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Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering

Selective detection of signal over noise is essential to measurement and signal processing. Time-frequency filtering has been the standard approach for the optimal detection of non-stationary signals. However, there is a fundamental tradeoff between the signal detection efficiency and the amount of...

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Autores principales: Shahverdi, Amin, Sua, Yong Meng, Tumeh, Lubna, Huang, Yu-Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529523/
https://www.ncbi.nlm.nih.gov/pubmed/28747645
http://dx.doi.org/10.1038/s41598-017-06564-7
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author Shahverdi, Amin
Sua, Yong Meng
Tumeh, Lubna
Huang, Yu-Ping
author_facet Shahverdi, Amin
Sua, Yong Meng
Tumeh, Lubna
Huang, Yu-Ping
author_sort Shahverdi, Amin
collection PubMed
description Selective detection of signal over noise is essential to measurement and signal processing. Time-frequency filtering has been the standard approach for the optimal detection of non-stationary signals. However, there is a fundamental tradeoff between the signal detection efficiency and the amount of undesirable noise detected simultaneously, which restricts its uses under weak signal yet strong noise conditions. Here, we demonstrate quantum parametric mode sorting based on nonlinear optics at the edge of phase matching to improve the tradeoff. By tailoring the nonlinear process in a commercial lithium-niobate waveguide through optical arbitrary waveform generation, we demonstrate highly selective detection of picosecond signals overlapping temporally and spectrally but in orthogonal time-frequency modes as well as against broadband noise, with performance well exceeding the theoretical limit of the optimized time-frequency filtering. We also verify that our device does not introduce any significant quantum noise to the detected signal and demonstrate faithful detection of pico-second single photons. Together, these results point to unexplored opportunities in measurement and signal processing under challenging conditions, such as photon-starving quantum applications.
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spelling pubmed-55295232017-08-02 Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering Shahverdi, Amin Sua, Yong Meng Tumeh, Lubna Huang, Yu-Ping Sci Rep Article Selective detection of signal over noise is essential to measurement and signal processing. Time-frequency filtering has been the standard approach for the optimal detection of non-stationary signals. However, there is a fundamental tradeoff between the signal detection efficiency and the amount of undesirable noise detected simultaneously, which restricts its uses under weak signal yet strong noise conditions. Here, we demonstrate quantum parametric mode sorting based on nonlinear optics at the edge of phase matching to improve the tradeoff. By tailoring the nonlinear process in a commercial lithium-niobate waveguide through optical arbitrary waveform generation, we demonstrate highly selective detection of picosecond signals overlapping temporally and spectrally but in orthogonal time-frequency modes as well as against broadband noise, with performance well exceeding the theoretical limit of the optimized time-frequency filtering. We also verify that our device does not introduce any significant quantum noise to the detected signal and demonstrate faithful detection of pico-second single photons. Together, these results point to unexplored opportunities in measurement and signal processing under challenging conditions, such as photon-starving quantum applications. Nature Publishing Group UK 2017-07-26 /pmc/articles/PMC5529523/ /pubmed/28747645 http://dx.doi.org/10.1038/s41598-017-06564-7 Text en © The Author(s) 2017 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/.
spellingShingle Article
Shahverdi, Amin
Sua, Yong Meng
Tumeh, Lubna
Huang, Yu-Ping
Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering
title Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering
title_full Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering
title_fullStr Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering
title_full_unstemmed Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering
title_short Quantum Parametric Mode Sorting: Beating the Time-Frequency Filtering
title_sort quantum parametric mode sorting: beating the time-frequency filtering
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529523/
https://www.ncbi.nlm.nih.gov/pubmed/28747645
http://dx.doi.org/10.1038/s41598-017-06564-7
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