Rapid phase retrieval of ultrashort pulses from dispersion scan traces using deep neural networks

verfasst von

Sven Kleinert, Ayhan Tajalli, Tamas Nagy, Uwe Morgner

Abstract

The knowledge of the temporal shape of femtosecond pulses is of major interest for all their applications. The reconstruction of the temporal shape of these pulses is an inverse problem for characterization techniques, which benefit from an inherent redundancy in the measurement. Conventionally, time-consuming optimization algorithms are used to solve the inverse problems. Here, we demonstrate the reconstruction of ultrashort pulses from dispersion scan traces employing a deep neural network. The network is trained with a multitude of artificial and noisy dispersion scan traces from randomly shaped pulses. The retrieval takes only 16 ms enabling video-rate reconstructions. This approach reveals a great tolerance against noisy conditions, delivering reliable retrievals from traces with signal-to-noise ratios down to 5.

Organisationseinheit(en)

Institut für Quantenoptik
PhoenixD: Simulation, Fabrikation und Anwendung optischer Systeme

Externe Organisation(en)

Max-Born-Institut für Nichtlineare Optik und Kurzzeitspektroskopie (MBI)
Laser Zentrum Hannover e.V. (LZH)

Typ

Artikel

Journal

Optics Letters

Band

44

Seiten

979-982

Anzahl der Seiten

4

ISSN

0146-9592

Publikationsdatum

15.02.2019

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Atom- und Molekularphysik sowie Optik

Elektronische Version(en)

https://doi.org/10.1364/ol.44.000979 (Zugang: Geschlossen)