WW Scattering at ATLAS

1. WW Scattering at ATLAS Sarah Allwood

2. Introduction • An important goal of LHC is to investigate electroweak symmetry breaking. • Without some new physics WLWL→ WLWL violates perturbative unitarity at CoM E~1.2 TeV. • Possibilities are: additional particle(s) with m ≤ 1TeV, and/or W and Z interactions become strong at E ~TeV. • WL WL → WL WL is described at low energy by an effective Lagrangian: the EWChL. • a4 and a5 parameterise the “new physics”. • EWChL made valid up to higher energies by unitarity constraints: this can predict resonances ~1 TeV in WW scattering. Map of a4-a5 space obtained using the Padé unitarisation protocol. Taken from hep-ph/0201098 J.M. Butterworth, B.E. Cox, J.R. Forshaw. Sarah Allwood

3. Signal Scenarios Five representative scenarios for the “new physics” were chosen: • a scalar resonance of 0.9 TeV, • a vector resonance of 1.4 TeV, • a vector resonance of 1.9 TeV, • a double resonance of a scalar at 800 GeV and a vector at 1.4 TeV, • a scenario with no resonances (the continuum). How sensitive is ATLAS to these resonances in WW→WW→lqq ? All investigated using kT and cone algorithms. Sarah Allwood

4. Signal and Backgrounds • high pT lepton • high ETmiss and high pT of the leptonic W reconstructed from these. • Jet(s) with high pT and m ~ mW. • Little hadronic activity in the central region (|η|<2.5) apart from the hadronic W. • Tag jets at large η (|η|>2), from the quarks that produced the W’s. The main backgrounds are from W+jets (where W  l)and production, with cross sections ~60,000 fb and ~16,000 fb compared to signal cross sections ~100 fb. Sarah Allwood

5. ATLFAST • The fast detector simulation and reconstruction program for ATLAS. • Includes magnetic field and the η coverage and size of detectors. • Constructs 3 simple calorimeters – barrel (0.1×0.1 in η×φ) and forward (0.2×0.2). • Part of ATHENA, the ATLAS software framework, and linked to other ATHENA packages (event generators and jet algorithms). • Changes made to • add the modified version of Pythia, • output ntuple with extra information – the 4-vectors of the W’s, and the calorimeter cells, • add pile-up for low luminosity running and other detector smearing to cells before clustering – important if we want to change the cone radius or use the kT algorithm. • Underlying event included. Sarah Allwood

6. Jet Finding Cone algorithm: Constructs cones of a fixed radius ΔR=√(Δη2 + Δφ2) around seed cells. Defines these as jets. Kt algorithm: For each object, calculate • dkl (~pT2 of k with respect to l) • dkB (~pT2 of k with respect to the beam) • Scale dkB by the R-parameter dk=dkBR2 • If dk < dkl, k is a jet. • If dkl < dk, merge k and l (add their 4-momenta) and define this as a new object. • Repeat until all objects are in jets. Sarah Allwood

7. cone kT Reconstructing the hadronic W Mass of the highest pT jet in the event: For the cone, a better procedure than 1 jet approach: • Use cones of ΔR=0.2 to find 2 jet centres. • Sum 4–momenta of all calorimeter cells within ΔR=0.4 of the jet centres to define the hadronic W. • Best resolution for kT: R=0.5 • Best resolution for cone: ΔR=0.7 Sarah Allwood

8. Reconstructing the hadronic W, kT • For the kT, use an R-parameter of 0.5 and get an extra cut from “subjet analysis”: • Rerun kT algorithm in subjet mode on the cells in the highest pT jet. • Clustering is stopped at a scale ycutpT2→ clusters remaining are subjets. • Scale at which jet is resolved into two subjets is ~mW2 for a true W. • Make a cut at 1.55<log(pT√y)<2.0. • R=0.5 used for all other jet finding in the event. Sarah Allwood

9. kT cone Summary of analysis • Select highest pT isolated lepton in event. • Reconstruct leptonic W from lepton and missing energy. • Reject events with pTW < 320 GeV. • Reconstruct hadronic W • From two jets for the cone, • From one jet and a subjet cut for the kT. • Reject events with pTW < 320 GeV. • Reject events outside the range mW±2σ Sarah Allwood

10. Further cuts Top mass cut – reject events where m(W+jet)~mtop Tag jet veto – require forward and backward jets with E > 300 GeV and |η| > 2. pT cut – reject events with pT(WW+tag jets) > 50 GeV Minijet veto – reject events that have more than one jet (pT > 15 GeV) in the central region Sarah Allwood

11. kT cone Low luminosity results For 30 fb-1: Sarah Allwood

12. Full simulation • ATLAS is preparing samples for the Rome physics workshop (June 2005), where each working group will present results from full simulation. • The full chain is • generation → outputs 4-momentum of particles. • simulation → tracks particles through detector, outputs hits in the detector. • pile-up → merging hits that came from the same (or close) bunch crossings. • digitisation → simulates the response of the detector. Output should look like raw data. • mixing → mix different physics events. • reconstruction → output reconstructed particles and jets. • 15 million events overall, of which 10 million are backgrounds that are common between several working groups (mine fall into this category): • 4 million W+jets, where W→l. A high pT subsample will be generated. • 1.5 million , including a subset with pT(t) > 500 GeV • Generate 10000 events for each of the signals. • The emphasis is on the first year of running – i.e. low luminosity. Sarah Allwood

13. Conclusions and further work • The results depend on the cone radius and kT R-parameter used. • For kT, can reconstruct hadronic W using one jet (due to the useful subjet analysis cut) and the optimum R-parameter to use is 0.5. • kT and cone results are similar. • Final signal/background > 1 in all cases. • Will get much more information (spin of resonance) from one year of high luminosity running (100 fb-1): • Pile-up is much worse – perform a similar analysis, but: • Use a cell threshold E > 2 GeV (was 1 GeV for low luminosity), • Minijet veto on pT > 25GeV jets (was 15 GeV for low luminosity). • But this is just fast simulation – next step is to look at full simulation. Sarah Allwood