This lesson is in the early stages of development (Alpha version)

Monte Carlo Event Generators in HEP

Monte Carlo Event Generator (MCEG) play an essential in LHC analysis as well as in planning of Future Colliders. In this lesson we aim to introduce the basics involved in the event generators. In order to understand the essential ideas behind the MCEG and not just employ these tools as “black box” we provide a tutorial on how one can make their own MC generator. We also demonstrate how to use some of the well known packages like Madgraph, Pythia and Whizard to calculate cross sections as well as generate events. Finally as optional episode we overview the Machine Learning techniques that could be used to generate events at LHC.

Prerequisites

  • Basics of Shell (see e.g., https://swcarpentry.github.io/shell-novice/)
  • Python (see e.g., http://swcarpentry.github.io/python-novice-inflammation)

HSF Software Training

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This training module is part of the HSF Software Training Center, a series of training modules that serves HEP newcomers the software skills needed as they enter the field, and in parallel, instill best practices for writing software.

Schedule

Setup Download files required for the lesson
00:00 1. Introduction to LHC Event Generation Chain What are the monte carlo tools used to generate events at LHC?
How do the tools differ from each other?
00:35 2. Introduction to Monte Carlo Integration Techniques How to integrate a function using a monte carlo method?
What is the acceptance-rejection method?
01:10 3. How to make your own Monte Carlo Event Generator How to make your own monte carlo event generator using basic python?
01:45 4. Madgraph5 - Matrix Element Generator How to calculate cross section and generate events using Madgraph5?
02:20 5. Hadronization - Pythia8 How to calculate cross section and generate events using Pythia8?
02:55 6. LHC Event Generation Chain: Madgraph5_aMC@NLO and Pythia8 How to use Madgraph5_aMC@NLO and Pythia8 together?
03:30 7. Lepton Collider Event Generator: Whizard How to generate events using Whizard?
04:05 8. (Optional) Generative Adversarial Neural Network to generate LHC events How to use Generative Adversarial Neural Network to generate LHC events?
04:40 9. Summary
05:20 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

Authors

The following people contributed to the content of this lesson:
Note that this list does not include the contributors to the framework as developed by the carpentries.