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
My research talk for CCA promotion
Search
Dan Foreman-Mackey
February 03, 2022
Science
1
740
My research talk for CCA promotion
A summary of what I've been up to for the past few years and where my research program is going.
Dan Foreman-Mackey
February 03, 2022
Tweet
Share
More Decks by Dan Foreman-Mackey
See All by Dan Foreman-Mackey
Open software for Astronomical Data Analysis
dfm
0
110
Open Software for Astrophysics, AAS241
dfm
2
440
Astronomical software
dfm
1
690
emcee-odi
dfm
1
590
Exoplanet population inference: a tutorial
dfm
3
420
Data-driven discovery in the astronomical time domain
dfm
6
680
TensorFlow for astronomers
dfm
6
710
How to find a transiting exoplanets
dfm
1
440
Long-period transiting exoplanets
dfm
1
290
Other Decks in Science
See All in Science
Snowflake上でRを使う: RStudioセットアップとShinyアプリケーションのデプロイ
ktatsuya
0
330
2024-06-16-pydata_london
sofievl
0
460
第4回ナレッジグラフ勉強会 Knowledge Graph Embedding
maruru0090
0
250
Machine Learning for Materials (Lecture 3)
aronwalsh
0
960
『データ可視化学入門』を PythonからRに翻訳した話
bob3bob3
1
460
Science of Scienceおよび科学計量学に関する研究論文の俯瞰可視化_LT版
hayataka88
0
800
【人工衛星開発】能見研究室紹介動画
02hattori11sat03
0
120
20240127_OpenRadiossエアバッグ解析
kamakiri1225
0
240
ultraArmをモニター提供してもらった話
miura55
0
170
対外衝撃波療法_井野辺病院リハビリ部
naoyukihiro1
0
130
240510 COGNAC LabChat
kazh
0
110
Pericarditis Comic
camkdraws
0
260
Featured
See All Featured
Designing for humans not robots
tammielis
248
25k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
26
2k
Into the Great Unknown - MozCon
thekraken
29
1.4k
Facilitating Awesome Meetings
lara
49
5.9k
Building an army of robots
kneath
302
42k
BBQ
matthewcrist
83
9.2k
Bootstrapping a Software Product
garrettdimon
PRO
304
110k
Java REST API Framework Comparison - PWX 2021
mraible
PRO
27
7.4k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
230
17k
Faster Mobile Websites
deanohume
304
30k
For a Future-Friendly Web
brad_frost
174
9.3k
ParisWeb 2013: Learning to Love: Crash Course in Emotional UX Design
dotmariusz
109
6.9k
Transcript
BUILDING THE SOFTWARE INFRASTRUCTURE FOR ASTROPHYSICS by Dan Foreman-Mackey
who am I? / / what’ve I been up to?
1
7 [1] solving Hard™ data analysis problems [2] enabling and
empowering astrophysicists
implementation.
data = > physics
open source software for astrophysics 2
why?
credit: Adrian Price-Whelan / / data: SAO/NASA ADS
my open source contributions 3
None
gaussian processes 4
p(data|physics)
data ~ N(model; noise)
°0.6 °0.3 0.0 0.3 0.6 raw [ppt] 0 5 10
15 20 25 time [days] °0.30 °0.15 0.00 de-trended [ppt] N = 1000 reference: DFM+ (2017)
°0.6 °0.3 0.0 0.3 0.6 raw [ppt] 0 5 10
15 20 25 time [days] °0.30 °0.15 0.00 de-trended [ppt] N = 1000 reference: DFM+ (2017)
data ~ N(model; noise)
data ~ N(model; noise)
so. why not?
data ~ N(model; noise)
None
reference: Ambikasaran, DFM+ (2015)
None
reference: Ambikasaran, DFM+ (2015)
reference: DFM, Agol, Ambikasaran, Angus (2017); DFM (2018); DFM, Luger,
et al. (2021)
None
reference: Gordon, Agol, DFM (2020)
what’s next?
None
None
None
credit: Quang Tran
reference: Luger, DFM, Hedges (2021)
probabilistic inference 5
p(data|physics)
have: physics = > data
want: data = > physics
integral of the form f(physics) p(physics|data) dphysics
None
number of parameters patience required a few tenish not outrageously
many reference: DFM (priv. comm.)
number of parameters patience required emcee a few tenish not
outrageously many reference: DFM (priv. comm.)
number of parameters patience required emcee a few tenish not
outrageously many how things should be reference: DFM (priv. comm.)
None
None
None
None
gradients!
dp(data|physics) / dphysics
automatic differentiation aka “backpropagation”
your model is just code
apply the chain rule
apply the chain rule over and over again . .
.
sounds silly?
it's not! (mostly)
None
None
what’s next?
None
jax.readthedocs.io
my approach to open source 6
None
[1] don’t underestimate users [2] build libraries, not (just) scripts
[3] teach by example
None
None
None
bringing open source practices to research more generally
None
None
None
None
what’s next? 7
7 [1] inference with stochastic or intractable models [2] what
can we do to better support open source in astrophysics
7
7 credit: Adrian Price-Whelan
many fundamental software packages have a shockingly small number of
maintainers.
a selection of some* CCA-supported software: * my apologies for
neglecting your favorites!
None
BUILDING THE SOFTWARE INFRASTRUCTURE FOR ASTROPHYSICS @ CCA