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To compute the spatially distributed dielectric constant from the backscattering data, we study a coefficient inverse problem for a 1D hyperbolic equation. To solve the inverse problem, we establish a new version of Carleman estimate and…

Numerical Analysis · Mathematics 2021-04-26 Michael V. Klibanov , Thuy T. Le , Loc H. Nguyen , Anders Sullivan , Lam Nguyen

Since the pioneering work of Canham and Helfrich, variational formulations involving curvature-dependent functionals, like the classical Willmore functional, have proven useful for shape analysis of biomembranes. We address minimizers of…

Analysis of PDEs · Mathematics 2012-07-24 Rustum Choksi , Marco Veneroni

A new convenient method of describing flat convex compact sets is proposed. It generalizes classical trigonometric functions $\sin$ and $\cos$. Apparently, this method may be very useful for explicit description of solutions of optimal…

Optimization and Control · Mathematics 2020-05-01 L. V. Lokutsievskiy

The divergence minimization problem plays an important role in various fields. In this note, we focus on differentiable and strictly convex divergences. For some minimization problems, we show the minimizer conditions and the uniqueness of…

Information Theory · Computer Science 2020-01-30 Tomohiro Nishiyama

We show that in the two-dimensional case, every objective, isotropic and isochoric energy function which is rank-one convex on $\mathrm{GL}^+(2)$ is already polyconvex on $\mathrm{GL}^+(2)$. Thus we negatively answer Morrey's conjecture in…

Analysis of PDEs · Mathematics 2019-09-04 Robert J. Martin , Ionel-Dumitrel Ghiba , Patrizio Neff

In this paper we study certain variational aspects of the volume product functional restricted to the space of small projective deformations of a fixed convex body. In doing so, we provide a short proof of a theorem by Klartag: a strong…

Metric Geometry · Mathematics 2023-04-03 Florent Balacheff , Gil Solanes , Kroum Tzanev

In this short note we prove the convexity of minimizers of some variational problem in the Gauss space. This proof is based on a geometric version of an older argument due to Korevaar.

Analysis of PDEs · Mathematics 2011-10-27 Michael Goldman

Minimax problems are notoriously challenging to optimize. However, we present that the two-timescale extragradient method can be a viable solution. By utilizing dynamical systems theory, we show that it converges to points that satisfy the…

Optimization and Control · Mathematics 2024-04-23 Jiseok Chae , Kyuwon Kim , Donghwan Kim

The paper studies continutity of Moser nonlinearity in two dimensions with respect to weak convergence. Unlike the critical nonlinearity in the Sobolev inequality, which lacks weak continuity at any point, Moser functional fails to be…

Analysis of PDEs · Mathematics 2013-04-02 Adimurthi , Kyril Tintarev

We prove minimax theorems for lower semicontinuous functions defined on a Hilbert space. The main tool is the theory of $\Phi$-convex functions and sufficient and necessary conditions for the minimax equality to hold for $\Phi$-convex…

Optimization and Control · Mathematics 2016-06-29 Ewa M. Bednarczuk , Monika Syga

The scalar potential of the two-Higgs-doublet model (2HDM) may have more than one local minimum and the usually considered vacuum could be located at one of them that could decay to another. This paper studies the condition that the usually…

High Energy Physics - Phenomenology · Physics 2017-08-02 Xun-Jie Xu

We consider the analogue of Rayleigh's conjecture for the clamped plate in Euclidean space weighted by a log-convex density. We show that the lowest eigenvalue of the bi-Laplace operator with drift in a given domain is bounded below by a…

Spectral Theory · Mathematics 2018-11-16 L. M. Chasman , Jeffrey J Langford

We introduce a new class of asymptotic contractions that employs two quasi-metrics defined directly in terms of the underlying mapping. The contraction condition compares these two quantities via a sequence of bounding functions that…

Functional Analysis · Mathematics 2026-04-20 Jie Shi

Given a convex set $C$ in a real vector space $E$ and two points $x,y\in C$, we investivate which are the possible values for the variation $f(y)-f(x)$, where $f:C\longrightarrow [m,M]$ is a bounded convex function. We then rewrite the…

Optimization and Control · Mathematics 2015-03-18 Joon Kwon

Aim of this paper is to discuss convergence of pointed metric measure spaces in absence of any compactness condition. We propose various definitions, show that all of them are equivalent and that for doubling spaces these are also…

Metric Geometry · Mathematics 2017-05-17 Nicola Gigli , Andrea Mondino , Giuseppe Savaré

In this paper, we generalize the chance optimization problems and introduce constrained volume optimization where enables us to obtain convex formulation for challenging problems in systems and control. We show that many different problems…

Optimization and Control · Mathematics 2017-02-01 Ashkan Jasour , Constantino Lagoa

A complete classification of continuous, dually epi-translation invariant, and rotation equivariant valuations on convex functions is established. This characterizes the recently introduced functional Minkowski vectors, which naturally…

Metric Geometry · Mathematics 2025-04-24 Mohamed A. Mouamine , Fabian Mussnig

This paper concerns the study of a broad class of minimal time functions corresponding to control problems with constant convex dynamics and closed target sets in arbitrary Banach spaces. In contrast to other publications, we do not impose…

Optimization and Control · Mathematics 2010-09-09 Boris Mordukhovich , Nguyen Mau Nam

Characterizing the solution sets in a problem by closedness under operations is recognized as one of the key aspects of algorithm development, especially in constraint satisfaction. An example from the Boolean satisfiability problem is that…

Data Structures and Algorithms · Computer Science 2024-01-15 Kei Kimura , Kazuhisa Makino , Shota Yamada , Ryo Yoshizumi

On Euclidean and Hilbert spaces, Riemannian manifolds, and CAT$(0)$-spaces, gradient flows of convex functions are known to satisfy the contraction property, which plays a fundamental role in optimization theory and possesses fruitful…

Optimization and Control · Mathematics 2025-07-21 Shin-ichi Ohta