Transformer Models for Symbolic Calculations of Squared Amplitudes in HEP


One of the most important physical quantities in particle physics is the cross section, or a probability that a particular process takes place in the interaction of elementary particles. Its measure provides a testable link between theory and experiment. It is obtained theoretically mainly by calculating the squared amplitude. The approach we use in this project is to treat the amplitude and squared amplitude as mathematical symbolic expressions and use language-translation models to map from the amplitude to squared-amplitude.


Total project length: 175/350 hours.

Task ideas and expected results


Significant experience with Transformer machine learning models in Python (preferably using pytorch).

Difficulty Level



Please use this link to access the test for this project.


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Corresponding Project

Participating Organizations