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

verfasst von

Sven Kleinert, Ayhan Tajalli, Tamas Nagy, Uwe Morgner

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].

Organisationseinheit(en)

Institut für Quantenoptik
PhoenixD: Simulation, Fabrikation und Anwendung optischer Systeme
Hannoversches Zentrum für Optische Technologien (HOT)

Externe Organisation(en)

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

Typ

Aufsatz in Konferenzband

Publikationsdatum

2019

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Elektronische, optische und magnetische Materialien, Werkstoffmechanik

Elektronische Version(en)

https://doi.org/10.1109/CLEOE-EQEC.2019.8872570 (Zugang: Geschlossen)