COSFAST · Fast algorithms in cosmology and the study of dark energy
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2006-01-01 → 2007-12-31
- EU contribution
- €80,000
- Participants
- 1
- Scheme
- IRG
Lines connect the coordinator with its partners.
Results in brief
Final Activity Report Summary - COSFAST (Fast algorithms in cosmology and the study of dark energy)
This IRG grant was awarded to Prof. Bob Nichol to aid in his return from the Unites States to Europe. He is now a permanent staff member at the Institute of Cosmology and Gravitation at the University of Portsmouth. This grant was to help him in his continued multi-disciplinary research into developing new and efficient computational algorithms for the application to massive cosmological datasets. The funding was used to partially support Edd Edmondson, a postdoctoral researcher at the University of Portsmouth. During the last two years of this IRG grant, Bob and Edd have published important research papers including: (1) Bryan et al. (2007), which used a combination of new statistical methodology (non-parametric fitting) and advanced parameter searching techniques to determine the best cosmological parameters based solely on the WMAP dataset. This paper built upon earlier work by Bob in a paper entitled 'Nonparametric inference for the cosmic microwave background' published in 2005 in Statistical Science. (2) In Edmondson et al. (2006; Mon. Not. Roy. Astron. Soc. 371, 1693-1704), we describe an optimum Bayesian method for extracting redshift distributions from photometric data. Overall, the new techniques developed during this grant will become important as the amount of astronomical data increases with new survey telescopes like the ESO VST and VISTA.
Data: CORDIS, © European Union
Project objective
The full exploitation of science data is being impeded by statistical and computational intractability. Cosmologists are now deluged by large, complex datasets, and the scientific value of these data is presently lessened by the laborious efforts needed to analyse them. The primary goal of this project is to tackle this problem through the combination of new computer science and statistics by developing, and deploying on the Grid, efficient algorithms for the analysis of massive cosmological datasets e.g. fast, tree-based versions of the n-point correlation functions and Kernel density estimation. A secondary goal is the use of these algorithms to obtain more precise measurements of the dark energy content of the Universe, particularly as a function of red shift. Such measurements will provide critical constraints on the origin of dark energy: one of the biggest conundrums in science.This will be achieved using these new catalogues of galaxies and quasars from the completed Sloan Digital Sky Survey. This pro ject will be done in collaboration with the US Virtual Observatory, UK AstroGrid, the department of the Institute of Cosmology and Gravitation (ICG) and the Pittsburgh Computational AstroStatistics (PiCA) group. Such multi-disciplinary research facilitates new fundamental physics and demonstrates the synergy between statistics, computer science and astrophysics. The algorithms and techniques developed during this project will also be invaluable to other areas of science and industry e.g. biology, manufacturing.Dr. Robert Nichol is a recognized leader in the development of data-mining algorithms for massive astronomical datasets. He returns to the UK (ICG) after 12 years in the US. The ICG has offered him a permanent position, and is committed to support the project for at least 3 years. Dr Nichol will bring a new aspect of high-tech training to researchers at the ICG and throughout Europe, as well as fostering new US-European collaborations.
Original text from CORDIS.
Participants
- UNIVERSITY OF PORTSMOUTH HIGHER EDUCATION CORPORATION · PORTSMOUTHCoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union