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Parametric Quantum Noise Spectroscopy Using SchWARMA

ORAL

Abstract

Markovian noise is a fundamental assumption in many characterization and analysis protocols for quantum circuits. However, this assumption is generally not valid in reality, which has led to considerable efforts to characterize and alleviate temporally correlated errors. Here, we adapt techniques from classical time series analysis to model, simulate, and estimate non-Markovian noise. We call this family of techniques Schrodinger Wave ARMA (SchWARMA), and show that it is not only a flexible method for representing noise spectra, but that it is a powerful statistical model that can be used for estimating noise and predicting the effects of non-Markovian noise on quantum circuits.

Presenters

  • Kevin Schultz

    Johns Hopkins University Applied Physics Lab, Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory

Authors

  • Kevin Schultz

    Johns Hopkins University Applied Physics Lab, Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory

  • Gregory Quiroz

    Johns Hopkins University Applied Physics Lab, Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory, Johns Hopkins University

  • David Clader

    Applied Phys Lab/JHU, Johns Hopkins University Applied Physics Laboratory, Johns Hopkins University Applied Physics Lab