I am a Postdoctoral Researcher jointly supervised by Dr. Nai-Hui Chia at Rice University and Dr. Fang Song at Portland State University. I earned a PhD in Computer Science at UT Austin while advised by Scott Aaronson. Prior to that, I received a Bachelor of Science in Engineering from Cornell University in both Computer Science and Engineering Physics.
Research Interests
I am broadly interesting in quantum computing, complexity theory, and learning theory, with a focus on questions of how to time-efficiently extract information from unknown quantum systems. Motivations include algorithms to discover new kinds of physics, benchmark quantum computers, and understanding the limits of quantum computation itself.
Publications [Author Order is Alphabetical unless specified by an asterisk (*)]
Hamiltonian Locality Testing via Trotterized Postselection (arXiv)
John Kallaugher, Daniel Liang
To appear in TQC 2025Tolerant Testing of Stabilizer States with Mixed State Inputs (arXiv)
Vishnu Iyer, Daniel Liang
Quantum State Learning Implies Circuit Lower Bounds (arXiv)
Nai-Hui Chia, Daniel Liang, Fang Song
To appear in COLT 2025
TQC 2024
- My talk at TQC’24 (link)Agnostic Tomography of Stabilizer Product States (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang
Pseudoentanglement Ain’t Cheap (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang
TQC 2024
- My talk at TQC’24 (link)Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates (arXiv)
Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang
QIP 2024
- My Talk at IPAM (link)
- William’s talk at Simons (link)Improved Stabilizer Estimation via Bell Difference Sampling (arXiv, STOC 2024)
Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang
Proceedings of the 56th Annual ACM Symposium on Theory of Computing (STOC 2024)
QIP 2024
- Talks by Sabee (QIP’24) (STOC’24)Clifford Circuits can be Properly PAC Learned if and only if RP=NP (arXiv, Journal)
Daniel Liang
Quantum 7, 1036 – 2023Low-Stabilizer-Complexity Quantum States Are Not Pseudorandom (arXiv, ITCS 2023)
Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang
14th Innovations in Theoretical Computer Science Conference (ITCS 2023)
ITCS 2023 Best Student Paper Award
- Talk by Sabee (link)On the Hardness of PAC-learning stabilizer States with Noise (arXiv, Journal)
Aravind Gollakota, Daniel Liang
Quantum 6, 640 – 2022* Investigating quantum approximate optimization algorithms under bang-bang protocols (arXiv, Journal)
Daniel Liang, Li Li, Stefan Leichenauer
Physical Review Research 2 (3) – 2020* Simulation of qubit quantum circuits via Pauli propagation (arXiv, Journal)
Patrick Rall, Daniel Liang, Jeremy Cook, William Kretschmer
Physical Review A 99 (6) – 2019