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Recently it is established, via lower order moments, that the univariate q-normal distribution, which is the weight function for $q$-Hermite polynomials, describes the ensemble averaged eigenvalue density from many-particle random matrix…

Mathematical Physics · Physics 2021-07-06 V. K. B. Kota , Manan Vyas

Embedded random matrix ensembles are generic models for describing statistical properties of finite isolated interacting quantum many-particle systems. For the simplest spinless systems, with say $m$ particles in $N$ single particle states…

Quantum Physics · Physics 2015-04-06 V. K. B. Kota , Manan Vyas

Following the earlier studies on embedded unitary ensembles generated by random two-body interactions [EGUE(2)] with spin SU(2) and spin-isospin SU(4) symmetries, developed is a general formulation, for deriving lower order moments of the…

Mathematical Physics · Physics 2015-06-05 Manan Vyas , V. K. B. Kota

Embedded random matrix ensembles are generic models for describing statistical properties of finite isolated quantum many-particle systems. For the simplest spinless fermion (or boson) systems with say $m$ fermions (or bosons) in $N$ single…

Mathematical Physics · Physics 2015-06-23 V. K. B. Kota

Numerical simulations of the two-point eigenvalue correlation and cluster functions of the Gaussian unitary ensemble (GUE) are carried out directly from their definitions in terms of deltas functions. The simulations are compared with…

Nuclear Theory · Physics 2021-02-23 Adam James Sargeant

In finite many-body quantum systems such as nuclei, atoms, mesoscopic systems like quantum dots and small metallic grains, interacting spin systems modeling quantum computing core and BEC, the interparticle interactions are essentially…

Quantum Physics · Physics 2017-10-24 Manan Vyas

The eigenvalue probability density function of the Gaussian unitary ensemble permits a $q$-extension related to the discrete $q$-Hermite weight and corresponding $q$-orthogonal polynomials. A combinatorial counting method is used to specify…

Probability · Mathematics 2024-04-05 Sung-Soo Byun , Peter J. Forrester , Jaeseong Oh

The embedded ensembles were introduced by Mon and French as physically more plausible stochastic models of many--body systems governed by one--and two--body interactions than provided by standard random--matrix theory. We review several…

Condensed Matter · Physics 2008-11-26 L. Benet , H. A. Weidenmueller

We present a method using Feynman-like diagrams to calculate the statistical properties of random many-body potentials. This method provides a promising alternative to existing techniques typically applied to this class of problems, such as…

Other Condensed Matter · Physics 2015-06-23 Rupert Small , Sebastian Müller

Exploiting the explicit bijection between the density of singular values and the density of eigenvalues for bi-unitarily invariant complex random matrix ensembles of finite matrix size, we aim at finding the induced probability measure on…

Probability · Mathematics 2026-03-24 Matthias Allard , Mario Kieburg

Spatial and momentum correlations are important in the analysis of the quantum states and different phases of trapped ultracold atom systems as a function of the strength of interatomic interactions. Identification and understanding of…

Quantum Gases · Physics 2017-12-08 Benedikt B. Brandt , Constantine Yannouleas , Uzi Landman

Recently Pluhar and Weidenmueller [Ann. Phys. (N.Y.) Vol 297, 344 (2002)] showed that the eigenvectors of the matrix of second moments of embedded Gaussian unitary ensemble of random matrices generated by k-body interactions (EGUE(k)) for m…

Nuclear Theory · Physics 2009-11-10 V. K. B. Kota

In the random-interaction ensembles, three proportional correlations between quadrupole moments of the first two $I^{\pi}=2^+$ states robustly emerge, including $Q(2^+_1)=\pm Q(2^+_2)$ correlations consistently with realistic nuclear…

Nuclear Theory · Physics 2016-03-10 Y. Lei

We consider $m$ spinless Fermions in $l > m$ degenerate single-particle levels interacting via a $k$-body random interaction with Gaussian probability distribution and $k <= m$ in the limit $l$ to infinity (the embedded $k$-body random…

Condensed Matter · Physics 2009-10-31 Luis Benet , Thomas Rupp , Hans A. Weidenmueller

The eigenvalue probability density functions of the classical random matrix ensembles have a well known analogy with the one component log-gas at the special couplings \beta = 1,2 and 4. It has been known for some time that there is an…

Mathematical Physics · Physics 2015-05-20 Peter J. Forrester , Christopher D. Sinclair

We introduce in this paper embedded Gaussian unitary ensemble of random matrices, for $m$ fermions in $\Omega$ number of single particle orbits, generated by random two-body interactions that are SU(4) scalar, called EGUE(2)-SU(4). Here the…

Nuclear Theory · Physics 2010-11-02 Manan Vyas , V. K. B. Kota

Statistical ensembles of reduced density matrices of bipartite quantum systems play a central role in entanglement estimation, but do not capture the non-stationary nature of entanglement relevant to realistic quantum information…

Mathematical Physics · Physics 2026-01-27 Youyi Huang , Lu Wei

Classical random matrix ensembles were originally introduced in physics to approximate quantum many-particle nuclear interactions. However, there exists a plethora of quantum systems whose dynamics is explained in terms of few-particle…

Quantum Physics · Physics 2021-11-17 Manan Vyas , Thomas H. Seligman

We analyze the properties of entangled random pure states of a quantum system partitioned into two smaller subsystems of dimensions $N$ and $M$. Framing the problem in terms of random matrices with a fixed-trace constraint, we establish,…

Statistical Mechanics · Physics 2016-05-11 Pierpaolo Vivo , Mauricio P. Pato , Gleb Oshanin

Motivated by questions of present interest in nuclear and condensed matter physics we consider the superposition of a diagonal matrix with independent random entries and a GUE. The relative strength of the two contributions is determined by…

Disordered Systems and Neural Networks · Physics 2009-10-30 Thomas Guhr , Axel Mueller-Groeling
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