Backward diffusion-wave problem: stability, regularization and approximation

TL;DR

This paper develops and analyzes numerical schemes for the backward diffusion-wave problem involving fractional derivatives, addressing stability, regularization for noisy data, and providing error estimates with practical implications.

Contribution

It introduces a regularization method for the ill-posed backward diffusion-wave problem and proposes a fully discrete scheme with error bounds for both smooth and nonsmooth data.

Findings

Existence, uniqueness, and stability under certain conditions.

Convergence of the regularized solution with noisy data.

Error bounds guiding discretization and regularization choices.

Abstract

We aim at the development and analysis of the numerical schemes for approximately solving the backward diffusion-wave problem, which involves a fractional derivative in time with order $\alpha\in(1,2)$. From terminal observations at two time levels, i.e., $u(T_1)$ and $u(T_2)$, we simultaneously recover two initial data $u(0)$ and $u_t(0)$ and hence the solution $u(t)$ for all $t > 0$. First of all, existence, uniqueness and Lipschitz stability of the backward diffusion-wave problem were established under some conditions about $T_1$ and $T_2$. Moreover, for noisy data, we propose a quasi-boundary value scheme to regularize the "mildly" ill-posed problem, and show the convergence of the regularized solution. Next, to numerically solve the regularized problem, a fully discrete scheme is proposed by applying finite element method in space and convolution quadrature in time. We establish error bounds of the discrete solution in both cases of smooth and nonsmooth data. The error estimate is very useful in practice since it indicates the way to choose discretization parameters and regularization parameter, according to the noise level. The theoretical results are supported by numerical experiments.