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RPC_sim Optimization w ith Positrons (+ Pions)PowerPoint Presentation

RPC_sim Optimization w ith Positrons (+ Pions)

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RPC_sim Optimization w ith Positrons (+ Pions)

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RPC_sim Optimization

with Positrons (+ Pions)

Burak Bilki

Argonne National Laboratory

University of Iowa

(S)DHCAL Meeting

January 15, 2014

Lyon, France

DHCAL Simulation Strategy

GEANT4 →points in the gas gap with energy loss

RPC_sim→ generates and distributes the charge over pads

applies a threshold to determine pad hits

Simulated data→pad hits

RPC_sim tuning

Tune major parameters to reproduce the muon response (José)

Match number of hits per layer in the clean regions

Tune charge at edges of chambers to reproduce tapering off of efficiency

Tune the remaining parameters to reproduce the positron response (Kurt →Burak)

Match mean and sigma of Nhits distributions, longitudinal profiles, density plots

No tuning based on pion response

The 4 RPC_sim Versions

3 Versions of the dcut

weight

weight

A

B

1

1

dcut suppresses avalanches close to others

Can not be tuned with μ‘s

ecut

dcut

dcut

r

r

weight

C

(tanh(A*(r-B))+1)/2

1

r

Tuning of dcut Values

Use Positron distributions at 8 GeV

Mean of hit distribution

Sigma of hit distribution

Density distribution (0÷8)

Longitudinal profile

Measure difference to measured distributions

Define a χ2

Tuning

Identify smallest χ2

RPC_sim_3_A

2 exponential lateral charge distribution

1 dcut parameter

χ2

Mean

Sigma

Density

Longitudinalprofile

Simulation index

Best result fordcut = 0.1

RPC_sim_3_A with dcut= 0.1

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_4_A

1 exponential lateral charge distribution

1 dcutparameter

χ2

Mean

Sigma

Density

Longitudinalprofile

Simulation index

No best solution

RPC_sim_4_A with dcut= 0.05

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_5_A

1 Gaussian lateral charge distribution

1 dcutparameter

χ2

Mean

Sigma

Density

Longitudinalprofile

Simulation index

Best result for dcut = 0.18

RPC_sim_5_A with dcut= 0.18

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_6_A

Lateral charge distribution with 1(a+r2)3/2

1 dcutparameter

χ2

Mean

Sigma

Density

Longitudinalprofile

No best solution

Simulation index

RPC_sim_3_B

weight

B

2 exponential lateral charge distribution

2dcutparameters

1

χ2

Mean

Sigma

Density

Longitudinalprofile

ecut

dcut

r

Check 0.01/0.35

Simulation index

Best solution with 0.01/0.35

RPC_sim_3_B with dcut/ecut= 0.01/0.35

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_5_B

2 exponential lateral charge distribution

2dcutparameters

χ2

Mean

Sigma

Density

Longitudinalprofile

Best result with 0.15/0.40

Simulation index

RPC_sim_5_B with dcut/ecut= 0.15/0.40

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_3_C

2 exponential lateral charge distribution

Smooth transition with 2 parameters

χ2

Mean

Sigma

Density

Longitudinalprofile

weight

C

1

Simulation index

Best result with 20.0/0.225

r

RPC_sim_3_C with A/B= 20.0/0.225

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_5_C

2 exponential lateral charge distribution

Smooth transition with 2 parameters

χ2

Mean

Sigma

Density

Longitudinalprofile

Best result with 40.0/0.40

Simulation index

RPC_sim_5_C with A/B= 40.0/0.40

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim Charge Generation

Default

Sample distribution measured

with cosmic rays

dE/dx based sampling

Model the gas with heed++

pC

μ

# of primary ionizations

βγ

Charge Generation using βγ

Sample βγ from cosmic muon spectrum

Sample ionization location d

inside gas gap from heed++

Generatecharge spectrum

using empirical function

βγ→ d →Q

Q=5.46(1-tanh(60.8(d-0.1012)))

RPC_sim_3_A with βγ

1 exponential lateral charge distribution

1 dcutparameter

χ2

Mean

Sigma

Density

Longitudinalprofile

Best result with dcut = 0.01

Simulation index

RPC_sim_3_A with dcut= 0.01 and βγ

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

RPC_sim_5_A with βγ

2 exponential lateral charge distribution

1 dcutparameter

χ2

Mean

Sigma

Density

Longitudinalprofile

Best result with dcut = 0.01

Simulation index

RPC_sim_5_A with dcut= 0.01 and βγ

Data

RPC_sim

π+

e+

Not used for tuning

Number of hits

Number of hits

e+

μ+

e+

Layer number

Number of hits

Density bin

Conclusions

Even though muons are well simulated, the simulation of positrons is not trivial

The simulation of positrons depends strongly on the RPC_simversion, even though all

reproduce the muons quite well

The simulation of positrons depends strongly on the dcut parameter/implementation

Treating the energy loss in the gap properly (using βγ) might be necessary

Current implementation of ionization losses not yet successful

Other approaches are being explored

None of the digitizers satisfactory yet

RPC_sim_5 with 2 Gaussians performs best

(I have been told that OPAL never succeeded in simulating their high granularity gaseous HCAL response)