Trevisan, M | Search NASA

DOE OSTI2012

CONSTRAINTS ON FEEDBACK PROCESSES DURING THE FORMATION OF EARLY-TYPE GALAXIES

Galaxies are found to obey scaling relations between a number of observables. These relations follow different trends at the low- and high-mass ends. The processes driving the curvature of scaling relations remain uncertain. In this Letter, we focus on the specific family of early-type galaxies, deriving the star formation histories of a complete sample of visually classified galaxies from Sloan Digital Sky Survey DR7 over the redshift range 0.01 < z < 0.025, covering a stellar mass interval from 10{sup 9} to 3 Multiplication-Sign 10{sup 11} M{sub Sun }. Our sample features the characteristic 'knee' in the surface brightness versus mass distribution at M{sub *} {approx} 3 Multiplication-Sign 10{sup 10} M{sub Sun} . We find a clear difference between the age and metallicity distributions of the stellar populations above and beyond this knee, which suggests a sudden transition from a constant, highly efficient mode of star formation in high-mass galaxies, gradually decreasing toward the low-mass end of the sample. At fixed mass, our early-type sample is more efficient in building up the stellar content at early times in comparison to the general population of galaxies, with half of the stars already in place by redshift z {approx} 2 for all masses. The metallicity-age trend in low-mass galaxies is not compatible with infall of metal-poor gas, suggesting instead an outflow-driven relation.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2011

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 {<=} r {<=} 21 (85.2%) and r {>=} 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 {<=} r {<=} 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (>80%) while simultaneously achieving low contamination ({approx}2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 {<=} r {<=} 21.

79 ASTRONOMY AND ASTROPHYSICS↗