Conditional variational generative network for attosecond pulse retrieval

Zheyuan Zhu; Jonathon White; Zenghu Chang; Sean Pang

doi:10.1364/COSI.2022.CF2C.4

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper CF2C.4
•https://doi.org/10.1364/COSI.2022.CF2C.4

Conditional variational generative network for attosecond pulse retrieval

Zheyuan Zhu, Jonathon White, Zenghu Chang, and Sean Pang

Computational Optical Sensing and Imaging 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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Spectral Imaging and Machine Learning for Sensing and Imaging (Joint Theme COSI and LACSEA on Machine Learning) (CF2C)

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Z. Zhu, J. White, Z. Chang, and S. Pang, "Conditional variational generative network for attosecond pulse retrieval," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper CF2C.4.

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Abstract

We present a conditional variational generative network (CVGN) for characterizing attosecond XUV pulses from noisy streaking traces. CVGN captures the uncertainty and ambiguity arising from the streaking process, providing guidelines to attosecond pump-probe experiments.

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