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The random matrix ensembles (RME) of quantum statistical Hamiltonian operators, e.g. Gaussian random matrix ensembles (GRME) and Ginibre random matrix ensembles (Ginibre RME), are applied to following quantum statistical systems: nuclear…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

We investigate the spectral statistics of Hermitian matrices in which the elements are chosen uniformly from U (1), called the uni-modular ensemble (UME), in the limit of large matrix size. Using three complimentary methods; a…

Mathematical Physics · Physics 2017-09-13 Christopher H. Joyner , Uzy Smilansky , Hans A. Weidenmüller

We propose an experimental scheme to probe the quantum statistics of two identical particles. The transition between the quantum and classical statistics of two identical particles is described by the particles having identical multiple…

Quantum Physics · Physics 2025-06-11 Won-Young Hwang , Kicheon Kang

We propose to analyse the statistical properties of a sequence of vectors using the spectrum of the associated Gram matrix. Such sequences arise e.g. by the repeated action of a deterministic kicked quantum dynamics on an initial condition…

Mathematical Physics · Physics 2007-05-23 Mieke De Cock , Mark Fannes , Pascal Spincemaille

Fractional revival occurs between two vertices in a graph if a continuous-time quantum walk unitarily maps the characteristic vector of one vertex to a superposition of the characteristic vectors of the two vertices. This phenomenon is…

Combinatorics · Mathematics 2019-07-11 Ada Chan , Gabriel Coutinho , Christino Tamon , Luc Vinet , Hanmeng Zhan

The eigenstate thermalization hypothesis provides to date the most successful description of thermalization in isolated quantum systems by conjecturing statistical properties of matrix elements of typical operators in the (quasi-)energy…

Statistical Mechanics · Physics 2021-06-30 Felix Fritzsch , Tomaž Prosen

We investigate the spectral fluctuation properties of constrained ensembles of random matrices (defined by the condition that a number N(Q) of matrix elements vanish identically; that condition is imposed in unitarily invariant form) in the…

Mathematical Physics · Physics 2009-11-13 Z. Pluhar , H. A. Weidenmueller

Exceptional points are special degeneracy points in parameter space that can arise in (effective) non-Hermitian Hamiltonians describing open quantum and wave systems. At an n-th order exceptional point, n eigenvalues and the corresponding…

Quantum Physics · Physics 2024-09-23 Daniel Grom , Julius Kullig , Malte Röntgen , Jan Wiersig

Orthogonal - unitary and symplectic - unitary crossover ensembles of random matrices are relevant in many contexts, especially in the study of time reversal symmetry breaking in quantum chaotic systems. Using skew-orthogonal polynomials we…

Mathematical Physics · Physics 2011-05-30 Santosh Kumar , Akhilesh Pandey

The spectral fluctuations of complex quantum systems, in appropriate limit, are known to be consistent with that obtained from random matrices. However, this relation between the spectral fluctuations of physical systems and random matrices…

Quantum Physics · Physics 2020-09-16 S. Harshini Tekur , M. S. Santhanam

We study multifractal properties of wave functions for a one-parameter family of quantum maps displaying the whole range of spectral statistics intermediate between integrable and chaotic statistics. We perform extensive numerical…

Chaotic Dynamics · Physics 2008-03-18 J. Martin , O. Giraud , B. Georgeot

We study operators on rooted graphs with a certain spherical homogeneity. These graphs are called path commuting and allow for a decomposition of the adjacency matrix and the Laplacian into a direct sum of Jacobi matrices which reflect the…

Spectral Theory · Mathematics 2012-01-04 Jonathan Breuer , Matthias Keller

We study the problem of irreversibility when the dynamical evolution of a many-body system is described by a stochastic quantum circuit. Such evolution is more general than a Hamiltonian one, and since energy levels are not well defined,…

Quantum Physics · Physics 2015-06-17 Claudio Chamon , Alioscia Hamma , Eduardo R. Mucciolo

The distance energy of a graph $G$ is a recently developed energy-type invariant, defined as the sum of absolute values of the eigenvalues of the distance matrix of $G$. There was a vast research for the pairs and families of non-cospectral…

Combinatorics · Mathematics 2011-04-07 Aleksandar Ili\' c

In this paper we will apply the tensor and its traces to investigate the spectral characterization of unicyclic graphs. Let $G$ be a graph and $G^m$ be the $m$-th power (hypergraph) of $G$. The spectrum of $G$ is referring to its adjacency…

Combinatorics · Mathematics 2025-07-22 Yi-Zheng Fan , Hong-Xia Yang , Jian Zheng

In the broad range of studies related to quantum graphs, quantum graph spectra appear as a topic of special interest. They are important in the context of diffusion type problems posed on metric graphs. Theoretical findings suggest that…

Numerical Analysis · Mathematics 2023-12-15 Chong-Son Dröge , Anna Weller

We analyze the spectral properties of the high-dimensional random geometric graph $G(n, d, p)$, formed by sampling $n$ i.i.d vectors $\{v_i\}_{i=1}^{n}$ uniformly on a $d$-dimensional unit sphere and connecting each pair $\{i,j\}$ whenever…

Probability · Mathematics 2026-02-11 Yifan Cao , Yizhe Zhu

We study the effect of gradual symmetry breaking in a non-integrable system on the level fluctuation statistics. We consider the case when the symmetry is represented by a quantum number that takes one of two possible values, so that the…

Chaotic Dynamics · Physics 2009-11-07 A. Abd El-Hady , A. Y. Abul-Magd , M. H. Simbel

We examine the empirical distribution of the eigenvalues and the eigenvectors of adjacency matrices of sparse regular random graphs. We find that when the degree sequence of the graph slowly increases to infinity with the number of…

Probability · Mathematics 2012-10-15 Ioana Dumitriu , Soumik Pal

Even pruned by the state-of-the-art network compression methods, Graph Neural Networks (GNNs) training upon non-Euclidean graph data often encounters relatively higher time costs, due to its irregular and nasty density properties, compared…

Machine Learning · Computer Science 2022-10-04 Chunhui Zhang , Chao Huang , Yijun Tian , Qianlong Wen , Zhongyu Ouyang , Youhuan Li , Yanfang Ye , Chuxu Zhang