Structured photocathodes for improved high-energy x-ray efficiency in streak cameras
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The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.
We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the "brighter-fatter" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within $\approx 2$ mmag and $\approx 3$ mas, respectively, of fundamental atmospheric and statistical limits. In conclusion, the DES techniques should be broadly applicable to wide-field imagers.
Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best-practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open-grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data.
This work evaluated the iX Cameras iSpeed 727, a commercial CMOS-based continuous- recording high-speed camera. Various parameters of importance in the scheme of accurate time-resolved measurements and photonic quantification have been measured under controlled conditions on the bench, using state-of-the-art instrumentation. We will detail the procedures and results of the tests laid out to measure sensor sensitivity, linearity, signal-to-noise ratio and image lag. We also looked into the electronic shutter performance and accuracy, as exposure time is of particular interest to high-speed imaging. The results of the tests show that this camera matches or exceeds the performance of competing units in most aspects, but that, as is the case for other high-speed camera systems, corrections are necessary to make full use of the image data from a quantitative perspective.
We report simulations and experiments that demonstrate an increase in spatial resolution of the NIF core diagnostic x-ray streak cameras by at least a factor of two, especially off axis. A design was achieved by using a corrector electron optic to flatten the field curvature at the detector plane and corroborated by measurement. In addition, particle in cell simulations were performed to identify the regions in the streak camera that contribute the most to space charge blurring. These simulations provide a tool for convolving synthetic pre-shot spectra with the instrument function so signal levels can be set to maximize dynamic range for the relevant part of the streak record.
The third-generation South Pole Telescope camera is designed to measure the cosmic microwave background across three frequency bands (centered at 95, 150 and 220 GHz) with ~ 16,000 transition-edge sensor (TES) bolometers. Each multichroic array element on a detector wafer has a broadband sinuous antenna that couples power to six TESs, one for each of the three observing bands and both polarizations, via lumped element filters. Ten detector wafers populate the detector array, which is coupled to the sky via a large-aperture optical system. Here we present the frequency band characterization with Fourier transform spectroscopy, measurements of optical time constants, beam properties, and optical and polarization efficiencies of the detector array. The detectors have frequency bands consistent with our simulations and have high average optical efficiency which is 86, 77 and 66% for the 95, 150 and 220 GHz detectors. The time constants of the detectors are mostly between 0.5 and 5 ms. The beam is round with the correct size, and the polarization efficiency is more than 90% for most of the bolometers.
Crystal x–ray imaging is commonly used in inertial confinement fusion and laser-plasma interaction applications as it has advantages compared to pinhole imaging, such as higher signal throughput, better achievable spatial resolution, and chromatic selection. Yet, currently used x–ray detectors are only able to obtain a single time resolved image per crystal. The dilation aided single–line–of–sight x–ray camera described here was designed for the National Ignition Facility (NIF) and combines two recent diagnostic developments, the pulse dilation principle used in the dilation x-ray imager and a ns–scale multi-frame camera that uses a hold and readout circuit for each pixel. This enables multiple images to be taken from a single–line–of–sight with high spatial and temporal resolution. Presently, the instrument can record two single–line–of–sight images with spatial and temporal resolution of 35 μm and down to 35 ps, respectively, with a planned upgrade doubling the number of images to four. Here we present the dilation aided single–line–of–sight camera for the NIF, including the x–ray characterization measurements obtained at the COMET laser, as well as the results from the initial timing shot on the NIF.
The multi-institution Single-Volume Scatter Camera (SVSC) collaboration led by Sandia National Laboratories (SNL) is developing a compact, high-efficiency double-scatter neutron imaging system. Kinematic emission imaging of fission-energy neutrons can be used to detect, locate, and spatially characterize special nuclear material. Neutron-scatter cameras, analogous to Compton imagers for gamma ray detection, have a wide field of view, good event-by-event angular resolution, and spectral sensitivity. Existing systems, however, suffer from large size and/or poor efficiency. We are developing high-efficiency scatter cameras with small form factors by detecting both neutron scatters in a compact active volume. This effort requires development and characterization of individual system components, namely fast organic scintillators, photodetectors, electronics, and reconstruction algorithms. In this presentation, we will focus on characterization measurements of several SVSC candidate scintillators. The SVSC collaboration is investigating two system concepts: the monolithic design in which isotropically emitted photons are detected on the sides of the volume, and the optically segmented design in which scintillation light is channeled along scintillator bars to segmented photodetector readout. For each of these approaches, we will describe the construction and performance of prototype systems. We will conclude by summarizing lessons learned, comparing and contrasting the two system designs, and outlining plans for the next iteration of prototype design and construction.
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We apply a cascaded linear model analysis to a micro-channel plate x-ray framing camera. We establish a theoretical expression of the Noise Power Spectrum (NPS) at the detector’s output and assess its accuracy by comparing it to the NPS of Monte Carlo simulations of the detector’s response to a uniform illumination. We also reflect that fitting the NPS of experimental data against a parametric model based on this expression can yield valuable information on the imaging ability of framing cameras, offering an alternative method to the usual avenue employed to measure their modulation transfer functions.
The hardened single line of sight camera has been recently characterized in preparation for its deployment on the National Ignition Facility. The latest creation based on the pulse-dilation technology leads to many new features and improvements over the previous-generation cameras to provide better quality measurements of inertial confinement fusion experiments, including during high neutron yield implosions. Here, we present the characterization data that illustrate the main performance features of this instrument, such as extended dynamic range and adjustable internal magnification, leading to improved spatial resolution.
We report the results of a deep search for an optical counterpart to the gravitational wave (GW) event GW150914, the first trigger from the Advanced LIGO GW detectors. We used the Dark Energy Camera (DECam) to image a 102 deg{sup 2} area, corresponding to 38% of the initial trigger high-probability sky region and to 11% of the revised high-probability region. We observed in the i and z bands at 4–5, 7, and 24 days after the trigger. The median 5 σ point-source limiting magnitudes of our search images are i = 22.5 and z = 21.8 mag. We processed the images through a difference-imaging pipeline using templates from pre-existing Dark Energy Survey data and publicly available DECam data. Due to missing template observations and other losses, our effective search area subtends 40 deg{sup 2}, corresponding to a 12% total probability in the initial map and 3% in the final map. In this area, we search for objects that decline significantly between days 4–5 and day 7, and are undetectable by day 24, finding none to typical magnitude limits of i = 21.5, 21.1, 20.1 for object colors ( i − z ) = 1, 0, −1, respectively. Our search demonstrates the feasibility of a dedicated search program with DECam and bodes well for future research in this emerging field.
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