Lindblad Tomography of a Superconducting Quantum Processor

Dr Gabriel O. Samach
Graduate Fellow, Engineering Quantum Systems Group, MIT
Associate Staff Scientist, Quantum Information and Integrated Nanosystems Group, MIT Lincoln Laboratory

Abstract
"As progress is made towards the first generation of error-corrected quantum computers, careful characterization of a processor’s noise environment will be crucial to designing tailored, low-overhead error correction protocols. 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 multi-qubit loss channels responsible for processor errors, which can be described more fully by a Lindblad operator in the master equation formalism.

In this talk, I outline and present the results of the first experimental demonstration of Lindblad Tomography, a hardware-agnostic characterization protocol for tomographically reconstructing the Hamiltonian and Lindblad operators of a quantum channel from an ensemble of time-domain measurements [1]. Performing Lindblad Tomography on a small superconducting quantum processor, we show that this technique characterizes and accounts for state-preparation and measurement (SPAM) errors and allows one to place strong bounds on the degree of non-Markovianity in the channels of interest. 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."

[1] G. O. Samach, A. Greene, J. Borregaard, M. Christandl, D. K. Kim, C. M. McNally, A. Melville, B. M. Niedzielski, Y. Sung, D. Rosenberg, M. E. Schwartz, J. L. Yoder, T. P. Orlando, J. I-Jan Wang, S. Gustavsson, M. Kjaergaard, W. D. Oliver, Lindblad Tomography of a Superconducting Quantum Processor, arXiv: 2105.02338 (2021)