Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2001-01-22
Physics
Condensed Matter
Disordered Systems and Neural Networks
submitted to J. Comput. Phys
Scientific paper
A fast algorithm to study one-dimensional self-gravitating systems, and, more generally, systems that are Lagrangian integrable between collisions, is presented. The algorithm is event-driven, and uses a heap-ordered set of predicted future events. In the limit of large number of particles $N$, the operation count is dominated by the cost of reordering the heap after each event, which goes asymptotically as $\log N$. Some applications are discussed in detail.
Aurell Erik
Fanelli Duccio
Noullez Alain
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