Associate Professor Natalia Ares works on experiments to advance the development of quantum technologies, with a focus on artificial intelligence for quantum device control and quantum thermodynamics. She joined the Materials Department at the University of Oxford in 2013. She was awarded a series of fellowships, including a Marie Skłodowska-Curie and a Royal Society University Research Fellowship, and was awarded a European Research Council Starting Grant in 2020. During her PhD she focused on silicon-based devices for quantum computing at CEA Grenoble, France. She completed her undergraduate studies in Physics and a Masters equivalent in the theory of quantum chaos at the University of Buenos Aires, Argentina, where she was born and raised. In October 2021 she was appointed as Associate Professor in the Department of Engineering Science and Tutorial Fellow at New College.
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My main research area is on quantum technologies and nanoscale quantum devices that allows fine control over individual charges and spins which are used to encode and manipulate quantum information. In addition, I am interested in hybrid devices, in which individual quantum systems are coupled to nanomechanical resonators such that their thermodynamic quantities can be measured and harnessed to further optimise these quantum systems.
I share my time between Natalia Ares' group at University of Oxford and Janet Anders' group at University of Exeter. My main research interests are in aspects of non-equilibrium thermodynamics of quantum systems, the link between thermodynamics and information theory, and the effects of strong coupling with the environment. Recently I have also developed interest in the theory of quantum devices.
Vincent is a theoretical quantum physicist, his research interests include the physical implementation of quantum information processing in semiconducting and hybrid (semi/superconducting) systems, out of equilibrium quantum dynamics, and quantum simulation. He is involved in a project that aims at controlling quantum devices with machine learning techniques.
Dr. Yikai YANG completed his undergraduate education in theoretical physics at Lanzhou University in China. He pursued a Master's in physics at University of Alberta in Canada, focusing on unconventional superconductors. After working in industry for four years, he joined EPFL in Switzerland for a PhD in the Laboratory for Quantum Magnetism, investigating critical behaviours of a model Ising magnet using microwave spectroscopy. In 2023, he joined Dr. Natalia Ares' group at the University of Oxford.
Combining machine learning methods with physical models to understand transport in electrostatic quantum dot devices.
Designing algorithms to improve quantum dot device readout and working on pulse optimisation for semiconductor qubits.
AI for qubit readout. Focused on taking Silicon devices from cool down to qubits with a flick of a switch.
Barnaby van Straaten
Machine learning techniques for high bandwidth measurements to ease the burden of transport measurements, for more scalable quantum computing architectures.
Exploring thermodynamics in the nanoscale regime using carbon nanotube-based electromechanical resonators.
Combining the necessary parts (and proposing methods where there are gaps) to achieve fully automated tuning of semiconducting qubits. This will lead to an understanding of how highly complex algorithms can work together to contribute to the final goal of scalable quantum computers.
Theory of open quantum systems, specifically interested in investigating continuous measurements and feedback control in non markovian systems.