Agentic AI for High Energy Physics Analyses at the CMS Detector

Description

The Compact Muon Solenoid (CMS) collaboration is a high energy particle collision detector experiment at the Large Hadron Collider. The group has developed extensive software packages for tasks ranging from Monte Carlo generation of data samples and reonstruction analysis software to tools for handling data structures and even plot generation. Developing and implementing software solutions for this subfield generally requires specialized knowledge of both physics and an extensive array of niche software tools developed by CMS. In order to assist and accelerate CMS analyses, this project aims to develop a specizlied AI agent following the HEPTAPOD framework.

Duration

Total project length: 175 hours.

Task ideas

Develop and test an AI physics agent following the HEPTAPOD framework.

Expected results

Complete an AI agent to accelerate and assist in CMS analyses.
Document results formally or informally to support ongoing research.

Requirements

C++, Python, PyTorch, Tensorflow, previous experience in Deep Learning.

Project difficulty level

Advanced

Mentors

Alexander Roman (University of Alabama)
Konstantin Matchev (University of Alabama)
Ruchi Chudasama (University of Alabama)
Emanuele Usai (University of Alabama)
Sergei Gleyzer (University of Alabama)

Test

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

Please DO NOT contact mentors directly by email. Questions should instead be directed to ml4-sci@cern.ch which is forwarded to mentors. To submit your proposal, CV, and test task solutions, please use this Google form.