Lindblad Tomography of a Superconducting Quantum Processor

Journal Article (2022)
Author(s)

Gabriel O. Samach (Massachusetts Institute of Technology)

Ami Greene (Massachusetts Institute of Technology)

Johannes Borregaard (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences, University of Copenhagen)

Matthias Christandl (University of Copenhagen)

Joseph Barreto (Student TU Delft, Kavli institute of nanoscience Delft)

David K. Kim (Massachusetts Institute of Technology)

Christopher M. McNally (Massachusetts Institute of Technology)

Alexander Melville (Massachusetts Institute of Technology)

Bethany M. Niedzielski (Massachusetts Institute of Technology)

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Research Group
QN/Borregaard groep
DOI related publication
https://doi.org/10.1103/PhysRevApplied.18.064056 Final published version
More Info
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Publication Year
2022
Language
English
Research Group
QN/Borregaard groep
Issue number
6
Volume number
18
Article number
064056
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369
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Abstract

As progress is made towards the first generation of error-corrected quantum computers, robust characterization and validation protocols are required to assess the noise environments of physical quantum processors. While standard coherence metrics and characterization protocols such as T1 and T2, process tomography, and randomized benchmarking are now ubiquitous, these techniques provide only partial information about the dynamic multiqubit loss channels responsible for processor errors, which can be described more fully by a Lindblad operator in the master equation formalism. Here, we introduce and experimentally demonstrate Lindblad tomography, a hardware-agnostic characterization protocol for tomographically reconstructing the Hamiltonian and Lindblad operators of a quantum noise environment from an ensemble of time-domain measurements. Performing Lindblad tomography on a small superconducting quantum processor, we show that this technique naturally builds on standard process tomography and T1/T2 measurement protocols, characterizes and accounts for state-preparation and measurement errors, and allows one to place bounds on the fit to a Markovian model. Comparing the results of single- and two-qubit measurements on a superconducting quantum processor, we demonstrate that Lindblad tomography can also be used to identify and quantify sources of crosstalk on quantum processors, such as the presence of always-on qubit-qubit interactions.