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Deflectometric profilometers are used to precisely measure the form of beam shaping optics of synchrotrons and X-ray free-electron lasers. They often utilize autocollimators which measure slope by evaluating the displacement of a reticle image on a detector. Based on our privileged access to the raw image data of an autocollimator, novel strategies to reduce the systematic measurement errors by using a set of overlapping images of the reticle obtained at different positions on the detector are discussed. It is demonstrated that imaging properties such as, for example, geometrical distortions and vignetting, can be extracted from this redundant set of images without recourse to external calibration facilities. This approach is based on the fact that the properties of the reticle itself do not change - all changes in the reticle image are due to the imaging process. Firstly, by combining interpolation and correlation, it is possible to determine the shift of a reticle image relative to a reference image with minimal error propagation. Secondly, the intensity of the reticle image is analysed as a function of its position on the CCD and a vignetting correction is calculated. Thirdly, the size of the reticle image is analysed as a function of its position and an imaging distortion correction is derived. It is demonstrated that, for different measurement ranges and aperture diameters of the autocollimator, reductions in the systematic errors of up to a factor of four to five can be achieved without recourse to external measurements.

The rapid development of artificial intelligence (AI) technology is leading a paradigm shift in optical metrology, from physics‐ and knowledge‐based modeling to data‐driven learning. In particular, the integration of structured‐light techniques with deep learning has garnered widespread attention and achieved significant success due to its capability to enable single‐frame, high‐speed, and high‐accuracy 3D surface imaging. However, most algorithms based on deep neural networks (DNNs) face a critical challenge: they assume the training and test data are independent and identically distributed, leading to performance degradation when applied across different image domains, especially when test images are acquired from unseen systems and environments. A cross‐domain learning framework for adaptive structured‐light 3D imaging is proposed to address this challenge. This framework's adaptability is enhanced by a novel mixture‐of‐experts (MoE) architecture, capable of dynamically synthesizing a network by integrating contributions from multiple expert DNNs. Experimental results demonstrate the method exhibits superior generalization performance across diverse systems and environments over both “specialist” DNNs developed for fixed domains and “generalist” DNNs trained by brute‐force approaches. This work offers fresh insights into substantially enhancing the generalization of deep‐learning‐based structured‐light 3D imaging and advances the development of versatile, robust AI‐driven optical metrology techniques. [ABSTRACT FROM AUTHOR]

Seed analysis is a cornerstone in advancing agriculture, with vigor tests playing a critical role in evaluating the physiological quality of seeds. However, monitoring seed vigor over time poses a significant challenge for the seed industry, as traditional methods are time-consuming and heavily reliant on subjective human judgment. Concerning these limitations, optical-based techniques have emerged as promising alternatives. Among them, the biological laser speckle phenomenon, rooted in optical interferometry, has proven effective in sensitively detecting and monitoring activity levels in living tissues. Known as the biospeckle laser (BSL) technique, this approach offers reliable results in assessing seed vigor. The BSL technique stands out due to its simplicity, rapid analysis, objectivity, and potential for automation, making it a valuable tool for seed analysis. This paper explores the state-of-the-art application of the BSL technique for evaluating seed vigor, highlighting successful approaches, identifying current challenges, and outlining areas for future research. It delves into the experimental setup for seed illumination and discusses the associated image processing methods. Furthermore, the paper examines the numerical and graphical outcomes, underscoring the BSL technique's ability to carry out seed analysis by addressing the limitations of traditional methods and enhancing efficiency in the agricultural sector. [ABSTRACT FROM AUTHOR]

In this paper, we propose a zoom auxiliary imaging lens based on the four-component mechanical zoom method for a modulation transfer function (MTF) test system. The auxiliary imaging lenses of the current MTF test system typically use fixed-focus optical systems, which are unable to meet the test scenarios of fast and batch measurement and measure lenses with an extensive focal length range. Compared with the fixed-focus auxiliary imaging lens, the zoom auxiliary imaging lens can simultaneously satisfy the measurement of wide-angle and telephoto miniature lenses without losing measurement accuracy. The entrance pupil distance of the zoom lens is greater than that of traditional lenses, and it is constant for each focal length of the zoom lens. The zoom lens uses an intermediate real image surface to obtain the perfect image quality and lower the diameter of the rear group. Additionally, the zoom lens dynamically adjusts magnification to optimize image size and align with the detector's pixel resolution, thereby preventing undersampling and enhancing measurement precision. The optical design is optimized for stability, delivering high resolution and minimal aberrations across the zoom range. The image quality of the zoom lens is nearly at the diffraction limit at each focal length, which significantly reduces the impact of the auxiliary lens on MTF test results, enhancing both flexibility and accuracy. This design is particularly well suited for testing miniature lenses in optoelectronic technology applications. [ABSTRACT FROM AUTHOR]

Second harmonic generation (SHG) microscopy is applied to image honey sugar crystals, with the advantage of avoiding the surrounding signal of the liquid honey. It is a non-contact method where the specialized preparation of the honey is not required. Since the crystallization process of honey depends upon its floral origin, among other conditions, analyzing its crystallographic behavior results in a challenging task as the crystals are mixed and overlapped. This work introduces a simple, multi-variable data analysis requiring only one SHG image, where its gray-level histogram was retrieved and processed from eight Mexican bee honey samples. These honey samples represent a broad range of regions from the central–east part of Mexico, describing different environments and climates. The results obtained with this simplified methodology can differentiate among the botanical origin of the honey samples at different crystallization times and storage conditions. A repeatability test was performed using three honey samples with different crystal morphologies to expand the method to all of the samples. The results show that the proposed methodology could be a helpful alternative to identifying the botanical origin of honey despite its crystallization time. [ABSTRACT FROM AUTHOR]

Accurately measuring the form of structured composite surfaces in situ is critical for advanced manufacturing in various engineering fields. However, challenges persist in achieving precision, miniaturization, and calibration using current structured light techniques. In this work, a hybrid structured light with compact configuration is proposed for the in-situ and embedded form metrology of structured composite surfaces. The proposed technique contains three subsystems: phase-measuring deflectometry (PMD), fringe projection profilometry (FPP), and stereo vision. The PMD subsystem accurately reconstructs the form data of specular surfaces based on the principle of structured light reflection, and the FPP subsystem measures rough surfaces by projecting structured light onto them. Output data from these subsystems are then stitched to reconstruct a complete form of the measured composite surfaces. The compact configuration is explored to reduce the system volume to improve the technique's portability and embedded measurement ability. With the stereo vision subsystem as an intermediary, a novel calibration method is applied for calculating the relations among the subsystems to improve the hybrid structured light system's calibration and data stitching accuracy between PMD and FPP subsystems. Three calibration tools are designed and manufactured for the proposed calibration technique. A portable metrology prototype based on the proposed hybrid structured light technique's principle and configuration is also developed and then calibrated using the novel calibration method. An embedded measurement experiment in a diamond turning machine demonstrates that the proposed techniques can achieve 400 nm form accuracy in specular surface measurement. Highlights: A novel hybrid structured light-based technique is proposed for the in-situ and embedded form metrology of structured composite surfaces. A beam splitter (BS)-based compact configuration is used to improve the technique' portability and embedded measurement ability. A novel calibration method is applied to calculate the relations among the subsystems using the stereo vision subsystem as an intermediary. [ABSTRACT FROM AUTHOR]

The amplitude modulation of a pump field and the phase-sensitive detection of a pump-induced intensity change of a probe field encompass a common practice in nonlinear spectroscopies to enhance the detection sensitivity. A drawback of this approach arises when the modulation frequency is comparable to the width of the spectral feature of interest, since the presence of sidebands in the amplitude-modulated pump field provides distortion to the observed spectral lineshape. This represents a problem when accurate measurements of spectral lineshapes and line positions are pursued, as recently happened in our group with the metrology of the Q(1) line in the 1-0 band of molecular hydrogen. The measurement was performed with a Stimulated Raman Scattering spectrometer that was calibrated, for the first time, against an optical frequency comb. In this work, we develop an analytical tool for nonlinear Stimulated Raman spectroscopies that allows us to precisely quantify spectral distortions arising from high-frequency amplitude modulation in one of the interacting fields. Once they are known, spectral distortions can be deconvolved from the measured spectra to retrieve unbiased data. The application of this tool to the measured spectra is discussed. [ABSTRACT FROM AUTHOR]

Progress in the semiconductor industry relies on the development of increasingly compact devices consisting of complex geometries made from diverse materials. Precise, label‐free, and real‐time metrology is needed for the characterization and quality control of such structures in both scientific research and industry. However, optical metrology of 2D sub‐wavelength structures with nanometer resolution remains a major challenge. Here, a single‐shot and label‐free optical metrology approach that determines 2D features of nanostructures, is introduced. Accurate experimental measurements with a random statistical error of 18 nm (λ/27) are demonstrated, while simulations suggest that 6 nm (λ/81) may be possible. This is far beyond the diffraction limit that affects conventional metrology. This metrology employs neural network processing of images of the 2D nano‐objects interacting with a phase singularity of the incident topologically structured superoscillatory light. A comparison between conventional and topologically structured illuminations shows that the presence of a singularity with a giant phase gradient substantially improves the retrieval of object information in such an optical metrology. This non‐invasive nano‐metrology opens a range of application opportunities for smart manufacturing processes, quality control, and advanced materials characterization. [ABSTRACT FROM AUTHOR]

The point cloud is one of the measurement results of local measurement and is widely used because of its high measurement accuracy, high data density, and low environmental impact. However, since point cloud data from a single measurement are generally small in spatial extent, it is necessary to accurately globalize the local point cloud to measure large components. In this paper, the method of using an iGPS (indoor Global Positioning System) as an external measurement device to realize high-accuracy globalization of local point cloud data is proposed. Two calibration models are also discussed for different application scenarios. Verification experiments prove that the average calibration errors of these two calibration models are 0.12 mm and 0.17 mm, respectively. The proposed method can maintain calibration precision in a large spatial range (about 10 m × 10 m × 5 m), which is of high value for engineering applications. [ABSTRACT FROM AUTHOR]

Digital holography has transformative potential for the measurement of stacked-chip microstructures due to its non-invasive, single-shot, full-field characteristics. However, significant light scattering and diffraction at steep edges in step microstructures cause the batwing effect, leading to measurement errors. Herein, we propose a standard-deviation-based adaptive median filter to eliminate batwing effects in step microstructure measurement using digital holography. The standard deviation determines the positions of the steps and the range of the batwing effect. During filtering, the filter window size varies: it adjusts according to the center's position within the batwing effect range and reduces outside this range to prevent distortion in other regions. Filtering weights are set to maintain information integrity while using larger filter windows. Experiments on the Standard Resolution Target USAF 1951 and the standard step height target show that our method successfully eliminates batwings while preserving the integrity of the remaining profile. [ABSTRACT FROM AUTHOR]

We use non-destructive Digital Holographic Speckle Pattern Interferometry (DHSPI), post-processing image analysis and one-dimensional exponential analysis to visualize, map and describe the structural condition of a plaster-based material. The body is heated by infrared radiation for two different time windows and the cooling process that follows is monitored in time by the so-called interferograms that are developed and are the result of the superposition of the holographic recordings of the sample prior to the thermal load and at variable time intervals during the cooling process. The fringe patterns in the interferometric images reveal features and characteristics of the interior of the material, with the experimental method and the post-process analysis adopted in this work offering accuracy, sensitivity and full-field diagnosis, in a completely non-destructive manner, without the need of sampling. [ABSTRACT FROM AUTHOR]

Here, we report on a simplified laser frequency noise measurement technique employing an acousto-optic modulator, a delay line, and a real-time oscilloscope. The technique is a slight modification of the typical delayed heterodyne method. Instead of using a swept frequency spectrum to analyze the laser emission spectrum, the waveform captured on a real-time oscilloscope is used to directly calculate the laser frequency noise. The oscilloscope bandwidth and sampling requirements can be kept modest by choosing a modulator driven at a few hundred megahertz, making this technique attractive for a large number of laboratories. We show the frequency noise measurements of two different lasers with linewidths at 2.7 kHz and 2 MHz. We took the opportunity to investigate the noise floor of the frequency noise measurement system, and we found that the noise floor of the frequency noise measurement depends on the power level of the laser that is being characterized, with the kilohertz linewidths laser requiring more power to reduce the noise floor to acceptable levels. [ABSTRACT FROM AUTHOR]

Overlay (OVL) is one significant performance indicator for the lithography process control in semiconductor manufacturing. The accuracy of the OVL metrology is extremely critical for guarantee the lithography quality. Currently, diffraction-based overlay (DBO) is one of the mainstream OVL metrology techniques. Unfortunately, the accuracy of the DBO metrology is largely affected by the defect features of the OVL target. Therefore, there is a strong need to investigate the impacts of these target defects on the DBO metrology performance. However, efficiently investigating the statistical and interactive impacts of various DBO target defects remains challenging. This study aims to address this issue through proposing an intelligent sensitivity analysis approach. A cumulative distribution based global sensitivity analysis (GSA) method is utilized to assess the nonlinear influences of multiple defects in the OVL target on the DBO inaccuracy. The scenarios with both known and unknown distributions of the OVL target defects are considered. For the former, a neural network driven forward model is constructed for fast calculating the optical diffraction responses to accelerate the GSA process. For the latter, another neural network based inverse model are built for efficiently estimating the distribution of the target defects. Finally, a series of simulation experiments are conduct for typical DBO targets with multiple common defect features. The results demonstrate the effectiveness and robustness of the proposed approach as well as give valuable insights into the DBO defect analysis. Our study provides a strong tool to assist the practitioners in achieving intelligent and efficient DBO analysis and thus in enhancing OVL metrology performance. [ABSTRACT FROM AUTHOR]

Deflectometric profilometers are used to precisely measure the form of beam shaping optics of synchrotrons and X-ray free-electron lasers. They often utilize autocollimators which measure slope by evaluating the displacement of a reticle image on a detector. Based on our privileged access to the raw image data of an autocollimator, novel strategies to reduce the systematic measurement errors by using a set of overlapping images of the reticle obtained at different positions on the detector are discussed. It is demonstrated that imaging properties such as, for example, geometrical distortions and vignetting, can be extracted from this redundant set of images without recourse to external calibration facilities. This approach is based on the fact that the properties of the reticle itself do not change – all changes in the reticle image are due to the imaging process. Firstly, by combining interpolation and correlation, it is possible to determine the shift of a reticle image relative to a reference image with minimal error propagation. Secondly, the intensity of the reticle image is analysed as a function of its position on the CCD and a vignetting correction is calculated. Thirdly, the size of the reticle image is analysed as a function of its position and an imaging distortion correction is derived. It is demonstrated that, for different measurement ranges and aperture diameters of the autocollimator, reductions in the systematic errors of up to a factor of four to five can be achieved without recourse to external measurements.

Concentrating Solar Power (CSP) mirrors must have high slope accuracy in order to achieve high solar concentration. Deflectometry is an established method for measuring high-resolution, high-accuracy maps of mirror slope. In this paper we describe improvements to Sandia’s deflectometry system, SOFAST, which enable it to be accurately calibrated even in difficult conditions of poor access to system components, imperfect components, and varying ambient light. These extensions improve the robustness of the system and expand the range of problems it can solve.

In this paper, we propose a zoom auxiliary imaging lens based on the four-component mechanical zoom method for a modulation transfer function (MTF) test system. The auxiliary imaging lenses of the current MTF test system typically use fixed-focus optical systems, which are unable to meet the test scenarios of fast and batch measurement and measure lenses with an extensive focal length range. Compared with the fixed-focus auxiliary imaging lens, the zoom auxiliary imaging lens can simultaneously satisfy the measurement of wide-angle and telephoto miniature lenses without losing measurement accuracy. The entrance pupil distance of the zoom lens is greater than that of traditional lenses, and it is constant for each focal length of the zoom lens. The zoom lens uses an intermediate real image surface to obtain the perfect image quality and lower the diameter of the rear group. Additionally, the zoom lens dynamically adjusts magnification to optimize image size and align with the detector’s pixel resolution, thereby preventing undersampling and enhancing measurement precision. The optical design is optimized for stability, delivering high resolution and minimal aberrations across the zoom range. The image quality of the zoom lens is nearly at the diffraction limit at each focal length, which significantly reduces the impact of the auxiliary lens on MTF test results, enhancing both flexibility and accuracy. This design is particularly well suited for testing miniature lenses in optoelectronic technology applications.

We have recently demonstrated that the 3D shape of micro-parts can be measured using LED illumination based on speckle contrast evaluation in the recently developed SPICE profilometry (shape measurements based on imaging with spatially partially coherent illumination). The main advantage of SPICE is its improved robustness and measurement speed compared to confocal or white light interferometry. The limited spatial coherence of the LED illumination is used for depth discrimination. An electrically tunable lens in a 4 f -configuration is used for fast depth scanning without mechanically moving parts. The approach is efficient, takes less than a second to capture required images, is eye-safe and offers a depth of focus of a few millimeters. However, SPICE's main limitation is its assumption of a small illumination aperture. Such a small illumination aperture affects the axial scan resolution, which dominates the measurement uncertainty. In this paper, we propose a novel method to overcome the aperture angle limitation of SPICE by illuminating the object from different directions with several independent LED sources. This approach reduces the full width at half maximum of the contrast envelope to one-eighth, resulting in a twofold improvement in measurement accuracy. As a proof of concept, shape measurements of various metal objects are presented. [ABSTRACT FROM AUTHOR]

Monoscopic deflectometry is a powerful and flexible measuring method for optical surfaces. Precise workpiece positioning is of significance because it directly determines the reliability of the measurement results. But unfortunately, the need for additional facilities severely limits the application of the monoscopic deflectometry. In this paper, a self-positioning method is proposed by combining the ray-tracing and Gaussian process regression. The phases retrieved from the captured images are parameterized using the Zernike polynomials. Then a training model is established for describing the relationship between the Zernike coefficients and the workpiece positions. Workpiece positioning is implemented by computing the associated joint Gaussian distribution. Experimental results show that the positioning accuracy of optical surfaces is comparable with that of a coordinate measuring machine, with a deviation less than 8 × 10−4° in tilt and 4 μm in translation. This greatly simplifies the sophisticated operation and improves the practicability and efficiency of deflectometric measurements. • Workpiece positioning for monoscopic deflectometry can be achieved without auxiliary instruments. • The retrieved phases are parameterized so that the position-independent error can be suppressed. • The required training samples can be conveniently obtained by numerical simulations. [ABSTRACT FROM AUTHOR]

A Michelson interferometer has been developed which uses a right-angled prism mirrored on the sides containing the right angle, to measure small tilt angles with double sensitivity compared to the classical Michelson interferometer. The design of the interferometer, theory, relative sensitivity as well as experimental results are presented. With this setup, we could measure tilt angle up to 1 μ rad . [ABSTRACT FROM AUTHOR]

Immersion microscope objectives stand out for their large numerical aperture, which improves the optical resolution of imaging systems such as those used in microscopic interferometry. These objectives increase the gradient forces of a beam focused through them, forming an Optical Trap (OT). However, many studies on microscopic interferometry neglect the contributions of different optical materials in the system that are also exposed to laser radiation, perhaps simply assuming transparency. In this work, a Mach–Zehnder interferometer and an OT, which share several components (including the same oil immersion objective), were coupled. Here, the response of the interferometer to a progressive increase in the OT laser power, while the interferometer laser power remains constant, is reported. Changes in laser power affect the oil temperature, altering its refractive index and volume, which in turn causes a phase shifting on the transmitted wavefront. Optical phase analysis is applied in the three-dimensional measurement of the damage produced by the OT on a paint film. This study suggests that the refractive index variations in the immersion oil affect interferograms because they will then exhibit an additive phase term that must be considered in that final measurement. Additionally, the OT geometry changes with the power increase. [ABSTRACT FROM AUTHOR]

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 naïve, 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.

Second harmonic generation (SHG) microscopy is applied to image honey sugar crystals, with the advantage of avoiding the surrounding signal of the liquid honey. It is a non-contact method where the specialized preparation of the honey is not required. Since the crystallization process of honey depends upon its floral origin, among other conditions, analyzing its crystallographic behavior results in a challenging task as the crystals are mixed and overlapped. This work introduces a simple, multi-variable data analysis requiring only one SHG image, where its gray-level histogram was retrieved and processed from eight Mexican bee honey samples. These honey samples represent a broad range of regions from the central–east part of Mexico, describing different environments and climates. The results obtained with this simplified methodology can differentiate among the botanical origin of the honey samples at different crystallization times and storage conditions. A repeatability test was performed using three honey samples with different crystal morphologies to expand the method to all of the samples. The results show that the proposed methodology could be a helpful alternative to identifying the botanical origin of honey despite its crystallization time.

We use non-destructive Digital Holographic Speckle Pattern Interferometry (DHSPI), post-processing image analysis and one-dimensional exponential analysis to visualize, map and describe the structural condition of a plaster-based material. The body is heated by infrared radiation for two different time windows and the cooling process that follows is monitored in time by the so-called interferograms that are developed and are the result of the superposition of the holographic recordings of the sample prior to the thermal load and at variable time intervals during the cooling process. The fringe patterns in the interferometric images reveal features and characteristics of the interior of the material, with the experimental method and the post-process analysis adopted in this work offering accuracy, sensitivity and full-field diagnosis, in a completely non-destructive manner, without the need of sampling.

Optical measurements are increasingly widely used as preferential techniques to evaluate dimensional and surface quantities in micro-products. However, uncertainty estimation is more critical on micro-products than macro, and it needs careful attention for evaluating the obtained quality, the requested tolerance, and the correct setting of experimental process settings. In this study, optical measurements characterized micro-injected products by linear and surface acquisition and considered all the sources contributing to uncertainties. The results show that the measure uncertainty could be underestimated if only the standard deviation on simple measurements is considered; this could cause a significant restriction of the estimated range covering the measured values. Furthermore, the findings confirm that the correct evaluation of the potential uncertainties contributes to accurately assessing the process behavior and improving product quality. [ABSTRACT FROM AUTHOR]

Optics with high-precision height and slope are increasingly desired in numerous industrial fields. For instance, Kirkpatrick–Baez (KB) mirrors play an important role in synchrotron X-ray applications. A KB system is composed of two aspherical, grazing-incidence mirrors used to focus an X-ray beam. The fabrication of KB mirrors is challenging due to the aspherical departure of the mirror surfaces from base geometries and the high-quality requirements for slope and height residuals. In this paper, we present the process of manufacturing an elliptical cylinder KB mirror using our in-house-developed ion beam figuring (IBF) and metrology technologies. First, the key aspects of figuring and finishing processes with IBF are illustrated in detail. The effect of positioning error on the convergence of the residual slope error is highlighted and compensated. Finally, inspection and cross-validation using different metrology instruments are performed and used as the final validation of the mirror. Results confirm that relative to the requested off-axis ellipse, the mirror has achieved 0.15-µrad root mean square (RMS) and 0.36-nm RMS residual slope and height errors, respectively, while maintaining the initial 0.3-nm RMS microroughness.Highlights: Demonstrated our in-house developed, high-performance Kirkpatrick–Baez mirror manufacturing solution. Highlighted the key factors and strategies in achieving stringent mirror design specifications. Achieved excellent slope error (0.15 µrad RMS), height error (0.36 nm RMS), and microroughness (0.3 nm RMS). [ABSTRACT FROM AUTHOR]

Scatterometry-based metrology has the capability to perform high-throughput inspection of large-area nanopatterned surfaces. It utilizes physics-based dependencies between reflectance spectra of light scattered from nanopatterned surfaces and the geometric parameters, or so-called Critical Dimensions (CDs), of such nanopatterns. This paper proposes a novel method for rapid and accurate inference of CDs of complex nanopatterned surfaces through the use of a Machine Learning (ML)-based inverse problem mapping, coupled with the use of a strategic feature selection algorithm, which also originated from the ML domain. Specifically, Latin Hypercube Sampling was utilized to create a multi-dimensional grid of CDs which are used as inputs for physics-based simulations of scattered light spectra for nanopatterned surfaces with those CDs. Simulation results are used to build the training data for the ML model relating simulated reflectance spectra with the corresponding CDs. The Extreme Gradient Boosting (XGBoost) algorithm was utilized to realize the aforementioned mapping. In addition, most informative spectral wavelengths were selected using Recursive Feature Elimination (RFE) algorithm based on the feature importance scores obtained from XGBoost. Capabilities of the newly proposed approach were evaluated through inspection of a semiconductor wafer sample with hourglass patterns, which are characterized by eight CDs. It was observed that the proposed method is capable of real-time CD metrology of large-area nanostructured surfaces with complex nanopatterns, with accuracy and repeatability comparable to that of Scanning Electron Microscopy. [ABSTRACT FROM AUTHOR]

Periodic arrays of metallic nanostructures were fabricated by electron beam lithography and studied by means of spectroscopic imaging ellipsometry in the near infrared to ultraviolet spectral ranges. The sample consists of gold nanodisc and nanorod gratings on a silicon substrate. Spectroscopic imaging ellipsometry, allowing for the simultaneous observation of all gratings with microscopic resolution, was used to systematically analyze the varying grating and nanostructure parameters. The ellipsometric spectra obtained for a full in‐plane sample rotation proved to be a highly sensitive measure of the gratings' Rayleigh–Wood anomalies. Their dependence on the sample azimuth was in excellent agreement with the Rayleigh lines calculated from the grating parameters and could be tracked for both the ambient‐to‐grating and the grating–substrate interfaces. Contrary to other studies on similarly sized nanoparticle arrays, we found no indication of localized plasmon resonance in the visible range of the spectrum, but only a weak NIR response truncated by the Rayleigh lines. Finally, the symmetry of the structures was investigated by imaging Mueller‐matrix measurements. [ABSTRACT FROM AUTHOR]

Here, we report on a simplified laser frequency noise measurement technique employing an acousto-optic modulator, a delay line, and a real-time oscilloscope. The technique is a slight modification of the typical delayed heterodyne method. Instead of using a swept frequency spectrum to analyze the laser emission spectrum, the waveform captured on a real-time oscilloscope is used to directly calculate the laser frequency noise. The oscilloscope bandwidth and sampling requirements can be kept modest by choosing a modulator driven at a few hundred megahertz, making this technique attractive for a large number of laboratories. We show the frequency noise measurements of two different lasers with linewidths at 2.7 kHz and 2 MHz. We took the opportunity to investigate the noise floor of the frequency noise measurement system, and we found that the noise floor of the frequency noise measurement depends on the power level of the laser that is being characterized, with the kilohertz linewidths laser requiring more power to reduce the noise floor to acceptable levels.

High-strength and corrosion-resistant materials, such as the nickel-based superalloy Inconel 718, are widely used in the energy and aerospace industries. However, machining these materials results in high process forces and significant tool wear. This tool wear negatively influences the resulting surface topography. Nevertheless, the accuracy requirements for functional surfaces are extremely high. Simulation systems can be used to design these processes. However, time-consuming and cost-intensive experiments often have to be conducted to develop and parameterize the required models. To overcome this problem, an analogy test setup for in-process measurements of wear-dependent properties was developed, which allows a multi-level evaluation of the process. By combining different measurement techniques, wear-dependent process characteristics can be determined and analyzed, which is usually only possible for initial and final conditions requiring a significant measurement effort. [ABSTRACT FROM AUTHOR]

To fully exploit the advantages of fourth-generation synchrotron light sources, diffraction-limited-storage-rings (DLSR) and fully coherent free electron lasers (FELs), beamline mirrors and diffraction grating must be of exceptional quality. To achieve the required mirror and grating quality, the metrology instrumentation and methods used to characterize these challenging optics and, even more so, optical assemblies must also offer exceptional functionality and performance. One of the most widely used slope measuring instruments for characterizing x-ray optics is the long trace profiler (LTP). The easily reconfigurable mechanical design of the LTP allows optimization of the profiler arrangement to the specifics of a particular metrology task. Here, we discuss the optical schematic, design, and performance of an original multifunctional light beam source that provides functional flexibility of the LTP optical sensor. With this source, the LTP can be easily reconfigured for measurements of x-ray mirrors or diffraction gratings that have widely different source coherence requirements. Usage of a source with a low degree of coherence for mirror metrology helps to suppress the LTP systematic errors due to spurious interference effects in the LTP optical elements. A high-coherence narrow-band source is used for groove-density-distribution characterization of x-ray diffraction gratings. The systematic error and spatial resolution of the LTP with the different sources is also measured and analyzed.

Femtosecond frequency combs are among the most precise measurement tools in existence. They have applications ranging from high‐precision spectroscopy and metrology to time‐domain quantum physics. Maximizing the passive stability of these instruments is essential to achieve their full potential in fundamental science and high‐tech industry. However, the noise mechanisms across the entire operating space of these devices have not been fully characterized. Here the noise properties of fiber‐based frequency combs are studied as a function of intracavity dispersion, pump power, and repetition rate. Distinct minima are discovered in this parameter space where the free‐running linewidth of the carrier‐envelope offset (CEO) frequency fCEO drops below 1 kHz. The individual comb lines are analyzed spread over a wide spectral range producing a complete understanding of the particular contributions to the phase noise and their interplay. Exploiting these findings, combs featuring sharp teeth at specific frequency positions and over the entire spectrum from fCEO to 300 THz are demonstrated. The ultrabroadband stability offered by these compact systems provides a new level of quality for front‐end measurement tasks in both time and frequency domains. [ABSTRACT FROM AUTHOR]

Immersion microscope objectives stand out for their large numerical aperture, which improves the optical resolution of imaging systems such as those used in microscopic interferometry. These objectives increase the gradient forces of a beam focused through them, forming an Optical Trap (OT). However, many studies on microscopic interferometry neglect the contributions of different optical materials in the system that are also exposed to laser radiation, perhaps simply assuming transparency. In this work, a Mach–Zehnder interferometer and an OT, which share several components (including the same oil immersion objective), were coupled. Here, the response of the interferometer to a progressive increase in the OT laser power, while the interferometer laser power remains constant, is reported. Changes in laser power affect the oil temperature, altering its refractive index and volume, which in turn causes a phase shifting on the transmitted wavefront. Optical phase analysis is applied in the three-dimensional measurement of the damage produced by the OT on a paint film. This study suggests that the refractive index variations in the immersion oil affect interferograms because they will then exhibit an additive phase term that must be considered in that final measurement. Additionally, the OT geometry changes with the power increase.

The dataset presented contains microtopographies of various materials and processing methods. These microtopographies were measured using a Confocal Laser Scanning Microscope, which provides RGB-D data. This means the dataset comprises accurate height maps for each measurement and microscopic RGB images. The height maps can be used to quantify and characterize small-scale surface features such as pits and grooves, surface roughness, texture direction, and surface anisotropy. These features can significantly impact a material's properties and behavior, making them essential in many fields, such as biomaterials and tribology. Additionally, the dataset contains metadata about the specimens and the measurement conditions, such as material, surface processing method, roughness, and optical magnification. Therefore, this dataset provides an opportunity to develop and test surface classification and characterization algorithms.

High-precision electro-optic distance measurement (EDM) is essential for deformation monitoring. Although sub-ppm instrumental accuracy is already feasible with state-of-the-art commercial technology, the practically attainable accuracy on distances over more than a few hundred meters is limited by uncertainties in estimating the integral refractive index along the propagation path, which often results in measurement errors of several ppm. This paper presents a new instrumental basis for high-accuracy multispectral EDM using an optical supercontinuum to enable dispersion-based inline refractivity compensation. Initial experiments performed on two spectrally filtered bands of 590 and 890 nm from the supercontinuum show measurement precision better than 0.05 mm over 50 m for an acquisition time of around 3 ms on the individual bands. This represents a comparable performance to our previously reported results on 5 cm by over a range of 3 orders of magnitude longer, which can still be improved by increasing the acquisition time. The preliminary results indicate a relative accuracy of about 0.1 mm at 50 m on each wavelength. Improvement is possible by calibration and by implementing a self-reference scheme that mitigates slow drifts caused by power-to-phase coupling. The results reported herein thus indicate that the presented approach can be further developed for achieving sub-ppm accuracy of refractivity compensated distance measurements on practically useful ranges and under outdoor conditions. [ABSTRACT FROM AUTHOR]

Atomic state manipulation by laser radiation requires a stringent control of the light phase noise for precise spectroscopy and quantum computation. In this work we describe a novel interferometer recently employed to estimate the phase noise induced by an optical frequency shifter based on serrodyne modulation for optical frequency standards (Barbiero et al., 2023). The interferometer is generated by an acousto-optic actuator working in the Raman-Nath regime. Using the heterodyne detection between the unshifted optical mode with the first higher order optical components, we are able to detect the differential phase between the two optical path arms with a reduction of the phase noise induced by the actuator. We provide a theoretical treatment for the actuator phase suppression and we estimate the detectable phase noise limit of this interferometer. Finally, we discuss the possible applications in the field of precision measurements. • Composite heterodyne interferometer generated by Raman-Nath diffraction regime. • 4 dB phase noise improvement compared to the classic heterodyne interferometers. • Accurate physical model describing the signal extraction mechanisms. [ABSTRACT FROM AUTHOR]

• Developed a pseudo-light source for digital holographic microscopy through AI model, effectively achieving both characteristics of high coherence and low speckle noise. • Utilized conditional generative adversarial networks to train the pseudo-light source on the paired holograms, adeptly mimicking the low-noise characteristics of partially coherent quantum dot (QD)-based light while preserving the high-resolution interference patterns of highly coherent laser. • Achieving significant speckle noise contrast reduction from 0.602 to 0.0691, resulting in clear interference patterns even under conditions that surpass the coherence length limitation of QD-based light system. • Experimentally validated the pseudo-light source's capability to maintain accurate phase information in the AI-generated holograms, enabling precise three-dimensional reconstruction of surface depth distribution. Digital holography, a promising technology for optical imaging, is limited by the fundamental challenge of speckle noise when based on coherent lasers. These approaches often compromise either coherence, affecting surface depth measurement capabilities, or introduce excessive noise, degrading image clarity. To eliminate this trade-off, this study introduces a novel solution based on an AI-driven pseudo-light source that simultaneously achieves high coherence and low speckle noise in holographic imaging. Consisting of conditional generative adversarial networks, the AI model was trained on paired holograms from both highly coherent laser light and partially coherent quantum dot (QD)-based light sources to generate holograms that mimicked the low-noise characteristics of QD-based light while retaining the high coherence length of laser. The effectiveness of the pseudo-light source was validated through holographic observations on a reflective 8.0-µm-deep specimen. Compared to the laser, the AI-driven pseudo-light source achieved substantial improvement in interference pattern clarity and reduced speckle noise contrast from 0.602 to 0.0873. Moreover, the standard deviation of the surface depth distribution was notably reduced from 215.3 nm to 44.7 nm. Quantitative phase evaluations further confirmed the preservation of accurate phase information in the generated holograms, verifying the successful reconstruction of the three-dimensional specimen structure. [ABSTRACT FROM AUTHOR]

Some metrological means, such as Shack-Hartmann, deflectometry sensors or fringe projection profilometry, measure the shape of an optical surface indirectly from slope measurements. Zonal shape reconstruction, a method to reconstruct shape with a high number of degrees of freedom, is used for all of these applications. It has risen in interest with the use of deflectometers for the acquisition of high resolution slope data for optical manufacturing, especially because shape reconstruction is limiting in terms of shape estimation error. Zonal reconstruction methods all rely on the choice of a data formation model, a basis on which the shape will be decomposed, and an estimator. In this paper, we first study the canonical Fried and Southwell models of the literature and analyze their limitations. We show that modeling the slope measurement by a point-wise derivative as they both do can induce a bias on the shape estimation, and that the bases on which the shape is decomposed are imposed because of this assumption. In the second part of this paper, we propose to build an unbiased model of the data formation, without constraints on the choice of the decomposition basis. We then compare these models to the canonical models of Fried and Southwell. Lastly, we perform a regularized MAP reconstruction, and compare the performance in terms of total shape error of this method to the state of the art for the Southwell and Fried models, first by simulation, then on experimental data. We demonstrate that the suggested method outperforms the canonical models in terms of total shape reconstruction error on a deflectometry measurement of the high-frequency content of a freeform mirror. • Shape reconstruction algorithms are limiting slope-based metrology methods. • Uncontrolled forward models can generate systematic errors. • Well-chosen estimators enable free-form mirror high frequency metrology by deflectometry. [ABSTRACT FROM AUTHOR]