This is supplemental data and code for: T. Proctor et al., Scalable randomized benchmarking of quantum computers using mirror circuits, arXiv 2112.09853 (2021). 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 Timothy Proctor (tjproct@sandia.gov).SAND2021-8118
This is supplemental data and code for: T. Proctor et al, Detecting and tracking drift in quantum in...
Producing useful quantum information devices requires efficiently assessing control of quantum syste...
Dataset containing raw data presented in the publication "Parallel window decoding enables scalable ...
This is supplemental data and code for: T. Proctor et al., Scalable randomized benchmarking of quant...
This is supplemental data and code for: T. Proctor et al., Scalable randomized benchmarking of quant...
This is supplemental data and code for: D. Hothem et al., Learning a quantum computer's capability u...
This is supplemental data and code for: T. Proctor et al., Measuring the Capabilities of Quantum Com...
The performance of quantum gates is often assessed using some form of randomized benchmarking. Howev...
Quantum computers promise an exponential speed-up over their classical counterparts for certain task...
Randomized benchmarking is an experimental procedure intended to demonstrate control of quantum syst...
Randomized benchmarking is an experimental procedure intended to demonstrate control of quantum syst...
Quantum computers promise to be a revolutionary new technology. However, in order to realise this pr...
Quantum computers promise to be a revolutionary new technology. However, in order to realise this pr...
This is supplemental data and code for: T. Proctor et al., Establishing trust in quantum computation...
Code that executes and interprets the experiment displayed in fig 1 of the manuscript, as well as pi...
This is supplemental data and code for: T. Proctor et al, Detecting and tracking drift in quantum in...
Producing useful quantum information devices requires efficiently assessing control of quantum syste...
Dataset containing raw data presented in the publication "Parallel window decoding enables scalable ...
This is supplemental data and code for: T. Proctor et al., Scalable randomized benchmarking of quant...
This is supplemental data and code for: T. Proctor et al., Scalable randomized benchmarking of quant...
This is supplemental data and code for: D. Hothem et al., Learning a quantum computer's capability u...
This is supplemental data and code for: T. Proctor et al., Measuring the Capabilities of Quantum Com...
The performance of quantum gates is often assessed using some form of randomized benchmarking. Howev...
Quantum computers promise an exponential speed-up over their classical counterparts for certain task...
Randomized benchmarking is an experimental procedure intended to demonstrate control of quantum syst...
Randomized benchmarking is an experimental procedure intended to demonstrate control of quantum syst...
Quantum computers promise to be a revolutionary new technology. However, in order to realise this pr...
Quantum computers promise to be a revolutionary new technology. However, in order to realise this pr...
This is supplemental data and code for: T. Proctor et al., Establishing trust in quantum computation...
Code that executes and interprets the experiment displayed in fig 1 of the manuscript, as well as pi...
This is supplemental data and code for: T. Proctor et al, Detecting and tracking drift in quantum in...
Producing useful quantum information devices requires efficiently assessing control of quantum syste...
Dataset containing raw data presented in the publication "Parallel window decoding enables scalable ...