Turing Bifurcation in the Swift–Hohenberg Equation on Deterministic and Random Graphs

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Georgi S. Medvedev, Dmitry E. Pelinovsky
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引用次数: 0

Abstract

The Swift–Hohenberg equation (SHE) is a partial differential equation that explains how patterns emerge from a spatially homogeneous state. It has been widely used in the theory of pattern formation. Following a recent study by Bramburger and Holzer (SIAM J Math Anal 55(3):2150–2185, 2023), we consider discrete SHE on deterministic and random graphs. The two families of the discrete models share the same continuum limit in the form of a nonlocal SHE on a circle. The analysis of the continuous system, parallel to the analysis of the classical SHE, shows bifurcations of spatially periodic solutions at critical values of the control parameters. However, the proximity of the discrete models to the continuum limit does not guarantee that the same bifurcations take place in the discrete setting in general, because some of the symmetries of the continuous model do not survive discretization. We use the center manifold reduction and normal forms to obtain precise information about the number and stability of solutions bifurcating from the homogeneous state in the discrete models on deterministic and sparse random graphs. Moreover, we present detailed numerical results for the discrete SHE on the nearest-neighbor and small-world graphs.

Abstract Image

确定性和随机图上斯威夫特-霍恩伯格方程的图灵分岔
斯威夫特-霍恩伯格方程(SHE)是一个偏微分方程,用于解释图案如何从空间均匀状态中产生。它被广泛应用于模式形成理论。根据 Bramburger 和 Holzer 的最新研究(SIAM J Math Anal 55(3):2150-2185, 2023),我们考虑了确定性图和随机图上的离散 SHE。这两个离散模型系列具有相同的连续极限,即圆周上的非局部 SHE。对连续系统的分析与对经典 SHE 的分析类似,显示了在控制参数临界值处空间周期解的分岔。然而,离散模型与连续极限的接近并不能保证离散设置在一般情况下发生同样的分岔,因为连续模型的某些对称性在离散化后并不存在。我们利用中心流形还原和正则表达式,获得了关于离散模型在确定性和稀疏随机图上从均匀状态分岔的解的数量和稳定性的精确信息。此外,我们还给出了最近邻图和小世界图上离散 SHE 的详细数值结果。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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