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Observable Optimization for Precision Theory Machine Learning Energy Correlators

A Bhattacharya, K Fraser, MD Schwartz - arXiv preprint arXiv:2508.10988, 2025 - arxiv.org
Physics paper hep-ph Suggest

… ML again proves to be an incredibly useful tool for parameter inference by providing methods that are broadly termed as neural simulation-based inference (NSBI) [55–60]. …

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BibTeX

@misc{bhattacharya2025observableoptimizationprecisiontheory,
title={Observable Optimization for Precision Theory Machine Learning Energy Correlators},
author={Arindam Bhattacharya and Katherine Fraser and Matthew D. Schwartz},
year={2025},
eprint={2508.10988},
archivePrefix={arXiv},
primaryClass={hep-ph},
url={https//arxiv.org/abs/2508.10988},
}

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