This repository demonstrates how the public data released by the CERN based ALICE collaboration can be analyzed with the Rust programming language. He

alice-rs/cbourjau

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2021-05-19 09:28:31

This repository demonstrates how the public data released by the CERN based ALICE collaboration can be analyzed with the Rust programming language.

Here are some example figures produced with this project. The first two show the distribution of produced particles in the longitudinal and azimuthal dimensions. The third figure shows where the collisions (aka events) took place along the direction of the particle beams in the collider. The last figure shows how many charged particles were produced per collision:

There are no dependencies on any ALICE specific software, nor ROOT itself. The software from this repository can be run on Linux, MacOS, and Windows.

ALICE (A Large Ion Collider Experiment) is the dedicated Heavy Ion experiment at the Large Hadron Collider (LHC) in Switzerland. Just like most other CERN based experiments, its goal is to better understand the fundamental particles and forces of the universe. In particular, ALICE is concerned with the so called strong force which is the dominant actor for processes within an atomic nuclei. Many of the properties of this force manifest them self at extreme pressures and temperatures as they were found micro seconds after the Big Bang. By colliding heavy nuclei such as lead ions at nearly the speed of light, we are able to recreate such extreme conditions for a very brief moment within the ALICE detector. By carefully studying the particles produced at such collisions we can deduce the properties of the strong force which will help us to better understand nuclear reactions, neutron stars, the first moments of the universe and much more.

ALICE, as well as some other CERN based experiments have released a small subset of their recorded data into the public domain. The dataset in question for this project is in total approximately 6TB. While some analyses really need all the data they can get, others (like the example one) can be run on just a ~1GB. With this project it is perfectly feasile to download the complete public dataset to a large external hard drive and run a complex analysis over night on a laptop.

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