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In this paper we give a multiresolution construction in Bergman space. The successful application of rational orthogonal bases needs a priori knowledge of the poles of the transfer function that may cause a drawback of the method. We give a…

Complex Variables · Mathematics 2011-09-08 Margit Pap

A joint characterisation of the controllability and observability of a particular kind of discrete system has been developed. The key idea of the procedure can be reduced to a correct choice of the sampling sequence. This freedom, owing to…

Dynamical Systems · Mathematics 2010-06-14 Amparo Fúster-Sabater , J. M. Guillén

We investigate the reproducing properties of Gabor systems within the context of expansible groups. These properties are established in terms of density conditions. The concept of density that we employ mirrors the well-known Beurling…

Functional Analysis · Mathematics 2024-10-16 Emily King , Rocio Nores , Victoria Paternostro

Using the notion of commutative operator vessels, this work investigates de Branges-Rovnyak spaces whose elements are sections of a line bundle of multiplicative half-order differentials on a compact real Riemann surface. As a special case,…

Complex Variables · Mathematics 2020-07-15 Daniel Alpay , Ariel Pinhas , Victor Vinnikov

We demonstrate the synthesis of sparse sampling and machine learning to characterize and model complex, nonlinear dynamical systems over a range of bifurcation parameters. First, we construct modal libraries using the classical proper…

Pattern Formation and Solitons · Physics 2015-10-28 Syuzanna Sargsyan , Steven L. Brunton , J. Nathan Kutz

An infinite system of nonlocal, individually confining solitons is considered as a model of high-density nuclear matter. The soliton-lattice problem is discussed in the Wigner-Seitz approximation. The cell size is varied to study the…

Nuclear Theory · Physics 2008-11-26 Charles W. Johnson , George Fai

The paper establishes an equivalence between pure point diffraction and certain types of model sets, called inter model sets, in the context of substitution point sets and substitution tilings. The key ingredients are a new type of…

Metric Geometry · Mathematics 2009-10-23 Jeong-Yup Lee

The density matrix formalism is a fundamental tool in studying various problems in quantum information processing. In the space of density matrices, the most well-known measures are the Hilbert-Schmidt and Bures-Hall ensembles. In this…

Quantum Physics · Physics 2023-05-26 Lu Wei , Nicholas Witte

Obtaining general relations between macroscopic properties of random assemblies, such as density, and the microscopic properties of their constituent particles, such as shape, is a foundational challenge in the study of amorphous materials.…

Soft Condensed Matter · Physics 2016-05-05 Yoav Kallus

We prove that the highest density of non-overlapping translates of a given centrally symmetric convex domain relative to its outer parallel domain of given outer radius is attained by a lattice packing in the Euclidean plane. This…

Metric Geometry · Mathematics 2025-12-30 Károly Bezdek , Zsolt Lángi

The problem of covering random points in a plane with sets of a given shape has several practical applications in communications and operations research. One especially prominent application is the coverage of randomly-located points of…

Computational Geometry · Computer Science 2022-09-01 Christophter Thron , Anthony Moreno

Given a compact Riemannian manifold $M$, we consider the subspace of $L^2(M)$ generated by the eigenfunctions of the Laplacian of eigenvalue less than $L\geq 1$. This space behaves like a space of polynomials and we have an analogy with the…

Classical Analysis and ODEs · Mathematics 2012-09-28 Joaquim Ortega-Cerdà , Bharti Pridhnani

The aim of this paper is to extend the concept of measure density introduced by Buck for finite unions of arithmetic progressions, to arbitrary subsets of N defined by a given system of decompositions. This leads to a variety of new…

Classical Analysis and ODEs · Mathematics 2015-04-10 Maria Rita Iacò , Milan Paštéka , Robert F. Tichy

The goal of the paper is to obtain analogs of the sampling theorems and of the Riesz-Boas interpolation formulas which are relevant to the Discrete Hilbert and Kak-Hilbert transforms in $l^{2}$.

Classical Analysis and ODEs · Mathematics 2021-11-04 Isaac Pesenson

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. Previous known results show that for any $N$-dimensional subspace of the space of continuous functions it is…

Functional Analysis · Mathematics 2024-05-08 E. D. Kosov , V. N. Temlyakov

The Patterson-Sullivan construction is proved almost surely to recover a Bergman function from its values on a random discrete subset sampled with the determinantal point process induced by the Bergman kernel on the unit ball $\mathbb{D}_d$…

Complex Variables · Mathematics 2021-01-26 Alexander I. Bufetov , Yanqi Qiu

We study the uniqueness sets, the weak interpolation sets, and convergence of the Lagrange interpolation series in radial weighted Fock spaces

Classical Analysis and ODEs · Mathematics 2012-02-21 André Dumont , Karim Kellay

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. We pay special attention to the case of trigonometric polynomials with frequencies from an arbitrary finite set…

Numerical Analysis · Mathematics 2021-12-14 Boris Kashin , Sergei Konyagin , Vladimir Temlyakov

There is a growing body of results in the theory of discrete point sets and tiling systems giving conditions under which such systems are pure point diffractive. Here we look at the opposite direction: what can we infer about a discrete…

Metric Geometry · Mathematics 2009-10-26 Jeong-Yup Lee , Robert V. Moody , Boris Solomyak

In this paper, we propose a general methodology for sampling from un-normalized densities defined on Riemannian manifolds, with a particular focus on multi-modal targets that remain challenging for existing sampling methods. Inspired by the…

Machine Learning · Statistics 2026-02-03 Alain Durmus , Maxence Noble , Thibaut Pellerin