8 papers · 1 filter
Multicriticality in stochastic dynamics protected by self-duality
Konstantinos Sfairopoulos, Luke Causer, Juan P. Garrahan
We study the dynamical large deviations (LD) of a class of one-dimensional kinetically constrained models whose (tilted) generators can be mapped into themselves via duality transf…
Spin models from nonlinear cellular automata
Konstantinos Sfairopoulos, Luke Causer, Jamie F. Mair +2
We study classical and quantum spin models derived from one-dimensional cellular automata (CA) with nonlinear update rules, focusing on rules 30, 54 and 201. We argue that the clas…
Discrete generative diffusion models without stochastic differential equations: a tensor network approach
Luke Causer, Grant M. Rotskoff, Juan P. Garrahan
Diffusion models (DMs) are a class of generative machine learning methods that sample a target distribution by transforming samples of a trivial (often Gaussian) distribution using…
Dynamical heterogeneity and large deviations in the open quantum East glass model from tensor networks
Luke Causer, Mari Carmen Bañuls, Juan P. Garrahan
We study the non-equilibrium dynamics of the dissipative quantum East model via numerical tensor networks. We use matrix product states to represent evolution under quantum-jump un…
Non-thermal eigenstates and slow relaxation in quantum Fredkin spin chains
Luke Causer, Mari Carmen Bañuls, Juan P. Garrahan
We study the dynamics and thermalization of the Fredkin spin chain, a system with local three-body interactions, particle conservation and explicit kinetic constraints. We consider…
Cellular automata in dimensions and ground states of spin models in dimensions
Konstantinos Sfairopoulos, Luke Causer, Jamie F. Mair +1
We show how the trajectories of -dimensional cellular automata (CA) can be used to determine the ground states of -dimensional classical spin models, and we characterise…