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
Compromise-free scaling of qubit speed and coherence.
Carballido MJ, Svab S, Eggli RS, Patlatiuk T, Chevalier Kwon P et al. (2025), Nat Commun, 16(1), 7616
BibTeX
@article{compromisefrees-2025/8,
title={Compromise-free scaling of qubit speed and coherence.},
author={Carballido MJ, Svab S, Eggli RS, Patlatiuk T, Chevalier Kwon P et al.},
journal={Nat Commun},
volume={16},
pages={7616},
year = "2025"
}
Rapid optimal work extraction from a quantum-dot information engine
Aggarwal K, Rolandi A, Yang Y, Hickie J, Jirovec D et al. (2025), Physical Review Research, 7(3), l032017-l032017
BibTeX
@article{rapidoptimalwor-2025/7,
title={Rapid optimal work extraction from a quantum-dot information engine},
author={Aggarwal K, Rolandi A, Yang Y, Hickie J, Jirovec D et al.},
journal={Physical Review Research},
volume={7},
pages={l032017-l032017},
publisher={American Physical Society (APS)},
year = "2025"
}
Extra cost of erasure due to quantum lifetime broadening
Dunlop J, Cerisola F, Monsel J, Sevitz S, Tabanera-Bravo J et al. (2025), Physical Review A, 112(1), l010601-l010601
BibTeX
@article{extracostoferas-2025/7,
title={Extra cost of erasure due to quantum lifetime broadening},
author={Dunlop J, Cerisola F, Monsel J, Sevitz S, Tabanera-Bravo J et al.},
journal={Physical Review A},
volume={112},
pages={l010601-l010601},
publisher={American Physical Society (APS)},
year = "2025"
}
Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures
Papatheodorou A, Vaidhyanathan P, Ares N & Havoutis I (2025)
BibTeX
@misc{learningphysica-2025/6,
title={Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures},
author={Papatheodorou A, Vaidhyanathan P, Ares N & Havoutis I},
year = "2025"
}
Quantum computing and artificial intelligence: status and perspectives
Acampora G, Ambainis A, Ares N, Banchi L, Bhardwaj P et al. (2025)
BibTeX
@misc{quantumcomputin-2025/6,
title={Quantum computing and artificial intelligence: status and perspectives},
author={Acampora G, Ambainis A, Ares N, Banchi L, Bhardwaj P et al.},
year = "2025"
}
Meta-learning characteristics and dynamics of quantum systems
Schorling L, Vaidhyanathan P, Schuff J, Carballido MJ, Zumbühl D et al. (2025)
BibTeX
@misc{metalearningcha-2025/3,
title={Meta-learning characteristics and dynamics of quantum systems},
author={Schorling L, Vaidhyanathan P, Schuff J, Carballido MJ, Zumbühl D et al.},
year = "2025"
}
MetaSym: A Symplectic Meta-learning Framework for Physical Intelligence
Vaidhyanathan P, Papatheodorou A, Mitchison MT, Ares N & Havoutis I (2025)
BibTeX
@misc{metasymasymplec-2025/2,
title={MetaSym: A Symplectic Meta-learning Framework for Physical Intelligence},
author={Vaidhyanathan P, Papatheodorou A, Mitchison MT, Ares N & Havoutis I},
year = "2025"
}
Automated long-range compensation of an rf quantum dot sensor
Hickie J, van Straaten B, Fedele F, Jirovec D, Ballabio A et al. (2024), Physical Review Applied, 22(6), 064026
BibTeX
@article{automatedlongra-2024/12,
title={Automated long-range compensation of an rf quantum dot sensor},
author={Hickie J, van Straaten B, Fedele F, Jirovec D, Ballabio A et al.},
journal={Physical Review Applied},
volume={22},
pages={064026},
publisher={American Physical Society (APS)},
year = "2024"
}
Differentiable master equation solver for quantum device characterization
Craig DL, Ares N & Gauger EM (2024), Physical Review Research, 6(4)
BibTeX
@article{differentiablem-2024/10,
title={Differentiable master equation solver for quantum device characterization},
author={Craig DL, Ares N & Gauger EM},
journal={Physical Review Research},
volume={6},
year = "2024"
}
QArray: A GPU-accelerated constant capacitance model simulator for large quantum dot arrays
van Straaten B, Hickie J, Schorling L, Schuff J, Fedele F et al. (2024), SciPost Physics Codebases, 035-035
BibTeX
@article{qarrayagpuaccel-2024/10,
title={QArray: A GPU-accelerated constant capacitance model simulator for large quantum dot arrays},
author={van Straaten B, Hickie J, Schorling L, Schuff J, Fedele F et al.},
journal={SciPost Physics Codebases},
pages={035-035},
publisher={Stichting SciPost},
year = "2024"
}
Cross-architecture tuning of silicon and SiGe-based quantum devices using machine learning
Severin B, Lennon DT, Camenzind LC, Vigneau F, Fedele F et al. (2024), Scientific Reports, 14(1)
BibTeX
@article{crossarchitectu-2024/7,
title={Cross-architecture tuning of silicon and SiGe-based quantum devices using machine learning},
author={Severin B, Lennon DT, Camenzind LC, Vigneau F, Fedele F et al.},
journal={Scientific Reports},
volume={14},
number={17281},
publisher={Nature Research},
year = "2024"
}
Looping in the human: collaborative and explainable Bayesian optimization
Adachi M, Planden B, Howey DA, Osborne MA, Orbell S et al. (2024), Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 505-513
BibTeX
@inproceedings{loopinginthehum-2024/4,
title={Looping in the human: collaborative and explainable Bayesian optimization},
author={Adachi M, Planden B, Howey DA, Osborne MA, Orbell S et al.},
booktitle={27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024)},
pages={505-513},
year = "2024"
}
Stability of long-sustained oscillations induced by electron tunneling
Tabanera-Bravo J, Vigneau F, Monsel J, Aggarwal K, Bresque L et al. (2024), Physical Review Research, 6(1)
BibTeX
@article{stabilityoflong-2024/3,
title={Stability of long-sustained oscillations induced by electron tunneling},
author={Tabanera-Bravo J, Vigneau F, Monsel J, Aggarwal K, Bresque L et al.},
journal={Physical Review Research},
volume={6},
number={013291},
publisher={American Physical Society},
year = "2024"
}
High-fidelity spin qubit operation and algorithmic initialization above 1 K
Huang JY, Su RY, Lim WH, Feng M, van Straaten B et al. (2024), Nature, 627(8005), 772-777
BibTeX
@article{highfidelityspi-2024/3,
title={High-fidelity spin qubit operation and algorithmic initialization above 1 K},
author={Huang JY, Su RY, Lim WH, Feng M, van Straaten B et al.},
journal={Nature},
volume={627},
pages={772-777},
publisher={Springer Nature},
year = "2024"
}
Bridging the reality gap in quantum devices with physics-aware machine learning
Craig DL, Moon H, Fedele F, Lennon DT, van Straaten B et al. (2024), Physical Review X, 14(1)
BibTeX
@article{bridgingthereal-2024/1,
title={Bridging the reality gap in quantum devices with physics-aware machine learning},
author={Craig DL, Moon H, Fedele F, Lennon DT, van Straaten B et al.},
journal={Physical Review X},
volume={14},
number={11001},
publisher={American Physical Society},
year = "2024"
}
