Cryogenic silicon neuromorphic processor for quantum computing

The field of quantum computing offers exponential computational speedup for a number of important problems. However, there are still a lot of challenges to realizing large-scale quantum computers. One of them is related to the ultra-low-power dissipation requirement for cryogenic auxiliary electronics interfacing quantum bits (qubits). Commercial nano-transistors dissipate too much power at low temperatures to be used for cryogenic electronics in a future quantum computer consisting of millions of qubits. Here we propose an alternative, non von Neuman processor architecture based on brain-neuron-mimicking artificial neural networks functioning at cryogenic temperatures. Fabricated within standard silicon transistor technology, our cryo-neuromorphic processors offer fast and ultra-low-power computation capabilities to realize, for example, on-chip qubit error classification. Moreover, the proposed cryo-neuromorphic processors can be co-integrated with spin qubits on the same silicon chip, thus offering great scalability prospects.