Abstract
In this interdisciplinary research we apply the tools of algorithmic complexity theory to three important non-equilibrium growth models that are used in statistical physics. Much of the insight into these models has been derived by numerical simulation; it is important to develop good parallel algorithms for them. Eden growth, solidon-solid growth and ballistic deposition are all seemingly highly sequential processes. However, we are able to provide algorithms for the models that run in time O(log2 N) using a polynomial number of processors on a randomized CREW P-RAM, where N is the system size. In addition to their potential practical value, our algorithms serve to classify these growth models as less complex than other growth models, such as diffusion-limited aggregation, for which fast parallel algorithms probably do not exist.
This research was partially funded by the National Science Foundation Grant CCR-9209184.
This research was partially funded by the National Science Foundation Grant DMR-9311580.
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© 1994 Springer-Verlag Berlin Heidelberg
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Greenlaw, R., Machta, J. (1994). The parallel complexity of eden growth, solid-on-solid growth and ballistic deposition. In: van Leeuwen, J. (eds) Algorithms — ESA '94. ESA 1994. Lecture Notes in Computer Science, vol 855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0049429
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DOI: https://doi.org/10.1007/BFb0049429
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