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
SMHASH telecon 03/2015
Search
Adrian Price-Whelan
March 11, 2015
Science
0
100
SMHASH telecon 03/2015
Adrian Price-Whelan
March 11, 2015
Tweet
Share
More Decks by Adrian Price-Whelan
See All by Adrian Price-Whelan
the Astropy project - Flatware
adrn
1
230
the dynamic Milky Way in the Gaia era
adrn
1
200
The Astropy Project
adrn
1
120
Git and version control
adrn
1
120
Chaos and stellar streams
adrn
1
180
Software testing
adrn
0
200
Local Group Astrostatistics
adrn
1
88
100% Outer Space
adrn
1
160
Caltech 03/2015
adrn
0
160
Other Decks in Science
See All in Science
Introd_Img_Process_2_Frequ
hachama
0
560
実力評価性能を考慮した弓道高校生全国大会の大会制度設計の提案 / (konakalab presentation at MSS 2025.03)
konakalab
2
170
統計的因果探索: 背景知識とデータにより因果仮説を探索する
sshimizu2006
4
910
[第62回 CV勉強会@関東] Long-CLIP: Unlocking the Long-Text Capability of CLIP / kantoCV 62th ECCV 2024
lychee1223
1
940
Valuable Lessons Learned on Kaggle’s ARC AGI LLM Challenge (PyDataGlobal 2024)
ianozsvald
0
390
統計学入門講座 第4回スライド
techmathproject
0
140
生成AIと学ぶPythonデータ分析再入門-Pythonによるクラスタリング・可視化をサクサク実施-
datascientistsociety
PRO
4
1.6k
モンテカルロDCF法による事業価値の算出(モンテカルロ法とベイズモデリング) / Business Valuation Using Monte Carlo DCF Method (Monte Carlo Simulation and Bayesian Modeling)
ikuma_w
0
170
眼科AIコンテスト2024_特別賞_6位Solution
pon0matsu
0
400
「美は世界を救う」を心理学で実証したい~クラファンを通じた新しい研究方法
jimpe_hitsuwari
1
130
CV_5_3dVision
hachama
0
140
Online Feedback Optimization
floriandoerfler
0
2.2k
Featured
See All Featured
Learning to Love Humans: Emotional Interface Design
aarron
273
40k
Adopting Sorbet at Scale
ufuk
77
9.4k
Practical Orchestrator
shlominoach
188
11k
Building Applications with DynamoDB
mza
95
6.5k
Writing Fast Ruby
sferik
628
61k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
48
5.4k
Java REST API Framework Comparison - PWX 2021
mraible
31
8.6k
For a Future-Friendly Web
brad_frost
179
9.8k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
34
5.9k
The Pragmatic Product Professional
lauravandoore
35
6.7k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
130
19k
Designing for humans not robots
tammielis
253
25k
Transcript
Rewinder adrian price-whelan
Tidal disruption is simple
t = 0 Price-Whelan et al. (2014) Rewinder
Rewinder Price-Whelan et al. (2014) t = -1 evaluate likelihood
Rewinder Price-Whelan et al. (2014) t = -2 evaluate likelihood
Rewinder Price-Whelan et al. (2014) t = -3
⌧ub K unbinding time leading/trailing tail M mass today any
parametrization per star progenitor potential (l, b, d, µl, µb, vr) (l, b, d, µl, µb, vr) marginalize out WE’RE HOSED Rewinder Price-Whelan et al. (2014)
−100 −50 0 50 X [kpc] −100 −50 0 X
[kpc] x “Data”: Price-Whelan et al. (2014) 8 “RR Lyrae” stars Gaia velocity errors 2% distance errors + Progenitor, same errors
8 RR Lyrae stars Gaia velocity errors 2% distance error
Price-Whelan et al. (2014)
Price-Whelan et al. (2014) 8 RR Lyrae stars 2% distance
errors No proper motions
Price-Whelan et al. (2014) Recover unobserved proper motion for stars
Nparams / 6Nstars Good: Bad: - test particle orbits (no
N-body) - arbitrary potentials - observational uncertainties / missing data - less sensitive to observational biases
Next Marginalize true phase-space positions of the stars Marginal likelihood
has fixed dimensionality set by potential params., progenitor params Price-Whelan et al. (in prep.)