Taking the LISA system as a reference, the phase noise of the inter-satellite transmission needs to be less than 1 pm. Research has shown that the defocus and the astigmatism are the main aberrations affecting jitter noise at a distance of 2.5×10⁹ m. There is a deviation between the phase stationary point and the origin position. To minimize the phase noise, the telescope angle needs to be adjusted. The gravitational wave detection at the phase stationary point can effectively reduce the phase noise and the requirements of the telescope exit pupil wavefront RMS. The large defocus and small coma can make the phase stationary point close to the optical axis and increase the received laser power.

Three-dimensional (3D) nonlinear photonic crystals have received intensive interest as an ideal platform to study nonlinear wave interactions and explore their applications. Periodic fork-shaped gratings are extremely important in this context because they are capable of generating second-harmonic vortex beams from a fundamental Gaussian wave, which has versatile applications in optical trapping and materials engineering. However, previous studies mainly focused on the normal incidence of the fundamental Gaussian beam, resulting in symmetric emissions of the second-harmonic vortices. Here we present an experimental study on second-harmonic vortex generation in periodic fork-shaped gratings at oblique incidence, in comparison with the case of normal incidence. More quasi-phase-matching resonant wavelengths have been observed at oblique incidence, and the second-harmonic emissions become asymmetric against the incident beam. These results agree well with theoretic explanations. The oblique incidence of the fundamental wave is also used for the generation of second-harmonic Bessel beams with uniform azimuthal intensity distributions. Our study is important for a deeper understanding of nonlinear interactions in a 3D periodic medium. It also paves the way toward achieving high-quality structured beams at new frequencies, which is important for manipulation of the orbital angular momentum of light.

Light-field fluorescence microscopy (LFM) is a powerful elegant compact method for long-term high-speed imaging of complex biological systems, such as neuron activities and rapid movements of organelles. LFM experiments typically generate terabytes of image data and require a substantial amount of storage space. Some lossy compression algorithms have been proposed recently with good compression performance. However, since the specimen usually only tolerates low-power density illumination for long-term imaging with low phototoxicity, the image signal-to-noise ratio (SNR) is relatively low, which will cause the loss of some efficient position or intensity information using such lossy compression algorithms. Here, we propose a phase-space continuity-enhanced bzip2 (PC-bzip2) lossless compression method for LFM data as a high-efficiency and open-source tool that combines graphics processing unit-based fast entropy judgment and multicore-CPU-based high-speed lossless compression. Our proposed method achieves almost 10% compression ratio improvement while keeping the capability of high-speed compression, compared with the original bzip2. We evaluated our method on fluorescence beads data and fluorescence staining cells data with different SNRs. Moreover, by introducing temporal continuity, our method shows the superior compression ratio on time series data of zebrafish blood vessels.

Phase-change material (PCM) is widely used in thermal management due to their unique thermal behavior. However, related research in thermal rectifier is mainly focused on exploring the principles at the fundamental device level, which results in a gap to real applications. Here, we propose a controllable thermal rectification design towards building applications through the direct adhesion of composite thermal rectification material (TRM) based on PCM and reduced graphene oxide (rGO) aerogel to ordinary concrete walls (CWs). The design is evaluated in detail by combining experiments and finite element analysis. It is found that, TRM can regulate the temperature difference on both sides of the TRM/CWs system by thermal rectification. The difference in two directions reaches to 13.8 K at the heat flow of 80 W/m². In addition, the larger the change of thermal conductivity before and after phase change of TRM is, the more effective it is for regulating temperature difference in two directions. The stated technology has a wide range of applications for the thermal energy control in buildings with specific temperature requirements.

The ability to overcome the negative effects, induced by obstacles and turbulent atmosphere, is a core challenge of long-distance information transmission, and it is of great significance in free-space optical communication. The spatial-coherence structure, that characterizes partially coherent fields, provides a new degree of freedom for carrying information. However, due to the influence of the complex transmission environment, the spatial-coherence structure is severely damaged during the propagation path, which undoubtedly limits its ability to transmit information. Here, we realize the robust far-field orbital angular momentum (OAM) transmission and detection by modulating the spatial-coherence structure of a partially coherent vortex beam with the help of the cross-phase. The cross-phase enables the OAM information, quantified by the topological charge, hidden in the spatial-coherence structure can be stably transmitted to the far field and can resist the influence of obstructions and turbulence within the communication link. This is due to the self-reconstruction property of the spatial-coherence structure embedded with the cross-phase. We demonstrate experimentally that the topological charge information can be recognized well by measuring the spatial-coherence structure in the far field, exhibiting a set of distinct and separated dark rings even under amplitude and phase perturbations. Our findings open a door for robust optical signal transmission through the complex environment and may find application in optical communication through a turbulent atmosphere.

Deconvolution is a commonly employed technique for enhancing image quality in optical imaging methods. Unfortunately, its application in optical coherence tomography (OCT) is often hindered by sensitivity to noise, which leads to additive ringing artifacts. These artifacts considerably degrade the quality of deconvolved images, thereby limiting its effectiveness in OCT imaging. In this study, we propose a framework that integrates numerical random phase masks into the deconvolution process, effectively eliminating these artifacts and enhancing image clarity. The optimized joint operation of an iterative Richardson-Lucy deconvolution and numerical synthesis of random phase masks (RPM), termed as Deconv-RPM, enables a 2.5-fold reduction in full width at half-maximum (FWHM). We demonstrate that the Deconv-RPM method significantly enhances image clarity, allowing for the discernment of previously unresolved cellular-level details in nonkeratinized epithelial cells exvivo and moving blood cells invivo.

Recently, deep learning has yielded transformative success across optics and photonics, especially in optical metrology. Deep neural networks (DNNs) with a fully convolutional architecture (e.g., U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks, such as fringe denoising, phase unwrapping, and fringe analysis. However, the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best na?ve, as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice. To this end, we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (LeFTP) module. By parameterizing conventional phase retrieval methods, the LeFTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples, while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods. Guided by the initial phase from LeFTP, the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks. Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval, exhibiting its excellent generalization to various unseen objects during training. The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches, opening new avenues to achieve fast and accurate single-shot 3D imaging.