A5086630410- Quantum and electron transport phenomena
- Advancements in Semiconductor Devices and Circuit Design
- Semiconductor materials and devices
- Semiconductor Quantum Structures and Devices
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Topological Materials and Phenomena
- Machine Learning in Materials Science
- Experimental and Theoretical Physics Studies
- Physics of Superconductivity and Magnetism
- Mechanical and Optical Resonators
- Nanowire Synthesis and Applications
- Advanced MEMS and NEMS Technologies
- Electronic and Structural Properties of Oxides
- Cold Atom Physics and Bose-Einstein Condensates
- Force Microscopy Techniques and Applications
- Carbon Nanotubes in Composites
- Semiconductor materials and interfaces
- Analog and Mixed-Signal Circuit Design
- Nonlinear Dynamics and Pattern Formation
University of Oxford
2020-2025
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
2018-2019
Institut Nanosciences et Cryogénie
2018-2019
Université Grenoble Alpes
2016-2019
CEA Grenoble
2018-2019
Université de Toulouse
2018
Université Toulouse III - Paul Sabatier
2016-2018
Centre National de la Recherche Scientifique
2016-2018
Laboratoire National des Champs Magnétiques Intenses
2014-2016
Institut National des Sciences Appliquées de Toulouse
2016
Many important phenomena in quantum devices are dynamic, meaning that they cannot be studied using time-averaged measurements alone. Experiments measure such transient effects collectively known as fast readout. One of the most useful techniques electrical readout is radio-frequency reflectometry, which can changes impedance (both resistive and reactive) even when their duration extremely short, down to a microsecond or less. Examples reflectometry experiments, some have been realised others...
Hybrid superconductor–semiconductor structures attract increasing attention owing to a variety of potential applications in quantum computing devices. They can serve the realization topological superconducting systems as well gate-tunable bits. Here, we combine SiGe/Ge/SiGe quantum-well heterostructure hosting high-mobility two-dimensional holes and aluminum leads realize prototypical hybrid devices, such Josephson field-effect transistors (JoFETs) interference devices (SQUIDs). We observe...
Abstract Deep reinforcement learning is an emerging machine-learning approach that can teach a computer to learn from their actions and rewards similar the way humans experience. It offers many advantages in automating decision processes navigate large parameter spaces. This paper proposes efficient measurement of quantum devices based on deep learning. We focus double dot devices, demonstrating fully automatic identification specific transport features called bias triangles. Measurements...
<title>Abstract</title> The ability to couple a solitary spin high-frequency motion would constitute crucial advancement for range of applications, including quantum sensing, intermediate and long-distance spin-spin coupling, information processing. While the possibility such coupling has been explored theoretically more than decade ago, experimental demonstrations have remained elusive. Here we report on first observation spin-mechanical in carbon nanotube device. We demonstrate this two...
The discrepancies between reality and simulation impede the optimization scalability of solid-state quantum devices. Disorder induced by unpredictable distribution material defects is one major contributions to gap. We bridge this gap using physics-aware machine learning, in particular, an approach combining a physical model, deep Gaussian random field, Bayesian inference. This enables us infer disorder potential nanoscale electronic device from electron-transport data. inference validated...
Abstract The potential of Si and SiGe-based devices for the scaling quantum circuits is tainted by device variability. Each needs to be tuned operation conditions each realisation requires a different tuning protocol. We demonstrate that it possible automate 4-gate FinFET, 5-gate GeSi nanowire 7-gate Ge/SiGe heterostructure double dot from scratch with same algorithm. achieve times 30, 10, 92 min, respectively. algorithm also provides insight into parameter space landscape these devices,...
Device variability is a bottleneck for the scalability of semiconductor quantum devices. Increasing device control comes at cost large parameter space that has to be explored in order find optimal operating conditions. We demonstrate statistical tuning algorithm navigates this entire space, using just few modelling assumptions, search specific electron transport features. focused on gate-defined dot devices, demonstrating fully automated two different devices double regimes an up...
We report experimental evidence of ballistic hole transport in one-dimensional quantum wires gate-defined a strained SiGe/Ge/SiGe well. At zero magnetic field, we observe conductance plateaus at integer multiples 2e^2/h. finite the splitting these by Zeeman effect reveals largely anisotropic g-factors, with absolute values below 1 quantum-well plane, and exceeding 10 out plane. This g-factor anisotropy is consistent heavy-hole character propagating valence-band states, line predominant...
Fault-tolerant spin-based quantum computers will require fast and accurate qubit readout. This can be achieved using radio-frequency reflectometry given sufficient sensitivity to the change in capacitance associated with states. Here, we demonstrate a 23-fold improvement by supplementing cryogenic semiconductor amplifier SQUID preamplifier. The operates at frequency near 200 MHz achieves noise temperature below 600 mK when integrated into circuit, which is within factor 120 of limit. It...
Self-oscillations are the result of an efficient mechanism generating periodic motion from a constant power source. In quantum devices, these oscillations may arise due to interaction between single electron dynamics and mechanical motion. We show that, complexity this mechanism, self-oscillations irrupt, vanish, or exhibit bistable behavior causing hysteresis cycles. observe cycles characterize stability different regimes in both single- double-quantum-dot configurations. particular cases,...
We report on magneto-transport measurements in InAs nanowires under large magnetic field (up to 55T), providing a direct spectroscopy of the 1D electronic band structure. Large modulations magneto-conductance mediated by an accurate control Fermi energy reveal Landau fragmentation, carrying fingerprints confined material. Our numerical simulations structure consistently support experimental results and key parameters confinement.
The ultrastrong coupling of single-electron tunneling and nanomechanical motion opens exciting opportunities to explore fundamental questions develop new platforms for quantum technologies. We have measured modeled this electromechanical in a fully suspended carbon nanotube device report ratio ${g}_{\text{m}}/{\ensuremath{\omega}}_{\mathrm{m}}=2.72\ifmmode\pm\else\textpm\fi{}0.14$, where...
Abstract Quantum devices with a large number of gate electrodes allow for precise control device parameters. This capability is hard to fully exploit due the complex dependence these parameters on applied voltages. We experimentally demonstrate an algorithm capable fine-tuning several at once. The acquires measurement and assigns it score using variational auto-encoder. Gate voltage settings are set optimize this in real-time unsupervised fashion. report times double quantum dot within...
Pauli spin blockade (PSB) can be employed as a great resource for qubit initialisation and readout even at elevated temperatures but it difficult to identify. We present machine learning algorithm capable of automatically identifying PSB using charge transport measurements. The scarcity data is circumvented by training the with simulated cross-device validation. demonstrate our approach on silicon field-effect transistor device report an accuracy 96% different test devices, giving evidence...
The discrepancies between reality and simulation impede the optimisation scalability of solid-state quantum devices. Disorder induced by unpredictable distribution material defects is one major contributions to gap. We bridge this gap using physics-aware machine learning, in particular, an approach combining a physical model, deep Gaussian random field, Bayesian inference. This has enabled us infer disorder potential nanoscale electronic device from electron transport data. inference...
Narrow band gap III-V based nanowires are subject to intense research, notably thanks the exceptional mobility of carriers. Moreover, due strong spin-orbit coupling combined with ability host superconductivity, they provide a platform for realization Majorana fermions. Here, authors performed very high field magnetotransport measurements (50T) on InAs in both longitudinal and perpendicular configuration, giving access, quasiballistic regime, energy spectrum. The experimental results...
The charge transport properties of individual InSb nanowires based transistors are studied at 4.2 K in the quasiballistic regime. energy level separations zero magnetic field extracted from a bias voltage spectroscopy. magnetoconductance under applied perpendicularly to nanowire axis is investigated up 50 T. Owing reduction backscattering, electronic states quasi-one-dimensional electron gas revealed by Landauer-B\"uttiker conductance quantization. results compared theoretical predictions...
The potential of Si and SiGe-based devices for the scaling quantum circuits is tainted by device variability. Each needs to be tuned operation conditions. We give a key step towards tackling this variability with an algorithm that, without modification, capable tuning 4-gate FinFET, 5-gate GeSi nanowire 7-gate SiGe heterostructure double dot from scratch. achieve times 30, 10, 92 minutes, respectively. also provides insight into parameter space landscape each these devices. These results...
Abstract Radio-frequency measurements could satisfy DiVincenzo's readout criterion in future large-scale solid-state quantum processors, as they allow for high bandwidths and frequency multiplexing. However, the scalability potential of this technique can only be leveraged if device tuning is performed using exclusively radio-frequency measurements, i.e. without resorting to current measurements. By exploiting their bandwidth impedance matching, we demonstrate an algorithm that automatically...
Many important phenomena in quantum devices are dynamic, meaning that they cannot be studied using time-averaged measurements alone. Experiments measure such transient effects collectively known as fast readout. One of the most useful techniques electrical readout is radio-frequency reflectometry, which can changes impedance (both resistive and reactive) even when their duration extremely short, down to a microsecond or less. Examples reflectometry experiments, some have been realised others...
Abstract Pauli spin blockade (PSB) can be employed as a great resource for qubit initialisation and readout even at elevated temperatures but it difficult to identify. We present machine learning algorithm capable of automatically identifying PSB using charge transport measurements. The scarcity data is circumvented by training the with simulated cross-device validation. demonstrate our approach on silicon field-effect transistor device report an accuracy 96% different test devices, giving...
Radio-frequency measurements could satisfy DiVincenzo's readout criterion in future large-scale solid-state quantum processors, as they allow for high bandwidths and frequency multiplexing. However, the scalability potential of this technique can only be leveraged if device tuning is performed using exclusively radio-frequency i.e. without resorting to current measurements. We demonstrate an algorithm that automatically tunes double dots reflectometry. Exploiting bandwidth measurements, was...