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Preservation of quadratic invariants of stochastic differential equations via Runge–Kutta methods
- Source :
- Applied Numerical Mathematics. 87:38-52
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- In this paper, we give conditions for stochastic Runge–Kutta (SRK) methods to preserve quadratic invariants. It is shown that SRK methods preserving quadratic invariants are symplectic. Based on both convergence order conditions and quadratic invariant-preserving conditions, we construct some SRK schemes preserving quadratic invariants with strong and weak convergence order with the help of computer algebra, respectively. Numerical experiments are executed to verify our theoretical analysis and show the superiority of these schemes.
- Subjects :
- Numerical Analysis
Weak convergence
Applied Mathematics
Mathematical analysis
MathematicsofComputing_NUMERICALANALYSIS
Symbolic computation
Computational Mathematics
symbols.namesake
Stochastic differential equation
Runge–Kutta methods
Quadratic equation
Runge–Kutta method
symbols
Applied mathematics
Invariant (mathematics)
Mathematics
Symplectic geometry
Subjects
Details
- ISSN :
- 01689274
- Volume :
- 87
- Database :
- OpenAIRE
- Journal :
- Applied Numerical Mathematics
- Accession number :
- edsair.doi...........6ffb0439dd382b657544578889324f6d