Data Products and Processing Tutorial

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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:

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.

  • 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

class description contents
StrawDigi Offline format of a single Tracker hit TDC and TOT from both straw ends, ADC waveform
ComboHit Calibrated Tracker hit, or an aggregate of several hits position in space, time, and time differences
TimeCluster Collection of ComboHits nearby in time and (roughly) space average time and error
HelixSeed Helix interpretation of a subset of hits in a TimeCluster Helix parameters, t0, ComboHits with position along the helix
KalRep Full Kalman filter fit result: not persistable Complete set of weight and parameter matrices and vectors used in the fit
KalSeed Compact summary of the Kalman filter fit result Sampled fit segments, associated straw hits and straws
KalSegment KalSeed component: local fit result Fit parameters and covariance at a particular point
TrkStrawHitSeed KalSeed component: straw hit as used in fit hit position, residual, time, drift radius, errors, ...
TrkStraw KalSeed component: straw intersected by the fit strawID, DOCA to wire, radiation length, energy loss, ...
CaloCluster Cluster of calorimeter crystal energy deposits Total energy, center of gravity (COG), energy moments
CrvCoincidenceCluster Cluster of adjacent CRV reco pulses position, PE count, start and end times

Glossary of Principle Reconstruction Modules

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