def Sfitter_bench():
"""SMEFiT 2.0 vs SFitter NLO, Quadratic comparison"""
fit_smefit = FitManager(
f"{path}/SMEFiT20",
"NS_GLOBAL_NLO_HO",
label=r"${\rm SMEFiT\ Top+H+VV,\ NLO\ QCD\ \mathcal{O}(\Lambda^4)}$",
)
fit_sfitter = FitManager(
f"{path}/external",
"SFitter_TOP_NLO_HO",
label=r"${\rm SFitter\ Top-only,\ NLO\ QCD\ \mathcal{O}(\Lambda^4)}$",
has_posterior=False,
)
report_name = "sfitter_bench"
smefit = Runner(f"{report_path}/{report_name}", [fit_smefit, fit_sfitter])
smefit.run(
free_dofs={"show": ["cpWB", "cpD"], "hide": ["cB", "cW"]},
plot_only=[
"cl_vals",
"cl_bars",
"residuals",
"coeff_table",
],
)
def NLO_Lin_Bench():
"""SMEFiT 2.0 vs ATLAS EFT vs SFitter, Linear comparison"""
fit_smefit = FitManager(
f"{path}/SMEFiT20",
"NS_GLOBAL_NLO_NHO",
label=r"${\rm SMEFiT\ Top+H+VV,\ NLO\ QCD\ \mathcal{O}(\Lambda^2)}$",
)
fit_atlas = FitManager(
f"{path}/external",
"ATLAS_eft_note_NLO_NHO",
label=r"${\rm ATLAS\ H-STXS,\ NLO\ QCD\ \mathcal{O}(\Lambda^2)}$",
has_posterior=False,
)
report_name = "Lin_NLO_bench"
smefit = Runner(f"{report_path}/{report_name}", [fit_smefit, fit_atlas])
smefit.run(
free_dofs={"show": ["cpWB", "cpD"], "hide": ["cB", "cW"]},
plot_only=[
"cl_vals",
"cl_bars",
"residuals",
"coeff_table",
],
)
def plot_hist_only(coeff_name):
fit_linear = FitManager(data_path,
"NS_GLOBAL_NLO_NHO",
label=r"${\rm NLO~EFT,~Linear~EFT}$")
fit_quad = FitManager(data_path,
"NS_GLOBAL_NLO_HO",
label=r"${\rm NLO~EFT,~Quadratic~EFT}$")
report_name = f"/test_{coeff_name}"
smefit = Runner(f"{report_path}/{report_name}", [fit_linear, fit_quad])
smefit.run(plot_only=coeff_name)
def report_test():
fit_linear = FitManager(
data_path,
"NS_GLOBAL_LO_NHO",
label=r"${\rm SMEFiT\ Top+H+VV,\ LO\ EFT\ \mathcal{O}(\Lambda^2)}$")
fit_quad = FitManager(
data_path,
"NS_GLOBAL_NLO_HO",
)
report_name = "test"
smefit = Runner(f"{report_path}/{report_name}", [fit_linear, fit_quad])
smefit.run(free_dofs={"show": ["cpWB", "cpD"], "hide": ["cB", "cW"]})
def marginalized_bench(self):
"""SMEFiT 2.0 vs FitMarker LO, Linear comparison"""
fit_smefit = FitManager(
f"{path}/SMEFiT20",
"NS_GLOBAL_LO_NHO",
label=r"${\rm SMEFiT\ Top+H+VV,\ LO\ QCD\ \mathcal{O}(\Lambda^2)}$",
)
fit_fitmarker = FitManager(
f"{path}/external",
"FitMaker_GLOBAL_LO_NHO",
label=r"${\rm FitMaker\ Top+H+VV,\ LO\ QCD\ \mathcal{O}(\Lambda^2)}$",
has_posterior=False,
)
report_name = "fitmaker_bench"
smefit = Runner(f"{report_path}/{report_name}", [fit_smefit, fit_fitmarker])
smefit.run(free_dofs=self.free_dofs, plot_only=self.plot_only)
def Individual_bench():
"""
VBS SMEFiT vs FitMarker and BDHLL20 Individual LO, Linear comparison
IMOPRTANT note:
the coeffientes cpe, cpl1, c3pl1, cpui, cpdi, cpqi, cpq3
here follow the SMEFiT2.0 notation to have a consistent code,
but they are not exactly the very same.
See the different flavour assumptions of SMEFiT2.0 paper and VBS_SMEFiT paper.
Inside the VBS_SFEFiT paper they are called: cpe, cpl, c3pl, cpu, cpd, cpq, cpq3.
In paricular cpe, cpl1 and c3pl1 here are the average of the flavourful coefficients.
cpui, cpdi, cpqi, cpq3 are the same as in the SMEFiT2.0 since top/b quark do not contribute
any role in VBS, VV process
"""
plot_only = [
"cl_vals",
"cl_bars",
"coeff_table",
]
free_dofs = {
"hide": [
"cB",
"cW",
"cQQ1",
"cQQ8",
"cQt1",
"cQt8",
"cQb1",
"cQb8",
"ctt1",
"ctb1",
"ctb8",
"cQtQb1",
"cQtQb8",
"c81qq",
"c11qq",
"c83qq",
"c13qq",
"c8qt",
"c1qt",
"c8ut",
"c1ut",
"c8qu",
"c1qu",
"c8dt",
"c1dt",
"c8qd",
"c1qd",
"ctp",
"ctG",
"cbp",
"ccp",
"ctap",
"cmup",
"ctW",
"ctZ",
"ctB",
"cpl2",
"c3pl2",
"cpl3",
"c3pl3",
"cpmu",
"cpta",
"c3pQ3",
"cpqMi",
"cpQM",
"cpQ",
"cpt",
"cptb",
"cll",
"cpG",
"cpGtil",
"cpd",
"cW",
"cB",
]
}
fit_smefit = FitManager(
f"{path}/VBS_SMEFiT",
"SNS_VV_VBS_LO_NHO",
label=r"${\rm SMEFiT\ VV+VBS,\ LO\ QCD\ \mathcal{O}(\Lambda^2)}$",
is_individual=True,
)
fit_fitmarker = FitManager(
f"{path}/external",
"FitMaker_INDIV_LO_NHO",
label=r"${\rm FitMaker\ Top+H+VV,\ LO\ QCD\ \mathcal{O}(\Lambda^2)}$",
has_posterior=False,
)
fit_bdhll = FitManager(
f"{path}/external",
"BDHLL20_INDIV_LO_NHO",
label=r"${\rm BDHLL20\ VV+VH,\ LO\ QCD\ \mathcal{O}(\Lambda^2)}$",
has_posterior=False,
)
report_name = "vv_vbs_individual_bench"
smefit = Runner(f"{report_path}/{report_name}",
[fit_smefit, fit_bdhll, fit_fitmarker])
smefit.run(free_dofs=free_dofs, plot_only=plot_only)