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At least 55 records · Page 3

NASA Today - Mars Observer Segment (Part 4 of 6)

This videotape consists of eight segments from the NASA Today News program. The first segment is an announcement that there was no date set for the launch of STS-51, which had been postponed due to mechanical problems. The second segment describes the MidDeck Dynamic Experiment Facility. The third segment is about the scheduled arrival of the Mars Observer at Mars, it shows an image of Mars as seen from the approaching Observer spacecraft, and features an animation of the approach to Mars, including the maneuvers that are planned to put the spacecraft in the desired orbit. The fourth segment describes a discovery from an infrared spectrometer that there is nitrogen ice on Pluto. The fifth segment discusses the Aerospace for Kids (ASK) program at the Goddard Space Flight Center (GSFC). The sixth segment is about the high school and college summer internship programs at GSFC. The seventh segment announces a science symposium being held at Johnson Space Center. The last segment describes the National Air and Space Museum and NASA's cooperation with the Smithsonian Institution.

Source record↗

Spatial scale of motion segmentation from speed cues

For the accurate perception of multiple, potentially overlapping, surfaces or objects, the visual system must distinguish different local motion vectors and selectively integrate similar motion vectors over space to segment the retinal image properly. We recently showed that large differences in speed are required to yield a percept of motion transparency. In the present study, to investigate the spatial scale of motion segmentation from speed cues alone, we measured the speed-segmentation threshold (the minimum speed difference required for 75% performance accuracy) for 'corrugated' random-dot patterns, i.e. patterns in which dots with two different speeds were alternately placed in adjacent bars of variable width. In a first experiment, we found that, at large bar widths, a smaller speed difference was required to segment and perceive the corrugated pattern of moving dots, while at small bar-widths, a larger speed difference was required to segment the two speeds and perceive two transparent surfaces of moving dots. Both the perceptual and segmentation performance transitions occurred at a bar width of around 0.4 degrees. In a second experiment, speed-segmentation thresholds were found to increase sharply when dots with different speeds were paired within a local pooling area. The critical pairing distance was about 0.2 degrees in the fovea and increased linearly with stimulus eccentricity. However, across the range of eccentricities tested (up to 15 degrees ), the critical pairing distance did not change much and remained close to the receptive field size of neurons within the primate primary visual cortex. In a third experiment, increasing dot density changed the relationship between speed-segmentation thresholds and bar width. Thresholds decreased for large bar widths, but increased for small bar widths. All of these results are well fit by a simple stochastic model, which estimates the probabilities of having identical or different motion vectors within a local pooling area whose size is the same as that of primate V1 neurons. Altogether, these results demonstrate that speed-based segmentation can function well, even at small spatial scales (i.e. high-spatial frequencies of spatial corrugation) and thereby emphasizes the critical role of a local pooling process early in the cortical motion-processing pathway.

NASA Discipline Neuroscience↗

The spatial and temporal expression of Ch-en, the engrailed gene in the polychaete Chaetopterus, does not support a role in body axis segmentation

We are interested in understanding whether the annelids and arthropods shared a common segmented ancestor and have approached this question by characterizing the expression pattern of the segment polarity gene engrailed (en) in a basal annelid, the polychaete Chaetopterus. We have isolated an en gene, Ch-en, from a Chaetopterus cDNA library. Genomic Southern blotting suggests that this is the only en class gene in this animal. The predicted protein sequence of the 1.2-kb cDNA clone contains all five domains characteristic of en proteins in other taxa, including the en class homeobox. Whole-mount in situ hybridization reveals that Ch-en is expressed throughout larval life in a complex spatial and temporal pattern. The Ch-en transcript is initially detected in a small number of neurons associated with the apical organ and in the posterior portion of the prototrochophore. At later stages, Ch-en is expressed in distinct patterns in the three segmented body regions (A, B, and C) of Chaetopterus. In all segments, Ch-en is expressed in a small set of segmentally iterated cells in the CNS. In the A region, Ch-en is also expressed in a small group of mesodermal cells at the base of the chaetal sacs. In the B region, Ch-en is initially expressed broadly in the mesoderm that then resolves into one band/segment coincident with morphological segmentation. The mesodermal expression in the B region is located in the anterior region of each segment, as defined by the position of ganglia in the ventral nerve cord, and is involved in the morphogenesis of segment-specific feeding structures late in larval life. We observe banded mesodermal and ectodermal staining in an anterior-posterior sequence in the C region. We do not observe a segment polarity pattern of expression of Ch-en in the ectoderm, as is observed in arthropods. Copyright 2001 Academic Press.

Non-NASA Center↗

Design and Optimization of the SPOT Primary Mirror Segment

The 3m Spherical Primary Optical Telescope (SPOT) will utilize a single ring of 0.86111 point-to-point hexagonal mirror segments. The f2.85 spherical mirror blanks will be fabricated by the same replication process used for mass-produced commercial telescope mirrors. Diffraction-limited phasing will require segment-to-segment radius of curvature (ROC) variation of approx.1 micron. Low-cost, replicated segment ROC variations are estimated to be almost 1 mm, necessitating a method for segment ROC adjustment & matching. A mechanical architecture has been designed that allows segment ROC to be adjusted up to 400 microns while introducing a minimum figure error, allowing segment-to-segment ROC matching. A key feature of the architecture is the unique back profile of the mirror segments. The back profile of the mirror was developed with shape optimization in MSC.Nastran(TradeMark) using optical performance response equations written with SigFit. A candidate back profile was generated which minimized ROC-adjustment-induced surface error while meeting the constraints imposed by the fabrication method. Keywords: optimization, radius of curvature, Pyrex spherical mirror, Sigfit

Budinoff, Jason G.↗

Metric Learning to Enhance Hyperspectral Image Segmentation

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

Thompson, David R.↗

Application of unsupervised deep learning to image segmentation and in-situ contact angle measurements in a CO 2 -water-rock system

Rock surface wettability is a critical property that regulates multiphase flows in porous media, which can be quantified using the surface contact angle (CA). X-ray micro-computed tomography (μCT) provides an effective approach to in-situ measurements of surface CAs. However, the CA measurement accuracy depends significantly on the quality of CT image segmentation, which is the clustering of CT pixels into separate phases. Inspired by this, we developed a deep learning (DL)-based CA measurement workflow. Motivated by the recent tremendous progress in unsupervised learning techniques and aiming to avoid expensive manual data annotations, an unsupervised DL pipeline for CT image segmentation was proposed and implemented, which includes unsupervised model training and post-processing. The unsupervised model training was driven by a novel loss function constrained with feature similarity and spatial continuity and implemented by iterative forward and backward paths; the former clustered the pixel-wise feature vectors extracted by convolution neural networks, whereas the latter updated the parameters using gradient descent. An over-segmentation strategy was adopted for model training. The post-processing steps based on agglomerative hierarchical clustering (AHC) were implemented to further merge the over-segmented model output to the desired cluster number, which is intended to improve the efficiency of image segmentation. The developed unsupervised DL pipeline was compared with other commonly-used image segmentation methods using pixel-wise and physics-based evaluation metrics on a synthetic raw-image dataset, which had a known ground truth. The unsupervised DL pipeline showed the best performance. Next, the segmented images were input to an automatic CA measurement tool, and the results were validated by comparisons with manual measurements. The CA values from the manual and automatic measurements showed similar distributions and statistical properties. The automatic measurement demonstrated a wider spectrum because of the much larger number of measurement data points. The primary novelty of the unsupervised DL pipeline developed in this study lies in the novel loss function and the over-segmentation strategy associated with AHC post-processing. Finally, the workflow has been proven an efficient tool for pore-scale wettability characterization, which has a wide range of applications in fundamental studies of multiphase flows in natural porous media, which have critical implications to geological carbon sequestration, hydrocarbon energy recovery, and contaminant transport in groundwater.

42 ENGINEERING↗

Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM

We report three-dimensional (3D) X-ray micro-computed tomography (μCT) has been widely used in petroleum engineering because it can provide detailed pore structural information for a reservoir rock, which can be imported into a pore-scale numerical model to simulate the transport and distribution of multiple fluids in the pore space. The partial volume blurring (PVB) problem is a major challenge in segmenting raw μCT images of rock samples, which impacts boundaries and small targets near the resolution limit. We developed a deep-learning (DL)-based workflow for accurate and fast partial volume segmentation. The DL model's performance depends primarily on the training data quality and model architecture. This study employed the entropy-based-masking indicator kriging (IK-EBM) to segment 3D Berea sandstone images as training datasets. The comparison between IK-EBM and manual segmentation using a 3D synthetic sphere pack, which had a known ground truth, showed that IK-EBM had higher accuracy on partial volume segmentation. We then trained and tested the UNet++ model, a state-of-the-art supervised encoder-decoder model, for binary (i.e., void and solid) and four-class segmentation. We compared the UNet++ with the commonly used U-Net and wide U-Net models and showed that the UNet++ had the best performance in terms of pixel-wise and physics-based evaluation metrics. Specifically, boundary-scaled accuracy demonstrated that the UNet++ architecture outperformed the regular U-Net architecture in the segmentation of pixels near boundaries and small targets, which were subjected to the PVB effect. Feature map visualization illustrated that the UNet++ bridged the semantic gaps between the feature maps extracted at different depths of the network, thereby enabling faster convergence and more accurate extraction of fine-scale features. The developed workflow significantly enhances the performance of supervised encoder-decoder models in partial volume segmentation, which has extensive applications in fundamental studies of subsurface energy, water, and environmental systems.

02 PETROLEUM↗

A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials

In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.

36 MATERIALS SCIENCE↗

Real-time correlation of crystallization and segmental order in conjugated polymers

Modulating the segmental order in the morphology of conjugated polymers is widely recognized as a crucial factor for achieving optimal electronic properties and mechanical deformability. However, it is worth noting that the segmental order is typically associated with the crystallization process, which can result in rigid and brittle long-range ordered crystalline domains. To precisely control the morphology, a comprehensive understanding of how highly anisotropic conjugated polymers form segmentally ordered structures with ongoing crystallization is essential, yet currently elusive. To fill this knowledge gap, we developed a novel approach with a combination of stage-type fast scanning calorimetry and micro-Raman spectroscopy to capture the series of specimens with a continuum in the polymer percent crystallinity and detect the segmental order in real-time. Through the investigation of conjugated polymers with different backbones and side-chain structures, we observed a generally existing phenomenon that the degree of segmental order saturates before the maximum crystallinity is achieved. This disparity allows the conjugated polymers to achieve good charge carrier mobility while retaining good segmental dynamic mobility through the tailored treatment. Moreover, the crystallization temperature to obtain optimal segmental order can be predicted based on T g and T m of conjugated polymers. In conclusion, this in-depth characterization study provides fundamental insights into the evolution of segmental order during crystallization, which can aid in designing and controlling the optoelectronic and mechanical properties of conjugated polymers.

36 MATERIALS SCIENCE↗

Few-shot leaf segmentation

In this work, we use few-shot learning to segment the body and vein architecture of Populus trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the "vein density" trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code, we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes.

Lagergren, John [Oak Ridge National Lab. (ORNL), O↗

Circumferentially segmented duct lines optimized for axisymmetric and standing wave sources

Optimum and off-optimum properties of circumferentially segmented duct liners are compared with those of uniform liners to identify any potential benefits of circumferentially segmented liners. High- and low-order spinning-mode sources are considered in the study. The solution for the segmented liner is obtained by a multimodal expansion of the segmented-liner eigenmodes in terms of a series of hardwall duct models. The coefficients in the hard-wall series are obtained by using Galerkin's method. Results show that for some frequencies and duct lengths, circumferentially segmented liners scatter energy equally between a higher and lower order circumferential wave number. Studies for higher order spinning-mode sources show that an optimized segmented liner with a hard-wall/soft-wal admittance variation representing an optimum configuration gives better performance than an optimized uniform liner. Overall, the greatest benefit of the segmented liner over the uniform liner occurs under off-optimum conditions. The optimized segmented liner gives more effective broadband performance than the optimized uniform liner.

Watson, W. R.↗

Performance characterization of a segmented anode arcjet thruster

A modular, 1 to 2 kW class arcjet thruster incorporating a segmented anode/nozzle was operated on a thrust stand to obtain performance characteristics of the device and further study its operating characteristics under a number of experimental conditions. The nozzle was composed of five axial conducting segments isolated from one another by boron nitride spacers. The electrical configuration allowed the current delivered to the arcjet to be collected at any combination of segments. Both the current collected by each segment, and the potential difference between the cathode and each segment were monitored throughout the test period. As in previous tests a similar device, current appeared to attach diffusely in the anode when all of the segments were allowed to conduct. Improvements to the device allowed long term (4 to 8 hour) operation at steady-state and operating characteristics were repeatable over extended periods. Performance characteristics indicated that the segmented anode reasonably simulates the behavior of solid anodes of similar geometry. Current distribution depended on flow rate as the arc attachment moved downstream in the nozzle with increases in the mass flow rate. The current level had little effect on current distribution on the anode segments. Thrust measurements indicated that the current distribution in the nozzle did not significantly affect performance of the device.

Curran, Francis M.↗

Strehl Ratio Meter for Focusing Segmented Mirrors 1

Initial focusing segmented mirrors that must be deployed in space, such as the Next Generation Space Telescope (NGST), provide challenges not faced before in the area of adaptive optics. The devices used to focus the mirror must minimize the power used and unnecessary mechanical movement. The device described in this report requires no movable parts except for the essential actuators required to move the mirror segments. Detail description of the components can be found in Coker, 1996. The primary mirror of the NGST will consist of 9 segments, a central annular segment, surrounded by 8 segments. The entire mirror assembly will be an 8 meter nearly filled circle (with the corners of the segments clipped to allow for storage in an Atlas IIe shroud). As the segments of the primary mirror are deployed to their operational positions, they must be positioned to within small fractions of a wavelength of near infrared light. When focused, the NGST will put most of its collected li-ht into the small region near the center of its focal plane. The ratio of the total light in the diffraction limited spot about the center of the focal plane to the total light in the focal plane. The purpose of this research effort is to design and build a device that will measure Strehl ratio and to use demonstrate that the Strehl ratio can be used to focus a segmented mirror.

Olivier, Philip D.↗

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Tilton, James C.↗

Calcium ion dependency of ethylene production in segments of primary roots of Zea mays

We investigated the effect of Ca2+ on ethylene production in 2-cm long apical segments from primary roots of corn (Zea mays L., B73 x Missouri 17) seedlings. The seedlings were raised under different conditions of Ca2+ availability. Low-Ca and high-Ca seedlings were raised by soaking the grains and watering the seedlings with distilled water or 10 mM CaCl2, respectively. Segments from high-Ca roots produced more than twice as much ethylene as segments from low-Ca roots. Indoleacetic acid (IAA; 1 micromole) enhanced ethylene production in segments from both low-Ca and high-Ca roots but auxin-induced promotion of ethylene production was consistently higher in segments from high-Ca roots. Addition of 1-aminocyclopropane-1-carboxylic acid (ACC) to root segments from low-Ca seedlings doubled total ethylene production and the rate of production remained fairly constant during a 24 h period of monitoring. In segments from high-Ca seedlings ACC also increased total ethylene production but most of the ethylene was produced within the first 6 h. The data suggest that Ca2+ enhances the conversion of ACC to ethylene. The terminal 2 mm of the root tip were found to be especially important to ethylene biosynthesis by apical segments and, experiments using 45Ca2+ as tracer indicated that the apical 2 mm of the root is the region of strongest Ca2+ accumulation. Other cations such as Mn2+, Mg2+, and K+ could largely substitute for Ca2+. The significance of these findings is discussed with respect to recent evidence for gravity-induced Ca2+ redistribution and its relationship to the establishment of asymmetric growth during gravitropic curvature.

NASA Discipline Plant Biology↗

Laser ablation of persistent twist cells in Drosophila: muscle precursor fate is not segmentally restricted

In Drosophila the precursors of the adult musculature arise during embryogenesis. These precursor cells have been termed Persistent Twist Cells (PTCs), as they continue to express the transcription factor Twist after that gene ceases expression elsewhere in the mesoderm. In the larval abdomen, the PTCs are associated with peripheral nerves in stereotypic ventral, dorsal, and lateral clusters, which give rise, respectively, to the ventral, dorsal, and lateral muscle fiber groups of the adult. We tested the developmental potential of the PTCs by using a microbeam laser to ablate specific clusters in larvae. We found that the ablation of a single segmental PTC cluster does not usually result in the deletion of the corresponding adult fibers of that segment. Instead, normal or near normal numbers of adult fibers can form after the ablation. Examination of pupae following ablation showed that migrating PTCs from adjacent segments are able to invade the affected segment, replenishing the ablated cells. However, the ablation of homologous PTCs in multiple segments does result in the deletion of the corresponding adult muscle fibers. These data indicate that the PTCs in an abdominal segment can contribute to the formation of muscle fibers in adjacent abdominal segments, and thus are not inherently restricted to the formation of muscle fibers within their segment of origin.

NASA Discipline Neuroscience↗

Segmented trapped vortex cavity

An annular trapped vortex cavity assembly segment comprising includes a cavity forward wall, a cavity aft wall, and a cavity radially outer wall there between defining a cavity segment therein. A cavity opening extends between the forward and aft walls at a radially inner end of the assembly segment. Radially spaced apart pluralities of air injection first and second holes extend through the forward and aft walls respectively. The segment may include first and second expansion joint features at distal first and second ends respectively of the segment. The segment may include a forward subcomponent including the cavity forward wall attached to an aft subcomponent including the cavity aft wall. The forward and aft subcomponents include forward and aft portions of the cavity radially outer wall respectively. A ring of the segments may be circumferentially disposed about an axis to form an annular segmented vortex cavity assembly.

Grammel, Jr., Leonard Paul↗

Multi-Segment Radius Measurement Using an Absolute Distance Meter Through a Null Assembly

This system was one of the test methods considered for measuring the radius of curvature of one or more of the 18 segmented mirrors that form the 6.5 m diameter primary mirror (PM) of the James Webb Space Telescope (JWST). The assembled telescope will be tested at cryogenic temperatures in a 17-m diameter by 27-m high vacuum chamber at the Johnson Space Center. This system uses a Leica Absolute Distance Meter (ADM), at a wavelength of 780 nm, combined with beam-steering and beam-shaping optics to make a differential distance measurement between a ring mirror on the reflective null assembly and individual PM segments. The ADM is located inside the same Pressure-Tight Enclosure (PTE) that houses the test interferometer. The PTE maintains the ADM and interferometer at ambient temperature and pressure so that they are not directly exposed to the telescope s harsh cryogenic and vacuum environment. This system takes advantage of the existing achromatic objective and reflective null assembly used by the test interferometer to direct four ADM beamlets to four PM segments through an optical path that is coincident with the interferometer beam. A mask, positioned on a linear slide, contains an array of 1.25 mm diameter circular subapertures that map to each of the 18 PM segments as well as six positions around the ring mirror. A down-collimated 4 mm ADM beam simultaneously covers 4 adjacent PM segment beamlets and one ring mirror beamlet. The radius, or spacing, of all 18 segments can be measured with the addition of two orthogonally-oriented scanning pentaprisms used to steer the ADM beam to any one of six different sub-aperture configurations at the plane of the ring mirror. The interferometer beam, at a wavelength of 687 nm, and the ADM beamlets, at a wavelength of 780 nm, pass through the objective and null so that the rays are normally incident on the parabolic PM surface. After reflecting off the PM, both the ADM and interferometer beams return to their respective instruments on nearly the same path. A fifth beamlet, acting as a differential reference, reflects off a ring mirror attached to the objective and null and returns to the ADM. The spacings between the ring mirror, objective, and null are known through manufacturing tolerances as well as through an in situ null wavefront alignment of the interferometer test beam with a reflective hologram located near the caustic of the null. Since total path length between the ring mirror and PM segments is highly deterministic, any ADM-measured departures from the predicted path length can be attributed to either spacing error or radius error in the PM. It is estimated that the path length measurement between the ring mirror and a PM segment is accurate to better than 100 m. The unique features of this invention include the differential distance measuring capability and its integration into an existing cryogenic and vacuum compatible interferometric optical test.

Merle, Cormic↗