Single-shot ultrafast pulse reconstruction with deep learning

Ron Ziv; Alex Dikopoltsev; Tom Zahavy; Ittai Rubinstein; Pavel Sidorenko; Oren Cohen; Mordechai Segev

doi:10.1364/CLEO_SI.2020.SM3H.4

Single-shot ultrafast pulse reconstruction with deep learning

Ron Ziv^*, Alex Dikopoltsev, Tom Zahavy, Ittai Rubinstein, Pavel Sidorenko, Oren Cohen, Mordechai Segev

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We propose a simple all-in-line single-shot scheme for diagnostics of ultrashort laser pulses, consisting of a multi-mode fiber and a χ⁽²⁾ nonlinear crystal. Complete pulse characterization is done from the measurements using Deep Learning methods.

Original language	English
Title of host publication	CLEO
Subtitle of host publication	Science and Innovations, CLEO_SI 2020
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Print)	9781943580767
DOIs	https://doi.org/10.1364/CLEO_SI.2020.SM3H.4
State	Published - 2020
Externally published	Yes
Event	CLEO: Science and Innovations, CLEO_SI 2020 - Washington, United States Duration: 10 May 2020 → 15 May 2020

Publication series

Name	Optics InfoBase Conference Papers
Volume	Part F183-CLEO-SI 2020
ISSN (Electronic)	2162-2701

Conference

Conference	CLEO: Science and Innovations, CLEO_SI 2020
Country/Territory	United States
City	Washington
Period	10/05/20 → 15/05/20

Access to Document

10.1364/CLEO_SI.2020.SM3H.4

Cite this

Ziv, R., Dikopoltsev, A., Zahavy, T., Rubinstein, I., Sidorenko, P., Cohen, O., & Segev, M. (2020). Single-shot ultrafast pulse reconstruction with deep learning. In CLEO: Science and Innovations, CLEO_SI 2020 Article SM3H.4 (Optics InfoBase Conference Papers; Vol. Part F183-CLEO-SI 2020). Optica Publishing Group (formerly OSA). https://doi.org/10.1364/CLEO_SI.2020.SM3H.4

@inproceedings{df74284cee774e1c939c950416e9c2dc,

title = "Single-shot ultrafast pulse reconstruction with deep learning",

abstract = "We propose a simple all-in-line single-shot scheme for diagnostics of ultrashort laser pulses, consisting of a multi-mode fiber and a χ(2) nonlinear crystal. Complete pulse characterization is done from the measurements using Deep Learning methods.",

author = "Ron Ziv and Alex Dikopoltsev and Tom Zahavy and Ittai Rubinstein and Pavel Sidorenko and Oren Cohen and Mordechai Segev",

note = "Publisher Copyright: {\textcopyright} OSA 2020 {\textcopyright} 2020 The Author(s); CLEO: Science and Innovations, CLEO_SI 2020 ; Conference date: 10-05-2020 Through 15-05-2020",

year = "2020",

doi = "10.1364/CLEO_SI.2020.SM3H.4",

language = "英语",

isbn = "9781943580767",

series = "Optics InfoBase Conference Papers",

publisher = "Optica Publishing Group (formerly OSA)",

booktitle = "CLEO",

}

Ziv, R, Dikopoltsev, A, Zahavy, T, Rubinstein, I, Sidorenko, P, Cohen, O & Segev, M 2020, Single-shot ultrafast pulse reconstruction with deep learning. in CLEO: Science and Innovations, CLEO_SI 2020., SM3H.4, Optics InfoBase Conference Papers, vol. Part F183-CLEO-SI 2020, Optica Publishing Group (formerly OSA), CLEO: Science and Innovations, CLEO_SI 2020, Washington, United States, 10/05/20. https://doi.org/10.1364/CLEO_SI.2020.SM3H.4

Single-shot ultrafast pulse reconstruction with deep learning. / Ziv, Ron; Dikopoltsev, Alex; Zahavy, Tom et al.
CLEO: Science and Innovations, CLEO_SI 2020. Optica Publishing Group (formerly OSA), 2020. SM3H.4 (Optics InfoBase Conference Papers; Vol. Part F183-CLEO-SI 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Single-shot ultrafast pulse reconstruction with deep learning

AU - Ziv, Ron

AU - Dikopoltsev, Alex

AU - Zahavy, Tom

AU - Rubinstein, Ittai

AU - Sidorenko, Pavel

AU - Cohen, Oren

AU - Segev, Mordechai

PY - 2020

Y1 - 2020

N2 - We propose a simple all-in-line single-shot scheme for diagnostics of ultrashort laser pulses, consisting of a multi-mode fiber and a χ(2) nonlinear crystal. Complete pulse characterization is done from the measurements using Deep Learning methods.

AB - We propose a simple all-in-line single-shot scheme for diagnostics of ultrashort laser pulses, consisting of a multi-mode fiber and a χ(2) nonlinear crystal. Complete pulse characterization is done from the measurements using Deep Learning methods.

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U2 - 10.1364/CLEO_SI.2020.SM3H.4

DO - 10.1364/CLEO_SI.2020.SM3H.4

M3 - 会议稿件

AN - SCOPUS:85095409274

SN - 9781943580767

T3 - Optics InfoBase Conference Papers

BT - CLEO

PB - Optica Publishing Group (formerly OSA)

T2 - CLEO: Science and Innovations, CLEO_SI 2020

Y2 - 10 May 2020 through 15 May 2020

ER -

Single-shot ultrafast pulse reconstruction with deep learning

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