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Scalable Randomized Benchmarking of Quantum Computers using Mirror Circuits

<p>This is supplemental data and code for: T. Proctor et al.,&nbsp;<em><a href="http://https://doi.org/10.48550/arXiv.2112.09853">Scalable randomized benchmarking of quantum computers using mirror circuits</a>, </em>arXiv 2112.09853 (2021).</p> <p>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&nbsp;<a href="https://github.com/pyGSTio/pyGSTi">https://github.com/pyGSTio/pyGSTi</a>.</p> <p>Please direct any questions to Timothy Proctor&nbsp;(tjproct@sandia.gov).</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0