boss_bench

The BoSS: a benchmark of stellarator simulations

The BoSS: a benchmark of stellarator simulations#

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The Benchmark of Stellarator Simulations (BoSS) is a database of stellarator configurations paired with physics simulations. It holds about 3 TB of data from ideal MHD and collisionless guiding-center simulations of roughly 180,000 stellarators. The database keeps growing: new configurations are added over time, and results from other kinds of simulation will be added as new sections. It can be used to develop machine-learning methods for fusion applications, or to improve our understanding of the underlying physics.

A burst of 400 alpha particles followed along their guiding-center orbits in one stellarator configuration. Orange marks show where lost particles strike the plasma boundary. The panel on the right counts the particles lost so far: the loss fraction is the share of the 400 particles that have been lost, and the loss rate is the number of particles lost per millisecond at each moment.

Installation#

The BoSS comes with a Python package for working with the data: reading the files, computing derived quantities such as loss fractions and heat fluxes, and evaluating models with the benchmark’s metrics. It needs Python 3.9 or newer. Install it with:

pip install boss-bench

From source#

git clone https://github.com/mishapadidar/boss_bench.git
cd boss_bench
pip install .

See the package documentation for how to use it.

Citing the BoSS#

If you find this project useful for your research, please consider citing:

The BibTeX entry is below.

@unpublished{boss,
  author       = {Author, A. and Author, B. and Author, C.},
  title        = {The {BoSS}: a benchmark of stellarator simulations},
  eprint       = {XXXX.XXXXX},
  eprinttype   = {arxiv},
  eprintclass  = {physics.plasm-ph},
  year         = 2026,
  doi          = {XX.XXXXX/XXXXX},
}

License#

The data is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. The boss-bench package is released under the Apache License 2.0. Copyright 2026 The Simons Foundation.

Contact#

For questions regarding this project, please contact Misha Padidar.

Acknowledgments#

We thank the Flatiron Institute’s Scientific Computing Core and the Simons Foundation.