Asphere and freeform metrology forms the basis of precision optics fabrication. Stitching or scanning methods provide the necessary flexibility, but require measurement times of several minutes. Using parallel information channels of light (wavelength, polarization, phase) in combination with the model-based tilted wave interferometry approach boosts the measurement possibilities. In this proceeding we show how these information channels can be used to enhance the measurement capabilities regarding reconstruction quality and show how the complete shape information of strong aspheres can be recorded by TWISS (tilted wave interferometry single-shot) within milliseconds.

In this study we have designed, assembled, and characterized a wavefront sensor that works with defocused intensity images and the wavefront phase imaging (WFPI) algorithm. This approach allows for the potential utilization of the entire sensor surface, enabling high-resolution operation. This sensor, equipped with an electrically tuneable lens (ETL), performs focus movements of more than 60 Hz, enough for real time applications. We have developed numerical tools, as a practical software environment, with a graphical user interface (GUI), to make the camera a versatile instrument easily adaptable to different experimental setups without drastic changes in the optical configuration. These tools allow to analyse the wavefront in real time to extract the desired metrics and results.

The refractive index structure constant C²_n and the microscale ℓ₀ of turbulence contribute as crucial indicators of turbulence strength in a medium, such as the atmosphere. These parameters exert a substantial influence on measurements performed with Laser Doppler Vibrometry in an open atmosphere. Their significance becomes evident through variations in the phase characteristics of laser beams induced by outdoor turbulent phenomena, thereby impacting the precision and reliability of measurements. We discuss the measurement of turbulence parameters through application of the Rytov approximation using a specialized arrangement with laser Doppler vibrometers. In this paper, we investigate how this method allows deriving key turbulence parameters, such as the refractive index structure constant C²_n and the inner scale of turbulence ℓ₀.

In this work, we exploit HHG in a noble gas to merge the azimuthally twisted wavefront of a vortex beam and the spatially varying polarization of a vector beam, yielding EUV vector-vortex beams (VVB) that are tailored simultaneously in their SAM and OAM. Employing a high-resolution EUV Hartmann wavefront sensor (EUV HASO, Imagine Optic), we perform the complete spatial intensity and wavefront characterization of the vertical polarization component of the 25th harmonic beam centered at a wavelength of 32.6 nm. By driving the HHG using IR VVB, we show that HHG enables the production of EUV VVB exhibiting radial, azimuthal, or even intermediate polarization distribution. Furthermore, the wavefront characterization allows for the unambiguous confirmation of the topological charge and OAM helicity of the upconverted harmonic VVB. Notably, our work reveals that HHG provides a means for the synchronous and controlled manipulation of SAM and OAM. The production of ultrafast EUV VVB with high OAM and adjustable polarization distributions opens up promising prospects for their applications at nanometric spatial and sub-femtosecond temporal resolutions using a table-top harmonic source.

The upcoming IEEE standard P4001 outlines a set of parameters for characterizing the performance of hyperspectral cameras along with recommended measurement procedures. This study concentrates on validating a simplified approach to measure the across-track spatial resolution of a pushbroom hyperspectral camera with a sensor sampling factor of two or higher, in comparison to the scanning-based approach described in the standard. The findings indicate that the snapshot-based method produces values for the width of the sampling line spread function in the across-track direction that closely match those obtained through scanning with sub-pixel steps for hyperspectral cameras with a sensor sampling factor of two or higher.

Conventional agriculture relies heavily on herbicides for weed control. Smart farming, particularly through the use of mechanical weed control systems, has the potential to reduce the herbicide usage and the associated negative impact on our environment. The growing accessibility of multispectral cameras in recent times poses the question if their added expenses justify the potential advantages they offer. In this study we compare the weed and crop detection performance between RGB and multispectral VIS-NIR imaging data. Therefore, we created and annotated a multispectral instance segmentation dataset for sugar beet crop and weed detection. We trained Mask-RCNN models on the RGB images and on images composed of different vegetation indices calculated from the multispectral data. The outcomes are thoroughly analysed and compared across various scenarios. Our findings indicate that the use of vegetation indices can significantly improve the weed detection performance in many situations.

The significance of precise metrology in various industries, particularly within manufacturing plants, is undeniable, especially as components and devices continue to undergo miniaturization. The emergence of nanomanufacturing further amplifies the necessity for meticulous measurement techniques. Coherent Fourier scatterometry is a non-imaging, model-based, bright-field optical metrology technique used for retrieving complex geometric parameters of nanostructures. However, the scanning time has been a limiting factor in its wider adoption as a commercial metrology tool. To address this limitation, we propose a novel design utilizing a galvo mirror for faster scanning, offering significant improvements in scan speed.

Production and qualification of electronic cameras currently requires the use of optical target projectors. The quality of the target projectors used impacts the quality of the final products. We designed and constructed an apparatus for evaluating target projector parameters, such as the projection distance, target backlighting, projector FoV and projection quality. This device allows us to qualify optical target projectors and to perform long term and under stress tests.

We employ aligned two-photon lithography (A2PL®), to push high precision alignment tasks from the photonic packaging step towards the fabrication process in a one step process. Combined with Two-Photon Grayscale Lithography (2GL®), this approach enables direct fabrication of micro-optical elements onto devices, enhancing functionality with highest surface quality and shape fidelity at high throughput. We demonstrate automated 3D alignment using customer-ready detection algorithms, to fabricate micro-optical elements attached to various topographies and material platforms with exceptional accuracy below 100 nm. We showcase micro-optical elements aligned to fiber tips, photonic edge couplers, and photonic grating couplers to demonstrate the validity of A2PL for improved coupling losses and beam quality.

In an industrial context, AI-based methods are becoming increasingly important in the optical systems used for identification, inspection and classification. The reasons for this are that AI-based image processing algorithms are easy to use on the operator side and often achieve superior results. E.g. in complex classification tasks. In the sand cast industry, the complexity in optical inspection of cast parts is connected with strong variations in the local surface topography and in the global object geometry change. Despite the great potential of AI-based methods, application is often hindered by the immense effort involved in acquiring a suitable training dataset. This refers not only to the acquisition of the required number of images but also to the tedious labelling. In this work, we investigate the capabilities and limits of synthetic training data on an AI-based optical scanner used to identify and track cast parts. The optical scanner is capable of detecting and classifying a codification specifically designed for the casting industry. By reading the code, the scanner can deduce the specific number of the cast part. For synthetic image generation, we use physically based rendering, which has advantage of full control over all rendering parameters. This allows for both a systematic investigation of the importance of the parameters and, an automatic labelling process of the training datasets. Our results show that, in particular, a detailed geometric modelling of the local surface topography and global object geometry of the pins have a positive influence on the recognition rate of the neural network. With that accuracy rates up to 56 % are achieved using synthetic training datasets, only.

Miniature microscopy provides a transformative approach to observe objects and enable continuous monitoring with ultra-compact microscopes attached directly to specimens, facilitating parallel analysis. This innovation is particularly valuable for applications such as drug discovery using organ-on-a-chip devices, which require the assessment of numerous drug/sample pairs prior to clinical trials. Ultra-compact microscopes were previously limited to brightfield techniques, which prevented the use of powerful tools like fluorescent microscopy. In this work, we present a miniature microscope with integrated fluorescence measurement capabilities. This microscope consists of a custom chip with a 10 μm-diameter single-photon avalanche diode (SPAD) faced to a 640 × 480 InGaN/GaN 4 μm-pitch LED microdisplay. It operates in raster mode, activating individual LEDs to map specimens in 2D while measuring fluorescence light with the SPAD chip. Our results demonstrate its suitability for life sciences imaging. For example, we observed a muscle-ona-chip stained with Alexa Fluor 488 to study drug efficacy on sarcopenia. Furthermore, these microscopes exhibit superior speed compared to the previously reported ultra-compact brightfield microscopes, achieving a 240-fold increase in imaging rate by means of hardware controller integration on FPGA.

Ongoing research is actively exploring microendoscopy systems for high-resolution imaging and disease diagnosis. State-of-the-art commercial endoscopes use fiber bundles for relaying the image formed by the lens system in the imaging probe head. However, they are expensive and resolution is limited by the spacing between the cores and cross-talk between the pixels. Fiber scanning-based imaging systems are promising due to their ability to be designed with a single fiber alongside micro-objective lenses. However, these systems face a significant challenge when it comes to the necessity of free space optics and photomultiplier tubes for fluorescence detection, which can be tricky in terms of alignment. Furthermore, the existing imaging systems at near-infrared wavelengths utilize double-clad fiber with larger clad for fluorescence collection. We present a compact, low-cost, and portable system for imaging at visible wavelength that utilizes a double-clad fiber of smaller inner clad (diameter of 15 µm) in conjunction with a bandpass filter and Avalanche Photodetector to detect fluorescence emission. To assess the effectiveness of this system, we conducted a study on the performance of an imaging head consisting of a gradient refractive index (GRIN) lens (diameter of 1 mm) as a micro-objective in a fiber-scanning setup by actuating a piezoelectric tube with a fiber channel inside. We demonstrated the reflectance imaging of a standard resolution chart and fluorescence detection from microspheres at 644 nm.

Microscopy is essential in academic and medical research, driving the quest for cost-effective solutions. Inspired by modified 3D printers, these innovations enable the scanning of 2D and 3D samples, leveraging affordability and three-dimensional movement. In the realm of multimodal imaging, LED panels and LCD screens offer adaptable lighting options, balancing cost, ergonomics, and image quality remains a formidable challenge. Introducing OpenMIC, a groundbreaking solution seamlessly integrating multiple scanning features and multimodal lighting. Transformed from a 3D printer using a Raspberry Pi 4, a 64x64 LED array, and an optical module, it offers four lighting modalities, micrometric autofocus, focus stacking, image stitching, and automated scanning of 12 histological slides. OpenMIC is marked by its scalability, professional imaging quality, and a manufacturing cost under 4,000 euros.

Spectrum data obtained from hyperspectral optical systems were analyzed with a CNN-based deep learning model to detect and identify maritime small objects. The hyperspectral data set for learning was extracted from more than 60 aerial observation images, and classification accuracy was derived by applying a total of 7 CNN models. Among the models used, Inception_v3 was the best at 94.9%, and this result showed more than 10% improvement in accuracy over previous studies conducted with multi-layer perceptron (MLP). If further research breaks down classification items and increases the size of datasets, we expect that the technology will become increasingly utilized in the field of maritime search and surveillance.

Wavefront sensors (WFS) have now become core components in the fields of metrology of optical systems, biomedical optics, or adaptive optics systems for astronomy. However, none of the designs defined so far achieves simultaneously a high spatial resolution at the pupil of the tested optics and absolute measurement accuracy comparable to that of laser-interferometers. This paper presents an improved WFS design that reaches both previous goals. The device is named Crossed-sine phase sensor (CSPS) and is based on a fully transparent Gradient phase filter (GPF) whose virtual image is located forward or backward the exit pupil of the tested optical system. After briefly summarizing the theoretical principle of the CSPS, we describe four different optical layouts meeting its requirements and evaluate them with the help of Zemax modeling. We finally select the best optical design and discuss the achieved optical performance.

The Gran Telescopio de Canarias Adaptive Optic System (GTCAO) is built to provide nearly diffraction-limited images to GTC. GRANCAIN (GRAN CAmara INfrarroja) is the first light cryogenic imaging instrument in J, H, and K infrared bands, which will be integrated into the Nasmyth focus of GTCAO. The instrument is designed to image the NIR (NearInfrared) diffraction limit for a field of view of 22x22 arcsec operating up to conditions of 1.5 arcsec and zenithal distances up to 60 deg. The instrument has a telecentric optical design based on a collimator camera with a 2:1 magnification, with a cold stop, and the filters between with an infrared detector everything inside the cryostat for operating at 50 K. This article presents a comprehensive overview of the end-to-end optical design of GRANCAIN. It explores the selection criteria for diverse commercial elements, conducts thermal analysis utilizing Ansys Zemax OpticStudio, and delineates the acceptance tests performed at the IAC. The article also encompasses tolerance analysis using Ansys Zemax OpticStudio and establishing the error budget. Furthermore, the text provides a detailed account of the alignment process, achieved through the mechanical positioning of each optical element with a laser tracker and the confirmation of positions under cryogenic conditions is conducted using an alignment telescope. Lastly, the article discusses the optical acceptance plans for the instrument before its integration into GTCAO.

The ASTRABAX project ("Aschaffenburg Stratospheric Balloon Experiment"), being funded for the years 2024 to 2026, is designed as a multimodal platform for the investigation of radiation exposures at high altitude. The UV-C spectral region is of special interest. Spectral measurements observe this region of interest using miniature UV-VIS spectrometers. The platform also contains a radiation dosimetry, a power source for on-board electronics, and common shielding setups for multiple spectral combinations. Human cells are exposed simultaneously to radiation of different compositions as particle, X-ray and UV radiation. After the flight, possible changes in the spatial chromatin organization are examined. Material samples intended for the development of satellite components are irradiated also. Investigations under such conditions are realistic and crucial for high altitude flights in the atmosphere, for space flights as well as for comparable exposures on other objects of the solar system, and even for exoplanet habitats to some extent.

This project aims to formulate, design , build and test a versatile, high-efficiency, low-resolution spectrograph to function as the G-CLEF (GMT-Consortium Large Earth Finder) exposure meter. G-CLEF, the first-generation Giant Magellan Telescope's (GMT) instrument, is a state-of-the-art, high-resolution, echelle spectrograph for the GMT, expected to be completed for the telescope's first light. The exposure meter plays a vital role for adjusting barycentric corrections of Doppler radial velocity (RV) by accounting for t Earth's chromatic atmospheric influences. Its significance becomes pronounced in Extreme Precision RV (EPRV) measurements, where the atmosphere's wavelength dependency contributes to errors at the scale of tens of centimeters per second, the same level of precision required for detecting Earth-analog planets orbiting stars similar to the Sun, aligning with one of the primary scientific objectives of G-CLEF. This paper explores the scientific motivation in detail, describes the designs trade-off analysis and the performance simulations aiming to achieve 1cm/s precision on EPRV measurements and outlines the resulting principal parameters derived from these analyses.

In current camera sensor-objective alignment approaches for an automotive industry, slow and iterative scan methods are widely used with a cycle time not fully compatible with contemporary production lines. New method is proposed to facilitate immediate active alignment of the sensor comprising a focal plane array and an objective. The method is based on a single-shot sensor data read-out with unknown absolute and correct alignment positions in all six degrees of freedom. First three unknown alignment values can be calculated based on a classical centroid approach, while the remaining three are calculated using an AI model. This immediately leads to massive production line simplification and cost reduction, so important for the automotive industry.

Remote sensing is a very promising technology and technique for gathering data about whatever is under consideration. It has become indispensable for various applications like physical geography, bathymetry, forestry, archeology, agriculture, and autonomous vehicles. This technology uses diversified instruments, sensors, and imaging devices to accomplish its goal. There are different types of remote sensing, in which our focus is active remote sensing. Active remote sensing involves the emission of pulses and the capturing of their returns. One of the state-of-the-art technology used for such types of sensing is LiDAR (Light Detection and Ranging). LiDAR technology is a key player in measuring distances and creating a 3D illustration. In the past, multiple works have been published on LiDAR for various applications to get a large field of view, smaller spot size, and high spatial resolution. The focus of this review paper is to describe the development of a LiDAR system through cutting-edge simulation tools, such as Zemax. To cope with the exclusive demands of remote sensing, the tools provide us the opportunity to refine the LiDAR designs and enhance the methods of data collection, accuracy, speed, and spatial resolution. The internal components like scanners, detectors, and sources can also be optimized for better performance. The outcome of this review work is to help researchers enhance the LiDAR performance for a range of applications in remote sensing, specifically in the fields that require precise and high 3D resolution for monitoring and decision-making.

Many biological processes and microstructures are imperceptible to the naked eye. To pose this challenge microscope is regarded as an indispensable tool for studying and working with the microworld. With the use of a microscope, one can examine an object at the cellular level and determine the structure of cells, tissues, and microbes. Using microscopes, science, technology, engineering, and math (STEM), education has been able to overcome significant obstacles, and learning has become more interactive and engaging. Students can explore the intricate details of the microstructures they are studying, which enhances comprehension and retention of knowledge. In biology courses, students are encouraged to engage in hands-on microscope experiments. With the remarkable technological advancements in interactive learning (IL) over the last decade, there has been a notable increase in productivity and interactivity. Consequently, IL has emerged as a potentially valuable way to enhance the understanding and practical competencies of students. This study introduces an educational compound microscopic system that utilizes IL technology to facilitate the examination of under-observation samples by showing information in real time. Students can complete most microscope-based experiments in biology courses and will be able to identify and analyze the biological samples when the prepared slides are seen under our designed compound microscope. The integration of IL technology enhances the performance and applicability of traditional compound microscopes. In addition to this, our portable microscope is costeffective, easy to use, and more efficient than traditional compound microscopes utilized for education purposes.