NANASep 20, 2016

A New Family of Regularized Kernels for the Harmonic Oscillator

arXiv:1407.11081 citations
Originality Synthesis-oriented
AI Analysis

Provides a new kernel family for N-body simulations, but the improvement is incremental and domain-specific.

The paper introduces a two-parameter family of regularized kernels for N-body simulations, enabling high-order time stepping. Numerical experiments demonstrate improved accuracy over standard kernels.

In this paper, a new two-parameter family of regularized kernels is introduced, suitable for applying high-order time stepping to N-body systems. These high-order kernels are derived by truncating a Taylor expansion of the non-regularized kernel about $(r^2+ε^2)$, generating a sequence of increasingly more accurate kernels. This paper proves the validity of this two-parameter family of regularized kernels, constructs error estimates, and illustrates the benefits of using high-order kernels through numerical experiments.

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