1. Freiburg Seminar, Sept. 2005 Sascha Caron Finding the Higgs or something else ideas to improve the discovery ideas to improve the discovery potential at hadron colliders

2. The 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 yet  The 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 of  typical solutions by increasing the number of symmetries, dimensions, forces, … symmetries, dimensions, forces, … Higgs ? Something else? Higgs ? Something else? Sascha Caron page 1

3. Investigate if there is other physics beyond the Standard Model Investigate if there is other physics beyond the Standard Model Investigate if EW symmetry breaking is caused by the Higgs. Investigate if EW symmetry breaking is caused by the Higgs. Part 1 Increase Higgs finding capabilities in ‘most likely‘ SM decay modes/channels (I chose H -> bb) Part 1 Increase Higgs finding capabilities in ‘most likely‘ SM decay modes/channels (I chose H -> bb) Part 2 Data mining strategies How to find something potentially interesting and previously unexpected in the data? unexpected in the data? Part 2 Data mining strategies How to find something potentially interesting and previously unexpected in the data? unexpected in the data? The situation in 2005 Sascha Caron page 2

4. Part 1 Some ideas to improve H->bb Part 2 Is there something else? Outline Sascha Caron page 3

5. Some ideas to improve H->bb Part 1

6. o Background for Higgs->bb is in some channels so high that even triggering becomes difficult: even triggering becomes difficult: B-triggering at DZero B-triggering at DZero o b-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 ATLAS Study b-jets using top events at ATLAS The quest for H->bb_bar Sascha Caron page 5

7. B trigger at DØ Sascha Caron page 6 Find b-events early to keep high efficiency at an acceptable rate Find b-events early to keep high efficiency at an acceptable rate Eventspersecond QCD E T >30 GeV dijet production Goals Z->bb, HZ->bbvv, H->bb, etc. Z->bb, HZ->bbvv, H->bb, etc. maybe B physics b-jets E T >30 GeV Z-> b bbar Higgs->b bbar ZH-> bbvv, bH->bbb etc. >10 0.1 0.01

8. DØ in Run II The Silicon Track Trigger is based on information of the : Silicon Microstrip Tracker Central Fiber Tracker The Silicon Track Trigger at D0 Sascha Caron page 7

9. L1 Trigger decision time decision time about 4 μs 2000 Hz 1000Hz 50 Hz 2.5MHz L2 Trigger decision time decision time about 200 μs L3 Trigger decision time decision time about 50 ms Trigger System p p bunch crossing frequency ¯ o Hardware based o tracks made with central fiber tracker, calorimeter towers, muons o Hardware/Software o simple jets, electrons, muons, taus o Silicon Microvertex improved tracks (STT)  L2 global processor combines information (e.g. STT tracks for very fast B-id) o Software based o partial event reconstruction (also simple B-id) The Silicon Track Trigger at D0 Sascha Caron page 8

10. Principal Idea B decay length is mm Impact parameter (2d in x-y plane) B decay products o Silicon Improved Tracks with 2d impact parameter 2d impact parameter o Select events with large impact parameter tracks Interaction point is mean beam spot The Silicon Track Trigger at D0 Sascha Caron page 9

11. How can the tracking be improved? o Tracks found at L1 with the Central Fiber Tracker are used to define roads into the Silicon o Silicon hits are clustered o Track is re-fit within the road (IP, χ 2 ) within about 50 µs (IP, χ 2 ) within about 50 µs The Silicon Track Trigger at D0 IP resolution ≈ 50 μm ≈ 50 μm Sascha Caron page 10 Silicon detector Fiber Tracker Old idea : select event by a cut on IP

12. ONLINE ALGORITHM Loop over the 5 ‘good’ tracks with largest IP and derive the product : Derive probability density functions of tracks in B-events : P B and non-B events : P non-B   Store their ratio into a lookup table on the L2 global processor A fast B-id algorithm for Level 2 New Idea: Combine tracks in a fast, multivariate algorithm Probabilityratio P B /P non-B Sascha Caron page 11 P B,i / P non-B,i

13. A fast B-id algorithm for Level 2 Derive performance of the STT+B-id algorithm with D0 data Data with offlineb-tags Cut method B-id algorithm Sascha Caron page 12 Data without offline b-tag Discriminator of the B-id algorithm Background efficiency Signal efficiency Events

14. The quest for H->bb_bar Next step:  Have we learned something for ATLAS/CMS? Sascha Caron page 13 o Silicon Track Trigger at DZero works o Further improvement by up to a factor 2 with the B-id algorithm with the B-id algorithm  Impact in next Higgs trigger strategy for difficult channels

15. Improving B-id at ATLAS/CMS Yes, by using b-jets from data and not from MC to make b-id algorithms b-id algorithms Idea: Select clean sample of b-jets from data  We know which jet is the b-jet from top kinematics in the background free and large tt sample at ATLAS Combinatoricalbackground Correctly assigned jets Can we further improve the b-jet identification? Sascha Caron page 14 M qqb (GeV)

16. Improving B-id at ATLAS/CMS Expected purity >70% without doing kinematic fit or anything sophisticated sophisticated Use this side to get a completely clean sample Use this side to get b-jet (3-jets with highest vector summed pt) Correctly assigned jets -> We know the b-jet ! M qqb (GeV) W=Two jets with highest momentum in reconstructed jjj C.M. frame. … many ideas how to improve this … Sascha Caron page 15 |M qq -M W |<10 GeV

17. Improving B-id at ATLAS/CMS Old Idea: - Derive b-efficiency using this b-jet New Idea: - Important to derive P B and P non-B distributions using b-jets in different samples and to use data information for tagging in different samples and to use data information for tagging … get all b-jet info from data … ALTAS b-tagging: Tracks i in the jet P B (MC b-jets) P non-B (MC u-jets) Sascha Caron page 16 Can we reproduce this? P B,i / P non-B,i

18. Is there something else ? Part 2

19. What do we expect to find at the LHC? The situation in 2005 One physicist's schematic view of particle physics in the 21st century (Courtesy of Hitoshi Murayama) (Courtesy of Hitoshi Murayama) Sascha Caron page 17

20. MSSM CMSSM SUSY VERSIONS OF THE SM NMSSM (+ an additional Higgs singlet) MN2SSM (2 Q’s with Mirror particles In addition) SUSY with extra Dim Or SUSY with extra forces Or …. The situation in 2005 Choose this point, look at the LHC data, exclude or not! Sascha Caron page 18

21. 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’ model is this parameter point?  Is it efficient to work like this?

22. YES, IT HAS BEEN DONE ! General Search for new Phenomena at H1 Finding the unexpected – explaining the origin New Strategy: START FROM THE DATA 1)Search for deviations in all final states (they are all interesting either as signal or to understand background) 2)Determine the regions of ‘greatest deviation’ 3)Determine the origin of these deviations Is this possible? Sascha Caron page 19

23. Event yields for HERA 1 data (all channels with SM exp. > 0.01 event) Good agreement for (almost) all channels H1 General Search Sascha Caron page 19 Channels which have not been syst. studied before

24. General Search Sascha Caron page 19 I spend some time at the New Phenomena web pages at LHC experiments A count of final states planned to be studied leads to 100-500 However consider permutations of j,b,e,µ,τ,v,γ, + consider e.g. charge? Up to 8 particle final states lead to about 40000 Did you have events with 2 photons, a jet and a muon at your LEP exp.?

25. Search 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 Search Need to explore automated data analysis strategies Need to explore automated data analysis strategies - Idea to completely automate a search (DØ Sleuth analysis) - H1 General Search : Sascha Caron page 20

26. Investigate M all and ΣP T 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 Search Sascha Caron page 21

27. Investigate M all and ΣP T 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 Search Sascha Caron page 21

28. Investigate all M all and ΣP T distributions Sascha Caron page 22

29. 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 data taking

30. Wait - What is the SM? “ SM” = State of the art MCs + δ theory (pdf, scale, model) + δ data(jet energy scale, etc.) Derive uncertainties and MC tuning from data by looking at various final states … a factor of 10 in luminositylater

31. A significant danger is finding correlations and signals that do not really exist. that do not really exist. Many examples in particle physics history We are looking for deviations … How surprised should we be to find some? How likely is a 4-5 sigma deviation at LHC even if there is nothing in the data? Sascha Caron page 24  Unsolvable problem if you use 2000 PhD students

32. Step 1: Repeat the whole analysis with a pseudo data experiment (dice your own MC data) many times. Quantify the deviations 3% Sascha Caron page 25 Step 2: Count how many times you find deviations bigger than in those in your real data. 3% of the “Pseudo H1 experiments” have found a bigger deviation Number of channels 1 10 -1 10 -2 Probability to find deviation in this channel I know that this is not a new idea, but we do not use it

33. What are the numbers for ATLAS?

34. An General analysis of LHC data Going the way into the other direction…

35. I’ve tried to illustrate some ideas to improve the discovery potential at LHC and the Tevatron. Improving the Higgs discovery potential by an improved Trigger and B-id A General Search for new phenomena strategy for the LHC Summary

36. Search for deviations Search for deviations between data and SM prediction in 1 dim. Distributions (M all and ΣP T )   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 Search