Studies towards TGC limit extraction Nick Edwards, University of Glasgow Nick Edwards 1

Outline  Reminder on TGC binnings.  Comparison of SM and TGC distributions at truth level in these bins.  Check how C ZZ looks in the four TGC samples compared to the SM.  First results using a grid method to parameterise yields as a function of the coupling. Nick Edwards 2 Quick reminder on TGCs We add them as extra terms in an effective Lagrangian. For on shell ZZ, we can parameterise them in four independent constants: f5Z, f4Z, f4γ,f5γ With the 1fb -1 analysis we set limits at the 0.1 level

Variables and Bins  Reminder: We have chosen to use the leading Z pT, four- lepton mass and leading lepton pT to calculate the TGC limits.  Chosen bins: –M(4l) : 0-240, , , , 600+ –Pt(lead Z) : 0-60, , , , 300+ –Pt(lead lepton) : 0-60, , , , 250+  Check how TGC distributions look in these binnings using the four Sherpa MC11c samples: –nTGC 0(f4γ=0.1, f5γ=f4Z=f5Z=0.0) –nTGC 1(f5γ=-0.1, f4γ=f4Z=f5Z=0.0) –nTGC 2(f4γ=f5γ=0.1, f4Z=f5Z=0.0) –nTGC 3 (f4γ=f5γ=0.0, f4Z=f5=0.1)  NB these samples are roughly at the boundary of what we have already excluded.  These distributions are at truth level. Nick Edwards 3

Four Lepton Mass Nick Edwards 4 Not really sensitive in first 2 bins

Leading Z pT Nick Edwards 5 Not really sensitive in first 2 bins

Leading Lepton pT Nick Edwards 6 Not really sensitive in first 2 bins

C ZZ in TGC samples  CZZ seems to be ~ 10% higher in the TGC samples in the four electron channel and ~5% in the 2e2mu channel. Nick Edwards 7

C ZZ in TGC samples : m ZZ Nick Edwards 8 In the electron channels, C ZZ seems much higher in the TGC samples in the high bins than in the SM. In four muon channel is a bit lower in the last bin – but could be stats.

C ZZ in TGC samples : P T Z1 Nick Edwards 9

C ZZ in TGC samples : P T Lep1 Nick Edwards 10

Yield Parameterisation  Need to parameterise the predicted yield at as a function of the anomalous coupling, varying one and holding the others constant.  Doing this find a quadratic dependence: e.g. Yield = F 00 + F 44 (f 5 Z ) 2  Previously we used afterburner, which takes the 4 fully reconstructed TGC samples (actually it can do it with one, but four are used as a cross check) and reweights to different values of the couplings to obtain the yield curves.  An alternative “brute force” approach is to generate a grid of samples: –Pick one constant to vary, holding the others constant. –Generate a load of samples at different values of the coupling. –Obtain the predicted yield at each value of the coupling, then can fit a parabola to obtain the paramaterised yield. Nick Edwards 11 From 1fb-1 analysis Differential Cx including TGCsSet all except f 5 Z to 0

f 5 Z Parameterisation  Try this approach this for f 5 Z.  Generate 100k events with Sherpa with f 5 Z = -0.4, -0.25, , 0.1, 0.25, 0.4.  f 5 Z = -0.4 sample not finished yet…  Then run analysis code to obtain predicted yield at truth level and fit to a parabola.  These “predicted yields” are all at truth level so far.  What we want is the predicted yield at reconstruction level – ie what we observe. Unfortunately it’s not really practical to fully simulate and reconstruct a grid of samples, so instead predict the yield at truth level and use C ZZ to come back to the reconstruction level –Relies on C ZZ being the same in the TGC samples as the SM – have shown it isnt’!  Also need to apply k-factor to get normalisation right. Nick Edwards 12

f 5 Z Parameterisation - Unbinned Nick Edwards 13

f 5 Z Parameterisation - m ZZ Nick Edwards 14 Same thing but in the 5 bins of m ZZ that we’ve chosen. Fit looks worse in the first 2 bins, but this is just because it’s very zoomed in compared to the other 2. Can see by looking at the “b” parameter that sensitivity is very low in these bin.

f 5 Z Parameterisation – P T Z1 Nick Edwards 15 Same thing but in the 5 bins of P T Z1 that we’ve chosen.

f 5 Z Parameterisation – P T lep1 Nick Edwards 16 Same thing but in the 5 bins of P T lep1 that we’ve chosen.

Conclusions  C ZZ seems to be 5-10% different in the TGC samples to the SM ones. Difference seems to be coming mainly from electron channels. –Need to understand where this comes from.  First attempts at parameterising “truth yield” as a function of f 5 Z. If C ZZ were the same would be simple to convert this to expected observed events.  Then can compare this to afterburner as a cross- check. Nick Edwards 17