Welcome to BrahMap

This project is currently under active development!!!

BrahMap is a scalable and modular map-making framework for CMB experiments. It features a user-friendly Python interface for the linear operators used in map-making. The Python interface seamlessly handles the workflow while delegating the heavy computations to highly optimized C++ extensions. In addition to the core linear operators, BrahMap offers a wrapper for Generalized Least Squares (GLS) map-making using a Preconditioned Conjugate Gradient (PCG) solver. BrahMap is also fully integrated with litebird_sim through dedicated wrappers.

For a quick introduction to map-making with BrahMap, refer to the quick start guide. For a complete reference to the BrahMap API, refer to the API reference. Complete example notebooks and scripts can be found here. A performance benchmarking suite for the core numerical routines can be found in the benchmarks directory.

You can find detailed information on the implementation and features of BrahMap at arXiv:2501.16122.

Citation

This work can be cited with:

@misc{anand2025brahmap,
      title={\texttt{BrahMap}: A scalable and modular map-making framework for the CMB experiments}, 
      author={Avinash Anand and Giuseppe Puglisi},
      year={2025},
      eprint={2501.16122},
      archivePrefix={arXiv},
      primaryClass={astro-ph.CO},
      url={https://arxiv.org/abs/2501.16122}, 
}

Acknowledgement

This work is supported by Italian Research Center on High Performance Computing, Big Data and Quantum Computing (ICSC), project funded by European Union - NextGenerationEU - and National Recovery and Resilience Plan (NRRP) - Mission 4 Component 2 within the activities of Spoke 3 (Astrophysics and Cosmos Observations).