(For more details about my research, see the "Publications" section of my CV page.)
Most of the content of our Universe (about 95%) is in the form of dark matter and dark energy. We can’t see them, but we can infer their presence through their gravitational influence on the motions of stars, the clustering of galaxies, and the expansion of the Universe as a whole. The nature of dark matter and dark energy is an unsolved problem in fundamental physics, and astronomical observations are our primary (and perhaps only!) means of solving this problem experimentally.
The Universe has been expanding and evolving under the influence of dark matter and dark energy since the Big Bang some 13.8 billion years ago. As we look farther out into the Universe, we are also looking back in time. We can trace the history of cosmic evolution by building three-dimensional maps of the large-scale distribution of galaxies, and we can infer the properties of dark matter and dark energy from the effects that they imprint on these maps.
We obtain the first two dimensions of these maps through wide-field imaging surveys of the night sky. The third dimension comes from spectroscopic observations of millions of galaxies and quasars, which allow us to measure the cosmological Doppler shifts (or “redshifts”) indicating how far away these objects are. I am member of the Dark Energy Spectroscopic Instrument (DESI) collaboration that is currently building the largest-ever 3D map of the Universe, which will deliver the most precise constraints ever on the nature of dark energy.
On the scale of individual galaxies, one of our most powerful tools for studying dark matter is the phenomenon of strong gravitational lensing, which happens when two distant galaxies happen by chance to fall along the same line of sight. The gravity of the stars and dark matter in the more nearby galaxy distorts the image of the more distant galaxy dramatically, and we can infer the more nearby galaxy’s mass by analyzing this effect. My collaborators and I have pioneered methods for discovering strong lenses in spectroscopic surveys, along with techniques for measuring the dark matter within galaxies using Hubble Space Telescope images of strong lenses.
The most massive galaxies in the Universe are the end states of a complex process of galaxy formation and merging over cosmic time. They obey empirical scaling relations that encode the details of that evolutionary history. Large spectroscopic surveys observe massive galaxies by the thousands, providing a unique opportunity to measure their population demographics. My collaborators and I have developed hierarchical Bayesian inference methods to study massive galaxy populations in this "large-N, low signal-to-noise" regime.
The mystery of dark matter and dark energy has motivated us to survey the Universe at unprecedented scales. This has ushered in an era of “big-data astronomy”, which requires us to use new algorithms, software automation, and advanced statistical methods to make discoveries and extract knowledge from data sets that are too large for the traditional “by-hand” methods of astronomical data analysis. To meet this challenge, my collaborators and I have developed and deployed new algorithms for precision data calibration, automated classification and analysis, and astronomical data mining.
The era of big-data astronomy has created an explosion of opportunities for participation in forefront research. When released publicly, large astronomical survey data sets offer nearly unlimited possibilities for making new discoveries that were not anticipated by the original survey team. As Principal Data Scientist for the Sloan Digital Sky Survey from 2012-2015, I worked with the SDSS data team to extend and expand the project’s legacy of enabling data-driven discovery through the public release of science-ready data products.
Since December 2015 I have led the Community Science and Data Center (CSDC), which is now a part of NSF’s NOIRLab, the recently created US national laboratory for ground-based optical and infrared astronomy. CSDC is a team of scientists, software engineers, data analysts, and administrative professionals who are focused on making data-intensive astronomy accessible to the broadest possible community of researchers worldwide.
Copyright © 2022 Adam S. Bolton - All Rights Reserved.