Abstract
We introduce a new method for coarse-graining polymer chains, based on the wavelet transform, a multiresolution data analysis technique. This method, which assigns a cluster of particles to a coarse-grained bead located at the center of mass of the cluster, reduces the complexity of the problem significantly by dividing the simulation into several stages, each with a small fraction of the number of beads in the overall chain. At each stage, we compute the distributions of coarse-grained internal coordinates as well as potential functions required for subsequent simulation stages. We show that, with this wavelet-accelerated Monte Carlo method, coarse-grained Gaussian and self-avoiding random walks can reproduce results obtained from atomistic simulations to a high degree of accuracy in orders of magnitude less time.
Original language | English (US) |
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Pages (from-to) | 897-910 |
Number of pages | 14 |
Journal | Journal of Polymer Science, Part B: Polymer Physics |
Volume | 43 |
Issue number | 8 |
DOIs | |
State | Published - Apr 15 2005 |
Externally published | Yes |
Keywords
- Coarse-graining
- Lattice models
- Molecular modelling
- Monte Carlo simulation
ASJC Scopus subject areas
- Condensed Matter Physics
- Physical and Theoretical Chemistry
- Polymers and Plastics
- Materials Chemistry