| Name | Syed Mustafa Ahmed |
|---|---|
| Dated: | June, 2020 |
| For: | Numerical Computing |
The Particle collider at CERN bombards particles close to the speed of light. These collisions create a large amount of data collected by 8 different particle detectors. This data is immense in size (25 petabytes per year) and thus bottlenecks the number of collisions the facility can perform in a given period of time.
An algorithm that predicts the supposed trajectory of particles can focus on collecting data in more focused regions. Techniques that support storage more efficiently need to be implemented alongside the algorithm for better results. This can decrease the amount of space required per collision to save its data hence possibly aiding in costs, frequency of runs, data management etc. Additionally, numerous other optimization steps can be added to this methodology to ensure the best results.
This assignment/project is supposed to be an amateur's attempt at solving problems that already may have been solved. The purpose of the project was to see what solutions I could come up with using the limited knowledge of the particle colliders, physics, mathematics and the things I learnt from the Numerical Computing course. Still, I do appreciate any form of critique.