Probing Convolutional Neural Networks for Event Reconstruction in {\gamma}-Ray Astronomy with Cherenkov Telescopes

A dramatic progress in the field of computer vision has been made in recent years by applying deep learning techniques. State-of-the-art performance in image recognition is thereby reached with Convolutional Neural Networks (CNNs). CNNs are a powerful class of artificial neural networks, characterized by requiring fewer connections and free parameters than traditional neural networks and exploiting spatial symmetries in the input data. Moreover, CNNs have the ability to automatically extract general characteristic features from data sets and create abstract data representations which can perform very robust predictions. This suggests that experiments using Cherenkov telescopes could harness these powerful machine learning algorithms to improve the analysis of particle-induced air-showers, where the properties of primary shower particles are reconstructed from shower images recorded by the telescopes. In this work, we present initial results of a CNN-based analysis for background rejection and shower reconstruction, utilizing simulation data from the H.E.S.S. experiment. We concentrate on supervised training methods and outline the influence of image sampling on the performance of the CNN-model predictions.Comment: 8 pages, 4 figures, Proceedings of the 35th International Cosmic Ray Conference (ICRC 2017), Busan, Kore

Comparison of discharge lamp and laser pumped cesium magnetometers

We have performed a comparison of laser (LsOPM) and lamp (LpOPM) pumped cesium vapor magnetometers. Although the LsOPM operated 50% above its shot- noise limit we found an intrinsic sensitivity of 15 fT/√Hz and 25 fT/√Hz for the LsOPM and the LpOPM, respectively. Two modes of operation, viz. the phase-stabilized and the self-oscillating modes, were investigated and found to yield a similar performance. We have compared the performance of the LsOPM and the LpOPM directly by simultaneous measurements of field fluctuations of a 2-μT magnetic field inside a multilayer magnetic shield and have used one of the magnetometers for an active field stabilization. In the stabilized mode we found a gradient instability of 25 fT within an integration time of 100 s, which represents an upper limit of the long-term stability of the magnetometers. Our research is motivated by the need for an improved control of magnetic fields and gradients in a planned neutron electric dipole experiment

Systematic Cross-biospecimen Evaluation of DNA Extraction Kits for Long- and Short-read Multi-metagenomic Sequencing Studies

High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients

Chronology and climate forcing of the last four interglacials

International audienceThe last four interglacials (intervals during which global ice volume was similar to, or less than, that of our current warm stage) correspond to the warmest parts of the marine oxygen isotope stages marine isotopic age (MIS) 5, 7, 9, and 11. These interglacials followed the 100-kyr rhythm of eccentricity, but each had different insolation regimes, different durations, different ice volumes, and different sea-level heights. However, atmospheric greenhouse gas concentrations were similar and reached values, which, largely, were close to those of the current interglacial (Holocene or MIS 1) before the industrial revolution led to the artificial enrichment of the atmosphere's greenhouse gas concentrations via the burning of fossil fuels. This chapter summarizes the state of knowledge on each of the climatic warm intervals