Finding Galactic- halo substructure in the Gaia data Amina Helmi - - PowerPoint PPT Presentation

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Finding Galactic- halo substructure in the Gaia data Amina Helmi - - PowerPoint PPT Presentation

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Finding Galactic- halo substructure in the Gaia data Amina Helmi Stellar halo: treasure trove of merger relics t = 1 Gyr t = 2 Gyr Cosmological models characteristic: hierarchical growth: mergers Disrupted galaxies/debris naturally in a

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Finding Galactic-halo substructure

in the Gaia data

Amina Helmi

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t = 1 Gyr t = 2 Gyr t = 3 Gyr t = 4.5 Gyr t = 8 Gyr t = Tnow

today

snapshots: J. Gardner

Stellar halo: treasure trove of merger relics

  • Cosmological model’s characteristic: hierarchical

growth: mergers

  • Disrupted galaxies/debris naturally in a stellar halo:

!merger signatures: Substructures and tidal streams

  • Questions:
  • Were mergers important for galaxies like MW?
  • How often and when did they happen?
  • What were the building blocks?
  • Stars are “fossils”
  • Motions, ages, chemical composition trace origin
  • Substructures pinpoint to merger debris
  • Probe force field ! mass (gravity)
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Testing the cold dark matter paradigm

Is this “picture” correct?

  • Are galaxies like the Milky Way and its nearest neighbours embedded in dark matter halos like

those predicted by the cosmological model?

Credit: V. Springel

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Testing the cold dark matter paradigm

Is this “picture” correct?

  • Are galaxies like the Milky Way and its nearest neighbours embedded in dark matter halos like

those predicted by the cosmological model?

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Testing the cold dark matter paradigm

Is this “picture” correct?

  • Are galaxies like the Milky Way and its nearest neighbours embedded in dark matter halos like

those predicted by the cosmological model?

  • How much dark matter is there?

– how is it distributed? – what is the dark matter?

  • Is Gravity correct?

Credit: V. Springel

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A stream in a dark halo with substructure

Granularity: Hundreds of thousands dark clumps if dark matter particle is cold Springel et al. 2008

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Belokurov et al. 2006 +

Outer halo: R > 20 kpc

  • Clear evidence of substructure
  • Limited to high-surface brightness features

(progenitors/time of events)

  • Qualitatively consistent with expectations from

ΛCDM (Helmi et al. 2011; Deason et al. 2014)

North Galac?c Cap

Galac?c An?centre

Slater et al. 2014+

The accretion history unveiled so far:

The Galactic halo from SDSS/PanStarrs

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PanSTARRS 3π survey

Many narrow streams mapped/discovered. Bernard et al. (2016)

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The relevance of kinema?c informa?on

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The relevance of kinema?c informa?on

Proper motions from Gaia DR2 (April 2018)

vt=200 km/s ! μ~1 – 5 mas/yr (d ~ 10 – 40 kpc) expected error: σμ ~ 0.1mas/yr (G ~ 17)

! Trace substructures, outlier removal, and map MW potential

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Not all substructure is accreted – does pinpoint to interactions and mergers

Li et al 2017 Price-Whelan et al 2015 Deason et al 2014

Gomez et al. (2016, 2017)

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angular momentum energy

conserved quantities

Nearby halo

Memory of origin: retained in the motions

" 100s of streams should cross Sun’s vicinity " So far.. not much evidence (small samples) " How to find more? ! Clustering in conserved quantities

Helmi & de Zeeuw 2000

https://www.astro.rug.nl/~ahelmi/research/gaia/movie.html

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Construction of a halo sample: TGAS x RAVE

  • TGAS dataset is significant improvement, but need full

phase-space information ! cross-match to RAVE survey

  • RAVE: spectra for 500k stars in southern sky: vlos, [M/H],

spectrophotometric distance/parallax

(with TGAS priors, McMillan et al. 2017)

! ~ 200,000 stars in common

  • Metallicity cut [M/H]cal < -1 dex

to select preferentially halo

  • Remove stars with disk-like

kinematics

  • 2-Gaussian decomposition

! sample of 1307 genuine halo stars

−600 −400 −200 200 400 600

vx (km/s)

−600 −400 −200 200 400 600

vy (km/s)

−600 −400 −200 200 400 600

vz (km/s)

−600 −400 −200 200 400 600

vy (km/s)

Maarten Breddels Jovan Veljanoski

Helmi, Veljanoski, Breddels et al. (2017), Veljanoski et al. (in prep)

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Statistical tests and searches of substructure

Models predict

  • several hundred moving groups or

streams in Solar Neighbourhood ! we search for excess clustering in velocity space with a correlation function

  • substructure to be more easily apparent

in Integrals of Motion space ! we characterise the distribution, degree of clustering and establish significance

20 10 10 20

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100 200 300 400 500 600 700

velocity difference |vi − vj| (km/s)

0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

1+<ξ>

Velocity correlation function

  • Very significant excess of pairs in data compared to random/smooth

– for Δ < 20 km/s, 5.5σ (120 pairs of stars in excess) – for 20 < Δ < 40 km/s: 8.8σ (328 pairs in excess)

  • Also for very large separations, there is a significant excess

Helmi et al. (2017) Helmi, Veljanoski et al. (2017)

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The amount of substructure: comparison to cosmological simulations

  • Simulations of halos purely built via accretion show excess on small and large separations
  • f similar amplitude

– some variation from halo to halo ! Milky Way halo consistent with being fully built via accretion

Cooper et al. (2010)

Helmi et al. (2017)

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−4000 −3000 −2000 −1000 1000 2000 3000 4000

Lz (km/s kpc)

−200000 −175000 −150000 −125000 −100000 −75000 −50000 −25000

E (km2/s2)

! very retrograde motions: 73% of all stars (for E > -1.3x105 km2/s2)

In randomised (re-shuffled) smooth distributions the probability of having so many loosely bound

counter-rotating stars is < 0.1% retrograde less-bound

Helmi, Veljanoski et al. (2017)

Integrals of motion - space

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Integrals of motion – space

  • Statistical comparison to smooth

distributions allows identification of

  • verdensities in E vs Lz
  • Structures at Lz ~-500 km/s kpc

could be related to OmegaCen debris (Dinescu 2002)

  • VelHel-6: stars with disk-like

kinematics but counter-rotating

−3 −2 −1 1 2 3 scaled Lz −10 −9 −8 −7 −6 scaled E

3 6 7 9 13 14 18 21

−200000 −180000 −160000 −140000 −120000 −100000 E (km2/s2) −2000 −1000 1000 2000 Lz (km/s kpc)

Helmi, Veljanoski, Breddels et al. (2017), Veljanoski et al. (in prep)

see also Myuoung et al. (2017)

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The retrograde halo in context

  • Not common in cosmological

simulations

(e.g. Illustris; Vogelsberger et al. 2014)

  • Less than 1% of MW-mass

galaxies have more than 60% of the less bound stars on retrograde orbits (here defined as r > 15 kpc)

Helmi et al. (2017)

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Chemical abundances

Helmi et al. (2017)

  • C. Boeche chemical pipeline, not all stars have detailed abundances (SNR > 20, McMillan sample)
  • Stars with Lz < 0 on average lower metallicity, both [M/H] and [Fe/H]
  • May be some clumpiness (?)

−2000 −1000 1000 2000

Lz (km/s kpc)

−210000 −200000 −190000 −180000 −170000 −160000 −150000 −140000 −130000

E (km2/s2)

−2.4 −2.2 −2.0 −1.8 −1.6 −1.4 −1.2 −1.0 −0.8

[Fe/H] (dex)

−4000 −3000 −2000 −1000 1000 2000

Lz (km/s kpc)

−200000 −175000 −150000 −125000 −100000 −75000 −50000 −25000

E (km2/s2)

−2.4 −2.2 −2.0 −1.8 −1.6 −1.4 −1.2 −1.0 −0.8

[M/H] (dex) Veljanoski (in prep)

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Chemical abundances: substructures

Helmi et al. (2017)

−1.0 −0.5 0.0 0.5 1.0

[Mg/Fe] (dex)

Retrograde halo Stars not in substructures Substructure 3 Substructure 6 Substructure 7

−3 −2 −1

[Fe] (dex)

−1.0 −0.5 0.0 0.5 1.0

[Mg/Fe] (dex)

Substructure 9

−3 −2 −1

[Fe] (dex)

Substructure 13

−3 −2 −1

[Fe] (dex)

Substructure 14

−3 −2 −1

[Fe] (dex)

Substructure 18

−3 −2 −1

[Fe] (dex)

Substructure 21 2 4 6 8

Number of stars

Retrograde halo

20 40 60 80 100

Stars not in substructures

2 4 6 8

Substructure 3

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Substructure 6

1 2 3 4 5 6

Substructure 7

−2 −1

[Fe/H] (dex)

1 2 3 4 5 6

Number of stars

Substructure 9

−2 −1

[Fe/H] (dex)

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Substructure 13

−2 −1

[Fe/H] (dex)

1 2 3 4 5 6

Substructure 14

−2 −1

[Fe/H] (dex)

0.0 0.5 1.0 1.5 2.0

Substructure 18

−2 −1

[Fe/H] (dex)

0.0 0.2 0.4 0.6 0.8 1.0

Substructure 21

p < 0.1% p < 1% p < 0.1% p < 1% p < 6% p < 1%

Veljanoski (in prep) Probabilities drawn from

  • verall population can be

relatively small Similar behaviour in e.g. [Mg/Fe] Generally limited by number of stars

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PI – GA surveys: Vanessa Hill

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Clustering in integrals of motion (e.g. actions) maximal for right gravitational potential (DR2)

Sanderson et al. (2014, 2016)

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Summary

  • Halo substructure is useful for dynamics (dark matter) and merger history
  • Photometric surveys mapped large structures in the outer halo
  • TGAS x RAVE: excess of close velocity pairs and IoM space rich in substructure

– at level consistent with cosmological simulations of halos purely built via accretion – Less-bound halo stars predominantly retrograde (significance > 99.9%) – Many overdensities for more bound halo

  • What’s coming:

– DR2 (April 2018) will be fantastic: proper motions and parallaxes for 1 billion stars! – 4MOST and WEAVE: spectroscopic follow – Characterization of the stars in the structures found, e.g. chemical abundances, ages – Numerical simulations for orbits, infall times, link to other structures in the halo – constraints on characteristic mass and scale of Milky Way