Machine learning of phase transitions in the percolation and models
In this paper, we apply machine learning methods to study phase transitions in certain
statistical mechanical models on the two-dimensional lattices, whose transitions involve …
statistical mechanical models on the two-dimensional lattices, whose transitions involve …
Unsupervised learning of topological phase transitions using the Calinski-Harabaz index
Machine learning methods have been recently applied to learning phases of matter and
transitions between them. Of particular interest is the topological phase transition, such as in …
transitions between them. Of particular interest is the topological phase transition, such as in …
A new look at the collapse of two-dimensional polymers
We study the collapse of two-dimensional polymers, via an O (n) model on the square lattice
that allows for dilution, bending rigidity and short-range monomer attractions. This model …
that allows for dilution, bending rigidity and short-range monomer attractions. This model …
The O (n) loop model on a three-dimensional lattice
We study a class of loop models, parameterized by a continuously varying loop fugacity n,
on the hydrogen peroxide lattice, which is a three-dimensional cubic lattice of coordination …
on the hydrogen peroxide lattice, which is a three-dimensional cubic lattice of coordination …
Tethered Monte Carlo: Computing the effective potential without critical slowing down
We present Tethered Monte Carlo, a simple, general purpose method of computing the
effective potential of the order parameter (Helmholtz free energy). This formalism is based …
effective potential of the order parameter (Helmholtz free energy). This formalism is based …
Worm Monte Carlo study of the honeycomb-lattice loop model
We present a Markov-chain Monte Carlo algorithm of worm type that correctly simulates the
O (n) loop model on any (finite and connected) bipartite cubic graph, for any real n> 0, and …
O (n) loop model on any (finite and connected) bipartite cubic graph, for any real n> 0, and …
Loop-Cluster Coupling and Algorithm for Classical Statistical Models
Potts spin systems play a fundamental role in statistical mechanics and quantum field theory
and can be studied within the spin, the Fortuin–Kasteleyn (FK) bond or the q-flow (loop) …
and can be studied within the spin, the Fortuin–Kasteleyn (FK) bond or the q-flow (loop) …
Critical behavior of the Chayes–Machta–Swendsen–Wang dynamics
We study the dynamic critical behavior of the Chayes-Machta dynamics for the Fortuin-
Kasteleyn random-cluster model, which generalizes the Swendsen-Wang dynamics for the q …
Kasteleyn random-cluster model, which generalizes the Swendsen-Wang dynamics for the q …
Rugged free-energy landscapes in disordered spin systems
D Yllanes - arXiv preprint arXiv:1111.0266, 2011 - arxiv.org
This thesis is an attempt to provide a new outlook on complex systems, as well as some
physical answers for certain models, taking a computational approach. We have focused on …
physical answers for certain models, taking a computational approach. We have focused on …
Phase transition in site-diluted Josephson junction arrays: A numerical study
We numerically investigate the intriguing effects produced by random percolative disorder in
two-dimensional Josephson junction arrays. By dynamic scaling analysis, we evaluate …
two-dimensional Josephson junction arrays. By dynamic scaling analysis, we evaluate …