| 7 |
|
in the signal region, defined as SumJetPt$>$300 GeV and |
| 8 |
|
\met/$\sqrt{\rm SumJetPt}>8.5$ GeV$^{\frac{1}{2}}$. |
| 9 |
|
|
| 10 |
< |
The background prediction from the SM Monte Carlo is |
| 11 |
< |
1.3 events. |
| 10 |
> |
The background prediction from the SM Monte Carlo is 1.3 events. |
| 11 |
|
%, where the uncertainty comes from |
| 12 |
|
%the jet energy scale (30\%, see Section~\ref{sec:systematics}), |
| 13 |
|
%the luminosity (10\%), and the lepton/trigger |
| 15 |
|
%the modeling of $t\bar{t}$ in MadGraph have not been evaluated. |
| 16 |
|
%The uncertainty on $pp \to \sigma(t\bar{t})$ is also not included.}. |
| 17 |
|
The data driven background predictions from the ABCD method |
| 18 |
< |
and the $P_T(\ell\ell)$ method are $1.5 \pm 0.9({\rm stat}) \pm 0.3({\rm syst})$ |
| 19 |
< |
and $4.3 \pm 3.0({\rm stat}) \pm 1.2({\rm syst})$, respectively. |
| 18 |
> |
and the $P_T(\ell\ell)$ method are $1.3 \pm 0.8({\rm stat}) \pm 0.3({\rm syst})$ |
| 19 |
> |
and $2.1 \pm 2.1({\rm stat}) \pm 0.6({\rm syst})$, respectively. |
| 20 |
|
|
| 21 |
|
These three predictions are in good agreement with each other |
| 22 |
|
and with the observation of one event in the signal region. |
| 24 |
|
on the number of non SM events in the signal region to be 4.1. |
| 25 |
|
We have also calculated this limit using a profile likelihood method |
| 26 |
|
as implemented in the cl95cms software, and we also find 4.1. |
| 27 |
< |
These limits were calculated using a background prediction of $N_{BG}=1.7 \pm 1.1$ |
| 28 |
< |
events. The upper limit is not very sensitive to the choice of |
| 27 |
> |
These limits were calculated using a background prediction of $N_{BG} = 1.4 \pm 0.8$ |
| 28 |
> |
events, the error-weighted average of the ABCD and $P_T(\ell\ell)$ background |
| 29 |
> |
predictions. The upper limit is not very sensitive to the choice of |
| 30 |
|
$N_{BG}$ and its uncertainty. |
| 31 |
|
|
| 32 |
|
To get a feeling for the sensitivity of this search to some |
| 33 |
|
popular SUSY models, we remind the reader of the number of expected |
| 34 |
< |
LM0 and LM1 events from Table~\ref{tab:sigcont}: $6.3 \pm 1.3$ |
| 35 |
< |
events and $2.6 \pm 0.4$ |
| 36 |
< |
respectively, where the uncertainties |
| 34 |
> |
LM0 and LM1 events from Table~\ref{tab:sigcont}: $8.6 \pm 1.6$ |
| 35 |
> |
events and $3.6 \pm 0.5$ events respectively, where the uncertainties |
| 36 |
|
are from energy scale (Section~\ref{sec:systematics}), luminosity, |
| 37 |
|
and lepton efficiency. Note that these expected SUSY yields |
| 38 |
|
are computed using LO cross-sections, and are therefore underestimated. |
| 57 |
|
efficiency in top events varies from $\approx 83\%$ (muons) |
| 58 |
|
and $\approx 89\%$ (electrons) at $P_T=10$ GeV to |
| 59 |
|
$\approx 95\%$ for $P_T>60$ GeV. |
| 60 |
< |
{\bf \color{red} THE FOLLOWING QUANTITIES SHOULD BE RECALCULATED AFTER |
| 61 |
< |
WE FIX THE BUGS WITH THE MET IN LM SAMPLES} |
| 60 |
> |
{\bf \color{red} The following quantities were calculated |
| 61 |
> |
with Spring10 samples. } |
| 62 |
|
The average detector |
| 63 |
|
responses for SumJetPt and $\met/\sqrt{\rm SumJetPt}$ are |
| 64 |
|
$1.00 \pm 0.05$ and $0.94 \pm 0.05$ respectively, where |
| 74 |
|
signal region. |
| 75 |
|
% (SumJetPt $>$ 300 GeV and \met/$\sqrt{\rm SumJetPt} > 8.5$ |
| 76 |
|
% Gev$^{\frac{1}{2}}$). |
| 77 |
< |
{\bf \color{red} THE FOLLOWING QUANTITIES SHOULD BE RECALCULATED AFTER |
| 79 |
< |
WE FIX THE BUGS WITH THE MET IN LM SAMPLES} |
| 77 |
> |
{\bf \color{red} The following numbers were derived from Spring10 samples.} |
| 78 |
|
We find that the average SumJetPt response |
| 79 |
< |
in the Monte Carlo |
| 80 |
< |
is very close to one, with an RMS of order 10\% while |
| 83 |
< |
the |
| 84 |
< |
response of \met/$\sqrt{\rm SumJetPt}$ is approximately 0.94 with an |
| 79 |
> |
in the Monte Carlo is very close to one, with an RMS of order 10\% while |
| 80 |
> |
the response of \met/$\sqrt{\rm SumJetPt}$ is approximately 0.94 with an |
| 81 |
|
RMS of 14\%. |
| 82 |
|
|
| 83 |
|
%Using this information as well as the kinematical |
| 101 |
|
to the true quantity in MC. These plots are done using the LM0 |
| 102 |
|
Monte Carlo, but they are not expected to depend strongly on |
| 103 |
|
the underlying physics. |
| 104 |
< |
{\bf \color{red} UPDATE AFTER FIXING BUGS WITH LM SAMPLES. } } |
| 104 |
> |
{\bf \color{red} These plots were made with Spring10 samples. } } |
| 105 |
|
\end{center} |
| 106 |
|
\end{figure} |
| 107 |
+ |
|
| 108 |
+ |
|
| 109 |
+ |
|
| 110 |
+ |
%%% Nominal |
| 111 |
+ |
% ----------------------------------------- |
| 112 |
+ |
% observed events 1 |
| 113 |
+ |
% relative error on acceptance 0.000 |
| 114 |
+ |
% expected background 1.400 |
| 115 |
+ |
% absolute error on background 0.770 |
| 116 |
+ |
% desired confidence level 0.95 |
| 117 |
+ |
% integration upper limit 30.00 |
| 118 |
+ |
% integration step size 0.0100 |
| 119 |
+ |
% ----------------------------------------- |
| 120 |
+ |
% Are the above correct? y |
| 121 |
+ |
% 1 16.685 0.29375E-06 |
| 122 |
+ |
% |
| 123 |
+ |
% limit: less than 4.112 signal events |
| 124 |
+ |
|
| 125 |
+ |
|
| 126 |
+ |
|
| 127 |
+ |
%%% Add 20% acceptance uncertainty based on LM0 |
| 128 |
+ |
% ----------------------------------------- |
| 129 |
+ |
% observed events 1 |
| 130 |
+ |
% relative error on acceptance 0.200 |
| 131 |
+ |
% expected background 1.400 |
| 132 |
+ |
% absolute error on background 0.770 |
| 133 |
+ |
% desired confidence level 0.95 |
| 134 |
+ |
% integration upper limit 30.00 |
| 135 |
+ |
% integration step size 0.0100 |
| 136 |
+ |
% ----------------------------------------- |
| 137 |
+ |
% Are the above correct? y |
| 138 |
+ |
% 1 29.995 0.50457E-06 |
| 139 |
+ |
% |
| 140 |
+ |
% limit: less than 4.689 signal events |
