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We prove a constant term conjecture of Robbins and Zeilberger (J. Combin. Theory Ser. A 66 (1994), 17-27), by translating the problem into a determinant evaluation problem and evaluating the determinant. This determinant generalizes the…

Combinatorics · Mathematics 2007-05-23 Christian Krattenthaler

For an arbitrary parameter $p\in [1,+\infty]$, we consider the problem of exponential stabilization in the spatial $L^{p}$-norm, and $W^{1,p}$-norm, respectively, for a class of anti-stable linear parabolic PDEs with space-time-varying…

Optimization and Control · Mathematics 2022-07-05 Qiaoling Chen , Jun Zheng , Guchuan Zhu

Linear perturbations of solutions of dynamical systems exhibit different asymptotic growth rates, which are naturally characterized by so-called covariant Lyapunov vectors (CLVs). Due to an increased interest of CLVs in applications,…

Dynamical Systems · Mathematics 2019-05-30 Florian Noethen

We derive the limiting matrix kernels for the the Gaussian Orthogonal and Symplectic ensembles scaled at the edge, with proofs of convergence in the operator norms that assure convergence of the determinants.

Mathematical Physics · Physics 2007-05-23 Craig A. Tracy , Harold Widom

In nonparametric statistical problems, we wish to find an estimator of an unknown function f. We can split its error into bias and variance terms; Smirnov, Bickel and Rosenblatt have shown that, for a histogram or kernel estimate, the…

Statistics Theory · Mathematics 2013-02-19 Adam D. Bull

Convergence rates of kernel density estimators for stationary time series are well studied. For invertible linear processes, we construct a new density estimator that converges, in the supremum norm, at the better, parametric, rate…

Statistics Theory · Mathematics 2009-09-29 Anton Schick , Wolfgang Wefelmeyer

We study conditions so that the determinantal point process $\Lambda_\phi$ associated to a generalized Fock space defined by a doubling subharmonic weight $\phi$ is almost surely a separated sequence in $\mathbb C$. Under a natural…

Complex Variables · Mathematics 2025-02-11 Giuseppe Lamberti , Xavier Massaneda

Let $\mathbf x=\{x^{(1)},\dots,x^{(n)}\}$ be a space filling-design of $n$ points defined in $[0{,}1]^d$. In computer experiments, an important property seeked for $\mathbf x$ is a nice coverage of $[0{,}1]^d$. This property could be…

Probability · Mathematics 2020-02-28 Adrien Mazoyer , Jean-François Coeurjolly , Pierre-Olivier Amblard

We study a family of Fredholm determinants associated to deformations of the sine kernel, parametrized by a weight function w. For a specific choice of w, this kernel describes bulk statistics of finite temperature free fermions. We…

Mathematical Physics · Physics 2023-09-08 Tom Claeys , Sofia Tarricone

The present work stemmed from the study of the problem of harmonic analysis on the infinite-dimensional unitary group U(\infty). That problem consisted in the decomposition of a certain 4-parameter family of unitary representations, which…

Representation Theory · Mathematics 2016-03-10 Vadim Gorin , Grigori Olshanski

The aim of the paper is to develop a general theory of solvability of linear inhomogeneous boundary-value problems for systems of ordinary differential equations of arbitrary order in Sobolev spaces. Boundary conditions are allowed to be…

Classical Analysis and ODEs · Mathematics 2023-10-12 Vladimir Mikhailets , Olena Atlasiuk

As is well known the kernel of the orthogonal projector onto the polynomials of degree $n$ in $L^2(w_{\a,\b}, [-1, 1])$ with $w_{\a,\b}(t) = (1-t)^\a(1+t)^\b$ can be written in terms of Jacobi polynomials. It is shown that if the…

Classical Analysis and ODEs · Mathematics 2007-05-23 Pencho Petrushev , Yuan Xu

Determinantal point processes (DPPs for short) are a class of repulsive point processes. They have found some statistical applications to model spatial point pattern datasets with repulsion between close points. In the case of DPPs on…

Statistics Theory · Mathematics 2025-07-28 Poinas Arnaud

The Determinantal Point Process (DPP) is a parameterized model for multivariate binary variables, characterized by a correlation kernel matrix. This paper proposes a closed form estimator of this kernel, which is particularly easy to…

Machine Learning · Statistics 2025-05-21 Christian Gouriéroux , Yang Lu

An explicit Fredholm determinant formula is derived for the multipoint distribution of the height function of the totally asymmetric simple exclusion process (TASEP) with arbitrary right-finite initial condition. The method is by solving…

Probability · Mathematics 2021-11-25 Konstantin Matetski , Jeremy Quastel , Daniel Remenik

Determinantal point processes (DPPs) offer an elegant tool for encoding probabilities over subsets of a ground set. Discrete DPPs are parametrized by a positive semidefinite matrix (called the DPP kernel), and estimating this kernel is key…

Machine Learning · Computer Science 2015-10-12 Zelda Mariet , Suvrit Sra

We study the $L^{\infty}$ discrepancy of point sets generated by determinantal point processes on all compact, connected two-point homogeneous spaces, namely spheres and projective spaces. Using concentration inequalities and variance…

Classical Analysis and ODEs · Mathematics 2026-05-22 Carlos Beltrán , Ujué Etayo , Giacomo Gigante , Pedro R. López-Gómez , Ryan W. Matzke

We prove that matrix Fredholm determinants related to multi-time processes can be expressed in terms of determinants of integrable kernels \`a la Its-Izergin-Korepin-Slavnov (IIKS) and hence related to suitable Riemann-Hilbert problems,…

Mathematical Physics · Physics 2013-06-06 M. Bertola , M. Cafasso

Iterated Geronimus transformations generate Sobolev-type orthogonal polynomials from classical families. We establish a direct equivalence between a Sobolev inner product involving point evaluation and the first derivative at a point a…

Classical Analysis and ODEs · Mathematics 2026-04-14 N. Neha

In this paper we investigate the approximation properties of kernel interpolants on manifolds. The kernels we consider will be obtained by the restriction of positive definite kernels on $\R^d$, such as radial basis functions (RBFs), to a…

Functional Analysis · Mathematics 2011-01-19 Edward Fuselier , Grady Wright
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