arXiv subjects

A. De Angelis

Publications and source records attributed to A. De Angelis.

At least 217 records · Page 12Linked to original sources

arXiv2007

MAGIC upper limits on the very high energy emission from GRBs

The fast repositioning system of the MAGIC Telescope has allowed during its first data cycle, between 2005 and the beginning of year 2006, observing nine different GRBs as possible sources of very high energy gammas. These observations were triggered by alerts from Swift, HETE-II, and Integral; they started as fast as possible after the alerts and lasted for several minutes, with an energy threshold varying between 80 and 200 GeV, depending upon the zenith angle of the burst. No evidence for gamma signals was found, and upper limits for the flux were derived for all events, using the standard analysis chain of MAGIC. For the bursts with measured redshift, the upper limits are compatible with a power law extrapolation, when the intrinsic fluxes are evaluated taking into account the attenuation due to the scattering in the Metagalactic Radiation Field (MRF).

astro-ph↗

arXiv2006

Discovery of VHE gamma-ray emission from 1ES1218+30.4

The MAGIC collaboration has studied the high peaked BL-Lac object 1ES1218+30.4 at a redshift z = 0.182, using the MAGIC imaging air Cherenkov telescope located on the Canary island of La Palma. A gamma-ray signal was observed with 6.4sigma significance. The differential energy spectrum for an energy threshold of 120GeV can be fitted by a simple power law yielding F_E(E) = (8.1+-2.1)*10^-7 (E/250GeV)^(-3.0+-0.4) TeV^-1 m^-2 s^-1. During the six days of observation in January 2005 no time variability on time scales of days was found within the statistical errors. The observed integral flux above 350GeV is nearly a factor two below the the upper limit reported by the Whipple Collaboration in 2003.

astro-ph↗

arXiv2006

Flux upper limit of gamma-ray emission by GRB050713a from MAGIC Telescope observations

The long-duration GRB050713a was observed by the MAGIC Telescope, 40 seconds after the burst onset, and followed up for 37 minutes, until twilight. The observation, triggered by a SWIFT alert, covered energies above ~175 GeV. Using standard MAGIC analysis, no evidence for a gamma signal was found. As the redshift of the GRB was not measured directly, the flux upper limit, estimated by MAGIC, is still compatible with the assumption of an unbroken power-law spectrum extending from a few hundred keV to our energy range.

astro-ph↗

arXiv2005

Using the photons from the Crab Nebula seen by GLAST to calibrate MAGIC and the Imaging Air Cherenkov Telescopes

In this article we discuss the possibility of using the observations by GLAST of standard gamma sources, as the Crab Nebula, to calibrate Imaging Air Cherenkov detectors, MAGIC in particular, and optimise their energy resolution. We show that at around 100 GeV the absolute energy calibration uncertainty of Cherenkov telescopes can be reduced to <10% by means of such cross-calibration procedure.

astro-ph↗

arXiv2005

The MAGIC Experiment and Its First Results

With its diameter of 17m, the MAGIC telescope is the largest Cherenkov detector for gamma ray astrophysics. It is sensitive to photons above an energy of 30 GeV. MAGIC started operations in October 2003 and is currently taking data. This report summarizes its main characteristics, its rst results and its potential for physics.

astro-ph↗

arXiv2005

Neural networks for gamma-hadron separation in MAGIC

Neural networks have proved to be versatile and robust for particle separation in many experiments related to particle astrophysics. We apply these techniques to separate gamma rays from hadrons for the MAGIC Cerenkov Telescope. Two types of neural network architectures have been used for the classi cation task: one is the MultiLayer Perceptron (MLP) based on supervised learning, and the other is the Self-Organising Tree Algorithm (SOTA), which is based on unsupervised learning. We propose a new architecture by combining these two neural networks types to yield better and faster classi cation results for our classi cation problem.

astro-ph↗

arXiv2005

Simulating the High Energy Gamma-ray sky seen by the GLAST Large Area Telescope

This paper presents the simulation of the GLAST high energy gamma-ray telescope. The simulation package, written in C++, is based on the Geant4 toolkit, and it is integrated into a general framework used to process events. A detailed simulation of the electronic signals inside Silicon detectors has been provided and it is used for the particle tracking, which is handled by a dedicated software. A unique repository for the geometrical description of the detector has been realized using the XML language and a C++ library to access this information has been designed and implemented. A new event display based on the HepRep protocol was implemented. The full simulation was used to simulate a full week of GLAST high energy gamma-ray observations. This paper outlines the contribution developed by the Italian GLAST software group.

astro-ph↗

arXiv2005

Data Mining in Gamma Astrophysics Experiments

Data mining techniques, including clustering and classification tasks, for the automatic information extraction from large datasets are increasingly demanded in several scientific fields. In particular, in the astrophysical field, large archives and digital sky surveys with dimensions of 10E12 bytes currently exist, while in the near future they will reach sizes of the order of 10E15. In this work we propose a multidimensional indexing method to efficiently query and mine large astrophysical datasets. A novelty detection algorithm, based on the Support Vector Clustering and using density and neighborhood information stored in the index structure, is proposed to find regions of interest in data characterized by isotropic noise. We show an application of this method for the detection of point sources from a gamma-ray photon list.

astro-ph↗

arXiv2005

Grid services for the MAGIC experiment

Exploring signals from the outer space has become an observational science under fast expansion. On the basis of its advanced technology the MAGIC telescope is the natural building block for the first large scale ground based high energy gamma-ray observatory. The low energy threshold for gamma-rays together with different background sources leads to a considerable amount of data. The analysis will be done in different institutes spread over Europe. Therefore MAGIC offers the opportunity to use the Grid technology to setup a distributed computational and data intensive analysis system with the nowadays available technology. Benefits of Grid computing for the MAGIC telescope are presented.

astro-ph↗

arXiv2004

Multidimensional data classification with artificial neural networks

Multi-dimensional data classification is an important and challenging problem in many astro-particle experiments. Neural networks have proved to be versatile and robust in multi-dimensional data classification. In this article we shall study the classification of gamma from the hadrons for the MAGIC Experiment. Two neural networks have been used for the classification task. One is Multi-Layer Perceptron based on supervised learning and other is Self-Organising Map (SOM), which is based on unsupervised learning technique. The results have been shown and the possible ways of combining these networks have been proposed to yield better and faster classification results.

cs.NE↗

arXiv2004

Self-Organising Networks for Classification: developing Applications to Science Analysis for Astroparticle Physics

Physics analysis in astroparticle experiments requires the capability of recognizing new phenomena; in order to establish what is new, it is important to develop tools for automatic classification, able to compare the final result with data from different detectors. A typical example is the problem of Gamma Ray Burst detection, classification, and possible association to known sources: for this task physicists will need in the next years tools to associate data from optical databases, from satellite experiments (EGRET, GLAST), and from Cherenkov telescopes (MAGIC, HESS, CANGAROO, VERITAS).

cs.NE↗

arXiv2004

Perspects in astrophysical databases

Astrophysics has become a domain extremely rich of scientific data. Data mining tools are needed for information extraction from such large datasets. This asks for an approach to data management emphasizing the efficiency and simplicity of data access; efficiency is obtained using multidimensional access methods and simplicity is achieved by properly handling metadata. Moreover, clustering and classification techniques on large datasets pose additional requirements in terms of computation and memory scalability and interpretability of results. In this study we review some possible solutions.

cs.DB↗

arXiv2003

Gleam: the GLAST Large Area Telescope Simulation Framework

astro-ph↗

arXiv2003

Sensitivity of Gamma Astroparticle Experiments to the Detection of Photon Oscillations

The mixing of the photon with a hypothetical sterile paraphotonic state would have consequences on the cosmological propagation of photons. Observations of gamma-rays from active galactic nuclei in GLAST and MAGIC will open a new domain in the search for such a phenomenon.

astro-ph↗

arXiv2003

Automatic Classification using Self-Organising Neural Networks in Astrophysical Experiments

Self-Organising Maps (SOMs) are effective tools in classification problems, and in recent years the even more powerful Dynamic Growing Neural Networks, a variant of SOMs, have been developed. Automatic Classification (also called clustering) is an important and difficult problem in many Astrophysical experiments, for instance, Gamma Ray Burst classification, or gamma-hadron separation. After a brief introduction to classification problem, we discuss Self-Organising Maps in section 2. Section 3 discusses with various models of growing neural networks and finally in section 4 we discuss the research perspectives in growing neural networks for efficient classification in astrophysical problems.

cs.NE↗

arXiv2003

Data Management and Mining in Astrophysical Databases

We analyse the issues involved in the management and mining of astrophysical data. The traditional approach to data management in the astrophysical field is not able to keep up with the increasing size of the data gathered by modern detectors. An essential role in the astrophysical research will be assumed by automatic tools for information extraction from large datasets, i.e. data mining techniques, such as clustering and classification algorithms. This asks for an approach to data management based on data warehousing, emphasizing the efficiency and simplicity of data access; efficiency is obtained using multidimensional access methods and simplicity is achieved by properly handling metadata. Clustering and classification techniques, on large datasets, pose additional requirements: computational and memory scalability with respect to the data size, interpretability and objectivity of clustering or classification results. In this study we address some possible solutions.

cs.DB↗

arXiv2002

Improved limits on photon velocity oscillations

The mixing of the photon with a hypothetical sterile paraphotonic state would have consequences on the cosmological propagation of photons. The absence of distortions in the optical spectrum of distant Type Ia supernovæallows to extend by two orders of magnitude the previous limit on the Lorentz-violating parameter $δ$ associated to the photon-paraphoton transition, extracted from the abscence of distortions in the spectrum of the cosmic microwave background. The new limit is consistent with the interpretation of the dimming of distant Type Ia supernovæas a consequence of a nonzero cosmological constant. Observations of gamma-rays from active galactic nuclei allow to further extend the limit on $δ$ by ten orders of magnitude.

astro-ph↗

arXiv1998

The Estimation of the Effective Centre of Mass Energy in q-qbar-gamma Events from DELPHI

The photon radiation in the initial state lowers the energy available for the e$^+$e$^-$ collisions; this effect is particularly important at LEP2 energies (above the mass of the Z boson). Being aligned to the beam direction, such initial state radiation is mostly undetected. This article describes the procedure used by the DELPHI experiment at LEP to estimate the effective centre-of-mass energy in hadronic events collected at energies above the Z peak. Typical resolutions ranging from 2 to 3 GeV on the effective center-of-mass energy are achieved, depending on the event topology.

hep-ex↗