Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A reduced-order modeling of pattern formations (2403.03632v2)

Published 6 Mar 2024 in math.AP, cs.NA, and math.NA

Abstract: Chemical and biochemical reactions can exhibit a wide range of complex behaviors, including multiple steady states, oscillatory patterns, and chaotic dynamics. These phenomena have captivated researchers for many decades. Notable examples of oscillating chemical systems include the Briggs--Rauscher, Belousov--Zhabotinskii, and Bray--Liebhafsky reactions, where periodic variations in concentration are often visualized through observable color changes. These systems are typically modeled by a set of partial differential equations coupled through nonlinear interactions. Upon closer analysis, it appears that the dynamics of these chemical/biochemical reactions may be governed by only a finite number of spatial Fourier modes. We can also draw the same conclusion in fluid dynamics, where it has been shown that, over long periods, the fluid velocity is determined by a finite set of Fourier modes, referred to as determining modes. In this article, we introduce the concept of determining modes for a two-species chemical models, which covers models such as the Brusselator, the Gray-Scott model, and the Glycolysis model \cite{ashkenazi1978spatial,segel1980mathematical}. We demonstrate that it is indeed sufficient to characterize the dynamic of the model using only a finite number of spatial Fourier modes.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (15)
  1. F. Boyer and P. Fabrie. Mathematical tools for the study of the incompressible Navier-Stokes equations and related models, volume 183 of Applied Mathematical Sciences. Springer, New York, 2013.
  2. I. D. Chueshov. A remark on sets of determining elements for reaction-diffusion systems. Math. Notes, 63(5):679–687, 1998.
  3. Asymptotic analysis of the Navier-Stokes equations. Phys. D, 9(1-2):157–188, 1983.
  4. Navier-Stokes equations and turbulence, volume 83 of Encycl. Math. Appl. Cambridge: Cambridge University Press, paperback reprint of the hardback edition 2001 edition, 2008.
  5. C. Foiaş and R. Temam. Determination of the solutions of the Navier-Stokes equations by a set of nodal values. Math. Comput., 43:117–133, 1984.
  6. Determining finite volume elements for the 2D Navier–Stokes equations. Physica D: Nonlinear Phenomena, 60(1):165–174, 1992.
  7. Upper bounds on the number of determining modes, nodes, and volume elements for the Navier-Stokes equations. Indiana Univ. Math. J., 42:875–887, 1993.
  8. V. Kalantarov and E. Titi. Global stabilization of the Navier-Stokes-voight and the damped nonlinear wave equations by finite number of feedback controllers. Discrete Contin. Dyn. Syst., Ser. B, 23:1325–1345, 2018.
  9. J. P. Keener. Biology in time and space. A partial differential equation modeling approach, volume 50 of Pure Appl. Undergrad. Texts. Providence, RI: American Mathematical Society (AMS), 2021.
  10. R. Kumar Upadhyay and S. R. K. Iyengar. Spatial dynamics and pattern formation in biological populations. Boca Raton, FL: CRC Press, 2021.
  11. A priori bounds for reaction-diffusion systems arising in chemical and biological dynamics. Appl. Math. Comput., 163(1):1–16, 2005.
  12. B. Perthame. Parabolic equations in biology. Growth, reaction, movement and diffusion. Lect. Notes Math. Model. Life Sci. Cham: Springer, 2015.
  13. A. Turing. The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London B, 237:37–72, 1952.
  14. J. Wei and M. Winter. Mathematical aspects of pattern formation in biological systems, volume 189 of Appl. Math. Sci. London: Springer, 2014.
  15. V. Zucatti and W. Wolf. Data-driven closure of projection-based reduced order models for unsteady compressible flows. Comput. Methods Appl. Mech. Eng., 386:29, 2021. Id/No 114120.

Summary

We haven't generated a summary for this paper yet.