We applied the maximum likelihood (ML) method, as an image reconstruction algorithm, to the BAT (Burst Alert Telescope) X-Ray Survey (BXS). This method was specifically designed to preserve the full statistical information in the data and to avoid mosaicking of many exposures with different pointing directions, thus reducing systematic errors when co-adding images. We reconstructed, in the 14-170keV energy band, the image of a 90x90deg^2^ sky region, centered on (RA, DE)=(105{deg}, -25{deg}), which BAT surveyed with an exposure time of ~1Ms (in 2005 November). The best sensitivity in our image is ~0.85mCrab or 2.0x10^-11^ergs/cm^2^. We detect 49 hard X-ray sources above the 4.5{sigma} level; of these, only 12 were previously known as hard X-ray sources (>15keV). Swift XRT observations allowed us to firmly identify the counterparts for 15 objects, while 2 objects have Einstein IPC counterparts (Harris et al., 1990, in Imaging X-Ray Astronomy. A Decade of Achievements, ed. M. Elvis (Cambridge: Cambridge Univ. Press), 309); in addition to those, we found a likely counterpart for 13 objects by correlating our sample with the ROSAT All-Sky Survey Bright Source Catalog (Voges et al., 1999, Cat. <IX/10>). Seven objects remain unidentified.
In this concluding part of the series of three papers dedicated to the Swift BAT hard X-ray survey (BXS), we focus on the X-ray spectral analysis and statistical properties of the source sample. Using a dedicated method to extract time-averaged spectra of BAT sources, we show that Galactic sources have, generally, softer spectra than extragalactic objects and that Seyfert 2 galaxies are harder than Seyfert 1's.
This table contains the BAX X-Ray Galaxy Clusters and Groups Catalog. BAX (`Base de Donnees Amas de Galaxies X': see <a href="http://bax.ast.obs-mip.fr/">http://bax.ast.obs-mip.fr/</a> for more details) is a multi-wavelength database dedicated to X-ray clusters and groups of galaxies which allows detailed information retrieval. BAX is designed to support astronomical research by providing access to published measurements of the main physical quantities and to the related bibliographic references: basic data stored in the database are cluster/group identifiers, equatorial coordinates, redshift, flux, X-ray luminosity (in the ROSAT band) and temperature, and (in the online version at <a href="http://bax.ast.obs-mip.fr/">http://bax.ast.obs-mip.fr/</a>) links to additional linked parameters (in X-rays, such as spatial profile parameters, as well as SZ parameters of the hot gas, lensing measurements, and data at other wavelengths, such as the optical and radio bands). The clusters and groups in the online BAX database can be queried by the basic parameters as well as the linked parameters or combinations of these. The authors expect BAX to become an important tool for the astronomical community. BAX will optimize various aspects of the scientific analysis of X-ray clusters and groups of galaxies, from proposal planning to data collection, interpretation and publication, from both ground based facilities like MEGACAM (CFHT), VIRMOS (VLT) and from space missions like XMM-Newton, Chandra and Planck. This table was created by the HEASARC in October 2004 based on CDS table B/bax/bax.dat. This is a service provided by NASA HEASARC .
Age is a fundamental parameter of stars, yet in many cases, ages of individual stars are presented without robust estimates of the uncertainty. We have developed a Bayesian framework, BAFFLES, to produce the age posterior for a star from its calcium emission strength (log(R_HK_^'^)) or lithium abundance (Li EW) and B-V color. We empirically determine the likelihood functions for calcium and lithium as functions of age from literature measurements of stars in benchmark clusters with well-determined ages. We use a uniform prior on age, which reflects a uniform star formation rate. The age posteriors we derive for several test cases are consistent with literature ages found from other methods. BAFFLES represents a robust method to determine the age posterior probability distribution for any field star with 0.45<=B-V0.9 and a measurement of R_HK_^'^ and/or 0.35<=B-V<=1.9 and measured Li EW. We compile colors, R_HK_^'^, and Li EW from over 2630 nearby field stars from the literature, and present the derived BAFFLES age posterior for each star.
We introduce a Bayesian method for fitting faint, resolved stellar spectra in order to obtain simultaneous estimates of redshift and stellar-atmospheric parameters. We apply the method to thousands of spectra - covering 5160-5280{AA} at resolution R~20000 - that we have acquired with the MMT/Hectochelle fibre spectrograph for red giant and horizontal branch candidates along the line of sight to the Milky Way's dwarf spheroidal satellite in Draco. The observed stars subtend an area of ~4deg^2^, extending ~3 times beyond Draco's nominal 'tidal' radius. For each spectrum, we tabulate the first four moments - central value, variance, skewness and kurtosis - of posterior probability distribution functions representing estimates of the following physical parameters: line-of-sight velocity (v_los_), effective temperature (T_eff_), surface gravity (logg) and metallicity ([Fe/H]). After rejecting low-quality measurements, we retain a new sample consisting of 2813 independent observations of 1565 unique stars, including 1879 observations for 631 stars with (as many as 13) repeat observations. Parameter estimates have median random errors of v_los_=0.88km/s, T_eff_=162K, {sigma}logg=0.37dex and {sigma}[Fe/H]=0.20dex. Our estimates of physical parameters distinguish ~470 likely Draco members from interlopers in the Galactic foreground.
In "A Bayesian Approach to Locating the Red Giant Branch Tip Magnitude (Part I)," a new technique was introduced for obtaining distances using the tip of the red giant branch (TRGB) standard candle. Here we describe a useful complement to the technique with the potential to further reduce the uncertainty in our distance measurements by incorporating a matched-filter weighting scheme into the model likelihood calculations. In this scheme, stars are weighted according to their probability of being true object members. We then re-test our modified algorithm using random-realization artificial data to verify the validity of the generated posterior probability distributions (PPDs) and proceed to apply the algorithm to the satellite system of M31, culminating in a three-dimensional view of the system. Further to the distributions thus obtained, we apply a satellite-specific prior on the satellite distances to weight the resulting distance posterior distributions, based on the halo density profile. Thus in a single publication, using a single method, a comprehensive coverage of the distances to the companion galaxies of M31 is presented, encompassing the dwarf spheroidals Andromedas I-III, V, IX-XXVII, and XXX along with NGC 147, NGC 185, M33, and M31 itself. Of these, the distances to Andromedas XXIV-XXVII and Andromeda XXX have never before been derived using the TRGB. Object distances are determined from high-resolution tip magnitude posterior distributions generated using the Markov Chain Monte Carlo technique and associated sampling of these distributions to take into account uncertainties in foreground extinction and the absolute magnitude of the TRGB as well as photometric errors. The distance PPDs obtained for each object both with and without the aforementioned prior are made available to the reader in tabular form. The large object coverage takes advantage of the unprecedented size and photometric depth of the Pan-Andromeda Archaeological Survey.
We propose a probabilistic galaxy group detection algorithm based on marked point processes with interactions. The pattern of galaxy groups in a catalogue is seen as a random set of interacting objects. The positions and the interactions of these objects are governed by a probability density. The parameters of the probability density are chosen using a priori knowledge. The estimator of the unknown cluster pattern is given by the configuration of objects maximising the proposed probability density. Adopting the Bayesian framework, the proposed probability density is maximised using a simulated annealing (SA) algorithm. At fixed temperature, the SA algorithm is a Monte Carlo sampler of the probability density. Hence, the method provides "for free" additional information such as the probabilities that a point or two points in the observation domain belong to the cluster pattern, respectively. These supplementary tools allow the construction of tests and techniques to validate and to refine the detection result. To test the feasibility of the proposed methodology, we applied it to the well-studied 2MASS Redshift Survey (2MRS) data set. Compared to previously published Friends-of-Friends (FoF) group finders, the proposed Bayesian group finder gives overall similar results. However, for specific applications, like the reconstruction of the local Universe, the details of the grouping algorithms are important.
We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of 'quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.
Spectral analysis is a powerful tool to investigate stellar properties and it has been widely used for decades now. However, the methods considered to perform this kind of analysis are mostly based on iteration among a few diagnostic lines to determine the stellar parameters. While these methods are often simple and fast, they can lead to errors and large uncertainties due to the required assumptions. Here, we present a method based on Bayesian statistics to find simultaneously the best combination of effective temperature, surface gravity, projected rotational velocity, and microturbulence velocity, using all the available spectral lines. Different tests are discussed to demonstrate the strength of our method, which we apply to 54 mid-resolution spectra of field and cluster B stars obtained at the Observatoire du Mont-Megantic. We compare our results with those found in the literature. Differences are seen which are well explained by the different methods used. We conclude that the B-star microturbulence velocities are often underestimated. We also confirm the trend that B stars in clusters are on average faster rotators than field B stars.
Bayesian time-resolved spectra of Fermi GBM pulses
Short Name:
J/ApJ/886/20
Date:
21 Oct 2021
Publisher:
CDS
Description:
We performed time-resolved spectroscopy on a sample of 38 single pulses from 37 gamma-ray bursts detected by the Fermi/Gamma-ray Burst Monitor during the first 9yr of its mission. For the first time a fully Bayesian approach is applied. A total of 577 spectra are obtained and their properties studied using two empirical photon models, namely the cutoff power law (CPL) and Band model. We present the obtained parameter distributions, spectral evolution properties, and parameter relations. We also provide the result files containing this information for usage in further studies. It is found that the CPL model is the preferred model, based on the deviance information criterion and the fact that it consistently provides constrained posterior density maps. In contrast to previous works, the high-energy power-law index of the Band model, {beta}, has in general a lower value for the single pulses in this work. In particular, we investigate the individual spectrum in each pulse, that has the largest value of the low-energy spectral indexes, {alpha}. For these 38 spectra, we find that 60% of the {alpha} values are larger than -2/3, and thus incompatible with synchrotron emission. Finally, we find that the parameter relations show a variety of behaviors. Most noteworthy is the fact that the relation between {alpha} and the energy flux is similar for most of the pulses, independent of any evolution of the other parameters.
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