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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI

We introduce GenAI4UQ, a software package for forward and inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting. GenAI4UQ leverages a generative AI-based conditional modeling framework to address limitations of traditional inverse modeling techniques, such as Markov Chain Monte Carlo (MCMC) methods. By replacing computationally intensive iterative processes with a direct, learned mapping, GenAI4UQ enables efficient calibration of input parameters and generation of predictions directly from observations. The software supports rapid ensemble forecasting with robust uncertainty quantification while maintaining computational and storage efficiency. Built-in auto-tuning of hyperparameters simplifies model training, ensuring accessibility for users with varying expertise. Its versatile conditional generative framework is applicable across diverse scientific domains. While GenAI4UQ offers significant advantages in flexibility and efficiency, users should interpret its uncertainty estimates with caution in data-sparse scenarios, as the model may overestimate uncertainty—an effect common to all surrogate-based approaches including MCMC with surrogate models. Despite this, GenAI4UQ transforms inverse modeling by providing a fast, reliable, and user-friendly solution. It empowers researchers and practitioners to quickly estimate parameter distributions and generate model predictions for new observations, facilitating efficient decision-making and advancing the state of uncertainty quantification in computational modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A vortex sheet based analytical model of the curled wake behind yawed wind turbines

Motivated by the need for compact descriptions of the evolution of non-classical wakes behind yawed wind turbines, we develop an analytical model to predict the shape of curled wakes. Interest in such modelling arises due to the potential of wake steering as a strategy for mitigating power reduction and unsteady loading of downstream turbines in wind farms. We first estimate the distribution of the shed vorticity at the wake edge due to both yaw offset and rotating blades. By considering the wake edge as an ideally thin vortex sheet, we describe its evolution in time moving with the flow. Vortex sheet equations are solved using a power series expansion method, and an approximate solution for the wake shape is obtained. The vortex sheet time evolution is then mapped into a spatial evolution by using a convection velocity. Apart from the wake shape, the lateral deflection of the wake including ground effects is modelled. Our results show that there exists a universal solution for the shape of curled wakes if suitable dimensionless variables are employed. For the case of turbulent boundary layer inflow, the decay of vortex sheet circulation due to turbulent diffusion is included. Finally, we modify the Gaussian wake model by incorporating the predicted shape and deflection of the curled wake, so that we can calculate the wake profiles behind yawed turbines. Model predictions are validated against large-eddy simulations and laboratory experiments for turbines with various operating conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations

Abstract The atmospheric component of Energy Exascale Earth System Model version 1 has included many new features in the physics parameterizations compared to its predecessors. Potential complex nonlinear interactions among the new features create a significant challenge for understanding the model behaviors and parameter tuning. Using the one‐at‐a‐time method, the benefit of tuning one parameter may offset the benefit of tuning another parameter, or improvement in one target variable may lead to degradation in another target variable. To better understand the Energy Exascale Earth System Model version 1 model behaviors and physics, we conducted a large number of short simulations (three days) in which 18 parameters carefully selected from parameterizations of deep convection, shallow convection, and cloud macrophysics and microphysics were perturbed simultaneously using the Latin hypercube sampling method. From the perturbed parameter ensemble simulations and use of different skill score functions, we identified the most sensitive parameters, quantified how the model responds to changes of the parameters for both global mean and spatial distribution, and estimated the maximum likelihood of model parameter space for a number of important fidelity metrics. Comparison of the parametric sensitivity using simulations of two different lengths suggests that perturbed parameter ensemble using short simulations has some bearing on understanding parametric sensitivity of longer simulations. Results from this analysis provide a more comprehensive picture of the Energy Exascale Earth System Model version 1 behavior. The difficulty in reducing biases in multiple variables simultaneously highlights the need of characterizing model structural uncertainty (so‐called embedded errors) to inform future development efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Helium in Stream Water as a Volcanic Monitoring Tool

Abstract We show that synoptic sampling of streams can be used to characterize volcanic volatiles in groundwater over large spatial scales. Synoptic sampling of dissolved noble gases, 222 Rn, major ions, and stream discharge was carried out along a 30 km reach of the Gibbon River, near Norris Geyser Basin in Yellowstone National Park, USA. Groundwater discharge location, volume, and composition were estimated by constrained calibration of a stream flow and solute transport model. Estimated groundwater composition from stream modeling was compared to shallow groundwater concentrations measured in nearby springs. 3 He, 222 Rn, and Cl signatures in the Gibbon River are indicative of groundwater discharge with a volcanic signature along the study reach. Stream water noble gas isotopic composition has similar isotopic mixing patterns to springs. The model‐estimated composition of groundwater discharging to the Gibbon agrees well with observed groundwater composition from nearby springs for all modeled analytes. We present the first observations of elevated mantle helium in stream water and show that stream water can be used as a convenient collection point to estimate spatially distributed groundwater composition and to monitor changes in volatile flux over large spatial areas. These results offer the possibility that stream surveys in volcanic terrain could be a new method for distributed volcanic monitoring at the catchment scale and beyond.

Gardner, W. Payton↗
DOE OSTI2025

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗
DOE OSTI2021

Projected land ice contributions to twenty-first-century sea level rise

The land ice contribution to global mean sea level rise has not yet been predicted using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models, but primarily used previous-generation scenarios and climate models, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios using statistical emulation of the ice sheet and glacier models. In this work, we find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Food resources affect territoriality of invasive wild pig sounders with implications for control

Abstract Interest in control methods for invasive wild pigs ( Sus scrofa ) has increased due to their range expansion, population growth, and an improved understanding of their destructive ecological and economic effects. Recent technological advances in traps for control of pig populations facilitate capture of entire social groups (sounders), but the efficacy of “whole-sounder” trapping strategies is heavily dependent on the degree of territoriality among sounders, a topic little research has explored. We assessed territoriality in wild pig sounders on the Savannah River Site, South Carolina, USA, and examined whether availability of food resources provided by a municipal-waste landfill affected among-sounder territoriality. We estimated utilization distribution overlap and dynamic interactions among 18 neighboring sounders around a landfill. We found that although neighboring sounders overlapped in space, intensity of use in shared areas was uniformly low, indicating territorial behavior. Neighbors tended to share slightly more space when closer to the landfill waste cells, indicating availability of a super-abundant resource somewhat weakens the degree of territoriality among sounders. Nevertheless, we conclude that sounders behaved in a generally territorial manner, and we discuss implications for whole-sounder trapping programs, particularly near concentrated resources such as landfills and crop fields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

Sensing and measurement systems are quintessential to the safe and reliable operation of electric power grids. Their strategic placement is of ultimate importance because it is not economically viable to install measurement systems on every node and branch of a power grid, though they need to be monitored. An overwhelming number of strategies have been developed to meet oftentimes multiple conflicting objectives. The prime challenge in formulating the problem lies in developing a heuristic or an optimisation model that, though mathematically tractable and constrained in cost, leads to trustworthy technical solutions. Further, large-scale, long-term deployments pose additional challenges because the boundary conditions change as technologies evolve. For instance, the advent of new technologies in sensing and measurement, as well as in communications and networking, might impact the cost and performance of available solutions and shift initially set conditions. Also, the placement strategies developed for transmission grids might not be suitable for distribution grids, and vice versa, because of unique characteristics; therefore, the strategies need to be flexible, to a certain extent, because no two power grids are alike. Despite the extensive literature on the present topic, the focus of published works tends to be on a specific subject, such as the optimal placement of measurements to ensure observability in transmission grids. There is a dearth of work providing a comprehensive picture for developing optimal placement strategies. Because of the ongoing efforts on the modernisation of electric power grids, there is a need to consolidate the status quo while exposing its limitations to inform policymakers, industry stakeholders, and researchers on the research-and-development needs to push the boundaries for innovation. Accordingly, this paper first reviews the state-of-the-art considering both transmission and distribution grids. Then, it consolidates the key factors to be considered in the problem formulation. Finally, it provides a set of perspectives on the measurement placement problem, and it concludes with future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Ultra diffuse galaxies in the MATLAS low-to-moderate density fields

Recent advances in deep dedicated imaging surveys over the past decade have uncovered a surprisingly large number of extremely faint low surface brightness galaxies with large physical sizes called ultra diffuse galaxies (UDGs) in clusters and, more recently, in lower density environments. As part of the Mass Assembly of early-Type GaLAxies with their fine Structures (MATLAS) survey, a deep imaging large program at the Canada-France-Hawaii Telescope (CFHT), our team has identified 2210 dwarf galaxies, 59 (~3%) of which qualify as UDGs. Averaging over the survey area, we find ~0.4 UDG per square degree. They are found in a range of low to moderate density environments, although 61% of the sample fall within the virial radii of groups. Based on a detailed analysis of their photometric and structural properties, we find that the MATLAS UDGs do not show significant differences from the traditional dwarfs, except from the predefined size and surface brightness cut. Their median color is as red as the one measured in galaxy clusters, albeit with a narrower color range. The majority of the UDGs are visually classified as dwarf ellipticals with log stellar masses of ~6.5 – 8.7. The fraction of nucleated UDGs (~34%) is roughly the same as the nucleated fraction of the traditional dwarfs. Only five (~8%) UDGs show signs of tidal disruption and only two are tidal dwarf galaxy candidates. A study of globular cluster (GC) candidates selected in the CFHT images finds no evidence of a higher GC specific frequency S N for UDGs than for classical dwarfs, contrary to what is found in most clusters. The UDG halo-to-stellar mass ratio distribution, as estimated from the GC counts, peaks at roughly the same value as for the traditional dwarfs, but spans the smaller range of ~10 – 2000. Finally, we interpret these results to mean that the large majority of the field-to-group UDGs do not have a different formation scenario than traditional dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Milky Way archaeology using RR Lyrae and type II Cepheids: II. High-velocity RR Lyrae stars and Milky Way mass

We report the discovery of high-velocity candidates among RR Lyrae stars found in the Milky Way halo. We identified nine RR Lyrae stars with Galactocentric velocities exceeding the local escape velocity based on the assumed Galaxy potential. Furthermore, based on a close examination of their orbits’, we ruled out their ejection location in the Milky Way disk and bulge. The spatial distribution revealed that seven out of nine pulsators overlap with the position of the Sagittarius stellar stream. Two out of these seven RR Lyrae stars can be tentatively linked to the Sagittarius dwarf spheroidal galaxy on the basis of their orbits. Focusing on the high-velocity tail of the RR Lyrae velocity distribution, we estimated the escape velocity in the Solar neighborhood to be v esc = 512$_{-37}^{+94}$ km s -1 (4 to 12 kpc); and beyond the Solar neighborhood as v esc = 436$_{-22}^{+44}$ km s -1 and v esc = 393$_{-26}^{+53}$ km s -1 (for distances between 12 to 20 kpc and 20 to 28 kpc), respectively. We utilized three escape velocity estimates together with the local circular velocity to estimate the Milky Way mass. The resulting measurement M 200 = 0.83$_{-0.16}^{+0.29}$ x 10 12 M ⊙ falls on the lower end of the current Milky Way mass estimates, but once corrected for the likely bias in the escape velocity (an increase of approximately 10% in terms of the escape velocity), our mass estimate yields M 200 = 1.26$_{-0.22}^{+0.40}$ x 10 12 M ⊙ which is in agreement with estimates based on different diagnostics of the Milky Way (MW) mass. The MW mass of within 20 kpc then corresponds to M MW (r , 20 kpc) = 1.9$_{-0.1}^{+0.2}$ x 10 11 M ⊙ without any correction for bias, and M MW (r , 20 kpc) = 2.1$_{-0.1}^{+0.2}$ x 10 11 M ⊙ corrected for a likely offset in escape velocities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effects of surface diffusion in electrocatalytic CO 2 reduction on Cu revealed by kinetic Monte Carlo simulations

We report Kinetic Monte Carlo (KMC) methods are frequently used for mechanistic studies of thermally driven heterogeneous catalysis systems but are underused for electrocatalysis. Here, we develop a lattice KMC approach for electrocatalytic CO 2 reduction. The work is motivated by a prior experimental report that performed electroreduction of a mixed feed of 12 CO 2 and 13 CO on Cu; differences in the 13 C content of C2 products ethylene and ethanol (Δ 13 C) were interpreted as evidence of site selectivity. The lattice KMC model considers the effect of surface diffusion on this system. In the limit of infinitely fast diffusion (mean-field approximation), the key intermediates 12 CO* and 13 CO* would be well mixed on the surface and no evidence of site selectivity could have been observed. Using a simple two-site model and adapting a previously reported microkinetic model, we assess the effects of diffusion on the relative isotope fractions in the products using the estimated surface diffusion rate of CO* from literature reports. We find that the size of the active sites and the total surface adsorbate coverage can have a large influence on the values of Δ 13 C that can be observed. Δ 13 C is less sensitive to the CO* diffusion rate as long as it is within the estimated range. We further offer possible methods to estimate surface distribution of intermediates and to predict intrinsic selectivity of active sites based on experimental observations. This work illustrates the importance of considering surface diffusion in the study of electrochemical CO 2 reduction to multi-carbon products. Our approach is entirely based on a freely available open-source code, so will be readily adaptable to other electrocatalytic systems.

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

Non-destructive depth-resolved characterization of residual strain fields in high electron mobility transistors using differential aperture x-ray microscopy

Localized residual stress and elastic strain concentrations in microelectronic devices often affect the electronic performance, resistance to thermomechanical damage, and, likely, radiation tolerance. A primary challenge for the characterization of these concentrations is that they exist over sub-μm length-scales, precluding their characterization by more traditional residual stress measurement techniques. Here, in this study, we demonstrate the use of synchrotron x-ray-based differential aperture x-ray microscopy (DAXM) as a viable, non-destructive means to characterize these stress and strain concentrations in a depth-resolved manner. DAXM is used to map two-dimensional strain fields between the source and the drain in a gallium nitride (GaN) layer within high electron mobility transistors (HEMTs) with sub-μm spatial resolution. Strain fields at various positions in both pristine and irradiated HEMT specimens are presented in addition to a preliminary stress analysis to estimate the distribution of various stress components within the GaN layer. γ-irradiation is found to significantly reduce the lattice plane spacing in the GaN along the sample normal direction, which is attributed to radiation damage in transistor components bonded to the GaN during irradiation.

42 ENGINEERING↗
DOE OSTI2025

An efficient surrogate model of secondary electron formation and evolution

This work extends the adjoint-deep learning framework for runaway electron (RE) evolution, developed by McDevitt et al. [Phys. Plasmas 32, 042503 (2025)], to account for large-angle collisions. By incorporating large-angle collisions, the framework allows the avalanche of REs to be captured, an essential component of RE dynamics. This extension is accomplished by using a Rosenbluth–Putvinski approximation to estimate the distribution of secondary electrons generated by large-angle collisions. By evolving both the primary and multiple generations of secondary electrons, the present formulation can capture both the detailed temporal evolution of a RE population beginning from an arbitrary initial momentum space distribution, along with providing approximations to the saturated growth and decay rates of the RE population. Predictions of the adjoint-deep learning framework are verified against a traditional RE solver, with good agreement present across a broad range of parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Investigation of fast particle redistribution induced by sawtooth instability in NSTX-U

The effects of sawtooth on fast ion transport have been examined in reproducible, 2s long sawtoothing L-mode discharges during the 2016 experimental campaign on National Spherical Torus Experiment Upgrade (NSTX-U) [J.E. Menard et al. Nucl. Fusion (2012) 083015]. Analysis of the discharges showed that standard sawtooth models (full/partial reconnection models) in the TRANSP code were not capable to fully reproduce the fast ion redistribution induced by sawtooth crashes. Some global parameters such as neutron rate can be recovered while detailed features, e.g. distribution functions, estimated using the models were different from the experimental observation. The standard sawtooth models in TRANSP do not take into account the different effect of sawtooth crashes depending on fast ion energy and orbit type and that may cause the disagreement between experiments and simulations. In this work, the newly developed kick model has been applied to replace the standard sawtooth models for the fast ion transport. TRANSP simulation results using the kick model, taking into account the characteristics of fast ion such as energy and pitch angle, can reproduce experimental neutron rates within 10\% difference. The qualitative comparison of the measurements and synthetic diagnostics of FIDA and SSNPA using the TRANSP simulation results with kick model demonstrates good agreements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Mass calibration of distant SPT galaxy clusters through expanded weak-lensing follow-up observations with HST, VLT, & Gemini-South

Expanding from previous work, we present weak-lensing (WL) measurements for a total sample of 30 distant (z median = 0.93) massive galaxy clusters from the South Pole Telescope Sunyaev–Zel’dovich (SPT-SZ) Survey, measuring galaxy shapes in Hubble Space Telescope (HST) Advanced Camera for Surveys images. We remove cluster members and preferentially select z ≳ 1.4 background galaxies via V - I colour, employing deep photometry from VLT/FORS2 and Gemini-South/GMOS. We apply revised calibrations for the WL shape measurements and the source redshift distribution to estimate the cluster masses. In combination with earlier Magellan/Megacam results for lower-redshifts clusters, we infer refined constraints on the scaling relation between the SZ detection significance and the cluster mass, in particular regarding its redshift evolution. The mass scale inferred from the WL data is lower by a factor $0.76^{+0.10}_{-0.14}$ (at our pivot redshift z = 0.6) compared to what would be needed to reconcile a flat Planck νΛCDM cosmology (in which the sum of the neutrino masses is a free parameter) with the observed SPT-SZ cluster counts. In order to sensitively test the level of (dis-)agreement between SPT clusters and Planck, further expanded WL follow-up samples are needed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogues from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multiband deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalogue created from N-body simulations. Here, it yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σ Δz = 0.007, which is a 60 per cent improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Clustering redshifts and importance sampling of self-organized-maps 𝑛⁡(𝑧) realizations for 3 × 2 ⁢pt samples

This work is part of a series establishing the redshift framework for the 3 × 2 ⁢pt analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived 𝑛⁡(𝑧) realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales corresponding to 1.5–5 Mpc to optimize signal-to-noise ratio while mitigating modeling uncertainties and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation CARDINAL . While a sparser spectroscopic reference sample limits WZ constraining power at 𝑧 >1.1, particularly for source bins, we demonstrate that combining SOM with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. As a result, we estimate an improvement in 𝑆 8 of approximately 10% for cosmic shear and 3 ×2⁢pt analysis, primarily due to the WZ calibration of the source samples.

Cosmological parameters↗
DOE OSTI2026

Signatures of QCD conductivities in heavy-ion collisions

Dissipative processes are pivotal for understanding the hydrodynamic evolution of hot and dense quantum chromodynamics (QCD) matter created in relativistic nuclear collisions. The interplay of multiple conserved charges—net baryon, strangeness, and electric charge—is of particular interest. Here, we simulate the longitudinal hydrodynamic evolution with the three diffusion currents in a hydrodynamic model with a lattice-QCD-based equation of state, NEOS -4 D , and estimate rapidity distributions including diffusive corrections to the phase-space distribution in the presence of multiple charges, which ensure charge conservation at particlization. We determine the response of particle yields at midrapidity to changes in the diagonal and off-diagonal conductivities. Inversely, we find that most components of the conductivity matrix can be constrained experimentally using identified particle multiplicities at different collision energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗