Convergence and regularity of probability laws by using an interpolation method

Abstract

In [18] Fournier and Printems establish a methodology which allows to prove the absolute continuity of the law of the solution of some stochastic equations with Hölder continuous coefficients. This is of course out of reach by using already classical probabilistic methods based on Malliavin calculus. In [11] Debussche and Romito employ some Besov space technics in order to substantially improve the result of Fournier and Printems. In our paper we show that this kind of problem naturally fits in the framework of interpolation spaces: we prove an interpolation inequality (see Proposition 2.5) which allows to state (and even to slightly improve) the above absolute continuity result. Moreover it turns out that the above interpolation inequality has applications in a completely different framework: we use it in order to estimate the error in total variance distance in some convergence theorems.

arXiv admin note: text overlap with arXiv:1211.0052

References in corpus (3)

• Smoothness and asymptotic estimates of densities for SDEs with locally smooth coefficients and applications to square root-type diffusions
• Finiteness of entropy for the homogeneous Boltzmann equation with measure initial condition
• On the distance between probability density functions

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• Arbitrary order total variation Convergence of Markov semigroups using random grids
• Regularity of Wiener functionals under a Hörmander type condition of order one