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Distribution Development for the RDX Regional Model at Los Alamos National Laboratory - 20385

Representing uncertainty in model inputs often means finding a balance between uncertainty and physical reality. Developing wide distributions may seem conservative in principle, but this approach may lead to unrealistic model results. Characterizing the current state of knowledge of stochastic inputs presents many challenges, especially if the data available are limited or have limited relevance to the site. Relationships among these inputs may also be important to represent but are typically complex or difficult to define. Often special adjustments must be made to account for reduced credibility in particular data. If parameters are strongly related to one another, a correlation structure may be developed for input to the model. Other techniques such as regression models may be used to incorporate relationships between the information available and the desired parameters. The process of developing distributions must consider details of the model in terms of what the distribution is meant to represent. This paper uses the example of a probabilistic fate and transport model for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in the regional aquifer at Los Alamos National Laboratory (LANL). For many parameters, a single draw is applied to all space and time over which the model is run, for a single iteration. This simplification is often made for many reasons, and can often be beneficial, but also adds additional complexity in the distribution development process. Defining the distributional goals as they relate to the modeling process is an important step, which should take place prior to evaluation of the data. Usually, the distributions developed are meant to characterize the average value of the parameter over the spatial and temporal domain of the model. Distribution development requires consideration of many sources of information on the parameter where available, ideally from multiple references. Examples of different sources include data from different references but also from different conditions, measurement methods, or experimental types. Depending on these conditions and the reliability or relevance of particular references, different sources of data may each contribute valuable information but have varying relevance to the site. In these cases, weighting data unequally is a useful way to incorporate this information. As an example, aqueous dispersivity data are available for a variety of rock types. Only a few values are available for the desired rock type, and this is not enough to develop a distribution. Therefore, dispersivity values from other rock types are included in distribution development but are down-weighted such that the best data have the most influence on the distribution developed. In another case, K{sub d} distributions in the model are meant to represent a known composition of multiple soil types. Data from these materials are weighted accordingly to develop a distribution for the weighted average K{sub d} across soil types. Other cases include varying reliability of different sources, and weighting data according to the confidence in these sources. In some cases, input parameters are correlated with one another. An example is advective porosity, which is positively correlated with total porosity and must be less than total porosity. Paired data with both parameters must exist to discern the relationship between the two parameters and if it is necessary to build a correlation structure into the model. In general, correlated parameters may be represented in the model by a multivariate distribution, or perhaps more desirably, capturing the correlation within the developed distributions which may be treated as independent from one another. In the example of porosity, this can be done by transforming advective porosity into a proportion of total porosity which may be drawn independently from the distribution of total porosity. This paper explores how complex data and correlations can be incorporated to meet the distributional goals of the model, using the RDX regional model as a detailed example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Geochemical advances in Arctic Alaska oil typing – North Slope oil correlation and charge history

The Arctic Alaska petroleum province is geologically and geochemically complex. Mixed hydrocarbon charge from multiple source rocks and/or levels of thermal maturity is common within an individual oil pool. Biomarker and chemometric statistical analyses were used to correlate twenty-nine oils to five oil families derived from: (1) Triassic Shublik Formation (calcareous organofacies), (2) Triassic Shublik Formation (shaly organofacies), (3) Jurassic Kingak Shale, (4) Cretaceous shale (pebble shale unit and Hue Shale), and (5) Paleogene shale (Canning Formation). Age-diagnostic and source-related oil biomarker parameters establish clear genetic relationships between the normal oil-window components and their putative source designations. However, application of diamondoid analyses reveals mixed-oil accumulations with postmature charge contributions (diamondoid-rich and biomarker-poor) in many oils. Most sampled reservoirs contain a predominant charge derived from a single oil-window source plus a minor contribution from one or more higher maturity source(s). Variations in source organofacies also are recognized in the Shublik, Kingak, and Cretaceous oil families. In some cases, oils from multiple pools within a single field display relatively homogeneous geochemical profiles, suggesting a common source and migration pathway. For example, oil from the significant Pikka discovery is inferred to originate mainly from the calcareous Shublik Formation. In other cases, variability among oils from multiple pools within a single field (e.g., Milne Point, Colville River, and Northstar) likely indicates a more complex source, migration, and charge history. The results of this study may be useful for anticipating the composition of oil charge in stratigraphic traps with low-permeability sandstone reservoirs, where oil gravity and other chemical parameters may influence economic viability.

58 GEOSCIENCES↗

Partitioning maternal and exogenous diet contributions to otolith 87 Sr/ 86 Sr in kokanee salmon ( Oncorhynchus nerka )

Strontium isotopes ( 87 Sr/ 86 Sr) recorded in the otoliths of Pacific salmon (Oncorhynchus spp.) are commonly used to identify natal origin. For species that migrate at or soon after emergence, the embryonic region of the otolith provides the only record of provenance. However, maternal contribution of Sr from the yolk can confound the isotopic signature of the natal site. We experimentally quantified maternal and exogenous diet contributions to otolith 87 Sr/ 86 Sr over embryonic development in kokanee salmon (Oncorhynchus nerka). Eggs from two populations in isotopically distinct lakes were incubated and reared in a common water source. Timing of developmental events and proportional contribution from yolk to otolith 87 Sr/ 86 Sr differed significantly between the two populations. We suggest that the magnitude of difference in 87 Sr/ 86 Sr between yolk and water, the relative concentrations of Sr and Ca in these isotopic sources, and population-specific effects on otolith growth and composition contribute to this variation. Furthermore, understanding how these factors affect otolith 87 Sr/ 86 Sr could extend the use of otolith geochemistry for determining provenance to species and populations in which natal site rearing is limited.

59 BASIC BIOLOGICAL SCIENCES↗

A general predictive methodology for fuel-mixture properties up to supercritical conditions

A predictive thermodynamic model is utilized for the calculation of fuel properties of oxymethylene dimethyl ethers (OME 3–4 ), surrogates for gasoline, diesel and aviation fuel, as well as alcohol blends with gasoline and diesel. The alcohols used for these blends are methanol, ethanol, propanol, butanol and pentanol; their mixing ratio ranges from 10 to 50% by volume. The model is based on the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EoS) and Vapor Liquid Equilibrium (VLE) calculations at constant temperature, density and composition. The model includes the association term, with the assumption of two association sites (2B scheme), to enable the modeling of alcohols. The pure-component parameters are estimated based on the Group Contribution (GC) method of various sources, as well as a parametrization model specifically designed for the case of OME 3–4 . The results of the computational model for the density, vapor pressure and distillation curves at various conditions, including high-pressure, high-temperature (HPHT), are compared to experimental and computational data available in the literature. In the cases where no measurements are available for the surrogates, experimental data for the corresponding target fuel are used, taking into consideration the inherent deviation in properties between real and surrogate fuel. Overall, the results are in good agreement with the data from the literature, with the average deviation not exceeding 12% for temperature (Kelvin) on the distillation curves, 10% for density and 46% for vapor pressure and the general trend being captured successfully. The use of different pure component parameter estimation techniques can further improve the prediction quality in the cases of OME3–4 and the aviation fuel surrogate, especially for the vapor pressure, leading to an average deviation lower than 18%. These results demonstrate the predictive capabilities of the model, which extend to a wide range of fuel types and pressure/temperature conditions. Through this investigation, the present work aims to establish the limits of applicability of this thermodynamic property prediction methodology.

33 ADVANCED PROPULSION SYSTEMS↗

Uncovering a chirally suppressed mechanism of oνββ decay with LHC searches

Δ L = 2 lepton number violation (LNV) at the TeV scale could provide an alternative interpretation of positive signal(s) in future neutrinoless double beta (0 νββ ) decay experiments. An interesting class of models from this point of view are those that at low energies give rise to dimension-9 vector operators and a dimension-7 operator, both of whose 0 νββ -decay rates are “chirally suppressed”. We study and compare the sensitivities of 0 νββ -decay experiments and LHC searches to a simplified model in this class of TeV-scale LNV that is also SU(2) L × U(1) Y gauge invariant. The searches for 0 νββ decay, which are here diluted by a chiral suppression of the vector operators, are found to be less constraining than LHC searches whose reach is increased by the assumed kinematic accessibility of the mediator particles. For the chirally suppressed dimension-7 operator generated by TeV-scale mediators, in contrast, 0 νββ -decay searches place strong constraints on the size of the new Yukawa coupling. Signals of this model at the LHC and 0 νββ -decay experiments are entirely uncorrelated with the observed neutrinos masses, as these new sources of LNV give negligible contributions to the latter. We find the prospects for the high-luminosity LHC and ton-scale 0 νββ -decay experiments to uncover the chirally-suppressed mechanism with TeV-scale LNV to be promising. We also comment on the sensitivity of the 0 νββ -decay lifetime to certain unknown low-energy constants that in the case of dimension-9 scalar operators are expected to be large due to non-perturbative renormalization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of gamma-ray transmission through rectangular collimator slits for application in nuclear fuel spectrometry

Gamma-ray spectrometry is widely applied in several science fields, and in particular in non-destructive gamma scanning and gamma emission tomography of irradiated nuclear fuel. Usually, a collimator is used in the experimental setup, to selectively interrogate a region of interest in the fuel. For the optimization of instrument design, as well as for planning measurement campaigns, predictive models for the transmitted gamma-ray intensity through the collimator are needed. Commonly, Monte Carlo Radiation Transport tools are used for accurate prediction of gamma-ray transport, however, the long computation time requirements when used in low-efficiency experimental setups present challenges. Here, the full-energy peak intensity transmitted through a rectangular collimator slit was examined. A uniform planar surface source emitting isotropically was considered, and the rate of photons reaching an ideal counter plane on the opposite side of the collimator was evaluated by analytical integration. To find a closed-form primitive function, some idealizations were required, and thereby parametric models were obtained for the optical field of view, dependent on slit dimensions (length, height and width) and source-to-collimator distance. For contributions from outside the optical field of view, where a closed-form expression cannot be found, fast numerical integral methods were instead used. The results were validated using the Monte Carlo code MCNP6 and show an agreement within three percent for the numerical method. For the analytical method, deviations up to tens of percent were obtained, which is deemed to still be sufficient for instrument design and measurement planning, where often the order of magnitude of the count rate is not a priori known. The method is planned for use in iterative optimization routines in the design of Gamma Emission Tomography devices, as well as for the prediction of gamma spectra obtained in the planning of fuel inspections. An application of the proposed method was demonstrated in spectrum prediction for a short cooling-time fuel rod test from the Halden reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A neural network for beam background decomposition in Belle II at SuperKEKB

Here, we describe a neural network for predicting the background hit rate in the Belle II detector produced by the SuperKEKB electron-positron collider. The neural network, BGNet, learns to predict the individual contributions of different physical background sources, such as beam-gas scattering or continuous top-up injections into the collider, to Belle II sub-detector rates. The samples for learning are archived 1 Hz time series of diagnostic variables from the SuperKEKB collider subsystems and measured hit rates of Belle II used as regression targets. We test the learned model by predicting detector hit rates on archived data from different run periods not used during training. We show that a feature attribution method can help interpret the source of changes in the background level over time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Interplay between Electrostatic Properties of Molecular Adducts and Their Positions at Carbon Nanotubes

Formation of the sp 3 -defect due to covalent functionalization of a single-walled carbon nanotube (SWCNT) results in a new red-shifted emissive excitons. Here, using density functional theory, we study the impact of the intrinsic molecular dipole moments and the local charges induced by various molecular adducts on the energy and localization properties of the optically active defect-based exciton in a (10,5) SWCNT. The interplay of two effects plays a role in the localization of the exciton and, therefore, its red shift, but at different scales: The source of the leading order contribution is the defect conformation, resulting in the red shift of the defect-associated exciton with respect to the E 11 band of the pristine SWCNT on the order of ~100 meV, while the individual dipoles and polarization properties of molecular adducts lead to significantly smaller red shifts on the order of ~10 meV. While the species-dependent trends in defect-induced charges do not directly correlate to the exciton red shift, the charge at the sp 3 -defect exhibits a distinct behavior between ortho- and para-defect configurations and is relevant to the chemical reactivity of the defect position depending on the adduct type. Overall, our computational results may be helpful for diverse synthetic strategies to fine-tune emission of SWCNTs toward desired applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorption of Neodymium, Dysprosium, and Ytterbium to Goethite under Varying Aqueous Chemistry Conditions

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (<5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (>5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple-layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. An SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. Furthermore, this predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗

Relic neutrino decay solution to the excess radio background

Abstract The excess radio background detected by ARCADE 2 represents a puzzle within the standard cosmological model. There is no clear viable astrophysical solution, and therefore, it might indicate the presence of new physics. Radiative decays of a relic neutrino ν_i (either i=1, or i=2, or i=3) into a sterile neutrino ν_ s, assumed to be quasi-degenerate, provide a solution that currently evades all constraints posed by different cosmological observations and reproduces very well the ARCADE 2 data. We find a very good fit to the ARCADE 2 data with best fit values τ_i = 1.46 × 10^21 s and Δ m_i = 4.0 × 10^-5 eV, where τ_i is the lifetime and Δ m_i is the mass difference between the decaying active neutrino and the sterile neutrino. On the other hand, if relic neutrino decays do not explain ARCADE 2 data, then these place a stringent constraint Δ m_i^3/2τ_i ≳ 2 × 10^14 eV^3/2 s in the range 1.4 × 10^-5 eV<Δ m_i < 2.5 × 10^-4 eV. The solution also predicts a stronger 21 cm absorption global signal than the predicted one from the ΛCDM model, with a contrast brightness temperature T_21 = -238^+21_-20 mK (99% C.L.) at redshift z≃ 17. This is in mild tension with the even stronger signal found by the EDGES collaboration, T_21 = - 500^+200_-500 mK, suggesting that this might have been overestimated, possibly receiving a contribution from some unidentified foreground source.

Astronomy & Astrophysics↗

A high-resolution clock phase shifter circuitry for ALTIROC

Abstract A high-resolution clock phase shifter is implemented to adjust the phase of multiple clocks at 40 MHz, 80 MHz, or 640 MHz in the ALTIROC chip. The phase shifter has a coarse-phase shifter and a fine-phase shifter to achieve a step size of 97.7 ps and an adjustable range of 25 ns. The fine delay unit is based on a Delay Locked Loop (DLL) operating at 640 MHz. The phase shifter is fabricated in a 130 nm CMOS process. The area of the phase shifter is 725 µm × 248 µm. The Differential Non-Linearity (DNL) and the Integral Non-Linearity (INL) are ±0.6 LSB and ±0.75 LSB, respectively. The jitter from −25 °C to 20 °C is less than 15.5 ps (RMS), including the contributions from the FPGA clock source and the PLL. The power consumption is 11.2 mW.

Instruments & Instrumentation↗

Sulfide stress tolerance as a controller of methane production in temperate wetlands

Abstract Wetlands are a major source of methane emissions and contribute to the observed increase in atmospheric methane over the last 20 years. Methane production in wetlands is the final step of carbon decomposition performed by anaerobic archaea. Although hydrogen/carbon dioxide and acetate are the substrates most often attributed to methanogenesis, other substrates—such as methylated compounds—may additionally play important roles in driving methane production in wetland systems. Here we conducted mesocosm experiments combined with genome-resolved metatranscriptomics to investigate the impact of diverse methanogenic substrate amendment on methanogenesis in two high methane-emitting wetlands with distinct geochemistry, termed P7 and P8. Methanol amendment resulted in high methane production at both sites, whereas acetate and formate amendment only stimulated methanogenesis in P7 mesocosms, where aqueous sulfide concentrations were lower. In P7 sediments, formate amendment fueled acetogenic microbes that produced acetate, which was subsequently utilized by acetoclastic methanogens. In contrast to expression profiles in P7 mesocosms, active methylotrophic methanogen genomes from P8 showed increased expression of genes related to membrane remodeling and DNA damage repair, indicative of stress tolerance mechanisms to counter sulfide toxicity. Methylotrophic methanogenesis generates higher free energy yields than acetoclastic methanogenesis, which likely enables allocation of more energy toward stress responses. These findings contribute to the growing body of literature highlighting methylotrophic methanogenesis as an important methane production pathway in wetlands. By using less competitive substrates like methanol that provide greater energy yields, methylotrophic methanogens may invest in physiological strategies that provide competitive advantages across a range of environmental stresses.

Environmental Sciences & Ecology↗

Processing Aleatory and Epistemic Uncertainties in Experimental Data From Sparse Replicate Tests of Stochastic Systems for Real-Space Model Validation

This paper presents a practical methodology for propagating and processing uncertainties associated with random measurement and estimation errors (that vary from test-to-test) and systematic measurement and estimation errors (uncertain but similar from test-to-test) in inputs and outputs of replicate tests to characterize response variability of stochastically varying test units. Also treated are test condition control variability from test-to-test and sampling uncertainty due to limited numbers of replicate tests. These aleatory variabilities and epistemic uncertainties result in uncertainty on computed statistics of output response quantities. The methodology was developed in the context of processing experimental data for “real-space” (RS) model validation comparisons against model-predicted statistics and uncertainty thereof. The methodology is flexible and sufficient for many types of experimental and data uncertainty, offering the most extensive data uncertainty quantification (UQ) treatment of any model validation method the authors are aware of. It handles both interval and probabilistic uncertainty descriptions and can be performed with relatively little computational cost through use of simple and effective dimension- and order-adaptive polynomial response surfaces in a Monte Carlo (MC) uncertainty propagation approach. A key feature of the progressively upgraded response surfaces is that they enable estimation of propagation error contributed by the surrogate model. Sensitivity analysis of the relative contributions of the various uncertainty sources to the total uncertainty of statistical estimates is also presented. Finally, the methodologies are demonstrated on real experimental validation data involving all the mentioned sources and types of error and uncertainty in five replicate tests of pressure vessels heated and pressurized to failure. Simple spreadsheet procedures are used for all processing operations.

97 MATHEMATICS AND COMPUTING↗

PFLOTRAN 5

PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase flow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface environment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class supercomputers for over two decades. The code is designed to predict the future estate of environmental systems and better inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for nuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and maintenance under an open-source licensing agreement and manages contributions from an international community of researchers.

Hammond, Glenn↗

Node-red Software Architecture For Soec System Control

The software workflows that have been developed are open-source and therefore can be accessed and utilized by researchers and students all around the world for free of cost. The software is flexible and easily modifiable to suit the needs for testing bench-scale to system-level setups, and is not limited to just hydrogen generation facilities. The web-interface of the code allows for easy remote access and management, which is especially useful for distributed systems. This is more challenging with traditional PLCs, which often require direct connections or specialized software, making remote troubleshooting more cumbersome. Additionally, since the underlying interface is open-source, with an active community contributing to its development, regular updates, new features, and a wealth of community support and shared solutions will keep improving the overall architecture without excessive fees for upgrades.

Shigrekar, Amey [Idaho National Laboratory (INL), ↗

Idaho National Laboratory CY 2021 National Emission Standards for Hazardous Air Pollutants Analysis, Methodology and Results for Radionuclides

This report details calculations of potential dose at public receptor locations surrounding the Idaho National Laboratory (INL) Site boundary, and INL in-town facilities, from radionuclides reported to be in use and potentially emitted from INL facilities during calendar year (CY) 2021. All calculations were performed in accordance with the requirements in Code of Federal Regulations (CFR), Title 40, “Protection of the Environment,” Part 61, “National Emission Standards for Hazardous Air Pollutants (NESHAPs),” Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” (40 CFR 61, Subpart H). Modeling methodology, model input parameters, and contribution to dose by facility, source, and radionuclide at the maximally exposed individual (MEI) location are also discussed. The information in this report supports the “National Emission Standards for Hazardous Air Pollutants - Calendar Year 2021 INL Report for Radionuclides” (INL 2022). In CY 2021, the estimated annual potential dose at the INL Site MEI location was 6.67E-02 mrem/yr, up slightly from the previous year, but far less than the regulatory standard of 10 mrem/yr (CFR 40 Part 61, Subpart H). Approximately 97% of the total dose to the INL Site MEI originated from MFC sources. Emissions from INL in-town facilities resulted in an estimated annual potential dose of 6.21E-03 mrem/yr to the MEI, down 40% from the CY 2020 estimated dose. Year-to-year variations in estimated annual dose can be attributed to adjustments in laboratory operations, changes to facility infrastructure, and variation in meteorological conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Idaho National Laboratory CY 2022 National Emission Standards for Hazardous Air Pollutants Analysis, Methodology and Results for Radionuclides

This report details calculations of potential dose at public receptor locations surrounding the Idaho National Laboratory (INL) Site boundary, and INL in-town facilities, from radionuclides reported to be in use and potentially emitted from INL facilities during calendar year (CY) 2022. All calculations were performed in accordance with the requirements in Code of Federal Regulations (CFR), Title 40, “Protection of the Environment,” Part 61, “National Emission Standards for Hazardous Air Pollutants (NESHAPs),” Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” (40 CFR 61, Subpart H). Modeling methodology, model input parameters, and contribution to dose by facility, source, and radionuclide at the maximally exposed individual (MEI) location are also discussed. The information in this report supports the “National Emission Standards for Hazardous Air Pollutants – Calendar Year 2022 INL Report for Radionuclides” (DOE-ID 2023). In CY 2022, the estimated annual potential dose at the INL Site MEI location was 1.78E-02 mrem/yr, down from the previous year, and far less than the regulatory standard of 10 mrem/yr (CFR 40 Part 61, Subpart H). Approximately 87% of the total dose to the INL Site MEI originated from Materials and Fuels Complex sources. Emissions from INL in-town facilities resulted in an estimated annual potential dose of 4.03E-03 mrem/yr to the MEI, down 35% from the CY 2021 estimated dose. Year-to-year variations in estimated annual dose can be attributed to adjustments in laboratory operations, changes to facility infrastructure, and variation in meteorological conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗