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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Increased accuracy and signal-to-noise ratio through recent improvements in infra-red video bolometer fabrication and calibration

The infra-red video bolometer (IRVB) is a diagnostic equipped with an infra-red camera that measures the total radiated power in thousands of lines of sight within a large field of view. Recently validated in MAST-U [Fderici et al., Rev. Sci. Instrum. 94, 033502 (2023)], it offers a high spatial resolution map of the radiated power in the divertor region, where large gradients are expected. The IRVB’s sensing element comprises a thin layer of high Z absorbing material, typically platinum, usually coated with carbon to reduce reflections [Peterson et al., Rev. Sci. Instrum. 79, 10E301 (2008)].Here, the possibility of using a relatively inert material such as titanium, is explored that can be produced in layers up to 1 μm compared to 2.5 μm for Pt and then coat it with Pt of the desired thickness (0.3 μm per side here) and carbon. This leads to a higher temperature signal (about 3 times) and better spatial resolution (about 4 times), resulting in higher accuracy in the measured power [Peterson et al., Rev. Sci. Instrum. 79, 10E301 (2008)]. This assembly is also expected to improve foil uniformity, as the Pt layer is obtained via deposition rather than mechanical processes [Mukai et al., Rev. Sci. Instrum. 87, 2014 (2016)].Given its multi-material composition, measuring the thermal properties of the foil assembly is vital. Various methods using a calibrated laser as a heat source have been developed, analyzing the temperature profile shape [Sano et al., Plasma and Fusion Res. 7, 2405039 (2012)] and [Mukai et al., Rev. Sci. Instrum. 89, 10E114 (2018)] or fitting the calculated laser power for different intensities and frequencies [Fderici et al., Rev. Sci. Instrum. 94, 033502 (2023)]. Here, a simpler approach is presented, which relies on analyzing the separate components of the foil heat equation for a single laser exposure in a given area. This can then be iterated over the entire foil to capture local deviations.

Magnetic Fusion Energy↗

lumicap v0.1

Automated HDR luminance imaging system designed for daylighting research and building science. It controls a fisheye-lens camera to capture time-lapse bracket sequences, merges them into calibrated HDR images, and runs a full post-processing pipeline — all unattended. Features: - Scheduled LDR bracket capture via gphoto2 - HDR merging with vignetting, ND filter, and fisheye projection corrections - Illuminance and luminance meter integration (Konica Minolta T-10A, LS-100/150) - Daylight glare probability (DGP) and solar position computation - Automated false-color rendering, JPEG thumbnails, and daily time-lapse video - CSV data logging per timestep Uses: - Long-term monitoring of daylight conditions in buildings - Glare analysis for occupant comfort research - Solar irradiance and sky luminance studies Advantages: - End-to-end automation — capture, calibration, analysis, and archiving run without manual intervention - Built on the proven Radiance toolchain, ensuring photometrically accurate HDR output - Hardware-agnostic meter support via serial auto-detection - Lightweight — no GUI overhead, deployable on a headless Raspberry Pi or similar embedded system

Wang, Taoning [Lawrence Berkeley National Laborato↗

Upgrade of the Lyman-alpha diagnostic system on DIII-D for main chamber edge neutral studies

The LLAMA (Lyman Alpha Measurement Apparatus) pinhole camera diagnostic had previously been deployed on DIII-D to measure radial profiles of the Lyman-α (Ly-α) deuterium neutral line brightness across the plasma boundary in the lower chamber to infer neutral deuterium density and ionization rate profiles. This system has recently been upgraded with a new diagnostic head, named ALPACA, that also encloses two pinhole cameras and duplicates the LLAMA views in the upper chamber. Similar to LLAMA, ALPACA provides two times 20 lines of sight, viewing the plasma edge on the inboard and outboard sides with a radial resolution of ~2.5 cm (FWHM) and an effective time resolution of ~1 ms that allows for the investigation of inter-ELM dynamics. The extended Ly-α system provides better coverage to study neutrals in experiments with various plasma shapes utilizing both the upper and lower divertors. Furthermore, post-campaign calibration of the LLAMA diagnostic has successfully been demonstrated for the first time. This was facilitated by various upgrades to the calibration set-up and detailed measurements of the emissivity distribution of the Ly-α calibration source using a pinhole collimator. It was found that the sensitivity of the inboard LLAMA pinhole camera was reduced by a factor of 2.0 ± 0.2 over the course of six months of plasma operation in 2021. In conclusion, the upgraded Ly-α system, equipped with improved absolute calibration, will provide key input for neutral fueling and pedestal particle transport studies and for 2D edge transport code validation on the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Speed estimation from a single image of a disc: theory

We develop an approach to estimate the tangential speed of the edge of a rotating disc using a single image captured from a moving camera. The only dimensional information required for the estimate is the velocity of the camera relative to the ground. Notably, the size of the disc is not used, and the scene requires no calibration. The side of a tire and wheel assembly (TWA) on a motor vehicle can be a good approximation to a rotating disc, and, under reasonable assumptions, the tangential speed of the tire tread equals the speed of the vehicle. This indirect measurement of vehicle speed is passive, works independently of camera orientation, and is unaffected by obstructions between the vehicle and camera as long as one TWA is visible. The technique is readily adapted for application to a disc attached to a stationary mount.

airborne camera↗

The Dark Energy Bedrock All-sky Supernova Program: Motivation, Design, Implementation, and Preliminary Data Release

Precise measurements of Type Ia supernovae (SNe Ia) at low redshifts (z) serve as one of the most viable keys to unlocking our understanding of cosmic expansion, isotropy, and growth of structure. The Dark Energy Bedrock All-Sky Supernovae (DEBASS) program will deliver a uniformly calibrated low-z dataset of more than 400 spectroscopically confirmed SNe Ia in the Southern Hemisphere. DEBASS utilizes the Dark Energy Camera to image supernovae in conjunction with the Wide-Field Spectrograph to gather comprehensive host-galaxy information. By using the same photometric instrument as both the Dark Energy Survey (DES) and the DECam Local Volume Exploration Survey, DEBASS not only benefits from a robust photometric pipeline and well-calibrated images across the Southern sky, but can replace the historic and external low-z samples that were used in the final DES supernova analysis. In this paper, along with a companion paper, we present an early data release of 77 DEBASS SNe within the DES footprint. We introduce the DEBASS program, discuss its scientific goals and the advantages it offers for supernova cosmology, and present our initial results demonstrating data quality. With this early data release, we find a robust median absolute standard deviation of Hubble diagram residuals of ∼0.10 mag and an initial measurement of the host-galaxy mass step of 0.06 ± 0.04 mag, both before performing bias corrections. This low scatter shows the promise of a low-z SN Ia program with a well-calibrated telescope and high signal-to-noise ratio across multiple bands.

Sherman, Nora F. [Boston U.] (ORCID:00000001539901↗

Advancements in reflected target nonintrusive assessment (ReTNA) for large optical surface measurement

Reflected computer vision targets are a powerful tool for measurement of mirror surface shape, with several important advantages over traditional fringe deflectometry methods. This method was first presented in 2021 and has undergone significant improvement and demonstration since. We describe a new baseline system using reflected computer vision targets, and present results from a large-scale measurement campaign conducted on both commercial heliostats and test mirrors in the laboratory. Calibration of the measurement system with photogrammetry allows for accurate measurement without careful control of target shape or camera position. Overall, the results show that a baseline setup using this method achieves measurement uncertainties in the slope error root-mean-square less than ±0.11 milliradian due to a series of repeatability conditions, varying sample position, rotation, lighting, camera settings, and system rebuild and recalibration. We present a detailed description of the setup, the results generated by this measurement tool, repeated measurement results, and the strengths and limitations of this metrology system.

14 SOLAR ENERGY↗

The Dark Energy Bedrock All-sky Supernova Program: Cross Calibration, Simulations, and Cosmology Forecasts

Type Ia supernovae (SNe Ia) have been essential for probing the nature of dark energy; however, most SN analyses rely on the same low-redshift sample, which may lead to shared systematics. In a companion paper, we introduce the Dark Energy Bedrock All-Sky Supernova (DEBASS) program, which has already collected more than 500 low-redshift SNe Ia on the Dark Energy Camera, and present an initial release of 77 SNe Ia within the Dark Energy Survey (DES) footprint observed between 2021 and 2024. Here, we examine the systematics, including photometric calibration and selection effects. We find agreement at the 10 mmag level among the tertiary standard stars of DEBASS, DES, and Pan-STARRS1. Our simulations reproduce the observed distributions of DEBASS SN light-curve properties, and we measure a bias-corrected Hubble residual scatter of 0.08 mag, which, while small, is found in 10% of our simulations. We compare the DEBASS SN distances to the Foundation sample and find consistency with a median residual offset of 0.016 ± 0.019 mag. Selection effects have negligible impacts on distances, but a different photometric calibration solution shifts the median residual −0.015 ± 0.019 mag, highlighting calibration sensitivity. Using conservative simulations, we forecast that replacing historical low-redshift samples with the full DEBASS sample will improve the statistical uncertainties on dark energy parameters w 0 and w a by 30% and 24%, respectively, enhance the dark energy Figure of Merit by up to 60%, and enable a measurement of fσ 8 at the 25% level.

Acevedo, Maria [Duke Univ., Durham, NC (United Sta↗

CHESS 2025: Post-survey report for 2025 NEON AOP Assignable Asset collection of East River and Washington Gulch, Almont and Upper Taylor watersheds at Crested Butte, CO

This report contains details of the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) Research Support Services (RSS) Assignable Asset (AA) flights of the East River, Almont and Upper Taylor watersheds near Crested Butte, CO, June–July 2025. The Rocky Mountain Biological Laboratory (RMBL) contracted the NEON AOP AA flights to observe watersheds of interest near Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The report includes a summary of the acquired flight lines over the planned survey areas, results of calibration flights, and results of the acquired data. The report details how the AOP has met the contracted delivery requirements in terms of the data delivered, quality of the data, and describes issues that resulted in data degradation or data loss. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Novel Technology of Non-Contact Real-Time Radiation Damage Sensor for High Power Targets

High-power proton beams planned for forthcoming long-baseline neutrino experiments will subject solid targets to unprecedented radiation damage, threatening reliability and increasing costs. To address this challenge, we are building a real-time, non-contact sensor that tracks damage by measuring broadband laser reflectivity changes from the target surface. A low-power super-continuum Class 3B laser illuminates the sample inside a vacuum test chamber while a high-resolution fiber-coupled spectrometer captures S- and P-polarized light; spectral shifts reveal defect-driven variations in optical constants. My internship goal is to design, build, and commission this prototype by implementing a laser-safety interlock and light shield, integrating remote-operation cameras, and fabricating modular 3-D-printed mounts that enable tool-free swaps without disturbing alignment. The laser, spectrometer, and vacuum chamber have been delivered; interlock hardware, cameras, and mounts are in final assembly, and leak testing of the chamber is underway. Upcoming work will focus on initial calibration of the sensor and executing first beam-irradiation studies.

Pumarino, Rafael↗

AutoSourceID-Classifier: Star-galaxy classification using a convolutional neural network with spatial information

Aims.Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods.The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results.We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Astronomy & Astrophysics↗

Plasma modification through boron particulate injection in the full tungsten environment of WEST

Recent experiments have confirmed the compatibility of extended boron particulate injections with high performance plasma discharges in the full tungsten (W) environment of WEST. Utilizing an impurity powder dropper (IPD) equipped with boron (B) powders a series of extended experimental programs providing controlled injections have quantified plasma response to varying levels of injection rate and total injection quantity. Calibration of injection quantities confirmed through post-situ testing of the IPD and cross-correlated with both high-speed camera illumination and spectroscopic measurement have allowed for the first time a fine scale determination of the effects of powder introduction on plasma performance. Plasma enhancement, consistent with turbulence reduction through profile modification, has been observed with sustained increases in the stored energy (WMHD), by 18%, electron temperature (T e ) by 35%, and neutron rate (N n ) by up to 200%, all of which scale positively with increasing powder injection rates. These injections have also resulted in both prompt and extended reductions in native impurity content, decreases in post injection radiated power, and strong decreases in divertor deuterium signatures signifying a reduction in recycling suggesting enhanced boron layer formation which provides a reduction of source terms and leads to enhanced gettering of main ion and impurity sources.

Lunsford, R. [Princeton Plasma Physics Laboratory ↗

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

One-dimensional temperature measurement of supersonic jet flow by resonantly ionized photoemission thermometry of molecular nitrogen

As the field of fluid dynamics progresses, the demand for sophisticated diagnostic methods to accurately assess flow conditions rises. In this work, resonantly ionized photoemission thermometry (RIPT) has been used to directly target and ionize diatomic nitrogen (N 2 ) to measure one-dimensional (1D) temperature profiles in a supersonic jet flow. This technique can be considered non-intrusive as the premise uses resonantly enhanced multiphoton ionization (REMPI) to target molecular nitrogen. This resonance excites N 2 into absorption bands of the P, Q, and R rotational branches of N 2 ( b 1 Π u ). The ideal (3 + 1) REMPI scheme excites from the ground state and ionizes N 2 ( b 1 Π u ← X 1 Σ g + ) where de-excitation results in photoemission from the first negative band of ionized N 2 + ( B 2 Σ u + → X 2 Σ g + ) as nitrogen returns to the ground state. The resulting emission can be observed using an intensified camera, thus permitting inference of the rotational temperature of ground-state molecular nitrogen. A linearly regressive Boltzmann distribution is applied based on previous calibration data for this technique to quantify the temperature along the ionized line. This work applies this technique to a pure N 2 supersonic jet in cross-flow and counter-flow orientations to demonstrate N 2 RIPT’s applications in a supersonic flow. Temperature variations are observed at different locations downstream of the exit in cross-flow, and axisymmetric in counter-flow, to generate profiles characterizing the flow dynamics. Due to the collisional effects resulting from the number density of N 2 at higher pressures, a (3 + 2) REMPI scheme is observed throughout this text.

Clark, Aleksander (ORCID:0009000855600042)↗

Legacy Survey of Space and Time Data Preview 1: calibrations dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the calibrations dataset type. These are a collection of calibration datasets such as biases, darks, and flats used to construct the data release. This release contains 496 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 1: visit_image dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the visit_image dataset type. These are individual processed and calibrated sky images obtained from a single observation with a single filter. This release contains 15,972 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy Survey of Space and Time Data Preview 1: deep_coadd dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the deep_coadd dataset type. These are the combination of multiple processed, calibrated, and background- subtracted images, for a patch of sky, for each of the six filters. This release contains 2,644 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Collision Tracking in OpenMC: Methods and Applications in Neutron Noise, Neutron Imaging, Time-of-Flight, and Multiplicity Counting

We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.

Monte Carlo code↗

The Absolute Color Calibration of the Dark Energy Survey: A Spectrophotometric Sample of DA White Dwarfs in the Southern Sky

The Dark Energy Survey (DES), which is nearing the completion of the analysis of its full data set, is an imaging survey of one-quarter of the Southern sky down to an apparent magnitude of $i\sim24.5$. The survey observations were conducted between 2013 and 2019 with a 3-square-degree wide-field CCD mosaic camera (the Dark Energy Camera, or DECam) on the Blanco 4-meter telescope at the Cerro Tololo Interamerican Observatory in the Chilean Andes. The primary scientific goal of the DES was to measure properties of Dark Energy. In order to achieve its science goals, the DES had tight requirements on both its relative and absolute photometric calibrations. In this poster, we describe the sample of pure-hydrogen-atmosphere (“DA”) white dwarfs which were instrumental in working to establish the requirement on the absolute color calibration -- i.e., the calibration across the filter bands -- of the DES.

79 ASTRONOMY AND ASTROPHYSICS↗