Salman Habib - Academia.edu (original) (raw)
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Papers by Salman Habib
Physical review, Feb 2, 1999
arXiv (Cornell University), Mar 14, 2022
American Astronomical Society Meeting Abstracts, Dec 1, 2005
Oxford University Press eBooks, Aug 8, 2018
This article focuses on the use of a Bayesian approach that combines simulations and physical obs... more This article focuses on the use of a Bayesian approach that combines simulations and physical observations to estimate cosmological parameters. It begins with an overview of the Λ-cold dark matter (CDM) model, the simplest cosmological model in agreement with the cosmic microwave background (CMB) and largescale structure analysis. The CDM model is determined by a small number of parameters which control the composition, expansion and fluctuations of the universe. The present study aims to learn about the values of these parameters using measurements from the Sloan Digital Sky Survey (SDSS). Computationally intensive simulation results are combined with measurements from the SDSS to infer about a subset of the parameters that control the CDM model. The article also describes a statistical framework used to determine a posterior distribution for these cosmological parameters and concludes by showing how it can be extended to include data from diverse data sources.
arXiv (Cornell University), Jan 23, 2014
arXiv (Cornell University), Feb 17, 2023
arXiv (Cornell University), Jul 25, 2022
arXiv (Cornell University), Mar 26, 2020
arXiv (Cornell University), Feb 6, 2022
arXiv (Cornell University), Sep 7, 2021
HST Proposal, Aug 1, 2017
Astrophysical Journal Supplement Series, Feb 28, 2022
The Astrophysical Journal, Jun 20, 2019
The Astrophysical Journal, May 29, 2019
Physical review, Feb 2, 1999
arXiv (Cornell University), Mar 14, 2022
American Astronomical Society Meeting Abstracts, Dec 1, 2005
Oxford University Press eBooks, Aug 8, 2018
This article focuses on the use of a Bayesian approach that combines simulations and physical obs... more This article focuses on the use of a Bayesian approach that combines simulations and physical observations to estimate cosmological parameters. It begins with an overview of the Λ-cold dark matter (CDM) model, the simplest cosmological model in agreement with the cosmic microwave background (CMB) and largescale structure analysis. The CDM model is determined by a small number of parameters which control the composition, expansion and fluctuations of the universe. The present study aims to learn about the values of these parameters using measurements from the Sloan Digital Sky Survey (SDSS). Computationally intensive simulation results are combined with measurements from the SDSS to infer about a subset of the parameters that control the CDM model. The article also describes a statistical framework used to determine a posterior distribution for these cosmological parameters and concludes by showing how it can be extended to include data from diverse data sources.
arXiv (Cornell University), Jan 23, 2014
arXiv (Cornell University), Feb 17, 2023
arXiv (Cornell University), Jul 25, 2022
arXiv (Cornell University), Mar 26, 2020
arXiv (Cornell University), Feb 6, 2022
arXiv (Cornell University), Sep 7, 2021
HST Proposal, Aug 1, 2017
Astrophysical Journal Supplement Series, Feb 28, 2022
The Astrophysical Journal, Jun 20, 2019
The Astrophysical Journal, May 29, 2019