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Search for X WZ 0  evjj Paper Seminar. David Toback & Chris Battle Texas A&M Henry Frisch University of Chicago. Outline. Theory and Signature Overview of Analysis; Event Selection and What signal would look like; Acceptance Backgrounds Comparing Data, Signal and Backgrounds

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search for x wz 0 evjj paper seminar

Search for XWZ0  evjjPaper Seminar

David Toback & Chris Battle

Texas A&M

Henry Frisch

University of Chicago

outline
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
x wz 0 evjj
XWZ0  evjj
  • We want to search for new physics in a model independent manner
  • Many models predict new particles which decay via XWZ0
  • The Wen and Z0jj have advantages:
    • Electrons are straightforward to trigger on and identify
    • Z0jj has a large branching fraction
example feynman diagram
Example Feynman Diagram
  • Heavy Charged Vector Boson: W’ WZ0
  • Technicolor Rho: rT WZ0

W’ width, G(W’), can vary greatly

Search for X as a function of mass and width

0

outline1
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
w 2jets event selection summary
W+2jets Event Selection & Summary
  • 1 electron
  • Missing ET
  • 2 Jets
  • 110 pb-1 of data from Run 1A and 1B
looking for signal
Looking for Signal
  • Model X production using W’  WZ0 in Pythia
  • Look for X WZ0 mass bumps in both Mjj and MW+jj
overview of analysis
Overview of Analysis
  • Constrain PZn using W mass
  • Reconstruct dijet and W+dijet masses
  • Look for bumps in dijet vs. W+dijet mass plane using a fit

Reconstruction procedure does a good job of reproducing W’

acceptance vs mass
Acceptance vs. Mass

Good Acceptance as a function of mass

G(X)<< MX

outline2
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
backgrounds
Backgrounds
  • W+jets ( W  eν, W τν  eννν )
  • Non W+jets
    • Fakes
    • `tt
    • `bt
    • WW
    • WZ0
    • Z0 ( ee) + jets
    • Z0 (ττ) + jets
background normalization
Background Normalization
  • All but W+jets have an absolute normalization
  • W+jets has a large normalization error
  • Take normalization from the data:

Ndata= NW+jets + Nother + Nsignal

summary of backgrounds
Summary of Backgrounds

Estimated from data

{

Use PYTHIA and normalize to known cross sections

Combination of VECBOS and PYTHIA. Norm to measured Z0ee data

Use VECBOS for shape. Large k factor uncertainty. Take normalization from fit to data. Agrees with Duke Group results

outline3
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
dijet mass distributions
Dijet Mass Distributions
  • No evidence of Z0 produced in association with a W
  • W+jets normalized to data and non-W+jets (no signal assumption)
w dijet mass distributions
W+dijet Mass Distributions
  • No evidence of W’ or other new particle production
  • W+jets normalized to the data and non-W+jets (no signal assumption)
w dijet in 3 mass regions
W+dijet in 3 Mass Regions
  • Use previous normalization and check Z0 region
  • Data outside Z0 mass region is well modeled telling us that the background estimate inside the Z0 mass region is well modeled (both norm & shape).
  • No evidence for WZ0 production.

( *Figure 1 in PRL)

outline4
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
turning the crank
Turning the Crank
  • Searching the data for X
    • Look for excess in dijet vs. W+dijet mass plane
  • Fit the data to signal, W+jets and non-W+jets
    • Fix non-W+jets background
    • Allow W+jets and signal to float
    • Binned likelihood fit in the 2-d dijet vs. W+Dijet mass plane
      • Normalization mostly comes from outside signal region
    • Same technique as Dijet Mass bump search (R. Harris)
  • No evidence for signal (as seen in previous plots and in the fit results)
  • Get 95% C.L. cross section upper limit from the fit
  • Incorporate systematic errors
example signal fits i
Example Signal Fits I

Data vs. background with no signal from “reference model” W’ with a mass of 300 GeV .

example signal fits ii
Example Signal Fits II

Data vs. expectations (back & signal) with best fit amount of signal from reference model W’ with a mass of 300 GeV .

example signal fits iii
Example: Signal Fits III

Data vs. expectations (back and signal): signal level which is excluded at the 95% C.L. (reference model, MW’= 300 GeV) .

example signal fits iv
Example: Signal Fits IV

Data vs. expectations (back & signal) with reference model; theoretical production cross section

Excluded at the 95% C.L.

systematic errors
Systematic Errors

Use same (conservative) methods as dijet mass bump search and `bb mass bump search

  • Find the no-systematic 95% C.L. upper limit
  • Vary background or signal (depending on effect) by +1σ and –1σ and re-fit
  • Recalculate new limit
  • Take absolute value of % change in limit (even if the cross section limit goes down!)
  • Take the larger % of the two variations (+1σ and –1σ) as the % smearing
  • Take all variations and add them in quadrature
  • Use this as a Gaussian smearing to the likelihood
systematic errors1
Systematic errors

Vary both signal and background separately to over-estimate the magnitude of the effect

  • Amount of non-W+jets (vary background)
  • Absolute jet energy scale (vary signal)
  • Energy resolution (vary signal)
  • Radiation (vary signal)
  • Q2 scale of W+Jets (vary background)
  • Structure functions (vary background)
  • Acceptance (add % error)
  • Luminosity (add % error)
systematic errors2
Systematic Errors
  • Absolute energy scale dominates the error
    • Shifts signal into region with lots more background
  • Checked with Pseudo-Expts
errors cont extended gauge model
Errors Cont.:Extended Gauge Model
  • Narrower width = less signal in high background region
  • Absolute energy scale again dominates the error
systematic error summary
Systematic Error Summary
  • Systematic errors for lots of effects
  • Conservative estimation methods
  • We are not pulled unreasonably by an unexpected fluctuation in the data
  • Data is well modeled
  • Set limits
outline5
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
setting limits
Setting Limits
  • We set generic 95% C.L. cross section limits on X production as a function of mass and width
    • Use W’ production as a good approximation
  • Use W’ production as a model (determines production cross sections) and set mass limits
  • Begin with an theoretical overview of W’
reference model
Reference Model
  • Simplest W’ Model
    • W’ is the same as W only heavier (same couplings to quarks and leptons)
    • No new neutrinos
    • Call this “Reference Model”
  • Consequences
    • Large production cross sections
    • Γ(W’  WZ0)  M5W’
    • Large branching fraction to WZ0
    • Large total width, Γ(W’)
    • Model becomes unphysical at approx. MW  Γ(W’) which occurs at approx. MW’  425 GeV/c2
extended gauge model
Extended Gauge Model
  • Simplest W’ model unphysical (can be no W’WZ0 vertex in SM)
  • Simplest extension is W’-W mixing as in extended gauge models (e.g. L-R symmetry)
  • Effective W’WZ vertex; same as in reference model but vertex multiplied by  , which is estimated (non-trivially) by  = C(MW / MW’)2 where C is of order 1
  • Γ(W’ WZ0)  MW’
  • Narrow width  Small Br; most previous W’ searches assume this (e.g. W’  eν )
  • Use  = C(MW / MW’)2 as general Г(W’) << MW’
  • Large production cross section
theoretical consequences
Theoretical Consequences
  • Comparison of the reference and extended gauge models
  • Drastic differences in width and branching ratios

Wide Widths

Small Br

Narrow Widths

Large Br

branching ratio for w wz 0
Branching Ratio for W’WZ0
  • Reference Model
    • W’ is the same as the SM W only heavier
    • Large width large branching ratio
  • Extended Gauge Model
    • Mixing factor between W and W’
    • Small width
    • Small branching ratio
mass dist for reference model
Mass Dist. For Reference Model
  • 1000 PYTHIA generated events for the reference model
  • Width increases as a function of mass
95 c l limits reference model
95% C.L. Limits: Reference Model
  • We exclude the reference model of W’ from 200 to 480 GeV.
  • Taken in conjunction with low mass exclusions from the W’lν , we exclude the entire model
95 c l limits ext gauge model
95% C.L. Limits: Ext. Gauge Model
  • 95% C.L. upper limits on cross section vs. W’ mass for the extended gauge model
  • No mass limits for very small factors (branching ratio is tiny)
  • Cross section limits applicable for any new particle production with narrow width XWZ0
cross section vs mixing factor
Cross Section vs. Mixing Factor

95% C.L. upper limits on cross section vs. W – W’ mixing factor

cross section vs w width
Cross Section vs. W’ Width
  • 95% C.L. upper limits on the cross section vs. W’ width
  • These limits are good for any new particle production with XWZ0; narrow or wide width

* PRL Figure 2

limits on mixing factor vs w mass
Limits on Mixing Factor vs. W’ Mass

95% C.L. exclusion region for W-W’ mixing factor vs. W’ mass

* PRL Figure 3

outline6
Outline
  • Theory and Signature
  • Overview of Analysis; Event Selection and What signal would look like; Acceptance
  • Backgrounds
  • Comparing Data, Signal and Backgrounds
  • Fitting and Systematics
  • Limits
  • Conclusions
conclusions
Conclusions
  • No evidence forXWZ0in the enjjdecay channel
    • Narrow and width width approximations
  • Most comprehensive limits on direct W’ WZ0
    • Reference model completely excluded
    • Large exclusions in an extended gauge model
  • Web page at -hepr8.physics.tamu.edu/hep/wprime/
  • Documentation in CDF Note 5610
  • PRL draft in CDF Note 5629
acceptance vs w mass
Acceptance vs. W’ Mass
  • Good Acceptance for W’
  • Reference Model
    • Large width at large mass
    • Lots of low mass events
    • Lower acceptance
pseudo experiments check
Pseudo-Experiments: Check

Re-run entire analysis on fake data generated from backgrounds only

  • Generate fake data set
  • Allow number of events to float
  • Re-estimate the effect of all systematic errors for the fake data set
  • Add errors in quadrature as for data
  • Re-estimate the limit from the fake data set
  • Repeat many times
  • Repeat for different masses and mixing factors
pseudo exp jet energy error
Pseudo-Exp: Jet Energy Error
  • The effect on the limit (in %) of the jet energy scale uncertainty for a set of pseudo-experiments with W’ mass of 200, 300, 400, 500, & 600 GeV respectively. This is for the extended gauge model with C=1.
pseudo experiments total error
Pseudo-Experiments: Total Error
  • The total effect on the limit (in %) due to all systematic uncertainties for a set of pseudo-experiments with W’ mass of 200, 300, 400, 500, & 600 GeV respectively. This is for the extended gauge model with C=1.
pseudo experiments limit
Pseudo-Experiments: Limit
  • 95% cross section upper limit from a set of pseudo-experiments with W’ mass of 200, 300, 400, 500, & 600 GeV respectively. This is for the reference model.
pseudo experiments total error1
Pseudo-Experiments: Total Error
  • The total effect on the limit (in %) due to all systematic uncertainties for a set of pseudo-experiments with W’ mass of 200, 300, 400, 500, & 600 GeV respectively. This is for the reference model.
pseudo exper jet energy scale
Pseudo-Exper: Jet Energy Scale
  • The effect on the limit (in %) of the jet energy scale uncertainty for a set of pseudo-experiments with W’ mass of 200, 300, 400, 500, & 600 GeV respectively. This is for the reference model.
pseudo experiments limit1
Pseudo-Experiments: Limit
  • 95% cross section upper limit from pseudo-experiments with W’ mass of 200, 300, 400, 500, & 600 GeV respectively. This is for the extended gauge model.
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