Deep Learning Reconstruction of Ultra-Short Pulses
March 15, 2018 Β· Declared Dead Β· π Conference on Lasers and Electro-Optics
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Authors
Tom Zahavy, Alex Dikopoltsev, Oren Cohen, Shie Mannor, Mordechai Segev
arXiv ID
1803.06024
Category
physics.optics
Cross-listed
cs.AI,
cs.LG,
stat.ML
Citations
146
Venue
Conference on Lasers and Electro-Optics
Last Checked
1 month ago
Abstract
Ultra-short laser pulses with femtosecond to attosecond pulse duration are the shortest systematic events humans can create. Characterization (amplitude and phase) of these pulses is a key ingredient in ultrafast science, e.g., exploring chemical reactions and electronic phase transitions. Here, we propose and demonstrate, numerically and experimentally, the first deep neural network technique to reconstruct ultra-short optical pulses. We anticipate that this approach will extend the range of ultrashort laser pulses that can be characterized, e.g., enabling to diagnose very weak attosecond pulses.
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