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Welcome to BrahMap

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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.

  • Installation – How to install and set up BrahMap on your system
  • Quick Start – A quick introduction to map-making with BrahMap
  • Examples – Complete example notebooks and scripts to get started
  • API Reference – A complete reference to the BrahMap API
  • Benchmarking – A performance benchmarking suite for core numerical routines

For detailed information on the implementation and features of BrahMap, please refer to the paper arXiv:2501.16122.

Citation

This work can be cited with:

@misc{anand2025brahmap,
      title={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).