New infrared camera of the Caucasian Mountain Observatory of the SAI MSU:
design, main parameters, and first light

Zheltoukhov S. G.1,2, Tatarnikov A. M.1,2a, Belyakova A. A.2, Koksharova E.
A.2

1 Faculty of Physics, M.V.Lomonosov Moscow State University, Moscow 119991,
Russia.
2Sternberg Astronomical Institute, M.V.Lomonosov Moscow State University,
Moscow 119191, Russia.
E-mail<EMAIL_ADDRESS>
This paper presents a prototype of an infrared photometer, created at SAI of
MSU based on the commercial infrared module Gavin-615A. The operating spectral
range of the photometer is 3-5 $\mu$m. Investigations of the photometer’s
detector have shown that its parameters coincide with those stated by the
manufacturer. The nonlinearity of the detector does not exceed $\sim 5\%$
across the entire signal range, and coefficients for correction functions were
determined. Additionally, we determined the readout noise $RN=1200\pm 210$ e-,
the conversion coefficient GAIN $=520\pm 9$ e${}^{-}/$ADU, the signal
magnitude of the bias frame BIAS $=960.5\pm 2.2$ ADU, and the dark current
$\approx(9.3\pm 1.1)\cdot 10^{6}$ e-/s, which is the sum of the detector’s
dark current and the radiation from the entrance window of the detector
module. The value of dark current was measured at a window temperature of
$6^{\circ}$C. Observations commenced with the photometer at the 2.5-m
telescope of the Caucasian Mountain Observatory of MSU, with the first results
presented in this paper. The unvignetted field of view was
$30^{\prime\prime}$. In the $M$ band under good atmospheric conditions, an
image quality close to the diffraction limit was achieved. Images of a star
with brightness $L=7.96$ and $M=6.78$ were obtained over the 20-second
exposure time and a SNR$\sim 10$ ratio. t is shown that at high image quality
with SNR=3 and exposure of 20 seconds it is possible to observe stars up to
$L\sim$9m and $M\sim$8m. The main module of the photometer was also used in
measurements of the sky background brightness.

PACS: 95.85.Jq

Keywords: IR astronomy, photometry.

DOI: 10.55959/MSU0579-9392.79.2410801

## Introduction

The infrared range occupies almost 10 octaves on the electromagnetic waves
scale, while the visible range, in which most astronomical observations are
made —just one octave. All types of astronomical objects — from exoplanets and
active galactic nuclei to solar system bodies and artificial satellites can be
observed in the infrared range. At the same time, observations in the IR range
have a number of advantages: the maximum emission of cold objects (stars of
late spectral types, dust envelopes, interstellar gas-dust clouds, etc.) falls
in the IR region of the spectrum, low interstellar absorption allows us to
observe objects hidden behind dense dust clouds, lower sensitivity to
atmospheric turbulence makes it easier to obtain high angular resolution, and
the sharp decrease in light scat tering in the Earth’s atmosphere with
increasing wave length allows for daytime observations in the mid-IR range.

The possibility of making observations of faint objects in the IR range
depends largely on the location of the observatory and its astroclimate.
Regular observations in this region of the spectrum are carried out in Russia
in two observatories — the Crimean Astronomical Station of the SAI MSU with a
single-element photometer based on an InSb photodiode ([1]) and the Caucasus
Mountain Observatory of the SAI MSU (CMO, [2]) with the ASTRONIRCAM
spectrograph camera ([3]) based on the Hawaii-2RG matrix detector. The
astroclimate of CMO is well studied. This observatory is well suited for IR
observations due to its high altitude (2110 m), low water vapor amount in the
atmosphere (median PWV less than 8 mm [4]), and high image quality ([5]).
According to [6], 1 square arcsec of the night sky has an average brightness
of $J=15.5^{m}$, $H=13.7^{m}$, $K=13.1^{m}$, which corresponds to the best
observatories of the world located at similar altitudes above sea level.

In recent years, significant progress has been made in the technology of IR
detectors — the size of the sensitive region is increasing, quantum efficiency
is close to unity, and the cost of some detector is decreasing. Estimates made
in [7] show that when using a ground-based telescope not optimized for IR
observations, modern commercial matrix detectors can be used at wavelengths up
to 5 µm — noise limitations in observations of faint objects will be
determined mainly by background radiation, not by the noise of the detector
itself.

At the end of 2022, MSU acquired a commercial IR matrix detector designed for
thermal imaging cameras with an operating wavelength range of $3-5$ µm, on the
basis of which we built a prototype of an astronomical IR camera, which was
given the abbreviation LMP — L and M bands Photometer by the CMO and installed
in 2023 on the 2.5-m telescope of this observatory. In this paper we present a
characterization of the LMP camera as an instrument for astronomical
observations in the $3-5$ µm wavelength region and the results of the first
observations with it.

##  1\. Instrument design

At present, the LMP photometer is assembled according to the scheme proposed
earlier in our paper [7]. It is not the most optimal scheme from the point of
view of the instrumental background value, but it allows us to build a working
instrument at minimal cost. In the future, we plan to add a focus reducer and
move all the optical elements of the camera into a separate cooled module.

The photometer is based on a Gavin-615A light-sensitive module with a 640x512
HgCdTe matrix as an image detector cooled to $\approx 82$ K by a Stirling
machine. From the basic model of the module, the manufacturer, at our request,
removed the internal bandpass filter. This made it possible to extend the
spectral range of the camera sensitivity and to use external light filters
realizing standard photometric bands coinciding with the windows of
transparency of the Earth’s atmosphere.

Figure 1: Transmission curves of $L^{\prime}$ and $M^{\prime}$ filters and the
Earth’s atmosphere for an altitude of 2 km above sea level and a PWV=5 mm

Initially (until November 2023), $L$ $(\lambda_{c}=3.7$ $\mu$m,
$\Delta\lambda_{0.5}=0.49$ $\mu$m) and $M$ $(\lambda_{c}=4.8$ $\mu$m,
$\Delta\lambda_{0.5}=0.54$ $\mu$m) filters similar to those used in the
single-channel infrared photometer on the 1.25-m ZTE telescope of the Crimean
Astronomical Station [1]. The expansion of the sensitivity range also allowed
us to install the $K$ filter with a central wavelength of 2.2 $\mu$m, but the
quantum efficiency of the camera at this wavelength is several times lower
than in the main range, and only the brightest objects can be observed with
it. As suggested in [7], mirrored surfaces are installed around the light
filters to reduce the instrumental background from the filters. All the light
filters, as well as the open aperture and calibration plug, are mounted in a
wheel driven by a stepper motor. A spring-loaded stop mechanism (detend
mechanism) is used to lock the wheel in the operating position. The filter
change time is approximately 5 s.

In November 2023, we replaced the $L$ and $M$ filters with new ones
manufactured by the Russian company ALKOR Technologies
LLC111https://alkor.net/, realizing the photometric bands $L^{\prime}$ and
$M^{\prime}$ of the MKO-NIR ([8]) system. Their response curves are shown in
Fig. 1. They are chosen to fit optimally into the corresponding transparency
windows of the Earth’s atmosphere. The average transmission of the filters
calculated by the formula $T_{avr}=\int T(\lambda)d\lambda/FWHM$, the central
wavelength, and other filter parameters are given in Table 1.

Table 1: Filter parameters Parameter | $L^{\prime}$ | $M^{\prime}$
---|---|---
Central wavelength, $\mu$m | 3.77 | 4.68
FWHM, $\mu$m | 0.63 | 0.2
Cut-on (at 10% of the peak), $\mu$m | 3.39 | 4.52
Cut-off (at 10% of the peak), $\mu$m | 4.18 | 4.83
Average transmission, % | 92 | 86
Out-of-band transmission, % | <0.2 | <0.5
Substrate diameter, mm | 25
Light diameter, mm | 20
Thickness, mm | 3

For the possibility of manual calibration of the device, a hole is provided in
the case, into which a cooled (for measuring dark current) or heated metal
plate (for obtaining a map of pixel sensitivity distribution) can be inserted.

All main parts of the device body and filter wheel are 3D-printed from PETG-
plastic. Experience has shown that its stability is sufficient to ensure the
required positioning accuracy of all photometer components. Fig. 2 and Fig. 3
show the 3D model of the setup and its photos. As can be seen, the Gavin-615A
photosensitive module is mounted on a monolithic part (shaded red in the 3D
model) with a flange thickness of 20 mm and a mounting table thickness of 8
mm. The part has a 30% fill rate when printed in 0.2 mm thick layers. The
total weight of the photometer is 1350 g, of which 900 g is the photosensitive
module.

Figure 2: 3D model of the photometer with filter wheel (left) and a photo of
the finished device from the side of the filter wheel (right).

Figure 3: Photo of the finished device (left) and the photometer mounted on
the telescope (right).

Images are registered using a single-board computer Banana Pi BPI-M5, based on
a 4-core Cortex-A55 processor under the Ubuntu 20.04. The computer is
installed on the telescope near the camera, since the use of USB 3.0 port for
data transfer from the camera does not allow to place the computer far enough
away. This choice of computer is due to the fact that from the manufacturer we
managed to get the basic software (SDK) only for aarch64 architecture. On the
basis of the SDK, which lacked some important functions, we developed our own
software in C++ and Python. It can be used to acquire frames and control
camera parameters through the built-in serial port. It is possible to control
exposure in the range from 346 microseconds to 50 milliseconds, frame reading
frequency, reading mode (raw frame, frame calibrated with internal algorithms
of the module, color frame with superimposed thermal palette) and shutter
trigger mode (automatic exposure start or using an external signal), as well
as to get information about the state and temperature of the detector. On the
basis of our improved SDK we wrote programs both for automatic acquisition of
observing series and a graphical user interface for the operator of the 2.5-m
telescope of CMO. The computer also controls the filter wheel and the
instrument power supply. The observation control system with the LMP
photometer is integrated into the Oplan system for planning and controlling
observations of the 2.5-m telescope.

##  2\. Observations

Astronomical observations with the LMP photometer were carried out on the
2.5-m telescope of CMO. The telescope has one Cassegrain focus, two main
Nesmith focuses (overlooking the balconies and equipped with derotators) and
two additional Nesmith focuses, which are simply holes in the middle of the
telescope tube. The LMP camera is mounted in one of the additional focuses.
During the observations, low-frequency modulation of the light flux with an
angular amplitude of $10^{\prime\prime}-15^{\prime\prime}$ for point objects
and $1^{\prime}$ for extended objects was performed by moving the telescope.
Depending on the brightness of the object and the planned total duration of
accumulation, the number of individual frames and the exposure time in each
frame after moving the telescope tube were selected. The time taken by the
telescope to move the telescope is practically independent of the displacement
angle (within the angles used for modulation) and is 3 s.

To measure the brightness of the sky background, we took a photometer from a
telescope. The photometer was mounted on a massive base so that its optical
axis was positioned horizontally. A ZnSe lens with a focal length of 38 mm was
installed in front of the entrance window with the filter. The sky radiation
was guided into the lens using a flat mirror fixed on the axis of a stepper
motor. By rotating the mirror, the field of view of the photometer was changed
on the celestial sphere in such a way as to perform scanning from the zenith
to the horizon in the selected vertical.

Most of the measurements used to obtain the parameters of the camera were made
with the black body (BB) model made at the SAI many years ago. This device is
a heater in the form of a spiral located on the perimeter of a metal cylinder.
The cylinder is placed inside an insulating container. Asbestos cloth is used
for thermal protection inside the container. Radiation from the heated cavity
of the cylinder passes through a small hole in its base. In front of the hole,
a rotating disk with $34$ holes of different diameters is mounted on heat-
insulating legs, the use of which allows to vary the area of the radiating
surface (the heat insulation eliminates the heating of the disk and reduces
its own radiation of the diaphragms). The BB temperature is measured using a
laboratory thermometer with a scale from $200$ to $300^{\circ}$C, which is
placed in the cavity through a hole in the opposite base of the cylinder. Due
to the large mass of the inner cylinder and high thermal inertia, the time to
establish the operating temperature of the BB is about $5$ hours, which makes
it possible to obtain high temperature stability in short time intervals
required for measurements.

##  3\. Camera characterization

The basis of the LMP photometer is a light-sensitive module Gavin-615A
manufactured by Global Sensor Technology (China) on the basis of HgCdTe
640x512/15$\mu$m MWIR detector and RS085 cryomodule. The manufacturer reports
only some parameters of the detector (see Table 2). In addition to these basic
parameters, the GAIN, read noise, dark current and BIAS are required to
process the observations.

Table 2: Parameters of the Gavin-615A module installed in the LMP photometer (according to the manufacturer) Parameter | Value
---|---
Detector | HgCdTe
Format | 640x512
Pixel size | 15x15 $\mu$m
Sensitivity spectral region (at 50% level) | 3.0 - 4.9 $\mu$m
Nonlinearity | < 8%
Pixel capacity |  $7.8\cdot 10^{6}$ e-
NETD |  $\leq 20$ mK (at 23∘C)
Discretization | 14 bit
Operating temperature of the detector | 85 K
Cool down time |  $\leq 8$ minute

###  3..1 Nonlinearity

Detector nonlinearity means the nonlinear dependence of the detector response,
represented in relative digital ADU units and recorded in the final image
file, on the magnitude of the incident radiation flux. For a constant
radiation flux, this is equivalent to an accumulation time dependence.

We took a series of frames of the BB with different accumulation times: from
the minimum $\approx$0.35 ms to $\approx$16 ms, when the filling of the cell
capacitance occurred. Fig. 4 shows a plot of the dependence on exposure $t$ of
the average signal $F_{meas}$ in the center region of a 100x100 pixel frame.
Assuming, as was done in [9], that in the first measurements the nonlinearity
is small and comparable to the contribution of noise, we drew a straight line
$s(t)$ along the four starting points to illustrate the expected signal values
assuming linearity of the detector response. The monotonic deviation of the
recorded signal from this straight line is clearly visible in the figure.

Figure 4: Dependence of the signal on the accumulation time $t$ (points) and
the line $s(t)$ drawn along the four initial points

Then, according to the algorithm from [9], the values $s(t)/F_{meas}-1$ were
calculated. Their dependence on the measured signal has a complex form (see
Fig. 5), which can be approximated by a polynomial of degree 6-7 $f(F_{meas})$
or by the function $f(F_{meas})=0.051-50/(F_{meas}-400)$. Knowing this
function allows us to make a correction for nonlinearity:
$F_{corr}=F_{meas}[1+f(F_{meas})]$. The degree of the polynomial turns out to
be larger than in the [9], which suggests using the 3rd degree, but smaller
than the 7-9 degree in the [10] pipeline. The dependence itself is also
different — in [9] it is a parabolic dependence, while in ours it is
hyperbolic.

Figure 5: Dependence of the nonlinearity magnitude $NL=s(t)/F_{meas}-1$ on the
mean signal (points) and its approximation by a hyperbola (solid line)

###  3..2 Conversion coefficient

The ratio between the digital data in ADU units and the number of
photoelectrons captured by the detector is characterized by the conversion
coefficient (GAIN), which is measured in [e-/ADU].

To measure the GAIN value, we obtained two series of 11 frames of the BB with
pairwise equal accumulation times. The data were corrected for nonlinearity
and the average signal level in ADU as well as the variance of the pairwise
frame differences were calculated from them. The dependence of the signal
variance on the average level was plotted from these series (Fig. 6). The GAIN
value is defined as twice the inverse of the slope of the straight line
approximating this dependence. For LMP camera, GAIN = $520\pm 9~{}e^{-}/$ ADU.

Figure 6: Dependence of variance of difference frames on the average signal

###  3..3 Readout noise and bias frame

Another important parameter of any detector that determines its ability to
observe faint objects — readout noise (RN). It can be measured from a series
of bias frames, which are usually recorded at zero exposure with the shutter
closed. However, the light-sensitive module of an LMP photometer has no
shutter (unlike CCD cameras), it cannot be set to zero exposure, and even in
the dark it stores signal from ambient thermal radiation. Therefore, to record
bias frames, we used the minimum available exposure and installed a metal
plate cooled in liquid nitrogen in front of the entrance window of the module.

In this work, 4 series of 1000 frames with an accumulation time of 346
microseconds were obtained to estimate the readout noise and master-bias frame
formation. From these series, the average frame (bias frame) and the
distribution frame of the standard deviation of the recorded signal (i.e., the
distribution frame of the read noise value) were calculated by pixel-by-pixel
signal averaging. The frame-averaged RN $=2.3\pm 0.6$ ADU or, in terms of
electrons, $1200\pm 310$ e-.

To determine bias, the same series with minimum accumulation time are used as
for measuring read noise. Now on these series was calculated pixel-by-pixel
average value, which is the bias value we need, because it is already said
above that on these frames only it remains. The obtained BIAS $=960.5\pm
2.2~{}ADU$.

As will be shown below, the detector has a high dark current. However, its
noise at minimum exposure does not exceed $\sim$60 e- (0.1 ADU), and we
neglected its contribution when calculating RN and BIAS.

###  3..4 Dark current

Another detector parameter can be a factor limiting sensitivity — dark
current. It can be a major source of noise when large. Measurement of dark
current in infrared detectors requires the use of a cold blanking plate placed
in front of the detector’s entrance window and placing the detector in a
cooled enclosure to avoid reflection of radiation from the warm parts of the
instrument from the blanking plate to the detector.

In our case, we used a blackened metal plate cooled in liquid nitrogen and
located 5 mm from the entrance window of the photosensitive module. In images
taken under these conditions, the signal consists of bias with readout noise,
the dark signal accumulated over the exposure time, the intrinsic thermal
emission from the entrance window of the detector, and the radiation reflected
from the cold blanking plate, which always remains despite the protection
methods taken. The entrance window of the module has an AR coating, so we will
neglect its contribution (or rather, we will consider this contribution as a
part of the dark current of the detector, depending on the external
temperature). The radiation reflected from the cold plate due to the presence
of a cold aperture inside the light-sensitive module falls only on the outer
edges of the frame. That is, by examining the central part of the frame, it is
possible to obtain an estimate of the dark current.

Figure 7: Histogram of dark signal magnitude in the central region of the
detector and normal distribution curve with mean dark current 19.61 and
$\sigma=0.28$

We performed 8 series of measurements of the dark current at an entrance
window temperature of $\approx 6^{\circ}$C. In each of them, the dark current
was calculated for a frame area of 250x250 pixels using a series of frames
obtained with exposures from minimum to 65 ms. For each pixel in this region,
a linear approximation of the time dependence of the accumulated signal was
performed. The histogram of the dark current for one of the series is shown in
Fig. 7. It can be seen that its shape is close to a normal distribution. This
shows in favor of the correct cutting out of the area of the frame not
illuminated by reflected radiation. The average value of the dark current
measured in this series turns out to be 19.6 ADU/ms. The average over all
series of the LMP-photometer dark current was found to be $17.8\pm 2.2$ ADU/ms
or $\approx(9.3\pm 1.1)\cdot 10^{6}$ e-/s.

In addition to "normal" pixels whose dark signal accumulation rate corresponds
to a normal distribution, located both in the region we studied and at the
edges of the frame, there are $\approx$200 pixels (<0.1% of the number of
working pixels) whose dark current significantly ($>4\sigma$) exceeds the
average value. These are so-called "hot" pixels characterized by an increased
rate of "dark" electrons generation.

###  3..5 First light and observations with LMP photometer

The first light with the prototype photometer was obtained on January 31, 2023
on the 2.5 meter telescope KGO GAISH MSU. The well-known carbon star CW Leo
was chosen as the object for the first observations as one of the brightest
objects in the infrared sky. During these observations, the position of the
focal plane was refined (the out-of-flange position of the Nasmyth N3 focus at
the position of the secondary mirror corresponding to the sharp images in the
other Nasmyth N1 focus, where the ASTRONIRCAM near-infrared camera was
installed, was 102 cm), estimates of the background level, noise, typical
exposure time, and FWHM of the stellar images were made, and images of Jupiter
and Mars were obtained (Fig. 8). In April 2023, images of Venus were obtained
in $K,L$, and $M$ filters, shown in Fig. 9. It is interesting to note, despite
the fact that the phase of the planet was 0.75 during the observations, the
entire disk of Venus is visible in the $M$ band.

Figure 8: Photographs of Jupiter and Mars obtained on February 02, 2023 during
photometer test. Angular sizes of planets at the moment of observations 36′′
and 10.7′′, respectively Figure 9: Images of Venus taken on April 13, 2023.
Phase of Venus 0.75, angular diameter 14′′

The prototype photometer has an unvignetted field of view of
$30^{\prime\prime}$, with vignetting at 50% — $50^{\prime\prime}$. The image
scale is $\approx$$0.15^{\prime\prime}$/pixel. The typical sizes of the
stellar images (FWHM ) in the averaged images are $\sim
0.6-0.7^{\prime\prime}$ (4-5 pixels), which is close enough to the diffraction
limit for a wavelength of 4.8 $\mu$m ($0.48^{\prime\prime}$). Fig. 10 shows an
example of an image of a star obtained under a quiet atmosphere with an
exposure of 10 ms (single frame). The first diffraction ring and fragments of
the following rings are clearly visible.

At the end of February 2023, after the installation of the filter wheel,
observations of stars at different stages of evolution were started with the
LMP photometer. For example, carbon stars V Cyg, $\chi$ Cyg, S Cep, T Dra,
young star ZZ Tau IRS ([11]), as well as standard stars of different spectral
types from the list of [1]. From the observations of the standards, the
sensitivity of the instrument can be determined. At signal-to-noise ratio
SNR=3 and good image quality, it is possible to observe stars up to 9.3m and
8.1m in the $L$ and $M$ bands, respectively, during the accumulation time of
20 s.

Figure 10: Brightness distribution in the image of the carbon star RW LMi
obtained on March 02, 2023 in the $M$ band Figure 11: Dependence of sky
brightness relative to zenith on air mass for filters $L$ and $M$

Since August 2023, the LMP photometer has also been used in the study of sky
brightness at wavelengths of 3-5 µm. For this purpose, a separate setup has
been built to provide sky scans in a selected vertical. The scanning step can
be chosen to be any step, but $\sim 5^{\circ}$ is usually used. After each
step, measurements of brightness at zenith are made, which allows to
compensate for fluctuations in the intrinsic radiation of the filters, lens
and instrument walls on the assumption of constant sky brightness for short
time intervals ($\sim$3 seconds).

An example of the sky brightness record obtained on October 20, 2023 at KGO is
shown in Fig. 11. The points on the graph represent the differences in signal
from the background at airmass Mz and Mz=1 (at zenith) averaged over 10
separate scans. It can be seen that at small air masses the sky brightness
depends almost linearly on Mz in both filters, following the expected
dependence for spherically symmetric air layers. At Mz>2 in the $M$ band there
is a marked difference from the straight line — the signal grows slower than
expected. We attribute this to the location of the setup on top of a hill,
because of which, at about $>50$ m, the surface begins to deviate from the
plane and the beam of view begins to cross higher ( colder and less humid)
layers of the atmosphere than if we were observing over a flat surface. Such
dependence is not observed in the $L$ band, which is due to its lower
sensitivity to air temperature and humidity (this band has a shorter
wavelength and the atmosphere is more transparent, see Fig. 1).

## Conclutions

The need to expand the spectral range, in which observations can be carried
out on the 2.5-m telescope of the KGO, towards long wavelengths is beyond
doubt — this is required by modern research trends and it is allowed by the
astroclimate of the observatory and the appearance of an appropriate detector.
At the same time, the possibilities of studying different classes of objects
are significantly expanded: young stars, AGB and post-AGB stars, comets,
bright AGN with excess IR radiation, and, finally, objects with circumstellar
dust shells.

The photometer design we have implemented at this stage is not optimal in
terms of minimizing the instrumental background and matching the scale to the
average image quality in the CMO (instead of the recommended 3 pixels per FWHM
of a point source, the $\approx 5-6$ pixels is implemented). However, it
allows, with a minimal project budget, to obtain a working tool that can
access hundreds of thousands of objects on the sky.

The basis of the instrument is the light-sensitive module Gavin-615A, which
was studied by us in laboratory conditions and in real conditions of the dome
space. To ensure its operation and the possibility of interaction with the
software and equipment of the 2.5-m telescope, we improved the software
provided by the supplier and developed new ones that implement various modes
of photometer operation.

The module detector has a large pixel capacity (see Tab. 2), which, combined
with the 14-bit digitization of the signal, results in a large conversion
factor GAIN$\approx 520$ e-/ADU.

The nonlinearity of the detector turned out to be low, and according to our
estimates at full pixel filling is $\leq 5$ % (less than the manufacturer’s
stated value). The curve of nonlinearity dependence on the signal has a
complex form — nonlinearity increases rapidly up to 4% as the cell is filled,
but after reaching 30% of the capacity it almost stops changing. Correction
functions with the coefficients we found can be used to account for it over
the entire signal range.

Unfortunately, the detector has a large dark current (consisting of the
detector’s own dark current and radiation from the entrance window of the
photosensitive module), which we estimate to be $\approx(9.3\pm 1.1)\cdot
10^{6}$ e-/s at an entrance window temperature of $6^{\circ}$C. That is, the
pixel is completely filled with dark signal in a time <1 s. Such exposure for
the mid-infrared range is not a significant limitation, since due to the
presence of a large instrumental and atmospheric background and a large flux
of IR photons from objects, the typical accumulation time in IR instruments is
usually tens of milliseconds.

When the signal is registered, the noise will be composed of the noise of the
measured signal and detector noise, among which in our case the dark current
noise and readout noise, which is $1200\pm 310$ e-, are dominant. These noises
equalize at exposures of about 150 ms. At operating exposures of 10-20 ms, the
dark current noise becomes 3-4 times less than the read noise.

Observations with the LMP photometer were started on the 2.5-m telescope,
showing the possibility of using it to study objects up to 8-9 magnitude in
the $L,M$ bands. Thus, we obtained estimates of the brightness of several
bright carbon stars, standard stars of different spectral types from the list
of [1] and a faint young star ZZ Tau IRS ([11]), which had a brightness of
$L=7.96$ and $M=6.78$ at the time of the observations, and for which the
SNR$\sim 10$ ratio was obtained for an accumulation time of 20 s (sum of 1000
frames of 20 ms). The estimation of the LMP photometer limiting agnitude shows
that at SNR=3 and good image quality, it is possible to observe stars up to
$\sim$9m and $\sim$8m in the $L$ and $M$ bands, respectively, during the
accumulation time of 20 seconds.

At present, one of the factors limiting the photometer’s ability to observe
faint objects is the absence of a derotator at the focus of the Nasmyth N3
2.5-telescope. This leads to rotation of the field of view, which becomes
noticeable already at measurement times longer than a few minutes. As a
result, stacking individual frames to increase the signal-to-noise ratio
becomes possible only when observing relatively bright objects brighter than
approximately $7^{m}-8^{m}$, i.e., those objects whose images can be
registered during the observation time (including accumulation time and
overhead for signal reading and modulation) not exceeding several minutes.
When observing extended objects, the brightness requirements increase even
more. The installation of a mechanical derotator or the development of a
software field rotation correction becomes the first priority to improve the
efficiency of the photometer.

The authors are grateful for the support of the Development Program of M. V.
Lomonosov Moscow State University (Scientific and Educational School
<<Fundamental and Applied Space Research>>). The work of S. Zheltoukhov (3D
modeling, photometer assembly and adjustment, software development,
observations) was supported by the Russian Science Foundation (RNF grant
21-12-00210). The authors are grateful to Vladimir Senyavin (Department of
Physical Chemistry, Moscow State University) for obtaining the transmission
curves of the filters.

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# Hong-Ou-Mandel Interference with a Coexisting Clock using Transceivers for
Synchronization over Deployed Fiber

Anirudh Ramesh  Daniel R. Reilly  Kim Fook Lee  Paul M. Moraw  Joaquin Chung
Md Shariful Islam  Cristián Peña  Xu Han  Rajkumar Kettimuthu  Prem Kumar
Gregory Kanter

###### Abstract

Interference between independently generated photons is a key step towards
distributing entanglement over long distances, but it requires synchronization
between the distantly-located photon sources. Synchronizing the clocks of such
photon sources using coexisting two-way classical optical communications over
the same fiber that transport the quantum photonic signals is a promising
approach for achieving photon-photon interference over long distances,
enabling entanglement distribution for quantum networking using the deployed
fiber infrastructure. Here, we demonstrate photon-photon interference by
observing the Hong-Ou-Mandel dip between two distantly-located sources: a weak
coherent state source obtained by attenuating the output of a laser and a
heralded single-photon source. We achieve a maximum dip visibility of $0.58\pm
0.04$ when the two sources are connected via $4.3$ km of deployed fiber. Dip
visibilities $>0.5$ are nonclassical and a first step towards achieving
teleportation over the deployed fiber infrastructure. In our experiment, the
classical optical communication is achieved with $-21$ dBm of optical signal
launch power, which is used to synchronize the clocks in the two independent,
distantly-located photon sources. The impact of spontaneous Raman scattering
from the classical optical signals is mitigated by appropriate choice of the
quantum and classical channel wavelengths. All equipment used in our
experiment (the photon sources and the synchronization setup) is commercially
available. Finally, our experiment represents a scalable approach to enabling
practical quantum networking with commercial equipment and coexistence with
classical communications in optical fiber.

###### keywords:

Quantum networking , Quantum Interference , Quantum Optics , Single Photons ,
Classical Communications , Clock Distribution

[DSL]organization=Data Science and Learning Division, Argonne National
Laboratory,addressline=9700 S. Cass Avenue, city=Lemont, postcode=60439,
state=IL, country=USA [NU]organization=Center for Photonic Communication and
Computing, Department of Electrical and Computer Engineering, Northwestern
University,addressline=2145 Sheridan Road, city=Evanston, postcode=60208,
state=IL, country=USA [NuCrypt]organization=NuCrypt LLC,addressline=1460
Renaissance Drive, #205, city=Park Ridge, postcode=60068, state=IL,
country=USA

[Fermi]organization=Fermi National Accelerator Laboratory,addressline=Kirk
Road and Pine Street, city=Batavia, postcode=60510, state=IL, country=USA

[CNM]organization=Center for Nanoscale Materials, Argonne National
Laboratory,addressline=9700 S. Cass Avenue, city=Lemont, postcode=60439,
state=IL, country=USA

##  1 Introduction

Photonics is an actively pursued platform for quantum communications due to
the ability of photons to be transmitted over low loss optical fiber in the
telecommunications band[1]. Quantum networking aims to build infrastructure
that transmits photonic quantum states over optical fiber. This can enable
future quantum computers and sensors to operate in parallel and elevate their
capabilities by increasing their overall computational power, analogous to a
high performance computing cluster[2, 3]. Significant demonstrations of
quantum networking have been made across the world in the United States[4, 5,
6], UK[7], China[8] and the European Union[9], involving the distribution and
measurement of entangled photonic qubits and quantum keys. However,
transmission of entanglement over larger distances is sensitive to attenuation
in optical fiber and is bottlenecked by the no-cloning theorem that prevents
amplification of quantum states[10]. Entanglement swapping with quantum
repeaters can help overcome these issues by extending the range of
entanglement distribution[11]. Quantum repeaters can also enable distributed
quantum sensing, such as long baseline interferometry for telescopes[12] as
well as large scale quantum key distribution networks without trusted
nodes[13]. A key step in entanglement swapping using photons involves Hong-Ou-
Mandel (HOM) interference of identical photons at a beamsplitter as a part of
a Bell state measurement (BSM)[14, 15]. HOM interference involves multiple
challenges, for instance alignment of photon polarizations and arrival times,
as well as matching of their spectro-temporal shapes at the beamsplitter.[16].
Although most examples of HOM interference have been confined to those between
two single photon Fock states, it can also occur between a weak coherent state
(WCS) and a single photon Fock state[17], with similar experimental
constraints. A WCS can be obtained by strongly attenuating a laser, to
intensities comparable to a single photon Fock state.

Although high visibility HOM interference has been successfully achieved in
nearly every photonics platform, it is necessary to achieve reliable HOM
interference across fiber networks to connect quantum systems that are not in
the same location. In order to maximize teleportation and swapping rates, one
would aim to to use photons confined to a narrow pulse duration to arrive at a
beamsplitter for HOM interference, at a timing precision that is within a
fraction of their pulse duration[18]. If performed over deployed fiber
networks, it becomes necessary to use an optical clock for low latency and
high precision clock distribution between the interfering sources to
orchestrate their simultaneous arrival at the beamsplitter. Using these
techniques, several demonstrations of HOM interference have been achieved
whether as standalone experiments, or as a part of a BSM for teleporting
qubits over deployed fiber networks[19, 20, 21, 22]. Although most of these
experiments achieved high HOM visibilties and successful qubit
teleportation/BSM, in most cases the optical clock is transmitted between the
nodes in a separate fiber, and there are usually no other signals coexisting
with the quantum photonic states. Some reports have sought to demonstrate
coexistence of quantum signals used for HOM/BSM with independent classical
traffic[22, 23] (with the exception of [24], which multiplexes a clock
signal).

We believe that having the optical clock signals coexisting with the quantum
signal in the same fiber is the next step in enabling quantum networks, since
fiber infrastructure can factor in as a major overhead cost and fiber
availability may be limited. In a coexisting clock scheme, a common electrical
reference is utilized to generate high-precision optical clock signals with
modulated lasers. This reference also times the generation of photonic quantum
states. Both the clock signals and quantum states are then multiplexed and
transmitted through the same fiber[4, 25]. An advantage of quantum-classical
coexistence is that since the properties of optical signals in fiber are
sensitive to mechanical and thermal disturbances, a coexisting optical clock
signal is sensitive to the same perturbations which affect the quantum signal.
A coexisting clock with high precision clock recovery has been shown to be
achievable[25] and can significantly improve the accuracy of quantum
networking experiments across distant nodes. However, the optical clock
signals can have average optical powers that are in the microwatts to
milliwatts range, and hence they can degrade the quantum signal due to
spontaneous Raman scattering (SpRS) of the clock signal due to its interaction
with the optical fiber[26]. The broadband Raman response of silica fiber leads
to generation of Raman scattered photons in the quantum signal spectrum[27],
which requires careful selection of the quantum and classical channel
wavelengths.

In this work, we show successful HOM interference between independently
generated WCS and heralded single photons across 4.3 km of deployed
underground fiber with a coexisting clock. To incorporate scalability in our
approach, we interface our commercially available measurement system with
inexpensive 2 Gbps small form factor pluggable (SFP) transceivers for clock
distribution, and demonstrate a non-classical visibility for HOM interference.

##  2 Experimental setup

HOM interference occurs as a result of destructive interference between the
wavefunction amplitudes of two single photons that are sent into the input
ports of a beamsplitter, when they are in the same spatio-temporal and
polarization modes[15]. In HOM interference, coincident detections between the
two output ports of a beamsplitter reduce as the photons overlap, which is
usually controlled by adding an optical delay line in one of the arms. The
reduction in visibility is a result of both photons exiting the beamsplitter
at the same output port, and depends on the indistinguishability between the
photons. Considering $C$ the number of coincident detections in the
interferogram, the visibility $V$ is defined in [16] as follows:

$V=\frac{C_{max}-C_{min}}{C_{max}}$ (1)

For interference between a WCS and a heralded single photon (HSP) from a
photon-pair source, we measured the threefold coincidences between the signal,
herald and the WCS to characterize the HOM visibility while varying the delay
between the HSP and the WCS[17]. Measurements involving threefold coincidences
between a photon-pairs and a WCS have applications in BSM and teleportation
experiments[20, 19] aimed towards enabling entanglement distribution and
secure communications[22], and similar HOM measurements could eventually be
used to teleport quantum information. However, the HOM visibility is limited
by multi-pair generation which causes an inherent trade-off between
measurement rate (high photon rates) and optimal visibility (low photon
rates). In this work, we generated the HSP using a NuCrypt Entangled Photon
Source EPS-1000-W (EPS) [28]. The EPS-1000-W is based on a periodically poled
lithium niobate (PPLN) waveguide and generates photon-pairs by cascaded second
harmonic generation and spontaneous parametric downconversion (c-SHG-
SPDC)[29]. The EPS also has the ability to delay the electrical pulse that
drives the intensity modulator that defines its pump. This can be thus used to
control the generation and the subsequent HSP arrival time at the
beamsplitter. In this work, the EPS-1000 pump phase delay has a minimum step
size of $10$ ps. The EPS was pumped with 60 ps pulses centered at 1551.7 nm at
a 100 MHz rate, and 100 GHz dense wavelength division multiplexers (DWDMs)
were used to demultiplex out photon-pairs from the PPLN c-SHG-SPDC
phasematched spectrum at central wavelengths of 1552.89 nm and 1550.2 nm. The
heralding photon at 1552.89 nm was filtered by a 5 GHz tunable fiber Fabry-
Perot filter (FFP) after which an ID Quantique single photon detector (SPD)
detects the photon to serve as a heralding signal, as shown in Fig. 1. The
signal photon was directed towards the HOM interference setup. The WCS was
generated by intensity modulating a Purephotonics Integrable Tunable Laser
Assembly (ITLA) using 80 ps electrical pulses, with the same center wavelength
as the signal photon, henceforth called the WCS source. A series of fixed
fiber optic attenuators were used to reduce the probability of a photon per
pulse $\bar{n}$ of the WCS source to $\approx 0.01$. The interfering weak
coherent state and idler photon were directed through a fiber polarization
controller (FPC), fiber polarizer and a fixed FFP with a 10 GHz bandwidth, to
a polarization maintaining (PM) 50:50 coupler for HOM interference, as shown
in the schematic in Fig.1. The use of a single mode fiber allowed us to
enforce spatial indistinguishability, while the PM 50:50 coupler and fiber
polarizer helped impose polarization indistinguishability. The heralding
filter and HOM filters had different bandwidths since these were the ones
available at the time of the experiment, but typically all the filters would
be identical. Their detection was carried out using two Quantum Opus
Superconducting Nanowire Single Photon Detectors (SNSPDs). The signal, herald
and WCS detection signals from the SPAD and SNSPDs were then collected by a
NuCrypt Remote Correlation System RCS-2000[30] (RCS) for correlation
measurements. The RCS is an electronic correlator which can be used as to
generate and recover clock signals and sample detection signals to perform
time-correlated measurements. All the measurements were sampled at a rate of
$1.2$ GHz.

The EPS and WCS must share a common clock so that their pulse outputs can
arrive synchronously at the beam splitter. An internal EPS clock serves as the
master clock that governs the photon-pair generation. This clock is shared
with the WCS by employing a fiber-optic link embedded in the RCS. The EPS
clock is connected via an SMA electrical cable to a first RCS-2000 system
(RCS-EPS). The RCS-EPS generates an optical data stream at a nominal 2 Gbps
data rate via a SFP transceiver using the EPS clock as a reference clock to an
internal phase-locked loop (PLL). The optical data stream is connected to a
second RCS (RCS-WCS) over a fiber connection. The RCS-WCS recovers the clock
from the data and generates an output reference clock that is sent to the WCS
via an SMA RF cable. This experimental topology allowed us to treat the WCS
source as an independent node, since it was connected with the rest of the
setup with only fiber optic links. The transceivers used to transmit the
optical clock operated at a wavelength of 1310 nm, in the O-band. The O-band
wavelength was chosen due its relatively modest SpRS into the 1550 nm band,
low loss in optical fiber, and compatibility with convenient coarse wavelength
division multiplexers (CWDMs). We note that a 1270 nm wavelength would produce
significantly less SpRS noise[27] but the RCS-EPS had a 1310 nm SFP installed
at the time of this experiment.

In the next section, we report two experiments that characterized the HOM
interference visibility between our WCS and HSP. In the first experiment, we
established a baseline HOM visibility by interfering the HSP and WCS at the
beamsplitter. This experiment demonstrated that we could achieve HOM
interference by using an optical clock for synchronizing both interfering
quantum signals. In the second experiment, we implemented the same experiment,
except we used a single loop of fiber deployed over the Argonne National
Laboratory campus to transmit the WCS state to the beamsplitter, and
distribute the optical clock from RCS-EPS to time the WCS generation. This
experiment showed that our quantum signals could still show HOM interference
while the WCS was coexisting with a classical signal in the same fiber. Both
the HSP system and the WCS system are highlighted by blue boxes in Fig. 1.

##  3 Results

Figure 1: a) Experimental setup for establishing HOM interference baseline,
and the b) HOM interferogram. The threefold coincidence counts were integrated
at each EPS pump phase delay setting for $60$ s, providing us with a triple
coincidences rate of 4.2 triples/second when the pulses were completely
misaligned. The error bars on the data are estimated assuming Poissonian
distributed arrival times for the photons and the shading represents the 95%
confidence interval for the fit.

The first experiment sought to set a baseline HOM visibility for this system,
by measuring the maximum HOM visibility achievable with the optical components
available. After setting up the system as shown in Fig. 1, FPCs were used to
align the polarizations of the incoming WCS and HSP with the polarizers before
the 50:50 coupler. Polarization indistinguishability is ensured by maximizing
the detected counts at the SNSPDs. Following that, the EPS pump delay was
scanned. This changed the arrival times of the HSP at the beamsplitter, and
allows control over the temporal overlap of the HSP and WCS pulses at the
50:50 coupler. The acquired interferogram was then fit to the following
expression for the threefold coincidences $C_{123}$[31]:

$C_{123}=C\times(1-V\times e^{-(t/\tau)^{2}})$ (2)

This is an inverse Gaussian function where $V$ is the interference visibility,
$C$ is the maximum threefolds coincidences and $\tau$ is related to the
standard deviation $\sigma$ of the Gaussian by the relation:
$\sigma=2\tau\times(log_{e}(2))^{\frac{1}{2}}$. In the first experiment, the
WCS $\bar{n}_{baseline}$ was estimated to be $0.007$ (with $\bar{n}$ defined
as the average WCS photon number per pulse the input to the 50/50 coupler) and
the coincidences-to-accidentals ratio (CAR) of the photon-pair source was
estimated to be $40$. The former was estimated by observing the singles count
rate due to the WCS (assuming a typical SNSPD efficiency), and the latter was
calculated by measuring correlations between the signal and idler photons in
RCS-EPS.

This experiment resulted in a HOM visibility of $0.63\pm 0.02$. This
visibility is unambiguously non-classical, and cannot be attributed to
classical interference. However, the imperfect visibility can be attributed to
three main factors. The first was due to mismatch in the spectro-temporal
modes between the HSP and the WCS. These modes are defined by a combination of
the spectral filters and the input pulse-shapes. The 5 GHz filter before the
heralding detector set the effective bandwidth of the HSP, and the $\approx
80$ ps full-width at half maximum (FWHM) pulse duration of the WCS created an
estimated spectral FWHM of $5.5$ GHz for the WCS, assuming a transform limited
Gaussian as the pulse shape as a reasonable approximation. Hence, this
mismatch was expected to lower the HOM interference visibility. A second
factor was the timing jitter between the recovered clock at RCS-WCS and the
EPS clock, which was measured using a digital communications analyzer
(sampling oscilloscope) to be about 20 ps RMS when the systems were connected
by a short fiber. No further efforts were made to optimize the filters or
pulse-shapes for maximum interference since our focus was to study HOM with
the coexistence of an optical clock. A third factor limiting visibility are
multi-photon events from the HSPS or WCS, which are controlled but not
eliminated by operating at low photon levels.

Figure 2: a) Experimental setup, b) map of deployed fiber loop for HOM with
quantum-classical coexistence at Argonne National Laboratory, and c) HOM
interferograms for $\bar{n}$ = 0.012 and $\bar{n}$ = 0.003. The map was
acquired from Cadmapper[32].

To test this approach in a networked setting, a pair of deployed optical
fibers between the site of the experiment and the Center for Nanoscale
Materials building (CNM) were looped back at CNM, as shown in Fig. 2 b). A
Polatis series 6000 software-defined networking switch was used to route the
WCS and clock signals from their sources to the deployed fiber loop. Optical
time-domain reflectometry (OTDR) was used to determine the overall fiber loop
length as $4.3$ km. A total of 6 dB of loss was measured for the fiber loop in
the C-band. This loss can be attributed to multiple junctions in the fiber
network. As displayed in Fig. 2, this experiment sought to emulate two
independent and separated quantum nodes both connected by a single strand of
deployed fiber. The fiber loop carried the WCS to the beamsplitter, as well as
a coexisting counter-propagating classical clock signal from RCS-EPS which was
recovered by the RCS-WCS and used to time the WCS generation. O-band/C-band
CWDMs were used to multiplex and separate the WCS and clock signals. This
enabled the synchronization of the generation of the WCS and the HSP. In order
to reduce SpRS noise from the optical clock, we aimed to have as low a
coexisting classical launch power as possible that could be successfully
recovered by the transceivers. Fiber optic attenuators were added at the
output of the transceiver that generated the clock signal before being
launched into the loop, and a launch power of -21 dBm was measured. The clock
signal was estimated to have an optical power level of $\approx-27$ dBm after
travelling over the deployed fiber, which was still successfully recovered by
RCS-WCS after being demultiplexed from the fiber loop by the CWDM. Using these
settings, two HOM interferograms were acquired and are shown in Fig. 2 c).
Each interferogram in this experiment was acquired with the WCS having a
different $\bar{n}$, namely $\bar{n}_{loop-1}$ = $0.012$ and
$\bar{n}_{loop-2}$ = $0.003$. For the case with $\bar{n}_{loop-1}$ = $0.012$,
we observed a reduced visibility of $0.58\pm 0.04\ $ compared to the baseline
visibility of $\approx 0.63$ for $\bar{n}_{baseline}$ = $0.007$. Hence, our
coexisting optical clock distribution method helped maintain sufficient timing
synchronization between the HSP and WCS systems to measure a non-classical HOM
fringe. For the next measurement, we further reduced $\bar{n}$ by programming
a variable optical attenuator in the WCS source while keeping all other
parameters the same, to $\bar{n}_{loop-2}$ = $0.003$. The resulting
interferogram brought the visibility into the classical regime, which is
defined as V $<0.5$, to V = $0.49\pm 0.06$.

To understand these visibilities, we refer to the following model[33]:

$V_{\text{HOM}}=\frac{4\delta\omega_{A}\delta\omega_{B}}{(\frac{\bar{n}}{\mu}+2+\frac{N_{\text{sys}}}{\bar{n}\mu})(\delta\omega_{A}^{2}+\delta\omega_{B}^{2})}\exp\left(-\frac{(\delta\omega_{A}^{2}\delta\omega_{B}^{2})t^{2}}{\delta\omega_{A}^{2}+\delta\omega_{B}^{2}}\right)$
(3)

Here the measured HOM visibility is described as a function of $\bar{n}$, the
probability of a HSP arriving at the beamsplitter per pulse $\mu$, the
spectral bandwidths of the WCS and HSP, $\delta\omega_{A}$ and
$\delta\omega_{B}$ respectively, and $N_{sys}$, which is the probability of a
threefolds coincidence resulting either from noise or higher photon number
states from the WCS.

According to this model, we expect an optimal visibility limited by noise from
the laser and background counts. We assume a common noise level for all our
experiments, since our choice of wavelengths would greatly reduce SpRS from
the clock. Upon fitting for this expression using the lmfit package in Python
with $\delta\omega_{A}=11\pi\times 10^{9}$ rad, $\delta\omega_{B}=10\pi\times
10^{9}$ rad ($5.5$ and $5$ GHz in angular units) at $t=0$ s. The fit
converges, although sub-optimally. It should be noted that the values for the
spectral bandwidths are estimates calculated by the combinations of filters
and pulse durations used in the experiment, and not exact values.
Additionally, other experimental effects such as jitter are not included in
the analysis. The fitting is thus not expected to be very accurate but is a
mechanism to explore trends in the data.

Figure 3: Fit obtained from Eq 3. The y-axis error bars for the data points
were obtained by fitting the HOM interferograms to Eq 2 and the x-axis error
bars were based on experimental uncertainties.

Based on the fit in Fig. 3, we obtain $N_{sys}=1.3\pm 0.47,\times 10^{-4}$ per
pulse and $\mu=0.021\pm 0.004$ per pulse. $\mu$ here can be interpreted as the
probability of a photon entering the HOM beamsplitter conditioned on a
heralding detection event per pulse. This can be independently estimated [34]
as $0.04$ using the relation $P(h|s)=\mu=\frac{P_{cc}}{P_{h}\times\eta_{s}}$
where $P_{cc}$ is the probability of a coincidence between the heralding SPD
and both SNSPDs, $P_{h}$ is the probability of a singles count in the
heralding SPAD and $\eta_{s}$ is the efficiency of one of the the singles
channels. By adding count probabilities from both SNSPD channels, we find
$P_{cc}=8\times 10^{-6}$. $P_{h}$ was estimated to be $2.6\times 10^{-4}$ and
$\eta_{s}$ was estimated to be $0.72$, which provides with our independent
value for $\mu$. The fit produces a lower heralding efficiency estimate.
However, as previously noted, Eq. 3 is a simple model that is used here
primarily for investigating general trends and is not expected to lead to the
most accurate parameter estimates. The $N_{sys}$ value in our case is expected
to be a combination of noise from the EPS, and higher order photon Fock states
from WCS and the EPS.

Broadly, our visibility measurements follow a trend similar to that predicted
by Eq. 3, such that there is an optimal value for the visibility based on the
interplay of $N_{sys}$, $\mu$ and $\bar{n}$. Further detailed characterization
efforts will be helpful to pinpoint parameters more accurately and achieve
higher quality fits.

##  4 Discussion

In this work, we achieved HOM interference between a WCS and HSP with a
coexisting optical clock in the same fiber, which was generated and received
by commercial SFP transceivers. In spite of a mismatch in the spectro-temporal
properties of the pulses and classical coexistence, we still observed non-
classical HOM visibility. Although our transceivers had some jitter, we were
still able to push the limits of the experiment above $V=0.5$ (the classical
regime), and we expect that the use of faster transceivers can close the gap
in the timing synchronization precision between transceivers and sophisticated
modulated laser pulse sources. A better HOM visibility can also be achieved by
using matching filter bandwidths for all the channels involved in the
measurement. As quantum networks develop alongside advances in quantum
computing and transduction, using existing tools in the telecommunications
industry like transceivers to implement entanglement distribution will enable
rapid scalability in quantum communications. Coexisting classical and quantum
communications would enable rapid proliferation of quantum traffic by sharing
the existing infrastructure.

##  Appendix A Acknowledgements and funding

We thank Jordan M. Thomas, Northwestern University for useful discussions.
This material is based upon work supported by the U.S. Department of Energy
(DOE), Office of Science, Advanced Scientific Computing Research (ASCR)
program under contract number DE-AC02-06CH11357 as part of the InterQnet
project, and the DOE ASCR Transparent Optical Quantum Networks for Distributed
Science program through the Illinois Express Quantum Network project, but no
government endorsement is implied. Part of this work was also performed at the
Center for Nanoscale Materials, a U.S. Department of Energy Office of Science
User Facility, was supported by the U.S. DOE, Office of Basic Energy Sciences,
under Contract No. DE-AC02-06CH11357.

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