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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

PyXAS – an open-source package for 2D X-ray near-edge spectroscopy analysis

In the synchrotron X-ray community, X-ray absorption near-edge spectroscopy (XANES) is a widely used technique to probe the local coordination environment and the oxidation states of specific elements within a sample. Although this technique is usually applied to bulk samples, the advent of new synchrotron sources has enabled spatially resolved versions of this technique (2D XANES). This development has been extremely powerful for the study of heterogeneous systems, which is the case for nearly all real applications. However, associated with the development of 2D XANES comes the challenge of analyzing very large volumes of data. As an example, a single 2D XANES measurement at a synchrotron can easily produce ~106 spatially resolved XANES spectra. Conventional manual analysis of an individual XANES spectrum is no longer feasible. Here, a software package is described that has been developed for high-throughput 2D XANES analysis. A detailed description of the software as well as example applications are provided.

25 ENERGY STORAGE↗
DOE OSTI2025

Evaluating the feasibility of LA-ICP-TOF-MS for the analysis of environmental particle collections

Laser ablation-inductively coupled plasma-time-of-flight-mass spectrometry (LA-ICP-TOF-MS) was employed to rapidly analyze environmental particle samples collected using aerosol contaminate extractors (ACE). The ACE particle collectors were placed at various distances (0.5, 1.3, and 4.5 km) from a source that released Ru-bearing particles. Samples for measurement were then generated (as sub-samples) from the ACE collection plates via particle “lift off” with gunshot residue (GSR) tabs. The LA-ICP-TOF-MS method was employed such that 10+ samples could be analyzed in a single unattended analytical session. A 3 × 1 mm area of individual GSR tab samples were analyzed in less than 30 minutes. This provided spatially resolved elemental and isotopic measurements of the particulate content and confirmed the presence of Ru-bearing particles within the complex background environmental particle loading. As anticipated, measurements showed collectors closest to the source had the highest concentration of the released Ru-bearing particles, while all collectors, regardless of distance, contained similar levels of background particles (e.g., Fe and Sr). Sequential scanning electron microscopy – automated particle analysis (SEM-APA) and LA-ICP-TOF-MS analysis was employed for method validation and a demonstration of the multi-modal approach. The same 2-dimensional region was analyzed by both methods and the particles identified via SEM-APA were also detected using LA-ICP-TOF-MS, with 100% accuracy. Overall, LA-ICP-TOF-MS demonstrated its utility for rapid elemental and isotopic particle analysis from environmental air samples.

Manard, Benjamin T. [Oak Ridge National Laboratory↗
DOE OSTI2021

Effect of Groundwater Age and Recharge Source on Nitrate Concentrations in Domestic Wells in the San Joaquin Valley

Nitrate is one of the most abundant contaminants in groundwater globally, in the United States, and in California (CA). We studied well construction information, water chemistry, stable isotopes, and noble gases to understand how groundwater travel time and recharge source and mechanism control nitrate concentrations in domestic wells in the San Joaquin Valley (SJV), CA, a large semiarid, irrigated agricultural region. Using nonparametric statistics, we find a decreasing trend in nitrates with groundwater travel time and well depth. Samples collected from wells that are closer to rivers and that show indications of river water recharge, either low recharge temperature or low δ 18 O signature, have lower concentrations of nitrates than samples with isotopic signatures indicating mixed source or local precipitation recharge. The curbing effect of river water recharge on nitrate concentrations in domestic wells is similar for direct river recharge and water applied as irrigation. This suggests that irrigation with river water also has a diluting effect that reduces the concentration of nitrate found in groundwater. This conclusion supports the idea that flood-managed aquifer recharge may be considered for remediation of groundwater nitrate when designing replenishment of aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Bioenergy Feedstock Library Annual Summary Report

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at INL, is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use as well as samples generated from across U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2022 is to focus on the (1) publicly available analytical data and equipment tracked through the BFNUF, (2) physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities. This report highlights key statistics from FY22 and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗
DOE OSTI2023

Bioenergy Feedstock Library 2023 Annual Summary Report

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at INL, is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use as well as samples generated from across U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2023 is to focus on the updates to (1) publicly available analytical data and equipment tracked through the BFNUF, (2) physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available datasets created upon request from BETO, INL projects, or outside entities compared to the 2022 Bioenergy Feedstock Library Annual Summary Report. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗
DOE OSTI2024

Bioenergy Feedstock Library Annual Summary Report 2024

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at Idaho National Laboratory (INL), is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use, as well as samples generated from U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture-funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2024, similar to the 2023 Annual Summary Report , is to focus on the updates to: (1) publicly available analytical data and equipment tracked through the BFNUF, (2) significant increases in the physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities compared to the previous annual summary reports. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗
DOE OSTI2025

MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics

General proteomics research for fundamental science typically addresses laboratory- or patient-derived samples of known origin and composition. However, in a few research areas, such as environmental proteomics, clinical identification of infectious organisms, archeology, art/cultural history, and forensics, attributing the origin of a protein-containing sample to the organisms that produced it is a central focus. A small number of groups have approached this problem and developed software tools for taxonomic characterization and/or identification using bottom-up proteomics. Most such tools identify peptides via database search, and many rely on organism-specific peptides as markers. Our group recently introduced MARLOWE, a software tool for taxonomic characterization of unknown samples based on de novo peptide identification and signal-erosion-resistant strong peptides, which are shared peptides distributed in a taxonomy-dependent manner. In the current work, we further characterize the utility of MARLOWE using publicly available proteomics data from forensically-relevant samples. MARLOWE characterizes samples based on their protein profile, and returns ranked organism lists of potential contributors and taxonomic scores based on shared strong peptides between organisms. Overall, the correct characterization rate ranges between 44 and 100%, depending on the sample type and data acquisition parameters (with lower numbers associated with lower-quality data sets). MARLOWE demonstrates successful characterization of true contributors and close relatives, and provides sufficient specificity to distinguish certain microbial species. MARLOWE demonstrates its ability to provide insight into potential taxonomic sources for a wide range of sample types without prior assumptions about sample contents. As a result, this approach can find utility in forensic science and also broadly in bioanalytical applications that utilize proteomics approaches for taxonomic characterization.

Bacteria↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

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

Implementation and verification of PyNE R2S with DAG-OpenMC

The mesh-based Rigorous-Two-Step (R2S) method has been widely used in the accurate estimation of the shutdown dose rate (SDR) of fusion systems. Several mesh-based R2S code has been implemented based on Monte Carlo particle transport code MCNP5 or DAG-MCNP5 and inventory calculation code such as FISPACT-II, ALARA or ACAB. Recently, the OpenMC, a community-developed Monte Carlo particle transport code, implemented the photon particle transport capability, which enables OpenMC to be used in R2S. In this paper, PyNE R2S is extended with the support of DAG-OpenMC, i.e., OpenMC with DAGMC. Modifications that allow PyNE to read the flux result in the state point file of OpenMC has been implemented to PyNE R2S workflow. A custom source routine of OpenMC that reads the photon source file from PyNE R2S and sampling photon particle in OpenMC photon transport has been implemented in OpenMC. With these modifications, PyNE R2S is now capable of performing R2S calculations with both DAG-MCNP5 and DAG-OpenMC. The ITER FNG dose rate benchmark problem has been used to validate the code. The FNG neutron source has been modified for neutron transport with DAG-OpenMC. The shutdown dose rate of 19 cooling times has been calculated and compared with the experimental data and the computational results of other R2S codes. The results of PyNE R2S with DAG-OpenMC show satisfactory agreement with the experimental data and other computational results. Therefore, we consider PyNE R2S with DAG-OpenMC is a reliable code to calculate the SDR of fusion systems.

fusion↗
DOE OSTI2022

Isotopic discrimination of natural and anthropogenic perchlorate sources in groundwater in a semi-arid region of northeastern Oregon (USA)

Perchlorate (ClO 4 - ) has synthetic and natural sources. Synthetic ClO 4 - is released to the environment from its use as an oxidant in military and aerospace applications, and from its presence in a variety of common commercial products, such as safety flares, chlorate herbicides, and fireworks. Natural sources of ClO 4 - in the environment include imported nitrate fertilizers derived from salt deposits in the Atacama Desert of Chile and indigenous natural ClO 4 - that accumulates in unsaturated soils and groundwaters in other arid and semi-arid environments, largely from atmospheric deposition. The stable isotope ratios of chlorine ( 37 Cl/ 35 Cl) and oxygen ( 18 O/ 16 O, 17 O/ 16 O) and the isotopic abundance of radioactive 36 Cl in ClO 4 - can be used to discriminate these different sources. Perchlorate was previously detected at relatively high concentrations (3.8–34.7 μg/L) in groundwater from many wells in the Boardman-Umatilla area near the Columbia River in northeastern Oregon, which is a semi-arid, highly agricultural, heavily irrigated area that includes several past and current military installations. Eight representative groundwater wells were sampled throughout this region and isotopic characteristics of ClO 4 - collected from each well were measured along with other chemical and isotopic parameters including tritium and other groundwater age indicators. We report isotopic data indicate that indigenous natural ClO 4 - was present in groundwater from all sampled wells and was the predominant source in five of the wells. Synthetic ClO 4 - was present in the three remaining wells with natural ClO 4 - , and a minor fraction of Atacama-fertilizer-derived ClO4- was indicated in one of the wells. Data from this study expand the geographic area of the USA in which indigenous natural ClO 4 - has been detected to include the semi-arid northwest. This study also illustrates the role of irrigation recharge as a mechanism for producing relatively high concentrations of indigenous natural ClO 4 - in groundwater by flushing accumulated salts from the unsaturated zone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Performance Improvement of LTS Undulators for Synchrotron Light Sources

The joint expertise of ANL and FNAL has led to the production of $\text{Nb}_{3}\text{Sn}$ undulator magnets in operation in the ANL Advanced Photon Source (APS). These magnets showed performance reproducibility close to the short sample limit, and a design field increase of 20% at 820 A. However, the long training did not allow obtaining the expected 50% increase of the on-axis magnetic field with respect to the ∼1 T produced at 450 A current in the ANL NbTi undulator. To address this, 10-pole long undulator prototypes were fabricated, and CTD-101K was replaced as impregnation material with TELENE, an organic olefin-based thermosetting dicyclopentadiene resin produced by RIMTEC Corporation, Japan. Training and magnet retraining after a thermal cycle were nearly eliminated, with only a couple of quenches needed before reaching short sample limit at over 1,100 A. TELENE will enable operation of $\text{Nb}_{3}\text{Sn}$ undulators much closer to their short sample limit, expanding the energy range and brightness intensity of light sources. TELENE is Co-60 gamma radiation resistant up to 7–8 MGy, and therefore already applicable to impregnate planar, helical and universal devices operating in lower radiation environments than high energy colliders.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Demonstration of a laser-driven, narrow spectral bandwidth x-ray source for collective x-ray scattering experiments

X-ray Thomson scattering (XRTS) is a powerful diagnostic technique that involves an x-ray source interacting with a dense plasma sample, resulting in a spectrum of elastically and inelastically scattered x-rays. Depending on the plasma conditions, one can measure a range of parameters from the resulting spectrum, including plasma temperature, electron density, and ionization state. To achieve sensitivity to collective electron oscillations, XRTS measurements require limited momentum transfer where the spectral separation of elastic and inelastic scattering is small. Such measurements require an x-ray probe source with a narrow bandwidth in order to reduce the spectral overlap between scattering contributions, allowing for the different features to be more precisely deconvolved. In this investigation, we discuss the theory behind how the bandwidth for a common XRTS probe, Zn He-α emission at 9 keV, can be reduced using a Cu K-edge filter.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quantifying uncertainty in uranium concentration measurements via K-edge densitometry

This study quantifies the uncertainty in uranium concentration predictions of fluoride and chloride-based salts within a steel pipe using K-edge densitometry. Modeling and simulation was conducted with the Monte Carlo N-Particle Transport (MCNP) code. The quality of of this technique’s prediction in a pipe requires proper characterization of the pipe’s thickness, which is dependent on the source size and axial offset from the pipe centerline. The thickness was determined as either the center-line thickness seen by the X-ray source or an average value determined through random sampling. Generally, the predicted concentrations were slightly better at lower offset with the random sampling thickness and using the center-line thickness for the highest offsets. For a line-beam source and varying axial offsets, the relative error of concentration was within 1% of the true value but uncertainty increased by 2 orders of magnitude. Similarly, for no axial offset, the relative error was significantly less than 1% while no trend for uncertainty was found. However, at the largest possible offset for a given source size, the concentrations become erroneous and greater than the allowable 1% relative error. Furthermore, high offsets tended to increase the variance of the transmission spectra by 3 orders of magnitude.

Characterization and Analytical Technique↗
DOE OSTI2022

XXL-HSC: An updated catalogue of high-redshift ( z ≥ 3.5) X-ray AGN in the XMM-XXL northern field

X-rays offer a reliable method to identify active galactic nuclei (AGNs). However, in the high-redshift Universe, X-ray AGNs are poorly sampled due to their relatively low space density and the small areas covered by X-ray surveys. In addition to wide-area X-ray surveys, it is important to have deep optical data in order to locate the optical counterparts and determine their redshifts. Here, in this work, we built a high-redshift (z ≥ 3.5) X-ray-selected AGN sample in the XMM-XXL northern field using the most updated [0.5–2 keV] catalogue along with a plethora of new spectroscopic and multi-wavelength catalogues, including the deep optical Subaru Hyper Suprime-Cam (HSC) data, reaching magnitude limits i ~ 26 mag. We selected all the spectroscopically confirmed AGN and complement this sample with high-redshift candidates that are HSC g- and r-band dropouts. To confirm the dropouts, we derived their photometric redshifts using spectral energy distribution techniques. We obtained a sample of 54 high-z sources (28 with spec-z), the largest in this field so far (almost three times larger than in previous studies), and we estimated the possible contamination and completeness. We calculated the number counts (log N-log S) in different redshift bins and compared our results with previous studies and models. We provide the strongest high-redshift AGN constraints yet at bright fluxes (f 0.5 – 2 keV > 10 –15 erg s –1 cm –2 ). The samples of z ≥ 3.5, z ≥ 4, and z ≥ 5 are in agreement with an exponential decline model similar to that witnessed at optical wavelengths. Our work emphasises the importance of using wide-area X-ray surveys with deep optical data to uncover high-redshift AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Trace Impurities Identified as Forensic Signatures in CMX-5 Fuel Pellets Using X-ray Spectroscopic Techniques

We report that small-particle analysis is a highly promising emerging forensic tool for analysis of interdicted special nuclear materials. Integration of microstructural, morphological, compositional, and molecular impurity signatures could provide significant advancements in forensic capabilities. We have applied rapid, high-sensitivity, hard X-ray synchrotron chemical imaging to analyze impurity signatures in two differently fabricated fuel pellets from the 5th Collaborative Materials Exercise (CMX5) of the IAEA Nuclear Forensics International Working Group. The spatial distributions, chemical compositions, and morphological and molecular characteristics of impurities were evaluated using X-ray absorption near-edge structure (XANES) and X-ray fluorescence chemical imaging to discover principal impurities, their granularity, particle sizes, modes of occurrence (distinct grains vs incorporation in the UO 2 lattice), and sources and mechanisms of incorporation. Differences in UO 2+x stoichiometry were detected at the microscale in nominally identical UO 2 ceramics (CMX5-A and CMX5-B), implying the presence of multiple UO 2 host phases with characteristic microstructures and feedstock compositions. Al, Fe, Ni, W, and Zr impurities and integrated impurity signature analysis identified distinctly different pellet synthesis and processing methods. For example, two different Al, W, and Zr populations in the CMX5-B sample indicated a more complex processing history than the CMX5-A sample. K-edge XANES measurements reveal both metallic and oxide forms of Fe and Ni but with different proportions between each sample. Altogether, these observations suggest multiple sources of impurities, including fabrication (e.g., force-sieving) and feedstock (mineral oxides). This study demonstrates the potential of synchrotron techniques to integrate different signatures across length scales (angstrom to micrometer) to detect and differentiate between contrasting UO 2 fuel fabrication techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Design and Characterization of an Extremely-Sensitive, Large-Volume Gamma-Ray Spectrometer for Environmental Samples

A large volume gamma spectrometer was designed and constructed to analyze foodstuffs and environmental samples having low radionuclide concentrations. This system uses eight 11-cm × 42.5-cm × 5.5-cm NaI(Tl) detectors, chosen due to their relatively high sensitivity and availability and arranged in an octagonal configuration. The sensitive volume of the system is ~28 cm in diameter and ~42 cm deep. Shielding consists of an 86-cm × 86-cm square, 64-cm-tall lead brick enclosure with 18-cm-thick lead walls lined by 0.3-cm-thick copper plates. An aluminum top was machined to suspend the detectors within this shield. The shielding reduces background counts by 72% at 100 keV and 42% at 1,000 keV. The positional variability in sensitivity of the well was determined by both simulation and experiment. A 2.1-L volume of nearly uniform sensitivity, varying less than 10%, exists in the well's center. Energy resolutions of 14.6% and 7.8% were measured for 241 Am and 137 Cs, respectively. Energy resolution shows a 0.2% variation for both 241 Am and 137 Cs as a function of position within all regions of the well’s central sensitive volume. Dead time was also determined to be less than 35% for all sources measured in the system, the largest of which had an activity of 1,760 kBq. Simulated results for various source geometries show higher counts for smaller samples, especially at lower energies due to less attenuation of low energy photons. In conclusion, minimum detectable activities were determined for all source energies used, less than 5.1 Bq kg -1 for reasonable background and sample counting times.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗
DOE OSTI2020

Propagating sample variance uncertainties in redshift calibration: simulations, theory, and application to the COSMOS2015 data

ABSTRACT Cosmological analyses of galaxy surveys rely on knowledge of the redshift distribution of their galaxy sample. This is usually derived from a spectroscopic and/or many-band photometric calibrator survey of a small patch of sky. The uncertainties in the redshift distribution of the calibrator sample include a contribution from shot noise, or Poisson sampling errors, but, given the small volume they probe, they are dominated by sample variance introduced by large-scale structures. Redshift uncertainties have been shown to constitute one of the leading contributions to systematic uncertainties in cosmological inferences from weak lensing and galaxy clustering, and hence they must be propagated through the analyses. In this work, we study the effects of sample variance on small-area redshift surveys, from theory to simulations to the COSMOS2015 data set. We present a three-step Dirichlet method of resampling a given survey-based redshift calibration distribution to enable the propagation of both shot noise and sample variance uncertainties. The method can accommodate different levels of prior confidence on different redshift sources. This method can be applied to any calibration sample with known redshifts and phenotypes (i.e. cells in a self-organizing map, or some other way of discretizing photometric space), and provides a simple way of propagating prior redshift uncertainties into cosmological analyses. As a worked example, we apply the full scheme to the COSMOS2015 data set, for which we also present a new, principled SOM algorithm designed to handle noisy photometric data. We make available a catalogue of the resulting resamplings of the COSMOS2015 galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗