A unique K-band selected high-redshift spectroscopic dataset (UDSz) is exploited to gain further understanding of galaxy evolution at z > 1. Acquired as part of an ESO Large Programme, this thesis presents the reduction and analysis of a sample of ∼ 450 deep optical spectra of a random 1 in 6 sample of the KAB < 23, z > 1 galaxy population. Based on the final reduced dataset, spectrophotometric modelling of the optical spectra and multi-wavelength photometry available for each galaxy is performed using a combination of single and dual component stellar population models. The stellarmass and age estimates provided by the spectrophotometric modelling are exploited throughout the rest of the thesis to investigate the evolution of massive galaxies at z > 1. Focusing on a K-band bright (K < 21.5) sub-sample in the redshift range 1.3 < z < 1.5 the galaxy size-mass relation has been studied in detailed. In agreement with some previous studies it is found that massive, old, early-type galaxies (ETGs) have characteristic radii a factor ~- 1.5 − 3.0 smaller than their local counterparts at a given stellar-mass. Due to the potential errors in spectrophotometric estimates of the stellarmasses at high redshift velocity dispersion measurements are derived for a sub-sample of massive ETGs at z > 1.3 in order to calculate dynamical mass estimates. To date, only a handful of objects at z > 1.3 have individual velocity dispersion estimates in the literature. Here the largest single sample (13 objects) of velocity dispersion measurements at high redshift is presented. The results for the sub-sample of objects with dynamical mass estimates confirm the results based on stellar mass estimates that high redshift massive systems are more compact than their local counterparts. The fraction of K-band bright objects at high redshift that are passively evolving is calculated with specific star-formation rates from the UV rest-frame continuum, [OII] emission and 24μm data. It is concluded that ∼ 58 ± 10% of the K < 21.5, 1.3 < z < 1.5 galaxy population is passively evolving. Various photometric techniques for separating star-forming and passively evolving galaxies are assessed by exploiting the accurate spectral types derived for the UDSz spectroscopic sample. Popular highredshift selection techniques are shown to fail to effectively select complete samples of passive objects with low levels of contamination. Using detailed information available for the UDSz dataset, various techniques are optimised and then used to estimate the passive fraction from the full UDS photometric catalog. The passive fraction results from the full photometric catalog are found to agree well with the results derived from the UDSz sample. With the Visible and Infrared Survey Telescope for Astronomy (VISTA) now starting to produce data, the opportunity has been taken to develop high-redshift galaxy population dividers based on the VISTA filters. Using the first data release from the VISTA Deep Extragalactic Observations (VIDEO) survey (VVDS D1 field), the passive fractions of K-band limited samples have been estimated to compare with results derived in the UDS. Within the errors the passive fraction estimates in the UDS and VISTA VVDS D1 field are found to agree reasonably well. Finally, composite spectra are used to study the evolution of various different galaxy sub-samples as a function of redshift, age, stellar-mass and specific star-formation rate. This work produces an remarkably clean result, showing that the massive, absolute Kband bright, passively evolving ETGs are always the oldest population, with ages close to the age of the Universe at z ∼ 1.4. In contrast, the late-type, low-mass, star-forming galaxies are always found to be much younger systems. This result strongly supports the downsizing scenario, in which more massive systems complete their stellar-mass assembly before lower-mass counterparts.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:563745 |
| Date | January 2012 |
| Creators | Pearce, Henry James |
| Contributors | McLure, Ross. : Cirasuolo, Michele. : Dunlop, James |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/6228 |
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