February 26, 2014
130

# Yale Galaxy Lunch

February 26, 2014

## Transcript

1. ### Adrian Price-Whelan Kathryn Johnston David Hendel David Hogg adrn/streams POTENTIAL

MILKY WAY THE OF THE

5. ### VIRIALIZED SPHERES Simple halo models are Vc( r ) ⇡

Const . r d ( r ) dr / Const . (r) / ln(r) ⇢(r) / r 2

+ Rs)2

9. ### Simulated haloes are x y z y e.g., Jing &

Suto 2002 TRIAXIAL

et al. 2011

orthogonal

orthogonal

18. ### Shape: spherical? prolate? triaxial? Inertia: aligned at all radii? !

Substructure: how much?

et al. 2011

24. ### ( x1, v1) ( x2, v2) ( x1) ( x2)

= 1 2 (v2 2 v2 1 )

26. ### d(⌫v2 r ) dr + 2 r ⌫v2 r =

⌫ d dr Velocity dispersion Potential

32. ### EVAPORATION rtide ⇠ f ✓ m Menc ◆1/3 R f

⇠ O(1) M m m << M
33. ### TIDAL SHOCKING K ! K + K E ! E

2 K E ⇡ 4 3 G2m ✓ M V ◆2 hr2 tide i R4 v ⇠ " 8 3 G2 ✓ M V ◆2 hr2 tide i R4 #1/2 (at pericenter)

35. ### rtide R ⇠ ⇣ m M ⌘1/3 v ⇡ ✓

Gm rtide ◆1/2 V ⇡ ✓ GMenc R ◆1/2 v V ⇠ ⇣ m M ⌘1/3 v ⇠ ⇣ m M ⌘1/2 ⇣rtide R ⌘ 1/2 V and
36. ### (r) = GM r disk( R, z ) = GMdisk

q R 2 + ( a + p z 2 + b 2)2 spher( r ) = GMspher r + c halo ( x, y, z ) = v 2 h ln( C1x 2 + C2y 2 + C3xy + ( z/qz )2 + r 2 h ) Law & Majewski 2010
37. ### 2.5 x 106 M☉ 2.5 x 107 M☉ 2.5 x

108 M☉ 2.5 x 109 M☉
38. ### −100 −50 0 50 Y [kpc] 2.5e6M¯ 2.5e7M¯ 2.5e8M¯ 2.5e9M¯

−100 −50 0 50 X [kpc] −100 −50 0 50 Z [kpc] −100 −50 0 50 X [kpc] −100 −50 0 50 X [kpc] −100 −50 0 50 X [kpc]

40. ### 2.5 ⇥ 106M Time [Myr] |v vs | t=tub |r

rs | t=tub [kpc] [km/s] mass loss
41. ### Time [Myr] |v vs | t=tub |r rs | t=tub

[kpc] [km/s] 2.5 ⇥ 107M
42. ### Time [Myr] |v vs | t=tub |r rs | t=tub

[kpc] [km/s] 2.5 ⇥ 108M
43. ### Time [Myr] |v vs | t=tub |r rs | t=tub

[kpc] [km/s] 2.5 ⇥ 109M

46. ### Each star: PARAMETERS Progenitor: ⌧ub K true 6D position unbinding

time leading/trailing tail true 6D position M mass today Potential: anything! W = (l, b, d, µl, µb, vr) W p = (l, b, d, µl, µb, vr)
47. ### THE POSTERIOR Gaussian errors p( , W , W p,

⌧, K | D, Dp) = 1 Z p(D | W )p(Dp | W p)p(W | W p, ⌧, , K)p( )p(⌧)p(K) Priors Likelihood
48. ### p(W | W p, ⌧, , K) = p(X |

Xp, ⌧, ) |J(⌧)| p(X | Xp, ⌧, ) = [N(r | rs + Krtide ˆ rs, rtide) ⇥ N(v | vs, v)]t=⌧

51. ### disk( R, z ) = GMdisk q R 2 +

( a + p z 2 + b 2)2 spher( r ) = GMspher r + c halo ( x, y, z ) = v 2 h ln( C1x 2 + C2y 2 + C3xy + ( z/qz )2 + r 2 h )

54. ### Time-dependent / non-integrable potentials Multiple streams Missing dimensions / realistic

uncertainties No progenitor
55. ### David Hogg (NYU) Kathryn Johnston (Columbia) David Hendel (NYU) Ana

Bonaca (Yale) Dan Foreman-Mackey (NYU)` Marla Geha (Yale) Andreas Küpper (Columbia) David Law (Toronto) Sarah Pearson (Columbia) Barry Madore (Carnegie) Steve Majewski (UVA) Allyson Sheﬀield (Columbia) Thanks!