how to find a higgs boson€¦ · scalar higgs boson 12/10/2012 3 . sm higgs bosons identifying a...
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How to find a Higgs boson
Jonathan Hays
QMUL
12th October 2012
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Outline
Introducing the scalar boson
Experimental overview
Where and how to search
Higgs properties
Prospects and summary
12/10/2012 2
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The Scalar boson
Makes the SM work
allows massive W & Z
allows fermion masses
Testable prediction of Electroweak
theory
Scalar Higgs Boson
12/10/2012 3
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SM Higgs bosons
Identifying a SM Higgs boson or “how to get Peter Higgs (and others) a Nobel prize”
Neutral Mass consistent with EWK fits Spin-0 Correct couplings
12/10/2012 4
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Production at the LHC
12/10/2012 5
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Higgs decay
12/10/2012 6
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Indirect Constraints on the Higgs
12/10/2012 7
Latest indirect constraints prior to discovery…
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How to find a Higgs
Lots of energy to make them
Sensitive detector(s)
Some smart people to make it work and analyze the data
Look everywhere you can
12/10/2012 8
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Large Hadron Collider
12/10/2012 9
7TeV in 2011 8TeV in 2012
Proton-proton collider Designed to run at s=14 TeV
About 10fb-1 data in results here Another 10fb-1 already recorded
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Compact Muon Solenoid
12/10/2012 10
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Compact Muon Solenoid
12/10/2012 11
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Triggering
12/10/2012 12
Event rates of Higgs several orders of magnitude smaller than total cross section
Need a good trigger system to cut the rate down and reject backgrounds
Reading out every event would be TB/s !
Two level solution at CMS L1 fast decision, factor 1000 reduction HLT down to about 100 Hz
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12/10/2012 13 Over 4000 collaborators now on CMS!
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Channel Overview
12/10/2012 14
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Higgs Discovery?
12/10/2012 15
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Higgs? Discovery
12/10/2012 16
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hbb Associated production pp->VH Leptonic (e,,) decays give clean signature Events classification: lepton species and Higgs boost Require: isolated leptons missing transverse energy (neutrinos) 2 b-tagged jets
Boosted Decision Tree used to discriminate between signal and backgrounds Output distribution of the BDT used in statistical analysis Main backgrounds: W/Z+jets and top pairs – rates from control samples
Additional channel included sensitive to ttH production 12/10/2012 17
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hbb
12/10/2012 18
Not quite sensitive to SM yet, next update should achieve that
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h
12/10/2012 19
Select events with one or more leptonic tau decays: categorize according to flavour: e, eh h
Further subdivide into 3 categories: VBF : + 1 forward, 1 backward jets Boost : +1 high pT jet 0-jet: remaining events
Dominant backgrounds estimated from control samples in data
VBF Boosted 0-jet
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h
12/10/2012 20
Close to SM sensitivity and no sign of a Higgs – though be aware of the size of the bands! Next updates should prove interesting!
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(W/Z)hWW(W/Z)
12/10/2012 21
Four basic channels: 2l2, ljj, 3l3, 2l2jj
Classify events according to lepton flavour and charge and jet multiplicity
Main backgrounds come from diboson production, top pairs and W+jets - depending on category. Data driven for major contributions
MVA techniques, eg BDTs and NN, used to enhance sensitivity as well as cut based selection
Select events with isolated leptons, missing transverse energy and up to 2 jets
0-jet 1-jet
Cut based @ 8TeV
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hWW2l2
12/10/2012 22
Sensitivity dominated by 2l2
SM like Higgs excluded across much of the mass range. Broad excess in low mass region compatible with SM Higgs
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Golden channel: hZZ4l
12/10/2012 23
4 isolated leptons give extremely clean signature Excellent energy resolution gives narrow signal peak
Angular analysis using matrix-element likelihood approach enhances sensitivity
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Golden channel: hZZ4l
12/10/2012 24
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Other ZZ channels
12/10/2012 25
Look for two leptons and large missing transverse energy
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Golden Low Mass Channel: h
12/10/2012 26
Tiny branching ratio but very clean signature Two isolated high pT photons
In principle a simple analysis: look for a bump in diphoton mass spectrum accumulate data and wait for it to appear!
Narrow resonance – performance completely driven by the detector Was the benchmark channel for the ECAL design
ECAL TDR
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h
12/10/2012 27
Slightly more complicated than making a mass plot and waiting for a signal!
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Event selection
12/10/2012 28
Select events with 2 isolated photons, with cuts on pt/M
2 high-pt jets plus high jet mass for VBF search
Look for a bump on a smoothly falling backgound
Pretty good agreement between MC and data
Split events into different categories to optimize sensitivity
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Photon ID
12/10/2012 29
Boosted decision tree trained to separate prompt photons from 0
Use isolation, shower shape and related
Efficiency measured in Zee with corrections to photons derived from MC
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Vertexing
12/10/2012 30
Correct vertex needs to be identified precision < 10mm
BDT based vertexing algorithm based on event kinematics Gives vertex + event-by-event error estimate
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Vertexing
12/10/2012 31
Methods validated on Zµµ events by throwing away muon tracks
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Energy Reconstruction
12/10/2012 32
Number of corrections applied to ECAL cluster energies: shower containment conversion recovery pile-up mitigation
BDT based regression algorithm used trained on MC
MC tuned to data in Zee events
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Signal Extraction
3 procedures used:
simple categorisation with mass fit
used for earlier results now dropped
BDT categorisation with mass fit
“mass factorised”
BDT categorisation with “sideband method”
12/10/2012 33
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“Mass factorized” : Categorisation
Train a BDT with photon-ID and kinematic information
Choose carefully to avoid dependence on mass hypothesis
Use BDT output value to define categories – optimised for best expected sensitivity from simulation
12/10/2012 34
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“Mass factorized” : Signal Model
12/10/2012 35
Sum of gaussians fit to tuned Monte-Carlo in each category Systematics mapped onto variations in model parameters MC generated at 5 GeV intervals in mass – parameters interpolated inbetween
Category 0 1 2 3 VBF1 VBF2
Resolution / GeV 1.34 1.44 1.82 2.96 1.87 2.13
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“Mass factorized” : Background Model
Problem: how to chose a parameterised model?
Solution: compare performance with many classes of functions in simulation
Generate with one function – fit with another Pick the function with the best performance with respect to biases in the signal extraction
Separate fit in each category
12/10/2012 36
Polynomials give smallest bias, order ranges from 3 to 5 depending on cat.
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Sideband Method
For each mass hypothesis: Split mass spectrum into windows +/-2% wide
Use data from sidebands to constrain a model of the background in the signal window
Alternative approach designed to avoid some pitfalls of pure parametric approach
12/10/2012 37
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Sideband Method
Instead of mass fit: combine information from diphoton BDT with ΔM/MH in a further BDT
Use output of BDT to categorize events with similar S/B
12/10/2012 38
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Sideband Method
Assume that variation of fractional yield in a category from one sideband to another approximately constant Follows from approximate independence of diphoton BDT to mass hypothesis
Fit a straight line and parabola to extract relative yield in the signal region
Uncertainties propagated forward from fit and systematic variation from comparing parabola and straight line fit
12/10/2012 39
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Sideband Method
Fit “double-power-law” across sum of all categories to estimate total yield in signal region
In practise can do all fits in one big simultaneous method
Add uncertainties to yield in each category based on global fit uncertainties and estimate of bias from MC studies similar to those in the “mass factorised” method 12/10/2012 40
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Sideband Method Advantages: each assumption has an associated systematic uncertainty no need to re-determine polynomial order as data accumulate constraints on background yields across categories
Disadvantages: complexity non-parametric less smooth variation of results
12/10/2012 41
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VBF Tagged Categories
12/10/2012 42
2 Categories for 2012, 1 cat categories for 2011 running
2-jets well separated in rapidity, select for high dijet mass to further enrich VBF content
Large systematics from jet modelling and “category migration” (large on ggH)
Mjj > 500 GeV Mjj > 250 GeV
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Results
12/10/2012 43
Results of inclusive + VBF searches
“Mass factorised” “sideband”
Both methods give consistent results
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Results
12/10/2012 44
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Higgs Properties: Mass
12/10/2012 45 2D likelihood scan. Approach using 2D Feldman-Cousins also underway
Eur. Phys. J. C 60, 543 (2009)
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Higgs properties: Cross section
12/10/2012 46
For the moment everything looks consistent with the SM
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Higgs Properties: Couplings
12/10/2012 47
Fit data with simplified models for couplings
Revisit analyses to optimise for parameter extraction rather than discovery
Systematic uncertainties will become increasingly important
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Higgs Properties: Spin and CP
12/10/2012 48
arXiv:1208.4018
Might start to see some separation with 2012 data but likely nothing conclusive until 14TeV
Scalar Higgs Pseudo-scalar Higgs Spin-2 minimal graviton-like Spin-2 higher order couplings Background
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Prospects and Summary
After nearly 60 years the easy bit is done!
A good candidate for a Higgs boson has been discovered at ~125 GeV
2012 Data may yet reveal some surprises! But probably not conclusive on SM nature of the boson
Post-shutdown era will hopefully be Higgs Physics instead of Higgs searches!
12/10/2012 49
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Polynomials
12/10/2012 50
F-prob = probability to falsely claim model 2 better than model 1
= pol5
Toy simulations generating a mass spectrum with different models and then fitting it (NB not the actual stuff used in CMS)
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BDT
12/10/2012 51