Regularized Reconstruction of Scalar Parameters in Subdiffusion with Memory via a Nonlocal Observation

Fuente: arXiv
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Main Authors: Hulianytskyi, Andrii, Pereverzyev, Sergei, Siryk, Sergii, Vasylyeva, Nataliya
Format: Preprint
Published: 2025
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author Hulianytskyi, Andrii
Pereverzyev, Sergei
Siryk, Sergii
Vasylyeva, Nataliya
author_facet Hulianytskyi, Andrii
Pereverzyev, Sergei
Siryk, Sergii
Vasylyeva, Nataliya
contents In the paper, we propose an analytical and numerical approach to identify scalar parameters (coefficients, orders of fractional derivatives) in the multi-term fractional differential operator in time, $\mathbf{D}_t$. To this end, we analyze inverse problems with an additional nonlocal observation related to a linear subdiffusion equation $\mathbf{D}_{t}u-\mathcal{L}_{1}u-\mathcal{K}*\mathcal{L}_{2}u=g(x,t),$ where $\mathcal{L}_{i}$ are the second order elliptic operators with time-dependent coefficients, $\mathcal{K}$ is a summable memory kernel, and $g$ is an external force. Under certain assumptions on the given data in the model, we derive explicit formulas for unknown parameters. Moreover, we discuss the issues concerning to the uniqueness and the stability in these inverse problems. At last, by employing the Tikhonov regularization scheme with the quasi-optimality approach, we give a computational algorithm to recover the scalar parameters from a noisy discrete measurement and demonstrate the effectiveness (in practice) of the proposed technique via several numerical tests.
format Preprint
id arxiv_https___arxiv_org_abs_2511_05277
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Regularized Reconstruction of Scalar Parameters in Subdiffusion with Memory via a Nonlocal Observation
Hulianytskyi, Andrii
Pereverzyev, Sergei
Siryk, Sergii
Vasylyeva, Nataliya
Analysis of PDEs
Numerical Analysis
In the paper, we propose an analytical and numerical approach to identify scalar parameters (coefficients, orders of fractional derivatives) in the multi-term fractional differential operator in time, $\mathbf{D}_t$. To this end, we analyze inverse problems with an additional nonlocal observation related to a linear subdiffusion equation $\mathbf{D}_{t}u-\mathcal{L}_{1}u-\mathcal{K}*\mathcal{L}_{2}u=g(x,t),$ where $\mathcal{L}_{i}$ are the second order elliptic operators with time-dependent coefficients, $\mathcal{K}$ is a summable memory kernel, and $g$ is an external force. Under certain assumptions on the given data in the model, we derive explicit formulas for unknown parameters. Moreover, we discuss the issues concerning to the uniqueness and the stability in these inverse problems. At last, by employing the Tikhonov regularization scheme with the quasi-optimality approach, we give a computational algorithm to recover the scalar parameters from a noisy discrete measurement and demonstrate the effectiveness (in practice) of the proposed technique via several numerical tests.
title Regularized Reconstruction of Scalar Parameters in Subdiffusion with Memory via a Nonlocal Observation
topic Analysis of PDEs
Numerical Analysis
url https://arxiv.org/abs/2511.05277