Transient absorption spectroscopy (TAS) is a cornerstone for investigating dynamical mechanisms in quantum dots, photovoltaics, and photosynthesis. A primary challenge in the field is the development of high-sensitivity techniques capable of probing species in low-signal regimes, such as single-molecule detection, spatially resolved TAS, and the tracking of short-lived intermediates. While advancements in instrumentation have pushed the physical limits of detection, extracting meaningful dynamics from noise-limited data remains a bottleneck. In this work, we propose a residual U-Net framework integrated with a spectral-temporal decoupling module, namely TS-ResUNet for denoising and reconstruction of transient maps. Quantitative evaluations demonstrate that TS-ResUNet consistently outperforms conventional algorithms and standard U-Net architectures in denoising, while maintaining high fidelity in the extracted spectral and kinetic information. Furthermore, sim-to-real transfer learning performed on experimental data sets indicates that effective adaptation is achievable with a small number of paired training data. This framework provides a robust methodology for refining low signal-to-noise ratio measurements and significantly accelerating data acquisition in ultrafast spectroscopy.

Femtosecond laser direct writing (FLDW) serves as a prominent method in the area of micro-nano fabrication. Employing a high numerical aperture objective lens and coordinating galvanometer scanners with translation stages, enables the stitching of samples with cross-scale and large-area features. Errors in the galvanometer scanning optical system and translation stage can significantly impair the quality of the desired micro-structures during cross-scale stitching processing. It is crucial to assess and modify these errors in the FLDW system. Traditional methods require various instruments to measure different types of errors, with each using different references, making them unsuitable for high-precision stitching processing. In this study, we identify errors associated with the galvanometer optical system and the translation stage, which impact the stitching quality of FLDW systems. We propose utilizing critical sites identified by the FLDW technique and acquiring microscopic images of the designated areas using commercial devices. By combining algorithms for extracting image feature points, it not only mitigates the uncertainties linked to manual selection in conventional measurements but also facilitates the precise acquisition of various error values under a consistent reference. Utilizing this technology to calibrate the FLDW system enables the attainment of defect-free femtosecond laser stitching processing. Meanwhile, it inspires the integration of the FLDW system with real-time microscopic stitching measurements on a same platform, which enhances operational convenience and improves manufacturing efficiency for femtosecond laser fabrication. The developed system and method enabled the processing of grid structures and computer-generated holograms characterized by cross-scale and large-area features. Experimental results demonstrate the significant potential for manufacturing large-area micro-nano optical devices.

Photon-counting polarimetric imaging provides more dimensional information compared to conventional imaging systems. We present a compact dual-wavelength infrared polarimetric light detection and ranging system operating at 1550 and 2004 nm, utilizing direct detection with superconducting nanowire single-photon detectors. This system achieves millimeter-scale resolution in both lateral and axial dimensions at a target distance of similar to 1.3 m. Experimental results demonstrate an improved material discrimination advantage at low photon flux by integrating dual-band photon counting detection with polarimetric imaging, outperforming traditional intensity-based measurement methods. This work demonstrates broad application prospects in scenarios involving mid-infrared remote sensing and complex environmental exploration.

Objective Laser-induced breakdown spectroscopy (LIBS) is a powerful technique for real-time, in-situ elemental analysis without sample preparation. It has been widely applied in planetary exploration, geological surveys, metallurgical quality control, and hazardous material detection. To enable long-distance and non-contact operation under extreme conditions, remote LIBS systems have been developed by spatially separating the excitation and detection subsystems. However, the implementation of large-aperture optical probes in such systems often requires the addition of a beam-expanding structure to ensure that the laser beam fully illuminates the secondary mirror and ultimately the entire entrance pupil of the Cassegrain telescope. This introduces severe limitations in system miniaturization due to increased optical path size, limited broadband compatibility, and the difficulty of aligning coaxial excitation and collection paths. Additionally, conventional beam expanders result in a short depth of focus, making the system highly sensitive to focal shifts, which significantly impacts detection efficiency and system stability in complex field conditions. Methods To address these challenges, this paper proposes a compact and long-depth-of-focus optical probe design for remote LIBS systems, wherein a concave lens is embedded into the Cassegrain configuration to replace the traditional standalone beam expander. This embedded lens expands the narrow-diameter laser beam to match the secondary mirror aperture, enabling full-aperture illumination and efficient plasma generation at long distances. Made of fused silica, the lens ensures high transmittance across a wide spectral range and supports coaxial reuse of the optical path for both excitation and collection, reducing optical complexity and system volume. Moreover, the lens design intrinsically enhances the depth of focus, improving robustness against target displacement along the optical axis. A mathematical model of the system geometry is established to derive analytical expressions for focal length, lens position, and depth of field. The optical characteristics of the design are further validated and optimized using Zemax simulations. Results and Discussions To determine the optimal positioning between the concave lens and the Cassegrain system and to characterize the optical properties of the miniaturized probe, a mathematical model of the remote optical system is developed. Detailed theoretical calculations are conducted to derive key parameters, including the system focal length, depth of focus, and inter-element spacing. To evaluate the elemental detection capability of the proposed remote LIBS system, standard copper (Cu) is used as the test sample at a working distance of 8.1 m. A 26 mJ pulsed laser is used for excitation, with a spectral acquisition range of 350-690 nm, a trigger delay of 220 mu s, and an integration time of 1 ms. The resulting LIBS spectra match well with the NIST copper atomic database, confirming the system's high detection accuracy and spectral fidelity under remote conditions. Additionally, four representative mineral samples-hematite, gold ore, obsidian, and glass meteorite-are analyzed under the same conditions. Characteristic elements such as Fe, Al, and Si are reliably identified, demonstrating the robustness and applicability of the method for complex mineral analysis. Conclusions To meet the growing demand for compact and stable remote LIBS systems, this study proposes a novel miniaturized and long-depth-of-focus optical design that integrates a concave lens into a Cassegrain-based system. By replacing conventional beam expanders, the concave lens enables coaxial integration of the excitation and collection paths, significantly reducing the system size (Phi 120 mm & times; 190 mm) while maintaining high energy utilization and effective focusing. Experimental results at an 8.1 m distance confirm the system's ability to deliver stable plasma excitation and high-quality spectra, with strong resistance to focal drift. Overall, this work presents a compact, high-stability solution for remote LIBS applications such as planetary exploration, geological mapping, and hazardous material detection.

Due to the orientation differences in molecular chains, anisotropic packaging materials exhibit chaotic surface spectral signals, making it difficult to detect deep-layer signals, which are easily overwhelmed. Traditional scanning methods are limited by coverage range, detection stability, system complexity, and other factors, making it challenging to detect deep-layer material components within anisotropic packaging materials. To address this issue, this paper proposes a dual-galvanometer mirror ring scanning remote Spatial Offset Raman Spectroscopy (SORS) detection method. This method combines dual-galvanometer mirror scanning with remote SORS technology to eliminate signal differences caused by molecular chain orientation, enhancing the stability and accuracy of deep-layer detection. Experiments show that at a detection distance of 5 meters, the surface PTFE signal is reduced by 42% compared to traditional methods. In actual HDPE sample detection, the standard deviation of the deep/surface signal ratio at different points is only 2.5%, which is far superior to the standard deviation of 72.5% achieved by the traditional detection method, significantly improving the identification and detection stability of deep-layer targets. This method provides a new solution for remote non-invasive detection of deep-layer targets in fields such as public safety and customs anti-smuggling.

Due to differences in the molecular chain orientation of anisotropic packaging materials, the Raman scattering intensity of their surface layers exhibits significant directional dependence, which severely hinders the effective extraction of signals from deeper layers. Traditional remote SORS systems typically use single-point, fixed-position detection, making it difficult to ensure reliable detection of materials deep within anisotropic packaging materials. Therefore, we propose a dual-galvanometer mirror ring scanning remote SORS detection method, which uses ring scanning to achieve omnidirectional spectral signal accumulation, effectively suppressing signal differences caused by molecular chain orientation and enhances the stability of deep-layer detection. Experiments have shown that , at a detection distance of 5 meters, the interference signal of surface PTFE is reduced by 42% compared to traditional detection methods; In the multi-point detection of actual HDPE samples, the relative standard deviation of the ratio of deep-to-surface signals has been reduced from 70.6% in traditional single point detection methods to 2.9%, significantly improving the identification and detection stability of deep target objects. This method is expected to provide a potential technical solution for non-invasive remote detection of deep substances.

To address the demand for high-precision surface profiling of non-full spherical surfaces and the issues of low accuracy, inefficiency, and poor stability associated with current manual subaperture stitching measurement methods, this paper proposes a model reference adaptive control (MRAC)-based automatic stitching method for differential confocal global subaperture measurements using a common sphere centre. Utilising MRAC as the decision centre for global pose control of the tested mirror, it generates desired trajectories via reference models and adapts control parameters online through adaptive laws, thereby resolving the issues of insufficient robustness and ineffective suppression of non-linear disturbances caused by fixed parameters in traditional PID control. High-resolution axial focusing achieved through laser differential confocal zero-crossing fitting provides nanometre-level co-centredness reference input to MRAC, establishing a unified global co-centredness origin for stitching. In-situ multi-aperture phase-shifting interference stitching enables MRAC to implement high-precision closed-loop feedback, accomplishing high-fidelity surface data acquisition and phase reconstruction. This approach achieves high-precision, high-stability, and high-efficiency automated stitching measurement of non-full spherical surface using a global subaperture co-centred approach. Based on the proposed method, an MRAC-based differential confocal global subaperture concentric-spherical automatic stitching measurement instrument was constructed. Experimental results demonstrate that the axial focusing accuracy of the proposed method is better than 40 nm, the adaptive pose-control accuracy of the measured mirror reaches 0.74 μm (0.012%), the RMS repeatability of the full-area automatic stitching measurement is better than 0.00042λ (λ = 632.8 nm) and a single stitching measurement cycle is completed within 4.4 min, which transcends the performance limitations of fixed-gain control, offering an effective technical approach for high-precision, high-efficiency, and highly robust automatic stitching measurement of non-full spherical surfaces.

Confocal microscopy (CM) has emerged as a widely adopted technique for the three-dimensional geometric characterization of micro-electromechanical systems (MEMS), owing to its non-contact nature and submicrometer resolution. However, the rapid development and widespread adoption of MEMS resonant devices have rendered standalone static topography measurements inadequate to meet evolving characterization requirements. This gap necessitates innovative approaches for synchronous in-situ detection of geometric and dynamic parameters during device operation. To address this challenge, this study proposes a novel laser scanning confocal vibration microscopy (LSCVM) method that enables simultaneous topographical mapping and vibrational parameter acquisition without requiring operational state switching. The LSCVM method utilizes continuous wavelet transform (CWT) to perform time-frequency analysis on vibration-coupled confocal axial response curves, thereby extracting vibrational parameters. Concurrently, linear bilateral fitting of skewed segments is applied to derive topographic parameters. Through this approach, the LSCVM method achieves simultaneous topographic and vibrational detection via a single axial scan, attaining a geometric spatial resolution of 300 nm and an amplitude resolution of 0.4 nm. Experimental validation using a micro-cantilever beam device confirmed the feasibility and advantages of the LSCVM method, demonstrating its potential as a novel approach for the in-situ performance evaluation of operational MEMS devices.

Single-molecule localization microscopy (SMLM) is a powerful imaging technique that surpasses the diffraction limit of light by computationally localizing individual fluorescent molecules. However, achieving sufficient spatial resolution in SMLM requires extensive frame acquisition, limiting temporal resolution. Increasing the density of fluorescent molecules is a common strategy to enhance temporal resolution, but this often results in overlapping point spread functions and computational challenges in distinguishing adjacent molecules. We developed a deep learning-driven approach, termed super-resolution spatiotemporal information integration (SRST), for ultra-high-density molecules' precise three-dimensional (3D) localization. SRST leveraged temporal information from adjacent frames and the blinking mechanism to enhance localization accuracy, demonstrating a 10% increase in the Jaccard index and a 14 nm reduction in localization error compared with the state-of-the-art methods in low signal-to-noise ratio conditions. SRST exhibited broad applicability and maintains accurate reconstruction in ultra-high-density scenarios, enhancing structural detail in 3D imaging of subcellular structures such as mitochondria and microtubules while reducing imaging artifacts and improving structural smoothness. SRST will hold substantial promise for detailed structural analysis of cellular components, providing high-resolution imaging with enhanced localization accuracy.

Considering the high-speed, large-range and high-resolution optical measurement demand in the fields of optical precision machining and semiconductor manufacturing, we propose a laser differential confocal measurement method based on galvanometer and displacement stage (GSLDCM). The method obtains a fitting equation through the differential confocal detection signal near the zero-point with high sensitivity and linearity, to achieve high-speed, high-resolution measurements without axial scanning. Utilizing the galvanometer scanning at a high speed in the transverse fast axis, together with the slow-axis displacement stage scanning, realizes highspeed two-dimensional transverse scanning measurements and large-range scanning in X-direction. This enables cross-scale, high-speed, and high-precision three-dimensional measurements of surface topography. A simulation analysis and experimental verification show that the axial resolution of this method is up to 1 nm. When a 100x measurement objective is used, a three-dimensional morphology measurement of 128 mu m x 4 mm can be completed in 855 s. The measurement efficiency is approximately 5 times that of the traditional confocal splicing scanning measurement, which provides an effective technology pathway for a large-scale high-precision inspection in semiconductor manufacturing and other fields.

To accomplish ultraprecise noncontact scanning of freeform, this article proposes a technique for measuring normal vectors (NVs) using differential confocal absolute position triggering (NDCAPT), and using the accurately obtained NV to reconstruct the freeform under test (FUT) profile. First, the absolute zero position of the laser differential confocal (LDC) is used to trigger the position-sensitive detector (PSD) to collect the spot centroid position (SCP) at the focus, eliminating the influence of the defocus of the sampling point (SP) on the SCP. Second, a defocus distance estimation model based on proximal policy optimization (PPO) to analysis of the light spot is established. Through deep learning to track the profile of freeform to improve the scanning efficiency. Finally, an NV reconstruction model of freeform is constructed. Based on the high-precision NVs measured, the profile of the freeform can be accurately reconstructed. The preliminary experimental results show that the profile measurement accuracy of this method is better than +/- 50 nm. By implementing precision NV metrology, it is possible to realize high-precision inspection of freeform, and reduce the demand for a high-precision reference monitoring framework and displacement measurement methods in the profile measurement of freeform.

The manufacturing accuracy of freeform surface is limited by its detection accuracy. In this paper, a laser differential confocal freeform surface shape measurement method based on translational motion error monitoring and compensation is proposed. This method realizes helical scanning measurements of a freeform surface via sensor translation and freeform surface rotation. Based on normal tracking principle, a position-sensitive detector is used to track the normal direction, solving the problem of large inclination freeform surface measurements limited by the maximum measurable inclination of the sensor. The laser differential confocal sensor is used to precisely focus of the surface, realizing a high-spatial-resolution measurement of the surface normal vector, with an axial resolution of up to 1 nm. By introducing a reference frame into the system, an independent translational motion reference is provided for freeform surface measurement. By monitoring, decoupling and compensating the 2D translational motion errors, the impact of these errors on measurement accuracy is greatly reduced. High-accuracy freeform surface shape measurement is finally realized. The experimental results show that after error compensation, the PV repeatability is superior to ±50 nm (3σ), RMS repeatability is superior to ±14 nm (3σ), and the measurement results are close to the standard values, enabling high-accuracy measurement of freeform surface shapes.

This work proposes a precise temperature measurement method based on wavelength modulation heterodyne phase-sensitive dispersion spectroscopy (WM-HPSDS). Before the light intensity of the laser was modulated by an electro-optic modulator to generate a three-tone beam, the laser produced additional wavelength modulation by superimposing a high-frequency sinusoidal waveform on a slow sawtooth wave. The second harmonic peak value of the H2O dispersion phase at 7185.59 cm−1 and 7182.94 cm−1 was used to extract temperature through two-line thermometry. The experiment was carried out on a water-based thermostat and an acoustically excited Bunsen burner. The extracted temperatures of the thermostat agreed well with the reference temperature, and the deviation was within 1.5 °C. The measurement stability of the Bunsen burner flame was approximately 10.4 dB higher than that of direct HPSDS. Furthermore, measuring the peak values under varying laser powers demonstrated that WM-HPSDS was immune to optical power fluctuations. Therefore, this method has potential for measuring temperature in harsh environments.

Crossed Czerny-Turner (C-T) spectrometers are limited by significant aberrations due to large off-axis angles in spherical mirrors. A method is proposed to effectively reduce aberrations in portable crossed C-T spectrometers. The method optimizes grating position for field curvature correction, uses the Shafer equation to reduce coma across a wide spectral range, and employs a cylindrical lens for astigmatism correction by adjusting its tilt and wedge angles. The method significantly improves imaging quality, reducing spot width by 93.3 %. Additionally, a wavelength calibration model for the crossed C-T spectrometer was developed. This model employs an optimization fitting algorithm based on a sine-constrained least squares to accurately correct the optical system parameters. It achieves a wavelength calibration accuracy of 0.01 nm and a spectral resolution better than 3212 over a 200 nm range. This performance meets the requirements for detecting weak light signals in applications such as Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS).

The performance of quartz accelerometers heavily relies on the high-quality fabrication of their key component, the quartz pendulous, which remains a significant challenge using conventional techniques. Here, we propose a femtosecond laser Bessel beam writing-enhanced wet etching method to significantly improve the fabrication efficiency and quality of quartz pendulous. Through orthogonal experiments, we analyze the effects of pulse spacing, single-pulse energy, defocusing distance, and etching time on cutting cross-section roughness and edge residual stress. Using optimized parameters, we achieve high-quality quartz pendulous with an average crosssection roughness of 521 nm, maximum residual stress of 0.496 MPa, and a taper angle of 0.012 degrees. Raman spectroscopy reveals the mechanism of silica glass modification under high-energy laser ablation, forming microcavities along the laser propagation direction. Importantly, the roughness and etching rate are found to be independent of laser polarization. These results demonstrate the effectiveness of the proposed method for highprecision machining of quartz pendulous and other complex glass structures, offering a reliable approach for advanced quartz device fabrication.

Large-aperture optical components are of paramount importance in domains such as integrated circuits, photolithography, aerospace, and inertial confinement fusion. However, measuring their surface profiles relies predominantly on the phase-shifting approach, which involves collecting multiple interferograms and imposes stringent demands on environmental stability. These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements. Therefore, this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement (LA-SFISPM) method based on deep learning and explores its capability to realize dynamic measurements with high accuracy. The interferogram is matched to the phase by training the data measured using the small aperture. The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment. Hence, high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter. The experimental results show that for the tested mirror with Φ = 820 mm, the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth, resulting in a maximum single-point error of 4.56 nm. Meanwhile, the peak-to-valley (PV) value is 0.075 8 λ, and the simple repeatability of root mean square (SR-RMS) value is 0.000 25 λ, which aligns well with the measured results obtained by ZYGO. In particular, a significant reduction in the measurement time (reduced by a factor of 48) is achieved compared with that of the traditional phase-shifting method. Our proposed method provides an efficient, rapid, and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach, which is highly desired in large-aperture interferometric measurement systems.

To address the problem of a small linear sensing range in differential confocal measurement methods, this study proposes a large linear sensing range measurement method for a laser differential confocal (LDC) based on transverse split-spot detection using a multi-element detector (MED). This method converts the axial defocusing change of the measured object surface into transverse movement of the spot on the detected focal plane through the principle of transverse differential confocal (TDC), where the intensity of the spot on the focal plane is split and detected by MED. Two-by-two differential subtraction and normalization are processed to obtain multiple sets of normalized TDC response curves, which realize a large-range sensing confocal measurement without sacrificing the high-resolution axial fixed-focus measurement. The analytical and experimental validation shows that the axial resolution of this method is 0.5 nm, the linear sensing range is up to 13.667 mu m, which is about 11.4 times of the linear sensing range of TDC, and the maximum fitting error is 2.3 nm in the large sensing measurement range. This provides a new method for high-precision, large-range, and fast sensor-scanning measurement of precision element surfaces.

To address the issue of freeform surface profile scanning measurement relying on high-precision linear motion datum, this paper proposes a high-precision normal vector measurement method based on laser confocal fixed-focus (NVM-LCFF) for freeform surface detection. This method utilizes the precise correspondence between the peak position of laser confocal axial response and objective lens focus. Through axial scanning, it simultaneously acquires both the laser confocal axial response and the spot centroid position detected by the position-sensitive detector (PSD). Capitalizing on the spot centroid measurement accuracy at the focus is the highest, this method acquires spot centroid at the focus by computationally the focus position of the laser confocal axial response, and effectively eliminates defocus-induced errors in centroid positioning. By leveraging the rotation-translation invariance of distances between sampling points and angles between normal vectors of sampling points. This method performs pre-registration by pre-scanning the coordinates and normal vectors of at least 4 sampling points. Through nonlinear least-squares optimization, an initial estimation of the position of freeform surface is obtained, thereby substantially reducing the precision requirements of position adjustment. Initial experimental verification demonstrates that this approach achieves freeform surface measurement with accuracy better than +/- 50 nm, effectively reducing the influence of straightness errors on measurement accuracy, and eliminating the dependence on the ultra-precise height measurement references in traditional freeform surface metrology.

A B-spline adaptive sampling (B-SAS) method is proposed for three-dimensional freeform surface measurements using a laser differential confocal sensor (LDCS). High-precision focusing on optical freeform surfaces was achieved by axial scanning using the LDCS. The B-SAS method, based on the arc length and curvature uniformity, was introduced to enable the adaptive distribution of sampling points on freeform surfaces. Experiments show that the B-SAS method improves the repeatability accuracy of the peak-to-valley (PV) (3 sigma) for freeform surfaces by 27% compared to the uniform sampling method, and the corresponding measurement efficiency is improved by 41%. The repeatability accuracy of the PV (3 sigma) and root-mean-square (3 sigma) of the measured surfaces, using the B-SAS method, are lower than 27 and 8.5 nm, respectively. This method realizes highly accurate and efficient freeform surface measurements and provides a solution for measuring freeform surfaces with large angles.