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. 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. The library supports many common formats, such as .stl, .off, .ply, .mesh and tetgen's .node and .face. These properties make the application of this implementation straightforward to (re-)use in an arbitrary context.     «

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. 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 parall...     »