Lindblad Tomography of a Superconducting Quantum Processor

Research output: Contribution to journalConference articleResearchpeer-review


  • Gabriel O. Samach
  • Ami Greene
  • Johannes Borregaard
  • Christandl, Matthias
  • Joseph Barreto
  • David K. Kim
  • Christopher M. Mcnally
  • Alexander Melville
  • Bethany M. Niedzielski
  • Youngkyu Sung
  • Danna Rosenberg
  • Mollie E. Schwartz
  • Jonilyn L. Yoder
  • Terry P. Orlando
  • Joel I-jan Wang
  • Simon Gustavsson
  • Kjaergaard, Morten
  • William D. Oliver
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.
Original languageEnglish
Article number064056
JournalPhysical Review Applied
Issue number6
Number of pages24
Publication statusPublished - 2022

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