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SUMMARY:DESI and the matter density distribution of the Milky Way from fie
 ld halo stars
DTSTART;VALUE=DATE-TIME:20230320T162500Z
DTEND;VALUE=DATE-TIME:20230320T164000Z
DTSTAMP;VALUE=DATE-TIME:20240704T115719Z
UID:indico-contribution-190@meetings.aip.de
DESCRIPTION:Speakers: Monica Valluri (University of Michigan)\nThe Dark En
 ergy Spectroscopic Instrument (DESI) is currently one of the most powerful
  instruments for wide-field multi-object spectroscopy. The synergy of DESI
  with current (e.g. ESA’s Gaia satellite) and future observing facilitie
 s including the Vera Rubin Observatory’s Legacy Survey of Space and Time
  (LSST)\, and the Nancy Grace Roman Space Telescope’s High Latitude Surv
 ey (HLS) will yield datasets of unprecedented size and coverage that will 
 enable strong constraints on the dark matter distribution in the Milky Way
  (MW) and Local Group galaxies including M31. By the end of 2024 DESI spec
 tra (350nm-980nm) will be obtained for 7.2 million stars in the main progr
 am and for up to another 5 million stars via the backup program (bright/po
 or sky condition) in the MW alone. As of May 2021 (when Kitt Peak shut dow
 n due to the Conteras Fire) DESI had already obtain spectra of 3.6 million
  unique stars. After a brief introduction to the DESI MW survey\, its spec
 troscopic pipeline and what to expect in the early data release (mid 2023)
 \, I will present results from two new modeling codes that have been recen
 tly developed to constrain the mass distribution of the MW that utilize th
 e full 6D as well as 5D phase space data. First I will describe a new B-sp
 line based non-parametric spherical Jeans modeling code (NIMBLE\, Rehemtul
 la et al. 2022). Tests of NIMBLE with mock data from the Latte cosmologica
 l simulations show that it is possible to constraint the mass of the MW ou
 t to ~80kpc with ~15\\% accuracy even in the presence of halo substructure
  and moderate amounts of disequilibrium. I will then show preliminary resu
 lts of the application of NIMBLE to Survey Validation data from DESI. Fina
 lly\, I will describe results from an axisymmetric distribution function f
 itting code (Hattori et al. 2021) and results from its application to Gaia
  RRLyrae data.\n\nhttps://meetings.aip.de/event/20/contributions/190/
LOCATION:Haus H\, Telegrafenberg
URL:https://meetings.aip.de/event/20/contributions/190/
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