Stochastic Resonances in Photon Number Resolving Detectors
Shree Krishnamoorthy
1
, Harish Ravishankar
2
, Pradeep K. Kumar
3
and Anil Prabhakar
1
1
Indian Institute of Technology, Madras, Chennai, India
2
Indian Institute of Science, Bangalore, India
3
Indian Institute of Technology, Kanpur, India
Keywords:
Avalanche Photodiodes (APDs), Low Light Level, Photodetectors, Fiber Optics Sources and Detectors.
Abstract:
The photon number statistics of a coherent optical pulse will typically follow a Poissonian distribution. At
low photon numbers, a gated avalanche photo-detector (GAPD) is used to detect the presence of photons in
each optical pulse. GAPDs use a thresholding logic, but suffer from after-pulsing effects. The efficiency of
a GAPD was characterized and its after-pulses were analyzed by looking at the detection patterns obtained.
The GAPD was found to show evidence of stochastic resonance which affected the dark noise of the detector.
We post-process the detected bit patterns to eliminate the resonances and estimate the true dark count of the
detector. The GAPD was then used with a recirculating optical loop to build a multi-photon resolving detector
(MPRD). In the MPRD, the probability of detection at consecutive loop round trip times were used to estimate
the mean photon number. We quantify these statistics and establish a reliable measure of photon number at
an optical power of -94 dBm. The digital electronics was able to store data for 2
24
optical pulses, making the
statistical analysis meaningful.
1 INTRODUCTION
Quantum cryptography holds the promise of uncon-
ditional security (Bennett et al., 1984; Lo and Chau,
1999). However, practical implementations of quan-
tum key distribution, such as DPS-QKD or FC-QKD,
use coherent optical states that are susceptible to pho-
ton number splitting attacks (Norbert and Mika, 2002;
Inoue et al., 2003; Bloch et al., 2007; Valerio et al.,
2009). In the absence of purely single photon sources,
development of QKD systems need photon number
resolution (Hadfield, 2009). While, optical fibers
are easily adapted for quantum communication, the
detectors needed for photon number resolution are
not easily available and the development of photon
counting detectors continues to be of current inter-
est (Blasej et al., 2014). In the telecommunication
band, around 1.55 µm, PMTs have very low efficien-
cies of about 2% where as InGaAs avalanche pho-
todiodes (APDs) provide an efficiency of 20% with
lower dark counts (Hadfield, 2009). APDs operated
in Geiger mode indicate only the presence of or ab-
sence of photons and cannot resolve the number of
incident photons, making their output binary in na-
ture. The Geiger mode enhances the sensitivity, but is
accompanied by a degradation in the signal to noise
ratio (Kolb, 2014). For photon number resolution,
the incoming photons are redistributed to multiple de-
tection slots, using spatial or temporal multiplexing
methods (Fitch et al., 2003; Mogilevtsev, 2010). Tem-
poral multiplexing can be achieved by an optical fiber
loop connected to the coupler (Haderka et al., 2004;
Ravi and Prabhakar, 2011), and the timing informa-
tion can be used to gate the APD.
APDs are based on the avalanche process which
dictates the noise characteristics in them (McIntyre,
1966). Gated APD (GAPD) systems suffer from dark
counts and after-pulsing (Cova et al., 2004; Tosi et al.,
2009). Other than the known noises, our implemen-
tation of the GAPD shows evidence of stochastic res-
onance at low photon numbers. In this article we an-
alyze the probabilities of occurrence of different bit
patterns to extract the photon number statistics in the
presence of stochastic resonance. We first character-
ize the GAPD, and estimate the efficiency of detec-
tion. We then measure the photon arrival statistics and
compare them to theoretical predictions for a GAPD
in the presence of noise and underlying stochastic res-
onance.
We implement a MPRD with a recirculating op-
tical loop followed by the GAPD. When a coherent
state is input to the MPRD, the bit pattern that ensues
should follow a statistical distribution. The roundtrip
time of the circulating loop was less than one-eighth
40
Krishnamoorthy S., Ravishankar H., K. Kumar P. and Prabhakar A..
Stochastic Resonances in Photon Number Resolving Detectors.
DOI: 10.5220/0005335800400046
In Proceedings of the 3rd International Conference on Photonics, Optics and Laser Technology (PHOTOPTICS-2015), pages 40-46
ISBN: 978-989-758-093-2
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
of the time between coherent optical pulses input to
the loop. This allowed us to use digital electronics to
store and analyze the 8-bit pattern of 1’s and 0’s fol-
lowing each input pulse, and to repeat the exercise for
N = 2
24
input pulses. Our experiments validate the
Poissonian statistics of the coherent state down to an
average photon number of 0.024.
2 DETECTOR
CHARACTERIZATION
When counting photons, we often assume that the
sources of noise (typically shot and thermal noise)
are independent of the photon counts. In cases where
there are other low amplitude stationary processes
that look like noise, the assumption of independent
noise statistics breaks down. Stochastic resonance is
one such phenomenon that can cause higher null de-
tections at periodic intervals in a system using gated
detection, like in our system. We find a suitable op-
erating point for the GAPD and extract actual photon
detection probabilities with proper data analysis in the
presence of stochastic resonances.
2.1 Efficiency
Dark counts are a result of thermally triggered elec-
tron currents. We describe how to find the optimal op-
erating point for the detector and find average contri-
bution of the underlying noise. A null detection must
occur in the absence of any electron currents, trig-
gered either thermally or by incident photons. We as-
sume that dark counts occur, with a probability p
d
(1)
and an efficiency η for the detector. When a pulse
with mean photon number n is incident on the detec-
tor from a coherent laser source, we could register a
’1’ either due to a photo-generated avalanche process,
or due to the dark noise of the detector. The probabil-
ity of no detection, p(0), occurs when there are no
photons and there is also no dark count, i.e.,
p(0) = e
ηn
(1 p
d
(1)). (1)
To arrive at the probability of a positive detection,
p(1), we recognize that a detection occurs either
due to the presence of a photons, with a probability
(1 e
ηn
), or due to the dark count, with a probabil-
ity p
d
(1). However, since the two events are indepen-
dent, we must subtract the probability of both events
occurring together, i.e., p
d
(1)(1 e
ηn
). Thus,
p(1) = (1 e
ηn
) + p
d
(1) p
d
(1)(1 e
ηn
)
= 1 p(0). (2)
Figure 1: Null detections with increasing mean photon
numbers, used to find detector efficiency η.
Figure 2: Detection efficiency for different case tempera-
tures and dark counts at constant bias. The APD was cooled
by an internal Peltier, to about 20
C below the case temper-
ature.
For our experiments, we have used an InGaAs APD
(model NR8300FP from NEC) with an internal Peltier
cooler. The detector case was further cooled by an
external Peltier stage. The breakdown voltage of the
APD was about 71 V at a case temperature of 4
C. To
operate the APD in Geiger mode, we bias the APD
below 71 V and apply a gating voltage of 3.3 V for
5.2 ns. The GAPD followed by digital counting elec-
tronics (FPGA based), acted as one photon counter.
The digital electronics had 2 GB RAM, or 16 Gbits,
to easily collect and store obtained statistics.
Fig. 1 shows the dependence of p(0)/(1 p
d
(1))
on n, from which we extract the efficiency η of the
detector. At a bias of 69.7 V and a detector case
temperature of 4
C, we found that the efficiency η
was 0.0893±0.006. We also confirm that a change
in temperature and bias conditions change the dark
count and the efficiency of the detector, as shown in
Fig. 2.Thus, we find the optimal operating point for
the GAPD at a case temperature of 2
C with a bias
voltage of 69.7 V, where η = 0.11 , and the dark
count p
d
(1) = 0.085. For a 10% higher detection
rate than the dark count the null detection probability
is p(0) = 0.9065. Substituting p(0) in (1) and using
η = 0.11, we estimate the average photons per pulse
to be n = 0.0848, or one true detection for every 12
gate pulses at the GAPD. The average photon number
StochasticResonancesinPhotonNumberResolvingDetectors
41
Figure 3: Effect of bias voltage and optical input, on the
time between consecutive detections. Each 0 bit corre-
sponds to a delay of 1µs.
resolution can be further improved by using this de-
tector after a recirculating loop as described in Sec.3.
2.2 Detection Probabilities and
Stochastic Resonance
In the previous section, we obtained the optimal op-
erating point for the GAPD by studying the average
noise statistics. However, we are in a position to look
at the statistics of how the detector responds in Geiger
mode, both with and without an incident optical pulse.
Consider a coherent optical pulse train, with an
average of n photons in each pulse, incident on the
detector. For the experimental setup in the inset of
Fig. 3, we send N such pulses, and collect statistics
on the number of times the detector is triggered. For
each received pulse, if a null detection occurs then a
“0” is recorded and when a positive detection occurs
a “1” is recorded. We thus obtain binary statistics of
(0,1) for each received pulse.
For N incident optical pulses, positive detections
will follow a binomial distribution with a mean µ =
N p and a variance of N(1 p)p, p , p(1) is the prob-
ability of detection for each incident pulse. Averaging
over the number of detection events, we get an esti-
mate ¯p = µ/N = p , with the standard deviation
σ
N
=
r
p(1 p)
N
decreasing with increasing N.
There is a 1 µs gap between successive gate pulses.
Analyzing the digital bit pattern at the output of the
GAPD is akin to obtaining a digital frequency spec-
trum, with a resolution of 1 MHz. In Fig. 3, we
plot the frequency of occurrence of the m consecu-
tive 0-bits for N = 2
24
bits collected in each exper-
iment.We observe an increased occurrence of some
patterns when compared to others, as indicated by the
arrows. These “resonances” are quenched when op-
tical pulses of power of -72 dBm are provided. The
Figure 4: GAPD behavior in terms of bit pattern occu-
rances, with change in bias and temperature. The arrows
mark anomalous increases in event detections, and are at-
tributed to a stochastic resonance.
Figure 5: Frequency of stochastic resonance of the GAPD,
with inset showing the experimental setup used.
occurrence of patterns at periodic intervals and its re-
duction due to the incidence of a few photons is sug-
gestive of a stochastic resonance in the system (Gam-
maitoni, 1995).
In Fig. 4, we see that these resonances persist,
and are even magnified, as we change the bias and
increase the temperature. Both bias voltage and the
temperature signal change the noise in the system and
affect the intensity of the resonance. To further con-
firm the stochastic resonance behavior, we perform
a separate experiment with the same detection sys-
tem. We used a laser modulated by a sinusoidal sig-
nal, as shown in the inset of Fig. 5. We found that the
GAPD shows a four fold increase in signal to noise ra-
tio (SNR) close to 66 kHz. This enhancement in SNR
is related to the Kramer’s rate of switching between
the 0 and 1 bit for the binary output detector system
(McDonnell et al., 2008).
Previous experiments on the GAPD at a lower bias
of 67 V, had established that a 1 µs gap between gate
pulses would be sufficient to release any trapped en-
ergy (Kumar et al., 2009). With increasing ON time
of the laser pulses (20 ns), longer dead times of up to
PHOTOPTICS2015-InternationalConferenceonPhotonics,OpticsandLaserTechnology
42
Figure 6: After pulsing statistics in the presence of stochas-
tic resonances. The APD was gated every 1 µs.
10 µs in the GAPD has been reported in other studies
(Ben-Michael et al., 2006; Tosi et al., 2009).
Longer dead times are attributed to after-pulsing
effects in the avalanche photodetector. We take a
closer look at one of the data sets in Fig. 4, with optics
off, and estimate the probability of dark count detec-
tion in the presence of stochastic resonances. Since
p
d
< 0.1, the probability of detecting more than two
after-pulses becomes negligible. Hence, we restrict
our analysis to understanding the probability of ob-
serving two 1s separated by m 0s. This is equivalent
to the probability of obtaining m 0s followed by a 1
in the state diagram model for the gated Geiger mode
APD, developed by Kolb, for obtaining SNR with af-
terpulsing (Kolb, 2014). Assuming that our first bit is
detected with a probability p
d
, followed by m 0s, the
next bit is detected with a probability p
2
d
(1 p
d
)
m
.
Repeating this experiment N times, we obtain
P(m) = N p
2
d
(1 p
d
)
m
. (3)
To estimate the probability p from the data we ignore
the regions affected by the resonance and fit the re-
maining data using (3). In all the collected data-sets,
we found that resonance peaks occur every m = 16
pulses, consistent with one of the stochastic resonance
peaks in Fig. 5. The width of each resonance is 4 con-
sistently for all bias and temperature conditions. With
this information we exclude the data around the local
maxima, fit the rest of the data to a semilog function,
find the slope and extract p
d
= 0.024. Since the data
was obtained in the absence of any optical signal, we
found that removing the resonance peak in the col-
lected data, while post-processing, decreased the ef-
fective dark counts by a factor of four. In Fig. 6, the
residuals were scaled with respect to the number of
events found experimentally for each point. Fig. 6
also shows that we can observe stochastic resonances
till approximately 0.2 ms, corresponding to m = 200,
beyond which the residual error in our fit builds up.
Figure 7: The MPRD setup showing timing information
(T
i
),coupler splitting ratio (ε),and transmittances (θ
i
).
3 RESOLVING PHOTON
NUMBERS
The MPRD setup consists of a coherent, pulsed laser
source, a variable optical attenuator (VOA) followed
by an optical recirculating loop and GAPD as shown
in Fig. 7. The laser pulses, attenuation of the VOA
and the gating of GAPD are computer controlled. To
analyze the working of the MPRD, we use the GAPD
characteristics obtained in Sec. 2, and estimate the
decrease in detection probability for each recircula-
tion of the optical pulse. Finally, we analyze the bit
patterns obtained at the detector for consecutive de-
tections and compare them to theoretical probability
estimates. With 2 GB RAM, we were able to collect
over a million instances of the experiment.
3.1 Experimental Setup
The MPRD experiment was first reported in (Ravi and
Prabhakar, 2011). A laser pulse of 5.2 ns pulse width
is sent through the MPRD. We chose a delay fiber
length of 2 km, which gave the detector 10 µs to re-
cover between successive measurements. The recir-
culation repeats until the pulses are sufficiently atten-
uated in the system. We used a 3 dB splitter, connec-
tors with about 0.5 dB loss and a 2 km long spool with
0.4 dB loss. The optical path lengths were adjusted so
that the return pulses arrived in synchronization with
the system clock. For this purpose, we used an optical
fiber array with length increasing in steps of 20 cms
(1 ns delay) in series with our fiber spool until our
pulses were correctly synchronized and the detection
probability was maximized.
All the elements in the MPRD were controlled
electronically, by a XILINX (SPARTAN XC3S400)
field programmable gate array (FPGA). The FPGA
was clocked at 24 MHz and two digital clock man-
agers (DCMs) available on the FPGA were used to
StochasticResonancesinPhotonNumberResolvingDetectors
43
Figure 8: Pulse travel time from the laser to the detector
after multiple round trips in the MPRD (Number of gating
pulses, N=8).
multiply the clock frequency to 48 MHz and to pro-
vide a 90 degree phase shifted signal. These were
used to generate laser pulses of width 5.2 ns and gat-
ing pulses of width 10.4 ns. The FPGA was used for
pulsing the laser, gating the APD, setting of bias and
threshold. The variable optical attenuator was used to
change the incident power or photon number in the
optical pulse. At the output of the comparator in the
GAPD, eight detections are recorded for each laser
pulse transmitted through the MPRD, giving us a byte
of data for each laser pulse, with each bit synchro-
nized to the round trip time of the recirculating loop.
3.2 Timing Synchronization in MPRD
To synchronize the detector gates to the incoming op-
tical pulses from the recirculating loop, we look at the
pulse arrival times in Fig. 8. The pulses arrive at the
GAPD with a fixed delay T
delay
from the laser. The
detector has a gating period of 10.4 ns twice that of
the optical pulse. The off time (T
off
) of the detec-
tor needs to be precisely matched to the subsequent
pulse arrival. If the pulse takes time T
1
to travel up
to the coupler, time T
2
to travel from the edge of
the coupler to the GAPD, time T
3
to loop once in
the fiber and time T
c
to travel through the coupler.
Thus, the arrival time for the k
th
pulse at the detec-
tor is found to be T
1
+ T
c
+ (T
3
+ T
c
)k + T
2
. We set
T
delay
= T
1
+ T
c
+ T
2
using multiple sections of opti-
cal fiber, while T
off
= T
3
+ T
c
is set electronically.
3.3 Photon Redistribution Statistics
The coupler has a division ratio of ε : 1 ε, the op-
tical delay fiber has a transmittance t
f
, the connec-
tors have a transmittance of θ
i
=θ and the detector has
an efficiency of detection η as shown in Fig. 8. We
calculate the transmission of the k
th
pulse (Ravi and
Prabhakar, 2011)
T
eff
k
= θ
2
ε
k1
(1 ε)
2
(t
f
θ
3
θ
1
)
k
θ
4
η. (4)
Figure 9: Average detection probability of successive return
pulse in MPRD.
Figure 10: Measured versus predicted bit pattern probabil-
ities of detection patterns obtained in MPRD at -63 dBm.
Modified from (Ravi and Prabhakar, 2011).
For a coherent input with an average photon number
n, the k
th
detection pulse corresponds to an average
photon number of nT
eff
k
.
Starting from an average photon number n, the
theoretical prediction for the probability of detection
p
k
(1) for the k
th
pulse is,
p
k
(1) = 1 e
ηnT
eff
k
| {z }
no photon
(1 p
d
)
| {z }
no noise
. (5)
For n = 30, η = 0.15, T
eff
k
= 0.398 (corresponding to
4dB loss), and p
d
(1) = 0.014, Fig. 9 shows the de-
creasing probability of a detection for each round trip
and we observe a good match between our theoretical
estimates and our experimental observations.
For each byte recorded, we analyzed bit patterns
for 3, 4 and 5 bits as shown in Fig. 10. An input pulse
with average power of 63 dBm at the input of the
3dB splitter in the MPRD, goes through seven round
trips through the optical loop, with a loss of 4 dB per
recirculation, to produce the last detection bit. The
last bit out of the recirculating loop will, now, have an
average power of 94dBm, assuming a 5.2ns pulse
of optical wavelength 1.55 µm, corresponding to an
average photon number of 0.024. Even so, the Poisso-
nian statistics of a coherent pulse are well preserved
and the occurrence of a bit pattern follows the pre-
dicted probabilities.
PHOTOPTICS2015-InternationalConferenceonPhotonics,OpticsandLaserTechnology
44
4 SUMMARY
This article describes the characterization of a gated
avalanche photo-detector, used subsequently in a
multi-photon resolving detector. We first experimen-
tally characterize the GAPD and find its efficiency.
We found that the GAPD was susceptible to stochas-
tic resonance, which was affected by temperature and
bias. The stochastic resonance was further investi-
gated, and we saw that it had characteristic frequency
around 66 kHz. When we used gated detection, with
a delay of 1 µs between gate pulses, we were in ef-
fect digitally sampling the stochastic resonance. Dis-
counting these resonances in our experimentally mea-
sured probabilities, we were able to characterize the
GAPD for very low average photon numbers.
A recirculating loop is a simple way of splitting
a Poissonian state into a series of temporal pulses.
We described the statistical properties of such a multi-
photon resolving detector. In our experiments, the re-
circulating loop was set up to achieve a delay of 10µs
between successive optical pulses, while we gated the
avalanche photodiode every 1µs. After each input co-
herent optical pulse we recorded the output for 8 gate
pulses as one byte, and did this for N = 2
24
optical
pulses. We then searched for correlations between
successive gate pulses in the data bytes by looking
at the bit patterns for 3, 4 and 5 bits. The probability
of occurrence of a bit pattern followed the predicted
probabilities, within the noise bounds of the system.
Thus, we conclude that the MPRD could be used for
photon number resolution, for average photon num-
bers as low as n = 0.024 per pulse.
We observed that the stochastic resonance de-
pends on both APD bias and temperature. Conse-
quently, we were able to adjust these parameters and
avoid the resonance, as we set up our photon number
resolving experiments. We believe that we are the first
authors to report on stochastic resonances in a GAPD
system. Further investigations about the origins of the
resonace, along with an appropriate statistical noise
model, will help improve the performance of single
photon detectors.
ACKNOWLEDGEMENTS
This work was partly funded by the Department
of Science and Technology, India under Grant No.
SR/S3/EECE/21/2005. HR and PK were at IIT-
Madras during the course of their studies. HR is also
grateful to IIT-Madras for supporting his work as an
Innovative Student Project.
REFERENCES
Ben-Michael, R., Itzler, M. A., Nyman, B., and Entwistle,
M. (2006). Afterpulsing in InGaAs/InP single photon
avalanche photodetectors. In Dig. LEOS Summer Top.
Meet., pages 15–16, Quebec City. IEEE.
Bennett, C. H., Brassard, G., et al. (1984). Quantum cryp-
tography: Public key distribution and coin tossing. In
Proc. IEEE Int. Conf. Computers, Systems and Signal
Processing, Bangalore, volume 175-179, Bangalore.
New York, IEEE.
Blasej, K., Prochazka, I., and Kodet, J. (2014). Photon
counting detector for high-repetition-rate optical time
transfer providing extremely high data yield. Optical
Engineering, 53:081903.
Bloch, M., McLaughlin, S. W., Merolla, J. M., and Patois,
F. (2007). Frequency-coded quantum key distribution.
Opt. Lett., 32:301–303.
Cova, S., Ghioni, M., Lotito, A., Rech, I., and Zappa, F.
(2004). Evolution and prospects for single-photon
avalanche diodes and quenching circuits. J. Mod. Op-
tic, 51(9-10):1267–1288.
Fitch, M., Jacobs, B., Pittman, T., and Franson, J. (2003).
Photon-number resolution using time-multiplexed
single-photon detectors. Phys. Rev. A, 68(4):043814.
Gammaitoni, L. (1995). Stochastic resonance and the
dithering effect in threshold physical systems. Phys.
Rev. E, 52(5):4691.
Haderka, O., Hamar, M., and Peˇrina Jr, J. (2004). Exper-
imental multi-photon-resolving detector using a sin-
gle avalanche photodiode. Eur. Phys. J. D - Atomic,
Molecular, Optical and Plasma Physics, 28:149–154.
Hadfield, R. H. (2009). Single-photon detectors for opti-
cal quantum information applications. Nat. photonics,
3(12):696–705.
Inoue, K., Waks, E., and Yamamoto, Y. (2003). Differential-
phase-shift quantum key distribution using coherent
light. Phy. Rev. A, 68:022317.
Kolb, K. (2014). Signal-to-noise ratio of geiger-mode
avalanche photodiode single-photon counting detec-
tors. Optical Engineering, 53(8):081904–081904.
Kumar, P., Thevan, S., and Prabhakar, A. (2009). Optimiza-
tion of gated photodetection for quantum key distri-
bution. In SPIE Europe Optics and Optoelec. Conf.,
Prague. SPIE.
Lo, H.-K. and Chau, H. F. (1999). Unconditional security
of quantum key distribution over arbitrarily long dis-
tances. Science, 283(5410):2050–2056.
McDonnell, M. D., Stocks, N. G., Pearce, C. E. M.,
and Abbott, D. (2008). Stochastic resonance: from
suprathreshold stochastic resonance to stochastic sig-
nal quantization. Cambridge University Press, Cam-
bridge.
McIntyre, R. (1966). Multiplication noise in uniform
avalanche diodes. IEEE Trans. Electron Devices, ED-
13(1):164–168.
StochasticResonancesinPhotonNumberResolvingDetectors
45
Mogilevtsev, D. (2010). Calibration of single-photon
detectors using quantum statistics. Phys. Rev. A,
82(2):021807.
Norbert, L. and Mika, J. (2002). Quantum key distribu-
tion with realistic states: photon-number statistics in
the photon-number splitting attack. New J. of Phys.,
4(1):44.
Ravi, H. and Prabhakar, A. (2011). Coherent state statistics
from time-resolved photon counting. In SPIE OPTO,
pages 79600S–79600S, San Francisco. SPIE.
Tosi, A., Mora, A. D., Zappa, F., and Cova, S. (2009).
Single-photon avalanche diodes for the near-infrared
range: detector and circuit issues. J. Mod. Optic, 56(2-
3):299–308.
Valerio, S., Helle, B. P., Nicolas, C., Miloslav, D., Norbert,
L., and Momtchil, P. (2009). The security of prac-
tical quantum key distribution. Rev. of Mod. Phys.,
81(3):1301.
PHOTOPTICS2015-InternationalConferenceonPhotonics,OpticsandLaserTechnology
46