Data Analysis in Cosmology [electronic resource] / edited by Vicent J. Martinez, Enn Saar, Enrique Martinez Gonzales, Maria Jesus Pons-Borderia.

Contributor(s): Martinez, Vicent J [editor.] | Saar, Enn [editor.] | Gonzales, Enrique Martinez [editor.] | Pons-Borderia, Maria Jesus [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Physics ; 665Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: XII, 636 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540447672Subject(s): Physics | Relativity (Physics) | Statistics | Physics | Relativity and Cosmology | Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences | Numerical and Computational MethodsAdditional physical formats: Printed edition:: No titleOnline resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
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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.

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.

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