The angular momentum of molecules, or, equivalently, their rotation in three-dimensional
space, is ideally suited for quantum control. Molecular angular momentum is naturally …

Simulating quantum mechanics is known to be a difficult computational problem, especially
when dealing with large systems. However, this difficulty may be overcome by using some …

In this book, we provide a comprehensive introduction to the most recent advances in the
application of machine learning methods in quantum sciences. We cover the use of deep …

The goal of the present article is to review the major developments that have led to the
current understanding of molecule–field interactions and experimental methods for …

This paper reviews recent advances in the study of strongly interacting systems of dipolar
molecules. Heteronuclear molecules feature large and tunable electric dipole moments …

It is widely accepted that phonon-mediated high-temperature superconductivity is
impossible at ambient pressure, because of the very large effective masses of polarons or …

We present a machine-learning method for predicting sharp transitions in a Hamiltonian
phase diagram by extrapolating the properties of quantum systems. The method is based on …

Quantum systems are notoriously difficult to simulate with classical means. Recently, the
idea of using another quantum system—which is experimentally more controllable—as a …

We show that an array of ultracold Rydberg atoms embedded in a laser driven background
gas can serve as an aggregate for simulating exciton dynamics and energy transport with a …

Implementing a scalable quantum information processor using polar molecules in optical
lattices requires precise control over the long-range dipole–dipole interaction between …