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Curvature Motion Perturbed by a Direction-Dependent Colored Noise

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Stochastic Partial Differential Equations and Related Fields (SPDERF 2016)

Abstract

The aim of this paper is twofold. First we give a brief overview of several results on the deterministic and stochastic motions by mean curvature and their derivation under the so-called sharp interface limit. Then, we study the motions by mean curvature perturbed by a direction-dependent Gaussian colored noise described by \(V=\kappa + \dot{W}(t,\mathbf n )\). This part is a generalization of (Funaki, Acta Math Sin (Engl Ser), 15:407–438, 1999) [10] where the noise is independent from space. We derive a uniform moment estimate on solutions of approximating equations and prove a Wong–Zakai type convergence theorem (in law) for the SPDEs for the curvature of a convex curve in two-dimensional space before the time the curve exhibits a singularity.

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Acknowledgements

We thank the referee who suggested the proof of Theorem 1, in particular, the SPDE (26) and the reference [5]. We acknowledge the support from the training course at ENS Cachan, under which C. Denis could visit Tokyo and stayed for four months in 2016.

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Correspondence to Tadahisa Funaki .

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Denis, C., Funaki, T., Yokoyama, S. (2018). Curvature Motion Perturbed by a Direction-Dependent Colored Noise. In: Eberle, A., Grothaus, M., Hoh, W., Kassmann, M., Stannat, W., Trutnau, G. (eds) Stochastic Partial Differential Equations and Related Fields. SPDERF 2016. Springer Proceedings in Mathematics & Statistics, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-319-74929-7_9

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