COMP/CSA06DOC/analysisdemo.tex

\section {Analysis Demonstrations}


Different physics groups prepared some analysis codes to extract
physics results by running on skimmed files at Tier-2s.

\subsection {Calibration}

\subsection {Allignment}

\subsection {Physics Analysis Exercises}

\subsubsection {Effect of tracker misalignment on track reconstruction performances}

The alignment uncertainties of the CMS Tracker detector, made of a huge amount of independent silicon sensors with an excellent position resolution, affect the performances of the track reconstruction and track parameters measurement. 
The analysis exercise performed by the team at Bari during the CSA06 had the purpose of study the effect of the CMS tracker misalignment on the performances of the track reconstruction \cite{misalignment}. Realistic estimates for the expected displacements of the tracking systems were supplied in different scenarios as specified in the following: 
 
\begin{itemize}
\item the ideal scenario with a perfect tracker geometry;
\item the short term misalignment scenario supposed to reproduce the mis-alignment conditions during the first 
data taking when the uncertainties on the position of the sub-structures of the CMS
tracker will be between $10 \, \mu$ for pixel detectors and $400 \, \mu$ for microstrip silicon detectors in 
the endcaps. Detector position and errors are read
 from the offline database at CERN by caching the needed information locally via frontier/squid
software \cite{frontier}.

\item the long term scenario when the alignment uncertainties are supposed to be a factor 10 smaller because of the
improvement obtained by using aligmnent algorithms with a high statistics of tracks.
 
\item the CSA06 aligned scenario by using the tracker module position and errors as obtained by the output of the
 alignment procedure that was run at CERN Tier-0 to verify the efficiency of the alignment procedure on the track
reconstruction. The refit of tracks is performed also in this case.
 
\end{itemize}

Track reconstruction is based on the Kalman Filter formalism \cite{Kalman} for trajectory building, cleaning and 
smoothing steps and uses hits from pixel detector as seeds to provide initial trajectory candidates. 
Because of the misalignment the analysis requires to refit tracks with a misaligned tracker geometry.
Global efficiency of track recostruction and track parameter resolutions for muons were
compared in all the cases. The association between simulated track and reconstruted tracks is performed
by comparing the corresponding track parameters at the closest approach point and choosing the pair which gives 
the minimum $\chi^2$ from the best fit procedure.

Events from CSA06 $Z\rightarrow \mu \mu $ sample were firstly skimmed by selecting events with 
 Hep MC muons from Z decay with pseudorapidity, $\eta$, in the tracker acceptance, $|\eta| < 2.55$, 
with transverse momentum larger than $5 \, \mathrm{GeV}/c^2$ and di-muons invariant mass in the following 
range aroung the Z peak: $50 < m_{\mu\mu}(\mathrm{GeV}/c^2) < 130$; the efficiency of the previous selection is 
between 50 and 60 \% mainly due to the cut on the acceptance, for a final statistics of 1 million events. 
The output files in RECOSIM format were needed for the subsequent analysis.


Jobs executing the misalignment analysis were submitted at Bari with CRAB\_1\_4\_0 in the LCG infrastructure.
A total of about 2.5 thousands jobs (45 at most in parallel) ran with a grid efficiency of 90 \% and an 
application efficiency of 80\%, by accessing detector position and errors from the offline database via 
frontier.


Some results of the misalignment analysis were summarized below. The global efficiency of track reconstruction of muons coming from
Z decay is shown in Fig.~\ref{eff} as a function of the pseudorapidity, $\eta$, in the tracker acceptance. 
In the case of a perfect geometry the global track reconstruction was not fully efficient over all the $\eta$ 
range because of the track associator algorithm itself which discards tracks with  $\chi^2$ of the fit less 
than 25. The effect of misalignment is relevant in the short term scenario and causes a partial inefficiency of the
track reconstruction; that can be recovered if the intrinsic position resolution of the tracker
 detector is combined with the alignment uncertainties to make larger the error on the position of the
reconstructed hit (called alignment position error, APE) so improving the track fit at the
expence of a larger rate of fake tracks.
                                    

The tranverse momentum resolution as a function of the transverse momentum is reported in Fig.~\ref{respt};
the degradation of the tranverse momentum resolution at large $p_{T}$ because of the misalignment is in a factor
 between 2 and 3 with respect to the perfect geometry case. At low transverse momentum (less than few $\mathrm{GeV}/c$ 
the multiple scattering is the 
most important contribution to the resolution so the effect of misalignment is overwhelmed at all.
                                                                                    
The residual of Z mass obtained as the invariant mass of muons coming from Z decay in the case of perfect
tracker geometry and in short-term and long term misalignment scenarios is shown in Fig.~\ref{mz}; the $\sigma$ of 
the Gaussian fit of the residual ditribution can be quoted as the Z mass resolution which is degradated of a factor 2 
because of the tracker misalignment in the short term scenario.
                                                                         
\begin{2figures}{hbt}
  \resizebox{\linewidth}{!}{\includegraphics{figs/Eff_eta.eps}} &
  \resizebox{\linewidth}{!}{\includegraphics{figs/SigmapT_pT.eps}} \\
  \caption{Global track reconstrution efficiency vs pseudorapidity for muons coming from Z decay in the case of perfect 
tracker geometry and in short-term and long term misalignment scenarios when the APE is not used.}
  \label{eff} &
  \caption{$P_{T}$ resolution vs $p_{T}$ in the case of perfect
tracker geometry and in short-term and long term misalignment scenarios.}
  \label{respt} \\
\end{2figures}


\begin{figure}[htb]
  \begin{center}
  \resizebox{0.7\linewidth}{!}{\includegraphics{figs/Residual_mZ_mu.eps}} 
  \end{center}
  \caption{Residual of Z mass obtained as the invariant mass of muons coming from Z decay in the case of perfect
tracker geometry and in short-term and long term misalignment scenarios.}
  \label{mz} 
\end{figure}

         
Revision:	1.4
Committed:	Wed Nov 29 12:43:47 2006 UTC (18 years, 5 months ago) by ndefilip
Content type:	application/x-tex
Branch:	MAIN
Changes since 1.3:	+56 -24 lines
Log Message:	Updated text for the misalignment analysis
#	User	Rev	Content
1	fisk	1.1	\section {Analysis Demonstrations}
2
3	ndefilip	1.3
4			Different physics groups prepared some analysis codes to extract
5			physics results by running on skimmed files at Tier-2s.
6
7	fisk	1.1	\subsection {Calibration}
8
9			\subsection {Allignment}
10
11			\subsection {Physics Analysis Exercises}
12
13	ndefilip	1.2	\subsubsection {Effect of tracker misalignment on track reconstruction performances}
14
15	ndefilip	1.3	The alignment uncertainties of the CMS Tracker detector, made of a huge amount of independent silicon sensors with an excellent position resolution, affect the performances of the track reconstruction and track parameters measurement.
16			The analysis exercise performed by the team at Bari during the CSA06 had the purpose of study the effect of the CMS tracker misalignment on the performances of the track reconstruction \cite{misalignment}. Realistic estimates for the expected displacements of the tracking systems were supplied in different scenarios as specified in the following:
17
18			\begin{itemize}
19			\item the ideal scenario with a perfect tracker geometry;
20			\item the short term misalignment scenario supposed to reproduce the mis-alignment conditions during the first
21			data taking when the uncertainties on the position of the sub-structures of the CMS
22			tracker will be between $10 \, \mu$ for pixel detectors and $400 \, \mu$ for microstrip silicon detectors in
23			the endcaps. Detector position and errors are read
24			from the offline database at CERN by caching the needed information locally via frontier/squid
25			software \cite{frontier}.
26
27			\item the long term scenario when the alignment uncertainties are supposed to be a factor 10 smaller because of the
28			improvement obtained by using aligmnent algorithms with a high statistics of tracks.
29
30			\item the CSA06 aligned scenario by using the tracker module position and errors as obtained by the output of the
31			alignment procedure that was run at CERN Tier-0 to verify the efficiency of the alignment procedure on the track
32			reconstruction. The refit of tracks is performed also in this case.
33
34			\end{itemize}
35
36	ndefilip	1.4	Track reconstruction is based on the Kalman Filter formalism \cite{Kalman} for trajectory building, cleaning and
37			smoothing steps and uses hits from pixel detector as seeds to provide initial trajectory candidates.
38			Because of the misalignment the analysis requires to refit tracks with a misaligned tracker geometry.
39			Global efficiency of track recostruction and track parameter resolutions for muons were
40			compared in all the cases. The association between simulated track and reconstruted tracks is performed
41			by comparing the corresponding track parameters at the closest approach point and choosing the pair which gives
42			the minimum $\chi^2$ from the best fit procedure.
43	ndefilip	1.3
44	ndefilip	1.4	Events from CSA06 $Z\rightarrow \mu \mu $ sample were firstly skimmed by selecting events with
45			Hep MC muons from Z decay with pseudorapidity, $\eta$, in the tracker acceptance, $\|\eta\| < 2.55$,
46			with transverse momentum larger than $5 \, \mathrm{GeV}/c^2$ and di-muons invariant mass in the following
47			range aroung the Z peak: $50 < m_{\mu\mu}(\mathrm{GeV}/c^2) < 130$; the efficiency of the previous selection is
48			between 50 and 60 \% mainly due to the cut on the acceptance, for a final statistics of 1 million events.
49			The output files in RECOSIM format were needed for the subsequent analysis.
50	ndefilip	1.3
51
52	ndefilip	1.4	Jobs executing the misalignment analysis were submitted at Bari with CRAB\_1\_4\_0 in the LCG infrastructure.
53			A total of about 2.5 thousands jobs (45 at most in parallel) ran with a grid efficiency of 90 \% and an
54			application efficiency of 80\%, by accessing detector position and errors from the offline database via
55			frontier.
56	ndefilip	1.3
57	ndefilip	1.4
58			Some results of the misalignment analysis were summarized below. The global efficiency of track reconstruction of muons coming from
59			Z decay is shown in Fig.~\ref{eff} as a function of the pseudorapidity, $\eta$, in the tracker acceptance.
60			In the case of a perfect geometry the global track reconstruction was not fully efficient over all the $\eta$
61			range because of the track associator algorithm itself which discards tracks with $\chi^2$ of the fit less
62			than 25. The effect of misalignment is relevant in the short term scenario and causes a partial inefficiency of the
63			track reconstruction; that can be recovered if the intrinsic position resolution of the tracker
64			detector is combined with the alignment uncertainties to make larger the error on the position of the
65			reconstructed hit (called alignment position error, APE) so improving the track fit at the
66			expence of a larger rate of fake tracks.
67
68
69			The tranverse momentum resolution as a function of the transverse momentum is reported in Fig.~\ref{respt};
70			the degradation of the tranverse momentum resolution at large $p_{T}$ because of the misalignment is in a factor
71			between 2 and 3 with respect to the perfect geometry case. At low transverse momentum (less than few $\mathrm{GeV}/c$
72			the multiple scattering is the
73			most important contribution to the resolution so the effect of misalignment is overwhelmed at all.
74
75			The residual of Z mass obtained as the invariant mass of muons coming from Z decay in the case of perfect
76			tracker geometry and in short-term and long term misalignment scenarios is shown in Fig.~\ref{mz}; the $\sigma$ of
77			the Gaussian fit of the residual ditribution can be quoted as the Z mass resolution which is degradated of a factor 2
78			because of the tracker misalignment in the short term scenario.
79
80			\begin{2figures}{hbt}
81	ndefilip	1.3	\resizebox{\linewidth}{!}{\includegraphics{figs/Eff_eta.eps}} &
82	ndefilip	1.4	\resizebox{\linewidth}{!}{\includegraphics{figs/SigmapT_pT.eps}} \\
83	ndefilip	1.3	\caption{Global track reconstrution efficiency vs pseudorapidity for muons coming from Z decay in the case of perfect
84			tracker geometry and in short-term and long term misalignment scenarios when the APE is not used.}
85			\label{eff} &
86	ndefilip	1.4	\caption{$P_{T}$ resolution vs $p_{T}$ in the case of perfect
87			tracker geometry and in short-term and long term misalignment scenarios.}
88			\label{respt} \\
89			\end{2figures}
90
91
92			\begin{figure}[htb]
93			\begin{center}
94			\resizebox{0.7\linewidth}{!}{\includegraphics{figs/Residual_mZ_mu.eps}}
95			\end{center}
96	ndefilip	1.3	\caption{Residual of Z mass obtained as the invariant mass of muons coming from Z decay in the case of perfect
97			tracker geometry and in short-term and long term misalignment scenarios.}
98	ndefilip	1.4	\label{mz}
99			\end{figure}
100
101