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
750
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
120
Open Software for Astrophysics, AAS241
dfm
2
500
Astronomical software
dfm
1
700
emcee-odi
dfm
1
630
Exoplanet population inference: a tutorial
dfm
3
430
Data-driven discovery in the astronomical time domain
dfm
6
690
TensorFlow for astronomers
dfm
6
760
How to find a transiting exoplanets
dfm
1
450
Long-period transiting exoplanets
dfm
1
300
Other Decks in Science
See All in Science
Celebrate UTIG: Staff and Student Awards 2024
utig
0
590
サメのはなし / How Sharks are born
naospon
0
2.2k
学術講演会中央大学学員会いわき支部
tagtag
0
130
(論文読み)贈り物の交換による地位の競争と社会構造の変化 - 文化人類学への統計物理学的アプローチ -
__ymgc__
1
180
06_浅井雄一郎_株式会社浅井農園代表取締役社長_紹介資料.pdf
sip3ristex
0
170
機械学習を支える連続最適化
nearme_tech
PRO
1
260
butterfly_effect/butterfly_effect_in-house
florets1
1
150
Coqで選択公理を形式化してみた
soukouki
0
290
3次元点群を利用した植物の葉の自動セグメンテーションについて
kentaitakura
2
910
最適化超入門
tkm2261
14
3.5k
02_西村訓弘_プログラムディレクター_人口減少を機にひらく未来社会.pdf
sip3ristex
0
160
非同期コミュニケーションの構造 -チャットツールを用いた組織における情報の流れの設計について-
koisono
0
210
Featured
See All Featured
The Pragmatic Product Professional
lauravandoore
32
6.4k
Site-Speed That Sticks
csswizardry
4
410
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
47
5.2k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
53k
[RailsConf 2023 Opening Keynote] The Magic of Rails
eileencodes
28
9.3k
RailsConf 2023
tenderlove
29
1k
Building Flexible Design Systems
yeseniaperezcruz
328
38k
Evolution of real-time – Irina Nazarova, EuRuKo, 2024
irinanazarova
6
570
Six Lessons from altMBA
skipperchong
27
3.6k
Gamification - CAS2011
davidbonilla
80
5.2k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
45
9.4k
How GitHub (no longer) Works
holman
314
140k
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