Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761491
Title: Mock catalogues for large scale structure surveys and DESI
Author: Smith, Alexander Mark Joseph
ISNI:       0000 0004 7652 3609
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2018
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Abstract:
The upcoming Dark Energy Spectroscopic Instrument (DESI) and Euclid galaxy surveys aim to make the most precise galaxy clustering measurements yet in order to probe the nature of the mysterious dark energy that is thought to make up the majority of the energy density of the Universe today. To reach the required precision, it is essential that the systematics that affect these measurements are understood, which requires realistic mock galaxy catalogues. This thesis focuses on building a mock catalogue for the DESI Bright Galaxy Survey (BGS), and applications of this mock. We outline the methods used to create halo merger trees from N-body and Monte Carlo simulations, which is the first step towards creating a mock catalogue. We show how these methods can be extended beyond ΛCDM to warm dark matter, and show applications. We have developed a halo occupation distribution (HOD) method for creating a BGS mock catalogue from the Millennium-XXL (MXXL) simulation, with galaxies being assigned r-band magnitudes and g-r colours. The mock catalogue is able to reproduce the luminosity function and clustering of the Sloan Digital Sky Survey (SDSS) and Galaxy And Mass Assembly (GAMA) survey at different redshifts. The mock is used to quantify incompleteness in the DESI BGS due to fibre assignment, which depends on the surface density of galaxies, and to assess correlation function correction methods. An inverse pair weighting method is able to provide an unbiased correction on all scales. Finally, we show how the HOD methodology can be extended to construct mock catalogues for Euclid, and other large galaxy surveys.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.761491  DOI: Not available
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