Large-Scale Structure

When we look out into the Universe, we find many galaxies and dense galaxy clusters which can contain up to around a thousand galaxies. Moreover, we do not see a random distribution of these objects, but rather find that the Universe is very clustered, with some locations having many galaxies and some having very few.

We see this clustering in both data and simulations. Both show that this clustering grows with time due to the attractive force of gravity. Early in its history, the Universe was much more smooth in its matter distribution. We have strong evidence that most of the matter in the Universe is actually dark matter, meaning the galaxies we see are only part of the picture of how matter is distributed in the Universe. Galaxies are believed to form in the largest concentrations of dark matter known as dark matter halos.

Dark Energy

Large-scale structure measurements play a key role in understanding dark energy, or more specifically, what is causing cosmic acceleration. As time goes on, gravity makes the Universe more clustered. However, the accelerating expansion of the Universe acts to slow down this process. Measuring what is called the 'growth of structure' across cosmic history thus tells us how strong these competing forces, gravity and cosmic expansion, have been across time. This is important for understanding the cause of cosmic acceleration. The two major types of models for this cause, an otherwise unseen energy filling the Universe we have named 'dark energy' or some type of modification to the currently understood laws of gravity (aka general relativity), in general provide different predictions for how large-scale structure changes over time. By combining measurements of large-scale structure and the expansion history of the Universe, we aim to narrow in on the source cosmic acceleration.

The Dark Energy Survey

Most of my research has been part of the Dark Energy Survey (DES, darkenergysurvey.org). DES is a 5-year photometric survey, collecting images of some 300 million galaxies, galaxy clusters, gravitational lensing signatures, supernovae among several other types of objects. DES studies large-scale structure across cosmic history in a number of different ways. Areas I have been involved with include galaxy clustering, gravitational lensing, and combined probes, where we often combine data from other surveys with data from DES. One example is gravitational lensing as measured in the cosmic microwave background with instruments such as the South Pole Telescope and the Planck Satellite.

Redshifts

Some of my recent work has focused on the estimation of redshifts, a key factor in large-scale structure measurements. Cosmological redshifts measure the expansion rate of the Universe between when light was emitted from a galaxy to present day, which is often over billions of years. Given our already fairly accurate knowledge of the expansion rate of the Universe, a redshift of a galaxy serves to approximately determine how far away it is, and how long ago in time we are observing its light from. Thus, what we usually do is measure large-scale structure as a function of galaxy redshifts, which serves as a proxy for measuring the time-evolution of large-scale structure.

Estimating redshifts from a photometric survey can be tricky. When a spectrum of a galaxy's light is taken, it is usually very simple to see how much that spectrum is redshifted based on various spectral features. With photometry (color band) measurements alone though, there are only 4-5 data points to estimate the redshift with. I work on a couple methods to estimate redshifts in new ways. One method I have worked on extensively is called the 'cross-correlations' or 'clustering-redshifts' method. In this technique, we measure how correlated an 'unknown' sample of galaxies is with other samples of galaxies that have known redshifts. These correlations can infer the redshift distribution of the 'unknown' sample.