Video-rate phase retrievals from dispersion scan traces using artificial neural networks

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

External Research Organisations

  • Max Born Institute for Nonlinear Optics and Short Pulse Spectroscopy im Forschungsbund Berlin e.V. (MBI)
  • Laser Zentrum Hannover e.V. (LZH)
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Details

Original languageEnglish
Title of host publicationThe European Conference on Lasers and Electro-Optics, CLEO_Europe_2019
ISBN (electronic)978-1-7281-0469-0
Publication statusPublished - 2019
EventThe European Conference on Lasers and Electro-Optics, CLEO_Europe_2019 - Munich, Germany
Duration: 23 Jun 201927 Jun 2019

Abstract

The full characterization of ultrashort pulses is crucial for all their applications. Lately, the dispersion scan (d-scan) technique has been developed, which stands out by its simplicity [1, 2]. Therefore, it is a promising candidate for a low-maintenance pulse characterization technique. The reconstruction of the spectral phase from a d-scan measurement relies on optimization algorithms [3, 4]. Considering the fact that the spectral phase of the pulses is directly imprinted on the d-scan trace, the phase reconstruction can also be regarded as an image recognition task. During the last few years, artificial neural networks have shown excellent performance in different fileds, e.g. image recognition [5].

ASJC Scopus subject areas

Cite this

Video-rate phase retrievals from dispersion scan traces using artificial neural networks. / Kleinert, Sven; Tajalli, Ayhan; Nagy, Tamas et al.
The European Conference on Lasers and Electro-Optics, CLEO_Europe_2019. 2019. 2019-cf_6_3.

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Kleinert, S, Tajalli, A, Nagy, T & Morgner, U 2019, Video-rate phase retrievals from dispersion scan traces using artificial neural networks. in The European Conference on Lasers and Electro-Optics, CLEO_Europe_2019., 2019-cf_6_3, The European Conference on Lasers and Electro-Optics, CLEO_Europe_2019, Munich, Germany, 23 Jun 2019. https://doi.org/10.1109/CLEOE-EQEC.2019.8872570
Kleinert, S., Tajalli, A., Nagy, T., & Morgner, U. (2019). Video-rate phase retrievals from dispersion scan traces using artificial neural networks. In The European Conference on Lasers and Electro-Optics, CLEO_Europe_2019 Article 2019-cf_6_3 https://doi.org/10.1109/CLEOE-EQEC.2019.8872570
Kleinert S, Tajalli A, Nagy T, Morgner U. Video-rate phase retrievals from dispersion scan traces using artificial neural networks. In The European Conference on Lasers and Electro-Optics, CLEO_Europe_2019. 2019. 2019-cf_6_3 doi: 10.1109/CLEOE-EQEC.2019.8872570
Kleinert, Sven ; Tajalli, Ayhan ; Nagy, Tamas et al. / Video-rate phase retrievals from dispersion scan traces using artificial neural networks. The European Conference on Lasers and Electro-Optics, CLEO_Europe_2019. 2019.
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abstract = "The full characterization of ultrashort pulses is crucial for all their applications. Lately, the dispersion scan (d-scan) technique has been developed, which stands out by its simplicity [1, 2]. Therefore, it is a promising candidate for a low-maintenance pulse characterization technique. The reconstruction of the spectral phase from a d-scan measurement relies on optimization algorithms [3, 4]. Considering the fact that the spectral phase of the pulses is directly imprinted on the d-scan trace, the phase reconstruction can also be regarded as an image recognition task. During the last few years, artificial neural networks have shown excellent performance in different fileds, e.g. image recognition [5].",
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