Introduction l An alternative framework for probing physics beyond SM is effective field theories(EFT) the SM Lagrangian is supplemented by additional dimension-D operators ℒ "#$ =ℒ ’( + ∑ + , (.) 0 .12 Ο 4 (5) 4,5 l 4 (5) specify the strength of new interaction, are known as Wilson coefficients l In this analysis, limits are set in Wilson coefficients of dimension-6 operators 2019/12/15 1
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Introduction - indico.cern.ch€¦ · Introduction l An alternative framework for probing physics beyond SM is effective field theories(EFT) the SM Lagrangianis supplemented by additional
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Introduction
l An alternative framework for probing physics beyond SM is effective field theories(EFT)
the SM Lagrangian is supplemented by additional dimension-D operators
ℒ"#$ = ℒ'( +∑+,(.)
0.12 Ο4(5)
4,5
l 𝑐4(5) specify the strength of new interaction, are known as Wilson coefficients
l In this analysis, limits are set in Wilson coefficients of dimension-6 operators
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Effective field theories
l There are two bases for a dimension-6 EFT Lagrangian
l SILH: the basis of Strongly-Interacting-Light-Higgs Lagrangian
l SMEFT: the “Warsaw” basis of SM Effective Field Theory Lagrangian
l For different bases, different Wilson coefficients take effect
l Parameter ranges for each EFT parameter
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EFT analysis workflow
l Generate samples with MadGraph5, and output EVNT.root
l Change parameters in the param_card, generate a variety of samples
l Use Rivet to select over those EVNT.root and generate histograms into .yoda files
l Calculate Reweight scale factors, and applying reweight factors to all of the yoda files
l Use Professor software to make 2nd order polynomial interpolation over reweighted .yoda
files
l Scan over parameters in EFT through gamma-combo to obtain confidence intervals of these
parameters.2019/12/15 3
0 2 4 6 8 10 12 14 16 180
0.1
0.2
0.3
0.4
0.5
0.6Powheg ggH
SILH c=0
γγpT
0 0.5 1 1.5 2 2.5 3 3.5 4~
5
10
15
20
25
30
~
Powheg ggH
SILH c=0
From Amed
30 GeVjetexcl N
N_j_30
MadGraph generation with SILH modell Try to reproduce SM expectation with SILH model
generate ggH samples with commands below
l Import model HEL_UFO(set all Wilson coefficients to 0)
l Generate p p > h NP=1 QED=1 QCD=99, h > aa NP=1 QED=2 @0
l Add process p p > hj NP =1 QED=1 QCD=99, h > aa NP=1 QED=2 @1
l Add process pp > hjj NP=1 QED=1 QCD=99, h > aa NP=1 QED=2 @2
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l ggH125 Powheg+Pythia(H+j) as comparisonl There is still deviation on N_j_30 and pT_yyl More jet numbers in SILH(coefficients = 0)
than Powheg ggH
pT_yy
EFT parameters tested in ggH samples
l Choose two EFT parameters as tested( 𝑐89 & 𝑐8: : 5 points for per parameter, 25 points
totally), while keeping other Wilson coefficients to 0:
𝑐89 : [-0.001 , -0.0005 , 0.0 , 0.0005 ,0.001]
𝑐8: : [-0.001 , -0.0005 , 0.0 , 0.0005 ,0.001]
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Event Selection with HGamRivetl Perform event selection on EVNT.root from samples generated by MadGraph5 to generate
histogram(.yoda files)
l Selection Criteria for Photons(same as H->yy fiducial region):
l pT > 25GeV
l |eta| <1.37 or 1.52 < |eta| < 2.37
l Photons.size > 2 & relative pT cut 0.35(0.25)
for leading(sub-leading)photon
l 105GeV < m_yy < 160GeV
l HGamRivet can save distributions of a set of variables, and they will work in the period of limit-
setting.
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Rivet results of N_j_30 and pT_yyl HGamRivet can get N_j_30 and pT_yy distributions in the events passing event selection
l For different Wilson coefficient sets, the histograms would be quite different, even with one or two order of magnitude