Natalia Ares
Royal Society University Research Fellow
I started in the Materials Department at Oxford in 2013 and I was awarded a Royal Society University Research Fellowship in 2019. I focus on radio-frequency reflectometry for fast and sensitive readout of spin qubits and carbon nanotube electromechanics. I now aim at realising thermodynamics experiments and I work on machine learning for qubit scalability.
New Postgraduate Research Projects Available
Selected Publications
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Quantum device fine-tuning using unsupervised embedding learning
September 2020|Journal article|New Journal of Physics -
Machine learning enables completely automatic tuning of a quantum device faster than human experts.
August 2020|Journal article|Nature communicationsVariability is a problem for the scalability of semiconductor quantum devices. The parameter space is large, and the operating range is small. Our statistical tuning algorithm searches for specific electron transport features in gate-defined quantum dot devices with a gate voltage space of up to eight dimensions. Starting from the full range of each gate voltage, our machine learning algorithm can tune each device to optimal performance in a median time of under 70 minutes. This performance surpassed our best human benchmark (although both human and machine performance can be improved). The algorithm is approximately 180 times faster than an automated random search of the parameter space, and is suitable for different material systems and device architectures. Our results yield a quantitative measurement of device variability, from one device to another and after thermal cycling. Our machine learning algorithm can be extended to higher dimensions and other technologies. -
Sensitive radio-frequency read-out of quantum dots using an ultra-low-noise SQUID amplifier
June 2020|Journal article|Journal of Applied Physics -
Sensitive radiofrequency readout of quantum dots using an ultra-low-noise SQUID amplifier
June 2020|Journal article|JOURNAL OF APPLIED PHYSICS -
Radio-frequency optomechanical characterization of a silicon nitride drum.
February 2020|Journal article|Sci RepOn-chip actuation and readout of mechanical motion is key to characterize mechanical resonators and exploit them for new applications. We capacitively couple a silicon nitride membrane to an off resonant radio-frequency cavity formed by a lumped element circuit. Despite a low cavity quality factor (QE ≈ 7.4) and off resonant, room temperature operation, we are able to parametrize several mechanical modes and estimate their optomechanical coupling strengths. This enables real-time measurements of the membrane's driven motion and fast characterization without requiring a superconducting cavity, thereby eliminating the need for cryogenic cooling. Finally, we observe optomechanically induced transparency and absorption, crucial for a number of applications including sensitive metrology, ground state cooling of mechanical motion and slowing of light. -
A coherent nanomechanical oscillator driven by single-electron tunnelling.
January 2020|Journal article|Nature physicsA single-electron transistor embedded in a nanomechanical resonator represents an extreme limit of electron-phonon coupling. While it allows fast and sensitive electromechanical measurements, it also introduces backaction forces from electron tunnelling that randomly perturb the mechanical state. Despite the stochastic nature of this backaction, it has been predicted to create self-sustaining coherent mechanical oscillations under strong coupling conditions. Here, we verify this prediction using real-time measurements of a vibrating carbon nanotube transistor. This electromechanical oscillator has some similarities with a laser. The single-electron transistor pumped by an electrical bias acts as a gain medium and the resonator acts as a phonon cavity. Although the operating principle is unconventional because it does not involve stimulated emission, we confirm that the output is coherent. We demonstrate other analogues of laser behaviour, including injection locking, classical squeezing through anharmonicity, and frequency narrowing through feedback. -
Efficiently measuring a quantum device using machine learning (vol 5, 79, 2019)
November 2019|Journal article|NPJ QUANTUM INFORMATION -
Efficiently measuring a quantum device using machine learning
September 2019|Journal article|NPJ QUANTUM INFORMATION -
Measuring carbon nanotube vibrations using a single-electron transistor as a fast linear amplifier
October 2018|Journal article|APPLIED PHYSICS LETTERS -
Displacemon Electromechanics: How to Detect Quantum Interference in a Nanomechanical Resonator
May 2018|Journal article|PHYSICAL REVIEW X