Mapping the Universe with the Lyman alpha forest
Lead Research Organisation:
UNIVERSITY COLLEGE LONDON
Department Name: Physics and Astronomy
Abstract
The study of the large scale structure of the Universe can answer some of the most important and challenging questions in physics: the nature of the dark energy causing the acceleration of the Universe; the inflationary origin of the density fluctuations; the physical properties of the dark matter component; and the number of neutrino species and their mass. A novel and exciting approach is to study this structure by looking at the distribution of intergalactic gas as seen in absorption features in the spectra of very high redshift quasars, a phenomenon known as the Lyman alpha forest. The goal of this project is to develop a theoretical framework to model the clustering of the Lyman alpha forest, and compare the predictions to recent and future observations from different international surveys (mainly BOSS and DESI) to provide new insights on dark energy, the nature of dark matter, the mass of the neutrinos and the initial stages of the Universe.
Organisations
People |
ORCID iD |
Andreu Font-Ribera (Primary Supervisor) | |
James Farr (Student) |
Publications

Du Mas Des Bourboux H
(2020)
The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations with Lya Forests
in The Astrophysical Journal

Farr J
(2020)
Optimal strategies for identifying quasars in DESI
in Journal of Cosmology and Astroparticle Physics

Farr J
(2020)
LyaCoLoRe : synthetic datasets for current and future Lyman-a forest BAO surveys
in Journal of Cosmology and Astroparticle Physics
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/R505183/1 | 30/09/2017 | 29/09/2021 | |||
1923402 | Studentship | ST/R505183/1 | 30/09/2017 | 29/09/2020 | James Farr |
Description | Through this award, I developed new software to generate synthetic datasets for testing analysis pipelines. This has already been used in one major analysis, and will be used extensively in the next 5 years as the Dark Energy Spectroscopic Instrument (DESI) begins to make measurements. Additionally, I developed methods to make best use of classification tools in DESI. This will be used in the near future to improve DESI's data pipeline. |
Exploitation Route | The outcomes of this funding will continue to be developed by members of DESI in the coming years. |
Sectors | Other |