Eides, Michael

Deep Learning for Analytical Amplitude Calculations:

This project deals with the state-of-the-art mathematical symbolic calculations of the elementary particle interaction amplitudes. We use deep learning models which can be trained to learn the mapping between two different expressions and contexts. We will include processes in both the standard model and beyond the standard model. We will use c++ language to generate the data that we need to train, and then we use Python to perform the training.

Goal:

Generate huge amounts of amplitudes and use them to train the deep learning model.

Participants:

Dr. Sergei Gleyzer (leader, U. of Alabama)

Dr. Harrison Prosper (Florida State U.)

Students:

Abdulhakim Alnuqaydan, Added 09/14/2021

Software:

Marty (C++)

Pytorch (Python)

Tensorflow (Python)