Minimum Relaxation N-body Simulations Using Orthogonal Series Force Computation

This report describes a modiication of the orthogonal function Poisson solver for n-body simulations that minimizes relaxation caused by small particle number uctuations. With the standard algorithm, the noise leading to relaxation can be reduced by making the expansion basis similar to the particle distribution and by carefully choosing the maximum order in the expansion. The proposed algorithm accomplishes both tasks simultaneously while the simulation is running. This procedure is asymptotically equivalent to expanding in an orthogonal series which is matched to the distribution to start and truncating at low order. Because the modiied algorithm adapts to a time-evolving distribution, it has advantage over a xed basis. The required changes to the standard algorithm are minor and do not aaect its overall structure or scalability. Tests show that the overhead in CPU time is small in practical applications. The decrease in relaxation rate is demonstrated for both axisymmetric and non-axisymmetric systems and the robustness of the algorithm is demonstrated by following the evolution of unstable generalized polytropes. Finally, the empirically based moment analysis which leads to the uncorrelated basis is an ideal tool for investigating structure and modes in n-body simulations and an example is provided.