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Discovery of Milky Way Dwarf Galaxies in the Dark Energy Survey

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Discovery of Milky Way Dwarf Galaxies in the Dark Energy Survey Discovery of Milky Way Dwarf Galaxies in the Dark Energy Survey Ting Li on behalf of the DES Collaborations Milky Way Working Group Department of Physics and Astronomy Texas A&M University APS DFP2015 Aug 4, Ann Arbor 1 Credit: Reidar Hahn, Yuanyuan Zhang The formation of Milky Way • ELS Monolithic Collapse Model (top-down) Eggen, Lynden-Bell and Sandage 1962 Milky Way formed from the rapid collapse of a large proto-galac@c nebula • SZ Merger and Accretion Model (bottom-up) Searle & Zinn 1978 Galaxies are built up from merging or accre@ng smaller fragments N-body simula@ons under ΛCDM context 2 Milky Way Satellite Galaxies The Milky Way is surrounded by small satellite galaxies Segue 1 Distances ranges from 25 kpc to a few hundred kpc Luminosities range 7 3 M. Geha from 10 L⊙ to 10 L⊙ The stars are moving too fast to be explained by visible Fornax mass ——— dark matter dominated Astrophysically simple and clean D. Malin 3 30Birth kpc of near-field (Bullock, Geha, Powell) cosmology Dwarf Galaxies as Cosmological Probes • Missing Satellites Problem? • CDM simulations predict thousands of dark matter substructures • Only dozens of dwarf galaxies are found • “Too big to fail” Problem? • Circular velocities of known dwarf galaxies are significantly smaller than predicted by simulations. • Cold dark matter? • Density profile of dark matter halo • Warm dark matter? • cusp vs core problem • Self-interacting dark matter? • Or other? • Gamma rays from dark matter annihilation • Study the property of dark matter particles 4 Finding Milky Way Satellite Galaxies 5 Classical Dwarf Spheroidal Galaxies (dSph) Sculptor ESO/DSS2 6 Milky Way Satellite Galaxies Discovery Timeline 7 4 Finding Milky Way Advances in Astronomy 14 Satellite14 4 Galaxies14 14 Advances in Astronomy 20 kpc 100 kpc 16 45216 WALSH,16 WILLMAN, & JERJEN16 Vol. 137 14 14 Table 1 14 14 Angular Sizes of the Satellites Detected in SDSS 20 kpc 100 kpc Koposov et al. r 18(2008) r 18 r 18 Object r 18 rh (arcmin) Walsh et al. (2009) 16 16 Bootes¨ 12.6 16 16 Bootes¨ II 4.2 Willman et al. (2010)20 20 20 Canes Venatici20 8.9 Canes Venatici II 1.6 Coma Berenices 6.0 r Hercules 8.6 r 22 22 18 22 r 18 22 18 r 18 0.5 010.5 1.5 0.5 010.5 1.5 0.5 010.5 Leo IV1.5 0.5 010.5 2.5 1.5 − − − Leo V− 0.8 g r g r g r Leo Tg r 1.4 − − − Segue 1− 4.4 (a) 20 (b) (c) 20 Ursa Major(d) 11.3 20 20 Color-Magnitude Ursa Major II 16.0 Willman 1 2.3 DomainFigure 1: A color-magnitude (CM) filter used to suppress the noise from foreground stars while preserving the signal from dwarf galaxy stars at a specific distance. (a) and (c) CM filters for22 an old and metal-poor stellar population at22 a distance modulus of 16.5 and 20.0, respectively.22 22 The solid lines show Girardi isochrones for 8 and 14Gyr populations with [Fe/H] 1.5system and to2. avoid3. (b) projection and (d) Theseeffects. CM We then filters convolve overplotted this two- 2 0.5 010.5 1.5= − dimensional0.5− (2D)01 array0.5 with a spatial kernel1.5 corresponding0.5 to 010.5 1.5 0.5 010.5 1.5 on stars from a 1 deg field to illustrate the character− of the foreground contamination asthe a− expected function surface of dwarf density distance. profile of Data a dSph. are We from refer SDSS− to this − DR7. Figure 1. (g r, r)CMDshowingthetworeddestandtwobluesttheoreticalg r smoothed spatial arrayg as A r.Forourspatialkernelweusea g r g r isochrones for− old stellar populations ([Fe/H] 2−.27, 1.5andage 8, 14 − − − = − − = Plummer profile with a 4.′5scalelength.Thisvalueprovides Gyr) at a distance modulus of m M 16.5( 20 kpc), generated from Girardi an effective compromise between the angular scale lengths et al. (2004). The shaded region− shows= pixels∼ that pass the selection criteria. (a) of compact and/or distant(b) objects with those of closer/more (c) (d) extended objects. For reference the angular sizes of the new populated by old, metal-poor stars. Simon & Geha (2007)ob- satellites are listed in Table 1.Weusetherh values derived by Spatial tained spectraFigure of stars in eight1: A of color-magnitude the newly discovered dwarfs— (CM) filter used to suppress the noise from foreground stars while preserving the signal from dwarf galaxy stars 0.5 0.5 Martin et al.0.5 (2008)exceptforLeoV(Belokurovetal.2008). CVn, CVn II,at Com, a specific Her, Leo IV, distance. Leo T, UMa, (a) and UMa and II—and (c) CM filtersThe normalized for an signal old inand each metal-poor pixel of A,denotedby stellarS,gives population at a distance modulus of 16.5 and 20.0, respectively. Domain found mean metallicities in the range 2.29 < [Fe/H]< 1.97. the number of standard deviations above the local mean for each − − Based on thisThe result, solid we consider lines show isochrones Girardi for populations isochroneselement: for 8 and 14Gyr populations with [Fe/H] 1.5 and 2.3. (b) and (d) These CM filters overplotted with metallicities of [Fe/H] 1.5and2 2.27 (the lower = − − 0 limit in Girardion et stars al. 2004 from)andwithages8and14Gyr.Four0 = − a 1 deg−field to illustrate the character0 of theA foregroundA contamination as a function of dwarf distance. Data are from SDSS ¯ isochrones in these ranges can be used to bound the region of S − . DR7. = Aσ dec (degrees) CMD space we are interested in, namely the four combina- dec (degrees) dec (degrees) δ δ tions of [Fe/H] 1.5and 2.27 and ages 8 and 14 Gyr. The arraysδ of running means, A,andrunningstandarddevia- Figure 1 shows these= − four isochrones− projected to a distance of ¯ 0.5 0.5 tions, Aσ ,arebothcalculatedovera00.5 ◦.9 0◦.9windowaround − 20 kpc. − − × each pixel of A.Inparticular,Aσ is given by We define the selection criteria by the CMD envelope inclu- sive of these isochrones +/ the 1σ (g r)colormeasurement 2 2 error as a function of r magnitude.− Shifting− these isochrones n(A A) B ((A A) B) 8 0.5 0 0.5 0.5 0 0.5 Aσ −0.5¯ ∗ − 0 − ¯ ∗ 0.5. over distances− between0.5m M 16.5 and 24.0 in 0.5 mag steps− = ! 0.5 n(n 1) − 0.5 δ ra (degrees)defines 16 different selection− criteria= appropriateδ ra (degrees) for old stellar δ ra− (degrees) populations between d 20 kpc and 630 kpc. We truncate B is a box filter with n elements and is the same size as (a) ∼ ! (b) (c) our color–magnitude selection template at a faint magnitude the running average window. The resulting array Aσ gives limit of r 22.0, beyond which photometric uncertainties in the standard deviation value for each pixel of A as measured = Figure 2: (a) Map of all stars inthe the colors field and around star/galaxy the Ursa separation Major limit I dwarf the ability satellite, to detectM over5.5, thed 0◦.91000◦. kpc.9spanofthefilter.Inthenextsection,wewill (b) Map of stars passing the CM V = − = × filter projected to m M 20these.0 shown populations. in Figure We also0 1(c) truncate. (c) Spatially the selection smoothed template number at define density the mapdetection of the threshold stars0 of in this (b). survey The Ursa in terms Major of S,as I 0 − = g r 1.0, as including2 redder objects adds more noise from well as in terms of the local stellar density E. dwarf galaxy has a µV,0 of onlyMW 27.5− dwarf mag= arcsecstars than[63 signal]. Data from are more from distant SDSS red giant DR7. branch dec (degrees) 3.4. dec (degrees) Detection Threshold(s) (RGB) stars. Finally we do not include stars with δg or δr> dec (degrees) δ δ 0.3 mag in our analysis. To efficiently select stars within this In a large survey such as ours, it is critical to set detection δ CMD envelope, we treat the CMD as an image of 0.025 0.125 0.5 × thresholds strict enough0.5 to eliminate false detections but loose 0.5 (color mag) pixels− and determine which stars fall into pixels enough to retain known− objects and promising candidates. To − (iii) Identify Statisticallyclassified Significant× as “good” according Overdensities. to the selectionA criteria.possible Figure overdensities1 of point sources expected in the sky. 2 characterize the frequency and magnitude of purely random search of 10 000 deg of SDSSshows data, an example optimized of the selection for dwarfs criteria, inFor this case example, for fluctuations in stellar in the density abundant analyzed with tidal our debrisalgorithm, in we m M 16.5( 20 kpc). The shaded region highlights pixels at 16 different distances, and a single choice of stellar the Milky Way’smeasure halo the or maximum (un)bound value of S starfor 199,000 clusters 5◦.5 could3◦ simulated be that− would= be classed∼ as “good” for a system at 20 kpc. × population and scale size require evaluating the statistical0.5 ∼detected.0 It is0.5fields essential of randomly to obtain distributed follow-up stars that0.5 photometry have been smoothed0 to 0.5 0.5 0 0.5 3.3. Spatial Smoothing − as described in the previous section. The only difference is − − significance of 600 million data pixels that do not necessarily δ rafind (degrees) the color-magnitudethat there is no sequence gradient in stellar of stars density expected acrossδ ra each(degrees) for field.
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