The BTV exercise aims to demonstrate the concept of flavor tagging and its usage in analyses.
The first part of this exercise will cover the fundamental principle of b tagging, starting with understanding the discrimination power of the inputs to the tagging algorithm and is continued by evaluating the performance of the trained model.
The second part of this exercise will be dedicated to...
Electrons and photons are widely used and play an essential role in the success of CMS. They are indispensable for searches of new physics, including many models of supersymmetry. Knowing the characteristics of electrons and photons in the CMS detector is helpful. This long exercise shows how electrons and photons are reconstructed and how we get their correct energy. The attendees are assumed...
We discuss the clustering algorithms, reconstruction, and calibration of jets. We alternate slides with open questions, exercises in plain C++, and exercises with Jupyter notebooks in Python.
The students will be introduced to the luminosity measurement at CMS, perform their own luminosity calibration with 2023 data, and learn how to calculate the integrated luminosity of a data set.
In this session, we will start by introducing some basic concepts about muons: what they are, the sources of muons in CMS, the muon reconstruction algorithm, and the criteria used to select interesting muons for analyses.
After that, you can familiarize yourself with muons in three tasks resembling real analysis tasks:
The first exercise will get you familiar on how to handle muons in CMSSW:...
We discuss the clustering algorithms, reconstruction, and calibration of jets. We alternate slides with open questions, exercises in plain C++, and exercises with Jupyter notebooks in Python.
The students will be introduced to the luminosity measurement at CMS, perform their own luminosity calibration with 2023 data, and learn how to calculate the integrated luminosity of a data set.
In this session, we will start by introducing some basic concepts about muons: what they are, the sources of muons in CMS, the muon reconstruction algorithm, and the criteria used to select interesting muons for analyses.
After that, you can familiarize yourself with muons in three tasks resembling real analysis tasks:
The first exercise will get you familiar on how to handle muons in CMSSW:...
The exercises introduce the basics of track and vertex reconstruction at CMS. The main track reconstruction algorithms are discussed with explanations on how to understand and access the reconstructed quantities. A few implications on the physics analysis are illustrated. The exercises are based on the standard CMSSW workflows with pythonic interface for job configurations.
Electrons and photons are widely used and play an essential role in the success of CMS. They are indispensable for searches of new physics, including many models of supersymmetry. Knowing the characteristics of electrons and photons in the CMS detector is helpful. This long exercise shows how electrons and photons are reconstructed and how we get their correct energy. The attendees are assumed...
We discuss the clustering algorithms, reconstruction, and calibration of jets. We alternate slides with open questions, exercises in plain C++, and exercises with Jupyter notebooks in Python.
In this exercise you will learn to find the samples you need for an analysis and information about them, for instance their cross section or how they were produced. You will also learn how the CMS simulation chain works and how to run FullSim and FastSim on your own.
Tau leptons are excellent probes of electroweak physics, they decay before reaching the inner layers of the CMS tracker and require a dedicated reconstruction algorithm. With this exercise you will see how hadronically decaying tau leptons are identified with respect to jets, muons, and electrons, and measure the efficiency of the tau identification algorithm in order to measure the Z cross...
The exercises introduce the basics of track and vertex reconstruction at CMS. The main track reconstruction algorithms are discussed with explanations on how to understand and access the reconstructed quantities. A few implications on the physics analysis are illustrated. The exercises are based on the standard CMSSW workflows with pythonic interface for job configurations.
In this exercise you will learn to find the samples you need for an analysis and information about them, for instance their cross section or how they were produced. You will also learn how the CMS simulation chain works and how to run FullSim and FastSim on your own.
The forward proton detectors are new detectors introduced during LHC Run 2 by the CMS collaboration and are used to recontsruct scattered protons that emerge intact from the proton-proton interaction. In this exercise, we will learn about the process of proton reconstruction and its application in analysis, following the latest recommendations provided by the Proton Object Group.
Throughout...
