3 kW passive-gain-enabled metalized Raman fiber amplifier based on passive gain

Raman fiber lasers (RFLs) are currently promising and versatile light sources for a variety of applications. So far, operations of high power and brightness-enhanced RFLs have absorbed enormous interests along with rapid progress. Nevertheless, the stable Raman lasing at high power levels remains challenged by the thermal effects. In an effort to realize more effective thermal management in high power RFLs, here we demonstrate, for the first time, an all-fiberized RFA employing metal-coated passive fiber enabling high power lasing. By employing aluminum to the cladding of graded-index (GRIN) passive fiber, the thermal abstraction of the laser devices is more sufficient to support low-temperature operation. The maximum output power reaches 3.083 kW at 1130 nm with a conversion efficiency of 78.7%. To the best of our knowledge, this is the first Raman laser generation based on metal-coated passive fiber. Meanwhile, it is also the highest power attained in the fields of all kinds of Raman lasers based on merely nonlinear gain

simulation_slowx10.mp4

the results of processing simulated beam pattern through the network with GPU with slow 10

experiment.mp4

the processing results through the network with GPU for real beam pattern

Pure passive fiber enabled highly efficient Raman fiber amplifier with record kilowatt power

Kilowatt-level high efficiency all-fiberized Raman fiber amplifier based on pure passive fiber is proposed for the first time in this paper. The laser system is established on master oscillator power amplification configuration while a piece of graded-index passive fiber is utilized as stokes shifting as well as gain medium, which is entirely irrelevant to rare-earth-doped gain mechanism. When the pump power is 1368.8 W, we obtained 1002.3 W continuous-wave laser power at 1060 nm with the corresponding optical-to-optical efficiency of 84%. The beam parameter M2 improves from 9.17 of the pump laser to 5.11 of the signal laser through the amplification process, and the brightness enhancement is about 2.57 at maximum output power as a consequence of the beam clean-up process in the graded-index fiber. To the best of our knowledge, we have demonstrated the first kilowatt-level high efficiency Raman fiber amplifier based on pure passive fiber with brightness enhancement

experiment_slowx3.mp4

the processing results through the network with GPU for real beam patterns, slowing 3

simulation.mp4

the processing results of simulated beam pattern through the network with GP

Learning to decompose the modes in few-mode fibers with deep convolutional neural network

We introduce deep learning technique to perform complete mode decomposition for few-mode optical fiber for the first time. Our goal is to learn a fast and accurate mapping from near-field beam profiles to the complete mode coefficients, including both modal amplitudes and phases. We train the convolutional neural network with simulated beam patterns, and evaluate the network on both of the simulated beam data and the real beam data. In simulated beam data testing, the correlation between the reconstructed and the ideal beam profiles can achieve 0.9993 and 0.995 for 3-mode case and 5-mode case respectively. While in the real 3-mode beam data testing, the average correlation is 0.9912 and the mode decomposition can be potentially performed at 33 Hz frequency on Graphic Processing Unit, indicating real-time processing ability. The quantitative evaluations demonstrate the superiority of our deep learning based approach

Simulated_6mode_slow_10x.mp4

This is the simulated results of M^2 estimation for the 6-mode case with slow 10x

Experiment_M^2_Comparison.mp4

This is the experimental results of M^2 estimatio

Simulated_5mode_slow_10x.mp4

This is the simulated results of M^2 estimation for the 5-mode case with slow 10x