Related papers: Self-Organising Networks for Classification: devel…
The unrivalled, extreme luminosities of gamma-ray bursts (GRBs) make them the favored beacons for sampling the high redshift Universe. To employ GRBs to study the cosmic terrain -- e.g., star and galaxy formation history -- GRB luminosities…
We review the status of indirect Dark Matter searches, focusing in particular on the connection with gamma-ray Astrophysics, and on the prospects for detection with the upcoming space telescope GLAST and Air Cherenkov Telescopes such as…
Gamma Ray Bursts are among the most powerful astrophysical sources and they release up to 1.e54 erg, if isotropic, in less than few hundred seconds. Their detection in the hard X/gamma ray band (at energies >10 keV) and out to very high…
Astronomy is increasingly encountering two fundamental truths: (1) The field is faced with the task of extracting useful information from extremely large, complex, and high dimensional datasets; (2) The techniques of astroinformatics and…
Detectors for gamma-ray astronomy are complex: they often comprise multiple sub-systems and utilize new and/or custom-developed detector components and readout electronics. Gamma rays are typically not detected directly: ground-based…
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…
High precision asteroseismic data provide a unique opportunity to test input microphysics such as stellar opacities, chemical composition or equation of state. These tests are possible because pulsational frequencies as well as amplitudes…
Multivariate clustering in astrophysics is a recent development justified by the bigger and bigger surveys of the sky. The phylogenetic approach is probably the most unexpected technique that has appeared for the unsupervised classification…
This project outlines the complete development of a variable star classification algorithm methodology. With the advent of Big-Data in astronomy, professional astronomers are left with the problem of how to manage large amounts of data, and…
It is developed a very complex system (hardware/software) to detect luminosity variations connected with the discovery of new planets outside the Solar System. Traditional imaging approaches are very demanding in terms of computing time;…
In this thesis the data analysis designed by author for the "Pi of the Sky" experiment is presented. The data analysis consists of data reduction and specific algorithms for identification of short time scale astrophysical processes. The…
This report reviews methods of pattern recognition and event reconstruction used in modern high energy physics experiments. After a brief introduction into general concepts of particle detectors and statistical evaluation, different…
Transient and variable phenomena in astrophysical sources are of particular importance to understand the underlying gamma-ray emission processes. In the very-high energy gamma-ray domain, transient and variable sources are related to…
The widespread dissemination of machine learning tools in science, particularly in astronomy, has revealed the limitation of working with simple single-task scenarios in which any task in need of a predictive model is looked in isolation,…
The cosmological redshift of a galaxy's light is inferable from its observable properties in images. Because imaging is much easier to acquire than spectroscopic observations that would allow the identification of distinct line features,…
The study of high energy cosmic rays is a diversified field of observational and phenomenological physics addressing questions ranging from shock acceleration of charged particles in various astrophysical objects, via transport properties…
The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the…
Gamma-ray studies are an essential tool in our search for the origin of cosmic rays. Instruments like the Fermi-LAT, H.E.S.S., MAGIC and VERITAS have revolutionized our understanding of the high energy Universe. This paper describes the…
Classification is a popular task in the field of Machine Learning (ML) and Artificial Intelligence (AI), and it happens when outputs are categorical variables. There are a wide variety of models that attempts to draw some conclusions from…
In this work we present some applications about the use of the so-called Cosmography with GRBs. In particular, we try to calibrate the Amati relation by using the luminosity distance obtained from the cosmographic analysis. Thus, we analyze…