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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Sensitivity of modelled passive margin stratigraphy to variations in sea level, sediment supply and subsidence

Abstract We produced a 10 Myr synthetic stratigraphic section using a forward stratigraphic model that generates marine deltaic stratigraphy over geological timescales. We recursively fit the model using a Bayesian inversion algorithm to test: (1) if it could be accurately reconstructed; (2) if the parameters used to create it could be recovered; and (3) the sensitivity of the model output to given model parameters and the attendant physical processes. The original synthetic stratigraphic section was produced with cyclical sea‐level variations of 40 and 30 m with 2.4 and 10 Myr periods respectively. Sediment was also supplied cyclically, in 2.4 and 10 Myr cycles with amplitudes of 30 and 80 tons/100 kyr, respectively, varying from a mean of 232 tons/100 kyr. Parameter values were sampled to fit the model using a Markov chain Monte Carlo algorithm, resulting in a ±5 m (1σ) variation between the experimental output and the original. Sea level varied by ±7 m (1σ) within the posterior distribution of parameters. As a result, both the 10 Myr and 2.4 Myr sea‐level cycles could be extracted from the original output. The variation in sediment supply was approximately ±38 tons/100 kyr (1σ) and, as a result, only the larger long‐term supply variations could be accurately recovered in refitting the model. The variation in thermal, flexural and total subsidence across those parameter sets is less than ±10 m (1σ). The original section experienced 150 m of total subsidence at the depocentre. Our results demonstrate the distinct and interpretable imprint of sea level and subsidence on continental margin stratigraphy can be quantified. Moreover, we conclude that sea‐level change produces a defined effect on the geometries of stratigraphic architecture, and that techniques applied for the purpose of delineating sea‐level variation from continental margin strata have a well‐founded conceptual basis.

Schmelz, William J.↗
DOE OSTI2017

A kinetic study of the fast micro-pyrolysis of hybrid poplar

Here, hybrid poplar from the clone DN34 was studied to determine the rate of production of bio-oil species with respect to time during the fast pyrolysis process. 300–660 ug samples were pyrolyzed using a micropyrolzer at 500 °C at very high heating rates and very short vapor residence times. Individual poplar samples were run in triplicate at discrete time points ranging from 1 to 20 s in the micropyrolzer. Several bio-oil compounds from each individual sample were analyzed using GC/MS. Select bio-oil compounds, derived from the hemicellulose, cellulose, and lignin fractions of the wood, were used to determine their rates of production from thermal degradation of the biomass. These rates were quantified using standards to determine the weight percent relative to the original raw biomass with respect to time. Pyrolysis kinetic reaction models were fit to this experimental data in order to determine suitability of each model. A first order exponential decay model for degradation of the solid biomass was fit against the data along with a six-step consecutive degradation model previously developed by our group. The experimental data suggests that compounds derived from the hemicellulose are produced at faster rates than that of the lignin or cellulose fractions of the wood, consistent with prior data from thermogravimetric analysis (TGA). When applying the first order exponential decay model, the reaction rates calculated did prove that holocellulose compounds reaction rates were approximately twice that of the lignin compounds reaction rate but did not provide the best fit. The six-step degradation model provided a better fit to all of the biooil compounds and char data, and the stoichiometric parameters derived from the model fit showed that the first three reactions involved mostly the hemicellulose derived compounds while reaction steps 4–6 released cellulose- and lignin-derived compounds.

09 BIOMASS FUELS↗
DOE OSTI2024

Constrained curve fitting for semi-parametric models with radial basis function networks

Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global optimization algorithm. Parameter constraints are enforced through Gaussian priors. The viability of our method is tested by examining its use in a finite-size scaling analysis of the $q$-state Potts model and $p$-state clock model with $q=2,3$ and $p=4,\infty$.

Peterson, Curtis T.↗
DOE OSTI2015

Nonparametric test of consistency between cosmological models and multiband CMB measurements

We present a novel approach to test the consistency of the cosmological models with multiband CMB data using a nonparametric approach. In our analysis we calibrate the REACT (Risk Estimation and Adaptation after Coordinate Transformation) confidence levels associated with distances in function space (confidence distances) based on the Monte Carlo simulations in order to test the consistency of an assumed cosmological model with observation. To show the applicability of our algorithm, we confront Planck 2013 temperature data with concordance model of cosmology considering two different Planck spectra combination. In order to have an accurate quantitative statistical measure to compare between the data and the theoretical expectations, we calibrate REACT confidence distances and perform a bias control using many realizations of the data. Our results in this work using Planck 2013 temperature data put the best fit ΛCDM model at 95% (∼ 2σ) confidence distance from the center of the nonparametric confidence set while repeating the analysis excluding the Planck 217 × 217 GHz spectrum data, the best fit ΛCDM model shifts to 70% (∼ 1σ) confidence distance. The most prominent features in the data deviating from the best fit ΛCDM model seems to be at low multipoles 18 < ℓ < 26 at greater than 2σ, ℓ ∼ 750 at ∼1 to 2σ and ℓ ∼ 1800 at greater than 2σ level. Excluding the 217×217 GHz spectrum the feature at ℓ ∼ 1800 becomes substantially less significance at ∼1 to 2σ confidence level. Results of our analysis based on the new approach we propose in this work are in agreement with other analysis done using alternative methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Is Radioactive Tank Waste a Bingham Fluid?

Slurries and sludges across the United States Department of Energy (DOE) complex rank among the most rheologically interesting. Their composition is heterogeneous, spanning a very broad range of particle sizes, densities, and interparticle forces. All exhibit shear thinning, some have yield stresses, and many are thixotropic. Despite the variety, these complex fluids are often represented using the historic Bingham fluid model, which fits higher shear rate data to a simple straight line. The intercept provides a yield stress, which has been a key design parameter in construction of large-scale waste processing facilities. However, many radioactive wastes are simply not Bingham fluids, which extrapolate but poorly across low to intermediate shear rates that are characteristic of typical processing conditions. Indeed, processing shear rates as high as 200 1/s, which has been a typical minimum shear rate used in fitting, are seldom encountered in nuclear waste processing. Therefore, more realistic rheological models are necessary to accurately predict waste processing performance. PNNL recently re-evaluated the rheology of reconstituted Hanford REDOX sludge waste against a wide variety of rheological models including the Bingham, Cross, Cross with yield stress, Carreau, biviscous, Herschel-Bulkley (which includes a power law dependence), Casson, and Gay models. They found that all of the models provided a closer fit than the Bingham model and that the biviscous model and Cross with yield stress model were convincing. However, reconstituted Hanford REDOX sludge waste is but one type of DOE waste and a direct contrast and comparison of these three models against undiluted, unmixed tank waste (actual not simulant) has not been performed previously. Therefore, the purpose of this paper is to evaluate the rheology of actual tank waste with these more accurate rheological models. In this paper, we evaluate select rheological data for slurry samples from Hanford’s AZ-101, AZ-102, and SY-101 waste tanks. In each of these cases, we find that Cross’ model with yield stress and the biviscous model significantly outperform the Bingham fluid model. Furthermore, the AZ-101 data also shows that the shear stress peak that startup significantly exceeds the Bingham yield stress, which is commonly observed in the incipient moments of rheological measurements on simulants. In contrast, Cross’ model may empirically accommodate an initial spike in shear stress at modest shear rates. These are important observations because computational and analytical fluid dynamics simulations rely on rheological constitutive models for accurately and conservatively predict waste processing performance. These findings suggest the need for better rheological modeling of and validation against radioactive waste.

Rheology, Radioactive Waste↗
DOE OSTI2019

On spectral line shifts from analytic fits to the ion-sphere model potential

A simplification of a fit to the ion-sphere model potential that provides analytic level shifts [X. Li & F.B. Rosmej, EPL 99, 33001(2012)] is shown to have an inconsistency. On the other hand, the original fit [F.B. Rosmej et al., Phys. Rev. A84, 032512(2011)] not only avoids the problem but also leads to an overlooked analytic formula for level shifts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Thermal Contact Conductance Modeling

Elastic, plastic and elastic-plastic thermal conductance models were run for Al-6061 and SS-304, respectively. Thermal conductance models were compared to experimental data of samples being pressed together as a function of contact pressure. For SS-304, Elastic and Plastic models did not fit the experimental data well. The Elastic-Plastic model fit the data well and it was shown that surface roughness did not play a major role. For Al-6061, the Elastic model worked best and the models strongly suggested that surface roughness Al plays an important role in how well a thermal conductance model can predict conductance through two pieces of Al in contact with one another.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Using geochemical indicators to distinguish high biogeochemical activity in floodplain soils and sediments

A better understanding of how microbial communities interact with their surroundings in physically and chemically heterogeneous subsurface environments will lead to improved quantification of biogeochemical reactions and associated nutrient cycling. This paper develops a methodology to predict potential elevated rates of biogeochemical activity (microbial “hotspots”) in subsurface environments by correlating microbial DNA and aspects of the community structure with the spatial distribution of geochemical indicators in subsurface sediments. Multiple linear regression models of simulated precipitation leachate, HCl and hydroxylamine extractable iron and manganese, total organic carbon (TOC), and microbial community structure were used to identify sample characteristics indicative of biogeochemical hotspots within fluvially-derived aquifer sediments and overlying soils. The method has been applied to (a) alluvial materials collected at a former uranium mill site near Rifle, Colorado and (b) relatively undisturbed floodplain deposits (soils and sediments) collected along the East River near Crested Butte, Colorado. At Rifle, 16 alluvial samples were taken from 8 sediment cores, and at the East River, 46 soil/sediment samples were collected across and perpendicular to 3 active meanders and an oxbow meander. Regression models using TOC and TOC combined with extractable iron and manganese results were determined to be the best fitting statistical models of microbial DNA (via 16S rRNA gene analysis). Finally, fitting these models to observations in both contaminated and natural floodplain deposits, and their associated alluvial aquifers, demonstrates the broad applicability of the geochemical indicator based approach.

58 GEOSCIENCES↗
DOE OSTI2013

HerMES: COSMIC INFRARED BACKGROUND ANISOTROPIES AND THE CLUSTERING OF DUSTY STAR-FORMING GALAXIES

We present measurements of the auto- and cross-frequency power spectra of the cosmic infrared background (CIB) at 250, 350, and 500 {mu}m (1200, 860, and 600 GHz) from observations totaling {approx}70 deg{sup 2} made with the SPIRE instrument aboard the Herschel Space Observatory. We measure a fractional anisotropy {delta}I/I = 14% {+-} 4%, detecting signatures arising from the clustering of dusty star-forming galaxies in both the linear (2-halo) and nonlinear (1-halo) regimes; and that the transition from the 2- to 1-halo terms, below which power originates predominantly from multiple galaxies within dark matter halos, occurs at k{sub {theta}} {approx} 0.10-0.12 arcmin{sup -1} (l {approx} 2160-2380), from 250 to 500 {mu}m. New to this paper is clear evidence of a dependence of the Poisson and 1-halo power on the flux-cut level of masked sources-suggesting that some fraction of the more luminous sources occupy more massive halos as satellites, or are possibly close pairs. We measure the cross-correlation power spectra between bands, finding that bands which are farthest apart are the least correlated, as well as hints of a reduction in the correlation between bands when resolved sources are more aggressively masked. In the second part of the paper, we attempt to interpret the measurements in the framework of the halo model. With the aim of fitting simultaneously with one model the power spectra, number counts, and absolute CIB level in all bands, we find that this is achievable by invoking a luminosity-mass relationship, such that the luminosity-to-mass ratio peaks at a particular halo mass scale and declines toward lower and higher mass halos. Our best-fit model finds that the halo mass which is most efficient at hosting star formation in the redshift range of peak star-forming activity, z {approx} 1-3, is log(M{sub peak}/M{sub Sun }) {approx} 12.1 {+-} 0.5, and that the minimum halo mass to host infrared galaxies is log(M{sub min}/M{sub Sun }) {approx} 10.1 {+-} 0.6.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations

This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019–2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

ON THE ROBUSTNESS OF z = 0-1 GALAXY SIZE MEASUREMENTS THROUGH MODEL AND NON-PARAMETRIC FITS

We present the size-stellar mass relations of nearby (z = 0.01-0.02) Sloan Digital Sky Survey galaxies, for samples selected by color, morphology, Sérsic index n, and specific star formation rate. Several commonly employed size measurement techniques are used, including single Sérsic fits, two-component Sérsic models, and a non-parametric method. Through simple simulations, we show that the non-parametric and two-component Sérsic methods provide the most robust effective radius measurements, while those based on single Sérsic profiles are often overestimates, especially for massive red/early-type galaxies. Using our robust sizes, we show for all sub-samples that the mass-size relations are shallow at low stellar masses and steepen above ∼3-4 × 10{sup 10} M{sub ☉}. The mass-size relations for galaxies classified as late-type, low-n, and star-forming are consistent with each other, while blue galaxies follow a somewhat steeper relation. The mass-size relations of early-type, high-n, red, and quiescent galaxies all agree with each other but are somewhat steeper at the high-mass end than previous results. To test potential systematics at high redshift, we artificially redshifted our sample (including surface brightness dimming and degraded resolution) to z = 1 and re-fit the galaxies using single Sérsic profiles. The sizes of these galaxies before and after redshifting are consistent and we conclude that systematic effects in sizes and the size-mass relation at z ∼ 1 are negligible. Interestingly, since the poorer physical resolution at high redshift washes out bright galaxy substructures, single Sérsic fitting appears to provide more reliable and unbiased effective radius measurements at high z than for nearby, well-resolved galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Augmented Adam-Gibbs model for glass melt viscosity and configuration entropy as functions of temperature and composition

As the temperature of glass melt increases, its structure approaches the state of a simple liquid while the configuration entropy approaches a maximum value. We describe this gradual change using a power law function of inverse temperature. The Adam-Gibbs model for glass viscosity as a function of temperature and glass composition augmented in this way is greatly simplified when applied to common glass families occupying moderate composition regions, such as float glass or nuclear waste glasses, on which properties can be approximated as linear functions of composition. The parsimonious model thus obtained is preferable for use in optimizing glass formulation and mathematical modeling of glass melting and forming. For multicomponent glasses with N viscosity-affecting components, the augmented Adam-Gibbs model requires 2N + 3 adjustable parameters. The model efficacy is demonstrated by fitting the model to a viscosity-temperature-composition dataset for low-activity nuclear waste glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling ethanol/water adsorption in all-silica zeolites using the real adsorbed solution theory

A comprehensive set of single-component and binary isotherms were collected for ethanol/water adsorption into the siliceous forms of 185 known zeolites using grand-canonical Monte Carlo simulations. Using these data, a systematic analysis of ideal/real adsorbed-solution theory (IAST/RAST) was conducted and activity coefficients were derived for ethanol/water mixtures adsorbed in different zeolites based on RAST. It was found that activity coefficients of ethanol are close to unity while activity coefficients of water are larger in most zeolites, indicating a positive excess free energy of the mixture. This observation can be attributed to water/ethanol interactions being less favorable than water/water interactions in the single-component adsorption of water at comparable loadings. The deviation from ideal behavior can be highly structure-dependent but no clear correlation with pore diameters was identified. Furthermore, our analysis also demonstrates the following: (1) accurate unary isotherms in the low-loading regime are critical for obtaining physically sensible activity coefficients; (2) the global regression scheme to solve for activity model parameters performs better than fitting activity models to activity coefficients calculated locally at each binary state point; and (3) including the dependence on adsorption potential offers only a minor benefit for describing binary adsorption at the lowest fugacities. Finally, the Margules activity model was found incapable of capturing the non-ideal adsorption behavior over the entire range of fugacities and compositions in all zeolites, but for conditions typical of solution-phase adsorption, RAST predictions using zeolite-specific or even bulk Margules parameters provide an improved description compared to IAST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

MODELING THE HD 32297 DEBRIS DISK WITH FAR-INFRARED HERSCHEL DATA

HD 32297 is a young A-star ({approx}30 Myr) 112 pc away with a bright edge-on debris disk that has been resolved in scattered light. We observed the HD 32297 debris disk in the far-infrared and sub-millimeter with the Herschel Space Observatory PACS and SPIRE instruments, populating the spectral energy distribution (SED) from 63 to 500 {mu}m. We aimed to determine the composition of dust grains in the HD 32297 disk through SED modeling, using geometrical constraints from the resolved imaging to break the degeneracies inherent in SED modeling. We found the best fitting SED model has two components: an outer ring centered around 110 AU, seen in the scattered light images, and an inner disk near the habitable zone of the star. The outer disk appears to be composed of grains >2 {mu}m consisting of silicates, carbonaceous material, and water ice with an abundance ratio of 1:2:3 respectively and 90% porosity. These grains appear consistent with cometary grains, implying the underlying planetesimal population is dominated by comet-like bodies. We also discuss the 3.7{sigma} detection of [C II] emission at 158 {mu}m with the Herschel PACS instrument, making HD 32297 one of only a handful of debris disks with circumstellar gas detected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

ULTRAVIOLET SPECTROSCOPY OF TYPE IIB SUPERNOVAE: DIVERSITY AND THE IMPACT OF CIRCUMSTELLAR MATERIAL

We present new Hubble Space Telescope (HST) multi-epoch ultraviolet (UV) spectra of the bright Type IIb SN 2013df, and undertake a comprehensive analysis of the set of four SNe IIb for which HST UV spectra are available (SN 1993J, SN 2001ig, SN 2011dh, and SN 2013df). We find strong diversity in both continuum levels and line features among these objects. We use radiative-transfer models that fit the optical part of the spectrum well, and find that in three of these four events we see a UV continuum flux excess, apparently unaffected by line absorption. We hypothesize that this emission originates above the photosphere, and is related to interaction with circumstellar material (CSM) located in close proximity to the SN progenitor. In contrast, the spectra of SN 2001ig are well fit by single-temperature models, display weak continuum and strong reverse-fluorescence features, and are similar to spectra of radioactive {sup 56}Ni-dominated SNe Ia. A comparison of the early shock-cooling components in the observed light curves with the UV continuum levels which we assume trace the strength of CSM interaction suggests that events with slower cooling have stronger CSM emission. The radio emission from events having a prominent UV excess is perhaps consistent with slower blast-wave velocities, as expected if the explosion shock was slowed down by the CSM that is also responsible for the strong UV, but this connection is currently speculative as it is based on only a few events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: large-scale structure catalogues and measurement of the isotropic BAO between redshift 0.6 and 1.1 for the Emission Line Galaxy Sample

ABSTRACT We present the Emission Line Galaxy (ELG) sample of the extended Baryon Oscillation Spectroscopic Survey from the Sloan Digital Sky Survey IV Data Release 16. We describe the observations and redshift measurement for the 269 243 observed ELG spectra, and then present the large-scale structure catalogues, used for the cosmological analysis, and made of 173 736 reliable spectroscopic redshifts between 0.6 and 1.1. We perform a spherically averaged baryon acoustic oscillations (BAO) measurement in configuration space, with density field reconstruction: the data two-point correlation function shows a feature consistent with that of the BAO, the BAO model being only weakly preferred over a model without BAO (Δχ2 < 1). Fitting a model constrained to have a BAO feature provides a 3.2 per cent measurement of the spherically averaged BAO distance DV(zeff)/rdrag = 18.23 ± 0.58 at the effective redshift zeff = 0.845.

Raichoor, Anand↗