# Fabrication of low-loss III-V Bragg-reflection waveguides for parametric
down-conversion

Hannah Thiel  1,* Marita Wagner  1,2,3 Bianca Nardi  1 Alexander Schlager  1
Robert J. Chapman  1,4 Stefan Frick  1 Holger Suchomel  5 Martin Kamp  5 Sven
Höfling  5 Christian Schneider  5,6 and Gregor Weihs1  1Institut für
Experimentalphysik, Universität Innsbruck, 6020 Innsbruck, Austria
2CIC biomaGUNE, Basque Research and Technology Alliance, 20014 Donostia-San
Sebastian, Spain
3CIC nanoGUNE, Basque Research and Technology Alliance, 20018 Donostia-San
Sebastian, Spain
4Optical Nanomaterial Group, Institute for Quantum Electronics, Department of
Physics, ETH Zurich, 8093 Zurich, Switzerland
5Technische Physik, Universität Würzburg, 97074 Würzburg, Germany
6Institute of Physics, University of Oldenburg, 26129 Oldenburg, Germany
<EMAIL_ADDRESS>
††journal: opticajournal††articletype: Research Article

Entangled photon pairs are an important resource for quantum cryptography
schemes that go beyond point-to-point communication. Semiconductor Bragg-
reflection waveguides are a promising photon-pair source due to mature
fabrication, integrability, large transparency window in the telecom
wavelength range, integration capabilities for electro-optical devices as well
as a high second-order nonlinear coefficient. To increase performance we
improved the fabrication of Bragg-reflection waveguides by employing fixed-
beam-moving-stage optical lithography, low pressure and low chlorine
concentration etching, and resist reflow. The reduction in sidewall roughness
yields a low optical loss coefficient for telecom wavelength light of
$\alpha_{\mathrm{reflow}}=0.08\left(6\right)\,\mathrm{mm}^{-1}$. Owing to the
decreased losses, we achieved a photon pair production rate of
$8800\left(300\right)\,\left(\mathrm{mW\cdot s\cdot mm}\right)^{-1}$ which is
15-fold higher than in previous samples.

##  1 Introduction

Nonlinear optics has a multitude of applications, such as all-optical
switching, efficient detection, and multiplexing for increased data transfer
rates in fiber networks. In addition to its classical applications, nonlinear
optics has strong applications in quantum communication. Protocols that go
beyond point-to-point quantum cryptography, like device-independent schemes
and quantum repeaters, rely on entangled photon pairs [1, 2]. A leading method
to produce entangled photons is by parametric down-conversion. As the need for
mass-deployable devices with increased complexity grows, integrable on-chip
systems become the only practical solution. While the significance of
miniaturized systems is undisputed, it remains uncertain what would constitute
the ideal platform.

An ideal photon-pair source has to offer integration capabilities in
monolithic or hybrid approaches and be scalable as well as affordable in
fabrication [3]. The silicon platform and the maturity of its fabrication make
it a natural choice for integration. However, for optical applications in
communication, silicon has multiple drawbacks, including the lack of a direct
bandgap, low transmission across the telecom C-band at high powers due to two-
photon absorption and the lack of a second-order nonlinear coefficient. These
limitations make silicon a difficult choice for quantum communication systems
using entangled photons [4, 5].

The ideal material parameters for an integrated quantum optical device are a
direct bandgap, a high $\chi^{(2)}$ nonlinear coefficient, high index
contrast, and low-loss waveguiding in the telecom C-band. Commonly used
material platforms are silicon nitride, which, except for the transparency
window, inherits most of the drawbacks of silicon, lithium niobate and KTP,
which lack the potential for active components, and indium phosphide and
gallium arsenide, which suffer from losses due to a bandgap around 900 nm
wavelength. A material platform without these drawbacks is aluminum gallium
arsenide (AlGaAs), which has a large transparency window in the telecom
wavelength range, integration capabilities for electro-optical devices like
light-emitting diodes, lasers and modulators as well as a high second order
nonlinear coefficient [6].

In the form of Bragg-reflection waveguides (BRWs), AlGaAs simultaneously
offers waveguiding and nonlinear conversion via modal phase matching [7, 8,
9]. This enables the production of polarization, energy-time, and time-bin
entangled photon pairs in the telecom wavelength range [10, 11, 12, 13, 14].
Additionally, owing to the direct bandgap of AlGaAs, a pump laser for
nonlinear conversion processes or quantum dots for the creation of single
photons can be directly integrated on chip [15, 16, 17, 18]. As such, AlGaAs
BRWs offer an ideal resource for quantum communication schemes in existing
fiber networks.

While low loss is important in classical optical communication, it is
paramount in entanglement-based quantum applications, as both photons of an
entangled pair need to be preserved. The fabrication of both classical AlGaAs
devices, like lasers, photodetectors and modulators, as well as more complex
quantum devices has seen significant advancements and has reached the level of
sophistication required for large scale integration [19, 20, 21, 22].

In this article, we report on the fabrication of low-loss AlGaAs BRWs, which
serve as sources of correlated photon pairs. By optimizing the etching recipe
for near-vertical waveguide sidewalls and using resist reflow, we reduce the
root-mean-square area sidewall roughness of our BRWs from 16.05(2) nm to
4.736(7) nm and the corresponding optical loss coefficient from between
$\alpha_{\mathrm{no\,reflow}}=0.23\left(9\right)\,\mathrm{mm}^{-1}\,\,\mathrm{and}\,\,0.32\left(9\right)\,\mathrm{mm}^{-1}$
to $\alpha_{\mathrm{reflow}}=0.08\left(6\right)\,\mathrm{mm}^{-1}$. Resist
reflow increases the photon pair production rate by around six-fold. Overall,
the optimized fabrication recipe leads to a 15-fold increase in photon pair
production rate compared to previous samples.

The rest of this paper is organized as follows. We first introduce BRWs and
their layer structure needed for mode guiding and phase matching. The second
part of the article details the fabrication steps and highlights the measures
taken to handle the challenges introduced by the layer stack. The third part
focuses on the characterization of BRWs including measurements of the sidewall
roughness and the loss coefficients via Fourier transforming the Fabry-Perot
transmission spectrum [23]. Finally, we demonstrate the increased correlated
photon pair production rates.

##  2 Bragg-reflection waveguides

The AlGaAs material platform features a high $\chi^{(2)}$ coefficient that
allows nonlinear processes like second harmonic generation, difference-
frequency generation, and parametric down-conversion (PDC). The efficiency of
these processes hinges on the momentum conservation between input and output
photons as well as the low-loss guiding of the respective modes in the
material. We achieve low loss and phase matching in a BRW made of AlGaAs
layers with varying aluminum concentrations. Fig. 1 shows the layer structure
and guided modes in a BRW.

1 [very thick,black] (1.45,1.82) node[anchor=north
west]$4\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$; [very thick,black]
(-3.6,1.8) node[anchor=north west]Upper Bragg Mirror:; [very thick,black]
(-3.6,1.4) node[anchor=north west]Al0.20Ga0.80As; [very thick,black]
(-3.6,1.05) node[anchor=north west]Al0.63Ga0.37As; [very thick,black]
(-3.6,0.45) node[anchor=north west]Core:; [very thick,black] (-3.6,0.05)
node[anchor=north west]Al0.43Ga0.57As; [very thick,black] (-3.6,-0.55)
node[anchor=north west]Lower Bragg Mirror:; [very thick,black] (-3.6,-0.95)
node[anchor=north west]Al0.20Ga0.80As; [very thick,black] (-3.6,-1.3)
node[anchor=north west]Al0.63Ga0.37As;

1 [very thick,black] (-1.6,-2.1) node[anchor=north west]Horizontal Direction
($\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$); [very thick,black]
(-2.1,-1.9) node[anchor=south west, rotate=90]Vertical Direction
($\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$); [very thick,black]
(-1.9,-1.1) node[anchor=north west]-; [very thick,black] (-1.9,0.20)
node[anchor=north west]-; [very thick,black] (-1.9,1.50) node[anchor=north
west]-; [very thick,black] (-2.4,-1) node[anchor=north west]$-5$; [very
thick,black] (-2.2,0.30) node[anchor=north west]$0$; [very thick,black]
(-2.2,1.6) node[anchor=north west]$5$; [very thick,black] (-1.4,-1.35)
node[anchor=north west]$\mid$; [very thick,black] (0.35,-1.35)
node[anchor=north west]$\mid$; [very thick,black] (2.1,-1.35)
node[anchor=north west]$\mid$; [very thick,black] (-1.6,-1.8)
node[anchor=north west]$-5$; [very thick,black] (0.32,-1.8) node[anchor=north
west]$0$; [very thick,black] (2.07,-1.8) node[anchor=north west]$5$;

1 [very thick,black] (-1.95,-2.1) node[anchor=north west]Horizontal Direction
($\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$); [very thick,black]
(-1.9,-1.35) node[anchor=north west]$\mid$; [very thick,black] (-0.15,-1.35)
node[anchor=north west]$\mid$; [very thick,black] (1.6,-1.35)
node[anchor=north west]$\mid$; [very thick,black] (-2.1,-1.8)
node[anchor=north west]$-5$; [very thick,black] (-0.18,-1.8) node[anchor=north
west]$0$; [very thick,black] (1.55,-1.8) node[anchor=north west]$5$;

Figure 1: Top: Schematic of a BRW with layers of different aluminum
concentration. The core (bright red) with a composition of Al0.43Ga0.57As lies
between two optical matching layers and six Bragg mirror pairs above and below
the core which are made up of Al0.20Ga0.80As (orange) and Al0.63Ga0.37As (dark
red). Bottom: Simulations of the electric field absolute value for the TE-
polarized Bragg mode at 775 nm wavelength (left) and the total internal
reflection mode at 1550 nm wavelength for TE polarization (right). The image
for the TM polarization at the latter wavelength is not shown as it is very
similar to the TE one.

A high index core realized via a low aluminum fraction guides two fundamental
modes, one TE, the other TM polarized, at 1550 nm wavelength via total
internal reflection. Two Bragg mirror stacks above and below the waveguide
core confine the so-called Bragg mode at 775 nm wavelength in the vertical
direction. These consist of six mirror pairs each. We optimize the confinement
by sizing the layer thicknesses at one quarter of the wavelength of the
transverse component of the electric field at 775 nm and by maximizing the
difference in refractive index between the layers [7]. The ridge structure of
the waveguide ensures the confinement of the modes in the horizontal
direction. The BRW supports multiple spatial modes and the Bragg mode at 775
nm wavelength is actually a higher order spatial mode.

Adjusting the refractive indices and layer thicknesses of the AlGaAs layers
enables modal phase matching between the NIR Bragg and telecom fundamental
modes of the waveguide. For optimization, we take into account the increased
nonlinear conversion efficiency with decreasing aluminum fraction as well as
the simultaneous decrease in band gap and resulting pump absorption. For a
comprehensive guide to BRW design, refer to Ref. [9]. While the elaborate
layer structure of the BRWs affords wavelength flexibility and phase matching
optimization in nonlinear processes, it poses a challenge for fabrication.

##  3 Fabrication

In the following section, three different fabrication recipes are described.
One that we call the “previous" recipe uses e-beam lithography with stitching
of write fields and metal mask deposition. It is our starting point for
improving the fabrication process of BRWs. The new recipe is detailed in this
section and is used in two versions: with and without reflowing the
photoresist. The epitaxial layers we use to fabricate BRWs are grown via
molecular beam epitaxy on (100) GaAs substrates and are subsequently processed
as shown in Fig. 2. We first clean the wafer surface in an oxygen plasma in an
inductively coupled plasma reactive ion etcher (ICP-RIE) (Sentech SI 500), the
same machine that is later used for etching the waveguides.

1 [very thick,black] (-3.9,1.85) node[anchor=north west]a); [very thick,black]
(-1.15,1.85) node[anchor=north west]b); [very thick,black] (1.55,1.85)
node[anchor=north west]c); [very thick,black] (-3.9,-0.1) node[anchor=north
west]d); [very thick,black] (-1.15,-0.1) node[anchor=north west]e); [very
thick,black] (1.55,-0.1) node[anchor=north west]f); [very thick,black]
(-1.65,0.75) node[anchor=north west]$\rightarrow$; [very thick,black]
(1.1,0.75) node[anchor=north west]$\rightarrow$; [very thick,black]
(-1.65,-1.15) node[anchor=north west]$\rightarrow$; [very thick,black]
(1.1,-1.15) node[anchor=north west]$\rightarrow$; [very thick,black]
(-3.5,0.75) node[anchor=north west]AlGaAs; [very thick,white] (-0.65,1.47)
node[anchor=north west]Resist; [very thick,black] (-0.75,0.75)
node[anchor=north west]AlGaAs; [very thick,black] (2,0.75) node[anchor=north
west]AlGaAs; [very thick,black] (-3.5,-1.15) node[anchor=north west]AlGaAs;
[very thick,black] (-0.75,-1.15) node[anchor=north west]AlGaAs; [very
thick,black] (2,-1.15) node[anchor=north west]AlGaAs;

Figure 2: BRW fabrication steps include oxygen plasma cleaning of the AlGaAs
wafer surface (a), spinning of photoresist (b), photolithographic exposure
(c), development (d), photoresist reflow (e), and etching (f).

A photo lithography machine (Microtech LaserWriter) exposes the waveguide
pattern into the photoresist. Using a direct laser writer and etch resistant
resist allows us to readily adapt our design to different requirements.
Another advantage of this method is that it does not require an e-beam
lithography machine and the more problematic chemicals needed for the
deposition of a metal mask and lift-off. Due to diffraction, the 405 nm
wavelength of the UV laser writer limits the feature size. This, however, does
not pose any problem for straight waveguides. The lithography mode we employ
is fixed-beam-moving-stage (FBMS) to avoid stitching errors between write
fields. This is the first step towards achieving smooth sidewalls and
decreasing losses due to scattering.

We spin the plasma-resistant photoresist AR-P3740 (Allresist) at 4000 rpm to
obtain a $1.4\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$ thick layer. This
allows us to etch the $3.34\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$
trench depth required for the BRWs with sufficient resist left to protect the
surface of the wafer. The photoresist is positive, enabling us to realize the
structure shown in Fig. 4 (top), which facilitates integration with other
components and systems. Each waveguide is defined by trenches etched on either
side with most of the material between waveguides remaining intact. This
results in a shorter etch time, as less material needs to be removed, and more
stable plasma, as less of the etched-away material accumulates in the etching
chamber. Removing less material during the etch also means that the chip can
be handled more easily in semi-automatic assembly and flip-chip coupling.

After development of the photoresist in AR 300-35 (Allresist), we reflow the
resist in a convection oven for 25 minutes at 140°C. As the fluidity of the
resist increases, its surface smoothens leading to a significant reduction in
line edge roughness. Any imperfections present in the photoresist transfer
directly to the waveguide sidewall during the etching step and are evidenced
by vertical striations. Therefore, the reflow step is the most important in
reducing sidewall roughness of the waveguides.

After reflow, we transfer the pattern in the resist to the AlGaAs in the ICP-
RIE in a plasma mixture of argon and chlorine species. The etch recipe needs
to be finely tuned to achieve near-vertical, smooth sidewalls as well as non-
selective etching in the lateral direction with respect to layers of different
compositions.

1 [ultra thick,white] (-2,0.8) node[anchor=north west]$\searrow$; [ultra
thick,white] (-3.2,1.2) node[anchor=north west]Sidewall; [ultra thick,black]
(1,1.2) node[anchor=north west]Facet; [ultra thick,white] (-3.2,-1.47)
node[anchor=north west]——; [ultra thick,white] (-3.2,-1.48) node[anchor=north
west]——; [ultra thick,white] (-3.2,-1.46) node[anchor=north west]——; [ultra
thick,white] (-3.2,-1.6) node[anchor=north
west]$0.5\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$;

Figure 3: Inhomogeneous lateral etch of layers with different aluminum
fraction in high chlorine concentration recipes. Note that this is not a BRW
sample but the aluminum fractions in the layers are comparable to BRW wafers.

Vertical sidewalls are usually obtained in predominantly chemical etch
processes where material is removed mainly via reactions with radicals in the
plasma. As radicals gather on the surface of the sample, etching occurs in the
lateral direction removing material from the base of a waveguide ridge. While
such a chemical etch is fast and results in vertical sidewalls, the major
drawback is the anisotropy of the etch at the sidewalls. Layers with lower
aluminum concentrations etch faster than those with a higher aluminum
fraction, as shown in Fig. 3. The aluminum, having a lower electronegativity
than the gallium, tends to react with other components available in the
plasma. This could be resist material that has been removed from the surface
by the etch gases. The resulting aluminum oxide layers then protect the high
aluminum content layers from further chemical etching [24]. This roughness is
not homogeneous along the length of the waveguide and thus contributes
immensely to scattering losses.

Oxidation films on high aluminum fraction layers can best be avoided in
physical etch processes. Here, charged atoms and molecules impinging on the
sample surface remove material. This role is mainly played by the argon atoms
in our etch recipe. This sputter component is increased by replacing the
chlorine with boron trichloride. Boron trichloride undergoes dissociation and
recombination processes in the etch chamber and thereby reduces the amount of
free chlorine available for the etch. In addition, it reacts with aluminum
oxide and water vapor lessening the inhomogeneity of the sidewalls [24].

The chemical mixture of the etch gas alone, however, is not enough to attain
vertical and non-selectively etched sidewalls at the same time. We therefore
tune the other settings of the ICP-RIE. We flood the etch chamber with 40 SCCM
of argon and 4 SCCM of boron trichloride at a low pressure of 0.3 Pa. While
the effects of the pressure on the etch strongly depend on all other
parameters, we find in this regime that the low pressure avoids the
accumulation of reactive species on the sample surface.

1 [ultra thick,white] (-3.2,-0.84) node[anchor=north west]——; [ultra
thick,white] (-3.2,-0.85) node[anchor=north west]——; [ultra thick,white]
(-3.2,-0.86) node[anchor=north west]——; [ultra thick,white] (-3.2,-1)
node[anchor=north west]$3\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$;

1 [ultra thick,white] (-0.8,1.7) node[anchor=north west]$\searrow$; [ultra
thick,white] (-1.8,2.1) node[anchor=north west]Sidewall; [ultra thick,white]
(1.5,-0.9) node[anchor=north west]Facet; [ultra thick,white] (-3.2,-1.94)
node[anchor=north west]——; [ultra thick,white] (-3.2,-1.95) node[anchor=north
west]——; [ultra thick,white] (-3.2,-1.96) node[anchor=north west]——; [ultra
thick,white] (-3.2,-2.1) node[anchor=north
west]$1\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$;

Figure 4: BRWs with homogeneously etched sidewalls in argon-borontrichloride
plasma. A waveguide is defined by a trench on either side (top). The close-up
of the sidewall shows the smooth corner between waveguide facet and sidewall
(bottom).

The plasma is ignited via an RF-coupled induction coil at the top of the etch
chamber. The ICP power is set to a commonly employed value of 400 W. In order
to accelerate the ions in the plasma towards the sample, we apply an RF signal
that leads to a self-biasing of the sample holder. We obtain high-momentum
particles impinging on the sample surface anisotropically by setting the self-
bias to a high value of 150 V. This makes the etch sufficiently physical for
the removal of oxidation products, leading to homogeneous sidewalls. It also
means that the ions reach the lower parts of the already etched sidewall,
leading to an almost vertical sidewall otherwise not possible in such a
physical etch. Two scanning electron micrographs of a BRW fabricated in this
way are shown in Fig. 4. The SEM images show no noticeable inhomogeneity
between the different layers on the sidewall. Small vertical striations are
visible and will be analyzed in the following section.

##  4 Characterization

We assess the quality of the BRWs by determining the sidewall roughness,
optical loss coefficient, and photon pair production rate in PDC. In order to
quantify the improvement of the fabrication after adding the reflow step into
the recipe, we employ two different methods. We first determine the sidewall
roughness using an atomic force microscope (AFM) and then measure the optical
loss in the BRW via a Fourier transform analysis of the transmission spectrum
for the wavelength range around 1550 nm.

Assessment of the sidewall roughness is done using an AFM (Nanosurf NaioAFM)
with a $<10\,\mathrm{nm}$ radius cantilever tip (BudgetSensors Tap190GD-G). As
we would like to separate the effect of the reflow from the inhomogeneity
introduced by the layer stack, we perform this analysis on GaAs waveguides
etched in the same recipe as the BRWs.

1 [very thick,black] (-3.7,0) node[anchor=north west]Parallel waveguide
structures; [very thick,black] (-3.5,-2.1) node[anchor=north west]Cleave along
trench; [very thick,black] (1.1,-1.6) node[anchor=north west]Rotate; [very
thick,black] (1.2,0.9) node[anchor=north west]Cantilever on sidewall;

Figure 5: After cleaving along a trench between waveguides, we rotate our
sample such that the AFM tip has access to the full width and height of the
waveguide’s sidewall.

We cleave the sample along the trench on one side of the waveguide and then
mount it in the AFM sample holder with the waveguide sidewall facing upward.
This offers access for the AFM tip to the entire length and width of the
sidewall, as illustrated in Fig. 5. We scan squares of
$8\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$ width on the samples
fabricated with and without reflow and compare them. Fig. 6 shows cutouts of
two such profiles corresponding to the middle parts of the sidewalls. These
can be reproducibly imaged by the AFM as opposed to the sections near the
substrate or the upper edge of the sidewall. In order to improve the
illustration of the sidewall roughness in this figure, we enhance both images
by removing the same low spatial frequency components from each horizontal
line profile. These low components result from the way the cantilever moves
across the sample, moving slightly upward in the center of a scanned section.
For the quantitative investigation of the sidewall roughness, we use the
original AFM data. From the AFM profiles, we calculate the root-mean-square
area roughness of the sidewalls

$\sigma_{\mathrm{RMS}}=\sqrt{\frac{\sum_{\begin{subarray}{c}N\end{subarray}}(z-\bar{z})^{2}}{N-1}}$
(1)

where $N$ is the number of pixels, $z$ is the height value recorded for a
certain pixel and $\bar{z}$ is the mean height. We obtain values of 16.05(2)
nm for the no-reflow samples and 4.736(7) nm for the samples fabricated using
the reflow method. Absolute area roughness values depend strongly on the
cantilever tip and measurement mode, but the relative roughness can be
estimated. Here, the area roughness is reduced by a factor of more than three
when employing the reflow method.

1 [very thick,black] (-1.3,0.5) node[anchor=north west]Image Length
($\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$); [very thick,black]
(-1.2,-3) node[anchor=north west]Pixel Height (nm); [very thick,black]
(-4.5,-1.5) node[anchor=north west, rotate=90]Image Width
($\text{\,}\mathrm{\SIUnitSymbolMicro m}\text{/}$); [very thick,black]
(-4.2,-2.62) node[anchor=north west]-10.0; [very thick,black] (-3.16,-2.62)
node[anchor=north west]-7.5; [very thick,black] (-2.22,-2.62)
node[anchor=north west]-5.0; [very thick,black] (-1.28,-2.62)
node[anchor=north west]-2.5; [very thick,black] (-0.3,-2.62) node[anchor=north
west]0.0; [very thick,black] (0.65,-2.62) node[anchor=north west]2.5; [very
thick,black] (1.58,-2.62) node[anchor=north west]5.0; [very thick,black]
(2.50,-2.62) node[anchor=north west]7.5; [very thick,black] (3.35,-2.62)
node[anchor=north west]10.0; [very thick,black] (-3.87,0.77) node[anchor=north
west]0; [very thick,black] (-2.92,0.77) node[anchor=north west]1; [very
thick,black] (-1.97,0.77) node[anchor=north west]2; [very thick,black]
(-1.02,0.77) node[anchor=north west]3; [very thick,black] (-0.07,0.77)
node[anchor=north west]4; [very thick,black] (0.88,0.77) node[anchor=north
west]5; [very thick,black] (1.83,0.77) node[anchor=north west]6; [very
thick,black] (2.78,0.77) node[anchor=north west]7; [very thick,black]
(-4.14,1.07) node[anchor=north west]0; [very thick,black] (-4.14,1.93)
node[anchor=north west]1; [very thick,black] (-4.14,-1.55) node[anchor=north
west]0; [very thick,black] (-4.14,-0.69) node[anchor=north west]1; [very
thick,black] (-3.94,1.9) node[anchor=north west]–; [very thick,black]
(-3.94,1.03) node[anchor=north west]–; [very thick,black] (-3.94,-1.63)
node[anchor=north west]–; [very thick,black] (-3.94,-0.76) node[anchor=north
west]–; [very thick,black] (-3.85,0.58) node[anchor=north west, rotate=90]–;
[very thick,black] (-2.9,0.58) node[anchor=north west, rotate=90]–; [very
thick,black] (-1.95,0.58) node[anchor=north west, rotate=90]–; [very
thick,black] (-1,0.58) node[anchor=north west, rotate=90]–; [very thick,black]
(-0.05,0.58) node[anchor=north west, rotate=90]–; [very thick,black]
(0.9,0.58) node[anchor=north west, rotate=90]–; [very thick,black] (1.85,0.58)
node[anchor=north west, rotate=90]–; [very thick,black] (2.8,0.58)
node[anchor=north west, rotate=90]–; [very thick,black] (-3.85,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (-2.9,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (-1.95,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (-1,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (-0.05,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (0.9,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (1.85,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (2.8,-0.27)
node[anchor=north west, rotate=90]–; [very thick,black] (-3.85,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (-2.9225,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (-1.995,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (-1.0675,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (-0.14,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (0.7875,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (1.715,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (2.6425,-2.82)
node[anchor=north west, rotate=90]–; [very thick,black] (3.568,-2.82)
node[anchor=north west, rotate=90]–;

Figure 6: Cutouts of the full AFM images, with low Fourier components omitted.
The sample made without the reflow step shows clear vertical striations near
the top of the waveguide and a honeycomb-like structure towards the substrate
(top). Reflowing the resist smoothens the sidewall (bottom).

From the findings in the AFM studies on GaAs, we expect the scattering losses
in the reflow BRW sample to be substantially lower than in previous samples.
This is because we consider the sidewall roughness a variation in the
waveguide width, and thus a grating coupler to the radiation modes [25, 26,
27, 28]. The decreased scattering losses are confirmed by measuring the
transmission spectrum of the BRW in the telecom wavelength range, where the
photons are produced during PDC. We couple a tunable telecom laser (Santec
TSL-710) into the waveguide via a 100x microscope objective and collect the
output light using an aspheric lens. A powermeter (Thorlabs S122C) measures
the transmitted light. The facets of the waveguide have a reflectivity of
35(4)%, meaning the waveguide acts as a weak cavity [23]. As light from
multiple reflections interferes at the output facet of the waveguide, the
power meter detects interference fringes when the wavelength of the input
light is scanned. In a single mode system, one could readily determine the
losses in the waveguide from the visibility of these Fabry-Perot fringes. The
BRW, however, supports higher order spatial modes including the Bragg mode.
Due to the multimodal nature of the waveguide, the fringes exhibit a beat
pattern that is more difficult to interpret. In order to modally resolve this
transmissivity measurement, we Fourier-transform the transmission spectrum as
detailed in Ref. [23].

1 [very thick,black] (-1.7,-2.8) node[anchor=north west]Optical Length $d$
(mm); [very thick,black] (-2.93,-2.5) node[anchor=north west]2; [very
thick,black] (-1.92,-2.5) node[anchor=north west]4; [very thick,black]
(-0.91,-2.5) node[anchor=north west]6; [very thick,black] (0.09,-2.5)
node[anchor=north west]8; [very thick,black] (1,-2.5) node[anchor=north
west]10; [very thick,black] (2.02,-2.5) node[anchor=north west]12; [very
thick,black] (3.03,-2.5) node[anchor=north west]14; [very thick,black]
(-4.3,-2) node[anchor=south west, rotate=90]Spectral Amplitude (a.u.); [very
thick,black] (-4.5,-2.4) node[anchor=south west]$10^{0}$; [very thick,black]
(-4.5,-1.47) node[anchor=south west]$10^{1}$; [very thick,black] (-4.5,-0.55)
node[anchor=south west]$10^{2}$; [very thick,black] (-4.5,0.37)
node[anchor=south west]$10^{3}$; [very thick,black] (-4.5,1.31)
node[anchor=south west]$10^{4}$; [very thick,black] (-4.5,2.2)
node[anchor=south west]$10^{5}$; [very thick,black] (0.9,0.4)
node[anchor=south west]1520nm; [very thick,black] (2.55,0.4) node[anchor=south
west]1550nm; [very thick,black] (0.5,0.72) node[anchor=south west]5$\%$; [very
thick,black] (0.4,1.3) node[anchor=south west]10$\%$; [very thick,black]
(0.4,1.9) node[anchor=south west]15$\%$; [very thick,black] (1.02,1.21)
node[anchor=north west]-; [very thick,black] (1.02,1.78) node[anchor=north
west]-; [very thick,black] (1.02,2.35) node[anchor=north west]-; [very
thick,black] (1.15,0.65) node[anchor=north west, rotate=90]-; [very
thick,black] (3.37,0.65) node[anchor=north west, rotate=90]-; [dashed][line
width=0.5mm, orange ] (-3.3,2.42) – (0.96,-1) node [midway] ;

1 [very thick,black] (-1.7,-2.8) node[anchor=north west]Optical Length $d$
(mm); [very thick,black] (-2.93,-2.5) node[anchor=north west]2; [very
thick,black] (-1.92,-2.5) node[anchor=north west]4; [very thick,black]
(-0.91,-2.5) node[anchor=north west]6; [very thick,black] (0.09,-2.5)
node[anchor=north west]8; [very thick,black] (1,-2.5) node[anchor=north
west]10; [very thick,black] (2.02,-2.5) node[anchor=north west]12; [very
thick,black] (3.03,-2.5) node[anchor=north west]14; [very thick,black]
(-4.3,-2) node[anchor=south west, rotate=90]Spectral Amplitude (a.u.); [very
thick,black] (-4.5,-2.4) node[anchor=south west]$10^{0}$; [very thick,black]
(-4.5,-1.47) node[anchor=south west]$10^{1}$; [very thick,black] (-4.5,-0.55)
node[anchor=south west]$10^{2}$; [very thick,black] (-4.5,0.37)
node[anchor=south west]$10^{3}$; [very thick,black] (-4.5,1.31)
node[anchor=south west]$10^{4}$; [very thick,black] (-4.5,2.2)
node[anchor=south west]$10^{5}$; [very thick,black] (0.9,0.4)
node[anchor=south west]1520nm; [very thick,black] (2.55,0.4) node[anchor=south
west]1550nm; [very thick,black] (0.4,1.0) node[anchor=south west]10$\%$; [very
thick,black] (0.4,1.93) node[anchor=south west]20$\%$; [very thick,black]
(1.02,1.47) node[anchor=north west]-; [very thick,black] (1.02,2.4)
node[anchor=north west]-; [very thick,black] (1.15,0.65) node[anchor=north
west, rotate=90]-; [very thick,black] (3.37,0.65) node[anchor=north west,
rotate=90]-; [dashed][line width=0.5mm, red ] (-3,2.4) – (1.5,-0.63) node
[midway] ; [dashed][line width=0.5mm, orange ] (-3,1.95) – (1.5,-0.37) node
[right] ;

Figure 7: Fourier transform of the transmission spectrum (inset) for TE
polarized input light in the telecom wavelength range for the BRW fabricated
without (top) and with reflow (bottom). For the latter, the peak height ratios
of early peaks (red line) differ from those of later peaks (orange line). An
early peak refers to a peak farther to the left in the plot and corresponds to
light that has only survived one or two passes through the waveguide cavity.
Light that contributes to a late peak farther to the right has passed through
the waveguide four or five times.

The resulting Fourier spectra, shown in Fig. 7, can be interpreted as follows.
Light in the waveguide experiences a time delay at every pass through the
waveguide and at every reflection from the facets. This time delay corresponds
to a translation in Fourier space and manifests as peaks at integer multiples
of the resonator length for each mode. The Fourier spectra shown here feature
a pattern of one strong peak and smaller side peaks that repeat again after a
distance of one resonator length. This corresponds to one or more strong modes
at similar effective refractive index and weaker modes with different
effective refractive indices. The ratio of heights $\tilde{R}$ of subsequent
peaks belonging to one mode thus contains information about the loss during
one pass through the waveguide for that specific mode. For a known
reflectivity of the facets $R$ and resonator length $L$, the loss coefficient
can be readily calculated:

$\alpha=-\frac{1}{L}\mathrm{ln}\left(\frac{\tilde{R}}{R}\right).$ (2)

The optical length $d$ is proportional to $L$ via the factor $\pi/n$, where
$n$ is the group refractive index. We determine the loss coefficient for each
ratio of neighboring peak heights separately. Fig. 8 shows a comparison of the
loss coefficients of two BRWs made with (orange) and without (grey) the reflow
step but coming from the same wafer. The loss coefficient of the latter varies
between $\alpha_{\mathrm{no\,reflow}}=0.23\left(9\right)\,\mathrm{mm}^{-1}$
and $\alpha_{\mathrm{no\,reflow}}=0.32\left(9\right)\,\mathrm{mm}^{-1}$
without any upward or downward trend. The loss coefficient of the BRW
fabricated with reflow is higher than that of the no-reflow sample for the
first two peaks in the Fourier spectrum. This is counterintuitive, as we would
expect a smoother sidewall leading to lower loss coefficients. However, for
later peaks, the loss coefficient drops below that of the BRW made without
reflowed resist. It also follows a clear trend, decreasing down to a loss
coefficient of
$\alpha_{\mathrm{reflow}}=0.08\left(6\right)\,\mathrm{mm}^{-1}$.

All but the fundamental telecom mode are strongly dampened within the
waveguide, which was manufactured without reflow. Mode simulations show that
higher-order modes exhibit higher field strengths closer to the waveguide
surface and are thus more easily scattered with increased surface roughness.
Thus, mainly the fundamental mode survives. When the sidewall roughness is
reduced by reflowing the resist, another, higher order mode with higher loss
can also propagate within the waveguide. This mode has an effective refractive
index difference to the fundamental mode of only about 0.01 at 1535 nm
wavelength. This higher-loss mode dominates the early peak height ratios,
causing high loss coefficients. As its contribution diminishes, the losses go
down, revealing how much the reflow step improved the propagation of the
original mode. Overall, the losses for TE polarized light in the telecom
wavelength range were reduced from between
$\alpha_{\mathrm{no\,reflow}}=0.23\left(9\right)\,\mathrm{mm}^{-1}\,\,\mathrm{and}\,\,0.32\left(9\right)\,\mathrm{mm}^{-1}$
to $\alpha_{\mathrm{reflow}}=0.08\left(6\right)\,\mathrm{mm}^{-1}$.

1 [very thick,black] (-3.7,2.9) node[anchor=north west]Peaks $1\&2$; [very
thick,black] (-1.8,2.9) node[anchor=north west]Peaks $2\&3$; [very
thick,black] (0.10,2.9) node[anchor=north west]Peaks $3\&4$; [very
thick,black] (1.97,2.9) node[anchor=north west]Peaks $4\&5$; [very
thick,black] (0.13,-1.3) node[anchor=north west]No reflow; [very thick,black]
(0.13,-1.65) node[anchor=north west]Reflow; [very thick,black] (-4.35,-0.75)
node[anchor=south west, rotate=90]$\alpha\left(\mathrm{mm}^{-1}\right)$; [very
thick,black] (-4.5,2.6) node[anchor=north west]$0.00$; [very thick,black]
(-4.5,2.078) node[anchor=north west]$0.05$; [very thick,black] (-4.5,1.556)
node[anchor=north west]$0.10$; [very thick,black] (-4.5,1.034)
node[anchor=north west]$0.15$; [very thick,black] (-4.5,0.512)
node[anchor=north west]$0.20$; [very thick,black] (-4.5,-0.01)
node[anchor=north west]$0.25$; [very thick,black] (-4.5,-0.532)
node[anchor=north west]$0.30$; [very thick,black] (-4.5,-1.054)
node[anchor=north west]$0.35$; [very thick,black] (-4.5,-1.576)
node[anchor=north west]$0.40$; [very thick,black] (-4.5,-2.098)
node[anchor=north west]$0.45$;

Figure 8: Loss coefficients $\alpha$ derived from the Fourier transform of the
transmission spectrum of two BRWs fabricated with reflow shown in orange and
those fabricated without in grey. The bars represent the loss coefficients
calculated from the ratios of neighboring peaks in the Fourier spectrum.

Reducing the losses on this scale has a significant effect on nonlinear
conversion processes. We test this by measuring the coincidence rates between
the signal and idler photons produced in PDC. To do so, we pump the sample
with a NIR laser (MSquared SolsTis 6W PSX-R) set to the phase-matching
wavelength. A dichroic mirror placed at the output of the BRW filters out the
remaining pump light. The down-converted photon pair is orthogonally polarized
and can therefore be split up at a polarizing beam splitter and relayed to two
superconducting nanowire single photon detectors (Single Quantum Eos 720 CS).
We measure the coincidence rate between the two detectors for a pump power of
1 mW and normalize to the length of the waveguide sample. Table 1 lists the
results for the BRWs fabricated using the recipe with and without reflow
detailed above, and the previous recipe employing e-beam lithography and a
metal mask for etching. The coincidence rate and therefore the conversion
efficiency is highest in the sample fabricated using the reflow step. Both of
the recipes employing FBMS optical lithography perform better than the recipe
using e-beam lithography and metal mask deposition. By adding the reflow step
to the recipe, the coincidence rate could be increased by around six-fold.
Note that the measured coincidence rates depend on the coupling efficiencies
in the setup. The values shown here were measured at similar conditions in the
setup to allow a comparison. However, much higher coincidence rates of
$89\left(5\right)\,\mathrm{Hz/\mathrm{\mu}W}$ have been achieved in the
meantime using the reflow-sample in an optimized setup [29]. Such an
improvement in performance through careful optimization of the fabrication
recipe means that BRWs are a reliable option where an integrable source for
photon pairs is needed.

Recipe | reflow | no reflow | previous
---|---|---|---
Coincidences | 8800(300) | 1490(60) | 600(100)
Table 1: Comparison of coincidence counts measured per second per mm waveguide
length at 1 mW external pump power for the three different fabrication
recipes. The value for the previous recipe is taken from Ref. [30].

##  5 Conclusion and outlook

We optimized the fabrication recipe for BRWs to yield samples with lower
optical loss and therefore higher photon pair production rates. By employing
FBMS optical lithography, low pressure and low chlorine concentration etching,
and resist reflow, we reduced the RMS area sidewall roughness in test GaAs
sample waveguides from 16.05(2) nm to 4.736(7) nm. For our BRWs, the improved
etch recipe results in a low optical loss coefficient for telecom wavelength
light of $\alpha_{\mathrm{reflow}}=0.08\left(6\right)\,\mathrm{mm}^{-1}$. The
lower optical losses lead to higher coincidence rates between the signal and
idler photons created in PDC. The rate of
$8800\left(300\right)\,\left(\mathrm{mW\cdot s\cdot mm}\right)^{-1}$ is around
a six-fold increase compared to samples produced without the reflow step and a
factor of around 15 better than previous samples. This shows that a
fabrication recipe benefits from optimization of every manufacturing step.
Resist reflow is a particularly important step in reducing the sidewall
roughness of waveguides and is one of the main factors contributing to optical
losses in miniaturized optical devices. The improved fabrication and resulting
low loss BRWs testify to the adequacy of the AlGaAs platform for quantum
communication applications.

Funding The authors acknowledge funding by the Uniqorn project (Horizon 2020
grant agreement no. 820474) and the BeyondC project (FWF project no. F7114).

Acknowledgments We thank Felix Laimer and Elisabeth Gruber for help with
atomic force microscopy and Markus Weiss for support and fruitful discussions
in the cleanroom.

Author contributions Conceptualization, H.T., R.J.C., S.F., G.W.; Formal
analysis, H.T., M.W., S.F.; Methodology, H.T., M.W., R.J.C., S.F.;
Investigation, H.T., M.W., B.N., A.S.; Resources, H.S., M.K., S.H., C.S.;
Software, H.T., S.F.; Supervision, R.J.C., S.F., C.S., G.W.; Writing -
original draft, H.T.; Writing - review & editing, All Authors; Funding
acquisition, C.S., G.W.

Disclosures The authors have nothing to disclose.

Data availability Data underlying the results presented in this paper are
available at 10.5281/zenodo.7702404.

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# A radio loud semiregular variable

Pedro L. Luque-Escamilla Departamento de Ingeniería Mecánica y Minera,
Escuela Politécnica Superior de Jaén, Universidad de Jaén,
Campus Las Lagunillas s/n, 23071 Jaén, Spain  Josep Martí Departamento de
Física,
Escuela Politécnica Superior de Jaén, Universidad de Jaén,
Campus Las Lagunillas s/n, 23071 Jaén, Spain

###### Abstract

As a byproduct of our search for Galactic stellar systems with gamma-ray
emission, we have identified an unrelated cool and evolved star (IRC$-$10412)
that attracted our attention due to its strong radio emission level with a
spectral index matching, almost perfectly, the canonical +0.6 value expected
from an ionized stellar wind. A follow-up observational analysis was
undertaken given that these two properties are hard to reconcile as
originating in the same stellar object. As a result, IRC$-$10412 has been
classified as a new semiregular variable of SRb type in the asymptotic giant
branch, and different but consistent estimates of its mass-loss parameter are
reported. We propose that its unusually high radio emission arises from a
$\sim 10^{-5}M_{\odot}$ yr-1 stellar wind exposed to an external source of
ionizing photons, possibly coming from nearby OB associations.

Stars: variables: general — Stars: supergiants — Stars: winds, outflows —
Stars: individual: IRC -10412

##  1 Introduction

Mining the multi-wavelength data archives currently available provides ample
room for discovery and scientific exploitation. Moreover, research in a given
area of Astrophysics sometimes leads to unexpected findings in another. This
is the case reported here. In the course of our efforts to identify compact
radio sources of early-type stellar nature that could be behind potential
gamma-ray emitters (e.g. Martí et al., 2020; Martí & Luque-Escamilla, 2021;
Luque-Escamilla et al., 2023), we came across an interesting object worth of
being reported for its scientific interest in the domain of cool, evolved
stars. These objects at the end of their lives often behave as long-period
variables (LPVs), which are specially interesting as independent distance
calibrators via period–luminosity relations (Whitelock & Feast, 2014; Rau et
al., 2019; Trabucchi et al., 2021). Moreover, these aged stars are major
contributors to the processed material in the interstellar medium (e.g.
Sedlmayr, 1994; Karakas & Lattanzio, 2014). Estimating their mass-loss rates
is therefore of great astrophysical interest (Winters et al., 2000).

Stars at such advanced stages of evolution are also known to be sources of
thermal radio emission originating in their winds and envelopes. Our
understanding of this phenomenon is mostly based around the concept of stellar
radio photosphere. Its radius corresponds to optical depth unity of the
dominant free-free emission mechanism, that usually amounts to a few times the
optical photospheric radius (Reid & Menten, 1997; Matthews et al., 2018). The
observed radio brightness for giant and supergiant stars closer than 1 kpc are
typically below the 1 mJy level (Drake et al., 1991; Rudnitskij & Chapman,
2007). Radio studies of these systems and their stellar activity have seen
their motivation enhanced in recent times given their connection with exo-
space weather phenomena and life sustainability in exo-planets (Carilli et
al., 2018).

In this work, we report the identification of a new asymptotic giant branch
(AGB) LPV star with heavy absorption from a circumstellar dust that exhibits a
remarkable differential feature: an intense radio emission exceeding by at
least two orders of magnitude the typical radio luminosity of other members of
its class. This unique behavior opens the possibility to an independent
estimation of its mass-loss rate with no need of empirical prescriptions,
together with engrossing the so-called dust-enshrouded AGB star family.

The rest of the manuscript is organized as follows: the next section
introduces the target of our study, the system IRC$-$10412, and how we focused
our attention on it. The paper continues with a section devoted to present the
multi-wavelength observational evidence followed by another section of
discussion and modeling of the spectral energy distribution (SED). Conclusions
are summarized at the end.

##  2 The elusive nature of IRC$-$10412

IRC$-$10412 (a.k.a. IRAS 18179$-$1346 and StRS177) is one of entries in the
historical Infrared Catalog (IRC) compiled by Neugebauer & Leighton (1969).
After a first unsuccessful classification attempt (Hansen & Blanco, 1973), the
star was photometrically observed by Lockwood (1985) who assigned it a
supergiant M7.0 spectral type. In addition, these authors provided the first
suspicion of IRC$-$10412 variability as they consider it a possible member of
the so called ”M10 Mira variables”. IRAS low-resolution spectra, reported by
Volk & Cohen (1989) and later Kwok et al. (1997), displayed a featureless
continuum consistent with a M star. This interpretation was at some point
challenged given the apparent non-detection of TiO bands in the photographic-
infrared objective prism survey by Stephenson (1992). Together with strong
H$\alpha$ emission detected in the optical by Rawlings et al. (2000), these
two last works pointed to a highly-reddened, early-type classification instead
of a late evolved star. Independently, the Very Large Array (VLA) survey of
the Galactic Plane, conducted by Becker et al. (1994), revealed the radio
source GPS5 017.223+0.395, whose position is very close to that of
IRC$-$10412, and then believed to be an ultra compact HII region (UCHII). It
was studied as such in follow-up work, but this GPS5 object was noticed not to
agree well with the typical properties of high-mass star formation sites, in
particular its non-flat spectral index (Leto et al., 2009). A possible UCHII
mis-classification was even suspected (Anderson et al., 2009). In recent
times, the Gaia Data Release 3 (Lebzelter et al., 2023) has provided the
latest improvement of our knowledge about IRC$-$10412 with a trigonometric
parallax distance of $d=1.6\pm 0.1$ kpc, which will be adopted here. They also
find additional hints of being a LPV around a mean apparent magnitude G=12.48.

In parallel, IRC$-$10412 would not have attracted the attention of the authors
if it had not been for our attempt to search for possible stellar gamma-ray
sources among highly reddened luminous stars (to be reported elsewhere).
Indeed, a significant fraction of currently known gamma-ray binaries have
luminous, early-type optical counterparts (Paredes & Bordas, 2019), in
addition to compact radio emission. Why not similar obscured systems could be
waiting for discovery? Our starting point was the Stephenson (1992) list of
highly reddened objects with unbanded spectra suspected to be distant luminous
stars. We cross-identified them with different radio surveys, in particular
the NRAO VLA Sky Survey (NVSS) by Condon et al. (1998). At this point,
IRC$-$10412 emerged as one of the matches deserving additional study after
exploring the literature quoted in the previous paragraph. We also noticed
that IRC$-$10412 had been detected, and proposed to be a likely radio-star, in
the 5 GHz CORNISH survey (Hoare et al., 2012), hence encouraging further
investigation.

##  3 Observational properties

###  3.1 The radio spectrum and morphology

.

Table 1: Radio flux densities of IRC$-$10412

Freq. | Integrated |
---|---|---
(GHz) | Flux Density | Reference
| (mJy) |
1.4 | $87.9\pm 2.7$ | NVSS, Condon et al. (1998)
1.4 | $99^{*}$ | GPS5, Becker et al. (1994)
3.0 | $157.43\pm 0.56$ | VLASS1 and VLASS2∗∗
| $160.29\pm 0.56$ | https://science.nrao.edu/vlass
5.0 | $199.86\pm 19.69$ | CORNISH, Hoare et al. (2012)
5.0 | $151.6^{*}$ | GPS5, Becker et al. (1994)
42.95 | $595\pm 90$ | Hoare et al. (2012)

(*) Error unavailable. (**) Measured using AIPS JMFIT.

Figure 1: Radio spectrum of IRC$-$10412, in the cm-mm wavelength domain,
assembled using the survey data listed in Table 1. The dashed line is a simple
power-law fit.  Figure 2: VLSS1 resolved radio map of IRC$-$10412 at the 3.0
GHz frequency with observation date 2019 June $19^{th}$. The bottom left
ellipse represents the clean synthesized beam of $3.31\times 2.12$ arc-
second2, with position angle $-8.0^{\circ}$. The star symbol indicates the
Gaia DR3 optical position of IRC$-$10412\.

Radio flux densities of IRC$-$10412 can be found in the literature from
different sources. We have collected them in Table 1. In addition, we have
also used the recent VLA Sky Survey (VLASS)
maps111https://science.nrao.edu/vlass, and directly measured the target flux
density using the JMFIT task of the AIPS software package for the two epochs
available. The result is plotted in Figure 1. Neglecting radio variability, a
simple least squares fit indicates that the radio spectrum is well represented
by $S_{\nu}=(79\pm 4)~{}{\rm mJy}\left[\nu/{\rm GHz}\right]^{+0.63\pm 0.05}$,
where $\nu$ is the observing frequency. On the other hand, the VLASS angular
resolution is high enough to resolve the IRC$-$10412 morphology at 3.0 GHz as
evidenced in the contour map of Figure 2. By fitting an elliptical Gaussian
using JMFIT, the deconvolved angular size turns out to be $(3.5\pm
0.1)\times(2.87\pm 0.04)$ arc-second2, with position angle $165^{\circ}\pm
3^{\circ}$.

###  3.2 The IRC$-$10412 optical light curve

Given the hints of optical variability mentioned above, we decided to further
explore this issue. Although IRC$-$10412 is much brighter in the infrared, it
is still accessible in red optical filters where most dedicated variability
surveys are at work. In particular, the Zwicky Transient Facility (ZTF) (Masci
et al., 2019) appeared as the most suitable for this purpose with hundreds of
images of available for differential photometry. A stacked ZTF view of the
IRC$-$10412 field of view in its $r$-band is shown in Figure 3 displaying both
the central target and our two comparison stars labelled as C1 and C2.

Figure 3: ZTF $r$-band image of the IRC$-$10412 field. The orientation and
image scale are given by the yellow bars. The target and comparison stars are
marked using dashed circles.

These two objects correspond to stars Gaia DR3 4152417198316110336 and Gaia
DR3 4152420221973094144, respectively. We downloaded the ZTF frames and
conducted our own differential photometry on them using the IRAF software
package. The resulting light curve is plotted in Figure 4 where strong
variability with amplitude of $\sim 1$ magnitude on time scales of hundreds of
days is evident. When comparing with the light curve produced by the ZTF
pipeline, whose mean level is $r=15.30$ magnitudes, the same variability
behavior is obtained .

Figure 4: Photometric analysis of IRC$-$10412 using ZTF $r$-band images. Black
points correspond to the target light curve. Red points represent the
difference between comparison star C1 and the check star C2, that remains
stable within about 0.02 magnitudes.  Figure 5: Wavelet periodogram of the ZTF
$r$-band light curve of IRC$-$10412\. Two main periods of 553 and 219 days are
shown with dashed horizontal lines.

To better assess the variability time scale we carried out a period search
using different methods. Phase Dispersion Minimization (PDM; Stellingwerf,
1978) Lomb-Scargle (Scargle, 2002) and wavelet analysis (see Figure 5) yield
the same result: the star light curve appears to evolve under two main
periods, estimated as 219 and 553 day, that stand out above the rest of
spectral features. Although the 219 days period could be the one year alias of
the fundamental mode, the CLEAN algorithm, which deals better with sampling
problems, clearly maintains the two mentioned periods.

###  3.3 Assembling the IRC$-$10412 SED

Figure 6: Dereddened SED of IRC$-$10412 and model fit given by the continuous
red line. How the fit has been assembled in the different wavelength regions
is explained in the text. The dotted lines with black, orange and blue colors
correspond to the components modeled as ionized wind radio emission, external
cold dust emission and inner dust shell emission, respectively.

In order to facilitate the discussion of the physical nature of IRC$-$10412,
we took advantage of the spectral energy distribution (SED) building tools
provided by the Strasbourg astronomical Data
Center222https://vizier.cds.unistra.fr, Ochsenbein et al. (2000) and
references therein.. We have built an empirical broad-band SED by using the
multi-wavelength data available from 2MASS, WISE, Palomar POSS/ZTF, Gaia,
SDSS, Hipparcos, IRAS, AKARI, UKIDS/UKIRT, Pan-STARRS, SkyMapper, MSX,
together with the radio data collected in Subsection 3.1. Optical and infrared
fluxes have been dereddened from interstellar extinction taking into account
the model of Marshall et al. (2006) and the stilism app based on the work of
Capitanio et al. (2017). As a result, we estimate the interstellar absorption
as $A_{V}=3.1\pm 0.6$, assuming an optical parameter $R_{V}=3.1$. The
corresponding absorption coefficients for other bands were obtained from the
SVO profile filter (Rodrigo & Solano, 2020). The final plot is shown in Figure
6 as a function of frequency.

##  4 Results and discussion

The Gaia DR3 release delivers for our source $T_{\mathrm{eff}}=3722\pm 4$ K,
$\log(g/\rm{cm~{}s}^{-2})=0.125^{+0.012}_{-0.007}$ and a chemical abundance
[M/H]$=-0.82$ dex computed with its Apsis pipeline based on low-resolution
BP/RP spectra (GSP-Phot module). These values are typical for cool, giant,
evolved stars. Moreover, they are consistent with the M spectral type proposed
in the literature for IRC$-$10412\. However, the parameters from Apsis for
this kind of stars do not consider the effects of circumstellar envelopes and
compositional changes due to dredge-up. In fact, Messineo (2023) shows that
while gravity measures are not far from literature values, $T_{\mathrm{eff}}$
is overestimated and [M/H] is poorly constrained. In any case, chemical
abundance in IRC$-$10412 should not exceed $0.5$ dex, and its
$T_{\mathrm{eff}}$ must be close to 3000 K, in accordance with its suspected
cool, evolved stellar nature.

###  4.1 Classifying IRC$-$10412

IRC$-$10412 is clearly an optical variable source on time scales of hundreds
of days thus confirming the Gaia LPV classification. These objects are
commonly related to cool stars in the last stages of their evolution, mainly
Miras, AGB stars (with masses below about $8M_{\odot}$), and the more massive
red supergiants (RSGs). The main cause under this variability seem to be
pulsation. Although the driving mechanism is not well known (see Percy (2007)
for an introductory review), much effort have been recently devoted to obtain
a improved modeling (see, for instance, Trabucchi et al., 2019, 2020).

The variability cycles are often related to the fundamental and higher
overtone pulsations. With al caution, it is tempting to associate the light
curve 553 days periods found in section 3.2 with the fundamental mode. If the
219 days period was real, it could be related to the first overtone. On the
other hand, the observed optical variability is small compared to the expected
in Mira systems ($\gtrsim 2.5$ mag in $V$ filter, moving down to $\gtrsim 0.4$
mag for $K$ filter, e.g. Whitelock et al., 1994). Taking all these facts,
IRC$-$10412 qualifies to be considered a likely semi-regular variable SRb.

As AGBs show larger amplitudes in their pulsations than RSGs, the $\sim 1$ mag
bright variations of IRC$-$10412 seem to be more suitable to a star of the
first kind. Here we are assuming that the observed peak-to-peak amplitude is
intrinsic to IRC$-$10412\. A non-variable infrared component, either internal
to the IRC$-$10412 system or unnoticed inside the photometric aperture, could
be reducing the true variability amplitude. However, we do not have evidence
that this is actually one of these cases.

Both AGBs and RSGs are highly reddened stars, probably associated with the
absorption of their light output by dust grains and its posterior re-emission
at longer wavelengths. Significant extinction in the optical together with
excess emission in the thermal infrared is then a clear indication of this
scenario. This seems to be the case in the IRC$-$10412 SED displayed in Figure
6. In order to get a deeper insight into the properties of our source, we will
proceed trying to fit the observed broad-band SED regions having in mind that
the available data points are not strictly simultaneous in time.

###  4.2 Radio counterpart association with IRC$-$10412

The 1-$\sigma$ uncertainty for the the CORNISH radio survey, where the best
radio position comes from at the present time, amounts to 0.147 arc-second.
The coincidence between IRC$-$10412 and the proposed radio counterpart is at
the 2.6 and 1.4-$\sigma$ level in right ascension and declination,
respectively. This is a pretty good agreement for the radio photocenter and
the optical Gaia DR3 position considering that we are dealing with a slightly
extended radio source. Given this small offset, we consider that the chances
of association are very high and will proceed under the assumption that radio
and optical/IR emission come from the same object. Moreover, an extragalactic
source mimicking so well the radio spectrum and extended morphology of a
stellar wind will be very unlikely.

###  4.3 SED radio modelling and mass-loss estimate

A specially striking characteristic of our source is its unusually high level
of radio emission with respect to typical cool, evolved stars. For instance,
the RSG VY CMa integrated flux density ranges from $0.24\pm 0.02$ mJy at $8.4$
GHz to $2.5\pm 0.5$ mJy at $42.95$ GHz (Lipscy et al., 2005), which is at
least two orders of magnitude smaller than in our source. This contrast cannot
be accounted for the difference in distance and is even more dramatic for
other LPVs (Reid & Menten, 1996). In addition, these authors find that the
power-law spectral index in these objects is of the order of $1.7$-$2$,
pointing to an optically-thick emission that they modeled as a “radio
photosphere”. However, this value is far from the spectral index of $0.6$
observed for IRC$-$10412 (see 3.1), Another possible scenario involves an
asymmetric, ionized region produced when the stellar wind of our cool, evolved
star is ionized by a hot companion, like a white dwarf. The strong H$\alpha$
line emission reported by Rawlings et al. (2000) would fit with this picture,
that resembles a symbiotic Mira (Seaquist et al., 1984; Taylor & Seaquist,
1984; Seaquist & Ivison, 1994). The well-known STB model proposed by these
authors is capable to explain radio emission based on a single ionization
parameter $X$ which defines the geometry of the ionized region, and depends on
the red giant mass-loss rate, the binary separation, and the Lyman continuum
luminosity of the ionizing source. If we assume reasonable typical values for
the sum of masses of cool giant and white dwarf from $2$ to $10$ $M_{\odot}$
and a period of about 2 years, we get a binary separation $a\sim 10^{13}$ cm.
Taking into account the mass-loss rate and wind terminal velocity derived
below from infrared data, we finally obtain an ionization parameter $X\sim
10^{-4}$. However, $X>\pi/4$ is needed to get the radio spectral index of
$0.6$ observed for IRC$-$10412 (Taylor & Seaquist, 1984). This fact, together
with the lack of any conspicuous period of the order of years in the light
curve, led us to discard this binary scenario.

Therefore, we finally propose that radio emission comes from a spherically
symmetric stellar wind whose density decays as the inverse of the distance
squared (Panagia & Felli, 1975; Wright & Barlow, 1975), which theoretically
gives an spectral index of $0.6$, remarkably coincident with that observed for
IRC$-$10412\. Thus, we would be facing a thermal free-free emission in a
completely ionized outflow from the star, in spite of its intrinsic cool
nature. Of course, an external source of ionizing photons needs to be invoked
if this is the case. These facts could be reconciled if we take into account
the close vicinity of the Serpens 2 and Scutum 3 OB associations (Mel’Nik &
Efremov, 1995). Under this assumption, we fitted the observed SED at radio
wavelengths with the Panagia & Felli (1975) model together with an exponential
cutoff (at $\nu_{c}=10^{11}$ Hz), adopting a plasma electron temperature of
$T_{e}=10^{4}$ K for a completely ionized wind, an average ionic charge
$\bar{Z}=0.9$ for a cold star with neutral Helium, and a typical mean atomic
weight per electron $\mu=1.2$. We have also fixed a wind terminal velocity of
$17.5$ km s-1, which is a mean value between the $10$ to $25$ km s-1 typical
range for AGBs and RSGs, and is appropriate for nearby dust-enshrouded AGBs
(Olivier et al., 2001). In this way, we get the best fit for a mass-loss rate
of $\dot{M}=1.05\times 10^{-5}M_{\odot}$ yr-1 (dot-dashed black line in Fig.
6). It is noteworthy that the Panagia & Felli (1975) formalism leads us to
directly obtain the mass-loss rate without the need of an optical-infrared SED
fit or a empirical prescription, as usual for cool, evolved stars. This
historic model also allows us to estimate the angular diameter of the radio
emitting region, yielding $\sim 1.8^{\prime\prime}$. It is really noteworthy
that this value compares well, within a factor of two, with the deconvolved
angular size obtained in subsection 3.1 from the VLSS map in Figure 2
($\nu=3.0$ GHz). Despite the model simplicity, this close coincidence is
reassuring with respect to the correctness of the stellar wind interpretation.

###  4.4 SED optical-infrared modelling and envelope parameters

The IRC$-$10412 SED shows a clear infrared excess and optical absorption as
previously stated, which lead us to suspect the existence of a dense
circumstellar envelope. We have then modeled the optical-infrared emission
with the code DUSTY (Ivezic et al., 1999), which solves the radiative transfer
for a spherically symmetric dust distribution around a central source. For the
theoretical fit shown in Figure 6 (blue dashed line), we need to set an opaque
optical depth $\tau_{V}=10.8$ at $0.55$ $\mu$m. The central star is modeled
with a blackbody with $T_{\mathrm{eff}}=3300$ K. For the chemical composition
of the dust we take into account the existence of an observed peak around
$10\,\mu$m which is characteristic of silicate grains, although our best
result is obtained with a mixture of 40% of astronomical silicate and a 60% of
graphite with properties adopted from Draine & Lee (1984). We also used a
standard MRN grain size distribution (a power-law with exponent $-3.5$; Mathis
et al., 1977) typical of cool, evolved stars (e.g. van Loon et al., 2005). To
derive the mass-loss rate one has to know the dust grain density and the gas-
to-dust mass ratio $r_{gd}$. For the former we consider a default $\rho_{d}=3$
g cm-3, but the ratio $r_{gd}$ is itself not well constrained. Different
studies for classical RSGs allow a comparison between gas mass-loss rates
(i.e. De Beck, E. et al., 2010) and dust mass-loss rates (i.e. Verhoelst et
al., 2009) returning ratios between tenths to several hundreds. Similar values
have been measured for AGBs (Knapp, 1985; Dharmawardena et al., 2018). Here,
we have adopted an intermediate $r_{gd}=350$, which is the expected value for
the galactic longitude of IRC$-$10412 (Groenewegen et al., 2002). The density
distribution is based upon a hydrodynamic computation of a dust-driven wind at
constant mass-loss rate, with an asymptotic dependence with the distance from
the star $\rho\sim r^{-2}$. The innermost part of the dust shell in our fit is
at a temperature $T_{in}=1500$ K, which is a commonly adopted value for dust
sublimation. The shell is assumed to extend up to $10^{4}$ times its inner
radius (so we define $\xi\equiv R_{out}/R_{in}=10^{4}$), such that the dust
density is low enough at the outskirts so that it has no effect on the
spectrum. The DUSTY parameters corresponding to the blue dotted line fit
displayed in Figure 6 are collected in Table 2.

Table 2: Output of DUSTY model used. Parameter | Value
---|---
Inner radius of the dust shell $R_{in}/10^{3}~{}R_{\odot}$ | $1.7$
$R_{in}$ to stellar $R_{\star}$ ratio | $6.4$
Dust temperature at shell outskirt $T_{d}$ (K) | 23
mass-loss rate (dust+gas) $\dot{M}/10^{-5}~{}M_{\odot}~{}{\rm yr}^{-1}$ | $1.3\pm 0.4$
Dust mass-loss rate $\dot{M}_{dust}/10^{-8}~{}M_{\odot}~{}{\rm yr}^{-1}$ | $3.9\pm 0.3$
Terminal wind velocity $v_{\infty}$ (km s-1) | $18\pm 5$
Bolometric luminosity $\log(L_{bol}/L_{\odot})$ | $3.9\pm 0.1$
Bolometric magnitude $M_{bol}$ (mag) | $-4.9\pm 0.3$

At this point, an extra infrared excess in the Figure 6 SED, peaking at $\sim
10^{12}$ Hz (or about $60\,\mu$m), remains to be accounted for. We attempted
different multilayer models with DUSTY, but with physically unacceptable
results. Alternatively, this far infrared feature could be explained (see
dotted orange line) with an additional shell of cold dust (with temperature
$T_{cd}=35$ K, comparable to the value at the outer shell in Table 2)
amounting to a mass of $M_{cd}=10^{-2}M_{\odot}$ according to the simple
modified blackbody model of Dwek & Werner (1981) with emissivity index
$\beta=1$, similar to that observed in dense circumstellar envelopes
(Weintraub et al., 1989; Beckwith & Sargent, 1991; Knapp et al., 1993). This
dust is probably of smaller size (Draine, 2003), and could come from previous
episodes of mass-loss, located above the material responsible for radio
emission, just on top of the shell modeled using DUSTY and giving rise to the
near-infrared emission.

As the SED is dominated by the optical-infrared emission, the DUSTY output
parameters for IRC$-$10412 in Table 2 are expected to be reliable. For
instance, the derived terminal wind velocity is in close accordance with the
value assumed to model the radio part of the SED. In addition, the model
output puts the inner radius of the circumstellar shell very close to the
stellar surface, $R_{in}\simeq 7R_{\star}$, which is the expected behaviour
for cool, evolved stars, where the dust condensates out of stellar wind where
the temperature falls enough, near $R_{\star}$ (van Loon et al., 2005).

###  4.5 Further insight photometric considerations

The bolometric luminosity $\log(L_{\mathrm{bol}}/L_{\odot})=3.9$ in Table 2
has been estimated from the SED of a dust-enshrouded star, but assuming that
the absorbed optical radiation is re-emitted at longer wavelengths. Therefore,
this value must be consistent with the intrinsic IRC$-$10412 luminosity. In
fact, the integration of the SED in Figure 6 yields the same result. This
luminosity, and its corresponding $M_{bol}=-4.9$, are too low for an RSG, so
IRC$-$10412 is plausibly an AGB. Our previous photometric analysis in
Subsection 4.1 pointed in the same direction.

Although our source is clearly variable, we can also cautiously explore
colour-colour and colour-magnitude diagrams of the interstellar corrected
magnitudes to clarify its nature. For IRC$-$10412 the near-infrared colours
are $(J-K_{s})=3.78$, $(J-H)=2.16$, and $(H-K_{s})=1.62$ (and their
corresponding values in Bessell & Brett system, $(J-K)=3.90$, $(J-H)=2.21$,
$(H-K)=1.59$ mag (Carpenter, 2001)), while the absolute M${}_{K}=-8.29$. These
extremely reddened values suggest our source is heavily obscured by
circumstellar matter, and can be classified333Some of the studies published in
the literature are referred to Magallanic Clouds, so we correct for the
distance modulus in each case for an adequate comparison. as dust-enshrouded
extreme AGB (i.e. Olivier et al., 2001; van Loon et al., 2005; Boyer et al.,
2011; Groenewegen et al., 2020). More sophisticated photometric diagram has
been recently suggested using an extinction-free colour ($W_{RP,BP-
RP}-W_{K_{s},J-K_{s}}$) defined in Abia et al. (2022), which for IRC$-$10412
amounts to $3.76$, reinforcing the hyphotesis of dust-enshrouded AGB
(Lebzelter et al., 2018; Groenewegen et al., 2020; Messineo, 2023).

It is possible to determine the radius of IRC$-$10412 from the luminosity and
the Stephan-Boltzmann law, yielding $R_{\star}=233$ $R_{\odot}$, which is not
far from the value derived from the DUSTY model (see Table 2), and typical for
an AGB star.

###  4.6 Mass-loss and other estimates from DUSTY modeling and photometric
data

The mass-loss rate, which is a key parameter in AGBs and RSGs as it helps us
in understanding the late stages of star evolution. Our combined DUSTY model
fit (see Table 2) renders $\dot{M}=(1.3\pm 0.4)\times 10^{-5}M_{\odot}$ yr-1,
in excellent agreement with the value obtained above from the radio emission.
Moreover, we can estimate the mass-loss rate from photometric data using the
prescription for dust-enshrouded AGBs of Jura & Kleinmann (1989). For the
$60\,\mu$m flux of $65.54$ Jy, together with the assumed distance and wind
velocity, we get again a very consistent $\dot{M}=1.02\times 10^{-5}M_{\odot}$
yr-1. Here, we have used the bolometric luminosity in Table 2 and a mean
wavelength in the SED in units of $10\,\mu$m, $\lambda_{10}\simeq 0.7$ as
colour ($K-[12]$)$=4.1$, being $[12]$ the twelve micron magnitude (Olivier et
al., 2001). Again, all these rates are plausible for our scenario of
IRC$-$10412 being a dust-enshrouded AGB. These compatible values from
different methods give us confidence on the results.

It is also interesting to derive the bolometric magnitude from the
period–luminosity relation for dust-enshrouded AGBs in our Galaxy (Olivier et
al., 2001; Karambelkar et al., 2019), assuming that IRC$-$10412 is a
fundamental mode pulsator. The resulting M${}_{bol}\simeq-5$ is not far from
the obtained from the SED analysis, and compatible with other AGB period-
luminosity relations in Magellanic Cloud (Groenewegen et al., 2020).

Period or bolometric luminosity in LPVs could additionally be related to the
actual stellar mass from different prescriptions (i.e. Gough et al., 1965;
Wood et al., 1983; Takeuti et al., 2013), rendering always $M_{\star}\sim
1M_{\odot}$, compatible with the suspected AGB origin.

###  4.7 The nebula around IRC$-$10412

Figure 7: Trichromatic IRC$-$10412 field showing cold dust enshrouding the
source. Blue is Herschel PACS $70\,\mu$m emission, green is Herschel PACS
$160\,\mu$m and red is Herschel SPIRE $250\,\mu$m. Black circle marks the
position of the nebula around IRC$-$10412\.

Successive episodic outflows from old, evolved stars usually create spherical
envelopes around the source. Thus, thermal emission from dust in the
circumstellar environments may be evidence of mass-loss episodes. For
IRC$-$10412 we can observe the cold dust in the Herschel PACS $70~{}\mu$m
image (Figure 7). Inside the black circle we can find the compact dust shell
enshrouding the source, with a mean angular radius of $\sim 9^{\prime\prime}$.
This value should be similar to the outer radius of the shell, where the cold
dust has a temperature of about $T_{d}=23$ K (see Table 2). Given that we
assumed $\xi=10^{4}$, and that the distance to the source is $1.6$ kpc, the
angular size agreement is remarkable.

##  5 Conclusions.

In this paper we have presented the discovery of IRC$-$10412 as an out of
common LPV. The reported photometry shows a variability amplitude not as high
as to be considered a Mira, but clearly fitting the criteria to be considered
a semiregular variable of SRb type.

The most prominent feature of IRC$-$10412 rendering it a singular case among
LPVs, is its strong radio emission with $\nu^{+0.6}$ dependence. Giants and
supergiant stars radio fluxes are typically much weaker than the values
observed for IRC$-$10412\. This peculiarity makes this target stand out
strongly among its peers and worth of additional follow-up work. We speculate
that the strong radio luminosity of IRC$-$10412 could be due to its powerful
wind, when completely ionized by the nearby OB associations (Serpens 2 and
Scutum 3). This allows us to estimate its mass-loss rate in a completely
independent manner directly from radio emission. Comparison with other
traditional methodologies used for AGBs and RSGs, which involve empirical
prescriptions or optical-infrared SED fitting has been satisfactory, thus
adding reliability to out knowledge of this important parameter.

The high optical depth, effective temperature, reddish colours, and other
properties derived from our SED and photometric analysis of IRC$-$10412 make
it to be plausibly a heavily absorbed, low-mass, dust-enshrouded AGB of
spectral type M, as originally proposed by Lockwood (1985). The period-
luminosity relations also support the membership of this source to this scarce
kind of cool, evolved stars. Its bolometric luminosity is
$\log(L_{\mathrm{bol}}/L_{\odot})=3.9$, while its estimated mass-loss rate
using different methods consistently points to a result very close to
$10^{-5}M_{\odot}$ yr-1 .

Authors acknowledge support from project PID2022-136828NB-C42 funded by the
Spanish MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe”.
Partly based on observations obtained with the Samuel Oschin Telescope 48-inch
and the 60-inch Telescope at the Palomar Observatory as part of the Zwicky
Transient Facility project. ZTF is supported by the National Science
Foundation under Grants No. AST-1440341 and AST-2034437 and a collaboration
including current partners Caltech, IPAC, the Oskar Klein Center at Stockholm
University, the University of Maryland, University of California, Berkeley ,
the University of Wisconsin at Milwaukee, University of Warwick, Ruhr
University, Cornell University, Northwestern University and Drexel University.
Operations are conducted by COO, IPAC, and UW. This research has made use of
the SIMBAD database, operated at CDS, Strasbourg, France This work has made
use of data from the European Space Agency (ESA) mission Gaia processed by the
Gaia Data Processing and Analysis Consortium, the Wide-field Infrared Survey
Explorer (WISE; funded by UCLS and JPL/CIT (NASA)), the 2MASS (funded by
University of Massachusetts and IPAC/CIT (NASA)), the SDSS (funded by the
Alfred P. Sloan Foundation, the NSF, NASA, the Japanese Monbukagakusho, the
Max Planck Society, and the Higher Education Funding Council for England), the
Midcourse Space Experiment (MSX; funded by the Ballistic Missile Defense
Organization with additional support from NASA), AKARI (a JAXA project with
the participation of ESA), and the Pan-STARRS1 Surveys (PS1, funded from the
members of its consortium (https://ippc20.ifa.hawaii.edu/pswww/?page_id=226)).
This research has also made use of the NASA/ IPAC Infrared Science Archive,
which is operated by the Jet Propulsion Laboratory, California Institute of
Technology, under contract with the National Aeronautics and Space
Administration. This research has also made use of the VizieR catalogue access
tool, CDS, Strasbourg, France.

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