English
Related papers

Related papers: Hadamard Regularization

200 papers

We construct a class of real-valued nonnegative binary functions on a set of jointly distributed random variables, which satisfy the triangle inequality and vanish at identical arguments (pseudo-quasi-metrics). These functions are useful in…

Probability · Mathematics 2016-02-12 Ehtibar N. Dzhafarov , Janne V. Kujala

We prove that any given function can be smoothly approximated by functions lying in the kernel of a linear operator involving at least one fractional component. The setting in which we work is very general, since it takes into account…

Analysis of PDEs · Mathematics 2018-10-22 Alessandro Carbotti , Serena Dipierro , Enrico Valdinoci

The aim of this work is to develop a global calculus for pseudo-differential operators acting on suitable algebras of generalized functions. In particular, a condition of global hypoellipticity of the symbols gives a result of regularity…

Analysis of PDEs · Mathematics 2007-05-23 Claudia Garetto

We characterize microlocal regularity of Colombeau generalized functions by an appropriate extension of the classical notion of micro-ellipticity to pseudodifferential operators with slow scale generalized symbols. Thus we obtain an…

Analysis of PDEs · Mathematics 2007-05-23 Claudia Garetto , Guenther Hoermann

Given cell-average data values of a piecewise smooth bivariate function $f$ within a domain $\Omega$, we look for a piecewise adaptive approximation to $f$. We are interested in an explicit and global (smooth) approach. Bivariate…

Numerical Analysis · Mathematics 2022-01-27 Sergio Amat , David Levin , Juan Ruiz-Alvarez , Dionisio F. Yáñez

In this paper, we first define a discrete version of the fractional Laplace operator $(-\Delta)^{s}$ through the heat semigroup on a stochastically complete, connected, locally finite graph $G = (V, E, \mu, w)$. Secondly, we define the…

Analysis of PDEs · Mathematics 2025-06-10 Mengjie Zhang , Yong Lin , Yunyan Yang

Neural networks are versatile tools for computation, having the ability to approximate a broad range of functions. An important problem in the theory of deep neural networks is expressivity; that is, we want to understand the functions that…

Machine Learning · Computer Science 2021-08-16 Khashayar Filom , Konrad Paul Kording , Roozbeh Farhoodi

The final goal of the present work is to extend the Fourier transform on the Heisenberg group $\H^d,$ to tempered distributions. As in the Euclidean setting, the strategy is to first show that the Fourier transform is an isomorphism on the…

Functional Analysis · Mathematics 2017-05-08 Hajer Bahouri , Jean-Yves Chemin , Raphael Danchin

We establish pointwise formulas for the shape derivative of solutions to the Dirichlet problem associated with the fractional Laplacian. Specifically, we consider the equation $(-\Delta)^s u = h$ in $\Omega$ and $u=0$ in $\Omega^c$, where…

Analysis of PDEs · Mathematics 2026-02-10 Sidy M. Djitte , Franck Sueur

It is strange but fruitful to think about the functions as random processes. Any function can be viewed as a martingale (in many different ways) with discrete time. But it can be useful to have continuous time too. Processes can emulate…

Probability · Mathematics 2011-06-21 Alexander Volberg

By means of several examples, we motivate that universal properties are the simplest way to solve a given mathematical problem, explaining in this way why they appear everywhere in mathematics. In particular, we present the co-universal…

Functional Analysis · Mathematics 2024-04-25 Djamel eddine Kebiche , Paolo Giordano

This is a tutorial introduction to the functional analysis mathematics needed in many physical problems, such as in waves in continuous media. Functional analysis takes us beyond finite matrices, allowing us to work with infinite sets of…

Functional Analysis · Mathematics 2019-04-15 David A. B. Miller

We consider the behaviour of holomorphic functions on a bounded open subset of the plane, satisfying a Lipschitz condition with exponent $\alpha$, with $0<\alpha<1$, in the vicinity of an exceptional boundary point where all such functions…

Complex Variables · Mathematics 2017-01-04 Anthony G. O'Farrell

In this paper, we solve certain Fermat-type partial differential-difference equations for finite order entire functions of several complex variables. These results are significant generalizations of some earlier findings, especially those…

Complex Variables · Mathematics 2024-12-30 Hong Yan Xu , Rajib Mandal , Raju Biswas

This paper introduces a new functional expansion framework that extends classical ideas beyond the Taylor series. Unlike traditional Taylor expansions based on local polynomial approximations, the proposed approach arises from exact…

Numerical Analysis · Mathematics 2026-02-03 Junping Wang

Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of large systems. To date, DPFT has been applied mainly to quantum…

Materials Science · Physics 2023-04-21 Martin-Isbjörn Trappe , William C. Witt , Sergei Manzhos

We study Hadamard variation of eigenvalues of Laplacian with respect to general domain perturbations. We show their existence up to the second order rigorously and characterize the derivatives, using associated eigenvalue problems in finite…

Spectral Theory · Mathematics 2024-06-06 Takashi Suzuki , Takuya Tsuchiya

Partition functions of certain classes of "spin glass" models in statistical physics show strong connections to combinatorial graph invariants. Also known as homomorphism functions they allow for the representation of many such invariants,…

Computational Complexity · Computer Science 2010-04-08 Marc Thurley

In this paper we briefly review the main idea of the localization technique and its extension suitable in supersymmetric gauge field theory. We analyze the partition function of the vector multiplets with supercharges and its blocks on the…

High Energy Physics - Theory · Physics 2021-01-25 A. A. Bytsenko , M. Chaichian , A. E. Gonçalves

The Feynman-Kac equations are a type of partial differential equations describing the distribution of functionals of diffusive motion. The probability density function (PDF) of Brownian functionals satisfies the Feynman-Kac formula, being a…

Computational Physics · Physics 2015-02-03 Weihua Deng , Minghua Chen , Eli Barkai
‹ Prev 1 3 4 5 6 7 10 Next ›