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 # Summary
 
 Polyhedral gravity models are essential for modeling the gravitational field of irregular bodies, such as asteroids and comets.
-We present an open-source C++ library for the efficient, parallelized computation of a polyhedral gravity model following the line integral approach by Tsoulis [@tsoulis2012analytical]. A slim, easy-to-use Python interface using *pybind11* accompanies the library. The library is particularly focused on delivering high performance and scalability, which we achieve through vectorization and parallelization with *xsimd* and *thrust*, respectively. For example, the average evaluation of 1 out of 1000 randomly sampled points took 253 microseconds on a M1 Pro chip for the mesh of Eros consisting of 7374 vertices and 14744 faces (see downscaled to 10% in \autoref{fig:mesh} [@gaskell2008eros]).
+We present an open-source C++ library for the efficient, parallelized computation of a polyhedral gravity model following the line integral approach by Tsoulis [@tsoulis2012analytical]. A slim, easy-to-use Python interface using *pybind11* accompanies the library. The library is particularly focused on delivering high performance and scalability, which we achieve through vectorization and parallelization with *xsimd* and *thrust*, respectively. For example, the average evaluation of 1 out of 1000 randomly sampled points took 253 microseconds on a M1 Pro chip for the mesh of Eros consisting of 7374 vertices and 14744 faces [see downscaled to 10% in \autoref{fig:mesh}, @gaskell2008eros].
 The library supports many common formats, such as *.stl*, *.off*, *.ply*, *.mesh* and *tetgen*'s *.node* and *.face* [@hang2015tetgen]. These properties make the application of this implementation straightforward to (re-)use in an arbitrary context.
 
 ![Downscaled mesh of (433) Eros to 10% of its original vertices and faces.\label{fig:mesh}](figures/eros_010.png){ width=50% }