Error Mitigation, Optimization, and Extrapolation on a Trapped Ion Testbed
ORAL
Abstract
Zero Noise Extrapolation (ZNE) is useful as an error mitigation technique because it is broadly applicable to a variety of quantum devices and applications. We test three implementations of ZNE on the Quantum Scientific Computing Open User Testbed (QSCOUT) ion-trap device at Sandia National Laboratories. We study ZNE in the context of the Variational Quantum Eigensolver (VQE), specifically using VQE to solve the electronic structure problem for HeH+. Our experimental results show that a naive implementation of ZNE via increasing the duration of our two-qubit gates does not scale our device noise enough for extrapolation. Similarly, scaling the two-qubit gate detuning only accounted for some of the noise present in our experiment. Instead, a gate-based, unitary folding noise scaling approach wherein two-qubit identity operations are added to the circuit proved amenable to error mitigation. Fitting a linear function to this data, we obtained noiseless energy estimates with 30x less error than an unmitigated estimate, 4 millihartree away from the ground state energy. This result shows that while ZNE can be used on almost any device, it is important to tailor noise scaling methods to the hardware. In addition, ZNE can be used as a practical benchmark for probing the most dominant sources of noise in experiment.
*Sandia National Laboratories is managed and operated by NTESS, LLC, a subsidiary of Honeywell International, Inc. for the US DOE NNSA under contract DE-NA0003525. This work is funded by the US DOE Office of Science ASCR Quantum Testbed Program. This work was done in collaboration with Infleqtion, funded in part by the US DOE Office of Science ASCR under award DE-SC0021526. The views expressed here do not necessarily represent the views of the DOE or the US Government. SAND2023-XXXXX.
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Publication:Maupin, Oliver G., et al. "Error mitigation, optimization, and extrapolation on a trapped ion testbed." arXiv preprint arXiv:2307.07027 (2023).
Presenters
Oliver Maupin
Tufts University
Authors
Oliver Maupin
Tufts University
Ashlyn D Burch
Sandia National Laboratories
Christopher G Yale
Sandia National Laboratories
Brandon P Ruzic
Sandia National Laboratories
Antonio E Russo
Sandia National Laboratories, Sandia National Lab
Daniel S Lobser
Sandia National Laboratories
Melissa C Revelle
Sandia National Laboratories
Matthew N Chow
Sandia National Labs; University of New Mexico; CQuIC