Yuxuan (Vincent) Zhang
PH H1 477,
1015 Lausanne
Switzerland
Hello! This is Yuxuan (Vincent) Zhang (张宇轩). I am currently a postdoctoral researcher in Prof. Dmitry Abanin’s group, superposed between Princeton and EPFL. I am also a part-time Research Scientist at BlueQubit, working on quantum algorithm development.
My research lies at the interface of quantum information, quantum many-body physics, and artificial intelligence. I am strongly motivated by questions such as: How can we achieve verifiable quantum advantage on near-term hardware? How can ideas from many-body physics advance quantum computation, and how can quantum computers help us better understand the laws of nature? And how can we best use machine-learning tools to improve the design of quantum computers?
Previously, I was a CQIQC Fellow at the Centre for Quantum Information and Quantum Control at the University of Toronto, with a joint appointment at the Vector Institute for Artificial Intelligence, where I worked closely with Yong-Baek Kim, Juan Carrasquilla(now at ETHz), and Dvira Segal.
I obtained my Ph.D. in Physics from The University of Texas at Austin, where I was fortunate to be mentored by Andrew C. Potter(now at Quantinuum) and Scott Aaronson. During my Ph.D., I became deeply interested in quantum information, quantum matter, and the computational structure of physical systems. Before that, I received my B.S. in Physics with Highest Honors from the University of California, Santa Barbara in 2016, and then spent a year at the Institute of High Energy Physics in Beijing, working on collider physics and detector reconstruction.
Outside research, I enjoy traveling, photography, classical music, and real-time strategy games.
After all, what have I learned about the quantum world so far? Well, in short:
You observed me, and thus we entangled — though I could never be a copy of you.
selected publications
2025
- Probing mixed-state phases on a quantum computer via Renyi correlators and variational decodingarXiv preprint arXiv:2505.02900, 2025
- Observation of a non-Hermitian supersonic mode on a trapped-ion quantum computerNature Communications, 2025
2024
- Classical Simulability of Quantum Circuits with Shallow Magic DeptharXiv preprint arXiv:2409.15065, 2024
- Scalable quantum dynamics compilation via quantum machine learningarXiv preprint arXiv:2409.16346, 2024
- On verifiable quantum advantage with peaked circuit samplingApr 2024
2023
- Quantum Volume for Photonic Quantum ProcessorsPhysical Review Letters, Apr 2023
- Holographic quantum simulation of entanglement renormalization circuitsPRX Quantum, Apr 2023
2022
- Holographic simulation of correlated electrons on a trapped-ion quantum processorPRX Quantum, Apr 2022
2021
- QED driven QAOA for network-flow optimizationQuantum, Apr 2021