
The earliest galaxies are those that are most distant. Staff associate Dan Kelson is interested in how these ancient relics evolved. The latest generation of telescopes and advanced spectrographs—instruments that analyze light to determine properties of celestial objects—allow astronomers to accurately measure enormous numbers of distant galaxies. Kelson uses the Magellan 6.5-meter telescopes and high-resolution imaging from the Hubble Space Telescope to study distant galaxies.His observations of their masses, sizes and morphologies allow him to directly measure their stars' aging to infer their formation history. Kelson is the principal investigator of the Carnegie-Spitzer-IMACS Redshift Survey of very distant and old galaxies. He is also a senior co-investigator of the Cluster Lensing and Supernova with Hubble Multi-Cycle Treasury Program with the Hubble Space Telescope.
This survey of faint galaxies probes the largest unbiased volume of galaxies in the universe when it was 5-10 billion years ago, targeting galaxies more uniformly and over a wide area of the sky. The survey used 100 nights of Magellan time with the Inamori Magellan Areal Camera and Spectrograph, as well as almost 50 nights of 4-meter time at the National Optical Astronomical Observatories.
In order to better understand how galaxies have been forming and evolving over cosmic time, and to specifically interpret the data gathered in the Carnegie-Spitzer-IMACS Redshift Survey, Kelson has also begun development of a new theoretical framework. Using modern mathematical theorems, one can accurately model the evolution of the ensembles of galaxies over time and in groundbreaking ways that will ultimately allow astronomers, for the first time, to empirically decouple the rates of in situ and ex situ mass growth in galaxies.
Because Kelson's research involves making precision measurements from large quantities of data, he is keenly interested in modern numerical methods and techniques for automating processes for reducing raw data to measured, physical quantities.His work in creating and maintaining the Carnegie Python Distribution currently enables large imaging and spectroscopic datasets to be reduced with little or no human intervention, improving the efficiency of astronomers at Carnegie and around the world.
Kelson received his B.S. in astronomy and physics from the University of Michigan, Ann Arbor, and his Ph.D. in astronomy from UC-Santa Cruz. For more information see http://obs.carnegiescience.edu/users/kelson