1,652 research outputs found
Dust extinction bias in the column density distribution of gamma-ray bursts; high column density, low redshift GRBs are more heavily obscured
The afterglows of gamma-ray bursts (GRBs) have more soft X-ray absorption
than expected from the foreground gas column in the Galaxy. While the redshift
of the absorption can in general not be constrained from current X-ray
observations, it has been assumed that the absorption is due to metals in the
host galaxy of the GRB. The large sample of X-ray afterglows and redshifts now
available allows the construction of statistically meaningful distributions of
the metal column densities. We construct such a sample and show, as found in
previous studies, that the typical absorbing column density (N_HX) increases
substantially with redshift, with few high column density objects found at low
to moderate redshifts. We show, however, that when highly extinguished bursts
are included in the sample, using redshifts from their host galaxies, high
column density sources are also found at low to moderate redshift. We infer
from individual objects in the sample and from observations of blazars, that
the increase in column density with redshift is unlikely to be related to
metals in the intergalactic medium or intervening absorbers. Instead we show
that the origin of the apparent increase with redshift is primarily due to dust
extinction bias: GRBs with high X-ray absorption column densities found at
typically have very high dust extinction column densities, while
those found at the highest redshifts do not. It is unclear how such a strongly
evolving N_HX/A_V ratio would arise, and based on current data, remains a
puzzle.Comment: 7 pages, 3 figures. Accepted for publication in ApJ, 1 August 201
Near-optimal RNA-Seq quantification
We present a novel approach to RNA-Seq quantification that is near optimal in
speed and accuracy. Software implementing the approach, called kallisto, can be
used to analyze 30 million unaligned paired-end RNA-Seq reads in less than 5
minutes on a standard laptop computer while providing results as accurate as
those of the best existing tools. This removes a major computational bottleneck
in RNA-Seq analysis.Comment: - Added some results (paralog analysis, allele specific expression
analysis, alignment comparison, accuracy analysis with TPMs) - Switched
bootstrap analysis to human sample from SEQC-MAQCIII - Provided link to a
snakefile that allows for reproducibility of all results and figures in the
pape
Long Gamma-Ray Burst Host Galaxies and their Environments
In this book-chapter we first briefly discuss some basic observational issues
related to what a GRB host galaxy is (whether they are operationally well
defined as a class) and sample completeness. We then describe some of the early
studies of GRB hosts starting with statistical studies of upper limits done
prior to the first detections, the first host detection after the BeppoSAX
breakthrough and leading up to the current Swift era. Finally, we discuss the
status of efforts to construct a more complete sample of GRBs based on Swift
and end with an outlook. We only consider the host galaxies of long-duration
GRBs.Comment: 31 pages, 14 figures; Chapter 13 in "Gamma-Ray Bursts", eds. C.
Kouveliotou, R. A. M. J. Wijers, S. E. Woosley, Cambridge University Press,
201
Relative relocation of earthquakes without a predefined velocity model: an example from a peculiar seismic cluster on Katla volcano's south-flank (Iceland)
Relative relocation methods are commonly used to precisely relocate
earthquake clusters consisting of similar waveforms. Repeating waveforms are
often recorded at volcanoes, where, however, the crust structure is expected to
contain strong heterogeneities and therefore the 1D velocity model assumption
that is made in most location strategies is not likely to describe reality. A
peculiar cluster of repeating low-frequency seismic events was recorded on the
south flank of Katla volcano (Iceland) from 2011. As the hypocentres are
located at the rim of the glacier, the seismicity may be due to volcanic or
glacial processes. Information on the size and shape of the cluster may help
constraining the source process. The extreme similarity of waveforms points to
a very small spatial distribution of hypocentres. In order to extract
meaningful information about size and shape of the cluster, we minimize
uncertainty by optimizing the cross-correlation measurements and
relative-relocation process. With a synthetic test we determine the best
parameters for differential-time measurements and estimate their uncertainties,
specifically for each waveform. We design a relocation strategy to work without
a predefined velocity model, by formulating and inverting the problem to seek
changes in both location and slowness, thus accounting for azimuth, take-off
angles and velocity deviations from a 1D model. We solve the inversion
explicitly in order to propagate data errors through the calculation. With this
approach we are able to resolve a source volume few tens of meters wide on
horizontal directions and around 100 meters in depth. There is no suggestion
that the hypocentres lie on a single fault plane and the depth distribution
indicates that their source is unlikely to be related to glacial processes as
the ice thickness is not expected to exceed few tens of meters in the source
area
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