Randomized trial investigates recovering a potential coefficient in a nonlinear inverse problem, indicating potential advancements in mathematical models.
This paper investigates a nonlinear inverse problem in a time fractional diffusion-wave equation, in which a spatially varying potential coefficient is recovered from noisy final-time measurements. A local uniqueness result for the inverse problem is first established in a finite-dimensional admissible space. To support the reconstruction, the Fréchet derivative of the forward map and its adjoint representation are derived to provide the gradient information required in the inversion procedure. A Banach space regularization scheme with a combined L1 and L2 penalty is then proposed to stabilize the nonlinear inverse problem, and the resulting nonsmooth minimization problem is solved by a locally linearized split Bregman iterative scheme. Numerical experiments in one and two spatial dimensions demonstrate the accuracy and stability of the proposed method for smooth, corner-type, localized, and discontinuous coefficient profiles.
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Xian et al. (2026) studied this question.
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