Nolan J. Coble

Computer Science PhD Candidate

About

I am a fourth-year PhD student at the Joint Center for Quantum Information and Computer Science (QuICS) at the University of Maryland, College Park. I graduated from SUNY Brockport in 2020 majoring in mathematics and physics.

My research interests are in quantum information and theoretical computer science. Recently, I have been interested in the use of error-correcting codes in Hamiltonian complexity and in understanding transversal logic in quantum codes.

Experience

Education

Doctor of Philosophy

2020 — present

University of Maryland, College Park, MD

Computer Science

Bachelor of Science

2016 — 2020

SUNY Brockport, Brockport, NY

Physics and Mathematics Major

Programs Attended

Simons Institute

Spring 2024

UC Berkeley, Berkeley, CA

Park City Mathematics Institute (PCMI) Graduate Summer School

Summer 2023
  • Three-week long program on quantum computation

Quantum Computing Summer School Fellowship

Summer 2021

Los Alamos National Laboratory, Los Alamos, NM

  • Advised by Yiğit Subaşı

Publications

Articles

  1. 2024. Geometric structure and transversal logic of quantum Reed–Muller codes, Alexander Barg, Nolan J. Coble, Dominik Hangleiter, and Christopher Kang. Preprint. [arXiv:2410.07595]
  2. 2023. Hamiltonians whose low-energy states require Ω(n) T gates, Nolan J. Coble, Matthew Coudron, Jon Nelson, and Seyed Sajjad Nezhadi. Preprint. [arXiv:2310.01347]
  3. 2023. Local Hamiltonians with no low-energy stabilizer states, Nolan J. Coble, Matthew Coudron, Jon Nelson, and Seyed Sajjad Nezhadi. Theory of Quantum Computation, Communication and Cryptography (TQC 2023). [arXiv:2302.14755] or [Conference Version] or [Slides]
  4. 2023. Nonlinear transformations in quantum computation, Zoë Holmes, Nolan J. Coble, Andrew T. Sornborger, and Yiğit Subaşı. Phys. Rev. Research 5, 013105. [arXiv:2108.12129] or [APS]
  5. 2022. Parallel Machine Learning for Forecasting the Dynamics of Complex Networks, Keshav Srinivasan, Nolan J. Coble, Joy Hamlin, Thomas Antonsen, Edward Ott, and Michelle Girven. Phys. Rev. Lett. 128, 164101. [arXiv:2108.12129] or [APS]
  6. 2022. Spectra of Quaternion Unit Gain Graphs, Francesco Belardo, Maurizio Brunetti, Nolan J. Coble, Nathan Reff, and Howard Skogman. Linear Algebra and its Applications. 632, p.15-49. [ScienceDirect]
  7. 2021. Quasi-polynomial time approximation of output probabilities of geometrically-local, shallow quantum circuits, Nolan J. Coble and Matthew Coudron. Conference on Quantum Information Processing (QIP 2021). Symposium on Foundations of Computer Science (FOCS 2021). [arXiv:2012.05460] or [Conference Version]
  8. 2020. A Reservoir Computing Scheme for Multi-class Classification, Nolan J. Coble and Ning Yu. 2020 ACM Southeast Conference, Tampa, FL. [ACM Digital Library] or [pdf]

Talks

  1. 2024. Hamiltonians whose low-energy states require Ω(n) T gates, presented to the IQC Math & CS Seminar. [pdf]
  2. 2023. Poster: Hamiltonians whose low-energy states require Ω(n) T gates, presented at the IPAM Workshop on Topology, Quantum Error Correction, and Quantum Gravity. [pdf]
  3. 2021. Divide-and-conquer method for approximating output probabilities of geometrically-local, shallow-depth quantum circuits, presented to the IQC-QuICS Math and Computer Science Seminar. [pdf]
  4. 2020. Developing a Parallel Machine Learning Approach for Network Predictions, presented to SUNY Brockport physics department. [pdf]
  5. 2020. Poster: Predicting Oscillatory Systems with Machine Learning, presented at SUNY Brockport Scholars Day. [pdf] or [SUNY Brockport Digital Commons]
  6. 2019. Poster: Parallel Machine Learning Prediction of Network Dynamics, presented at University of Maryland TREND REU Research Fair. [pdf]

Contact Me

Feel free to contact me about anything! The best way to reach me is through my email below.

Email: nolanjcoble [at] gmail [dot] com