Large Deviation Principle for Mild Solutions of Stochastic Evolution Equations with Multiplicative L\'{e}vy Noise

We demonstrate the large deviation principle in the small noise limit for the mild solution of stochastic evolution equations with monotone nonlinearity. A recently developed method, weak convergent method, has been employed in studying the large deviations. we have used essentially the main result of Budhiraja et al., [4] which discloses the variational representation of exponential integrals w.r.t. the L'{e}vy noise. An It^{o}-type inequality is a main tool in our proofs. Our framework covers a wide range of semilinear parabolic, hyperbolic and delay differential equations. We give some examples to illustrate the applications of the results.