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
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
Dan Foreman-Mackey
July 25, 2012
Science
0
170
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
180
Open Software for Astrophysics, AAS241
dfm
2
570
My research talk for CCA promotion
dfm
1
800
Astronomical software
dfm
1
760
emcee-odi
dfm
1
700
Exoplanet population inference: a tutorial
dfm
3
490
Data-driven discovery in the astronomical time domain
dfm
6
740
TensorFlow for astronomers
dfm
6
850
How to find a transiting exoplanets
dfm
1
490
Other Decks in Science
See All in Science
データマイニング - グラフデータと経路
trycycle
PRO
1
290
Kaggle: NeurIPS - Open Polymer Prediction 2025 コンペ 反省会
calpis10000
0
380
ド文系だった私が、 KaggleのNCAAコンペでソロ金取れるまで
wakamatsu_takumu
2
1.9k
安心・効率的な医療現場の実現へ ~オンプレAI & ノーコードワークフローで進める業務改革~
siyoo
0
450
機械学習 - K-means & 階層的クラスタリング
trycycle
PRO
0
1.2k
次代のデータサイエンティストへ~スキルチェックリスト、タスクリスト更新~
datascientistsociety
PRO
2
28k
Amusing Abliteration
ianozsvald
0
100
KH Coderチュートリアル(スライド版)
koichih
1
58k
Celebrate UTIG: Staff and Student Awards 2025
utig
0
790
Accelerating operator Sinkhorn iteration with overrelaxation
tasusu
0
200
凸最適化からDC最適化まで
santana_hammer
1
350
Accelerated Computing for Climate forecast
inureyes
PRO
0
150
Featured
See All Featured
The State of eCommerce SEO: How to Win in Today's Products SERPs - #SEOweek
aleyda
2
9.6k
Large-scale JavaScript Application Architecture
addyosmani
515
110k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
141
34k
Jess Joyce - The Pitfalls of Following Frameworks
techseoconnect
PRO
1
67
Conquering PDFs: document understanding beyond plain text
inesmontani
PRO
4
2.3k
Beyond borders and beyond the search box: How to win the global "messy middle" with AI-driven SEO
davidcarrasco
1
56
HDC tutorial
michielstock
1
390
How To Speak Unicorn (iThemes Webinar)
marktimemedia
1
380
Intergalactic Javascript Robots from Outer Space
tanoku
273
27k
How to Build an AI Search Optimization Roadmap - Criteria and Steps to Take #SEOIRL
aleyda
1
1.9k
Digital Projects Gone Horribly Wrong (And the UX Pros Who Still Save the Day) - Dean Schuster
uxyall
0
380
BBQ
matthewcrist
89
10k
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