Uniform and efficient beam shaping for high-energy lasers

Design of a compact off-axis two-mirror freeform optical antenna for shaping and transmitting an elliptical beam emitted by laser diode

Elliptical Gaussian beams generated by laser diodes (LDs) often exhibit asymmetrical divergence angle distribution, which limits their practical applications. In this study, we propose what we believe is a novel approach to shape and collimate the elliptical output beam from a LD. The design process involves the construction of two freeform reflective surfaces on a reference circle using a three-dimensional point-by-point iterative method, based on the law of conservation of energy, the vector reflection theory, and Fermat's principle. The output beam's maximum divergence angle is effectively compressed to 3.1579 mrad. The design is compact with a folded optical path and antenna size of 368.8c m 3. This paper presents a comprehensive design and optimization process, along with an in-depth analysis of the system's performance, thereby offering novel insights for emerging optical design practitioners.

Inverse design of gradient-index volume multimode converters

Graded-index optical elements are capable of shaping light precisely and in very specific ways. While classical freeform optics uses only a two-dimensional domain such as the surface of a lens, recent technological advances in laser manufacturing offer promising prospects for the realization of arbitrary three-dimensional graded-index volumes, i.e. transparent dielectric substrates with voxel-wise modified refractive index distributions. Such elements would be able to perform complex light transformations on compact scales. Here we present an algorithmic approach for computing 3D graded-index devices, which utilizes numerical beam propagation and error reduction based on gradient descent. We present solutions for millimeter-sized elements addressing important tasks in photonics: a mode sorter, a photonic lantern and a multimode intensity beam shaper. We further discuss suitable cost functions for all designs to be used in the algorithm. The 3D graded-index designs are spatially smooth and require a relatively small refractive index range in the order of 10^-2, which is within the reach of direct laser writing manufacturing processes such as two-photon polymerization.

Dual-task convolutional neural network based on the combination of the U-Net and a diffraction propagation model for phase hologram design with suppressed speckle noise

In this paper, a dual-task convolutional neural network based on the combination of the U-Net and a diffraction propagation model is proposed for the design of phase holograms to suppress speckle noise of the reconstructed images. By introducing a Fresnel transmission layer, based on angular spectrum diffraction theory, as the diffraction propagation model and incorporating it into U-Net as the output layer, the proposed neural network model can describe the actual physical process of holographic imaging, and the distributions of both the light amplitude and phase can be generated. Afterwards, by respectively using the Pearson correlation coefficient (PCC) as the loss function to modulate the distribution of the amplitude, and a proposed target-weighted standard deviation (TWSD) as the loss function to limit the randomness and arbitrariness of the reconstructed phase distribution, the dual tasks of the amplitude reconstruction and phase smoothing are jointly solved, and thus the phase hologram that can produce high quality image without speckle is obtained. Both simulations and optical experiments are carried out to confirm the feasibility and effectiveness of the proposed method. Furthermore, the depth of field (DOF) of the image using the proposed method is much larger than that of using the traditional Gerchberg-Saxton (GS) algorithm due to the smoothness of the reconstructed phase distribution, which is also verified in the experiments. This study provides a new phase hologram design approach and shows the potential of neural networks in the field of the holographic imaging and more.

High-Flexibility Control of Structured Light with Combined Adaptive Optical Systems

Combining the specific advantages of high-resolution liquid-crystal-on-silicon spatial light modulators (LCoS-SLMs) and reflective or refractive micro-electro-mechanical systems (MEMS) presents new prospects for the generation of structured light fields. In particular, adaptive self-apodization schemes can significantly reduce diffraction by low-loss spatial filtering. The concept enables one to realize low-dispersion shaping of nondiffracting femtosecond wavepackets and to temporally switch, modulate or deflect spatially structured beams. Adaptive diffraction management by structured illumination is demonstrated for piezo-based and thermally actuated axicons, spiral phase plates (SPPs) and Fresnel bi-mirrors. Improved non-collinear autocorrelation with angular-tunable Fresnel-bi-mirrors via self-apodized illumination and phase contrast of an SLM is proposed. An extension of the recently introduced nondiffractive Talbot effect to a tunable configuration by combining an SLM and a fluid lens is reported. Experimental results for hexagonal as well as orthogonal array beams are presented.