Antonela Monachesi Universidad de La Serena E. Bell, B. Harmsen, R. - - PowerPoint PPT Presentation

Comparing results from the GHOSTS survey and the Auriga simulations

Antonela Monachesi

Universidad de La Serena

• E. Bell, B. Harmsen, R. de Jong, D. Radburn-Smith,
• J. Bailin + GHOSTS team

F . Gomez, R. Grand, V. Springel, G. Kauffmann + Auriga collaboration

Stellar halos across the cosmos, Heidelberg, 03-07-2018

Resolved stellar halo measurements

Probe individual galaxies to very low surface brightness. It is possible to quantify substructure. Immune to flat-field/sky background uncertainties and PSF scattered light issue. Allows to constrain the halo stellar population (especially with HST). Limited distance (out to ~10 Mpc), so low statistics + background contamination + small FoV when observing with HST

Cen A; Crnojevic et al. (2016) M81; Okamoto et al. (2015)

It is possible to reach μ ~ 33- 34 mag/arcsec2

Radburn-Smith et al. (2011)

PANDAS; Resolved RGB stars McConnachie + 09; Ibata + 14

The Milky Way’s and M31’s stellar halos have similarities but differ greatly from each other

Credit: Koposov et al. SDSS

MW M31 4-7 108 M◉ 1010 M◉ 3-D Power law profile

• 2.5; r < 20kpc -3.7; r < 150kpc
• 3.5; r > 20kpc

~Const. [Fe/H] [Fe/H] gradient c/a~0.6

• blate!prolate

Both halos are highly structured

e.g., Ivesic+00; Newberg, Yanny+07; Bell+08; Carollo+10, Sesar + 11, Carollo+16; Slater+16; Fernández-Alvar+17; Kalirai + 06; Gilbert + 12,14; Ibata +14

GHOSTS Survey team:

PI: Roelof de Jong (AIP) Jeremy Bailin (UA) Eric Bell (UM) Tom Brown (STScI) James Bullock (UC Irving) Stephane Courteau (Queens) Julianne Dalcanton (UW) Harry Ferguson (STScI) Paul Goudfrooij (STScI) Benjamin Harmsen (UM) Benne Holwerda (UL) Antonela Monachesi (ULS) Chris Purcell (WVU) David Radburn-Smith (FB) Anil Seth (Utah) Jonathan Sick (Queens) David Streich (AIP) In Sung Yang (AIP) Dan Zucker (Macquarie)

de Jong+(2007, 2009), Bailin+(2011), Radburn-Smith+(2011, 2012, 2014), Monachesi+(2013, 2014, 2016a), Streich+(2016), Carrillo+(2016) Harmsen, Monachesi+(2017) Bell, Monachesi+(2017), Yang+, in prep.

GHOSTS survey: HST ACS/WFC3 observations in the outskirts of 18+ nearby disk galaxies. Provide statistics on galaxy stellar outskirts beyond the MW and M31

NGC 0247 NGC 0253 NGC 4945 NGC 3031 NGC 2403 NGC 0891 NGC 4244 NGC 4565 NGC 4631 NGC 4736 NGC 5023 IC 5052 NGC 5236 NGC 5907 NGC 7793 NGC 7814 NGC 5457

GHOSTS Sample Overview

N G N G C 5 4 5 7

NGC 0247

NGC 0253 NGC 4945 NGC 3031

NGC 2403

NGC 0891

NGC 4244

NGC 4565

NGC 4631 NGC 4736 NGC 5023 IC 5052 NGC 5236 NGC 5907 NGC 7793

NGC 7814

GHOSTS MW-mass Disk Galaxies

HST resolves red giant branch stars and measures stellar density and color/metallicity

NGC 0247

NGC 0253 NGC 4945 NGC 3031

NGC 2403

NGC 0891

NGC 4244

NGC 4565

NGC 4631 NGC 4736 NGC 5023 IC 5052 NGC 5236 NGC 5907 NGC 7793

NGC 7814

Projected minor axis stellar halo surface brightness profiles

Harmsen, Monachesi et al. (2017)

In general, power law profiles r-α where -2>α>-3.7 over 10 to 70 kpc. Substructure on top of power law.

Stellar halos appear flattened with 0.4<c/a<0.75 at ~ 25 kpc.

RGB colors in old populations reflect their metallicities

Steep metallicity gradients in half halos, very weak or absent in the other half

Monachesi et al. 2013, 2016a

Minor axis stellar halo Color/Metallicity profiles

[Fe/H] (dex)

NGC 0247

NGC 0253 NGC 4945 NGC 3031

NGC 2403

NGC 0891

NGC 4244

NGC 4565

NGC 4631 NGC 4736 NGC 5023 IC 5052 NGC 5236 NGC 5907 NGC 7793

NGC 7814

Milky Way mass disk galaxies have a broad range of stellar halo masses and properties

Harmsen, Monachesi et al. , 2017 Poner plot del paper

x30 range in stellar halo mass Significant variation in [Fe/H] gradients Large variation in density slopes an order of magnitude range metallicities X15 scatter in stellar halo mass fraction

The Milky Way and M31 are at the extremes of these correlations

See also next talk by In Sung Yang and Dragonfly results (Merritt et al. 2016)

Harmsen, Monachesi et al. , 2017 See talk by Eric Bell

See also Deason et al. 2016, Bell&Monachesi et al. 2017, D´Souza&Bell 2017, Amorisco 2017a

The stellar halo metallicity and mass correlation reflects the properties of the dominant accreted satellites. Larger halos accrete more massive satellites

We can use stellar halo mass or metallicity to quantify dominant merger

The Auriga simulations: 30 Milky Way-mass halos

Auriga Core team:

PI: Volker Spingel (HITS-MPA) David Campbell (Durham) Carlos Frenk (Durham) Facundo Gomez (ULS) Robert Grand (HITS) Adrian Jenkins (Durham) Federico Marinacci (MIT) Rudiger Pakmor (HITS) Christine Simpson (HITS) Simon White (MPA)

m(dm)~ 2x105 MSUN m(g) ~ 5x104 MSUN Fully cosmological hydrodynamical simulations

• f very high resolution +

statistics

Grand et al. (2017)

Halos of (1-2)x1012 MSun

V-band surface brightness maps of stellar halos, Monachesi et al. (2018)

Some of the Auriga stellar halo metallicity and age profiles along different directions

Stellar halos have diverse median ages and metallicities, even the accreted-only component, and are composed of a mixture

• f populations at each

radius

Monachesi et al. 2018, arXiv:1804.07798

Projected minor axis surface brightness and color profiles Auriga vs. observations

Results from observations in general agree better with accreted-only stellar halos, except M31 which shows a prominent and metal-rich halo

Monachesi et al. 2018, arXiv:1804.07798

The Auriga simulations reproduce the diversity found in

• bserved stellar halos of Milky Way-mass galaxies

Accreted-only component

This broad range in properties is driven by diversity in merger history

Monachesi et al. 2018, arXiv:1804.07798, See also Harmsen et al. 2017, Bell et al. 2017

Accreted + in-situ halo

Too massive in-situ stellar halos in Auriga sims compared with

• bservations (and in general in all hydro simulations)

Monachesi et al. 2018, arXiv:1804.07798, See also Harmsen et al. 2017, Bell et al. 2017

Halo metallicity gradients and density profiles may quantify the degree of dominance of the largest accretion

# significant progenitors: Number of satellites that make up 90% of the stellar halo

Larger gradients are found when fewer significant progenitors built up the stellar halo

Monachesi et al. 2018, arXiv:1804.07798 5 10 15

# significant progenitors

• 8
• 6
• 4
• 2

[Fe/H] slope (10-3 dex/kpc)

All halo 5 10 15

# significant progenitors

• 8
• 6
• 4
• 2

2

[Fe/H] slope (10-3 dex/kpc)

Accreted

Au2 Au3 Au4 Au5 Au6 Au7 Au8 Au9 Au10 Au12 Au13 Au14 Au15 Au16

# significant progenitors

• 3.6
• 3.4
• 3.2
• 3
• 2.8
• 2.6
• 2.4
• 2.2

Projected power law density slope

5 10 15

# significant progenitors

• 3
• 2.8
• 2.6
• 2.4
• 2.2
• 2
• 1.8

Projected power law density slope

Accreted

All GHOSTS MW-mass disc galaxies have extended stellar halos Milky Way-mass disc galaxies have diverse stellar halo properties

(Monachesi+ 2013, 2016a, Harmsen+2017)

A tight stellar halo mass — [Fe/H] (minor axis) relation is discovered empirically, confirming an accretion origin of stellar halos. Larger halos are formed from few larger satellites

(Harmsen+2017; see also Deason+2016, D’Souza & Bell 2018, Monachesi+2018)

New hydrodynamical simulations of high resolution, Auriga, lead to a good agreement with the data (Importance of a careful and fair comparison) Too high in-situ stellar halo masses

(Monachesi+2016b, Monachesi+2018)

Gradients may better quantify the merger history (Monachesi+2018)

Summary

Bright Future for stellar halo studies

Expand de sample of individual galaxies studied to ~20 Mpc and obtain panoramic maps of many more galaxies. Excellent to sample diversity in halos as well as in galaxy types

JWST, 2021? ELT, Chile, 2024 GMT , Chile, 2023 TMT , Hawaii, 2027 WFIRST, 2020? From Ben Williams´talk LSST, Chile, 2023