Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/173863
Title: Extracting quantum dynamical resources: consumption of non-Markovianity for noise reduction
Authors: Berk, Graeme D.
Milz, Simon
Pollock, Felix A.
Modi, Kavan
Keywords: Physics
Issue Date: 2023
Source: Berk, G. D., Milz, S., Pollock, F. A. & Modi, K. (2023). Extracting quantum dynamical resources: consumption of non-Markovianity for noise reduction. Npj Quantum Information, 9(1). https://dx.doi.org/10.1038/s41534-023-00774-w
Project: NRF2021-QEP2-02-P06 
RG146/20 
Journal: npj Quantum Information 
Abstract: A great many efforts are dedicated to developing noise reduction and mitigation methods. One remarkable achievement in this direction is dynamical decoupling (DD), although its applicability remains limited because fast control is required. Using resource theoretic tools, we show that non-Markovianity is a resource for noise reduction, raising the possibility that it can be leveraged for noise reduction where traditional DD methods fail. We propose a non-Markovian optimisation technique for finding DD pulses. Using a prototypical noise model, we numerically demonstrate that our optimisation-based methods are capable of drastically improving the exploitation of temporal correlations, extending the timescales at which noise suppression is viable by at least two orders of magnitude, compared to traditional DD which does not use any knowledge of the non-Markovian environment. Importantly, the corresponding tools are built on operational grounds and can be easily implemented to reduce noise in the current generation of quantum devices.
URI: https://hdl.handle.net/10356/173863
ISSN: 2056-6387
DOI: 10.1038/s41534-023-00774-w
Schools: School of Physical and Mathematical Sciences 
Research Centres: Nanyang Quantum Hub
Rights: © The Author(s) 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http:// creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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