Advanced Statistical Methods for Astrophysical Probes of Cosmology
Seiten
2013
|
2013
Springer Berlin (Verlag)
978-3-642-35059-7 (ISBN)
Springer Berlin (Verlag)
978-3-642-35059-7 (ISBN)
This book explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations, in particular dark energy from observations of supernovae type Ia.
This thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations.Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how good a model is.Supernovae type Ia were the first astrophysical observations to indicate the late time acceleration of the Universe - this work presents a detailed Bayesian Hierarchical Model to infer the cosmological parameters (in particular dark energy) from observations of these supernovae type Ia.
This thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations.Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how good a model is.Supernovae type Ia were the first astrophysical observations to indicate the late time acceleration of the Universe - this work presents a detailed Bayesian Hierarchical Model to infer the cosmological parameters (in particular dark energy) from observations of these supernovae type Ia.
Marisa Cristina March is currently a Postdoctoral Research Fellow at the Univeristy of Sussex, and was formerly a postgraduate cosmology student at Imperial College working with Dr Roberto Trotta, in the field of dark energy science.
Introduction.- Cosmology background.- Dark energy and apparent late time acceleration.- Supernovae Ia.- Statistical techniques.- Bayesian Doubt: Should we doubt the Cosmological Constant?.- Bayesian parameter inference for SNeIa data.- Robustness to Systematic Error for Future Dark Energy Probes.- Summary and Conclusions.- Index.
| Erscheint lt. Verlag | 12.1.2013 |
|---|---|
| Reihe/Serie | Springer Theses |
| Zusatzinfo | XX, 180 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 425 g |
| Themenwelt | Naturwissenschaften ► Physik / Astronomie ► Astronomie / Astrophysik |
| Naturwissenschaften ► Physik / Astronomie ► Relativitätstheorie | |
| Schlagworte | Baryon Acoustic Oscillations • Bayesian Hierarchical Model • Bayesian model selection • Bayesian Statistics • Cosmological Model Selection • Cosmological Parameters • Dark Energy Parameters • Expansion of the Universe • Fisher Forecasts • Statistical Models for Observational Cosmology • supernovae type Ia |
| ISBN-10 | 3-642-35059-3 / 3642350593 |
| ISBN-13 | 978-3-642-35059-7 / 9783642350597 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Grundlagen, Anwendungen in Astrophysik und Kosmologie sowie …
Buch | Softcover (2022)
Springer Spektrum (Verlag)
CHF 69,95
die Geschichte und Erforschung unserer Galaxie
Buch | Hardcover (2023)
C.Bertelsmann (Verlag)
CHF 40,80
Von Hubble-, James-Webb- und anderen Großteleskopen bis zu …
Buch | Softcover (2024)
Springer (Verlag)
CHF 32,15
