Figure 1 Simplified scheme of the experimental setup.

Impact of Dark Counts in Low-light Level Silicon Photomultiplier Multi-readout Applications

I.F. Castro, A.J. Soares, J.F. Veloso I3N, Physics Department, University of Aveiro

Campus Universitrio de Santiago 3810-193 Aveiro, Portugal ifcastro@ua.pt

AbstractThe Silicon Photomultiplier (SiPM) generates noise due to thermal excitation, producing dark counts. This may be a critical performance drawback of the SiPM for low light level applications, despite its otherwise promising features such as high internal gain and quantum efficiency, low power consumption and insensitivity to magnetic fields. The dark count rate is highly dependent on temperature and bias voltage, increasing with both. Dark count pulses are similar to single photon interactions and introduce complex challenges in low light level measurements. In applications where the pulse integration time is dependent on the decay time of a slow scintillation counter, the longer the signal integration the higher the probability of dark counts during the integration period, and this can be critical for detecting very low number of photons in that period. For higher light levels, the effects of dark counts can be reduced by setting an appropriate threshold. This work presents Monte Carlo simulation techniques to evaluate the impact of dark counts into position detection algorithms, in low light level imaging applications where multiple SiPMs are used to detect position of interaction.

I. INTRODUCTION As a solid state device, the Silicon Photomultiplier (SiPM)

generates noise due to thermal excitation, i.e., it produces an electric signal even in the total absence of light (dark counts). Since it operates in Geiger mode, these dark counts produce output signals identical to single photo-electron events which introduce complex challenges in applications where low light levels should be detected in simultaneously triggered events. Depending on the charge integration time required, and on the dark pulse rate of the SiPM, the dark pulse signal may be equivalent to multiple photo-electron pulses and, for gated applications, this may severely impact the usability of this device for low light level detection. In some applications, the integration time depends on the decay time of the light source (e.g. scintillation counter) and it may be required to extend it to maximise the signal. However, this can be a critical problem in detecting a very low number of photons. For higher light levels, the effects of dark counts can be significantly reduced by setting an appropriate threshold.

The number of output dark pulses measured with a threshold of 0.5 p.e. is usually defined as the dark count (number of times that one or more photons are detected). In some cases, a threshold of 1.5 p.e. in dark count measurements is used to evaluate optical crosstalk, which consists of the

excitation of neighbour cells due to photon emission during an avalanche discharge in a given cell [1,2]. Afterpulsing is another source of noise of SiPM, which arises from charge carrier trapping and delayed release, due to traps formed in the breakdown volume of the silicon [3]. In this work, dark counts refer to all these three contributing sources of dark noise.

II. EXPERIMENTAL MEASUREMENTS

A. Setup Photon-counting spectra of SiPM devices have been

obtained using the Hamamatsu S10362-11-100-U MPPC and characterized in terms of their background noise. The dark rates and their variation with temperature and bias voltage were measured in a dark chamber specially built for this purpose, as depicted in Fig. 1. An Ortec 710 power supply was used to bias the SiPM between 69 and 70V. The SiPM output was initially amplified with a linear amplifier (Canberra 2111) with no shaping and fed into a peak sensing MCA. This was later replaced by a custom amplifying circuit (Fig. 2) which was developed and included inside the dark chamber, providing similar results. To study the variation of the dark rate with temperature, a cooling module was set up, consisting of a thermoelectric Peltier module with a heat-sink and extracting fan, controlled with a thermocouple.

Measurements were also taken with low light levels. A high resolution pulse generator (BNC PB-5) was used to illuminate a 470 nm LED and also to trigger the ADC gate for signal acquisition from the SiPM. A BC-91A wavelength shifting optical fiber was used between the LED and the SiPM. SiPMs are known to be a good choice to detect light emitted from scintillating fibers [4,5].

This work was supported by project GAMACAM through FEDER andADI (Lisbon) programs. I.F. Castro is grateful to portuguese Agncia deInovao for funding this project via QREN project 1607.

2009 IEEE Nuclear Science Symposium Conference Record N25-152

9781-4244-3962-1/09/$25.00 2009 IEEE 1592

B. Results The following experimental results were obtained using the initial amplifying scheme. The dark rates for different bias voltage values were measured at room temperature and are shown in Fig. 3, where it is clearly visible the dependence with bias voltage and with detection threshold, as expected. The photo-electron pulse-height spectrum for one of the test conditions (Vb = 69.4V) is shown in Fig. 4. The single electron peak is clearly visible (second peak from the left), and so are the 2nd and even 3rd electron peaks, corresponding to multiple simultaneous dark pulses within the device. Results of the dark rate variation with temperature, for different threshold values, are summarized in Fig. 5, where no light source was used. It is seen that the dark rate (at a threshold of 0.5 p.e.) becomes approximately half at every 9C.

The ADC spectrum of the time gated signal obtained with the pulsed LED coupled to an optical fiber is shown in Fig. 6. The high photo-electron resolution of the SiPM allows a clear separation of several electron peaks. It can be seen that for very low light levels, the single electron peak coincides with the dark pulse shown above.

III. SIMULATION

A. Method The SiPM charge signal from primary photoelectrons

follows an approximate Poisson distribution. The charge amplification process and other events such as small differences between pixels or photon interactions in recharging pixels, introduce Gaussian spreads in the signals collected [6]. Therefore, the expected SiPM charge spectrum is a Poisson distribution convoluted with Gaussian distributions, as seen in Fig. 4. A MATLAB application was developed to simulate SiPM charge signals, for a given Poisson mean and Gaussian standard deviation , ignoring counts below a given threshold value. The values of and were taken from experimental data, for different conditions of temperature, bias voltage and charge integration time. The value of was found to vary approximately between 0.2 and 0.75 and between 0.25 and 0.3. As shown in Fig. 7, the simulated spectrum shows a good agreement with the acquired one, considering that the simulation ignores the electronic noise.

Figure 6 Low light response spectrum. Vb=69.4V, T=25C.

Figure 4 Dark pulses spectrum. Vb=69.4V, T=25C.

Figure 3 Dark rate vs. bias voltage, T=25C.

Figure 2 Pre-amplifying circuit developed for the Hamamatsu MPPC.

Figure 5 Dark rate vs. temperature (constant gain).

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B. Simulated setup and conditions

To test a detection apparatus of 120 per 120 SiPMs triggered by a common gate, the application simulates 120 per 120 SiPM charge spectra acquired simultaneously, where 5 of the SiPMs in each direction have a low light signal, i.e., have a higher Poisson mean than the average for dark noise. The configuration may consist for example of an inorganic scintillation crystal coupled to two orthogonal layers of 120 wavelength shifting fibers, each of which is read out by a SiPM. For the purpose of this study, the light levels reaching the SiPM were considered to be 10 photons in the central fiber, 6 in the two neighbor fibers and 2 in the next surrounding ones. The position of the central fiber was defined to be (10, 10) and 5000 counts (events) were simulated. Table I summarizes the relevant parameters used in the simulation:

TABLE I. SIMULATED CONDITIONS

Parameter Simulated values

Number of events 5000 0.3, 0.5, 0.7 0.25

Threshold 0.5, 1, 2, 3, 4 Position of the central fiber (10, 10)

Number of photons in the 5 fibers 10, 6, 2 Photo detection efficiency (PDE) 20, 30, 40, 50%

C. Position detection algorithms Three position detection algorithms were used to calculate

the centroid for each count:

(1)

, where qi is the charge signal of the ith SiPM.

(2)

, where i is the SiPM with maximum charge signal.

(3)

, for the 3 neighbor signals which sum is maximum.

D. Results

The centroids in x and y directions were used to generate 2D images, as exemplified in Fig. 8. The image efficiency of these position detection algorithms, defined as the ratio between the number of centroids calculated and the total number of events, was determined for different sets of fibers or image pixels (Fig. 9) and for different values of PDE, and threshold. Results are shown in Figs. 10 and 11. Thresholds were defined to allow ignoring low signals from certain fibers.

Figure 8 Example of simulation images obtained with the 3 position detection algorithms, for PDE=50%, =0.3, =0.25, threshold=2.

Figure 7 a) Acquired spectrum: Vb=68.8V, T=20C. b) Simulated spectrum: = 0.6, = 0.3.

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The reverse analysis was carried out, calculating the radius around the central fiber within which 76% of events fall, as shown in Fig. 12. This percentage level was chosen because it represents the theoretical percentage for 2.35 of a Gaussian distribution, i.e., the FWHM. Most of the times, and especially for algorithms B and C, the centroids distribution is narrower than a Gaussian one, so this value gives us an overestimated approximation of the FWHM, i.e., of the spatial resolution.

Figure 9 Sets of fibers (1 mm2 image pixels)

Figure 11 Algorithm efficiency vs. threshold, for a PDE of 30% (same legend as Fig. 10).

Figure 10 Algorithm efficiency vs. threshold, for a PDE of 50%.

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CONCLUSIONS AND FURTHER WORK An application was developed to simulate a configuration where 240 SiPMs are used to readout wavelength shifting optical fibers coupled to a scintillation crystal. In this kind of configuration, the light levels at the end of the fiber are expected to be in the order of only a few photons for gamma rays in the range of 80 to 200 keV, so the SiPM is a very interesting readout device due to its excellent photon counting capability. On the other hand, the SiPM has high dark counts, so it is of great importance to discriminate this low light signal from the random dark noise signal. From the experimental measurements, it is evident that the stability of bias voltage and temperature is crucial for good signal stability and dark rate control of each individual SiPM. Cooling the SiPM significantly reduces the dark counts approximately by half at every 9C, but on the other hand it increases afterpulsing. Lowering the bias voltage reduces noise, but with loss of gain and PDE [3], which is critical for low-light level applications. The simulation allowed us to evaluate the impact of the simultaneously acquired dark counts into position detection algorithms and the results show that an image with good resolution can be obtained, despite the very low light levels. Of the three algorithms tested, algorithm C shows the best results for low light level centroiding, indicating that a sub-milimetric spatial resolution is possible, as suggested by the results in Fig. 12. Algorithm A leads to high efficiencies but only for thresholds over 3 and it is more vulnerable to changes in dark noise. On the contrary, algorithms B and C show better performance for lower threshold values, independently of the

dark noise average. This happens because these algorithms rely on maximum values.

Further work is currently under way for developing a small prototype of the proposed configuration, where all SiPMs will have a simultaneous readout triggered by a common gate based on the scintillation signals obtained by a PMT, thus reducing the impact of dark counts. A point image can then be created and compared with the simulation results. Preliminary measurements of the scintillation light retained in a fiber, made both with a PMT and a SiPM, clearly show that this external trigger is indispensable with the SiPM (Fig. 13).

ACKNOWLEDGMENT I.F. Castro is grateful to the IEEE 2009 NSS-MIC General and Scholarship Chairs for the Trainee Grant attributed.

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IEEE J. Quant. Electron., vol. 44, n. 2, 2008. [2] K. Yamamoto et al., Development of Multi-Pixel Photon Counter

(MPPC), IEEE Nucl. Sci. Symp. Conf. Rec., vol. 2, pp. 1094-1097, 2006.

[3] D. Renker and E. Lorenz, Advances in solid state photon detectors, J.Inst. 4, 4004-4052, 2009.

[4] B.W. Baumbaugh et al., Studies of SiPM and Scintillation Plates with Waveshifter Fiber and SiPM Readout, presented at the IEEE Nuclear Science Symposium, Orlando, FL, 2009.

[5] M. Yokoyama et al., Application of Hamamatsu MPPCs to T2K neutrino detectors, Nucl.Instrum. Meth. A, 610, pp. 128-130, 2009.

[6] P. Finocchiaro et al., Characterization of a Novel 100-Channel Silicon Photomultiplier Part II: Charge and Time, IEEE Trans. Elect. Dev., vol. 55, n. 10, pp. 2765-2763, 2008.

Figure 13 Spectra of scintillation light from 241Am retained in one fiber, compared to noise, with no external trigger applied.

Figure 12 Radius where 76% of events above threshold fall inside (PDE=50%). The same legend as above applies.

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