Some quenched and annealed limit theorems of superprocesses in random environments

Abstract: Let $X=(X_t, t\geq 0)$ be a superprocess in a random environment described by a Gaussian noise $W={W(t,x), t\geq 0, x\in \mathbb{R}^d}$ white in time and colored in space with correlation kernel $g(x,y)$. When $d\geq 3$, under the condition that the correlation function $g(x,y)$ is bounded above by some appropriate function $\bar{g}(x-y)$, we present the quenched and annealed Strong Law of Large Numbers and the Central Limit Theorems regarding the weighted occupation measure $\int_0^t X_s ds$ as $t\to \infty$.