Download The CMS Fast Simulation

The CMS Fast Simulation
Do we need a Fast Simulation ?
How does it work ?
tracking
calorimeter
muons
Performance
Conclusion
Why do we need a Fast Simulation ?
Large samples of simulated data are needed
to develop reconstruction algorithms, analyses
to adapt the trigger tables to new conditions (like 14->10 TeV)
in addition when we have data, to determine the efficiencies on the signal,
to determine some background contamination, to perform scans of the
parameter space, evaluate systematic errors....
why producing only one million events when we could produce one billion
of events of the same quality ?
In the physics TDR, many analyses relied totally or partially on FAMOS,
the previous version of the Fast Simulation
the new version is, of course, much better
it is not only a simulation, it also produces reconstructed quantities
(tracks, RecHits ...). The standard reconstruction algorithm are used as much
as possible
The goal is to be as fast as possible (possibly 1000 times faster than the slow
simulation/reconstruction) while keeping the same level of accuracy
Track propagation, Interaction with the tracker material
TEC
TOB
TIB
A simplified interaction geometry is used !
with some details though 
Active and passive layers are modelled
The complete magnetic field map is used for
the track propagation between two surfaces
TEC
Pixels
Material effects simulation
R. Ranieri
Do we need to simulate the material effects ?
magnetic field
4T
~35% of the electrons radiate more than 70% of
their initial energy before reaching the ECAL
the energy is spread in j  impact on the cluster shape
Simulating properly the material effects is not
only needed, it is essential !
Bremsstrahlung simulation
The Brem photon emission probability and spectrum are calculated
analytically, layer by layer
The layer thickness is tuned to reproduce the number of photons in the
Geant-based simulation:
the photon energy spectrum is beautifully reproduced...
(incidentally , this tuning reproduces the actual layer thickness in x/x0)
Absolute normalization !
Single electrons pT=35 GeV/c
Flat in h
Fast Simulation
– Slow Simulation
Material effects simulation
The Bremsstrahlung, the photon conversion, the multiple scattering
as well as the energy loss and the in-flight decays are simulated
analytically
The nuclear interactions are of utmost importance ! 20% of the pions
undergo a N.I in the tracker
consequence on the pion track reconstruction efficiency (several percent
at 1 GeV)
A single tau event where
a pion undergoes a nuclear
interaction in the tracker
(full simulation)
Nuclear interactions simulation
total
The elastic and inelastic cross
sections are taken from expt'al
measurements (PDG)
elastic
Full Geometry
The tracker layer thickness is
expressed in terms of /0
FAMOS
0.31 x/X0 (total) or 0.25 x/X0 (inelastic)
not strictly true, but good approximation in the tracker acceptance
Data files of inelastic N.I have been created
2.5 million N.I saved, 9 different hadrons, 1<E<1000 GeV
when a N.I occurs, a N.I is picked up randomly in the relevant energy
range
a rotation around the particle direction is made (extra randomness)
Nuclear interactions
Number of nuclear interactions
for 500K 15 GeV pions
Fast Simulation
− Full Simulation
A single tau event where
a pion undergoes a nuclear
interaction in the tracker
(fast simulation)
Tracking SimHits
The hits are located on the detailed
tracker module geometry (propagation to
the closest active layer modules)
only for charged particle with p > 0.5
GeV/c
create a SimHit if an intersection
exists
this allows the mis-alignment to be
simulated
The energy loss is simulated as well
Tracking RecHits smearing
The SimHits are then smeared
a layer-dependent Gaussian smearing is applied in the strips
in the pixels, the smearing is done according to cluster-multiplicityand incidence-angle-dependent position resolution distributions
(obtained from the full sim – will be obtained from the data)
the result is turned into tracking RecHits
Resolution function
vs. Fast Sim
Track reconstruction in the fast simulation
Two possibilities
up to now, a "fast tracking" has been implemented
the seeding efficiency is emulated : check that at least one
combination of hits fulfills the seed selection criteria
the hits belonging to a given track are fit (standard fitter)
the pattern recognition is also emulated (outlier rejection) : remove hits
with large contribution to the c2 and redo the fit
as a result, there are no fake tracks (the fraction of fake tracks with
≥8 hits in the standard tracking is well below 1%)
special treatment required to mimic the pattern recognition
behaviour in the case of in-flight decays/N.I.
the possibility to run the full tracking on the Fast Sim output is being
implemented
Track reconstruction : comparisons in tt events
Fast
Full
Track quality
Calorimeter simulation
At this level, the particles have been propagated, they
interacted with the tracker material, new particles have been
created... So we are left with the list of the particles reaching
the ECAL
all the showers are simulated individually using a shower
parameterizatio à la GFLASH
to properly simulate the detector effects, which are
essential, the showers are placed in the (crystals, towers,
strips, cracks, leakage..) detailed geometry
The CaloHits thus obtained are then turned into RecHits
(noise, zero-suppression...)
A parameterization à la GFLASH is also used for the hadrons;
the response and resolution of the HCAL is taken from the fullsim
Electromagnetic showers : test-beam
•
The simulation is done in two steps
– the shower is simulated as if the ECAL was an homogeneous medium
– then the shower is transported into the actual ECAL, taking into account
several detector effects which are essential (cracks, leakage, magnetic
field...)
– it is very challenging to do it quickly. In the end ~6ms for a 40 GeV shower
•
The lateral shower profile can be checked/tuned on test-beam data
x (mm)
y
H4
FAMOS
|y-yM| < 2 mm
y
xM
beam
x (mm)
|x-xM| < 2 mm
y (mm)
M
x
Electron reconstruction
•
A Gaussian Sum Filter algorithm is used for the electron track fit
Single electrons
Total Brem energy, as measured
by the tracker
Reconstructed Z-mass
an excellent agreement is obtained
the electron fake rates are also well reproduced
(at the level of precision allowed by the Full sim samples statistics)
Hadron simulation and jets
The single hadron response has been retuned on single pions not undergoing
an inelastic interaction in the tracker Di-jets event
ETrec / ETgen
40 < pT < 50 GeV
iterative cone R=0.5
600< pT < 800 GeV
jet EM-energy
HB
HE
HF
Slow
Fast
the error bar is
actually the RMS
jet HAD-energy
A very good agreement is obtained for jets for all pT's and all h's !
... but the agreement with test-beam data for single particles has
to be improved
HB
Muons
•
Two versions available
– Parameterized (resolution, efficiencies): the matching with the trackertracks being done by the standard algorithm
– a tracker-like simulation: simulating the hits, propagation in the iron..
• Then apply standard digi+reco.
Parameterization, used
for the L1 simulation
Muon from SimHits will become soon
the default, alowing the
mis-alignment to be simulated
Topological variables
Usually, the “4-vector smearing”-based
fast simulations fail at correctly reproducing
the MET as well as the topological variables
here the agreement is remarkably good !
(mostly thanks to the implementation of
the N.I. in the tracker)
SUSY events
b tagging
The track counting, track probability and secondary vertex algorithms are
available
b jets
udsg
Difference at 10-4 level !!!
(will be recovered; slightly
different seedings in the
two versions)
Fraction of the jet energy
carried by the tracks linked
to the reconstructed seconda
vertex
combined SV
algorithm with
MVA setup
udsg -efficiency
charm -efficiency
b tagging : final results
b-efficiency
Very good agreement
b-efficiency
Pile-up simulation
• Only the in-time pile-up is implemented (no plan to do
the out-of-time)
• The generated particles of the pile-up events (with a
smeared vertex) are added to the signal event
particles
• only the primary particles are saved (home-made format rootfiles)
• the decays and a rotation are done in the Fast Sim (extra
randomness)
• 1 million of pile-up events is available by default on disk (only
700MB!)
Other goodies
•
The trigger is available
– the real L1 emulators are used
– the standard HLT code, using the Fast Sim “special” tracking is used,
thus
–
allowing to use the Fast Sim for trigger menu optimization
•
Tracker mis-alignment, calorimeter mis-calibration
Fast only
ideal alignment
Fast vs. Full
Leading jet
0/pb
10/pb
100/pb
IP/sIP (2nd track)
Timing
•
With the current version, the simulation of a physics event, with
pile-up and HLT takes 2-3 s
– the timing is actually dominated by the reconstruction
– the simulation (which includes the tracking) takes ~400ms
•
In addition, the full job (generation->HLT->reconstruction) can
be done in one go, with the possibility to run the reconstruction
only on the events that pass the HLT
– a half-a-billion events production with Madgraph has recently been
done in less than two weeks
– an similar one at 10 TeV is planned
Summary
•
The CMS Fast Simulation is widely used by the collaboration
–
–
–
–
•
the full compatibility with the standard software
the flexibility and the speed
the precision
the “tunability”, which will be of utmost importance when the first
data arrive are major assets for this simulation, even if there are
still items to develop,or to improve
The maintenance is heavy because the reconstruction software
is evolving quickly
– In addition, the changes in the standard tracking have to be
carefully followed and implemented in the Fast Sim tracking
•
Developing a Fast Sim is a great experience: one learns a lot
on the physics in the detector and on reconstruction algorithms