BrahMap: A scalable and modular map-making framework for the CMB experiments
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| Format: | Preprint |
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2025
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| _version_ | 1866917058501935104 |
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| author | Anand, Avinash Puglisi, Giuseppe |
| author_facet | Anand, Avinash Puglisi, Giuseppe |
| contents | The cosmic microwave background (CMB) experiments have reached an era of unprecedented precision and complexity. Aiming to detect the primordial B-mode polarization signal, these experiments will soon be equipped with $10^{4}$ to $10^{5}$ detectors. Consequently, future CMB missions will face the substantial challenge of efficiently processing vast amounts of raw data to produce the initial scientific outputs - the sky maps - within a reasonable time frame and with available computational resources. To address this, we introduce BrahMap, a new map-making framework that will be scalable across both CPU and GPU platforms. Implemented in C++ with a user-friendly Python interface for handling sparse linear systems, BrahMap employs advanced numerical analysis and high-performance computing techniques to maximize the use of super-computing infrastructure. This work features an overview of the BrahMap's capabilities and preliminary performance scaling results, with application to a generic CMB polarization experiment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_16122 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | BrahMap: A scalable and modular map-making framework for the CMB experiments Anand, Avinash Puglisi, Giuseppe Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics The cosmic microwave background (CMB) experiments have reached an era of unprecedented precision and complexity. Aiming to detect the primordial B-mode polarization signal, these experiments will soon be equipped with $10^{4}$ to $10^{5}$ detectors. Consequently, future CMB missions will face the substantial challenge of efficiently processing vast amounts of raw data to produce the initial scientific outputs - the sky maps - within a reasonable time frame and with available computational resources. To address this, we introduce BrahMap, a new map-making framework that will be scalable across both CPU and GPU platforms. Implemented in C++ with a user-friendly Python interface for handling sparse linear systems, BrahMap employs advanced numerical analysis and high-performance computing techniques to maximize the use of super-computing infrastructure. This work features an overview of the BrahMap's capabilities and preliminary performance scaling results, with application to a generic CMB polarization experiment. |
| title | BrahMap: A scalable and modular map-making framework for the CMB experiments |
| topic | Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2501.16122 |