Learning a quantum computer's capability using convolutional neural networks

This is supplemental data and code for: D. Hothem et al., Learning a quantum computer's capability using convolutional neural networks, (to be published). This folder contains all the data and the analysis code to generate the results presented in that paper. The core data analysis routines use PyGSTi, which can be found at https://github.com/pyGSTio/pyGSTi. Please direct any questions to Daniel Hothem (dhothem@sandia.gov). NOTE: This description template was borrowed from Timothy Proctor's Zenodo entry for: Scalable Randomized Benchmarking of Quantum Computers using Mirror Circuits.