Multi-operator iterative regularization framework for caputo-Hadamard fractional diffusion with environmental applications

Le Dinh Long

doi:10.1016/j.chaos.2025.117556

Multi-operator iterative regularization framework for caputo-Hadamard fractional diffusion with environmental applications

2025-11-15

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Behrouz Parsa Moghaddam *

DOI：10.1016/j.chaos.2025.117556

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Abstract

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• Novel framework resolves Caputo-Hadamard inverse problems optimally. • Method establishes new benchmark for fractional inverse source problems. • Spectral analysis reveals 20-fold conditioning improvement over standards. • Memory effects alter remediation timeframes by factors of 2–5 critically. • Superlinear rates achieve optimal reconstruction across noise spectrum. • Framework bridges rigorous theory with environmental engineering practice.

Multi-operator iterative regularization framework for caputo-Hadamard fractional diffusion with environmental applications

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