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Jupyter Notebooks

Uproot

Higgs to ZZ

This notebook uses ATLAS Open Data to show you the steps to rediscover the Higgs boson yourself! You will discover the Higgs boson decaying into a pair of Z bosons, which are in turn decaying into a lepton-antilepton pair each.
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Higgs to ZZ with Boosted Decision Tree

This notebook uses ATLAS Open Data to show you the steps to apply a Machine Learning approach to discover the Higgs boson yourself! You will discover the Higgs boson decaying into a pair of Z bosons, which are in turn decaying into a lepton-antilepton pair each, and you will learn how to use a boosted decision tree (BDT) like a professional data analist in Physics!
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Higgs to ZZ with a neural network

This notebook uses ATLAS Open Data to show you the steps to apply a Machine Learning approach to discover the Higgs boson yourself! You will discover the Higgs boson decaying into a pair of Z bosons, which are in turn decaying into a lepton-antilepton pair each, and you will learn how to use a simple neural network like a professional data analist in Physics!
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Higgs to ZZ with the Coffea framework

This notebook uses ATLAS Open Data to show you the steps to rediscover the Higgs boson yourself, with the Coffea framework!
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Higgs to γγ analysis

This notebook uses ATLAS Open Data to show you the steps to rediscover the Higgs boson yourself! You will discover the Higgs boson decaying into two photons.
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Seeking the Invisible: Dark Matter Search with Neural Networks at ATLAS

This notebook deals with a search for Dark Matter with neural networks at the ATLAS Experiment at the LHC, using ATLAS Open Data.
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Find the Z boson yourself!

This notebook uses ATLAS Open Data to show you the steps to find the shape of the resonance of the Z boson.
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Search for the Graviton yourself!

This notebook uses ATLAS Open Data to show you the steps to search for the Graviton yourself!
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Machine Learning for ttZ opposite-sign dilepton analysis

This notebook uses ATLAS Open Data to show you the steps to implement Machine Learning in the opposite-sign dilepton analysis, with a special focus on the definition of the learning rate, following the ATLAS published paper Measurement of the ttZ and ttW cross sections in proton-proton collisions at sqrt(s)= 13 TeV with the ATLAS detector".
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Machine Learning for ttZ in ATLAS

This notebook uses ATLAS Open Data to show you the steps to implement Machine Learning in the opposite-sign dilepton analysis, following the ATLAS published paper Measurement of the ttZ and ttW cross sections in proton-proton collisions at sqrt(s)= 13 TeV with the ATLAS detector".
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Machine Learning and BDT for ttZ in ATLAS

This notebook uses ATLAS Open Data to show you the steps to implement Machine Learning, in particular a boosted decision tree, in the opposite-sign dilepton analysis, following the ATLAS published paper Measurement of the ttZ and ttW cross sections in proton-proton collisions at sqrt(s)= 13 TeV with the ATLAS detector".
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C++

An introductional notebook to HEP analysis in C++

This notebook helps you to find an easy set of commands that show some basic computing techniques commonly used in High Energy Physics (HEP) analyzes, in few lines of code. It also shows how to create an histogram, fill it and draw it. Moreover it is an introduction to ROOT too. The final output is a plot with the number of leptons. The library used is ROOT, a scientific data analysis software framework that provides a large set of functionalities needed to deal with big data processing, statistical analysis, visualisation and storage.
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Searching for the Higgs boson in the H→γγ channel

This notebook uses ATLAS Open Data to show you the steps to rediscover the Higgs boson decaying in two photons.
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Python

Get running the full H→γγ analysis using the 13 TeV dataset in 5 minutes!

The analysis is based on the 13 TeV Open Data by the ATLAS Experiment. The ATLAS note ATL-OREACH-PUB-2020-001 can be used as a guide on the content, properties, capabilities and limitations of the released datasets. In this tutorial, in about 5 minutes you are going to re-produce the H→γγ analysis plots from the note.
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Invariant mass recontruction using TLorentz_vectors

The analysis presented in this notebook consists in searching for events where one or two Z bosons decay to two (or four) leptons of same flavour and opposite charge.
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Simple two-samples comparison

The analysis presented in this notebook consists in comparing the kinematics between events coming from the Standard Model Higgs boson decaying to two W bosons to those coming from the Standard Model WW-diboson background production.
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A simple introductional notebook to HEP analysis in python

In this notebook you can find an easy set of commands that show the basic computing techniques commonly used in high energy physics (HEP) analyzes. It also shows how to create a histogram, fill it and draw it. Moreover it is an introduction to ROOT too. At the end you get a plot with the number of leptons.
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Searching for the Higgs boson in the H→γγ channel

In this notebook you can learn how to discover the Higgs boson at the LHC, using ATLAS Open Data.
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RDataFrame

Searching for the Higgs boson in the H→γγ channel in RDataFrame

In this notebook you can learn how to discover the Higgs boson at the LHC in the two-photon channel, using ATLAS Open Data and ROOTDataFrame.
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A simple example for the Higgs boson decay in the H→γγ channel in RDataFrame

In this notebook you can inspect a simple example to discover the Higgs boson at the LHC in the two-photon channel, using ATLAS Open Data and ROOTDataFrame.
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Kaggle Notebooks

Python

Introduction to Machine Learning completed

This notebook uses ATLAS Open Data to show you the steps to apply a Machine Learning approach to discover the Higgs boson yourself! You will discover the Higgs boson decaying into a pair of Z bosons, which are in turn decaying into a lepton-antilepton pair each.
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[Matplotlib Data vs MC(https://www.kaggle.com/code/meirinevans/matplotlib-data-vs-mc)

This notebook uses ATLAS Open Data to show you the steps to apply a Machine Learning approach to discover the Higgs boson yourself! In particular, you will learn how to use the Matplotlib tool to compare real data from the ATLAS Experiment at the LHC with simulated Monte Carlo data, which are generated to mimic the real Physics of the Higgs boson.
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How to rediscover the Higgs!

This notebook uses ATLAS Open Data to show you the steps to apply a Machine Learning approach to discover the Higgs boson yourself!
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How to rediscover the Higgs!

This notebook uses ATLAS Open Data to show you the steps to apply a Machine Learning approach to discover the Higgs boson yourself!
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W branching ratio

This notebook uses ATLAS Open Data to show you the steps to measure the W-boson decay branching ratios yourself!
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