We present a slab laser amplifier beam cleanup experimental system based on a 39-actuator rectangular piezoelectric deformable mirror. Rather than use a wave-front sensor to measure distortions in the wave-front and then apply a conjugation wave-front for compensating them, the system uses a Stochastic Parallel Gradient Descent algorithm to maximize the power contained within a far-field designated bucket. Experimental results demonstrate that at the output power of 335W, more than 30% energy concentrates in the 1x diffraction-limited area while the beam quality is enhanced greatly.

To correct wavefront aberrations, commonly employing proportional-integral control in adaptive optics (AO) systems, the control process depends strictly on the response matrix of the deformable mirror. The alignment error between the Hartmann–Shack wavefront sensor and the deformable mirror is caused by various factors in AO systems. In the conventional control method, the response matrix can be recalibrated to reduce the impact of alignment error, but the impact cannot be eliminated. This paper proposes a control method based on a deep learning control model (DLCM) to compensate for wavefront aberrations, eliminating the dependence on the deformable mirror response matrix. Based on the wavefront slope data, the cost functions of the model network and the actor network are defined, and the gradient optimization algorithm improves the efficiency of the network training. The model network guarantees the stability and convergence speed, while the actor network improves the control accuracy, realizing an online identification and self-adaptive control of the system. A parameter-sharing mechanism is adopted between the model network and the actor network to control the system gain. Simulation results show that the DLCM has good adaptability and stability. Through self-learning, it improves the convergence accuracy and iterations, as well as the adjustment tolerance of the system.

Metalenses recently have attracted attention because of their more compact size in comparison with conventional lenses; they can also achieve better optical performance with higher resolution. Duplexer is an interesting function of a metalens that can distinguish different sources and divide them into two parts for specific purposes. In this article, we design tunable duplex metalenses with phase-change material Ge₂Sb₂Te₅ for the first time. Two types of special unit cells are designed to modulate the incident lights, and four metalenses are designed based on the two types of unit cells. Specific phase profiles are calculated for different sections of metalens in which the corresponding unit cells are settled; accordingly, the metalenses can focus the incident lights at any positions according to our design. Moreover, the metalenses become selectable via tuning the state of phase-change material, which means that the output light field can be actively controlled. The proposal of our tunable duplex metalenses will offer new opportunities for active three-dimensional imaging or optical coding.

In this paper, an aberration correction algorithm for wavefront sensorless adaptive optics system is presented, which is based on the approximately linear relation between the mean square of the aberration gradients and the second moment of far-field intensity distribution. To demonstrate algorithm’s performance, an experiment system of aberration corrections for Fresnel zone plates imaging is set up. The correction results show the excellent performance of this method in correction speed, and correction capability. Comparing with conventional stochastic parallel gradient descent (SPGD) algorithm, the correction speed with this method is improved about four times for the similar correction effect.

A simple but effective decoupling control algorithm based on Zernike mode decomposition for adaptive optics systems with dual deformable mirrors is proposed. One of the two deformable mirrors is characterized with a large stroke (woofer) and the other with high spatial resolutions (tweeter). The algorithm works as follows: wavefront gradient vector is decoupled using the Zernike modes at first, and then the control vector for the woofer is generated with low order Zernike coefficients to eliminate high order modes. At the same time the control vector for the tweeter is reset by a constraint matrix in order to avoid coupling error accumulation. Simulation indicates the algorithm could get better performance compared with traditional Zernike mode decomposition control algorithms. Experiments demonstrate that this algorithm can effectively compensate for phase distortions and significantly suppress the coupling between the woofer and tweeter.