Physics Event Classification Using Large Language Models
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866929306336231424 |
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| author | Fanelli, Cristiano Giroux, James Moran, Patrick Nayak, Hemalata Suresh, Karthik Walter, Eric |
| author_facet | Fanelli, Cristiano Giroux, James Moran, Patrick Nayak, Hemalata Suresh, Karthik Walter, Eric |
| contents | The 2023 AI4EIC hackathon was the culmination of the third annual AI4EIC workshop at The Catholic University of America. This workshop brought together researchers from physics, data science and computer science to discuss the latest developments in Artificial Intelligence (AI) and Machine Learning (ML) for the Electron Ion Collider (EIC), including applications for detectors, accelerators, and experimental control. The hackathon, held on the final day of the workshop, involved using a chatbot powered by a Large Language Model, ChatGPT-3.5, to train a binary classifier neutrons and photons in simulated data from the \textsc{GlueX} Barrel Calorimeter. In total, six teams of up to four participants from all over the world took part in this intense educational and research event. This article highlights the hackathon challenge, the resources and methodology used, and the results and insights gained from analyzing physics data using the most cutting-edge tools in AI/ML. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_05752 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Physics Event Classification Using Large Language Models Fanelli, Cristiano Giroux, James Moran, Patrick Nayak, Hemalata Suresh, Karthik Walter, Eric Data Analysis, Statistics and Probability Machine Learning High Energy Physics - Experiment The 2023 AI4EIC hackathon was the culmination of the third annual AI4EIC workshop at The Catholic University of America. This workshop brought together researchers from physics, data science and computer science to discuss the latest developments in Artificial Intelligence (AI) and Machine Learning (ML) for the Electron Ion Collider (EIC), including applications for detectors, accelerators, and experimental control. The hackathon, held on the final day of the workshop, involved using a chatbot powered by a Large Language Model, ChatGPT-3.5, to train a binary classifier neutrons and photons in simulated data from the \textsc{GlueX} Barrel Calorimeter. In total, six teams of up to four participants from all over the world took part in this intense educational and research event. This article highlights the hackathon challenge, the resources and methodology used, and the results and insights gained from analyzing physics data using the most cutting-edge tools in AI/ML. |
| title | Physics Event Classification Using Large Language Models |
| topic | Data Analysis, Statistics and Probability Machine Learning High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2404.05752 |