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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Collecting and Processing Earth Science Data Metrics at NASA ESDIS

Since the launch of Terra satellite in 1999, the number of Earth Science remote sensing data products created and distributed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS) has increased from a few hundred to nearly ten thousand. NASA's Earth Science Data and Information System (ESDIS) Metrics System (EMS) collects metrics on data ingest, archive, and distribution by its Distributed Active Archive Centers (DAACs) and the Science Investigator-led Systems (SIPS), known as Data Providers. These metrics are critical in helping NASA management as well as data producers in resource planning and gaining a wide range of knowledge of data users and data usage.EMS receives flat files, or log files of data archive, ingest, and distribution either in their raw format, such as Apache web logs, or text files of log records formatted by the Data Providers. Tens of millions of records are processed each day to extract metrics on data products, user information, distribution protocols and services, and so on. The metrics are then made available to designated parties.This presentation provides an overview of the EMS processing workflow and improvement efforts made in recent years to handle ever-increasing number of data records and new metrics requirements, discusses several key steps including mapping log records to data products and identifying user communities along with geo-distribution, and demonstrates typical metrics capabilities produced by the EMS system. Challenges and potential approaches to improve the system are also discussed.

Pan, Jianfu↗
DOE OSTI2013

Determination of the Distribution and Inventory of Radionuclides within a Savannah River Site Waterway - 13202

An investigation was conducted to evaluate the radionuclide inventory within the Lower Three Runs (LTR) Integrator Operable Unit (IOU) at the U.S. Department of Energy's (DOE's) Savannah River Site (SRS). The scope of this effort included the analysis of previously existing sampling and analysis data as well as additional stream bed and flood plain sampling and analysis data acquired to delineate horizontal and vertical distributions of the radionuclide as part of the ongoing SRS environmental restoration program, and specifically for the LTR IOU program. While cesium-137 (Cs-137) is the most significant and abundant radionuclide associated with the LTR IOU it is not the only radionuclide, hence the scope included evaluating all radionuclides present and includes an evaluation of inventory uncertainty for use in sensitivity and uncertainty analyses. The scope involved evaluation of the radionuclide inventory in the P-Reactor and R-Reactor cooling water effluent canal systems, PAR Pond (including Pond C) and the flood plain and stream sediment sections of LTR between the PAR Pond Dam and the Savannah River. The approach taken was to examine all of the available Sediment and Sediment/Soil analysis data available along the P- and R-Reactor cooling water re-circulation canal system, the ponds situated along those canal reaches and along the length of LTR below Par Pond dam. By breaking the IOU into a series of sub-components and sub-sections, the mass of contaminated material was estimated and a representative central concentration of each radionuclide was computed for each compartment. The radionuclide inventory associated with each sub-compartment was then aggregated to determine the total radionuclide inventory that represented the full LTR IOU. Of special interest was the inventory of Cs-137 due to its role in contributing to the potential dose to an offsite member of the public. The overall LTR IOU inventory of Cs-137 was determined to be 2.87 E+02 GBq, which is similar to two earlier estimates. This investigation provides an independent, ground-up estimate of Cs-137 inventory in LTR IOU utilizing the most recent field data. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

GPS-Based Gamma Survey for Characterizing and Decommissioning NORM Sites - 20389

Gamma survey techniques are an especially powerful decommissioning tool at naturally occurring radioactive material (NORM) sites due to both the low cost to obtain data over a large spatial scale and the abundance of gamma emitters in the uranium and thorium decay series. Gamma surveys are executed by coupling a detector - most often a sodium iodide crystal - to a global positioning system (GPS), then reporting a location and gross gamma reading coincidentally to a data logger. Systems may be carried by workers or mounted to a car, all-terrain vehicle, or unmanned aerial system (UAS). The resulting data set provides a high-resolution but low precision map of the gamma radiation field over the area surveyed. Frequently this map is also correlated to soil concentrations of NORM radionuclides (most often, Ra-226) and/or exposure rate. Gamma survey parameters such as movement speed, transect spacing, and data logging frequency define the spatial resolution of the resulting surface, and can be optimized depending on the desired survey sensitivity. This paper examines gamma survey as a tool for decommissioning NORM sites and provides an overview of current gamma survey technology designed to improve the efficiency and effectiveness of the decommissioning process. Topics to be discussed in the paper include: - An overview of gamma survey systems, and the utility of different delivery vehicles depending on desired cost, desired spatial resolution, and site topography. - The influence of physical detector characteristics on detection sensitivity and survey planning. - The tradeoff between high-resolution and large spatial extent, but inherently uncertain data, and low-resolution, low spatial extent, but highly certain data, as well as the specific utility of each of these types of data during NORM facility decommissioning. - Confounding variables that may limit the utility of gamma survey at some sites (e.g., radon gas and spatial heterogeneity / hot spots), and methods to plan for and control these conditions. Results show that the confounding variables, such as radon and data output can greatly influence the overall data quality associated with the decommissioning process. In addition, the use of real-time and aerial survey platforms provides a method for ensuring proper spatial extent of the data. When applied thoughtfully, gamma survey is a powerful tool for detecting NORM radionuclides in the environment and a cost-effective technique for identifying areas requiring remediation. However, entities performing or using gamma survey as a decommissioning tool must be aware of both its advantages and its limitations before basing remediation or regulatory action on gamma survey results. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

FORGE STRESS annual report

The project's goal is to combine high-fidelity numerical models and true-triaxial block fracturing tests at high temperatures to understand the relationship between in situ stress, thermal effects, wellbore orientations and hydraulic fracture patterns. The numerical models are calibrated against field data, such as well pressures and microseismic data, and employed to estimate the in situ stress at the FORGE site. Laboratory experiments investigate the complex physics driving hydraulic fracture nucleation in EGS, enhancing understanding of the role of parameters like temperature, well orientation, and stress. Additionally, they are employed to validate some of the numerical tools used in the project. The project will have a significant impact by: (1) improving the characterization of the in-situ stress field at FORGE; (2) demonstrating the use of high-fidelity modeling tools for EGS; (3) providing a unique set of high-temperature hydraulic fracturing results to identify key components for in-situ stress estimation, validate current theories, and propose new ones; (4) offering a validated set of numerical tools within an open-source simulation framework, GEOS, that will be available to any future user.

15 GEOTHERMAL ENERGY↗
NASA NTRS2018

The Ocean Carbon States Database: A Proof-of-Concept Application of Cluster Analysis in the Ocean Carbon Cycle

In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the 'ocean carbon states', as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical-subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air-sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias.

carbon cycle↗
NASA NTRS2006

Compressing Image Data While Limiting the Effects of Data Losses

ICER is computer software that can perform both lossless and lossy compression and decompression of gray-scale-image data using discrete wavelet transforms. Designed for primary use in transmitting scientific image data from distant spacecraft to Earth, ICER incorporates an error-containment scheme that limits the adverse effects of loss of data and is well suited to the data packets transmitted by deep-space probes. The error-containment scheme includes utilization of the algorithm described in "Partitioning a Gridded Rectangle Into Smaller Rectangles " (NPO-30479), NASA Tech Briefs, Vol. 28, No. 7 (July 2004), page 56. ICER has performed well in onboard compression of thousands of images transmitted from the Mars Exploration Rovers.

Kiely, Aaron↗
DOE OSTI2024

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2015

sRecovery Act: Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO 2 Storage

This study focuses on evaluating the feasibility and suitability of using the Jurassic/Triassic (J/TR) sediments of the South Georgia Rift basin (SGR) for CO 2 storage in southern South Carolina and southern Georgia The SGR basin in South Carolina (SC), prior to this project, was one of the least understood rift basin along the east coast of the U.S. In the SC part of the basin there was only one well (Norris Lightsey #1) the penetrated into J/TR. Because of the scarcity of data, a scaled approach used to evaluate the feasibility of storing CO 2 in the SGR basin. In the SGR basin, 240 km (~149 mi) of 2-D seismic and 2.6 km2 3-D (1 mi2) seismic data was collected, process, and interpreted in SC. In southern Georgia 81.3 km (~50.5 mi) consisting of two 2-D seismic lines were acquired, process, and interpreted. Seismic analysis revealed that the SGR basin in SC has had a very complex structural history resulting the J/TR section being highly faulted. The seismic data is southern Georgia suggest SGR basin has not gone through a complex structural history as the study area in SC. The project drilled one characterization borehole (Rizer # 1) in SC. The Rizer #1 was drilled but due to geologic problems, the project team was only able to drill to 1890 meters (6200 feet) instead of the proposed final depth 2744 meters (9002 feet). The drilling goals outlined in the original scope of work were not met. The project was only able to obtain 18 meters (59 feet) of conventional core and 106 rotary sidewall cores. All the conventional core and sidewall cores were in sandstone. We were unable to core any potential igneous caprock. Petrographic analysis of the conventional core and sidewall cores determined that the average porosity of the sedimentary material was 3.4% and the average permeability was 0.065 millidarcy. Compaction and diagenetic studies of the samples determined there would not be any porosity or permeability at depth in SC. In Georgia there appears to be porosity in the J/TR section based on neutron log porosity values. The only zones in Rizer #1 that appear to be porous were fractured diabase units where saline formation water was flowing into the borehole. Two geocellular models were created for the SC and GA study area. Flow simulation modeling was performed on the SC data set. The injection simulation used the newly acquired basin data as well as the Petrel 3-D geologic model that included geologic structure. Due to the new basin findings as a result of the newly acquired data, during phase two of the modeling the diabase unit was used as reservoir and the sandstone units were used as caprock. Conclusion are: 1) the SGR basin is composed of numerous sub-basins, 2) this study only looked at portions of two sub-basins, 3) in SC, 30 million tonnes of CO 2 can be injected into the diabase units if the fracture network is continuous through the units, 4) due to the severity of the faulting there is no way of assuring the injected CO 2 will not migrate upward into the overlying Coastal Plain aquifers, 5) in Georgia there appears to porous zones in the J/TR sandstones, 6) as in SC there is faulting in the sub-basin and the seismic suggest the faulting extends upward into the Coastal Plain making that area not suitable for CO 2 sequestration, 7) the complex faulting observed at both study areas appear to be associated with transfer fault zones (Heffner 2013), if sub-basins in the Georgia portion of the SGR basin can be located that are far away from the transfer fault zones there is a strong possibility of sequestering CO 2 in these areas, and 9) the SGR basin covers area in three states and this project only studied two small areas so there is enormous potential for CO 2 sequestration in other portions the basin and further research needs to be done to find these areas.

58 GEOSCIENCES↗
DOE OSTI2024

Single-channel and single-energy partial-wave analysis with continuity improved through minimal phase constraints

Single-energy partial-wave analysis has often been applied as a way to fit data with minimal model dependence. However, remaining unconstrained, partial waves at neighboring energies will vary discontinuously because the overall amplitude phase cannot be determined through single-channel measurements. This problem can be mitigated through the use of a constraining penalty function based on an associated energy-dependent fit. However, the weight given to this constraint results in a biased fit to the data. In this paper, for the first time, we explore a constraining function which does not influence the fit to data. The constraint comes from the overall phase found in multichannel fits which, in the present study, are the Bonn-Gatchina and Jülich-Bonn multichannel analyses. The data are well reproduced and weighting of the penalty function does not influence the result. The method is applied to K⁢Λ photoproduction data and all observables can be maximally well reproduced. While the employed multichannel analyses display very different multipole amplitudes, we show that the major difference between two sets of multipoles can be related to the different overall phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2018

NOAA-20 VIIRS Thermal Emissive Bands On-Orbit Performance

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument onboard the NOAA-20 satellite (launched on November 18, 2017) started to collect Earth-view data after its nadir door opened on December 13, 2017. Seven of the VIIRS bands, I4-5 and M12-16 are thermal emissive bands (TEBs), covering a spectral range from 3.6 to 12.5 meters. They began collecting valid data after the cold focal plane assembly (CFPA) cooled down to its nominal operating temperature on January 6, 2018. This paper will present the performance of each TEB, including calibration coefficients, noise equivalent differential temperature (NEdT), on-orbit calibration coefficient estimates from scheduled onboard blackbody warm-up and cool-down (WUCD) data, as well as related telemetry temperatures. Several methods are tested and compared in the WUCD data analysis for estimating the calibration coefficients. Based on the preliminary results, the NEdT of each band is well below the design specification and very close to that of the VIIRS onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The detector gains appear stable for bands on the short- and mid-wave infrared CFPA, whereas the detector gains have larger than expected degradation for bands on the long-wave infrared CFPA during the early mission. All TEB-related telemetry temperatures are stable. The on-orbit performance of NOAA-20 VIIRS TEB is compared with VIIRS onboard the SNPP.

Thermal Emissive Bands (TEB)↗
NASA NTRS2011

Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to Soil Moisture and Ocean salinity (SMOS) mission validation and the pre-launch assessment of Soil Moisture and Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (Leaf Area Index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Besides, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km x 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data. The Radio frequency interference (RFI) observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of SMOS soil moisture product matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates are more closely correlated with measured soil moisture.

Magagi, Ramata↗
DOE OSTI2021

Quasi-differential neutron induced neutron emissions from 235 U, and 239 Pu

Uncertainty in nuclear reaction cross sections, angular distributions, and other nuclear data directly impact how well simulations of nuclear systems represent physical observations. Here, to determine how well the nuclear data in ENDF/B-VIII.0, JEFF-3.3, and JENDL-4.0 evaluations describe the physical behaviour of 235 U, and 239 Pu when subjected to a neutron flux, the neutron emission spectrum was measured for carbon, 93.0% 235 U, and 93.9% 239 Pu samples, and compared against detailed MCNP6 simulations. The measurements were performed at the Los Alamos Neutron Science Center using a quasi-differential method previously developed at Rensselaer Polytechnic Institute. The measurement spanned 0.82–20 MeV and 30–150 degrees. The measurements show there are a significant number of discrepancies between library predictions of the neutron yield and physical observation. A few of the main discrepancies found are described in this paper. Based on these results a new evaluation utilizing these results for carbon, 235 U, and 239 Pu is recommended.

235U↗
DOE OSTI2021

Application of spectroscopic evidence to diffuse layer model (DLM) parameter estimation for cation adsorption onto ferrihydrite in single- and bi-solute systems

The diffuse layer model (DLM) is one of the most frequently used surface complexation models (SCM) for predicting cation adsorption onto ferrihydrite. However, the DLM with its existing database sometimes fails to predict cation adsorption, especially in multi-solute systems. Notably, the failure is often attributed to inaccurate selection of the surface complexes and/or underestimation of the site density for DLM formulation. DLM simulations of batch adsorption data conducted with cadmium, copper, lead, and zinc on ferrihydrite in CO2 free systems demonstrates the ability of the DLM to fit single-solute data reasonably well but highlights its limitations with respect to predicting bi-solute data. Modifications to the DLM were made in two steps. First, spectroscopic evidence was used to guide cation complexation reactions at the ferrihydrite surface. Second, surface characteristics (reactive site density, specific surface area, and acidity constants) of ferrihydrite were updated according to recent literature. The results from this study suggest that when spectroscopic verification is employed and surface site density is increased, a simple two-site DLM can predict cation adsorption on ferrihydrite in single-solute systems for pH data above 3.5 and in most of the bi-solute systems tested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Use of carbon stable isotopes to monitor biostimulation and electron donor fate in chromium-contaminated groundwater

Hexavalent chromium Cr(VI) is a common inorganic contaminant in industrial areas and represents a serious threat to human health due its toxicity. Here we report experimental results from a field-scale investigation of Cr(VI) bio-immobilization at Hanford 100H reservation, a U.S Department of Energy facility (Washington State, USA). Microbial Cr(VI) reduction was stimulated via injection of a 13 C-labeled sodium lactate solution into the high-permeability aquifer consisting of gravel and coarse sand sediments. Concentrations and carbon isotope ratios of metabolites, including dissolved inorganic carbon and total organic carbon, and compound-specific analysis of acetate and propionate, together with phospholipid fatty acids (biomass) have been analyzed to help provide an understanding of the predominant redox processes accompanying Cr(VI) reduction. Results of our study indicate that the injection of an electron donor caused a sharp decrease of Cr(VI) concentration from ~ 32 to ~ 10 nM. Cr(VI) reduction was associated with a decrease in the concentration of carboxylic acids, such as lactate (~ 6 mM to undetectable), propionate (~ 9 mM to undetectable), and acetate (~ 6 mM to undetectable), as well as dissolved inorganic carbon (30 to 10 mM C). Carbon isotope data indicate carbon transfers from the original substrate to organic byproducts and mineralized carbon. Concentrations of metabolites and stable isotope data as well as carbon isotope mass balance calculations were used to monitor biologically mediated reduction of Cr(VI).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Beyond optimization—supervised learning applications in relativistic laser-plasma experiments

We explore the applications of machine learning techniques in relativistic laser-plasma experiments beyond optimization purposes. We predict the beam charge of electrons produced in a laser wakefield accelerator given the laser wavefront change caused by a deformable mirror. Machine learning enables feature analysis beyond merely searching for an optimal beam charge, showing that specific aberrations in the laser wavefront are favored in generating higher beam charges. Supervised learning models allow characterizing the measured data quality as well as recognizing irreproducible data and potential outliers. Furthermore, we also include virtual measurement errors in the experimental data to examine the model robustness under these conditions. This work demonstrates how machine learning methods can benefit data analysis and physics interpretation in a highly nonlinear problem of relativistic laser-plasma interaction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Stacked reverberation mapping of high-redshift quasars in DESI. I. Feasibility analysis

The broad-line region of quasars has long been probed by reverberation mapping techniques that measure time lags between continuum and broad emission-line variations. Stacked reverberation mapping has been proposed as a less observationally expensive alternative to traditional methods. This ensemble approach also reduces biases from small-number statistics. The Dark Energy Spectroscopic Instrument (DESI) is conducting the most extensive spectroscopic survey of quasars to date. We create mock light curves emulating expected DESI quasar observations at redshifts $1.48\lt z\lt 5.2$ and luminosities $44.68 \le \log \lambda L_{1350 \mathring{\rm A}{}} / \mathrm{erg\, s^{-1}} \le 45.99$ to test stacked reverberation mapping feasibility using sparse spectroscopic data paired with well-sampled photometric data. The pipeline, using the lag estimation code JAVELIN (Just Another Vehicle for Estimating Lags In Nuclei), successfully recovers the simulated C IV lags within 1σ of the true values using spectroscopic light curves composed of only a few spectral epochs (2–10) with irregular cadences. We investigate how observational factors, including C IV flux error magnitude, number of stacked quasars, and spectral epoch count, affect performance. This work motivates a pathway for future stacked reverberation mapping projects with large-scale spectroscopic surveys of quasars having $\ge 2$ spectroscopic observations. Our results suggest an economical alternative for constraining and extending the radius–luminosity relation to higher redshifts and luminosities. Subsequently, this relation can be employed more reliably in single-epoch black hole mass measurements and quasar cosmology in these distant regimes.

quasars: general, quasars: supermassive black hole↗
DOE OSTI2018

Measurement of the In 115 ( γ , γ ' ) In 115 m inelastic scattering cross section in the 1.8 to 3.7 MeV energy range with monoenergetic photon beams

For the first time the excitation cross section of $^{115}\mathrm{In}$ to its first excited state at 336.24 keV has been measured with monoenergetic photon beams at 15 energies between 1.8 and 3.7 MeV. The measurements were performed at the High-Intensity Gamma-ray Source ($\mathrm{HI}{\gamma}\mathrm{S}$) facility with natural In targets and incident photon fluxes ranging from $0.7\times{}{10}^{7}{\gamma}/({\mathrm{cm}}^{2}{s})$ to $3.2\times{}{10}^{7}{\gamma}/({\mathrm{cm}}^{2}{s})$. The inelastic scattering cross section was obtained from the yield of the 336.24 keV deexcitation ${\gamma}$ rays. The cross-section values varied between < 0.05 and 28.7 ${\mu}\mathrm{b}$ at 1.8 and 3.7 MeV, respectively. Compared to standard photon inelastic scattering cross-section data in this energy range of medium-mass nuclei, these extremely small values are not completely unexpected, given the nature of the low-lying nuclear levels of $^{115}\mathrm{In}$. Model calculations, however, overestimate the measured cross-section data by approximately one order of magnitude. Using different choices for the $E1 {\gamma}$-ray strength function, the data can be well described. Finally, the data are important for improving our knowledge of the level scheme of $^{115}\mathrm{In}$, especially spin and parity assignments of already known states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗