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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


Feynman diagram

Feynman Diagram

X

0


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


Backups

Backups


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.


Systematic backup

Systematic Backup


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