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In this paper we analyze the covariance kernel of the Gaussian process that arises as the limit of fluctuations of linear spectral statistics for Wigner matrices with a few moments. More precisely, the process we study here corresponds to…

Probability · Mathematics 2022-02-16 Asad Lodhia , Anna Maltsev

In supersymmetric theories, one can obtain striking results and insights by exploiting the fact that the superpotential and the gauge coupling function are holomorphic functions of the model parameters. The precise meaning of this…

High Energy Physics - Theory · Physics 2009-10-28 M. Dine , Y. Shirman

We summarize the recent results about complete solvability of Hermitian and rectangular complex matrix models. Partition functions have very simple character expansions with coefficients made from dimensions of representation of the linear…

High Energy Physics - Theory · Physics 2017-08-11 A. Mironov , A. Morozov

The family of Mat\'ern kernels are often used in spatial statistics, function approximation and Gaussian process methods in machine learning. One reason for their popularity is the presence of a smoothness parameter that controls, for…

Statistics Theory · Mathematics 2025-06-06 Moritz Korte-Stapff , Toni Karvonen , Eric Moulines

We investigate the physical interpretation of the Riemann zeta function as a FZZT brane partition function associated with a matrix/gravity correspondence. The Hilbert-Polya operator in this interpretation is the master matrix of the large…

Mathematical Physics · Physics 2007-08-07 Michael McGuigan

The symmetries described by Pin groups are the result of combining a finite number of discrete reflections in (hyper)planes. The current work shows how an analysis using geometric algebra provides a picture complementary to that of the…

Mathematical Physics · Physics 2025-10-16 Martin Roelfs , Steven De Keninck

In this work, some classical results of the pfaffian theory of the dimer model based on the work of Kasteleyn, Fisher and Temperley are introduced in a fermionic framework. Then we shall detail the bosonic formulation of the model {\it via}…

Statistical Mechanics · Physics 2015-06-23 Nicolas Allegra

We show that the metric structure of morphisms $f\colon Y\to X$ between quasi-smooth compact Berkovich curves over an algebraically closed field admits a finite combinatorial description. In particular, for a large enough skeleton…

Algebraic Geometry · Mathematics 2017-03-02 Michael Temkin

Suppose $A$ is a positive real linear transformation on a finite dimensional complex inner product space $V$. The reproducing kernel for the Fock space of square integrable holomorphic functions on $V$ relative to the Gaussian measure…

Functional Analysis · Mathematics 2007-05-23 R. Fabec , G. Olafsson , A. Sengupta

In data science, individual observations are often assumed to come independently from an underlying probability space. Kernel matrices formed from large sets of such observations arise frequently, for example during classification tasks. It…

Machine Learning · Statistics 2026-05-27 Mikhail Lepilov

Bayesian model updating based on Gaussian Process (GP) models has received attention in recent years, which incorporates kernel-based GPs to provide enhanced fidelity response predictions. Although most kernel functions provide high fitting…

The central objects in a quantum field theory are its n-point correlation functions and matrix elements. Their structure is determined by Lorentz invariance and leads to tensor decompositions whose Lorentz-invariant coefficient functions…

High Energy Physics - Phenomenology · Physics 2026-03-03 Gernot Eichmann

We study the hermitian one matrix model with semi-classical potential. This is a general unitary invariant random matrix ensemble in which the potential has a derivative that is a rational function and the measure is supported on some…

Mathematical Physics · Physics 2015-04-20 Max R. Atkin

We use heat kernels or eigenfunctions of the Laplacian to construct local coordinates on large classes of Euclidean domains and Riemannian manifolds (not necessarily smooth, e.g. with $\mathcal{C}^\alpha$ metric). These coordinates are…

Analysis of PDEs · Mathematics 2008-10-09 Peter W. Jones , Mauro Maggioni , Raanan Schul

We develop a coordinate-free probabilistic framework for determinantal point processes associated with Bergman kernels on compact complex manifolds. The basic issue is that Bergman kernels are naturally line-bundle-valued:…

Complex Variables · Mathematics 2026-05-27 Thibaut Lemoine

We discuss how methods developed in the context of perturbation theory can be applied to the computation of lattice correlation functions, in particular in the non perturbative regime. The techniques we consider are integration-by-parts…

High Energy Physics - Theory · Physics 2023-09-19 Federico Gasparotto , Andreas Rapakoulias , Stefan Weinzierl , Xiaofeng Xu

We extend the Nakajima-Zwanzig projection operator technique to the determination of multitime correlation functions of open quantum systems. The correlation functions are expressed in terms of certain multitime homogeneous and…

Quantum Physics · Physics 2017-02-16 Anton Ivanov , Heinz-Peter Breuer

Computing the Pfaffian of a skew-symmetric matrix is a problem that arises in various fields of physics. Both computing the Pfaffian and a related problem, computing the canonical form of a skew-symmetric matrix under unitary congruence,…

Mesoscale and Nanoscale Physics · Physics 2015-03-19 M. Wimmer

Polterovich proved a remarkable closed formula for heat kernel coefficients of the Laplace operator on compact Riemannian manifolds involving powers of Laplacians acting on the distance function. In the case of K\"ahler manifolds, we prove…

Differential Geometry · Mathematics 2016-12-21 Kefeng Liu , Hao Xu

A new approach to the correlation functions is presented for the XXZ model in the anti-ferroelectric regime. The method is based on the recent realization of the quantum affine symmetry using vertex operators. With the aid of a boson…

High Energy Physics - Theory · Physics 2016-09-06 Michio Jimbo , Kei Miki , Tetsuji Miwa , Atsushi Nakayashiki