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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Particle Swarm Optimisation for group structure optimization for radiotherapy shielding

Neutron transport simulations are ubiquitous in nuclear engineering because they allow one to model experimental systems and render a model platform for easy perturbation of experimental designs. In addition, simulations allow one to gain experimental insight without actually having to go through the trouble of building a physical experiment. Neutron transport simulations can be stochastic or deterministic based. Stochastic neutron transport simulations are typically simulated using the Monte Carlo method and yield very accurate solutions but are computationally expensive, while deterministic methods are typically faster but can be less accurate. Here we focus on optimizing the accuracy of deterministic neutron transport simulations for radiotherapy simulations. Deterministic neutron transport requires discretization of angle, energy, and space to appropriately analyze the system one is trying to model. Discretization of energy is challenging because of the highly variable neutron flux at certain neutron energies. Improper discretization of energy in the transport model can lead to erroneous results and therefore inaccurate interpretations of the solution. In this study, we evaluate Particle Swarm Optimization (PSO) as a mechanism for selecting optimal group structures for radiotherapy shielding. We tested the particle swarm optimization algorithm on radiotherapy shielding problems using Los Alamos National Laboratory's (LANL) main deterministic transport code PARTISN. Results show that the optimized energy group structures generated from the optimization algorithm outperformed LANL's standard energy group structures, and therefore demonstrate utility in using PSO to expedite computation times due to the increased accuracy obtained with a smaller but optimized group structure. (authors)

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Variable-moment fluid closures with Hamiltonian structure

Abstract Based on ideas due to Scovel–Weinstein, I present a general framework for constructing fluid moment closures of the Vlasov–Poisson system that exactly preserve that system’s Hamiltonian structure. Notably, the technique applies in any space dimension and produces closures involving arbitrarily-large finite collections of moments. After selecting a desired collection of moments, the Poisson bracket for the closure is uniquely determined. Therefore data-driven fluid closures can be constructed by adjusting the closure Hamiltonian for compatibility with kinetic simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

In Situ Methods for Metal-Flux Synthesis in Inert Environments

Flux growth synthesis is an advantageous synthetic method as it allows for the growth of single crystals of both congruently melting and metastable phases. The determination of synthetic parameters for the flux growth of new crystalline phases is complex as many factors and parameters need to be considered, such as purity and morphology of starting material and heating profile variables including maximum temperature, dwell time, cooling rate and flux removal temperature. In situ monitoring of crystallite growth can lead to elucidation of reaction intermediates and growth mechanisms. The determination of pivotal reaction parameters can revolutionize the way growth parameters are selected. In this work, we report a new sample environment and furnace apparatus for synchrotron in situ synthesis of crystalline materials, including flux grown intermetallics.

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

Permafrost microbial communities and functional genes are structured by latitudinal and soil geochemical gradients

Permafrost underlies approximately one quarter of Northern Hemisphere terrestrial surfaces and contains 25–50% of the global soil carbon (C) pool. Permafrost soils and the C stocks within are vulnerable to ongoing and future projected climate warming. The biogeography of microbial communities inhabiting permafrost has not been examined beyond a small number of sites focused on local-scale variation. Permafrost is different from other soils. Perennially frozen conditions in permafrost dictate that microbial communities do not turn over quickly, thus possibly providing strong linkages to past environments. Thus, the factors structuring the composition and function of microbial communities may differ from patterns observed in other terrestrial environments. Here, we analyzed 133 permafrost metagenomes from North America, Europe, and Asia. Permafrost biodiversity and taxonomic distribution varied in relation to pH, latitude and soil depth. The distribution of genes differed by latitude, soil depth, age, and pH. Genes that were the most highly variable across all sites were associated with energy metabolism and C-assimilation. Specifically, methanogenesis, fermentation, nitrate reduction, and replenishment of citric acid cycle intermediates. This suggests that adaptations to energy acquisition and substrate availability are among some of the strongest selective pressures shaping permafrost microbial communities. The spatial variation in metabolic potential has primed communities for specific biogeochemical processes as soils thaw due to climate change, which could cause regional- to global- scale variation in C and nitrogen processing and greenhouse gas emissions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Multiplicity dependence of charged-particle intra-jet properties in pp collisions at $\sqrt{s}$ = 13 TeV

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. The mean charged particle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy $\sqrt{s}$ = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η| < 0.9) using the sequential recombination anti-k T algorithm with jet resolution parameters R = 0.2, 0.3, and 0.4 for the trans verse momentum (p T ) interval 5–110 GeV/c. The high multiplicity events are selected by the forward V0 scintilla tor detectors. The mean charged-particle multiplicity inside the leading jet cone rises monotonically with increasing jet p T in qualitative agreement with previous measurements at lower energies. The distributions of jet fragmentation function variables z ch and ξ ch are measured for different jet-p T intervals. Jet-p T independent fragmentation of leading jets is observed for wider jets except at high- and low-z ch values. The observed “hump-backed plateau” structure in the ξ ch distribution indicates suppression of low-p T particles. In high-multiplicity events, an enhancement of the fragmen tation probability of low-z ch particles accompanied by a suppression of high-zch particles is observed compared to minimum-bias events. This behavior becomes more promi nent for low-p T jets with larger jet radius. The results are compared with predictions of QCD-inspired event generators, PYTHIA 8 with Monash 2013 tune and EPOS LHC. It is found that PYTHIA 8 qualitatively reproduces the jet modification in high-multiplicity events except at high jet p T . These measurements provide important constraints to models of jet fragmentation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Development of Scalable Reactive Transport Framework for PFAS

Research on PFAS chemicals is extensive and covers all aspects, including analytical quantification, determination of properties, toxicology, ex situ treatment, and in situ remediation. PFAS chemicals are very stable and thus persistent/recalcitrant in the environment. Although there are many unknowns about PFAS chemicals, degradation pathways, reaction rates, etc., many different sorption, oxidation, reduction, biological, and innovative treatment approaches are being developed. Sorption with activated carbon is currently the only fully available in situ treatment technology for PFAS-impacted groundwater. Given the wide array of PFAS chemicals and transformation products, remediation may need multi-step treatment trains to fully address the PFAS contamination. The work here provides kinetic reaction modules that represent an initial cut at functionality representing PFAS migration and reaction in groundwater aquifer flow and transport models. One reaction kinetics module provides a method to model kinetically limited adsorption using a mass transfer model. The second reaction module represents biological transformation of 8:2 FTOH and daughter species, illustrating how a complex reaction pathway network can be represented. Both reaction modules allow for spatially variable parameter values so that a variety of remediation approaches (e.g., a PRB or volumetric treatment or variations in geochemical conditions) can be simulated. The intent with these PFAS reaction modules is to provide tools for practitioners to aid in the selection, design, and assessment of potential in situ PFAS remediation strategies. It is anticipated that, as PFAS remediation technologies and scientific understanding advances, these modules would be refined or replaced to match new knowledge.

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

Measurements of Nuclear Effects and the $\bar \nu_\mu +H \to \mu^+ + n$ Cross Section in MINERνA with Neutron Tagging

MINERνA, or Main INjector ExpeRiment for ν-A, at Fermilab, is an experimentdedicated to the study of neutrino-nucleus interactions in the GeV regime. Itsgoal is to illustrate the interplay between hadronic and nuclear physics and measure intranuclear dynamics crucial for the present and future neutrino oscillationmeasurements. We first measure a set of variables sensitive to how Monte Carlo(MC) simulations of neutrino-nucleus interactions implement binding energy andthen move on to measure the antineutrino CCQE cross section on the hydrogentargets in MINERνA’s CH detector. We have developed a method to preferentially select events on the hydrogen by comparing outgoing neutrons’ directions totheoretical neutron directions assuming two-body interactions. We measured thecross section, extracted the axial form factor, and performed a Z-expansion fit. Weobserve larger values in the axial form factor at high Q2than current best fits. Finally, we show a preliminary selection of events with both protons and neutrons toinvestigate nuclear processes responsible for producing these final states.

Cai, Tejin↗
DOE OSTI2023

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

Abstract Background and Aims New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae. Methods We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally. Key Results Using sliding-window population genetic analyses we find that differentiation is concentrated within ‘islands’ of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap. Conclusions We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth’s climate rapidly changes.

58 GEOSCIENCES↗
DOE OSTI2026

Transverse Kinematic Imbalance in MicroBooNE's New nue CC0pi Measurements

Neutrino-nucleus cross section measurements require accurate modelling of neutrino interactions. Neutrino beams are not monoenergetic, and the energy of each interaction must instead be modelled using nuclear interaction assumptions. This introduces significant systematic uncertainty into cross section measurements. Effects such as Fermi motion, nuclear correlations, and final-state interactions (FSI) smear the underlying quasi-elastic scattering signal, making it difficult to disentangle genuine quasi-elastic kinematics from nuclear effects across the full range of interaction channels (QE, MEC, RES, DIS) probed in these measurements. Transverse Kinematic Imbalance (TKI) variables, such as $\delta p_T$ and $\delta \alpha_T$, probe this same phase space by exploiting the fact that the incoming neutrino has zero transverse momentum ($\vec{p}_T^{\,\nu} = 0$). Any measured transverse imbalance in the final state therefore arises from nuclear effects rather than from uncertainty in the incident neutrino energy, allowing cross section measurements to select a phase space that is rich in quasi-elastic-like events with minimal contamination from FSI and other nuclear effects, independent of energy reconstruction. Recent unfolded MicroBooNE cross section measurements of electron-neutrino charged-current interactions with zero pions and at least one proton ($\nu_e$ CC0$\pi$, 1eNp0$\pi$) show that several leading nuclear interaction generators (including GENIE variants, NuWro, GiBUU, and NEUT) reproduce the differential cross section in electron energy reasonably well, but consistently struggle to describe the differential cross section in the cosine of the leading proton's angle, yielding lower $p$-values across all seven generators tested. This tension points to a more fundamental, kinematics-driven disagreement between data and generators that is not visible in energy-only cross section observables. This is precisely the regime TKI variables are designed to probe. Following previous TKI cross section measurements with muon-neutrino data in MicroBooNE, this poster presents the case for extending the TKI framework to electron-neutrino cross section measurements as a next step to isolate and characterize the source of the observed generator tension in proton kinematics.

Burridge, Jessica [U. Manchester (main)] (ORCID:00↗
DOE OSTI2022

Selective Dynamical Imaging of Interferometric Data

Recent developments in very long baseline interferometry (VLBI) have made it possible for the Event Horizon Telescope (EHT) to resolve the innermost accretion flows of the largest supermassive black holes on the sky. The sparse nature of the EHT’s (u, v)-coverage presents a challenge when attempting to resolve highly time-variable sources. We demonstrate that the changing (u, v)-coverage of the EHT can contain regions of time over the course of a single observation that facilitate dynamical imaging. These optimal time regions typically have projected baseline distributions that are approximately angularly isotropic and radially homogeneous. We derive a metric of coverage quality based on baseline isotropy and density that is capable of ranking array configurations by their ability to produce accurate dynamical reconstructions. We compare this metric to existing metrics in the literature and investigate their utility by performing dynamical reconstructions on synthetic data from simulated EHT observations of sources with simple orbital variability. We then use these results to make recommendations for imaging the 2017 EHT Sgr A* data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Do Genetic Drift and Gene Flow Affect the Geographic Distribution of Female Plants in Gynodioecious Lobelia siphilitica?

Variation in population sex ratio is particularly pronounced in gynodioecious angiosperms. Extremely high female frequencies in gynodioecious populations cannot be readily explained by selective forces alone. To assess the contributions of drift and gene flow to extreme sex-ratio variation, we documented sex ratio and population size in 92 populations of Lobelia siphilitica across its range and genotyped plants using plastid and nuclear genetic markers. Similarity in spatial patterns of genetic and demographic variables may suggest that drift and/or gene flow have contributed to population sex-ratio variation in L. siphilitica. We found strong spatial structuring of extremely high female frequencies: populations with >50% female plants are restricted to the south–central portion of the range. However, we did not detect any spatial structuring in population size nor metrics of genetic diversity, suggesting that extreme variation in female frequency is not strongly affected by drift or gene flow. Extreme sex-ratio variation is frequently observed in gynodioecious plants, but its causes are difficult to identify. Further investigation into mechanisms that create or maintain the spatial structure of sex ratios in gynodioecious species will provide much needed insight.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mediating Photochemical Reaction Rates at Lewis Acidic Rare Earths by Selective Energy Loss to 4f-Electron States

Manifesting chemical differences in individual rare earth (RE) element complexes is challenging due to the similar sizes of the tripositive cations and the corelike 4f shell. In this work, we disclose a new strategy for differentiating between similarly sized Dy 3+ and Y 3+ ions through a tailored photochemical reaction of their isostructural complexes in which the f-electron states of Dy 3+ act as an energy sink. Complexes RE(hfac) 3 (NMMO) 2 (RE = Dy (2-Dy) and Y (2-Y), hfac = hexafluoroacetylacetonate, and NMMO = N-methylmorpholine-N-oxide) showed variable rates of oxygen atom transfer (OAT) to triphenylphosphine under ultraviolet (UV) irradiation, as monitored by 1 H and 19 F NMR spectroscopies. Ultrafast transient absorption spectroscopy (TAS) identified the excited state(s) responsible for the photochemical OAT reaction or lack thereof. Competing sensitization pathways leading to excited-state deactivation in 2-Dy through energy transfer to the 4f electron manifold ultimately slows the OAT reaction at this metal cation. The measured rate differences between the open-shell Dy 3+ and closed-shell Y 3+ complexes demonstrate that using established principles of 4f ion sensitization may deliver new, selective modalities for differentiating the RE elements that do not depend on cation size.

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

Spectroscopic Studies of 30 Short-period Cataclysmic Variable Stars and Remarks on the Evolution and Population of Similar Objects

We present spectroscopy and orbital periods P {sub orb} for 30 apparently nonmagnetic cataclysmic binaries with periods below ∼3 hr, nearly all of which are dwarf novae, mostly of the SU Ursae Majoris subclass. We then turn to the evidence supporting the prediction that short-period dwarf novae evolve toward longer periods after passing through a minimum period—the “period bounce” phenomenon. Plotting data from the literature reveals that for superhump period excess ϵ = (P {sub sh} − P {sub orb})/P {sub orb} below ∼0.015, the period appears to increase with decreasing ϵ, agreeing at least qualitatively with the predicted behavior. Next, motivated by the long (decadal) outburst intervals of the WZ Sagittae subclass of short-period dwarf novae, we ask whether there could be a sizable population of “lurkers”—systems that resemble dwarf novae at minimum light, but which do not outburst over accessible timescales (or at all) and therefore do not draw attention to themselves. By examining the outburst history of the Sloan Digital Sky Survey sample of CVs, which were selected by color and not by outburst, we find that a large majority of the color-selected dwarf-nova-like objects have been observed to outburst, and we conclude that “lurkers,” if they exist, are a relatively minor part of the CV population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗
DOE OSTI2026

Climate change drives convergent evolution of root traits on Sky Island climate relicts

Roots are essential to the strategies plants use to survive in variable environments, yet we know little of how they vary within species. Experimental conditions demonstrate that intraspecific plant root traits respond strongly to variation in the environment; however, it is unclear when these responses can be characterized as evolution in response to selective pressures of climate change over many generations. Sky Islands are model, natural climate relict ecosystems to examine climate-change driven evolution. Utilizing a common garden with replicate genotypes of Populus angustifolia (Narrowleaf cottonwood) from six Sky Island (SI) populations and nine adjacent Mountain Chain (MC) populations across three genetic provenances, we hypothesized that SI root traits have diverged due to historical isolation in warmer, drier climates. When grown in common conditions, populations originating on SI’s showed convergent evolution across three distinct genetic provenances, which was characterized by 44.16% decreased total root length, 42.64% decreased average root volume, 43.31% decreased root surface area, and significantly less root trait variation, relative to adjacent mountain chains. Convergent evolution of root traits from trees originating on SI’s is correlated with changes in mean annual precipitation and potential evapotranspiration in the field over the past ~ 125 years. These results demonstrate a consistent pattern in root trait evolution at the landscape scale and the role of climate on the evolution of root traits in a genetic and geographic context relevant to climate change.

Convergent evolution↗
DOE OSTI2020

Policy-Driven Sustainable Saline Drainage Disposal and Forage Production in the Western San Joaquin Valley of California

Environmental policies to address water quality impairments in the San Joaquin River of California have focused on the reduction of salinity and selenium-contaminated subsurface agricultural drainage loads from westside sources. On 31 December 2019, all of the agricultural drainage from a 44,000 ha subarea on the western side of the San Joaquin River basin was curtailed. This policy requires the on-site disposal of all of the agricultural drainage water in perpetuity, except during flooding events, when emergency drainage to the River is sanctioned. The reuse of this saline agricultural drainage water to irrigate forage crops, such as ‘Jose’ tall wheatgrass and alfalfa, in a 2428 ha reuse facility provides an economic return on this pollutant disposal option. Irrigation with brackish water requires careful management to prevent salt accumulation in the crop root zone, which can impact forage yields. The objective of this study was to optimize the sustainability of this reuse facility by maximizing the evaporation potential while achieving cost recovery. This was achieved by assessing the spatial and temporal distribution of the root zone salinity in selected fields of ‘Jose’ tall wheatgrass and alfalfa in the drainage reuse facility, some of which have been irrigated with brackish subsurface drainage water for over fifteen years. Electromagnetic soil surveys using an EM-38 instrument were used to measure the spatial variability of the salinity in the soil profile. The tall wheatgrass fields were irrigated with higher salinity water (1.2–9.3 dS m -1 ) compared to the fields of alfalfa (0.5–6.5 dS m -1 ). Correspondingly, the soil salinity in the tall wheatgrass fields was higher (12.5 dS m -1 –19.3 dS m -1 ) compared to the alfalfa fields (8.97 dS mm -1 –14.4 dS mm -1 ) for the years 2016 and 2017. Better leaching of salts was observed in the fields with a subsurface drainage system installed (13–1 and 13–2). The depth-averaged root zone salinity data sets are being used for the calibration of the transient hydro-salinity computer model CSUID-ID (a one-dimensional version of the Colorado State University Irrigation Drainage Model). This user-friendly decision support tool currently provides a useful framework for the data collection needed to make credible, field-scale salinity budgets. In time, it will provide guidance for appropriate leaching requirements and potential blending decisions for sustainable forage production. This paper shows the tie between environmental drainage policy and the role of local governance in the development of sustainable irrigation practices, and how well-directed collaborative field research can guide future resource management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Corrosion testing needs and considerations for additively manufactured materials in nuclear reactors

Additive manufacturing (AM) technologies have developed rapidly in recent years, creating new opportunities and challenges for the nuclear industry; however, adoption requires that their corrosion performance be evaluated. Here, we discuss known reactor-specific corrosion issues for multiple reactor types and engineering concerns such as regulations and standards. A review of corrosion studies conducted on select AM alloys informs a discussion on key bulk and surface factors likely to impact corrosion behaviors. Recommendations to assess corrosion performance for AM materials are provided, including management of the unique nature of as-built AM surfaces and the inherent process variability that occurs for AM components.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Measurement of photonuclear jet production in ultraperipheral Pb + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with the ATLAS detector

In ultrarelativistic heavy ion collisions at the LHC, each nucleus acts a sources of high-energy real photons that can scatter off the opposing nucleus in ultraperipheral photonuclear (𝛾 + 𝐴) collisions. Hard scattering processes initiated by the photons in such collisions provide a novel method for probing nuclear parton distributions in a kinematic region not easily accessible to other measurements. ATLAS has measured production of dijet and multijet final states in ultraperipheral Pb + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV using a dataset recorded in 2018 with an integrated luminosity of 1.72 nb −1 . Photonuclear final states are selected by requiring a rapidity gap in the photon direction; this selects events where one of the outgoing nuclei remains intact. Jets are reconstructed using the anti-𝑘 t algorithm with radius parameter, 𝑅 = 0.4. Triple-differential cross sections, unfolded for detector response, are measured and presented using two sets of kinematic variables. The first set consists of the total transverse momentum (𝐻 T ), rapidity, and mass of the jet system. The second set uses 𝐻 T and particle-level nuclear and photon parton momentum fractions, 𝑥 A and 𝑧 𝛾 , respectively. The results are compared with leading-order perturbative QCD calculations of photonuclear jet production cross sections, where all leading order predictions using existing fits fall below the data in the shadowing region. More detailed theoretical comparisons will allow these results to strongly constrain nuclear parton distributions, and these data provide results from the LHC directly comparable to early physics results at the planned Electron-Ion Collider.

Parton distribution functions↗