Automatic Code Generation for Stochastic Runge–Kutta Methods

Abstract

In this paper we consider in detail the realization of Runge–Kutta stochastic numerical methods with weak and strong convergence for systems of stochastic differential equations in Ito form. The algorithm for generating the Wiener stochastic process, the algorithm for approximation of Ito stochastic integrals, and the code generation algorithms for numerical schemes are described. Python and Julia languages are used. The Jinja2 template engine is used for the code generation.

Type
Publication
Proceedings of the Selected Papers of the 8th International Conference “Information and Telecommunication Technologies and Mathematical Modeling of High-Tech Systems” (ITTMM-2018), Moscow, Russia, April 16, 2018