A Monte Carlo Template based analysis for Air-Cherenkov Arrays

We present a high-performance event reconstruction algorithm: an Image Pixel-wise fit for Atmospheric Cherenkov Telescopes (ImPACT). The reconstruction algorithm is based around the likelihood fitting of camera pixel amplitudes to an expected image template. A maximum likelihood fit is performed to find the best-fit shower parameters. A related reconstruction algorithm has already been shown to provide significant improvements over traditional reconstruction for both the CAT and H.E.S.S. experiments. We demonstrate a significant improvement to the template generation step of the procedure, by the use of a full Monte Carlo air shower simulation in combination with a ray-tracing optics simulation to more accurately model the expected camera images. This reconstruction step is combined with an MVA-based background rejection. Examples are shown of the performance of the ImPACT analysis on both simulated and measured (from a strong VHE source) gamma-ray data from the H.E.S.S. array, demonstrating an improvement in sensitivity of more than a factor two in observation time over traditional image moments-fitting methods, with comparable performance to previous likelihood fitting analyses. ImPACT is a particularly promising approach for future large arrays such as the Cherenkov Telescope Array (CTA) due to its improved high-energy performance and suitability for arrays of mixed telescope types.Comment: 13 pages, 10 figure

The lunar atmosphere Scientific report

Lunar atmosphere data and postulated theory of its structur

ShapeCodes: Self-Supervised Feature Learning by Lifting Views to Viewgrids

We introduce an unsupervised feature learning approach that embeds 3D shape information into a single-view image representation. The main idea is a self-supervised training objective that, given only a single 2D image, requires all unseen views of the object to be predictable from learned features. We implement this idea as an encoder-decoder convolutional neural network. The network maps an input image of an unknown category and unknown viewpoint to a latent space, from which a deconvolutional decoder can best "lift" the image to its complete viewgrid showing the object from all viewing angles. Our class-agnostic training procedure encourages the representation to capture fundamental shape primitives and semantic regularities in a data-driven manner---without manual semantic labels. Our results on two widely-used shape datasets show 1) our approach successfully learns to perform "mental rotation" even for objects unseen during training, and 2) the learned latent space is a powerful representation for object recognition, outperforming several existing unsupervised feature learning methods.Comment: To appear at ECCV 201

Decaying dark matter: a stacking analysis of galaxy clusters to improve on current limits

We show that a stacking approach to galaxy clusters can improve current limits on decaying dark matter by a factor $\gtrsim 5-100$, with respect to a single source analysis, for all-sky instruments such as Fermi-LAT. Based on the largest sample of X-ray-selected galaxy clusters available to date (the MCXC meta-catalogue), we provide all the astrophysical information, in particular the astrophysical term for decaying dark matter, required to perform an analysis with current instruments.Comment: 6 pages, 3 figures, supplementary file available on demand, accepted for publication in PR

The background from single electromagnetic subcascades for a stereo system of air Cherenkov telescopes

The MAGIC experiment, a very large Imaging Air Cherenkov Telescope (IACT) with sensitivity to low energy (E < 100 GeV) VHE gamma rays, has been operated since 2004. It has been found that the gamma/hadron separation in IACTs becomes much more difficult below 100 GeV [Albert et al 2008] A system of two large telescopes may eventually be triggered by hadronic events containing Cherenkov light from only one electromagnetic subcascade or two gamma subcascades, which are products of the single pi^0 decay. This is a possible reason for the deterioration of the experiment's sensitivity below 100 GeV. In this paper a system of two MAGIC telescopes working in stereoscopic mode is studied using Monte Carlo simulations. The detected images have similar shapes to that of primary gamma-rays and they have small sizes (mainly below 400 photoelectrons (p.e.)) which correspond to an energy of primary gamma-rays below 100 GeV. The background from single or two electromagnetic subcascdes is concentrated at energies below 200 GeV. Finally the number of background events is compared to the number of VHE gamma-ray excess events from the Crab Nebula. The investigated background survives simple cuts for sizes below 250 p.e. and thus the experiment's sensitivity deteriorates at lower energies.Comment: 15 pages, 7 figures, published in Journ.of Phys.

EDGE: a code to calculate diffusion of cosmic-ray electrons and their gamma-ray emission

The positron excess measured by PAMELA and AMS can only be explained if there is one or several sources injecting them. Moreover, at the highest energies, it requires the presence of nearby ($\sim$hundreds of parsecs) and middle age (maximum of $\sim$hundreds of kyr) source. Pulsars, as factories of electrons and positrons, are one of the proposed candidates to explain the origin of this excess. To calculate the contribution of these sources to the electron and positron flux at the Earth, we developed EDGE (Electron Diffusion and Gamma rays to the Earth), a code to treat diffusion of electrons and compute their diffusion from a central source with a flexible injection spectrum. We can derive the source's gamma-ray spectrum, spatial extension, the all-electron density in space and the electron and positron flux reaching the Earth. We present in this contribution the fundamentals of the code and study how different parameters affect the gamma-ray spectrum of a source and the electron flux measured at the Earth.Comment: Presented at the 35th International Cosmic Ray Conference (ICRC2017), Bexco, Busan, Kore

Transcriptional profiling of colicin-induced cell death of Escherichia coli MG1655 identifies potential mechanisms by which bacteriocins promote bacterial diversity

We report the transcriptional response of Escherichia coli MG1655 to damage induced by colicins E3 and E9, bacteriocins that kill cells through inactivation of the ribosome and degradation of chromosomal DNA, respectively. Colicin E9 strongly induced the LexA-regulated SOS response, while colicin E3 elicited a broad response that included the induction of cold shock genes, symptomatic of translational arrest. Colicin E3 also increased the transcription of cryptic prophage genes and other laterally acquired mobile elements. The transcriptional responses to both these toxins suggest mechanisms that may promote genetic diversity in E. coli populations, pointing to a more general role for colicins in adaptive bacterial physiology than has hitherto been realized