Recovery of initial displacement and velocity in anisotropic elastic systems by the time dimensional reduction method

TL;DR

This paper presents a novel time-dimensional reduction method using Legendre polynomial-exponential basis for stable and accurate reconstruction of initial displacement and velocity in anisotropic elastic systems from boundary measurements.

Contribution

It introduces a new spectral time representation and a reduction technique that simplifies the inverse problem, with proven stability and demonstrated numerical effectiveness.

Findings

The method accurately reconstructs initial data in noisy conditions.

The spectral basis enables stable decomposition in time.

Numerical experiments confirm theoretical convergence and robustness.

Abstract

We introduce a time-dimensional reduction method for the inverse source problem in linear elasticity, where the goal is to reconstruct the initial displacement and velocity fields from partial boundary measurements of elastic wave propagation. The key idea is to employ a novel spectral representation in time, using an orthonormal basis composed of Legendre polynomials weighted by exponential functions. This Legendre polynomial-exponential basis enables a stable and accurate decomposition in the time variable, effectively reducing the original space-time inverse problem to a sequence of coupled spatial elasticity systems that no longer depend on time. These resulting systems are solved using the quasi-reversibility method. On the theoretical side, we establish a convergence theorem ensuring the stability and consistency of the regularized solution obtained by the quasi-reversibility method as the noise level tends to zero. On the computational side, two-dimensional numerical experiments confirm the theory and demonstrate the method's ability to accurately reconstruct both the geometry and amplitude of the initial data, even in the presence of substantial measurement noise. The results highlight the effectiveness of the proposed framework as a robust and computationally efficient strategy for inverse elastic source problems.