AcerDET.tex
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\begin{titlepage}

\begin{flushright}
%%{\rm  ATLAS Physics Communication}\\
%%{\rm  ATL-COM-PHYS-2001-032}\\
{\rm   ICSJU-004/2002}\\
{\rm   TPJU-14/2002}\\
{\rm   30 July  2002}
\end{flushright}


\begin{center}
\vspace{2.0cm} 
  {\bf \LARGE AcerDET\footnote{Package is available for the web page 
  {\tt http://erichter.home.cern.ch/erichter/AcerDET.html}}
  : a particle level } \\
\vspace{0.25cm} 
  {\bf \LARGE fast simulation and reconstruction package} \\
\vspace{0.25cm} 
  {\bf \LARGE for  phenomenological studies on high $p_T$ physics at LHC.}\\
\end{center}
\vspace{1.0cm} 
 

\begin{center}
  {\bf El\. zbieta Richter-W\c{a}s\footnote{ Supported in part by
  Polish Government grant KBN 2 P03B 001 22.}}\\ 
  {\em Institute of Computer Science, Jagellonian University;}\\
  {\em 30-072 Krakow, ul. Nawojki 11, Poland.}\\
  {\em Institute of Nuclear Physics}\\
  {\em 31-342 Krakow, ul. Radzikowskiego 152, Poland.}\\

\end{center}

\vspace{1.0cm}
\begin{center}
{\bf Abstract}
\end{center}

This paper documents  package for the particle level fast simulation.
The package is designed to complete the {\tt AcerMC} generator
framework with the easy-to-use simulation and reconstruction algorithms.
The package provides, starting
from list of particles in the event, the list of reconstructed
jets, isolated electrons, muons and photons and
reconstructed missing transverse energy.
The {\tt AcerDET} represents a simplified version of the package called
{\tt ATLFAST}, used since several years within ATLAS Collaboration.
In the {\tt AcerDET}  version some functionalities of the former one 
have been removed, only the most crucial detector effects are
implemented and the  parametrisations are largely simplified.
Therefore it is not representing in details neither ATLAS nor
CMS detectors.
Nevertheless, we believe that the package can be well adequate for some
feasibility studies of the high $p_T$ physics at LHC and in future,
after some adjustments, of other detectors as well.


%\vspace{1.0cm}
%PACS number(s): 


\newpage
\boldmath
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
{PROGRAM SUMMARY}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath
\\
{\it Title of the program:} {\bf AcerDET version 1.0}\\
{\it Operating system:} Linux\\
{\it Programming language:} FORTRAN 77 with popular extensions.\\
{\it External libraries:} CERNLIB.\\
{\it Size of the compressed distribution directory:} about 25 kB.\\ 
{\it Key words:} Fast simulation, Physics at LHC.\\ 
{\it Nature of physical problem:} A particle level fast simulation and
reconstruction package. The package provides, starting
from the list of particles in the event, list of reconstructed
jets, isolated electrons, muons and photons and
reconstructed missing transverse energy.
The package is aimed to complete  the {\tt AcerMC}  framework
[1] with the easy-to-use simulation and reconstruction algorithms.
The interface subroutines to {\tt PYTHIA 6.2} [2] or {\tt HERWIG 6.3}
[3] are provided. Distribution version includes also example of the
main program for execution with  {\tt PYTHIA 6.2} generator.
 Implemented set of parametrisations is 
not representing in details ATLAS or
CMS detectors, some of them are simple and can be considered
rather as place-holders for future adaptation of any detector. 
Nevertheless, we believe that the package will be well adequate for some
feasibility studies on the high $p_T$ physics at LHC.

\vspace{0.5cm}  
  
[1]. B. Kersevan and E. Richter-Was, {\it The Monte Carlo event generator 
AcerMC version 1.0 with interfaces to PYTHIA 6.2 and HERWIG 6.3},
hep-ph/0201302, Comp. Phys. Commun. in print., 
{\tt http://kersevan.home.cern.ch/borut}

[2]. T. Sjostrand et al., {\it High energy physics generation with PYTHIA~6.2},
eprint hep-ph/0108264, LU-TP  01-21, August 2001.

[3]. G. Marchesini et al., Comp. Phys. Commun. {\bf 67} (1992) 465,
G. Corcella et al., JHEP {\bf 0101} (2001) 010.


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%\boldmath
%\tableofcontents
%\unboldmath


\boldmath
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Introduction}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

The potential of the LHC detectors for physics at high  $p_T$ will be
very rich, see \cite{ATL-PHYS-TDR} for comprehensive review. 
Prospects for observability of eg. the
Higgs boson(s), Supersymmetry particles, Exotic particles, New Vector
Bosons is very impressive. All these thanks to the high sensitivity 
of the detectors
in terms of acceptance and identifying efficiencies to variety of 
signatures: photons, electrons, muons, multi-b-jets, tau-jets, missing
transverse energy.

Those high sensitivities will allow to study very
exclusive signatures and so the discovery potential will be 
limited in some cases by the rare background processes.
It is becoming evident  that the multi-jet and multi-b-jet
production in association with known vector bosons, W and/or Z, or with
top-quark pair will be the serious background to the several
observables as well. 
 As so, should be understood  beyond the leading order.
One will likely need to understand well effects coming from the 
finite width or angular spin correlations (eg. from the intermediate
resonances decays). Moreover one should be able
to understand limitations and complementarity of the matrix
element and parton shower predictions for the diversity of signatures.

The package for particle-level simulation and reconstruction 
is  one of the intermediate steps between 
simple parton-level analysis and very sophisticated and CPU consuming
full detector simulation. The package provides, starting
from  list of particles in the event, list of reconstructed
jets, isolated electrons, muons and photons and
reconstructed missing transverse energy.
It can serve for several phenomenological 
feasibility studies on the prospects for observability of a given
signature. One of the example of such application reported in
\cite{hep-ph-0207014} are studies on prospects for observability of
the invisibly decaying Higgs boson in the $t \bar t H$ production process.
Our package can be also useful for the dedicated comparisons between
matrix element and parton shower predictions. In that case one can
compare experimental signatures (reconstructed jets,
leptons, photons) to quantify size of the discrepancies between
different predictions in straightforward way. 
Such comparison was recently reported in \cite{hep-ph-0203148} for 
 $Wb \bar b$, $Z b \bar b$ and $t \bar t$ processes.

The package simulates some key features of the LHC detectors like
ATLAS and CMS. It is based on the calorimetric energy deposition for
 jets reconstruction
and tracks reconstruction for electrons and muons. It takes into
account very high granularity of the electromagnetic calorimetry
for the photon reconstruction. The missing transverse energy is
calculated for the total energy balance of the reconstructed objects.
The capability for the identification of b-jets and tau-jets is also
explored. Implemented set of parametrisations is 
not representing in details performance of neither ATLAS nor
CMS detectors. 
Nevertheless, we believe that the package will be adequate for some
feasibility studies on the high $p_T$ physics at LHC and offer option
also for LC. 


The paper is organised as follows. In Section 2 we discuss algorithms
used for objects reconstruction and show benchmarking
distributions. Section 3 gives an outlook. Some comparison
numbers with the performance of the ATLAS detector are collected in
Appendix A.  In the Appendixes B-F we give more technical details
concerning input parameters and output structure.
In  Appendix G we show control output.  
 
\newpage
\boldmath
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Simulation and reconstruction}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Fully or partially generated event i.e. event generated including 
or not QED/QCD initial and final state radiation, fragmentation,
hadronisation and decays of unstable particles can by analysed by 
this package. The list of the partons/particles of the generated event should
be rewritten (including information on their history) from the event record, filled
by the event generator, to the {\tt COMMON /ACMCEVENT/}. 
Stored there information is used by the {\tt AcerDET} algorithms for
event simulation and reconstruction.\\
Events simulation is limited to the following steps:
\begin{itemize}
\item
Deposition of the particles energies in the calorimetric cells.
\item
Smearing of the energy of electrons, photons, muons with the parametrised
resolutions.
\item
Smearing of the energy of hadronic clusters and not-clustered cells
with the parametrised resolution.
\end{itemize}
Events reconstruction is limited to the following steps:
\begin{itemize}
\item
Reconstruction of the calorimetric clusters.
\item
Verification of the isolation criteria for electrons/photons/muons.
\item
Rejection of clusters associated with electrons and photons.
\item
Acceptation of remaining clusters as hadronic jets and identification
 (labeling)  of those associated with b-quarks, c-quarks, tau-leptons.
\item 
Jets energy calibration.
\end{itemize}
There is no clear separation between the {\it simulation} and {\it
reconstruction} parts in the structure of algorithms. Some larger
blocks ({\tt subroutines}) might realise both tasks.

As a final result provided are four-momenta of reconstructed electrons,
photons, muons, labeled and calibrated jets and calculated is
total missing transverse energy.


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Calorimetric clusters}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

 The transverse energy of all undecayed particles stored in 
 {\tt COMMON /ACMCEVENT/}, except for muons, neutrinos and other 
 {\it invisible} particles\footnote{User may want to make any particle
 invisible to the detector. For this one should redefine its code in the 
 {\tt COMMON /ACMCEVENT/} to that specified for the invisible particles in {\tt
 acerdet.dat} file.} eg. the lightest SUSY particle,
 are summed up in the map of
 calorimetric cells with a given granularity in $(\eta \times \phi)$
 coordinates (default: $0.1 \times 0.1$ for $|\eta| < 3.2$ and 
 $0.2 \times 0.2$ for  $|\eta| > 3.2$, with the calorimetric coverage
 up to  $|\eta| = 5.0$). As an effect of the solenoidal magnetic field
 in  the inner part of the detector we assume that the $\phi$ position of charged
 particles with transverse momenta above  the threshold 
 (default: $p_T > 0.5$~GeV) will be shifted as parametrised in function
 {\tt  FLDPHI}. The contribution from all charged particles with
 transverse momenta  below that threshold is neglected.

 All calorimetric cells with the transverse energy greater than a
 given threshold (default: $E_T > 1.5$ GeV) are taken as possible
 initiators of clusters. They are scanned in order of decreasing $E_T$
 to verify whether the total $E_T$ summed over all cells in a cone
 $\Delta R = \sqrt{ \Delta^2 \eta + \Delta^2 \phi}$ exceeds the
 minimum required threshold for the reconstructed cluster (default
 $E_T > 5$ GeV). Cells with deposited transverse energy below the
 threshold (default: $E_T=0$) are not accounted for. As a coordinates
 $(\eta^{clu} \times \phi^{clu})$ of the reconstructed cluster
 taken are the coordinates of the bary-center of the cone weighted
 by the cells $E_T$ for all cells inside the cone around the
 initiator cell.

 All reconstructed clusters are stored in the  {\tt COMMON /CLUSTE/}.
Fig.~\ref{FS2.1} shows the  $\Delta \eta$ (left) and  $\Delta \phi$ (right) distribution
between the reconstructed bary-center of particles falling within the
geometrical cluster cone  and the reconstructed cluster position.

\begin{Fighere}
\begin{center}
     \epsfig{file=plot-etaclu.eps,width=6.0cm}
     \epsfig{file=plot-etaphi.eps,width=6.0cm}\\
\end{center}
\caption{\em
The $\Delta \eta$ (left) and  $\Delta \phi$ (right) distribution
between the reconstructed bary-center of particles falling within the
cluster cone  and the reconstructed cluster position. Shown are results 
for generated  $WH, H \to u \bar u$ process with $m_H~=~100$~GeV.
\label{FS2.1}} 
\end{Fighere}


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Isolated muons}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Algorithm reconstructing isolated muons uses information
of the generated muons, reconstructed calorimetric clusters and
the cells map.

Isolated muon candidates are searched for in the 
{\tt COMMON /ACMCEVENT/}. The inverse muon four-momentum is
smeared according to the Gaussian resolution parametrised with
function {\tt RESMUO} (default: $\sigma = 0.05\% \cdot p_{T}$).
 The muon direction remains unsmeared.

For all muons which pass selection criteria in $p_T$ and $\eta$
(default: $p_T >$ 6 GeV and $|\eta| < 2.5$ GeV), isolation criteria,
in terms of the distance from calorimetric  clusters and of
maximum transverse energy 
deposition in cells in a cone around the muon, are then applied
(defaults: separation by $\Delta R > 0.4$ from other clusters and
$\sum E_T < 10$ GeV in a cone  $\Delta R = 0.2$ around the muon).
All muons passing the isolation criteria are stored in 
{\tt COMMON /ISOMUO/} and those not passing are stored in
 {\tt COMMON /NIOMUO/}. 
 
As a control physics process  the
 $gg \to H \to ZZ^* \to 4 \mu $ production with the 
Higgs boson mass of 130 GeV is used. The default
isolation selection has 97.8\% efficiency for muons passing kinematical selection  with 
$p_T^{\mu_1, \mu_2} > 20$~GeV and $p_T^{\mu_3, \mu_4} > 7$~GeV. 
As the predicted intrinsic width
of the Higgs boson of this mass is very small, the resolution is
completely dominated by the resolution assumed for the 
single muon reconstruction. Fig.~\ref{FS2.4} (left) shows the
reconstructed distribution of the 4-muon system.
The assumed single muon transverse momenta resolution
 of $\sigma = 0.05\% \cdot p_T$
leads to the $\sigma_m = 1.57$~GeV resolution for the invariant mass
of the four-muon system originating from the $ H \to ZZ^* \to 4 \mu $
decay. Please note that the photon bremsstrahlung
was omitted in the event generation.


The second  control physics process
is the di-jet production. Here we
don't expect isolated muons to be present, just muons from the
semileptonic cascade within the jets. Nevertheless
some of those muons will also pass isolation criteria. 
Fig.~\ref{FS2.4} (right) shows the $p_T$ distribution of the true
(dashed) and classified as isolated (solid) muons passing the
default selection criteria.  


\begin{Fighere}
\begin{center}
     \epsfig{file=plot-h4mu.eps,width=6.0cm}
     \epsfig{file=plot-dijet-muo.eps,width=6.0cm}\\
\end{center}
\caption{\em
Left: The reconstructed mass, $m_{4\mu}$, for $H \to ZZ^* \to 4\mu$ 
events with $m_H=130$~GeV; Right: the transverse momenta spectrum of 
true (solid) and reconstructed isolated (dashed) muons in the di-jet
sample  generated with $p_T^{hard} > 17$~GeV.  
\label{FS2.4}} 
\end{Fighere}


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Isolated electrons}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Algorithm reconstructing isolated electrons uses information
of the generated electrons, reconstructed calorimetric clusters and
the cells map.

Isolated electron candidates are searched for in the 
{\tt COMMON /ACMCEVENT/}. The electron four-momentum is
smeared according to the Gaussian resolution parametrised with
function {\tt RESELE} (default: $\sigma = 12\%/\sqrt{E}$).
 The electron direction remains unsmeared.

For all electrons which pass selection criteria in $p_T$ and $\eta$
(default: $p_T >$ 5 GeV and $|\eta| < 2.5$ GeV), the associated 
reconstructed  calorimeter cluster is identified (default: $\Delta
R_{e, cluster} < 0.1$). Electron isolation criteria, in terms of
the distance from other clusters and of maximum transverse energy 
deposition in cells in a cone around the electron, are then applied
(defaults: separation by $\Delta R > 0.4$ from other clusters and
$\sum E_T < 10$ GeV in a cone  $\Delta R = 0.2$ around the electron).
All electrons passing the isolation criteria are stored in 
{\tt COMMON /ISOELE/} and the clusters associated with them are
removed from the {\tt COMMON /CLUSTE/}. 

As a control physics process  the
 $gg \to H \to ZZ^* \to 4e $ production with the 
Higgs boson mass of 130 GeV is used. The default
isolation selection has 95.2\% efficiency for electrons passing
kinematical selection  with 
$p_T^{e_1, e_2} > 20$~GeV and $p_T^{e_3, e_4} > 7$~GeV.
As the predicted intrinsic width
of the Higgs boson of this mass is very small, the resolution is
completely dominated by the resolution assumed for the 
single electron reconstruction. Fig.~\ref{FS2.3} (left) shows the
reconstructed distribution of the 4-electron system.
The assumed single electron energy resolution of $\sigma = 12\%/\sqrt{E}$
leads to the $\sigma_m = 1.26$~GeV resolution for the reconstructed invariant mass
of the four-electron system originating from the $ H \to ZZ^* \to 4e $
decay. Please note that the photon bremsstrahlung
was omitted in the events generation.

The second control physics process 
is the di-jet production. Here we
don't expect isolated electrons to be present, just electrons from the
semileptonic cascade or Dalitz decays within the jets. Nevertheless
some of these electrons will also pass isolation criteria. 
Fig.~\ref{FS2.3} (right) shows the $p_T$ distribution of the true
(dashed) and classified as isolated (solid) electrons passing the
default selection criteria.  


\begin{Fighere}
\begin{center}
     \epsfig{file=plot-h4e.eps,width=6.0cm}
     \epsfig{file=plot-dijet-ele.eps,width=6.0cm}\\
\end{center}
\caption{\em
Left: The reconstructed mass, $m_{4e}$, for $H \to ZZ^* \to 4e$ 
events with $m_H=130$~GeV; Right: the transverse momenta spectrum of 
true (solid) and reconstructed isolated (dashed) electrons in the di-jet
sample  generated with $p_T^{hard} > 17$~GeV.  
\label{FS2.3}} 
\end{Fighere}


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Isolated photons}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Algorithm reconstructing isolated photons uses information
of the generated photons, reconstructed calorimetric clusters and
the cells map.
 
Isolated photon candidates are searched for in the 
{\tt COMMON /ACMCEVENT/}. The photon four-momentum is
smeared according to the Gaussian resolution parametrised with
function {\tt RESPHO} (default: $\sigma = 10\%/\sqrt{E}$).
The photon direction remains unsmeared.

For all photons which pass selection criteria in $p_T$ and $\eta$
(default: $p_T >$ 5 GeV and $|\eta| < 2.5$ GeV), the associated 
reconstructed  calorimeter cluster is identified (default: $\Delta
R_{\gamma, cluster} < 0.1$). Photon isolation criteria, in terms of
the distance from other clusters and of maximum transverse energy 
deposition in cells in a cone around the photon, are then applied
(defaults: separation by $\Delta R > 0.4$ from other clusters and
$\sum E_T < 10$ GeV in a cone  $\Delta R = 0.2$ around the photon).
All photons passing the isolation criteria are stored in 
{\tt COMMON /ISOPHO/} and the clusters associated with them are
removed from the {\tt COMMON /CLUSTE/}. 

As a control physics process  the  Standard Model
$gg \to H \to \gamma \gamma$ production with the 
Higgs boson mass of 100 GeV is used. The 
isolation selection has 98.0\% efficiency for photons passing
the  kinematical selection of
 $p_T^{\gamma_1} > 40$ GeV and $p_T^{\gamma_2} > 25$ GeV.
 As the predicted intrinsic width
of the Higgs boson of this mass is much below 1 GeV, the resolution 
of the reconstructed invariant mass of the di-photon system is
completely dominated by the resolution assumed for the 
single photon reconstruction. Fig.~\ref{FS2.2} (left) shows the
reconstructed distribution of the di-photon system of photons passing selection
criteria. The assumed energy resolution of $\sigma = 10\%/\sqrt{E}$
leads to the $\sigma_m = 0.85$ GeV resolution for the reconstructed
invariant mass of the di-photon system originating from the 
$ H \to \gamma \gamma$ decay.
 
The second control physics process is the di-jet production. Here we
don't expect isolated photons to be present, just photons from the
radiative cascade or $\pi's$ decays within the jets. Nevertheless,
some of those photons will also pass isolation criteria. 
Fig.~\ref{FS2.2} (right) shows the $p_T$ distribution of the true
(dashed) and classified as isolated (solid) photons passing the
default selection criteria. 

\begin{Fighere}
\begin{center}
     \epsfig{file=plot-hgamgam.eps,width=6.0cm}
     \epsfig{file=plot-dijet-pho.eps,width=6.0cm}\\
\end{center}
\caption{\em
Left: The reconstructed mass, $m_{\gamma \gamma}$, for $H \to \gamma \gamma$ 
events with $m_H=100$~GeV; Right: the transverse momenta spectrum for 
true (solid) and reconstructed isolated (dashed) photons in the di-jet
sample  generated with $p_T^{hard} > 17$~GeV.  
\label{FS2.2}} 
\end{Fighere}


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Jets}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Clusters which have not been selected as associated with electrons or
photons are smeared with Gaussian resolution parametrised in function
{\tt RESHAD} (default: $\sigma = 50\%/\sqrt{E}$ and $100\%/\sqrt{E}$).
 

\begin{Fighere}
\begin{center}
{
     \epsfig{file=plot-u-kh0.eps,width=6.0cm}
     \epsfig{file=plot-b-kh0.eps,width=6.0cm}\\
}
{
     \epsfig{file=plot-ujet-keyhad2.eps,width=6.0cm}
     \epsfig{file=plot-bjet-keyhad2.eps,width=6.0cm}\\
}
{
     \epsfig{file=plot-ujet-keyhad3.eps,width=6.0cm}
     \epsfig{file=plot-bjet-keyhad3.eps,width=6.0cm}\\
}
\end{center}
\caption{\em
The ratio of $p_T^{u-jet}/p_T^{u-quark}$ (left) and
$p_T^{b-jet}/p_T^{b-quark}$ (right) for events generated with 
hard process only (top), hard process and ISR/FSR (middle) and 
full generation (hard process + ISR/FSR + hadronisation) (bottom).
Events are calibrated only in case of the full  generation
(bottom plots). The HP denotes hard process, ISR/FSR initial and final
state radiation respectively and HD denotes hadronisation.
\label{FS2:5}} 
\end{Fighere}
\newpage


 If the non-isolated muon falls into the cone of a
cluster its 4-momenta  is added to the cluster 4-momenta and the
cluster direction is recalculated.
The resulting clusters are classified as jets if their transverse momentum
is greater than a given threshold (default: $p_T > 15$~GeV).
They are removed from the  {\tt COMMON /CLUSTE/} and stored in the 
common  {\tt COMMON /JETALL/}.

The jets reconstruction efficiencies and di-jet mass resolution
have been studied using control physics process of the $WH$ production
with $m_H=100$~GeV and forcing the Higgs boson decay into specific
partons, namely $H \to u \bar u$, $H \to c \bar c$  and $H \to b \bar b$.
We used also process $gg \to H \to \tau \tau$ for estimating tau-jet
reconstruction efficiency (we forced tau-leptons decay into hadrons).
For estimating reconstruction efficiency we consider only jets which
have been reconstructed within the cone $\Delta R = 0.4$ from the
primary parton (particle) and we require that the primary parton
(particle) has passed
the same kinematical selection as required for reconstructed jets.

\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsubsection{Labeling}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Very important for the physics at LHC  are jets originating from b-quarks (so called
b-jets) which can be identified in the detector using b-tagging technique (vertex or
soft-lepton tags). The package labels a jet  as a b-jet if it is 
reconstructed within a limited rapidity
range (default: $|\Delta \eta| < 2.5$) and if a b-quark
of a transverse momenta (after FSR) above the threshold
(default: $p_T > 5$ GeV) is found within the cone 
(default: $\Delta R = 0.2$) around the axis of reconstructed jet.
The similar criteria are used for labeling the c-jets.

Equivalently important are also jets originating from the hadronic 
$\tau$-decay (so called $\tau$-jets) which can be identified using
dedicated algorithms.
The package labels jet as a tau-jet if the hadronic decay product is relatively
hard (default: $p_T^{\tau-had} > 10$ GeV), inside limited rapidity
range (default: $|\eta|<2.5$), dominates reconstructed jet transverse
momenta (default:  $p_T^{\tau-had}/p_T^{jet} > 0.9$), and is within
the cone (default: $\Delta R_{jet, \tau-had} < 0.3$) around the axis of a jet.  

Table~\ref{T2.1} summarises the jets reconstruction+labeling efficiencies as
obtained for the $WH, H \to b \bar b, c \bar c, u \bar u$ and
$gg \to H \to \tau \tau$ events.
Jets labeling is optional, can be switched off for b- and c-jets and/or separately
for tau-jets (default: ON).


\begin{Tabhere} 
\newcommand{\lstrut}{{$\strut\atop\strut$}}
  \caption {\em Efficiency for jet reconstruction+labeling for different types
  of initial partons with $p_T^{parton}> 15$ GeV (required 
  $p_T^{jet}> 15$ GeV). The rapidity coverage is limited to $|\eta| <2.5$.
  The $\Delta R_{cone}=0.4$ is used for cluster
  reconstruction and  $\Delta R_{cone}=0.2$ is used for matching
  criteria. The $WH, H \to b \bar b, c \bar c, u \bar u$ and $gg \to H
  \to \tau \tau$ processes were generated with $m_H = 100$ GeV.
In case of tau-jets only hadronic tau decays were generated.  
\label{T2.1}} 
\vspace{2mm}  
\begin{center}
\begin{tabular}{|c||c|} \hline \hline
Parton type & Reconstruction + Labeling  \\
\hline \hline
u-quark  &    95\%      \\
\hline
b-quark  &    81\%      \\
\hline
c-quark  &    87\%      \\
\hline
tau-jet  &    80\%      \\
\hline \hline
\end{tabular}
\end{center}
\end{Tabhere}

\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsubsection{Calibration}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

The reconstructed jets four-momenta need to be 
 corrected for the out-cone energy
loss (cascade outside the jet-cone) and for the loss of the particles
escaping detection (those below threshold at $p_T=0.5$ GeV, neutrinos,
invisible particles, muons outside acceptance range or 
below the observability threshold).
Such correction, called calibration, can be performed on the
statistical basis only.
The single default calibration function (the same for any type of
jets), as a function of transverse momenta 
of reconstructed jet, $p_T^{jet}$,  is provided in the package.
The calibration algorithm corrects jets four-momenta
 without altering their direction.
Calibration can be switched off (default: ON). 

The quality of the calibration algorithm can be verified by monitoring
the ratio of $p_T^{b-quark}/p_T^{b-jet}$, taking into account
a hard-process quark which originates a given jet.
One can note, (see Fig.~\ref{FS2:5}, bottom plots) 
 that the implemented calibration function has a tendency to
undercalibrate b-jets while calibrates reasonably well u-jets. We can
observe also rather large tail in the $p_T^{jet}/p_T^{b-quark}$
distribution, caused by the semileptonic b-quarks decays and larger
spread of the cascading particles than in the  case of light jets.


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsubsection{Reconstruction of the resonance}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

As an effect of the hadronisation and cascading decays, the expected
resolution for the resonance reconstruction in the hadronic channels
will be much worse than in the leptonic ones.
The precision for reconstructing the peak position of the 
invariant mass  of the di-jet system will relay on the 
precision of the calibration procedure.
Fig.~\ref{FS2:6} shows two examples of the reconstruction of 
invariant mass of the di-jet system in the $WH$
production with $H \to u \bar u$ and  $H \to b \bar b$ decays.
The long tail at the lower side of the invariant mass distribution is
an effect of hadronisation and cascading decays which was not
sufficiently corrected by the imposed calibration.
One may also notice the effect of the ISR/FSR
originated jets contributing to the distribution in the low mass range 
for the $H \to u \bar u$ case where jets identification is more ambiguous.

\begin{Fighere}
\begin{center}
     \epsfig{file=plot-h2u.eps,width=6.0cm}
     \epsfig{file=plot-h2b.eps,width=6.0cm}\\
\end{center}
\caption{\em
Left: The reconstructed mass, $m_{jj}$, for the $WH$ with  $H \to u
\bar u$  (left) and $H \to b \bar b$  (right)
events with $m_H=100$~GeV.
\label{FS2:6}} 
\end{Fighere}


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Missing transverse energy}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

The missing transverse energy is calculated by summing the transverse
momenta of identified isolated photons, electrons and muons, of jets
and clusters not accepted as jets and of
non-isolated muons not added to any jet. Finally, the
transverse energies deposited in cells not used for clusters
reconstruction are also included in the total sum. Transverse energies
deposited in unused cells are smeared with the same energy resolution
function as for jets, and cells with deposited transverse energy below
a given threshold (default: 0 GeV) are excluded from the sum. From
the calculation of the total sum $E_T^{obs}$ the missing transverse
energy is obtained, $E_T^{miss} =  E_T^{obs}$ as well as the missing
transverse momentum components $p_x^{miss} = - p_x^{obs}$, 
$p_y^{miss} = - p_y^{obs}$. The total calorimeter transverse energy,
$\sum E_T^{calo}$, is calculated as the sum of all the above
transverse energies except that of muons.
Please note, that missing transverse energy is calculated from the
energy balance before jets calibration is performed, as the possible 
out-cone energy loss is already taken into account by summing up energy
deposition of unused cells/clusters.

Fig.~\ref{FS2:7} shows the resolution of the transverse missing energy
obtained for the di-jet events generated with the transverse momenta
of the hard process above 17 GeV.

\begin{Fighere}
\begin{center}
     \epsfig{file=plot-pxmiss.eps,width=6.0cm}
     \epsfig{file=plot-pymiss.eps,width=6.0cm}\\
\end{center}
\caption{\em
The $p_x^{miss}$ and  $p_y^{miss}$ resolutions for the di-jet events.
\label{FS2:7}} 
\end{Fighere}



\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Additional efficiencies}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

The algorithms of the {\tt AcerDET} package are not correcting for
inefficiencies of photon, electron and muon reconstruction and
identification. To be more realistic, one should apply a weighting
factor of 70\%-90\% for each isolated lepton used in the analysis and of
80\% for each isolated photon.

The package is also not correcting for tagging-efficiencies, namely
the labeling procedure is not equivalent to the b- and tau-jet
identification in the experiment. One can assume b-tagging efficiency 
of 60\% per b-labeled jet with mistagging probability of 10\% for
c-labeled jet and 1\% for the light jet.
For the tau-jets using efficiency of 50\% (per tau-labelled jet)
and 5 - 10 \% mistagging probability for other jets could be a reasonable
assumptions. One should be well aware that what proposed above 
represents quite crude estimates.

The package is also not correcting for trigger efficiencies which has
to be applied in addition if a given reconstructed object is foreseen to
trigger an event. 

\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{OUTPUT format}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

By the end of the simulation and reconstruction algorithm,
reconstructed entities: photons, electrons, muons, jets, transverse
missing energy are rewritten to the set of {\tt COMMON BLOCKS}.
Provided is algorithm to store this information in the {\tt PAW HBOOK} \cite{HBOOK}
data-base, so called {\tt PAW NTUPLE}. However, the user might decide to
use his preferred data-base technology for storing output from the 
simulation and reconstruction algorithms.





\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Outlook}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

We presented package which  can be useful for several
phenomenological studies on the high $p_T$ physics at LHC.
One of the favoured application might be the comparison
studies on the matrix element and parton shower Monte Carlo
predictions for different background processes at LHC,
 like  eg. presented in \cite{hep-ph-0203148}.
It is not the aim of the package to represent in details performance of
neither ATLAS nor CMS detectors, nevertheless some global features
of these would be reproduced well. In particular we believe that the
analyses performed with the package for physics at LHC will be more
realistic than parton-level studies alone.
The package allows also for rather flexible 
adjusting of several key parameters which characterise features of any
detector for LHC or LC experiments. 


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Acknowledgments}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

This work was inspired by the several years of my involvement in the activity 
of the  Physics Working Groups of the ATLAS Collaboration.
I am  grateful to all colleagues for a very creative atmosphere.
In particular for several suggestions and inspiring discussions to
Daniel Froidevaux, who  some years ago initiated and guided 
 my work on the first version of the fast simulation package.

\newpage
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{thebibliography}{}

\bibitem{ATL-PHYS-TDR}
ATLAS Collaboration, ATLAS Detector and Physics Performance TDR,
ATLAS TDR 15, CERN/LHCC/99-15, 25 May 1999.

\bibitem{ATL-PHYS-98-131}
E. Richter-Was, D. Froidevaux and L. Poggioli, ATLAS Internal Note 
 ATL-PHYS-98-131 (1998).

\bibitem{AcerMC}
B. Kersevan and E. Richter-Was, {\it The Monte Carlo event generator 
AcerMC version 1.0 with interfaces to PYTHIA 6.2 and HERWIG 6.3},
hep-ph/0201302, Comp. Phys. Commun. in print.

\bibitem{hep-ph-0207014}
B. Kersevan, M. Malawski and E. Richter-Was, {\it Prospects for
observing an invisibly decaying Higgs boson in the $t \bar t H$
production at the LHC}, hep-ph/0207014.

\bibitem{hep-ph-0203148}
B. Kersevan and E. Richter-Was, {\it What is the $W b \bar b$, $Z b
\bar b$ and $t \bar t b \bar b$ background at LHC}, hep-ph/0203148, JHEP in print.

\bibitem{HBOOK}
CERN program Library Long Writeups Y250. HBOOK Statistical Analysis
and Histogramming, Reference Manual.

\bibitem{PYTHIA6.2}
T. Sjostrand et al., {\it High energy physics generation with PYTHIA~6.2},
eprint hep-ph/0108264, LU-TP  01-21, August 2001.

\bibitem{HERWIG6.3}
G. Marchesini et al., Comp. Phys. Commun. {\bf 67} (1992) 465,
G. Corcella et al., JHEP {\bf 0101} (2001) 010.

\end{thebibliography}

\newpage
\appendix


\boldmath 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{AcerDET versus ATLAS detector fast and full simulation}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\unboldmath

Below we compare few benchmarking numbers obtained with the {\tt AcerDET}
code, the fast simulation of ATLAS detector {\tt ATLFAST}
\cite{ATL-PHYS-98-131} and the results from the full
simulation/reconstruction expected with ATLAS
detector \cite{ATL-PHYS-TDR} at the luminosity of $10^{33}
cm^{-2}s^{-1}$. Numbers are given after event selection
as foreseen for the analysis in the specific channel  \cite{ATL-PHYS-TDR}.




\begin{Tabhere} 
\newcommand{\lstrut}{{$\strut\atop\strut$}}
  \caption {\em Benchmarking numbers for fast simulation {\tt AcerDET},  {\tt ATLFAST}
 package and  results from full simulation of ATLAS detector at the
 luminosity of $10^{33} cm^{-2}s^{-1}$  
\label{T2.5}} 
\vspace{2mm}  
\begin{center}
\begin{tabular}{|c||c|c|c|} \hline \hline
Parton type &           AcerDET     &    ATLFAST   &   ATLAS full sim.\\
            &      $\sigma_m$       &    $\sigma_m$ &   $\sigma_m$  \\
\hline \hline
$H \to \gamma \gamma$   &   0.85 GeV &    1.0 GeV   &   1.1 GeV  \\
 ($m_H=100$ GeV)        &            &              &            \\
\hline
$H \to ZZ \to 4e$       &   1.26 GeV &    1.45 GeV  &   1.5 GeV  \\
 ($m_H=130$ GeV)        &            &              &            \\
\hline
$H \to ZZ \to 4 \mu$    &   1.57 GeV &    1.34 GeV  &   1.4 GeV  \\
 ($m_H=130$ GeV)        &            &              &            \\
\hline
$H \to ZZ \to 2e 2\mu$  &   1.40 GeV &    1.40 GeV  &   1.5 GeV  \\
 ($m_H=130$ GeV)        &            &              &            \\
\hline
$WH, H \to b \bar b$    &   10   GeV &    12.5 GeV  &   14.7 GeV \\
 ($m_H=100$ GeV)        &            &              &            \\
\hline
$E_T^{miss}$ resolution &  5.0   GeV &     5.7 GeV  &   6.3 GeV  \\
(di-jet events $p_T^{hard}>17$ GeV)  
                        &            &              &            \\
\hline \hline
\end{tabular}
\end{center}
\end{Tabhere}



%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{General infomations}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

The simulation and reconstruction algorithm is executed by a call to the
routine {\tt ACERDET}. 
The events which is going to be processed should be stored
in the {\tt COMMON /ACMCEVENT/}:
{\scriptsize
\begin{verbatim}  
 INTEGER N, K
 REAL P, V
 COMMON/ACMCEVENT/N,K(10000,5),P(10000,5),V(10000,5)
\end{verbatim}  
}

The convention for the particles status, mother-daughter relations,
particles codes, etc. should be the same as in the {\tt COMMON
/PYJETS/} of the {\tt PYTHIA 6.2} event generator \cite{PYTHIA6.2}.

The input/output logical identifiers should be defined in 
 {\tt COMMON /ACDNOUT/}:
{\scriptsize
\begin{verbatim}  
 INTEGER NINP,NOUT
 COMMON /ACDNOUT/ NINP,NOUT
\end{verbatim}  
}

The package reads single input file {\tt acerdet.dat} which contains
parameters for events simulation and reconstruction and write out
single control output file  {\tt acerdet.out}. If initialised by the
user in the main program, control histograms and ntuple with
reconstructed events will be stored in the  {\tt acerdet.ntup} file.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Subroutine ACERDET}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

This is the main subroutine, called to execute simulation and
reconstruction algorithms. The following modes of executing this
subroutine are implemented:
\begin{itemize}
\item
{\tt MODE=-1} -- initalisation, which should be called before the first
event is processed.
\item
{\tt MODE= 0} -- simulation and reconstruction, should be called event
by event.
\item 
{\tt MODE= 1} -- finalisation, should be called after last event is
processed.
\end{itemize}

This subroutines invokes other subroutines: {\tt  ACDINF},
{\tt  ACDINI}, {\tt  ACDCEL}, {\tt  ACDCLU}, {\tt ACDELE}, 
{\tt ACDMUO}, {\tt  ACDPHO}, {\tt  ACDJET}, {\tt ACDMIS}, {\tt ACDBJE}, 
{\tt  ACDCJE}, {\tt ACDTAU} and {\tt ACDCAL}.
    

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Interfaces to Event Generators}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

The event, which is going to be processed, should be stored
in the {\tt COMMON /ACMCEVENT/}. In the source code of the program
provided are subroutines {\tt ACDPYTHIA6} and {\tt ACDHERWIG6} which
respectively fills the  {\tt COMMON /ACMCEVENT/} with the event content
from  {\tt COMMON /PYJETS/} (for {\tt PYTHIA} generator) and 
{\tt COMMON /HEPEVT/} (for  {\tt HERWIG} generator \cite{HERWIG6.3}). In the second
case also the convention for status of the particles is modified and
made consistent with that used by the {\tt ACERDET}.


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{External calling sequence}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

The following calling sequence should be provided
in the main program

{\scriptsize
\begin{verbatim}  
      Initialise Generator
      CALL ACERDET(-1)
      CALL ACERDETNTUP(-1)
      DO II= 1,NEVENT
         Generate Event (PYTHIA) or  Generate Event (HERWIG)
         CALL ACDPYTHIA6 or  CALL ACDHERWIG6
         CALL ACERDET(0)
         CALL ACERDETNTUP(0)
      ENDDO
      Finalise Generator
      CALL ACERDET(1)
      CALL ACERDETNTUP(1)
\end{verbatim}  
}

Invoking subroutine {\tt ACERDETNTUP} is optional. It stores
data-base with processed events in the {\tt HBOOK NTUPLE} \cite{HBOOK}
from {\tt cernlib} library. It
creates also output file for storing control histograms and ntuple
in {\tt acerdet.ntup}. User however may decide on a different output format.

If user do not wish, the dependencies on {\tt cernlib} could be easily
removed. It requires linking into executable the respective library 
and providing very simple conversion package where the existing calls to
{\tt cernlib} functions for random number generation and histograming
are used  to fill information into the user's preferred ones.


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Execution sequence}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

After the initialisation phase, the event by event execution sequence
 is a following one: 
\begin{itemize}
\item
Map of the cells energy deposition is created: {\tt SUBROUTINE ACDCEL}.
\item
Calorimetric clusters are reconstructed: {\tt SUBROUTINE ACDCLU}.
\item
Isolated and non-isolated muons are reconstructed: {\tt SUBROUTINE ACDMUO}.
\item
Isolated electrons are reconstructed: {\tt SUBROUTINE ACDELE}.
\item
Isolated photons are reconstructed: {\tt SUBROUTINE ACDPHO}.
\item
The remaining calorimetric clusters are identified as jets: {\tt SUBROUTINE ACDJET}.
\item
Missing transverse is calculated for the reconstructed event: {\tt SUBROUTINE ACDMIS}.
\item
Optionally, if specified in the acerdet.dat file, algorithms for 
jets labeling and calibration of jets are executed (default=ON): 
{\tt SUBROUTINE ACDBJE, SUBROUTINE ACDCJE, SUBROUTINE ACDTAU, SUBROUTINE ACDCAL}
\item
Reconstructed event is stored in the final common blocks: {\tt
SUBROUTINE  ACDOUT}.
\end{itemize}


The respective sequence of calls is executed in the {\tt SUBROUTINE ACERDET}.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Structure of the distribution version}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

The distribution version consists of the source code of the {\tt
AcerDET} and example of the main program for execution with {\tt
PYTHIA 6.2} generator. The {\tt acerdet.dat} file resides in
subdirectory {\tt acerdet\_dat}. Source code resides in {\tt
acerdet\_src} with includes files stored in {\tt acerdet\_inc} 
The library will be created in {\tt acerdet\_lib}. provided is also
example of the main program {\tt demo.f} to execute {\tt AcerDET} algorithms
with  {\tt PYTHIA 6.2} generator.

{\scriptsize
\begin{verbatim}  
  -rw-rw-r--    1 erichter erichter     1613 Jul 30 08:46 AAREADME 
  drwxr-xr-x    2 erichter erichter     4096 Jul 29 20:17 acerdet_dat
  drwxr-xr-x    2 erichter erichter     4096 Jul 29 20:17 acerdet_inc
  drwxrwxr-x    2 erichter erichter     4096 Jul 29 20:21 acerdet_lib
  drwxr-xr-x    2 erichter erichter     4096 Jul 29 20:21 acerdet_src
  -rw-r--r--    1 erichter erichter    10682 Jul  5 16:48 demo.f
  -rw-r--r--    1 erichter erichter     1337 Jul 29 20:23 makefile
  drwxr-xr-x    2 erichter erichter     4096 Jul 29 20:24 prod 
\end{verbatim} 
}
To execute the package following actions should be taken:
\begin{itemize}
\item
In subdirectory {\tt acerdet\_src} type: {\it make install}. It will
compile the code and create the {\tt libacerdet.a} library in 
{\tt acerdet\_lib} subdirectory
\item
Edit {\tt makefile} in main directory to define {\tt PYPATH} and {\tt
CERNLIB} environmental variables
\item
In main directory type: {\it make}. It will create {\tt demo.exe} executable.
\item
Optional: Edit {\tt run.dat} file in subdirectory {\tt prod} to
redefine generated process, number of events, random seed, etc.
\item
In main directory type: {\it make run}. It will create link to the {\tt
acerdet.dat} file in {\tt prod} subdirectory and will execute the
executable. Output will be stored in subdirectory {\tt prod}. 
\end{itemize}



\newpage
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{List of input parameters: {\tt acerdet.dat} file}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
{\scriptsize
\begin{verbatim}  
C------ flags and switches ---------------
     10000       ---  LPAR(1)   ....id for histograms
         1       ---  LPAR(2)   ....smearing on=1, off=0
         1       ---  LPAR(3)   ....B-field  on=1, off=0
        66       ---  LPAR(4)   ....code for invisible particle
         1       ---  LPAR(5)   ....b- and c-labeling  on=1, off=0
         1       ---  LPAR(6)   ....tau-labeling  on=1, off=0
         1       ---  LPAR(7)   ....calibration   on=1, off=0
C------ parameters for ACDCEL ---------------
     5.000       ---  YPAR(1)  ....rapidity coverage
     0.500       ---  YPAR(2)  ....min p_T for B-field
     0.000       ---  YPAR(3)  ....min E_T for cell 
     3.200       ---  YPAR(4)  ....eta transition in cells granularity
     0.100       ---  YPAR(5)  ....granularity in eta (within YPAR(17)), 2x outside
     0.100       ---  YPAR(6)  ....granularity in phi (within YPAR(17)), 2x outside
C------ parameters for ACDCLU ---------------
     5.000       ---  YPAR(10)  ....minimum E_T for cluster
     0.400       ---  YPAR(11)  ....cone R for clustering 
     5.000       ---  YPAR(12)  ....rapidity coverage
     1.500       ---  YPAR(13)  ....min E_T for cluster initiator
C------ parameters for ACDMUO ---------------
     6.000       ---  YPAR(20)  ....minimum muon-momenta to be detected
     2.500       ---  YPAR(21)  ....maximum muon eta to be detected
     0.400       ---  YPAR(27)  ....min R_lj for muon-isolation
     0.200       ---  YPAR(28)  ....R_cone for energy deposition 
    10.000       ---  YPAR(29)  ....max energy deposition for isol
C------ parameters for ACDPHO ---------------
     5.000       ---  YPAR(30)  ....minimum photon-momenta to be isol
     2.500       ---  YPAR(31)  ....maximum photon eta to be isol
     0.150       ---  YPAR(35)  ....min R_lj for photon-jet
     0.400       ---  YPAR(37)  ....min R_lj for photon-isolation
     0.200       ---  YPAR(38)  ....R_cone for energy deposition 
    10.000       ---  YPAR(39)  ....max energy deposition for isol
C------ parameters for ACDELE ---------------
     5.000       ---  YPAR(40)  ....minimum electron-momenta to be isol
     2.500       ---  YPAR(41)  ....maximum electron eta to be isol
     0.150       ---  YPAR(45)  ....min R_lj for electron-jet
     0.400       ---  YPAR(47)  ....min R_lj for electron-isolation
     0.200       ---  YPAR(48)  ....R_cone for energy deposition 
    10.000       ---  YPAR(49)  ....max energy deposition for isol
C------ parameters for ACDJET ---------------
    10.000       ---  YPAR(51)  ....jets energy_min  threshold
     5.000       ---  YPAR(52)  ....rapidity coverage for jets
C------ parameters for ACDBJE ---------------
     5.000       ---  YPAR(61)  ....minimum b-quark pT (after FSR) momenta for b-jet label
     2.500       ---  YPAR(62)  ....maximum b-quark eta for  b-jet label
     0.200       ---  YPAR(63)  ....max R_bj for b-jet label
C------ parameters for ACDCJE ---------------
     5.000       ---  YPAR(71)  ....minimum c-quark pT (after FSR) momenta for c-jet label
     2.500       ---  YPAR(72)  ....maximum c-quark eta for  c-jet label
     0.200       ---  YPAR(73)  ....max R_cj for c-jet label
C------ parameters for ACDTAU ---------------
    10.000       ---  YPAR(90)  ....minimum tau-had pT for  tau-jet label
     2.500       ---  YPAR(91)  ....maximum tau-eta for  tau-jet label
     0.300       ---  YPAR(92)  ....max R_tauj for tau-jet
     0.900       ---  YPAR(93)  ....max R_tauj for tau-jet
C------ parameters for ACDMIS ---------------
     0.000       ---  YPAR(80)  ....min E_T for energy in cell to count unused cell
C------   end of data files   ---------------
\end{verbatim}  
}

\newpage
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Reconstructed entities}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Isolated photons are stored in {\tt COMMON /ACDPHOT/}, given are
4-momenta in the laboratory frame {\tt PXPHOT, PYPHOT, PZPHOT, EEPHOT},
and code for the photon {\tt KFPHOT=22}. Photons are
ordered  with the decreasing transverse momenta.

{\scriptsize
\begin{verbatim}  
      INTEGER MAXPHOT
      PARAMETER(MAXPHOT=12)
      INTEGER NPHOT,KFPHOT
      REAL PXPHOT,PYPHOT,PZPHOT,EEPHOT
      COMMON /ACDPHOT/ NPHOT,KFPHOT(MAXPHOT),
     +                 PXPHOT(MAXPHOT),PYPHOT(MAXPHOT),PZPHOT(MAXPHOT),
     +                 EEPHOT(MAXPHOT) 

\end{verbatim} 
}

Isolated leptons are stored in {\tt COMMON /ACDLEPT/}, given are
4-momenta in the laboratory frame {\tt PXLEPT, PYLEPT, PZLEPT, EELEPT},
and code for the lepton {\tt KFLEPT=$\pm$ 11, $\pm$
13}. Leptons are ordered with the decreasing transverse momenta.

{\scriptsize
\begin{verbatim}  
      INTEGER MAXLEPT
      PARAMETER(MAXLEPT=12)
      INTEGER NLEPT,KFLEPT
      REAL PXLEPT,PYLEPT,PZLEPT,EELEPT
      COMMON /ACDLEPTT/ NLEPT,KFLEPT(MAXLEPT),
     +                 PXLEPT(MAXLEPT),PYLEPT(MAXLEPT),PZLEPT(MAXLEPT),
     +                 EELEPT(MAXLEPT)
\end{verbatim} 
}
Reconstructed jets stored in {\tt COMMON /ACDJETS/}, given are
4-momenta in the laboratory frame {\tt PXJETS, PYJETS, PZJETS, EEJETS},
and code for the jet {\tt KFJETS= 5, 4, 15, 98};
respectively for b-jets, c-jets, tau-jets and light-jets.
Jets are ordered with the decreasing transverse moment.

{\scriptsize
\begin{verbatim}  
      INTEGER MAXJET
      PARAMETER(MAXJET=20)
      INTEGER NJETS,KFJETS
      REAL PXJETS,PYJETS,PZJETS,EEJETS
      COMMON /ACDJETS/  NJETS,KFJETS(MAXJET),
     +                  PXJETS(MAXJET),PYJETS(MAXJET),PZJETS(MAXJET),
     +                  EEJETS(MAXJET)
\end{verbatim}  
}

Information on the reconstructed missing transverse energy is stored
in {\tt COMMON  /ACDMISS/}. Given  are both transverse
components {\tt PXMISS,PYMISS}, sum of transverse momenta components
of neutrinos and invisible particles (as defined by the user) 
 present in the event {\tt PXNUES,PYNUES}
and finally sum of the total transverse energy components deposited in the
calorimeter {\tt PXCALO,PYCALO}. 

{\scriptsize
\begin{verbatim}  
      REAL PXMISS,PYMISS,PXNUES,PYNUES,PXCALO,PYCALO
      COMMON /ACDMISS/PXMISS,PYMISS,PXNUES,PYNUES,PXCALO,PYCALO 
\end{verbatim}  
}

For the convenience stored is also information on the history of all particles
participating in the {\it hard-scattering} in which event was created.
Included are those with the status code $=21$ (convention of {\tt PYTHIA}
generator). Given is: status of particle {\tt KSPART}, its flavour code
 {\tt KFPART} and 4-momenta in the laboratory frame
 {\tt PXPART, PYPART, PZPART, EEPART}.

{\scriptsize
\begin{verbatim}  
      INTEGER MAXPART
      PARAMETER(MAXPART=40)
      INTEGER NPART,KSPART,KFPART
      REAL PXPART,PYPART,PZPART,EEPART
      COMMON /ACDPART/ NPART,KSPART(MAXPART),KFPART(MAXPART),
     +                 PXPART(MAXPART),PYPART(MAXPART),
     +                 PZPART(MAXPART),EEPART(MAXPART)
\end{verbatim}  
}

Some additional information, if required, can be also extracted from
the  internal variables/common blocks of simulation and reconstruction
algorithms: eg. on used/unused cells, non-isolated muons, 
unused clusters, etc.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Parametrisation for energy/momenta resolution}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\subsection{Function RESPHO}

The parametrisation for photon energy resolution assumes only 
energy dependence and the Gaussian
smearing with $10\%/\sqrt{E_{\gamma}}$ resolution.
\begin{equation}
 E_{\gamma}^{smeared}  = 
E_{\gamma}^{true} \cdot (1+ r_n \cdot \frac{0.10}{\sqrt{E_{\gamma}^{true}}}). 
\end{equation}
Where $r_n$ is the random number generated according to the Gaussian
distribution (function {\tt RANNOR} from {\tt cernlib} library is used).
All 4-momenta components of the photon are smeared with the same
resolution so the direction of the photon is not altered. 

\subsection{Function RESELE}

The parametrisation for electron energy resolution assumes only 
energy dependence and the Gaussian
smearing with $12\%/\sqrt{E_{e}}$ resolution.
\begin{equation}
 E_{e}^{smeared}  = 
E_{e}^{true} \cdot (1+ r_n \cdot \frac{0.12}{\sqrt{E_{e}^{true}}}). 
\end{equation}
Where $r_n$ is the random number generated according to the Gaussian
distribution (function {\tt RANNOR} from {\tt cernlib} library is used).
All 4-momenta components of the electron are smeared with the same
resolution so the direction of the electron is not altered. 

\subsection{Function RESHAD}

The parametrisation for clusters momenta resolution assumes only 
energy dependence and Gaussian
smearing with $50\%/\sqrt{E_{clu}}$ or $100\%/\sqrt{E_{clu}}$
resolution.
The transition region, $|\eta^{clu}| = CALOTH$  is the same as the 
transition of the cells granularity. \\
For  $|\eta^{clu}| < CALOTH$:
\begin{equation}
 E_{clu}^{smeared}  = 
E_{clu}^{true} \cdot (1+ r_n \cdot \frac{0.50}{\sqrt{E_{clu}^{true}}}). 
\end{equation}
For  $|\eta^{clu}| > CALOTH$:
\begin{equation}
 E_{clu}^{smeared}  = 
E_{clu}^{true} \cdot (1+ r_n \cdot \frac{1.00}{\sqrt{E_{clu}^{true}}}). 
\end{equation}
Where $r_n$ is the random number generated according to the Gaussian
distribution (function {\tt RANNOR} from {\tt cernlib} library is used).
All 4-momenta components of the muon are smeared with the same
resolution so the direction of the muon is not altered. 

\subsection{Function RESMUO}

The parametrisation for muon momenta resolution assumes only 
transverse momenta dependence and Gaussian
smearing with $0.0005 \cdot pT_{\mu}$ resolution.
\begin{equation}
 pT_{\mu}^{smeared}  = 
pT_{\mu}^{true}/(1+ r_n \cdot 0.0005 \cdot pT_{\mu}^{true}). 
\end{equation}
Where $r_n$ is the random number generated according to the Gaussian
distribution (function {\tt RANNOR} from {\tt cernlib} library is used).
All 4-momenta components of the muon are smeared with the same
resolution so the direction of the muon is not altered. 

\subsection{Function FLDPHI}

The effect of the magnetic field is included by simple shifting the
$\phi$ position of the charged particles respectively to its
transverse momenta, parametrised as following:
\begin{equation}
 \delta \phi   =  0.5 / pT^{part}. 
\end{equation}
The $ \delta \phi$ is calculated in radians and $pT^{part}$ is
given in $GeV$.
The sign of the  $ \delta \phi$ is the same as the sign of the
particle charge.
Charged particles with  $pT^{part} < 0.5$ GeV are assumed to be
looping in the detector and not depositing energy in the calorimeter.


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Some formulas}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

We work with the assumptions of massless reconstructed objets. The
following relations were used to translate between $(p_T, \eta, \phi)$
coordinates and four-momenta $(p_x, p_y, p_z, E)$.

\begin{equation}
 p_x=p_T \cdot cos(\phi) 
\end{equation}
\begin{equation}
 p_y=p_T \cdot sin(\phi)
\end{equation}
\begin{equation}
 p_z=p_T \cdot cosh(\eta) 
\end{equation}
\begin{equation}
 E  =p_T \cdot sinh(\eta)
\end{equation}

\begin{equation}
 p_T = \sqrt{p_x^2 + p_y^2}
\end{equation}
\begin{equation}
\eta = sign(\ln{\frac{\sqrt{p_T^2+p_z^2}+|p_z|}{p_T}},p_z)
\end{equation}
\begin{equation}
 \phi = asinh(p_y/\sqrt{p_x^2+p_y^2}) 
\end{equation}

\newpage
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Output content}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Output ntuple content: {\tt acerdet.ntup} file}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
The content of the ntuple is exactly as described in the previous
section. As an auxiliary info, within the stored information,
could be provided code on the generated process, {\tt IDPROC}.

{\scriptsize
\begin{verbatim}  
 ******************************************************************
 * Ntuple ID = 3333   Entries = 100000    ACERDET
 ******************************************************************
 * Var numb * Type * Packing *    Range     *  Block   *  Name    *
 ******************************************************************
 *      1   * I*4  *         *              * ACDINFO  * IDPROC
 *      1   * R*4  *         *              * ACDMISS  * PXMISS
 *      2   * R*4  *         *              * ACDMISS  * PYMISS
 *      3   * R*4  *         *              * ACDMISS  * PXNUES
 *      4   * R*4  *         *              * ACDMISS  * PYNUES
 *      5   * R*4  *         *              * ACDMISS  * PXCALO
 *      6   * R*4  *         *              * ACDMISS  * PYCALO
 *      1   * I*4  *         * [0,12]       * ACDLEPT  * NLEPT
 *      2   * I*4  *         *              * ACDLEPT  * KFLEPT(NLEPT)
 *      3   * R*4  *         *              * ACDLEPT  * PXLEPT(NLEPT)
 *      4   * R*4  *         *              * ACDLEPT  * PYLEPT(NLEPT)
 *      5   * R*4  *         *              * ACDLEPT  * PZLEPT(NLEPT)
 *      6   * R*4  *         *              * ACDLEPT  * EELEPT(NLEPT)
 *      1   * I*4  *         * [0,12]       * ACDPHOT  * NPHOT
 *      2   * I*4  *         *              * ACDPHOT  * KFPHOT(NPHOT)
 *      3   * R*4  *         *              * ACDPHOT  * PXPHOT(NPHOT)
 *      4   * R*4  *         *              * ACDPHOT  * PYPHOT(NPHOT)
 *      5   * R*4  *         *              * ACDPHOT  * PZPHOT(NPHOT)
 *      6   * R*4  *         *              * ACDPHOT  * EEPHOT(NPHOT)
 *      1   * I*4  *         * [0,20]       * ACDJETS  * NJETS
 *      2   * I*4  *         *              * ACDJETS  * KFJETS(NJETS)
 *      3   * R*4  *         *              * ACDJETS  * PXJETS(NJETS)
 *      4   * R*4  *         *              * ACDJETS  * PYJETS(NJETS)
 *      5   * R*4  *         *              * ACDJETS  * PZJETS(NJETS)
 *      6   * R*4  *         *              * ACDJETS  * EEJETS(NJETS)
 *      1   * I*4  *         * [0,40]       * ACDPART  * NPART
 *      2   * I*4  *         *              * ACDPART  * KSPART(NPART)
 *      3   * I*4  *         *              * ACDPART  * KFPART(NPART)
 *      4   * R*4  *         *              * ACDPART  * PXPART(NPART)
 *      5   * R*4  *         *              * ACDPART  * PYPART(NPART)
 *      6   * R*4  *         *              * ACDPART  * PZPART(NPART)
 *      7   * R*4  *         *              * ACDPART  * EEPART(NPART)
 ******************************************************************
 *  Block   *  Entries  * Unpacked * Packed *   Packing Factor    *
 ******************************************************************
 * ACDINFO  *  100000   * 4        * 4      *       1.000         *
 * ACDMISS  *  100000   * 24       * 24     *       1.000         *
 * ACDLEPT  *  100000   * 244      * Var.   *    Variable         *
 * ACDPHOT  *  100000   * 244      * Var.   *    Variable         *
 * ACDJETS  *  100000   * 404      * Var.   *    Variable         *
 * ACDPART  *  100000   * 964      * Var.   *    Variable         *
 * Total    *    ---    * 1884     * Var.   *    Variable         *
 ******************************************************************
 * Blocks = 6            Variables = 32      Max. Columns = 471   *
 ******************************************************************                    \end{verbatim}  
} 

\newpage
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Control printout: acerdet.out file}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

{\scriptsize
\begin{verbatim}  
 ***************************************************************************
 *                                                                         *
 *                      **************************                         *
 *                       AcerDET, version: 1.0                             *
 *                       Released at: 30.07.2002                           *
 *                      **************************                         *
 *                                                                         *
 *          Simplied event simulation and reconstruction package           *
 *                                                                         *
 *                         by E. Richter-Was                               *
 *                    Institute of Computer Science                        *
 *               Jagellonian University, Cracow, Poland                    *
 *                                                                         *
 *                                                                         *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***  ACDCEL   ***         *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 clusters definition ....                                *
 *          5.00000                eta coverage              ETACEL        *
 *          0.00000                E_T_min cell thresh       ETTHR         *
 *          3.20000                eta gran. transition      CALOTH        *
 *          0.10000                gran in eta(central)      DBETA         *
 *          0.10000                gran in phi(central)      DBPHI         *
 *                 B field apply ....                                      *
 *                1                B-field on/off            KEYFLD        *
 *          0.50000                p_T min non looping       PTMIN         *
 *                 invisible particles ....                                *
 *               66                KF code for invis         KFINVS        *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***  ACDCLU   ***         *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 clusters definition ....                                *
 *          5.00000                E_T_min cluster          ETCLU          *
 *          1.50000                E_T_min cell initia      ETINI          *
 *          0.40000                R cone                   RCONE          *
 *          5.00000                eta coverage             ETACLU         *
 *          3.20000                eta gran. transition     CALOTH         *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDMUO   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 muon isolation ....                                     *
 *          6.00000                min. muon p_T            PTMUMIN        *
 *          2.50000                max. muon eta            ETAMAX         *
 *          0.40000                min R_lj for isolat.     RISOLJ         *
 *          0.20000                R for energy deposit     RDEP           *
 *         10.00000                max E_dep for isolat     EDMAX          *
 *          0.00000                min. muon p_T unsmea     PTMUMIT        *
 *                1                smearing on/off          KEYSME         *
 ***************************************************************************
\end{verbatim}  
}
\newpage
{\scriptsize
\begin{verbatim}  
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDELE  ***         *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 electron isolation ....                                 *
 *          5.00000                min. lepton p_T          PTLMIN         *
 *          2.50000                max. lepton eta          ETAMAX         *
 *          0.15000                max R_ej for ele-clu     RJE            *
 *          0.40000                min R_lj for isolat.     RISOLJ         *
 *          0.20000                R for energy deposit     RDEP           *
 *         10.00000                max E_dep for isolat     EDMAX          *
 *                1                smearing on/off          KEYSME         *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDPHO   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 photon  isolation ....                                  *
 *          5.00000                min. photon p_T          PTLMIN         *
 *          2.50000                max. photon eta          ETAMAX         *
 *          0.15000                max R_gam-clust          RJE            *
 *          0.40000                min R_isol               RISOLJ         *
 *          0.20000                R for energy deposit     RDEP           *
 *         10.00000                max E_dep for isolat     EDMAX          *
 *                1                smearing on/off          KEYSME         *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***  ACDJET   ***         *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 clusters definition ....                                *
 *          0.40000                R cone                    RCONE         *
 *                 jets definition ....                                    *
 *         10.00000                E_T_jets [GeV]            ETJET         *
 *          5.00000                eta coverage jets         ETAJET        *
 *                1                smearing on/off           KEYSME        *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDMIS   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                    muon coverage     ....                               *
 *          6.00000                min. muon p_T             PTMUMIN       *
 *          2.50000                max. muon eta             ETAMAX        *
 *                    unused cells     ....                                *
 *                1                smearing on/off           KEYSME        *
 *          0.00000                cells threshold           ETCELL        *
 *                    invisible particles     ....                         *
 *               66                KF code for invis         KFINVS        *
 ***************************************************************************
\end{verbatim}  
}
\newpage
{\scriptsize
\begin{verbatim}  
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDBJE   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                   jets labeling ....                                    *
 *                1       labeling on/off                    KEYBCL        *
 *                   jets definition ....                                  *
 *         10.00000                E_T_jets [GeV]            ETJET         *
 *                   b-jets............. ....                              *
 *          5.00000                min b-quark p_T           PTBMIN        *
 *          2.50000                max b-quark eta           ETBMAX        *
 *          0.20000                max R_bj for b-jet        RJB           *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDCJE   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 jets labeling ....                                      *
 *                1       labeling on/off                    KEYBCL        *
 *                 jets definition ....                                    *
 *         10.00000                E_T_jets [GeV]            ETJET         *
 *                 c-jets.............                                     *
 *          5.00000                min c-quark p_T           PTCMIN        *
 *          2.50000                max c-quark eta           ETCMAX        *
 *          0.20000                max R_cj for c-jet        RJC           *
 ***************************************************************************
 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDTAU   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                 jets labeling ....                                      *
 *                1       labeling on/off                    KEYBCL        *
 *                 jets definition ....                                    *
 *         10.00000                E_T_jets [GeV]            ETJET         *
 *                 tau-jets.............                                   *
 *         10.00000                min tau-had p_T           PTTAU         *
 *          2.50000                max tau-had eta           ETATAU        *
 *          0.30000                max R_tauj for tau-j      RJTAU         *
 *          0.90000                tau-had frac. of jet      PTFRAC        *
 ***************************************************************************

 ***************************************************************************
 *               *********************************                         *
 *               *     *****************         *                         *
 *               *     ***   ACDCAL   ***        *                         *
 *               *     *****************         *                         *
 *               *********************************                         *
 *                jets calibration ....                                    *
 *                1                calibration n/off         KEYCAL        *
 ***************************************************************************
\end{verbatim}  
}
\newpage
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Control histograms: acerdet.ntup file}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Below is the list of control histograms which monitors performance of
the simulation/reconstruction. The are store together with {\tt ACERDET}
ntuple in file acerdet.ntup.
\scriptsize{
\begin{verbatim}  
      10001 (1)   ACDCEL: cells multiplicity
      10101 (1)   ACDCLU: clusters multiplicity
      10111 (1)   ACDCLU: delta phi clu-barycentre
      10112 (1)   ACDCLU: delta eta clu-barycentre
      10113 (1)   ACDCLU: delta r clu-barycentre
      10123 (1)   ACDCLU: delta r clu-parton
      10114 (1)   ACDCLU: pTclu/SumpTparticle
      10124 (1)   ACDCLU: pTclu/pTparton
      10210 (1)   ACDMUO: muon multiplicity NOISOLATED
      10211 (1)   ACDMUO: muon multiplicity ISOLATED
      10221 (1)   ACDMUO: muon multiplicity HARD
      10231 (1)   ACDMUO: muon multiplicity HARD+isol
      10311 (1)   ACDELE: electron multiplicity ISOLATED
      10321 (1)   ACDELE: electron multiplicity HARD
      10331 (1)   ACDELE: electron multiplicity HARD+isol
      10411 (1)   ACDPHO: photon multiplicity ISOLATED
      10421 (1)   ACDPHO: photon multiplicity HARD
      10431 (1)   ACDPHO: photon multiplicity HARD+ISO
      10501 (1)   ACDJET: jets multiplicity
      10511 (1)   ACDJET: delta phi jet-barycentre
      10512 (1)   ACDJET: delta eta jet-barycentre
      10513 (1)   ACDJET: delta r jet-barycentre
      10523 (1)   ACDJET: delta r jet-parton
      10514 (1)   ACDJET: pTjet/SumpTparticle
      10524 (1)   ACDJET: pTjet/pTparton
      10611 (1)   ACDMIS: reconstructed p_T
      10612 (1)   ACDMIS: reconstructed p_T +cells
      10613 (1)   ACDMIS: pTmiss
      10621 (1)   ACDMIS: p_T nu
      10711 (1)   ACDBJE: b-jets multiplicity
      10721 (1)   ACDBJE: b-quarks HARD multiplicity
      10723 (1)   ACDJET: delta r bjet-bquark
      10724 (1)   ACDJET: pTbjet/pTbquark
      10811 (1)   ACDCJE: c-jets multiplicity
      10821 (1)   ACDCJE: c-quarks HARD multiplicity
      10823 (1)   ACDJET: delta r cjet-cquark
      10824 (1)   ACDJET: pTcjet/pTcquark
      10911 (1)   ACDTAU: tau-jets multiplicity
      10921 (1)   ACDTAU: taus  multiplicity
      11010 (1)   ACDCAL: calibration entry
      11011 (1)   ACDCAL: calibration factor
      11020 (1)   ACDCAL: pTjetCALIB/pTparton
      11030 (1)   ACDCAL: pTjetNONCALIB/pTparton
\end{verbatim}  
}

\end{document}


















hep-ph0207355.extracted_bib
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