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The A-hypergeometric system studied by I.M. Gelfand, M.I. Graev, A.V. Zelevinsky and the author, is defined for a set A of characters of an algebraic torus. In this paper we propose a generalization of the theory where the torus is replaced…

alg-geom · Mathematics 2007-05-23 M. Kapranov

This survey is a preliminary version of a chapter of the forthcoming book "Stochastic Analysis for Poisson Point Processes: Malliavin Calculus, Wiener-It\^o Chaos Expansions and Stochastic Geometry" edited by Giovanni Peccati and Matthias…

Probability · Mathematics 2014-05-20 Günter Last

In this paper, we present recent results in harmonic analysis in the real line R and in the half-line R^+, which show a closed relation between Hermite and Laguerre functions, respectively, their symmetry groups and Fourier analysis. This…

Mathematical Physics · Physics 2018-11-14 Enrico Celeghini , Manuel Gadella , Mariano A. del Olmo

A density matrix describes the statistical state of a quantum system. It is a powerful formalism to represent both the quantum and classical uncertainty of quantum systems and to express different statistical operations such as measurement,…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Alejandro Gallego , Santiago Toledo-Cortés , Vladimir Vargas-Calderón

This work addresses an extension of Fourier-Stieltjes transform of a vector measure defined on compact groups to locally compact groups, by using a group representation induced by a representation of one of its compact subgroups.

Functional Analysis · Mathematics 2022-08-16 Y. I. Akakpo , M. N. Hounkonnou , K. Enakoutsa , V. S. K. Assiamoua

We study Gelfand pairs for locally compact quantum groups. We give an operator algebraic interpretation and show that the quantum Plancherel transformation restricts to a spherical Plancherel transformation. As an example, we turn the…

Operator Algebras · Mathematics 2011-09-07 Martijn Caspers

Quantum Mechanics and Signal Processing in the line R, are strictly related to Fourier Transform and Weyl-Heisenberg algebra. We discuss here the addition of a new discrete variable that measures the degree of the Hermite functions and…

Mathematical Physics · Physics 2015-06-23 Enrico Celeghini , Mariano A. del Olmo

In our previous articles "A local Paley-Wiener theorem for compact symmetric spaces", Adv. Math. 218 (2008), 202--215, and "Fourier series on compact symmetric spaces" (submitted) we studied Fourier series on a compact symmetric space…

Functional Analysis · Mathematics 2009-04-29 Gestur Olafsson , Henrik Schlichtkrull

Convolution operation is indispensable in studying analog optical and digital signal processing. Equally important is the correlation operation. The time domain community often teaches convolution and correlation only with one dimensional…

Physics Education · Physics 2018-10-22 Debesh Choudhury

We study one and two point functions of conformal field theories on spaces of maximal symmetry with and without boundaries and investigate their spectral representations. Integral transforms are found, relating the spectral decomposition to…

High Energy Physics - Theory · Physics 2015-09-30 Kurt Hinterbichler , James Stokes , Mark Trodden

The graph Fourier transform (GFT) is an important tool for graph signal processing, with applications ranging from graph-based image processing to spectral clustering. However, unlike the discrete Fourier transform, the GFT typically does…

Signal Processing · Electrical Eng. & Systems 2019-10-02 Keng-Shih Lu , Antonio Ortega

We revisit the Fourier transform of a Hankel function, of considerable importance in the theory of knife edge diffraction. Our approach is based directly upon the underlying Bessel equation, which admits manipulation into an alternate…

General Mathematics · Mathematics 2021-12-21 J. A. Grzesik

Matrix elements of spinor and principal series representations of the Lorentz group are studied in the basis of complex angular momentum (helicity basis). It is shown that matrix elements are expressed via hyperspherical functions…

Mathematical Physics · Physics 2007-05-23 V. V. Varlamov

Fast Fourier transform (FFT) based methods have turned out to be an effective computational approach for numerical homogenisation. In particular, Fourier-Galerkin methods are computational methods for partial differential equations that are…

Numerical Analysis · Mathematics 2020-04-22 Jaroslav Vondřejc , Dishi Liu , Martin Ladecký , Hermann G. Matthies

We present a fast and numerically accurate method for expanding digitized $L \times L$ images representing functions on $[-1,1]^2$ supported on the disk $\{x \in \mathbb{R}^2 : |x|<1\}$ in the harmonics (Dirichlet Laplacian eigenfunctions)…

Numerical Analysis · Mathematics 2022-12-23 Nicholas F. Marshall , Oscar Mickelin , Amit Singer

Using the Fourier-Laplace transform, we describe the isomonodromy equations for meromorphic connections on the Riemann sphere with unramified irregular singularities as those for connections with a (possibly ramified) irregular singularity…

Classical Analysis and ODEs · Mathematics 2014-01-28 Daisuke Yamakawa

In this paper, we study the group Fourier transform and the Kohn-Nirenberg quantization for homogeneous Lie groups as mappings between certain Gelfand triples. For this, we restrict our considerations to the case, where the homogeneous Lie…

Functional Analysis · Mathematics 2020-11-10 Jonas Brinker , Jens Wirth

We consider symmetry operations on the four-dimensional vector space that is spanned by the local versions of the Minkowski functionals (or fundamental measures): volume, surface, integral mean curvature, and Euler characteristic, of an…

Mathematical Physics · Physics 2015-05-27 Matthias Schmidt

The eigenfunctions of the Laplacian are a natural basis of functions for many tasks in computational mathematics. On the circle and sphere, the eigenfunctions are given by complex periodic exponentials and spherical harmonics, respectively,…

Numerical Analysis · Mathematics 2026-05-22 Paul G. Beckman , Samuel F. Potter , Michael O'Neil

In a range of fields including the geosciences, molecular biology, robotics and computer vision, one encounters problems that involve random variables on manifolds. Currently, there is a lack of flexible probabilistic models on manifolds…

Machine Learning · Statistics 2019-04-23 Taco S. Cohen , Max Welling
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