Physics
Scientific paper
May 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001phrvl..86.4741q&link_type=abstract
Physical Review Letters, vol. 86, Issue 21, pp. 4741-4744
Physics
3
Scientific paper
We show a new approach for solving the N-body problems based on neural networks. Without loss of generality, we derived a network solution for the time-dependent positions of N bodies in self-gravitating systems. The simulation is limited to a system of collisionless disks-a case for determining the spatial distributions of dark matter and in reproducing global effects such as formation of spiral galaxies. Our approach yields a solution that is analytic with time-reversed path-tracing capabilities that could lead to new findings in the study of the collective behavior of N-body systems.
Monterola Christopher
Quito Marcelino
Saloma Caesar
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