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Title: Python GST Implementation (PyGSTi) v. 0.9

Abstract

PyGSTi is a Python package for modeling and characterizing noise (errors) in small quantum information processors. In addition to being a basic framework for describing quantum circuits and noise models, it implements mainstream quantum characterization, verification, and validation (QCVV) protocols such as Gate Set Tomography (GST), Randomized Benchmarking (RB), Robust Phase Estimation, and Idle Tomography. It also implements prototype protocols used for timeseries analysis and crosstalk detection, all of which have the goal of better understanding the noise found in existing as-built experimental devices. The central protocol of pyGSTi (from where it derives its name) is Gate Set Tomography. GST is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the “goodness” of qubits but also a means of debugging (i.e. improving) them. The other protocols follow this similar pattern in that they use statistical inference and analysis of experimental data tomore » estimate one or more properties of the noise in a device.« less

Developers:
 [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Release Date:
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Version:
v. 0.9
Licenses:
Apache License 2.0
Sponsoring Org.:
USDOE

Primary Award/Contract Number:
NA0003525
Code ID:
28250
Site Accession Number:
SCR#2018.2
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

Citation Formats

Nielsen, Erik, Blume-Kohout, Robin J, Rudinger, Kenneth M, Proctor, Timothy J, Saldyt, Lucas, and USDOE. Python GST Implementation (PyGSTi) v. 0.9. Computer software. https://www.osti.gov//servlets/purl/1543289. Vers. v. 0.9. USDOE. 10 Jul. 2019. Web. doi:10.11578/dc.20190722.2.
Nielsen, Erik, Blume-Kohout, Robin J, Rudinger, Kenneth M, Proctor, Timothy J, Saldyt, Lucas, & USDOE. (2019, July 10). Python GST Implementation (PyGSTi) v. 0.9 (Version v. 0.9) [Computer software]. https://www.osti.gov//servlets/purl/1543289. doi:10.11578/dc.20190722.2.
Nielsen, Erik, Blume-Kohout, Robin J, Rudinger, Kenneth M, Proctor, Timothy J, Saldyt, Lucas, and USDOE. Python GST Implementation (PyGSTi) v. 0.9. Computer software. Version v. 0.9. July 10, 2019. https://www.osti.gov//servlets/purl/1543289. doi:10.11578/dc.20190722.2.
@misc{osti_1543289,
title = {Python GST Implementation (PyGSTi) v. 0.9, Version v. 0.9},
author = {Nielsen, Erik and Blume-Kohout, Robin J and Rudinger, Kenneth M and Proctor, Timothy J and Saldyt, Lucas and USDOE},
abstractNote = {PyGSTi is a Python package for modeling and characterizing noise (errors) in small quantum information processors. In addition to being a basic framework for describing quantum circuits and noise models, it implements mainstream quantum characterization, verification, and validation (QCVV) protocols such as Gate Set Tomography (GST), Randomized Benchmarking (RB), Robust Phase Estimation, and Idle Tomography. It also implements prototype protocols used for timeseries analysis and crosstalk detection, all of which have the goal of better understanding the noise found in existing as-built experimental devices. The central protocol of pyGSTi (from where it derives its name) is Gate Set Tomography. GST is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the “goodness” of qubits but also a means of debugging (i.e. improving) them. The other protocols follow this similar pattern in that they use statistical inference and analysis of experimental data to estimate one or more properties of the noise in a device.},
url = {https://www.osti.gov//servlets/purl/1543289},
doi = {10.11578/dc.20190722.2},
year = {2019},
month = {7},
note =
}

Software:
Publicly Accessible Repository
https://github.com/pyGSTio/pyGSTi

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