The University of Southampton
University of Southampton Institutional Repository

Improving readout of a superconducting qubit using the path signature method

Improving readout of a superconducting qubit using the path signature method
Improving readout of a superconducting qubit using the path signature method
One major challenge in quantum computing is to implement fast, high-accuracy quantum state readout. For superconducting circuits, this problem reduces to a time series classification problem [1]. We propose that using path signature methods to extract features can enhance existing techniques for quantum state discrimination [2]. We demonstrate the superior performance of our proposed approach over conventional methods in distinguishing three different quantum states on real experimental data from a superconducting transmon qubit.
0003-0503
Cao, Shuxiang
6cd16673-7545-490d-86ab-30410feb2ad1
Shao, Zhen
8d349f5c-2295-4471-bd7b-52b6a9bf9cc1
Zheng, Jian-Qing
06ac8c6e-d3a5-42d6-a933-992975a30675
Alghadeer, Mohammed
b38fb4f2-8402-4b8d-91a3-1c311fbcdb34
Fasciati, Simone D.
1c075964-4477-4027-b516-697372be3af9
Piscitelli, Michele
1e9e726d-e40a-4ecb-8f39-4cb374723a34
Taravati, Sajjad
0026f25d-c919-4273-b956-8fe9795b31ce
Bakr, Mustafa S.
e9ad9391-8122-49f3-85f2-c945c10d8300
Lyons, Terry
941d109b-1877-42a7-9d8b-547c61403c7e
Leek, Peter J.
83bec238-7cf7-4a5a-a650-c49d4584b284
Cao, Shuxiang
6cd16673-7545-490d-86ab-30410feb2ad1
Shao, Zhen
8d349f5c-2295-4471-bd7b-52b6a9bf9cc1
Zheng, Jian-Qing
06ac8c6e-d3a5-42d6-a933-992975a30675
Alghadeer, Mohammed
b38fb4f2-8402-4b8d-91a3-1c311fbcdb34
Fasciati, Simone D.
1c075964-4477-4027-b516-697372be3af9
Piscitelli, Michele
1e9e726d-e40a-4ecb-8f39-4cb374723a34
Taravati, Sajjad
0026f25d-c919-4273-b956-8fe9795b31ce
Bakr, Mustafa S.
e9ad9391-8122-49f3-85f2-c945c10d8300
Lyons, Terry
941d109b-1877-42a7-9d8b-547c61403c7e
Leek, Peter J.
83bec238-7cf7-4a5a-a650-c49d4584b284

Cao, Shuxiang, Shao, Zhen, Zheng, Jian-Qing, Alghadeer, Mohammed, Fasciati, Simone D., Piscitelli, Michele, Taravati, Sajjad, Bakr, Mustafa S., Lyons, Terry and Leek, Peter J. (2024) Improving readout of a superconducting qubit using the path signature method. Bulletin of the American Physical Society, [G47.00004].

Record type: Meeting abstract

Abstract

One major challenge in quantum computing is to implement fast, high-accuracy quantum state readout. For superconducting circuits, this problem reduces to a time series classification problem [1]. We propose that using path signature methods to extract features can enhance existing techniques for quantum state discrimination [2]. We demonstrate the superior performance of our proposed approach over conventional methods in distinguishing three different quantum states on real experimental data from a superconducting transmon qubit.

This record has no associated files available for download.

More information

Published date: 5 March 2024
Venue - Dates: APS March Meeting 2024, Minneapolis Convention Center, Minneapolis, United States, 2024-03-04 - 2024-03-08

Identifiers

Local EPrints ID: 486888
URI: http://eprints.soton.ac.uk/id/eprint/486888
ISSN: 0003-0503
PURE UUID: e7a87cb1-2b6a-4c92-88d0-86396b9bde4d
ORCID for Sajjad Taravati: ORCID iD orcid.org/0000-0003-3992-0050

Catalogue record

Date deposited: 08 Feb 2024 17:34
Last modified: 29 Apr 2024 02:04

Export record

Contributors

Author: Shuxiang Cao
Author: Zhen Shao
Author: Jian-Qing Zheng
Author: Mohammed Alghadeer
Author: Simone D. Fasciati
Author: Michele Piscitelli
Author: Sajjad Taravati ORCID iD
Author: Mustafa S. Bakr
Author: Terry Lyons
Author: Peter J. Leek

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×