Stochastic Runge-Kutta Methods with Deterministic High Order for Ordinary Differential Equations
Yoshio Komori, Evelyn Buckwar, Theodore E. Simos, George Psihoyios, Ch. Tsitouras, Zacharias Anastassi
Abstract
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Yoshio Komori, Evelyn Buckwar, Theodore E. Simos, George Psihoyios, Ch. Tsitouras, Zacharias Anastassi
Abstract
Open-access reader
Our aim is to show that the embedding of deterministic Runge-Kutta methods with higher order than necessary order to achieve a weak order can enrich the properties of stochastic Runge-Kutta methods with respect to not only practical errors but also stability. This will be done through the comparisons between our new schemes and an efficient weak second order scheme with minimized error constant proposed by Debrabant and Robler (2009).
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Our aim is to show that the embedding of deterministic Runge-Kutta methods with higher order than necessary order to achieve a weak order can enrich the properties of stochastic Runge-Kutta methods with respect to not only practical errors but also stability. This will be done through the comparisons between our new schemes and an efficient weak second order scheme with minimized error constant proposed by Debrabant and Robler (2009).
Key concepts: Runge–Kutta methods, Embedding, Ordinary differential equation, Order (exchange), Constant (computer programming), Applied mathematics, Stability (learning theory), Stochastic differential equation