# Nolan J. Coble

Applied Mathematics PhD Student

I am a second 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 the field of quantum computing. Recently, I have worked on classically simulating constant-depth quantum circuits. I am broadly interested in the application of pure mathematics to quantum information.

## Experience

### Education

#### Doctor of Philosophy

##### 2020 — present

University of Maryland, College Park, MD

Applied Mathematics & Statistics, and Scientific Computation

• Applied Mathematics Track
• Application Area: Quantum Information

#### Bachelor of Science

##### 2016 — 2020

SUNY Brockport, Brockport, NY

Physics and Mathematics Major

### Research Programs

#### Quantum Computing Summer School Fellowship

##### Summer 2021

Los Alamos National Laboratory, Los Alamos, NM

• Advised by Dr. Yigit Subasi

#### Training and Research Experiences in Nonlinear Dynamics (TREND) REU

##### Summer 2019

University of Maryland, College Park, MD

#### Photonics REU

##### Summer 2018

University or Rochester, Rochester, NY

## Articles

1. 2022. Parallel Machine Learning for Forecasting the Dynamics of Complex Networks, Keshav Srinivasan$$^\star$$, Nolan J. Coble$$^\star$$, Joy Hamlin$$^\star$$, Thomas Antonsen, Edward Ott, and Michelle Girven. Phys. Rev. Lett. 128, 164101. [pdf] or [arXiv:2108.12129] or [APS]
2. 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]
3. 2021. On nonlinear transformations in quantum computation, Zoë Holmes$$^\star$$, Nolan J. Coble, Andrew T. Sornborger, and Yiğit Subaşı$$^\star$$. Preprint. [pdf] or [arXiv:2108.12129]
4. 2021. Quasi-polynomial time approximation of output probabilities of geometrically-local, shallow quantum circuits, Nolan J. Coble$$^\star$$ and Matthew Coudron$$^\star$$. Conference on Quantum Information Processing (QIP 2021). Symposium on Foundations of Computer Science (FOCS 2021). [pdf] or [arXiv:2012.05460]
5. 2020. A Reservoir Computing Scheme for Multi-class Classification, Nolan J. Coble$$^\star$$ and Ning Yu. 2020 ACM Southeast Conference, Tampa, FL. [pdf] or [ACM Digital Library]
$$^\star$$ denotes a main contributor

## Talks

1. 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] and [Seminar Website]
2. 2020. Developing a Parallel Machine Learning Approach for Network Predictions, presented to SUNY Brockport physics department. [pdf]
3. 2020. Poster: Predicting Oscillatory Systems with Machine Learning, presented at SUNY Brockport Scholars Day. [pdf] or [SUNY Brockport Digital Commons]
4. 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.
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