Data Products and Processing Tutorial
Tutorial Session Goal
This tutorial will explore the data products used in Mu2e and the modules and algorithms which create them. It is part of the June 2019 Computing and Software tutorial
Session Prerequisites and Advance Preparation
This tutorial assumes knowledge of art and the Mu2e detector. You will need to understand basic principles of how modules and event processing function in art. You will need to understand C++ data structures and fundamental types. You should have completed the following tutorials:
- Mu2e detector overview
- Mu2e_Offline_Tutorial
- Running_Art_Tutorial
Session Introduction
The information content of Mu2e is stored in the form of art data products. There are several levels of information:
- Monte Carlo generator information
- Geant4 information
- Digitized detector data, or digis (Offline format)
- Reconstructed data
We will explore a few of these, and the algorithms which create them.
Exercises
General
- Search for content (data products) in RecoDataProducts, MCDataProducts, etc
- Search for algorithms (modules) that (say) build tracks, find clusters, identify background ,...
- examine classes_def.html
Monte Carlo Generators
- Mu2e generators and GenParticle class
Geant4 and Detector Simulation
- The G4 Mu2e Detector description text files
- Examine the SimParticle and StepPointMC classes
- Virtual detectors
Digitized signals
- Digi specification
The term 'digi' refers to the digitized detector data stored during Mu2e operations by the Data Acquisition (DAQ) system.
- Download and open doc doc 4914
- Digitization simulation (tracker, CRV, ...)
Reconstruction
- Track reconstruction algorithms and data products
- Hit Reconstruction
- Time Clusters
- Helices
- Kalman Fit
- Calorimeter reconstruction algorithms and data products
- CRV reconstruction algorithms and data products
Reference Materials
Glossary of Data Products
- KalSeed
- CaloCluster