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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dwarf Galaxies at Cosmic Noon: New JWST Constraints on Satellite Models and Subhalo Tidal Evolution

The advent of JWST has revolutionized the study of faint satellite galaxies at z ≳ 1, enabling statistical constraints on galaxy evolution and the galaxy–halo connection in a previously unexplored mass and redshift regime. We compare satellite abundances at 1 < z < 3.5 from recent JWST observations with predictions from cosmological dark-matter-only zoom-in simulations. We identify and quantify several sources of biases that can impact theoretical satellite counts, finding that assumptions about subhalo tidal evolution introduce the largest uncertainty in predictions for the satellite mass function. Using a flexible galaxy disruption model, we explore a range of disruption scenarios, spanning hydrodynamically motivated and idealized prescriptions, to bracket plausible physical outcomes. We show that varying galaxy durability can change the predicted satellite mass functions by a factor of ∼3.5. The JWST data and our fiducial model are consistent within 1σ–2σ across the full redshift (1 < z < 3.5) and stellar mass (M⋆ > 10 7 M ⊙ ) range probed. We find evidence that subhalos are at least as long-lived as predicted by hydrodynamic simulations. Our framework will enable robust constraints on the tidal evolution of subhalos with future observations. This work presents the first direct comparison between cosmological models and observations of the high-redshift satellite population in this low-mass regime. These results showcase JWST’s emerging power to test structure formation in the first half of the Universe in a new domain and to constrain the physical processes driving the evolution of low-mass galaxies across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Tussock tundra surface temperatures, ambient air and incoming photosynthetically active radiation measured at the NGEE Arctic Council site, 2021 - 2023

This dataset contains temperature measurements carried out along two fiber optics cables/lines (150 m each) laid out along the ground at the Next Generation Ecosystem Experiment (NGEE) Arctic site near Council, Alaska. The lines traverse an heterogeneous part of the tussock tundra site including thermokarst features and lichen dominated sections of the tundra. Measurements were done using a Sensornet Oryx DTS, a Distributed Temperature sensor that was installed in September 2021 and taken down in August 2023. The sensor was powered by solar power with data being collected every 30 minutes at 1 m resolution. In addition to these measurements air temperature and incoming photosynthetically active radiation (PAR) are provided. These measurements are co-located with the NGEE Arctic Council eddy flux and meteorological station (AmeriFlux ID US-NGC). Included are six *.csv files (four data files and two reporting format files) and two *.kml files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Air temperature↗
DOE OSTI2023

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? In conclusion, the analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Properties of the Prompt Optical Counterpart Arising from the Cooling of Electrons in Gamma-Ray Bursts

This work extends a contemporaneous effort to study the properties of the lower-energy counterpart synchrotron emission produced by the cooling of relativistic gamma-ray burst (GRB) electrons through radiation (synchrotron and self-Compton) emission and adiabatic losses. We derive the major characteristics (pulse duration, lag time after burst, and brightness relative to the burst) of the prompt optical counterpart (POC) occurring during or after the GRB. Depending on the magnetic field lifetime, duration of electron injection, and electron transit time Δt o from hard X-ray (GRB) to optical-emitting energies, a POC may appear during the GRB pulse (of duration δt γ ) or after (delayed OC). The signature of counterparts arising from the cooling of GRB electrons is that POC pulses (Δto < δtγ) last as long as the corresponding GRB pulse (δt o ≃ δt γ ), while delayed OC pulses (Δt o > δt γ ) last as long as the transit time (δt o ≃ Δt o ). If OC variability can be measured, then another signature for this OC mechanism is that the GRB variability is passed on to POCs but not to delayed OCs. Within the GRB electron cooling model for counterparts, POCs should be on average dimmer than delayed ones (consistent with the data), and harder GRB low-energy slopes β LE should be associated more often with the dimmer POCs. The latter sets an observational bias against detecting POCs from (the cooling of electrons in) GRBs with a hard slope β LE , making it more likely that the detected POCs of such bursts arise from another mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

New Physics in the Hot Electron Furnace (Final Report)

The primary purpose of this award was experiments and simulations related to the idea of a ‘Hot Electron Furnace’ where nonlocal heat transport would allow unique new experimental opportunities at x-ray free electron lasers. The period of this award included beamtime at the MEC endstation of the LCLS, and the execution of those experiments was a primary goal. Unfortunately, the beamtime had limited success due to (1) inability of the LCLS to deliver the expected two-color operations mode, and (2) failure of the MEC endstation’s own software to save the cavity timing data that would have allowed inference of time delays for the few hours when two-color mode briefly operated. The beamtime was then switched to operate in single-color (one pulse) mode, and studies were performed of x-ray heating and probe, simultaneously. Two interesting manuscripts are finally near submission, having been delayed by student graduations, need for collaborator simulations of x-ray heating processes, and then COVID. I am hopeful that they will soon be submitted (especially the paper on x-ray heating of MgO) because one of the principal students involved has returned from industry to take a postdoc position at SLAC. Below, we first list all publications and other work products (including the two that are nearing submission) and then summarize several outcomes from this effort. During the term of this award three UW physics graduate students were at least partially supported, and all three received their Ph.D.’s with significant components of their supported work in the dissertation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Protocols for x-ray transient grating pump/optical probe experiments at x-ray free electron lasers

Abstract Transient grating spectroscopy is a specialized application of the four-wave-mixing methodology and constitutes a versatile technique for investigating the dynamics of vibrational, magnetic and electronic degrees of freedom of matter in a background-free fashion. Recent developments in free-electron laser sources have enabled the extension of this technique into the extreme ultraviolet range. Ongoing efforts to expand transient grating spectroscopy into the x-ray regime promise numerous advantages: (1) substantial penetration depths that allow for probing bulk material properties, (2) element specificity via specific core-excited states, and (3) short wavelengths that allow for excitation gratings with higher momentum transfer and improved spatial resolution. In this study, we comprehensively outline the procedures for conducting x-ray transient grating pump/optical probe experiment. The process encompasses the design and alignment of the experimental setup, as well as the subsequent steps involved in data acquisition and analysis. This paper is intended as a comprehensive guide for researchers interested in implementing x-ray transient grating spectroscopy, providing valuable insights into the intricacies of the experimental workflow required for this novel technique. Furthermore, we discuss the potential for extending this methodology to an x-ray pump/x-ray probe scheme, envisioning a future direction that holds promise for enhancing the capabilities and scope of x-ray transient grating spectroscopy, opening new opportunities for studying ultrafast processes with unprecedented temporal and spatial resolutions.

Optics↗
DOE OSTI2023

Enhancing Nanoparticle Detection in Interferometric Scattering (iSCAT) Microscopy Using a Mask R-CNN

Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, in this paper, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.

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

The eROSITA Final Equatorial-Depth Survey (eFEDS)

Theoretical models of the co-evolution of galaxies and active galactic nuclei (AGNs) ascribe an important role in the feedback process to a short, luminous, obscured, and dust-enshrouded phase during which the accretion rate of the supermassive black hole is expected to be at its maximum and the associated AGN-driven winds are also predicted to be maximally developed. Here, to test this scenario, we have isolated a textbook candidate from the eROSITA Final Equatorial-Depth Survey (eFEDS) obtained within the performance and verification program of the eROSITA telescope on board the Spectrum Röntgen Gamma mission. From an initial catalogue of 246 hard X-ray selected sources that are matched with the photometric and spectroscopic information available within the eROSITA and Hyper Suprime-Cam consortia, three candidates quasars in the feedback phase have been isolated applying a diagnostic proposed previously. Only one source (eFEDS J091157.4+014327) has a spectrum already available (from SDSS-DR16, z = 0.603) and it unambiguously shows abroad component (full width at half maximum ~1650 kms –1 ) in the [OIII]5007 line. The associated observed L [OIII] is ~2.6 × 10 42 erg s –1 , one to two orders of magnitude higher than that observed in local Seyfert galaxies and comparable to those observed in a sample of z ~ 0.5 type 1 quasars. From the multi-wavelength data available, we derive an Eddington ratio (L bol /L Edd ) of ~0.25 and a bolometric correction in the hard X-ray band of k bol ~ 10, which is lower than the corrections observed for objects at similar bolometric luminosity. These properties, along with the outflow, the high X-ray luminosity, the moderate X-ray obscuration (L X ~10 44.8 erg s –1 , N H ~2.7 × 10 22 cm –2 ), and the red optical colour, all match the prediction of quasars in the feedback phase from merger-driven models. Forecasting to the full eROSITA all-sky survey with its spectroscopic follow-up, we predict that by the end of 2024, we will have a sample of few hundred such objects at z= 0.5–2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Using CESM-RESFire to understand climate–fire–ecosystem interactions and the implications for decadal climate variability

Large wildfires exert strong disturbance on regional and global climate systems and ecosystems by perturbing radiative forcing as well as the carbon and water balance between the atmosphere and land surface, while short- and long-term variations in fire weather, terrestrial ecosystems, and human activity modulate fire intensity and reshape fire regimes. The complex climate–fire–ecosystem interactions were not fully integrated in previous climate model studies, and the resulting effects on the projections of future climate change are not well understood. Here we use the fully interactive REgion-Specific ecosystem feedback Fire model (RESFire) that was developed in the Community Earth System Model (CESM) to investigate these interactions and their impacts on climate systems and fire activity. We designed two sets of decadal simulations using CESM-RESFire for present-day (2001–2010) and future (2051–2060) scenarios, respectively, and conducted a series of sensitivity experiments to assess the effects of individual feedback pathways among climate, fire, and ecosystems. Our implementation of RESFire, which includes online land–atmosphere coupling of fire emissions and fire-induced land cover change (LCC), reproduces the observed aerosol optical depth (AOD) from space-based Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products and ground-based AErosol RObotic NETwork (AERONET) data; it agrees well with carbon budget benchmarks from previous studies. We estimate the global averaged net radiative effect of both fire aerosols and fire-induced LCC at –0.59±0.52 W m –2 , which is dominated by fire aerosol–cloud interactions (–0.82±0.19 W m –2 ), in the present-day scenario under climatological conditions of the 2000s. The fire-related net cooling effect increases by ~170 % to –1.60±0.27 W m –2 in the 2050s under the conditions of the Representative Concentration Pathway 4.5 (RCP4.5) scenario. Such considerably enhanced radiative effect is attributed to the largely increased global burned area (+19 %) and fire carbon emissions (+100 %) from the 2000s to the 2050s driven by climate change. The net ecosystem exchange (NEE) of carbon between the land and atmosphere components in the simulations increases by 33 % accordingly, implying that biomass burning is an increasing carbon source at short-term timescales in the future. High-latitude regions with prevalent peatlands would be more vulnerable to increased fire threats due to climate change, and the increase in fire aerosols could counter the projected decrease in anthropogenic aerosols due to air pollution control policies in many regions. We also evaluate two distinct feedback mechanisms that are associated with fire aerosols and fire-induced LCC, respectively. On a global scale, the first mechanism imposes positive feedbacks to fire activity through enhanced droughts with suppressed precipitation by fire aerosol–cloud interactions, while the second one manifests as negative feedbacks due to reduced fuel loads by fire consumption and post-fire tree mortality and recovery processes. These two feedback pathways with opposite effects compete at regional to global scales and increase the complexity of climate–fire–ecosystem interactions and their climatic impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-pitch nano-accuracy surface profiler for strongly curved X-ray mirror metrology

We present our recent research and development effort on the Multi-Pitch Nano-accuracy Surface Profiler (MPNSP). This metrology instrument is developed to characterize strongly curved X-ray mirrors proposed to achieve diffraction-limited soft X-ray focusing for scientific applications at the synchrotron beamlines. The measurement process consists of forward-and-backward scans on the test mirror surface along its tangential direction at multiple pitch angles. Our research and development in this work aim to take the challenge of measuring strongly curved X-ray mirrors with a typical total slope range ≳10 mrad, while maintaining the Root Mean Square (RMS) value of measurement repeatability and self-consistency at 50 nrad RMS level. We first introduce the mechanical design, followed by a brief review of the mathematical model and the optimization algorithm for the MPNSP technique. By detecting the rotation axis of the mirror pitch with a machine vision approach, we can determine and then reduce the vertical distance between the pitch rotation axis and the test mirror surface to a sub-mm level. In addition, we describe a practical data acquisition procedure for strongly curved X-ray mirrors with a total slope range larger than the slope measuring range of the autocollimator used in the instrument. As a result, the proposed MPNSP measurements with different mirror orientations achieve remarkable self-consistency and reproducibility of < 50 nrad RMS in slope and < 0.5 nm RMS in height.

42 ENGINEERING↗
DOE OSTI2021

Follow-up observations for IceCube-170922A: Detection of rapid near-infrared variability and intensive monitoring of TXS 0506+056

Abstract We present our follow-up observations to search for an electromagnetic counterpart of the IceCube high-energy neutrino IceCube-170922A. Monitoring observations of a likely counterpart, TXS 0506+056, are also described. First, we quickly took optical and near-infrared images of seven flat-spectrum radio sources within the IceCube error region right after the neutrino detection and found a rapid flux decline of TXS 0506+056 in Kanata/HONIR J-band data. Motivated by this discovery, intensive follow-up observations of TXS 0506+056 were continuously performed, including our monitoring imaging observations, spectroscopic observations, and polarimetric observations in optical and near-infrared wavelengths. TXS 0506+056 showed a large-amplitude (∼1.0 mag) variability in a time scale of several days or longer, although no significant variability was detected in a time scale of a day or shorter. TXS 0506+056 also showed a bluer-when-brighter trend in optical and near-infrared wavelengths. Structure functions of the variabilities were examined and indicate that TXS 0506+056 is not a special blazar in terms of optical variability. Polarization measurement results of TXS 0506+056 are also discussed.

(galaxies:) BL Lacertae objects: general↗
DOE OSTI2025

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗
DOE OSTI2024

NIST: Soil Respiration, Moisture, Temperature, Chemistry; and Fine Root Measurements from a Transect Through a Forest Edge, Gaithersburg, Maryland, 2017-2021

This dataset contains soil respiration, moisture, temperature, and chemistry, as well as fine root measurements from the National Institute of Standards and Technology (NIST) Forested Optical Reference for Evaluating Sensor Technology (FOREST) research facility at Gaithersburg, Maryland. Measurements were taken at an existing transect array that begins in a grassy meadow, crosses a sharp forest edge, then a small stream, and finally extends upwards in the interior of the forest at the top of a ridge. There are 6 different landscape positions replicated across three transects in the array. Soil respiration was measured during growing seasons in 2017-2019 (2017-06-02 to 2020-02-27). Pedons (1 m3) were isolated from surrounding tree roots using trenching and a fabric to inhibit root ingrowth. Flux measurements inside the pedons were thus assumed to represent heterotrophic only respiration in 2019, and these fluxes were paired with nearby fluxes assumed to represent total respiration. Deep vertical probes measured volumetric moisture content and temperature at the same points in the array every 10 cm in depth to either 90 cm or 120 cm total depth, at 15 minute intervals, from 2019-2021 (2019-07-09 to 2021-09-10). Soil core samples were collected from each of the array points for three different months in early- to mid-2019 (2019-03-19 to 2019-07-10), at three depths each. Soils were analyzed for gravimetric moisture content; pH; total carbon, nitrogen, and phosphorus; texture; microbial biomass carbon, nitrogen, and phosphorus; extractable dissolved organic carbon, nitrogen, and phosphorus; extractable nitrate and ammonia; and extracellular hydrolytic enzyme activities. The fine roots were separated from the cores and segregated by plant functional type (grass or tree species) and if they were dead or alive. Fine roots were then measured for length, surface area, diameter, and dry mass. This dataset contains four data files in comma separated (*.csv) format. These data serve to deepen our understanding of root and soil processes at forest edges and in transitional zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Reconciling calculations and measurements of inverse bremsstrahlung absorption

It was recently shown that the use of Coulomb logarithms appropriate for bremsstrahlung radiation (rather than transport processes) along with corrections for the Langdon effect and ion screening reproduced measurements of collisional absorption in well-characterized underdense plasmas [D. Turnbull et al., Phys. Rev. Lett. 130, 145103 (2023)]. However, it was recognized at the time that the use of the standard absorption-reduction factor from Langdon's seminal paper was inconsistent with the use of Coulomb logarithms that are thermally averaged over a Maxwellian electron-velocity distribution function. A more accurate approach would be to average over the expected super-Gaussian distribution function while accounting for the Gaunt factor's velocity dependence, which somewhat mitigates the Langdon effect; however, at that time, this theory matched the data less well. This conflict is now eliminated with the additional insight that the ionization state of our mid-Z ion species (when present) was lower than had been assumed, as evidenced by the Thomson-scattering data and time-dependent Cretin simulations. We are now able to show that an improved treatment of the Langdon effect provides the best match to data. Otherwise, the prior conclusions remain unchanged. We also show an example of the substantial expected impact to the absorption rate in calculations of indirect-drive hohlraums.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Efficient analysis routines for single and double peaked Type 2 AGN spectra

Driven by the imminent need to rapidly process and classify millions of AGN spectra drawn from next generation astronomical facilities, we present a spectral fitting routine for Type 2 AGN spectra optimized for high volume processing, using the quasar spectral fitting library (qsfit). We analyse an optically selected sample of 813 luminous Type 2 AGN spectra at z < 0.83 from the Sloan Digital Sky Survey (SDSS) to qualify its performance. We report a median narrow line H α/H β Balmer decrement of 4.5 ± 0.8, alluding to the presence of dust in the narrow line region (NLR). We publish a specialized QSFIT fitting routine for high signal-to-noise ratio spectra and general fitting routine for double peaked Type 2 AGN spectra applied on a subsample of 45 spectra from our parent sample. We report a median red and blue peak velocity separation of 390 ± 60 kms −1 . No trend is found for red or blue peaks to exhibit systematically different luminosity or ionization properties. Emission line diagnostics show that the double peaks in all sources are illuminated by an AGN-powered ionizing continuum. Finally, we examine the morphology of host galaxies of our double peaked sample. We find double peaked Type 2 AGN reside in merging systems at a comparable frequency to single peaked AGN. This suggests that the double peaked AGN phenomenon is likely to have a bi-conical outflow origin in the majority of cases. We publicly release the code used for spectral analysis and produced catalogues used in this work.

79 ASTRONOMY AND ASTROPHYSICS↗