I am a Staff Research Scientist at Sandia National Laboratories, as a member of the Quantum Algorithms and Applications Collaboratory (QuAAC). Previously, I was a Gil Herrera Postdoctoral Fellow at Sandia from 2024–2026. I received my PhD in physics in 2024 from the University of New Mexico, advised by Akimasa Miyake. I completed my BSc in physics in 2018 at the University of Maryland, College Park, where I was introduced to quantum computing through the mentorship of Shelby Kimmel (now at Middlebury College).

Research Interests

I am broadly interested in the theory of quantum computation & information. However, the central thesis driving much of my research is to contribute to an information-theoretic understanding of quantum matter. This is exemplified by many-body systems of fermions: What is the computational power of different fermionic models? Where does fermionic quantum information qualitatively diverge from the usual model of qubits? And what does this theory teach us about the complexity of matter—the electrons and atoms that make up the world around us?¹

Selected Publications

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• Polynomial-time classical and quantum simulation of quantum impurity models
  (alphabetical order) Jiaqing Jiang, Nathan Ju, Ojas Parekh, Chaithanya Rayudu, Andrew Zhao.
  arXiv:2610.02167 (2026).
  [arXiv]
• Lee-Yang theorem for fermions
  Chaithanya Rayudu, Takahiro Misawa, Andrew Zhao, Jun Takahashi.
  arXiv:2609.23942 (2026).
  [arXiv]
• Fermionic Insights into Measurement-Based Quantum Computation: Circle Graph States Are Not Universal Resources
  (alphabetical order) Brent Harrison, Vishnu Iyer, Ojas Parekh, Kevin Thompson, Andrew Zhao.
  arXiv:2510.05557 (2025).
  [arXiv] [TQC]
• Learning the Structure of Any Hamiltonian from Minimal Assumptions
  Andrew Zhao.
  Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 1201–1211 (2025).
  [arXiv] [STOC] [QIP]
• Fermionic partial tomography via classical shadows
  Andrew Zhao, Nicholas Rubin, Akimasa Miyake.
  Physical Review Letters 127, 110504 (2021).
  [arXiv] [DOI]

Dissertation

Learning, Optimizing, and Simulating Fermions with Quantum Computers
Committee: Akimasa Miyake, Ivan Deutsch, Milad Marvian, Andrew Landahl.
Chairman’s Award for Best Dissertation, Department of Physics and Astronomy (2024)
[arXiv] [UNM ETD]