Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
The Mass of M31
Search
Dan Foreman-Mackey
July 25, 2012
Science
0
180
The Mass of M31
Dan Foreman-Mackey
July 25, 2012
Tweet
Share
More Decks by Dan Foreman-Mackey
See All by Dan Foreman-Mackey
Open software for Astronomical Data Analysis
dfm
0
190
Open Software for Astrophysics, AAS241
dfm
2
580
My research talk for CCA promotion
dfm
1
800
Astronomical software
dfm
1
770
emcee-odi
dfm
1
700
Exoplanet population inference: a tutorial
dfm
3
500
Data-driven discovery in the astronomical time domain
dfm
6
740
TensorFlow for astronomers
dfm
6
860
How to find a transiting exoplanets
dfm
1
500
Other Decks in Science
See All in Science
あなたに水耕栽培を愛していないとは言わせない
mutsumix
1
290
Algorithmic Aspects of Quiver Representations
tasusu
0
230
防災デジタル分野での官民共創の取り組み (1)防災DX官民共創をどう進めるか
ditccsugii
0
570
SHINOMIYA Nariyoshi
genomethica
0
110
AI(人工知能)の過去・現在・未来 —AIは人間を超えるのか—
tagtag
PRO
1
250
Celebrate UTIG: Staff and Student Awards 2025
utig
0
1.3k
やるべきときにMLをやる AIエージェント開発
fufufukakaka
2
1.3k
DMMにおけるABテスト検証設計の工夫
xc6da
1
1.6k
俺たちは本当に分かり合えるのか? ~ PdMとスクラムチームの “ずれ” を科学する
bonotake
2
2.1k
動的トリートメント・レジームを推定するDynTxRegimeパッケージ
saltcooky12
0
270
Navigating Weather and Climate Data
rabernat
0
140
論文紹介 音源分離:SCNET SPARSE COMPRESSION NETWORK FOR MUSIC SOURCE SEPARATION
kenmatsu4
0
580
Featured
See All Featured
Designing for humans not robots
tammielis
254
26k
SEO Brein meetup: CTRL+C is not how to scale international SEO
lindahogenes
1
2.5k
Hiding What from Whom? A Critical Review of the History of Programming languages for Music
tomoyanonymous
2
590
Collaborative Software Design: How to facilitate domain modelling decisions
baasie
0
170
The Cult of Friendly URLs
andyhume
79
6.8k
Leveraging Curiosity to Care for An Aging Population
cassininazir
1
200
How to Think Like a Performance Engineer
csswizardry
28
2.5k
Max Prin - Stacking Signals: How International SEO Comes Together (And Falls Apart)
techseoconnect
PRO
0
130
Mobile First: as difficult as doing things right
swwweet
225
10k
Marketing to machines
jonoalderson
1
5k
Side Projects
sachag
455
43k
KATA
mclloyd
PRO
35
15k
Transcript
THE MASS OF M31 THE FULLY SELF-CONSISTENT DYNAMICAL MODEL GALAXY
COFFEE MPIA 2012
DAN FOREMAN-MACKEY DANFM.CA GITHUB.COM/DFM NEW YORK UNIVERSITY LARRY WIDROW WITH:
QUEEN'S UNIVERSITY, CANADA
WHAT DO WE WANT TO DO? BUILD A TOOL FOR
DYNAMICAL MODELING OF DISK GALAXIES USING ALL AVAILABLE DATASET SELF-CONSISTENTLY PHYSICALLY MOTIVATED i.e. not mass modeling...
WHAT HAVE WE DONE? BUILT A MODEL OF ANDROMEDA USING
A LOT OF DATASETS SELF-CONSISTENTLY PHYSICALLY MOTIVATED * *WAIT TWO SLIDES
van der Marel & Guhathakurta (2008) Widrow, Pym & Dubinski
(2005) Evans & Wilkinson (2000) Kuijken & Dubinski (1995) WHERE DOES THIS COME FROM?
Radius HI-rotation curve Corbelli et al. (2010) surface brightness profile
Barmby et al. (2006) satellite galaxy kinematics PAndAS, SPLASH, et al. Conn et al. (2011, in prep) ~10 kpc ~500 kpc Data PLUS: HALO STARS GLOBULAR CLUSTERS PLANETARY NEBULAE ETC.
GALACTICS f(E, Lz, Ez) = fh(E) + fb(E) + fd(E,
LzEz) ⇢(r, z) = ⇢h( (r, z)) + ⇢b( (r, z)) + ⇢d(r, z) r2 = 4 ⇡ G ⇢
GALACTICS f(E, Lz, Ez) = fh(E) + fb(E) + fd(E,
LzEz) ⇢(r, z) = ⇢h( (r, z)) + ⇢b( (r, z)) + ⇢d(r, z) r2 = 4 ⇡ G ⇢ Generative Model
GALACTICS f(E, Lz, Ez) = fh(E) + fb(E) + fd(E,
LzEz) ⇢(r, z) = ⇢h( (r, z)) + ⇢b( (r, z)) + ⇢d(r, z) r2 = 4 ⇡ G ⇢ Generative Model Likelihood Function
GALACTICS f(E, Lz, Ez) = fh(E) + fb(E) + fd(E,
LzEz) ⇢(r, z) = ⇢h( (r, z)) + ⇢b( (r, z)) + ⇢d(r, z) r2 = 4 ⇡ G ⇢ Generative Model Likelihood Function 19 Parameters
Generative Model Likelihood Function ☁ x
Generative Model Likelihood Function ☁ x emceethe MCMC Hammer arxiv.org/abs/1202.3665
danfm.ca/emcee github.com/dfm/emcee paper documentation issues/contributions
40 60 80 100 120 140 160 R [arcmin] 180
200 220 240 260 280 300 320 vcirc [km s 1] 100 101 102 R [arcmin] 15 16 17 18 19 20 21 22 23 24 µ [mag arcsec 2]
None
BONUS
BONUS