1 citations · 3 across the 10 of their papers we have counts for
6 papers · 1 filter
Computational thresholds for the fixed-magnetization Ising model
Charlie Carlson, Ewan Davies, Alexandra Kolla +1
The ferromagnetic Ising model is a model of a magnetic material and a central topic in statistical physics. It also plays a starring role in the algorithmic study of approximate co…
Approximately counting independent sets in bipartite graphs via graph containers
Matthew Jenssen, Will Perkins, Aditya Potukuchi
By implementing algorithmic versions of Sapozhenko's graph container methods, we give new algorithms for approximating the number of independent sets in bipartite graphs. Our first…
Approximation algorithms for the random-field Ising model
Tyler Helmuth, Holden Lee, Will Perkins +2
Approximating the partition function of the ferromagnetic Ising model with general external fields is known to be #BIS-hard in the worst case, even for bounded-degree graphs, and i…
Approximate counting and sampling via local central limit theorems
Vishesh Jain, Will Perkins, Ashwin Sah +1
We give an FPTAS for computing the number of matchings of size in a graph of maximum degree on vertices, for all , where is fixed and $m^*(…
Counting independent sets in unbalanced bipartite graphs
Sarah Cannon, Will Perkins
We give an FPTAS for approximating the partition function of the hard-core model for bipartite graphs when there is sufficient imbalance in the degrees or fugacities between the si…
Fast algorithms at low temperatures via Markov chains
Zongchen Chen, Andreas Galanis, Leslie Ann Goldberg +3
We define a discrete-time Markov chain for abstract polymer models and show that under sufficient decay of the polymer weights, this chain mixes rapidly. We apply this Markov chain…