no significant impact on our conclusions.

Classification using PCA supercolours
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We classify galaxies using a Principal Component Analysis (PCA) method applied to the broad-band photometric data, using the techniques outlined in Wild et al. (2014; hereafter W14). The aim of the PCA analysis is to describe the variation in galaxy SEDs using the linear combination of only a small number of components. The components are derived using a library of spectral synthesis models from BC03, using a wide range of stochastic star formation histories, metallicities, and dust-reddening. We found that only three principal components (effectively low-resolution “eigenspectra”) are required, in linear combination, to account for $>$99.9% of the variance in photometric SEDs. The amplitude of each component defines a “supercolour”, analogous to a traditional colour but defined using all available photometric bands. Supercolours allow the comparison of SEDs without the need for model fitting, and galaxies with extreme properties are free to have colours that differ substantially from any of the input model components.

Using the supercolour technique, we separated the UDS galaxy population into three categories; passive galaxies (with low specific star-formation rates), star-forming galaxies, and post-starburst galaxies. Post-starburst galaxies are identified as a well-defined stream of galaxies 