Abstract
Deep ultraviolet lasers based on the phenomenon of mode-locking have been used widely in many areas in recent years, for example, in semiconductors, the environment and biomedicine. In the development of a mode-locked deep ultraviolet laser, one of the most important aspects is to optimize the multiple parameters of the complex system. Traditional optimization methods require experimenters with more optimization experience, which limits the wide application of the lasers. In this study, we optimize the deep ultraviolet mode-locked laser system using an online neural network to solve this problem. The neural network helps us control the position of the crystal, the length of the cavity, the position of the focusing lens and the temperature of the frequency doubling crystal. We generate a deep ultraviolet mode-locked laser with a power of 18 mW and a spectral center at 205 nm. This result is greatly improved compared to previous results with the same pump power. This technology provides a universal solution to multiparameter problems in the optimization of lasers.
Highlights
Deep ultraviolet (DUV) lasers have many practical applications in many fields
The frequency doubling of a mode-locked laser (MLL) is a viable way to obtain a stable DUV laser
Many recent studies[29,30,31,32,33,34] have used neural networks to solve the multiparameter adjustment problem of complex systems in experiments and have shown great advantages over human. These techniques are utilized in lasers and related applications, such as laser cutting[35], optical communication[36,37] and mode-locked laser[38]
Summary
Deep ultraviolet (DUV) lasers have many practical applications in many fields. Almost all materials have a spectral fingerprint in the ultraviolet range[1,2,3,4,5,6,7,8] (especially at [30–200] nm). Compared with the fiber laser, if we can solve the parameter optimization problem, the Ti:Sapphire laser can generate sufficient power . It has a lager adjustable laser spectral range and low phase noise. Many recent studies[29,30,31,32,33,34] have used neural networks to solve the multiparameter adjustment problem of complex systems in experiments and have shown great advantages over human These techniques are utilized in lasers and related applications, such as laser cutting[35], optical communication[36,37] and mode-locked laser[38]. This means that these techniques are difficult to optimize in real time for environmental changes that occur while the experiment is taking place
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