simulation of efficiency and time resolution of resistive plate chambers at high rate

Simulation of efficiency and time resolution of Resistive Plate Chambers

at high rate

Simulation of efficiency and time resolution of Resistive Plate Chambers

at high rate

Presented by

Marcello Abbrescia University and INFN - Bari - Italy

CBM meetingDarmstadt

GSI, GermanyMarch 10th, 2005

The problemThe problem

GSI-2005 Darmstadt, March 10th, 2005GSI-2005 Darmstadt, March 10th, 2005

Marcello Abbrescia - University of BariMarcello Abbrescia - University of Bari

Resistive Plate Chamber are wide spread gaseous detectors, introduced in the 1970s.

RPCs were at first used in streamer mode, for cosmic rays applications, then in avalanche mode, to increase rate capability

Their physics has been understood, partially, much later; in particular almost no theoretical prediction could be made until two years ago about their behaviour at high rate … i.e. the LHC, or other important cases

The goal of this study was to write a comprehensive model which could help to explain the observed features, predict its behaviour and help in detector design

The story up to nowThe story up to now



satsat

wxx

we

ind xg

xgVMeMnV

g

qq sat

10

0

Exponential growth Drift

Exponential growthxsat

Saturation

“Drift”

Many quantities in the formula above are themselves stochastic variables.

The induced charge is the “convolution” of all these variables.A Monte Carlo rather elaborated

When saturation does not playWhen saturation does not play


Gap: 2 mm

Gap: 9 mm

Charge Spectra shape: these are the most fundamental information you can get

1

Rqqind

Comparison between Monte-Carlo predictions and experimental data

Freon rich mixture

Argon rich mixture

: primary cluster density (from 3 to 5 cl/mm): 1st Townsend “effective” coefficient


...and when saturation becomes important...and when saturation becomes important


HV=9.2 kV

SimulationExperiment

Experimental data from Camarri et al., NIM A 414 (1998) 317-324

Gas mixture: C2H2F4/C4H10 97/3 + SF6 2%Input for simulation: Colucci et al., NIM A 425 (1999) 84-91

This is not a fit!




HV=9.4 kV




This is not a fit!




HV=9.5 kV




Inefficiency peak Saturation

broad peak

This is not a fit!




HV=9.7 kV




Inefficiency peak

Saturation broad peak

This is not a fit!




HV=9.9 kV




Inefficiency peak


This is not a fit!




HV=10.1 kV




Inefficiency peak


This is not a fit!


The “single cell” modelThe “single cell” model


None of the simulations up to now take into account the

role of the bakelite resistivity ... we could be simulating metal or insulating electrodes

g

bCCR rbgbb 2222 0

g

bCCR rbgbb 2222 0

Recovery time independent of the cell dimension ...

Cg

RbCb

A few numbers:

typical avalanche radius: 100 mtypical avalanche charge: 1 pCtypical external charge contained in 100 m: 10 pC


What happens in the “single cell”What happens in the “single cell”


Applied HV

High HV “at start”

Big pulses

cl

d

n

jj

jtvedind Mneqti

10)(

wEv

t

ext eHVtHV 1)(

=1500 ms

There is a sort of feedback ...

Area of the cell = 1 mm2

5 10 11 cm

=20 Hz


Effective HV vs. rateEffective HV vs. rate


Applied HV

10 Hz

13 Hz

20 Hz

The effective HV diminishes and its distribution is broader.

(...until HVeff is too low)

Two consequences:•lower HV at high rate•greater HV variations at high rate


Efficiency vs. rateEfficiency vs. rate


From C. Bacci et al., NIM A 352(1995) 552-556

Experiment

Simulation

4 1010 cm

8 1010 cm

Cut-off rate of the experimental efficiency well simulated: slightly higher value of resistivity needed (significant?)


Rate capability dependancesRate capability dependances


HV=10100 V

HV=9800 V

HV=9600 V

HV=9200 V

independent of applied voltage

4 1011 cm

8 1010 cm

1011 cm

strongly dependent on resistivityTrue in the “single cell” model only

Cut-off rate

4 1011 cm HV=10100 V


6 1011 cm

Rate capability in streamer modeRate capability in streamer mode


From R. Arnaldi et al., NIM A 456(2000) 73-76

Exp. streamer

Exp. avalanche

Simulation streamer

Streamer charge distribution has been simulated also by “artificially” multiplying by 10 both avalanche charge, and area on the electrodes.

Cut off rate reproduced also in the streamer case.

8 1010 cm

Efficiency rate dependance different.


Efficiency vs. HV and rateEfficiency vs. HV and rate


Data from G. Aielli et al., NIM A 478(2002) 271-276

Simulation

Experimental

~ 1.5 kHz/cm2

~ 2 Hz/cm2 Very good agreement

At high rate the shape of the simulated efficiency curve seem to change and differ from the experimental one.

1ln

1

1 A

qg thr

e

g

MnVqA we

0


Time resolutionTime resolution



What is the origin of signal time fluctuations in an RPC? There are very good analytic studies (Mangiarotti et al.),

here just a few hints will be given from a MC point of view.

RMneqRtitvcl

d

n

jj

jtvedindout

10)()(

wEv discrv

All the cluster in the gap contribute at the same manner to the signal

• Total number of clusters• Total number of electrons in each cluster• Fluctuations superimposed on the exponential growth

They are not related to the particle transit time in the gas gap

Reasons for time fluctuationsReasons for time fluctuations



Total number of electrons

Other types of fluctuations

Avalanche growth fluctuations

• local charge density• surface charging and discharging

In a real RPC:• signal delay time along the strip• deformation during propagation• electronics

… not directly related to the gap width

Some (obvious) resultsSome (obvious) results



Time delay decreases with a HV increase ...

A double gap has a better resolution with respect to a single gap

Time resolution becomes better with a HV increase

Time resolution vs. rateTime resolution vs. rate


Data from C. Bacci et al., NIM A 352(1995) 552-556

0.2 kHz/cm2

=0.9 ns 1 kHz/cm2

=1.2 ns 4 kHz/cm2

=1.6 ns

Simulated Experimental

General behaviour well reproduced ... Simulated time resolutions slightly less than experimental.

1. Systematics on drift velocity2. “Instrumental” effects not reproducedPossible Reasons


Time delay and resolution vs. rateTime delay and resolution vs. rate


Experimental (arbitary zero)

Simulation (absolute scale) Experimental Simulation

Time Delay Time resolution

4 ns3.8 ns

The absolute scale of the simulation refers to the passage of the ionising particle.

75.1

2/

2/

2.0

4

cmkHzt

cmkHzt

77.1

2/

2/

2.0

4

cmkHzt

cmkHzt


The future 1/2: The multi cell modelThe future 1/2: The multi cell model


The area of the inefficiency cell increases as the bakelite surface resistivity decreases.

vol

sup

“large” “small”vol

sup

avalanche

“Surface” coupling resistors

Cg

RbCb

Rs,b

The net results is that the current flows not only in the “central” cell, but also in the neighbouring ones.


The future 2/2:The future 2/2:


The model has been mainly applied to predict the behaviour of “trigger” RPCs,i.e. tipically 2-3 mm gas gap, high efficiency and good (~ 1 ns) time resolution.


It would be interesting to use it in the most recent and interesting application, i.e. T.O.F. RPCs, where very good time resolution (better than 100 ps) is required.

The problems in this case:

•probably very strong saturation effects take place (to account for the observed efficiency)

•The gas parameters are even less known that in the trigger RPCs case, due to the higher electric field

It would be interesting to compare with analytical models (Fonte, Mangiarotti, Gobbi, et al.), for a cross-check

ConclusionsConclusions


Even the single cell model reproduces well the efficiency and time resolution vs. rate.

The role of resistivity and collected charge seems to be clear.

Charge spectra are well understood.

Slight differences remain, both for the “static” and the “dynamic” case ... could be due to• uncertainty in gas (and other) parameters.• possible refinements of the model.

It is the first time the role of resistivity is taken into account in simulation of Resistive Plate Chambers ... The model of the dry water becomes wet.


simulation of efficiency and time resolution of resistive plate chambers at high rate

Documents

marcello abbrescia university

bariexperimental data

gas mixture

elaboratedwhen saturation

simulation of efficiency

monte carlo

montecarlo predictions

high ratepresented