SIMULATION OF THE AEROGEL PROXIMITY FOCUSING RICH

References:

• P.Krizan, R.Pestotnik, S.Fratina: Fast simulation of the upgraded PID device, PID upgrade meeting, May 29, 2003

• R.Pestotnik et al.: Particle identification with proximity focusing RICH: Maximum likelihood technique,BGM 3/2003

• P.Baillon: Cherenkov ring search using a maximum likelihood technique, Nucl. Instr. And Meth. A238 (1985) p.341-346

• M.Staric et al.: An iterative method for the analysis of Cherenkov rings in the HERA-B RICH, Nucl. Instr. and Meth. A433 (1999) 279-285

Author: Rok Pestotnik

Date: 30.5.2003

Source Code:17^th June 2003: arichlkh.r00_alpha.tar.gz

CopyRight notice

Programming Language: C++

Compiler: gcc 2.95.2

Libraries used: CLHEP-1.8.0

Automatically created documentation: doc

Full documentation: under development.

Reference machine: f9pc43.ijs.si

cpu : AMD Athlon(tm) XP processor 2100+ ( 1733.470 MHz)

cache size: 256 KB, RAM : 512MB

OS: RedHatLinux 8.0 kernel Linux release 2.4.18

Current Benchmark:

CPU usage for 10000 events:

Input:

Track parameters: position, momentum and MonteCarlo identity

Output:

Likelihood probabilities for each of the particle hypotheses for each track.

STATUS:

Overall : 95% finished

Full Simulation:

Full simulation includes the simulation of the following physical processes:

• particle tracking in the homegenius magnetic field ( will be finally replaced by the common routine)

• Cerenkov photon emission in the aerogel

• Photon Tracking to the photon detector (reflection / refraction processes on the aerogel surface + Rayleigh scattering in the aerogel tile)

• Additional background photons generation on the detector plane

• Photon detection

• Digitization of the hits

• Hit Reconstruction

• Cerenkov angle reconstruction

Fast Simulation:

Instead of full simulation of the detector response, cerenkov angle distribution is generated randomly using expected value for the cherenkov angle and expected values for number of signal and background photons.

Construction of the extended likelihood function:

same for full and fast simulation

Input:

• cerenkov angle distribution,

• expected numbers of detected signal photons for different particle hypotheses (e, mu, pi, K, p)

• expected numbers of detected background photons

Output:

• particle probabilities for different particle hypotheses

USAGE:

...

#include "PID_Arich.hh"

...

PID_Arich *pid_arich= new PID_Arich(); // initialization

// mode : 0 full simulation; 1:fast simulation

pid_arich->init(debug=0,mode=0); // before first event

for (int ieve=0; ieve< n; ieve++) pid_arich->Run(); // executed for each event

pid_arich->End(); // after last event

Calculated efficiencies for fast simulation method:

Efficiency = N(K->K) / N(K->anything)

Purity = N(K->K) / ( N(K->K)+N(pi->K) )

fake=1% efficiency=0.858888 +- 0.00714513 purity=0.965893 +- 0.0213905

fake=2% efficiency=0.916596 +- 0.00567467 purity=0.939957 +- 0.0201502

fake=5% efficiency=0.96588 +- 0.00372583 purity=0.869549 +- 0.018159

fake=10% efficiency=0.984415 +- 0.00254219 purity=0.775382 +- 0.0160393

fake=20% efficiency=0.996209 +- 0.0012613 purity=0.644414 +- 0.013251

Figure 1Efficiency for identifying kaons as kaons as a function of particle momentum for a fixed fake rate 5%

fastpid_arich_efficiency.eps