SDEs

SDEs

Supersymmetric Theory of Stochastics:Demystification of Self-Organized Criticality

Published in Christos H. Skiadas, Charilaos Skiadas, Handbook of Applications of Chaos Theory, 2017

Among all the classes of mathematical models, stochastic (partial) (integro-) differential equations (SDEs) have the widest applicability in modern science. For example, SDEs describe all natural dynamical systems (DSs) above the scale of quantum degeneracy/coherence because (i) time is continuous in nature (above the Planck scale) and (ii) no natural DS can be completely isolated from the stochastic influence of its environment. In quantum models, on the other hand, SDEs are often used as additional tools.

Euler-Maruyama and Kloeden-Platen-Schurz computing paradigm for stochastic vector-borne plant epidemic model

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Journal Information

Published in Waves in Random and Complex Media, 2023

Nabeela Anwar, Iftikhar Ahmad, Adiqa Kausar Kiani, Muhammad Shoaib, Muhammad Asif Zahoor Raja

Stochastic differential equation (SDE) refers to a differential equation in which some of its terms and solutions are stochastic processes [53]. SDEs are used in a variety of applications, including optimal stopping, filtering problems, stochastic control, stochastic methods to deterministic ordinary differential equations (ODEs) models, and finance [54–57].

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Supersymmetric Theory of Stochastics:Demystification of Self-Organized Criticality

Euler-Maruyama and Kloeden-Platen-Schurz computing paradigm for stochastic vector-borne plant epidemic model