On large deviations for small noise It\^o processes
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🧮 math.PR
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largedeviationnoisesmallapplicationsapproachassumptionscertain
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The large deviation principle in the small noise limit is derived for solutions of possibly degenerate It\^o stochastic differential equations with predictable coefficients, which may depend also on the large deviation parameter. The result is established under mild assumptions using the Dupuis-Ellis weak convergence approach. Applications to certain systems with memory and to positive diffusions with square-root-like dispersion coefficient are included.
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