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Transcript of 1 17 th May 2007 C.P. Ward Sensitivity of ZZ->llnunu to Anomalous Couplings Pat Ward University of...
![Page 1: 1 17 th May 2007 C.P. Ward Sensitivity of ZZ->llnunu to Anomalous Couplings Pat Ward University of Cambridge.](https://reader035.fdocuments.us/reader035/viewer/2022062314/56649c7c5503460f94930ef7/html5/thumbnails/1.jpg)
1 17th May 2007 C.P. Ward
Sensitivity of ZZ->llnunu to Anomalous Couplings
Pat Ward
University of Cambridge
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2 17th May 2007 C.P. Ward
Introduction
Advantage of ZZ->llnunu c.f. ZZ->llllLarger branching ratio: 6 times as many
events before cuts Disadvantage
Very large backgrounds from Z+jets and ttbar Investigate sensitivity of limits on
anomalous couplings to background level and systematic error on background
This is very preliminary ‘work in progress’
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3 17th May 2007 C.P. Ward
Anomalous Couplings
ZZZ and ZZg vertices forbidden in SM Production of on-shell ZZ probes ZZZ and ZZg
anomalous couplings: f4Z, f5Z, f4g f5g All = 0 in SM
Forbidden in SM
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4 17th May 2007 C.P. Ward
Anomalous Couplings
f4 violate CP; helicity amplitudes do not interfere with SM; cross-sections depend on f4**2 and sign cannot be determined
f5 violate P; do interfere with SM Couplings depend on energy. Usual to introduce
a form factor to avoid violation of unitarity: f(s’) = f0 / (1 + s’/Lambda**2)**n Studies below use n=3, Lambda = 2 TeV Also assume couplings are real and only one
non-zero
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5 17th May 2007 C.P. Ward
AC Monte Carlo
Study AC using LO Monte Carlo of Baur and Rainwater
First compare SM predictions for ZZ->eenunu cross-section with Pythia:
CTEQ4L pdfs; 76 < mZ < 106 GeV
BR Pythia (no showers)
Pythia
No cuts 125.5 fb 126.3 fb 126.3 fbpT(e)> 15 GeV
|eta(e)| < 2.5 pTmis > 50 GeV
35.1 fb 34.5 fb 39.5 fb
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6 17th May 2007 C.P. Ward
Comparison with Pythia
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7 17th May 2007 C.P. Ward
PDF dependence
Comparisons with Pythia used out-of-date CTEQ4L because BR program used pdflib
Have now modified it to use LHAPDF Following results use CTEQ6LL
pdf set ZZ->eenunu with cuts
CTEQ4L 36.85 fb
CTEQ6LL 36.51 fb
MRST2001LO 36.90 fb
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8 17th May 2007 C.P. Ward
Signature of Anomalous Couplings
Anomalous couplings produce increase in ZZ invariant mass, Z pT and lepton pT distributions
For ZZ->llnunu can use high pT(Z) cross-section to obtain limit, or fit Z pT distribution
e.g above for ZZ->eenunu
with pT(e) > 15 GeV,
|eta(e)| < 2.5
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9 17th May 2007 C.P. Ward
Limits from Cross-section Measurement
First consider measurement of ZZ->llnunu cross-section for pT(Z) > pTmin
N.B. this is LO: pT(ll) = pTmiss Take pT(e) > 15 GeV, |eta(e)| < 2.5, pTmin = 50
GeV SM: 72.7 fb -> 727 signal events for 10 fb-1 Calculate cross-section, hence expected events
as function of f4Z E.g. f4Z = 0.01: 76.2 fb -> 762 signal events
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10 17th May 2007 C.P. Ward
Limits from Cross-section Measurement
Use chi-squared comparison between expected and ‘observed’ (=SM) numbers of events to determine 95% c.l. on coupling
(assume only one coupling non-zero) Calculate limit as function of ratio of background
to SM signal First assume statistical errors only, then
consider effect of a systematic error on the background
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11 17th May 2007 C.P. Ward
pTmiss > 50 GeV; statistical errors onlyLittle dependence on background fraction
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12 17th May 2007 C.P. Ward
pTmiss > 50 GeV; 20% systematic error on background
Strong dependence on background: limits independent of luminosity for high background
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13 17th May 2007 C.P. Ward
pTmiss > 150 GeV; statistical errors only
Limits much better than using pTmiss > 50 GeV
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14 17th May 2007 C.P. Ward
Limits from Fits to pT Distribution
Limits from a simple cross-section measurement depend on pT cut – harder pT cut can give better limit despite much lower statistics
Therefore better to fit pT distribution Results below are for ZZ->llnunu with pT(l)>20
GeV, |eta(l)|<2.5 Use BR program to generate pT distributions for
several values of couplings (only one non-zero at a time)
In each pT bin fit cross-section to quadratic in coupling to obtain distribution at arbitrary value
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15 17th May 2007 C.P. Ward
Cross-section v f4Z in pT bins
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16 17th May 2007 C.P. Ward
Cross-section v f5Z in pT bins
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17 17th May 2007 C.P. Ward
Limits from Fits to pT Distribution
Create ‘fake data’ sample: Calculate expected SM events in each pT bin Add background – constant fraction of SM Apply Gaussian smearing
Construct error matrix Statistical errors plus systematic error on background
assumed fully correlated Fit fake data sample
One parameter fit to f4Z**2 or f5Z 95 % c.l. from X**2 – X**2min = 3.84
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18 17th May 2007 C.P. Ward
Limits from Fits to pT Distribution
Generate 1000 fake data samples for each value of background fraction and each value of background systematic
Mean X**2/dof = 1 Mean f4**2 = 0
As expected
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19 17th May 2007 C.P. Ward
Results for 100 fb-1, eff = 1.0 from Fit in Range 50 GeV < pT < 500 GeV
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20 17th May 2007 C.P. Ward
Results for 100 fb-1, eff = 1.0 from Different Fit Ranges and Binning
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21 17th May 2007 C.P. Ward
Summary so far….
Limits worse with more background – but not dramatically so
Limits worse with large systematic error on background – but not dramatically so
BUT this was assuming constant background – unrealistic
AC have little effect at low pT, so limits not too sensitive to overall normalization of pT distribution
Limits depend on binning of pT distribution – will need to be optimized for given integrated luminosity
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22 17th May 2007 C.P. Ward
Next Steps
Investigate effect of more realistic (steeply falling) background distribution
Investigate optimal binning Estimate limits for expected experimental
efficiency/background Set up framework for 2-D couplings Think how we are going to predict
expected pT distribution (reweighting, fast MC etc.)