms of correlation functions the same distribution…

Combinatorics · Mathematics 2007-05-23 Peter J. Forrester , Taro Nagao , Eric M. Rains

Universal limits for the eigenvalue correlation functions in the bulk of the spectrum are shown for a class of nondeterminantal random matrices known as the fixed trace ensemble.

Probability · Mathematics 2007-12-12 Friedrich Götze , Mikhail Gordin

This thesis reviews recent progress on products of random matrices from the perspective of exactly solved Gaussian random matrix models. We derive exact formulae for the correlation functions for the eigen- and singular values at arbitrary…

Mathematical Physics · Physics 2015-10-22 J. R. Ipsen

It is possible to extract values for critical couplings and gamma_string in matrix models by deriving a renormalization group equation for the variation of the of the free energy as the size N of the matrices in the theory is varied. In…

High Energy Physics - Theory · Physics 2009-10-28 D. Johnston

Networks are often studied using the eigenvalues of their adjacency matrix, a powerful mathematical tool with a wide range of applications. Since in real systems the exact graph structure is not known, researchers resort to random graphs to…

Spectral Theory · Mathematics 2020-01-30 Pau Vilimelis Aceituno

With a super-high-efficient numerical algorithm, we are able to self-consistently calculate the Green's function in the renormalized-ring-diagram approximation for a two-dimensional electron system with long-range Coulomb interactions. The…

Strongly Correlated Electrons · Physics 2011-11-09 Xin-Zhong Yan , C. S. Ting

Two different models exhibiting self-organized criticality are analyzed by means of the dynamic renormalization group. Although the two models differ by their behavior under a parity transformation of the order parameter, it is shown that…

Condensed Matter · Physics 2009-10-22 Albert Diaz-Guilera

We construct a very general family of characteristic functions describing Random Matrix Ensembles (RME) having a global unitary invariance, and containing an arbitrary, one-variable probability measure which we characterize by a `spread…

Other Condensed Matter · Physics 2009-11-11 K. A. Muttalib , J. R. Klauder

We describe a new formulation of the functional renormalization group (RG) for interacting fermions within a Wilsonian momentum-shell approach. We show that the Luttinger-Ward functional is a fixed point of the RG, and derive the infinite…

Strongly Correlated Electrons · Physics 2007-05-23 N. Dupuis

We extend a recent theory of parametric correlations in the spectrum of random matrices to study the response to an external perturbation of eigenvalues near the soft edge of the support. We demonstrate by explicit non-perturbative…

Condensed Matter · Physics 2009-10-22 A. M. S. Macedo

Because of the significant increase in size and complexity of the networks, the distributed computation of eigenvalues and eigenvectors of graph matrices has become very challenging and yet it remains as important as before. In this paper…

Numerical Analysis · Mathematics 2017-11-27 Konstantin Avrachenkov , Philippe Jacquet , Jithin Sreedharan

We consider a discrete, non-Hermitian random matrix model, which can be expressed as a shift of a rank-one perturbation of an anti-symmetric matrix. We show that, asymptotically almost surely, the real parts of the eigenvalues of the…

Probability · Mathematics 2016-11-22 Philippe Sosoe , Uzy Smilansky

The eigenvalue distribution of the sum of two large Hermitian matrices, when one of them is conjugated by a Haar distributed unitary matrix, is asymptotically given by the free convolution of their spectral distributions. We prove that this…

Probability · Mathematics 2016-12-21 Zhigang Bao , Laszlo Erdos , Kevin Schnelli

Recently much effort has been made towards the introduction of non-Hermitian random matrix models respecting $PT$-symmetry. Here we show that there is a one-to-one correspondence between complex $PT$-symmetric matrices and split-complex and…

Mathematical Physics · Physics 2015-09-17 Eva-Maria Graefe , Steve Mudute-Ndumbe , Matthew Taylor

Identifying the spectrum of the sum of two given Hermitian matrices with fixed eigenvalues is the famous Horn's problem.In this note, we investigate a variant of Horn's problem, i.e., we identify the probability density function (abbr. pdf)…

Quantum Physics · Physics 2019-09-20 Lin Zhang , Hua Xiang

The eigenvalue PDF for some well known classes of non-Hermitian random matrices --- the complex Ginibre ensemble for example --- can be interpreted as the Boltzmann factor for one-component plasma systems in two-dimensional domains. We…

Mathematical Physics · Physics 2016-04-20 Peter J. Forrester

In deriving large n probability distribution function of the rightmost eigenvalue from the classical Random Matrix Theory Ensembles, one is faced with que question of finding large n asymptotic of certain coupled set of functions. This…

Probability · Mathematics 2016-11-25 Leonard N. Choup