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QInfer: Statistical inference software for quantum applications

delete2017-04-25
delete36
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OA
AI
C
Christopher Granade *
C
Christopher Ferrie
I
Ian Hincks
S
Steven Casagrande
T
Thomas Alexander
J
Jonathan A. Gross
M
Michal Kononenko
Y
Yuval R. Sanders
DOI:10.22331/q-2017-04-25-5delete
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摘要

摘要

En 中文
Characterizing quantum systems through experimental data is critical to applications as diverse as metrology and quantum computing. Analyzing this experimental data in a robust and reproducible manner is made challenging, however, by the lack of readily-available software for performing principled statistical analysis. We improve the robustness and reproducibility of characterization by introducing an open-source library, QInfer, to address this need. Our library makes it easy to analyze data from tomography, randomized benchmarking, and Hamiltonian learning experiments either in post-processing, or online as data is acquired. QInfer also provides functionality for predicting the performance of proposed experimental protocols from simulated runs. By delivering easy-to-use characterization tools based on principled statistical analysis, Qlnfer helps address many outstanding challenges facing quantum technology.

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Quantum
IF:
5.4
论文数:
974
被引数:
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U
University of Sydney
学者数:
6.5W
论文数: 6.2W
被引数: 90
U
university of technology sydney
学者数:
1.6W
论文数: 2.0W
被引数: 25
U
university of new mexico
学者数:
1.6W
论文数: 1.3W
被引数: 25
U
University of Waterloo
学者数:
2.2W
论文数: 2.3W
被引数: 3.3W
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