A quasi-random walk method for one-dimensional reaction–diffusion equations

2003 ◽  
Vol 62 (3-6) ◽  
pp. 487-494 ◽  
Author(s):  
S. Ogawa ◽  
C. Lécot
Keyword(s):  
Random Walk ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
One Dimensional ◽  
Random Walk Method

Generic properties of equilibria of reaction-diffusion equations with variable diffusion

1985 ◽  
Vol 101 (1-2) ◽  
pp. 45-55 ◽  
Author(s):  
Carlos Rocha
Keyword(s):  
Parabolic Equations ◽  
Neumann Boundary ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
Equilibrium Solutions ◽  
Generic Properties ◽  
One Dimensional ◽  
Variable Diffusion ◽  
Node Type

SynopsisIt is shown that, generically, scalar one-dimensional parabolic equations ut = (a2(x)ux)x + f(u), x ∈ [0, 1], with Neumann boundary conditions, have all the equilibrium solutions hyperbolic.Moreover, the bifurcations of these equilibria are generically of the saddle-node type.

A stochastic simulation for solving scalar reaction–diffusion equations

1990 ◽  
Vol 22 (01) ◽  
pp. 88-100
Author(s):  
B. Chauvin ◽  
Rouault
Keyword(s):  
Monte Carlo ◽  
Limit Theorem ◽  
Branching Processes ◽  
Martingale Problem ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
Convergence Problem ◽  
One Dimensional ◽  
Spaces Of Measures

A recent Monte Carlo method for solving one-dimensional reaction–diffusion equations is considered here as a convergence problem for a sequence of spatial branching processes with interaction. The martingale problem is studied and a limit theorem is proved by embedding spaces of measures in Sobolev spaces.

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