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Tau Triggering at sLHC

Tau Triggering at sLHC. Alexei Safonov (Texas A&M University). Basics of Hadronic Tau Tagging. Tau hadronic decay modes: Br ~ 65% Br( t → h ± n t )~12% Br( t → h ± p o n t )~25% Br( t → h ± 2p o n t )~10% Tagging strategy – select a narrow jet: Typically done with a double cone:

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Tau Triggering at sLHC

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  1. Tau Triggering at sLHC Alexei Safonov (Texas A&M University)

  2. Basics of Hadronic Tau Tagging • Tau hadronic decay modes: Br ~ 65% • Br(t→h±nt)~12% • Br(t→h±pont)~25% • Br(t→h±2pont)~10% • Tagging strategy – select a narrow jet: • Typically done with a double cone: • Signal cone of ~10o (0.15 rad) • Isolation cone ~30o (0.5 rad) • Seeding (e.g. track pT) and energy thresholds are negotiable subject to desired signal to background ratio • Fine-tuning of the jet narrowness requirement

  3. Trigger Implementation • Typical triggering strategy: • Energy and isolation emulate narrow jet requirement to first order • Important refinements to improve background rejection: • Seed thresholds • Narrow cluster • General notes: • 3D tracking isolation is preferred b/c less sensitive to PU • Seeding is very efficient against jets

  4. Amount of energy carried by tracks around tau/jet direction (no PU) ~dET/dcosq Cone 10o-30o Ideal Tau Trigger • “Ideal Tau Trigger”: fit the profile of a candidate to distinguish from jets and PU fluctuations • Actual triggers are approximations of the “ideal trigger” • Key features: • Tau profile localized in DR~0.07-0.15 • Effective discrimination against jets requires fine sampling of energy distribution • Order of DR~0.05 Y-axis: average ET and RMS • Measuring energy in small cones - extra discriminating power

  5. Cone 10o-30o ~dET/dcosq Amount of energy carried by tracks around tau/jet direction (PU=100) Calorimeter Tau Trigger: High PU • High PU - PU becomes an independent player: • Softer “taus” just from PU fluctuations? • Straight Isolation won’t work anymore: • Before we could escape with summing up the surrounding energy as it is small for taus (PU), larger for jets • Now isolation is dominated by (fluctuating) PU • We loose jet rejection • Increase tower thresholds to decrease sensitivity to PU? • Jet rejection will diminish, but worth looking into • No doubt that discrimination of ideal cal trigger against jets will severely diminish at high PU • But is our current trigger ideal? Y-axis: average ET and RMS

  6. Current CMS Tau Trigger • Start with a regular jet • Energy from DR~0.5 • Narrow jet requirement: • Make clusters with • ET(ECAL)>3 GeV or ET(HCAL)>3 GeV • Fail if the cluster is not narrow • Isolation (being proposed now): • Count SET in each of the eight isolation regions • Fail if more than one region w/ SET>2 GeV

  7. Ongoing Incremental Improvements • Can sort of live ok as long as PU is reasonably low • Upcoming proposal will decrease rates by a factor of 2 (4) for single_tau+X (di-tau) triggers: • Loosened narrow cluster requirement and new isolation with partial sums

  8. Shortcomings of Existing Trigger • Optimal trigger requires fine samplings of spatial energy distribution. Is it what we do? No! • Currently, only full jet energy (sum in cone 0.5) is available • Actually even worse – we have access to “corrected” jet energy using ad hoc QCD jet correction (x1.8) • We need to measure energy from a small cone (cluster) • Rejection against jets (shifts the jet spectrum to the left) NPU=50 • At high PU such measurement will go completely insane due to huge PU contributions • CMSSW keeps crashing due to memory limitations. Even PU=50 is a serious problem (only can do local cal reco), PU=100 is plain impossible (ET(L1)-ET(t)/ET(t)

  9. Cone 10o-30o ~dET/dcosq Amount of energy carried by tracks around tau/jet direction (PU=100) Shortcomings of Existing Trigger • Optimal trigger has access to the jet energy profile. We don’t! • Current tau veto bit by construction is a mix of seeding and “narrow jet” requirement • At high PU will be completely inefficient as one will need to set very high thresholds to stay above PU, which in turn will totally mask jet contributions • Efficiency of isolation sums will become inefficient just as for the ideal trigger • And the sum runs around “far area”, so really no discrimination against jets

  10. Potential Improvements: Seeding • Track seeding is one way of using “energy profile”. Very efficient as taus have tracks. • But also photons: • Br(t→h±nt)~12% • Br(t→h±pont)~25% • Track based seeding • Top Figure: pT>5-10 GeV • Highly effective against jets • Photon-based seeding: • Why not? We have good ECAL! • Bottom Plot: pT(g)>5 GeV Taus (all hadronic modes!!!) Jets (PF based pT) pT(trk)>5 GeV Taus (all hadronic modes!!!) Jets (PF based pT) pT(g)>5 GeV

  11. Cone 10o-30o ~dET/dcosq Amount of energy carried by tracks around tau/jet direction (PU=100) Potential Improvements: Profile • Apart from seeding and narrow cone energy measurement, with finer energy sampling we increase ”significance” of the “signal” over PU and can get more sensitive to jets • Could be possible to construct a “fitting” algorithm that can be implemented on a chip • Compare hypothesis of a tau versus jet • Might be possible to optimize thresholds to suppress PU

  12. Density of tracks with pT>1 GeV around tau direction (no PU) Cone 10o-30o Potential Improvements: Tracking • 2D tracking implemented in L1: • Seeding significantly improves jet rejection • Thresholds to be optimized, probably 5-10 GeV • Matching with calorimeter can suppress fake rate • 2D+zo - can use isolation: • Effectively fall back into the low PU regime • Need low thresholds for efficient QCD jet rejection (1-2 GeV) • Reasonable resolution in zo • Need low fake rate to keep signal efficiency high Taus (all hadronic modes!!!) Jets (PF based pT) pT(trk)>5 GeV

  13. Summary • High PU will no doubt be very challenging • However, irrespective of tracking, significantly better performance achievable with following improvements to the calorimeter tau trigger: • Energy profiling with smaller spatial resolution • Tau energy measurement with small cone clustering (rather than from a huge cone) • Seeding (photons and/or narrow clusters) • Tracking in L1 can be very efficient for seeding and isolation • Requires several thresholds, reasonable resolution and low fake rate • Accurate quantitative estimations, optimization and implementation will require significant effort, but hardly avoidable • And reliable simulation tools (parameterization-based?)

  14. Willing and Unwilling Contributors • People whose ideas and plots were either borrowed or stolen from: • Alfredo Gurrola, Chi Nhan Nguyen, Teruki Kamon (Texas A&M) • Mike Bachtis, Sridhara Dasu (Wisconsin) • Sho Maruyama, Max Chertok (UC Davis)

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