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The Discrete Morse Theory of Forman appeared to be useful for providing filtration-preserving reductions of complexes in the study of persistent homology. So far, the algorithms computing discrete Morse matchings have only been used for…

Computational Geometry · Computer Science 2015-03-13 Madjid Allili , Tomasz Kaczynski , Claudia Landi

In this paper the interpolating rational functions introduced by Floater and Hormann are generalized leading to a whole new family of rational functions depending on $\gamma$, an additional positive integer parameter. For $\gamma = 1$, the…

Numerical Analysis · Mathematics 2023-10-20 Woula Themistoclakis , Marc Van Barel

Optimal transport (OT) theory underlies many emerging machine learning (ML) methods nowadays solving a wide range of tasks such as generative modeling, transfer learning and information retrieval. These latter works, however, usually build…

Machine Learning · Statistics 2021-12-03 Quang Huy Tran , Hicham Janati , Ievgen Redko , Rémi Flamary , Nicolas Courty

The optimal quantum measurements for estimating individual parameters might be incompatible with each other so that they cannot be jointly performed. The tradeoff between the estimation precision for different parameters can be…

Quantum Physics · Physics 2022-06-13 Jingjing Shao , Xiao-Ming Lu

We present a nonlinear interpolation technique for parametric fields that exploits optimal transportation of coherent structures of the solution to achieve accurate performance. The approach generalizes the nonlinear interpolation procedure…

Numerical Analysis · Mathematics 2023-10-09 Simona Cucchiara , Angelo Iollo , Tommaso Taddei , Haysam Telib

We consider perturbation defects obtained by perturbing a 2D conformal field theory (CFT) by a relevant operator on a half-plane. If the perturbed bulk theory flows to an infrared fixed point described by another CFT, the defect flows to a…

High Energy Physics - Theory · Physics 2014-07-25 Anatoly Konechny , Cornelius Schmidt-Colinet

The method of alternating projections involves projecting an element of a Hilbert space cyclically onto a collection of closed subspaces. It is known that the resulting sequence always converges in norm and that one can obtain estimates for…

Numerical Analysis · Mathematics 2019-02-14 Oscar Darwin , Aashraya Jha , Souktik Roy , David Seifert , Rhys Steele , Liam Stigant

We give two weighted norm estimates for higher order commutator of classical operators such as singular integral and fractional type operators, between weighted $L^p$ and certain spaces that include Lipschitz, BMO and Morrey spaces. We also…

Analysis of PDEs · Mathematics 2020-09-29 Gladis Pradolini , Wilfredo Ramos , Jorgelina Recchi

Craig interpolation in SMT is difficult because, e. g., theory combination and integer cuts introduce mixed literals, i. e., literals containing local symbols from both input formulae. In this paper, we present a scheme to compute Craig…

Logic in Computer Science · Computer Science 2017-05-16 Jürgen Christ , Jochen Hoenicke , Alexander Nutz

We establish a general transference principle for the irrationality measure of points with $\mathbb{Q}$-linearly independent coordinates in $\mathbb{R}^{n+1}$, for any given integer $n\geq 1$. On this basis, we recover an important…

Number Theory · Mathematics 2022-02-02 Ngoc Ai Van Nguyen , Anthony Poëls , Damien Roy

In a series of works published in the 1990-s, Kerov put forth various applications of the circle of ideas centred at the Markov moment problem to the limiting shape of random continual diagrams arising in representation theory and spectral…

Probability · Mathematics 2018-01-22 Sasha Sodin

The Empirical Interpolation Method (EIM) is a greedy procedure that constructs approximate representations of two-variable functions in separated form. In its classical presentation, the two variables play a non-symmetric role. In this…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Alexandre Ern , Tony Lelièvre

Krylov subspace methods are widely known as efficient algebraic methods for solving large scale linear systems. However, on massively parallel hardware the performance of these methods is typically limited by communication latency rather…

Numerical Analysis · Computer Science 2018-08-22 Siegfried Cools

This lecture presents recent advances in the theory of errors propagation. We first explain in which cases the propagation of errors may be performed with a first order differential calculus or needs a second order differential calculus.…

Probability · Mathematics 2007-05-23 Nicolas Bouleau

The error between appropriately smooth functions and their radial basis function interpolants, as the interpolation points fill out a bounded domain in R^d, is a well studied artifact. In all of these cases, the analysis takes place in a…

Numerical Analysis · Mathematics 2007-12-02 R. A. Brownlee

The Mayer cluster expansion technique is applied to the Nekrasov instanton partition function of $\mathcal{N}=2$ $SU(N_c)$ super Yang-Mills. The subleading small $\epsilon_2$-correction to the Nekrasov-Shatashvili limiting value of the…

High Energy Physics - Theory · Physics 2016-05-04 Jean-Emile Bourgine , Davide Fioravanti

When a solution to an abstract inverse linear problem on Hilbert space is approximable by finite linear combinations of vectors from the cyclic subspace associated with the datum and with the linear operator of the problem, the solution is…

Functional Analysis · Mathematics 2021-03-01 Noe Angelo Caruso , Alessandro Michelangeli

A general theory for obtaining anisotropic interpolation error estimates for macro-element interpolation is developed revealing general construction principles. We apply this theory to interpolation operators on a macro type of biquadratic…

Numerical Analysis · Mathematics 2014-02-21 Martin Schopf

We first consider the problem of approximating a few eigenvalues of a rational matrix-valued function closest to a prescribed target. It is assumed that the proper rational part of the rational matrix-valued function is expressed in the…

Numerical Analysis · Mathematics 2022-01-10 Rifqi Aziz , Emre Mengi , Matthias Voigt

Bivariate matrix functions provide a unified framework for various tasks in numerical linear algebra, including the solution of linear matrix equations and the application of the Fr\'echet derivative. In this work, we propose a novel…

Numerical Analysis · Mathematics 2018-02-22 Daniel Kressner