2013
DOI: 10.1002/cpa.21495
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Approximating Rough Stochastic PDEs

Abstract: We study approximations to a class of vector‐valued equations of Burgers type driven by a multiplicative space‐time white noise. A solution theory for this class of equations has been developed recently in Probability Theory Related Fields by Hairer and Weber. The key idea was to use the theory of controlled rough paths to give definitions of weak/mild solutions and to set up a Picard iteration argument. In this article the limiting behavior of a rather large class of (spatial) approximations to these equation… Show more

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Cited by 32 publications
(47 citation statements)
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“…Studying this issue in general is an extremely difficult task and goes beyond the scope of this paper. Similar questions have been addressed in the past in the context of the Allen-Cahn or the stochastic Ginzburg-Landau equations in relation to stochastic quantization [31,32], with very appealing new results in larger dimensions [33,34]. Therefore, with this in mind, we consider the simplest turbulent systems that exhibit random transitions between multiple coexisting attractors.…”
mentioning
confidence: 74%
“…Studying this issue in general is an extremely difficult task and goes beyond the scope of this paper. Similar questions have been addressed in the past in the context of the Allen-Cahn or the stochastic Ginzburg-Landau equations in relation to stochastic quantization [31,32], with very appealing new results in larger dimensions [33,34]. Therefore, with this in mind, we consider the simplest turbulent systems that exhibit random transitions between multiple coexisting attractors.…”
mentioning
confidence: 74%
“…The statement given here is actually slightly stronger than the bound stated in [1] because the norm appearing on the left hand side of (2) is bounded uniformly in t instead of allowing a blow up near 0. In [1] we had to introduce this blowup due to a slightly modified definition of the Gaussian process X : the process used in [1] does not start at 0, but with stationary initial condition, which was convenient for other reasons.…”
Section: R θ (T; X Y) := δ˜ θ (T; X Y) −θ(T X) δX (T; X Y)mentioning
confidence: 71%
“…In [1] we had to introduce this blowup due to a slightly modified definition of the Gaussian process X : the process used in [1] does not start at 0, but with stationary initial condition, which was convenient for other reasons. When going through the proof given in [1], one realises that when considering the process with zero initial condition, one can apply bound (3.74) for all times t and there is no need to use (3.75) for small times. Based on this version of Lemma 1, it is then straightforward to use the a priori information on the time regularity of R θ , combined with the fact that the "tilde" processes coincide with the "non-tilde" processes before time τ , to obtain the bound E R …”
Section: R θ (T; X Y) := δ˜ θ (T; X Y) −θ(T X) δX (T; X Y)mentioning
confidence: 99%
“…The reasons for not doing so are that the integral is well-defined without it and that non-geometric situations can arise naturally in the context of numerical approximations, see for example [HM10,HMW12].…”
Section: Remark 34mentioning
confidence: 99%