Integrated Control Electronics for Semiconductor Quantum Devices

For practical applications a quantum computer would need to host millions of quantum bits (qubits) with a high degree of inter-qubit connectivity. At present, rudimentary solid-state quantum processors operate in dilution refrigerators at sub-kelvin temperature and are controlled by general-purpose classical electronics at room temperature [1]. In order to enable large-scale quantum hardware, the main hurdle is in envisaging efficient interconnect approaches between classical and quantum electronics [2]. To this end, semiconductor-based quantum computers [3-4] could be advantageous because both the control electronics and the qubits could be integrated on the same chip, overcoming the wiring bottleneck.

This project will address some of the challenges to make this approach viable. Firstly, there will be a need to design a control electronics layer with extremely modest power consumption to avoid heating the quantum hardware to the detriment of its fragile quantum states. Secondly, the choice of the semiconductor material for the quantum layer will need to be carefully considered. The obvious choice may be silicon for its compatibility with integrated CMOS electronics, but other commercial semiconductors, such as silicon carbide and germanium will be also explored. This will entail characterisation of different quantum devices in typical operating conditions, such as microwave frequency drive and multiplexed radiofrequency readout, as well as in a range of temperatures and external magnetic fields.

The research activities will balance integrated circuit (IC) design and modelling, hands-on cleanroom fabrication, as well as experimental measurements at cryogenic temperatures. The student will be involved in making and characterising electronic devices in a range of semiconductor materials. Main responsibilities:
- Design IC electronics to drive and read quantum hardware.
- Perform low-temperature experiments and device characterisation.
- Analyse experimental data with appropriate software (e.g. Matlab, Python etc.).
- Prepare manuscripts for submission to peer-reviewed journals.
- Travel domestically across collaborating institutions to carry out part of the project's activities.

[1] F. Arute et al., Nature 574, 505 (2019)
[2] L. M. K. Vandersypen et al., npj Quantum Inf. 3, 34 (2017)
[3] T. F. Watson et al., Nature 555, 633 (2018)
[4] N. Hendrickx et al., Nature 577, 487 (2020)