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Lexing Ying   

  1. Department of Mathematics, Stanford University, Stanford, CA 94305, USA
  • Received:2022-07-26 Revised:2022-11-02 Published:2023-03-14
  • Supported by:
    This work is partially supported by NSF Grant No. DMS 2011699.

Lexing Ying. ANNEALED IMPORTANCE SAMPLING FOR ISING MODELS WITH MIXED BOUNDARY CONDITIONS[J]. Journal of Computational Mathematics, 2023, 41(3): 526-534.

This note introduces a method for sampling Ising models with mixed boundary conditions. As an application of annealed importance sampling and the Swendsen-Wang algorithm, the method adopts a sequence of intermediate distributions that keeps the temperature fixed but turns on the boundary condition gradually. The numerical results show that the variance of the sample weights is relatively small.

CLC Number: 

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