Data Analysis in Cosmology

2009
ISBN: 978-3-540-23972-7
Verlag: Springer Berlin Heidelberg

Buch, Englisch, Band 665, 636 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 1133 g

Reihe: Lecture Notes in Physics

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.

Zielgruppe

Research

Autoren/Hrsg.

Martinez, Vicent J.

Pons-Borderia, Maria Jesus

Saar, Enn

Gonzales, Enrique Martinez

Fachgebiete

• Naturwissenschaften Astronomie Kosmologie, Urknalltheorie
• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Naturwissenschaften Astronomie Astrophysik
• Naturwissenschaften Physik Angewandte Physik Astrophysik

Inhaltsverzeichnis

Universal Tools.- The Sea of Wavelets.- Fisher Matrices and All That: Experimental Design and Data Compression.- Data Compression, Classification and Parameter Estimation. Methods: Examples from Astronomy.- Statistics of Cosmic Background Radiation.- Cosmic Microwave Background Anisotropies: The Power Spectrum and Beyond.- Cosmic Microwave Background Polarization Analysis.- Diffuse Source Separation in CMB Observations.- Techniques for Compact Source Extraction in CMB Maps.- Determination of Cosmological Parameters from Cosmic Microwave Background Anisotropies.- Cosmic Microwave Background Data Analysis: From Time-Ordered Data to Angular Power Spectra.- Statistics of Large-Scale Structure.- The Large-Scale Structure in the Universe: From Power Laws to Acoustic Peaks.- The Cosmic Web: Geometric Analysis.- Power Spectrum Estimation. I. Basics.- Power Spectrum Estiamtion II. Linear Maximum Likelihood.- to Higher Order Spatial Statistics in Cosmology.- Phase Correlations and Topological Measures of Large-Scale Structure.- Multiscale Methods.- Gaussian Fields and Constrained Simulations of the Large-Scale Structure.- Weak Gravitational Lensing.- Mass Reconstruction from Lensing.