galpy: A python LIBRARY FOR GALACTIC DYNAMICS

By Jo Bovy. 2014

1,007 citations recorded by the source corpus.

I describe the design, implementation, and usage of galpy, a python package for galactic-dynamics calculations. At its core, galpy consists of a general framework for representing galactic potentials both in python and in C (for accelerated computations); galpy functions, objects, and methods can generally take arbitrary combinations of these as arguments. Numerical orbit integration is supported with a variety of Runge–Kutta-type and symplectic integrators. For planar orbits, integration of the phase-space volume is also possible. galpy supports the calculation of action–angle coordinates and orbital frequencies for a given phase-space point for general spherical potentials, using state-of-the-art numerical approximations for axisymmetric potentials, and making use of a recent general approximation for any static potential. A number of different distribution functions (DFs) are also included in the current release; currently, these consist of two-dimensional axisymmetric and non-axisymmetric disk DFs, a three-dimensional disk DF, and a DF framework for tidal streams. I provide several examples to illustrate the use of the code. I present a simple model for the Milky Way's gravitational potential consistent with the latest observations. I also numerically calculate the Oort functions for different tracer populations of stars and compare them to a new analytical approximation. Additionally, I characterize the response of a kinematically warm disk to an elliptical m = 2 perturbation in detail. Overall, galpy consists of about 54,000 lines, including 23,000 lines of code in the module, 11,000 lines of test code, and about 20,000 lines of documentation. The test suite covers 99.6% of the code. galpy is available at http://github.com/jobovy/galpy with extensive documentation available at http://galpy.readthedocs.org/en/latest.

Subfields: Astronomy and Astrophysics, Global and Planetary Change, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/335f3deaa48d17e9d545d6010d06a7b7f3b1bcad

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Citations in the corpus

The origin of accreted stellar halo populations in the Milky Way using APOGEE,Gaia, and the EAGLE simulations (2018, methodology): “All estimates are performed using the implementation of the Stäckel approximation in the python package galpy (Bovy 2015), and assuming the MWPotential2014 MilkyWay mass model included in galpy.”
The total mass of the Large Magellanic Cloud from its perturbation on the Orphan stream (2018, methodology): “Assuming a progenitor mass of 107 M and a pericentre of 15 kpc, this would correspond to a tidal radius of 493 pc and thus a velocity dispersion of ∼5 km s−1 in MWPotential2014 from Bovy (2015).”
THE SHAPE OF THE INNER MILKY WAY HALO FROM OBSERVATIONS OF THE PAL 5 AND GD–1 STELLAR STREAMS (2016, methodology): “Unlike Bovy (2015), we allow the Sun’s distance to the Galactic center R0 and the circular velocity Vc(R0) at R0 to vary.”
The GALAH+ survey: Third data release (2020, methodology): “For the calculation of orbit information we use version 1.6 of the python packagegalpy (Bovy 2015).”
The biggest splash (2019, methodology): “Actions have been calculated using the GALPY package (Bovy 2015), adopting the MWPotential2014 model for the potential.”
The hidden giant: discovery of an enormous Galactic dwarf satellite in Gaia DR2 (2018, methodology): “We apply the kinematics of Ant 2 obtained above to gauge the satellite’s orbital properties using galpy (Bovy 2015).”
Constraints on Radial Migration in Spiral Galaxies - II. Angular momentum distribution and preferential migration (2018, background): “Bovy (2015) investigated the response of both cold and warm 2D discs to a non-axisymmetric perturbation and found that the warmer the disc, the less it responded.”
Towards constraining warm dark matter with stellar streams through neural simulation-based inference (2020, methodology): “We use the streampepperdf simulator2 that is based within the galpy framework (Bovy 2015) tomodel stream-subhalo interactions.”
In Disguise or Out of Reach: First Clues about In Situ and Accreted Stars in the Stellar Halo of the Milky Way from Gaia DR2 (2018, methodology): “…parameters, by integrating their orbits over the last 6 Gyr, using four different Galaxy potentials: the axisymmetric potential of Allen & Santillan (1991), the two axisymmetric potentials, including a thick disc component, in Pouliasis et al (2017), and the MWpotential2014 from Bovy (2015).”
Dissecting stellar chemical abundance space with t-SNE (2018, methodology): “…/ TGAS positions and proper motions, radial velocities from Adibekyan et al. (2012), our StarHorse distances, and the orbit-integration tool galpy (Bovy 2015), using the new Staeckel approximation implementation of Mackereth & Bovy (2018) to determine orbital eccentricities e and maximum heights…”
Painting a portrait of the Galactic disc with its stellar clusters (2020, methodology): “For the MWPotential2014 which was shipped with galpy (Bovy 2015), the relation is close to Zmax ∝ v1.”
Vertical waves in the solar neighbourhood inGaiaDR2 (2018, methodology): “They are first transformed to the rectangular Galactic coordinate frame using the galpy.util Python package2 (Bovy 2015).”
Gaia DR2 proper motions of dwarf galaxies within 420 kpc (2018, methodology): “For the MW dark matter halo mass we explore two cases: a light halo with virial mass 0.8×1012M⊙ (Bovy 2015) and an heavier model, identical to MWPotential14 but for the MW DM halo virial mass, which is 1.6×1012M⊙ (Fritz et al. 2017).”
The GALAH survey and Gaia DR2: dissecting the stellar disc’s phase space by age, action, chemistry, and location (2018, background): “Our actions were compared to those computed from galpy (Bovy 2015) and the results are broadly similar given the observational uncertainties.”
The vertical metallicity gradients of mono-age stellar populations in the Milky Way with the RAVE and Gaia data (2017, methodology): “The RAVE web site is at http://www.ravesurvey.org We thank Jo Bovy for making GALPY publicly available (Bovy 2015) and to Željko Ivezić, Andrew J. Connolly, Jacob T. VanderPlas and Alexander Gray for doing the same with astroML (Vanderplas et al. 2012).”
Evidence from the H3 Survey That the Stellar Halo Is Entirely Comprised of Substructure (2020, background): “This potential, based on Bovy (2015), is composed of a Hernquist (1990) nucleus (m=1.7×109Me, a=1 kpc) and bulge (m=5×109Me, a=1 kpc), a Miyamoto & Nagai (1975) disk (m=6.8×1010Me, a”
Untangling the Galaxy. I. Local Structure and Star Formation History of the Milky Way (2019, methodology): “The positions are then converted into the heliocentric XYZ reference frame, and the UVW velocity vectors are computed using GalPy (Bovy 2015).”
Proper motions and dynamics of the Milky Way globular cluster system fromGaiaDR2 (2018, background): “For comparison, we also show the circular velocity of our default potential, taken from McMillan (2017), and the one from Bovy (2015) (MWPotential2014).”