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
• Digitized data formats for different subsystems
• 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

• Mu2e doc 4914

Glossary of Data Products

• KalSeed
• CaloCluster