SL_OS_SS_combined_blind.json
contains the upper limit on tttt cross section.
Edit this file if you want to get different constrains.
python EFT.py -c conf2d_cff.py
result is stored in build folder
python EFT.py -c conf_cff.py
- Select 13 TeV of 14 TeV predictions in mg_calcuations.py
sig_SM=sig_SM_13TeV
sig_SM=sig_SM_14TeV
# and
MG_SM=MG_SM_13TeV
MG_SM=MG_SM_14TeV
- To calculate tttt cross sections as function of EFT parameters
from eft_coefficients import EftPredictions
from mg_calculations import wilson_coefficients, MG_SM, sig_SM
eft = EftPredictions(wilson_coefficients, MG_SM, sig_SM)
tttt_xs = eft.gen_eft_xs([C_OR,C_OL1,C_OL8,C_B1,CB8])
# or
tttt_xs = eft.vgen_eft_xs(C_OR,C_OL1,C_OL8,C_B1,CB8) # optimzed for numpy
alternatively one can use 13 and 14 TeV constants directly
from eft_coefficients import EftPredictions
from mg_calculations import wilson_coefficients, MG_SM_13TeV, sig_SM_13TeV, MG_SM_14TeV, sig_SM_14TeV
eft13 = EftPredictions(wilson_coefficients, MG_SM_13TeV, sig_SM_13TeV)
eft14 = EftPredictions(wilson_coefficients, MG_SM_14TeV, sig_SM_14TeV)
tttt_xs_14_to_13_ratio = eft13.gen_eft_xs([C_OR,C_OL1,C_OL8,C_B1,CB8])/eft14.gen_eft_xs([C_OR,C_OL1,C_OL8,C_B1,CB8])
# test
eft13.gen_eft_xs([0.,0.,0.,0.,0.]) # should give 9.201
eft14.gen_eft_xs([0.,0.,0.,0.,0.]) # should give 11.31723
python matrix_coef.py
# python matrix_coef_old.py # outdated version is kept for historical purposes only. Use the script above!
python matrix_coef.py
is an improved version of python matrix_coef_old.py
. The logic of limits calculation and plotting is separated into several modules:
mg_calculations.py
--- Contains predictions such as tttt cross section values in a given point of the EFT parameter space. The predictions are obtained from MG, substituting a vector of Wilson coefficients in the steering cards.eft_coefficients.py
--- Contains logic for the determination of analytic parametrisation of the tttt cross section as function of Wilson coefficients
IMPORTANT
Results were compared with Mathias Mancini. Full agreement in the predicted values was obtained!