3 /*! \page README_sim Simulation
5 The simulation encompasses the following tasks :
7 - Generation of MC particles (the kinematics of the event ends up in the TreeK
10 - Tracking particles through the detector using
11 the Virtual Monte Carlo, producing AliMUONHit objects, that end up in
12 the TreeH of MUON.Hits#.root file(s). This part is steered by AliMUON and its child
15 - Converting MC hits into AliMUONVDigit, called SDigits, that end up in the TreeS
16 of the MUON.SDigits#.root file(s). A S(ummable)Digit is a pad with its associated
17 charge, but no noise or electronics response function applied. Steered by AliMUONSDigitizerV2 class.
19 - Converting SDigits into Digits, by applying electronics calibrations. Actually, we de-calibrate
20 the digits at this stage, by adding a pedestal and dividing by a gain, more or less. Steered
21 by AliMUONDigitizerV3 class. Digits end up in TreeD of MUON.Digits#.root file(s). In addition,
22 for the trigger, we create AliMUONLocalTrigger, AliMUONRegionalTrigger and AliMUONGlobalTrigger objects
23 at this stage, that ends up in TreeD as well.
25 - Convert the Digits into RAW data, in a format that should be exactly the same as real data from the
26 DAQ. Performed by AliMUONRawWriter.
28 From there on, the reconstruction can proceed, in the very same way for real or simulated data,
29 as long as they are in RAW format.
31 \section sim_s1 How to run a MUON generation
33 You only need to run the simulation part of the test script
34 AlirootRun_MUONtest.sh
37 \section sim_s2 Tracking parameters, cuts, energy loss and physics processes
39 Tracking parameters in MUON are automatically defined by GEANT
40 MUON takes the default values of CUTs and physics processes
41 defined by the Config files, except for the gas mixture medium
42 of the tracking chambers. The CUT's and physics processes of
43 the gas mixture medium is then defined in the galice.cuts file
44 in the data directory. In particular ILOSS parameter MUST be
45 equal unity (1) in order simulate a realistic energy loss
46 distribution (mean value and fluctuations) in the active gas.
48 \section sim_s3 Tracking of particle in the magnetic field
50 GEANT has two integration methods for tracking charged particles in the
51 magnetic field: HELIX et RKUTA.
52 HELIX is faster and works well if the gradient of magnetic
54 For MUON, HELIX is a not a good approximation and we must
55 use RKUTA to get the optimal mass resolution of the
56 spectrometer. The choice of HELIX or RKUTA is done in the
57 config file when the magnetic field is defined:
59 TGeoGlobalMagField::Instance()
60 ->SetField(new AliMagF("Maps","Maps", INTEG, FACTOR_SOL, FACTOR_DIP, MAXB, AliMagF::k5kG));
62 INTEG must be 1 for RKUTA and 2 for HELIX (the default value for aliroot is 2 (HELIX)).
63 FACTOR_SOL, FACTOR_DIP allow you to set the multiplicative factor for solenoid
64 and dipole, respectively; just putting FACTOR_SOL=0 or FACTOR_DIP=0 will set the
65 magnetic field for solenoid or dipole to 0. Default values are 1.0, 1.0.
66 MAXB is the maximum magnetic field which default value is 10.T
68 \section sim_s4 Tailing effect
70 The control to turn on/off the parametrized tailing effect:
72 AliMUON::SetTailEffect(Bool_t),
75 The parameter to tune increase/decrease the tailing effect is kept inside,
76 AliMUONResponseV0::DisIntegrate(). This parameter is an integer number
77 (excluding zero and four), the higher the value is the less is the tailing
82 Zero is excluded because it gives straight line transformation, and four
83 is excluded because the AliRoot simulation chain spends VERY VERY long
84 time in AliMUONResponseV0::DisIntegrate method, which reason was not yet
85 understood. The parameter for 1, 2, 3, 5, 6, 7, 8, 9, 10 were checked with
86 no slowing down problem, however parameters greater than 6 give almost no
87 tailing effect since they basically correspond to higher order polynomial
91 \section sim_s5 MUON cocktail generator
93 There is a MUON cocktail generator of the muon sources in the
94 EVGEN directory. This class derives from AliGenCocktail.
95 In the init of this class I have filled the cocktail with
96 the muon sources: J/Psi, Upsilon, Open Charm, Open Beauty,
97 Pion, Kaons. The code needs only the production cross section
98 at 4pi (for the moment this values are in the code since I
99 prefere them do not be modified), and the code calculates the
100 rate of particles in the acceptance, making the scaling based
101 on the number of collisions for the hard probes and on the
102 number of participants for soft sources: Pions and Kaons.
104 In the Genereate of this class all entries in the cocktail
105 are called and we define a "primordial trigger" with requires
106 a minimum number of muons above a Pt cut in the required acceptance.
107 In order to normalized to the real number of simulated events,
108 there are 2 data members in the class fNsuceeded adn fNGenerate
109 which tell us what is the biais source.
111 Enclose an example to use this generator:
113 AliGenMUONCocktail * gener = new AliGenMUONCocktail();
114 gener->SetPtRange(1.,100.); // Transverse momentum range
115 gener->SetPhiRange(0.,360.); // Azimuthal angle range
116 gener->SetYRange(-4.0,-2.4);
117 gener->SetMuonPtCut(1.);
118 gener->SetMuonThetaCut(171.,178.);
119 gener->SetMuonMultiplicity(2);
120 gener->SetImpactParameterRange(0.,5.); // 10% most centra PbPb collisions
121 gener->SetVertexSmear(kPerTrack);
122 gener->SetOrigin(0,0,0); // Vertex position
123 gener->SetSigma(0,0,0.0); // Sigma in (X,Y,Z) (cm) on IP position
127 \section sim_s6 How to simulate events with misaligned geometry in local CDB
129 If you want to use a misaligned geometry to simulate some
130 events you can use a local CDB. For this need to follow
133 - Generate misaligned data in local CDB.
134 You can use MUONGenerateGeometryData.C as described above in
135 the corresponding section. Let's assume you used the default
136 residual misalignment settings, then you have a local CDB in
137 your working directory called ResMisAlignCDB containing
138 misalignement data (ResMisAlignCDB/MUON/Align).
140 - Tell AliSimulation you want to use your local CDB for
142 To do this you need to instantiate the AliCDBManager, set the
143 default storage and set the specific storage for MUON/Align/Data,
144 before instantiating AliSimulation (see for example the commented
145 lines AlirootRun_MUONtest.sh).
148 aliroot -b >& testSim.out << EOF
149 AliCDBManager* man = AliCDBManager::Instance();
150 man->SetDefaultStorage("local://$ALICE_ROOT/OCDB");
151 man->SetSpecificStorage("MUON/align/Data","local://ResMisAlignCDB");
152 AliSimulation MuonSim("$ALICE_ROOT/MUON/Config.C");
153 MuonSim.SetWriteRawData("MUON");
159 \section sim_s7 How to Merge events
161 You can merge 2 types of simulated events. For example,
162 you can simulate Hijing events, and then simulate muons
165 Merging is done at the sdigits level, so Kinematics files
166 of the merged events will just correspond to the
167 Config.C simulated file).
169 You must, first, do the Hijing simulation and store it
170 in directory $HIJING_SIM. Note that for merging you
171 won't need Kinematics files of the Hijing simulation...
177 AliSimulation HijingSim("$HIJING_SIM/YourConfigForHIJING.C")
183 You cand build YourConfigFroHIJING.C File from the
184 ConfigPPR file in AliRoot/macros module.
186 Then you can do muon simulation and reconstruction
187 merging both simulated events. In next example, we are
188 merging 20 times each Hijing event in order to simulate
189 100 muons merged with 5 Hijing events.
193 AliSimulation MuonSim("$ALICE_ROOT/MUON/Config.C")
194 MuonSim.MergeWith("$HIJING_SIM/galice.root",20) //parameters are the Hijing simulation file and the number of times we use each Hijing event
195 MuonSim.Run(100) // number of muon (Config.C) events
201 TPluginManager * pluginmanager = gROOT->GetPluginManager()
202 pluginmanager->AddHandler("AliReconstructor","MUON","AliMUONReconstructor","MUON","AliMUONReconstructor()")
203 AliReconstruction MuonRec("galice.root")
204 MuonRec.SetRunTracking("")
205 MuonRec.SetRunVertexFinder(kFALSE)
206 MuonRec.SetRunLocalReconstruction("MUON")
207 MuonRec.SetFillESD("MUON")
213 \section sim_s8 On track numbering
215 All generated particles, including primary and secondary
216 particles are put on the stack. The secondary particles are kept
217 in the stack only if they gave a hit in *any* of the ALICE detectors
218 The number of all particles placed on the stack for a given event
220 Int_t nPart = AliStack::GetNtrack();
221 Looping from 0 to nPart via AliStack::Particle(ipart)
222 gives the particle listing as obtained from the particle generator (primaries)
223 and Monte Carlo (secondaries).
225 The particle response in the detector, a hit, is registered
226 in the hits tree and the hits are filled with each primary track.
227 The total number of "tracks" (fills of the tree) can be obtained
228 with ntracks = AliMUONMCDataInterface::NumberOfTracks(event) and is usually smaller than "nPart".
229 Since particles can also deposit hits in other detectors than
230 the MUON spectrometer, there will be many "tracks" (fills) in the hit-tree
231 without a hit in MUON.
233 The correspondence between "track ID" in the hits-tree ("itr") and the
234 particle ID for particles on the stack (i.e. generated particles) can be
237 for (Int_t itr = 0; itr < ntracks; itr++) {
238 AliMUONVHitStore* hitStore = mcDataInterface.HitStore(event,itr);
239 //track "itr" of the hits-tree
240 Int_t nhitstot = hitStore->GetSize();
242 TIter next(hitStore->CreateIterator());
243 while ( ( mHit = static_cast<AliMUONHit*>(next()) ) )
245 Int_t id = mHit->Track(); //gives particle ID on stack
246 TParticle* particle = mcDataInterface.Stack(event)->Particle(id);
251 where mcDataInterface has been obtained by
252 AliMUONMCDataInterface mcDataInterface("galice.root");
254 During the procedure to go from hits to digits, the hits
255 are summed up such that more than one track can contribute
256 to a given digit. As a consequence the method
257 Int_t AliMUONDigit::Track(Int_t trackID)
258 takes an argument, where "trackID" runs from 0 to
259 AliMUONDigit::Ntracks() to provide the reference to *all*
260 tracks that contributed to it. The returned track ID is the one
261 referred to in the hit-tree. To know which is the generated particle
262 that deposited a given digit one has to follow the sequence of the kind:
263 (shown here using the simple, but not fast, DataInterface interfaces) :
266 AliMUONMCDataInterface mcdi("galice.root");
267 AliMUONDataInterface di("galice.root");
269 AliMUONVDigitStore* digitStore = di.DigitStore(event);
270 AliMUONVDigit* mDigit = ... get some digit from the digitStore
272 for (int tr = 0; tr < mDigit->Ntracks(); tr++)
274 Int_t hitTrackID = mDigit->Track(tr);
275 // get the hits corresponding to this trackID
276 AliMUONHitStore* hitStore = mcdi.HitStore(event,hitTrackID);
277 // loop over the hits
278 TIter hNext(hitStore->CreateIterator());
280 while ( ( mHit = static_cast<AliMUONHit*>(hNext()) ) )
282 Int_t numPart = mHit->Track(); //gives ID of particle on the stack
283 Int_t idTrack = mHit->Particle(); //gives flavour code of the particle
288 This chapter is defined in the READMEsim.txt file.