The LHCb Masterclass explained

For the outreach programme LHCb Masterclass students from secondary schools are invited to analyze a sample of D0 → K− pi+ decays as collected from the LHCb experiment to measure the lifetime of the D0 meson.

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The website of the LHCb International Masterclass, where the excercise is shortly explained can be found at this link.

Static jupyer notebook: https://github.com/landerlini/MLINFN-TutorialNotebooks/blob/master/LHCbMasterclassExplained.ipynb

Requirements 

To run this exercise you will need python3, tensorflow 1.x and PyROOT for python3. 

Contents

With this tutorial, we will introduce the following topics:

1. Download data with jupyter via http 
2. Exploring a dataset with pandas 
3. Exploring a dataset with matplotlib
4. Obtaining high quality plots with ROOT
5. Modelling the data with RooFit 
6. Perform a per-event subtraction of the background using sPlot
7. Training a simple neural network on nTuple data with keras
8. Evaluate the performance of the trained algorithm
9. Apply the neural network to data
10. Studying systematic effects induced by the neural network