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

authored by

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.

Organisation(s)

Institute of Quantum Optics
PhoenixD: Photonics, Optics, and Engineering - Innovation Across Disciplines

External Organisation(s)

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

Type

Article

Journal

Optics Letters

Volume

44

Pages

979-982

No. of pages

4

ISSN

0146-9592

Publication date

15.02.2019

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics

Electronic version(s)

https://doi.org/10.1364/ol.44.000979 (Access: Closed)