4 papers
Model-aware reinforcement learning for high-performance Bayesian experimental design in quantum metrology
Federico Belliardo, Fabio Zoratti, Florian Marquardt +1
Quantum sensors offer control flexibility during estimation by allowing manipulation by the experimenter across various parameters. For each sensing platform, pinpointing the optim…
Fast quantum control of cavities using an improved protocol without coherent errors
Jonas Landgraf, Christa Flühmann, Thomas Fösel +2
The selective number-dependent arbitrary phase (SNAP) gates form a powerful class of quantum gates, imparting arbitrarily chosen phases to the Fock states of a cavity. However, for…
Preparing Schrödinger cat states in a microwave cavity using a neural network
Hector Hutin, Pavlo Bilous, Chengzhi Ye +8
Scaling up quantum computing devices requires solving ever more complex quantum control tasks. Machine learning has been proposed as a promising approach to tackle the resulting ch…
Discovering Local Hidden-Variable Models for Arbitrary Multipartite Entangled States and Arbitrary Measurements
Nick von Selzam, Florian Marquardt
Measurement correlations in quantum systems can exhibit non-local behavior, a fundamental aspect of quantum mechanics with applications such as device-independent quantum informati…