### Abstract

Original language | English |
---|---|

Article number | Volume 87 |

Pages (from-to) | 145 |

Number of pages | 156 |

Journal | Applied Numerical Mathematics |

Volume | 87 |

Issue number | 1 |

Early online date | 30 Oct 2014 |

Publication status | Published - 1 Jan 2015 |

### Fingerprint

### Keywords

- Parasitism, starting method

### Cite this

*Applied Numerical Mathematics*,

*87*(1), 145. [Volume 87].

**An iterative starting method to control parasitism for the Leapfrog method.** / Hill, Adrian; Norton, Terence.

Research output: Contribution to journal › Article

*Applied Numerical Mathematics*, vol. 87, no. 1, Volume 87, pp. 145.

}

TY - JOUR

T1 - An iterative starting method to control parasitism for the Leapfrog method

AU - Hill, Adrian

AU - Norton, Terence

PY - 2015/1/1

Y1 - 2015/1/1

N2 - The Leapfrog method is a time–symmetric multistep method, widely used to solve the Euler equations and other Hamiltonian systems, due to its low cost and geometric properties. A drawback with Leapfrog is that it suffers from parasitism. This paper describes an iterative starting method, which may be used to reduce to machine precision the size of the parasitic components in the numerical solution at the start of the computation. The severity of parasitic growth is also a function of the differential equation, the main method and the time–step. When the tendency to parasitic growth is relatively mild, computational results indicate that using this iterative starting method may significantly increase the time–scale over which parasitic effects remain acceptably small. Using an iterative starting method, Leapfrog is applied to the cubic Schrödinger equation. The computational results show that the Hamiltonian and soliton behaviour are well–preserved over long time-scales.

AB - The Leapfrog method is a time–symmetric multistep method, widely used to solve the Euler equations and other Hamiltonian systems, due to its low cost and geometric properties. A drawback with Leapfrog is that it suffers from parasitism. This paper describes an iterative starting method, which may be used to reduce to machine precision the size of the parasitic components in the numerical solution at the start of the computation. The severity of parasitic growth is also a function of the differential equation, the main method and the time–step. When the tendency to parasitic growth is relatively mild, computational results indicate that using this iterative starting method may significantly increase the time–scale over which parasitic effects remain acceptably small. Using an iterative starting method, Leapfrog is applied to the cubic Schrödinger equation. The computational results show that the Hamiltonian and soliton behaviour are well–preserved over long time-scales.

KW - Parasitism, starting method

M3 - Article

VL - 87

SP - 145

JO - Applied Numerical Mathematics

JF - Applied Numerical Mathematics

SN - 0168-9274

IS - 1

M1 - Volume 87

ER -