Welcome to galpy’s documentation¶

galpy is a Python 2 and 3 package for galactic dynamics. It supports orbit integration in a variety of potentials, evaluating and sampling various distribution functions, and the calculation of action-angle coordinates for all static potentials.

Papers using galpy¶

galpy is described in detail in this publication:

• galpy: A Python Library for Galactic Dynamics, Jo Bovy (2015), Astrophys. J. Supp., 216, 29 (arXiv/1412.3451).

The following is a list of publications using galpy; please let me (bovy -at- ias.edu) know if you make use of galpy in a publication.

1. Tracing the Hercules stream around the Galaxy, Jo Bovy (2010), Astrophys. J. 725, 1676 (2010ApJ...725.1676B):

Uses what later became the orbit integration routines and Dehnen and Shu disk distribution functions.

2. The spatial structure of mono-abundance sub-populations of the Milky Way disk, Jo Bovy, Hans-Walter Rix, Chao Liu, et al. (2012), Astrophys. J. 753, 148 (2012ApJ...753..148B):

Employs galpy orbit integration in galpy.potential.MWPotential to characterize the orbits in the SEGUE G dwarf sample.

3. On the local dark matter density, Jo Bovy & Scott Tremaine (2012), Astrophys. J. 756, 89 (2012ApJ...756...89B):

Uses galpy.potential force and density routines to characterize the difference between the vertical force and the surface density at large heights above the MW midplane.

4. The Milky Way’s circular velocity curve between 4 and 14 kpc from APOGEE data, Jo Bovy, Carlos Allende Prieto, Timothy C. Beers, et al. (2012), Astrophys. J. 759, 131 (2012ApJ...759..131B):

Utilizes the Dehnen distribution function to inform a simple model of the velocity distribution of APOGEE stars in the Milky Way disk and to create mock data.

5. A direct dynamical measurement of the Milky Way’s disk surface density profile, disk scale length, and dark matter profile at 4 kpc < R < 9 kpc, Jo Bovy & Hans-Walter Rix (2013), Astrophys. J. 779, 115 (2013ApJ...779..115B):

Makes use of potential models, the adiabatic and Staeckel actionAngle modules, and the quasiisothermal DF to model the dynamics of the SEGUE G dwarf sample in mono-abundance bins.

6. The peculiar pulsar population of the central parsec, Jason Dexter & Ryan M. O’Leary (2013), Astrophys. J. Lett., 783, L7 (2014ApJ...783L...7D):

Uses galpy for orbit integration of pulsars kicked out of the Galactic center.

7. Chemodynamics of the Milky Way. I. The first year of APOGEE data, Friedrich Anders, Christina Chiappini, Basilio X. Santiago, et al. (2013), Astron. & Astrophys., 564, A115 (2014A&A...564A.115A):

Employs galpy to perform orbit integrations in galpy.potential.MWPotential to characterize the orbits of stars in the APOGEE sample.

8. Dynamical modeling of tidal streams, Jo Bovy (2014), Astrophys. J., 795, 95 (2014ApJ...795...95B):

Introduces galpy.df.streamdf and galpy.actionAngle.actionAngleIsochroneApprox for modeling tidal streams using simple models formulated in action-angle space (see the tutorial above).

9. The Milky Way Tomography with SDSS. V. Mapping the Dark Matter Halo, Sarah R. Loebman, Zeljko Ivezic Thomas R. Quinn, Jo Bovy, Charlotte R. Christensen, Mario Juric, Rok Roskar, Alyson M. Brooks, & Fabio Governato (2014), Astrophys. J., 794, 151 (2014ApJ...794..151L):

Uses galpy.potential functions to calculate the acceleration field of the best-fit potential in Bovy & Rix (2013) above.

10. The power spectrum of the Milky Way: Velocity fluctuations in the Galactic disk, Jo Bovy, Jonathan C. Bird, Ana E. Garcia Perez, Steven M. Majewski, David L. Nidever, & Gail Zasowski (2015), Astrophys. J., 800, 83 (arXiv/1410.8135):

Uses galpy.df.evolveddiskdf to calculate the mean non-axisymmetric velocity field due to different non-axisymmetric perturbations and compares it to APOGEE data.

11. Generation of mock tidal streams, Mark A. Fardal, Shuiyao Huang, & Martin D. Weinberg (2014), Mon. Not. Roy. Astron. Soc., submitted (arXiv/1410.1861):

Uses galpy.potential and galpy.orbit for orbit integration in creating a particle-spray model for tidal streams.

12. The nature and orbit of the Ophiuchus stream, Branimir Sesar, Jo Bovy, Edouard J. Bernard, et al. (2015), Astrophys. J., submitted (arXiv/1501.00581):

Uses the Orbit.fit routine in galpy.orbit to fit the orbit of the Ophiuchus stream to newly obtained observational data and the routines in galpy.df.streamdf to model the creation of the stream.

13. The LMC geometry and outer stellar populations from early DES data, Eduardo Balbinot, B. X. Santiago, L. Girardi, et al. (2015), Mon. Not. Roy. Astron. Soc., 449, 1129 (arXiv/1502.05050):

Employs galpy.potential.MWPotential as a mass model for the Milky Way to constrain the mass of the LMC.

14. Young Pulsars and the Galactic Center GeV Gamma-ray Excess, Ryan M. O’Leary, Matthew D. Kistler, Matthew Kerr, & Jason Dexter (2015), Phys. Rev. Lett., submitted (arXiv/1504.02477):

Uses galpy orbit integration and galpy.potential.MWPotential2014 as part of a Monte Carlo simulation of the Galactic young-pulsar population.

Acknowledging galpy¶

If you use galpy in a publication, please cite the following paper

• galpy: A Python Library for Galactic Dynamics, Jo Bovy (2015), Astrophys. J. Supp., 216, 29 (arXiv/1412.3451).

and link to http://github.com/jobovy/galpy. Please also send me a reference to the paper or send a pull request including your paper in the list of galpy papers on this page (this page is at doc/source/index.rst). Thanks!

When using the galpy.actionAngle.actionAngleAdiabatic and galpy.actionAngle.actionAngleStaeckel modules, please cite 2013ApJ...779..115B in addition to the papers describing the algorithm used. When using galpy.actionAngle.actionAngleIsochroneApprox, please cite 2014ApJ...795...95B, which introduced this technique.