Justin Yirka
Research Interests / Education / Papers / Experience
Ph.D. Candidate in Computer Science
Quantum computing and theoretical computer science
Advised by Scott Aaronson at UT Austin
📢 Graduating in 2025. Looking for an industry position.
Other profiles:
Research Interests
My research focuses on quantum computation and theoretical computer science.
Specific topics include complexity theory, Hamiltonian complexity, and quantum algorithms.
Some of my work has focused on the difficulty of computing properties in low-energy quantum systems, on quantifying the amount of “useful” information in a quantum state, and on the robustness of quantum algorithmic speed-ups compared to classical algorithms.
My PhD dissertation (in preparation) focuses on my contributions developing new areas of complexity theory (QPH, Hamiltonian problems beyond ground state energy, …) and new quantum algorithms.
In other words, I’m interested in what quantum computers can do, what they cannot do, and the structure that creates those differences.
📢 I plan to graduate in 2025 and am looking for a new position outside of academia.
My one-sentence summary: 10+ years in quantum computing, 7+ publications including QIP/TQC/CCC, 20+ presentations, 2 National Labs, and 8+ semesters teaching with demonstrated experience identifying research questions and leading projects.
Please reach out if you’re interested in my research or would like to discuss future opportunities!
Education
Ph.D. in Computer Science | The University of Texas at Austin (UT) | Expected 2025
Advised by Scott Aaronson.
M.S. in Computer Science | The University of Texas at Austin | 2022
B.S. in Computer Science | Virginia Commonwealth University (VCU) | 2018
B.S. in Mathematical Sciences
Research Papers
Click on a paper to expand and see the publication history and any relevant links.
There are 2 to 3 projects I expect to add to this list by mid-2025 (when I graduate).
I’m happy to discuss ongoing projects one-on-one.
J. Yirka. Even quantum advice is unlikely to solve PP.
arXiv:2403.09994, March 2024.
S. Grewal and J. Yirka. The Entangled Quantum Polynomial Hierarchy Collapses.
arXiv:2401.01453, January 2024. CCC 2024.
J. Kallaugher, O. Parekh, K. Thompson, Y. Wang, J. Yirka. Complexity Classification of Product State Problems for Local Hamiltonians.
arXiv:2401.06725, January 2024. QIP 2024 and ITCS 2025.
J. Yirka and Y. Subasi. Qubit-efficient entanglement spectroscopy using qubit resets.
arXiv:2010.03080, 2020. Quantum.
S. Gharibian, S. Piddock, J. Yirka. Oracle complexity classes and local measurements on physical Hamiltonians.
arXiv:1909.05981, 2019. QIP 2020 and STACS 2020.
- Symposium on Theoretical Aspects of Computer Science (STACS), 2020. doi:10.4230/LIPIcs.STACS.2020.20.
- Conference on Quantum Information Processing (QIP), 2020.
Video here. Slides here.
- Contributed talk at Asian Quantum Information Science Conference (AQIS), 2018. Slides here.
- arXiv:1909.05981, 2019.
- Poster available here.
- Additional videos:
Seminar by Sev in "Quantum computing in isolation" series available here.
S. Gharibian, M. Santha, J. Sikora, A. Sundaram, J. Yirka. Quantum generalizations of the polynomial hierarchy with applications to QMA(2).
arXiv:1805.11139, 2018. computational complexity and MFCS 2018.
S. Gharibian and J. Yirka. The complexity of simulating local measurements on quantum systems.
arXiv:1606.05626, 2016. Quantum and TQC 2017.
Non-quantum computing work
N. Bushaw, V. Gupta, C. Larson, S. Loeb, M. Norge, J. Parrish, N. Van Cleemput, J. Yirka, and G. Wu.
New conditions for graph Hamiltonicity.
2025. Involve.
J. Yirka. Evaluation of TCP header fields for data overhead efficiency.
2015. Poster only.
- Awarded "Launch Award for Outstanding Research Poster" at VCU Symposium for Undergraduate Research and Creativity, 2015.
Research Experience
- R&D Intern | Sandia National Laboratories | Summer 2023 - present
Advised by Ojas Parekh and John Kallaugher
Topic: Hardness of estimating optimum product states of local Hamiltonians. Quantum Max-Cut, Vector Max-Cut, and Quantum constrained optimization problems. Alternative query models.
- Summer School Fellow | Los Alamos National Laboratories | Summer 2019
Advised by Yigit Subasi
Topic: Near-term (NISQ) quantum algorithms. Studied use of mid-circuit measurements and resets to construct circuits for entanglement spectroscopy which were noise-resilient and low-width.
Implemented noisy simulations with Qiskit, Python, Unix, Jupyter. Managed project with git. Tested algorithms on Honeywell quantum hardware.
- Research Assistant | Graph Theory Computational Discovery Lab, VCU | Summer 2018
Supervisor: Craig Larson
Topic: Automated conjecturing software applied to graph theory.
Maintained a growing database of graphs, their properties, and known theorems. Managed open-source project and programmed using git, GitHub, and Sage/Python.
- NSF REU Researcher | QuICS, University of Maryland | Summer 2017
Advised by Andrew Childs, Jianxin Chen, and Amir Kalev
Topic: Investigated minimum number of measurements for pure state quantum tomography.
- Research Assistant | Quantum Computing Lab, VCU | 2015 - 2016
Advised by Sevag Gharibian, Ph.D.
Topic: Complexity theory. QMA oracles, Hamiltonian problems beyond QMA (e.g. P^QMA[log]), quantum polynomial hierarchy and “quantum Toda’s Theorem” (QCPH ⊆ P^PP^PP).
See My CV for full details on my Research, Awards, Funding, Teaching Experience, and Service.
Last updated: January 25, 2025