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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Abundances of CNO elements in z ∼ 0.3–0.4 Lyman continuum leaking galaxies

We present observations with the Space Telescope Imaging Spectrograph onboard the Hubble Space Telescope (HST) of 11 Lyman continuum (LyC) leaking galaxies at redshifts, z , in the range 0.29–0.43, with oxygen abundances 12+log(O/H) = 7.64–8.16, stellar masses M ⋆ ∼ 10 7.8 –10 9.8 M ⊙ , and O 32 = [O III ] λ5007/[O II ] λ3727 of ∼ 5–20 aiming to detect the C III ] λ1908 emission line. We combine these observations with the optical Sloan Digital Sky Survey (SDSS) spectra for the determination of carbon, nitrogen, and oxygen abundances. Our sample was supplemented by 31 galaxies from the literature, for which carbon, nitrogen, and oxygen abundances can be derived from the HST and SDSS spectra. These additional galaxies, however, do not have LyC observations. We find that log(C/O) for the entire sample at 12+log(O/H) < 8.1 does not depend on metallicity, with a small dispersion of ∼0.13 dex around the average value of ∼−0.75 dex. On the other hand, the log(N/O) in galaxies at z > 0.1, including LyC leakers, is systematically higher compared to the rest of the sample with lower metallicity. We find that log(C/O) slightly decreases with increasing M ⋆ from ∼ −0.65 at M ⋆ = 10 6 M ⊙ to ∼ −0.80 at M ⋆ = 10 9 –10 10 M ⊙ , whereas log(N/O) is considerably enhanced at M ⋆ > 10 8 M ⊙ . The origin of these trends remains basically unknown. A possible solution would be to assume that the upper mass limit of the stellar initial mass function in more massive galaxies is higher. This would result in a higher production of oxygen and a larger fraction of massive stars with stellar wind polluting the interstellar medium with nitrogen.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A comparison of the baryonic Tully–Fisher relation in MaNGA and IllustrisTNG

We compare an observed baryonic Tully–Fisher relation (BTFR) from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) and HI-MaNGA surveys to a simulated BTFR from the cosmological magnetohydrodynamical simulation, IllustrisTNG. To do so, we calibrate the BTFR of the local universe using 377 galaxies from the MaNGA and HI-MaNGA surveys, and perform mock 21 cm observations of matching galaxies from IllustrisTNG. The mock observations are used to ensure that the comparison with the observed galaxies is fair since it has identical measurement algorithms, observational limitations, biases, and uncertainties. For comparison, we also calculate the BTFR for the simulation without mock observations and demonstrate how mock observations are necessary to fairly and consistently compare between observational and theoretical data. We report a MaNGA BTFR of log$_{10} (M_{ \rm Bary}/M_\odot)= (2.97 \pm 0.18)$ log$_{10} V_{ \rm Rot} + (4.04 \pm 0.41)\, \log _{10}{M_{\odot }}$ and an IllustrisTNG BTFR of log$_{10} (M_{ \rm Bary}/M_\odot) = (2.94 \pm 0.23$) log$_{10} V_{ \rm Rot} + (4.15 \pm 0.44)\, \log _{10}{M_{\odot }}$. Thus, MaNGA and IllustrisTNG produce BTFRs that agree within uncertainties, demonstrating that IllustrisTNG has created a galaxy population that obeys the observed relationship between mass and rotation velocity in the observed universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sentiment Analysis based Error Detection for Large-Scale Systems

Today's large-scale systems such as High Performance Computing (HPC) Systems are designed/utilized towards exascale computing, inevitably decreasing its reliability due to the increasing design complexity. HPC systems conduct extensive logging of their execution behaviour. In this paper, we leverage the inherent meaning behind the log messages and propose a novel sentiment analysis-based approach for the error detection in large-scale systems, by automatically mining the sentiments in the log messages. Our contributions are four-fold. (1) We develop a machine learning (ML) based approach to automatically build a sentiment lexicon, based on the system log message templates. (2) Using the sentiment lexicon, we develop an algorithm to detect system errors. (3) We develop an algorithm to identify the nodes and components with erroneous behaviors, based on sentiment polarity scores. (4) We evaluate our solution vs. other state-of-the-art machine/deep learning algorithms based on three representative supercomputers' system logs. Experiments show that our error detection algorithm can identify error messages with an average MCC score and f -score of 91% and 96% respectively, while state of the art ML/deep learning model (LSTM) obtains only 67% and 84%. To the best of our knowledge, this is the first work leveraging the sentiments embedded in log entries of large-scale systems for system health analysis.

error detection↗
DOE OSTI2018

Spatio-Temporal Analysis of HPC I/O and Connection Data

The HPC system consists of a set of layers of software and hardware for I/O and networking. System logs are helpful resources to understand what is going on in the system. A challenge is that it is non-trivial to analyze the logs maintained in various levels of the stack. Independent analysis might lead to an incomplete conclusion due to the limited coverage of each log. This work takes a comprehensive approach to analysis that incorporates the logs in the multiple layers and components, in order to facilitate the detection of anomalous activities. This research aims to identify and predict potential performance bottlenecks in the HPC system, by capturing the temporal variation patterns from heterogeneous, high-dimensional, and non-linear log data. In this paper, we share our preliminary efforts for spatio-temporal analysis of HPC I/O and connection data, with our initial observations from the analysis of one-week HPC log data sets collected from one of NERSC systems.

Choi, Jinhwan↗
DOE OSTI2016

SU-G-JeP1-08: Dual Modality Verification for Respiratory Gating Using New Real- Time Tumor Tracking Radiotherapy System

Purpose: The respirato ry gating system combined the TrueBeam and a new real-time tumor-tracking radiotherapy system (RTRT) was installed. The RTRT system consists of two x-ray tubes and color image intensifiers. Using fluoroscopic images, the fiducial marker which was implanted near the tumor was tracked and was used as the internal surrogate for respiratory gating. The purposes of this study was to develop the verification technique of the respiratory gating with the new RTRT using cine electronic portal image device images (EPIDs) of TrueBeam and log files of the RTRT. Methods: A patient who underwent respiratory gated SBRT of the lung using the RTRT were enrolled in this study. For a patient, the log files of three-dimensional coordinate of fiducial marker used as an internal surrogate were acquired using the RTRT. Simultaneously, the cine EPIDs were acquired during respiratory gated radiotherapy. The data acquisition was performed for one field at five sessions during the course of SBRT. The residual motion errors were calculated using the log files (E{sub log}). The fiducial marker used as an internal surrogate into the cine EPIDs was automatically extracted by in-house software based on the template-matching algorithm. The differences between the the marker positions of cine EPIDs and digitally reconstructed radiograph were calculated (E{sub EPID}). Results: Marker detection on EPID using in-house software was influenced by low image contrast. For one field during the course of SBRT, the respiratory gating using the RTRT showed the mean ± S.D. of 95{sup th} percentile E{sub EPID} were 1.3 ± 0.3 mm,1.1 ± 0.5 mm,and those of E{sub log} were 1.5 ± 0.2 mm, 1.1 ± 0.2 mm in LR and SI directions, respectively. Conclusion: We have developed the verification method of respiratory gating combined TrueBeam and new real-time tumor-tracking radiotherapy system using EPIDs and log files.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Application of a new hybrid particle swarm optimization-mixed kernels function-based support vector machine model for reservoir porosity prediction: A case study in Jacksonburg-Stringtown oil field, West Virginia, USA

Porosity is a fundamental property that characterizes the storage capability of fluid and gas-bearing formations in a reservoir. An accurate porosity value can be measured from core samples in the laboratory; however, core analysis is expensive and time consuming. Well-log data can be used to calculate porosity, but the availability of log suites is often limited in mature fields. Therefore, robust porosity prediction requires integration of core-measured porosity with available well-log suites to control for changes in lithology and fluid content. A support vector machine (SVM) model with mixed kernel function (MKF) is used to construct the relationship between limited conventional well-log suites and sparse core data. Porosity is the desired output, and two conventional well-log responses (gamma ray [GR] and bulk density) and three well-log-derived parameters (the slope of GR, the slope of density, and [Formula: see text]) are input parameters. A global stochastic searching algorithm, particle swarm optimization (PSO), is applied to improve the efficiency of locating the appropriate values of five control parameters in MKF-SVM model. The results of SVM with different traditional kernel functions were compared, and the MKF-SVM model provided an improvement over the traditional SVM model. To confirm the advantage of the hybrid PSO-MKF-SVM model, the results from three models: (1) radial basis function (RBF)-based least-squares SVM, (2) multilayer perceptron artificial neural network (ANN), and (3) RBF ANN, are compared with the result of the hybrid PSO-MKF-SVM model. The results indicate that the hybrid PSO-MKF-SVM model improves porosity prediction with the highest correlation coefficient ([Formula: see text] of 0.9560), the highest coefficient of determination ([Formula: see text] of 0.9140), the lowest root-mean-square error (1.6505), average absolute error value (1.4050), and maximum absolute error (2.717).

Geochemistry & Geophysics↗
DOE OSTI2020

Multi-Scale Lithofacies and Chemostratigraphic Analysis of Two Middle Devonian Marcellus Shale Wells in Northern West Virginia, USA

The Marcellus Shale Energy and Environmental Laboratory (MSEEL) consists of two project areas within the dry gas producing region of the Marcellus shale play in Monongalia County, West Virginia. MSEEL is a collaborative field project led by West Virginia University, with Northeast Natural Energy LLC, several industrial partners, and sponsored by the US Department of Energy National Energy Technology Laboratory. The study areas are drilled approximately 8.5 miles apart to better understand the vertical and lateral changes in stratigraphy over a short distance. Two vertical pilot wells, MIP-3H and Boggess 17H were drilled in the fall of 2015 and spring of 2019, respectively. Core was recovered from the MIP-3H (API: 47-061-01707-00-00) 112 feet (34m) between depths of 7445 to 7557 feet, and from the Boggess 17H (API: 47-061-01812-00-00) 139 feet (42m) between depths of 7908 and 8012 ft. A full suite of triple combo (gamma ray, neutron, density logs), image logs, and advanced logging tools were run in both wells and calibrated to core analysis. Core analysis includes medical computed tomography (CT) scans, mineralogy and chemostratigraphy determined from handheld X-Ray fluorescence (hhXRF) and X-Ray powder diffraction (XRD) measurements, and determination of total organic content (TOC). Lithofacies were determined at core-scale using traditional core description techniques and medical CT-scan images. Log-scale facies are based on mineralogy and TOC data and developed using petrophysical logging data calibrated to core data (XRD and pyrolysis data). Chemostratigraphic analysis utilized hhXRF data to determine the major and trace element trends in the cores. In the two wells six shale lithofacies were recognized at the core and log scale. Both wells show organic-rich facies (TOC > 6.5%) primarily in the middle and lower Marcellus, with a slight decrease in thickness of this interval in the Boggess 17H. This interval is interpreted as an increase in paleo-productivity (increased Ni, Zn, and V), decreased sedimentation (decreased detrital proxies), and anoxic to euxinic conditions (increased Mo and chalcophile elements). Paleo-redox conditions in both wells are dynamic throughout deposition transitioning between euxinic/anoxic to dysoxic/oxic. This trend is seen through elemental proxies and calcite/pyrite concretion distributions.

03 NATURAL GAS↗
DOE OSTI2019

Frio 2 : Raw CASSM Datasets

This submission contains the raw SEG-2 seismic datasets acquired in the CASSM experiment, part of the Frio-2 GCS pilot. The directory also includes the log files generated by the Geode seismograph (geometrics) used during acquisition. All SEG-2 files have a ".dat" suffix and log files have a ".log" suffix. Various supplementary files are also included (see below) including a set of flow and seismic models used in interpretation. The earlyGathers.tar.gz resource includes raw data acquired during system testing and pre-injection periods. All files correspond to the single source continuous active source seismic monitoring (CASSM) dataset described in the following papers. Daley, T.M., Solbau, R.D., Ajo-Franklin, J.B., and Benson, S.M. 2007, “Continuous Active-Source Seismic Monitoring of CO2 Injection in a Brine Aquifer”, Geophysics, Vol. 72, No. 5, p. A57-A61 Daley, T., Ajo-Franklin, J.B., and C. Doughty, 2011, “Constraining the reservoir model of an injected CO2 plume with crosswell CASSM at the Frio-II Brine Pilot”, International Journal of Greenhouse Gas Control (IJGGC), Vol. 5, No. 2, pp. 1022-1030. Zhu, T., Ajo-Franklin, J., and T. Daley, 2017, “Spatio-temporal changes in seismic attenuation caused by injected CO2 at the Frio-II pilot site, Dayton TX, USA”, Journal of Geophysical Research – Solid Earth, Vol. 122, No. 9, pp. 7156-7171. cassmDataRaw.tar : The main tar file containing all of the SEG-2 field records and the Geode log files. Stacking, time sampling (dt), and date information should be in the .log file. Each file corresponds to a single stacked gather for the single source deployed. Data was recorded on a 24 channel downhole hydrophone array. fieldNotes.tar : contains some of the scanned observer logs from the experiments as well as some planning images fieldPhotos.tar : contains a small set of photographs taken during the experiment frio_flow_seismic_models.mat : a matlab structure containing a set of flow and seismic models used in interpreting the CASSM data (see IJGGC paper).

GCS↗
DOE OSTI2022

A Mountaintop View Requires Minimal Sorting: A Faster Contour Tree Algorithm

Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in R d . A level set, or contour, at value v is a connected component of f –1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$ pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$ pϵP |p| log |p| complexity is inherent to computing contour trees.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

On the state of a solar active region before flares and CMEs

Several attempts have been made to find reliable diagnostic tools to determine the state prior to flares and related coronal mass ejections (CMEs) in solar active regions (ARs). Characterization of the level of mixed states is carried out using the Debrecen sunspot Data for 116 flaring ARs. Conditional flare probabilities (CFPs) are calculated for different flaring classes. The association with slow/fast CMEs is examined. Two precursor parameters are introduced: (i) the sum of the (daily averaged) horizontal magnetic gradient G {sub S} (G {sub DS}) and (ii) the separation parameter S{sub l−f}. We found that if S{sub l−f}⩽1 for a flaring AR then the CFP of the expected highest-intensity flare being X-class is more than 70%. If 1⩽S{sub l−f}⩽3 the CFP is more than 45% for the highest-intensity flare(s) to be M-class, and if 3⩽S{sub l−f}⩽13 there is larger than 60% CFP that C-class flare(s) may have the strongest intensity within 48 hr. Next, from analyzing G {sub S} for determining CFP we found: if 5.5⩽log(G{sub S}) ⩽ 6.5, then it is very likely that C-class flare(s) may be the most intense; if 6.5⩽log(G{sub S})⩽7.5 then there is ∼45% CFP that M-class could have the highest intensity; finally, if 7.5⩽log(G{sub S}) then there is at least 70% chance that the strongest energy release will be X-class in the next 48 hr. ARs are unlikely to produce X-class flare(s) if 13⩽S{sub l−f} and log(G {sub S}) ⩽ 5.5. Finally, in terms of providing an estimate of an associated slow/fast CME, we found that, if log(S{sub l−f}) ⩾ 0.4 or log(G{sub DS}) ⩽ 6.5, there is no accompanying fast CME in the following 24 hr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A new prescription for the mass-loss rates of WC and WO stars

We present a new empirical prescription for the mass-loss rates of carbon- and oxygen-sequence Wolf–Rayet stars as a function of their luminosity, surface chemical composition, and initial metallicity. The new prescription is based on results of detailed spectral analyses of WC and WO stars and improves the often applied Nugis and Lamers relation. We find that the mass-loss rates of WC and WO stars (with X = 0 and Y ≲ 0.98) can be expressed as log M-dot =−9.20+0.85log(L/L {sub ⊙}) + 0.44 log Y + 0.25 log (Z {sub Fe}/Z {sub Fe,⊙}). This relation is based on mass-loss determinations that assume a volume-filling factor of 0.1, but the prescription can easily be scaled to account for other volume-filling factors. The residual of the fit is σ = 0.06 dex. We investigated whether the relation can also describe the mass loss of hydrogen-free WN stars and showed that it can when an adjustment of the metallicity dependence (log M-dot ∝1.3log(Z{sub Fe}/Z{sub Fe,⊙})) is applied. Compared to that of Nugis and Lamers, M-dot is less sensitive to the luminosity and the surface abundance, implying a stronger mass loss of massive stars in their late stages of evolution. The modest metallicity dependence implies that if WC or WO stars are formed in metal-deficient environments, their mass-loss rates are higher than currently anticipated. These effects may result in the formation of a larger number of SNe Ic and fewer black holes and may favor the production of superluminous SNe Ic through interaction with C- and O-rich circumstellar material or dense stellar wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The MASSIVE Survey. XVI. The Stellar Initial Mass Function in the Center of MASSIVE Early-type Galaxies

The stellar initial mass function (IMF) is a fundamental property in the measurement of stellar masses and galaxy star formation histories. In this work, we focus on the most massive galaxies in the nearby universe $\mathrm{log}({M}_{\star }/\,{M}_{\odot })\gt 11.2$. We obtain high-quality Magellan/LDSS-3 long-slit spectroscopy with a wide wavelength coverage of 0.4–1.01 μm for 41 early-type galaxies (ETGs) in the MASSIVE survey and derive high signal-to-noise spectra within an aperture of R e /8. Using detailed stellar synthesis models, we constrain the elemental abundances and stellar IMF of each galaxy through full spectral modeling. All the ETGs in our sample have an IMF that is steeper than a Milky Way (Kroupa) IMF. The best-fit IMF mismatch parameter, α IMF = (M/L)/(M/L) MW , ranges from 1.1 to 3.1, with an average of $\langle$α IMF $\rangle$ = 1.84, suggesting that on average, the IMF is more bottom heavy than Salpeter. Comparing the estimated stellar masses with the dynamical masses, we find that most galaxies have stellar masses that are smaller than their dynamical masses within the 1σ uncertainty. We complement our sample with lower-mass galaxies from the literature and confirm that $\mathrm{log}({\alpha }_{\mathrm{IMF}})$ is positively correlated with $\mathrm{log}(\sigma )$, $\mathrm{log}({M}_{\star })$, and $\mathrm{log}({M}_{\mathrm{dyn}})$. From the combined sample, we show that the IMF in the centers of more massive ETGs is more bottom heavy. In addition, we find that $\mathrm{log}({\alpha }_{\mathrm{IMF}})$ is positively correlated with both [Mg/Fe] and the estimated total metallicity [Z/H]. We find suggestive evidence that the effective stellar surface density Σ Kroupa might be responsible for the variation of α IMF . We conclude that σ, [Mg/Fe], and [Z/H] are the primary drivers of the global stellar IMF variation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

CLEAR: The Ionization and Chemical-enrichment Properties of Galaxies at 1.1 < z < 2.3

We use deep spectroscopy from the Hubble Space Telescope Wide-Field-Camera 3 IR grisms combined with broadband photometry to study the stellar populations, gas ionization and chemical abundances in star-forming galaxies at z ~ 1.1–2.3. The data stem from the CANDELS Lyα Emission At Reionization (CLEAR) survey. At these redshifts, the grism spectroscopy measure the [O II] λλ3727, 3729, [O III]λλ4959, 5008, and Hβ strong emission features, which constrain the ionization parameter and oxygen abundance of the nebular gas. We compare the line-flux measurements to predictions from updated photoionization models (MAPPINGS V; Kewley et al.), which include an updated treatment of nebular gas pressure, $\mathrm{log}P/k={n}_{e}{T}_{e}$. Compared to low-redshift samples (z ~ 0.2) at fixed stellar mass, $\mathrm{log}{M}_{* }/{M}_{\odot }\,=$ 9.4–9.8, the CLEAR galaxies at z = 1.35 (1.90) have lower gas-phase metallicity, ${\rm{\Delta }}(\mathrm{log}Z)$ = 0.25 (0.35) dex, and higher ionization parameters, ${\rm{\Delta }}(\mathrm{log}q)$ = 0.25 (0.35) dex, where U ≡ q/c. We provide updated analytic calibrations between the [O III], [O II], and Hβ emission-line ratios, metallicity, and ionization parameter. The CLEAR galaxies show that at fixed stellar mass, the gas ionization parameter is correlated with the galaxy specific star formation rates, where ${\rm{\Delta }}\mathrm{log}q\simeq 0.4\times {\rm{\Delta }}(\mathrm{log}\,\mathrm{sSFR})$, derived from changes in the strength of galaxy Hβ equivalent width. We interpret this as a consequence of higher gas densities, lower gas covering fractions, combined with a higher escape fraction of H-ionizing photons. We discuss both tests to confirm these assertions and implications this has for future observations of galaxies at higher redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

CLASSY IV. Exploring UV Diagnostics of the Interstellar Medium in Local High- z Analogs at the Dawn of the JWST Era

The Cosmic Origins Spectrograph (COS) Legacy Archive Spectroscopic SurveY (CLASSY) provides the first high resolution spectral catalog of 45 local high-z analogs in the ultraviolet (UV; 1200–2000 Å) to investigate their stellar and gas properties. Here we present a toolkit of UV interstellar medium (ISM) diagnostics, analyzing the main emission lines of CLASSY spectra (N IV] λλ1483,87, C IV λλ1548,51, He IIλ1640, O III]λλ1661,6, Si III] λλ1883,92, C III] λ1907,9). Specifically, our aim is to provide accurate diagnostics for the reddening E(B - V), electron density n e , electron temperature T e , metallicity 12+log(O/H), and ionization parameter log(U), taking the different ISM ionization zones into account. We calibrate our UV toolkit using well-known optical diagnostics, analyzing archival optical spectra for all CLASSY targets. We find that UV density diagnostics estimate n e values that are ~1–2 dex higher (e.g., n e (C III] λλ1907,9) ~ 10 4 cm -3 ) than those inferred from their optical counterparts (e.g., n e ([S II]λλ6717,31) ~ 10 2 cm -3 ; n e ([Ar IV]λλ4714,41) ~ 10 3 cm -3 ). T e derived from the hybrid ratio [O III] λ1666/λ5007 proves to be reliable, implying differences in determining 12+log(O/H) compared to the optical counterpart O III] λ4363/[O III] λ5007 within ~ ±0.3 dex. We also investigate the relation between the stellar and gas E(B - V), finding consistent values at high specific star formation rates (sSFRs; log sSFR ≳ -8 yr -1 ), while at low sSFRs we confirmed an excess of dust attenuation in the gas. Finally, we investigate UV line ratios and equivalent widths to provide correlations with 12+log (O/H) and log(U), but note that there are degeneracies between the two. With this suite of UV-based diagnostics, we illustrate the pivotal role CLASSY plays in understanding the chemical and physical properties of high-z systems that JWST can observe in the rest-frame UV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The Stellar Mass Function for Nine Massive Galaxy Clusters in the Local Universe

We measure galaxy stellar mass functions (SMFs) for nine of the most massive galaxy clusters in the local Universe (0.07 < z < 0.11) using deep and complete spectroscopy from the MAssive Cluster Survey with Hectospec (MACH). We construct the cluster SMFs down to log (M * /M ⊙ ) ≳ 8.5. For comparison, we measure the SMF for field galaxies, complete to log (M * /M ⊙ ) ≳ 10.5, based on Sloan Digital Sky Survey spectroscopy over the same redshift range. The mean MACH SMF shows a shape similar to that of the field SMF but with a significantly higher amplitude at log (M * /M ⊙ ) < 11.4. At log (M * /M ⊙ ) > 11.4, the MACH SMF shows a clear excess, indicating the contribution of massive galaxies, including brightest cluster galaxies (BCGs). Based on homogeneous MACH spectroscopy, we compare SMF shapes for quiescent and star-forming members as a function of the cluster-centric distance. The quiescent SMFs display a curved shape with a peak at log (M * /M ⊙ ) ≈ 10.5; the star-forming SMFs decline monotonically with increasing stellar mass. We further compare the mean MACH SMF with SMFs derived from similarly massive clusters in the IllustrisTNG-300 simulations. The shape of the observed and simulated SMFs agrees well overall. However, the MACH clusters contain roughly a factor of 2 more galaxies at 9.0 < log (M * /M ⊙ ) < 10.5. These results demonstrate that constructing cluster SMFs from complete spectroscopic samples can test simulations and provide powerful constraints on galaxy formation and evolution in dense environments.

Park, Jong-In [Seoul National University (Korea, R↗
DOE OSTI2016

Addressing numerical challenges in introducing a reactive transport code into a land surface model: a biogeochemical modeling proof-of-concept with CLM–PFLOTRAN 1.0

Abstract. We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models. A reaction network with the Community Land Model carbon–nitrogen (CLM-CN) decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN (massively parallel subsurface flow and reactive transport) code and couple it with the CLM. To make the rate formulae designed for use in explicit time stepping in CLMs compatible with the implicit time stepping used in PFLOTRAN, the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. We demonstrate that CLM–PFLOTRAN predictions (without invoking PFLOTRAN transport) are consistent with CLM4.5 for Arctic, temperate, and tropical sites.Switching from explicit to implicit method increases rigor but introduces numerical challenges. Care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance (STOL) to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10-3 to 10-9 mol m-3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %, double for log transformation. Overall, the log transformation method is accurate and robust, and the clipping and scaling methods are efficient. When the reaction network is highly nonlinear or the half saturation or residual concentration is very low, the allowable time-step cuts may need to be increased for robustness for the log transformation method, or STOL may need to be tightened for the clipping and scaling methods to avoid false convergence.As some biogeochemical processes (e.g., methane and nitrous oxide reactions) involve very low half saturation and thresholds, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in Earth system models to reduce climate prediction uncertainty.

58 GEOSCIENCES↗
NASA NTRS1981

The high-excitation planetary nebulae: NGC 3918 and IC 2448

International Ultraviolet Exploration observations of NGC 3918 and IC 2448 are presented. Combining these observations with data in the optical range and computed model structure, the chemical composition for these objects is derived. For NGC 3918 log C = -3.02, log N = -3.61 and log 0 = -3.22; while for IC 2448 log C = -3.44, log N = -81 and log 0 = 3.54.

Torres-Peimbert, S.↗