Computational Astrophysics, Data Science & AI/ML in Astronomy: A Perspective from Indian Community
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arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| author | Sharma, Prateek Vaidya, Bhargav Wadadekar, Yogesh Bagla, Jasjeet Chatterjee, Piyali Hanasoge, Shravan Kumar, Prayush Mukherjee, Dipanjan Philip, Ninan Sajeeth Singh, Nishant |
| author_facet | Sharma, Prateek Vaidya, Bhargav Wadadekar, Yogesh Bagla, Jasjeet Chatterjee, Piyali Hanasoge, Shravan Kumar, Prayush Mukherjee, Dipanjan Philip, Ninan Sajeeth Singh, Nishant |
| contents | In contemporary astronomy and astrophysics (A&A), the integration of high-performance computing (HPC), big data analytics, and artificial intelligence/machine learning (AI/ML) has become essential for advancing research across a wide range of scientific domains. These tools are playing an increasingly pivotal role in accelerating discoveries, simulating complex astrophysical phenomena, and analyzing vast amounts of observational data. For India to maintain and enhance its competitive edge in the global landscape of computational astrophysics and data science, it is crucial for the Indian A&A community to fully embrace these transformative technologies. Despite limited resources, the expanding Indian community has already made significant scientific contributions. However, to remain globally competitive in the coming years, it is vital to establish a robust national framework that provides researchers with reliable access to state-of-the-art computational resources. This system should involve the regular solicitation of computational proposals, which can be assessed by domain experts and HPC specialists, ensuring that high-impact research receives the necessary support. By building such a system, India can cultivate the talent, infrastructure, and collaborative environment necessary to foster world-class research in computational astrophysics and data science. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_03876 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Computational Astrophysics, Data Science & AI/ML in Astronomy: A Perspective from Indian Community Sharma, Prateek Vaidya, Bhargav Wadadekar, Yogesh Bagla, Jasjeet Chatterjee, Piyali Hanasoge, Shravan Kumar, Prayush Mukherjee, Dipanjan Philip, Ninan Sajeeth Singh, Nishant Instrumentation and Methods for Astrophysics In contemporary astronomy and astrophysics (A&A), the integration of high-performance computing (HPC), big data analytics, and artificial intelligence/machine learning (AI/ML) has become essential for advancing research across a wide range of scientific domains. These tools are playing an increasingly pivotal role in accelerating discoveries, simulating complex astrophysical phenomena, and analyzing vast amounts of observational data. For India to maintain and enhance its competitive edge in the global landscape of computational astrophysics and data science, it is crucial for the Indian A&A community to fully embrace these transformative technologies. Despite limited resources, the expanding Indian community has already made significant scientific contributions. However, to remain globally competitive in the coming years, it is vital to establish a robust national framework that provides researchers with reliable access to state-of-the-art computational resources. This system should involve the regular solicitation of computational proposals, which can be assessed by domain experts and HPC specialists, ensuring that high-impact research receives the necessary support. By building such a system, India can cultivate the talent, infrastructure, and collaborative environment necessary to foster world-class research in computational astrophysics and data science. |
| title | Computational Astrophysics, Data Science & AI/ML in Astronomy: A Perspective from Indian Community |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2501.03876 |