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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Modeling of the TREAT M8 Calibration Series Measurements using MAMMOTH

This presentation provides an overview of the modeling efforts performed in to validate the MAMMOTH multi-physics reactor analysis application using historical TREAT data. These data come from the M8 series of calibration measurements, which was the last series performed before TREAT was shut down in 1994. The data applied in this work include an experiment flux profile and low level steady state power coupling factors for both flux wires and fuel pins. MAMMOTH was able to obtain reasonable results for all cases with the exception of the H91-8-1 flux wire, the only flux wire containing highly-enriched uranium. The feasibility of performing similar simulations of the calibration series fuel pins was demonstrated with the flux wire calculations, and will be performed in future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Choirs H I galaxy groups: The metallicity of dwarf galaxies

We present a recalibration of the luminosity-metallicity relation for gas-rich, star-forming dwarfs to magnitudes as faint as M{sub R} ∼ –13. We use the Dopita et al. metallicity calibrations to calibrate the relation for all the data in this analysis. In metallicity-luminosity space, we find two subpopulations within a sample of high-confidence Sloan Digital Sky Survey (SDSS) DR8 star-forming galaxies: 52% are metal-rich giants and 48% are metal-medium galaxies. Metal-rich dwarfs classified as tidal dwarf galaxy (TDG) candidates in the literature are typically of metallicity 12 + log(O/H) = 8.70 ± 0.05, while SDSS dwarfs fainter than M{sub R} = –16 have a mean metallicity of 12 + log(O/H) = 8.28 ± 0.10, regardless of their luminosity, indicating that there is an approximate floor to the metallicity of low-luminosity galaxies. Our hydrodynamical simulations predict that TDGs should have metallicities elevated above the normal luminosity-metallicity relation. Metallicity can therefore be a useful diagnostic for identifying TDG candidate populations in the absence of tidal tails. At magnitudes brighter than M{sub R} ∼ –16, our sample of 53 star-forming galaxies in 9 H I gas-rich groups is consistent with the normal relation defined by the SDSS sample. At fainter magnitudes, there is an increase in dispersion of the metallicity of our sample, suggestive of a wide range of H I content and environment. In our sample, we identify three (16% of dwarfs) strong TDG candidates (12 + log(O/H) > 8.6) and four (21%) very metal-poor dwarfs (12 + log(O/H) < 8.0), which are likely gas-rich dwarfs with recently ignited star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Mads.jl

Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.

Vesselinov, Velimir↗
DOE OSTI2016

Mads.jl

Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.

Vesselinov, Velimir↗
NASA NTRS1987

Static calibration of the RSRA active-isolator rotor balance system

The Rotor Systems Research Aircraft (RSRA) active-isolator system is designed to reduce rotor vibrations transmitted to the airframe and to simultaneously measure all six forces and moments generated by the rotor. These loads are measured by using a combination of load cells, strain gages, and hydropneumatic active isolators with built-in pressure gages. The first static calibration of the complete active-isolator rotor balance system was performed in l983 to verify its load-measurement capabilities. Analysis of the data included the use of multiple linear regressions to determine calibration matrices for different data sets and a hysteresis-removal algorithm to estimate in-flight measurement errors. Results showed that the active-isolator system can fulfill most performance predictions. The results also suggested several possible improvements to the system.

Acree, C. W., Jr.↗
DOE OSTI2018

Nonnegative tensor factorization for contaminant source identification

Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. In this work, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the original groundwater types (including contaminant sources) present in geochemical mixtures observed in an aquifer. Frequently, groundwater types with different geochemical signatures are related to different background and/or contamination sources. The characterization of groundwater mixing processes is a challenging but very important task critical for any environmental management project aiming to characterize the fate and transport of contaminants in the subsurface and perform contaminant remediation. This task typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. Additionally, the application of inverse methods may introduce biases in the analyses through the assumptions made in the model development process. Here, we substitute the model inversion with unsupervised ML analysis. The ML analysis does not make any assumptions about underlying physical and geochemical processes occurring in the aquifer. Our ML methodology, called NTFk, is capable of identifying (1) the unknown number of groundwater types (contaminant sources) present in the aquifer, (2) the original geochemical concentrations (signatures) of these groundwater types and (3) spatial and temporal dynamics in the mixing of these groundwater types. These results are obtained only from the measured geochemical data without any additional site information. In general, the NTFk methodology allows for interpretation of large high-dimensional datasets representing diverse spatial and temporal components such as state variables and velocities. NTFk has been tested on synthetic and real-world site three-dimensional datasets. Finally, the NTFk algorithm is designed to work with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

58 GEOSCIENCES↗
DOE OSTI2017

Optical variability of AGNs in the PTF/iPTF survey

We characterize the optical variability of quasars in the Palomar Transient Factory and intermediate Palomar Transient Factory (PTF/iPTF) surveys. We re-calibrate the r-band light curves for ∼28,000 luminous, broad-line active galactic nuclei from the SDSS, producing a total of ∼2.4 million photometric data points. We utilize both the structure function (SF) and power spectrum density (PSD) formalisms to search for links between the optical variability and the physical parameters of the accreting supermassive black holes that power the quasars. The excess variance (SF{sup 2}) of the quasar sample tends to zero at very short time separations, validating our re-calibration of the time-series data. We find that the the amplitude of variability at a given time-interval, or equivalently the timescale of variability to reach a certain amplitude, is most strongly correlated with luminosity with weak or no dependence on black hole mass and redshift. For a variability level of SF(τ) = 0.07 mag, the timescale has a dependency of τ∝L{sup 0.4}. This is broadly consistent with the expectation from a simple Keplerian accretion disk model, which provides τ∝L{sup 0.5}. The PSD analysis also reveals that many quasar light curves are steeper than a damped random walk. We find a correlation between the steepness of the PSD slopes, specifically the fraction of slopes steeper than 2.5, and black hole mass, although we cannot exclude the possibility that luminosity or Eddington ratio are the drivers of this effect. This effect is also seen in the SF analysis of the (i)PTF data, and in a PSD analysis of quasars in the SDSS Stripe 82.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Airdata Measurement and Calibration

This Section provides a brief introduction to airdata measurement and calibration. Readers will learn about typical test objectives, quantities to measure, and flight maneuvers and operations for calibration. The Section informs readers about tower-flyby, trailing cone, pacer, radar-tracking, and dynamic airdata calibration maneuvers. Readers will also begin to understand how some data analysis considerations and special airdata cases, including high-angle-of-attack flight, high-speed flight, and nonobtrusive sensors are handled. This section is not intended to be all inclusive; readers should review AGARDograph 300, Volume 1, "Calibration of Airdata Systems and Flow Direction Sensors" for more detailed information. [11-1] References 11-2, 11-3, and 11-4 also supply pertinent information to better understand airdata measurement and calibration and related terminology. Airdata are vital to successfully complete an aircraft's mission and are derived from the air surrounding the aircraft. These airdata encompass indicated and true airspeed, pressure altitude, ambient air temperature, angles of attack and sideslip, Mach number, and rate of climb. Typically, pitot and static pressures are sensed and converted (by mechanical means in the instruments themselves) into indications on the altimeter, vertical speed indicator, airspeed indicator, and Machmeter. Similarly, measured local flow angles establish angles of attack and sideslip, and the outside air temperature is measured and indicated in the cockpit. (Instruments that can perform the conversion, such as airspeed indicators, altimeters, and Machmeters, do not correct for errors in the input values.) These measured parameters are commonly input to the airdata computer which, using appropriate algorithms and correction factors (or calibrations, as discussed later), can provide other parameters, such as true airspeed, required by the aircraft's avionics or flight control system. The presence of the aircraft in the airstream causes input errors to the measuring instruments - the aircraft disturbs the air that it flies through, thereby also disturbing the airdata measurements. Figure 11-1 shows the airflow around an airplane wing. The air above the wing has lower pressure than the ambient air, while the pressure below the wing is higher than the ambient air. Compressibility and shock waves also disturb the air and affect the measurements. Compressibility effects become important above approximately Mach number 0.3. As a result the static pressure around an airplane varies considerably with location. Local flow angles also differ from the free-stream flow direction. In straight-and-level flight the airflow rises to the wing leading edge and falls below the trailing edge, causing errors in flow direction measurements. To some extent these errors can be studied in wind tunnels, but wind-tunnel measurements cannot replace in-flight measurements.

Haering, Edward A., Jr.↗
DOE OSTI2014

Control rod calibration and reactivity effects at the IPEN/MB-01 reactor

Researches that aim to improve the performance of neutron transport codes and quality of nuclear cross section databases are very important to increase the accuracy of simulations and the quality of the analysis and prediction of phenomena in the nuclear field. In this context, relevant experimental data such as reactivity worth measurements are needed. Control rods may be made of several neutron absorbing materials that are used to adjust the reactivity of the core. For the reactor operation, these experimental data are also extremely important: with them it is possible to estimate the reactivity worth by the movement of the control rod, understand the reactor response at each rod position and to operate the reactor safely. This work presents a temperature correction approach for the control rod calibration problem. It is shown the control rod calibration data of the IPEN/MB-01 reactor, the integral and differential reactivity curves and a theoretical analysis, performed by the MCNP-5 reactor physics code, developed and maintained by Los Alamos National Laboratory, using the ENDF/B-VII.0 nuclear data library.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances

Abstract Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration “surrogates,” which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from “global” chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using “global” surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using “expert-selected” surrogates ( n = 3) instead of “global” surrogates ( n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases. Graphical Abstract

Pu, Shirley (ORCID:0000000201223797)↗
DOE OSTI2011

PRECISION SPECTROPHOTOMETRY AT THE LEVEL OF 0.1%

Accurate relative spectrophotometry is critical for many science applications. Small wavelength-scale residuals in the flux calibration can significantly impact the measurements of weak emission and absorption features in the spectra. Using Sloan Digital Sky Survey data, we demonstrate that the average spectra of carefully selected red-sequence galaxies can be used as a spectroscopic standard to improve the relative spectrophotometry precision to 0.1% on small wavelength scales (from a few to hundreds of Angstroms). We achieve this precision by comparing stacked spectra across tiny redshift intervals. The redshift intervals must be small enough that any systematic stellar population evolution is minimized and is less than the spectrophotometric uncertainty. This purely empirical technique does not require any theoretical knowledge of true galaxy spectra. It can be applied to all large spectroscopic galaxy redshift surveys that sample a large number of galaxies in a uniform population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

APASS Landolt-Sloan BVgri photometry of Rave stars. I. Data, effective temperatures, and reddenings

We provide AAVSO Photometric All-Sky Survey (APASS) photometry in the Landolt BV and Sloan g'r'i' bands for all 425,743 stars included in the fourth RAVE Data Release. The internal accuracy of the APASS photometry of RAVE stars, expressed as the error of the mean of data obtained and separately calibrated over a median of four distinct observing epochs and distributed between 2009 and 2013, is 0.013, 0.012, 0.012, 0.014, and 0.021 mag for the B, V, g', r', and i' bands, respectively. The equally high external accuracy of APASS photometry has been verified on secondary Landolt and Sloan photometric standard stars not involved in the APASS calibration process and on a large body of literature data on field and cluster stars, confirming the absence of offsets and trends. Compared with the Carlsberg Meridian Catalog (CMC-15), APASS astrometry of RAVE stars is accurate to a median value of 0.098 arcsec. Brightness distribution functions for the RAVE stars have been derived in all bands. APASS photometry of RAVE stars, augmented by 2MASS JHK infrared data, has been χ{sup 2} fitted to a densely populated synthetic photometric library designed to widely explore temperature, surface gravity, metallicity, and reddening. Resulting T {sub eff} and E {sub B–V}, computed over a range of options, are provided and discussed, and will be kept updated in response to future APASS and RAVE data releases. In the process, we find that the reddening caused by a homogeneous slab of dust, extending for 140 pc on either side of the Galactic plane and responsible for E{sub B−V}{sup poles} = 0.036 ± 0.002 at the Galactic poles, is a suitable approximation of the actual reddening encountered at Galactic latitudes |b| ≥ 25°.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

MILLISECOND IMAGING OF RADIO TRANSIENTS WITH THE POCKET CORRELATOR

We demonstrate a signal-processing concept for imaging the sky at millisecond rates with radio interferometers. The 'Pocket Correlator' (PoCo) correlates the signals from multiple elements of a radio interferometer fast enough to image brief, dispersed pulses. By the nature of interferometry, a millisecond correlator functions like a large, single-dish telescope, but with improved survey speed, spatial localization, calibration, and interference rejection. To test the concept, we installed PoCo at the Allen Telescope Array (ATA) to search for dispersed pulses from the Crab pulsar, B0329+54, and M31 using total-power, visibility-based, and image-plane techniques. In 1.7 hr of observing, PoCo detected 191 giant pulses from the Crab pulsar brighter than a typical 5{sigma} sensitivity limit of 60 Jy over pulse widths of 3 ms. Roughly 40% of pulses from pulsar B0329+54 were detected by using novel visibility-based techniques. Observations of M31 constrain the rate of pulses brighter than 190 Jy in a three-degree region surrounding the galaxy to <4.3 hr{sup -1}. We calculate the computational demand of various visibility-based pulse search algorithms and demonstrate how compute clusters can help meet this demand. Larger implementations of the fast imaging concept will conduct blind searches for millisecond pulses in our Galaxy and beyond, providing a valuable probe of the interstellar/intergalactic media, discovering new kinds of radio transients, and localizing them to constrain models of their origin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

FOUR FUNDAMENTAL FOREGROUND POWER SPECTRUM SHAPES FOR 21 cm COSMOLOGY OBSERVATIONS

Contamination from instrumental effects interacting with bright astrophysical sources is the primary impediment to measuring Epoch of Reionization (EoR) and Baryon Acoustic Oscillations (BAO) 21 cm power spectra-an effect called mode mixing. In this paper, we identify four fundamental power spectrum shapes produced by mode mixing that will affect all upcoming observations. We are able, for the first time, to explain the wedge-like structure seen in advanced simulations and to forecast the shape of an 'EoR window' that is mostly free of contamination. Understanding the origins of these contaminations also enables us to identify calibration and foreground subtraction errors below the imaging limit, providing a powerful new tool for precision observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

THE BLANCO COSMOLOGY SURVEY: DATA ACQUISITION, PROCESSING, CALIBRATION, QUALITY DIAGNOSTICS, AND DATA RELEASE

The Blanco Cosmology Survey (BCS) is a 60 night imaging survey of {approx}80 deg{sup 2} of the southern sky located in two fields: ({alpha}, {delta}) = (5 hr, -55 Degree-Sign ) and (23 hr, -55 Degree-Sign ). The survey was carried out between 2005 and 2008 in griz bands with the Mosaic2 imager on the Blanco 4 m telescope. The primary aim of the BCS survey is to provide the data required to optically confirm and measure photometric redshifts for Sunyaev-Zel'dovich effect selected galaxy clusters from the South Pole Telescope and the Atacama Cosmology Telescope. We process and calibrate the BCS data, carrying out point-spread function-corrected model-fitting photometry for all detected objects. The median 10{sigma} galaxy (point-source) depths over the survey in griz are approximately 23.3 (23.9), 23.4 (24.0), 23.0 (23.6), and 21.3 (22.1), respectively. The astrometric accuracy relative to the USNO-B survey is {approx}45 mas. We calibrate our absolute photometry using the stellar locus in grizJ bands, and thus our absolute photometric scale derives from the Two Micron All Sky Survey, which has {approx}2% accuracy. The scatter of stars about the stellar locus indicates a systematic floor in the relative stellar photometric scatter in griz that is {approx}1.9%, {approx}2.2%, {approx}2.7%, and {approx}2.7%, respectively. A simple cut in the AstrOmatic star-galaxy classifier spread{sub m}odel produces a star sample with good spatial uniformity. We use the resulting photometric catalogs to calibrate photometric redshifts for the survey and demonstrate scatter {delta}z/(1 + z) = 0.054 with an outlier fraction {eta} < 5% to z {approx} 1. We highlight some selected science results to date and provide a full description of the released data products.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

STELLAR COLOR REGRESSION: A SPECTROSCOPY-BASED METHOD FOR COLOR CALIBRATION TO A FEW MILLIMAGNITUDE ACCURACY AND THE RECALIBRATION OF STRIPE 82

In this paper we propose a spectroscopy-based stellar color regression (SCR) method to perform accurate color calibration for modern imaging surveys, taking advantage of millions of stellar spectra now available. The method is straightforward, insensitive to systematic errors in the spectroscopically determined stellar atmospheric parameters, applicable to regions that are effectively covered by spectroscopic surveys, and capable of delivering an accuracy of a few millimagnitudes for color calibration. As an illustration, we have applied the method to the Sloan Digital Sky Survey (SDSS) Stripe 82 data. With a total number of 23,759 spectroscopically targeted stars, we have mapped out the small but strongly correlated color zero-point errors present in the photometric catalog of Stripe 82, and we improve the color calibration by a factor of two to three. Our study also reveals some small but significant magnitude dependence errors in the z band for some charge-coupled devices (CCDs). Such errors are likely to be present in all the SDSS photometric data. Our results are compared with those from a completely independent test based on the intrinsic colors of red galaxies presented by Ivezić et al. The comparison, as well as other tests, shows that the SCR method has achieved a color calibration internally consistent at a level of about 5 mmag in u – g, 3 mmag in g – r, and 2 mmag in r – i and i – z. Given the power of the SCR method, we discuss briefly the potential benefits by applying the method to existing, ongoing, and upcoming imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Prototype acoustic positioning system for the Pacific Ocean Neutrino Experiment

We present the design and initial performance characterization of the prototype acoustic positioning system intended for the Pacific Ocean Neutrino Experiment. It comprises novel piezo-acoustic receivers with dedicated filtering- and amplification electronics installed in P-ONE instruments and is complemented by a commercial system comprised of cabled and autonomous acoustic pingers for sub-sea installation manufactured by Sonardyne Ltd. We performed an in-depth characterization of the acoustic receiver electronics and their acoustic sensitivity when integrated into P-ONE pressure housings. These show absolute sensitivities of up to -125 dB re V2/μPa2 in a frequency range of 10–40 kHz. We furthermore conducted a positioning measurement campaign in the ocean by deploying three autonomous acoustic pingers on the seafloor, as well as a cabled acoustic interrogator and a P-ONE prototype module deployed from a ship. Using a simple peak-finding detection algorithm, we observe high accuracy in the tracking of relative ranging times at approximately 230–280 μs at distances of up to 1600 m, which is sufficient for positioning detectors in a cubic-kilometer detector and which can be further improved with more involved detection algorithms. The tracking accuracy is further confirmed by independent ranging of the Sonardyne system and closely follows the ship's drift in the wind measured by GPS. The absolute positioning shows the same tracking accuracy with its absolute precision only limited by the large uncertainties of the deployed pinger positions on the seafloor.

Data analysis↗
DOE OSTI2014

A BAYESIAN METHOD FOR THE INTERCALIBRATION OF SPECTRA IN REVERBERATION MAPPING

Flux calibration of spectra in reverberation mapping (RM) is most often performed by assuming the flux constancy of some specified narrow emission lines, which stem from an extended region that is sometimes partially spatially resolved, in contrast to the point-like broad-line region and the central continuum source. The inhomogeneous aperture geometries used among different observation sets in a joint monitoring campaign introduce systematic deviations to the fluxes of broad lines and central continuum, and intercalibration over these data sets is required. As an improvement to the previous empirical correction performed by comparing the (nearly) contemporaneous observation points, we describe a feasible Bayesian method that obviates the need for (nearly) contemporaneous observations, naturally incorporates physical models of flux variations, and fully takes into account the measurement errors. In particular, it fits all the data sets simultaneously regardless of samplings and makes use of all of the information in the data sets. A Markov Chain Monte Carlo implementation is employed to recover the parameters and uncertainties for intercalibration. Application to the RM data sets of NGC 5548 with joint monitoring shows the high fidelity of our method.

79 ASTRONOMY AND ASTROPHYSICS↗