Numerical Identification of Nonlocal Potentials in Aggregation

Numerical Identification of Nonlocal Potentials in Aggregation

Year:    2022

Author:    Yuchen He, Sung Ha Kang, Wenjing Liao, Hao Liu, Yingjie Liu

Communications in Computational Physics, Vol. 32 (2022), Iss. 3 : pp. 638–670

Abstract

Aggregation equations are broadly used to model population dynamics with nonlocal interactions, characterized by a potential in the equation. This paper considers the inverse problem of identifying the potential from a single noisy spatial-temporal process. The identification is challenging in the presence of noise due to the instability of numerical differentiation. We propose a robust model-based technique to identify the potential by minimizing a regularized data fidelity term, and regularization is taken as the total variation and the squared Laplacian. A split Bregman method is used to solve the regularized optimization problem. Our method is robust to noise by utilizing a Successively Denoised Differentiation technique. We consider additional constraints such as compact support and symmetry constraints to enhance the performance further. We also apply this method to identify time-varying potentials and identify the interaction kernel in an agent-based system. Various numerical examples in one and two dimensions are included to verify the effectiveness and robustness of the proposed method.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2021-0177

Communications in Computational Physics, Vol. 32 (2022), Iss. 3 : pp. 638–670

Published online:    2022-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    33

Keywords:    Aggregation equation nonlocal potential PDE identification Bregman iteration operator splitting.

Author Details

Yuchen He

Sung Ha Kang

Wenjing Liao

Hao Liu

Yingjie Liu

  1. WeakIdent: Weak formulation for identifying differential equation using narrow-fit and trimming

    Tang, Mengyi | Liao, Wenjing | Kuske, Rachel | Kang, Sung Ha

    Journal of Computational Physics, Vol. 483 (2023), Iss. P.112069

    https://doi.org/10.1016/j.jcp.2023.112069 [Citations: 4]
  2. Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

    He, Yuchen | Kang, Sung Ha | Liao, Wenjing | Liu, Hao | Liu, Yingjie

    Journal of Computational Physics, Vol. 494 (2023), Iss. P.112526

    https://doi.org/10.1016/j.jcp.2023.112526 [Citations: 0]