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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Impedance Response Influenced by Variability in the Random Distribution of Physical Properties of Coated Materials in Two-Dimensional Space

Heterogeneous physical characteristics of a system featuring a single-layer film on a metallic surface have been explored via its impedance response. The Nyquist plot showed a distorted semicircle, indicative of the system's unique distribution characteristics. Utilizing a copula-based probability method, a two-dimensional deterministic impedance model was successfully integrated, accounting for spatial physical properties such as permittivity and electrical conductivity. This strategy enabled in-depth exploration and mechanistic quantification of a broad spectrum of properties. A quantitative understanding of impedance signal alterations, characterized by normally or log-normally correlated variables, was achieved through the variation in aspect ratio and characteristic frequency of the impedance spectra. Log-normally distributed electrical properties provided a superior representation of the distorted impedance spectra. As coefficient of variation (CV) values fluctuated, the aspect ratio and characteristic frequency showed heightened sensitivity to log-normal permittivity compared to log-normal electrical conductivity. Notably, a marked positive linear correlation between electrical properties resulted in an impedance response that approximated perfect semicircular spectra. The variability in the electrical properties' distribution was demonstrated by considering the correlation coefficient between electrical conductivity and the z-direction position. Furthermore, the highest aspect ratio of the impedance spectra was observed when the electrical conductivity was randomly distributed across the z-direction space.

36 MATERIALS SCIENCE↗

DOE OSTI2019

numericalFunctions

The numericalFunction C library is designed to handle point-wise interpolative data representing a mathematical function. The library currently handles 1-d functions (i.e., functions of the format f(x)). The main object is the ptwXYPoints C struct that holds list of x,y pairs sorted by ascending x-values with an interpolation rule. That is, it contains the 1-d function f(x) = y(x). Functions are included that support common unitary and binary operations (e.g., negation, addition, multiplication). As example, if f(x) and g(x) are two ptwXYPoints instances, then routines to calculate f(x) + g(x) and f(x) * g(x) are included. The library support storage of data with lin-lin, lin-log, log-lin, log-log and flat (or histogram) interpolation. Functions to convert any of the supported interpolation to lin-lin are included. However, many of the binary functions only support lin-lin interpolation. The library also contains a C struct for storing a Legendre series representation of a 1-d function, and functions to convert Legendre series to and from a ptwXYPoints instance. A python interface to the library is included, with the ptwXYPoints C struct treated as a class. This class has many of the standard python math methods (e.g., __add__, __mul__).

Beck, Bret↗

DOE OSTI2020

eBPF Community ID Calculation

The code titled “eBPF Community ID Calculation” allows easy correlation of monitoring logs with existing network forensics logs on high-performance computing (HPC) systems. This code implements the Community ID Flow Hashing standard to calculate community ID Flow identifiers. These identifiers will be used to correlate host forensics logs with network forensics logs. The correlation provides valuable insight and the ability to easily pivot between disparate data sources. The computer code removes the libpcap dependency from the code base.

Maerz, StefanA↗

DOE OSTI2019

Diventi

Diventi provides a write optimized index of network logs such as netflow or zeek. The program will ingest various network traffic logs (zeek connection logs or NetflowV5, v9 or IPFix logs) and index each IP address and time of its activity. This database can then be queried for timely tracking of network activity. It currently uses the ft-index library from Percona but is adaptable to any key-value store that supports the Berkeley DB api.SAND2019-15037 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Kroeger, Thomas↗

DOE OSTI2019

Application of a convolutional neural network in permeability prediction: A case study in the Jacksonburg-Stringtown oil field, West Virginia, USA

Permeability is a critical parameter for understanding subsurface fluid flow behavior, managing reservoirs, enhancing hydrocarbon recovery, and sequestering carbon dioxide. In general, permeability is measured in the laboratory based on subsurface core samples, calculated from well logs or estimated from well tests. However, laboratory measurements and well tests are expensive, time-consuming, and usually limited to a few core samples or wells in a hydrocarbon field or carbon storage site. Machine-learning techniques are good options for generating a rapid, robust, and cost-effective permeability prediction model because of their strengths to recognize the potential interrelationships between input and output variables. Convolutional neural networks (CNN), as a good pattern recognition algorithm, are widely used in image processing, natural language processing, and speech recognition, but are rarely used with regression problems and even less often in reservoir characterization. We have developed a CNN regression model to estimate the permeability in the Jacksonburg-Stringtown oil field, West Virginia, which is a potential carbon storage site and enhanced oil recovery operations field. We also evaluate the concept of the geologic feature image, which is converted from geophysical well logs. Five variables, including two commonly available conventional well logs (the gamma rays [GRs] and bulk density) and three well-log-derived variables (the slopes of the GR and bulk density curves, and shale content), are used to generate a geologic feature image. The CNN treats the geologic feature image as the input and the permeability as the desired output. In addition, the permeability predicted using traditional backpropagation artificial neural networks, which are optimized by genetic algorithms and particle swarm optimization, is compared with the permeability estimated using our CNN. Our results indicate that the CNN regression model provides more accurate permeability predictions than the traditional neural network.

Geochemistry & Geophysics↗

DOE OSTI2023

Reference data, predictors, and probability grids for forest degradation classes in three sites in the Brazilian Amazon

Forest degradation by fires and selective logging is widespread in the Amazon region. We implemented a gradient boosted classification modeling framework to classify intact, logged, and burned forests at three Amazonian sites: Feliz Natal Municipality and Xingu Indigenous Territory in Mato Grosso State, and Saracá-Taquera National Forest in Pará State. We used forest degradation history from Landsat time-series as reference data and textural metrics derived from PlanetScope images as predictors. Textural metrics were computed using the Gray-Level Co-Occurrence Matrix (GLCM) textural technique. Included in the attached zip file are ten files: - a shapefile containing the reference data (fire and selective logging polygons and year of event) for each site; - a multiband tif file containing the 8 GLCM metrics used as predictors (Mean, Variance, Homogeneity, Contrast, Dissimilarity, Entropy, Angular Second Moment, Correlation) at the original PlanetScope resolution (3.125m) for each site; - a multiband tif file containing the 72 aggregated GLCM metrics used as predictors (Mean, Variance, Homogeneity, Contrast, Dissimilarity, Entropy, Angular Second Moment, and Correlation aggregated using the mean, first quartile, third quartile, maximum, median, minimum, root mean square, standard deviation, and skewness statistics) at 562m resolution for each site; - a multiband tif file containing the 3 probability grids for either intact, logged, or burned forests at the aggregation resolution (562m) for each site.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Performance Evaluation of Darshan 3.0.0 on the Cray XC30

Abstract—Darshan is a lightweight I/O characterization tool used to gather and summarize salient I/O workload statistics from HPC applications. Darshan was designed to minimize any possible perturbations of an application’s performance, leading it to be enabled by default on a number of production HPC systems. For each file accessed by a given application, Darshan records the count and types of I/O operations performed, histograms of access sizes, cumulative timers on the amount of time spent doing I/O, and other statistical data. This type of data has proved invaluable in understanding and improving the I/O performance of HPC applications. Darshan 3.0.0 is the new modularized version of the traditional Darshan library and file format, allowing users to easily add more in-depth I/O characterization data to Darshan logs. In this work we perform an empirical evaluation of Darshan 3.0.0 to ensure that it continues to meet performance expectations for broad deployment. In particular, we evaluate the imposed overhead on instrumented I/O operations, time taken to shut down and generate corresponding Darshan log files, and resultant log file sizes for different workloads. These performance results are compared to results of Darshan 2.3.0 on the Edison XC30 system at NERSC to determine whether the new version is lightweight enough to run full-time on production HPC systems. Our evaluation shows that Darshan has limited impact on application I/O performance and can fully generate a corresponding log file for most application workloads in under two seconds.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗

DOE OSTI2024

Risk of theft and malicious use of radiation sources in transit

Remote radioactive source applications require frequent transportation of sources from storage locations to remote sites. This introduces risk of theft of a source during the transportation process, with the level of risk proportional to the radioactivity of the source. To that end, theft of smaller sources, such as microcurie-level moisture density gauges, are of minor concern, but larger sources, such as those used for radiography and well logging, present more risk. Radiography sources include 192 Ir, 75 Se, or 60 Co radionuclides with radioactivity amounts at or exceeding IAEA Category 2. Well-logging sources, primarily 241 Am/Be, are used for their neutron-emission properties. 137 Cs is also used in well-logging at lower activities than in radiography but at levels that still present some risk. The vulnerability for malicious use of such sources to cause contamination and associated economic effects is dependent on the elemental chemical and physical properties, especially melting point and bulk modulus. Theft of radiography sources is somewhat common, well-logging sources less so. Theft of sources commonly occurs in concert with theft of the vehicle, with the source subsequently abandoned. There have been some instances where a source appears to have been specifically targeted. There are a variety of security measures and protocols, available and under development, to mitigate the risk of theft and assist in source recovery.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2022

Quantum simulation of real-space dynamics

Quantum simulation is a prominent application of quantum computers. While there is extensive previous work on simulating finite-dimensional systems, less is known about quantum algorithms for real-space dynamics. We conduct a systematic study of such algorithms. In particular, we show that the dynamics of a d-dimensional Schrödinger equation with η particles can be simulated with gate complexity O ~ (ηdFpoly(log(g'/ϵ))), where ϵ is the discretization error, g' controls the higher-order derivatives of the wave function, and F measures the time-integrated strength of the potential. Compared to the best previous results, this exponentially improves the dependence on ϵ and g' from poly(g'/ϵ) to poly(log(g'/ϵ)) and polynomially improves the dependence on T and d, while maintaining best known performance with respect to η. For the case of Coulomb interactions, we give an algorithm using η 3 (d + η)Tpoly(log(ηdTg'/(Δϵ)))/Δ one- and two-qubit gates, and another using η 3 (4d) d/2 Tpoly(log(ηdTg'/(Δϵ)))/Δ one- and two-qubit gates and QRAM operations, where T is the evolution time and the parameter Δ regulates the unbounded Coulomb interaction. We give applications to several computational problems, including faster real-space simulation of quantum chemistry, rigorous analysis of discretization error for simulation of a uniform electron gas, and a quadratic improvement to a quantum algorithm for escaping saddle points in nonconvex optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Streptococcus mutans Displays Altered Stress Responses While Enhancing Biofilm Formation by Lactobacillus casei in Mixed-Species Consortium

Like Streptococcus mutans , lactobacilli are commonly isolated from carious sites, although their exact role in caries development remains unclear. This study used mixed-species models to analyze biofilm formation by major groups of oral lactobacilli, including L. casei, L. fermentum, L. rhamnosus, L. salivarius ssp. salivarius, and L. gasseri . The results showed that lactobacilli did not form good biofilms when grown alone, although differences existed between different species. When grown together with S. mutans , biofilm formation by L. gasseri and L. rhamnosus was increased by 2-log ( P < 0.001), while biofilms by L. fermentum reduced by >1-log ( P < 0.001). L. casei enhanced biofilm formation by ~2-log when grown with S. mutans wild-type, but no such effects were observed with S. mutans deficient of glucosyltransferase GtfB and adhesin P1. Both S. mutans and L. casei in dual-species enhanced resistance to acid killing with increases of survival rate by >1-log ( P < 0.001), but drastically reduced the survival rates following exposure to hydrogen peroxide ( P < 0.001), as compared to the respective mono-species cultures. When analyzed by RNA-seq, more than 134 genes were identified in S. mutans in dual-species with L. casei as either up- or down-regulated when compared to those grown alone. The up-regulated genes include those for superoxide dismutase, NADH oxidase, and members of the mutanobactin biosynthesis cluster. Among the down-regulated genes were those for GtfB and alternative sigma factor SigX. These results further suggest that interactions between S. mutans and oral lactobacilli are species-specific and may have significant impact on cariogenic potential of the community.

Immunology↗

DOE OSTI2025

Guiding Principles for Geochemical/Thermodynamic Model Development and Validation in Nuclear Waste Disposal: A Close Examination of Recent Thermodynamic Models for H + —Nd 3+ —NO 3 - (—Oxalate) Systems

Development of a defensible source-term model (STM), usually a thermodynamical model for radionuclide solubility calculations, is critical to a performance assessment (PA) of a geologic repository for nuclear waste disposal. Such a model is generally subjected to rigorous regulatory scrutiny. In this article, we highlight key guiding principles for STM model development and validation in nuclear waste management. We illustrate these principles by closely examining three recently developed thermodynamic models with the Pitzer formulism for aqueous H + —Nd 3+ —NO 3 - (—oxalate) systems in a reverse alphabetical order of the authors: the XW model developed by Xiong and Wang, the OWC model developed by Oakes et al., and the GLC model developed by Guignot et al., among which the XW model deals with trace activity coefficients for Nd(III), while the OWC and GLC models are for concentrated Nd(NO 3 ) 3 electrolyte solutions. The principles highlighted include the following: (1) Principle 1. Validation against independent experimental data: A model should be validated against experimental data or field observations that have not been used in the original model parameterization. We tested the XW model against multiple independent experimental data sets including electromotive force (EMF), solubility, water vapor, and water activity measurements. The results show that the XW model is accurate and valid for its intended use for predicting trace activity coefficients and therefore Nd solubility in repository environments. (2) Principle 2. Testing for relevant and sensitive variables: Solution pH is such a variable for an STM and easily acquirable. All three models are checked for their ability to predict pH conditions in Nd(NO 3 ) 3 electrolyte solutions. The OWC model fails to provide a reasonable estimate for solution pH conditions, thus casting serious doubt on its validity for a source-term calculation. In contrast, both the XW and GLC models predict close-to-neutral pH values, in agreement with experimental measurements. (3) Principle 3. Honoring physical constraints: Upon close examination, it is found that the Nd(III)-NO 3 association schema in the OWC model suffers from two shortcomings. Firstly, its second stepwise stability constant for Nd(NO 3 ) 2+ (log K 2 ) is much higher than the first stepwise stability constant for NdNO 3 2+ (log K 1 ), thus violating the general rule of (log K 2 –log K 1 ) < 0, or $\frac{K1}{K2}$>1. Secondly, the OWC model predicts abnormally high activity coefficients for Nd(NO 3 ) 2 + (up to ~900) as the concentration increases. (4) Principle 4. Minimizing degrees of freedom for model fitting: The OWC model with nine fitted parameters is compared with the GLC model with five fitted parameters, as both models apply to the concentrated region for Nd(NO 3 ) 3 electrolyte solutions. The latter appears superior to the former because the latter can fit osmotic coefficient data equally well with fewer model parameters. The work presented here thus illustrates the salient points of geochemical model development, selection, and validation in nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Pathogenicity in Chickens and Turkeys of a 2021 United States H5N1 Highly Pathogenic Avian Influenza Clade 2.3.4.4b Wild Bird Virus Compared to Two Previous H5N8 Clade 2.3.4.4 Viruses

Highly pathogenic avian influenza viruses (HPAIVs) of subtype H5 of the Gs/GD/96 lineage remain a major threat to poultry due to endemicity in wild birds. H5N1 HPAIVs from this lineage were detected in 2021 in the United States (U.S.) and since then have infected many wild and domestic birds. We evaluated the pathobiology of an early U.S. H5N1 HPAIV (clade 2.3.4.4b, 2021) and two H5N8 HPAIVs from previous outbreaks in the U.S. (clade 2.3.4.4c, 2014) and Europe (clade 2.3.4.4b, 2016) in chickens and turkeys. Differences in clinical signs, mean death times (MDTs), and virus transmissibility were found between chickens and turkeys. The mean bird infective dose (BID 50 ) of the 2021 H5N1 virus was approximately 2.6 log 10 50% embryo infective dose (EID 50 ) in chickens and 2.2 log 10 EID 50 in turkeys, and the virus transmitted to contact-exposed turkeys but not chickens. The BID 50 for the 2016 H5N8 virus was also slightly different in chickens and turkeys (4.2 and 4.7 log 10 EID 50 , respectively); however, the BID 50 for the 2014 H5N8 virus was higher for chickens than turkeys (3.9 and ~0.9 log 10 EID 50 , respectively). With all viruses, turkeys took longer to die (MDTs of 2.6–8.2 days for turkeys and 1–4 days for chickens), which increased the virus shedding period and facilitated transmission to contacts.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Near-infrared spectroscopy of the Y0 WISEP J173835.52+273258.9 and the Y1 WISE J035000.32-565830.2: the importance of non-equilibrium chemistry

We present new near-infrared spectra, obtained at Gemini Observatory, for two Y dwarfs: WISE J035000.32−565830.2 (W0350) and WISEP J173835.52+273258.9 (W1738). A FLAMINGOS-2 R = 540 spectrum was obtained for W0350, covering 1.0<λ μm < 1.7, and a cross-dispersed Gemini near-infrared spectrograph R = 2800 spectrum was obtained for W1738, covering 0.993–1.087 μm, 1.191–1.305 μm, 1.589–1.631 μm, and 1.985–2.175 μm, in four orders. We also present revised YJH photometry for W1738, using new NIRI Y and J imaging, and a re-analysis of the previously published NIRI H-band images. We compare these data, together with previously published data for late-T and Y dwarfs, to cloud-free models of solar metallicity, calculated both in chemical equilibrium and with disequilibrium driven by vertical transport. We find that for the Y dwarfs, the non-equilibrium models reproduce the near-infrared data better than the equilibrium models. The remaining discrepancies suggest that fine-tuning the CH{sub 4}/CO and NH{sub 3}/N{sub 2} balance is needed. Improved trigonometric parallaxes would improve the analysis. Despite the uncertainties and discrepancies, the models reproduce the observed near-infrared spectra well. We find that for the Y0, W1738, T{sub eff}=425±25 K, and log g=4.0±0.25, and for the Y1, W0350, T{sub eff}=350±25 K, and log g=4.0±0.25. W1738 may be metal-rich. Based on evolutionary models, these temperatures and gravities correspond to a mass range for both Y dwarfs of 3–9 Jupiter masses, with W0350 being a cooler, slightly older, version of W1738; the age of W0350 is 0.3–3 Gyr, and the age of W1738 is 0.15–1 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Deep mixing in stellar variability: improved method, statistics, and applications

The preliminary results on deep-mixing manifestations in stellar variability are tested using our improved method and extended data set. We measure the timescales τ {sub m} of the stochastic change in the spectral power of rotational harmonics with numbers m ≤ 3 in the light curves of 1361 main-sequence stars from the Kepler mission archive. We find that the gradient [log(τ{sub 2})−log(τ{sub 1})]/[log(2)−log(1)] has a histogram maximum at −2/3, demonstrating agreement with Kolmogorov’s theory of turbulence and therefore confirming the manifestation of deep mixing. The squared amplitudes of the first and second rotational harmonics, corrected for integral photometry distortion, also show a quasi-Kolmogorov character with spectral index ≈−5/3. Moreover, the reduction of τ {sub 1} and τ {sub 2} to the timescales τ {sub lam1} and τ {sub lam2} of laminar convection in the deep stellar layers reveals the proximity of both τ {sub lam1} and τ {sub lam2} to the turnover time τ {sub MLT} of standard mixing length theory. Considering this result, we use the obtained stellar variability timescales instead of τ {sub MLT} in our analysis of the relation between stellar activity and the Rossby number P/τ {sub MLT}. Comparison of our diagrams with previous results and theoretical expectations shows that best-fit correspondence is achieved for τ {sub lam1}, which can therefore be used as an analog of τ {sub MLT}. This means that the laminar component (giant cells) of stellar turbulent convection indeed plays an important role in the physics of stars. Additionally, we estimate the diffusivity of magnetic elements in stellar photospheres.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

DETECTION OF SOLAR-LIKE OSCILLATIONS, OBSERVATIONAL CONSTRAINTS, AND STELLAR MODELS FOR θ CYG, THE BRIGHTEST STAR OBSERVED BY THE KEPLER MISSION

θ Cygni is an F3 spectral type magnitude V = 4.48 main-sequence star that was the brightest star observed by the original Kepler spacecraft mission. Short-cadence (58.8 s) photometric data using a custom aperture were first obtained during Quarter 6 (2010 June–September) and subsequently in Quarters 8 and 12–17. We present analyses of solar-like oscillations based on Q6 and Q8 data, identifying angular degree l = 0, 1, and 2 modes with frequencies of 1000–2700 μ Hz, a large frequency separation of 83.9 ± 0.4 μ Hz, and maximum oscillation amplitude at frequency ν {sub max} = 1829 ± 54 μ Hz. We also present analyses of new ground-based spectroscopic observations, which, combined with interferometric angular diameter measurements, give T {sub eff} = 6697 ± 78 K, radius 1.49 ± 0.03 R {sub ⊙}, [Fe/H] = -0.02 ± 0.06 dex, and log g = 4.23 ± 0.03. We calculate stellar models matching these constraints using the Yale Rotating Evolution Code and the Asteroseismic Modeling Portal. The best-fit models have masses of 1.35–1.39 M {sub ⊙} and ages of 1.0–1.6 Gyr. θ Cyg’s T {sub eff} and log g place it cooler than the red edge of the γ Doradus instability region established from pre- Kepler ground-based observations, but just at the red edge derived from pulsation modeling. The pulsation models show γ Dor gravity modes driven by the convective blocking mechanism, with frequencies of 1–3 cycles per day (11 to 33 μ Hz). However, gravity modes were not seen in Kepler data; one signal at 1.776 cycles per day (20.56 μ Hz) may be attributable to a faint, possibly background, binary.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

THE REST-FRAME OPTICAL SPECTROSCOPIC PROPERTIES OF LY α -EMITTERS AT z ∼ 2.5: THE PHYSICAL ORIGINS OF STRONG LY α EMISSION

We present the rest-frame optical spectroscopic properties of 60 faint ( R {sub AB} ∼ 27; L ∼ 0.1 L {sub *}) Ly α -selected galaxies (LAEs) at z ≈ 2.56. These LAEs also have rest-UV spectra of their Ly α emission line morphologies, which trace the effects of interstellar and circumgalactic gas on the escape of Ly α photons. We find that the LAEs have diverse rest-optical spectra, but their average spectroscopic properties are broadly consistent with the extreme low-metallicity end of the populations of continuum-selected galaxies selected at z ≈ 2–3. In particular, the LAEs have extremely high [O iii] λ 5008/H β ratios (log([O iii]/H β ) ∼ 0.8) and low [N ii] λ 6585/H α ratios (log([N ii]/H α ) < 1.15). Coupled with a detection of the [O iii] λ 4364 auroral line, these measurements indicate that the star-forming regions in faint LAEs are characterized by high electron temperatures (T{sub e} ≈ 1.8 × 10{sup 4} K), low oxygen abundances (12 + log(O/H) ≈ 8.04, Z{sub neb} ≈ 0.22 Z {sub ⊙}), and high excitations with respect to their more luminous continuum-selected analogs. Several of our faintest LAEs have line ratios consistent with even lower metallicities, including six with 12 + log(O/H) ≈ 6.9–7.4 (Z {sub neb} ≈ 0.02–0.05 Z{sub ⊙}). We interpret these observations in light of new models of stellar evolution (including binary interactions) that have been shown to produce long-lived populations of hot, massive stars at low metallicities. We find that strong, hard ionizing continua are required to reproduce our observed line ratios, suggesting that faint galaxies are efficient producers of ionizing photons and important analogs of reionization-era galaxies. Furthermore, we investigate the physical trends accompanying Ly α emission across the largest current sample of combined Ly α and rest-optical galaxy spectroscopy, including both the 60 KBSS-Ly α LAEs and 368 more luminous galaxies at similar redshifts. We find that the net Ly α emissivity (parameterized by the Ly α equivalent width) is strongly correlated with nebular excitation and ionization properties and weakly correlated with dust attenuation, suggesting that metallicity plays a strong role in determining the observed properties of these galaxies by modulating their stellar spectra, nebular excitation, and dust content.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

H i Clouds in LITTLE THINGS Dwarf Irregular Galaxies

We identify 814 discrete H i clouds in 40 dwarf irregular galaxies from the LITTLE THINGS survey using an automated cloud-finding algorithm. The cloud masses range from ∼10{sup 3} to 10{sup 7} M {sub ⊙}, have a surface density averaged over all of the clouds of ∼9.65 M {sub ⊙} pc{sup −2}, and constitute 2%–53% of the total H i mass of the host galaxy. For individual clouds, the mass including He varies with cloud radius as log M{sub gas}=(2.11±0.04) × log R{sub cl} +(0.78±0.08) and the internal velocity dispersion varies as log V{sub disp}=0.5 × log R{sub cl}−0.57±0.21. The H i clouds tend to be in the outer regions of the galaxies, with 72% of the galaxies having more than 70% of their clouds outside one disk scale length and 32% of the galaxies having more than 50% of their clouds outside the radius encircling the H ii emission. Thirty-six percent of the clouds are essentially non-self-gravitating from H i alone, with a virial parameter that exceeds α {sub vir} ∼ 10, and 5% have α {sub vir} ≤ 2. We estimate the missing molecular mass, based on the total star formation rate and a typical molecular consumption time of 2 Gyr, as observed in CO-rich galaxies. The resulting molecular fraction has a value averaged over the galaxies of 0.23 and correlates with both the surface density of star formation and the fraction of H i clouds in the outer regions. We conclude that a significant fraction of the inner parts of these dwarf galaxy disks is in the form of dark molecular gas, and that this fraction could be high enough to make the inner disks mildly gravitationally unstable as a precursor to star formation.

79 ASTRONOMY AND ASTROPHYSICS↗