Laser is an important strategic technology that has been widely used in the processing, communication, military, and medical fields. Lasers are also indispensable tools for observing complex, multi-dimensional optical phenomena, especially in physics, biology, materials science, and astronomy. Laser possesses various modulable orthogonal physical dimensions, including wavelength, pulse width, repetition rate, intensity, phase, and polarization, which are the main objectives of laser manipulation. To explore new phenomena with high dimensions, laser manipulation is no longer limited to a single dimension, and the joint manipulation of multiple dimensions of laser is imperative.

Multi-dimensional (multi-mode) laser is important for breaking the bottleneck of single-mode laser performance, and it provides new opportunities for multidisciplinary research. Different from traditional single-mode lasers, multi-dimensional lasers exhibit a complex optical field that can be controlled through delicate tuning of the numerous parameters, but this complicacy also results in challenging manipulation of the performance of the multi-dimensional laser. Recently, with the rapid development of artificial intelligence, intelligent control techniques, particularly machine learning, have been widely applied to improve the performance of complex optical systems, which promotes the fast iteration of intelligent optics and related fields, elucidating the intelligent control of multi-dimensional lasers.

Here, we provide a literature review on the research progress of intelligent control in the field of multi-dimension laser manipulation from the aspects of in-cavity and out-of-cavity manipulation. First, in-cavity manipulation can be used in self-optimizing mode-locked lasers (Fig. 4) and precise control of the specific state (Fig. 5). The application of intelligent algorithms in multi-dimensional manipulation can be further explored using spatiotemporal mode-locked fiber lasers based on in-cavity manipulation. Subsequently, the applications of out-of-cavity manipulation in parameter control of laser beam (Fig. 10), dynamics in fibers (Fig. 11), and multi-dimensional information reconstruction of the light field (Fig. 13) are elaborated. Finally, we discuss the potential of intelligently-controlled multi-dimensional laser technology in the fields of optical micromanipulation (Fig. 15), laser micromachining (Fig. 17), and laser communication (Fig. 19). Future developments of multi-dimensional laser technologies with intelligent manipulation are discussed, and the possible problems and challenges are also discussed.

Driven by frontier exploration, intelligent manipulation of multi-dimensional laser technologies based on machine learning tools has become an important foundation for the study of complex physical phenomena and cross-disciplinary problems. With the increasing complexity of multi-dimensional laser systems, new intelligent manipulation techniques shoulds be exploited.