About the project
Quantum computers are limited by the quantum-classical interface, where power-hungry control electronics struggle to scale with growing qubit numbers. This project explores cryogenic memristors as ultra-low-power adaptive calibration elements that can learn and compensate for qubit drift, enabling more stable, scalable, and energy-efficient quantum computing systems and future architectures.
As qubit numbers increase, the control, calibration and readout electronics required to operate them consume significant power and generate substantial wiring complexity. A major challenge is qubit drift, where device characteristics change over time and require continuous recalibration. This project will investigate cryogenic memristors as ultra-low-power adaptive calibration and memory elements for future quantum-computing control systems.
The research aims to understand how memristors behave at cryogenic temperatures and determine whether their memory, non-linearity and learning capabilities can be exploited to compensate for qubit drift automatically. The outcomes will include new cryogenic memristor materials, device models, adaptive calibration circuits and proof-of-concept neuromorphic control architectures for scalable quantum technologies.
- Year 1: You will develop and optimise new thin-film materials for cryogenic operation, working closely with engineers from Von Ardenne GmbH through collaboration with the MEMNICS Laboratory. This will give you experience in advanced thin-film deposition, materials engineering and industrial device development.
- Year 2: You will fabricate and characterise cryogenic memristor chips, investigating switching behaviour, retention, endurance, multilevel operation and stability at low temperatures. Experimental protocols for electrical testing under cryogenic conditions will be established. Device physics models and cryogenic behavioural models will also be created.
- Year 3: You will design, build and experimentally evaluate adaptive calibration circuits and neuromorphic control architectures using cryogenic memristors. Demonstrator systems will be developed to assess their ability to compensate for qubit drift and reduce power consumption for future quantum-computing.
The project offers multidisciplinary training spanning nanofabrication, thin-film materials, cryogenic electronics, neuromorphic engineering and quantum technologies.
