muon simulation activities at vecc, india

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Muon Simulation activities at VECC, India. Partha Pratim Bhaduri, VECC Subhasis Chattopadhyay, VECC Bipasha Bhowmick, Calcutta Univ. Presented by Y. P. Viyogi IOP-Bhubaneswar, India. Topics. Update on the development of a Muon Trigger Muon simulation with addition of extra hits - PowerPoint PPT Presentation

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1

Muon Simulation activities at VECC, India

Presented by

Y. P. Viyogi

IOP-Bhubaneswar, India

Partha Pratim Bhaduri, VECCSubhasis Chattopadhyay, VECCBipasha Bhowmick, Calcutta Univ.

2

Topics

• Update on the development of a Muon Trigger

• Muon simulation with addition of extra hits

• Dynamic Range simulation

• Optimization of Muon Chamber design

3

Development of muon Trigger

4

Motivation

• Low cross section for rare probes

• High interaction rate (10 MHz)

• Online event selection

• Required background suppression : 400 (from foreseen DAQ BW)

5

Much Standard Geometry Much Standard Geometry

Geometry Used

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(,

(x1,y1 , z1)

(x2,y2,z2)

(x3,y3,z3)

16 17 18

Magnetic field

Z-axis

Development of trigger Algorithm

1.Choice of a hit-triplet

2. Two hit-triplets/event

3.Extrapolation up to vertex

For a st. line passing through points 1, 2, 3 : 12 = 13 ; 12 = 13 :Triplet

J/ multiplicity (@25 GeV/n Au+Au) : 5*10-5 B.R (J/ : +-) : 5%Event rate :10 MHzRecording rate : 25 kHz

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Trigger Simulation: Algorithm Trigger Simulation: Algorithm

1) Look for the hits in the last three detector stations i.e. station # 16, 17, 18.

2) Measure the space co-ordinates (x & y) of the hits in all the three stations. For a particular station z is fixed.

3) Calculate del X1(=x16-x17) , delX2(x16-x18) , delY1(=y16-y17) & delY2 (=y16-y18) and make hit-triplet by taking the hits (one from each of the three stations) which are in close proximity in space (x & y). Members of a triplet are chosen by applying cut values on delX & delY.

4) Accept only those events which have at least two such triplets.

5) Calculate the transverse co-ordinate r(=sqrt(x2+y2)) of the hits of each triplet plot r as a function of the horizontal co-ordinate z i.e. r = f(z).

6) Make straight line fitting such that r=ao+a1z & extrapolate it up to z=0.

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7) Look for the hits in the stations 13, 14 & 15 and calculate transverse co-ordinate using r(=sqrt(x2+y2)) from projected positions.

9)Take the difference rpro-rcal and plot delr for each station and apply the transverse cut.

10) Finally look for the value of r at z=0 (r (z=0)=a0) and apply the final(4th cut).

(a) delX, delY cut

(b) two triplet cut

(c ) projection on penultimate stations

(c ) Projection cut on z=0

Contd..

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Preliminary resultsPreliminary results

Aim:To optimize the algorithm

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Event

Input

Cut-1

(Hit Triplet)

Cut-2 ( 2 HitTriplets/event)

Cut-3(Transve-rse cut)

cut-4(Extrapol-ation cut)

Pluto 1000 806 310 309 220

UrQMD (mbias)

5500 350 30 27 14

UrQMD (central)

3500 684 104 103 54

Bkg. Suppression Factor:Central : 60 Minm. Bias : 375

Results ( Event selection)

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Calculation of Reconstruction EfficiencyCalculation of Reconstruction Efficiency

Sample : 1k embedded (central) eventsSample : 1k embedded (central) events

Input: Reconstructed Much tracks satisfying:Input: Reconstructed Much tracks satisfying:

NMuchHits =18 (Hard tracks)NMuchHits =18 (Hard tracks)

Fraction of true sts hits (truehits/(true hits+ wrong hits+fake hits) >= 0.7

Associated STSHits >=4Associated STSHits >=4

22primary primary <=2.0<=2.0

No. of missed stations =0No. of missed stations =0

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Result (# of Reconstructed J/

Trigger off Trigger cut 1

Trigger cut 2

Trigger cut3

Trigger cut 4

Minimal 124 124 94 94 54

Opening Angle

124 124 94 94 54

pT 115 115 87 87 51

All 115 115 87 87 51

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Observation

• Overall background suppression : ~375

• Most effective cut : 2 hit-triplets/event

• Around factor of 2 reduction in reco. efficiency

• More optimization under progress

Developing new software :

Muon simulation with addition of extra hits

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15

Method The addition is at the MC-Point level.• Take a MC point produced by GEANT.• Get its co-ordinates (x, y).• Apply Gaussian smearing both in x & y with a given resolution to

get a new point with a different (x, y). This is our added point.

- Added point has all other properties same as that of the

previous (eg. : mc_pdg, track-Id, motherID, momentum etc.).• Go through the digitization and add as hit.

Repeat above steps to add as many more hits as one wants.

We can vary the amount of the added hits for a track and amount of tracks for which hits are added independently.

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Hits used for Hits used for track reconstruction in L1track reconstruction in L1

Original 90% extra added

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Track reconstruction efficiency with different added-hit fractionTrack reconstruction efficiency with different added-hit fraction(Hit addition contd.)(Hit addition contd.)

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Dynamic Range simulation for n-XYTER in MUCH

• Dynamic range is a quantity essential for design of the read-out chips.

• Determination of the energy deposition at each cell of the muon chambers ( in terms of MIP as muons give MIP signal).

• Take different cell sizes (2mm. – 4cm.) & find out the fraction of multiple-hit cells & singly-hit cells for particles generated by UrQMD.

• Optimize the cell size based on multi-hit fraction.

• For the optimal cell size find cell by cell energy deposition (E_dep) both for single muons (MIP spectra) & UrQMD particles.

• Apply different MIP cuts & calculate the loss due to saturation.

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Fraction of multiple-hit cells= (total # of cells having >1 hit)/ (total # of cells hit)

Optimal cell-size : 4mm. for inner stations, 4cm. For outer stations (stn 12 onwards)

Optimise the cell size

20 E_dep by UrQMD particles

Station# 1

Cell size : 4mm.

Station# 12

Cell size: 4cm.

21

Single muon energy deposition spectra :

Fitted with Landau distribution

MIP value : 0.197 KeV (MPV of the Landau)

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Saturation loss : part of the energy spectra above the selected energy deposition cut (in terms of MIP) value

MIP cut: E_dep cut (keV)/MIP value(= 0.197 keV)

23

Summary:

Trigger study: Suppression factor upto 375 for minb

Hit addition: needs to optimise with new tracking algorithm. details need discussion

Digitization:Waiting for Dipanwita’s results

Dynamic range simulation: need to see the effect on tracking

24

MotivationMotivation

• One of the major experimental tasks of the CBM experiment is to identify hidden charms or charmonia (J’).

• They are rare probes i.e. they have very low multiplicity(~10-5 or 10-6). For example for central Au+Au collisions @25 AGeV beam energy multiplicity of J/ is 1.5*10-5 and that of ’ is 5*10-6.

• They have very low branching ratio (~5-6%) to decay into dimuon channel.

• Their detection requires an extreme interaction rate. For Example to detect one J/ through its decay into di-muons it requires around 107 collisions.

• Online event selection based on charmonium trigger signature is thus mandatory, in order to reduce the data volume to the recordable amount.

25

FocusFocus

• The main focus is to develop an algorithm to suppress the background as much as possible but simultaneously to preserve the reconstruction efficiency as much as possible.

• For feasibility study of the trigger algorithm for J/ we took 103 central and minimum bias events Au+Au events @ 25 AGeV.

• Reconstructed much-hits are used as input to our trigger study.• The idea is to look for high momentum muon tracks which reach up to

the last detector station & which propagate approximately in straight line (no magnetic field in Much system).

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With the application of trigger cuts (applied in sequential order) reconstruction efficiency (normalized w.r.t 1000 events) decreases.

• Application of 1st trigger cut (minimum 1 hit-triplet per event) does not change the no. of reconstructed J/compared to that in absence of trigger.

• Application of 2nd trigger cut (2 hit-triplet /event) reduces the no. of reconstructed J/.

• Application of 3rd trigger cut (transverse cut in the penultimate detector triplet i.e. station no. 13, 14 & 15) does no reduce the reconstructed J/ further.

• Application of 4th & final trigger cut ( Extrapolation cut at the target) further reduces the no. of reconstructed J/

Observation Observation

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