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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Benchmarking third-order cluster perturbation theory for electronically excited states

In this study, we investigate the reliability of cluster perturbation (CP) theory applied to the calculation of electronically excited states through a comprehensive benchmark. In CP theory, perturbative corrections are added to the properties of a parent excitation space, which converge toward the properties of a target excitation space. For the CPS(D-n) model, perturbative corrections through order n are added to the coupled cluster singles (CCS) excitation energies to target the coupled cluster singles and doubles (CCSD) excitation energies. Through a comparative analysis of excitation energy calculations across a diverse set of molecules and wavefunction methods, we present a comprehensive evaluation of the accuracy of the third-order CPS(D) model, CPS(D-3), in calculating excitation energies. Further, our findings demonstrate that CPS(D-3) is a reliable alternative to established methods, particularly CCSD, while systematically overestimating the excitation energies compared to high-level coupled cluster methods such as CC3. These results highlight the strengths and limitations of CPS(D-3), as well as the promising directions for its future development.

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

Joint galaxy–galaxy lensing and clustering constraints on galaxy formation

ABSTRACT We compare predictions for galaxy–galaxy lensing profiles and clustering from the Henriques et al. public version of the Munich semi-analytical model (SAM) of galaxy formation and the IllustrisTNG suite, primarily TNG300, with observations from KiDS + GAMA and SDSS-DR7 using four different selection functions for the lenses (stellar mass, stellar mass and group membership, stellar mass and isolation criteria, and stellar mass and colour). We find that this version of the SAM does not agree well with the current data for stellar mass-only lenses with $M_\ast \gt 10^{11}\, \mathrm{ M}_\odot$. By decreasing the merger time for satellite galaxies as well as reducing the radio-mode active galactic nucleus accretion efficiency in the SAM, we obtain better agreement, both for the lensing and the clustering, at the high-mass end. We show that the new model is consistent with the signals for central galaxies presented in Velliscig et al. Turning to the hydrodynamical simulation, TNG300 produces good lensing predictions, both for stellar mass-only (χ2 = 1.81 compared to χ2 = 7.79 for the SAM) and locally brightest galaxy samples (χ2 = 3.80 compared to χ2 = 5.01). With added dust corrections to the colours it matches the SDSS clustering signal well for red low-mass galaxies. We find that both the SAMs and TNG300 predict $\sim 50\, {{\ \rm per\ cent}}$ excessive lensing signals for intermediate-mass red galaxies with 10.2 < log10M*[M⊙] < 11.2 at $r \approx 0.6\, h^{-1}\, \text{Mpc}$, which require further theoretical development.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quantum circuit cutting with maximum-likelihood tomography

Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

COOL-LAMPS. I. An Extraordinarily Bright Lensed Galaxy at Redshift 5.04

In this paper, we report the discovery of COOL J1241+2219, a strongly lensed galaxy at redshift z = 5.043 ± 0.002 with observed magnitude z AB = 20.47, lensed by a moderate-mass galaxy cluster at z = 1.001 ± 0.001. COOL J1241+2219 is the brightest lensed galaxy currently known at optical and near-infrared wavelengths at z $\gtrsim$ 5; it is ~5 times brighter than the prior record-holder lensed galaxy, and several magnitudes brighter than the brightest unlensed galaxies known at these redshifts. It was discovered as part of COOL-LAMPS, a collaboration initiated to find strongly lensed systems in recent public optical imaging data. We characterize the lensed galaxy, as well as the central galaxy of the lensing cluster using ground-based grizJH imaging and optical spectroscopy. We report model-based magnitudes, and derive stellar masses, dust content, metallicity, and star-formation rates via stellar-population synthesis modeling. Our lens mass modeling, based on ground-based imaging, implies a median source magnification of ~30, which puts the stellar mass and star-formation rate (in the youngest age bin, closest to the epoch of observation) at logM* = ${10.11}_{-0.26}^{+0.21}$ and SFR = ${27}_{-9}^{+13} M_⊙$ yr –1 , respectively. We constrain a star-formation history for COOL J1241+2219 consistent with constant star formation across ~1 Gyr of cosmic time, and that places this galaxy on the high-mass end of the star-forming main sequence. COOL J1241+2219 is two to four times more luminous than a galaxy with the characteristic UV luminosity at these redshifts. The UV continuum slope β = –2.2 ± 0.2 places this galaxy on the blue side of the observed distribution of galaxies at z = 5, although the lack of Lyα emission indicates dust sufficient to suppress this emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Diagnostic assessment of reservoir response to fracturing: a case study from Hydraulic Fracturing Test Site (HFTS) in Midland Basin

Abstract This paper outlines a data collection and diagnostics case study involving multiple horizontal shale wells. We look at well production profiles using rate transient analysis, differences in near wellbore complexity, geologic variations within the area of interest, as well as compositional differences in the rocks based on cores obtained from within the stimulated reservoir. The Hydraulic Fracturing Test Site is a multi-well experiment involving stimulation of unconventional shale wells in the southeastern Midland portion of the Permian Basin. The targeted formations include both the upper as well as the middle Wolfcamp formations, also referred alternatively as Wolfcamp A and Wolfcamp B. Data integration and analysis shared in this paper help us understand the various geologic controls impacting well productivity, particularly the wide variance observed between the Wolfcamp A and Wolfcamp B formations. Rate transient analysis indicates similar system permeabilities for stimulated wells. However, we observe higher effective fracture half-lengths for upper Wolfcamp wells. Using observations from 3D seismic interpretations (such as pad scale faults) as well as petrophysical and image log data, we highlight the substantial differences in stimulation as we move along the well laterals from the heel toward the toe sections. These differences are further reconciled with observations from zones with high data density at the core locations through stimulated rock, as well as independent data such as microseismic emissions. At the test site, Wolfcamp A was found to be relatively quartz rich with significant heterogeneity whereas Wolfcamp B is richer in clay and organic content. This impacts the geomechanical characteristics of the rock mass with much higher natural fracture density in the shallower interval. Thus, the fracture growth is more uniform in the deeper interval and more heterogeneous with branching likely in upper interval. Increased complexity also leads to consistently better productivity from the wells in the shallower interval as demonstrated from RTA results. This case study is unique because it provides valuable insights from actual sampling of the stimulated zones in hydraulically fractured wells and helps understand impact of various factors that contribute toward variability in well production. The findings from this study provides insights into need for optimization of completion designs in the various Wolfcamp landing zones, such as optimization of cluster or fracture spacing in various Wolfcamp intervals. In addition, it provides a useful template for data collection and research direction in future field test sites of similar nature in unconventional reservoirs.

Energy & Fuels↗
DOE OSTI2021

Probing Intra-Halo Light with Galaxy Stacking in CIBER Images

We study the stellar halos of 0.2 ≲ $z$ ≲ 0.5 galaxies with stellar masses spanning $M$* ~ 10 10.5 to 10 12 $M$ ⊙ (approximately $L$* galaxies at this redshift) using imaging data from the Cosmic Infrared Background Experiment (CIBER). A previous CIBER fluctuation analysis suggested that intra-halo light (IHL) contributes a significant portion of the near-infrared extragalactic background light (EBL), the integrated emission from all sources throughout cosmic history. In this work, we carry out a stacking analysis with a sample of ~30,000 Sloan Digital Sky Survey (SDSS) photometric galaxies from CIBER images in two near-infrared bands (1.1 and 1.8 $μ$m) to directly probe the IHL associated with these galaxies. We stack galaxies in five sub-samples split by brightness and detect an extended galaxy profile beyond the instrument point-spread function (PSF) derived by stacking stars. We jointly fit a model for the inherent galaxy light profile plus large-scale one- and two-halo clustering to measure the extended galaxy IHL. We detect nonlinear one-halo clustering in the 1.8 $μ$m band at a level consistent with numerical simulations. Furthermore, by extrapolating the fraction of extended galaxy light, we measure to all galaxy mass scales, we find ~30%/15% of the total galaxy light budget from galaxies is at radius $r$ > 10/20 kpc, respectively. These results are new at near-infrared wavelengths at the $L$* mass scale and suggest that the IHL emission and one-halo clustering could have appreciable contributions to the amplitude of large-scale EBL background fluctuations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Independent Mutation of Two Bridging Carboxylate Ligands Stabilizes Alternate Conformers of the Photosynthetic O 2 -Evolving Mn 4 CaO 5 Cluster in Photosystem II

The O 2 -evolving Mn 4 CaO 5 cluster in Photosystem II is ligated by six carboxylate residues. One of these is D170 of the D1 subunit. This carboxylate bridges between one Mn ion (Mn4) and the Ca ion. A second carboxylate ligand is D342 of the D1 subunit. This carboxylate bridges between two Mn ions (Mn1 and Mn2). D170 and D342 are located on opposite sides of the Mn 4 CaO 5 cluster. Recently, it was shown that the D170E mutation perturbs both the intricate networks of H-bonds that surround the Mn 4 CaO 5 cluster and the equilibrium between different conformers of the cluster in two of its lower oxidation states, S 1 and S 2 , while still supporting O 2 evolution at approx. 50% the rate of wild-type. In this study, we show that the D342E mutation produces much the same alterations to the cluster’s FTIR and EPR spectra as D170E, while still supporting O 2 evolution at approx. 20% the rate of wild-type. Furthermore, the double mutation, D170E + D342E, behaves similarly to the two single mutations. We conclude that D342E alters the equilibrium between different conformers of the cluster in its S 1 and S 2 states in the same manner as D170E and perturbs the H-bond networks in a similar fashion. This is the second identification of a Mn 4 CaO 5 metal ligand whose mutation influences the equilibrium between the different conformers of the S 1 and S 2 states without eliminating O 2 evolution. Finally, this finding has implications for our understanding of the mechanism of O 2 formation in terms of catalytically active/inactive conformations of the Mn 4 CaO 5 cluster in its lower oxidation states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Structural diversity and clustering of bacterial flagellar outer domains

Supercoiled flagellar filaments function as mechanical propellers within the bacterial flagellum complex, playing a crucial role in motility. Flagellin, the building block of the filament, features a conserved inner D0/D1 core domain across different bacterial species. In contrast, approximately half of the flagellins possess additional, highly divergent outer domain(s), suggesting varied functional potential. In this study, we report atomic structures of flagellar filaments from three distinct bacterial species: Cupriavidus gilardii , Stenotrophomonas maltophilia , and Geovibrio thiophilus . Our findings reveal that the flagella from the facultative anaerobic G. thiophilus possesses a significantly more negatively charged surface, potentially enabling adhesion to positively charged minerals. Furthermore, we analyze all AlphaFold predicted structures for annotated bacterial flagellins, categorizing the flagellin outer domains into 682 structural clusters. This classification provides insights into the prevalence and experimental verification of these outer domains. Remarkably, two of the flagellar structures reported herein belong to a distinct cluster, indicating additional opportunities on the study of the functional diversity of flagellar outer domains. Our findings underscore the complexity of bacterial flagellins and open up possibilities for future studies into their varied roles beyond motility.

Science & Technology - Other Topics↗
DOE OSTI2022

Enhanced ionic conductivity and lack of paddle-wheel effect in pseudohalogen-substituted Li argyrodites

Superionic conductors are key to the development of safe and high-energy-density, all-solid-state batteries. Using a combined theoretical and experimental approach, we explore the feasibility of increasing the ionic conductivity through pseudohalogen substitution in the Li argyrodite structure. Under the guidance of calculated thermodynamic stability, BH 4 -substituted Li argyrodite, Li 5.91 PS 4.91 (BH 4 ) 1.09 , was successfully synthesized via a mechanochemical method. As-synthesized BH 4- substituted Li argyrodite displays an ionic conductivity of 4.8 mS/cm at 25°C. Ab initio molecular dynamics simulation trajectory analysis was used to investigate how BH 4 facilitates Li-ion diffusion and indicates only a weak correlation with the B–H bond motion. Here, we find that the enhanced conductivity mainly originates from the weak interaction between Li and BH 4 and find no evidence of a paddle-wheel effect from the polyanion. This work provides insight into how cluster ions enhance Li diffusion and systematically describes how to explore superionic conductors with pseudohalogen substitution.

25 ENERGY STORAGE↗
DOE OSTI2025

Ab-initio nucleon-nucleon correlations and their impact on high energy 16 O+ 16 O collisions

Investigating nucleon-nucleon correlations inherent to the strong nuclear force is one of the core goals in nuclear physics research. We showcase the unique opportunities offered by collisions of 16 O nuclei at high-energy facilities to reveal detailed many-body properties of the nuclear ground state. We interface existing knowledge about the geometry of 16 O coming from ab-initio calculations of nuclear structure with transport simulations of high-energy 16 O+ 16 O collisions. Bulk observables in these processes, such as the elliptic flow or the fluctuations of the mean transverse momentum, are found to depend significantly on the input nuclear model and to be sensitive to realistic clustering and short-range repulsive correlations, effectively opening a new avenue to probe these features experimentally. This finding demonstrates collisions of oxygen nuclei as a tool to elucidate initial conditions of small collision systems while fostering connections with effective field theories of nuclei rooted in quantum chromodynamics (QCD).

Zhang, Chunjian [Fudan University, Shanghai (China↗
DOE OSTI2024

Tetrameric self-assembling of water-lean solvents enables carbamate anhydride-based CO2 capture chemistry

Abstract Carbon capture, utilization and storage is a key yet cost-intensive technology for the fight against climate change. Single-component water-lean solvents have emerged as promising materials for post-combustion CO 2 capture, but little is known regarding their mechanism of action. Here we present a combined experimental and modelling study of single-component water-lean solvents, and we find that CO 2 capture is accompanied by the self-assembly of reverse-micelle-like tetrameric clusters in solution. This spontaneous aggregation leads to stepwise cooperative capture phenomena with highly contrasting mechanistic and thermodynamic features. The emergence of well-defined supramolecular architectures displaying a hydrogen-bonded internal core, reminiscent of enzymatic active sites, enables the formation of CO 2 -containing molecular species such as carbamic acid, carbamic anhydride and alkoxy carbamic anhydrides. This system extends the scope of adducts and mechanisms observed during carbon capture. It opens the way to materials with a higher CO 2 storage capacity and provides a means for carbamates to potentially act as initiators for future oligomerization or polymerization of CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Towards predictive control of reversible nanoparticle assembly with solid-binding proteins

Although a broad range of ligand-functionalized nanoparticles and physico-chemical triggers have been exploited to create stimuli-responsive colloidal systems, little attention has been paid to the reversible assembly of unmodified nanoparticles with non-covalently bound proteins. Previously, we reported that a derivative of green fluorescent protein engineered with oppositely located silica-binding peptides mediates the repeated assembly and disassembly of 10-nm silica nanoparticles when pH is toggled between 7.5 and 8.5. We captured the subtle interplay between interparticle electrostatic repulsion and their protein-mediated short-range attraction with a multiscale model energetically benchmarked to collective system behavior captured by scattering experiments. Here, in this work, we show that both solution conditions (pH and ionic strength) and protein engineering (sequence and position of engineered silica-binding peptides) provide pathways for reversible control over growth and fragmentation, leading to clusters ranging in size from 25 nm protein-coated particles to micrometer-size aggregate. We further find that the higher electrolyte environment associated with successive cycles of base addition eventually eliminates reversibility. Our model accurately predicts these multiple length scales phenomena. The underpinning concepts provide design principles for the dynamic control of other protein- and particle-based nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Nonperturbatively renormalized nucleon gluon momentum fraction in the continuum limit of N f = 2 + 1 + 1 lattice QCD

We present the nonperturbatively renormalized nucleon gluon momentum fraction using ensembles with 2+1+1 flavors of highly improved staggered quarks (HISQ), generated by the MILC Collaboration. The calculation is done using clover fermions for the valence action with three pion masses, 220, 310, and 690 MeV, and three lattice spacings, 0.09, 0.12, and 0.15 fm. The renormalization is done using RI/MOM nonperturbative renormalization and using cluster-decomposition error reduction (CDER) to enhance the signal-to-noise ratio of the renormalization constant. We find the CDER technique is particularly important to improve the signal at the finer lattice ensembles where the lattice volume is larger. We extrapolate the gluon momentum fraction to the continuum-physical limit and obtain $\langle{x}\rangle$ g = 0.502⁢(53) stat+NPR ⁢(50) mixing in the $\overline{MS}$ scheme at 2 GeV, where first error includes the statistical error and uncertainties in nonperturbative renormalization, while the latter systematic error accounts for ignoring quark mixing. Our gluon momentum fraction is consistent with other recent lattice-QCD results at physical pion mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Existing evidence on the effects of climate variability and climate change on ungulates in North America: a systematic map

Abstract Background Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors. Climate conditions can directly impact ungulates via changes in the costs of thermoregulation and locomotion, or indirectly, via changes in habitat and forage availability, predation, and species interactions. Many studies have documented the effects of climate variability and climate change on North America’s ungulates, recording impacts to population demographics, physiology, foraging behavior, migratory patterns, and more. However, ungulate responses are not uniform and vary by species and geography. Here, we present a systematic map describing the abundance and distribution of evidence on the effects of climate variability and climate change on native ungulates in North America. Methods We searched for all evidence documenting or projecting how climate variability and climate change affect the 15 ungulate species native to the U.S., Canada, Mexico, and Greenland. We searched Web of Science, Scopus, and the websites of 62 wildlife management agencies to identify relevant academic and grey literature. We screened English-language documents for inclusion at both the title and abstract and full-text levels. Data from all articles that passed full-text review were extracted and coded in a database. We identified knowledge clusters and gaps related to the species, locations, climate variables, and outcome variables measured in the literature. Review findings We identified a total of 674 relevant articles published from 1947 until September 2020. Caribou ( Rangifer tarandus ), elk ( Cervus canadensis ), and white-tailed deer ( Odocoileus virginianus ) were the most frequently studied species. Geographically, more research has been conducted in the western U.S. and western Canada, though a notable concentration of research is also located in the Great Lakes region. Nearly 75% more articles examined the effects of precipitation on ungulates compared to temperature, with variables related to snow being the most commonly measured climate variables. Most studies examined the effects of climate on ungulate population demographics, habitat and forage, and physiology and condition, with far fewer examining the effects on disturbances, migratory behavior, and seasonal range and corridor habitat. Conclusions The effects of climate change, and its interactions with stressors such as land-use change, predation, and disease, is of increasing concern to wildlife managers. With its broad scope, this systematic map can help ungulate managers identify relevant climate impacts and prepare for future changes to the populations they manage. Decisions regarding population control measures, supplemental feeding, translocation, and the application of habitat treatments are just some of the management decisions that can be informed by an improved understanding of climate impacts. This systematic map also identified several gaps in the literature that would benefit from additional research, including climate effects on ungulate migratory patterns, on species that are relatively understudied yet known to be sensitive to changes in climate, such as pronghorn ( Antilocapra americana ) and mountain goats ( Oreamnos americanus ), and on ungulates in the eastern U.S. and Mexico.

Malpeli, Katherine C. (ORCID:000000030780918X)↗
DOE OSTI2026

Probing the Coherence of Metal Absorbers toward Background Quasar Pairs

Abstract We investigate the spatial coherence of metal absorption lines in the circumgalactic medium using 4115 quasar pairs from Sloan Digital Sky Survey DR16. We identify 184 Mg ii (15 with dual detections) and 50 C iv (11 with dual detections) absorber pairs. The fraction of pairs with fractional equivalent width difference δW r ≤ 0.5 declines with projected separation: for Mg ii , it drops from ∼52% at 0–25 kpc to ∼7% at 100–200 kpc, while for C iv , it decreases from ∼100% to ∼21% over 0–200 kpc. In every separation bin, C iv absorbers with δW r ≤ 0.5 maintain a higher fraction than Mg ii absorbers. Similar results are obtained when the nondetections are treated as 2 σ W r upper limits in a survival analysis. The transverse autocorrelation function shows strong Mg ii clustering within 0–25 kpc, whereas the C iv excess remains relatively flat out to ∼100 kpc. These findings suggest that high-ionization C iv gas retains coherence over larger transverse scales than low-ionization Mg ii gas, in agreement with previous lensed quasar and high-resolution studies.

Li, Jing [Guangxi University] (ORCID:0009000148751↗
DOE OSTI2020

The clustering of DESI-like luminous red galaxies using photometric redshifts

ABSTRACT We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging data set, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of 0.4 < z < 0.9 over 5655 deg2. We have developed new photometric redshift (photo-z) estimates using the Legacy Survey DECam and WISE photometry, with σNMAD = 0.02 precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalogue, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N-body catalogues, and present a new technique for finding best-fitting parameters in this situation. Accompanying this paper, we have released the Photometric Redshifts for the Legacy Surveys catalogue of photo-z’s obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 data set. This catalogue provides accurate photometric redshifts for objects with z < 21 over more than 16 000 deg2 of sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Learning nuclear cross sections across the chart of nuclides with graph neural networks

We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.

Machine learning↗