DIGITAL PULSE PROCESSING IN HIGH RESOLUTION, HIGH THROUGHPUT GAMMA-RAY SPECTROSCOPY

Andrey Georgiev* and Werner Gast, lnstifuf f i r Kernphysik, Forschungszenfrum Julich, D5170 Alich, FRG

*Perm. address: Institute for Nuclear Research, boul.Trakia 72. B G 1784 Sofia. Bulgaria

Ab8- A new method for processing signals produced by high re-

solution. large volume semiconductor detectors is described. These detectors. to be used in the next generation of spectro- meter arrays for nuclear research (i.e. EUROBALL, etc.). pre- sent a set of problems like resolution degradation due to char- ge trapping and ballistic deficit effects, poor resolution at a high count rate, long term and temperature instability, etc. . To solve these problems a new approach based on digital Moving Win- dow Deconvolution (MWD) has been developed.

I. htrodudon In designing a modern system for high-resolution gamma

spectrometry one deals with the problem. how to measure the gamma radiation emmitted in a nuclear reaction as efficient, as accurate and as fast as possible. From the instrumental point of view high efficiency is provided by a large total solid angle of the spectrometer, while high photopeak efficiency. peak-to- background ratio and accuracy are provided by the use of Compton-suppressors and large volume or even composite Ge-detectors with high intrinsic resolution. However, the high instrumental efficiency of a modern spectrometer for instance may be seriously deteriorated by a bad resolving time, i.e. throughput of the processing system. Similarly the high intrin- sic resolution of the Ge-detectors may be heavily disturbed by imperfect pile-up rejection or ballistic deficit correction.

It is the aim of this paper to present a new signal processing method which is able to fully exploit the improved performance of modern spectrometer arrays like EUROBALL. The method allows to realize pulse-shaping filters which give the best tra- deoff between noise, resolving time and ballistic deficit. Since the latter qualities often put contradictory requirements on the shaping network, best tradeoff here means, to find an optimum compromise between achieving the best signalhoise ratio. permitting operation at high counting rates without degradation of the resolution, and making the result, i.e. the measured total energy of the radiation event, insensitive to rise time fluctu- ations in the detector signal.

II. Reconrrtructlon of the event chiuge The basic elements of the semiconductor system are a de-

tector followed by a charge sensitive preamplifier and a main ( linear or shaping ) amplifier. Any radiation event produces an amount of charge proportional to the absorbed energy. That charge results in a steplike waveform at the preamplifier out- put. In the system of our interest, i.e. a high resolution and high throughput system, preamplifiers with resistor discharge are mainly used, so the output step is followed by a decay with a very long time constant compared to the charge collection in- ter - Val. The preamplifier output signal U,( t) is described by a convolution between the charge distribution function g( t) and the preamplifier transfer function f ( t):

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If the charge collection time is instantaneous g ( t 1 becomes a delta function and the eq. ( 1 1 can be rewritten as: U ( t ) = G f ( t ) ( 2 ) where G is the proportional to the absorbed energy.

The existing analog processing systems employ a differen- tiitor, to extract G. followed by a set of integrators. They differ mainly in respect to how the integrations are realized ( i.e. acti- ve integrators, active integrator plus gated integrator, weighted sum of the integrator outputs C1 I. etc.). These processing se- quence works correctly only in case the charge function is a delta function, which has been the condition for the convolution integral ( eq. 1) to become a product ( eq. 2).

One correct and natural solution is to employ a deconvolu- tion as the first processing step. The effect of that approach is that the original charge distribution of the detector signal is re- constructed from the preamplifier output signal hence a true ballistic measurement of the total charge can be performed.

To perform a deconvolution by analog means is practically impossible. Therefore, by digitizing the preamplifier signal we transform the convolution integral into a sum:

(3)

where the time scale is normalized to the sampling interval t . In fact, eq. 3 is a set of equations to be solved with respect 'to g( j ). This task is difficult to be performed in real time, but so- me facts help to simplify the process. First, the deconvolution can be performed in a window with a limited size M Second, the preamplifier transfer function f ( i) is known or easily defi- nable under real conditions. For the most common systems with resistor-discharged preamplifiers this function is expo- nential. These assumptions permit to solve the equations ( 3 ) by applying a simple recurrent procedure, which requires only little hardware or relative small computing power to run conti- nuously in real time. We call the corresponding new processing unit Moving Window Deconvolver ( MWD 1..

III. Nohe rh.pine Recently noise analyses for semiconductor detectors were

carried out in the time domain 12.31. The equivalent detector noise circuit includes two generators - for the serial and the parallel noise. The deconvolution in a window extracts all char- ges ( signal and noise as well ) belonging to that time interval. If the window is by L sampling intervals wider than the charge distribution produced by a single radiation event, then L conse- quent windows. shifted by one sampling interval. will cover that distribution. i.e. L consequent results of the deconvolution will present one and the same event. Taking the mean value of these results the signal to noise ratio increases.

To obtain an analytical expression for the noise contribu- tions the time domain method has been used. On fig. I d the step ( charge 1 response of the system is shown, produced by shifting the deconvolution window ( fig. 1 b 1 stepwise L=MR times over the charge distribution ( fig. 1 a 1 and accumulating

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Fig. 1 : Development of the charge response and the noise residual function. the results. Shifting the delta noise charge. normalized to the event charge, from minus to plus infinity the noise residual function is obtained ( fig. le 1. As the residual function is a true trapeziodal. the parallel and serial noise indexes are:

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Two remarks should be made in connection with eq. 4. First. due to the sampling process the residual function is not smooth but contains steps with a magnitude 1/L To eliminate this in- fluence a low-pass filter has been placed in front of the samp- ling ADC. Second, the parallel noise has been taken as a se- quence of charges with a constant rate. This assumption is not correct with respect to the low frequency interference. the detector "microphony" effect and the temperature induced ba- seline fluctuations of the detector-preamplifier arrangement. To deal with these problems, a separate processing unit named Moving Average Unit ( MAU - see fig. 2 ) has been included in the system. The unit takes the results of the deconvolution in any S windows in which there are no radiation charges. Thus, the unit contains at any moment the mean value of the parallel noise. If the number of windows S is at least 1 0 times the num- ber of the charge windows L the impact of the MAU over the noise performance of the system is negligible, but still the unit suppresses the low frequency interferences.

IV. The pulm proceaaing ayatcm The proposed pulse processing system is shown in a block

form in fig. 2. A typical set of parameters would be 12-bit re- solution, 25 MSPS sampling ADC ( i.e. 40 ns sampling interval t 1, a MWD window size of 125 samples ( i.e. 5 ps peaking ti- &?e), 100 L-type windows ( i.e. 4 ps integration time and l ps protection time for full charge collection) and 1000 S-type windows (i.e. 40 ps integration time for the low frequency suppression). The amount of analog elements is considerably low: the low-pass filter with a corner frequency one half of the sampling one which in addition serves as a fixed gain amplifier, and a fast channel built as a delay-line arnplifier.The final result, i.e. the radiation energy. is produced directly in a digital form. It means that the system incorporates all necessary processing components and we call it a Pulse Processing Analog to Digital Convertor (PPADC) to stress on its completeness.

To check the ideas constituting the development a test sys-

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Fig. 2: Block diagram of the digital pulse processor. tern has been assembled. For the digital part a Personal Com- puter (PC) has been used. As the computing power of the PC is not sufficient to run the process in real time. the FIFO memo- ry is used to store time slices of 100 ps being triggered by an arbitrary event each. until they are processed by the PC. It me- ans that the test system operates in a pseudo-real time.

Using that test system all important performance features of the development could be estimated, except the dynamic count rate behaviour. Instead the double event resolving time could be defined. V. Dhcweion md firat expefimental reaulta

The reconstruction of the original charge distribution of the detector signal by deconvolution as the first processing step, the implementation of moving window processing over the full processing channel, and the complete digital design lead to particular features of the development:

( i ) The charge collection time does not influence the reso- lution of the system. This comes as a result of the true ballistic measurement which can be performed using a deconvolution as a first process in the signal processing channel. Fig.3 shows the comparison of calculated peak deficits due to balli- stic effects as function of the normalize&charge collection time for two different analog shapers (7 order Gauss shaper (GS) and Gated Integrator with Tth-order Gauss prefilter (GI) 1 and for the new pulse processing system ( PPADC-1). The normalization is done for each curve with respect to the peaking time of the corresponding shaper. The peaking times of the shapers are taken in a ratio which provides an equal se- rial noise suppression. While for the Gauss shaper for example no further improvement is possible, because its peaking and shaping times are related. an additional free parameter of the pulse processing system. called Collection Time Protection ( CTP) interval, allows to enhance its ballistic deficit perfor- mance even further without degradation of the noise perfor- mance ( see PPADC-2 curve in the fig. 3). The CTP intervals for the PPADC-1 and PPADC-2 curves in fig. 3 are respecti- vely 0.2 and 0.4 of the peaking time.

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Fig. 3 : Calculated peak deficit due to ballistic effect as function of the nor- malized charge collection t i e for two analog shapers compared to the Pulse Processing ADC ( see text ).

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Fig. 4: Measured ballistic deficit o f the Silena 7611 L spectroscopy amplifier with2 psshapingtimeforrisetimesof theinputsignalof 20,50,100. 200,and500ns (upperspectrum)comparedtothat of thePulsePro- cessing ADC under the sameconditions ( lower spectrum 1.

In fg. 4 the measured ballistic deficit performance of a Silena spectroscopy amplifier with 2 ps shaping time (or 4.8 pS peaking time) is compared to our pulse processing system for the same peaking time and for the same delta noise suppres- sion (or 4.8 pS peaking time, 3.8 pS integration time and 1 pS CTP interval for the PPADC). Energy shifts due to in- complete charge collection are displayed for various charge collection times, as simulated by pulser signals of equal ampli- tude but different risetimes of 20. 50. 100. 200. and 500ns. respective1 y.

( ii 1 The noise shaping function is a true symmetrical trian- gular ( in fact trapezoidal with a short flat top part 1. That shape is the best choice with respect to an optimal resolution - count rate performance 13.43. As that shape cannot be achieved by analog means in a pure form we consider it the second main achievement of the digital design. Moreover, due to the moving window processing the dead-time is close to two times the in- tegration time. This two features define the highest possible noise-rate performance for the new system. The calculated noise-rate performance of the digital p Ise processing system (PP1 is compared to that of the 7 -order Gauss shaper ( GS 1 and the Gated Integrator with 7thorder Gaus prefilter ( GI 1 in fig. 5 for equal serial (or delta) noise suppression at low count rate. In the calculations the GS with 5 pS peaking ti- me is taken as a reference. The improved count rate perfor- mance of the new system as represented by the low count losses as a function of the input rate ( see the solid lines in fig. 5) is not achieved at the expense of the noise performance as indicated by the relatively small increase of the Delta-Noi- se-Index ( DN I ) with increasing input rate ( compare the das- hed lines in the same figure).

The experimentally measured resolutions of one and the same detector (Ortec GMX-25190-S with 28.7% relative effi- ciency at 1.33 MeV. used in that measdvments after 7 rege- nerations) for the 1332 keV y-line of CO shown in fig. 6 in- dicate, how in an high rate application with 10 ps total proces- sing dead-time ( TOT). i.e. 1 ps shaping constant for the Gauss shaper. the conventional analog processing system em- ploying an Silena 7611 L spectroscopy amplifier and a Silena 7423 UHS converter ( 2.9 keV FWHM. upper spectrum 1 is significantly overperformed by the new system ( 1.9 keV FWHM, lower spectrum 1. Even for shaping constants of 6 ps. optimized to give the highest possible resolution for the given

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detector, however leading to a huge total processing dead-time of approx. 60 ps. the analog system cannot compete ( 2.1 keV FWHM. central spectrum 1.

( iii 1 As the full processing is performed in a digital environ- ment a number of advantages emerge: digital control of the processing parameters. reliability. temperature stability, on-li- ne optimization and testing, etc.

All results reported in this paragraph are still not represen- tative for the performance of the pulse processing system. They should be considered as a indication that the theoretical basis of the method is correct and that the digital pulse proces- sing in high-resolution spectroscopy is possible.The complete test of all performance parameters is planed with a real time system which is under development. Aclurowle4gmenh

This work was supported by Technologie Transfer Buro. Forschungszenfrum Jukh under Project No. 223610. and by target systemelectronic GmbH. Solingen under Contract No. TTBN.292.01.91.The authers would like to acknoledge also A. Buchner for its frequency domain analysis which will be pu- blished separately: and R. M. Lieder and H. Halling for the hel- pful coments and disscussions. Refen?nce8: [I 1 F. Goulding et al, IEEE Trans. Nucl. Sci..NS-30, No.1. (1983) 301. [2 1 M. Deighton. NIM 58 (1968) 201-212. 13 1 F. Goulding. D. Landis. IEEE Trans.Nucl.Sci..NS-29. No.3 (1982) 1125. [4 1 E. Fairstein. IEEE Trans.Nucl.Sci.,Vo1.37. No.2 (19901382.

PPADC 1 with 10 ps processing dead time.

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