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In this paper, we present studies for optimizing the next generation of ground-based imaging atmospheric Cherenkov telescopes (IACTs). Results focus on mid-sized telescopes (MSTs) for CTA, detecting very high energy gamma rays in the energy range from a few hundred GeV to a few tens of TeV. We describe a novel, flexible detector Monte Carlo package, FAST (FAst Simulation for imaging air cherenkov Telescopes), that we use to simulate different array and telescope designs. The simulation is somewhat simplified to allow for efficient exploration over a large telescope design parameter space. We investigate a wide range of telescope performance parameters including optical resolution, camera pixel size, and light collection area. In order to ensure a comparison of the arrays at their maximum sensitivity, we analyze the simulations with the most sensitive techniques used in the field, such as maximum likelihood template reconstruction and boosted decision trees for background rejection. Choosing telescope design parameters representative of the proposed Davies–Cotton (DC) and Schwarzchild–Couder (SC) MST designs, we compare the performance of the arrays by examining the gamma-ray angular resolution and differential point-source sensitivity. We further investigate the array performance under a wide range of conditions, determining the impact of the number of telescopes, telescope separation, night sky background, and geomagnetic field. We find a 30–40% improvement in the gamma-ray angular resolution at all energies when comparing arrays with an equal number of SC and DC telescopes, significantly enhancing point-source sensitivity in the MST energy range. Finally, we attribute the increase in point-source sensitivity to the improved optical point-spread function and smaller pixel size of the SC telescope design.
Since the creation of the first telescope in the 17th century, every major discovery in astrophysics has been the direct consequence of the development of novel observation techniques, opening new windows in the electromagnetic spectrum. After Karl Jansky discovered serendipitously the first radio source in 1933, Grote Reber built the first parabolic radio telescope in his backyard, planting the seed of a whole new field in astronomy. Similarly, new technologies in the 1950s allowed the establishment of other fields, such as the infrared, ultraviolet or the X-rays. The highest energy end of the electromagnetic spectrum, the gamma-ray range, represents the last unexplored window for astronomers and should reveal the most extreme phenomena that take place in the Universe. Given the technical complexity of gamma-ray detection and the extremely relative low fluxes, gamma-ray astronomy has undergone a slower development compared to other wavelengths. Nowadays, the great success of consecutive space missions together with the development and refinement of new detection techniques from the ground, has allowed outstanding scientific results and has brought gamma-ray astronomy to a worthy level in par with other astronomy fields. This work is devoted to the study and improvement of the future Cherenkov Telescope Array (CTA), the next generation of ground based gamma-ray detectors, designed to observe photons with the highest energies ever observed from cosmic sources. These results on the sensitivity studies performed for the CTA collaboration evaluate the observatory performance through the analysis of large-scale Monte Carlo (MC) simulations, along with an estimation of its future potential on specific physics cases. Together with the testing and development of the analysis tools employed, these results are critical to understand CTA's future capabilities, the efficiency of different telescope placement approaches and the effect on performance of the construction site, related to parameters such as the altitude or the geomagnetic field. The Northern Hemisphere proposed construction sites were analyzed and evaluated, providing an accurate estimation of their capabilities to host the observatory. As for the CTA layout candidates, an unbiased comparison of the different arrays proposed by the collaboration was performed, using Fermi-LAT catalogs to forecast the performance of each array over specific scientific cases. In addition, the application of machine learning algorithms on gamma-ray astronomy was studied, comparing alternative methods for energy reconstruction and background suppression and introducing new applications to these algorithms, such as the determination of gamma-ray source types through the training of their spectral features. The analysis presented here of both CTA-N and CTA-S candidates represents the most comprehensive study of CTA capabilities performed by the collaboration to date. Experience gained with the improvement of this software will guide the future gls{cta} analysis pipelines by comparing the attained sensitivity by alternative analysis chains. From these results, both CTA-N and CTA-S candidates "2N" and "2Q" fulfill the sensitivity, angular and energy resolution, effective area and off-axis performance requirements. MC simulations provide an useful test-bench for the different designs within the CTA project, and these results demonstrate their correct implementation would attain the desired performance and potential scientific output.
This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.
This book summarizes the science to be carried out by the upcoming Cherenkov Telescope Array, a major ground-based gamma-ray observatory that will be constructed over the next six to eight years. The major scientific themes, as well as core program of key science projects, have been developed by the CTA Consortium, a collaboration of scientists from many institutions worldwide.CTA will be the major facility in high-energy and very high-energy photon astronomy over the next decade and beyond. CTA will have capabilities well beyond past and present observatories. Thus, CTA's science program is expected to be rich and broad and will complement other major multiwavelength and multimessenger facilities. This book is intended to be the primary resource for the science case for CTA and it thus will be of great interest to the broader physics and astronomy communities. The electronic version (e-book) is available in open access.
This thesis presents the results of indirect dark matter searches in the gamma-ray sky of the near Universe, as seen by the MAGIC Telescopes. The author has proposed and led the 160 hours long observations of the dwarf spheroidal galaxy Segue 1, which is the deepest survey of any such object by any Cherenkov telescope so far. Furthermore, she developed and completely characterized a new method, dubbed “Full Likelihood”, that optimizes the sensitivity of Cherenkov instruments for detection of gamma-ray signals of dark matter origin. Compared to the standard analysis techniques, this novel approach introduces a sensitivity improvement of a factor of two (i.e. it requires 4 times less observation time to achieve the same result). In addition, it allows a straightforward merger of results from different targets and/or detectors. By selecting the optimal observational target and combining its very deep exposure with the Full Likelihood analysis of the acquired data, the author has improved the existing MAGIC bounds to the dark matter properties by more than one order of magnitude. Furthermore, for particles more massive than a few hundred GeV, those are the strongest constraints from dwarf galaxies achieved by any gamma-ray instrument, both ground-based or space-borne alike.