Quantum neuromorphic computing implements neural networks on quantum physical systems. Such physical quantum neural networks take advantage of the highly dimensional Hilbert space which allows to separate it in different classes. Moreover, quantum neural networks have the capacity to process input quantum states and learn to automatically recognize them, thus circumventing the need for a large number of classical measurements.
In our team, we study quantum properties and dynamics in superconducting circuits in order to develop and implement new learning methods with the quantum neural networks. On this topic we collaborate closely with QCMX team at Ecole Polytechnique.
We are currently looking for a post-doc to work with us on experimental implementation of quantum neural networks, contact us if you are interested!