Back to Search Start Over

An Algorithm for Reconstructing the Orphan Stream Progenitor with MilkyWay@home Volunteer Computing

Authors :
Shelton, Siddhartha
Newberg, Heidi Jo
Weiss, Jake
Bauer, Jacob S.
Arsenault, Matthew
Widrow, Larry
Rayment, Clayton
Desell, Travis
Judd, Roland
Magdon-Ismail, Malik
Mendelsohn, Eric
Newby, Matthew
Rice, Colin
Szymanski, Boleslaw K.
Thompson, Jeffery M.
Varela, Carlos
Willett, Benjamin
Ulin, Steve
Newberg, Lee
Publication Year :
2021

Abstract

We have developed a method for estimating the properties of the progenitor dwarf galaxy from the tidal stream of stars that were ripped from it as it fell into the Milky Way. In particular, we show that the mass and radial profile of a progenitor dwarf galaxy evolved along the orbit of the Orphan Stream, including the stellar and dark matter components, can be reconstructed from the distribution of stars in the tidal stream it produced. We use MilkyWay@home, a PetaFLOPS-scale distributed supercomputer, to optimize our dwarf galaxy parameters until we arrive at best-fit parameters. The algorithm fits the dark matter mass, dark matter radius, stellar mass, radial profile of stars, and orbital time. The parameters are recovered even though the dark matter component extends well past the half light radius of the dwarf galaxy progenitor, proving that we are able to extract information about the dark matter halos of dwarf galaxies from the tidal debris. Our simulations assumed that the Milky Way potential, dwarf galaxy orbit, and the form of the density model for the dwarf galaxy were known exactly; more work is required to evaluate the sources of systematic error in fitting real data. This method can be used to estimate the dark matter content in dwarf galaxies without the assumption of virial equilibrium that is required to estimate the mass using line-of-sight velocities. This demonstration is a first step towards building an infrastructure that will fit the Milky Way potential using multiple tidal streams.<br />Comment: 25 pages, 5 figures, to be submitted to ApJS

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2102.07257
Document Type :
Working Paper