Operational, gauge-free quantum tomography
Abstract
As increasingly impressive quantum information processors are realized in laboratories around the world, robust and reliable characterization of these devices is now more urgent than ever. These diagnostics can take many forms, but one of the most popular categories is tomography, where an underlying parameterized model is proposed for a device and inferred by experiments. Here, we introduce and implement efficient operational tomography, which uses experimental observables as these model parameters. This addresses a problem of ambiguity in representation that arises in current tomographic approaches (the gauge problem). Solving the gauge problem enables us to efficiently implement operational tomography in a Bayesian framework computationally, and hence gives us a natural way to include prior information and discuss uncertainty in fit parameters. We demonstrate this new tomography in a variety of different experimentally-relevant scenarios, including standard process tomography, Ramsey interferometry, randomized benchmarking, and gate set tomography.
- Authors:
-
- TRIUMF, Vancouver, BC (Canada); Univ. of Waterloo, ON (Canada)
- Microsoft Research, Redmond, WA (United States). Quantum Architectures and Computation Group
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Microsoft Research, Redmond, WA (United States). Quantum Architectures and Computation Group; Univ. of Washington, Seattle, WA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1725845
- Report Number(s):
- SAND-2020-12530J
Journal ID: ISSN 2521-327X; 692239; TRN: US2204867
- Grant/Contract Number:
- AC04-94AL85000; NA0003525
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Quantum
- Additional Journal Information:
- Journal Volume: 4; Journal ID: ISSN 2521-327X
- Publisher:
- Quantum Science Open Community
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
Citation Formats
Di Matteo, Olivia, Gamble, John, Granade, Chris, Rudinger, Kenneth, and Wiebe, Nathan. Operational, gauge-free quantum tomography. United States: N. p., 2020.
Web. doi:10.22331/q-2020-11-17-364.
Di Matteo, Olivia, Gamble, John, Granade, Chris, Rudinger, Kenneth, & Wiebe, Nathan. Operational, gauge-free quantum tomography. United States. https://doi.org/10.22331/q-2020-11-17-364
Di Matteo, Olivia, Gamble, John, Granade, Chris, Rudinger, Kenneth, and Wiebe, Nathan. Tue .
"Operational, gauge-free quantum tomography". United States. https://doi.org/10.22331/q-2020-11-17-364. https://www.osti.gov/servlets/purl/1725845.
@article{osti_1725845,
title = {Operational, gauge-free quantum tomography},
author = {Di Matteo, Olivia and Gamble, John and Granade, Chris and Rudinger, Kenneth and Wiebe, Nathan},
abstractNote = {As increasingly impressive quantum information processors are realized in laboratories around the world, robust and reliable characterization of these devices is now more urgent than ever. These diagnostics can take many forms, but one of the most popular categories is tomography, where an underlying parameterized model is proposed for a device and inferred by experiments. Here, we introduce and implement efficient operational tomography, which uses experimental observables as these model parameters. This addresses a problem of ambiguity in representation that arises in current tomographic approaches (the gauge problem). Solving the gauge problem enables us to efficiently implement operational tomography in a Bayesian framework computationally, and hence gives us a natural way to include prior information and discuss uncertainty in fit parameters. We demonstrate this new tomography in a variety of different experimentally-relevant scenarios, including standard process tomography, Ramsey interferometry, randomized benchmarking, and gate set tomography.},
doi = {10.22331/q-2020-11-17-364},
journal = {Quantum},
number = ,
volume = 4,
place = {United States},
year = {Tue Nov 17 00:00:00 EST 2020},
month = {Tue Nov 17 00:00:00 EST 2020}
}
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