485 citations · 3k across the 63 of their papers we have counts for
6 papers · 2 filters
On nonlinear transformations in quantum computation
Zoë Holmes, Nolan Coble, Andrew T. Sornborger +1
While quantum computers are naturally well-suited to implementing linear operations, it is less clear how to implement nonlinear operations on quantum computers. However, nonlinear…
Generalization in quantum machine learning from few training data
Matthias C. Caro, Hsin-Yuan Huang, M. Cerezo +4
Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a test…
Quantum simulation of operator spreading in the chaotic Ising model
Michael R. Geller, Andrew Arrasmith, Zoë Holmes +3
There is great interest in using near-term quantum computers to simulate and study foundational problems in quantum mechanics and quantum information science, such as the scramblin…
Universal compiling and (No-)Free-Lunch theorems for continuous variable quantum learning
Tyler Volkoff, Zoë Holmes, Andrew Sornborger
Quantum compiling, where a parameterized quantum circuit is trained to learn a target unitary, is an important primitive for quantum computing that can be used as a subroutine to o…
Experimental Quantum Learning of a Spectral Decomposition
Michael R. Geller, Zoë Holmes, Patrick J. Coles +1
Currently available quantum hardware allows for small scale implementations of quantum machine learning algorithms. Such experiments aid the search for applications of quantum comp…
Long-time simulations with high fidelity on quantum hardware
Joe Gibbs, Kaitlin Gili, Zoë Holmes +5
Moderate-size quantum computers are now publicly accessible over the cloud, opening the exciting possibility of performing dynamical simulations of quantum systems. However, while…