Recent advances on time-stretch dispersive Fourier transform and its applications

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Godin, T.; Sader, L.; Khodadad Kashi, A.; Hanzard, P.-H.; Hideur, A. et al.: Recent advances on time-stretch dispersive Fourier transform and its applications. In: Advances in Physics: X : APX 7 (2022), Nr. 1, 2067487. DOI: https://doi.org/10.1080/23746149.2022.2067487

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/12817

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Sum total of downloads: 31




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Abstract: 
The need to measure high repetition rate ultrafast processes cuts across multiple areas of science. The last decade has seen tremendous advances in the development and application of new techniques in this field, as well as many breakthrough achievements analyzing non-repetitive optical phenomena. Several approaches now provide convenient access to single-shot optical waveform characterization, including the dispersive Fourier transform (DFT) and time-lens techniques, which yield real-time ultrafast characterization in the spectral and temporal domains, respectively. These complementary approaches have already proven to be highly successful to gain insight into numerous optical phenomena including the emergence of extreme events and characterizing the complexity of laser evolution dynamics. However, beyond the study of these fundamental processes, real-time measurements have also been driven by particular applications ranging from spectroscopy to velocimetry, while shedding new light in areas spanning ultrafast imaging, metrology or even quantum science. Here, we review a number of landmark results obtained using DFT-based technologies, including several recent advances and key selected applications. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Fakultät für Mathematik und Physik

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pos. country downloads
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1 image of flag of Germany Germany 16 51.61%
2 image of flag of United States United States 6 19.35%
3 image of flag of China China 3 9.68%
4 image of flag of No geo information available No geo information available 1 3.23%
5 image of flag of Taiwan Taiwan 1 3.23%
6 image of flag of Russian Federation Russian Federation 1 3.23%
7 image of flag of Italy Italy 1 3.23%
8 image of flag of Hungary Hungary 1 3.23%
9 image of flag of Czech Republic Czech Republic 1 3.23%

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