This is a collection of Reading Material for students of Particle Physics. Some lists are so long that they deserve their own dedicated page.
Literature on Supersymmetry
- Andreas Hoecker: "Physics at the LHC Run-2 and Beyond", arXiv:1611.07864
- lecture about LHC physics in Run 2 in general
- W. Hollik: "Quantum field theory and the Standard Model", arXiv:1012.3883
- the mathematics behind the SM
ROOT is a software framework particle physicists use for their analyses.
- ROOT homepage: http://root.cern.ch/
- Here you can download ROOT and find its documentation.
- How-to: https://root.cern.ch/drupal/content/howtos
- To get you started with ROOT (if you already know the very basics, i.e. how to launch ROOT, what its purpose is etc.) the best place is probably the how-to.
- User guide: http://root.cern.ch/drupal/content/users-guide
- The user guide is a very comprehensive documentation of ROOT. You'll need some time to work through this.
- Tutorials: http://root.cern.ch/root/html/tutorials/
- The tutorials are rather specific, so they are mostly useful if you want to see an example of how to fulfill a given task. They offer little explanation and generally cannot be recommended for starters.
- Reference: https://root.cern.ch/root/html/ClassIndex.html
- The class index lists all classes defined in ROOT. It's the reference if you want to look up syntax or methods available in a given class.
The material of the introductory course for our Bachelor students can be found here:
- Günter Duckeck, Johannes Elmsheuser, "Blockkurs: Datenauswertung in der Teilchenphysik" (2014)
This is helpful not only for beginners in the field of Supersymmetry but for particle physics in general as it covers the basic techniques, relevant software frameworks etc. that are common to most particle physics analyses.
ATLAS Introductory Material
This material is ATLAS-specific and therefore password-protected.
- ATLAS-D tutorials (one day tutorial before the yearly ATLAS-D workshop, cf. e.g. 2018)
- ATLAS Software Tutorial (cf. ATLAS TWiki: SoftwareTutorial, takes place regularly (~ 4x a year) at CERN, one week)
- ATLAS Induction Day (recently became part of ATLAS Software Tutorials, cf. e.g. 2017 edition)
- Ian Goodfellow and Yoshua Bengio and Aaron Courville: "Deep Learning", free textbook
- Michael Kagan’s Academic Training Lectures, slides
- Stanford Course Machine Learning link
- Andreas C. Müller and Sarah Guido: "Introduction to Machine Learning with Python - A Guide for Data Scientists" (nicely written introduction with many examples but without technical details)
Dark Matter at ATLAS
- Searching for Dark Matter with the ATLAS detector (introductory / overview article for general audience from 2019)