Machine learning in the search for new fundamental physics

@article{Karagiorgi2021MachineLI,
  title={Machine learning in the search for new fundamental physics},
  author={Georgia Karagiorgi and Gregor Kasieczka and S. Kravitz and Benjamin Philip Nachman and David Shih},
  journal={Nature Reviews Physics},
  year={2021},
  volume={4},
  pages={399 - 412}
}
Compelling experimental evidence suggests the existence of new physics beyond the well-established and tested standard model of particle physics. Various current and upcoming experiments are searching for signatures of new physics. Despite the variety of approaches and theoretical models tested in these experiments, what they all have in common is the very large volume of complex data that they produce. This data challenge calls for powerful statistical methods. Machine learning has been in use… 

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