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Finding the Higgs or something else ideas to improve the discovery potential at hadron colliders. Sascha Caron. Freiburg Seminar, Sept. 2005. The situation in 2005. We still don’t know the origin of EW symmetry breaking The Higgs boson is not discovered yet Even with the SM Higgs: - PowerPoint PPT Presentation
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Freiburg Seminar, Sept. 2005Freiburg Seminar, Sept. 2005
Sascha Caron
Finding the Higgs or Finding the Higgs or something else something else
ideas to improve the discoveryideas to improve the discoverypotential at hadron colliderspotential at hadron colliders
The situation in 2005The situation in 2005
• We still don’t know the origin of EW symmetry breaking We still don’t know the origin of EW symmetry breaking The Higgs boson is not discovered yetThe Higgs boson is not discovered yet
• Even with the SM Higgs: Even with the SM Higgs: ‘‘fine tuning’ is required in the model to remain valid to high energies?,fine tuning’ is required in the model to remain valid to high energies?, Gravity is not included?, Fermion masses?Gravity is not included?, Fermion masses?
typical solutions by increasing the number oftypical solutions by increasing the number of symmetries, dimensions, forces, …symmetries, dimensions, forces, …
Higgs ? Something else?Higgs ? Something else?
Sascha Caron page 1Sascha Caron page 1
Investigate if there is Investigate if there is other physics beyond the other physics beyond the Standard ModelStandard Model
Investigate if there is Investigate if there is other physics beyond the other physics beyond the Standard ModelStandard Model
Investigate if EW Investigate if EW symmetry breaking symmetry breaking is caused by the Higgs.is caused by the Higgs.
Investigate if EW Investigate if EW symmetry breaking symmetry breaking is caused by the Higgs.is caused by the Higgs.
Part 1Part 1Increase Increase Higgs findingHiggs finding
capabilities in ‘most likely‘capabilities in ‘most likely‘SM decay modes/channelsSM decay modes/channels
(I chose H -> bb)(I chose H -> bb)
Part 1Part 1Increase Increase Higgs findingHiggs finding
capabilities in ‘most likely‘capabilities in ‘most likely‘SM decay modes/channelsSM decay modes/channels
(I chose H -> bb)(I chose H -> bb)
Part 2Part 2Data mining strategies Data mining strategies
How to find something potentially How to find something potentially interesting and previously interesting and previously unexpected in the data?unexpected in the data?
Part 2Part 2Data mining strategies Data mining strategies
How to find something potentially How to find something potentially interesting and previously interesting and previously unexpected in the data?unexpected in the data?
The situation in 2005The situation in 2005
Sascha Caron page 2Sascha Caron page 2
• Part 1 Some ideas to improve H->bb
• Part 2 Is there something else?
OutlineOutline
Sascha Caron page 3Sascha Caron page 3
Some ideas to improve H->bbSome ideas to improve H->bb
Part 1Part 1
o Background for Higgs->bb is in some channels so high thatBackground for Higgs->bb is in some channels so high that even triggering becomes difficult:even triggering becomes difficult: B-triggering at DZeroB-triggering at DZero
o b-jet identification important for early Higgs discoveryb-jet identification important for early Higgs discovery How can we further improve the b-identification?How can we further improve the b-identification?
Study b-jets using top events at ATLASStudy b-jets using top events at ATLAS
The quest for H->bb_barThe quest for H->bb_bar
Sascha Caron page 5Sascha Caron page 5
B trigger at DØB trigger at DØ
Sascha Caron page 6Sascha Caron page 6
Find b-events Find b-events early to keep early to keep high efficiencyhigh efficiency
at an acceptableat an acceptableraterate
Find b-events Find b-events early to keep early to keep high efficiencyhigh efficiency
at an acceptableat an acceptableraterate
Events Events per per
secondsecond
QCD EQCD ETT>30 GeV >30 GeV dijet productiondijet production
GoalsGoals Z->bb, HZ->bbvv, Z->bb, HZ->bbvv,
H->bb, etc.H->bb, etc.maybe B physicsmaybe B physics
b-jets Eb-jets ETT>30 GeV>30 GeV
Z-> b bbarZ-> b bbar
Higgs->b bbarHiggs->b bbar
ZH-> bbvv, bH->bbb etc.ZH-> bbvv, bH->bbb etc.
>10>10
0.10.1
0.010.01
DØ in Run IIDØ in Run II
The Silicon Track The Silicon Track Trigger is based Trigger is based on informationon informationof the :of the :
Silicon Microstrip Silicon Microstrip TrackerTracker
Central Fiber Central Fiber Tracker Tracker
The Silicon Track Trigger at D0The Silicon Track Trigger at D0
Sascha Caron page 7Sascha Caron page 7
L1 TriggerL1 Trigger decision timedecision time
about 4 about 4 μμss
2000 Hz2000 Hz 1000Hz1000Hz 50 Hz50 Hz2.5MHz2.5MHz L2 TriggerL2 Trigger
decision timedecision timeabout 200 about 200 μμss
L3 TriggerL3 Trigger decision timedecision timeabout 50 msabout 50 ms
Trigger SystemTrigger System
p p bunchp p bunch
crossing crossing frequencyfrequency
¯̄
o Hardware basedHardware basedo tracks made withtracks made withcentral fiber tracker, central fiber tracker, calorimeter towers, calorimeter towers, muonsmuons
o Hardware/Software Hardware/Software o simple jets, electrons, simple jets, electrons, muons, tausmuons, tauso Silicon Microvertex Silicon Microvertex improved tracks (STT)improved tracks (STT) L2 global processor L2 global processor combines informationcombines information (e.g. STT tracks for very (e.g. STT tracks for very fast B-id)fast B-id)
o Software basedSoftware basedo partial event partial event reconstructionreconstruction(also simple B-id)(also simple B-id)
The Silicon Track Trigger at D0The Silicon Track Trigger at D0
Sascha Caron page 8Sascha Caron page 8
Principal IdeaPrincipal Idea
B B decay length is mm
decay length is mm
Impact parameterImpact parameter(2d in x-y plane)(2d in x-y plane)
B decay productsB decay products
o Silicon Improved Tracks withSilicon Improved Tracks with 2d impact parameter2d impact parameter
o Select events with large impact parameter tracksSelect events with large impact parameter tracks
Interaction point Interaction point is mean beam spotis mean beam spot
The Silicon Track Trigger at D0The Silicon Track Trigger at D0
Sascha Caron page 9Sascha Caron page 9
How can the How can the tracking be tracking be improved?improved?
o Tracks found at L1 with the Central Fiber Tracks found at L1 with the Central Fiber Tracker are used to define roads into the Tracker are used to define roads into the Silicon Silicon
o Silicon hits are clusteredSilicon hits are clustered
o Track is re-fit within the roadTrack is re-fit within the road (IP, (IP, χχ22) within about 50 ) within about 50 µµss
The Silicon Track Trigger at D0The Silicon Track Trigger at D0
IP resolution IP resolution ≈ ≈ 50 50 μμmm
Sascha Caron page 10Sascha Caron page 10
Silicon detectorSilicon detector
Fiber TrackerFiber Tracker
Old idea : select event by a cut on IPOld idea : select event by a cut on IP
ONLINE ALGORITHMONLINE ALGORITHM Loop over the 5 ‘good’ tracks Loop over the 5 ‘good’ tracks
with largest IP and with largest IP and derive the product :derive the product :
Derive probability density functions of tracks in B-events : PB
and non-B events : Pnon-B
Store their ratio into a lookup table on the L2 global processor
A fast B-id algorithm for Level 2A fast B-id algorithm for Level 2
New Idea: Combine tracks in a fast, multivariate algorithmNew Idea: Combine tracks in a fast, multivariate algorithm
ProbabilityProbabilityratio ratio
PPBB/P/Pnon-Bnon-B
Sascha Caron page 11Sascha Caron page 11
P P B,iB,i/ P / P non-B,inon-B,i
A fast B-id algorithm for Level 2A fast B-id algorithm for Level 2
Derive performance of the STT+B-id algorithm with D0 dataDerive performance of the STT+B-id algorithm with D0 data
Data with Data with offlineofflineb-tagsb-tags
Cut methodCut method
B-id algorithmB-id algorithm
Sascha Caron page 12Sascha Caron page 12
Data without Data without offline b-tagoffline b-tag
Discriminator of the B-id algorithm Discriminator of the B-id algorithm Background efficiency Background efficiency
Sig
na
l effi
cie
ncy
Sig
na
l effi
cie
ncy
Eve
nts
E
ven
ts
The quest for H->bb_barThe quest for H->bb_bar
Next step:Next step: Have we learned something for ATLAS/CMS?Have we learned something for ATLAS/CMS?
Sascha Caron page 13Sascha Caron page 13
o Silicon Track Trigger at DZero worksSilicon Track Trigger at DZero works o Further improvement by up to a factor 2 Further improvement by up to a factor 2 with the B-id algorithmwith the B-id algorithm
Impact in next Higgs trigger strategy for difficult channelsImpact in next Higgs trigger strategy for difficult channels
Improving B-id at ATLAS/CMSImproving B-id at ATLAS/CMS
Yes, by using b-jets from dataYes, by using b-jets from dataand not from MC to makeand not from MC to make
b-id algorithms b-id algorithms
Idea:Idea: Select clean sample of Select clean sample of b-jets from datab-jets from data
We know which jet is the We know which jet is the b-jet from top kinematicsb-jet from top kinematics
in the in the background freebackground free and and largelarge tt sample at ATLAS tt sample at ATLAS
CombinatoricalCombinatoricalbackground background
Correctly Correctly assigned jetsassigned jets
Can we further improve the b-jet Can we further improve the b-jet identification?identification?
Sascha Caron page 14Sascha Caron page 14MMqqb qqb (GeV)(GeV)
Improving B-id at ATLAS/CMSImproving B-id at ATLAS/CMS
Expected purity Expected purity >70% >70%
without doingwithout doingkinematic fitkinematic fitor anythingor anything
sophisticatedsophisticated
Use this side Use this side to get a completely to get a completely
clean sampleclean sample
Use this side Use this side to get b-jet to get b-jet (3-jets with(3-jets with
highest vectorhighest vectorsummed pt)summed pt)
Correctly assigned jetsCorrectly assigned jets-> -> We know the b-jet !We know the b-jet !
M M qqb qqb (GeV)(GeV)
W=Two jets with highest
momentum in
reconstructed jjj C.M. frame.
… … many ideas how to improve this …many ideas how to improve this …Sascha Caron page 15Sascha Caron page 15
|M|Mqqqq-M-MWW|<10 GeV|<10 GeV
Improving B-id at ATLAS/CMSImproving B-id at ATLAS/CMS
Old Idea: - Derive b-efficiency using this b-jetOld Idea: - Derive b-efficiency using this b-jet
New Idea: - Important to derive PNew Idea: - Important to derive PBB and P and Pnon-Bnon-B distributions using b-jets distributions using b-jets in different samples and to use data information for taggingin different samples and to use data information for tagging
… … get all b-jet info from data …get all b-jet info from data …
ALTAS b-tagging: ALTAS b-tagging:
TracksTracks i i in the jetin the jet
PPB B (MC b-jets)(MC b-jets)
PPnon-Bnon-B(MC u-jets)(MC u-jets)
Sascha Caron page 16Sascha Caron page 16
Can we reproduce this?Can we reproduce this?
P P B,iB,i/ P / P non-B,inon-B,i
Is there something else ?Is there something else ?
Part 2Part 2
What do we expect to find at the LHC?What do we expect to find at the LHC?
The situation in 2005The situation in 2005
One physicist's schematic view of particle physics in the 21st centuryOne physicist's schematic view of particle physics in the 21st century (Courtesy of Hitoshi Murayama)(Courtesy of Hitoshi Murayama)Sascha Caron page 17Sascha Caron page 17
MSSM
CMSSM
SUSY VERSIONSOF THE SM
NMSSM(+ an additional Higgssinglet)
MN2SSM(2 Q’s withMirror particlesIn addition)
SUSY with extra DimOr SUSY with extra forcesOr ….
The situation in 2005The situation in 2005
Choose this point,Choose this point,look at the LHC data,look at the LHC data,
exclude or not!exclude or not!
Sascha Caron page 18Sascha Caron page 18
We found no deviation We have excluded this point/area which
is epsilon of the parameter space
We found a deviation
Does this mean that the ‘real’ modelis this parameter point?
Is it efficient to work like this?Is it efficient to work like this?
YES, IT HAS BEEN DONE !YES, IT HAS BEEN DONE !
General Search for new Phenomena at H1General Search for new Phenomena at H1
Finding the unexpected – explaining the originFinding the unexpected – explaining the origin
New Strategy: START FROM THE DATANew Strategy: START FROM THE DATA
1)1) Search for deviations in Search for deviations in allall final states final states(they are all interesting either as signal or to understand background)(they are all interesting either as signal or to understand background)
2)2) Determine the regions of ‘greatest deviation’Determine the regions of ‘greatest deviation’
3)3) Determine the origin of these deviations Determine the origin of these deviations
Is this possible?Is this possible?
Sascha Caron page 19Sascha Caron page 19
• Event yields for HERA 1 data (all channels with SM exp. > 0.01 event)
• Good agreement for (almost) all channels
H1 General SearchH1 General Search
Sascha Caron page 19Sascha Caron page 19
Channels which have Channels which have not been syst. studied beforenot been syst. studied before
General SearchGeneral Search
Sascha Caron page 19Sascha Caron page 19
I spend some time at the New Phenomena web pages at LHCI spend some time at the New Phenomena web pages at LHCexperimentsexperiments
A count of final states planned to be studied leads to A count of final states planned to be studied leads to 100-500100-500
However consider permutations of j,b,e,However consider permutations of j,b,e,µ,µ,ττ,v,,v,γγ, + consider e.g. charge?, + consider e.g. charge?
Up to 8 particle final states lead to about Up to 8 particle final states lead to about 4000040000
Did you have events with 2 photons , a jet and a muon at your LEP exp.?Did you have events with 2 photons , a jet and a muon at your LEP exp.?
Search for deviationsSearch for deviations
Search for deviations between data and SM prediction in 1 dim. distributions most sensitive to new physics Very simple and remarkably powerful
H1 General SearchH1 General Search
Need to explore automated data analysis strategiesNeed to explore automated data analysis strategies
- Idea to completely automate a search (DIdea to completely automate a search (DØØ Sleuth analysis) Sleuth analysis)
- H1 General Search : H1 General Search :
Sascha Caron page 20Sascha Caron page 20
Investigate Mall and ΣPT distributions for each channel
Check all connected regions with a size ≥ resolution in a histogram, i.e. calculate the probability p that data agrees with the SM Region of greatest interest is the one with the smallest p
H1 General SearchH1 General Search
Sascha Caron page 21Sascha Caron page 21
Investigate Mall and ΣPT distributions for each channel
Check all connected regions with a size ≥ resolution in a histogram, i.e. calculate the probability p that data agrees with the SM Region of greatest interest is the one with the smallest p
H1 General SearchH1 General Search
Sascha Caron page 21Sascha Caron page 21
Investigate allMall and ΣPT
distributions
Sascha Caron page 22Sascha Caron page 22
Wait - What is the SM?Wait - What is the SM?
“SM” = State of the art MCs
+ δ theory (pdf, scale, model) + δ data (jet energy scale,
etc.)
At the beginning of At the beginning of data takingdata taking
Wait - What is the SM?Wait - What is the SM?
“SM” = State of the art MCs
+ δ theory (pdf, scale, model) + δ data (jet energy scale,
etc.)
Derive uncertainties andDerive uncertainties andMC tuning fromMC tuning from
data by looking atdata by looking atvarious final statesvarious final states
… … a factor a factor of 10 in of 10 in
luminosity luminosity laterlater
A significant danger is finding correlations and signalsA significant danger is finding correlations and signals that do not really exist. that do not really exist.
Many examples in particle physics historyMany examples in particle physics history
We are looking for deviations …We are looking for deviations …How surprised should we be to find some?How surprised should we be to find some?
How likely is a 4-5 sigma deviation at LHCHow likely is a 4-5 sigma deviation at LHCeven if there is nothing in the data?even if there is nothing in the data?
Sascha Caron page 24Sascha Caron page 24 Unsolvable problem if you use 2000 PhD studentsUnsolvable problem if you use 2000 PhD students
Step 1: Repeat the whole analysis with a pseudo data experiment(dice your own MC data) many times.
Quantify the deviationsQuantify the deviations
3%3%
Sascha Caron page 25Sascha Caron page 25
Step 2: Count how manytimes you find deviations bigger than in those in your real data.
3%3% of the of the ““Pseudo H1 experiments”Pseudo H1 experiments”
have found have found a bigger deviation a bigger deviation
Num
ber
of c
hann
els
Num
ber
of c
hann
els
1 101 10-1-1 10 10-2-2 ProbabilityProbabilityto find to find
deviation indeviation inthis channelthis channel
I know that this is not a new idea, but we do not use itI know that this is not a new idea, but we do not use it
What are the numbers for ATLAS?What are the numbers for ATLAS?
An General analysis of LHC dataAn General analysis of LHC data
Going the way into the other direction…Going the way into the other direction…
I’ve tried to illustrate I’ve tried to illustrate some ideas to improve the discovery potential some ideas to improve the discovery potential
at LHC and the Tevatron.at LHC and the Tevatron.
Improving the Higgs discovery potential by an improvedImproving the Higgs discovery potential by an improvedTrigger and B-id Trigger and B-id
A General Search for new phenomena strategy for the LHC A General Search for new phenomena strategy for the LHC
SummarySummary
Search for deviationsSearch for deviations Search for deviations between data and
SM prediction in 1 dim. Distributions (Mall and ΣPT) Check all connected regions with a size ≥ resolution in a histogram, i.e. calculate the probability p that data agrees with the SM
H1 General SearchH1 General Search