figure from paper

Deep Potential

Recovering the Gravitational Potential from a Snapshot of Phase Space

Green, Ting & Kamdar (2023), ApJ.

ADS

9

figure from paper

A classifier for spurious astrometric solutions in Gaia eDR3

Rybizki*, Green*, Rix, et al. (2022), MNRAS.

*Equal contribution.

ADS code query

8

figure from paper

Data-driven Stellar Models

Green, Rix, Tschesche et al. (2021), ApJ.

ADS tutorial data

7

figure from paper

Deep Potential

Recovering the gravitational potential from a snapshot of phase space

Green & Ting (2020), arXiv:2011.04673.

ADS GitHub YouTube

6

figure from paper

A 3D Dust Map Based on Gaia, Pan-STARRS 1, and 2MASS

Green, Schlafly, Zucker, Speagle & Finkbeiner (2019), ApJ.

ADS project

5

figure from paper

Galactic reddening in 3D from stellar photometry

an improved map

Green, Schlafly, Finkbeiner et al. (2018), MNRAS.

ADS project

4

figure from paper

dustmaps

A Python interface for maps of interstellar dust

Green (2018), Journal of Open Source Software.

ADS code docs

3

figure from paper

A Three-dimensional Map of Milky Way Dust

Green, Schlafly, Finkbeiner et al. (2015), ApJ.

ADS project

2

figure from paper

Measuring Distances and Reddenings for a Billion Stars

Toward a 3D Dust Map from Pan-STARRS 1

Green, Schlafly, Finkbeiner et al. (2014), ApJ.

ADS

1

figure from paper

Parameters of 220 million stars from Gaia BP/RP spectra

Zhang, Green & Rix (2023), MNRAS.

ADS

32

figure from paper

Recovering the gravitational potential in a rotating frame

Deep Potential applied to a simulated barred galaxy

Kalda, Green & Ghosh (2023), arXiv:2310.00040.

ADS

31

figure from paper

Roman Early-Definition Astrophysics Survey Opportunity

Galactic Roman Infrared Plane Survey (GRIPS)

Paladini, [33 authors], Green, [35 authors] (2023), arXiv:2307.07642.

ADS

30

figure from paper

Quantifying the influence of bars on action-based dynamical modelling of disc galaxies

Ghosh, Trick & Green (2023), MNRAS.

ADS

29

figure from paper

The Dark Energy Camera Plane Survey 2 (DECaPS2)

More Sky, Less Bias, and Better Uncertainties

Saydjari, [3 authors], Green, [8 authors] (2023), ApJS.

ADS

28

figure from paper

An empirical model of the Gaia DR3 selection function

Cantat-Gaudin, [13 authors], Green (2023), A&A.

ADS

27

figure from paper

The First 3π 3D Map of ISM Dust Temperature

Zelko, Finkbeiner, Lee & Green (2022), arXiv:2211.07667.

ADS

26

figure from paper

Milky Way Satellite Census

IV. Constraints on Decaying Dark Matter from Observations of Milky Way Satellite Galaxies

Mau, [4 authors], Green, [64 authors] (2022), ApJ.

ADS

25

figure from paper

Science with the Ultraviolet Explorer (UVEX)

Kulkarni, [24 authors], Green, [30 authors] (2021), arXiv:2111.15608.

ADS

24

figure from paper

Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies

Nadler, [12 authors], Green, [55 authors] (2021), PRL.

ADS

23

figure from paper

Constraining the distance to the North Polar Spur with Gaia DR2

Das, [3 authors], Green, Alves, et al. (2020), MNRAS.

ADS

22

figure from paper

Planck 2018 results

XII. Galactic astrophysics using polarized dust emission

Planck Collaboration, [66 authors], Green, [95 authors] (2020), A&A.

ADS

21

figure from paper

Milky Way Satellite Census

II. Galaxy-Halo Connection Constraints Including the Impact of the Large Magellanic Cloud

Nadler, [3 authors], Green, [63 authors] (2020), ApJ.

ADS

20

figure from paper

A Galactic-scale gas wave in the solar neighbourhood

Alves, [7 authors], Green (2020), Nature.

ADS project Nature

19

figure from paper

A compendium of distances to molecular clouds in the Star Formation Handbook

Zucker, [2 authors], Green, [3 authors] (2020), A&A.

ADS

18

figure from paper

A Large Catalog of Accurate Distances to Local Molecular Clouds

The Gaia DR2 Edition

Zucker, [2 authors], Green, [3 authors] (2019), ApJ.

ADS

17

figure from paper

Overview of the DESI Legacy Imaging Surveys

A. Dey, [74 authors], Green, [85 authors] (2019), AJ.

ADS

16

figure from paper

Modeling the Connection between Subhalos and Satellites in Milky Way-like Systems

Nadler, Mao, Green & Wechsler (2019), ApJ.

ADS

15

figure from paper

The unWISE Catalog

Two Billion Infrared Sources from Five Years of WISE Imaging

Schlafly, Meisner & Green (2019), ApJS.

ADS catalog images

14

figure from paper

Mapping Distances across the Perseus Molecular Cloud Using CO Observations, Stellar Photometry, and Gaia DR2 Parallax Measurements

Zucker, [2 authors], Green, [3 authors] (2018), ApJ.

ADS

13

figure from paper

Quantitative reconstruction of seasonality from stable isotopes in teeth

D. Green, Smith, G. Green, et al. (2018), Geochimica et Cosmochimica Acta.

ADS

12

figure from paper

The DECam Plane Survey

Optical Photometry of Two Billion Objects in the Southern Galactic Plane

Schlafly, Green, Lang, et al. (2018), ApJS.

ADS catalog images

11

figure from paper

A Color-locus Method for Mapping RV Using Ensembles of Stars

Lee, Green, Schlafly, et al. (2018), ApJ.

ADS

10

figure from paper

Synchrotron imaging and Markov Chain Monte Carlo reveal tooth mineralization patterns

D. Green, G. Green, Colman, et al. (2017), PLoS ONE.

ADS

9

figure from paper

Mapping the Extinction Curve in 3D

Structure on Kiloparsec Scales

Schlafly, Peek, Finkbeiner & Green (2017), ApJ.

ADS

8

figure from paper

The Optical-infrared Extinction Curve and Its Variation in the Milky Way

Schlafly, [8 authors], Green, [12 authors] (2016), ApJ.

ADS

7

figure from paper

On Galactic Density Modeling in the Presence of Dust Extinction

Bovy, Rix, Green, Schlafly & Finkbeiner (2016), ApJ.

ADS

6

figure from paper

Constructing a Flexible Likelihood Function for Spectroscopic Inference

Czekala, Andrews, Mandel, Hogg & Green (2015), ApJ.

ADS

5

Starfish

Robust spectroscopic inference tools

Czekala, Andrews, Mandel, Hogg & Green (2015), ascl:1505.007.

ADS

4

figure from paper

Three-dimensional Dust Mapping Reveals that Orion Forms Part of a Large Ring of Dust

Schlafly, Green, Finkbeiner, et al. (2015), ApJ.

ADS data

3

figure from paper

A Map of Dust Reddening to 4.5 kpc from Pan-STARRS1

Schlafly, Green, Finkbeiner, et al. (2014), ApJ.

ADS data

2

figure from paper

A Large Catalog of Accurate Distances to Molecular Clouds from PS1 Photometry

Schlafly, Green, Finkbeiner, et al. (2014), ApJ.

ADS data

1

Dissertation Talk

10 May 2016 @ Cambridge, Massachusetts

European Week of Astronomy & Space Science

25 June 2015 @ Tenerife, Spain

Local Group Astrostatistics

2 June 2015 @ University of Michigan, Ann Arbor

Pan-STARRS 1 Science Consortium

24 June 2014 @ STScI, Baltimore

American Astronomical Society 224

3 June 2014 @ Boston

Sofja Kovalevskaja Group Leader (2020-)


Max Planck Institute for Astronomy, Heidelberg
Alexander von Humboldt Foundation

Independent Postdoc (2019-2020)


Max Planck Institute for Astronomy, Heidelberg
Advisor: Hans-Walter Rix

Porat Fellow (2016-2019)


Kavli Institute for Particle Astrophysics and Cosmology, Stanford University
Advisor: Risa Wechsler

Harvard Astronomy (2010-2016)


PhD: Mapping Milky Way Dust in 3D with Stellar Photometry
Advisor: Douglas Finkbeiner

U. of Michigan (2005-2009)


Ann Arbor
BA/BS in Physics (highest honors), History & German
ΦΒΚ (2009-)

U. of Freiburg (2007-2008)


Freiburg im Breisgau
Academic Year in Freiburg
Alte Geschichte
Deutsche Geschichte
Deutsche Sprache

Goethe-Institut (06-08.2006)


Berlin
German A2.1-B1.2

International Academy (2001-2005)


Bloomfield Hills, MI
IB Diploma
AP Biology, French

Bayesian Inference on Milky Way Datasets (October 2021)


Heidelberg University Physics Graduate Days
Instruction in German

Theoretical Physics 1 (PTP1, Winter 2020-21)


Heidelberg University
Teaching Assistant
Instruction in German

Astronomy 151: Fluids (Spring 2014)


Harvard
Teaching Fellow

Physics 15c: Waves (Fall 2013)


Harvard
Teaching Fellow

Fulbright ETA (Summer 2009-2010)


Dillingen, Saarland, DE
Albert-Schweitzer-Gymnasium
Technisch-Wissenschaftliches-Gymnasium
English Teaching Assistant

THCA Seminar


Milky Way Dust in 3D
14 July 2016

KIAA Lunch Talk


Milky Way Dust in 3D
14 July 2016

Dissertation Talk


Mapping Milky Way Dust in 3D with Stellar Photometry
Center for Astrophysics, Harvard University, Cambridge, MA
10 May 2016

Berkeley CosmoStats (2016)


Inferring Galactic Structure from a Billion Stellar Colors
UC Berkeley, CA
13 January 2016

Stanford/KIPAC Tea Talk


Mapping Milky Way Dust in 3D
10 November 2015

UK National Astronomy Meeting (2015)


A 3D Map of Dust from Pan-STARRS 1 Photometry
Llandudno, UK
7 July 2015

European Week of Astronomy & Space Science (2015)


A 3D Map of Dust from Pan-STARRS 1 Photometry
Tenerife, Spain
25 June 2015

Local Group Astrostatistics


Building a 3D Map of Milky-Way Dust
UMich, Ann Arbor
2 June 2015

AAS 225: Poster Session


Milky Way Stars and Dust in 3D
Seattle
6 January 2015

Carnegie Observatories: Morning Tea


3D Dust Mapping with Pan-STARRS 1
Pasadena
28 October 2014

Pan-STARRS 1 Science Consortium Meeting


3D Dust Mapping with PS1
STScI, Baltimore
24 June 2014

AAS 224: Poster Session


A 3D Dust Map from Pan-STARRS 1
Boston
3 June 2014

PS1 Key Project 5 Meeting


3D Dust Mapping: Method and Results
Max-Planck-Institut für Astrophysik, Heidelberg
4 March 2014

AAS 223: PS1 Special Session, Poster Session


Distances and Reddenings for a Billion Stars: Constructing a 3D Reddening Map
Chambliss Award Honorable Mention
Washington, DC
6/8 January 2014

PS1 Science Consortium Meeting


3D Dust: Method and First Results
Taipei
5 November 2013

MPIA Galaxy Coffee Talk


A 3D Dust Map from Stellar Photometry: A Bayesian Approach
Max-Planck-Institut für Astrophysik, Heidelberg
1 August 2013

PS1 Science Consortium Meeting


Producing a 3D Dust Map from Stellar Photometry
University of Durham, UK
13 August 2012