PROJECTS

Big Data: ATLAS

Unlock big data.

 

Empowering young people with the skills to explore their own questions in particle physics.

Project timeline

Phase1
4Weeks timeframe

Prepare & launch: Teachers get ready and launch Big Data: ATLAS, using our helpful guidance documents.

timeline-arrow-icon
Phase2
11Weeks timeframe

Background research & skills development:

With access to our support materials, students develop the knowledge and skills required to successfully complete research. Hosted securely on the Rutherford Appleton Laboratory server, the online resources provide training in using Python to access and manipulate the ATLAS data and ultimately to search for the Higgs Boson.

timeline-arrow-icon
Phase3
18Weeks timeframe

Student research: Using the skills acquired in Phase 2, students are provided with structured support to enable them to develop a research idea of their own using the ATLAS data. Who knows what discoveries lie hidden in the data?

timeline-arrow-icon
Phase4
9Weeks timeframe

Artefact development and conference: Students produce an article, academic poster presentation or academic paper, based on their research process and/or findings with the aim of exhibiting at IRIS’ conference.

timeline-arrow-icon

Overview

Skill level
Advanced
Age
suitability
16+
SubjectsPARTICLE PHYSICS/ COMPUTER SCIENCE/MATHS
SubjectsPARTICLE PHYSICS/ COMPUTER SCIENCE/MATHS

The ATLAS detector is used by physicists to observe the results of the collissions of particles in the Large Hadron Collider at CERN in Geneva. It’s one of just two colliders and the largest ever constructed for this purpose.

 

Big Data: ATLAS introduces to students the techniques used to analyse ATLAS data, giving them the chance to explore their own questions in particle physics.

 

Developed by IRIS with the University of Oxford and the Rutherford Appleton Laboratory for students who may not have never come across particle physics or computer programming before, it’s also hugely impactful for students passionate about these subjects.

 

Young people learn analytical and coding methods used by particle physicists. They develop critical skills in statistical analysis, Python computer programming, data presentation and interpretation of ATLAS Open-Source data, including how to find the Higgs Boson.

It was a nice introduction into particle physics even before we have learnt it in school.

SanjayWilson’s School