Research & Publications
Using galaxy clusters as a cosmological laboratory.
The Velocity Distribution Function of Galaxy Clusters as a Cosmological Probe.
Michelle Ntampaka, Hy Trac, Jessi Cisewski, and Layne C. Price.
2017 Astrophysical Journal, 835, 1.
We present a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements...
Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning.
Michelle Ntampaka, Hy Trac, Dougal J. Sutherland, Sebastien Fromenteau, Barnabas Poczos, and Jeff Schneider.
2016 Astrophysical Journal, 831, 2.
We study dynamical mass measurements of galaxy clusters contaminated by interlopers, and show that a modern machine learning algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach...
A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters.
Michelle Ntampaka, Hy Trac, Dougal J. Sutherland, Nicholas Battaglia, Barnabas Poczos, and Jeff Schneider.
2015 Astrophysical Journal, 803, 50.
We present a modern machine learning approach for cluster dynamical mass measurements that is a factor-of-two improvement over using a conventional scaling relation...
A First Look at Creating Mock Catalogs with Machine Learning Techniques.
Xiaoying Xu, Shirley Ho, Hy Trac, Jeff Schneider, Barnabas Poczos, and Michelle Ntampaka.
2013 Astrophysical Journal, 772, 147.
We investigate machine learning techniques for predicting the number of galaxies that occupy a halo, given the halo's properties...