QuReCo

QuReCo aims to push forward our current understanding of quantum reservoir computing, through the development of a precise characterization of the optimal architectures taking into account the features of the specific platforms used, as well as the impact of noise and thermodynamic constraints. The project will explore the range of tasks that can be efficiently solved by QRC and, notably, it will take advantage of the combination of analytical and numerical approaches, as well as the quantum simulation on a quantum-computer platform.

The most advanced tools to characterize general open-system dynamics and non-equilibrium processes will allow us to deal with multi-partite quantum systems and with the impact of realistic environments, where memory effects are prominent, also leading to non-trivial behaviors of the energy exchanges and the entropy production. Besides its intrinsic relevance for the actual implementation of QRC, the research activity carried out within QuReCo will be of major interest also on a more fundamental perspective, by improving our capability to investigate and quantify memory effects in non-Markovian dynamics, and by setting definite criteria to address the non-classicality of thermodynamic properties in the structured systems involved in QRC.

QuReCo gathers three research groups that have been actively contributing to cutting-edge research on the application of machine-learning based techniques to quantum systems,the theory of open quantum systems and quantum thermodynamics. The project will benefit from the presence of diverse and complementary expertise, which will result in a unique combination granting important advancements in the characterization of QRC under realistic conditions.