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Motivated by energy based analyses for descent methods in the Euclidean setting, we investigate a generalisation of such analyses for descent methods over Riemannian manifolds. In doing so, we find that it is possible to derive…

Optimization and Control · Mathematics 2022-12-13 Vishwak Srinivasan , Ashia Wilson

We study the approximation of operators acting on probability measures on a product space with prescribed marginal. Let $I$ be a label space endowed with a reference measure $\lambda$, and define $\cal M_\lambda$ as the set of probability…

Optimization and Control · Mathematics 2026-03-24 Samy Mekkaoui , Huyên Pham , Xavier Warin

A wide variety of (fixed-point) iterative methods for the solution of nonlinear equations (in Hilbert spaces) exists. In many cases, such schemes can be interpreted as iterative local linearization methods, which, as will be shown, can be…

Numerical Analysis · Mathematics 2019-10-16 Pascal Heid , Thomas P. Wihler

In this paper, we study Riemannian zeroth-order optimization in settings where the underlying Riemannian metric $g$ is geodesically incomplete, and the goal is to approximate stationary points with respect to this incomplete metric. To…

Machine Learning · Computer Science 2026-04-14 Shaocong Ma , Heng Huang

It is known that the De Giorgi's conjecture does not hold in two dimensions for semilinear elliptic equations with a nonzero drift, in general, $$ \Delta u+ q\cdot \nabla u+f(u)=0 \ \ \text{in } \ \ \mathbb R^2, $$ when $q=(0,-c)$ for…

Analysis of PDEs · Mathematics 2019-05-31 Mostafa Fazly

This paper is concerned with the semilinear damped wave equation on a measure space with a self-adjoint operator, instead of the standard Laplace operator. Under a certain decay estimate on the corresponding heat semigroup, we establish the…

Analysis of PDEs · Mathematics 2023-12-21 Masahiro Ikeda , Koichi Taniguchi , Yuta Wakasugi

The traveltime of compressional (P) and shear (S) waves have proven essential in many applications of earthquake and exploration seismology. An accurate and efficient traveltime computation for P and S waves is crucial for the success of…

Computational Physics · Physics 2022-02-09 Ali Can Bekar , Erdogan Madenci , Ehsan Haghighat , Umair bin Waheed , Tariq Alkhalifah

In this article we deal with the stability and convergence of numerical solutions of nonlinear evolution equations of the form $A(u(t))+f(u(t))=u'(t)$, the numerical analysis of solutions to this problems will be performed using some…

Functional Analysis · Mathematics 2010-12-30 Fredy Vides

A general solution for a coupled system of eikonal equations $u_\mu u_\mu =0$, $v_\mu v_\mu =0$, $u_\mu v_\mu =1$ is presented, where lower indices designate derivatives, $\mu=0,1,2,3$, and summation is implied over the repeated indices.…

Mathematical Physics · Physics 2024-12-05 Iryna Yehorchenko

The paper gives a survey of the modern results on elliptic problems on the H\"ormander function spaces. More precisely, elliptic problems are studied on a Hilbert scale of the isotropic H\"ormander spaces parametrized by a real number and a…

Analysis of PDEs · Mathematics 2009-07-19 Vladimir A. Mikhailets , Aleksandr A. Murach

We consider entropy solutions to the eikonal equation $|\nabla u|=1$ in two space dimensions. These solutions are motivated by a class of variational problems and fail in general to have bounded variation. Nevertheless they share with BV…

Analysis of PDEs · Mathematics 2024-11-20 Xavier Lamy , Elio Marconi

This paper presents a numerical approach to the stochastic obstacle problem using the stochastic Galerkin (SG) method. Due to the low regularity of the solution, linear finite elements are employed in both the physical and random variable…

Numerical Analysis · Mathematics 2026-04-29 Chenhui Zhu , Fei Wang , Weimin Han

We provide quantitative weighted estimates for the $L^p(w)$ norm of a maximal operator associated to cube skeletons in $\mathbb{R}^n$. The method of proof differs from the usual in the area of weighted inequalities since there are no…

Classical Analysis and ODEs · Mathematics 2019-03-18 Andrea Olivo , Ezequiel Rela

We present a dual weighted residual-based a posteriori error estimate for a discontinuous Galerkin (DG) approximation of a linear second-order elliptic problem on compact smooth connected and oriented surfaces in $\mathbb{R}^{3}$ which are…

Numerical Analysis · Mathematics 2014-02-11 Andreas Dedner , Pravin Madhavan

Discrete Ginzburg-Landau (DGL) equations with non-local nonlinearities have been established as significant inherently discrete models in numerous physical contexts, similar to their counterparts with local nonlinear terms. We study two…

Analysis of PDEs · Mathematics 2021-10-25 Dirk Hennig , Nikos I. Karachalios

We study generalized solutions of an evolutionary equation related to a densely defined skew-symmetric operator in a real Hilbert space. We establish existence of a contractive semigroup, which provides generalized solutions, and find…

Analysis of PDEs · Mathematics 2025-11-05 Evgeny Yu. Panov

The dynamics of any spherical cosmology with a scalar field (`scalaron') coupling to gravity is described by the nonlinear second-order differential equations for two metric functions and the scalaron depending on the `time' parameter. The…

High Energy Physics - Theory · Physics 2017-04-05 A. T. Filippov

We consider entire solutions to $L u= f(u)$ in $\RR^2$, where $L$ is a general nonlocal operator with kernel $K(y)$. Under certain natural assumtions on the operator $L$, we show that any stable solution is a 1D solution. In particular, our…

Analysis of PDEs · Mathematics 2015-05-27 Xavier Ros-Oton , Yannick Sire

We analyze the relationship between $n$-dimensional conformal metrics and a certain class of partial differential equations (PDEs) that are in duality with the eikonal equation. In particular, we extend the Null Surface Formulation of…

General Relativity and Quantum Cosmology · Physics 2012-06-08 Emanuel Gallo

Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum.…

Machine Learning · Statistics 2011-12-07 Philipp Hennig , Christian J. Schuler
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