A key challenge in the effort to simulate today's quantum computing devices is the ability to
learn and encode the complex correlations that occur between qubits. Emerging …

Recurrent neural networks (RNNs), originally developed for natural language processing,
hold great promise for accurately describing strongly correlated quantum many-body …

Nonequilibrium statistical mechanics exhibit a variety of complex phenomena far from
equilibrium. It inherits challenges of equilibrium, including accurately describing the joint …

Very often when studying non-equilibrium systems one is interested in analysing dynamical
behaviour that occurs with very low probability, so called rare events. In practice, since rare …

Sampling the collective, dynamical fluctuations that lead to nonequilibrium pattern formation
requires probing rare regions of trajectory space. Recent approaches to this problem, based …

Recent work has shown the effectiveness of tensor network methods for computing large
deviation functions in constrained stochastic models in the infinite time limit. Here we show …

The large deviation statistics of dynamical observables is encoded in the spectral properties
of deformed Markov generators. Recent works have shown that tensor network methods are …

We use projected entangled-pair states (PEPS) to calculate the large deviation statistics of
the dynamical activity of the two-dimensional East model, and the two-dimensional …

Variational Monte Carlo studies employing projected entangled-pair states (PEPS) have
recently shown that they can provide answers to long-standing questions such as the nature …

Force chains are quasi-linear self-organised structures carrying large stresses and are
ubiquitous in jammed amorphous materials like granular materials, foams or even cell …