Astronomical Distance Determination in the Space Age: Secondary Distance Indicators

The formal division of the distance indicators into primary and secondary leads to difficulties in description of methods which can actually be used in two ways: with, and without the support of the other methods for scaling. Thus instead of concentrating on the scaling requirement we concentrate on all methods of distance determination to extragalactic sources which are designated, at least formally, to use for individual sources. Among those, the Supernovae Ia is clearly the leader due to its enormous success in determination of the expansion rate of the Universe. However, new methods are rapidly developing, and there is also a progress in more traditional methods. We give a general overview of the methods but we mostly concentrate on the most recent developments in each field, and future expectations. © 2018, The Author(s)

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Discovery of a multiply lensed submillimeter galaxy in early HerMES Herschel/SPIRE data

‘In these times, during the rise in the popularity of institutional repositories, the Society does not forbid authors from depositing their work in such repositories. However, the AAS regards the deposit of scholarly work in such repositories to be a decision of the individual scholar, as long as the individual's actions respect the diligence of the journals and their reviewers.’ Original article can be found at: http://iopscience.iop.org/ Copyright American Astronomical SocietyWe report the discovery of a bright (f (250 μm)>400 mJy), multiply lensed submillimeter galaxy HERMES J105751.1+573027 in Herschel/SPIRE Science Demonstration Phase data from the HerMES project. Interferometric 880 μm Submillimeter Array observations resolve at least four images with a large separation of ∼9″. A high-resolution adaptive optics Kp image with Keck/NIRC2 clearly shows strong lensing arcs. Follow-up spectroscopy gives a redshift of z = 2.9575, and the lensing model gives a total magnification of μ ∼ 11 ± 1. The large image separation allows us to study the multi-wavelength spectral energy distribution (SED) of the lensed source unobscured by the central lensing mass. The far-IR/millimeter-wave SED is well described by a modified blackbody fit with an unusually warm dust temperature, 88 ± 3 K. We derive a lensing-corrected total IR luminosity of (1.43 ± 0.09) × 1013 L⊙, implying a star formation rate of ∼2500 M⊙ yr-1. However, models primarily developed from brighter galaxies selected at longer wavelengths are a poor fit to the full optical-to-millimeter SED. A number of other strongly lensed systems have already been discovered in early Herschel data, and many more are expected as additional data are collected.Peer reviewe

Gene and repetitive sequence annotation in the Triticeae

The Triticeae tribe contains some of the world’s most important agricultural crops (wheat, barley and rye) and is perhaps, one of the most challenging for genome annotation because Triticeae genomes are primarily composed of repetitive sequences. Further complicating the challenge is the polyploidy found in wheat and particularly in the hexaploid bread wheat genome. Genomic sequence data are available for the Triticeae in the form of large collections of Expressed Sequence Tags (>1.5 million) and an increasing number of bacterial artificial chromosome clone sequences. Given that high repetitive sequence content in the Triticeae confounds annotation of protein-coding genes, repetitive sequences have been identified, annotated, and collated into public databases. Protein coding genes in the Triticeae are structurally annotated using a combination of ab initio gene finders and experimental evidence. Functional annotation of protein coding genes involves assessment of sequence similarity to known proteins, expression evidence, and the presence of domain and motifs. Annotation methods and tools for Triticeae genomic sequences have been adapted from existing plant genome annotation projects and were designed to allow for flexibility of single sequence annotation while allowing a whole community annotation effort to be developed. With the availability of an increasing number of annotated grass genomes, comparative genomics can be exploited to accelerate and enhance the quality of Triticeae sequences annotation. This chapter provides a brief overview of the Triticeae genomes features that are challenging for genome annotation and describes the resources and methods available for sequence annotation with a particular emphasis on problems caused by the repetitive fraction of these genomes

Assessing wave energy effects on biodiversity: the Wave Hub experience

Marine renewable energy installations harnessing energy from wind, wave and tidal resources are likely to become a large part of the future energy mix worldwide. The potential to gather energy from waves has recently seen increasing interest, with pilot developments in several nations. Although technology to harness wave energy lags behind that of wind and tidal generation, it has the potential to contribute significantly to energy production. As wave energy technology matures and becomes more widespread, it is likely to result in further transformation of our coastal seas. Such changes are accompanied by uncertainty regarding their impacts on biodiversity. To date, impacts have not been assessed, as wave energy converters have yet to be fully developed. Therefore, there is a pressing need to build a framework of understanding regarding the potential impacts of these technologies, underpinned by methodologies that are transferable and scalable across sites to facilitate formal meta-analysis. We first review the potential positive and negative effects of wave energy generation, and then, with specific reference to our work at the Wave Hub (a wave energy test site in southwest England, UK), we set out the methodological approaches needed to assess possible effects of wave energy on biodiversity. We highlight the need for national and international research clusters to accelerate the implementation of wave energy, within a coherent understanding of potential effects—both positive and negative