In recent years tamed schemes have become an important technique for simulating SDEs and SPDEs whose continuous coefficients display superlinear growth. The taming method, which involves curbing the growth of the coefficients as a function of stepsize, has so far however not been adapted to preserve the monotonicity of the coefficients. This has arisen as an issue particularly in \cite{articletam}, where the lack of a strongly monotonic tamed scheme forces strong conditions on the setting. In the present work we give a novel and explicit method for truncating monotonic functions in separable Hilbert spaces, and show how this can be used to define a polygonal (tamed) Euler scheme on finite dimensional space, preserving the monotonicity of the drift coefficient. This new method of truncation is well-defined with almost no assumptions and, unlike the well-known Moreau-Yosida regularisation, does not require an optimisation problem to be solved at each evaluation. Our construction is the first infinite dimensional method for truncating monotone functions that we are aware of, as well as the first explicit method in any number of dimensions.
翻译:近些年来,调制方案已成为模拟SDE和SPDE的重要技术,其持续系数显示超线性增长。调制方法涉及抑制系数的增速,作为阶梯化的函数,但迄今为止尚未调整,以保持系数的单调性。这在以下几个方面尤其成为一个问题:cite{arttam},在这个方面,缺乏强烈的单调调制方案,使得环境的设置条件十分困难。在目前的工作中,我们为塞帕利·希尔伯特空间的单调函数提供了新颖和清晰的方法,并展示了如何用这种方法来定义关于有限维度空间的多角(tamed) Euler方案,保持漂移系数的单调性。这种新的调试方法定义得非常清楚,几乎没有假设,与众所周知的Moreau-Yosida正规化方案不同,不需要在每次评估中解决优化问题。我们的构造是用于计算单调数函数的首个无限的维度方法,这是我们所意识到的清晰度方法。