Implementing Few-Body Algorithmic Regularization with Post-Newtonian Terms
Seppo Mikkola, David Merritt

TL;DR
This paper introduces AR-CHAIN, a new regularization algorithm for simulating gravitational few-body systems, capable of handling post-Newtonian terms and extreme mass ratios with improved simplicity and performance.
Contribution
The paper presents AR-CHAIN, a novel regularization scheme that incorporates post-Newtonian terms up to 2.5 order, allowing for more accurate and flexible simulations of complex gravitational systems.
Findings
AR-CHAIN performs comparably or better than existing schemes.
It allows zero mass particles, unlike previous methods.
Application to S stars shows realistic orbital evolution.
Abstract
We discuss the implementation of a new regular algorithm for simulation of the gravitational few-body problem. The algorithm uses components from earlier methods, including the chain structure, the logarithmic Hamiltonian, and the time-transformed leapfrog. This algorithmic regularization code, AR-CHAIN, can be used for the normal N-body problem, as well as for problems with softened potentials and/or with velocity-dependent external perturbations, including post-Newtonian terms, which we include up to order PN2.5. Arbitrarily extreme mass ratios are allowed. Only linear coordinate transformations are used and thus the algorithm is somewhat simpler than many earlier regularized schemes. We present the results of performance tests which suggest that the new code is either comparable in performance or superior to the existing regularization schemes based on the Kustaanheimo-Stiefel (KS)…
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