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 $z\lesssim4$ 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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