Deep Learning Reconstruction of Ultra-Short Pulses

March 15, 2018 Β· Declared Dead Β· πŸ› 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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