dual-readout

Repository for GEANT4 simulation & analysis of the dual-readout calorimeter.

How-to

Compile

After fetching the repository, do

source init_hsf.sh
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=<path_to_install_directory> ..
make -j4
make install

Note that to use the installed binary & library files, need to do following (assuming $PWD=<path_to_install_directory>)

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD/lib64
export PYTHONPATH=$PYTHONPATH:$PWD/python

Generating events

Generating events relies on k4Gen, generates primary particle(s) in HepMC format with either particle gun or Pythia8 then converts it to edm4hep. Please refer to k4Gen/options for example configurations.

Running GEANT4 simulation

The typical GEANT4 configuration for DRC is located at DRsim/DRsimG4Components/test/runDRsim.py. After modifying the configuration based on your needs, run

k4run runDRsim.py

Note that there are several Gaudi components specific to DRC - SimG4OpticalPhysicsList, SimG4FastSimOpFiberRegion, and SimG4DRcaloActions.

from Configurables import SimG4Svc, SimG4FastSimPhysicsList, SimG4FastSimOpFiberRegion, SimG4OpticalPhysicsList
regionTool = SimG4FastSimOpFiberRegion("fastfiber")
opticalPhysicsTool = SimG4OpticalPhysicsList("opticalPhysics", fullphysics="SimG4FtfpBert")
physicslistTool = SimG4FastSimPhysicsList("Physics", fullphysics=opticalPhysicsTool)

from Configurables import SimG4DRcaloActions
actionTool = SimG4DRcaloActions("SimG4DRcaloActions")

# Name of the tool in GAUDI is "XX/YY" where XX is the tool class name and YY is the given name
geantservice = SimG4Svc("SimG4Svc",
  physicslist = physicslistTool,
  regions = ["SimG4FastSimOpFiberRegion/fastfiber"],
  actions = actionTool
)

from Configurables import SimG4Alg, SimG4PrimariesFromEdmTool
# next, create the G4 algorithm, giving the list of names of tools ("XX/YY")
edmConverter = SimG4PrimariesFromEdmTool("EdmConverter")

from Configurables import SimG4SaveSmearedParticles, SimG4SaveDRcaloHits, SimG4SaveDRcaloMCTruth
savePtcTool = SimG4SaveSmearedParticles("saveSmearedParticles")
saveDRcaloTool = SimG4SaveDRcaloHits("saveDRcaloTool", readoutNames = ["DRcaloSiPMreadout"])
saveMCTruthTool = SimG4SaveDRcaloMCTruth("saveMCTruthTool") # need SimG4DRcaloActions

geantsim = SimG4Alg("SimG4Alg",
  outputs = [
    "SimG4SaveSmearedParticles/saveSmearedParticles",
    "SimG4SaveDRcaloHits/saveDRcaloTool",
    "SimG4SaveDRcaloMCTruth/saveMCTruthTool"
  ],
  eventProvider = edmConverter
)

Optical physics is NOT simulated by GEANT4 default physics list due to the extensive computing. SimG4OpticalPhysicsList configures the Cherenkov and scintillation process and let GEANT4 track optical photons.

However, full tracking of optical photons makes the simulation extremely heavy to an unpractical scale (costs > 4-6 hours to simulate a 10 GeV e- event). It can be significantly improved (2-3 mins per 10 GeV e- event) by skipping exhaustive tracking of optical photons with a good approximation. FastSimModelOpFiber and SimG4FastSimOpFiberRegion define the fast simulation model and the corresponding region for tracking optical photons. Details of the logic can be found at GEANT4 R&D meeting.

SimG4DRcaloActions is responsible for initializing SimG4DRcaloSteppingAction, which retrieves MC truth energy deposit inside non-active absorbers. The resulting MC-truth energy deposit and counted number of photoelectrons are stored in the edm4hep collection named "SimCalorimeterHits" and "RawCalorimeterHits". The timing structure of arrived optical photons is stored in the user-class edm4hep::SparseVector "RawTimeStructs".

Digitization

SiPM digitization is based on the external package SimSiPM, please refer to the repository for the details. The default Gaudi configuration template can be found on DRdigi/test/runDigi.py. After modifying the configuration based on your needs, run

k4run runDigi.py

Parameters for SiPM digitization can be defined in the configuration, for example,

from Configurables import DigiSiPM
digi = DigiSiPM("DigiSiPM",
  # Hamamatsu S13615-1025
  signalLength = 500., # ns
  SiPMsize = 1., # mm
  DCR = 100e3, # kHz
  Xtalk = 0.03, # probability
  sampling = 0.1, # ns
  recovery = 20., # ns
  cellpitch = 25., # um
  afterpulse = 0.03, # probability
  falltimeFast = 50., # ns
  risetime = 1., # ns
  SNR = 30., # dB
  gateLength = 240., # ns
  OutputLevel = DEBUG
)

Calibration & Reconstruction

The Gaudi component DRcalib2D calculates reconstructed energy from ADC counts based on the calibration constants defined at DRreco/calib.csv. This requires the ROOT file generated from runDigi.py. The default Gaudi configuration template can be found on DRreco/test/runDRcalib.py. After modifying the configuration based on your needs, run

k4run runDRcalib.py

Analysis

This requires the ROOT file generated from runDRcalib.py.

./bin/analysis <histogram lower edge in [GeV]> <histogram higher edge in [GeV]> <file_*.root>

Note that the analysis is a mere example based on only ROOT, podio and edm4hep. Please make sure that you have implemented desired plots based on your needs and physics process.

Precaution

Since the GEANT4 simulation takes a very large amount of time per an event, it is assumed to run a few dozens of events per run. It can be run on parallel using torque or condor.