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A Monte Carlo method to sample a Stratification

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GCS - Geometry, compatibility and structure preservation in computational differential equations

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds, that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their equilibrium distribution, and there are several methods to sample subject to fixed constraints. We introduce a Monte Carlo method to handle the case when constraints can break and form. Abstractly, the method samples a probability distribution on a stratification: a collection of manifolds of different dimensions, where the lower-dimensional manifolds lie on the boundaries of the higher-dimensional manifolds. We show several applications in polymer physics, self-assembly of colloids, and volume calculation.

This talk is part of the Isaac Newton Institute Seminar Series series.

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