Statistical parameter identification of mixed-mode patterns from a single experimental snapshot
Parameter identification in pattern formation models from a single experimental snapshot is challenging, as traditional methods often require knowledge of initial conditions or transient dynamics-data that are frequently unavailable in experimental settings. In this study, we extend the recently dev...
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| Main Authors: | , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
15 December 2025
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| In: |
Journal of computational physics
Year: 2025, Volume: 543, Pages: 1-19 |
| ISSN: | 1090-2716 |
| DOI: | 10.1016/j.jcp.2025.114384 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.jcp.2025.114384 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S0021999125006667 
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| Author Notes: | Alexey Kazarnikov, Robert Scheichl, Irving R. Epstein, Heikki Haario, Anna Marciniak-Czochra |
| Summary: | Parameter identification in pattern formation models from a single experimental snapshot is challenging, as traditional methods often require knowledge of initial conditions or transient dynamics-data that are frequently unavailable in experimental settings. In this study, we extend the recently developed statistical approach, Correlation Integral Likelihood (CIL) method to enable robust parameter identification from a single snapshot of an experimental pattern. Using the chlorite-iodite-malonic acid (CIMA) reaction - a well-studied system that produces Turing patterns - as a test case, we address key experimental challenges such as measurement noise, model-data discrepancies, and the presence of mixed-mode patterns, where different spatial structures (e.g., coexisting stripes and dots) emerge under the same conditions. Numerical experiments demonstrate that our method accurately estimates model parameters, even with incomplete or noisy data. This approach lays the groundwork for future applications in developmental biology, chemical reaction modelling, and other systems with heterogeneous output. |
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| Item Description: | Online verfügbar: 25. September 2025, Artikelversion: 7. Oktober 2025 Gesehen am 23.03.2026 |
| Physical Description: | Online Resource |
| ISSN: | 1090-2716 |
| DOI: | 10.1016/j.jcp.2025.114384 |