Transport, metastability, and neuromorphic applications in quantum networks

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One challenge at the core of quantum technologies is the realization of coherent quantum dynamics at the mesoscopic scale. As the size of a device is scaled up, disorder and dissipation become increasingly relevant and tend to destroy quantum mechanical coherence. Most strategies for mitigating their detrimental effect on quantum operations become quickly inefficient when scaled up to larger numbers of qubits. The goal of QNet is to provide concepts and methods for manipulating quantum information, where fault-tolerant performance is assisted or even boosted by noise and dissipation. For this purpose, QNet will assess the out-of-equilibrium dynamics of a quantum network with long-range interactions in the presence and as a function of noise, with a specific focus on applications to quantum associative memories and quantum reservoir computing. QNet joins world-leading theory and experimental scientists with expertise including quantum optics, condensed matter, quantum information, and quantum thermodynamics. The proof-of-principle concepts will be tested on state-of-the-art experimental platforms consisting of (i) ultracold atoms in a high-finesse cavity with tunable temperature, noise and dissipation, and (ii) superconducting quantum circuits that are coupled to on-chip mesoscopic heat baths. On these platforms we will test the role of noise and dissipation on quantum neuromorphic computation. QNet will provide a toolbox of concepts and paradigms, paving the way to the next generation of quantum technologies.