Search NASA⌕ Search

SEARCH · Search NASA

Results for “image analyses”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Are Phosphatidic Acids Ubiquitous in Mammalian Tissues or Overemphasized in Mass Spectrometry Imaging Applications?

Abstract Mass spectrometry imaging (MSI) is an invaluable tool for the spatial visualization of molecules in vivo. However, the question of whether observed annotations are endogenous or artificial (i. e., from in‐source fragmentation) is critical and has been largely unexplored in multimodal MSI. In matrix‐assisted laser desorption/ionization (MALDI)‐MSI datasets from researchers worldwide, PAs were found to represent up to 18 % of annotations in rat brain. Rat brain was additionally imaged here using nanospray desorption electrospray ionization (nano‐DESI), a softer ionization strategy. No PAs observed with MALDI were present in the nano‐DESI dataset. Further investigation strongly indicated lipid fragmentation to PAs for MALDI‐MSI, but not with nano‐DESI‐MSI. We finally extend this observation to the MALDI‐MSI analyses of human tissues, showing that PA annotations comprised up to 16 % of annotations. Therefore, this study shows that MSI annotations should be carefully interrogated, as in‐source fragmentation or modification of lipids may contribute substantially to false annotations and incorrect biological interpretations.

Vandergrift, Gregory W.↗
DOE OSTI2022

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The mechanics of brittle granular materials with coevolving grain size and shape

The influence of particle shape on the mechanics of sand is widely recognized, especially in mineral processing and geomechanics. However, most existing continuum theories for engineering applications do not encompass the morphology of the grains and its evolution during comminution. Similarly, the relatively few engineering models accounting for grain-scale processes tend to idealize particles as spheres, with their diameters considered as the primary and sole geometric descriptor. This paper inspires a new generation of constitutive laws for crushable granular continua with arbitrary, yet evolving, particle morphology. We explore the idea of introducing multiple grain shape descriptors into Continuum Breakage Mechanics (CBM), a theory originally designed to track changes in particle size distributions during confined comminution. We incorporate the influence of these descriptors on the elastic strain energy potential and treat them as dissipative state variables. In analogy with the original CBM, and in light of evidence from extreme fragmentation in nature, the evolution of the additional shape descriptors is postulated to converge towards an attractor. Comparisons with laboratory experiments, discrete element analyses and particle-scale fracture models illustrate the encouraging performance of the theory. The theory provides insights into the feedback among particle shape, compressive yielding and inelastic deformation in crushable granular continua. These results inspire new questions that should guide future research into crushable granular systems using particle-scale imaging and computations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Geospatial Data Platform for All

Spatiotemporal data has evolved in scale due to augmented use in cross-domain applications. Simultaneously, there is substantial growth in the availability of Geographic Information Systems (GIS) data provided by the United States Geological Survey (USGS) along with other federal, state, county, or local agencies through open-data portals and public access APIs. However, data availability does not equate with accessibility. Large-scale analyses and applications require robust, performant data management with co-location of data storage and computing. The insufficiency of data management infrastructure compels researchers to adopt ad hoc project- specific GIS data storage solutions (e.g., copying data to High-Performance computer file systems). As an ad hoc storage strategy does not scale, it hampers cross-domain analyses causing difficulty in data reuse and utilizing existing code bases. Furthermore, GIS data is complex and requires expertise to analyze and manipulate due to its intricate data structures and data-specific projection transformations. Despite the challenges, we recognize that derived GIS data products, e.g., satellite or LIDAR-based images, can be used in downstream applications such as AI by domain, but non-GIS experts. To address the data needs and overcome the challenges, we are working towards a GIS Data Platform focused on efficient data storage, data discovery and access, and an API to enable common workflows. We propose a knowledge-graph (KG) approach for data discovery, whereby datasets are semantically linked to higher- level constructs such as projects and research areas. The semantic data links enable researchers to explore datasets in a top-down approach by specifying relevant and meaningful terms (assists in finding hidden data). An advantage is that the nodes and edges in a knowledge graph create built-in semantic documentation. Deeper spatiotemporal connections between data sources can be encoded via Graph Neural Networks (GNN) (Zhang et al., 2021). The KG approach can be extended to integrate the data itself in a Virtual KG (VKG). Our work will derive inspiration from large-scale VKG efforts that have been undertaken or are currently underway as part of the OpenStreetMap project (Ding et al., 2021). For DOE Data Days, we share the proposed geospatial data platform hybrid (cloud/on-prem) architecture, our work-to-date on storing, retrieving, and transforming LiDAR and raster data relevant to two important NREL use-cases, including the Renewable Energy Potential (reV) Model, and present our proposal for a KG based data discovery engine.

data platform↗
DOE OSTI2021

A transmission hologram for slitless spectrophotometry on a convergent telescope beam. 1. Focus and resolution

We report in this paper the test of a plane holographic optical element to be used as an aberration-corrected grating for a slitless spectrograph, inserted in a convergent telescope beam. Our long-term objective is the optimization of a specific hologram to switch the auxiliary telescope imager of the Vera Rubin Observatory into an accurate slitless spectrograph, dedicated to the atmospheric transmission measurement. We present and discuss here the promising results of tests performed with prototype holograms at the CTIO $0.9\,$m telescope during a run of 17 nights in 2017 May–June. After their on-sky geometrical characterization, the performances of the holograms as aberration-balanced dispersive optical elements have been established by analysing spectra obtained from spectrophotometric standard stars and narrow-band emitter planetary nebulae. Thanks to their additional optical function, our holographic disperser prototypes allow us to produce significantly better focused spectra within the full visible wavelength domain $[370,1050]\,$nm than a regular grating, which suffers from strong defocusing and aberrations when used in similar conditions. We show that the resolution of our slitless on-axis spectrograph equipped with the hologram approaches its theoretical performance. While estimating the benefits of a hologram for the spectrum resolution, the roadmap to produce a competitive holographic element for the Vera Rubin Observatory auxiliary telescope has been established.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Near-wake dynamics of a vertical-axis turbine

Cross-flow, or vertical-axis, turbines are a promising technology for capturing kinetic energy in wind or flowing water and their inherently unsteady fluid mechanics present unique opportunities for control optimization of individual rotors or arrays. To explore the potential for beneficial interactions between turbines in an array, as well as to characterize important cycle-to-cycle variations, coherent structures in the wake of a single two-bladed cross-flow turbine are examined using planar stereo particle image velocimetry in a water channel experiment. There are three main objectives in the present work. First, the mean wake structure of this high chord-to-radius ratio rotor is described, compared with previous studies, and a simple explanation for observed wake deflection is presented. Second, the unsteady flow is then analysed via the triple decomposition, with the periodic component extracted using a combination of traditional techniques and a novel implementation of the optimized dynamic mode decomposition. The latter method is shown to outperform conditional averaging and Fourier methods, as well as uncover frequencies suggesting a transition to bluff-body shedding in the far wake. Third, vorticity and finite-time Lyapunov exponents are then employed to further analyse the oscillatory wake component. Vortex streets on both sides of the wake are identified, and their formation mechanisms and effects on the mean flow are discussed. Strong axial (vertical) flow is observed in vortical structures shed on the retreating side of the rotor where the blades travel downstream. Time-resolved tracking of these vortices is performed, which demonstrates that vortex trajectories have significant rotation-to-rotation variation within one diameter downstream. This variability suggests it would be challenging to harness or avoid such structures at greater downstream distances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog

Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, astronomical imaging surveys. Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, star-galaxy classification, and photometric performance. We present here a source injection catalog of 146 million injections spanning the entire 5000 deg 2 DES footprint, generated using the Balrog SSI pipeline. Through this SSI sample, we demonstrate that the DES Year 6 (Y6) image processing pipeline provides accurate estimates of the object properties, for both galaxies and stars, at the percent-level, and we highlight specific regimes where the accuracy is reduced. We then show the consistency between SSI and data catalogs, for all galaxy samples developed within the weak lensing and galaxy clustering analyses of DES Y6. The consistency between the two catalogs also extends to their correlations with survey observing properties (seeing, airmass, depth, extinction, etc.). Lastly, we highlight a number of applications of this catalog to the DES Y6 cosmology analysis, such as estimates of the redshift distribution and lens magnification. This dataset is the largest SSI catalog produced at this fidelity and will serve as a key testing ground for exploring the utility of SSI catalogs in upcoming surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Defect and structural evolution under high-energy ion irradiation informs battery materials design for extreme environments

Understanding defect evolution and structural transformations constitutes a prominent research frontier for ultimately controlling the electrochemical properties of advanced battery materials. Herein, for the first time, we utilize in situ high-energy Kr ion irradiation with transmission electron microscopy to monitor how defects and microstructures evolve in Na- and Li-layered cathodes with 3d transition metals. Our experimental and theoretical analyses reveal that Li-layered cathodes are more resistant to radiation-induced structural transformations, such as amorphization than Na-layered cathodes. The underlying mechanism is the facile formation of Li-transition metal antisite defects in Li-layered cathodes. The quantitative mathematical analysis of the dynamic bright-field imaging shows that defect clusters preferentially align along the Na/Li ion diffusion channels ( a-b planes), which is likely governed by the formation of dislocation loops. Our study provides critical insights into designing battery materials for extreme irradiation environments and understanding fundamental defect dynamics in layered oxides.

25 ENERGY STORAGE↗
DOE OSTI2022

3D isotope density measurements by energy-resolved neutron imaging

Abstract Tools for three-dimensional elemental characterization are available on length scales ranging from individual atoms, using electrons as a probe, to micrometers with X-rays. However, for larger volumes up to millimeters or centimeters, quantitative measurements of elemental or isotope densities were hitherto only possible on the surface. Here, a novel quantitative elemental characterization method based on energy-resolved neutron imaging, utilizing the known neutron absorption cross sections with their ‘finger-print’ absorption resonance signatures, is demonstrated. Enabled by a pixilated time-of-flight neutron transmission detector installed at an intense short-pulsed spallation neutron source, for this demonstration 3.25 million state-of-the-art nuclear physics neutron transmission analyses were conducted to derive isotopic densities for five isotopes in 3D in a volume of 0.25 cm 3 . The tomographic reconstruction of the isotope densities provides elemental maps similar to X-ray microprobe maps for any cross section in the probed volume. The bulk isotopic density of a U-20Pu-10Zr-3Np-2Am nuclear transmutation fuel sample was measured, agrees well with mass-spectrometry and is evidence of the accuracy of the method.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles

The latest generation of geostationary satellites provide Earth observations similar to widely used polar-orbiting sensors but at intervals as frequently as every 5–10 min, making them ideal for studying the diurnal dynamics of land–atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations (GeCGO) dataset for terrestrial ecosystem studies and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 km × 10 km area surrounding 1586 network sites across the Americas. GeCGO makes it easy to compare the time series of geostationary data with the diurnal ground observations, including carbon/water fluxes and aerosol optical depth, and is extensible to other regions. We also develop GeoNEXTools to facilitate analyses that require both GeoNEX data and other NASA satellite data. The objectives of this paper are to introduce GeCGO and GeoNEXTools and demonstrate their applications. First, we describe the details of GeCGO and GeoNEXTools. Second, we explain how GeCGO can be integrated with other satellite data. Finally, we showcase comparisons between GeCGO and observations from three ground-based networks. GeCGO is available at https://doi.org/10.25966/y5pe-xp41 (Hashimoto et al., 2025).

Hashimoto, Hirofumi [NASA Ames Research Center (AR↗
DOE OSTI2026

Advancing Artificial Intelligence with Liquid Argon Neutrino Experiments (Technical Report)

The grant allowed two main contributions: 1) The development of a first successful demonstration of the employment of Optimal Transport in liquid argon time projection chamber neutrino detectors. Optimal Transport, used in other contexts and specifically with LHC calorimetric data, was adapted to address a key particle identification challenge in LArTPCs: the separation of pi0 backgrounds from single-electrons produced in charged-current electron neutrino interactions. The work, leveraging ML methods such as k-nearest-neighbor (kNN) and support-vector-machine (SVM), showed an increase in background rejection of a factor of two or more. Work is now ongoing to incorporate this development in physics analyses for LArTPC experiments and more broadly expand the use of OT in LArTPC detectors including DUNE. This work was done in collaboration with the phenomenology group led by Nathaniel Craig at UCSB. 2) The deployment of NuGraph2, a graph neural network developed for LArTPC reconstruction, in the MicroBooNE experiment. NuGraph2 uses novel graph-neural-network methods on the rather simple LArTPC inputs of reconstructed hits, greatly simplifying the workflow compared to the use of waveform or signal-deconvolved wire ROIs. The network performed particle classification and was shown to address many challenging problems in LArTPC imaging including track-shower separation and the identification of protons and charged pions from primary muons. Our group collaborated with Giuseppe Cerati (FNAL scientist) who is one of the core developers of NuGraph2 to integrate this tool in MicroBooNE’s analysis framework. This consisted in tow key contributions: a) Studying performance on real data, which came with several months of iterations because the MC-trained version of the network was found to show significant bias that our group investigated and addressed. b) Integrating the output hit labeling of NuGraph2 into the existing particle tracking and shower reconstruction code. As a result of this work led by our team NuGraph2 is now enabling a suite of new analyses which benefit from enhanced capabilities and thus broader physics reach. The grant supported primarily the salary of UCSB graduate student Chuyue “Michaelia” Fang as well as partial summer salary support for PI Caratelli. Some funds were used for travel by Michaelia to ML related schools and conferences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Variability and associated uncertainty in image analysis for soiling characterization in solar energy systems

The accumulation of soiling on photovoltaic modules and on the mirrors of concentrating solar power systems causes non-negligible energy losses with economic consequences. These challenges can be mitigated, or even prevented, through appropriate actions if the magnitude of soiling is known. Particle counting analysis is a common procedure to characterize soiling, as it can be easily performed on micrographs of glass coupons or solar devices that have been exposed to the environment. Particle counting does not, however, yield invariant results across institutions. The particle size distribution analysis is affected by the operator of the image analysis software and the methodology utilized. The results of a round-robin study are presented in this work to explore and elucidate the uncertainty related to particle counting and its effect on the characterization of the soiling of glass surfaces used in solar energy conversion systems. An international group of soiling experts analyzed the same 8 micrographs using the same open-source ImageJ software package. The variation in the particle analyses results were investigated to identify specimen characteristics with the lowest coefficient of variation (CV) and the least uncertainty among the various operators. The mean particle diameter showed the lowest CV among the investigated characteristics, whereas the number of particles exhibited the largest CV. Additional parameters, such as the fractional area coverage by particles and parameters related to the distribution's shape yielded intermediate CV values. These results can provide insights on the magnitude inter-lab variability and uncertainty for optical and microscope-based soiling monitoring and characterization.

14 SOLAR ENERGY↗
DOE OSTI2022

Nanotubes from the Misfit Layered Compound (SmS) 1.19 TaS 2 : Atomic Structure, Charge Transfer, and Electrical Properties

Misfit layered compounds (MLCs) MX-TX 2 , where M, T = metal atoms and X = S, Se, or Te, and their nanotubes are of significant interest due to their rich chemistry and unique quasi-1D structure. In particular, LnX-TX 2 (Ln = rare-earth atom) constitute a relatively large family of MLCs, from which nanotubes have been synthesized. The properties of MLCs can be tuned by the chemical and structural interplay between LnX and TX 2 sublayers and alloying of each of the Ln, T, and X elements. In order to engineer them to gain desirable performance, a detailed understanding of their complex structure is indispensable. MLC nanotubes are a relative newcomer and offer new opportunities. In particular, like WS 2 nanotubes before, the confinement of the free carriers in these quasi-1D nanostructures and their chiral nature offer intriguing physical behavior. High-resolution transmission electron microscopy in conjunction with a focused ion beam are engaged to study SmS-TaS 2 nanotubes and their cross-sections at the atomic scale. The atomic resolution images distinctly reveal that Ta is in trigonal prismatic coordination with S atoms in a hexagonal structure. Furthermore, the position of the sulfur atoms in both the SmS and the TaS 2 sublattices is revealed. X-ray photoelectron spectroscopy, electron energy loss spectroscopy, and X-ray absorption spectroscopy are carried out. These analyses conclude that charge transfer from the Sm to the Ta atoms leads to filling of the Ta 5d z 2 level, which is confirmed by density functional theory (DFT) calculations. Transport measurements show that the nanotubes are semimetallic with resistivities in the range of 10 –4 Ω·cm at room temperature, and magnetic susceptibility measurements show a superconducting transition at 4 K.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Real-time mixed reality display of dual particle radiation detector data

Radiation source localization and characterization are challenging tasks that currently require complex analyses for interpretation. Mixed reality (MR) technologies are at the verge of wide scale adoption and can assist in the visualization of complex data. Herein, we demonstrate real-time visualization of gamma ray and neutron radiation detector data in MR using the Microsoft HoloLens 2 smart glasses, significantly reducing user interpretation burden. Radiation imaging systems typically use double-scatter events of gamma rays or fast neutrons to reconstruct the incidence directional information, thus enabling source localization. The calculated images and estimated ’hot spots’ are then often displayed in 2D angular space projections on screens. By combining a state-of-the-art dual particle imaging system with HoloLens 2, we propose to display the data directly to the user via the head-mounted MR smart glasses, presenting the directional information as an overlay to the user’s 3D visual experience. We describe an open source implementation using efficient data transfer, image calculation, and 3D engine. We thereby demonstrate for the first time a real-time user experience to display fast neutron or gamma ray images from various radioactive sources set around the detector. We also introduce an alternative source search mode for situations of low event rates using a neural network and simulation based training data to provide a fast estimation of the source’s angular direction. Using MR for radiation detection provides a more intuitive perception of radioactivity and can be applied in routine radiation monitoring, education & training, emergency scenarios, or inspections.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys

Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r -band observations of 40 deg 2 to 10 yr LSST depth. In this paper, we present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N -body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (ℓ > 1200), highlighting the impact of blending in studies at small angular scales in LSST.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Supernova siblings and their parent galaxies in the Zwicky Transient Facility Bright Transient Survey

ABSTRACT Supernova (SN) siblings – two or more SNe in the same parent galaxy – are useful tools for exploring progenitor stellar populations as well as properties of the host galaxies such as distance, star-formation rate, dust extinction, and metallicity. Since the average SN rate for a Milky Way-type galaxy is just one per century, a large imaging survey is required to discover an appreciable sample of SN siblings. From the wide-field Zwicky Transient Facility (ZTF) Bright Transient Survey (which aims for spectroscopic completeness for all transients which peak brighter than r < 18.5 mag) we present 10 SN siblings in five parent galaxies. For each of these families, we analyse the SN’s location within the host and its underlying stellar population, finding agreement with expectations that SNe from more massive progenitors are found nearer to their host core and in regions of more active star formation. We also present an analysis of the relative rates of core collapse and thermonuclear SN siblings, finding a significantly lower ratio than past SN sibling samples due to the unbiased nature of the ZTF.

Graham, Melissa L. (ORCID:0000000291543136)↗
DOE OSTI2022

Computed Tomography Scanning and Geophysical Measurements of the Patterson #5-25 Well in Western Kansas

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) site in Morgantown, West Virginia, were used to characterize core from the Patterson Field site. This core came from a vertical well (Patterson #5-25 well) that was obtained as part of the U.S. Department of Energy (DOE) sponsored Integrated Midcontinental Stacked Carbon Storage Hub. The primary impetus of this work is a collaboration between NETL and the Kansas Geological Survey to characterize core from the Patterson Field site. The 625 ft of whole core from the Atoka Formation to Precambrian Basement was characterized at NETL. As part of this effort, bulk scans of core were obtained. This report, and the associated scans, provide detailed datasets not typically made publicly available for carbon capture utilization and storage analysis. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/patterson-5-25-well. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. None of the equipment used was suitable for direct visualization of the shale pore space, although fractures and discontinuities were detectable with the methods tested. Low resolution CT imagery with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with x-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL are useful in identifying zones of interest for more detailed analysis as well as fractured zones. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provided a multi-scale analysis of this core and provided both a macro and micro description of the core that is relevant for many subsurface energy related examinations that have traditionally been performed at NETL.

58 GEOSCIENCES↗
DOE OSTI2023

Disentangling the Hadronic Components in NGC 1068

The recent detection of high-energy neutrinos by IceCube in the direction of the nearby Seyfert/starburst galaxy NGC 1068 implies that radio-quiet active galactic nuclei can accelerate cosmic-ray ions. Dedicated multimessenger analyses suggest that the interaction of these high-energy ions with ambient gas or photons happens in a region of the galaxy that is highly opaque for GeV–TeV gamma rays. Otherwise, the GeV–TeV emission would violate existing constraints provided by the Fermi Large Area Telescope (LAT) and the Major Atmospheric Gamma Imaging Cherenkov. The conditions of high optical depth are realized near the central supermassive black hole (SMBH). At the same time, the GeV emission detected by the Fermi LAT is likely related to the galaxy’s sustained star formation activity. In this work, we derive a 20 MeV–1 TeV spectrum of NGC 1068 using 14 yr of Fermi LAT observations. We find that the starburst hadronic component is responsible for NGC 1068's emission above ~500 MeV. However, below this energy, an additional component is required. In the 20–500 MeV range, the Fermi LAT data are consistent with hadronic emission initiated by non-thermal ions interacting with gas or photons in the vicinity of the central SMBH. This highlights the importance of the MeV band to discover hidden cosmic-ray accelerators.

79 ASTRONOMY AND ASTROPHYSICS↗