Name
Abstract | ||
|---|---|---|
This article introduces a new specialized algorithm for equilibrium Monte Carlo sampling of binary-valued systems, which allows for large moves in the state space. This is achieved by constructing self-avoiding walks (SAWs) in the state space. As a consequence, many bits are flipped in a single MCMC step. We name the algorithm SARDONICS, an acronym for Self-Avoiding Random Dynamics on Integer Complex Systems. The algorithm has several free parameters, but we show that Bayesian optimization can be used to automatically tune them. SARDONICS performs remarkably well in a broad number of sampling tasks: toroidal ferromagnetic and frustrated Ising models, 3D Ising models, restricted Boltzmann machines and chimera graphs arising in the design of quantum computers. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2414416.2414790 | ACM Trans. Model. Comput. Simul. |
Keywords | Field | DocType |
equilibrium monte carlo sampling,ising model,algorithm sardonics,self-avoiding random dynamics,frustrated ising model,state space,bayesian optimization,complex systems,sampling task,new specialized algorithm,gibbs sampling,monte carlo,markov chain monte carlo | Monte Carlo method in statistical physics,Slice sampling,Mathematical optimization,Boltzmann machine,Computer science,Hybrid Monte Carlo,Quantum computer,Monte Carlo integration,Statistics,State space,Monte Carlo molecular modeling | Journal |
Volume | Issue | ISSN |
23 | 1 | 1049-3301 |
Citations | PageRank | References |
5 | 0.61 | 24 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Firas Hamze | 1 | 131 | 14.05 |
| Ziyu Wang | 2 | 372 | 23.71 |
| Nando De Freitas | 3 | 3284 | 273.68 |