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NEURAL NETWORKS IN HIGGS PHYSICS. Silvia Tentindo-Repond, Pushpalatha Bhat and Harrison Prosper Florida State University and Fermilab – D0 ACAT - Fermilab 16 Oct 2000. Higgs Physics. The most challenging task of HEP ( Tev and LHC ) in the coming decade will be the search for Higgs. - PowerPoint PPT Presentation
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NEURAL NETWORKS IN HIGGS PHYSICS
Silvia Tentindo-Repond,Pushpalatha Bhat and Harrison ProsperFlorida State University and Fermilab –
D0
ACAT - Fermilab 16 Oct 2000
S.Tentindo ACAT Oct 2000
Higgs Physics The most challenging task of HEP ( Tev and
LHC ) in the coming decade will be the search for Higgs.
In many theories, the Higgs Boson would explain the still mysterious fundamental mechanism of the electro-weak symmetry breaking (EWSB).
SM predicts Higgs in the mass range 107 Gev ( - 45, + 67 )
MSSM predicts a lighter Higgs at 130Gev, that would be reachable at Tev
Studied here : 90 < Mhiggs < 130 Gev
S.Tentindo ACAT Oct 2000
Predicted Higgs Mass from SM (measured Mtop and MW)Title:t99_mt_mw_contours.epsCreator:HIGZ Version 1.23/09Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Integrated Luminosities for Higgs Discoveryat Tev vs Higgs Mass (SM Higgs)
S.Tentindo ACAT Oct 2000
Multivariate Methods vs Traditional in Higgs Physics Multivariate Methods (NN) are used to
maximize the chance to discover the Higg Boson
To reduce the required Luminosity for equal signal Significance (S/sqrtB)
To reduce the required Luminosity for making a 5 sigma discovery
S.Tentindo ACAT Oct 2000
SM Higgs final states
use b-tagging to reduce background
use leptons to reduce QCD backg.
use particular lepton signatures,use angular correlations to reducedi-boson backg.
,bbH (mH<130 GeV)
ZZWWH , (mH>130 GeV)M.Spira
S.Tentindo ACAT Oct 2000
[pb] (mH=100 GeV)
Typical cross-sections ( TeV)2s
gg HWH
ZH
1.00.30.18
WZWbb
3.211
tttb+tq+tbq
7.53.4
QCD O(106)
WZ/ZH production are preferred
S.Tentindo ACAT Oct 2000
Traditional Analysis vs NN Example :
p p W H l v b b signal p p W b b background
Need to enhance signal over background Use global event variables (Ht, Sph, Apla,MissEt, etc) + jet variables ( Etj, Etaqj,Ehad, Eem,Ntr,Etr,btag,Ht InvMass(jj), etc )
Use corrections ( e.g. jet energy corrections). Use parametrized b tag – displaced vertex,soft lepton - etc.)
S.Tentindo ACAT Oct 2000
Traditional analysis vs NN (cont.)
Traditional Analysis improves S/B by imposing cuts to each event variable. Rarely optimized,unless signal and background distributions are well separated.
Multivariate Analysis uses for example NN to find optimal cuts. optimizes separation between signal and background; therefore maximizes the chance of discovery;
S.Tentindo ACAT Oct 2000
Example of NN for Higgs Search
Study the process p p -> W H -> l v b b signal
p p -> Z H -> l+ l- b b p p -> Z H -> v v b b
NN analysis of these three processes leads to remarkable Luminosity reduction allowing Higgs ( 90 < MH < 130) discovery at Tev
NN variables used to train : Etb1, Etb2, M(bb), Ht,Ete,ETAe,Etmiss, S,
dR(b1,b2), dR(b1,e) NN configuration : 7 input – 9 hidden nodes – 1
output node
PRD62,2000
S.Tentindo ACAT Oct 2000
NN for Higgs search: training variables
WH -> ev bb
Dark – Signal Light - background
Title:var_plots_wbb_v2.epsCreator:HIGZ Version 1.23/07Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN for Higgs search : NN Output
WH Signal - D=1
WBB Bkgd – D=0
Title:net_plots_zhnn_100.epsCreator:HIGZ Version 1.23/07Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN and Higgs Search : required Luminosities
Compared requiredLuminosities for Higgs Discovery NN cuts and Standard Cuts
Title:res4.epsCreator:HIGZ Version 1.23/07Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN and Higgs Search : Luminosity further studies
Can we do better ??
Re-train NN :Configuration 6-6-1-same as previous, but no S-Different number of epochs-and hidden nodes …….-----------------------------------Configuration 8-6-1-- same as before, add ntrj1 and ntrj2
YES
NO
S.Tentindo ACAT Oct 2000
NN and Higgs Search : Luminosity further studiesTitle:lum1.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN and Higgs Search : Luminosity further studiesTitle:lum2.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Channel-Independent B tagging with NN for Higgs Search
“Heavy Flavor Tagging “ ( C and B jet tagging) [ R. Demina ]
Traditional Analysis makes no distinction from b and c. NN Analysis combines lifetime variables (track consistent with secondary vertex, Impact Parameter ) and kinematic variables (mass, fragmentation)
This tagging method can potentially outperform existing Tagging algorithms .
S.Tentindo ACAT Oct 2000
Channel-independent B Tagging NN output (bottomness)
bottomcharmprimary
Points- single data, black - fit.
R. Demina, march 2000
S.Tentindo ACAT Oct 2000
Channel-Independent B Tag NN output ( jet)
primary
bottom
charm
R. Demina – march 2000
S.Tentindo ACAT Oct 2000
Channel-dependent B tagging with NN for Background Reduction in Higgs Search
In this study: Signal 1000 W H e v b b
Background 1000 W bb --------------------------------------
Parton level Monte Carlo: PYTHIA ( later on CompHEP )
Parton fragmentation : PYTHIA Approximate response of Detector ( D0/CDF) : SHW program - includes simulation of trigger, tracking, cal cluster, reconstruction and b tagging . [J.Conway]
S.Tentindo ACAT Oct 2000
Channel-dependent B tagging with NN (cont.)
Cuts for base sample: Pte > 15 Gev/c ETAe < 2, Met > 20 Gev, Etjet >10Gev, Njet>=2, ETAjet<2
Select jet variables that are connected to b tag of jet Selected: Etjet, Ntr jet, Width jet
Train NN with a signal sample: WH e v b b NN configuration : 3 - 5 – 1
3 input nodes Etjet, Ntr jet, Width jet 5 hidden nodes 1 output Channel-Dependent “ B tag “
Set NN function ( D= 1 for B jet, D=0 for non B jet)
S.Tentindo ACAT Oct 2000
Channel-dependent B tagging with NN (cont.)
QUESTION : Does this channel-dependent b-tagging push to lower values the background ( Wbb Massjj distribution ?)
S.Tentindo ACAT Oct 2000
Channel-dependent B tagging: Jet variables for NN training
Title:nnbtag1.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
Title:nnbtag2.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Channel-dependent B tagging :Jet variables for NN training
Title:nnbtag3.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
Title:nnbtag4.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN HB Tag output for B-flavor/no-B-flavor jets ( j1)
Title:j1btag.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN HB Tag output for B-flavor/no-B-flavor jets ( j2)
Title:j2btag.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN HB Tag output for WbbTitle:btagwbb.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN HB Tag output for WH (100)Title:btagwh100.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
NN HB Tag cut=0.4 WH(100)Title:btag_cut4.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Channel-dependent B tagging :separation signal/background
Title:nnbtag5.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Improving Mass Resolution with NN in Higgs Search M(jj) has proven to be a critical variable
to discriminate signal from background in Higgs physics, for any channel analysis
The assumed mass resolution in the recent RunII Susy/Higgs Workshop is 10%.
Methods and algorithms have still to be worked out to reach such resolution
S.Tentindo ACAT Oct 2000
Mass Resolution – Parton and Particle jets- Final State Radiation contributionsTitle:higgs.dviCreator:dvips(k) 5.86 Copyright 1999 Radical Eye SoftwarePreview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Mass Resolution – Parton and Particle jets- Final State Radiation contributions
Title:higgs.dviCreator:dvips(k) 5.86 Copyright 1999 Radical Eye SoftwarePreview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Mass Resolution – Detector jets - Final State Radiation contributions
Signal W H (M_H = 100 gev )
Background W b b
Title:masssb.epsCreator:HIGZ Version 1.26/04Preview:This EPS picture was not savedwith a preview included in it.Comment:This EPS picture will print to aPostScript printer, but not toother types of printers.
S.Tentindo ACAT Oct 2000
Improve Mass resolution with NN in Higgs Search ( cont.)
Possible strategies: Study correlations of jet properties and Inv
Mass distribution. Make a correction function to improve Pt and
Energy Resolution of jets and recalculate Inv. Mass of jets with the corrected values of Pt and E
S.Tentindo ACAT Oct 2000
Improve Mass resolution with NN in Higgs Search ( cont.)
Study correlations among Jet variables and Massjj Jet Variables : Nj, Et, Phi, ETA, d(e,j), Eem, Ehad, Etr, Ntr, Wid,
plus : Btag, d(b,j) , d(j,j), Mjj , Mbjj . No clear evidence of correlation.
Apply corrections to Pt and E that could
improve the Mjj resolution.
S.Tentindo ACAT Oct 2000
Corrections to Mass Resolution I Train NN to correct Mjj by giving Mjj and Ht
and forcing the output to be the true Higgs mass, for several values of Higgs masses
NN configuration : 2-6-1 2 input nodes ( Mjj, Ht )
6 hidden nodes, 1 output node ( MH) for several MH * 300 epochs 500 examples for each Higgs Mass
* MH = 100, 105,110,115,120,125,130,135,140
S.Tentindo ACAT Oct 2000
Improving the Higgs Mass Resolution
13.8% 12.2%
13.1% 11..3%
13%13% 11%11%
Use mjj and HT (= Etjets ) to train NNs to predict the Higgs boson mass
S.Tentindo ACAT Oct 2000
Corrections to Mass Resolution II
Train NN to correct Pt and E of jet, by giving Pt distributions at parton level. Generate a corrected Pt function Ptc(Et, Eta) to apply to Mjj .
NN configuration : 2-9-1 2 input nodes , 9 hidden nodes, 1 output node ( Mjj ) 5000 examples
……………………………..
S.Tentindo ACAT Oct 2000
Summary
NN used to maximize Discovery Potential B Tagging and good Mass ( Mjj) Resolution NN for B Tagging is very promising
( could Channel-Dependent B Tagging be used for reduction of Background ? )
Plan to continue systematic studies of the methods