92 citations · 800 across the 37 of their papers we have counts for
9 papers · 1 filter
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era
Brian Nord, Andrew J. Connolly, Jamie Kinney +35
The field of astronomy has arrived at a turning point in terms of size and complexity of both datasets and scientific collaboration. Commensurately, algorithms and statistical mode…
Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning
Sheridan B. Green, Michelle Ntampaka, Daisuke Nagai +4
We present a machine learning approach for estimating galaxy cluster masses, trained using both Chandra and eROSITA mock X-ray observations of 2,041 clusters from the Magneticum si…
A Hybrid Deep Learning Approach to Cosmological Constraints From Galaxy Redshift Surveys
Michelle Ntampaka, Daniel J. Eisenstein, Sihan Yuan +1
We present a deep machine learning (ML)-based technique for accurately determining and from mock 3D galaxy surveys. The mock surveys are built from the AbacusCosmos sui…
Astro2020 APC White Paper: The Early Career Perspective on the Coming Decade, Astrophysics Career Paths, and the Decadal Survey Process
Emily Moravec, Ian Czekala, Kate Follette +53
In response to the need for the Astro2020 Decadal Survey to explicitly engage early career astronomers, the National Academies of Sciences, Engineering, and Medicine hosted the Ear…
Cluster Cosmology with the Velocity Distribution Function of the HeCS-SZ Sample
Michelle Ntampaka, Ken Rines, Hy Trac
We apply the Velocity Distribution Function (VDF) to a sample of Sunyaev-Zel'dovich (SZ)-selected clusters, and we report preliminary cosmological constraints in the - co…
Increasing the Discovery Space in Astrophysics - A Collation of Six Submitted White Papers
G. Fabbiano, M. Elvis, A. Accomazzi +46
We write in response to the call from the 2020 Decadal Survey to submit white papers illustrating the most pressing scientific questions in astrophysics for the coming decade. We p…
Astro2020 Science White Paper: The Next Decade of Astroinformatics and Astrostatistics
A. Siemiginowska, G. Eadie, I. Czekala +49
Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quali…
The Role of Machine Learning in the Next Decade of Cosmology
Michelle Ntampaka, Camille Avestruz, Steven Boada +27
In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmologic…
A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters
Matthew Ho, Markus Michael Rau, Michelle Ntampaka +3
We demonstrate the ability of convolutional neural networks (CNNs) to mitigate systematics in the virial scaling relation and produce dynamical mass estimates of galaxy clusters wi…