2,310 research outputs found
Gamma-ray Bursts, Classified Physically
From Galactic binary sources, to extragalactic magnetized neutron stars, to
long-duration GRBs without associated supernovae, the types of sources we now
believe capable of producing bursts of gamma-rays continues to grow apace. With
this emergent diversity comes the recognition that the traditional (and newly
formulated) high-energy observables used for identifying sub-classes does not
provide an adequate one-to-one mapping to progenitors. The popular
classification of some > 100 sec duration GRBs as ``short bursts'' is not only
an unpalatable retronym and syntactically oxymoronic but highlights the
difficultly of using what was once a purely phenomenological classification to
encode our understanding of the physics that gives rise to the events. Here we
propose a physically based classification scheme designed to coexist with the
phenomenological system already in place and argue for its utility and
necessity.Comment: 6 pages, 3 figures. Slightly expanded version of solicited paper to
be published in the Proceedings of ''Gamma Ray Bursts 2007,'' Santa Fe, New
Mexico, November 5-9. Edited by E. E. Fenimore, M. Galassi, D. Palme
Predicting Short-duration GRB Rates in the Advanced LIGO Volume
Starting with models for the compact object merger event rate, the
short-duration Gamma-ray Burst (sGRB) luminosity function, and the Swift/BAT
detector, we calculate the observed Swift sGRB rate and its uncertainty. Our
probabilistic sGRB world model reproduces the observed number distributions in
redshift and flux for 123 Swift/BAT detected sGRBs and can be used to predict
joint sGRB/LIGO detection rates. We discuss the dependence of the rate
predictions on the model parameters and explore how they vary with increasing
experimental sensitivity. In particular, the number of bursts in the LIGO
volume depends strongly on the parameters that govern sGRB beaming. Our results
suggest that nearby sGRBs should be observed to have broader jets on average
( degrees), as compared to the narrowly-beamed
appearance of cosmological sGRBs due to detection selection effect driving
observed jet angle. Assuming all sGRBs are due to compact object mergers,
within a Mpc aLIGO volume, we predict sGRB/GW
associations all-sky per year for on-axis events at Swift sensitivities,
increasing to with the inclusion of off-axis events. We
explore the consistency of our model with GW170817/GRB~170817A in the context
of structured jets. Predictions for future experiments are made.Comment: ApJ accepte
Mid-infrared Period-Luminosity Relations of RR Lyrae Stars Derived from the WISE Preliminary Data Release
Interstellar dust presents a significant challenge to extending
parallax-determined distances of optically observed pulsational variables to
larger volumes. Distance ladder work at mid-infrared wavebands, where dust
effects are negligible and metallicity correlations are minimized, have been
largely focused on few-epoch Cepheid studies. Here we present the first
determination of mid-infrared period-luminosity (PL) relations of RR Lyrae
stars from phase-resolved imaging using the preliminary data release of the
Wide-Field Infrared Survey Explorer (WISE). We present a novel statistical
framework to predict posterior distances of 76 well-observed RR Lyrae that uses
the optically constructed prior distance moduli while simultaneously imposing a
power-law PL relation to WISE-determined mean magnitudes. We find that the
absolute magnitude in the bluest WISE filter is M_W1 = (-0.421+-0.014) -
(1.681+-0.147)*log(P/0.50118 day), with no evidence for a correlation with
metallicity. Combining the results from the three bluest WISE filters, we find
that a typical star in our sample has a distance measurement uncertainty of
0.97% (statistical) plus 1.17% (systematic). We do not fundamentalize the
periods of RRc stars to improve their fit to the relations. Taking the
Hipparcos-derived mean V-band magnitudes, we use the distance posteriors to
determine a new optical metallicity-luminosity relation which we present in
Section 5. The results of this analysis will soon be tested by HST parallax
measurements and, eventually, with the Gaia astrometric mission.Comment: 33 pages, 12 figures, 2 tables. Accepted for publication in ApJ, June
27th, 201
Optimal Time-Series Selection of Quasars
We present a novel method for the optimal selection of quasars using
time-series observations in a single photometric bandpass. Utilizing the damped
random walk model of Kelly et al. (2009), we parameterize the ensemble quasar
structure function in Sloan Stripe 82 as a function of observed brightness. The
ensemble model fit can then be evaluated rigorously for and calibrated with
individual light curves with no parameter fitting. This yields a classification
in two statistics --- one describing the fit confidence and one describing the
probability of a false alarm --- which can be tuned, a priori, to achieve high
quasar detection fractions (99% completeness with default cuts), given an
acceptable rate of false alarms. We establish the typical rate of false alarms
due to known variable stars as <3% (high purity). Applying the classification,
we increase the sample of potential quasars relative to those known in Stripe
82 by as much as 29%, and by nearly a factor of two in the redshift range
2.5<z<3, where selection by color is extremeley inefficient. This represents
1875 new quasars in a 290 deg^2 field. The observed rates of both quasars and
stars agree well with the model predictions, with >99% of quasars exhibiting
the expected variability profile. We discus the utility of the method at
high-redshift and in the regime of noisy and sparse data. Our time series
selection complements well independent selection based on quasar colors and has
strong potential for identifying high redshift quasars for BAO and other
cosmology studies in the LSST era.Comment: 28 pages, 8 figures, 3 tables; Accepted to A
A Bayesian Approach to Calibrating Period-Luminosity Relations of RR Lyrae Stars in the Mid-Infrared
A Bayesian approach to calibrating period-luminosity (PL) relations has
substantial benefits over generic least-squares fits. In particular, the
Bayesian approach takes into account the full prior distribution of the model
parameters, such as the a priori distances, and refits these parameters as part
of the process of settling on the most highly-constrained final fit.
Additionally, the Bayesian approach can naturally ingest data from multiple
wavebands and simultaneously fit the parameters of PL relations for each
waveband in a procedure that constrains the parameter posterior distributions
so as to minimize the scatter of the final fits appropriately in all wavebands.
Here we describe the generalized approach to Bayesian model fitting and then
specialize to a detailed description of applying Bayesian linear model fitting
to the mid-infrared PL relations of RR Lyrae variable stars. For this example
application we quantify the improvement afforded by using a Bayesian model fit.
We also compare distances previously predicted in our example application to
recently published parallax distances measured with the Hubble Space Telescope
and find their agreement to be a vindication of our methodology. Our intent
with this article is to spread awareness of the benefits and applicability of
this Bayesian approach and encourage future PL relation investigations to
consider employing this powerful analysis method.Comment: 6 pages, 1 figure. Accepted for publication in Astrophysics & Space
Science. Following a presentation at the conference The Fundamental Cosmic
Distance Scale: State of the Art and the Gaia Perspective, Naples, May 201
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