def dark_brem( ap_mass , lhe, detector ) :
"""Example configuration for producing dark brem interactions in the ECal.
This configures the simulator to fire a 4 GeV electron upstream of the
tagger tracker. The electron is allowed to propagate into the ECal where
the dark-photon production cross-section is biased up. Only events that
result in a dark-photon being produced in the ECal are kept.
Parameters
----------
ap_mass : float
The mass of the A' in MeV.
lhe : str
The path to the LHE file to use as vertices of the dark brem.
detector : str
Path to the detector.
Return
------
Instance of the simulator configured for dark-brem production in the ECal.
Example
-------
ecal_ap_sim = ecal.dark_brem(1000, 'path/to/lhe', 'ldmx-det-v12')
"""
sim = simulator.simulator( "darkBrem_%sMeV" % str(massAPrime) )
sim.description = "One e- fired far upstream with Dark Brem turned on and biased up in ECal"
sim.setDetector( detector , True )
sim.generators.append( generators.single_4gev_e_upstream_tagger() )
# Bias the electron dark brem process inside of the ECal
# These commands allow us to restrict the dark brem process to a given
# volume.
sim.biasingOn()
sim.biasingConfigure( 'eDBrem' , 'ecal' , 0. , 100000 )
sim.darkBremOn( massAPrime #MeV
, lheFile
, 1 ) #Forward Only
# the following filters are in a library that needs to be included
includeBiasing.library()
# Then give the UserAction to the simulation so that it knows to use it
sim.actions().extend([
# Only keep events when a dark brem happens in the target
filters.DarkBremFilter('ecal') ,
# Keep all of the dark brem daughters.
filters.TrackProcessFilter.dark_brem()
])
return sim
from LDMX.Framework import ldmxcfg
p = ldmxcfg.Process('target_en')
from LDMX.Biasing import target
from LDMX.SimCore import generators
import LDMX.Ecal.EcalGeometry
p.sequence = [
target.electro_nuclear(
'ldmx-det-v12' ,
generators.single_4gev_e_upstream_tagger()
)
]
p.maxEvents = 1000
p.outputFiles = [ '/tmp/target_en.root' ]
def dark_brem(ap_mass, lhe, detector):
"""Example configuration for producing dark brem interactions in the target.
This configures the sim to fire a 4 GeV electron upstream of the
tagger tracker. The dark-photon production cross-section is biased up in
the target. Only events that result in a dark-photon being produced in the
target are kept.
Parameters
----------
ap_mass : float
The mass of the A' in MeV.
lhe : str
The path to the LHE file to use as vertices of the dark brem.
detector : str
Name of detector to simulate in
Return
------
Instance of the sim configured for dark-brem production in the target.
Example
-------
target_ap_sim = target.dark_brem(1000, 'path/to/lhe', 'ldmx-det-v12')
"""
sim = simulator.simulator("darkBrem_" + str(massAPrime) + "_MeV")
sim.description = "One e- fired far upstream with Dark Brem turned on and biased up in target"
sim.setDetector(detector, True)
sim.generators.append(generators.single_4gev_e_upstream_tagger())
# Bias the electron dark brem process inside of the target
# These commands allow us to restrict the dark brem process to a given
# volume.
sim.biasingOn()
sim.biasingConfigure(
'eDBrem' #process
,
'target' #volume
,
0. #threshold
,
1000000 #factor
)
sim.darkBremOn(
massAPrime #MeV
,
lheFile,
1 #Forward Only
)
# the following filters are in a library that needs to be included
includeBiasing.library()
# Then give the UserAction to the simulation so that it knows to use it
sim.actions.extend(
[filters.DarkBremFilter(),
filters.TrackProcessFilter.dark_brem()])
return sim
from LDMX.Hcal import digi as hcal_digi
kaon_filter = particle_filter.PhotoNuclearProductsFilter("kaons_filter")
kaon_filter.pdg_ids = [
130, # K_L^0
310, # K_S^0
311, # K^0
321 # K^+
]
sim = simulator.simulator("target_photonNuclear")
sim.setDetector('ldmx-det-v12', True)
sim.runNumber = 0
sim.description = "Target photo-nuclear, xsec bias 1.1e9"
sim.beamSpotSmear = [20., 80., 0.]
sim.generators.append(generators.single_4gev_e_upstream_tagger())
allids = kaon_filter.pdg_ids
allids.append(-321)
sim.biasing_operators = [
bias_operators.PhotoNuclear('target_region',
1.1e9,
2500.,
only_children_of_primary=True)
]
includeBiasing.library()
sim.actions.extend([
filters.TaggerVetoFilter(),
filters.TargetBremFilter(),
filters.TargetPNFilter(),
