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R. Somerville

Publications and source records attributed to R. Somerville.

20 records · Page 2Linked to original sources

The Evolution of Early-type Field Galaxies Selected from a NICMOS Map of the Hubble Deep Field North

The redshift distribution of well-defined samples of distant early-type galaxies offers a means to test the predictions of monolithic and hierarchical galaxy formation scenarios. NICMOS maps of the entire Hubble Deep Field North in the F110W and F160W filters, when combined with the available WFPC2 data, allow us to calculate photometric redshifts and determine the morphological appearance of galaxies at rest-frame optical wavelengths out to z ~ 2.5. Here we report results for two subsamples of early-type galaxies, defined primarily by their morphologies in the F160W band, which were selected from the NICMOS data down to H160_{AB} < 24.0. The observed redshift distributions of our two early-type samples do not match that predicted by a monolithic collapse model, which shows an overabundance at z > 1.5. A hierarchical formation model better matches the redshift distribution of the HDF-N early-types at z > 1.5, but still does not adequately describe the observed early-types. The hierarchical model predicts significantly bluer colors on average than the observed early-type colors, and underpredicts the observed number of early-types at z < 1. [abridged]

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Objective Classification of Galaxy Spectra using the Information Bottleneck Method

A new method for classification of galaxy spectra is presented, based on a recently introduced information theoretical principle, the `Information Bottleneck'. For any desired number of classes, galaxies are classified such that the information content about the spectra is maximally preserved. The result is classes of galaxies with similar spectra, where the similarity is determined via a measure of information. We apply our method to approximately 6000 galaxy spectra from the ongoing 2dF redshift survey, and a mock-2dF catalogue produced by a Cold Dark Matter-based semi-analytic model of galaxy formation. We find a good match between the mean spectra of the classes found in the data and in the models. For the mock catalogue, we find that the classes produced by our algorithm form an intuitively sensible sequence in terms of physical properties such as colour, star formation activity, morphology, and internal velocity dispersion. We also show the correlation of the classes with the projections resulting from a Principal Component Analysis.

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