How to Identify Muons
Last update 27/5/03
Preamble
Various different algorithms are available to identify muons. They make
use of various combinations of tracking detectors and patterns of deposited
energy (compatible with m.i.p.s).
For an introduction, see also the lecture on Muon Finding in ZEUS.
Some preselection information is also available in ZES.
This page was originally created by Giuseppe Barbagli
and extended by Achim Geiser
1. General MUON finding in ZEUS using ORANGE
The General MUON finding (GMUON) package in ORANGE is based on a combination
of the GLOMU, BREMAT, MAMMA, MPMATCH, MUFO, MIP, MV, and MUBAC muon finders
described below (available from release 2003b onwards). A rudimentary BAC match
and FMUON standalone information based on the MFCTS tables are provided in
addition. Further extensions are forseen.
The algorithm finds prompt muons based on an "OR" of all these packages, and combines the
information into a single entry per muon candidate as much as possible. The
basic format of this entry is independent of the respective finder.
Cross references to more detailed
information for each finder and cross-correlations between the different
finders are provided.
In the case of ambiguities, alternative reconstructions of the same
muon are sometimes listed.
A muon quality flag is provided which should help the non-expert user to
select good quality muon candidates from this list as a starting point for an
analysis. Since muon quality is process specific, for critical applications
it is recommended that the user redefine his/her own quality criteria based
on the information provided.
Feedback on 'features',
bugs, missing information and/or possible improvements
is greatly appreciated.
Further technical information can be found here. A ZEUS note is in preparation.
MUON
In ORANGE releases 2003a and earlier, only a restricted subset of the
information above based on the GLOMU, MIP, MAMMA and MUBAC finders
is available as documented in ...
2. Muon finding (+ muon bg. rejection) using the Calorimeter
MV
Finds prompt muons anywhere in the CAL (+CTD) with a neural network algorithm.
This is the most advanced CAL-based algorithm available, fully optimized
for muons with p > 2 GeV, with good efficiency for muons down to p > 1 GeV.
It also provides a link to BREMAT (see below).
For documentation, see ...
MUONFIND (MIP)
Finds prompt muons in the CAL+CTD based on the association of a MIP
(Minimum Ionising Particle) calorimeter island to a high momentum track.
Good algorithm for very high momentum muons. Large background at low momenta.
For documentation, see ...
ISITAMU
Group of routines to flag muons looking at calorimeter information,
developed in the early years of ZEUS. It is available in Phantom.
MUTRIG
Finds muon background events in the TLT. It is available in Phantom.
FCALMU
Finds muons in FCAL with a neural network algorithm.
Superseded by MV package (see above).
MUFFIN
Finds muons using as many detectors as possible, especially suitable for
cosmic and beam-halo muons overlapping with events. Currently only available
on UNIX platforms.
3. Muons in the Barrel and Rear region
For a note on how to correct the BRMUON MC efficiencies for dead streamer
tubes (LST) see here.
BREMAT
Looks for muons combining CTD and B/RMUON information.
For low momentum muons seen in the inner muon chambers only, a sophisticated
match based on position, angle, and the full error matrix information is
performed (4 d.o.f.). For higher momentum muons also reaching the outer muon
chambers, a momentum consistency check based on an independent muon momentum
measurement from the muon spectrometer is added (5 d.o.f.).
GLOMU
Looks for low momentum muons combining CTD, calorimeter and B/RMUON
information. Also used by the TLT.
For muon track segments it is possible either to do a fast reconstruction
of track segments from raw data or the use of reconstructed quantities.
CTD tracks, transported to a reference
surface with a Runge-Kutta integration, are matched with track segments.
Calorimeter clusters compatible with m.i.p. passage are identified.
A final match combining muon track segments, CTD tracks and calorimeter
clusters is performed.
4. Muons in the Forward region
A general description of the recostruction software
for Forward Muons can be found in the:
FMUON OFFLINE
web page.
The MPMATCH2 finder looks for muons combining CTD and FMUON information.
FMUON information is extracted from the MFRTZ forward muon tables, which also
provide independent momentum information based on a Kalman filter fit.
Muon chamber tracks are matched to CTD tracks using a sophisticated matching
procedure based on the full error matrix, including an overall momentum fit.
An option to match directly to the primary vertex is also forseen, but not yet
fully implemented.
Significant parts of the algorithm are based on the MVMATCH package
Further documentation on the algorithm and parameters can be found in
the link above.
For even more information contact
Massimo Corradi.
MUFO
Looks for muons combining CTD and FMUON information.
The algorithm is very similar to the MPMATCH algorithm. CTD tracks are
reextrapolated to the CAL entry face using a private algorithm instead of
using the VCPARCAL information.
An option to match directly to the primary vertex using the momentum from the
muon spectrometer only is provided.
Further documentation on the algorithm can be found in ... (ZEUS note in
preparation).
For more information contact
Graziano Bruni.
MAMMA
MAMMA (Muon And Mips MAtcher) matches either tracks or hits in FMUON with
clusters in the FCAL and/or CTD tracks. For FMUON track matching it is based
on the MFCTS information and also used in the TLT.
See here for the
MAMMA documentation.
See also the
version of MAMMA used in ZES.
For more information contact
Graziano Bruni.
MVMATCH
5. Muon finding in the BACking calorimeter
Description will follow soon ...
ZEUS Analysis Home Page.