Analysis of a splitting method for stochastic balance laws

Abstract

We analyze a semi-discrete splitting method for conservation laws driven by a semilinear noise term. Making use of fractional $BV$ estimates, we show that the splitting method produces a compact sequence of approximate solutions converging to the exact solution, as the time step $\Delta t\to 0$. Under the assumption of a homogenous noise function, and thus the availability of $BV$ estimates, we provide an $L^1$ error estimate. Bringing into play a generalization of Kruzkov's entropy condition, permitting the "Kruzkov constants" to be Malliavin differentiable random variables, we establish an $L^1$ convergence rate of order $\frac{1}{3}$ in $\Delta t$.

References in corpus (2)

• Scalar conservation laws with stochastic forcing
• On Nonlinear Stochastic Balance Laws