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Sampling biased lattice configurations using exponential metrics
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Proceedings of the Nineteenth Annual ACM -SIAM Symposium on Discrete Algorithms table of contents
New York, New York
Pages 76-85  
Year of Publication: 2009
Authors
Sam Greenberg  Georgia Institute of Technology, Atlanta GA
Amanda Pascoe  Georgia Institute of Technology, Atlanta GA
Dana Randall  Georgia Institute of Technology, Atlanta GA
Publisher
Society for Industrial and Applied Mathematics  Philadelphia, PA, USA
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ABSTRACT

Monotonic surfaces spanning finite regions of Zd arise in many contexts, including DNA-based self-assembly, card-shuffling and lozenge tilings. We explore how we can sample these surfaces when the distribution is biased to favor higher surfaces. We show that a natural local chain is rapidly mixing with any bias for regions in Z2, and for bias λ > d2 in Zd, when d > 2. Moreover, our bounds on the mixing time are optimal on d-dimensional hyper-cubic regions. The proof uses a geometric distance function and introduces a variant of path coupling in order to handle distances that are exponentially large.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Sam Greenberg: colleagues
Amanda Pascoe: colleagues
Dana Randall: colleagues