Diapositiva 1

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Event generators
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Simulation of pp events
Many programs exist for the simulation of pp
collisions at high energy
For the study of global event properties,
simulations may be carried out by PYTHIA or
HERWIG event generators
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What is an event generator?
Event generators are programs suitable to
generate events as detailed as they could be
observed by an ideal detector. The output is in
the form of an event, i.e. a set of particles
with their momenta, exhibiting average properties
and statistical fluctuations as in real data,
provided by Monte Carlo techniques used to sort
out the informations according to probability
distributions
A typical output from an event generator may be
the following Particle Particle type
px py pz 1
ID1 .. .. ..
2 ID2 ..
.. ..
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An example of output from PYTHIA
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Why use event generators?
To provide a feeling of the type of events one
may expect to find in real data To estimate the
production rates of specific processes in real
events To help in the planning of new detectors
and estimate the detector performances To train
on simulated events the strategies for the
analysis of real data To estimate detector
corrections (acceptance, efficiency,) To provide
background events for rare processes
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Generated events may be a convenient input for
detector simulation programs (GEANT,) to
understand how the event would be seen in a real
detector
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PYTHIA event generator
PYTHIA can generate different types of
high-energy events. It is based on perturbative
QCD, but includes also soft interactions, parton
showers, multiple interactions, fragmentation and
decays. Due to the composite nature of hadrons,
several interaction between parton pairs are
expected to occur in a hadron-hadron collision.
Since the understanding of multiple interactions
is still very rough, several approaches (Models
1-4) may be used. One of the main parameter in
this model is ptmin, a sort of cut-off introduced
to regularize cross sections which diverge at
pt-gt0. To compare PYTHIA with data, ptmin must be
chosen to reproduce the observed charged particle
multiplicity. The result depend on c.m. energy,
multiple interaction model and parton
distribution functions.
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PYTHIA predictions for charged particle
multiplicity at ?0 as a function of c.m. energy
and different tuning of the model.
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PYTHIA predictions for pseudorapidity and
transverse momentum distributions charged
particle and different tuning of the model.
No large differences observed in pt-distribution
for different tuning of the model
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However, large differences are observed in the
multiplicity
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HERWIG
HERWIG is a general purpose event generator,
which takes into account hard lepton-lepton,
lepton-hadron and hadron-hadron hard scattering
and soft hadron-hadron scattering Some
difference is observed with respect to PYTHIA
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HERWIG Solid line
PYTHIA Dashed line
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In conclusion, no single event generator is able
to describe all the details of the available
data. Work is still in progress to refine the
models and tune their parameters, to try to
reduce the uncertainties in the predictions at
LHC energies. A lot of refinements came after
first data from RHIC
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What about event generators for heavy ion
collisions? A lot of different codes HIJING,
VENUS, DPMJET, SFM, For a short summary and
comparison between different model predictions
see the ALICE Physics Performance Report Vol. I
J.Phys. G 30(2004)1517-1763
Strong differences observed between different
models
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HIJING (Heavy Ion Jet INteraction Generator) and
parametrized HIJING
HIJING combines a QCD model for jet production
with the Lund model for jet fragmentation Hard
and semihard parton scatterings with pt up to a
few GeV/c dominate high energy heavy ion
collisions HIJING model is especially suited to
treat mini-jets in pp, pA and AA collisions at
high energies HIJING is able to reproduce many
inclusive spectra, two-particle correlations
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The formulation of HIJING is derived from the
FRITIOF and DPM models at lower energies (c.m.
energy around 20 GeV) Hadronic interactions were
treated according to QCD processes in
PYTHIA. Binary scattering with the Glauber
geometry for multiple collisions were used to
extrapolate from pp to pA and AA collisions Two
important aspects of HIJING Jet quenching
Nuclear shadowing
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Jet quenching Jet quenching is the energy loss
by partons in nuclear matter. It is responsible
for the increased particle multiplicities at
central rapidities
Nuclear shadowing Shadowing describes the
modifications of the free nucleon parton density
in the nucleus. Shadowing results in a decrease
of the multiplicity.
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HIJING 1.36 predictions for Pb-Pb central (blt3fm)
collisions at c.m. energy of 5.5 A TeV
With jet-quenching
Without jet-quenching
Pseudorapidity distribution
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HIJING 1.36 predictions for Pb-Pb central (blt3fm)
collisions at c.m. energy of 5.5 A TeV
Solid line With jet-quenching
Dashed line Without jet-quenching
Pt distribution
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HIJING 1.36 predictions for Pb-Pb central (blt3fm)
collisions at c.m. energy of 5.5 A TeV
Solid line With jet-quenching
Dashed line Without jet-quenching
Net baryon pseudo rapidity distribution
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Different scenarios for jet quenching in HIJING,
inspired by recent RHIC results at cm energy of
200 AGeV
New parameters decrease the expected charged
multiplicity at ?0 by 25
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Parametrized HIJING Sometimes a parametrized
version of HIJING event generator is used for the
simulation of heavy ion collisions, producing
only the most abundant particles (neutral and
charged pions and kaons) according to
parametrized rapidity and pt distributions with
proper mt scaling. This choice is usually good to
inject the bulk of the emitted particles into the
detector, to provide a background description of
the expected events in the detector, on top of
which one can superimpose specific particles,
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DPMJET (Dual Parton Model) event generator
DPMJET is an implementation of the dual parton
model for the description of nuclear interactions
based on the Glauber-Gribov approach. It treats
both hard and soft scattering processes in a
unified way. Particle production in the
fragmentation region is described by evaporation
processes of light nucleons, nuclei,
photons, Important features of DPMJET New
diagrams contributing to baryon stopping Better
calculations of Glauber cross sections
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DPMJET-II.5 predictions for Pb-Pb central (blt3
fm) collisions at 5.5 A TeV
Full linebaryon stopping
Dashed line without baryon stopping
The baryon stopping mechanism increases the
multiplicity by about 15
Pseudorapidity distribution
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DPMJET-II.5 predictions for Pb-Pb central (blt3
fm) collisions at 5.5 A TeV
Full linebaryon stopping
Dashed line without baryon stopping
Pt distribution
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DPMJET-II.5 predictions for Pb-Pb central (blt3
fm) collisions at 5.5 A TeV
Full linebaryon stopping
Dashed line without baryon stopping
Net baryon pseudo rapidity distribution
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SFM (String Fusion Model)
The main features of SFM are Soft interactions
described by the Gribov-Regge multipomeron
exchange Hard part of the interaction simulated
by PYTHIA Strings formed by gluon splitting
fragmented with JETSET Fusion of soft strings
included Rescattering of produced particles
included
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SFM predictions for Pb-Pb central (blt3 fm)
collisions at 5.5 A TeV (No rescattering)
Full line with string fusion
Dashed line without string fusion
Pseudorapidity distribution
Including string fusion reduces the multiplicity
by about 10
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SFM predictions for Pb-Pb central (blt3 fm)
collisions at 5.5 A TeV (No rescattering)
Full line with string fusion
Dashed line without string fusion
Pt distribution
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SFM predictions for Pb-Pb central (blt3 fm)
collisions at 5.5 A TeV (No rescattering)
Full line with string fusion
Dashed line without string fusion
Net baryon pseudo rapidity distribution
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Apart from the multiplicity and pt distributions,
these models exhibit differences also for other
observables
Pion transverse mass spectra
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Kaon transverse mass spectra
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Nucleon and antinucleon transverse mass spectra
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Inverse slope parameters obtained by fitting
transverse mass spectra by
Large differences observed from model to model
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Recent results at RHIC (Phenix Collaboration) for
different centrality selections
They are not reproduced by any of the existing
models !
Above 2 GeV pions and protons are comparable
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Predictions from HIJING
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Predictions from DPMJET
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Predictions from SFM
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Other event generators
Among other event generators widely used in the
heavy ion physics community, MEVSIM was developed
for the STAR experiment at RHIC to produce in a
fast way AA collisions. MEVSIM generates particle
spectra according to a momentum model chosen by
the user. Main input parameters Types and
number of generated particles Momentum
distribution model (pt and y-distributions)
Reaction plane and azimuthal asymmetry
Multiplicity fluctuations Specific signals
can be introduced on top of that (Event-by-event,
resonances, flow,)
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Quite often, one needs to superimpose some
specific feature of heavy ion collisions, which
theoretical models are not able to predict in
detail. One of such cases is the study of HBT
correlations, where one needs some specific
two-particle correlation at small relative
momenta. Correlation functions built with the
output of any event generator are normally flat
in the region of small relative momenta. HBT
processors afterburner introduce a two-particle
correlation at small relative momenta on the set
of generated events. To do this, particle momenta
are modified after generation, in order to fit a
specific correlation function.
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Correlation effects introduced in such a way
normally do not alter single particle
distributions and multiplicities, so that event
reconstruction procedures are identical with and
without correlation. However, tracking
efficiency, particle identification and momentum
resolution may be affected, since these are
sensitive to the details of the topology
involving particles at small relative momenta.
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Example of an HBT processor applied to MEVSIM
events
Two-particle correlation
Single particle distribution
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References
HIJING
DPMJET
SFM
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References/2
MEVSIM
PYTHIA
HERWIG
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Activity project Analyze pp or heavy ion
collisions simulated events from an event
generator
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• 0 20
• N.traccia pdg pt E pz
  py px theta
  phi eta y
• 0 5 3.84242 75.6509 75.4038
  0.471787 -3.81335 0.0509139 -0.123094 3.67055
  3.20778
• 1 -5 3.30503 67.5437 67.2954
  -0.751551 3.21845 0.0490729 2.91219
  3.70739 3.14853
• -523 3.05386 58.942 58.6215 0.226883
  -3.04542 0.0520475 -0.0743624 3.64852 2.95242

A real output from PYTHIA for pp collisions at LHC