Transcript LHC Detectors - Physics@Technion

LHC Detectors (ATLAS)
Shlomit Tarem
Technion, Israel Inst. of Tech.
The LHC and its detectors
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The LHC, a pp collider with 14 TeV pp cm energy will start
operation in 2008
4 experiments are working to finish assembly and
commissioning
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ATLAS – general purpose – discovery of new particles
CMS – general purpose – discovery of new particles
LHCB – B Physics – forward
ALICE – heavy ion physics
LHC collisions are a difficult experimental ground
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We won’t know the cm energy of each collision
There will be many pp collisions on top of each other
Most of the collisions are due to uninteresting physics
There will be too much data to collect
LHC Design Parameters
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Energy at collision
14 TeV
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Luminosity
1034/cm²/s
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Bunch spacing
7.48 m
25 ns
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Particles/bunch
1011
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Collisions per BC
23
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Luminosity lifetime
10 h
The ATLAS and CMS Experiments
ATLAS and CMS will start operation
at the LHC at the end of 2007
 Higgs bosons or alternatives for
SSB
 CP-violation with high precision
 Rare B decays
 Top mass
 SUSY particles?
 Beyond the SM
First conclusive Higgs
search
The ATLAS detector
Particle detection basics
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Fast particles created in LHC collisions will interact with the
detector in various ways and leave signals in it
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Charged particles will ionize it
Electrons will radiate in it
Photons will produce e+e- pairs
Hadrons will interact with nuclei
We use these interactions to build detectors
The different interaction of different particle types with the
detector help us distinguish between them
Different technologies help distinguish between different
particle types
Stable particle types which leave signals in the detector
include , e, m, p, k, p, n and hypothetical exotics
Particle detection basics
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A modern detector is like an onion
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The collision point is surrounded by a magnetic
field to bend charged particles according to their momentum
In the field region is a tracking detector to measure particle
trajectories and bending
Next are Electromagnetic calorimeters which utilize EM showers to
stop electrons and photons and measure/sample their energy
Then there are Hadronic Calorimeters which utilize nuclear
interactions with detector material to create and measure hadron
showers and stop hadrons
Outside are muon detectors – another tracking detector for the only
known charged particle type which is not stopped in the calorimeter
The muon detector may have it’s own magnets – then it’s a muon
spectrometer
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ATLAS has such a magnet for muons
CMS has all detectors inside one big magnet
Ionization energy loss
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Relativistic particles lose energy by ionizing atoms of the
material they pass
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Ionization occurs randomly at points along the particle path
We detect the ionization positions to find the particle trajectory
The amount of energy loss per unit path length, dE/dx, depends on
the particle charge and velocity and atomic properties of the
medium
For a known medium, and since most stable particles have 0 or unit
charge, dE/dx is a tool to
find the particle velocity
Knowing the momentum
and velocity we can obtain
the particle mass
Tracking detectors are
designed to measure energy
loss positions
Electromagnetic showers
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Relativistic electrons lose energy primarily via Bremsstrahlung
radiation due to acceleration by multiple scattering
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Photons create e+e- pairs
The distance over which these
happen is characterized by a
“radiation length”
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Energy loss by Brem is proportional to E
Energy loss by ionization is proportional to ln(E)
A characteristic of the medium
The distance over which an
electron is left with 1/e of it’s energy
The average path length for pair
creation
The repeated occurrence of
Brem and pair production create an EM shower
EM showers
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The number of particles at each
stage is N(t)=2t
The energy per particle is
E(t)=E02-t
The process continues until the
electrons go below the Brem
threshold Ec
The total number of electrons in a
shower is proportional to the initial
particle energy
EM showers are narrow and well
contained
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A shower of a 100 GeV electron in
lead is 4 cm wide and 16 cm long
EM calorimeters
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A calorimeter creates a shower and measures the number
of secondary electrons produced in it
A radiator is a heavy material with short radiation length,
which advances the shower process
Between radiators we place measurement layers to
measure how many electrons pass each layer
The measurement is either via ionization energy loss or via
scintillation
Some materials can radiate and measure (lead glass)
To measure correctly the electron/photon energy the
calorimeter has to be deep enough to stop the whole
shower
Muons and hadrons leave an ionization trail in the EM calo
Hadronic showers
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Hadron have strong interactions with the detector nuclei
New particles, mostly pions, are produced and continue to interact
The differences from EM showers:
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Greater distance between collisions
More than 2 particles produced per
interaction
Particles stopped at ~200 MeV
Larger scattering angles – wider
shower
If a p0 is produced it’ll start an EM shower
Large statistical differences in measured energy between showers from
similar particles
This is the only way to detect neutral hadrons
Both EM and hadronic showers are detected via ionization losses of the
resulting particles
The EM calorimeter is the first layer of the Hadronic calorimeter
Other interactions with matter
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Scintillation
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Cerenkov radiation
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In some materials 1-3% of the ionization e-loss goes into optic or
near optic photons
The light can be collected – very fast detectors
Used in the ATLAS tile calorimeter
Radiation created when the passing
particle is faster than the speed of
light in the medium
Can help distinguish between
particle types in energy ranges
depending on radiator
Transition radiation
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Radiation induced when a particle passes between two media
Also used to distinguish between particle types
Used in ATLAS tracking
Reconstructing an energetic collision
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In order to understand a collision we need to know
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When did the collision happen
The directions of final state particles
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The momenta and energy of final state particles
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Charged particle momenta from bending in B field
Neutral energy from EM or hadronic energy deposition
Velocity from TOF, dE/dx or Cerenkov angle
Energy and momenta of unstable particles from conservation laws
What type of particle?
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Ionization trajectories of charged particles
Shower position center for neutrals
Specific interaction – EM shower for electrons, lack of it for muons
Mass calculation from momentum and velocity
Particle spin? From decay angular distribution
Lifetime? Secondary vertex and proper decay time reconstruction
Important detector characteristics
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Time resolution t
Spatial resolution x
Energy resolution E
Detection efficiency 
Misidentification probability
Two track resolution x
Detector characteristics derived from the
above
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Momentum resolution from x and the B field integral
Velocity measurement resolution
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From t if by TOF
From E if by dE/dx
From x if by Cerenkov
Cost, stability (aging) and longevity are also important for detectors
Gas wire chambers
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Detection of ionization on a particle trajectory by electrons
drifting to a wire at high potential is known since Rutherford
built a gas tube with a central wire in 1900
At a high potentials the drifting electrons are accelerated
and ionize additional atoms in their path
An avalanche is formed, creating amplification >105
In MWPCs (G. Charpak, Nobel prize 1992) a plane of anode
wires at high potential is arranged between two cathodes
with amplifying gas between.
MWPC and TGC
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A particle passing in gas will leave a trail of electron clusters (+
ionized gas atoms). The electrons will drift in the E field towards
the closest wire, and will create an avalanche and charge on
the wire. The charge is read by readout electronics.
Since the signal arrives from the closest wire to the particle
passage, the “hit” resolution is the distance between wires.
Parallel to the wire direction the position can be obtained by
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Charge division between the wire ends (resolution 1% of wire length)
Difference in time of arrival on the 2 sides (resolution ~3 cm)
Measuring the induced charge on pick-up strips on the cathode
(resolution 30-100 mm)
With the last method there may be
ambiguities
In ATLAS the end-cap muon trigger (TGC) is made this way
Drift chambers
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In drift chambers we measure the time between the passage of
the energetic particle and the signal arrival to the wire.
This allows to estimate the distance
from the wire where the cluster was
produced, providing an accurate hit
position measurement
The electron drift velocities is ~50 mm/ns with little
dependence on the field – the position resolution is 50-200
mm
Traditionally large drift chambers surrounded the IP, now
largely replaced by semi-conductor trackers
The ATLAS Monitored Drift Tube (MDT), the precision muon
chambers, are a kind of drift chamber
Semiconductor trackers
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Charged particles produce electron-hole pairs in O(nm) thin reverse
bias junctions – ionization again
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The high electron density and low ionization potential (3 eV compared to
30 in gas) result in large signals in thin sensors without the need for
multiplication
The electrons/holes are collected on electrodes subdivided in thin microstrips or pixels of 20-100 mm
The detectors are fast because of the short distances
The charge is collected via tiny bump bonds connected to the readout
electronics
Basic particle identification
Advanced particle identification
dE/dx
Ring Imaging Cherenkov
Threshold Cerenkov
Comments on measurement accuracy
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Measuring a charged particle trajectory in a magnetic field
is an accurate way to measure momentum and direction
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At low energy, an EM calorimeter is less accurate E  10%
E
E
At high energies the EM calorimeter is competitive, but
since it’s far from the interaction point, the creation vertex
of the particle is unknown
Semiconductor trackers are very accurate but expensive
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Charged particles are easier to detect accurately
This affects which decay channels to measure
Readout is an issue, especially for pixel detectors
Many dense readout channels required
Very fine connection of readout to sensor - difficult
Silicon detectors used together with coarser
measurements
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In ATLAS with transition radiation tracker
Reconstructing short lived particles
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Reconstruct from decay products
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Need decay channels with easily
identified final state
Background
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Identify possible decay products
Calculate invariant mass
Reconstruct secondary decay vertex
b from D0
Combinatorial background from unrelated tracks falling randomly in
the mass window
Particle misidentification (fake muons or electrons)
Misaligned detector causes widening of invariant mass – more
background
Secondary vertex reconstruction for Ks, , b-hadrons
Impact parameter cuts in reconstruction may reduce
efficiency for Ks, 
The ATLAS detector
η
We work in the coordinate system , , z
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Inner Detector
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The ATLAS Inner Detector (ID) is inside a 2T solenoid magnet
There are 3 detector types:
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semi-conductor pixel
semi-conductor strips
transition radiation
tracker
The pixel and SCT will
provide a few very
accurate points
The TRT will provide
continuous tracking –
36 points
Each contributes similarly
to the resolution
Pixel detector
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3 barrel and 8 disk layers of 140 MILLION pixels on 2228
Silicon semiconductor modules
The 140 MILLION channels are read out providing a
resolution of 10 m in r- and 50 m in z
SCT
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SCT is designed to provide eight precision measurements per
track in the intermediate radial range
contributing to measurement of
 Momentum  Impact parameter  Vertex position
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In the barrel SCT eight layers of silicon
microstrip detectors
The end-cap modules use tapered
strips with one set aligned radially.
TRT
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The Transition radiation Tracker is based on the use of
straw drift detectors – like miniature MDTs
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can operate at high rates due to their small diameter and the
isolation of the sense wires within individual gas volumes
Electron identification capability is added by employing
Xenon gas to detect transition radiation photons created in
a radiator between the straws.
Each straw is 4 mm in diameter
and equipped with a 30 µm
diameter gold-plated W-Re wire
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The barrel has ~50,000 straws
The endcaps have 320 000 straws
Calorimeter
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The EM calorimeter, and part
of the Hadron calorimeter are
made of an accordion like
arrangement of lead radiator
and liquid argon measurement
medium
There are over 100000
channels in the barrel and
70000 in the endcap
The calorimeter takes part in
the level 1 trigger
H
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Why is this channel so difficult?
The final state is 2 neutral particles
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Almost every p0 decays into 2 photons
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No momentum and direction measurements in the tracking detector
are available
E 10%
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Photons shower in the EM calo, with energy resolution
E
E
The invariant mass of a pair of photons has to be calculated – mass
resolution is related to the single particle momentum resolution
We expect a wide distribution
There are many p0 produced in each collision
Highly boosted p0 produce  very close to each other
The calorimeter has to be highly segmented to tell one  from 2 
p0  is a big combinatorial background under the H peak.
This channel dictated the design of the EM calo
H
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Signal and background
After background subtraction
Tile hadronic calorimeter
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In the central region <1.3 there is also a scintillating tile
hadronic calorimeter
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The tile calorimeter is
highly segmented
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Steel is the absorber material (radiator) causing showers
Particle showers are sampled by tiles of scintillating plastic which
emit light when charged particles go through them.
The light pulses are carried by wavelength shifting optical fibers and
converted to electronic signals
0.1x0.1 in ,
3 radial segments
Can help identifying m
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Narrow (ionization)
signal continuing
into the outer layer
Jet energy scale
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The signal in the calorimeter requires translation into the
energy of the particle
This translation is particle type and detector region
dependent
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Jets are more complicated still
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Pions leave a different signal than electrons for the same energy loss
Different sampling depths result in different calibration
p0 and charged p, but also muons/electrons/neutrino
These calibrations are started at test-beams
Continue using simulation
Will continue using well understood samples
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Z+jets
“Missing energy”
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The total cm energy will be 14 TeV
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Hard interaction energy unknown and differs by event
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Most final state energy will go down the beam-pipe unmeasured
Products characterized by momentum transverse to the beam-line
pT
No way to measure “missing energy” out of unknown total
What we measure is the pT imbalance in the final state
No missing ET
Missing ET
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Z 0  ee
u~R  ~10  u
~
s  ~10  Z  s  ~10  d  d  s
Measured as vector sum
of energy deposition in
calo cells
Characterizes events with
particles that leave the
detector unobserved
Missing ET continued
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What particles result in missing ET?
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Neutrinos
The SUSY LSP or neutral stable NLSP
Muons?
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Charged stable NLSP?
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They leave little energy in the calorimeter, so if not accounted for, will produce fake
missing ET
They are not accounted for in the calorimeter trigger so high pT muons can produce
a missing ET trigger
This should be corrected at Event Filter or offline
Fake missing ET
Like muons
No other source of missing ET in event
Detector malfunction can fake missing ET
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A “hot” or “dead” area in the calorimeter will
change the ET balance artificially
Particles going through cracks also create
fake missing ET
H  m  m e e
Missing ET resolution
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A lot of work on understanding missing
ET and its dependence on
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topologies  jet energy calibration  e/p/
energy corrections  crack and dead
areas  Jet punch through seen as muon
The ATLAS detector – The Muon
spectrometer
Trigger chambers
Trigger chambers
 RPC and TGC are used
for triggering, measure
2 coordinates,  and 
Precision chambers
 The MDT are used for
precision
measurement and
measure only 
 The CSC measures 
Precision precisely and 
chambers coarsely
Tracking requires combining
the information from all subdetectors
Monitored Drift Tube chambers
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Precision measurements in the muon spectrometer are
performed by chambers of Monitored Drift Tubes (MDT)
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The basic elements are aluminum tubes with a 3 cm diameter and a
wire at HV in the middle
The basic measurement is the drift time of ionized electrons to the
wire
The measurement resolution is ~80 mm
Each chamber has 2 superlayers, each with 3 or 4 layers of tubes
Hit radius reconstruction in the MDT
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The radius from which the electrons drift to the wire is calculated from the
time measurement
These R-T relations have to be calibrated constantly to maintain the
resolution
t0m
tdrift
R=R(t-t0m)
=R(tdrift)
Segment reconstruction in MDT
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The segment is tangent to the radii
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To maintain resolution we also need to
know exactly where each tube is
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alignment is a big issue
t=t0m+tdrift
Reconstructing muons in ATLAS
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Muons appear in many heavy particle decays
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They are by far the easiest to identify
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Just look for energetic particles outside the calorimeter
Their momentum may be measured in the muon
spectrometer outside of the mess of tracks in the inner
detector
The experiment output is a list of hit
channels and some information on the
hit
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this makes them interesting
For MDT – drift time
For trigger chambers – Beam Crossing ID
For CSC – pulse height distribution
Noise hits too…(MDT)
Muon reconstruction in ATLAS detector
MDT
RPC/TGC
m
+++
Barrel Toroid
MDT
RPC/TGC
+
+
+
++
m
+
+
Calorimeter
Inner Detector
End Cap
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Toroid
+
+ +++ +
++
++
Muon reconstruction in ATLAS detector
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In ATLAS, muon tracks can be reconstructed independently
in the muon spectrometer. A search for all m is performed
+++
Track reconstruction in the
Muon Spectrometer is done
with MOORE or MuonBoy
+
+
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+
++
++
++
+
+ +++ +
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Large volume toroidal field –
bending in η direction
Low detector occupancy
Accurate high momentum
measurements
Muon reconstruction
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Short segments of the trajectory are found is the MS stations
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The segments are then connected into tracks
We know the B field
and thus the trajectory
of a m of a given momentum
The momentum is
obtained from the
track fit
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Muon reconstruction in ATLAS detector
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Similar programs reconstruct tracks in the Inner Detector
Reconstruction of all charged
particles is done in the Inner
Detector
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High track multiplicity
Bending in φ direction
Muon reconstruction in ATLAS detector
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Following this, muon tracks or segments are combined with
inner detector tracks to obtain the muon momentum at the
interaction point
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+
+
+
++
MuId/Staco
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Extrapolate muon tracks
back to the primary vertex
region
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Combines them with Inner
detector tracks
m
+
+
+
+ +++ +
++
++
Muon Reconstruction
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A different program, MuGirl, identifies muons by associating
muon hits and segments to an inner detector track in order to
flag the track as a muon
[1] Initialize Muon candidate from ID track parameters
[2] Extrapolate track to Muon Spectrometer chambers
[3] Look for hits in a road around the track extrapolation
[4] Make segments from hits
[5] Improve extrapolation by
using segment information
[6] Collect hit & segment
information to identify muon
[8] Select “muon like” candidates
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This method works better
for low pT muons
H4m, 2m2e
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Best channels for finding the Higgs
Good trigger with high pT muons
Low pT muon reconstruction an issue for low mass Higgs
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Lowest pT muon under 10 GeV for many events
Could require 2 high pT muons w Z mass and collect additional ones
Triggering at the LHC
Event rate 
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Level-1 
Level-2 
The LHC event rate is too high to collect
Selection of physics signals by
identification of objects that can be
isolated from the high particle density
environment.
Object
What physics?
e
Higgs, new gauge bosons, extra
dimensions, SUSY, W, top, Bphysics,

Higgs, extra dimensions, SUSY, Bphysics
m
Higgs, new gauge bosons, extra
dimensions, SUSY, W, top, Bphysics
Jets
SUSY, compositeness, resonances,
B-physics
Offline Analyses
The ATLAS Trigger
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The 3-level trigger selects interesting events at an output
rate of 100 Hz from the input rate of 40 MHz
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The Level-1 (LVL1) trigger – 40 MHz to 75 KHz
hardware
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The Level-2 (LVL2) trigger – 75 KHz to 5-10 KHz
software
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Uses custom electronics to make the decision in hardware
Uses low granularity data from a subset of trigger detectors
Identifies Regions of Interest
Identifies bunch crossing of interest
Has 2 msec to complete each selection
Uses the full granularity data
Starts from Regions of Interests flagged by LVL1
Only data requested by the algorithms are read out.
The average time budget ~10 ms.
The Event Filter (EF) – 10 KHz to 100 Hz
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Uses complete event information
Time budget of a few seconds.
Accepted events are written to mass storage
Goal of the level 1 muon trigger
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Select m from b, t, W, Z, H
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Look for muons from the
interaction point
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pT of muons from different processes
Low pT for b pT>6 GeV
High pT for Higgs pT>20 GeV
Eliminate cavern background
Eliminate beam halo and
cosmic muons
Reduce background from
decay in flight of p/K
Trigger scheme
Endcap muon trigger – more detail
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In passing the b field
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A m will bend up
A m will bend down
The window between them
contains all m with
pT>threshold
For large pT the window
becomes small, and we
need a longer lever-arm to
resolve it – add another
station
Windows
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pT thresholds are determined from
the maximal acceptable rate
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Each trigger type gets a bandwidth
Flexibility is required
Window sizes for each pT/η/φ are
found from simulation
The actual selection is done in
hardware
Endcap muon trigger –
the electronic implementation
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The charge created in the
chamber is digitized by an ASD
The digital signal passes in
cables 2-10 meters long
They are received at the trigger
electronics PS-Pack ladder on
the TGC sector
There is 1 PS-Pack ladder for each 1/24 triplet and doublet-pair
wire
pivot
doublet
pp
Slave boards
wire
doublet
inner
doublet
triplet
High pT
boards
electronic path
scheme
wire
wire
triplet
strip
pivot
doublet
strip
doublet
inner
doublet
triplet
strip
strip
triplet
sector
logic
Level-1: Calorimeter
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Calorimeter Trigger
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looking for e/ + Jets + t objects
Using trigger towers of Hadronic and
Electromagnetic calorimeters
The requirement for a trigger
object:
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The RoI cluster is a local maximum
The most energetic cluster > ET
Total ET in EM isolation < EM
Isolation Threshold
Total ET in Hadron < Hadronic
isolation threshold
Example of e/ trigger
algorithm:
Missing ET trigger
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At level 1 – jet energy sum processor computes total scalar
ET, Ex and Ey
Missing ET not an inclusive trigger but combined with single
jet or electron/photon or hadron/ triggers which may not
pass level 1 by themselves
Envisioned missing ET thresholds could start ~70 GeV
Does not fit the RoI mechanism – global by definition
At level 2 unpacking the data from 200,000 calorimeter
cells is prohibitive
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corrections for known level1 deficiencies
calculating missing ET from jet RoIs
It may be too slow even for the EF, in this case the missing
ET may be calculated from jets rather than calo cells
The CMS trigger


CMS has a 2 level trigger
LVL1




Uses muon chambers and calorimeter
Finds e, , , jet, m candidates above thresholds
40 MHz  100 KHz
HLT




Uses algorithms similar to offline
100 KHz  100 Hz
Inclusive b,c, trigger (high pT jet)
Partial reconstruction of exclusive decays around μ ROI
The ROI mechanism
m
m
e
m
e
1 in 5 000 000 events is kept




H  m  m e e
u~R  u  ~10
~
d L  d  ~20  d  m   m   ~10
At level 2 the processors run algorithms seeded by level 1 Regions of
Interest (RoI)
For each RoI the algorithm fetches the relevant data from subdetectors
which did not participate in the level 1 decision
Level 2 algorithms are run in a sequence, refining the decision in stages
They create new seeds for the Event Filter
Trigger issues for b-physics performance

LHC is geared towards “Discovery Physics”


B-physics performance is impacted strongly by trigger menus





Level-1 is in hardware – designed for 40MHz100KHz
The level-1 trigger for B-physics is based on one or more muons
Acceptable trigger rates in ATLAS and CMS have been reduced
due to “staging” of high level trigger processing power


Characteristic B-physics triggers are at low pT
The experiments have multilevel triggers


B physics is a side show
Envisioned trigger menus include 2 low pT m or one higher pT m
Algorithms are developed for recovery of events at level-2
First luminosity is expected to be lower and that will enable
collecting 6 GeV single muons at the beginning
Detector calibration depends on channels that are also good
for B Physics - J/ and m
Algorithms to recover events at level-2

The level 1 trigger output of is ~20 KHz of events with at
least one muon with pT > 6 GeV



At the level 2 trigger this rate must be reduced by x100




4 KHz from b events
Most triggers from cavern background or muons from K/p decays,
This may be achieved by confirming a muon in the Inner Detector in
addition to confirming it in the Muon Spectrometer
Then cutting harder on pT
This selection criterion removes many interesting b events
We would like to achieve
higher efficiency for the
“gold” channels (J/) at
level 2
After
Level-2
Example of level 2 algorithm



The rate of J/ and m+m–
events is low enough for the
second level trigger
A di-muon trigger will allow an
effective selection of channels
with J/  m+m– and rare di–m
b decays
One way is dimuon trigger at
level 2 based on a single muon
trigger at level1
The second muon, usually lower
pT, is found by searching in an
extended region of interest
around the level 1 RoI
Cross section, (nb)

single-muon
h
b
c
b
h
J/
c
@1033cm-2s-1
all
all
di-muon
Dimuon recovery at level 2
LVL1 pT(m) > 6GeV
RPC/TGC
MDT
m RoI ( φ, η )
μ
Create the pair of tracks
with opposite charge
Results from this algorithm
level 1
muon
RoI
Enlarged
muon
RoI
Efficiency of J/ψ (relative to level 1)
vs. fake rate for different cuts
The efficiency to find J/ψ vs. the size of
window opened around the level 1 μ RoI
The efficiency of J/ψ identification
vs. pT of the lower pT muon
J/ψμ(pT>6GeV)μ(pT>3GeV)
J/ψμ(pT>2.5GeV)μ(pT>4GeV
)
Detector issues for new Physics
The case of a new long lived particle

Heavy charged long lived particles exist in many theories
beyond the standard model


A case in point is GMSB where the stau is the NLSP and couples
weakly to the gravitino.
The signal we look for is a charged particle with low 



hence referred to as stau
Any slepton would have the same signature
R Hadrons also have strong interactions
An existing lower limit gives the stau M>100 GeV/c2
 Imagine a 100 GeV/c2 stable charged particle going through
a detector with pT of 100 GeV/c
This cannon-ball should be easily visible – we can’t miss
it…
Think again!!

How would the ~ look in ATLAS

A very slow stau would lose a lot of energy by ionization



BUT




A 100 GeV/c2 stau with pT < 25 GeV at eta=0.1, would be absorbed
in the calorimeter.
Likewise, a 200 GeV/c2 central stau with pT < 35 GeV
A particle with >0.5 would lose less than 7 GeV
A particle with >0.8 is almost minimum ionizing
Particles with <0.6-0.7 will arrive in the muon spectrometer
with a different beam crossing
Signals in the ID and Muon Spectrometer may be modified
due to higher ionization
The following study was done for a stau with a mass of 100GeV/c2 as
introduced in GMSB point 1 of CERN-TH/2000-206
Timing issues for a heavy charged particle




ATLAS length > 20m & Collision period = 25 ns  3 events coexist in the
detector at the same time
To match correctly event fragments from different sub-detectors BCID is
crucial
BCID is based on time measurements, each detector unit is calibrated with
respect to particles which move almost at the speed of light ( =1)
(stau)<1 so it may be marked with the wrong BCID
Delay in arriving to the muon spectrometer wrt a muon in units of BC
~ and LVL1 - the case of a “normal trigger”

Assuming a non stau trigger on event number N
The stau data is
associated with
event N+2
The stau data is
associated with
event N+1
Muon trigger chambers (TGC and RPC)
should read out BCs N, N+1, N+2.
calorimeters
The MDT always reads out many BCs.
The case of a calorimeter trigger
~
 A  with pT > 75 GeV can give a missing ET trigger

The resulting readout requirements are the same as above
~ and LVL1 - The case of a muon stau trigger

~~ with p > 30 GeV can give a high p
 triggered event number N.
A
T
T
muon trigger. Assuming the
The muons were
here in event N-2
All particles
were here in
event N-2

All sub detectors
have to read
events number
N, N-1, N-2
~



and LVL1 - conclusion
Different trigger scenarios result in different readout
requirements
The different sub-detectors have the ability to acquire data
from different (more than one) BCs.
BUT

Readout programming can not be changed by trigger type.

Moreover, it can not be changed during ATLAS run time
the decision of which events are to be read by each
sub detector will have a dramatic effect on ATLAS’s
ability to discover the ~
Possible data taking mode



Muon spectrometer collects data from events N, N+1 and N+2
Inner Detector collects data from events N, N-1 and N-2
Calorimeter collects data from events N, (N-1 and N+1)
Lost Data

If the stau produced a muon trigger, and there was also a
muon in the event (that didn’t trigger), then the muon
spectrometer data related to that muon is lost
Open questions



Is it possible to acquire data from more events at all
levels?
What needs to be done to actually do it?
How does this data taking mode effect the data size ?
Identification of the ~ in RPC



The RPC chambers have great time resolution - 3.125ns
The BC and the time within the BC are known it is possible to
calculate the Time Of Flight (TOF) from the interaction point
Apply the TOF calculation to the barrel LVL2 algorithm muFast
to get initial estimation of the particle’s speed
 Estimation in muFast for Different generated 
The RPC TOF can be estimated
at the level 2 trigger

An event identified at LVL2 as containing a slow high pT
particle could be moved directly to a rapid analysis track
reject
reject
~97%
~80%
of of
thethe
muons
muons
Hit radius reconstruction in the MDT


The long time window of the MDT guarantees that data of low 
particles will be saved.
The measured hit radius is incorrect
t0m+t
t0m
tdrift
tt=t
=t+t
+t+tdrift
stau0m
0mdrift
RstauR=R(t-t
=R(tstau-t0m0m) ) =
R(tdrift
+t)>R
=R(t
drift)
Segment reconstruction in the MDT


The segment is tangent to the radii
Larger radii result in


Badly fitted segment
Wrong direction segment
A  reconstruction algorithm






Relies on long time window of MDT and BCID from ID
Identify penetrating particle by associating muon hits and segments
with extrapolated ID track
Loop over possible t0s
 Change MDT digits’ time and hence radii.
 Create MDT segments from the re-timed digits.
Choose the segment with the best 2.
Obtain the real t0 (TOF) as the one
that minimizes the 2
Calculate 
GMSB – Example points
Background
Mass reconstruction


Main background is from muons
with pT>40
(m>40)/(stau point 1) ~ 25
  distribution not from model
Offline analysis – Signal and Background
Preliminary Results

Minimal cuts



<0.99
Reasonable 2
Segments in all the 3 stations
No cuts

With cuts
Background will be reduced by better  reconstruction
Heavy charged particle summary



If nature cooperates, we have a chance to find such a
particle
However, this requires paying attention to details of detector
and trigger operation
Some modifications are needed to previously envisioned
operation
Summary





We expect/hope the LHC will be an exciting place to do
physics – the new energy gives space for discoveries
Detector knowledge was required to design a detector (two)
which can find the interesting physics
Understanding the detector will help us in our analysis
Theorists should understand what measurements are
more/less possible as a guide to choosing the channels
they calculate
Theorist could use this info to understand how to assess
experimental measurements