Application of artificial neural networks to the measurement of ultrashort laser pulses

被引:0
|
作者
Krumbugel, MA
Trebino, R
Searcy, ML
Cooley, DH
Cheng, HD
机构
关键词
FROG; ultrashort laser pulse; phase retrieval; neural network; feature extraction; integral moments; wavelets;
D O I
10.1117/12.271494
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Frequency-resolved optical gating (FROG) is a technique for measuring the intensity and phase of ultrashort laser pulses. In FROG, a spectrogram of the pulse is produced from which the intensity and phase of the pulse's electric field is then retrieved using an iterative algorithm. This iterative algorithm performs well for all types of pulses, but it sometimes requires more than a minute to converge, and faster retrieval is desired for many applications. As a faster alternative, we therefore employed a neural network to invert the function that relates the pulse intensity and phase to its FROG trace. In previous work, we showed that a neural network can retrieve simple pulses, described by four or six parameters, rapidly and directly. In this contribution, we discuss our latest attempts to train an artificial neural network for more complex pulse shapes.
引用
收藏
页码:333 / 342
页数:10
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