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DOE OSTI2019

Searching for Quantum Black Hole Structure with the Event Horizon Telescope

The impressive images from the Event Horizon Telescope (EHT) sharpen the conflict between our observations of gravitational phenomena and the principles of quantum mechanics. Two related scenarios for reconciling quantum mechanics with the existence of black hole-like objects, with “minimal” departure from general relativity and local quantum field theory, have been explored; one of these could produce signatures visible to EHT observations. A specific target is temporal variability of images, with a characteristic time scale determined by the classical black hole radius. The absence of evidence for such variability in the initial observational span of seven days is not expected to strongly constrain such variability. Theoretical and observational next steps towards investigating such scenarios are outlined.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data

Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Evolution of (p)ppGpp-HPRT regulation through diversification of an allosteric oligomeric interaction

The alarmone (p)ppGpp regulates diverse targets, yet its target specificity and evolution remain poorly understood. Here, we elucidate the mechanism by which basal (p)ppGpp inhibits the purine salvage enzyme HPRT by sharing a conserved motif with its substrate PRPP. Intriguingly, HPRT regulation by (p)ppGpp varies across organisms and correlates with HPRT oligomeric forms. (p)ppGpp-sensitive HPRT exists as a PRPP-bound dimer or an apo- and (p)ppGpp-bound tetramer, where a dimer-dimer interface triggers allosteric structural rearrangements to enhance (p)ppGpp inhibition. Loss of this oligomeric interface results in weakened (p)ppGpp regulation. Our results reveal an evolutionary principle whereby protein oligomerization allows evolutionary change to accumulate away from a conserved binding pocket to allosterically alter specificity of ligand interaction. This principle also explains how another (p)ppGpp target GMK is variably regulated across species. Since most ligands bind near protein interfaces, we propose that this principle extends to many other protein–ligand interactions.

Life Sciences & Biomedicine - Other Topics↗

DOE OSTI2019

Evolution of (p)ppGpp-HPRT regulation through diversification of an allosteric oligomeric interaction

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

Interplanetary meteoroid debris in LDEF metal craters

The extraterrestrial meteoroid residue found lining craters in the Long Duration Exposure Facility (LDEF) aluminum and gold targets is highly variable in both quantity and type. In typical craters only a minor amount of residue is found and for these craters it is evident that most of the impacting projectile was ejected during crater formation. Less than 10 percent of the craters greater than 100 microns contain abundant residue consistent with survival of a major fraction of the projectile. In these cases the residue can be seen optically as a dark liner and it can easily be analyzed by SEM-EDX techniques. Because they are rare, the craters with abundant residue must be a biased sampling of the meteoroids reaching the earth. Factors that favor residue retention are low impact velocity and material properties such as high melting point. In general, the SEM-EDX observations of crater residues are consistent with the properties of chondritic meteorites and interplanetary dust particles collected in the stratosphere. Except for impacts by particles dominated by single minerals such as FeS and olivine, most of the residue compositions are in broad agreement with the major element compositions of chondrites. In most cases the residue is a thin liner on the crater floor and these craters are difficult to quantitatively analyze by EDX techniques because the electron beam excites both residue and underlying metal substrate. In favorable cases, the liner is thick and composed of vesicular glass with imbedded FeNi, sulfide and silicate grains. In the best cases of meteoroid preservation, the crater is lined with large numbers of unmelted mineral grains. The projectiles fragmented into micron sized pieces but the fragments survived without melting. In one case, the grains contain linear defects that appear to be solar flare tracks. Solar flare tracks are common properties of small interplanetary particles and their preservation during impact implies that the fragments were not heated above 600 C. We are investigating the meteoroid fragments in LDEF metal craters to determine the properties of interplanetary dust and to determine if there are meteoroid types that are overlooked or otherwise undetected in cosmic dust collections obtained from the stratosphere and polar ice.

Brownlee, D. E.↗

NASA NTRS2002

Prelaunch Instrument Calibration in the Real World: The GOES Example

The pre-launch ground infrared calibration of the Geostationary Operational Environmental Satellite (GOES) N-Q Imager and Sounder is presented. Ground calibration provides information necessary to the accurate on-orbit calibration of these radiometers. Infrared channels are calibrated in a thermal vacuum environment, under minimum and maximum mission operation temperatures, using a variable-temperature warm target to simulate the Earth scene and a cold target to simulate the space scene. Brightness temperatures derived from observation of the instrument internal calibration target, used for on-orbit calibration, are compared to brightness temperatures of the external calibration target as a check of relative accuracy using these two sources. Changes to the GOES N-Q specification from GOES I-M are highlighted, as well as results of noise, relative calibration accuracy, and spectral response performance to date. For completeness, results of spatial and pointing performance will be presented. Enhancements to test methodology and data processing techniques are highlighted throughout.

Murphy-Morris, J.↗

NASA NTRSDate not supplied

Using Controlled Impact Experiments to Understand the Effects of Cohesive Blocks on the Cratering Process

When considering large-scale impact events that occur in the gravity-regime, smallscale target heterogeneities (on order of the projectile diameter) are anticipated to have a minimal effect on the cratering process and are therefore not considered in scaling relations [1-3]. Such heterogeneities and other details of the target's strength and structure, however, become increasingly influential as the magnitude of the impact decreases [4]. At the scale of craters forming mostly in regolith on the Moon (< a few meters), for example, target properties such as cohesive strength, density, porosity, and friction have more leverage than gravity to influence the resultant crater dimensions [5]. Further complications beyond just target properties can manifest in many forms, such as subsurface layers [6]; the presence of random, competent blocks [7]; buried lenses of impact melt; and/or pockets of regolith compacted or indurated to varying degrees by previous impacts. Summing the total effect of target properties and any additional heterogeneities for integration into scaling relations is not straightforward, as each individual parameter will have unequal, and so far, unquantified, effects on the final crater. Even when craters are produced under a best-case scenario of controlled laboratory conditions, understanding the entire relevant parameter space can be a formidable task, and deconvolution of all the contributing factors can be a complex undertaking. To begin the process of quantifying such effects, we are conducting an extensive series of impact experiments to build a framework for the interpretation of craters observed on the characteristically complex surfaces throughout the solar system. Here we present the first, and simplest, configuration to be examined in this multi-year experimental campaign: one in which solitary, cohesive blocks are placed in the path of the projectile’s trajectory at different burial depths in granular, sand targets. Among the variables to be investigated in this configuration are the influence of block size, compressive strength, and burial depth.

impact crater↗

DOE OSTI2019

The ASAS-SN catalogue of variable stars – IV. Periodic variables in the APOGEE survey

ABSTRACT We explore the synergy between photometric and spectroscopic surveys by searching for periodic variable stars among the targets observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) using photometry from the All-Sky Automated Survey for Supernovae (ASAS-SN). We identified 1924 periodic variables among more than $258\, 000$ APOGEE targets; 465 are new discoveries. We homogeneously classified 430 eclipsing and ellipsoidal binaries, 139 classical pulsators (Cepheids, RR Lyrae, and δ Scuti), 719 long-period variables (pulsating red giants), and 636 rotational variables. The search was performed using both visual inspection and machine learning techniques. The light curves were also modelled with the damped random walk stochastic process. We find that the median [Fe/H] of variable objects is lower by 0.3 dex than that of the overall APOGEE sample. Eclipsing binaries and ellipsoidal variables are shifted to a lower median [Fe/H] by 0.2 dex. Eclipsing binaries and rotational variables exhibit significantly broader spectral lines than the rest of the sample. We make ASAS-SN light curves for all the APOGEE stars publicly available and provide parameters for the variable objects.

Pawlak, Michał↗

DOE OSTI2025

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗

DOE OSTI2020

Emulating climate extreme indices

We use simple pattern scaling and time-shift to emulate changes in a set of climate extreme indices under future scenarios, and evaluate the emulators' accuracy. We propose a metric for the error in emulation in the context of initial condition ensembles, to specifically characterize the role of internal variability in the emulation performance. Our metric separates systematic emulation errors from unavoidable discrepancies between emulated and target values due to internal variability. We compute the metricis at grid-point scale, and we show geographically resolved results, or aggregate them at global scale. We demonstrate the use of our error metric in the emulation of a suite of temperature and precipitation extreme indices. We test and compare simple pattern scaling and time-shift using a range of trajectories spanning targets inspired by the Paris agreement -- warming to 1.5C and 2.0C from the pre-industrial baseline -- and two of the longer-established trajectories, RCP4.5 and RCP8.5. With this suite of scenarios we can test the effects on the performance of the size of the temperature gap between emulation origin and target. We find that for most indices emulation the dominant source of discrepancy is internal variability. For at least one index, however, counting exceedances of a high temperature threshold, significant portions of the globally aggregated discrepancy and its regional pattern originate from the systematic emulation error. This error exceeds internal variability of both the target and the emulated quantities in large coherent regions at low latitudes, and the explanation can be found in the differential behavior of temperature distributions across latitudes. The metric also highlights a fundamental difference in the two methods related to the simulation of internal variability, which is dampened significantly by simple pattern scaling. This aspect is of consequence when using these methods for specific applications, where preserving variability for uncertainty quantification is deemed important. With this study we offer our metric as a diagnostic tool, facilitating the formulation of scientific hypotheses on the reasons for the error. In the meantime, we show that for many impact relevant indices by now traditional emulation techniques can be accurate within the variations unavoidably introduced by internal variability, establishing the fundamental condition for using their emulation in impact modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Crystal structure of a Thermus aquaticus diversity-generating retroelement variable protein

Diversity-generating retroelements (DGRs) are widely distributed in bacteria, archaea, and microbial viruses, and bring about unparalleled levels of sequence variation in target proteins. While DGR variable proteins share low sequence identity, the structures of several such proteins have revealed the C-type lectin (CLec)-fold as a conserved scaffold for accommodating massive sequence variation. This conservation has led to the suggestion that the CLec-fold may be useful in molecular surface display applications. Thermostability is an attractive feature in such applications, and thus we studied the variable protein of a DGR encoded by a prophage of the thermophile Thermus aquaticus. We report here the 2.8 Å resolution crystal structure of the variable protein from the T. aquaticus DGR, called TaqVP, and confirm that it has a CLec-fold. Remarkably, its variable region is nearly identical in structure to those of several other CLec-fold DGR variable proteins despite low sequence identity among these. TaqVP was found to be thermostable, which appears to be a property shared by several CLec-fold DGR variable proteins. These results provide impetus for the pursuit of the DGR variable protein CLec-fold in molecular display applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

To what extent can decommissioning options for marine artificial structures move us toward environmental targets?

Switching from fossil fuels to renewable energy is key to international energy transition efforts and the move toward net zero. For many nations, this requires decommissioning of hundreds of oil and gas infrastructure in the marine environment. Current international, regional and national legislation largely dictates that structures must be completely removed at end-of-life although, increasingly, alternative decommissioning options are being promoted and implemented. Yet, a paucity of real-world case studies describing the impacts of decommissioning on the environment make decision-making with respect to which option(s) might be optimal for meeting international and regional strategic environmental targets challenging. To address this gap, we draw together international expertise and judgment from marine environmental scientists on marine artificial structures as an alternative source of evidence that explores how different decommissioning options might ameliorate pressures that drive environmental status toward (or away) from environmental objectives. Synthesis reveals that for 37 United Nations and Oslo-Paris Commissions (OSPAR) global and regional environmental targets, experts consider repurposing or abandoning individual structures, or abandoning multiple structures across a region, as the options that would most strongly contribute toward targets. This collective view suggests complete removal may not be best for the environment or society. However, different decommissioning options act in different ways and make variable contributions toward environmental targets, such that policy makers and managers would likely need to prioritise some targets over others considering political, social, economic, and ecological contexts. Current policy may not result in optimal outcomes for the environment or society.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Spitzer Variability Properties of Low-gravity L Dwarfs

We present Spitzer Space Telescope variability monitoring observations of three low-gravity L dwarfs with previous detections of variability in the near-IR: 2MASS J0045+16, 2MASS J0501–00, and 2MASS J1425–36. We detect significant periodic variability in two of our targets, 2MASS J0045+16 and 2MASS J0501–00. We do not detect variability in 2MASS J1425–36. Combining our new rotation periods with rotational velocities, we calculate inclination angles of 22° ± 1°, 60{sub -8}{sup +13°}, and 52{sub -13}{sup +19°} for 2MASS J0045+16, 2MASS J0501–00, and 2MASS J1425–36, respectively. Our three new objects are consistent with the tentative relations between inclination, amplitude, and color anomaly previously reported. Objects with the highest variability amplitudes are inclined equator on, while the maximum observed amplitude decreases as the inclination angle decreases. We also find a correlation between the inclination angle and (J–K){sub 2MASS} color anomaly for the sample of objects with measured inclinations. Compiling the entire sample of brown dwarfs with Spitzer variability detections, we find no enhancement in amplitude for young, early-L dwarfs compared to the field dwarf population. We find a possible enhancement in amplitude of low-gravity late-L dwarfs at 4.5 μm. We do not find a correlation between amplitude ratio and spectral type for field dwarfs or for the young population. Finally, we compile the rotation periods of a large sample of brown dwarfs with ages 1 Myr–1 Gyr and compare the rotation rates predicted by evolutionary models assuming angular momentum conservation. We find that the rotation rates of the current sample of brown dwarfs fall within the expected range set by evolutionary models and breakup limits.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRSDate not supplied

Generalized Linear Targeting For Cislunar Flight

An important element of Artemis and NASA’s campaign to explore the Moon is the autonomous onboard two-level targeter (TLT) used during all cislunar flight phases. The function of the TLT is to autonomously recompute the burn targets for the upcoming burn (or multiple burns) in response to navigation and vehicle dispersion providing a solution that meets all of the trajectory constraints. Although the TLT has been utilized previously as a ground-based planning tool, and flown onboard during the Artemis I mission, it’s complexity and iterative nature make is difficult to incorporate into and support rapid analyses such as robust optimal trajectory design applications where speed is essential. In this paper, a set of generalized linear targeting algorithms that mimics many of the properties of the TLT is derived. The generalized algorithms can handle single or multiple impulsive maneuvers, with multiple constraints at multiple fixed or variable times. A linear targeting algorithm for finite burn maneuvers is also derived. The generalized linear targeting algorithms are exceptionally fast and easy to implement in Monte Carlo analysis, linear covariance (LinCov) analysis, and robust optimal trajectory design. Several cislunar flight examples are provided.

Linear Covariance Analysis↗

DOE OSTI2017

Identification of Young Stellar Variables with KELT for K2 . I. Taurus Dippers and Rotators

One of the most well-studied young stellar associations, Taurus–Auriga, was observed by the extended Kepler mission, K2 , in the spring of 2017. K2 Campaign 13 (C13) is a unique opportunity to study many stars in this young association at high photometric precision and cadence. Using observations from the Kilodegree Extremely Little Telescope (KELT) survey, we identify “dippers,” aperiodic and periodic variables among K2 C13 target stars. This release of the KELT data (light curve data in e-tables) provides the community with long-time baseline observations to assist in the understanding of the more exotic variables in the association. Transient-like phenomena on timescales of months to years are known characteristics in the light curves of young stellar objects, making contextual pre- and post- K2 observations critical to understanding their underlying processes. We are providing a comprehensive set of the KELT light curves for known Taurus–Auriga stars in K2 C13. The combined data sets from K2 and KELT should permit a broad array of investigations related to star formation, stellar variability, and protoplanetary environments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Searches for new phenomena in events with two leptons, jets, and missing transverse momentum in 139 fb –1 of √s = 13 TeV $pp$ collisions with the ATLAS detector

Searches for new phenomena inspired by supersymmetry in final states containing an e + e – or μ + μ – pair, jets, and missing transverse momentum are presented. These searches make use of proton–proton collision data with an integrated luminosity of 139 fb –1 , collected during 2015–2018 at a centre-of-mass energy √s = 13 TeV by the ATLAS detector at the Large Hadron Collider. Two searches target the pair production of charginos and neutralinos. One uses the recursive-jigsaw reconstruction technique to follow up on excesses observed in 36.1 fb –1 of data, and the other uses conventional event variables. The third search targets pair production of coloured supersymmetric particles (squarks or gluinos) decaying through the next-to-lightest neutralino ($\tilde{χ}$$^{0}_{2}$) via a slepton ($\tilde{ℓ}$) or Z boson into ℓ + ℓ – $\tilde{χ}$$^{0}_{1}$ , resulting in a kinematic endpoint or peak in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectations. Results are interpreted using simplified models and exclude masses up to 900 GeV for electroweakinos, 1550 GeV for squarks, and 2250 GeV for gluinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2009

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth s atmosphere is critical in assessing the planet s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars.

Vaughan, Mark A.↗