OPTIMIZATION OF THE READOUT PAD GEOMETRY FOR A GEM-BASED TIME PROJECTION CHAMBER
J. KAMINSKI, S. KAPPLER∗, B. LEDERMANN, TH. M ¨ULLER Institut f¨ur Experimentelle Kernphysik,
Universit¨at Karlsruhe (TH) Postfach 3640, 76137, Karlsruhe, Germany E-mail: [email protected]
M. T. RONAN
Lawrence Berkeley National Laboratory, Mail stop 50B-5239
1 Cyclotron Road, Berkeley, CA 94720, USA
In future time projection chamber (TPC) designs strong magnetic fields are fore- seen to reduce transverse cluster sizes and thus improve transverse spatial reso- lution and double-track resolution. This implies a high granularity of the TPC readout - a feature, which is provided by micropattern TPC readouts based on the Gas Electron Multiplier (GEM). Besides numerous further advantages, GEM readouts feature narrow and direct electron collection signals and allow to take full advantage of small cluster sizes. In this paper we present the study on the pad geometry optimization for large-scale GEM-based TPCs with magnetic fields up to 5T. Measurements with six different pad geometries in a prototype-TPC are presented and the results are compared to Monte Carlo simulations.
1. Introduction
Future high energy physics experiments require strong magnetic fields and excellent performance of the central tracking detectors to resolve the mo- mentum of highly energetic particles. In the technical design report (TDR) of the TESLA-project1 for example, the use of a time projection chamber (TPC) embedded in a 4 T magnetic field is foreseen. The readout is sug-
∗S. Kappler is now with the Rheinischwestf¨alische Technische Hochschule, Aachen, Ger- many
1
gested to be based on micropattern gas amplification stages, such as Gas Electron Multipliers (GEMs), and micro pads (rectangular, 2 mm × 6 mm).
These devices have many favorable features, some of which are:
• suppressed ion backflow into the drift volume,
• negligible E × B-effects,
• direct electron collection by pads below the last GEM.
The last item mentioned leads to fast and narrow signals. Hence the clus- ter size depends mostly on the diffusion processes in the drift region and therefore the spatial resolution in the transverse and the drifting direction as well as the double track resolution are significantly improved. However, if the cluster size becomes so small that only one pad collects the complete signal within one pad row, then the transverse spatial resolution (t.s.r.) degrades rapidly to (pitch of pads)/√
12. We have therefore studied the influence of the pad geometry on the t.s.r. in the limit of low diffusion.
2. Methods of Studying a Pad Geometry
In this study six different readout pads were compared to each other by measuring the t.s.r. in an experimental setup and confirming the results with a Monte Carlo simulation.
2.1. Experimental setup
For testing the various pad geometries a prototype chamber with a drift length of 25 cm and an inner diameter of 20 cm was used (detailed descrip- tion in2). This prototype detector has been operated in high magnetic fields and hadronic testbeams before3 and has demonstrated good performances with rectangular 1.27 mm × 12.5 mm pads. For the study presented in this paper, a new readout area had been developed to easily exchange the pad geometry, while leaving the remaining detector (especially the GEMs) un- touched. The setup (s. Fig. 1) had been placed in a 1 T-dipole magnet at DESY, Hamburg, and 5.2 GeV-electrons had been used to create straight tracks in the detector. In the gas mixture Ar:CH4 (95:5) and in an electric field of 60 V/cm the transverse diffusion coefficient is 116.8 µm/√
cm and therfore only 1.7 times larger than in the aforementioned TESLA-detector.
The six pad geometries, that were studied under these conditions, are shown in Fig. 2
Figure 1. Photograph of the pro- totype detector mounted together with the front-end electronics onto the support.
Figure 2. Schematic drawing: a) rectangu- lar pads, b) staggered rectangular pads, c) chevron-shaped pads, d) comblike pads, e) rhombic pads, and f) ’3+1’-pads
2.2. Monte Carlo Simulation Tool
The Monte Carlo tool traces electrons generated in the drift volume to the readout pads. It takes into account a realistic model of ionization along the track path, diffusion in the drift region, gas amplification inside the GEM-holes and diffusion below each GEM. The different processes have been modelled according data given in reference4.
2.3. Data Analysis
The data of the experimental setup and the Monte Carlo simulation were reconstructed and analyzed with the same JAVA-based software package according to the following procedure: First, the baseline was subtracted and the noise of individual pads was determined. Then a center of gravity algorithm was used to calculated the position of the charge clusters in ev- ery pad row and these clusters were merged to tracks by a combinatorical track finder. Finally, the t.s.r. is determined by the width of the residuals distribution σres of target row clusters with the reference tracks. Since the reference track is not known accurately, the uncertainty of the track pa- rameters have to be taken into account. This is done by determining the parameters of the reference track by once including and then excluding the information of the target row cluster. The true spatial resolution is then given by the geometric mean of the two different widths of the residual distributions5: t.s.r. =√σi, res ∗ σe, res.
Since a non-linear charge sharing is expected, if a narrow Gaussian- distributed charge is collected by two broad pads, a correction function has to be applied. An example of such a correction function can be seen in Fig. 3. Here a good agreement of Monte Carlo results, experimental data
Figure 3. Comparison of the correc- tion function for staggered rectangular pads. The tree different functions are derived from measured values, Monte Carlo data and a theoretical model.
Figure 4. Transverse spatial resolution in dependence on drift distance for var- ious pad geometries: closed symbols are experimental results, open symbols Monte Carlo results.
and a theoretical model based on a numerical integration of a homogeneous charge distribution is seen.
3. results
The results of the testbeam measurements are shown in Table 1, where the t.s.r. is given for effective gas gains of 4 ·103at drift distances of 7.5 cm and 17.5 cm. Also the result for higher effective gas gains of 104and with track inclinations of φ = −10◦are shown for a drift distance of 7.5 cm. Finally, also the probability of hitting only one pad is given.
Despite the fact that this probability is highest for the classical rectangular and the staggered pad geometry, they perform best with respect to the t.s.r. This fact is also shown in Fig. 4, where the t.s.r. is shown for four different pad geometries in dependence on the drift distance. Here, the test beam results as well as the Monte Carlo simulation results are shown. Both results agree qualitatively very well, but quantitatively, the Monte Carlo simulation results are 20-50 µm below the experimental ones originating most likely from simplification in the simulation.
4. Conclusion and Outlook
Both the testbeam experiment as well as the Monte Carlo simulation agree, that the staggered rectangular pads performed best and are therefore rec- ommendable for the use in any large scale detector. However, reasons for
Table 1. Summary of experimental results. Listed are transverse spatial resolutions σx(7.5 cm) and σx(17.5 cm) for a track inclination φ ≈ −2.0◦, an effective gas gain of 4 · 103 and a drift distance of 7.5 cm and 17.5 cm, respectively. Also transverse spatial resolutions σx(gain = 104) and σx(φ = 10◦) for drift distances of 7.5 cm with a gain = 104and track inclinations of 10◦are included. ncc indicates the fraction of clusters without charge sharing. Values without errors are linear interpolations between measured values.
Pad geometry σx σx σx σx ncc
(7.5 cm) (17.5 cm) (gain = 104) (φ = 10◦)
in µm in µm in µm in µm
Rectangular pads 172.3 190 158 186 0.150
2 × 6 mm2 ±0.6 ±2 ±1 ±2 ±0.001
Staggered rectangular 146 126 119 189 0.211
pads 2 × 6 mm2 ±1 ±2 ±2 ±0.001
Rhombic pads 179 150 130 232 0.141
±2 ±0.004
Chevron-shaped pads 265 250 220 286 0.078
±12 ±22 ±0.001
Comblike pads 315 231 260 437 0.039
±16 ±9 ±20 ±0.001
’3+1’ pads 178 191 174 445 0.074
±3 ±3 ±3 ±3 ±0.001
the worse performance of the more exotic pad geometries could be identified and improvements are tested with the Monte Carlo.
Acknowledgments
The authors would like to thank Norbert Meyners from DESY for helping with test beam related issues and providing the magnet, the FLC-group of DESY and especially T. Behnke and M. Ball for supporting this project in many ways, D. Karlen for modifying the electronics and T. Barvich for building the detector and parts of the equipment.
References
1. G. Alexander et al., TESLA Technical Design Report, Part IV: A Detector for TESLA. DESY-01-011 (2001).
2. S. Kappler et al. IEEE Trans. Nucl. Sci. 51(4), 1524 (2004).
3. J. Kaminski et al., Nucl. Instr. Meth. A535/1-2, 201 (2004).
4. W. Blum et al., ”Particle Detection with Drift Chambers”, Springer, (1993).
5. R. K. Carnegie et al., Nucl. Instr. Meth. A538, 372 (2005).
