Nathan Ju
I am a CS PhD student at UC Berkeley in the theory group, advised by Umesh Vazirani. My research interests are centered on quantum computation, with a particular focus on algorithms and complexity. Recently, I have been especially interested in algorithms for fermionic systems and complexity of many-body systems (e.g. area laws).
I gained my footing in research at UIUC, Los Alamos, and a wonderful summer at the IQC in Waterloo, with David Gosset.
π Papers
- Polynomial-time classical and quantum simulation of quantum impurity models
- Code Swendsen-Wang Dynamics
- Improved approximation algorithms for the EPR Hamiltonian
- Commitments to Quantum States
- Theory of overparametrization in quantum neural networks
- Interactive quantum advantage with noisy, shallow Clifford circuits
π Teaching
Graduate Student Instructor, UC Berkeley
-
CS C191: Introduction to Quantum Computing (Fall 2023)
Outstanding GSI Award
Teaching Assistant, UIUC
- CS 374: Algorithms and Models of Computation (Fall 2019, Spring 2020)
