Computer simulations of multiplicative stochastic differential equations

DOI10.1016/0021-9991(91)90077-XzbMath0714.65107MaRDI QIDQ751229

I. K. Mortimer, Peter D. Drummond

Publication date: 1991

Published in: Journal of Computational Physics (Search for Journal in Brave)

zbMATH Keywords

stabilitystochastic differential equationscomputer simulationsmultiplicative noisesemi-implicit methodKubo oscillatorwhite noise limit

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05) Numerical methods for initial value problems involving ordinary differential equations (65L05) Probabilistic methods, stochastic differential equations (65C99)

Related Items (12)

Robust algorithms for solving stochastic partial differential equations ⋮ Numerical simulations of generalized Langevin equations with deeply asymptotic parameters ⋮ A tractable prescription for large-scale free flight expansion of wavefunctions ⋮ Algorithms for integration of stochastic differential equations using parallel optimized sampling in the Stratonovich calculus ⋮ Simulations of quantum dynamics with fermionic phase-space representations using numerical matrix factorizations as stochastic gauges ⋮ On the numerical discretisation of stochastic oscillators ⋮ Asymptotical mean square stability of an equilibrium point of some linear numerical solutions with multiplicative noise ⋮ Higher-order implicit strong numerical schemes for stochastic differential equations ⋮ Variable-stepsize Runge-Kutta methods for stochastic Schrödinger equations ⋮ Accurate Monte Carlo tests of the stochastic Ginzburg-Landau model with multiplicative colored noise ⋮ Stochastic simulations of fermionic dynamics with phase-space representations ⋮ Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

Cites Work

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• Discretization and simulation of stochastic differential equations
• The Fokker-Planck equation. Methods of solution and applications
• A survey of numerical methods for stochastic differential equations
• Numerical integration of the Langevin equation: Monte Carlo simulation
• On the gap between deterministic and stochastic ordinary differential equations
• Numerical Integration of Multiplicative-Noise Stochastic Differential Equations
• Weak Approximation of Solutions of Systems of Stochastic Differential Equations
• Numerical Integration of Stochastic Differential Equations
• Algorithm 488: A Gaussian pseudo-random number generator
• Numerical Solution of Ito Integral Equations

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