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Abstract
This paper focuses on inverse problems arising in studying multi-population aggregations. The goal is to reconstruct the diffusion coefficient, advection coefficient, and interaction kernels of the aggregation system, which characterize the dynamics of different populations. In the theoretical analysis of the physical setup, it is crucial to ensure non-negativity of solutions. To address this, we employ the high-order variation method and introduce modifications to the systems. Additionally, we propose a novel approach called transformative asymptotic technique that enables the recovery of the diffusion coefficient preceding the Laplace operator, presenting a pioneering method for this type of problems. Through these techniques, we offer comprehensive insights into the unique identifiability aspect of inverse problems associated with multi-population aggregation models.
© 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
© 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
| Original language | English |
|---|---|
| Pages (from-to) | 94-124 |
| Journal | Journal of Differential Equations |
| Volume | 414 |
| Online published | 10 Sept 2024 |
| DOIs | |
| Publication status | Published - 5 Jan 2025 |
Funding
The research was supported by the Hong Kong RGC General Research Funds (No. 11311122, 11304224 and 11300821), the NSFC/RGC Joint Research Scheme (No. N_CityU101/21), and the ANR/RGC Joint Research Scheme (No. A_CityU203/19).
Research Keywords
- High-order variation method
- Inverse multi-population aggregation model
- Positive solutions
- Transformative asymptotic technique
- Unique identifiability
RGC Funding Information
- RGC-funded
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