From mesoscale back to microscale: reconstruction schemes for coarse-grained stochastic lattice systems

Trashorras, José and Tsagkarogiannis, Dimitrios K (2010) From mesoscale back to microscale: reconstruction schemes for coarse-grained stochastic lattice systems. SIAM Journal on Numerical Analysis, 48 (5). pp. 1647-1677. ISSN 0036-1429

[img]
Preview
PDF - Published Version
Download (410kB) | Preview

Abstract

Starting from a microscopic stochastic lattice spin system and the corresponding coarse-grained model we introduce a mathematical strategy to recover microscopic information given the coarse-grained data. We define “reconstructed” microscopic measures satisfying two conditions: (i) they are close in specific relative entropy to the initial microscopic equilibrium measure conditioned on the coarse-grained, data, and (ii) their sampling is computationally advantageous when compared to sampling directly from the conditioned microscopic equilibrium measure. By using different techniques we consider the cases of both short and long range microscopic models.

Item Type: Article
Keywords: coarse-graining, microscopic reconstruction, Monte Carlo simulation, parallel computing, lattice spin systems, Gibbs measure, cluster expansion
Schools and Departments: School of Mathematical and Physical Sciences > Mathematics
Subjects: Q Science > QA Mathematics > QA0297 Numerical analysis
Depositing User: Dimitrios Tsagkarogiannis
Date Deposited: 17 Sep 2013 09:50
Last Modified: 03 Jul 2019 00:46
URI: http://sro.sussex.ac.uk/id/eprint/46292

View download statistics for this item

📧 Request an update