Quantum bits
Quantum computers store, elaborate and transmit information in quantum bits. Qubits can be physically represented by basic two level quantum systems, such as the spin of an electron, the polarization of a photon, a non-linear LC oscillator created by a superconducting Josephson junction, trapped ions or nitrogen vacancies in diamond. Such systems typically require extremely low temperature to prevent thermal noise from destroying the quantum coherence, so qubits are cooled down in refrigerators operating down to 20 mK.
Classical control
In order to initialize, control and read out the state of qubits, complex high frequency electronics is normally used. State-of-the-art qubit fabrication has reached a few qubits only (up to tens at most), so control and readout is currently done with bulky instruments connected externally from room temperature to the cryogenic environment. However, scaling to very large number of qubits, as required to operate useful computational algorithms, would make this discrete approach impossible.
Cryo-CMOS for qubits
To tackle scalability, we propose to create integrated circuits operating directly at cryogenic temperatures, namely 4.2 K. This enables compactness and integration, eases interfacing with qubits and reduces the thermal noise brought by room temperature. We propose to use CMOS technology due its low cost, proven scalability and large scale integration. For spin qubits in silicon systems, this could also promise a co-integration between qubits and control electronics on the same chip.
The mission of AQUA in MOS-QUITO (MOS-based Quantum Information Technology) project is to develop the classical electronics required to control and read out the state of spin qubits. This mainly consists in analog and RF building blocks in CMOS technology, finally aiming to the creation of a cryogenic readout and control circuit to operate large multi-qubit quantum systems directly at 4.2 K [1].
References:
[1] E. Charbon et al., “Cryo-CMOS circuits and systems for scalable quantum computing”, in 2017 IEEE International Solid-State Circuits Conference (ISSCC), pp. 264–265, Feb 2017.