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We analyze mechanisms for universal out-of-equilibrium dynamics near criticality by exploring the effect of randomized quantum resetting (QR) under a finite-time quench across a quantum phase transition. Using the transverse-field Ising…

Statistical Mechanics · Physics 2026-02-03 R. Jafari , Henrik Johannesson , Sebastian Eggert

Many statistical applications, such as the Principal Component Analysis, matrix completion, tensor regression and many others, rely on accurate estimation of leading eigenvectors of a matrix. The Davis-Kahan theorem is known to be…

Methodology · Statistics 2026-04-09 Marianna Pensky

We construct the multilevel correlation kernel for the rising GUE eigenvalue process starting from a fixed initial configuration $x^{(m)}$, and show that it converges on short time scales (as quickly as $\text{polylog}(m)$) to the extended…

Probability · Mathematics 2026-05-01 Zoe Himwich

We review studies of entanglement entropy in systems with quenched randomness, concentrating on universal behavior at strongly random quantum critical points. The disorder-averaged entanglement entropy provides insight into the quantum…

Disordered Systems and Neural Networks · Physics 2015-05-13 Gil Refael , Joel E. Moore

We present a simple method, combining the density-matrix renormalization-group (DMRG) algorithm with finite-size scaling, which permits the study of critical behavior in quantum spin chains. Spin moments and dimerization are induced by…

Strongly Correlated Electrons · Physics 2009-10-31 Shan-Wen Tsai , J. B. Marston

In this paper we construct a class of random matrix ensembles labelled by a real parameter $\alpha \in (0,1)$, whose eigenvalue density near zero behaves like $|x|^\alpha$. The eigenvalue spacing near zero scales like $1/N^{1/(1+\alpha)}$…

High Energy Physics - Theory · Physics 2015-06-26 Romuald A. Janik

Kernel methods are successful approaches for different machine learning problems. This success is mainly rooted in using feature maps and kernel matrices. Some methods rely on the eigenvalues/eigenvectors of the kernel matrix, while for…

Machine Learning · Computer Science 2012-02-20 Nima Reyhani , Hideitsu Hino , Ricardo Vigario

The two-dimensional Ashkin-Teller model provides the simplest example of a statistical system exhibiting a line of critical points along which the critical exponents vary continously. The scaling limit of both the paramagnetic and…

High Energy Physics - Theory · Physics 2009-11-10 G. Delfino , P. Grinza

Eigenvalue correlations of random matrix ensembles as a function of an external perturbation are investigated vis the Dyson Brownian Motion Model in the situation where the level density has a hard edge singularity. By solving a linearized…

Condensed Matter · Physics 2009-10-22 Kasper Eriksen , Yang Chen

We study the Gaussian hermitian random matrix ensemble with an external matrix which has an arbitrary number of eigenvalues with arbitrary multiplicity. We compute the limiting eigenvalues correlations when the size of the matrix goes to…

Mathematical Physics · Physics 2008-03-06 N. Orantin

We explore the universal signatures of quantum phase transitions that can be extracted with the density matrix renormalization group (DMRG) algorithm applied to quantum chains with a gradient. We present high-quality data collapses for the…

Strongly Correlated Electrons · Physics 2024-10-04 Natalia Chepiga

We obtain the explicit rate of convergence $N^{-1/2 + \epsilon}$ for the gaps of generalized Wigner matrices in the bulk of the spectrum, for distributions of matrix entries possibly atomic and supported on enough points. The proof proceeds…

Probability · Mathematics 2025-09-24 Albert Zhang

Number theorists have studied extensively the connections between the distribution of zeros of the Riemann $\zeta$-function, and of some generalizations, with the statistics of the eigenvalues of large random matrices. It is interesting to…

Mathematical Physics · Physics 2009-10-31 E. Brezin , S. Hikami

Using a very efficient numerical algorithm of the strong disorder renormalization group method we have extended the investigations about the critical behavior of the random transverse-field Ising model in three and four dimensions, as well…

Disordered Systems and Neural Networks · Physics 2015-05-20 Istvan A. Kovacs , Ferenc Igloi

In this paper, we introduce new reference observables to establish a scaling formula in the renormalization group equation. Using the transfer matrix method, we calculate the two point observables of the one dimensional Ising model without…

Probability · Mathematics 2024-05-14 Cui Kaiyuan , Gong Fuzhou

We study random points on the real line generated by the eigenvalues in unitary invariant random matrix ensembles or by more general repulsive particle systems. As the number of points tends to infinity, we prove convergence of the…

Probability · Mathematics 2015-11-11 Kristina Schubert , Martin Venker

We study the eigenvalue distribution of a random matrix, at a transition where a new connected component of the eigenvalue density support appears away from other connected components. Unlike previously studied critical points, which…

Mathematical Physics · Physics 2007-05-23 Bertrand Eynard

The study of entanglement spectra is a powerful tool to detect or elucidate universal behaviour in quantum many-body systems. We investigate the scaling of the entanglement (or Schmidt) gap $\delta\xi$, i.e., the lowest laying gap of the…

Statistical Mechanics · Physics 2021-01-04 Sascha Wald , Raul Arias , Vincenzo Alba

We consider the complex eigenvalues of a Wishart type random matrix model $X=X_1 X_2^*$, where two rectangular complex Ginibre matrices $X_{1,2}$ of size $N\times (N+\nu)$ are correlated through a non-Hermiticity parameter $\tau\in[0,1]$.…

Probability · Mathematics 2021-03-26 Gernot Akemann , Sung-Soo Byun , Nam-Gyu Kang

We consider disordered ladders of the transverse-field Ising model and study their critical properties and entanglement entropy for varying width, $w \le 20$, by numerical application of the strong disorder renormalization group method. We…

Disordered Systems and Neural Networks · Physics 2015-05-14 Istvan A. Kovacs , Ferenc Igloi