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NewConfigs_v1-DarkHiggs.py
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NewConfigs_v1-DarkHiggs.py
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import numpy as np
from src.foresee import Foresee, Utility, Model
import os
run_plothadrons=False
run_setupmodel=True
run_LLPspectra=False
run_rateexample=False
run_setupscans=True
run_runscans=False
run_plotreach=True
#############
# Initialization
print("INFO : Initialise FORESEE")
foresee = Foresee()
#############
# Plot hadrons
if run_plothadrons:
print("INFO : Plot hadrons")
plot=foresee.get_spectrumplot(pid="511", generator="Pythia8", energy="14")
plot.savefig("NewConfigs_v1-DarkHiggs-Pythia8_Hadron-Angle_vs_Momentum.pdf")
#############
# Specifying the Model: Dark Higgss
if run_setupmodel:
print("INFO : Setting up Dark Higgs model")
energy = "14"
modelname = "DarkHiggs"
model = Model(modelname)
print("INFO : - Adding production modes")
## 2-body decays
model.add_production_2bodydecay(
pid0 = "5",
pid1 = "321",
br = "5.7 * coupling**2 * pow(1.-pow(mass/5.279,2),2)",
generator = "Pythia8",
energy = energy,
nsample = 10,
)
model.add_production_2bodydecay(
pid0 = "-5",
pid1 = "321",
br = "5.7 * coupling**2 * pow(1.-pow(mass/5.279,2),2)",
generator = "Pythia8",
energy = energy,
nsample = 10,
)
model.add_production_2bodydecay(
pid0 = "25",
pid1 = "0",
br = "2*0.05",
generator = "Pythia8",
energy = energy,
nsample = 100,
scaling = 0,
)
# 3-body
model.add_production_3bodydecay(
label= "5_di",
pid0 = "5",
pid1 = "321",
pid2 = "0",
br = "7.37e-10*np.sqrt(1-4*mass**2/q**2)*(1-q**2/4.5**2)**2",
generator = "Pythia8",
energy = energy,
nsample = 10,
scaling = 0,
)
model.add_production_3bodydecay(
label= "-5_di",
pid0 = "-5",
pid1 = "321",
pid2 = "0",
br = "7.37e-10*np.sqrt(1-4*mass**2/q**2)*(1-q**2/4.5**2)**2",
generator = "Pythia8",
energy = energy,
nsample = 10,
scaling = 0,
)
print("INFO : - Setting lifetimes")
## Lifetime
model.set_ctau_1d(
filename="files/models/"+modelname+"/ctau.txt",
coupling_ref=1
)
print("INFO : - Setting branching fractions")
## Branching ratio
model.set_br_1d(
modes=["e_e", "mu_mu"],
filenames=["files/models/"+modelname+"/br/e_e.txt","files/models/"+modelname+"/br/mu_mu.txt"]
)
## Set model just created
foresee.set_model(model=model)
masses = [
0.1 , 0.1122, 0.1259, 0.1413, 0.1585, 0.1778, 0.1995,
0.2239, 0.2512, 0.2818, 0.3162, 0.3548, 0.3981, 0.4467,
0.5012, 0.5623, 0.6026, 0.631 , 0.6457, 0.6607, 0.6761,
0.6918, 0.7079, 0.7244, 0.7413, 0.7586, 0.7762, 0.7943,
0.8128, 0.8318, 0.8511, 0.871 , 0.8913, 0.912 , 0.9333,
0.955 , 0.9772, 1. , 1.122 , 1.2589, 1.4125, 1.5 ,
1.5849, 1.7783, 1.9953, 2.2387, 2.5119, 2.8184, 3.1623,
3.5 , 3.7 , 3.9811, 5.0119, 6.3096, 7.9433, 10. ,
11.22 , 12.589, 14.125, 15.849, 17.783, 19.953, 22.387,
25.119, 28.184, 31.623, 39.811, 50.119, 55.000, 60.000,
63.096, 79.430, 99.9
]
##########
# Generate LLP Spectra
if run_LLPspectra:
print("INFO : Generating LLP Spectra")
## Look at benchmark scenario with m_phi=1.5 GeV and theta=10^-4
print("INFO : - Generating for m_phi=1.5 GeV and theta=10^-4")
plt = foresee.get_llp_spectrum(mass=1.5, coupling=1e-4, do_plot=True, print_stats=True)
plt.savefig("NewConfigs_v1-DarkHiggs-Pythia8_LLP_m1500_t10m4-Angle_vs_Momentum.pdf")
print("INFO : - Generating for all masses")
for mass in masses:
foresee.get_llp_spectrum(mass=mass,coupling=1)
#################
# Count Event Rate in Detector
if run_rateexample:
print("INFO : Count Event Rate in Detector")
## To count the #decays in detector volume need detector geometry
## These are FASER2 defaults
distance, selection, length, luminosity, channels = 480, "np.sqrt(x.x**2 + x.y**2)< 1", 5, 3000, None
foresee.set_detector(distance=distance, selection=selection, length=length, luminosity=luminosity, channels=channels)
print("INFO : - For dark higgs (m_phi=1.5 GeV) check #events in decay volume")
## For one dark higgs (m_phi=1.5 GeV) look at how many particles decay inside the decay volume.
output = foresee.get_events(mass=1.5, energy=energy, couplings = np.logspace(-8,-3,6))
coups, ctaus, nsigs, energies, weights, _ = output
for coup,ctau,nsig in zip(coups, ctaus, nsigs):
print ("epsilon =", '{:5.3e}'.format(coup), ": nsig =", '{:5.3e}'.format(nsig))
print("INFO : - Plot energy distribution for different couplings")
## Look at energy distribution of the dark higgs which decay inside the detector
fig = plt.figure(figsize=(7,5))
ax = plt.subplot(1,1,1)
for coup,en,weight in zip(coups,energies,weights):
if sum(weight)<10**-5 : continue
ax.hist(en, weights=weight, bins=np.logspace(2,4, 20), histtype='step', label=r"$\theta=$"+str(coup))
ax.set_xscale("log")
ax.set_yscale("log")
ax.set_ylim(10**-7,10**5)
ax.set_xlabel("E($\phi$) [GeV]")
ax.set_ylabel("Number of Events per bin")
ax.legend(frameon=False, labelspacing=0)
plt.tight_layout()
plt.savefig("NewConfigs_v1-DarkHiggs-Pythia8_LLP_m1500-Energy.pdf")
##########
# Parameter Scan
setup_dict={}
if run_setupscans:
print("INFO : Setup parameter scan for different detector configs")
## Get the LLP sensitivity reach for different detector configuraions. Just need to loop over different masses and use the previously introduced funtion get_events
setup_dict={
"default":{
"name":"L=5m D=2m (Default)",
"color":"red",
"selection":"np.sqrt(x.x**2 + x.y**2)< 1",
"length":5,
"distance":480,
"channels": None
},
"L5-D1":{
"name":"L=5m D=1m",
"color":"firebrick",
"selection":"np.sqrt(x.x**2 + x.y**2)< 0.5",
"length":5,
"distance":480,
"channels": None
},
"L5-D0p5":{
"name":"L=5m D=0.5m",
"color":"maroon",
"selection":"np.sqrt(x.x**2 + x.y**2)< 0.25",
"length":5,
"distance":480,
"channels": None
},
"L15-D2":{
"name":"L=15m D=2m",
"color":"mediumorchid",
"selection":"np.sqrt(x.x**2 + x.y**2)< 1",
"length":15,
"distance":480,
"channels": None
},
"L15-D1":{
"name":"L=15m D=1m",
"color":"darkorchid",
"selection":"np.sqrt(x.x**2 + x.y**2)< 0.5",
"length":15,
"distance":480,
"channels": None
},
"L15-D0p5":{
"name":"L=15m D=0.5m",
"color":"rebeccapurple",
"selection":"np.sqrt(x.x**2 + x.y**2)< 0.25",
"length":15,
"distance":480,
"channels": None
},
}
if run_runscans:
print("INFO : - Run each config")
for setup in setup_dict:
print(f"INFO : - Running config: {setup}")
#### Check if run already processed
outfile="files/models/"+modelname+"/results/"+energy+"TeV_"+setup+".npy"
#### Specify setup
luminosity = 3000
setup, selection, length, channels, distance = setup, setup_dict[setup]["selection"], setup_dict[setup]["length"], setup_dict[setup]["channels"], setup_dict[setup]["distance"]
foresee.set_detector(selection=selection, channels=channels, length=length, distance=distance, luminosity=luminosity)
#### Get reach
list_nevents = []
for mass in masses:
couplings, _, nevents, _, _ , _ = foresee.get_events(mass=mass, energy=energy, modes=["5","-5"], couplings = np.logspace(-9,-2,71))
list_nevents.append(nevents)
#### Save results
np.save(outfile,[masses,couplings,list_nevents])
##########
# Plot the Results - Configurations
if run_plotreach:
print("INFO : - Plotting reach")
#Now let's plot the results. We first specify all detector setups for which we want to show result (filename in model/results directory, label, color, linestyle, opacity alpha for filled contours, required number of events).
setups = [ ["14TeV_%s.npy"%setup, setup_dict[setup]["name"],setup_dict[setup]["color"], "solid", 0., 3] for setup in setup_dict ]
print(f"INFO : - Found {len(setups)} setups")
#Then we specify all the existing bounds (filename in model/bounds directory, label, label position x, label position y, label rotation)
bounds = [
["bounds_1508.04094.txt", "LHCb $B^0$" , 0.430, 2.2*10**-3, 90 ],
["bounds_1612.08718.txt", "LHCb $B^+$" , 0.330, 2.2*10**-3, 90 ],
["bounds_1612.08718.txt", "LHCb $B^+$" , 2.500, 2.2*10**-3, 90 ],
["bounds_LSND.txt" , "LSND" , 0.250, 9.0*10**-5, 90 ],
["bounds_CHARM.txt" , "CHARM" , 0.250, 4.0*10**-4, 90 ],
["bounds_MicroBoone.txt", "$\mu$BooNE" , 0.138, 3.4*10**-4, 90 ],
["bounds_E949.txt" , "E949" , 0.102, 1.5*10**-4, 90 ],
["bounds_2011.11329.txt", "NA62 $K^+$" , 0.170, 6.2*10**-4, 90 ],
["bounds_2010.07644.txt", "NA62 $\pi^+$", 0.125, 2.4*10**-3, 90 ],
]
#We then specify other projected sensitivitities (filename in model/bounds directory, color, label, label position x, label position y, label rotation)
projections = [
["limits_SHiP.txt", "teal", "SHiP" , 2.700, 3.2*10**-5, 0 ],
["limits_MATHUSLA.txt", "dodgerblue", "MATHUSLA", 0.120, 5.0*10**-6, 0 ],
["limits_CodexB.txt", "deepskyblue", "CodexB" , 1.700, 2.0*10**-5, 0 ],
["limits_LHCb.txt", "cyan", "LHCb" , 3.800, 1.0*10**-4, 0 ],
]
# Finally, we can plot everything using foresee.plot_reach(). It returns a matplotlib instance, to which we can add further lines and which we can show or save. Below, we add the dark matter relict target line for a specific benchmark.
plot = foresee.plot_reach(
setups=setups,
bounds=bounds,
projections=projections,
title="Dark Higgs",
xlims=[0.1,10],
ylims=[10**-5.5,10**-2.5],
xlabel=r"Dark Higgs Mass $m_{\phi}$ [GeV]",
ylabel=r"Mixing $\theta$",
legendloc=(1.00,0.95),
figsize=(8,6),
)
plot.subplots_adjust(left=0.12, right=0.97, bottom=0.10, top=0.95)
plot.savefig("NewConfigs_v1-DarkHiggs-Pythia8-Reach.pdf")