This article addresses the inference of physics models from data, from the perspectives of
inverse problems and model reduction. These fields develop formulations that integrate data …

In this paper, we analyze space-time finite element methods for the numerical solution of
distributed parabolic optimal control problems with energy regularization in the Bochner …

Optimal control problems with partial differential equations as constraints play an important
role in many applications. The inclusion of bound constraints for the state variable poses a …

Interior point methods provide an attractive class of approaches for solving linear, quadratic
and nonlinear programming problems, due to their excellent efficiency and wide …

Preconditioning for Krylov methods often relies on operator theory when mesh independent
estimates are looked for. The goal of this paper is to contribute to the long development of …

PDE-constrained optimization aims at finding optimal setups for partial differential equations
so that relevant quantities are minimized. Including nonsmooth L 1 sparsity promoting terms …

In this paper we describe the efficient solution of a partial differential equation (PDE)-
constrained optimization problem subject to the time-periodic heat equation. We propose a …

Hessian preconditioners are the key to efficient numerical solution of large-scale distributed
parameter PDE-constrained inverse problems with highly informative data. Such inverse …

In this paper, we develop a new central finite difference scheme in terms of both time and
space for solving the first-order necessary optimality systems that characterize the optimal …

Control constrained parabolic optimal control problems are generally challenging, from
either theoretical analysis or algorithmic design perspectives. Conceptually, the well-known …