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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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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. |
format | Online Article Text |
id | pubmed-5529523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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