The future development of quantum technologies relies on creating and manipulating
quantum systems of increasing complexity, with key applications in computation, simulation …

We review the development of generative modeling techniques in machine learning for the
purpose of reconstructing real, noisy, many-qubit quantum states. Motivated by its …

A major bottleneck in the development of scalable many-body quantum technologies is the
difficulty in benchmarking state preparations, which suffer from an exponential 'curse of …

While quantum state tomography is notoriously hard, most states hold little interest to
practically minded tomographers. Given that states and unitaries appearing in nature are of …

Quantum state tomography (QST) is a challenging task in intermediate-scale quantum
devices. Here, we apply conditional generative adversarial networks (CGANs) to QST. In the …

The precise control of complex quantum systems promises numerous technological
applications including digital quantum computing. The complexity of such devices renders …

Efficiently estimating properties of large and strongly coupled quantum systems is a central
focus in many-body physics and quantum information theory. While quantum computers …

The permutational invariance of identical two-level systems allows for an exponential
reduction in the computational resources required to study the Lindblad dynamics of …

Entanglement is the key quantum resource for improving measurement sensitivity beyond
classical limits. However, the production of entanglement in mesoscopic atomic systems has …

One of the greatest challenges in the fields of quantum information processing and quantum
technologies is the detailed coherent control over each and every constituent of quantum …