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\section{Introduction} |
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In this note we describe a search for new physics in the 2010 |
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In this note we describe a search for new physics in the 2011 |
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opposite sign isolated dilepton sample ($ee$, $e\mu$, and $\mu\mu$). |
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The main sources of high \pt isolated dileptons at CMS are Drell Yan and $t\bar{t}$. |
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The main sources of high \pt isolated dileptons at CMS are Drell Yan and \ttbar. |
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Here we concentrate on dileptons with invariant mass consistent |
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with $Z \to ee$ and $Z \to \mu\mu$. A separate search for new physics in the non-\Z |
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sample is described in~\cite{ref:GenericOS}. |
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We search for new physics in the final state of \Z plus two or more jets plus missing transverse energy (MET). We reconstruct the \Z boson |
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in its decay to $e^+e^-$ or $\mu^+\mu^-$. Our search regions are defined as MET $\ge$ 60~GeV (loose signal region) and MET $\ge$ 120~GeV (tight signal region), and two or more jets. We use data driven techniques to predict the |
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standard model background in this search region. |
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Contributions from Drell-Yan production combined with detector mis-measurements that produce fake MET are modeled via MET templates based on photon plus jets events. |
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We search for new physics in the final state of \Z plus two or more jets plus missing |
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transverse energy (MET). We reconstruct the \Z boson |
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in its decay to $e^+e^-$ or $\mu^+\mu^-$. Our search regions are defined as |
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MET $\ge$ \signalmetl~GeV (loose signal region) and MET $\ge$ \signalmett~GeV |
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(tight signal region), and two or more jets. We use data driven techniques to predict the |
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standard model background in these search regions. |
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Contributions from Drell-Yan production combined with detector mis-measurements that |
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produce fake MET are modeled via MET templates based on photon plus jets or QCD events. |
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Top pair production backgrounds, as well as other backgrounds for which the lepton |
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flavors are uncorrelated such as $VV$ and DY$\rightarrow\tau\tau$, are modeled via $e^\pm\mu^\mp$ subtraction. |
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flavors are uncorrelated such as WW and DY$\rightarrow\tau\tau$, are |
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modeled via $e^\pm\mu^\mp$ subtraction. |
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As leptonically decaying \Z bosons is a signature that has very little background, they provide a clean final state in which to search for new physics. |
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Because new physics is expected to be connected to the Standard Model Electroweak sector, it is likely that new particles will couple to W and Z bosons. |
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For example, in mSUGRA, low $M_{1/2}$ can lead to a significant branching fraction for $\chi_2^0 \rightarrow Z \chi_1^0$. |
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As leptonically decaying \Z bosons are a signature that has very little background, |
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they provide a clean final state in which to search for new physics. |
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Because new physics is expected to be connected to the Standard Model Electroweak sector, |
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it is likely that new particles will couple to W and Z bosons. |
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For example, in mSUGRA, low $M_{1/2}$ can lead to a significant branching fraction |
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for $\chi_2^0 \rightarrow Z \chi_1^0$. |
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In addition, we are motivated by the existence of dark matter to search for new physics with MET. |
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Enhanced MET is a feature of many new physics scenarios, and R-parity conserving SUSY again provides a popular example. The main challenge of this search is therefore to |
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Enhanced MET is a feature of many new physics scenarios, and R-parity conserving SUSY |
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again provides a popular example. The main challenge of this search is therefore to |
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understand the tail of the fake MET distribution in \Z plus jets events. |
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The basic idea of the MET template method~\cite{ref:templates1}\cite{ref:templates2} is to measure the MET distribution in a control sample which has no true MET and a similar topology to the signal events. |
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In our case, we choose a photon sample with two or more jets as the control sample. |
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Both the control sample and signal sample consist of a well measured object (either a photon or a leptonically decaying $Z$), which recoils against a system of hadronic jets. |
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In both cases, the instrumental MET is dominated by mismeasurements of the hadronic system. |
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The basic idea of the MET template method~\cite{ref:templates1}\cite{ref:templates2} is |
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to measure the MET distribution in data in a control sample which has no true MET |
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and a similar topology to the signal events. |
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%Start the qcd vs photon discussion |
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Templates can be derived from either a QCD sample (as was done in the original implementation) |
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or a photon plus jets sample. |
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%In our case, we choose a photon sample with two or more jets as the control sample. |
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%Both the control sample and signal sample consist of a well measured object (either a |
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%photon or a leptonically decaying $Z$), which recoils against a system of hadronic jets. |
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In both cases, the instrumental MET is dominated by mismeasurements of the hadronic system, |
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and can be classified by the number of jets in the event and the scalar sum of their transverse |
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momenta. |
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The prediction is made such that the jet system in the control sample is similar to that of the |
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signal sample. |
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By using two independent control samples--QCD and photon plus jets--we are able to illustrate |
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the robustness of the MET templates method and to cross check the data driven background |
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prediction. |
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This note is organized as follows. |
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In Sections~\ref{sec:datasets} and ~\ref{sec:trigSel} we start by describing |
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the triggers and datasets used, followed by the detailed object definitions (electrons, muons, photons, |
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jets, MET) and event selection which is described in Section~\ref{sec:eventSelection}. |
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We define a preselection and compare data vs. MC yields passing this preselection in Section~\ref{sec:yields}. |
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We then define the signal regions and show the number of observed events and MC expected yields in Section~\ref{sec:sigregion}. |
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Section~\ref{sec:templates} then introduces the MET template method and discusses its derivation |
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in some detail, followed by a demonstration in Section~\ref{sec:mc} that the method works in Monte Carlo. |
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Section~\ref{sec:topbkg} introduces the top background estimate based on opposite flavor subtraction, and contributions from other backgrounds are discussed in Section~\ref{sec:othBG}. |
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In sections \ref{sec:datasets} and \ref{sec:trigSel} we descibe |
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the datasets and triggers used, followed by the detailed object definitions (electrons, muons, photons, |
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jets, MET) and event selections in sections \ref{sec:evtsel} through \ref{sec:jetsel}. |
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We define a preselection and compare data vs. MC yields passing this preselection in |
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Section~\ref{sec:yields}. |
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We then define the signal regions and show the number of observed events and MC expected |
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yields in Section~\ref{sec:sigregion}. |
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Section~\ref{sec:templates} introduces the MET template method and discusses its derivation |
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in some detail and is followed by a demonstration in Section~\ref{sec:mc} |
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that the method works in Monte Carlo. |
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Section~\ref{sec:topbkg} introduces the top background estimate based on opposite flavor subtraction, |
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and contributions from other backgrounds are discussed in Section~\ref{sec:othBG}. |
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Section~\ref{sec:results} shows the results for applying these methods in data. |
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We analyze the systematic uncertainties in the background prediction in Section~\ref{sec:systematics} |
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and proceed to calculate an upper limit on the non SM contributions to our signal regions in Section~\ref{sec:upperlimit}. In Section~\ref{sec:models} we calculate upper limits on the quantity $\sigma \times BF \times A$, assuming |
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efficiencies and uncertainties from sample benchmark SUSY processes. We conclude in Section~\ref{sec:conclusion}. |
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and proceed to calculate an upper limit on the non-SM contributions to our signal regions |
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in Section~\ref{sec:upperlimit}. |
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Finally, in Section~\ref{sec:models} we calculate upper limits on the quantity |
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$\sigma \times BF \times A$, |
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assuming efficiencies and uncertainties from sample benchmark SUSY processes. |
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