The axion is a theoretical particle that could resolve multiple fundamental problems, most notably the strong Charge-conjugation-parity-symmetry (CP) problem in quantum chromodynamics and the nature of dark matter.To date, however, the axion has never been detected in any free-space experiment. In this work, we designed and constructed a laser-based system that generates a three-dimensional, closed trapping potential field with a null central region. Owing to its spindle-like geometry, we term this configuration an optical spindle trap (OST). Along the propagation axis, the photon population evolves in a distinct manner from the left to the right terminus of the trap: it first diminishes and then recovers to its baseline value.This behavior is analogous to the photon axion photon conversion process sought in light shining through wall experiments(LSW)1-3, in which a measured photon deficit would constitute evidence for axion conversion. The photon population was monitored with a single-photon counter (SPC) operated well below its saturation threshold, and the observed behavior was corroborated by charge-coupled device (CCD) imaging at extremely low optical powers, thereby excluding detector artefacts as the origin of the photon deficit.Under the constraint of energy conservation, the missing photons are attributed to conversion into axions that remain undetectable by both the SPC and the CCD. The underlying conversion mechanism is ascribed to spin-coupled axion photon interactions. This tens-of-millimeter-scale optical spindle trap thus provides a viable free-space axion source, generated by a table-top laser, for the study of the strong CP problem and axion-like dark matter candidates.

Single-pixel imaging (SPI), distinguished by its cost-efficiency, exceptional spectral adaptability, and robust sub-Nyquist-Shannon sampling reconstruction capabilities, demonstrates transformative potential across imaging applications yet faces critical limitations in capturing arbitrarily moving targets. This work introduces a simple yet effective SPI architecture capable of simultaneous real-time tracking and high-fidelity imaging of objects undergoing unconstrained 2D planar motion, encompassing both periodic and non-periodic translational/rotational kinematics. Our methodology employs six strategically designed Fourier patterns with optimized spatial frequencies as localization markers, combined with multichannel centroid tracking, to achieve precise motion dynamics characterization. Furthermore, we develop a straightforward inverse motion-compensated reconstruction method that efficiently reconstructs images of objects subjected to composite motion. The proposed framework notably maintains reconstruction integrity even when individual detection channels experience temporary out of the field of view.

Parallel single-pixel imaging (PSPI) enhances the data acquisition efficiency of single-pixel imaging, but its reconstruction quality depends on a cumbersome and noise-sensitive calibration process. To address this challenge, a PSPI strategy was introduced that leverages modulation region expansion and overlapping reconstruction. This method results in the calibration of modulation of the subregion for each detector, enabling robust operations with undersampled data. It compensates for misalignment via modulation region expansion and overlapping reconstruction, achieving seamless and high-quality imaging that surpasses conventional PSPI in simulations and experiments. Furthermore, this strategy exhibits remarkable robustness, maintaining high imaging quality under extremely nonideal conditions, such as large deflection angles between the array detector and the modulator. This work provides a simple, efficient, and robust framework that simplifies the PSPI workflow and offers broad applicability in high-resolution, high-speed computational imaging.

This paper presents a high-speed single-pixel tracking method that exceeds the modulation speed limit of the digital micromirror device (DMD) in conventional approaches. The proposed method adopts a polarization system to split the target image into two identical beams, which are modulated by two orthogonal steady-state geometric moment patterns and input into the dual channels of the DMD. This allows separate extraction of the target's x- and y-direction positional information without DMD pattern switching. The localization speed is no longer constrained by DMD switching but determined by high-speed single-pixel detectors. Experimental results demonstrate a localization speed of 450 kHz, achieving a one-order-of-magnitude improvement over traditional DMD-based methods.

This work proposes a geometry-optimized complex-domain error-diffusion encoding method for Fourier single-pixel imaging. Instead of independently binarizing multiple grayscale phase-shifting patterns, the proposed method directly represents each complex-valued Fourier basis pattern using K (K >= 3) weighted binary patterns while diffusing the residual error in the complex domain. A geometric interpretation is further established, revealing that the encoding process can be viewed as approximating the Fourier-basis unit circle by a regular polygon in the complex plane. Based on this geometric interpretation, practical optimization strategies are developed for K = 3, K = 4, and K = 7. Both numerical simulations and real-object experiments demonstrate consistently superior reconstruction quality compared with conventional phase-shifting dithering.

The detection of sounds employing optical techniques is a captivating and profoundly significant area of research. Here, we propose an optical microphone scheme based on single-pixel imaging. This scheme has a simple structure, low-cost, and eliminates the need for coherent light illumination. We experimentally validated this framework by using everyday items, such as paper cards and leaves, successfully detecting minute vibrations on their surfaces induced by sound waves. Another key advantage of this method is its minimal data volume, allowing for long-duration or even continuous measurements.

Compact optical systems are revolutionizing precision measurement with their miniaturized design and functionality. At the forefront of this revolution are metalenses, composed of sub‐wavelength nanostructures. They have emerged as novel planar optical elements capable of replacing traditional bulky lenses in various compact optical applications. Meanwhile, single‐pixel imaging provides a cost‐effective, computation‐based method for achieving exceptional imaging quality. In this work, a metalens is integrated with a single‐pixel imaging architecture to project high‐resolution Hadamard patterns onto microscopic samples, replacing conventional lens‐to‐detector configurations. The system can simultaneously retrieve high‐quality amplitude and phase maps of micro targets, even under single‐photon‐level illumination conditions (1.7 photons/pixel/s). This breakthrough is ideal for biological samples, particularly in live cell imaging, where minimizing light exposure is critical to avoid photobleaching and phototoxicity. By delivering a cost‐effective, compact, and high‐performance solution, this system sets a new era for precision imaging in science and industry.

Delayed luminescence (DL) is a quantized signal that is characteristic of photoexcited molecules entering a relaxed state. Studying DL provides critical insight into photophysical mechanisms through the analysis of specific spatiotemporal dynamics. In this study, we developed a high-sensitivity DL imaging system using a quantitative scientific complementary metal-oxide-semiconductor (qCMOS) camera and a single-photon counting resolution. By optimizing the optical architecture and signal processing algorithms together, we achieved full-field spatiotemporal DL imaging at megapixel resolution (i.e., 2304 × 4096 pixels). Key findings include the following: (1) we observed spatial heterogeneity in DL intensity across the leaves of Arabidopsis thaliana, with stronger signals detected in veins and at sites of mechanical injury; (2) species-specific DL responses occur in response to oxidative stress, with Hydrocotyle vulgaris and Ginkgo biloba showing enhanced central DL activity; (3) excitation using white light induced maximum DL intensity, while red and blue light differentially modulated decay kinetics. Finally, we develop a two-level quantum model that links DL dynamics to the populations of excited-state electrons, thereby developing a theoretical framework for future photophysical research. Collectively, this work establishes a theoretical and technological framework for advancing plant phenotyping under stress conditions and optimizing light environments.

Crystal defects in solid-state spintronic materials play a crucial role in altering the optical properties of their hosts, enabling widespread applications in the field of quantum information processing. While the majority of the leading platforms are inorganic, they come with limitations such as the challenging material preparations and insufficient amount of active spins. Here, pentacene-doped p-terphenyl (Pc:Ptp), an organic spintronic material with easy preparations and tailorable functionalities normally used for microwave quantum electronics, is demonstrated for the first time its ability of self-cavity laser emission at room temperature. The laser emission is characterized by strong polarization and anisotropy, attributed to the unique packing of the doped molecules (i.e., active spins) within the crystal. The optical coherence is found to be a figure of merit to distinguish the processes of the amplified spontaneous emission (ASE) and lasing in Pc:Ptp. This work highlights the potential of Pc:Ptp as a compact and efficient platform for light-matter interactions, offering significant promise for enhancing the performance of solid-state quantum devices based on the organic spintronic material.

Single-pixel imaging (SPI) exhibits cost-effectiveness, broad spectrum, and stable sub-Nyquist sampling reconstruction, enabling applications across diverse imaging fields.However, due to the inherent reconstruction mechanism, SPI is not well-suited for high-speed moving targets. To address these challenges, we propose a novel, universal SPI configuration for tracking and imaging moving objects.Unlike traditional motion compensation methods, our approach enables the recovery of targets undergoing arbitrary motion, including translation, rotation, periodic, or non-periodic movements, within a two-dimensional plane without increasing the number of modulation frames.By leveraging the centroid positions from multiple wavelength channels, we determine the target's motion state from a kinematic perspective. Moreover, we developed an adapted reconstruction method, the (P-IT) pseudo-inverse transformation method, which allows for the efficient reconstruction of objects with composite motion. With a maximum flip rate of 20 kHz for the digital micromirror device (DMD), the theoretical perception frame rate can reach up to 2222 Hz, comparable to that of conventional motion-compensated SPI for purely translational objects.

Single-pixel imaging (SPI) enables real-time observation of dynamic scenes by reducing the sampling rate. However, traditional methods often struggle to achieve high spatial resolution when aiming for high temporal resolution, particularly when imaging fast-moving objects. To address this challenge, we propose a real-time high-resolution imaging method for moving objects that combines Fourier modulation-based tracking with foveated modulation. In our approach, six Fourier patterns are employed to quickly locate the moving object and determine the foveal region of the field of view, after which preloaded foveated patterns are selected to perform foveated imaging. This strategy overcomes the transmission bandwidth constraint of the digital micromirror device, thereby enabling real-time monitoring. The experimental and simulation results show that our method can significantly improve the spatial resolution of the moving object compared to conventional Fourier single-pixel imaging with the same number of patterns. Furthermore, the process can also be combined with laser guidance to achieve high-resolution imaging in user-specified regions, extending the application scenarios of single-pixel imaging.

Fourier single-pixel imaging (FSI) takes full advantage of the high modulation speed of digital micromirror devices by applying upsampling and spatial dithering to binarize grayscale Fourier patterns, thereby achieving efficient imaging. However, the upsampling process of patterns sacrifices spatial resolution. Here, we propose a binarization method for FSI that enhances reconstructed image quality without the need for upsampling. The key is applying spatial dithering with a serpentine path directly to both positive and negative components of Fourier patterns before binarization. By quantizing these components into {-1, 0, +1} values and subsequently mapping them to binary patterns, our method reduces quantization errors in Fourier coefficient acquisition. Both simulation and experimental results demonstrate that the method significantly improves imaging quality. It can also be applied to other types of single-pixel imaging that use positive-negative grayscale patterns.

Single-photon sensors are novel devices with extremely high single-photon sensitivity and temporal resolution. However, these advantages also make them highly susceptible to noise. Moreover, single-photon cameras face severe quantization as low as 1 bit/frame. These factors make it a daunting task to recover high-quality scene information from noisy single-photon data. Most current image reconstruction methods for single-photon data are mathematical approaches, which limits information utilization and algorithm performance. In this work, we propose a hybrid information enhancement model which can significantly enhance the efficiency of information utilization by leveraging attention mechanisms from both spatial and channel branches. Furthermore, we introduce a structural feature enhance module for the FFN of the transformer, which explicitly improves the model's ability to extract and enhance high-frequency structural information through two symmetric convolution branches. Additionally, we propose a single-photon data simulation pipeline based on RAW images to address the challenge of the lack of single-photon datasets. Experimental results show that the proposed method outperforms state-of-the-art methods in various noise levels and exhibits a more efficient capability for recovering high-frequency structures and extracting information.

Quantum electronics operating in the microwave domain are burgeoning and becoming essential building blocks of quantum computers, sensors, and communication devices. However, the field of microwave quantum electronics has long been dominated by the need for cryogenic conditions to maintain delicate quantum characteristics. Here, a solid-state hybrid system, constituted by a photo-excited pentacene triplet spin ensemble coupled to a dielectric resonator, is reported for the first time capable of both coherent microwave quantum amplification and oscillation at X band via the masing process at room temperature. By incorporating external driving and active dissipation control into the hybrid system, efficient tuning of the maser emission characteristics at ≈9.4 GHz is achieved, which is key to optimizing the performance of the maser device. The work not only pushes the boundaries of the operating frequency and functionality of the existing pentacene masers but also demonstrates a universal route for controlling the masing process at room temperature, highlighting opportunities for optimizing emerging solid-state masers for quantum information processing and communication.

Laser-scanning confocal microscopy serves as a critical instrument for microscopic research in biology. However, it suffers from low imaging speed and high phototoxicity. Here we build a novel deep compressive confocal microscope, which employs a digital micromirror device as a coding mask for single-pixel imaging and a pinhole for confocal microscopic imaging respectively. Combined with a deep learning reconstruction algorithm, our system is able to achieve high-quality confocal microscopic imaging with low phototoxicity. Our imaging experiments with fluorescent microspheres demonstrate its capability of achieving single-pixel confocal imaging with a sampling ratio of only approximately 0.03% in specific sparse scenarios. Moreover, the deep compressive confocal microscope allows single-pixel imaging at the single-photon level, thus reducing the excitation light power requirement for confocal imaging and suppressing the phototoxicity. We believe that our system has great potential for long-duration and high-speed microscopic imaging of living cells.

Computed-tomography imaging spectrometry (CTIS) can achieve non-scanning and high speed imaging recording of spatial and spectral data of a rapidly changing target scene. However, it has the problem of missing cone, which means the projection data cannot be fully sampled. This limits its practicality due to the ill-posed spectral reconstruction from limited angles of projection tomography. This paper proposes a compressed sensing (CS) sampling model for the CTIS, or CSCTIS in short, with the under sampling advantage of CS to improve the problem. The simulation results validates that the CS model is more effective than the traditional computed-tomography (CT) one, and further experimental results prove that the CSCTIS performs more accurate spectral reconstruction than the traditional CTIS.

Single-pixel imaging (SPI), which offers high-throughput measurement capabilities and a simple structure, has promising applications in near-infrared single-photon imaging. Nevertheless, the low saturation count rate of near-infrared single-photon detectors often leads to photon pile-up effects. This paper delves into the influence of these effects on passive SPI under both random matrix modulation and Hadamard matrix modulation and offers corresponding noise removal solutions. The experimental results validated the efficacy of these noise removal schemes.

We report an experimental demonstration of temporal ghost imaging in which a digital micromirror device (DMD) and +1/-1 binary modulation have been combined to give an accurate reconstruction of a nonperiodic time object. Compared to the $0/1$ modulation, the reconstruction signal can be improved greatly by +1/-1 binary modulation even with half of the measurements. Experimental results show that 0/1 binary temporal objects up to 4 kHz and sinusoidal time objects up to 1 kHz can be reconstructed by this method. The influences of modulation speed and array detector gray levels are also discussed.

Recently, several single-pixel imaging (SPI) schemes have emerged for imaging fast-moving objects and have shown dramatic results. However, fast image reconstruction of a moving object with high quality is still challenging for SPI, thereby limiting its practical application. In this paper, we present a simultaneous tracking and imaging method that incorporates position encoding and spatial information encoding through Fourier patterns. The utilization of Fourier patterns with specific spatial frequencies ensures robust and accurate object localization. By exploiting the properties of the Fourier transforms, our method achieves a remarkable reduction in time complexity while significantly enhancing image quality. Furthermore, we introduce an optimized sampling strategy specifically designed for small moving objects, significantly reducing the required dwell time for imaging. The proposed method provides a practical solution for real-time tracking, imaging, and edge detection of moving objects, underscoring its considerable potential for diverse applications.