Simulating Level-set Percolation on the Discrete Gaussian Free Field with Arbitrary Conductances

Using a Conjugate Gradient Sampler

Bachelor thesis (2021)

Authors

P. Keer Applied Sciences

Contributors

A. Cipriani Applied Probability - EEMCS (supervisor 1)
J.M. Thijssen QN/Thijssen Group - AS (supervisor 1)
W.G.M. Groenevelt Analysis - EEMCS (supervisor 2)
A.R. Akhmerov QN/Akhmerov Group - AS (supervisor 2)
Alberto Chiarini Eindhoven University of Technology (coach)
Faculty
Applied Sciences
Copyright: © 2021 Pim Keer
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Published Date

13-07-2021

Language

English

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Faculty

Applied Sciences

Abstract

Level-set percolation on the Discrete Gaussian Free Field (DGFF) turned out to be
a hot topic within mathematical physics over the last couple of years. In particular, the DGFF on Z^d , with homogeneously weighted nearest-neighbour interactions, i.e. all conductances equal to 1, has been studied in detail. These models can be simulated with great efficiency. In this research, we abandon the homogeneity requirement and look at three-dimensional DGFFs with arbitrary conductances. Our goal is to find a quick and reliable method to simulate such DGFFs on a finite lattice. Since this is, in essence, a high-dimensional Gaussian sampling problem, we investigated this problem using the Conjugate Gradients (CG) linear solver as a Gaussian sampler. To see how it performed, we compared our implementation of the CG sampler with known methods for DGFFs in the unit conductance case. Finally, as a showcase of our implementation, we studied level-set percolation on a DGFF with a simple checkerboard conductance pattern.
Our main conclusion is that the CG algorithm is very suitable for simulating
Discrete Gaussian Free Fields. Since it does not make any assumptions on the conductances, it can be used to generate DGFFs with arbitrary conductances. However, there are still a number of issues with our implementation. The biggest one is concerning the stopping tolerance of the CG sampler. Once the tolerance is set smaller than some lattice size-dependent threshold, the percolative behaviour of the resulting sample changes drastically. We have not been able to explain this. Moreover, we would recommend making the implementation usable for parallel computing. We have been limited to relatively small lattice sizes during this project. Consequently, the use of certain finite-size scaling arguments when analysing level-set percolation might not always have been as justified.
Finally, based on our study of the DGFF on a lattice with checkerboard conductances a and b (a < b), we conjectured that, in its percolative behaviour, this DGFF resembles a DGFF defined on a lattice with constant conductance c, where c is a weighted average of a and b. The weight of a is expected to be larger than the weight of b.