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The main goal of this work is to study an averaging principle for two-time-scales stochastic partial differential equations with jumps. The solutions of reduced equations with modified coefficients are derived to approximate the slow component of the original equation under suitable conditions. It is shown that the slow component can strongly converge to the solution of the corresponding reduced equation in the pth-mean. Our key and novel idea is how to cope with the changes caused by jumps and higher order moments.

Strong convergence in the pth-mean of an averaging principle for two-time-scales SPDEs with jumps