The amount of cosmological data has dramatically increased in the past decades due to an unprecedented development of telescopes, detectors and satellites. Efficiently handling and analysing new data of the order of terabytes per day requires not only computer power to be processed but also the development of sophisticated algorithms and pipelines. Aiming at students and researchers the lecture notes in this volume explain in pedagogical manner the best techniques used to extract information from cosmological data, as well as reliable methods that should help us improve our view of the universe.

The international Workshop on "Data Analysis in Astronomy" was in tended to give a presentation of experiences that have been acqui red in data analysis and image processing, developments and appli cations that are steadly growing up in Astronomy. The quality and the quantity of ground and satellite observations require more so phisticated data analysis methods and better computational tools. The Workshop has reviewed the present state of the art, explored new methods and discussed a wide range of applications. The topics which have been selected have covered the main fields of interest for data analysis in Astronomy. The Workshop has been focused on the methods used and their significant applications. Results which gave a major contribution to the physical interpre tation of the data have been stressed in the presentations. Atten tion has been devoted to the description of operational system for data analysis in astronomy. The success of the meeting has been the results of the coordinated effort of several people from the organizers to those who presen ted a contribution and/or took part in the discussion. We wish to thank the members of the Workshop scientific committee Prof. M. Ca paccioli, Prof. G. De Biase, Prof. G. Sedmak, Prof. A. Zichichi and of the local organizing committee Dr. R. Buccheri and Dr. M.C. Macca rone together with Miss P. Savalli and Dr. A. Gabriele of the E. Majo rana Center for their support and the unvaluable part in arranging the Workshop.

This work deals with the search for signatures of non-Gaussianities in the cosmic microwave background (CMB). Probing Gaussianity in the CMB addresses one of the key questions in modern cosmology because it allows us to discriminate between different models of inflation, and thus concerns a fundamental part of the standard cosmological model. The basic goal here is to adapt complementary methods stemming from the field of complexity science to CMB data analysis. Two key concepts, namely the method of surrogates and estimators for local scaling properties, are applied to CMB data analysis. All results show strong non-Gaussianities and pronounced asymmetries. The consistency of the full sky and cut sky results shows convincingly for the first time that the influence of the Galactic plane is not responsible for these deviations from Gaussianity and isotropy. The findings seriously call into question predictions of isotropic cosmologies based on the widely accepted single field slow roll inflation model.

In this book are reported the main results presented at the "Fourth International Workshop on Data Analysis in Astronomy", held at the Ettore Majorana Center for Scientific Culture, Erice, Sicily, Italy, on April 12-19, 1991. The Workshop was preceded by three workshops on the same subject held in Erice in 1984, 1986 and 1988. The frrst workshop (Erice 1984) was dominated by presentations of "Systems for Data Analysis"; the main systems proposed were MIDAS, AlPS, RIAIP, and SAIA. Methodologies and image analysis topics were also presented with the emphasis on cluster analysis, multivariate analysis, bootstrap methods, time analysis, periodicity, 2D photometry, spectrometry, and data compression. A general presentation on "Parallel Processing" was made which encompassed new architectures, data structures and languages. The second workshop (Erice 1986) reviewed the "Data Handling Systems" planned for large major satellites and ground experiments (VLA, HST, ROSAT, COMPASS-COMPTEL). Data analysis methods applied to physical interpretation were mainly considered (cluster photometry, astronomical optical data compression, cluster analysis for pulsar light curves, coded aperture imaging). New parallel and vectorial machines were presented (cellular machines, PAPIA-machine, MPP-machine, vector computers in astronomy). Contributions in the field of artificial intelligence and planned applications to astronomy were also considered (expert systems, artificial intelligence in computer vision).

In the book are reported the main results presented at the Third International Workshop on Data Analysis in Astronomy, held at the EUore Majorana Center for Scientific Culture, Erice, Sicily, Italy, on June 20-27,1988. The Workshop was the natural evolution of the two previous ones. The main goal of the first edition (Erice 1984) was to start a scientific interaction between Astronomers and Computer Scientists. Aim of the second (Erice 1986) was to look at the progress in data analysis methods and dedicated hardware technology. Data analysis problems become harder whenever the data are poor in statistics or the signal is weak and embedded in structured background. Experiments collecting data of such a nature require new and non-standard methodologies. Possibilistic approaches could be merged with the statistical ones, in order to formalize all the knowledge used by the scientists to reach conclusions. Moreover, the last decade has been characterized by very fast developments of Intelligent Systems for data analysis (knowledge based systems, ... ) that would be useful to support astronomers in complex decision making. For these reasons, the last edition of the workshop was intended to provide an overview on the state of the art in the data analysis methodologies and tools in the new frontieres of the astrophysics (y-astronomy, neutrino astronomy, gravitational waves, background radiation and extreme cosmic ray energy spectrum). The book is organized in two sections: - Data analysis methods and tools, - New frontieres in astronomy.

This proceedings volume contains results presented at the Sixth International Workshop on Data Analysis in Astronomy OCo OC Modeling and Simulation in ScienceOCO held on April 15-22, 2007, at the Ettore Majorana Foundation and Center for Scientific Culture, Erice, Italy. Recent progress and new trends in the field of simulation and modeling in three branches of science OCo astrophysics, biology, and climatology OCo are described in papers presented by outstanding scientists. The impact of new technologies on the design of novel data analysis systems and the interrelation among different fields are foremost in scientists'' minds in the modern era. This book therefore focuses primarily on data analysis methodologies and techniques. Sample Chapter(s). Chapter 1: Simulations for Uhe Cosmic Ray Experiments (562 KB). Contents: Astrophysics, Cosmology and Earth Physics: Simulations for UHE Cosmic Ray Experiments (J Knapp); Problems and Solutions in Climate Modeling (A Sutera); Statistical Analysis of Quasar Data and Validity of the Hubble Law (S Roy et al.); Quantum Astronomy and Information (C Barbieri); Biology, Biochemistry and Bioinformatics: From Genomes to Protein Models and Back (A Tramontano et al.); Exploring Biomolecular Recognition by Modeling and Simulation (R Wade); BioInfogrid: Bioinformatics Simulation and Modeling Based on Grid (L Milanesi); Methods and Techniques: Optimization Strategies for Modeling and Simulation (J Louchet); Biclustering Bioinformatics Data Sets: A Possibilistic Approach (F Masulli); From the Qubit to the Quantum Search Algorithms (G Cariolaro & T Occhipinti); Comparison of Stereo Vision Techniques for Cloud-Top Height Retrieval (A Anzalone et al.); and other papers. Readership: Physicists; biologists; computer scientists and data analysts."

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers

This proceedings volume focuses on new methods of image and signal analysis in a wide range of energies (from radio to gamma ray astronomy) and advanced methodologies regarding problems and solutions in information fusion and retrieval, statistical pattern recognition, vision and advances in computing technology.A special section is devoted to the BeppoSAX mission (Satellite per Astronomia X) launched on April 30 1996, inside a program of the Italian Space Agency (ASI) and the Netherlands Agency for Aerospace Programs (NIVR).

This book has its roots in a series of collaborations in the last decade at the interface between statistical physics and cosmology. The speci?c problem which initiated this research was the study of the clustering properties of galaxies as revealed by large redshift surveys, a context in which concepts of modern statistical physics (e. g. scale-invariance, fractality. . ) ?nd ready application. In recent years we have considerably broadened the range of problems in cosmology which we have addressed, treating in particular more theoretical issues about the statistical properties of standard cosmological models. What is common to all this research, however, is that it is informed by a perspective and methodology which is that of statistical physics. We can say that, beyond its speci?c scienti?c content, this book has an underlying thesis: such interdisciplinary research is an exciting playground for statistical physics, and one which can bring new and useful insights into cosmology. The book does not represent a ?nal point, but in our view, a marker in the development of this kind of research, which we believe can go very much further in the future. Indeed as we complete this book, new developments - which unfortunately we have not been able to include here - have been made on some of the themes described here. Our focus in this book is on the problem of structure in cosmology.

With information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis using a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field and draw upon decades of experience. They have been playing leading roles in international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools. This second edition of Starck and Murtagh's highly appreciated reference again deals with topics that are at or beyond the state of the art. It presents material which is more algorithmically oriented than most alternatives and broaches new areas like ridgelet and curvelet transforms. Throughout the book various additions and updates have been made.