Jon Nelson

I am a fourth year PhD student in QuICS at the University of Maryland co-advised by Daniel Gottesman and Michael Gullans. Prior to Maryland I was a Post-Bacc researcher at Los Alamos National Laboratory mentored by Carleton Coffrin.

I am broadly interested in using algorithmic and complexity theoretic tools to gain insights into quantum physics. This has led me to a variety of topics in quantum information including quantum error correction, Hamiltonian complexity, and the complexity of noisy quantum circuits. To support these efforts I am fortunate to be funded by an NSF Graduate Research Fellowship.

Description of image
[CV] [google scholar]
email: nelson1@umd.edu
X: @jonnelson87

Papers

Ordered in reverse chronological order from arXiv date.

  • The rotation-invariant Hamiltonian problem is QMAEXP-complete. Jon Nelson, Daniel Gottesman. Accepted to TQC 2025.

  • Polynomial-time classical simulation of noisy circuits with naturally fault-tolerant gates. Jon Nelson, Joel Rajakumar, Dominik Hangleiter, Michael J. Gullans. In submission. [arXiv]

  • Hamiltonians whose low-energy states require Ω(n) T gates. Nolan J. Coble, Matthew Coudron, Jon Nelson, Seyed S. Nezhadi (Alphabetized). In submission. [arXiv]

  • Local Hamiltonians with no low-energy stabilizer states. Nolan J. Coble, Matthew Coudron, Jon Nelson, Seyed S. Nezhadi (Alphabetized). [TQC 2023]

  • Fault-tolerant quantum memory using low-depth random circuit codes. Jon Nelson, Gregory Bentsen, Steven T. Flammia, Michael J. Gullans. [Physical Review Research 2025]

  • High-quality thermal Gibbs sampling with quantum annealing hardware. Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Tameem Albash, Carleton Coffin [Physical Review Applied 2022]

  • Single-qubit cross platform comparison of quantum computing hardware. Adrien Suau, Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffin. [IEEE QCE 2023]

  • Single-qubit fidelity assessment of quantum annealing hardware. Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Carleton Coffin [IEEE Transactions on Quantum Engineering 2021]

  • AdaSense: Adaptive low-power sensing and activity recognition for wearable devices. Marina Naseem, Jon Nelson, Sherief Reda. [DAC 2020]

Teaching/Mentoring

  • Research Mentor for REU-CAAR: Mentored two undergraduate researchers and co-lead a research project on non-local graph planarity games, which was presented as a poster at QIP 2025. (Summer 2024).

  • Graduate Teaching Assistant: Algorithms at University of Maryland (Fall 2021).

  • Undergraduate Teaching Assistant: Design of Computing Systems at Brown University (Spring 2020).