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A framework for reconstruction of optical diffusion and absorption coefficients in quantitative photoacoustic tomography is presented. This framework is based on a Tikhonov-type functional with a regularization term promoting sparsity of…

Optimization and Control · Mathematics 2024-02-01 Anwesa Dey , Alfio Borzi , Souvik Roy

We consider the problem of making nonparametric inference in a class of multi-dimensional diffusions in divergence form, from low-frequency data. Statistical analysis in this setting is notoriously challenging due to the intractability of…

Methodology · Statistics 2025-01-23 Matteo Giordano , Sven Wang

This paper is concerned with the question of reconstructing a vector in a finite-dimensional complex Hilbert space when only the magnitudes of the coefficients of the vector under a redundant linear map are known. We present new…

Functional Analysis · Mathematics 2015-03-06 Radu Balan

In this paper, we present a unified approach to function approximation in reproducing kernel Hilbert spaces (RKHS) that establishes a previously unrecognized optimality property for several well-known function approximation techniques, such…

Statistics Theory · Mathematics 2013-01-08 Richard J. Barton

In this paper we develop theoretical analysis and numerical reconstruction techniques for the solution of an inverse boundary value problem dealing with the nonlinear, time-dependent monodomain equation, which models the evolution of the…

Analysis of PDEs · Mathematics 2017-01-27 Elena Beretta , Cecilia Cavaterra , Maria Cristina Cerutti , Andrea Manzoni , Luca Ratti

In this paper, we consider a class of structured nonsmooth fractional minimization, where the first part of the objective is the ratio of a nonnegative nonsmooth nonconvex function to a nonnegative nonsmooth convex function, while the…

Optimization and Control · Mathematics 2025-12-25 Junpeng Zhou , Na Zhang , Qia Li

We formulate and analyse an optimal control problem for the coagulation-fragmentation equation, where a scalar, time-dependent control modulates the coagulation rate by multiplying the coagulation kernel. The objective functional consists…

Optimization and Control · Mathematics 2026-04-16 Enrico Sartor

We explore the mathematical and numerical aspects of reconstructing a potential energy profile of a molecular bond from its rupture time distribution. While reliable reconstruction of gross attributes, such as the height and the width of an…

Statistical Mechanics · Physics 2015-05-18 Pak-Wing Fok , Tom Chou

This paper is concerned with an inverse problem of recovering a potential term and fractional order in a one-dimensional subdiffusion problem, which involves a Djrbashian-Caputo fractional derivative of order $\alpha\in(0,1)$ in time, from…

Analysis of PDEs · Mathematics 2021-09-22 Bangti Jin , Zhi Zhou

In this article, we are concerned with the analysis on the numerical reconstruction of the spatial component in the source term of a time-fractional diffusion equation. This ill-posed problem is solved through a stabilized nonlinear…

Numerical Analysis · Mathematics 2020-05-06 Daijun Jiang , Yikan Liu , Dongling Wang

We consider the inverse problem of reconstructing an effective model for a prototypical diffusion process in strongly heterogeneous media based on coarse measurements. The approach is motivated by quasi-local numerical effective forward…

Numerical Analysis · Mathematics 2020-05-05 Alfonso Caiazzo , Roland Maier , Daniel Peterseim

In this article we study inverse problems of recovering a space-time dependent source component from the lateral boundary observation in a subidffusion model. The mathematical model involves a Djrbashian-Caputo fractional derivative of…

Numerical Analysis · Mathematics 2021-05-19 Bangti Jin , Yavar Kian , Zhi Zhou

This contribution extends the localized training approach, traditionally employed for multiscale problems and parameterized partial differential equations (PDEs) featuring locally heterogeneous coefficients, to the class of linear, positive…

Numerical Analysis · Mathematics 2024-04-30 Christian Engwer , Mario Ohlberger , Lukas Renelt

We consider a (sub)diffusion equation with a nonlinearity of the form $pf(u)-qu$, where $p$ and $q$ are space dependent functions. Prominent examples are the Fisher-KPP, the Frank-Kamenetskii-Zeldovich and the Allen-Cahn equations. We…

Numerical Analysis · Mathematics 2026-02-02 Barbara Kaltenbacher , William Rundell

Block-coordinate algorithms are recognized to furnish efficient iterative schemes for addressing large-scale problems, especially when the computation of full derivatives entails substantial memory requirements and computational efforts. In…

Optimization and Control · Mathematics 2025-04-16 Pedro Pérez-Aros , David Torregrosa-Belén

Recovering high-dimensional statistical structure from limited measurements is a fundamental challenge in hyperspectral imaging, where capturing full-resolution data is often infeasible due to sensor, bandwidth, or acquisition constraints.…

Image and Video Processing · Electrical Eng. & Systems 2025-08-01 Jonathan Monsalve , Kumar Vijay Mishra

We consider the inverse problem of the simultaneous reconstruction of the dielectric permittivity and magnetic permeability functions of the Maxwell's system in 3D with limited boundary observations of the electric field. The theoretical…

Numerical Analysis · Mathematics 2015-12-03 Larisa Beilina , Michel Cristofol , Kati Niinimäki

We study a numerical reconstruction strategy for the potential in the fractional Calder\'on problem from a single partial exterior measurement. The forward model is the fractional Schr\"odinger equation in a bounded domain, with prescribed…

Numerical Analysis · Mathematics 2026-03-30 Mukul Dwivedi , Jesse Railo , Andreas Rupp

This paper presents a stochastic block-coordinate proximal Newton method for minimizing the sum of a blockwise Lipschitz-continuously differentiable function and a separable nonsmooth convex function. At each iteration, the method randomly…

Optimization and Control · Mathematics 2026-03-25 Hong Zhu , Xun Qian

Making the gradients small is a fundamental optimization problem that has eluded unifying and simple convergence arguments in first-order optimization, so far primarily reserved for other convergence criteria, such as reducing the…

Optimization and Control · Mathematics 2021-01-29 Jelena Diakonikolas , Puqian Wang