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

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 …

The field of classical stochastic processes forms a major branch of mathematics. Stochastic
processes are, of course, also very well studied in biology, chemistry, ecology, geology …

Quantum computers solve ever more complex tasks using steadily growing system sizes.
Characterizing these quantum systems is vital, yet becoming increasingly challenging. The …

Reinforcement learning has been widely used in many problems, including quantum control
of qubits. However, such problems can, at the same time, be solved by traditional, non …

The exponential growth in Hilbert space with increasing size of a quantum system means
that accurately characterizing the system becomes significantly harder with system …

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 …

This paper introduces a novel and efficient technique for quantum state estimation, coined
as low-rank matrix-completion quantum state tomography for characterizing pure quantum …

Recently, tremendous progress has been made in the field of quantum science and
technologies: different platforms for quantum simulation as well as quantum computing …

One of the ambitious goals of artificial intelligence is to build a machine that outperforms
human intelligence, even if limited knowledge and data are provided. Reinforcement …