4 papers
Scalable linearized gate set tomography
Ashe Miller, Corey Ostrove, Jordan Hines +4
Characterizing errors on many-qubit quantum computers remains a key challenge to understanding and improving the performance of these devices. Current characterization methods eith…
Learning Gaussian optical states with quantum computers
Spencer Dimitroff, John Kallaugher, Ashe Miller +1
Recent results have established dramatic advantages in learning properties of quantum states when a quantum computer is available to process or jointly measure multiple copies of t…
Efficient simulation of Clifford circuits with small Markovian errors
Ashe Miller, Corey Ostrove, Jordan Hines +3
Classical simulation of noisy quantum circuits is essential for understanding quantum computing experiments. It enables scalable error characterization, analysis of how noise impac…
What is my quantum computer good for? Quantum capability learning with physics-aware neural networks
Daniel Hothem, Ashe Miller, Timothy Proctor
Quantum computers have the potential to revolutionize diverse fields, including quantum chemistry, materials science, and machine learning. However, contemporary quantum computers…