Quantum Device Lab

We are currently working on the following projects:

• Efficient quantum device tuning using machine learning: Fault-tolerant quantum computers require hundreds to millions of physical qubits to be operated with high fidelity. Inevitable hardware imperfections must be tuned away. The technology is only scalable if this task can be efficiently automated. We are applying automating techniques experimentally, working with leaders in machine learning. The objective is to achieve automated tuning of semiconductor qubits encoded in gate-defined quantum dots. We expect this machine learning approach to enable the tuning of large quantum circuits.
• Quantum Information Thermodynamics in the solid state: The field of quantum thermodynamics has long been dominated by theoretical predictions, undermined by a severe lack of experimental tests. However, rapid breakthroughs in nanoscale fabrication and measurement are now presenting us with the opportunity to develop concrete experimental foundations for exploring quantum-thermodynamic processes. Understanding the peculiarities of thermodynamics in the quantum arena will be key for the construction of nanomachines, for energy harvesting, and to master the dissipation and thermalization of quantum systems. It will also improve the engineering basis of quantum technologies by allowing fully informed choices on device design and optimization and it may reveal possibilities for entirely novel technologies.