## Abstract

Numerical integration of Newton's equation in multiple dimensions plays an important role in many fields such as biochemistry and astrophysics. Currently, some of the most important practical questions in these areas cannot be addressed because the large dimensionality of the variable space and complexity of the required force evaluations precludes integration over sufficiently large time intervals. Improving the efficiency of algorithms for this purpose is therefore of great importance. Standard numerical integration schemes (e.g., leap-frog and Runge-Kutta) ignore the special structure of Newton's equation that, for conservative systems, constrains the force to be the gradient of a scalar potential. We propose a new class of "spatial interpolation" (SI) integrators that exploit this property by interpolating the force in space rather than (as with standard methods) in time. Since the force is usually a smoother function of space than of time, this can improve algorithmic efficiency and accuracy. In particular, an SI integrator solves the one-and two-dimensional harmonic oscillators exactly with one force evaluation per step. A simple type of time-reversible SI algorithm is described and tested. Significantly improved performance is achieved on one-and multi-dimensional benchmark problems.

Original language | English |
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Pages (from-to) | 87-100 |

Number of pages | 14 |

Journal | Journal of Computational Physics |

Volume | 129 |

Issue number | 1 |

DOIs | |

State | Published - Nov 1996 |

Externally published | Yes |

### Bibliographical note

Funding Information:We thank Dr. Alex Ulitsky for many helpful conversations and his help in developing the time-reversible three-point interpolation. This work was supported by NIH Grant GM48874, AFOSR Grant F49620, the Cornell Theory Center, and by the Technion V.P.R. fund.

## ASJC Scopus subject areas

- Numerical Analysis
- Modeling and Simulation
- Physics and Astronomy (miscellaneous)
- General Physics and Astronomy
- Computer Science Applications
- Computational Mathematics
- Applied Mathematics