Statistical Physics for Cosmic Structures. 1st ed. 2005

種類:

電子ブック

責任表示:

by Andrea Gabrielli, F. Sylos Labini, Michael Joyce, Luciano Pietronero

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005

著者名:

• Gabrielli, Andrea.
• Sylos Labini, F.
• Joyce, Michael.
• Pietronero, Luciano.
• SpringerLink (Online service)

ISBN:

9783540269991 [3540269991]    

注記:

Statistical Methods -- Uniform and Correlated Mass Density Fields -- The Power Spectrum and the Classification of Stationary Stochastic Fields -- Fractals -- Multifractals and Mass Distributions -- Applications to Cosmology -- Fluctuations in Standard Cosmological Models: A Real Space View -- Discrete Representation of Fluctuations in Cosmological Models -- Galaxy Surveys: An Introduction to Their Analysis -- Characterizing the Observed Distribution of Visible Matter I: The Conditional Average Density in Galaxy Catalogs -- Characterizing the Observed Distribution of Visible Matter II: Number Counts and Their Fluctuations -- Luminosity in Galaxy Correlations -- The Distribution of Galaxy Clusters -- Biasing a Gaussian Random Field and the Problem of Galaxy Correlations -- The Gravitational Field in Stochastic Particle Distributions.
The physics of scale-invariant and complex systems is a novel interdisciplinary field. Its ideas allow us to look at natural phenomena in a radically new and original way, eventually leading to unifying concepts independent of the detailed structure of the systems. The objective is the study of complex, scale-invariant, and more general stochastic structures that appear both in space and time in a vast variety of natural phenomena, which exhibit new types of collective behaviors, and the fostering of their understanding. This book has been conceived as a methodological monograph in which the main methods of modern statistical physics for cosmological structures and density fields (galaxies, Cosmic Microwave Background Radiation, etc.) are presented in detail. The main purpose is to present clearly, to a workable level, these methods, with a certain mathematical accuracy, providing also some paradigmatic examples of applications. This should result in a new and more general framework for the statistical analys

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