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

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 …

Full quantum tomography of high-dimensional quantum systems is experimentally infeasible
due to the exponential scaling of the number of required measurements on the number of …

We apply deep-neural-network-based techniques to quantum state classification and
reconstruction. Our methods demonstrate high classification accuracies and reconstruction …

Schrödinger's cat originates from the famous thought experiment querying the
counterintuitive quantum superposition of macroscopic objects. As a natural extension …

Quantum reservoir networks combine the intelligence of neural networks with the potential of
quantum computing in a single platform. This platform operates on the architecture of …

Modern day quantum simulators can prepare a wide variety of quantum states but the
accurate estimation of observables from tomographic measurement data often poses a …

Reconstructing quantum states is an important task for various emerging quantum
technologies. The process of reconstructing the density matrix of a quantum state is known …

The efficient and reliable certification of quantum states is essential for various quantum
information processing tasks as well as for the general progress on the implementation of …