Convolutional neural network reconstruction of ultrashort optical pulses

Joshua Noble; Chen Zhou; William Murray; Zhiwen Liu

doi:10.1117/12.2571172

20 August 2020 Convolutional neural network reconstruction of ultrashort optical pulses

Joshua Noble, Chen Zhou, William Murray, Zhiwen Liu

Proceedings Volume 11497, Ultrafast Nonlinear Imaging and Spectroscopy VIII; 114970L (2020) https://doi.org/10.1117/12.2571172
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

Ultrashort pulse characterization and measurement is critical in the field of ultrafast and nonlinear optics. Here we present a method to reconstruct the complex pulse profile using a colinear frequency resolved optical gating (CFROG) acquisition combined with a convolutional neural network (CNN). The CFROG approach can be implemented with nonlinear nanoprobes for probing complex ultrafast optical fields. Typically, a CFROG trace is filtered and converted to a standard FROG trace which can then be processed by using the FROG retrieval algorithm to reconstruct both the amplitude and the phase profiles of the pulse. In this method, however, the reconstruction is often dependent on the subjective filtering step. In our approach, a CNN is trained with simulated unfiltered CFROG traces. Furthermore, we customize the CNN architecture to mitigate the ambiguity in the solution space and minimizes the error between the predicted and the input

Conference Presentation

Citation Download Citation

Joshua Noble, Chen Zhou, William Murray, and Zhiwen Liu "Convolutional neural network reconstruction of ultrashort optical pulses", Proc. SPIE 11497, Ultrafast Nonlinear Imaging and Spectroscopy VIII, 114970L (20 August 2020); https://doi.org/10.1117/12.2571172

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