MilkyWay@home

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MilkyWay@home image

MilkyWay@home is a volunteer distributed computing project based at Rensselaer Polytechnics Institute that needs your help to optimize N-body simulations of dwarf galaxies around the Milky Way.

Milky Way image
A dwarf galaxy being disrupted by the Milky Way's gravity (the Milky Way is not shown, and would be at the center of the picture)

Why MilkyWay@home?

The N-body project on MilkyWay@home simulates dwarf galaxies colliding with (or being disrupted by) the Milky Way. The result from this project will give insight on how dwarf galaxies interact with the Milky Way given certain parameters and how those results look when compared to the data observed today.

Goal

The goal of the N-body project is to match simulated dwarf galaxies to real dwarf galaxy data, and thereby constrain the properties of the Milky Way galaxy's gravitational potential (as well as the properties of the dwarf galaxies).

Methods

MilkyWay@home studies the history of our galaxy by analyzing the stars in the Milky Way galaxy's Galactic Halo. This includes searching for elusive dark matter. This research is done by mapping structures of stars orbiting the Milky Way - many these structures are actually "tidal debris streams," or dwarf galaxies that are being pulled apart by our Galaxy's superior gravitational field. The orbits, shapes, and compositions of these dwarf galaxies provide vital clues to the history of our Galaxy, as well as to the distribution of dark matter. Additionally, MilkyWay@home has recently started developing the "N-body" sub-project, which creates simulated dwarf galaxies and "shoots" them into the Milky Way's gravitational field. We allow the simulated dwarf galaxy's initial conditions to vary until the final simulated dwarf matches what we see in actual halo structures. In other words, we are trying to match dwarf galaxy models to real data, in order to learn more about what is (and what isn't) possible for our Galaxy. For both projects, we use data from the Sloan Digital Sky Survey.

Using stellar data from the Sloan Digital Sky Survey (SDSS) and the Dark Energy Camera (DEC), we were able to use MilkyWay@home's N-body project to generate a mass estimate of the Orphan-Cehnab's original progenitor dwarf galaxy, the first time such an estimate has ever been made from tidal debris alone. The Orphan-Chenab Stream (OCS) is a tidal stream that was discovered in 2006 while examining the Sagittarius Stream. Because no progenitor core could be detected within the stream, it was originally named the 'Orphan Stream'. However, in 2018, the southern half of the stream was detected and named Chenab. Thus, the stream was renamed 'Orphan-Chenab'.

We found the total mass of the OCS's progenitor to be roughly 2 x 107 solar masses, with a mass-to-light ratio of 73.5 (about 98.6% dark matter). This is interesting because other mass estiamtes of the OCS progenitor placed this value somewhere between 108 and 109 solar masses. This is likely because these mass estimates used velocity dispersions for their calculation and assumed the system to be in equilibrium. However, we have also shown that the OCS has an unbound and heavily disrupted progenitor, shattering any assumption of dynamic equilibrium. We also find that the majority of the OCS's mass (especially its dark matter) resides within the tails of the stream, making them ideal candidates for indirect dark matter detection experiments.

It should still be noted, however, that this measurement is incomplete as our optimizations using MilkyWay@home require an in-depth analysis of the sources of systematic error, such as the accuracy of our Milky Way gravitational potential and the validity of our progenitor models. We also need to include the effects of the Large Magellanic Cloud as it was shown in 2019 to have a measurable effect on the Southern tail of the OCS (Erkal et. al. 2019). In future work, we plan on quantifying this systematic error as the effects of different galactic models on our final fitted mass.

Project team / Sponsors

Kevin Roux. Tom Donlon. Eric Mendelsohn. Matthew. Matt Arsenault. Jake Weiss. Rensselaer Polytechnics Institute.

Project support

This material is based upon work supported by the National Science Foundation under Grant Numbers 0612213, 0607618, 0448407, 1009670, 1615688, and 1908653.

  1. Charting the Structure of the Milky Way Stellar Halo and Disk, NSF AST Grant #1615688, 09/15/2016 - 08/31/2019, Principal Investigator: Heidi Jo Newberg
  2. Stars and Dark Matter in the Halo of the Milky Way, NSF AST Grant # 1009670, started 09/15/2010. Principal Investigator: Heidi Newberg.
  3. Data-Driven Discovery of the Milky Way Origin and Evolution from the Sloan Digital Sky Survey, NSF IIS Grant #0612213, started 07/26/2006. Principal Investigators: Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos Varela.
  4. Revealing the Structure of the Galactic Halo through Statistical Analysis - Middle School Teacher Training, NSF AST Grant #0607618, started 07/15/2006. Principal Investigators: Heidi Newberg, Malik Magdon-Ismail.
  5. Middleware and Programming Technology for Grid Computing, NSF CAREER Grant #0448407, started 01/21/2005. Principal Investigator: Carlos Varela.

Scientific publications

  1. Eric J. Mendelsohn. Using MilkyWay@home to Measure the Mass of the Orphan-Chenab Stream Progenitor Dowarf Galaxy. PhD thesis. Rensselaer Polytechnic Institute, 2022.
  2. Eric J. Mendelsohn, Heidi Jo Newberg, Siddhartha Shelton, Lawrence M. Widrow, Jeffery M. Thompson, Carl J. Grillmair. Estimate of the Mass and Radial Profile of the Orphan-Chenab Stream's Dwarf-galaxy Progenitor Using MilkyWay@home. The Astrophysical Journal, 2022.
  3. Siddhartha Shelton, Heidi Jo Newberg, Jake Weiss, Jacob S. Bauer, Matthew Arsenault, Larry Widrow, Clayton Rayment, Travis Desell, Roland Judd, Malik Magdon-Ismail, Eric Mendelsohn, Matthew Newby, Colin Rice, Boleslaw K. Szymanski, Jeffery M. Thompson, Carlos Varela, Benjamin Willett, Steve Ulin, Lee Newberg. An Algorithm for Reconstructing the Orphan Stream Progenitor with MilkyWay@home Volunteer Computing. The Astrophysical Journal, 2021.
  4. Heidi Jo Newberg, Siddhartha Shelton, Eric Mendelsohn, Jake Weiss, Matthew Arsenault, Jacob S. Bauer, Travis Desell, Roland Judd, Malik Magdon-Ismail, Lee A. Newberg, Matthew Newby, Clayton Rayment, Colin Rice, Boleslaw K. Szymanski, Jeffery M. Thompson, Steve Ulin, Carlos Varela, Lawrence M. Widrow, Benjamin A. Willett. Streams and the Milky Way Dark Matter Halo. International Astronomical Union, 2020.
  5. Siddhartha Shelton. Constraining Dwarf Galaxy Properties Using Tidal Streams. PhD thesis. Rensselaer Polytechnic Institute, 2018.
  6. Jake Weiss. The Stellar Density of the Major Substructure in the Milky Way Halo. PhD thesis. Rensselaer Polytechnic Institute, 2018.
  7. Jake Weiss, Heidi Jo Newberg, Travis Desell. A Tangle of Stellar Streams in the North Galactic Cap. The Astrophysical Journal, 2018.
  8. Jake Weiss, Heidi Jo Newberg, Matthew Newby, Travis Desell. Fitting the Density Substructure of the Stellar Halo with MilkyWay@home. The Astrophysical Journal, 2018.
  9. Julie Dumas, Heidi Jo Newberg, Bethany Niedzielski, Adam Susser, Jeffery M. Thompson, Jake Weiss, Kim M. Lewis. Testing the Dark Matter Caustic Theory Against Observations in the Milky Way. The Astrophysical Journal, 2015.
  10. Samantha Scibelli, Heidi Jo Newberg,  Jeffrey  L. Carlin, Brian Yanny. Census of Blue Stars in SDSS DR8. The Astrophysical Journal Supplement, Volume 215, Issue 2, pages 25 pp, 2014.
  11. Yan Xu, Heidi Jo Newberg. Exploration of Galactic Structures Beyond the Sun Toward the Anti-Center of the Milky Way. Proceedings of the International Astronomical Union, IAU Symposium, Volume 298, pp. 450-450, 2014
  12. Heidi Jo Newberg, Matthew Newby, Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela. MilkyWay@home: Harnessing Volunteer Computers to Constrain Dark Matter in the Milky Way. In the Proceedings of the International Astronomical Union, pages 98-104, 2014
  13. Matthew T. Newby. The Sagittarius Tidal Stream and the Shape Of The Galactic Stellar Halo. PhD thesis. Rensselaer Polytechnical Institute. 2013
  14. Matthew Newby, Nathan Cole, Heidi Newberg, Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Benjamin Willett, and Brian Yanny. Spatial Characterization of the Sagittarius Dwarf Galaxy Tidal Tails. Astronomical Journal, 145(163), May 2013.
  15. Benjamin Arthur Willett Simultaneous Orbit Fitting of Stellar Streams: Constraining the Galactic Dark Matter Halo. PhD thesis . Rensselaer Polytechnic Institute, 2010
  16. Travis Desell, David P. Anderson, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos A. Varela. An Analysis of Massively Distributed Evolutionary Algorithms. In the Proceedings of the 2010 IEEE Congress on Evolutionary Computation (IEEE CEC 2010), Barcelona, Spain, July 2010. To Appear.
  17. Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos A. Varela, Heidi Newberg and David P. Anderson. Validating Evolutionary Algorithms on Volunteer Computing Grids. In the Proceedings of the 10th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS 2010), Amsterdam, Netherlands, June 2010. To Appear.
  18. Nathan Cole, Travis Desell, Daniel Lombranaa Gonzalez, Francisco Fernandez de Vega, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos Varela. Evolutionary Algorithms on Volunteer Computing Platforms: The MilkyWay@Home Project. In F. Fernandez de Vega, E. Cantu-Paz (Eds.): Parallel and Distributed Computational Intelligence, SCI 269, pp 63-90. Springer-Verlag Berlin Heidelberg. 2010
  19. Travis Desell. Asynchronous Global Optimization for Massive-Scale Computing. PhD thesis. Rensselaer Polytechnic Institute. 2009
  20. Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Heidi Newberg and Nathan Cole. Robust Asynchronous Optimization for Volunteer Computing Grids. In the 5th IEEE International Conference on e-Science (eScience2009), Oxford, UK, pages 263-270, December 2009.
  21. Travis Desell, Anthony Waters, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Matthew Newby, Heidi Newberg, Andreas Przystawik and Dave Anderson. Accelerating the MilkyWay@Home volunteer computing project with GPUs. In 8th International Conference on Parallel Processing and Applied Mathematics (PPAM 2009), Wroclaw, Poland, September 2009. To appear.
  22. Nathan Cole. Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. PhD thesis. Rensselaer Polytechnic Institute. 2009.
  23. Nathan Cole, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Carlos Varela, and Boleslaw Szymanski. A Study of the Sagittarius Tidal Stream Using Maximum Likelihood. Astronomical Data Analysis Software and Systems XVIII, 411: 221, 2009.
  24. Nathan Cole, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Kristopher Dawsey, Warren Hayashi, Jonathan Purnell, Boleslaw Szymanski, Carlos A. Varela, Benjamin Willett, and James Wisniewski. Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. Astrophysical Journal, 683:750-766, 2008.
  25. Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. An Asynchronous Hybrid Genetic-Simplex Search for Modeling the Milky Way Galaxy using Volunteer Computing. In Genetic and Evolutionary Computation Conference (GECCO 2008), Atlanta, Georgia, pages 921-928, July 2008.
  26. Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. Asynchronous Genetic Search for Scientific Modeling on Large-Scale Heterogeneous Environments. In Proceedings of the 17th International Heterogeneity in Computing Workshop (HCW/IPDPS'08), Miami, FL, pages 12pp, April 2008. IEEE.
  27. Boleslaw Szymanski, Travis Desell, and Carlos A. Varela. The Effect of Heterogeneity on Asynchronous Panmictic Genetic Search. In Proc. of the Seventh International Conference on Parallel Processing and Applied Mathematics (PPAM'2007), LNCS, Gdansk, Poland, September 2007.
  28. Travis Desell, Nathan Cole, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski, and Carlos A. Varela. Distributed and Generic Maximum Likelihood Evaluation. In 3rd IEEE International Conference on e-Science and Grid Computing (eScience2007), Bangalore, India, pages 337-344, December 2007. Best paper finalist.
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