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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

On the Origin of the Fundamental Plane and Faber–Jackson Relations: Implications for the Star Formation Problem

We provide an explanation of the properties of the fundamental plane (FP) relation and its observed projections for a sample of nearby early-type galaxies (ETGs) in terms of a fine-tuning between the time-averaged star formation rate 〈Ψ〉 and their structural and dynamical characteristics. Their total V luminosity is linked with 〈Ψ〉 and the central velocity dispersion σ through the relation log(L)=0.48(±0.06)log(〈Ψ〉)+1.00 (±0.13)log(σ)+7.81(±0.26), with an rms = 0.215 (R = 0.64 and P<1.2×10{sup −16}). This fine-tuning permits us to obtain the FP in terms of two distinct “virtual planes” in the log(R{sub e})--log(〈I{sub e}〉)--log(σ) space. The first one (the virial plane; VP) represents the total galaxy mass derived from the scalar virial theorem and the mass-to-light ratio M/L, while the second plane comes from the relation L=L{sub 0}{sup ′}σ{sup −2}, where L{sub 0}{sup ′} is a parameter connected with 〈Ψ〉. This is a mathematically convenient way for expressing the independence of the galaxy light from the virial equilibrium. Each galaxy in the log(R{sub e})--log(〈I{sub e}〉)--log(σ) space is identified by the intersection of these two planes. A posteriori, we show that the properties of the FP (tilt and scatter) and the zone of exclusion visible in the FP projections are consequences of this fine-tuning. The link between the FP properties and the SFR of galaxies provides a new view of the star formation phenomenon. The star formation history of an unperturbed galaxy seems to be driven by the initial conditions in the protogalaxies and is regulated across cosmic epochs by the variation of the main galaxy parameters (mass, luminosity, structural shape, and velocity dispersion).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

REVISITING THE SCALING RELATIONS OF BLACK HOLE MASSES AND HOST GALAXY PROPERTIES

New kinematic data and modeling efforts in the past few years have substantially expanded and revised dynamical measurements of black hole masses (M {sub .}) at the centers of nearby galaxies. Here we compile an updated sample of 72 black holes and their host galaxies, and present revised scaling relations between M {sub .} and stellar velocity dispersion ({sigma}), V-band luminosity (L), and bulge stellar mass (M {sub bulge}), for different galaxy subsamples. Our best-fitting power-law relations for the full galaxy sample are log{sub 10}(M {sub .}) = 8.32 + 5.64log{sub 10}({sigma}/200 km s{sup -1}), log{sub 10}(M {sub .}) = 9.23 + 1.11log{sub 10}(L/10{sup 11} L {sub Sun }), and log{sub 10}(M {sub .}) = 8.46 + 1.05log{sub 10}(M {sub bulge}/10{sup 11} M {sub Sun }). A log-quadratic fit to the M {sub .}-{sigma} relation with an additional term of {beta}{sub 2} [log{sub 10}({sigma}/200 km s{sup -1})]{sup 2} gives {beta}{sub 2} = 1.68 {+-} 1.82 and does not decrease the intrinsic scatter in M {sub .}. Including 92 additional upper limits on M {sub .} does not change the slope of the M {sub .}-{sigma} relation. When the early- and late-type galaxies are fit separately, we obtain similar slopes of 5.20 and 5.06 for the M {sub .}-{sigma} relation but significantly different intercepts-M {sub .} in early-type galaxies are about two times higher than in late types at a given sigma. Within early-type galaxies, our fits to M {sub .}({sigma}) give M {sub .} that is about two times higher in galaxies with central core profiles than those with central power-law profiles. Our M {sub .}-L and M {sub .}-M {sub bulge} relations for early-type galaxies are similar to those from earlier compilations, and core and power-law galaxies yield similar L- and M {sub bulge}-based predictions for M {sub .}. When the conventional quadrature method is used to determine the intrinsic scatter in M {sub .}, our data set shows weak evidence for increased scatter at M {sub bulge} < 10{sup 11} M {sub Sun} or L{sub V} < 10{sup 10.3} L {sub Sun }, while the scatter stays constant for 10{sup 11} < M {sub bulge} < 10{sup 12.3} M {sub Sun} and 10{sup 10.3} < L{sub V} < 10{sup 11.5} L {sub Sun }. A Bayesian analysis indicates that a larger sample of M {sub .} measurements would be needed to detect any statistically significant trend in the scatter with galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE MOSDEF SURVEY: DISSECTING THE STAR FORMATION RATE VERSUS STELLAR MASS RELATION USING Hα AND Hβ EMISSION LINES AT z ∼ 2

We present results on the star formation rate (SFR) versus stellar mass (M{sub *}) relation (i.e., the “main sequence”) among star-forming galaxies at 1.37 ≤ z ≤ 2.61 using the MOSFIRE Deep Evolution Field (MOSDEF) survey. Based on a sample of 261 galaxies with Hα and Hβ spectroscopy, we have estimated robust dust-corrected instantaneous SFRs over a large range in M{sub *} (∼10{sup 9.5}–10{sup 11.5} M{sub ⊙}). We find a correlation between log(SFR(Hα)) and log(M{sub *}) with a slope of 0.65 ± 0.08 (0.58 ± 0.10) at 1.4 < z < 2.6 (2.1 < z < 2.6). We find that different assumptions for the dust correction, such as using the color excess of the stellar continuum to correct the nebular lines, sample selection biases against red star-forming galaxies, and not accounting for Balmer absorption, can yield steeper slopes of the log(SFR)–log(M{sub *}) relation. Our sample is immune from these biases as it is rest-frame optically selected, Hα and Hβ are corrected for Balmer absorption, and the Hα luminosity is dust corrected using the nebular color excess computed from the Balmer decrement. The scatter of the log(SFR(Hα))–log(M{sub *}) relation, after accounting for the measurement uncertainties, is 0.31 dex at 2.1 < z < 2.6, which is 0.05 dex larger than the scatter in log(SFR(UV))–log(M{sub *}). Based on comparisons to a simulated SFR–M{sub *} relation with some intrinsic scatter, we argue that in the absence of direct measurements of galaxy-to-galaxy variations in the attenuation/extinction curves and the initial mass function, one cannot use the difference in the scatter of the SFR(Hα)– and SFR(UV)–M{sub *} relations to constrain the stochasticity of star formation in high-redshift galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing

Abstract We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0–5‐log 10 reduction in Salmonella ) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400 – 248,000) cases/year. Risk reduction (by 5 ‐ to 7‐fold) predicted from a 1‐log 10 seed treatment alone was comparable to SIW testing alone, and each additional 1‐log 10 seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3‐log 10 or a 5‐log 10 seed treatment reduced the predicted cases/year to 139 (95% CI 33 – 448) or 1.4 (95% CI <1 – 4.5), respectively. Combined with SIW testing, a 3‐log 10 or 5‐log 10 seed treatment reduced the cases/year to 45 (95% CI 10–146) or <1 (95% CI <1 – 1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3‐log 10 seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22 – 298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

nSnare™

nSnare™ analyses and categorizes log messages generated by various and customizable third party software packages using a custom multi-tiered rules engine. Each log message is either determined to be a false positive, or it is assigned a score based on the severity of the potential attack and confidence that the activity described by the log message is not a false positive. Log messages are then assigned to an event, which is a collection of log messages related to a single potential attack. Meta-analysis rules run on the collection of all logs within an event to correlate multiple related logs into a single known attack signature. When the sum of the scores of all logs within an event exceeds a pre-defined threshold, the event is labelled as an attack and an automated response is generated to block the attacker from connecting to any protected resources, called quarantining within the application, for a variable length of time. The length of time that the quarantine lasts for is based on the severity and frequency of the attack, along with historical information on the attacker and any third party provided threat intelligence data that the system has gathered. An additional random length of time is added to each quarantine so the algorithm cannot easily be learned and bypassed by a persistent attacker. A confidence score is generated based on a proprietary algorithm that determines the likelihood that the data which lead to the attacker getting quarantined was a false positive. A threat intelligence record is created for each detected attack, with details on the attacker, a summary of what triggered the quarantine, the severity of the attack and the confidence the system has that the attack is not the result of false data, which can then be shared with external entities so that they can also protect themselves from a related attack. The software also includes a web based front end for analyzing the current quarantined attacks, removing a quarantine in the case of a false positive, viewing previously quarantined attacks, and tracking suspicious activity that the system is currently evaluating. The web interface also allows the creation and modification of rules used by the rules engine, and the maintenance of a whitelist of known good systems that should never be automatically quarantined.

Hoying, Andrew↗
DOE OSTI2017

Geomechanical Framework for Secure CO 2 Storage in Fractured Reservoirs and Caprocks for Sedimentary Basins in theMidwest United States

This report presents final technical results for the project Geomechanical Framework for Secure CO 2 Storage in Fractured Reservoirs and Caprocks for Sedimentary Basins in the Midwest United States (DE-FE0023330). The project was a three-year effort consisting of seven technical tasks focused on defining geomechanical factors for CO 2 storage applications in deep saline rock formations in Ohio and the Midwest United States, because geomechancial issues have been identified as a significant risk factor for large-scale CO 2 storage applications. A basin-scale stress-strain analysis was completed to describe the geomechanical setting for rock formations of Ordovician-Cambrian age in Ohio and adjacent areas of the Midwest United States in relation to geologic CO 2 storage applications. The tectonic setting, stress orientation-magnitude, and geomechanical and petrophysical parameters for CO 2 storage zones and caprocks in the region were cataloged. Ten geophysical image logs were analyzed for natural fractures, borehole breakouts, and drilling-induced fractures. The logs indicated mostly less than 10 fractures per 100 vertical feet in the borehole, with mostly N65E principal stress orientation through the section. Geophysical image logs and other logs were obtained for three wells located near the sites where specific models were developed for geomechanical simulations: Arches site in Boone County, Kentucky; Northern Appalachian Basin site in Chautauqua County, New York; and E-Central Appalachian Basin site in Tuscarawas County, Ohio. For these three wells, 9,700 feet of image logs were processed and interpreted to provide a systematic review of the distribution within each well of natural fractures, wellbore breakouts, faults, and drilling induced fractures. There were many borehole breakouts and drilling-induced tensile fractures but few natural fractures. Concentrated fractures were present at the Rome-basal sandstone and basal sandstone-Precambrian contacts at the Arches and East-Central Appalachian Basin sites. Geophysical logs were utilized to develop local-scale geologic models by determining geomechanical and petrophysical parameters within the geologic formations. These data were ported to coupled fluid-flow and reservoir geomechanics multi-phase CO 2 injection simulations. The models were developed to emphasize the geomechanical layers within the CO 2 storage zones and caprocks. A series of simulations were completed for each site to evaluate whether commercial-scale CO 2 could be safely injected into each site, given site-specific geologic and geomechanical controls. This involved analyzing the simulation results for the integrity of the caprock, intermediate, and reservoir zones, as well quantifying the areal uplift at the surface. Simulation results were also examined to ensure that the stress-stress perturbations were isolated within the subsurface, and that there was only limited upward migration of the CO 2 . Simulations showed capacity to inject more than 10 million metric tons of CO 2 in a single well at the Arches and East Central Appalachian Basin sites without excessive geomechanical risks. Low-permeability rock layers at the Northern Appalachian Basin study area well resulted in very low CO 2 injection capacity. Fracture models developed for the sites suggests that the sites have sparse fracture network in the deeper Cambrian rocks. However, there were indicators in image logs of a moderate fracture matrix in the Rose Run Sandstone at the Northern Appalachian Basin site. Dual permeability fracture matrix simulations suggest the much higher injection rates may be feasible in the fractured interval. Guidance was developed for geomechanical site characterization in the areas of geophysical logging, rock core testing, well testing, and site monitoring. The guidance demonstrates that there is a suitable array of options for addressing geomechanical issues at CO 2 storage sites. Finally, a review of Marcellus and Utica-Point Pleasant shale gas wells and CO 2 storage intervals indicates that these items are vertically separated, except for the Oriskany sandstone and Marcellus wells in southwest Pennsylvania and northern West Virginia. Together, project results present a more realistic portrayal of geomechanical risk factors related to CO 2 storage for existing and future coal-fired power plants in Ohio.

58 GEOSCIENCES↗
DOE OSTI2026

Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data

We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from $\sim 100 \; {\rm kpc}$ to $\sim 100 \; {\rm Mpc}$, using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of $\log M_\star/M_\odot \sim 9.6$ to $\sim 11.5$; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form $\log M_\star (M_h) = \log(εM_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{αx}+1) + δ[\log(1+\exp(x))]^γ/ [1+\exp(10^{-x})]$, to be $\log M_1 = 11.506^{+0.325}_{-0.404}$, $\log ε= -1.632^{+0.306}_{-0.181}$, $α= -1.638^{+0.108}_{-0.099}$, $γ= 0.596^{+0.251}_{-0.210}$ and $δ= 3.810^{+2.045}_{-1.811}$. The inferred average satellite fraction is within $\sim 5-35\%$ for our fiducial results and we do not see any clear trends with redshift or stellar mass. Furthermore, we find that the inferred average galaxy bias values follow the generally expected trends with stellar mass and redshift. Our study is the first SHMR in DES in this mass range, and we expect the stellar mass sample to be of general interest for other science cases.

Zacharegkas, G. [Argonne; Chicago U., KICP] (ORCID↗
NASA NTRS1986

Spectrum and chemical analysis of the double-ring planetary nebula IC 1297

The double-ring planetary nebula IC 1297 resembles NGC 7662 in appearance, although it is of much lower surface brightness. What is remarkable is the great strength of the dielectronic recombination O V line. Although this line is seen as a P Cygni feature in a number of planetary nebulae, it is in those instances accompanied by a strong continuum and other easily recognized features of stellar origin. No star is visible on CCD images of IC 1297. Optical region measurements are supplemented by IUE observations. The following logarithmic abundance values are found: log N(He) = 11.065; log N(forbidden C) = 8.6; log N(N) = 8.1; log N(O) = 8.74; log N(Ne) = 8.16; log N(S) = 7.0; log N(Cl) = 5.4; log N(Ar) = 6.2. The nebula shows no dramatic pattern of nucleogenesis events.

Aller, Lawrence H.↗
DOE OSTI2012

iSSH v. Auditd: Intrusion Detection in High Performance Computing

The goal is to provide insight into intrusions in high performance computing, focusing on tracking intruders motions through the system. The current tools, such as pattern matching, do not provide sufficient tracking capabilities. We tested two tools: an instrumented version of SSH (iSSH) and Linux Auditing Framework (Auditd). First discussed is Instrumented Secure Shell (iSSH): a version of SSH developed at Lawrence Berkeley National Laboratory. The goal is to audit user activity within a computer system to increase security. Capabilities are: Keystroke logging, Records user names and authentication information, and Catching suspicious remote and local commands. Strengths for iSSH are: (1) Good for keystroke logging, making it easier to track malicious users by catching suspicious commands; (2) Works with Bro to send alerts; could be configured to send pages to systems administrators; and (3) Creates visibility into SSH sessions. Weaknesses are: (1) Relatively new, so not very well documented; and (2) No capabilities to see if files have been edited, moved, or copied within the system. Second we discuss Auditd, the user component of the Linux Auditing System. It creates logs of user behavior, and monitors systems calls and file accesses. Its goal is to improve system security by keeping track of users actions within the system. Strenghts of Auditd are: (1) Very thorough logs; (2) Wider variety of tracking abilities than iSSH; and (3) Older, so better documented. Weaknesses are: (1) Logs record everything, not just malicious behavior; (2) The size of the logs can lead to overflowing directories; and (3) This level of logging leads to a lot of false alarms. Auditd is better documented than iSSH, which would help administrators during set up and troubleshooting. iSSH has a cleaner notification system, but the logs are not as detailed as Auditd. From our performance testing: (1) File transfer speed using SCP is increased when using iSSH; and (2) Network benchmarks were roughly the same regardless of which tool was running.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Energy deposition validation results for the evaluated electron data library in FRENSIE - 25357

The Framework for Research in Nuclear Science and Engineering (FRENSIE) is a collection of packages written in C++ that are designed primarily to aid in methods development. A recent development in FRENSIE is the modeling of single scattering electron interactions using the data in the Evaluated Electron Data Library (EEDL) from Lawrence Livermore National Laboratory (LLNL). Preliminary verification and validation (V and V) results using the well-known Lockwood energy deposition experiment and a comparison with MCNP6.2 were performed using several bivariate grid policies (Unit-base, Correlated, Unit-base Correlated), interpolation schemes (lin-lin, log-log, lin-log), and physics options (Coupled and Decoupled Elastic Scattering). The results show an agreement to within 0.5% between MCNP6.2 and FRENSIE when using the same bivariate grid policy (Correlated) and interpolation scheme (log-log). When compared to the experimental results of the Lockwood experiment, it was found that a Unit-base bivariate grid policy, lin-lin interpolation scheme, and lin-log interpolation scheme did not produce accurate results for the energy deposition in test problems. The log-log Correlated and Unit-base Correlated results showed the greatest agreement with the Lockwood experiment. The total energy deposition matched the experimental data to within 3%. Both the Correlated and Unit-base Correlated results had a tendency to estimate a higher energy deposition near the peaks and a lower energy deposition near the tails. The differences between coupled elastic scattering and decoupled scattering models were shown to be more prominent at higher energies with the results of the coupled elastic scattering being more accurate for the peak and less accurate for the tail of the energy deposition profiles. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Development of Enabling Scientific Tools to Characterize the Geologic Subsurface at Hanford

This final report to the Department of Energy provides a summary of activities conducted under our exploratory grant, funded through U.S. DOE Subsurface Biogeochemical Research Program in the category of enabling scientific tools, which covers the period from July 15, 2010 to July 14, 2013. The main goal of this exploratory project is to determine the parameters necessary to translate existing borehole log data into reservoir properties following scientifically sound petrophysical relationships. For this study, we focused on samples and Ge-based spectral gamma logging system (SGLS) data collected from wells located in the Hanford 300 Area. The main activities consisted of 1) the analysis of available core samples for a variety of mineralogical, chemical and physical; 2) evaluation of selected spectral gamma logs, environmental corrections, and calibration; 3) development of algorithms and a proposed workflow that permits translation of log responses into useful reservoir properties such as lithology, matrix density, porosity, and permeability. These techniques have been successfully employed in the petroleum industry; however, the approach is relatively new when applied to subsurface remediation. This exploratory project has been successful in meeting its stated objectives. We have demonstrated that our approach can lead to an improved interpretation of existing well log data. The algorithms we developed can utilize available log data, in particular gamma, and spectral gamma logs, and continued optimization will improve their application to ERSP goals of understanding subsurface properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

April 2020 Darshan counters from the Summit supercomputer

This dataset is the Darshan counters collected from the Summit supercomputer in a month of April 2020. 1. Description of methods used for collection/generation of data: Job submitted on Summit HPC system when completed successfully and has made I/O calls (captured by Darshan tool) writes a Darshan log file on alpine filesystem. One job can have multiple `jsrun` commands and Darshan will generate separate logs each log corresponding to an `jsrun` command, so a job can have one or more Darshan logs associated with it. 2. Methods for processing the data: To process the data, we first use `darshan-util` tool to parse the Darshan logs. Then we restructure the logs and merge data from multiple Darshan logs if they belong to the same Summit job.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Neural network modeling of in situ fluid-filled pore size distributions in subsurface shale reservoirs under data constraints

Subsurface nuclear magnetic resonance (NMR) logs acquired in the wellbore environment are sensitive to fluid-filled pore size distribution, fluid mobility, permeability, and porosity in the near-wellbore reservoir volume. NMR response of a formation layer is processed to extract the T2 distribution, which approximates the fluid-filled pore size distribution. NMR logs are acquired in limited number of wells due to financial and operational challenges, which adversely affects reservoir characterization. We developed here two neural-network-based machine learning techniques, long short-term memory (LSTM) network and variational autoencoder with a convolutional layer (VAEc) network, to process the ‘easy-to-acquire’ formation mineral and fluid saturation logs to generate synthetic NMR T2 distributions in the absence of ‘hard-to-acquire’ NMR T2 distribution log. Both the predictive models are trained and tested on limited wireline log measurements randomly selected from a 300-ft depth interval of the Bakken shale formation. Synthesis performances of LSTM and VAEc models in terms of R 2 are 0.78 and 0.75, respectively. Noise is inevitable in logging data due to the complex wellbore and formation conditions. Notably, both the predictive models robustly synthesize the fluid-filled pore size distributions in the presence of 50% noise in input logs and 30% noise in training T2 data. The performance of the proposed methodology improves with access to larger volume of training data from other formation types. The proposed method is critical to the synthesis of in situ fluid-filled pore size distributions in shale formations under data constraints due to financial and operational challenges.

58 GEOSCIENCES↗
DOE OSTI2011

KEPLER INPUT CATALOG: PHOTOMETRIC CALIBRATION AND STELLAR CLASSIFICATION

We describe the photometric calibration and stellar classification methods used by the Stellar Classification Project to produce the Kepler Input Catalog (KIC). The KIC is a catalog containing photometric and physical data for sources in the Kepler mission field of view; it is used by the mission to select optimal targets. Four of the visible-light (g, r, i, z) magnitudes used in the KIC are tied to Sloan Digital Sky Survey magnitudes; the fifth (D51) is an AB magnitude calibrated to be consistent with Castelli and Kurucz (CK) model atmosphere fluxes. We derived atmospheric extinction corrections from hourly observations of secondary standard fields within the Kepler field of view. For these filters and extinction estimates, repeatability of absolute photometry for stars brighter than magnitude 15 is typically 2%. We estimated stellar parameters {l_brace}T{sub eff}, log (g), log (Z), E{sub B-V}{r_brace} using Bayesian posterior probability maximization to match observed colors to CK stellar atmosphere models. We applied Bayesian priors describing the distribution of solar-neighborhood stars in the color-magnitude diagram, in log (Z), and in height above the galactic plane. Several comparisons with samples of stars classified by other means indicate that for 4500 K {<=}T{sub eff} {<=} 6500 K, our classifications are reliable within about {+-}200 K and 0.4 dex in log (g) for dwarfs, with somewhat larger log (g) uncertainties for giants. It is difficult to assess the reliability of our log (Z) estimates, but there is reason to suspect that it is poor, particularly at extreme T{sub eff}. Comparisons between the CK models and observed colors are generally satisfactory with some exceptions, notably for stars cooler than 4500 K. Of great importance for the Kepler mission, for T{sub eff} {<=} 5400 K, comparison with asteroseismic results shows that the distinction between main-sequence stars and giants is reliable with about 98% confidence. Larger errors in log (g) occur for warmer stars, for which our filter set provides inadequate gravity diagnostics. The KIC is available through the MAST data archive.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2010

STUDYING THE WHIM CONTENT OF LARGE-SCALE STRUCTURES ALONG THE LINE OF SIGHT TO H 2356-309

We make use of a 500 ks Chandra HRC-S/LETG spectrum of the blazar H 2356-309, combined with a lower signal-to-noise ratio (S/N; 100 ks) pilot LETG spectrum of the same target, to search for the presence of warm-hot absorbing gas associated with two large-scale structures (LSSs) crossed by this sight line and to constrain its physical state and geometry. Strong (log N{sub O{sub VII}} {>=} 10{sup 16} cm{sup -2}) O VII K{alpha} absorption associated with a third LSS crossed by this line of sight (the Sculptor Wall (SW)), at z = 0.03, has already been detected in a previous work. Here, we focus on two additional prominent filamentary LSSs along the same line of sight, one at z = 0.062 (the Pisces-Cetus Supercluster (PCS)) and another at z = 0.128 (the 'Farther Sculptor Wall' (FSW)). The combined LETG spectrum has an S/N of {approx}11.6-12.6 per resolution element in the 20-25 A and an average 3{sigma} sensitivity to intervening O VII K{alpha} absorption line equivalent widths (EWs) of EW{sub O{sub VII}} {approx_gt} 14 mA in the available redshift range (z < 0.165). No statistically significant (i.e., {>=}3{sigma}) individual absorption is detected from any of the strong He- or H-like transitions of C, O, and Ne (the most abundant metals in gas with solar-like composition) at the redshifts of the PCS and FSW structures and down to the EW thresholds mentioned above. However, we are still able to constrain the physical and geometrical parameters of the putative absorbing gas associated with these structures, by performing a joint spectral fit of various marginal detections and upper limits of the strongest expected lines with our self-consistent hybrid-ionization WHIM spectral model. At the redshift of the PCS, we identify a warm phase with log T = 5.35{sup +0.07}{sub -0.13} K and log N{sub H} = (19.1 {+-} 0.2) cm{sup -2} possibly co-existing with a much hotter and statistically less significant phase with log T = 6.9{sup +0.1}{sub -0.8} K and log N{sub H} = 20.1{sup +0.3}{sub -1.7} cm{sup -2} (1{sigma} errors). These two separate physical phases are identified through, and mainly constrained by, C V K{alpha} (warm phase) and O VIII K{alpha} (hot phase) absorption, with single line significances of 1.5{sigma} each. For the second LSS, at z {approx_equal} 0.128, only one hot component is hinted in the data, through O VIII K{alpha} (1.6{sigma}) and Ne IX K{alpha} (1.2{sigma}). For this system, we estimate log T = 6.6{sup +0.1}{sub -0.2} K and log N{sub H} = 19.8{sup +0.4}{sub -0.8} cm{sup -2}. Our column density and temperature constraints on the warm-hot gaseous content of these two LSSs, combined with the measurements obtained for the hot gas permeating the SW, allow us to estimate the cumulative number density per unit redshifts of O VII WHIM absorbers at three different EW thresholds of 0.4 mA, 7 mA, and 25.8 mA. This is consistent with expectations only at the very low end of EW thresholds, but exceeds predictions at 7 mA and 25.8 mA (by more than 2{sigma}). We also estimate the cosmological mass density of the WHIM based on the four absorbers we tentatively detect along this line of sight, obtaining {Omega}{sup WHIM}{sub b} = (0.021{sup +0.031}{sub -0.018})(Z/Z{sub sun}){sup -1}, consistent with the cosmological mass density of the intergalactic 'missing baryons' only if we assume high metallicities (Z {approx} Z{sub sun}).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Linearly supporting feature extraction for automated estimation of stellar atmospheric parameters

We describe a scheme to extract linearly supporting (LSU) features from stellar spectra to automatically estimate the atmospheric parameters T{sub eff}, log g, and [Fe/H]. “Linearly supporting” means that the atmospheric parameters can be accurately estimated from the extracted features through a linear model. The successive steps of the process are as follow: first, decompose the spectrum using a wavelet packet (WP) and represent it by the derived decomposition coefficients; second, detect representative spectral features from the decomposition coefficients using the proposed method Least Absolute Shrinkage and Selection Operator (LARS){sub bs}; third, estimate the atmospheric parameters T{sub eff}, log g, and [Fe/H] from the detected features using a linear regression method. One prominent characteristic of this scheme is its ability to evaluate quantitatively the contribution of each detected feature to the atmospheric parameter estimate and also to trace back the physical significance of that feature. This work also shows that the usefulness of a component depends on both the wavelength and frequency. The proposed scheme has been evaluated on both real spectra from the Sloan Digital Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF models. On real spectra, we extracted 23 features to estimate T{sub eff}, 62 features for log g, and 68 features for [Fe/H]. Test consistencies between our estimates and those provided by the Spectroscopic Parameter Pipeline of SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log T{sub eff} (83 K for T{sub eff}), 0.2345 dex for log g, and 0.1564 dex for [Fe/H]. For the synthetic spectra, the MAE test accuracies are 0.0022 dex for log T{sub eff} (32 K for T{sub eff}), 0.0337 dex for log g, and 0.0268 dex for [Fe/H].

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Compact galaxies and the size–mass galaxy distribution from a colour-selected sample at 0.04 < z < 0.15 supplemented by ugrizYJHK photometric redshifts

ABSTRACT The size–mass galaxy distribution is a key diagnostic for galaxy evolution. Massive compact galaxies are potential surviving relics of a high-redshift phase of star formation. Some of these could be nearly unresolved in Sloan Digital Sky Survey (SDSS) imaging and thus not included in galaxy samples. To overcome this, a sample was selected from the combination of SDSS and UKIRT Infrared Deep Sky Survey (UKIDSS) photometry to r < 17.8. This was done using colour–colour selection, and then by obtaining accurate photometric redshifts (photo-z) using scaled flux matching (SFM). Compared to spectroscopic redshifts (spec-z), SFM obtained a 1σ scatter of 0.0125 with only 0.3 per cent outliers (|Δln (1 + z)| > 0.06). A sample of 163 186 galaxies was obtained with 0.04 < z < 0.15 over $2300\, {\rm deg}^2$ using a combination of spec-z and photo-z. Following Barro et al. log Σ1.5 = log M* − 1.5log r50, maj was used to define compactness. The spectroscopic completeness was 76 per cent for compact galaxies (log Σ1.5 > 10.5) compared to 92 per cent for normal-sized galaxies. This difference is primarily attributed to SDSS ‘fibre collisions’ and not the completeness of the main galaxy sample selection. Using environmental overdensities, this confirms that compact quiescent galaxies are significantly more likely to be found in high-density environments compared to normal-sized galaxies. By comparison with a high-redshift sample from 3D-HST, log Σ1.5 distribution functions show significant evolution, with this being a compelling way to compare with simulations such as EAGLE. The number density of compact quiescent galaxies drops by a factor of about 30 from z ∼ 2 to log (n/Mpc−3) = − 5.3 ± 0.4 in the SDSS–UKIDSS sample. The uncertainty is dominated by the steep cut off in log Σ1.5, which is demonstrated conclusively using this complete sample.

Baldry, Ivan K.↗