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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 OSTI2022

The relation between optical and γ-ray emission in BL Lac sources

ABSTRACT The relativistic jets produced by some Active Galactic Nuclei (AGNs) are among the most efficient persistent sources of non-thermal radiation and represent an ideal laboratory for studying high-energy interactions. In particular, when the relativistic jet propagates along the observer’s line of sight, the beaming effect produces dominant signatures in the observed spectral energy distribution (SED), from the radio domain up to the highest energies, with the further possibility of resulting in radiation-particle multimessenger associations. In this work, we investigate the relationships between the emission of γ rays and the optical spectra of a sample of AGN, selected from BL Lac sources detected by the Fermi Large Area Telescope (Fermi-LAT). We find that there is a close relationship between the optical and γ-ray spectral indices. Despite all the limitations due to the non-simultaneity of the data, this observation strongly supports a substantial role of Synchrotron-Self Compton (SSC) radiation in a single zone leptonic scenario for most sources. This result simplifies the application of theoretical models to explore the physical parameters of the jets in this type of sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Risk Assessment of Industrial Microbes Using a Terrestrial Mesocosm Platform

Abstract Industrial microbes and bio-derived products have emerged as an integral component of the bioeconomy, with an array of agricultural, bioenergy, and biomedical applications. However, the rapid development of microbial biotechnology raises concerns related to environmental escape of laboratory microbes, detection and tracking thereof, and resultant impact upon native ecosystems. Indeed, though wild-type and genetically modified microbes are actively deployed in industrial bioprocesses, an understanding of microbial interactivity and impact upon the environment is severely lacking. In particular, the persistence and sustained ecosystem impact of industrial microbes following laboratory release or unintentional laboratory escape remains largely unexplored. Herein, we investigate the applicability of soil-sorghum mesocosms for the ecological risk assessment of the industrial microbe, Saccharomyces cerevisiae . We developed and applied a suite of diagnostic and bioinformatic analyses, including digital droplet PCR, microscopy, and phylogenomic analyses to assess the impacts of a terrestrial ecosystem perturbation event over a 30-day time course. The platform enables reproducible, high-sensitivity tracking of S. cerevisiae in a complex soil microbiome and analysis of the impact upon abiotic soil characteristics and soil microbiome population dynamics and diversity. The resultant data indicate that even though S. cerevisiae is relatively short-lived in the soil, a single perturbation event can have sustained impact upon mesocosm soil composition and underlying microbial populations in our system, underscoring the necessity for more comprehensive risk assessment and development of mitigation and biocontainment strategies in industrial bioprocesses.

09 BIOMASS FUELS↗
DOE OSTI2023

Doppler Lidar Measurements of Wind Variability and LLJ Properties in Central Oklahoma during the August 2017 Land–Atmosphere Feedback Experiment

Abstract Low-level jets (LLJs) are an important nocturnal source of wind energy in the U.S. Great Plains. An August 2017 lidar-based field-measurement campaign [the Land–Atmosphere Feedback Experiment (LAFE)] studied LLJs over the central SGP site in Oklahoma and found nearly equal occurrences of the usual southerly jets and postfrontal northeasterly jets—typically rare during this season—for an opportunity to compare the two types of LLJs during this month. Southerly winds were stronger than the northeasterlies by more than 4 m s −1 on average, reflecting a significantly higher frequency of winds stronger than 12 m s −1 . The analysis of this dataset has been expanded to other SGP Doppler-lidar sites to quantify the variability of winds and LLJ properties between sites of different land use. Geographic variations of winds over the study area were noted: on southerly wind nights, the winds blew stronger at the highest, westernmost sites by 2 m s −1 , whereas on the northeasterly flow nights, the easternmost sites had the strongest wind speeds. Lidar measurements at 5 sites during August 2017, contrasted to the 2016–21 summertime data, revealed unusual wind and LLJ conditions. Temporal hodographs using hourly averaged winds at multiple heights revealed unorganized behavior in the turbulent stable boundary layer (SBL) below the jet nose. Above the nose, some nights showed veering qualitatively similar to inertial oscillation (IO) behavior, but at amplitudes much smaller than expected for an IO, whereas other nights showed little veering. Vertical hodographs had a linear shape in the SBL, indicating little directional shear there, and veering above, resulting in a hook-shaped hodograph with height. Significance Statement Doppler-lidar measurements at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) were used to quantify the variability of winds and low-level jet (LLJ) properties between five sites of different land use and wind regimes across this area. Knowledge of wind and LLJ structure and dynamics is important for many applications, and strong southerly LLJ winds at night are an important resource for wind energy. The analysis of multiyear (2016–21) summertime LLJ parameters provided insight into the LLJ climatology in this part of the Great Plains.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Early dark energy constraints with late-time expansion marginalization

Abstract Early dark energy (EDE) is an extension to the ΛCDM model that includes an additional energy density contribution near recombination. The model was proposed to reduce the tension between the measurements of the Hubble constantH 0 from the cosmic microwave background (CMB) and from the local cosmic distance ladder. Some analyses in the recent literature have shown intriguing hints for EDE. However, this model increases the tension in the derived clustering of galaxies (as measured by the so-calledS 8 parameter) between CMB and large scale structure (LSS) measurements. This new tension limits the contribution of EDE during recombination, and thus its effect on the Hubble tension. In this work, we investigate whether the inclusion of a general, smooth late-time dark energy modification can increase back the EDE contribution when LSS data is included in the analysis. In order to generalize the late expansion with respect to the ΛCDM model, we substitute the cosmological constant by a late dark energy fluid model with a piecewise constant equation of state w(z) in redshift bins. We show that, when analysing this generalized model with combinations of CMB, LSS and type Ia supernovae data from several experiments no significant changes onS 8 and EDE parameter constraints is found. The contribution to the EDE fraction constraint with late-time expansion marginalization isf EDE = 0.067 +0.019 -0.027 using 3 redshift bins, with similar results for 5 and 10 redshift bins. This work shows that in order to solve simultaneously the Hubble andS 8 tensions, one needs a mechanism for increasing the clustering of matter at late times different from a simple change in the background evolution of late dark energy.

Astronomy & Astrophysics↗
DOE OSTI2021

Genomic characterization of three marine fungi, including Emericellopsis atlantica sp. nov. with signatures of a generalist lifestyle and marine biomass degradation

ABSTRACT Marine fungi remain poorly covered in global genome sequencing campaigns; the 1000 fungal genomes (1KFG) project attempts to shed light on the diversity, ecology and potential industrial use of overlooked and poorly resolved fungal taxa. This study characterizes the genomes of three marine fungi: Emericellopsis sp. TS7, wood-associated Amylocarpus encephaloides and algae-associated Calycina marina. These species were genome sequenced to study their genomic features, biosynthetic potential and phylogenetic placement using multilocus data. Amylocarpus encephaloides and C. marina were placed in the Helotiaceae and Pezizellaceae (Helotiales) , respectively, based on a 15-gene phylogenetic analysis. These two genomes had fewer biosynthetic gene clusters (BGCs) and carbohydrate active enzymes (CAZymes) than Emericellopsis sp. TS7 isolate. Emericellopsis sp. TS7 ( Hypocreales , Ascomycota ) was isolated from the sponge Stelletta normani . A six-gene phylogenetic analysis placed the isolate in the marine Emericellopsis clade and morphological examination confirmed that the isolate represents a new species, which is described here as E. atlantica . Analysis of its CAZyme repertoire and a culturing experiment on three marine and one terrestrial substrates indicated that E. atlantica is a psychrotrophic generalist fungus that is able to degrade several types of marine biomass. FungiSMASH analysis revealed the presence of 35 BGCs including, eight non-ribosomal peptide synthases (NRPSs), six NRPS-like, six polyketide synthases, nine terpenes and six hybrid, mixed or other clusters. Of these BGCs, only five were homologous with characterized BGCs. The presence of unknown BGCs sets and large CAZyme repertoire set stage for further investigations of E. atlantica . The Pezizellaceae genome and the genome of the monotypic Amylocarpus genus represent the first published genomes of filamentous fungi that are restricted in their occurrence to the marine habitat and form thus a valuable resource for the community that can be used in studying ecological adaptions of fungi using comparative genomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Artificial Intelligence Assisted Inversion (AIAI): Quantifying the Spectral Features of 56 Ni of Type Ia Supernovae

Abstract Following our previous study of Artificial Intelligence Assisted Inversion (AIAI) of supernova analyses, we train a set of deep neural networks based on the 1D radiative transfer code TARDIS to simulate the optical spectra of Type Ia supernovae (SNe Ia) between 10 and 40 days after the explosion. The neural networks are applied to derive the mass of 56 Ni in velocity ranges above the photosphere for a sample of 124 well-observed SNe Ia in the TARDIS model context. A subset of the SNe have multi-epoch observations for which the decay of the radioactive 56 Ni can be used to test the AIAI quantitatively. The 56 Ni mass derived from AIAI using the observed spectra as inputs for this subset agrees with the radioactive decay rate of 56 Ni. AIAI reveals that a spectral signature near 3890 Å is related to the Niii4067Å line, and the 56 Ni mass deduced from AIAI is found to be correlated with the light-curve shapes of SNe Ia, with SNe Ia with broader light curves showing larger 56 Ni mass in the envelope above the photosphere. AIAI enables spectral data of SNe to be quantitatively analyzed under theoretical frameworks based on well-defined physical assumptions.

Astronomy & Astrophysics↗
DOE OSTI2025

Discovering methylated DNA motifs in bacterial nanopore sequencing data with MIJAMP

Abstract Bacterial DNA methylation is involved in diverse cellular functions, including modulation of gene expression, DNA repair, and restriction–modification systems for defense against viruses and other foreign DNA. Restriction systems hinder efforts to engineer organisms to produce fuels and chemicals from waste and renewable feedstocks by degrading DNA during transformation. Methylome analysis allows identification of motifs within a bacterial chromosome that may be targeted by native restriction enzymes. Further expression of the corresponding methyltransferases in Escherichia coli allows plasmid DNA to be protected from restriction in the target organism, thereby drastically enhancing transformation efficiency. Nanopore sequencing can detect methylated bases, but software is needed to transform modified base coordinates into methylated motifs. Here, we develop MIJAMP (MIJAMP Is Just A MethylBED Parser), a software package that was developed to discover methylated motifs from the output of ONT’s Modkit or other data in the methylBED format. MIJAMP employs a human-driven refinement strategy that empirically validates all motifs against genome-wide methylation data, thus eliminating incorrect motifs. MIJAMP also reports methylation data on specific, user-defined motifs. Using MIJAMP, we determined the methylated motifs both in a control strain (wild-type E. coli) and in Synecococcus sp. strain PCC7002, laying the foundation for improved transformation in this organism. MIJAMP is available at https://code.ornl.gov/alexander-public/mijamp/. One Sentence Summary: Here we describe software written to discover DNA methylation motifs from nanopore sequencing data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Predation probabilities and functional responses: How piscivorous waterbirds respond to pulses in fish abundance

Abstract How predators respond to changes in prey abundance (i.e., functional responses) is foundational to consumer–resource interactions, predator–prey dynamics, and the stability of predator–prey systems. Predation by piscivorous waterbirds on out‐migrating juvenile steelhead trout ( Oncorhynchus mykiss ) is considered a factor affecting the recovery of multiple Endangered Species Act‐listed steelhead populations in the Columbia River basin. Waterbird functional responses, however, may vary by predator species and location, with important implications to predator management strategies. We used a 13‐year dataset on waterbird abundance across seven breeding colonies (three Caspian tern [ Hydroprogne caspia ], two double‐crested cormorant [ Nannopterum auritum ], and two California and ring‐billed gull [ Larus californicus and Larus delawarensis ] colonies) and steelhead tag‐recovery data (>645,000 tagged and >32,000 recovered steelhead) to quantify weekly predation probabilities and functional responses across waterbird species, colonies, and years. Weekly predation probabilities were highly variable, ranging from 0.01 to 0.30 at tern colonies, 0.01 to 0.20 at cormorant colonies, and 0.03 to 0.13 at gull colonies. Per capita predation probabilities were an order of magnitude higher at inland tern and cormorant colonies relative to estuary colonies of the same species. Terns displayed Type II functional responses across colonies and years, where predation probabilities peaked at low steelhead abundances and declined as steelhead abundance increased (i.e., predator swamping). Cormorants nesting at the large estuary colony (several thousand birds) displayed a Type III functional response, but cormorants nesting at the smaller inland colony (several hundred birds) displayed a Type II response. Consumption probabilities of steelhead by gulls remained consistent across a large range of steelhead availability, suggesting a Type I or a Type III functional response, but a lack of colony abundance data prevented quantifying functional responses. The level of tern predation combined with Type II functional responses indicate possible population‐level impacts that could destabilize small or declining prey populations. Conversely, the apparent Type III functional responses of gulls and estuary nesting cormorants are indicative of prey switching behaviors targeted at periods of high steelhead abundance. Our results illustrate the complexity of predator–prey interactions and the importance of quantifying predator‐ and location‐specific functional responses when predicting the efficacy of management strategies to enhance prey populations.

Hostetter, Nathan J.↗
DOE OSTI2024

Analysis of the first ten years of FDA’s rare pediatric disease priority review voucher program: designations, diseases, and drug development

Abstract Background The Rare Pediatric Disease (RPD) Priority Review Voucher (PRV) Program was enacted in 2012 to support the development of new products for children. Prior to requesting a voucher, applicants can request RPD designation, which confirms their product treats or prevents a rare disease in which the serious manifestations primarily affect children. This study describes the trends and characteristics of these designations. Details of RPD designations are not publicly disclosable; this research represents the first analysis of the RPD designation component of the program. Results We used an internal US Food and Drug Administration database to analyze all RPD designations between 2013 and 2022. Multiple characteristics were analyzed, including the diseases targeted by RPD designation, whether the product targeted a neonatal disease, product type (drug/biologic), and the level of evidence (preclinical/clinical) to support designation. There were 569 RPD designations during the study period. The top therapeutic areas were neurology (26%, n = 149), metabolism (23%, n = 131), oncology (18%, n = 105). The top diseases targeted by RPD designation were Duchenne muscular dystrophy, neuroblastoma, and sickle cell disease. Neonatology products represented 6% (n = 33), over half were for drug products and 38% were supported by clinical data. Conclusions The RPD PRV program was created to encourage development of new products for children. The results of this study establish that a wide range of diseases have seen development—from rare pediatric cancers to rare genetic disorders. Continued support of product development for children with rare diseases is needed to find treatments for all children with unmet needs.

Mease, Catherine (ORCID:000900050156198X)↗
DOE OSTI2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗
DOE OSTI2023

A Geo-Data Science Method for Assessing Unconventional Rare-Earth Element Resources in Sedimentary Systems

Abstract Rare-earth elements (REEs) supply raw materials that constitute many of our modern critical infrastructure, defense, technology, and electrification needs. Despite REE accumulations occurring in conventional bedrock and ion-adsorption deposits sourced from weathering of igneous rocks, unconventional host materials such as coal and related sedimentary strata have been identified as promising sources of REEs to meet growing demand. To maximize the potential of unconventional resources such as REE-coal systems, new approaches are needed overcome challenges from mineral systems with no known deposits and areas with sparse geochemical data. This article presents a systematic knowledge-data resource assessment method for predicting and identifying REE resource potential and occurrence in these unconventional systems. The method utilizes a geologic and geospatial knowledge-data approach informed and guided by REE accumulation mechanisms to systematically assess and identify areas of higher enrichment. An assessment of the Powder River Basin is presented as a test case to demonstrate the method workflow and results. The key output is a potential enrichment score map reported with varying confidence levels based on the amount of supporting evidence. Results from the test case indicate several locations with promising potential for different types of coal-REE deposits, demonstrating the viability of the method for exploration and assessment of unconventional REE resources. The method is flexible by design and, with sufficient applicable knowledge and data, can be adapted for assessing critical mineral systems in other sedimentary systems as well.

58 GEOSCIENCES↗
DOE OSTI2022

High‐Pressure and High‐Temperature Single‐Crystal Elasticity of Cr‐Pyrope: Implications for the Density and Seismic Velocity of Subcontinental Lithospheric Mantle

Abstract Single‐crystal X‐ray diffraction and Brillouin spectroscopy experiments were performed on a natural Cr‐pyrope (Prp 71.0 Alm 12.6 Sps 0.7 Grs 3.5 Uvr 12.2 ) at high pressure and high temperature up to 11.0 GPa and 800 K. Fitting the collected data to the third‐order finite strain equation yields bulk modulus ( K S 0 ), shear modulus ( G 0 ), their pressure ((∂ K S /∂ P ) T and (∂ G /∂ P ) T ) and temperature (( ∂K S /∂T ) P and ( ∂G/∂T ) P ) derivatives, K S 0 = 167.7(8) GPa, G 0 = 91.5(5) GPa, (∂ K S /∂ P ) T = 4.3(1), (∂ G /∂ P ) T = 1.4(1), ( ∂K S /∂T ) P = − 0.0175(1) GPa/K and ( ∂G/∂T ) P = − 0.0073(1) GPa/K. Using the obtained results, we examined whether the elastic properties of the Cr‐pyrope can be accurately calculated from those of endmembers including pyrope, almandine, grossular, and uvarovite assuming a linear relationship between elastic properties and composition (end‐member model). The results indicate that the end‐member model provides a sufficient approximation for the elastic properties of Cr‐pyrope in calculating the density and velocity of the subcontinental lithospheric mantle (SCLM). We modeled the densities and velocities of three typical types of SCLM (Archon, Proton, and Tecton) in order to investigate how the variation of chemical composition influences the SCLM. We obtained that the compositional change from the Archon to the Tecton increases the density of the SCLM significantly, which can be an important prerequisite for SCLM delamination. However, the compositional variation only slightly changes the velocity of the SCLM and the change is within the uncertainty of the calculation. Moreover, in comparison to the velocity, ρ / V P and ρ / V S are much more sensitive to the compositional change of the SCLM.

Xu, Jingui↗
DOE OSTI2022

Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Abstract Current and future cosmological analyses with Type Ia supernovae (SNe Ia) face three critical challenges: (i) measuring the redshifts from the SNe or their host galaxies; (ii) classifying the SNe without spectra; and (iii) accounting for correlations between the properties of SNe Ia and their host galaxies. We present here a novel approach that addresses each of these challenges. In the context of the Dark Energy Survey (DES), we analyze an SN Ia sample with host galaxies in the redMaGiC galaxy catalog, a selection of luminous red galaxies. redMaGiC photo- z estimates are expected to be accurate to σ Δ z /(1+ z ) ∼ 0.02. The DES-5YR photometrically classified SN Ia sample contains approximately 1600 SNe, and 125 of these SNe are in redMaGiC galaxies. We demonstrate that redMaGiC galaxies almost exclusively host SNe Ia, reducing concerns relating to classification uncertainties. With this subsample, we find similar Hubble scatter (to within ∼0.01 mag) using photometric redshifts in place of spectroscopic redshifts. With detailed simulations, we show that the bias due to using redMaGiC photo- z s on the measurement of the dark energy equation of state w is up to Δ w ∼ 0.01–0.02. With real data, we measure a difference in w when using the redMaGiC photo- z s versus the spec- z s of Δ w = 0.005. Finally, we discuss how SNe in redMaGiC galaxies appear to comprise a more standardizable population, due to a weaker relation between color and luminosity ( β ) compared to the DES-3YR population by ∼5 σ . These results establish the feasibility of performing redMaGiC SN cosmology with photometric survey data in the absence of spectroscopic data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Developing a Consistent Travel-Time Framework for Comparing Three-Dimensional Velocity Models for Seismic Location Accuracy

Abstract Location algorithms have historically relied on simple, one-dimensional (1D) velocity models for fast seismic event locations. 1D models are generally used as travel-time lookup tables, one for each seismic phase, with travel-times pre-calculated for event distance and depth. These travel-time lookup tables are extremely fast to use and this fast computational speed makes them the preferred type of velocity model for operational needs. Higher-dimensional (i.e., three-dimensional—3D) seismic velocity models are becoming readily available and provide more accurate event locations over 1D models. The computational requirements of these 3D models tend to make their operational use prohibitive. Additionally, comparing location accuracy for 3D seismic velocity models tends to be problematic, as each model is determined using different ray-tracing algorithms. Attempting to use a different algorithm than the one used to develop a model usually results in poor travel-time prediction. We demonstrate and test a framework to create first-P and first-S 3D travel-time correction surfaces using an open-source framework ( PCalc + GeoTess , https://www.sandia.gov/salsa3d/software/geotess ) that easily stores 3D travel-time and uncertainty data. This framework produces fast travel-time and uncertainty predictions and overcomes the ray-tracing algorithm hurdle because the lookup tables can be generated using the exact ray-tracing algorithm that is preferred for a model.

3D velocity models↗
DOE OSTI2023

Accurate model of the projected velocity distribution of galaxies in dark matter haloes

ABSTRACT We present a per cent-level accurate model of the line-of-sight velocity distribution of galaxies around dark matter haloes as a function of projected radius and halo mass. The model is developed and tested using synthetic galaxy catalogues generated with the UniverseMachine run on the Multi-Dark Planck 2 N-body simulations. The model decomposes the galaxies around a cluster into three kinematically distinct classes: orbiting, infalling, and interloping galaxies. We demonstrate that: (1) we can statistically distinguish between these three types of galaxies using only projected line-of-sight velocity information; (2) the halo edge radius inferred from the line-of-sight velocity dispersion is an excellent proxy for the three-dimensional halo edge radius; and (3) we can accurately recover the full velocity dispersion profile for each of the three populations of galaxies. Importantly, the velocity dispersion profiles of the orbiting and infalling galaxies contain five independent parameters – three distinct radial scales and two velocity dispersion amplitudes – each of which is correlated with mass. Thus, the velocity dispersion profile of galaxy clusters has inherent redundancies that allow us to perform non-trivial systematics checks from a single data set. We discuss several potential applications of our new model for detecting the edge radius and constraining cosmology and astrophysics using upcoming spectroscopic surveys.

Astronomy & Astrophysics↗
NASA NTRSDate not supplied

The Nucleosynthetic Heritage of Bennu

The OSIRIS-REx mission sampled the B-type asteroid Bennu and delivered 121.6 g of material to Earth in September 2023. Nucleosynthetic isotope variations are powerful tracers that can be used to establish relationships between different meteorite groups and the returned samples. They can also constrain the samples’ nucleosynthetic heritage, as well as mixing and reservoir formation in the protoplanetary disk. Nucleosynthetic variations reflect the heterogeneous distribution of isotopically distinct dust in the disk, and as such, they provide evidence for the formation of meteorite parent bodies from isotopically distinct dust reservoirs. They are thus also a means to identify exogenous clasts in Bennu materials. Here, we report Ti and Fe isotope data obtained from Bennu samples and carbonaceous chondrites. We also present Ti isotope data for hand-picked matrix from CV and CR chondrites. An isotopic dataset was obtained on aggregate sample OREX-803015-100 consisting of particles typically <500 μm; therefore, its composition represents an average for Bennu materials. A 20.66 mg aliquot was dissolved at Washington University, St. Louis. From this, 5 mg was analysed for Ti and Fe isotopes on a NeptunePlus MC-ICPMS at ETH Zurich; data from a separate aliquot, analysed at Lawrence Livermore National Laboratory, are reported in a companion abstract. Our results demonstrate a close relationship of Bennu to CI and Ryugu samples and therefore a formation outside the snowline, as hypothesized by the mission. Furthermore, the 50 Ti data from the CV and CR matrix fall consistently below the CI and Bennu values, indicating the presence of a uniform matrix mixed with ⁓0.1–0.7% of refractory inclusions in CIs and Bennu.

M. Schönbächler↗
DOE OSTI2020

The completed SDSS-IV extended baryon oscillation spectroscopic survey: pairwise-inverse probability and angular correction for fibre collisions in clustering measurements

ABSTRACT The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected $\rm {\mathit{ w}_p}\left(\mathit{ r}_p\right)$ and the redshift-space multipole ξ(ℓ = 0, 2, 4)(s) correlation functions down to $0.1\, h^{-1}{\rm Mpc}$, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales $s\gtrsim 20\, h^{-1}{\rm Mpc}$ for ξℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to $\sim 0.1\, h^{-1}{\rm Mpc}$ scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.

79 ASTRONOMY AND ASTROPHYSICS↗