A stochastic simulation for solving scalar reaction–diffusion equations

1990 ◽  
Vol 22 (1) ◽  
pp. 88-100 ◽  
Author(s):  
B. Chauvin ◽  
Rouault

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.

1990 ◽  
Vol 22 (01) ◽  
pp. 88-100
Author(s):  
B. Chauvin ◽  
Rouault

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.


Author(s):  
Carlos Rocha

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.


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