Frustration is a ubiquitous phenomenon in many-body physics that influences the nature of
the system in a profound way with exotic emergent behavior. Despite its long research …

Motivated by dipolar-coupled artificial spin systems, we present a theoretical study of the
classical J 1-J 2-J 3 Ising antiferromagnet on the kagome lattice. We establish the ground …

Motivated by the recent success of tensor networks to calculate the residual entropy of spin
ice and kagome Ising models, we develop a general framework to study frustrated Ising …

We introduce policy-guided Monte Carlo (PGMC), a computational framework using
reinforcement learning to improve Markov chain Monte Carlo (MCMC) sampling. The …

Despite their simple formulation, short-range classical antiferromagnetic Ising models on
frustrated lattices give rise to exotic phases of matter, in particular, due to their macroscopic …

Using renormalization group (RG) analyses and Monte Carlo (MC) simulations, we study the
fully packed dimer model on the bilayer square lattice with fugacity equal to z (1) for …

We use Monte Carlo simulations and tensor network methods to study a classical monomer-
dimer model on the square lattice with a hole (monomer) fugacity z, an aligning dimer-dimer …

We study the triangular-lattice Ising model with dipolar interactions, inspired by its realisation
in artificial arrays of nanomagnets. We show that a classical spin-liquid forms at intermediate …

We present a universal parameter-free quantum Monte Carlo (QMC) algorithm designed to
simulate arbitrary spin-1/2 Hamiltonians. To ensure the convergence of the Markov chain to …

Nonreversible Markov chains can outperform reversible chains in the Markov chain Monte
Carlo method. Lifting is a versatile approach to introducing net stochastic flow in state space …