Giving Pandas a ROOT to Chew on

Modern big data front and backends in the hunt for Dark Matter
Image: Membrane Club

Most matter in our Universe is “dark matter”, yet it remains invisible to our instruments. What constitutes dark matter is one of the most intriguing questions in modern physics.

Dark matter is the “Wild West” of physics research; in the coming few years researchers aim to discover what most of our Universe’s matter consists of. There is a tension between our novel Big Data solutions and the existing methods used in Big Science (e.g., Large Hadron Collider experiments). This project presents a way to harmonize these two ecosystems. The goal is to organize software and data such that researchers can work with existing particle physics infrastructure, yet still use modern communal Big Data tools.

A new computing model will be prototyped for small-to-mediumsized particle physics experiments, and the barrier for large experiments to benefit from advances in modern data analytics will be lowered. In addition to helping researchers discover dark matter interactions, this project will help shifting particle physics toward non-domain-specific codes.


  • Christopher Tunnell
    National Institute for Subatomic Physics