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Results for “model inference”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Inferring Plant Acclimation and Improving Model Generalizability With Differentiable Physics‐Informed Machine Learning of Photosynthesis
Net photosynthesis (A N ) is a key component of the global carbon cycle influencing climate feedback over decadal scales. Although plant acclimation to environmental changes can modify A N , traditional vegetation models in Earth system models (ESMs) often rely on plant functional type (PFT)-specific parameterizations or simplified acclimation assumptions limiting generalizability across time, space, and PFTs. In this study, we developed a differentiable photosynthesis model to learn the environmental dependencies of V c,max25 (maximum carboxylation rate at 25°C, representing photosynthetic capacity), as this genre of hybrid physics-informed machine learning can seamlessly train neural networks and process-based equations together. Compared to PFT-specific parameterization of V c,max25 , learning the environment dependencies of key photosynthetic parameters improved model spatiotemporal generalizability. Applying environmental acclimation to V c,max25 led to substantial variations in global mean A N indicating the need to address acclimation in ESMs. The model effectively captured multivariate observations (V c,max25 , A N , and stomatal conductance (g s )) simultaneously with multivariate constraints, improving generalization across space and PFTs. It also learned sensible acclimation relationships of V c,max25 to different environmental conditions. The model explained more than 54%, 57%, and 62% of the variance of A N , g s , and V c,max25 , respectively, presenting a first global-scale spatial test benchmark of A N and g s . These results highlight the potential for differentiable modeling to enhance process-based modules in ESMs and effectively leverage information from large, multivariate data sets.
Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities
Metabolite exchanges in microbial communities give rise to ecological interactions that govern ecosystem diversity and stability. It is unclear, however, how the rise of these interactions varies across metabolites and organisms. Here we address this question by integrating genome-scale models of metabolism with evolutionary game theory. Specifically, we use microbial fitness values estimated by metabolic models to infer evolutionarily stable interactions in multi-species microbial “games”. We first validate our approach using a well-characterized yeast cheater-cooperator system. We next perform over 80,000 in silico experiments to infer how metabolic interdependencies mediated by amino acid leakage in Escherichia coli vary across 189 amino acid pairs. While most pairs display shared patterns of inter-species interactions, multiple deviations are caused by pleiotropy and epistasis in metabolism. Moreover, simulated invasion experiments reveal possible paths to obligate cross-feeding. Our study provides genomically driven insight into the rise of ecological interactions, with implications for microbiome research and synthetic ecology.
Space geodetic monitoring of engineered structures: The ongoing destabilization of the Mosul dam, Iraq
We present a detailed survey of the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is poor due to a site geology formed by alternating strata of highly soluble materials including gypsum, anhydrite, marl and limestone. Here we present the first multi-sensor cumulative deformation map for the dam generated from space-based interferometric synthetic aperture radar measurements from the Italian constellation COSMO-SkyMed and the European sensor Sentinel-1a over the period 2014–2016 that we compare to an older dataset spanning 2004–2010 acquired with the European Envisat satellite. We found that deformation was rapid during 2004–2010, slowed in 2012–2014 and increased since August 2014 when grouting operations stopped due to the temporary capture of the dam by the self proclaimed Islamic State. We model the inferred deformation using a Markov chain Monte Carlo approach to solve for change in volume for simple tensile dislocations. Results from recent and historical geodetic datasets suggests that the volume dissolution rate remains constant when the equivalent volume of total concrete injected during re-grouting operations is included in the calculations.
Spectral dynamics and gas-phase oxidation of laser-produced plutonium plasmas
Pu gas-phase oxidation and Pu oxide bands identified with Pu I spectral modeling and time-resolved excitation temperature of Pu plasma.
Cracks and blisters formed close to a silicon wafer surface by He-H co-implantation at low energy
We have studied the effect of reducing the implantation energy towards low keV values on the areal density of He and H atoms stored within populations of blister cavities formed by co-implantation of the same fluence of He then H ions into Si(001) wafers and annealing. Using a variety of experimental techniques, we have measured blister heights and depth from the surface, diameter, areal density of the cracks from which they originate as functions of implantation energy and fluence. We show that there is a direct correlation between the diameters of the cracks and the heights of the associated blisters. This correlation only depends on the implantation energy, i.e., only on the depth at which the cracks are located. Using finite element method modeling, we infer the pressure inside the blister cavities from the elastic deformations they generate, i.e., from the height of the blisters. From this, we demonstrate that the gas pressure within a blister only depends on the diameter of the associated crack and not on its depth position and derive an analytical expression relating these parameters. Relating the pressure inside a blister to the respective concentrations of gas molecules it contains, we deduce the areal densities of He and H atoms contained within the populations of blisters. After low-energy implantations (8 keV He{sup +}, 3 keV H{sup +}), all the implanted He and H atoms contribute to the formation of the blisters. There is no measurable exo-diffusion of any of the implanted gases, in contrast to what was assumed at the state of the art to explain the failure of the Smart-Cut technology when using very low energy ion implantation for the fabrication of ultra-thin layers. Alternative explanations must be investigated.
The role of hot spot mix in the low-foot and high-foot implosions on the NIF
Hydrodynamic mix of the ablator into the DT fuel layer and hot spot can be a critical performance limitation in inertial confinement fusion implosions. This mix results in increased radiation loss, cooling of the hot spot, and reduced neutron yield. To quantify the level of mix, we have developed a simple model that infers the level of contamination using the ratio of the measured x-ray emission to the neutron yield. The principal source for the performance limitation of the “low-foot” class of implosions appears to have been mix. As a result, lower convergence “high-foot” implosions are found to be less susceptible to mix, allowing velocities of >380 km/s to be achieved.
Unfolded states under folding conditions accommodate sequence-specific conformational preferences with random coil-like dimensions
Proteins are marginally stable molecules that fluctuate between folded and unfolded states. Here, we provide a high-resolution description of unfolded states under refolding conditions for the N-terminal domain of the L9 protein (NTL9). We use a combination of time-resolved Förster resonance energy transfer (FRET) based on multiple pairs of minimally perturbing labels, time-resolved small-angle X-ray scattering (SAXS), all-atom simulations, and polymer theory. Upon dilution from high denaturant, the unfolded state undergoes rapid contraction. Although this contraction occurs before the folding transition, the unfolded state remains considerably more expanded than the folded state and accommodates a range of local and nonlocal contacts, including secondary structures and native and nonnative interactions. Paradoxically, despite discernible sequence-specific conformational preferences, the ensemble-averaged properties of unfolded states are consistent with those of canonical random coils, namely polymers in indifferent (theta) solvents. These findings are concordant with theoretical predictions based on coarse-grained models and inferences drawn from single-molecule experiments regarding the sequence-specific scaling behavior of unfolded proteins under folding conditions.
AGES AND METALLICITIES OF CLUSTER GALAXIES IN A779 USING MODIFIED STROeMGREN PHOTOMETRY
In the quest for the formation and evolution of galaxy clusters, Rakos and co-workers introduced a spectrophotometric method using modified Stroemgren photometry, but with the considerable debate toward the project's abilities, we re-introduce the system by testing for the repeatability of the modified Stroemgren colors and compare them with the Stroemgren colors, and check for the reproducibility of the ages and metallicities (using the Principle Component Analysis (PCA) technique and the GALEV models) for the six common galaxies in all three A779 data sets. As a result, a fair agreement between two filter systems was found to produce similar colors (with a precision of 0.09 mag in (uz - vz), 0.02 mag in (bz - yz), and 0.03 mag in (vz - vz)) and the generated ages and metallicities are also similar (with an uncertainty of 0.36 Gyr and 0.04 dex from PCA and 0.44 Gyr and 0.2 dex using the GALEV models). We infer that the technique is able to relieve the age-metallicity degeneracy by separating the age effects from the metallicity effects, but it is still unable to completely eliminate it. We further extend this paper to re-study the evolution of galaxies in the low mass, dynamically poor A779 cluster (as it was not elaborately analyzed by Rakos and co-workers in their previous work) by correlating the luminosity (mass), density, and radial distance with the estimated age, metallicity, and the star formation history. Our results distinctly show the bimodality of the young, low-mass, metal-poor population with a mean age of 6.7 Gyr ({+-} 0.5 Gyr) and the old, high-mass, metal-rich galaxies with a mean age of 9 Gyr ({+-} 0.5 Gyr). The method also observes the color evolution of the blue cluster galaxies to red (Butcher-Oemler phenomenon), and the downsizing phenomenon. Our analysis shows that modified Stroemgren photometry is very well suited for studying low- and intermediate-z clusters, as it is capable of observing deeper with better spatial resolution at spectroscopic redshift limits, and the narrowband filters estimate the age and metallicity with fewer uncertainties compared to other methods that study stellar population scenarios.
THE SL2S GALAXY-SCALE GRAVITATIONAL LENS SAMPLE. I. THE ALIGNMENT OF MASS AND LIGHT IN MASSIVE EARLY-TYPE GALAXIES AT z = 0.2-0.9
We study the relative alignment of mass and light in a sample of 16 massive early-type galaxies at z = 0.2-0.9 that act as strong gravitational lenses. The sample was identified from deep multi-band images obtained as part of the Canada-France-Hawaii Telescope Legacy Survey and as part of the Strong Lensing Legacy Survey (SL2S). Higher resolution follow-up imaging is available for a subset of 10 systems. We construct gravitational lens models and infer total enclosed mass, elongation, and position angle of the mass distribution. By comparison with the observed distribution of light we infer that there is a substantial amount of external shear with mean value ({gamma}{sub ext}) = 0.12 {+-} 0.05, arising most likely from the environment of the SL2S lenses. In a companion paper, we combine these measurements with follow-up Keck spectroscopy to study the evolution of the stellar and dark matter content of early-type galaxies as a function of cosmic time.
Diversity of extrasolar planets and diversity of molecular cloud cores. I. Semimajor axes
We show that the diversity of extrasolar planetary systems may be related to the diversity of molecular cloud cores. In previous studies of planet formation, artificial initial conditions of protoplanetary disks or steady state disks, such as the minimum mass nebula model, have often been used so that the influence of cloud core properties on planet formation is not realized. To specifically and quantitatively demonstrate our point, we calculate the dependence of disk properties on cloud core properties and show that the boundary of the giant planet formation region in a disk is a function of cloud core properties with the conventional core accretion model of giant planet formation. The gravitational stability of a disk depends on the properties of its progenitor cloud core. We also compare our calculations with observations of extrasolar planets. From the observational data of cloud cores, our model could infer the range and most frequent values of observed semimajor axes of extrasolar planets. Our calculations suggest that planet formation at the snowline alone could not completely explain the semimajor axis distribution. If the current observations are not biased, our calculations indicate that the planet formation at the snowline is inefficient. We suggest that there will be more observed planets with semimajor axis <9 AU than >9 AU, even with a longer duration of observations, if the planet formation at the snowline is inefficient.
Intergalactic medium emission observations with the cosmic web imager. II. Discovery of extended, kinematically linked emission around SSA22 Lyα BLOB 2
The intergalactic medium (IGM) is the dominant reservoir of baryons, delineates the large-scale structure of the universe at low to moderate overdensities, and provides gas from which galaxies form and evolve. Simulations of a cold-dark-matter- (CDM-) dominated universe predict that the IGM is distributed in a cosmic web of filaments and that galaxies should form along and at the intersections of these filaments. While observations of QSO absorption lines and the large-scale distribution of galaxies have confirmed the CDM paradigm, the cosmic web of IGM has never been confirmed by direct imaging. Here we report our observation of the Lyα blob 2 (LAB2) in SSA22 with the Cosmic Web Imager (CWI). This is an integral field spectrograph optimized for low surface brightness, extended emission. With 22 hr of total on- and off-source exposure, CWI has revealed that LAB2 has extended Lyα emission that is organized into azimuthal zones consistent with filaments. We perform numerous tests with simulations and the data to secure the robustness of this result, which relies on data with modest signal-to-noise ratios. We have developed a smoothing algorithm that permits visualization of data cube slices along image or spectral image planes. With both raw and smoothed data cubes we demonstrate that the filaments are kinematically associated with LAB2 and display double-peaked profiles characteristic of optically thick Lyα emission. The flux is 10-20 times brighter than expected for the average emission from the IGM but is consistent with boosted fluorescence from a buried QSO or gravitation cooling radiation. Using simple emission models, we infer a baryon mass in the filaments of at least 1-4 × 10{sup 11} M {sub ☉}, and the dark halo mass is at least 2 × 10{sup 12} M {sub ☉}. The spatial-kinematic morphology is more consistent with inflow from the cosmic web than outflow from LAB2, although an outflow feature maybe present at one azimuth. LAB2 and the surrounding gas have significant and coaligned angular momentum, strengthening the case for their association.
Understanding the formation and evolution of interstellar ices: a Bayesian approach
Understanding the physical conditions of dark molecular clouds and star-forming regions is an inverse problem subject to complicated chemistry that varies nonlinearly with both time and the physical environment. In this paper, we apply a Bayesian approach based on a Markov chain Monte Carlo (MCMC) method for solving the nonlinear inverse problems encountered in astrochemical modeling. We use observations for ice and gas species in dark molecular clouds and a time-dependent, gas-grain chemical model to infer the values of the physical and chemical parameters that characterize quiescent regions of molecular clouds. We show evidence that in high-dimensional problems, MCMC algorithms provide a more efficient and complete solution than more classical strategies. The results of our MCMC method enable us to derive statistical estimates and uncertainties for the physical parameters of interest as a result of the Bayesian treatment.
DEEP HE ii AND C iv SPECTROSCOPY OF A GIANT LYα NEBULA: DENSE COMPACT GAS CLUMPS IN THE CIRCUMGALACTIC MEDIUM OF A z ∼ 2 QUASAR
The recent discovery by Cantalupo et al. of the largest (∼500 kpc) luminous (L ≃ 1.43 × 10{sup 45} erg s{sup −1}) Lyα nebula associated with the quasar UM287 (z = 2.279) poses a great challenge to our current understanding of the astrophysics of the halos hosting massive z ∼ 2 galaxies. Either an enormous reservoir of cool gas is required M ≃ 10{sup 12} M{sub ⊙}, exceeding the expected baryonic mass available, or one must invoke extreme gas clumping factors not present in high-resolution cosmological simulations. However, observations of Lyα emission alone cannot distinguish between these two scenarios. We have obtained the deepest ever spectroscopic integrations in the He ii λ1640 and C iv λ1549 emission lines with the goal of detecting extended line emission, but detect neither line to a 3σ limiting SB ≃ 10{sup −18} erg s{sup −1} cm{sup −2} arcsec{sup −2}. We construct simple models of the expected emission spectrum in the highly probable scenario that the nebula is powered by photoionization from the central hyper-luminous quasar. The non-detection of He ii implies that the nebular emission arises from a mass M{sub c} ≲ 6.4 × 10{sup 10} M{sub ⊙} of cool gas on ∼200 kpc scales, distributed in a population of remarkably dense (n{sub H} ≳ 3 cm{sup −3}) and compact (R ≲ 20 pc) clouds, which would clearly be unresolved by current cosmological simulations. Given the large gas motions suggested by the Lyα line (v ≃ 500 km s{sup −1}), it is unclear how these clouds survive without being disrupted by hydrodynamic instabilities. Our work serves as a benchmark for future deep integrations with current and planned wide-field IFU spectrographs such as MUSE, KCWI, and KMOS. Our observations and models suggest that a ≃10 hr exposure would likely detect ∼10 rest-frame UV/optical emission lines, opening up the possibility of conducting detailed photoionization modeling to infer the physical state of gas in the circumgalactic medium.
OPTICAL/NEAR-INFRARED SELECTION OF RED QUASI-STELLAR OBJECTS: EVIDENCE FOR STEEP EXTINCTION CURVES TOWARD GALACTIC CENTERS?
We present the results of a search for red QSOs using a selection based on optical imaging from the Sloan Digital Sky Survey (SDSS) and near-infrared imaging from UKIDSS. Our main goal with the selection is to search for QSOs reddened by foreground dusty absorber galaxies. For a sample of 58 candidates (including 20 objects fulfilling our selection criteria that already have spectra in the SDSS), 46 (79%) are confirmed to be QSOs. The QSOs are predominantly dust-reddened except for a handful at redshifts z {approx}> 3.5. However, the dust is most likely located in the QSO host galaxies (and for two, the reddening is primarily caused by Galactic dust) rather than in the intervening absorbers. More than half of the QSOs show evidence of associated absorption (BAL absorption). Four (7%) of the candidates turned out to be late-type stars, and another four (7%) are compact galaxies. We could not identify the remaining four objects. In terms of their optical spectra, these QSOs are similar to the QSOs selected in the FIRST-2MASS Red Quasar Survey except they are on average fainter, more distant, and only two are detected in the FIRST survey. As per the usual procedure, we estimate the amount of extinction using the SDSS QSO template reddened by Small-Magellanic-Cloud-(SMC) like dust. It is possible to get a good match to the observed (rest-frame ultraviolet) spectra, but it is not possible to match the observed near-IR photometry from UKIDSS for nearly all the reddened QSOs. The most likely reasons are that the SDSS QSO template is too red at optical wavelengths due to contaminating host galaxy light and because the assumed SMC extinction curve is too shallow. Three of the compact galaxies display old stellar populations with ages of several Gyr and masses of about 10{sup 10} M{sub Sun} (based on spectral energy distribution modeling). The inferred stellar densities in these galaxies exceed 10{sup 10} M{sub Sun} kpc{sup -2}, which is among the highest measured for early-type galaxies. Our survey has demonstrated that selection of QSOs based on near-IR photometry is an efficient way to select QSOs, including reddened QSOs, with only small contamination from late-type stars and compact galaxies. This will be useful with ongoing and future wide-field near-IR surveys such as the VISTA and EUCLID surveys.
From minimum-viable-products to full models: a step-wise development of diagnostic forward models in support of design, analysis and modelling on the ST40 tokamak
Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-checks during commissioning, test analysis methods, and build workflows to constrain high-level parameters to inform interpretation, theory and modelling. For new models and new analysis workflows, minimum-viable-products are released early, and their complexity is increased in a step-wise manner, facilitating the support of all programme phases on multiple parallel applications, while enabling learning opportunities and feedback loops. In this contribution we review the philosophy, scope and architecture of the framework under development. We discuss the details of some forward models, with examples on how they are used to aid diagnostic design, to investigate analysis methodologies through synthetic data, and how they are embedded in experimental analysis workflows. We compare previously published experimental results with new, more advanced analysis workflows employing more recent, detailed models and new diagnostic data, providing confirmation of the published material from the 2021–22 experimental campaign.
Comparing cosmic web classifiers using information theory
We introduce a decision scheme for optimally choosing a classifier, which segments the cosmic web into different structure types (voids, sheets, filaments, and clusters). Our framework, based on information theory, accounts for the design aims of different classes of possible applications: (i) parameter inference, (ii) model selection, and (iii) prediction of new observations. As an illustration, we use cosmographic maps of web-types in the Sloan Digital Sky Survey to assess the relative performance of the classifiers T-WEB, DIVA and ORIGAMI for: (i) analyzing the morphology of the cosmic web, (ii) discriminating dark energy models, and (iii) predicting galaxy colors. Our study substantiates a data-supported connection between cosmic web analysis and information theory, and paves the path towards principled design of analysis procedures for the next generation of galaxy surveys. We have made the cosmic web maps, galaxy catalog, and analysis scripts used in this work publicly available.
Search for photons above 10 19 eV with the surface detector of the Pierre Auger Observatory
We use the surface detector of the Pierre Auger Observatory to search for air showers initiated by photons with an energy above 10 19 eV. Photons in the zenith angle range from 30° to 60° can be identified in the overwhelming background of showers initiated by charged cosmic rays through the broader time structure of the signals induced in the water-Cherenkov detectors of the array and the steeper lateral distribution of shower particles reaching ground. Applying the search method to data collected between January 2004 and June 2020, upper limits at 95% CL are set to an E -2 diffuse flux of ultra-high energy photons above 10 19 eV, 2 × 10 19 eV and 4 × 10 19 eV amounting to 2.11 × 10 -3 , 3.12 × 10 -4 and 1.72 × 10 -4 km -2 sr -1 yr -1 , respectively. While the sensitivity of the present search around 2 × 10 19 eV approaches expectations of cosmogenic photon fluxes in the case of a pure-proton composition, it is one order of magnitude above those from more realistic mixed-composition models. The inferred limits have also implications for the search of super-heavy dark matter that are discussed and illustrated.