Persistent Homology Classifies Parameter Dependence of Patterns in Turing Systems. [PDF]
Spector R, Harrington HA, Gaffney EA.
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Using Floquet theory to unravel far-from equilibrium dynamics in reaction-diffusion systems. [PDF]
Juma VO +3 more
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Emergent stable tissue shapes from the regulatory feedback between morphogens and cell growth. [PDF]
Kaity B, Lobo D.
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Stabilising spatiotemporal dynamics of mussel-algae coupled map lattices model via proportional-differential control. [PDF]
Zhu Y +4 more
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Exploring potential of Turing pattern classification through convolution maps. [PDF]
Shin J, Park J, Ji M, Lee S.
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Semantic Algorithmic Information Theory: From Kolmogorov Complexity to Semantic Equivalence. [PDF]
Wu J, Wang S, Niu K, She Y, Zhang P.
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Turing-patterned Ta<sub>2</sub>S<sub>3</sub> enables sub-2 nm diffusion barrier for advanced Cu interconnects. [PDF]
Tian X +15 more
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Numerical analysis & modelling in the life sciences: a topical collection in honor of Ezio Venturino. [PDF]
Bulai IM, Cavoretto R, De Rossi A.
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Widening the criteria for emergence of Turing patterns
The classical concept for emergence of Turing patterns in reaction–diffusion systems requires that a system should be composed of complementary subsystems, one of which is unstable and diffuses sufficiently slowly while the other one is stable and diffuses sufficiently rapidly. In this work, the phenomena of emergence of Turing patterns are studied and
Maxim Kuznetsov, Andrey Polezhaev
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