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This work presents a methodology for reconstructing the spatial distribution of the neutron flux in a nuclear reactor, leveraging real-time measurements obtained from ex-core detectors. The Kirchhoff-Helmholtz (K-H) equation inherently…

Numerical Analysis · Mathematics 2025-05-20 Roberto Ponciroli

This paper develops a novel mathematical framework for collaborative learning by means of geometrically inspired kernel machines which includes statements on the bounds of generalisation and approximation errors, and sample complexity. For…

We perform numerical experiments on the Serre-Green-Naghdi (SGN) equations and a fully dispersive "Whitham-Green-Naghdi" (WGN) counterpart in dimension 1. In particular, solitary wave solutions of the WGN equations are constructed and their…

Analysis of PDEs · Mathematics 2024-09-05 Vincent Duchêne , Christian Klein

We consider the sine-Gordon equation in laboratory coordinates in the quarter plane. The first part of the paper considers the construction of solutions via Riemann-Hilbert techniques. In addition to constructing solutions starting from…

Analysis of PDEs · Mathematics 2018-03-28 Lin Huang , Jonatan Lenells

Current methods for stochastic hyperparameter learning in Gaussian Processes (GPs) rely on approximations, such as computing biased stochastic gradients or using inducing points in stochastic variational inference. However, when using such…

Machine Learning · Computer Science 2025-08-29 Neta Shoham , Haim Avron

The boundary supersymmetric sinh-Gordon model is an integrable quantum field theory in 1+1 dimensions with bulk N=1 supersymmetry, whose bulk and boundary S matrices are not diagonal. We present an exact solution of this model. In…

High Energy Physics - Theory · Physics 2009-10-31 Changrim Ahn , Rafael I. Nepomechie

The notion of reproducing kernel Hilbert space (RKHS) has emerged in system identification during the past decade. In the resulting framework, the impulse response estimation problem is formulated as a regularized optimization defined on an…

Systems and Control · Electrical Eng. & Systems 2022-04-19 Mohammad Khosravi , Roy S. Smith

We present a unified method of construction of surfaces associated with Grassmannian sigma models, expressed in terms of an orthogonal projector. This description leads to compact formulae for structural equations of two-dimensional…

Differential Geometry · Mathematics 2007-05-23 A. M. Grundland , L. Snobl

We consider a Urysohn integral operator $\mathcal{K}$ with kernel of the type of Green's function. For $r \geq 1$, a space of piecewise polynomials of degree $\leq r-1 $ with respect to a uniform partition is chosen to be the approximating…

Numerical Analysis · Mathematics 2021-10-26 Gobinda Rakshit , Akshay S. Rane , Kshitij Patil

A framework for coherent pattern extraction and prediction of observables of measure-preserving, ergodic dynamical systems with both atomic and continuous spectral components is developed. It is based on an approximation of the generator of…

Dynamical Systems · Mathematics 2021-03-18 Dimitrios Giannakis , Suddhasattwa Das , Joanna Slawinska

This is a survey of the author's recent work rather than a broad survey of the literature. The survey is concerned with the global in time solutions of the Cauchy problem for matter waves propagating in the curved spacetimes, which can be,…

Analysis of PDEs · Mathematics 2013-05-21 Karen Yagdjian

The kernel herding algorithm is used to construct quadrature rules in a reproducing kernel Hilbert space (RKHS). While the computational efficiency of the algorithm and stability of the output quadrature formulas are advantages of this…

Numerical Analysis · Mathematics 2022-07-18 Kazuma Tsuji , Ken'ichiro Tanaka

In this paper, we design a new iterative algorithm for solving pseudomonotone equilibrium problems in real Hilbert spaces. The advantage of our algorithm is that it requires only one strongly convex programming problem at each iteration.…

Optimization and Control · Mathematics 2018-04-06 Nguyen The Vinh

In this article, we extend the framework developed in \cite{unbounded_domain_cadiot} to allow for rigorous proofs of existence of smooth, localized solutions in semi-linear partial differential equations possessing both space and non-space…

Analysis of PDEs · Mathematics 2026-01-19 Dominic Blanco , Matthieu Cadiot

This work deals with the influence of the gravitational field produced by a charged and rotating black hole (Kerr-Newman spacetime) on massive scalar fields. We obtain an exact solution of the Klein-Gordon equation in this spacetime, which…

General Relativity and Quantum Cosmology · Physics 2014-01-24 V. B. Bezerra , H. S. Vieira , André A. Costa

The aim of this paper is to introduce the Inverse Scattering Method for later studies of some problems in nonlinear dynamics, and describe the kink solution of the Sine Gordon Equation using the Inverse Scattering Method as a methodological…

Exactly Solvable and Integrable Systems · Physics 2018-03-23 Matej Hudak , Jana Tothova , Ondrej Hudak

We conduct a comprehensive analysis of the large-space and long-time asymptotics of kink-soliton gases in the sine-Gordon (sG) equation, addressing an important open problem highlighted in the recent work [Phys. Rev. E 109 (2024) 061001].…

Exactly Solvable and Integrable Systems · Physics 2025-01-08 Guoqiang Zhang , Weifang Weng , Zhenya Yan

We present a novel methodology for the numerical solution of problems of diffraction by infinitely thin screens in three dimensional space. Our approach relies on new integral formulations as well as associated high-order quadrature rules.…

Analysis of PDEs · Mathematics 2015-06-11 Oscar P. Bruno , Stephane K. Lintner

In this paper we consider a Robin problem for the Klein-Gordon equation in a doubly connected domain. The solution domain considered is a bounded smooth doubly connected planar domain bounded by two simple disjoint closed curves. The…

Numerical Analysis · Mathematics 2017-03-02 Myroslav Kryven

Stochastic Gradient Descent (SGD) is a known stochastic iterative method popular for large-scale convex optimization problems due to its simple implementation and scalability. Some objectives, such as those found in complex-valued neural…

Machine Learning · Computer Science 2026-05-26 Natanael Alpay , Emeric Battaglia
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