Recent years have seen the rapid growth and development of the field of smart photonics, where machine-learning algorithms are being matched to optical systems to add new functionalities and to enhance performance. An area where machine learning shows particular potential to accelerate technology is the field of ultrafast photonics — the generation and characterization of light pulses, the study of light–matter interactions on short timescales, and high-speed optical measurements. Our aim here is to highlight a number of specific areas where the promise of machine learning in ultrafast photonics has already been realized, including the design and operation of pulsed lasers, and the characterization and control of ultrafast propagation dynamics. We also consider challenges and future areas of research.

近年来，智能光子学领域迅猛发展，其中机器学习算法与光学系统相匹配，以增加新的功能并提高性能。机器学习在加速技术方面显示出特殊潜力的领域是超快光子学领域-光脉冲的生成和表征，短时间尺度上的光与物质相互作用的研究以及高速光学测量。我们的目的是强调一些已经实现超快光子学中的机器学习前景的特定领域，包括脉冲激光器的设计和操作以及超快传播动力学的特性和控制。我们还将考虑挑战和未来的研究领域。