DIRAC Researcher, Gwendolyn Eadie, published a paper in the Astrophysical Journal.
Published on September 24, 2018.
Estimating the Milky Way’s Mass via Hierarchical Bayes: A Blind Test on MUGS2 Simulated Galaxies
In a series of three papers, Eadie et al. developed a hierarchical Bayesian method to estimate the Milky Way Galaxy’s mass given a physical model for the potential, a measurement model, and kinematic data of test particles such as globular clusters (GCs) or halo stars in the Galaxy’s halo. The Galaxy’s virial mass was found to have a 95% Bayesian credible region (c.r.) of (0.67, 1.09) × 1012 . In the present study, we test the hierarchical Bayesian method against simulated galaxies created in the McMaster Unbiased Galaxy Simulations 2 (MUGS2), for which the true mass is known. We estimate the masses of MUGS2 galaxies using GC analogs from the simulations as tracers. The analysis, completed as a blind test, recovers the true M 200 of the MUGS2 galaxies within 95% Bayesian c.r. in 8 out of 18 cases. Of the 10 galaxy masses that were not recovered within the 95% c.r., a large subset have posterior distributions that occupy extreme ends of the parameter space allowed by the priors. A few incorrect mass estimates are explained by the exceptional evolution history of the galaxies. We also find evidence that the model cannot describe both the galaxies’ inner and outer structure simultaneously in some cases. After removing the GC analogs associated with the galactic disks, the true masses were found more reliably (13 out of 18 were predicted within the c.r.). Finally, we discuss how representative the GC analogs are of the real GC population in the Milky Way.
DIRAC Institute has the 1st Astronomy Open-source Sprint, Sep 28, 2018 at the University of Washington.
Science has become a big-data endeavor. But scientists are not universally adept in “data science” — the computing and statistical skillsets needed to handle, sort, analyze and draw conclusions from big data. The shortage of know-how in data science can hamper research, medicine and even private industry
A new paper led by Daniela Huppenkothen, Associate Director of DiRAC, was just published in the Proceedings of the National Academy of Sciences on how we can learn these skills by working collaboratively. With a team of researchers from the University of Washington, New York University and the University of California, Berkeley she developed an interactive workshop in data science for researchers at multiple stages of their careers. The course format, called “hack week,” blends elements from both traditional lecture-style pedagogy with participant-driven projects. The most recent was a neuroscience-themed event held in July on the UW campus organized by Ariel Rokem, a data scientist with the UW eScience Institute. As the team reports in a their paper published Aug. 20, participants rated the hack weeks as opportunities to learn about new concepts, foster new connections, share data openly, and develop skills and work on problems that will positively affect their day-to-day research lives.
Read more about this in the full UW press release
When: August 3, 2018 @ 3:00 pm
Where: PAB, WRF Data Science Studio, 6th floor
David A van Dyk, Statistics Section, Department of Mathematics, Imperial College London
Quantifying Discovery in Astro/Particle Physics: Frequentist and Bayesian Perspective
DIRAC Institute is hosting the 1st LSST Solar System Readiness Sprint, July 10-12, 2018 at the University of Washington. This is a LSST Solar System Science collaboration workshop to begin getting ready for LSST solar system science.
Live coverage is available here.
Astronauts, astronomers, scientists, students, teachers, and interested citizens around the world are coming together at this very moment to learn about and discuss asteroids.
UW is participating in Asteroid Day, a global day of education to help protect Earth from potentially hazardous asteroid. The movie below shows how UW LSST and DIRAC’s astronomical software group is assisting that effort by making the LSST an unprecedented asteroid discovery machine.
June 27th-29th, 2018
I work on Galactic Archaeology, which is the study of the structure and evolution of the Milky Way. I did my PhD at New Mexico State University working with Jon Holtzman and Jo Bovy with the APOGEE survey, which is an SDSS3 and SDSS4 spectroscopic survey of several hundred thousand red giants across the Milky Way. I spent two years working in Nice at the Observatoire de la Cote d’Azur with the Gaia-ESO and AMBRE projects, which have spectroscopic observations of tens of thousands of stars throughout the Galaxy.
Currently, I am an ASTRO 3D fellow working at the University of Sydney with the GALAH Survey. GALAH is a large-scale spectroscopic survey of 500,000 stars throughout the Milky Way, and aims to measure chemical abundances for 30 different elements to map and chemically tag the stellar populations of the Galaxy. In my talk, “Chemical Cartography of the Milky Way”, I will discuss the chemodynamic properties of different stellar populations throughout the disk and how they vary with location.
I attached a figure of some preliminary results from the GALAH survey, showing how the chemical structure of the disk varies from the inner Galaxy to the edge of the disk.
Dr. Eadie completed her doctoral studies at McMaster University under the supervision of Dr. William Harris. In her thesis entitled “Lights in Dark Places: Inferring the Milky Way Mass Profile using Galactic Satellites and Hierarchical Bayes”, she developed a high-level statistical method to derive the mass and mass distribution within astrophysical systems. Mass is a fundamental variable driving the evolution of galaxies like our Milky Way, but it is notoriously difficult to measure due to the fact that it is dominated by the dark matter extending well beyond the visible starlight. This challenge is compounded by incomplete data on the positions and velocities of “tracer particles” such as stars, star clusters and dwarf satellites scattered through the galaxy’s halo. Dr. Eadie developed a powerful Bayesian formulation of the problem combined with Markov Chain Monte Carlo calculations of the relevant parameters in the problem and their probability distributions. Her formulation also included a hierarchical treatment of measurement uncertainties for each tracer. She used it to place a new constraint on the mass profile and total mass of the Milky Way, and it will be a very powerful tool in the exploitation of future very large datasets from the Gaia mission and the Large Synoptic Survey Telescope (LSST). .
CASCA congratulates Dr. Eadie on the receipt of the 2018 Plaskett medal for her groundbreaking work to shed light on the dark side of our Milky Way galaxy and other corners of the Universe.
Read full announcement here.
Dr. Sarah Greenstreet and Bryce Bolin named first senior research fellows.
SILICON VALLEY, CA/SEATTLE WASH. (May 17,2018) — The Asteroid Institute has announced new appointments in the field of planetary defense and asteroids. Dr. Sarah Greenstreet and Bryce Bolin have been selected to serve as the first Senior Research Fellows, under the direction of Dr. Ed Lu, Executive Director of the Asteroid Institute, three time NASA astronaut, former Google executive and co-founder of B612 Foundation. The fellows study the application of new technologies for the discovery, tracking and potential deflection of asteroids.
Read full article here.