Micro/nanorobots have shown great potential to execute different tasks in microenvironments due to their small size, high controllability and environmental adaptability. However, it is still challenging to precisely control the deformation and navigation of soft micro/nanorobots to better adapt to unstructured and complex surroundings. Here, we report a photonic nanojet (PNJ)-regulated soft microalga robot (saBOT) based on Euglena gracilis with controlled deformation and precise navigation capability. The deformability of the saBOT was precisely controlled by the highly focused light energy from a microlens-based PNJ bound to a tapered optical fiber probe (TFP), which can precisely stimulate the channelrhodopsin-2 (ChR2) in the photoreceptor of the microalga. This saBOT can be further precisely navigated toward different positions in complex and unstructured microenvironments by combining the deformability with the phototaxis ability of the microalga via the flexible manipulation of TFP. Notably, due to the ability of controllable deformation and precision navigation, the saBOT can travel across cell clusters for precision drug delivery toward a target cell. This PNJ-regulated saBOT holds great promise in executing different biomedical tasks in complex and unstructured microenvironments that cannot be reached by conventional tools and rigid microrobots.

Nonlinear Raman-Nath diffraction (NRND) is a unique diffraction pattern formed when a high-intensity laser interacts with a nonlinear microstructure bulky medium relying only on the transverse phase matching condition. Here, we report on the first experimental observation of NRND in a submicron-thick periodically poled lithium niobate thin film (PPLNTF) by geometric reflection pumped via a near-infrared femtosecond pulse laser. We further observe the evolution of the diffracted signals after broadening of the pump laser via a fused silica plate. We systematically analyze the spectral properties of multi-order second harmonic generation (SHG) diffracted signals exhibiting asymmetric distributions and explicitly clarify their phase matching conditions, simultaneously considering the impacts of the incident pump wavelength, the sample poling period, and the incident angle on the properties of the angular distribution diffracted beams. The realization of NRND phenomena with appreciable on-chip efficiency at a submicron interaction length is mainly attributed to the significant contribution of domain walls to enhance the nonlinear effects along with the modulation of second-order nonlinear susceptibilities χ(2). This NRND scheme provides a high-resolution, non-destructive on-chip microstructure diagnostic method, and even has the potential to develop novel on-chip integrated optoelectronic devices for applications such as precision metrology, biosensing, and spectral analysis.

Soliton molecules (SMs) play a crucial role in nonlinear optical systems, enriching our understanding of nonlinear science through the study of their interaction dynamics. While passively mode-locked fiber lasers offer an efficient platform for generating diverse types of SMs, the complex internal dynamics of the laser often pose challenges in achieving predetermined temporal separations between SMs. Here, we implement a delayed optical feedback technique within a femtosecond optical parametric oscillator, enabling the generation of SMs with precise and controllable temporal separations. A theoretical model, which models the intracavity iterations of the signal with a simplified Ikeda map, is proposed to study the impact of parametric gain, intracavity feedback delay, and cavity length on the internal separations of the SMs. Our experimental results confirm that adjusting the cavity length allows for producing desired temporal separations within SMs. To reveal the evolution dynamics of the SMs, we further develop a rigorous numerical model using the carrier-resolved Forward Maxwell Equation, which is capable of modeling ultra-broadband complex dynamics based on a single equation without relying on the slowly-varying envelope approximation. The numerical model unveils the rich formation dynamics of the SMs at various separations, which confirms the critical role of the gain window provided by the pump. This work opens up new opportunities for the on-demand generation of SMs and provides valuable insights into the complex dynamics in femtosecond optical parametric oscillator systems with optical delayed feedback.

Holography is an essential technique of generating three-dimensional images. Recently, quantum holography with undetected photons (QHUP) has emerged as a groundbreaking method capable of capturing complex amplitude images. Despite its potential, the practical application of QHUP has been limited by susceptibility to phase disturbances, low interference visibility, and limited spatial resolution. Deep learning, recognized for its ability in processing complex data, holds significant promise in addressing these challenges. In this report, we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms, resulting in vastly reduced noise and distortion, alongside a notable enhancement in spatial resolution. The proposed and demonstrated deep learning QHUP (DL-QHUP) methodology offers a transformative solution by delivering high-speed imaging, improved spatial resolution, and superior noise resilience, making it suitable for diverse applications across an array of research fields stretching from biomedical imaging to remote sensing. DL-QHUP signifies a crucial leap forward in the realm of holography, demonstrating its immense potential to revolutionize imaging capabilities and pave the way for advancements in various scientific disciplines. The integration of DL-QHUP promises to unlock new possibilities in imaging applications, transcending existing limitations and offering unparalleled performance in challenging environments.

Information security plays an important role in every aspect of life to protect data from stealing and deciphering. However, most of the previously reported works were based on pure algorithm layer or pure physical layer encryptions, which have certain limitations in security. In this paper, a nondeterministic message encryption communication scheme is proposed based on a spin-space-frequency multiplexing metasurface (SSFMM), which integrates both algorithmic and physical layer encryptions, and can also produce multiple different ciphertexts for the same message to prevent the message from being cracked through frequency analysis, thus greatly enhancing the security of the information. To be specific, an SSFMM is first designed as a physical-layer meta-key, which can generate eight independent dot matrix holograms with different spin, space, and frequency characteristics. The target message is then encrypted based on these dot matrix holograms combined with algorithmic operations, and the encrypted message is converted into a quick response (QR) code for easy sending to the target users. Once the target user gets that QR code, he/she can scan it to obtain the encryption information, and then recover the target message according to the pre-agreed encryption protocol combined with the eight dot matrix holograms of SSFMM. Finally, the feasibility of the proposed encryption scheme was experimentally validated at the microwave frequency band.

The classical properties of thermal light fields were instrumental in shaping our early understanding of light. Before the invention of the laser, thermal light was used to investigate the wave-particle duality of light. The subsequent formulation of the quantum theory of electromagnetic radiation later confirmed the classical nature of thermal light fields. Here, we fragment a pseudothermal field into its multiparticle constituents to demonstrate that it can host multiphoton dynamics mediated by either classical or quantum properties of coherence. This is shown in a forty-particle system through a process of scattering mediated by twisted paths endowed with orbital angular momentum. This platform enables accurate projections of the scattered pseudothermal system into isolated multiphoton subsystems governed by quantum dynamics. Interestingly, the isolated multiphoton subsystems exhibiting quantum coherence produce interference patterns previously attributed to entangled optical systems. As such, our work unveils novel mechanisms to isolate quantum systems from classical fields. This possibility opens new paradigms in quantum physics with enormous implications for the development of robust quantum technologies.

Single-pixel detectors are popular devices in optical sciences because of their fast temporal response, high sensitivity, and low cost. However, when being used for imaging, they face a fundamental challenge in acquiring high-dimensional information of an optical field because they are essentially zero-dimensional sensors and measure only the light intensity. To address this problem, we developed a cascaded compressed-sensing single-pixel camera, which decomposes the measurement into multiple stages, sequentially reducing the dimensionality of the data from a high-dimensional space to zero dimension. This measurement scheme allows us to exploit the compressibility of a natural scene in multiple domains, leading to highly efficient data acquisition. We demonstrated our method in several demanding applications, including enabling tunable single-pixel full-waveform hyperspectral light detection and ranging (LIDAR) for the first time.

Pulsed polarized vortex beams, a special form of structured light, are generated by tailoring the light beam spatiotemporally and witness the growing application demands in nonlinear optics such as ultrafast laser processing and surface plasma excitation. However, existing techniques for generating polarized vortex beams suffer from either low compactness due to the use of bulky components or limited controlment of pulse performance. Here, an all-fiber technique combining plasmonic metafibers with mode conversion method is harnessed to generate high-performance pulsed polarized vortex beams. Plasmonic metafibers are utilized as saturable absorbers to produce Q-switched pulses with micro-second duration, while the offset splicing method is employed to partially convert the fundamental transverse mode (LP01\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{01}$$\\end{document}) to higher-order mode (LP11\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{11}$$\\end{document}). Eventually, a polarized vortex beams laser is achieved at the telecom band with a repetition frequency of 116.0 kHz. The impact of geometrical parameters including period of metafibers and offset of splicing on the spatiotemporal properties of pulsed polarized vortex beams is systematically investigated. Our findings could pave the way for design, control and generation of all-fiber pulsed polarized vortex beams, and also offer insights into the development of other types of structured laser sources.

Cancer-associated adipocytes (CAAs) have emerged as pivotal players in various cancers, particularly in such as breast cancer, significantly influencing their progression and therapy resistance. Understanding the adipocytes/cancer cells crosstalk is crucial for effective treatment strategies. Raman spectroscopy, a label-free optical technique, offers potential for characterizing biological samples by providing chemical-specific information. In this study, we used Raman spectroscopy and Trajectory Inference methods, specifically the Partition-based graph abstraction algorithm, to investigate the interactions between 3T3-L1 differentiated adipocytes and MDA-MB-231 breast cancer cells in a 2D co-culture model. We demonstrate the existence of subpopulations of adipocytes and the molecular changes associated with CAAs phenotype. This work contributes to understanding the role of CAAs in breast cancer progression and may guide the development of targeted therapies disrupting this interaction.

Computer holography is a prominent technique for reconstructing customized three-dimensional (3D) diffraction fields. However, the quality of optical reconstruction remains a fundamental challenge in 3D computer holography, especially for the 3D diffraction fields with physically continuous and extensive depth range. Here, we propose a 3D computer-generated hologram (CGH) optimization framework with phase space tailoring. Based on phase space analysis of the space and frequency properties in both lateral and axial directions, the intensity of the 3D diffraction field is adequately sampled across a large depth range. This sampling ensures the reconstructed intensity distribution to be comprehensively constrained with physical consistency. A physics-informed loss function is constructed based on the phase space tailoring to optimize the CGH with suppression of vortex stagnation. Numerical and optical experiments demonstrate the proposed method significantly enhances the 3D optical reconstructions with suppressed speckle noise across a continuous and extensive depth range.