Modeling noise and error correction for Majorana-based quantum computing
Christina Knapp, Michael Beverland, Dmitry I. Pikulin, Torsten Karzig

TL;DR
This paper develops and analyzes noise models specific to Majorana-based quantum computing, connecting physical error processes to fault tolerance thresholds and highlighting the role of correlated errors and quasiparticle dynamics.
Contribution
It introduces stochastic Majorana noise models that relate physical error parameters to standard fault tolerance models, enabling more accurate error correction analysis.
Findings
Pseudo-thresholds for Bacon-Shor code computed
Correlated errors significantly impact error correction
Fast quasiparticle relaxation allows Pauli error approximation
Abstract
Majorana-based quantum computing seeks to use the non-local nature of Majorana zero modes to store and manipulate quantum information in a topologically protected way. While noise is anticipated to be significantly suppressed in such systems, finite temperature and system size result in residual errors. In this work, we connect the underlying physical error processes in Majorana-based systems to the noise models used in a fault tolerance analysis. Standard qubit-based noise models built from Pauli operators do not capture leading order noise processes arising from quasiparticle poisoning events, thus it is not obvious {\it a priori} that such noise models can be usefully applied to a Majorana-based system. We develop stochastic Majorana noise models that are generalizations of the standard qubit-based models and connect the error probabilities defining these models to parameters of the…
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