Biography
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.
Research Interests
Natalia's research is in novel approaches to advance the engineering of quantum processors. To unleash the potential of quantum technologies, the intrinsic variability between individual devices has so far been a major hindrance.
For large arrays of devices, the tuning required to account for this variability quickly becomes an intractable task, presenting a bottleneck for the realisation of large quantum circuits. Natalia's group develops novel machine learning algorithms able to control complex quantum circuits in real time.
Natalia is also interested in the thermodynamics aspects of quantum information processing. The group fabricates devices at nanometre scales and holds them at millikelvin temperatures to explore the link between information and thermodynamics in the quantum world. Their exploration of information thermodynamics in the quantum arena will inform the construction of autonomous quantum machines such as quantum engines and quantum circuits with learning capabilities.
Current Projects
- Machine learning for quantum device control.
- Thermodynamics of quantum information processing.
Research Groups
Recent Publications
Probing quantum devices with radio-frequency reflectometry
Vigneau F, Fedele F, Chatterjee A, Reilly D, Kuemmeth F et al. (2023), Applied Physics Reviews, 10(2)
Ultrastrong coupling between electron tunneling and mechanical motion
Vigneau F, Monsel J, Tabanera J, Aggarwal K, Bresque L et al. (2022), Physical Review Research, 4(4)
Radio-frequency characterization of a supercurrent transistor made of a carbon nanotube
Mergenthaler M, Schupp FJ, Nersisyan A, Ares N, Baumgartner A et al. (2021), Materials for Quantum Technology, 1(3), 035003-035003
BibTeX
@article{radiofrequencyc-2021/9,
title={Radio-frequency characterization of a supercurrent transistor made of a carbon nanotube},
author={Mergenthaler M, Schupp FJ, Nersisyan A, Ares N, Baumgartner A et al.},
journal={Materials for Quantum Technology},
volume={1},
pages={035003-035003},
publisher={IOP Publishing},
year = "2021"
}
Deep reinforcement learning for efficient measurement of quantum devices
Nguyen V, Orbell S, Lennon D, Moon H, Vigneau F et al. (2021), npj Quantum Information, 7(1)
Quantum device fine-tuning using unsupervised embedding learning
van Esbroeck NM, Lennon DT, Moon H, Nguyen V, Vigneau F et al. (2020), New Journal of Physics, 22
Machine learning enables completely automatic tuning of a quantum device faster than human experts
Moon H, Lennon D, Kirkpatrick J, Esbroeck NMV, Camenzind L et al. (2020), Nature Communications , 11
BibTeX
@article{machinelearning-2020/8,
title={Machine learning enables completely automatic tuning of a quantum device faster than human experts},
author={Moon H, Lennon D, Kirkpatrick J, Esbroeck NMV, Camenzind L et al.},
journal={Nature Communications },
volume={11},
number={4161},
publisher={Springer Nature },
year = "2020"
}
Publisher Correction: Efficiently measuring a quantum device using machine learning
Lennon DT, Moon H, Camenzind LC, Zumbühl DM, Yu L et al. (2019), npj Quantum Information(1)
BibTeX
@article{publishercorrec-2019/12,
title={Publisher Correction: Efficiently measuring a quantum device using machine learning},
author={Lennon DT, Moon H, Camenzind LC, Zumbühl DM, Yu L et al.},
journal={npj Quantum Information},
publisher={Springer Science and Business Media LLC},
year = "2019"
}
A coherent nanomechanical oscillator driven by single-electron tunnelling
Wen Y, Ares N, Schupp FJ, Pei T, Briggs G et al. (2019), Nature Physics, 16(2020), 75-82
Efficiently measuring a quantum device using machine learning
Lennon DT, Moon H, Camenzind LC, Yu L, Zumbühl DM et al. (2019), npj Quantum Information, 5
Measuring carbon nanotube vibrations using a single-electron transistor as a fast linear amplifier
Wen Y, Ares N, Pei T, Briggs GAD & Laird EA (2018), APPLIED PHYSICS LETTERS, 113(15)
Displacemon Electromechanics: How to Detect Quantum Interference in a Nanomechanical Resonator
Khosla KE, Vanner MR, Ares N & Laird EA (2018), PHYSICAL REVIEW X, 8(2)
Strong coupling of microwave photons to antiferromagnetic fluctuations in an organic magnet
Mergenthaler M, Liu J, Le Roy J, Ares N, Thompson A et al. (2017), Physical Review Letters, 119(14), 147701
BibTeX
@article{strongcouplingo-2017/10,
title={Strong coupling of microwave photons to antiferromagnetic fluctuations in an organic magnet},
author={Mergenthaler M, Liu J, Le Roy J, Ares N, Thompson A et al.},
journal={Physical Review Letters},
volume={119},
pages={147701},
publisher={American Physical Society},
year = "2017"
}
Hyperfine and spin-orbit coupling effects on decay of spin-valley states in a carbon nanotube
Pei T, Palyi A, Mergenthaler M, Ares N, Mavalankar A et al. (2017), Physical Review Letters, 118(17)
BibTeX
@article{hyperfineandspi-2017/4,
title={Hyperfine and spin-orbit coupling effects on decay of spin-valley states in a carbon nanotube},
author={Pei T, Palyi A, Mergenthaler M, Ares N, Mavalankar A et al.},
journal={Physical Review Letters},
volume={118},
number={177701},
publisher={American Physical Society},
year = "2017"
}