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Unveiling galaxy assembly from next generation photometry

Final Report Summary - PHOTO-EV (Unveiling galaxy assembly from next generation photometry)

During this project the fellow began by further exploiting new spectroscopic datasets to explore different aspects of galaxy evolution. Through interaction with the host Stephane Charlot, she has significantly furthered her knowledge of stellar population synthesis models. In particular in Wild et al. (2009, MNRAS, 395, 144) she studied a high redshift spectroscopic dataset to study the formation of red-sequence galaxies through major mergers. Through additional comparisons to results from simulations of galaxy mergers she found that as much as 40% of the growth of red and dead galaxies could occur through the channel of major mergers of gas rich spiral galaxies (Science Objective 1, section B1.1 and Research Training Objective 3, Section B2.1). In Wild, Heckman & Charlot (2010, MNRAS, 405, 933) she exploited the detailed star formation histories available from high quality spectra to time precisely when the black hole starts to accrete following a strong burst of star formation. For the first time a significant offset was seen between the starburst and black hole accretion, which may be due to supernova feedback (Science Objective 2, section B1.1). New statitistical techniques are required to extract more information from large astronomical databases. Budavári, Wild et al. (2009, MNRAS, 394, 1496) developed a new statistical method to deal with spectroscopic data (Methodology objective 3 in B1.2 Research Training Objective 2, Section B2.1).

During the last 6 months of the project, the fellow focussed purely on extracting galaxy properties from photometric datasets, combining the ultraviolet, optical and near infrared data from the three largest surveys of local galaxies: GALEX, SDSS and UKIDSS (Research Training Objective 1, Section B2.1). She developed a novel method to extract dust attenuation curves from pair-matched samples of galaxies (Research Training Objective 2, Section B2.1). This has resulted in a paper, recently sent to collaborators for final comments, measuring the internal dust attenuation of galaxies as a function of their physical properties such as mass normalized star formation rate (Science Objective 3, Section B1.1). These results pave the way for a more detailed analysis of the physical properties of galaxies using broad band photometry, by removing the major uncertainty caused by dust attenuation.

The primary goal of this project was to develop a new statistical approach to derive physical properties of galaxies at any redshift from multi-waveband photometry. Due to the unexpected opportunities provided by recently available spectroscopic datasets, the fellow choose to postpone the exploration of the photometric datasets as described in the PhotoEV project, until the final stage of the fellowship. Finding a solution to the problem of dust attenuation was required before progress could be made on other physical parameters, and this was best achieved with low redshift datasets. In her new position within the high-redshift galaxy evolution group at the University of Edinburgh she will continue working directly on the Science and Methodology Objectives set out in the PhotoEV project.

Alongside the achievements of the Photo-EV project, the fellow continued to contribute significantly to her PhD field studying the association between QSO absorption line systems and nearby galaxy properties. In Menard, Wild et al. (2010, MNRAS, in press) they uncovered a very simple relation linking the strength of absorption lines to the star formation rate of galaxies, over half the age of the Universe. In Chen, Wild et al. (2010, ApJ, 724L, 176) the fellow exploited the new skills gained during the Photo-EV project to combine photometric datasets and measure galaxy properties from broad band photometry, for galaxies in absorber fields. The results showed that the extent of absorption around galaxies scales primarily with galaxy mass, but secondarily with specific star formation rate (sSFR = SFR/stellar mass).