Video URL

https://pirsa.org/15100120

Fault-tolerant error correction with the gauge color code

Brown, B. (2015). Fault-tolerant error correction with the gauge color code. Perimeter Institute for Theoretical Physics. https://pirsa.org/15100120

Brown, Benjamin. Fault-tolerant error correction with the gauge color code. Perimeter Institute for Theoretical Physics, Oct. 29, 2015, https://pirsa.org/15100120 

          @misc{ scivideos_PIRSA:15100120,
            doi = {10.48660/15100120},
            url = {https://pirsa.org/15100120},
            author = {Brown, Benjamin},
            keywords = {Quantum Information},
            language = {en},
            title = {Fault-tolerant error correction with the gauge color code},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2015},
            month = {oct},
            note = {PIRSA:15100120 see, \url{https://scivideos.org/pirsa/15100120}}
          }

Benjamin Brown University of Sydney

DOI 10.48660/15100120
Source Repository PIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

The gauge color code is a quantum error-correcting code with local syndrome measurements that, remarkably, admits a universal transversal gate set without the need for resource-intensive magic state distillation. A result of recent interest, proposed by Bombin, shows that the subsystem structure of the gauge color code admits an error-correction protocol that achieves tolerance to noisy measurements without the need for repeated measurements, so called single-shot error correction. Here, we demonstrate the promise of single-shot error correction by designing a two-part decoder and investigate its performance. We simulate fault-tolerant error correction with the gauge color code by repeatedly applying our proposed error-correction protocol to deal with errors that occur continuously to the underlying physical qubits of the code over the duration that quantum information is stored. We estimate a sustainable error rate, i.e. the threshold for the long time limit, of ~0.31% for a phenomenological noise model using a simple decoding algorithm.