Ponente
Descripción
Silicon photomultipliers (SiPMs) are solid-state photodetectors that are increasingly
utilized in various fields, such as high-energy physics experiments [1,2], medical
imaging and dosimetry [3,4], biophotonics [5], light detection and ranging (LiDAR)
systems [6], and more. Although SiPMs present numerous advantages over classical
photomultiplier tubes (PMT), SiPMs do also have some limitations. One of the most
important limitations is their nonlinear response, because it limits their dynamic range.
Nonlinearity in SiPMs takes place when the number of impinging photons is
comparable to the number of pixels of the device. The effect depends on the time it
takes for the overvoltage of a pixel to recover after a breakdown avalanche. For an
incident light pulse, a fraction of photons may interact with unrecovered pixels, which
have lower trigger probability and gain, resulting in a SiPM signal with lower amplitude
than expected. The pixel overvoltage can be also reduced due to the voltage drop
across the readout-circuit resistance [7]. Consequently, nonlinearity depends on the
photon rate (i.e., both the amplitude and width of the light pulse) and the recovery time
of pixels in a complex way. Additionally, SiPMs exhibit both correlated and uncorrelated
noise, further complicating their performance [8–10].
Due to the complexity of the problem, an exact analytical treatment of the nonlinear
response of SiPMs is infeasible. However, a Monte Carlo (MC) treatment can
potentially include all factors that affect SiPM performance, allowing a detailed
simulation of the response of any SiPM by utilizing appropriate input parameters. The
Matlab MC code developed by Abhinav et al [11] is especially complete, as it simulates
the triggering of breakdown avalanches from photons and noise on an individual pixel
basis, including the pixel recovering and the reduction of the pixel overvoltage due to
the voltage drop across the readout-circuit resistance.
We used this MC code to conduct a systematic analysis of the different factors affecting
the nonlinear response of SiPMs, regarding both the output charge and the signal
shape [12]. To this end, we modified the code to improve the description of the
correlated noise and the trigger probability of recovering pixels. In addition, we
implemented new light pulse shapes and a simplified electrical model to more easily
identify the main parameters on which nonlinearity depends and to understand their
role. Simulations were shown to reproduce experimental data on the output charge for
scintillation light pulses as a function of both the pulse intensity and the SiPM operation
overvoltage.
We found that the shape of the response curve is quite universal, essentially
depending on the balance between the photon rate and the pixel recovery time.
However, there are other relevant factors. When the operation overvoltage is high, the
trigger probability of a pixel recovers faster than the pixel overvoltage, reducing
nonlinearity in a similar way as if the recovery time is made shorter. We also found that
nonlinearity is stronger for pulses of finite duration than exponential-like pulses with the
same mean photon rate. Additionally, we showed that the correlated noise increases
the effective gain of the SiPM in the linear region, having a minor influence on
nonlinearity. Indeed, prompt crosstalk was found to be suppressed rapidly at increasing
photon rate. However, afterpulsing and delayed crosstalk may still be relevant for
intense light pulses because these noise components lead to a lengthening of the
output signal.
Finally, we obtained phenomenological analytical expressions that fit both simulation
and experimental results of the mean output charge for light pulses of different shapes
and arbitrary intensity over a very wide range of SiPM parameters (e.g., overvoltage,
correlated noise, and photon detection efficiency) [12]. The proposed models provide a
simple but accurate description (at the level of a few percent) of the SiPM response in
the nonlinear region, clearly showing the relationships among the many variables of the
problem.
References
1. Lapington, J.S.; CTA SST Collaboration. The silicon photomultiplier-based camera
for the Cherenkov Telescope Array small-sized telescopes. Nuclear Instruments and
Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and
Associated Equipment 2023, 1055, 168433.
2. Depaoli, D.; Chiavassa, A.; Corti, D.; Di Pierro, F.; Mariotti, M.; Rando, R.
Development of a SiPM Pixel prototype for the Large-Sized Telescope of the
Cherenkov Telescope Array. Nuclear Instruments and Methods in Physics Research
Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2023,
1055, 168521.
3. Gundacker, S.; Heering, A. The silicon photomultiplier: fundamentals and
applications of a modern solid-state photon detector. Physics in Medicine & Biology
2020, 65, 17TR01.
4. Caccia, M.; Giaz, A.; Galoppo, M.; Santoro, R.; Martyn, M.; Bianchi, C.; Novario, R.;
Woulfe, P.; O’Keeffe, S. Characterisation of a Silicon Photomultiplier Based Oncological
Brachytherapy Fibre Dosimeter. Sensors 2024, 24, 910.
5. Bruschini, C.; Homulle, H.; Antolovic, I.M.; Burri, S.; Charbon, E. Single-photon
avalanche diode imagers in biophotonics: review and outlook. Light: Science &
Applications 2019, 8, 87.
6. Agishev, R.; Comerón, A.; Bach, J.; Rodriguez, A.; Sicard, M.; Riu, J.; Royo, S. Lidar
with SiPM: Some capabilities and limitations in real environment. Optics & Laser
Technology 2013, 49, 86–90.
7. Seifert, S.; van Dam, H.T.; Huizenga, J.; Vinke, R.; Dendooven, P.; Lohner, H.;
Schaart, D.R. Simulation of Silicon Photomultiplier Signals. IEEE Transactions on
Nuclear Science 2009, 56, 3726–3733.
8. Rosado, J.; Hidalgo, S. Characterization and modeling of crosstalk and afterpulsing
in Hamamatsu silicon photomultipliers. Journal of Instrumentation 2015, 10, P10031.
9. Gallego, L.; Rosado, J.; Blanco, F.; Arqueros, F. Modeling crosstalk in silicon
photomultipliers. Journal of Instrumentation 2013, 8, P05010.
10. Vinogradov, S. Analytical models of probability distribution and excess noise factor
of solid state photomultiplier signals with crosstalk. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and
Associated Equipment 2012, 695, 247–251.
11. Jha, A.K.; Van Dam, H.T.; Kupinski, M.A.; Clarkson, E. Simulating silicon
photomultiplier response to scintillation light. IEEE transactions on nuclear science
2013, 60, 336–351.
12. Moya-Zamanillo, V.; Rosado J. Understanding the nonlinear response of SiPMs.
Sensors 2024, 24, 2648.
