## Some properties of superprocesses under a stochastic flow.(English)Zbl 1171.60011

Summary: For a superprocess under a stochastic flow in one dimension, we prove that it has a density with respect to the Lebesgue measure. A stochastic partial differential equation is derived for the density. The regularity of the solution is then proved by using Krylov’s $$L_p$$-theory for linear SPDE.

### MSC:

 60G57 Random measures 60H15 Stochastic partial differential equations (aspects of stochastic analysis) 60J80 Branching processes (Galton-Watson, birth-and-death, etc.)
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### References:

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