Yunchao Liu
I am a fifth-year PhD student in the Theory Group at UC Berkeley, advised by Umesh Vazirani. My research interests are in quantum information and computation. Recently, I have been working on establishing theoretical foundations for near-term quantum advantage.
I received my Bachelor's degree from Yao Class at Tsinghua University, where I worked with Xiongfeng Ma.
Email: yunchaoliu at berkeley dot edu | Google Scholar |
Selected Papers
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Learning quantum states prepared by shallow circuits in polynomial time
Zeph Landau, Yunchao Liu
[Manuscript] [talk at Simons] [slides]
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Incompressibility and spectral gaps of random circuits
Chi-Fang Chen, Jeongwan Haah, Jonas Haferkamp, Yunchao Liu, Tony Metger, Xinyu Tan
[arXiv] [𝕏 post]
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A generalized cycle benchmarking algorithm for characterizing mid-circuit measurements
Zhihan Zhang, Senrui Chen, Yunchao Liu, Liang Jiang
[arXiv]
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Quantum computational advantage with constant-temperature Gibbs sampling
Thiago Bergamaschi, Chi-Fang Chen, Yunchao Liu
65th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2024)
[arXiv] [talk by Thiago at Simons]
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Efficient approximate unitary designs from random Pauli rotations
Jeongwan Haah, Yunchao Liu, Xinyu Tan
65th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2024)
[arXiv]
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Learning shallow quantum circuits
Hsin-Yuan Huang, Yunchao Liu, Michael Broughton, Isaac Kim, Anurag Anshu, Zeph Landau, Jarrod R. McClean
27th Annual Conference on Quantum Information Processing (QIP 2024) plenary talk
56th Annual ACM Symposium on Theory of Computing (STOC 2024)
[arXiv] [STOC] [talk at Simons] [slides]
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A polynomial-time classical algorithm for noisy random circuit sampling
Dorit Aharonov, Xun Gao, Zeph Landau, Yunchao Liu, Umesh Vazirani
26th Annual Conference on Quantum Information Processing (QIP 2023) plenary talk
55th Annual ACM Symposium on Theory of Computing (STOC 2023)
- Invited to the SICOMP special issue for STOC 2023
[arXiv] [STOC] [talk at Simons] [slides] [Quanta Magazine]
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The learnability of Pauli noise
Senrui Chen, Yunchao Liu, Matthew Otten, Alireza Seif, Bill Fefferman, Liang Jiang
Nature Communications, 2023
[arXiv] [Nature Communications] [talk at Simons] [slides]
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Distributed quantum inner product estimation
Anurag Anshu, Zeph Landau, Yunchao Liu
25th Annual Conference on Quantum Information Processing (QIP 2022)
54th Annual ACM Symposium on Theory of Computing (STOC 2022)
[arXiv] [STOC] [talk at STOC] [slides]
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Benchmarking near-term quantum computers via random circuit sampling
Yunchao Liu, Matthew Otten, Roozbeh Bassirianjahromi, Liang Jiang, Bill Fefferman
[arXiv] [slides]
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Noise and the frontier of quantum supremacy
Adam Bouland, Bill Fefferman, Zeph Landau, Yunchao Liu
24th Annual Conference on Quantum Information Processing (QIP 2021)
62nd Annual IEEE Symposium on Foundations of Computer Science (FOCS 2021)
[arXiv] [FOCS] [talk at FOCS] [slides]
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A rigorous and robust quantum speed-up in supervised machine learning
Yunchao Liu, Srinivasan Arunachalam, Kristan Temme
Nature Physics, 2021
[arXiv] [Nature Physics] [slides] [IBM Research Blog] [Quanta Magazine]
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Universal and operational benchmarking of quantum memories
Xiao Yuan, Yunchao Liu, Qi Zhao, Bartosz Regula, Jayne Thompson, Mile Gu
23rd Annual Conference on Quantum Information Processing (QIP 2020)
npj Quantum Information, 2021
[arXiv] [npj QI]
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Operational resource theory of quantum channels
Yunchao Liu, Xiao Yuan
Physical Review Research, 2020
[arXiv] [PRResearch]
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One-shot coherence distillation: towards completing the picture
Qi Zhao, Yunchao Liu, Xiao Yuan, Eric Chitambar, Andreas Winter
IEEE Transactions on Information Theory, 2019
[arXiv] [IEEE-TIT]
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One-shot coherence dilution
Qi Zhao, Yunchao Liu, Xiao Yuan, Eric Chitambar, Xiongfeng Ma
Physical Review Letters, 2018
[arXiv] [PRL]