# heyoka.py#

The heyókȟa […] is a kind of sacred clown in the culture of the Sioux (Lakota and Dakota people) of the Great Plains of North America. The heyoka is a contrarian, jester, and satirist, who speaks, moves and reacts in an opposite fashion to the people around them.

heyoka.py is a Python library for the integration of ordinary differential equations (ODEs) via Taylor’s method. Notable features include:

• support for both double-precision and extended-precision floating-point types (80-bit and 128-bit),

• the ability to maintain machine precision accuracy over tens of billions of timesteps,

• high-precision zero-cost dense output,

• accurate and reliable event detection,

• batch mode integration to harness the power of modern SIMD instruction sets,

• ensemble simulations and automatic parallelisation,

• interoperability with SymPy,

• a high-performance implementation of Taylor’s method based on automatic differentiation techniques and aggressive just-in-time compilation via LLVM.

heyoka.py is based on the heyoka C++ library.

If you are using heyoka.py as part of your research, teaching, or other activities, we would be grateful if you could star the repository and/or cite our work. For citation purposes, you can use the following BibTex entry, which refers to the heyoka.py paper (arXiv preprint):

@article{10.1093/mnras/stab1032,
author = {Biscani, Francesco and Izzo, Dario},
title = "{Revisiting high-order Taylor methods for astrodynamics and celestial mechanics}",
journal = {Monthly Notices of the Royal Astronomical Society},
volume = {504},
number = {2},
pages = {2614-2628},
year = {2021},
month = {04},
issn = {0035-8711},
doi = {10.1093/mnras/stab1032},
url = {https://doi.org/10.1093/mnras/stab1032},