SEARCH · Engineering Papers

Results for “estimating”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,045 records · Page 58

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Evaluation of a New Approach for Entrainment and Detrainment Rate Estimation

Entrainment and detrainment rates (ε and δ) constitute the most critical free parameters in mass flux schemes commonly employed for cumulus parameterizations. Recently, Zhu et al. (2021) introduced a new approach that utilizes aircraft observations to simultaneously estimate ε and δ for cumulus clouds, overcoming the limitation of other observation-based approaches that solely yield ε without offering insights into δ. This study aims to comprehensively evaluate the reliability of this new approach. First, evaluation using an Explicit Mixing Parcel Model demonstrates the capability of the new approach to back-calculate predetermined ε and δ based on the physical properties before and after the entrainment mixing. Second, evaluation using large-eddy simulations illustrates that the new approach yields consistent ε and δ profiles compared to the traditional approach. Sensitivity tests indicate a weak sensitivity of the estimated δ with the new approach to the entrained air source. A decrease in the proportion of cloudy air in the assumed detrained air leads to a reduction in the estimated δ, while ε remains unaffected. Finally, the most appropriate assumptions for entrained and detrained air are discussed. Estimating ε for cumulus parameterizations involves acquiring ambient air more than 500 m away from the cloud edge as entrained air. Due to implicit mean field approximations in the traditional approach, determining the optimal assumption for detrained air properties proves challenging. Finally, this study confirms the reliability of the new approach in estimating ε and δ, providing confidence in its application to extensive observational data and advancement in parameterization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Distributed Acoustic Sensing to Estimate the Permeability

Optical fiber in a borehole can be interrogated with distributed acoustic sensors (DAS) to capture fracture displacements with the potential to map surrounding fracture networks. We designed a laboratory experiment to test the capability of DAS to determine borehole flow characteristics, and we show that for the first time DAS can be used to remotely estimate permeability. Optical fiber was wrapped around a bead filled pipe and the pressure drop and flow velocity were measured to directly calculate permeability. A machine learning model using statistical features from continuous DAS estimated the bulk permeability. Fluid interactions with the permeable material demonstrate insufficient resolution using DAS amplitude-based measurements for estimating pressure drop to infer permeability. Variations in the spectral domain relate DAS measurements to the pressure drop and provide consistent permeability estimates. Resolution with DAS is sufficient to estimate permeability and provides a reliable method to monitor at depth in borehole conditions.

58 GEOSCIENCES↗

DOE OSTI2026

Heterogeneous estimations of non-pharmaceutical mitigation behavior during the COVID-19 pandemic

The COVID-19 pandemic highlighted the importance of human behavior in mitigating the spread of disease. Nonetheless, human behavior is often overlooked in models of disease spread, particularly by underutilizing real-world data. We address this by estimating probabilities that individuals engage in behaviors that influence SARS-CoV-2 transmission risk during the COVID-19 pandemic, between September 2020 and June 2022. These behaviors include wearing a mask, using public transportation, spending time with others, avoiding contact with others, and going to work. Our estimates account for the age and sex of individuals and are generated for every county in the United States. We utilized multiple open-source datasets and United States Census data to produce these estimates. Multiple datasets were used for validation, showing our estimates demonstrated comparable accuracy and robustness. Our estimates aid in understanding human behavior dynamics during the COVID-19 pandemic and could be used to inform monthly or longer-term behavior in simulations of COVID-19. Moreover, the methods presented can be applied to other behaviors and features for future simulations of infectious disease.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Estimated timescales for wet deposition of organic compounds as a function of Henry's law constants

Atmospheric organic compounds may deposit to Earth's surfaces via dry deposition, driven by concentration gradients, and wet deposition, driven by the scavenging of compounds by precipitation. Their removal by deposition has downstream impacts on concentrations of secondary organic aerosol by removing potential aerosol precursors that would otherwise oxidize to form particulate matter. The impact of deposition processes can consequently be considered as competition between rates of oxidation and deposition, but timescales for deposition are not well constrained. While timescales for dry deposition have been estimated and experimentally validated in the past, understanding of wet deposition of organics is still very limited. In this work, we estimate the wet deposition timescale for gas-phase organic compounds in the atmosphere as a function of Henry's law constants, H, using real-world precipitation frequency and size distributions at five globally-distributed sites. The wet deposition timescale decreases significantly with the increase of H until reaching a stable minimum for compounds with H > 10 5 M per atm. We estimate that the median wet deposition timescale for highly soluble gases is approximately 5 hours during a continuous rain event for all sites. However, median estimated timescales ranged from 80 to 200 hours, depending on location. Timescales are found to depend primarily on the frequency and duration of precipitation events rather than their intensity or size characteristics. Based on these data, we demonstrate that timescales for wet deposition of gases can be estimated at any given location using only basic precipitation information, without detailed or high-precision measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Template for estimating uncertainties of measured neutron-induced fission cross-sections

A template for estimating uncertainties (unc.) of measured neutron-induced fission, (n,f), cross-sections (cs) is presented. This preliminary template not only lists all expected unc. sources but also supplies ranges of unc., estimates for correlations between unc. of the same and different experiments which can be used if the information is nonexistent. If this template is applied systematically when estimating experimental covariances for an evaluation, it may help in pinpointing missing unc. for individual datasets, identifying unreasonably low unc., and estimating correlations between different experimental datasets. Thus, a detailed unc. estimate – usually, a time-intensive procedure – can be undertaken more consistently and efficiently. As an example, it is shown that unc. and correlations of 239 Pu(n,f) by Merla et al. [Proceedings of the Conference on Nuclear Data for Science and Technology 1991 Jülich (Springer-Verlag, Berlin, 1992) pp. 510–513], which are questionably low in the GMA database underlying the neutron cs standards evaluations, are distinctly larger at 14.7 MeV and more strongly correlated if this template is used for reestimating the associated covariances.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Estimating uncertainties in statistics computed from direct numerical simulation

Rigorous assessment of uncertainty is crucial to the utility of direct numerical simulation (DNS) results. Uncertainties in the computed statistics arise from two sources: finite statistical sampling and the discretization of the Navier–Stokes equations. Due to the presence of non-trivial sampling error, standard techniques for estimating discretization error (such as Richardson extrapolation) fail or are unreliable. This work provides a systematic and unified approach for estimating these errors. First, a sampling error estimator that accounts for correlation in the input data is developed. Then, this sampling error estimate is used as part of a Bayesian extension of Richardson extrapolation in order to characterize the discretization error. These methods are tested using the Lorenz equations and are shown to perform well. These techniques are then used to investigate the sampling and discretization errors in the DNS of a wall-bounded turbulent flow at Reτ ≈ 180. Both small (Lx/δ × Lz/δ = 4π × 2π) and large (Lx/δ × Lz/δ = 12π × 4π) domain sizes are investigated. For each case, a sequence of meshes was generated by first designing a “nominal” mesh using standard heuristics for wall-bounded simulations. These nominal meshes were then coarsened to generate a sequence of grid resolutions appropriate for the Bayesian Richardson extrapolation method. In addition, the small box case is computationally inexpensive enough to allow simulation on a finer mesh, enabling the results of the extrapolation to be validated in a weak sense. For both cases, it is found that while the sampling uncertainty is large enough to make the order of accuracy difficult to determine, the estimated discretization errors are quite small. This indicates that the commonly used heuristics provide adequate resolution for this class of problems. However, it is also found that, for some quantities, the discretization error is not small relative to sampling error, indicating that the conventional wisdom that sampling error dominates discretization error for this class of simulations needs to be reevaluated.

Oliver, Todd A.↗

DOE OSTI2015

Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI

In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Quantitative estimation of localization errors of 3d transition metal pseudopotentials in diffusion Monte Carlo

The necessarily approximate evaluation of non-local pseudopotentials in diffusion Monte Carlo (DMC) introduces localization errors. In this paper, we estimate these errors for two families of non-local pseudopotentials for the first-row transition metal atoms Sc–Zn using an extrapolation scheme and multideterminant wavefunctions. Sensitivities of the error in the DMC energies to the Jastrow factor are used to estimate the quality of two sets of pseudopotentials with respect to locality error reduction. The locality approximation and T-moves scheme are also compared for accuracy of total energies. After estimating the removal of the locality and T-moves errors, we present the range of fixed-node energies between a single determinant description and a full valence multideterminant complete active space expansion. The results for these pseudopotentials agree with previous findings that the locality approximation is less sensitive to changes in the Jastrow than T-moves yielding more accurate total energies, however not necessarily more accurate energy differences. For both the locality approximation and T-moves, we find decreasing Jastrow sensitivity moving left to right across the series Sc–Zn. The recently generated pseudopotentials of Krogel et al. reduce the magnitude of the locality error compared with the pseudopotentials of Burkatzki et al. by an average estimated 40% using the locality approximation. The estimated locality error is equivalent for both sets of pseudopotentials when T-moves is used. Finally, for the Sc–Zn atomic series with these pseudopotentials, and using up to three-body Jastrow factors, our results suggest that the fixed-node error is dominant over the locality error when a single determinant is used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

Here, this work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstruction algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS are explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm’s precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm RMS for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. Finally, the effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

SCOPE: Spectral cloud optical property estimation using real-time GOES-R longwave imagery

The output of ground-based, solar power generation systems is strongly dependent on cloud cover, which is the main contributor to solar power variability and uncertainty. Cloud optical properties are typically over-simplified in forecasting applications due to the lack of realtime, accurate estimates. In this work, we introduce a method, the Spectral Cloud Optical Property Estimation (SCOPE), for estimating cloud optical properties directly from high-resolution (5-min, 2 km) imagery from Geostationary Operational Environmental Satellite (GOES)-R, which is the newest generation of the GOES system. The SCOPE method couples a two-stream, spectrally resolved radiative model with the longwave GOES-R sensor output to simultaneously estimate the cloud optical depth, cloud top height, and cloud thickness during both day and night at 5-min intervals. The accuracy of SCOPE is evaluated using one year (2018) of downwelling longwave (DLW) radiation measurements from the Surface Radiation Budget Network, which consists of seven sites spread across climatically diverse regions of the contiguous United States. During daytime clear-sky periods, SCOPE predicts DLW within instrument uncertainty (10 W m -2 ) for four of the seven locations, with the remaining locations yielding errors of the order of 11.2, 17.7, and 20.2 W m -2 . For daytime cloudy-sky, daytime all-sky (clear or cloudy), and nighttime all-sky periods, SCOPE achieves root mean square error values of 23.0–34.5 W m -2 for all seven locations. These results, together with the low-latency of the method (1 s per sample), show that SCOPE provides a viable solution to real-time, accurate estimation of cloud optical properties for both day and night.

42 ENGINEERING↗

DOE OSTI2018

Estimation of emigration, return migration, and transit migration between all pairs of countries

We propose a method for estimating migration flows between all pairs of countries that allows for decomposition of migration into emigration, return, and transit components. Current state-of-the-art estimates of bilateral migration flows rely on the assumption that the number of global migrants is as small as possible. We relax this assumption, producing complete estimates of all between-country migration flows with genuine estimates of total global migration. We find that the total number of individuals migrating internationally has oscillated between 1.13 and 1.29% of the global population per 5-year period since 1990. Return migration and transit migration are big parts of total migration; roughly one of four migration events is a return to an individual’s country of birth. In the most recent time period, we estimate particularly large return migration flows from the United States to Central and South America and from the Persian Gulf to south Asia.

Science & Technology - Other Topics↗

DOE OSTI2026

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2013

Estimating Air Chemical Emissions from Research Activities Using Stack Measurement Data

Current methods of estimating air emissions from research and development (R&D) activities use a wide range of release fractions or emission factors with bases ranging from empirical to semi-empirical. Although considered conservative, the uncertainties and confidence levels of the existing methods have not been reported. Chemical emissions were estimated from sampling data taken from four research facilities over ten years. The approach was to use a Monte Carlo technique to create distributions of annual emission estimates for target compounds detected in source test samples. Distributions were created for each year and building sampled for compounds with sufficient detection frequency to qualify for the analysis. The results using the Monte Carlo technique without applying a filter to remove negative emission values showed almost all distributions spanning zero, and forty percent of the distributions having a negative mean. This indicates that emissions are so low as to be indistinguishable from building background. Application of a filter to allow only positive values in the distribution provided a more realistic value for emissions and increased the distribution mean by an average of sixteen percent. Release fractions were calculated by dividing the emission estimates by a building chemical inventory quantity. Two variations were used for this quantity: chemical usage, and chemical usage plus one-half standing inventory. Filters were applied so that only release fraction values from zero to one were included in the resulting distributions. Release fractions had a wide range among chemicals and among data sets for different buildings and/or years for a given chemical. Regressions of release fractions to molecular weight and vapor pressure showed weak correlations. Similarly, regressions of mean emissions to chemical usage, chemical inventory, molecular weight and vapor pressure also gave weak correlations. These results highlight the difficulties in estimating emissions from R&D facilities using chemical inventory data.

air chemical sampling, air emissions, research and↗

DOE OSTI2012

CAN DUST EMISSION BE USED TO ESTIMATE THE MASS OF THE INTERSTELLAR MEDIUM IN GALAXIES-A PILOT PROJECT WITH THE HERSCHEL REFERENCE SURVEY

The standard method for estimating the mass of the interstellar medium (ISM) in a galaxy is to use the 21 cm line to trace the atomic gas and the CO 1-0 line to trace the molecular gas. In this paper, we investigate the alternative technique of using the continuum dust emission to estimate the mass of gas in all phases of the ISM. Using Herschel observations of 10 galaxies from the Herschel Reference Survey and the Herschel Virgo Cluster Survey, we show that the emission detected by Herschel is mostly from dust that has a temperature and emissivity index similar to that of dust in the local ISM in our galaxy, with the temperature generally increasing toward the center of each galaxy. We calibrate the dust method using the CO and 21 cm observations to provide an independent estimate of the mass of hydrogen in each galaxy, solving the problem of the uncertain ''X-factor'' for the CO observations by minimizing the dispersion in the ratio of the masses estimated using the two methods. With the calibration for the dust method and the estimate of the X-factor produced in this way, the dispersion in the ratio of the two gas masses is 25%. The calibration we obtain for the dust method is similar to those obtained from Herschel observations of M31 and from Planck observations of the Milky Way. We discuss the practical problems in using this method.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

HABITABLE ZONES AROUND MAIN-SEQUENCE STARS: NEW ESTIMATES

Identifying terrestrial planets in the habitable zones (HZs) of other stars is one of the primary goals of ongoing radial velocity (RV) and transit exoplanet surveys and proposed future space missions. Most current estimates of the boundaries of the HZ are based on one-dimensional (1D), cloud-free, climate model calculations by Kasting et al. However, this model used band models that were based on older HITRAN and HITEMP line-by-line databases. The inner edge of the HZ in the Kasting et al. model was determined by loss of water, and the outer edge was determined by the maximum greenhouse provided by a CO{sub 2} atmosphere. A conservative estimate for the width of the HZ from this model in our solar system is 0.95-1.67 AU. Here an updated 1D radiative-convective, cloud-free climate model is used to obtain new estimates for HZ widths around F, G, K, and M stars. New H{sub 2}O and CO{sub 2} absorption coefficients, derived from the HITRAN 2008 and HITEMP 2010 line-by-line databases, are important improvements to the climate model. According to the new model, the water-loss (inner HZ) and maximum greenhouse (outer HZ) limits for our solar system are at 0.99 and 1.70 AU, respectively, suggesting that the present Earth lies near the inner edge. Additional calculations are performed for stars with effective temperatures between 2600 and 7200 K, and the results are presented in parametric form, making them easy to apply to actual stars. The new model indicates that, near the inner edge of the HZ, there is no clear distinction between runaway greenhouse and water-loss limits for stars with T{sub eff} {approx}< 5000 K, which has implications for ongoing planet searches around K and M stars. To assess the potential habitability of extrasolar terrestrial planets, we propose using stellar flux incident on a planet rather than equilibrium temperature. This removes the dependence on planetary (Bond) albedo, which varies depending on the host star's spectral type. We suggest that conservative estimates of the HZ (water-loss and maximum greenhouse limits) should be used for current RV surveys and Kepler mission to obtain a lower limit on {eta}{sub Circled-Plus }, so that future flagship missions like TPF-C and Darwin are not undersized. Our model does not include the radiative effects of clouds; thus, the actual HZ boundaries may extend further in both directions than the estimates just given.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

UTILIZATION OF THE WAVEFRONT SENSOR AND SHORT-EXPOSURE IMAGES FOR SIMULTANEOUS ESTIMATION OF QUASI-STATIC ABERRATION AND EXOPLANET INTENSITY

Heretofore, the literature on exoplanet detection with coronagraphic telescope systems has paid little attention to the information content of short exposures and methods of utilizing the measurements of adaptive optics wavefront sensors. This paper provides a framework for the incorporation of the wavefront sensor measurements in the context of observing modes in which the science camera takes millisecond exposures. In this formulation, the wavefront sensor measurements provide a means to jointly estimate the static speckle and the planetary signal. The ability to estimate planetary intensities in as little as a few seconds has the potential to greatly improve the efficiency of exoplanet search surveys. For simplicity, the mathematical development assumes a simple optical system with an idealized Lyot coronagraph. Unlike currently used methods, in which increasing the observation time beyond a certain threshold is useless, this method produces estimates whose error covariances decrease more quickly than inversely proportional to the observation time. This is due to the fact that the estimates of the quasi-static aberrations are informed by a new random (but approximately known) wavefront every millisecond. The method can be extended to include angular (due to diurnal field rotation) and spectral diversity. Numerical experiments are performed with wavefront data from the AEOS Adaptive Optics System sensing at 850 nm. These experiments assume a science camera wavelength {lambda} of 1.1 {mu}, that the measured wavefronts are exact, and a Gaussian approximation of shot-noise. The effects of detector read-out noise and other issues are left to future investigations. A number of static aberrations are introduced, including one with a spatial frequency exactly corresponding the planet location, which was at a distance of Almost-Equal-To 3{lambda}/D from the star. Using only 4 s of simulated observation time, a planetary intensity, of Almost-Equal-To 1 photon ms{sup -1}, and a stellar intensity of Almost-Equal-To 10{sup 5} photons ms{sup -1} (contrast ratio 10{sup 5}), the short-exposure estimation method recovers the amplitudes' static aberrations with 1% accuracy, and the planet brightness with 20% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

CALIBRATING C-IV-BASED BLACK HOLE MASS ESTIMATORS

We present the single-epoch black hole mass estimators based on the C IV {lambda}1549 broad emission line, using the updated sample of the reverberation-mapped active galactic nuclei and high-quality UV spectra. By performing multi-component spectral fitting analysis, we measure the C IV line widths (FWHM{sub C{sub IV}} and line dispersion, {sigma}{sub C{sub IV}}) and the continuum luminosity at 1350 A (L{sub 1350}) to calibrate the C-IV-based mass estimators. By comparing with the H{beta} reverberation-based masses, we provide new mass estimators with the best-fit relationships, i.e., M{sub BH}{proportional_to}L{sub 1350}{sup 0.50{+-}0.07}{sigma}{sub C{sub IV}{sup 2}} and M{sub BH}{proportional_to}L{sub 1350}{sup 0.52{+-}0.09} FWHM{sub C{sub IV}{sup 0.56{+-}0.48}}. The new C-IV-based mass estimators show significant mass-dependent systematic difference compared to the estimators commonly used in the literature. Using the published Sloan Digital Sky Survey QSO catalog, we show that the black hole mass of high-redshift QSOs decreases on average by {approx}0.25 dex if our recipe is adopted.

79 ASTRONOMY AND ASTROPHYSICS↗