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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Lattice Refinements for Nonlinear Integrable Optics in IOTA

Nonlinear integrable optics of the type proposed by Danilov and Nagaitsev place strict constraints on the lattice parameters in the matching section outside of the nonlinear insert. In particular, the effects of energy spread in the beam have significant effects on the stability of the system. Typical chromatic compensation using sextupoles has significant perturbative effects on the dynamics but is operationally necessary to suppress fast losses. Fast decoherence of kicked beam measurements limits the available signal for studies. Refinements to the IOTA lattice parameters based on this experience with electron beam operation are presented.

Wieland, John [Fermilab] (ORCID:0000000289718523)↗
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗
DOE OSTI2024

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2023

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2024, with start- and end-of-season phenological transition dates derived through the end of autumn 2023. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) • Contains one file in *.csv format (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure • Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type • One additional file in HTML format with the transition dates plotted for each vegetation type, by year (2) R files for processing Phenocam files and flags. • Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released data inclusive of the 2015-2022 data (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

Spruce and Peatland Responses Under Changing Envir↗
DOE OSTI2025

SPRUCE Vegetation Phenology in Experimental Plots from PhenoCam Imagery, 2015-2024

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2025 (2015-08-24 to 2025-03-31), with start- and end-of-season phenological transition dates derived through the end of autumn 2024. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step. • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e., vegetation type). • Contains one file in *.csv format. (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure. • Contains two files in *.csv format, one for snow on trees and one for snow on ground. This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type. • One additional file in HTML format with the transition dates plotted for each vegetation type, by year. (2) R files for processing PhenoCam files and flags. • Contains five files in R file(*.R) format and the components of the phenocamr package (Version 1.1.4) used for calculating transition dates for 2015-2024. These are contained in a compressed (*.zip) file. User Note: All imagery is posted in near-real time to the PhenoCam Project web page (https://phenocam.nau.edu), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. This data set is based on the complete camera record from SPRUCE and supersedes all previously released PhenoCam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Image Analysis for Rapid Assessment and Quality-Based Sorting of Corn Stover

Imaging in the visible spectrum is a low-cost tool that can be readily deployed for in-field or over-belt monitoring of biomass quality for bio-refining operations. Rapid image analysis coupled with innovative preprocessing may reduce the impacts of feedstock variability through identification of contaminants or other material attributes to guide selective sorting and quality management. Image analysis was employed to evaluate the quality of corn stover in red-green-blue (RGB) chromatic space. This study used controlled, bench-scale imaging as a proof-of-concept for rapid quality assessment of corn stover based on variations in material attributes, including chemical and physical attributes, that relate to biological degradation and soil contamination. Additionally, logistic regression-based classification algorithms were used to develop a method for biomass screening as a function of biological degradation or soil contamination. This study demonstrated the use of image analysis to extract features from RGB color space to investigate variations in critical material attributes from chemical composition of corn stover. Fourier transform infrared (FT-IR) suggested a correlation between red band intensity and biological degradation, while detailed surface texture analysis was found to distinguish among variations in ash. These insights offer promise for development of a rapid screening tool that could be deployed by farmers for in-field assessment of biomass quality or biorefinery operators for in-line sorting and process optimization.

09 BIOMASS FUELS↗
DOE OSTI2021

Environmental Tuning of Homologs of the Orange Carotenoid Protein-Encoding Gene in the Cyanobacterium Fremyella diplosiphon

The orange carotenoid protein (OCP) family of proteins are light-activated proteins that function in dissipating excess energy absorbed by accessory light-harvesting complexes, i.e., phycobilisomes (PBSs), in cyanobacteria. Some cyanobacteria contain multiple homologs of the OCP-encoding gene ( ocp ). Fremyella diplosiphon , a cyanobacterium studied for light-dependent regulation of PBSs during complementary chromatic acclimation (CCA), contains several OCP homologs – two full-length OCPs, three Helical Carotenoid Proteins (HCPs) with homology to the N-terminus of OCP, and one C-terminal domain-like carotenoid protein (CCP) with homology to the C-terminus of OCP. We examined whether these homologs are distinctly regulated in response to different environmental factors, which could indicate distinct functions. We observed distinct patterns of expression for some OCP, HCP, and CCP encoding genes, and have evidence that light-dependent aspects of ocp homolog expression are regulated by photoreceptor RcaE which controls CCA. RcaE-dependent transcriptional regulator RcaC is also involved in the photoregulation of some hcp genes. Apart from light, additional environmental factors associated with cellular redox regulation impact the mRNA levels of ocp homologs, including salt, cold, and disruption of electron transport. Analyses of conserved sequences in the promoters of ocp homologs were conducted to gain additional insight into regulation of these genes. Several conserved regulatory elements were found across multiple ocp homolog promoters that potentially control differential transcriptional regulation in response to a range of environmental cues. The impact of distinct environmental cues on differential accumulation of ocp homolog transcripts indicates potential functional diversification of this gene family in cyanobacteria. These genes likely enable dynamic cellular protection in response to diverse environmental stress conditions in F . diplosiphon .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Fluorogenic Biosensing with Tunable Polydiacetylene Vesicles

Polydiacetylenes (PDAs) are conjugated polymers that are well known for their colorimetric transition from blue to red with the application of energetic stimulus. Sensing platforms based on polymerized diacetylene surfactant vesicles and other structures have been widely demonstrated for various colorimetric biosensing applications. Although less studied and utilized, the transition also results in a change from a non-fluorescent to a highly fluorescent state, making polydiacetylenes useful for both colorimetric and fluorogenic sensing applications. Here, we focus on the characterization and optimization of polydiacetylene vesicles to tune their sensitivity for fluorogenic sensing applications. Particularly, we look at how the structure of the diacetylene (DA) hydrocarbon tail and headgroup affect the self-assembled vesicle size and stability, polymerization kinetics, and the fluorogenic, blue to red phase transition. Longer DA acyl tails generally resulted in smaller and more stable vesicles. The polymerization kinetics and the blue to red transition were a function of both the DA acyl tail length and structure of the headgroup. Decreasing the acyl tail length generally led to vesicles that were more sensitive to energetic stimuli. Headgroup modifications had different effects depending on the structure of the headgroup. Ethanolamine headgroups resulted in vesicles with potentially increased stimuli responsivity. The lower energy stimulus to induce the chromatic transition was attributed to an increase in headgroup hydrogen bonding and polymer backbone strain. Boronic-acid headgroup functionalization led to vesicles that were generally unstable, only weakly polymerized, and unable to fully transform to the red phase due to strong polar, aromatic headgroup interactions. This work presents the design of PDA vesicles in the context of biosensing platforms and includes a discussion of the past, present, and future of PDA biosensing.

Chemistry↗
DOE OSTI2023

Atmospheric Pressure Plasma Treatment of Magnesium Alloy for Enhanced Coating Adhesion and Corrosion Resistance

Atmospheric pressure plasma (AP) treatment, using an open-air jet of ionized CO 2 , N 2 , or air, was applied to AZ91D Mg alloy surfaces to investigate its effects on primer coating adhesion and corrosion resistance. The CO 2 and air AP treatments formed an O- and C-rich surface layer (Mg-O-C) consisting of agglomerated nanoparticles and pits with a depth of a few microns and increasing the surface roughness by 6–8 times compared with the reference 600 grit-finished surface. Then, three commercial primers, zinc phosphate (ZnP), chromate-containing epoxy, and MIL23377, were applied on the treated surfaces to evaluate the corrosion resistance associated with the coating adhesion. Microscopic analysis demonstrated stronger interlocking between the primer layer and the nano-/microrough Mg-O-C surface compared to the untreated (600 grit-finished) surfaces, indicating improved coating adhesion and corrosion resistance. Crosscut tests of the MIL23377 primer on the CO 2 and air AP-treated surfaces showed the highest level of adhesion, ASTM class 5B. Salt spray corrosion tests showed that after 8 days of exposure, the primer coatings on air AP-treated surfaces had corrosion areas that were more than four times smaller than that of the 600 grit-finished surface. The N 2 AP treatment showed similar adhesion enhancement. The preliminary operation expenses for AP treatment using CO 2 , N 2 , and air were estimated at USD 30.62, USD 35.45, and USD 29.75 (from an air cylinder)/USD 0.66 (from an air compressor) per m 2 , respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Homologs of Phycobilisome Abundance Regulator PsoR Are Widespread across Cyanobacteria

During chromatic acclimation (CA), cyanobacteria undergo shifts in their physiology and metabolism in response to changes in their light environment. Various forms of CA, which involves the tuning of light-harvesting accessory complexes known as phycobilisomes (PBS) in response to distinct wavelengths of light, have been recognized. Recently, a negative regulator of PBS abundance, PsoR, about which little was known, was identified. We used sequence analyses and bioinformatics to predict the role of PsoR in cyanobacteria and PBS regulation and to examine its presence in a diverse range of cyanobacteria. PsoR has sequence similarities to the β-CASP family of proteins involved in DNA and RNA processing. PsoR is a putative nuclease widespread across Cyanobacteria, of which over 700 homologs have been observed. Promoter analysis suggested that psoR is co-transcribed with upstream gene tcpA. Multiple transcription factors involved in global gene regulation and stress responses were predicted to bind to the psoR-tcpA promoter. The predicted protein–protein interactions with PsoR homologs included proteins involved in DNA and RNA metabolism, as well as a phycocyanin-associated protein predicted to interact with PsoR from Fremyella diplosiphon (FdPsoR). The widespread presence of PsoR homologs in Cyanobacteria and their ties to DNA- and RNA-metabolizing proteins indicated a potentially unique role for PsoR in CA and PBS abundance regulation.

Layer, Alicia↗
DOE OSTI2020

Exoplanets in the Antarctic Sky. IV. Dual-band Photometry of Variables Found by the CSTAR-II Commissioning Survey at the North Sky

From the experiences learned in three decades of exoplanet search, wide-field transit surveys have proven to be one of the most effective ways to detect exoplanets. Wide field of view, however, suffers from high false-positive rates caused by blended eclipsing binaries. The chromaticity in eclipse depth is an effective feature to distinguish low-depth eclipsing binaries from transiting exoplanets, making multiple-band photometry follow-up advantageous before a target is passed onto more expensive spectroscopic follow-up. Moreover, a multiple-band photometric survey is itself a powerful method to find and vet planetary candidates and narrow down the candidate list of high-priority targets. In this work, we report the first results of a dual-band (Sloan-g and -i) wide-field photometry survey—the Chinese Small Telescope ARray II (CSTAR-II), an updated version of the original CSTAR. As a key component of the Chinese Exoplanet Searching Program from Antarctica, CSTAR-II has been tested thoroughly at a remote arctic site near Mohe during the winter of 2014. In total, 13,531 light curves with the best overall photometric precision of ∼3 mmag were extracted from 7721 stars in the Sloan-g and -i bands. Using a robust method, we have detected 63 variables, of which 48 are newly discovered. The dual-band photometric results as well as the stellar properties of the detected sources are provided in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Performance Verification of the EXtreme PREcision Spectrograph

The EXtreme PREcision Spectrograph (EXPRES) is a new Doppler spectrograph designed to reach a radial-velocity measurement precision sufficient to detect Earth-like exoplanets orbiting nearby, bright stars. We report on extensive laboratory testing and on-sky observations to quantitatively assess the instrumental radial-velocity measurement precision of EXPRES, with a focused discussion of individual terms in the instrument error budget. We find that EXPRES can reach a single-measurement instrument calibration precision better than 10 cm s{sup −1}, not including photon noise from stellar observations. We also report on the performance of the various environmental, mechanical, and optical subsystems of EXPRES, assessing any contributions to radial-velocity error. For atmospheric and telescope related effects, this includes the fast tip-tilt guiding system, atmospheric dispersion compensation, and the chromatic exposure meter. For instrument calibration, this includes the laser fRequency comb (LFC), flat-field light source, CCD detector, and effects in the optical fibers. Modal noise is mitigated to a negligible level via a chaotic fiber agitator, which is especially important for wavelength calibration with the LFC. Regarding detector effects, we empirically assess the impact on the radial-velocity precision due to pixel-position nonuniformities and charge transfer inefficiency (CTI). EXPRES has begun its science survey to discover exoplanets orbiting G-dwarf and K-dwarf stars, in addition to transit spectroscopy and measurements of the Rossiter–McLaughlin effect.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The Dark Energy Survey Supernova Program: Corrections on Photometry Due to Wavelength-dependent Atmospheric Effects

Abstract Wavelength-dependent atmospheric effects impact photometric supernova flux measurements for ground-based observations. We present corrections on supernova flux measurements from the Dark Energy Survey Supernova Program’s 5YR sample (DES-SN5YR) for differential chromatic refraction (DCR) and wavelength-dependent seeing, and we show their impact on the cosmological parameters w and Ω m . We use g − i colors of Type Ia supernovae to quantify astrometric offsets caused by DCR and simulate point-spread functions (PSFs) using the GalSIM package to predict the shapes of the PSFs with DCR and wavelength-dependent seeing. We calculate the magnitude corrections and apply them to the magnitudes computed by the DES-SN5YR photometric pipeline. We find that for the DES-SN5YR analysis, not accounting for the astrometric offsets and changes in the PSF shape cause an average bias of +0.2 mmag and −0.3 mmag, respectively, with standard deviations of 0.7 mmag and 2.7 mmag across all DES observing bands ( griz ) throughout all redshifts. When the DCR and seeing effects are not accounted for, we find that w and Ω m are lower by less than 0.004 ± 0.02 and 0.001 ± 0.01, respectively, with 0.02 and 0.01 being the 1 σ statistical uncertainties. Although we find that these biases do not limit the constraints of the DES-SN5YR sample, future surveys with much higher statistics, lower systematics, and especially those that observe in the u band will require these corrections as wavelength-dependent atmospheric effects are larger at shorter wavelengths. We also discuss limitations of our method and how they can be better accounted for in future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Shear Measurement Bias Due to Spatially Varying Spectral Energy Distributions in Galaxies

Galaxy color gradients (CGs)—i.e., spectral energy distributions that vary across the galaxy profile—will impact galaxy shape measurements when the modeled point-spread function (PSF) corresponds to that for a galaxy with spatially uniform color. This paper describes the techniques and results of a study of the expected impact of galaxy CGs on weak lensing measurements with the Large Synoptic Survey Telescope (LSST) when the PSF size depends on wavelength. The bias on cosmic shear measurements from CGs is computed both for parametric bulge$+$disk galaxy simulations and for more realistic chromatic galaxy surface brightness profiles based on Hubble Space Telescope V- and I-band images in the All-Wavelength Extended Groth Strip International Survey (AEGIS). For the parametric galaxies, and for the more realistic galaxies derived from AEGIS galaxies with a sufficient signal-to-noise ratio that CG bias can be isolated, the predicted multiplicative shear biases due to CGs are found to be at least a factor of two below the LSST full-depth requirement on the total systematic uncertainty in the redshift-dependent shear calibration. The analysis code and data products are publicly available (https://github.com/sowmyakth/measure_cg_bias).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

LensWatch. I. Resolved HST Observations and Constraints on the Strongly Lensed Type Ia Supernova 2022qmx (“SN Zwicky”)

Supernovae (SNe) that have been multiply imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest such discovery is of the quadruply imaged Type Ia SN 2022qmx (aka, "SN Zwicky") at z = 0.3544. SN Zwicky was discovered by the Zwicky Transient Facility in spatially unresolved data. Here we present follow-up Hubble Space Telescope observations of SN Zwicky, the first from the multicycle "LensWatch (www.lenswatch.org)" program. We measure photometry for each of the four images of SN Zwicky, which are resolved in three WFC3/UVIS filters (F475W, F625W, and F814W) but unresolved with WFC3/IR F160W, and present an analysis of the lensing system using a variety of independent lens modeling methods. We find consistency between lens-model-predicted time delays (≲1 day), and delays estimated with the single epoch of Hubble Space Telescope colors (≲3.5 days), including the uncertainty from chromatic microlensing (~1–1.5 days). Our lens models converge to an Einstein radius of ${\theta }_{{\rm{E}}}=({0.168}_{-0.005}^{+0.009})^{\prime\prime} $, the smallest yet seen in a lensed SN system. The "standard candle" nature of SN Zwicky provides magnification estimates independent of the lens modeling that are brighter than predicted by $\sim {1.7}_{-0.6}^{+0.8}$ mag and $\sim {0.9}_{-0.6}^{+0.8}$ mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology

In this work, we describe the Dark Energy Survey (DES) photometric data set assembled from the first three years of science operations to support DES Year 3 cosmologic analyses, and provide usage notes aimed at the broad astrophysics community. Y3 GOLD improves on previous releases from DES, Y1 GOLD, and Data Release 1 (DES DR1), presenting an expanded and curated data set that incorporates algorithmic developments in image detrending and processing, photometric calibration, and object classification. Y3 GOLD comprises nearly 5000 deg 2 of grizY imaging in the south Galactic cap, including nearly 390 million objects, with depth reaching a signal-to-noise ratio ~10 for extended objects up to iAB ~ 23.0, and top-of-the-atmosphere photometric uniformity <3 mmag. Compared to DR1, photometric residuals with respect to Gaia are reduced by 50%, and per-object chromatic corrections are introduced. Y3 GOLD augments DES DR1 with simultaneous fits to multi-epoch photometry for more robust galactic color measurements and corresponding photometric redshift estimates. Y3 GOLD features improved morphological star–galaxy classification with efficiency >98% and purity >99% for galaxies with 19 < i AB < 22.5. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used to select the cosmologic analysis samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

On the Existence of the Plateau Emission in High-energy Gamma-Ray Burst Light Curves Observed by Fermi-LAT

The Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope (Fermi) shows long-lasting high-energy emission in many gamma-ray bursts (GRBs), similar to X-ray afterglows observed by the Neil Gehrels Swift Observatory (Swift). Some LAT light curves (LCs) show a late-time flattening reminiscent of X-ray plateaus. We explore the presence of plateaus in LAT temporally extended emission analyzing GRBs from the second Fermi-LAT GRB Catalog from 2008 to 2016 May with known redshifts, and check whether they follow closure relations corresponding to four distinct astrophysical environments predicted by the external forward shock model. We find that three LCs can be fit by the same phenomenological model used to fit X-ray plateaus and show tentative evidence for the existence of plateaus in their high-energy extended emission. The most favorable scenario is a slow-cooling regime, whereas the preferred density profile for each GRBs varies from a constant-density interstellar medium to an r –2 wind environment. We also compare the end time of the plateaus in γ-rays and X-rays using a statistical comparison with 222 Swift GRBs with plateaus and known redshifts from 2005 January to 2019 August. Within this comparison, the case of GRB 090510 shows an indication of chromaticity at the end time of the plateau. Finally, we update the 3D fundamental plane relation among the rest-frame end time of the plateau, its correspondent luminosity, and the peak prompt luminosity for 222 GRBs observed by Swift. We find that these three LAT GRBs follow this relation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Remote-sensing detectability of airborne Arctic dust

Remote-sensing (RS)-based estimates of Arctic dust are oftentimes overestimated due to a failure in separating out the dust contribution from that of spatially homogeneous clouds or low-altitude cloud-like plumes. A variety of illustrations are given with a particular emphasis on questionable claims of using brightness temperature differences (BTDs) as a signature indicator of Arctic dust transported from mid-latitude deserts or generated by local Arctic sources. While there is little dispute about the presence of both Asian and local dust across the Arctic, the direct RS detectability of airborne dust, as ascribed to satellite (MODIS and AVHRR) measurements of significantly negative brightness temperature differences at 11 and 12 µm (BTD 11–12 ), has been misrepresented in certain cases. While it is difficult to account for all examples of strongly negative BTD 11–12 values in the Arctic, it is unlikely that airborne dust plays a significant role. One much more likely contributor would be water clouds in the Arctic inversion layer. The RS detectability of the impact of Arctic dust (notably due to Arctic dust from local sources) can, however, be of significance. Sustained dust deposition can substantially decrease (visible to shortwave IR) snow and ice reflectance albedo (pan-chromatic reflectance) and the signal measured by satellite sensors. Significantly negative BTD 11–12 values would, however, only represent a limited area near the drainage basin sources according to our event-level case studies. The enhanced ice-nucleating particle (INP) role of local Arctic dust can, for example, induce significant changes in the properties of low-level mixed-phase clouds (cloud optical depth changes <~ 1) that can readily be detected by active and passive RS instruments. It is critical that the distinction between the RS detectability of airborne Arctic dust versus the RS detectability of the impacts of that dust be understood if we are to appropriately parameterize, for example, the radiative forcing influence of dust in this climate-sensitive region.

54 ENVIRONMENTAL SCIENCES↗