Javascript must be enabled to continue!
An error-controlled fast multipole method
View through CrossRef
We present a two-stage error estimation scheme for the fast multipole method (FMM). This scheme can be applied to any particle system. It incorporates homogeneous as well as inhomogeneous distributions. The FMM error as a consequence of the finite representation of the multipole expansions and the operator error is correlated with an absolute or relative user-requested energy threshold. Such a reliable error control is the basis for making reliable simulations in computational physics. Our FMM program on the basis of the two-stage error estimation scheme is available on request.
Title: An error-controlled fast multipole method
Description:
We present a two-stage error estimation scheme for the fast multipole method (FMM).
This scheme can be applied to any particle system.
It incorporates homogeneous as well as inhomogeneous distributions.
The FMM error as a consequence of the finite representation of the multipole expansions and the operator error is correlated with an absolute or relative user-requested energy threshold.
Such a reliable error control is the basis for making reliable simulations in computational physics.
Our FMM program on the basis of the two-stage error estimation scheme is available on request.
Related Results
Corrected Article: “An error-controlled fast multipole method” [J. Chem. Phys. 131, 244102 (2009)]
Corrected Article: “An error-controlled fast multipole method” [J. Chem. Phys. 131, 244102 (2009)]
We present a two-stage error estimation scheme for the fast multipole method (FMM). This scheme can be applied to any particle system. It incorporates homogeneous as well as inhomo...
Fast Fourier Transforms in Electromagnetics
Fast Fourier Transforms in Electromagnetics
This Chapter review the fast Fourier transform (FFT) technique and its application to computational electromagnetics, especially to the fast solver algorithms including the Conjuga...
Dynamic stochastic modeling for inertial sensors
Dynamic stochastic modeling for inertial sensors
Es ampliamente conocido que los modelos de error para sensores inerciales tienen dos componentes: El primero es un componente determinista que normalmente es calibrado por el fabri...
Linear Regression to Minimize the Total Error of the Numerical Differentiation
Linear Regression to Minimize the Total Error of the Numerical Differentiation
AbstractIt is well known that numerical derivative contains two types of errors. One is truncation error and the other is rounding error. By evaluating variables with rounding erro...
A CUDA fast multipole method with highly efficient M2L far field evaluation
A CUDA fast multipole method with highly efficient M2L far field evaluation
Solving an N-body problem, electrostatic or gravitational, is a crucial task and the main computational bottleneck in many scientific applications. Its direct solution is an ubiqui...
Some Factors Analyzing of Blowout During Well Drilling Operation
Some Factors Analyzing of Blowout During Well Drilling Operation
Abstract
The 25 cases of oil well blowout, which happened in the oil field in China from 1962 to 1993[1], were analyzed. some conclusions about the factors relate...
Global component analysis of errors in five satellite-only global precipitation estimates
Global component analysis of errors in five satellite-only global precipitation estimates
Abstract. Revealing the error components for satellite-only precipitation products (SPPs) can help algorithm developers and end-users substantially understand their error features ...

