Finite Element Error Analysis for Elliptic Parameter Identification with Power-Type Nonlinearity

Abstract. This paper studies the numerical analysis of a parameter identification problem governed by elliptic equations with power-type nonlinearity. We propose a numerical reconstruction via a suitable least-squares minimization problem based on piecewise linear finite elements. As one of our main novelties, we establish conditional stability estimates at the continuous level, which form the theoretical foundation of the present finite element analysis. Our stability analysis relies on tailored analytical tools, including Hardy-type inequalities, fractional Gagliardo–Nirenberg inequalities, and weighted spaces with singular distance weights. By invoking the achieved conditional stability together with the Carstensen quasi-interpolation operator and associated estimates in negative Sobolev spaces, we derive a priori error estimates for the proposed finite element approximation in terms of the mesh size, the regularization parameter, the noise level, and the nonlinearity exponent. Our results extend the recent stability and error estimates for the linear case by Jin et al. [ 26 ] and sharpen their error estimates and convergence order under weaker regularity assumptions.

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Publication Details

Journal
SIAM Journal on Numerical Analysis
Published
2026-10-16
DOI
https://doi.org/10.1137/26m1842646
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.00

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article

Finite Element Error Analysis for Elliptic Parameter Identification with Power-Type Nonlinearity

Irwin Yousept, Yi‐Hsuan Lin, De-Han Chen
SIAM Journal on Numerical Analysis
Numerical methods in inverse problems
article

Finite Element Error Analysis for Elliptic Parameter Identification with Power-Type Nonlinearity

Irwin Yousept, Yi‐Hsuan Lin, De-Han Chen
article en

Abstract

Abstract. This paper studies the numerical analysis of a parameter identification problem governed by elliptic equations with power-type nonlinearity. We propose a numerical reconstruction via a suitable least-squares minimization problem based on piecewise linear finite elements. As one of our main novelties, we establish conditional stability estimates at the continuous level, which form the theoretical foundation of the present finite element analysis. Our stability analysis relies on tailored analytical tools, including Hardy-type inequalities, fractional Gagliardo–Nirenberg inequalities, and weighted spaces with singular distance weights. By invoking the achieved conditional stability together with the Carstensen quasi-interpolation operator and associated estimates in negative Sobolev spaces, we derive a priori error estimates for the proposed finite element approximation in terms of the mesh size, the regularization parameter, the noise level, and the nonlinearity exponent. Our results extend the recent stability and error estimates for the linear case by Jin et al. [ 26 ] and sharpen their error estimates and convergence order under weaker regularity assumptions.

SIAM Journal on Numerical AnalysisVol. 64(5)
National Yang Ming Chiao Tung University (TW), Central China Normal University (CN), University of Duisburg-Essen (DE)
Alexander von Humboldt-Stiftung, Deutsche Forschungsgemeinschaft, Universität Duisburg-Essen, National Science and Technology Council
Openalex Percentile: Top 66%
Numerical methods in inverse problems
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