activity
20212026
most citedTheory of overparametrization in quantum neural networks

170 citations · 171 across the 5 of their papers we have counts for

collaborators

6 papers

quant-ph2026

Polynomial-time classical and quantum simulation of quantum impurity models

Jiaqing Jiang, Nathan Ju, Ojas Parekh +2

Quantum impurity models are paradigmatic models of interacting quantum matter, as well as key computational primitives for modern electronic-structure methods. They describe a smal…

quant-ph2025

Code Swendsen-Wang Dynamics

Dominik Hangleiter, Nathan Ju, Umesh Vazirani

Recent advances in quantum Gibbs sampling leave open the central question of rapid mixing near and below phase transitions. This challenge is especially relevant for code Hamiltoni…

quant-ph2025

Improved approximation algorithms for the EPR Hamiltonian

Nathan Ju, Ansh Nagda

The EPR Hamiltonian is a family of 2-local quantum Hamiltonians introduced by King (arXiv:2209.02589). We introduce a polynomial time -approximat…

quant-ph2022

Commitments to Quantum States

Sam Gunn, Nathan Ju, Fermi Ma +1

What does it mean to commit to a quantum state? In this work, we propose a simple answer: a commitment to quantum messages is binding if, after the commit phase, the committed stat…

quant-ph2021★ 170 cited

Theory of overparametrization in quantum neural networks

Martin Larocca, Nathan Ju, Diego García-Martín +2

The prospect of achieving quantum advantage with Quantum Neural Networks (QNNs) is exciting. Understanding how QNN properties (e.g., the number of parameters ) affect the loss l…

quant-ph2021★ 1 cited

Interactive quantum advantage with noisy, shallow Clifford circuits

Daniel Grier, Nathan Ju, Luke Schaeffer

Recent work by Bravyi et al. constructs a relation problem that a noisy constant-depth quantum circuit (QNC) can solve with near certainty (probability ), but that an…