Evaluating the beam quality of double-cladding fiber lasers in applications

Er/Yb co-doped 345-W all-fiber laser at 1535 nm using hybrid fiber

The 1.5-µm fiber laser is widely used in the fields of laser lidar, remote sensing, and gas monitoring because of its advantages of being eye-safe and exhibiting low atmospheric transmission loss. However, due to the ∼1-µm amplified spontaneous emission (ASE) of the Er/Yb co-doped fiber (EYDF), it is difficult to improve the laser power. Here, we simulated the effect of the Er³⁺ concentration and the seed power on ∼1-µm ASE, and fabricated a large mode area EYDF by the modified chemical vapor deposition process. Additionally, a piece of ytterbium-doped fiber was introduced into the master oscillator power amplifier (MOPA) configuration to absorb the generated ∼1-µm ASE simultaneously. Experimental results show that an output power of 345 W with a slope efficiency of 43% at 1535 nm is obtained in an all-fiber configuration, profiting from effective suppression of ∼ 1-µm ASE. To the best of our knowledge, this is the highest output power available with an Er/Yb co-doped fiber from an all-fiber MOPA configuration.

Analytical study on the steady-state thermal blooming effect of high-power ytterbium-doped fiber lasers propagating through the atmosphere

Thermal blooming effect is one of the significant factors affecting the propagation performance of high-power ytterbium-doped fiber lasers (YDFLs) in the atmosphere. In this paper, two 20 kW YDFL systems with typical wavelengths (1070 nm and 1080 nm) are fabricated for propagation comparison experiments, which are used to investigate the thermal blooming effect induced by high-power YDFL propagation through the atmosphere. Under approximately the same laser system parameters (except wavelength) and atmospheric environment, the 1070 nm laser has better propagation characteristics than the 1080 nm laser. Due to the combined effect between the different central wavelengths of the two fiber lasers and the spectral broadening caused by output power scaling, the thermal blooming caused by the different absorptivity of water vapor molecules to the two fiber lasers is the main factor for the variation of the propagation properties. Through theoretical analysis and numerical calculation of factors affecting the thermal blooming effect, and considering the industrial manufacturing difficulty of YDFLs, a reasonable selection of fiber laser parameters can effectively improve atmospheric propagation performance and reduce manufacturing costs.

Amplification of random lasing enables a 10-kW-level high-spectral-purity Yb-Raman fiber laser

By amplifying the cascaded random Raman fiber laser (RRFL) oscillator and ytterbium fiber laser oscillator, we present the first, to the best of our knowledge, demonstration of a 10-kW-level high-spectral-purity all-fiber ytterbium-Raman fiber amplifier (Yb-RFA). With a carefully designed backward-pumped RRFL oscillator structure, the parasitic oscillation between the cascaded seeds is avoided. Leveraging the RRFL with full-open-cavity as the Raman seed, the Yb-RFA realizes 10.7-kW Raman lasing at 1125 nm, which is beyond the operating wavelengths of all the reflection components used in the system. The spectral purity of the Raman lasing reaches 94.7% and the 3-dB bandwidth is 3.9 nm. This work paves a way to combine the temporal stability of the RRFL seed and the power scaling of Yb-RFA, enabling the wavelength extension of high-power fiber lasers with high spectral purity.

Deep learning enabled superfast and accurate M2 evaluation for fiber beams

We introduce deep learning technique to predict the beam propagation factor M² of the laser beams emitting from few-mode fiber for the first time, to the best of our knowledge. The deep convolutional neural network (CNN) is trained with paired data of simulated near-field beam patterns and their calculated M² value, aiming at learning a fast and accurate mapping from the former to the latter. The trained deep CNN can then be utilized to evaluate M² of the fiber beams from single beam patterns. The results of simulated testing samples have shown that our scheme can achieve an averaged prediction error smaller than 2% even when up to 10 eigenmodes are involved in the fiber. The error becomes slightly larger when heavy noises are added into the input beam patterns but still smaller than 2.5%, which further proves the accuracy and robustness of our method. Furthermore, the M² estimation takes only about 5 ms for a prepared beam pattern with one forward pass, which can be adopted for real-time M² determination with only one supporting Charge-Coupled Device (CCD). The experimental results further prove the feasibility of our scheme. Moreover, the method we proposed can be confidently extended to other kinds of beams provided that adequate training samples are accessible. Deep learning paves the way to superfast and accurate M² evaluation with very low experimental efforts.

Low beam quality degradation, high-efficiency pump and signal combiner by built-in mode field adapter

A low beam quality degradation, high-efficiency (6+1)×1 pump and signal combiner based on an end-pumping technique was realized by a built-in mode field adapter. A 2D simulation model to calculate the taper ratios of signal input and output fibers for matching the mode field profile in the coupling region was established. Based on the simulation results, we fabricated a combiner, achieving a signal coupling ratio of 87.52% and an average pump coupling ratio of 98.56%. The beam quality degradation caused by the signal feed-through of the combiner was theoretically determined in terms of the well-known M² parameter and experimentally measured to be only ΔM²=0.15 (1.05 to 1.2). Theoretical results are in good agreement with the experimental results.