11institutetext: Departament de Física Quàntica i Astrofísica (FQA),
Universitat de Barcelona (UB), Martí i Franquès 1, E-08028 Barcelona,
Catalonia, Spain 22institutetext: Institut de Ciències del Cosmos (ICCUB),
Universitat de Barcelona, Martí i Franquès 1, E-08028 Barcelona, Catalonia,
Spain 33institutetext: Institut de Ciències de l’Espai (ICE, CSIC), Can
Magrans, s/n, E-08193 Cerdanyola del Vallès, Catalonia, Spain 44institutetext:
Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science
and Technology (BIST), 08193 Bellaterra, Catalonia, Spain 55institutetext:
Institut d’Estudis Espacials de Catalunya (IEEC), Gran Capità, 2-4, E-08034,
Barcelona, Catalonia, Spain 66institutetext: Instituto de Radioastronomía y
Astrofísica, Universidad Nacional Autónoma de México, Antigua Carretera a
Pátzcuaro 8701, Ex-Hda. San José de la Huerta, 58089 Morelia, Michoacán,
México 77institutetext: Department of Physics and Astronomy, California State
Polytechnic University, 3801 West Temple Avenue, Pomona, CA 91768, USA
88institutetext: Université Paris-Saclay, Université Paris Cité, CEA, CNRS,
AIM, 91191, Gif-sur-Yvette, France 99institutetext: Department of Physics,
National Sun Yat-Sen University, No. 70, Lien-Hai Road, Kaohsiung City 80424,
Taiwan, R.O.C. 1010institutetext: Harvard-Smithsonian Center for Astrophysics,
Cambridge, MA 02138, USA

# Radio survey of the stellar population in the infrared dark cloud
G14.225-0.506

Elena Díaz-Márquez 112233 Roger Grau 44 Gemma Busquet 112255 Josep Miquel
Girart 3355 Álvaro Sánchez-Monge 3355 Aina Palau 66 Matthew S. Povich 77 Nacho
Añez-López 88 Hauyu Baobab Liu 99 Qizhou Zhang 1010 Robert Estalella 112255

(Received 2023 September 27 / Accepted 2023 November 18)

###### Abstract

Context.  The infrared dark cloud (IRDC) G14.225-0.506, is part of the
extended and massive molecular cloud located at the south west of the H ii
region M17. The cloud is associated with a network of filaments, which result
in two different dense hubs, as well as with several signposts of star
formation activity and a rich population of protostars and YSOs.

Aims. The aim of this work is to study the centimeter continuum emission in
order to characterize the stellar population in both regions, as well as to
study the evolutionary sequence across the IRDC G14.225-0.506.

Methods. We performed deep ($\sim 1.5$–3 $\mu$Jy beam-1) radio continuum
observations at 6 and 3.6 cm toward the IRDC G14.225-0.506 using the Karl G.
Jansky Very Large Array (VLA) in its most extended A configuration ($\sim$
0.3′′). Data at both C and X bands were imaged using the same (u,v) range in
order to derive spectral indices. We have also made use of observations taken
during different days to study the presence of variability at short timescales
towards the detected sources.

Results. We detected a total of 66 sources, 32 in the northern region G14.2-N
and 34 in the southern region G14.2-S. Ten of the sources are found to be
variable, 3 located in G14.2-N and 7 in G14.2-S. Based on their spectral
index, the emission in G14.2-N is mainly dominated by non-thermal sources
while G14.2-S contains more thermal emitters. Approximately 75% of the sources
present a counterpart at other wavelengths. When considering the inner 0.4 pc
region around the center of each hub, the number of IR sources in G14.2-N is
larger than in G14.2-S by a factor of 4. We also studied the relation between
the radio luminosity and the bolometric luminosity, finding that the thermal
emission of the studied sources is compatible with thermal radio jets. For our
sources with X-ray counterparts, the non-thermal emitters follow a Güdel-Benz
relation with $\kappa=0.03$, as previously suggested for other similar
regions.

Conclusions. We found similar levels of fragmentation between G14.2-N and
G14.2-S, suggesting that both regions are most likely twin hubs. The non-
thermal emission found in the less evolved objects, mainly coming from
G14.2-N, suggests that G14.2-N may be composed of more massive YSOs as well as
being in a more advanced evolutionary stage, consistent with the filament-halo
gradient in age and mass from previous works. Overall, our results confirm a
wider evolutionary sequence from southwest to northeast starting in G14.2-S as
the youngest part, followed by G14.2-N, and ending with the most evolved
region M17.

###### Key Words.:

Stars: formation – ISM: jets and outflows – radio continuum: ISM – ISM:
individual objects (G14.225-0.506)

##  1 Introduction

The formation of intermediate and high-mass stars is a complex process that
involves several evolutionary stages, and it is usually found associated with
clusters of lower-mass stars (e. g., Pudritz 2002; Lada & Lada 2003). However,
when and in what stage massive stars form relative to their low-mass cluster
members remains an open question (e. g., Vázquez-Semadeni et al. 2017; Motte
et al. 2018). Moreover, it is interesting to probe the earliest stages at
which ionization might be present to understand the implications of stellar
feedback that could soon disrupt the star-forming cores and limit their
further growth. The lack of observational data characterizing these phenomena
is due to the distances involved, typically larger than 2 kpc, and the
clustered nature of high-mass star-forming regions, which call for high
angular resolution and high sensitivity observations.

The radio continuum emission at centimeter wavelengths is found in association
with young stellar objects (YSOs) in all stages of the star formation
processes (from Class 0 to Class III). The origin of radio continuum emission
can be distinguished through the spectral index $\alpha$, defined as
$S_{\nu}\propto\nu^{\alpha}$. A non-thermal origin for the radio continuum
emission results in a spectral index $\alpha<-0.1$ (in the frequency range
4–12 GHz, of interest for the current work), and it is generally the result of
electrons in presence of magnetic fields. In star-forming regions, this type
of emission is commonly detected towards YSOs with an active magnetosphere
(gyrosynchrotron radiation) corresponding to Class II/III YSOs (e. g.,
Feigelson & Montmerle 1985; Güdel 2002; Deller et al. 2013). Low-mass Class
0/I objects also have an active magnetosphere and sometimes present
synchrotron flares due to magnetic reconnections in the protostellar surface
(Liu et al. 2014). Synchrotron emission can also be generated in very strong
magnetized shock spots within jet lobes interacting with the ambient medium
(e. g., Carrasco-González et al. 2010; Ainsworth et al. 2014; Rodríguez-
Kamenetzky et al. 2016, 2017, 2019; Osorio et al. 2017), towards high-mass
binary stars producing synchrotron radiation in the region where their winds
collide (e. g., Rodríguez et al. 2012), towards some H ii regions (e. g.,
Padovani et al. 2019; Meng et al. 2019), and finally, as contaminating
background extragalactic sources.

On the other hand, the radio continuum emission can have a thermal origin
(thermal bremsstrahlung) which is characterized by spectral indices between
$-0.1$ and $+2$, and it is interpreted as emission from free-free electron
encounters. This emission can arise from shocks in jets powered by low,
intermediate and high-mass YSOs (see Anglada et al. 2018, for a review) with
typical values for the spectral index $\alpha\sim+0.6$. Thermal emission is
also commonly detected in the surroundings of massive stars, whose UV photons
can ionize the gas and generate an H ii region. Depending on the evolutionary
phase and the surrounding environment these H ii regions can be small ($<0.1$
pc) and dense ($>10^{5}$ cm-3), referred to as hypercompact and ultracompact H
ii regions, and be associated with both optically thin ($\alpha=-0.1$) and
partially thick ($\alpha\sim+0.6$–+2) emission, or they can be large ($>1$ pc)
and more diffuse ($<10^{3}$ cm-3), referred to as classical or giant H ii
regions, and preferentially associated with optically thin emission (e. g.,
Kurtz et al. 1994; Sánchez-Monge et al. 2013a, b). Other regions, such as the
Orion Nebula Cluster (ONC), present protoplanetary disks under the influence
of external photoevaporation by the cluster’s intense UV field. These
formations, known as proplyds, consist of a disk surrounded by an ionization
front and present strong thermal radio emission (Ballering et al. 2023).
Finally, Class 0/I objects may exhibit strong winds that result in optically
thick thermal emission, particularly in the dense region surrounding the
protostar (e. g., Rodríguez 1999). Consequently, even if the protostar were to
emit non-thermal radiation, it would likely be hidden by the optically thick
free-free emission from the surrounding material and remain undetectable to an
observer (e. g., Dzib et al. 2013, 2015).

Previous radio continuum studies conducted toward massive star-forming regions
and infrared dark clouds have been constrained by sensitivity limitations,
since the noise level is typically in the order of mJy/beam. This restricts
the detection to only the most massive objects (e. g., Kurtz et al. 1994;
Sánchez-Monge et al. 2013a; Purcell et al. 2013; De Pree et al. 2014;
Moscadelli et al. 2016; Rosero et al. 2016, 2019; Hofner et al. 2017; Medina
et al. 2018; Kavak et al. 2021; Purser et al. 2021; Irabor et al. 2023; Dzib
et al. 2023), thereby missing a significant fraction of the stellar
population. The new capabilities of the Karl G. Jansky Very Large Array (VLA),
reaching $\approx\mu$Jy/beam sensitivities, offer a unique opportunity to
extend radio continuum studies in nearby molecular clouds to more distant
regions, providing insights into the formation of massive stars, their
associated clusters and their implications on the surrounding medium.

Deep radio continuum surveys toward star-forming complexes in the solar
neighbourhood, such as Ophiuchus, Taurus-Auriga, Serpens, Perseus, R Coronae
Australis and Orion have shown the potential to characterize the population of
YSOs within the radio frequency range along with their characteristics at
other wavelengths (e. g., Dzib et al. 2013, 2015; Liu et al. 2014; Kounkel et
al. 2014; Ortiz-León et al. 2015; Pech et al. 2016; Forbrich et al. 2016;
Coutens et al. 2019; Vargas-González et al. 2021). Excluding Orion, the mean
flux density at 7.5 GHz of the low-mass YSOs in the Gould’s Belt VLA survey
ranges from $\sim 0.15$–0.8 mJy in Class 0/I protostars to $\sim 0.2$–4 mJy in
T Tauri stars (Dzib et al. 2015; Pech et al. 2016). Detecting such a low-mass
stellar population in regions lying more than 10 times further away is
challenging, since a 1 mJy source translates into a flux density of 10
$\mu$Jy, requiring, hence, a sensitivity of $\sim 2\leavevmode\nobreak\ \mu$Jy
beam-1 to be detectable at a 5$\sigma$ level. The only high-mass star-forming
complex that has been studied with such a sensitivity is the Orion Nebula
Cluster (Forbrich et al. 2016; Vargas-González et al. 2021), showing an
increase in the number of known compact radio sources compared to previous,
more shallow surveys (Zapata et al. 2004; Rivilla et al. 2015). We aim at
extending this kind of studies to other massive star-forming complexes.

The infrared dark cloud (IRDC) G14.22$-$0.506 (hereafter G14.2), also called
M17 SWex, is part of the extended ($77\times 15$ pc) and massive ($>10^{5}$
M☉) molecular cloud first reported by Elmegreen & Lada (1976), and located at
the southwest of the H ii region M17, which contains the rich cluster NGC 6618
with at least 16 O-type stars and over 100 B-type stars (Chini et al. 1980;
Hoffmeister et al. 2008). Based on parallax and proper motions of 12 GHz CH3OH
masers, the distance to the cloud is estimated to be 1.98 ${}^{+0.14}_{-0.12}$
kpc (Xu et al. 2011; Wu et al. 2014). More recently, Zucker et al. (2020)
obtained a distance range of 1488–1574 pc by combining stellar photometric
data with Gaia DR2 parallax measurements. For the present work, we use
$1.6^{+0.3}_{-0.1}$ kpc as the distance to the cloud.

High angular resolution observations of the dense gas (NH3 and N2H+) and
submillimeter dust continuum emission (Lin et al. 2017) unveil a network of
filaments comprising two hub-filament systems (see Fig. 1; Busquet et al.
2013; Chen et al. 2019). The cloud is associated with several signposts of
star formation activity, such as H2O and CH3OH masers (Jaffe et al. 1981;
Palagi et al. 1993; Wang et al. 2006; Green et al. 2010; Sugiyama et al.
2017), a rich population of protostars and YSOs detected with Spitzer, and a
population of intermediate-mass pre-main sequence stars emitting X-rays
detected with the Chandra X-ray Observatory, some of them lacking infrared
excess emission from circumstellar disks (Povich & Whitney 2010; Povich et al.
2016). The cloud has also been observed with the Atacama Large
Millimeter/submillimeter Array (ALMA) at 3 mm (Ohashi et al. 2016) and with
the Submillimeter Array (SMA) at 1.2 mm (Busquet et al. 2016). The embedded
population consists of 48 dust cores, with masses ranging from 0.7 M☉ up to 78
M☉.

One of the most prominent results found by Povich et al. (2016) is that,
despite the mass of the cloud ($>10^{5}$ M☉) and its high star formation rate
($\geqslant 0.007$ M☉ yr-1), there is a lack of O-type protostars. The
brightest IRAS source in the field, IRAS 18153$-$1651, is associated with an H
ii region hosting two stars with spectral types B1 and B3 (Gvaramadze et al.
2017). This absence suggests that either the IRDC G14.2 is only producing up
to intermediate-mass stars but does not form massive O-type stars, or the
massive clumps are still in the process of accreting enough material to form
later the high-mass stars. Interestingly, Povich et al. (2016) observed a
large-scale ‘filament-halo’ age gradient and mass segregation of the stellar
population. The less-obscured population, which corresponds to diskless stars,
is distributed across an extended halo of lower-density molecular gas
surrounding the IRDC filaments. In contrast, in the more obscured core regions
of the filaments ($A_{\mathrm{V}}>50$ mag), the more-obscured objects cluster
together, containing all the youngest and most massive YSOs. Thus, the spatial
distribution is accompanied by an apparent age spread. Diskless X-ray
population is more evolved, less obscured, and less clustered with respect to
the filaments in comparison to the YSOs, exhibiting an actual evolutionary
effect. These findings suggest that G14.2 is a complex and dynamic environment
with ongoing star formation activity. However, infrared and X-ray data suffer
from extinction limitations. In order to overcome these limitation, sensitive
and high-angular resolution centimeter continuum observations can fill the
missing piece of information by helping to identify which dust cores may
actually be associated with centimeter continuum emission. This will provide a
more representative sample of the protostellar population that might not be
detected at other wavelengths.

Figure 1: Spitzer image at 8 $\mu$m (color scale) overlaid on the NH3 (1,1)
integrated intensity (green contours) from Busquet et al. (2013). The contour
levels range from 3 to 27 in steps of 6, and from 27 to 67 in steps of 20
times the RMS noise of the map, 9 mJy beam-1 km s-1. The NH3 (1,1) synthesized
beam is shown in the bottom left corner. The black star depicts the position
of IRAS 18153$-$1651\. Blue crosses and cyan four-point stars depict radio
sources detected in this study only at 6 cm and 3.6 cm, respectively. Pink
three-point stars indicate radio sources detected at both frequency bands. The
black and yellow dashed circles represent the field of view at 6 cm ($\sim
7^{\prime}$ at 6 GHz) and 3.6 cm ($\sim 4.2^{\prime}$ at 10 GHz),
respectively. The two observed fields in this work, G14.2-N and G14.2-S are
labeled. The grey rectangles indicate the close-up images presented in Figs. 2
and 3.  Figure 2: ALMA image (grey) at 3 mm (Ohashi et al. 2016) of
G14.2-hub-N overlaid on the NH3 (1,1) integrated intensity (black dashed
contours) from Busquet et al. (2013). The left panel corresponds to the grey
rectangle marked in Figure 1 while the right panel shows a close -up of the
central region around G14.2-hub-N. In both panels contour levels of the
grayscale image start at 3$\sigma$ and increase in steps of 15$\sigma$, where
$\sigma$ is the rms of the map (0.2 mJy beam-1). Red dots depict the dust
continuum sources detected with ALMA at 1.3 mm (Zhang et al. private
communication). The synthesized beam is shown in the bottom left corner of
both images. Symbols are the same as in Figure 1.  Figure 3: ALMA image (grey)
at 3 mm (Ohashi et al. 2016) of G14.2-hub-S overlaid on the NH3 (1,1)
integrated intensity (black dashed contours) from Busquet et al. (2013). The
top panel corresponds to the grey rectangle marked in Figure 1 while the
bottom panel shows a close -up of the central region around G14.2-hub-N. In
both panels contour levels of the grayscale image start at 3$\sigma$ and
increase in steps of 6$\sigma$, where $\sigma$ is the rms of the map (0.2 mJy
beam-1). Red dots depict the dust continuum sources detected with ALMA at 1.3
mm (Zhang et al. private communication). The synthesized beam is shown in the
bottom left corner of both images. Symbols are the same as in Figure 1.
Figure 4: MIPSGAL image (Carey et al. 2009) at 24 $\mu$m overlaid on the
centimeter sources detected in this work in G14.2-N (top panel) and G14.2-S
(bottom panel). Red crosses depict radio sources with an IR counterpart
(Povich et al. 2016). Cyan crosses depict radio sources with an X-ray and IR
counterpart (Povich et al. 2016). Green diamonds depict radio sources with no
IR or X-ray counterpart.

In this work, we present deep, large-scale radio continuum observations
obtained with the VLA toward the IRDC G14.2. The paper is structured as
follows. In Sect. 2 we describe the VLA observations, the data reduction and
imaging processes. The results are presented in Sect. 3. We analyze the radio
properties (thermal/non-thermal emission) of the detected sources in Sect. 4
and discuss the characteristics of the stellar population in G14.2 in Sect. 5.
Finally, in Sect. 6, we present the summary and main conclusions of this work.

##  2 Observations

Table 1: Parameters of the observations at 6 cm and 3.6 cm with the VLA.

| $\lambda^{\mathrm{a}}$ | Project |  Phase centerc | Beam | P.A. | robust | rms | $t_{\mathrm{on-source}}$ |  Beam† |  P.A.†
---|---|---|---|---|---|---|---|---|---|---
Field | (cm) | code |  $\alpha$(J2000) |  $\delta$(J2000) | (arcsec) |  (∘) | weighting |  ($\mu$Jy beam-1) | (hours) | (arcsec) |  (∘)
G14.2-N |  0.6 | VLA19A-147 | 18 18 12.50 |  $-$16 50 00.0 |  0.55$\times$0.32 |  07.5 | $+1$ | 2.2 | 1.87 |  0.55$\times$0.32 |  07.5
| 3.6 | VLA19A-147 | 18 18 12.50 |  $-$16 50 00.0 |  0.42$\times$0.21 | 23.9 | $+2$ | 1.5 | 6.15 |  0.41$\times$0.22 | 22.4
G14.2-S |  0.6 | VLA19A-147 | 18 18 13.10 |  $-$16 57 20.0 |  0.55$\times$0.33 |  06.3 | $+1$ | 2.9 | 1.99 |  0.55$\times$0.33 |  06.5
|  3.6b | VLA17B-236 | 18 18 13.10 |  $-$16 57 20.0 |  0.56$\times$0.42 | 87.2 | $+2$ | 1.4 | 7.07 |  0.61$\times$0.45 | 81.6

111 Columns marked with † next to their names correspond to the parameters of
the observations using the common $(u,v)$ range. (a)3.6 cm observations were
performed in six runs while 6 cm observations were performed in two runs, with
the array in the A configuration. (b) During the first three runs the array
was in the BnA configuration while the array was being re-configured to its
high-resolution A configuration for the last three runs. (c) Units of right
ascension ($\alpha$) are hours, minutes, and seconds, and units of declination
($\delta$) are degrees, arcminutes, and arcseconds.

The radio continuum observations of G14.2 (project codes 17B-236 and 19A-147)
were carried out with the NSF’s VLA of the National Radio Astronomy
Observatory222The National Radio Astronomy Observatory is a facility of the
National Science Foundation operated under cooperative agreement by Associated
Universities, Inc. at C-band (4–8 GHz; i. e., $\sim$6 cm) and X-band (8–12
GHz; i. e., $\sim$3.6 cm). We performed two pointings, labeled G14.2-N and
G14.2-S, to encompass most of the cloud complex (see Fig. 1). The phase center
of each pointing was at $\alpha$(J2000)$=$18h18m12.50s and
$\delta$(J2000)$=-16$∘$50^{\prime}00.0^{\prime\prime}$ for G14.2-N and
$\alpha$(J2000)$=$18h18m13.10s and
$\delta$(J2000)$=-16$∘$57^{\prime}20.0^{\prime\prime}$ for G14.2-S.

The observations were conducted in two different epochs. First, X-band
observations toward G14.2-S were performed during February 2018 (project
17B-236). In the second epoch, we observed G14.2-S in the C-band in two runs
(2019 September 24 and 27). For G14.2-N, we followed the same strategy (i. e.,
two runs in C-band during 2019 September 25 and 26, and six runs in X-band
during 2019 August 26, 28, and September 3, 6, 9, and 16). The duration of
these individuals runs were 1.7 hours for C-band and 1.8 hours for X-band,
yielding a total observing time of 3.4 hours and 10.8 hours at C- and X-bands,
respectively. A summary of the VLA observational parameters is given in Table
1.

Data at both C- and X-bands were taken using two 2 GHz wide basebands (3-bit
samplers) and in full polarization mode. The total 4 GHz bandwidth was split
into 48 spectral windows, each with a bandwidth of 128 MHz, which were divided
into 64 channels with a channel width of 2 MHz. 3C286 was used as the primary
flux density and bandpass calibrator, and J1820$-$2528 was observed to
calibrate the complex gains. The FWHM of the primary beam (i. e., the field of
view) of the VLA has a diameter of $7^{\prime}$ at 6 GHz and $4.2^{\prime}$ at
10 GHz.

The data were processed using the VLA Calibration
Pipeline333https://science.nrao.edu/facilities/vla/data-processing/pipeline
within the Common Astronomy Software Applications (CASA) environment,
specifically the CASA 5.4.2 release. Once the data were calibrated, they were
imaged using the CASA task tclean at each frequency band. Each epoch was
analyzed separately to look for potential source variability. During this
analysis, two bright and highly variable sources that interfered in the final
image were found outside the field of view, one at C-band in G14.2-N and
another one at X-band in G14.2-S. The G14.2-N source peak showed approximately
a factor 6 of variability, and the peak intensity of the G14.2-S source has a
variability of more than one order of magnitude. In order to facilitate the
cleaning process, these two variable sources were subtracted (see Appendix A).
Additionally, there was a discrepancy in the positions and fluxes for all the
sources in the X-band, which required the recentering of the data for the
different observed days (see Appendix B).

For the purpose of creating the final images, once these variables sources
were subtracted and the recentering of the X-band was done, the visibilities
of all observations were inspected to establish the $(u,v)$ plane coverage.
For each region, images were created with the common $(u,v)$ range between the
C and the X band (10.8 to 969.7 k$\lambda$ for G14.2-N and 6.8 to 791.1
k$\lambda$ for G14.2-S) in order to ensure that similar spatial-scale
structures are recovered and detected in the images at both frequencies.
Finally, we performed the imaging including all epochs. All images have been
corrected for the primary beam attenuation. In Table 1 we list the robust
parameter used for the imaging, the synthesized beam, the position angle
(P.A.) and the rms noise level of the combined image. As we can see, the beams
in Table 1 are slightly different at each frequency. In order to ensure a
proper comparison between the images, we also created another set of images
for each field, frequency and day of observation with a common beam of
$0\aas@@fstack{\prime\prime}6\times 0\aas@@fstack{\prime\prime}4$ for G14.2-N
and $1\aas@@fstack{\prime\prime}0\times 0\aas@@fstack{\prime\prime}9$ for
G14.2-S. The position angle for the common beam images was set to zero. These
images have been used when a comparison of sources between different
frequencies was needed, e. g., when studying the variability or estimating the
spectral indices.

##  3 Results

###  3.1 Source identification

The 3.6 and 6 cm continuum images towards the IRDC G14.2 reveal a rich
population of compact radio continuum sources, whilst no extended emission is
detected. This is likely due to the interferometric filtering which resolves
out structures with sizes greater than 3′′. In order to identify compact
sources we used the Python Blob Detector and Source Finder package
(PyBDSF444https://pybdsf.readthedocs.io/en/latest/), which is a tool designed
to decompose radio interferometry images into sources. The identification of
the radio sources has been done by using the images without the primary beam
correction. By default, the PyBDSF module recognizes a source as those with a
peak intensity larger than a certain threshold above the rms of the image
($\sigma$). This tool allows us to get the positions, integrated flux, peak
intensity, sizes from an elliptical fit and position angle of each identified
source. Nevertheless, for homogeneity, we calculated the fluxes for each
source by defining a polygon at the 3$\sigma$ level based on the positions
identified as sources by PyBDSF. The same region defined has been used to get
the fluxes on the images for the individual days when studying the variability
(see Sect. 3.3) and when estimating the spectral index (see Sect. 3.4), using
the images with the same (uv) range and synthesized beam.

In our study, we adopted two different criteria to consider a firm detection:
(i) sources with a peak intensity larger than 6$\sigma$, where $\sigma$ is the
rms of the image, or (ii) sources with a reported counterpart at other
wavelenghts and a peak intensity larger than 3$\sigma$. In order to find the
counterparts at other wavelengths, we used the list of millimeter sources
identified by Busquet et al. (2016) and Ohashi et al. (2016), and the catalog
of infrared and X-ray sources from Povich et al. (2016). We established a
radius of 2′′ ($\sim 3200$ au) around every source and considered as
counterpart the closest source inside that radius. This search radius is
reasonable given that many of the VLA sources appear to be jets that ought to
be offset from the driving stars.

Figure 5: Kernel density estimation (KDE) of integrated fluxes (left) and
sizes (right) of the detected sources in G14.2. The middle and bottom panels
show the distribution in G14.2-N and G14.2-S, respectively, at C- (blue) and
X-band (orange). Vertical lines in the left panels show the 6$\sigma$ value
without primary beam correction for the C- (black) and X-band (grey), while
vertical lines in the right panels show the FWHM of the synthesized beams for
the C- (black) and X-band (grey).

By combining these two criteria, a total of 66 sources were detected in the
IRDC complex G14.2. Only $\sim 10$% of the sources present a peak intensity
between 3 and 6$\sigma$, and only 18 out of the 66 sources do not present a
reported counterpart at other wavelengths. A total of 52 sources were detected
at 6 cm and 36 at 3.6 cm. Of all these, 22 sources were detected at both
bands. Regarding their spatial distribution, 32 sources were located at the
G14.2-N field and 34 sources at the G14.2-S. Two sources were detected in both
regions because of the overlap in the field of view of the two pointings. Fig.
1 presents the location of the centimeter continuum sources detected in this
work overlaid on dense gas emission traced by the NH3 (1,1) from Busquet et
al. (2013), while a close-up view of the two hubs is presented in Figs. 2 and
3, showing also the ALMA 3 mm image from Ohashi et al. (2016). Fig. 4 present
the MIPSGAL 24 $\mu$m image (Carey et al. 2009) overlaid on the centimeter
sources detected in this work with their IR and/or X-ray counterparts.

Table 2: Median fluxes and sizes for the radio sources in G14.2. Region | Band | Flux ($\mu$Jy) | Size (mas)
---|---|---|---
G14.2-N | C-band | 40 |  $<$200
| X-band | 70 |  $<$230
G14.2-S | C-band | 72 |  $<$323
| X-band | 34 |  $<$323

The parameters of the radio sources detected can be found in Appendix C, where
the primary beam correction has been applied. Appendix D presents some of the
sources that have been studied in more depth. The individual images of each
source are presented in Appendix E. In Fig. 5 we show the distribution of
sizes and intensities for the identified radio sources. We split the sample
into sources detected at different frequency bands (top panels) as well as
sources detected in the two fields (middle and bottom panels). As can be seen
in the left column of Fig. 5, most of the radio sources detected in the IRDC
G14.2 have flux densities between 30 to 70 $\mu$Jy. This kind of sources would
have remained undetected in typical previous surveys of star-forming regions,
which typically reach sensitivities of 0.1–1 mJy. In G14.2-N, 15 sources (10
detected at C-band and 5 at X-band) are above 50 $\mu$Jy. Only one of them,
detected at X-band, has a flux density larger than 1 mJy. Regarding G14.2-S,
there are three sources above 1 mJy (two at C-band and one at X-band). We have
25 sources with flux densities larger than 50 $\mu$Jy, mostly detected at
C-band. G14.2-S presents a wider range of fluxes, although there are more
differences between the values detected at the different frequencies. At the
X-band, most of the sources are weaker than for the C-band, with 10 of them
having flux densities below 30 $\mu$Jy. The median fluxes per field and band
are reported in Table 2.

The right column of Fig. 5 shows the distribution of source sizes. Most of the
radio continuum sources in G14.2 detected in this work are compact ($<200$
mas, corresponding to $\approx 300$ au at the G14.2 distance), with 35 sources
(19 in G14.2-N and 16 in G14.2-S) remaining unresolved at our current angular
resolution. Interestingly, the sources in G14.2-N seem to be slightly more
compact than in G14.2-S. There are only 4 sources with sizes above 500 mas in
G14.2-N, including a very extended and clumpy source ($\sim 1100$ mas, or
$\approx 1700$ au) in VLA-19 (see Fig. 16), whereas for G14.2-S there are 13
sources over 500 mas. The median sizes of the sources per field and frequency
are listed in Table 2.

###  3.2 Background sources

Table 3: Number of background sources

Region | Band |  $<N_{\rm FWHM}>$aaaConsidering the field of view of the C-band ($\sim 7^{\prime}$) and X-band ($\sim 4.2^{\prime}$). |  $<N_{\rm 0.4\leavevmode\nobreak\ pc}>$bbbConsidering a diameter of 0.4 pc around the center of each hub.
---|---|---|---
G14.2-N | C-band | 8 | 0.11
| X-band | 3 | 0.11
G14.2-S | C-band | 7 | 0.09
| X-band | 3 | 0.11
555

After identifying all the compact radio continuum sources in both fields (i.
e., in G14.2-N and G14.2-S), an estimation of the number of background sources
for the VLA can be calculated using the formula from Anglada et al. (1998):

$\displaystyle\langle
N\rangle=1.4\left\\{1-\exp\left[-0.0066\left(\frac{\theta_{F}}{\mathrm{arcmin}}\right)^{2}\left(\frac{\nu}{5\,\mathrm{\mathrm{GHz}}}\right)^{2}\right]\right\\}\times$
(1)
$\displaystyle\left(\frac{S_{0}}{\mathrm{mJy}}\right)^{-0.75}\left(\frac{\nu}{5\,\mathrm{GHz}}\right)^{-2.52}$

where $\theta_{F}$ is the field of view, $\nu$ is the frequency and $S_{0}$ is
the flux density.

We used this expression and considered two different field of view sizes for
each region and a flux density of 6$\sigma$ to estimate the number of
background sources in our observations (see Table 3). When considering only a
region of 0.4 pc around the center of each hub ($\sim 42^{\prime\prime}$ at a
distance of 1.6 kpc), we obtain values below 1 for the number of background
sources. Therefore, the probability of detecting an object not associated with
the star-forming hub is small and we can assume that all the sources detected
within the 0.4 pc inner region of each hub are indeed associated with G14.2-N
and G14.2-S. Although the level of background contamination is low in the
inner region of the cluster-hubs, this may be an important factor when
considering the whole field of view at both frequency bands, since we have
about 6 to 15 sources being potential background sources (see Table 3).
Identifying counterparts at other wavelengths (see Sect. 3.5) will ensure the
membership of the object to the G14.2 complex.

###  3.3 Variability

Figure 6: Integrated flux of the variable sources detected in G14.2-N at
X-band during the observed days. The sources were observed during 2019 August
26, 28, and September 3, 6, 9 and 16. The black dashed line corresponds to the
established cutoff for each source shown in Table 5. Figure 7: Integrated flux
of the variable sources detected in G14.2-S at X-band during the observed
days. The sources were observed during 2018 February. The black dashed line
corresponds to the established cutoff for each source shown in Table 5.

We searched for variability in the radio continuum emission of the detected
sources by extracting the flux of each source in each of the different
observing days (see Sect. 2). We note that the synthesized beam of these
images vary slightly from day to day. In order to avoid possible biases, we
convolved all the images to a common beam of
$0\aas@@fstack{\prime\prime}6\times 0\aas@@fstack{\prime\prime}4$ for G14.2-N
and $1\aas@@fstack{\prime\prime}0\times 0\aas@@fstack{\prime\prime}9$ for
G14.2-S, and then evaluated the flux for each source and day. After that, we
calculated the difference in flux between the maximum and minimum value,
establishing a cutoff at 3$\sigma$ level for variability detection. This
cutoff was computed as
$3\sqrt{\sigma_{\text{max}}^{2}+\sigma_{\text{min}}^{2}}$ where
$\sigma_{\text{max}}$ and $\sigma_{\text{min}}$ are the uncertainties of the
maximum and minimum flux, respectively. As indicated in Appendix C, this
uncertainty takes into account the uncertainty in the rms and the uncertainty
in the flux calibration. Sources whose uncertainty in the measurement exceeded
this cutoff were considered as variable.

Tables 4 and 5 list the variable sources that have been detected at C-band and
X-band, respectively. Notably, certain sources exhibit variability in one band
but not in the other. It is important to note that this disparity does not
necessarily indicate exclusive variability in a specific band. It may be due
to variations in the observing days and in the duration of each observation,
potentially preventing some sources from achieving the established cutoff.

Figs. 6 and 7 show in more detail the evolution of the variable sources at
X-band over the six days of observation. The sources vary on short timescales,
as the difference between consecutive observations ranges from hours to weeks.
In G14.2-S, all sources present higher fluxes during the last three days of
observation, although their behavior differ from source to source. For the
rest of them, we cannot see any specific trend on the variability of the
sources. Since at C-band we only have two days of observations, we cannot
infer any specific trend on the variability from the fluxes reported in Table
4.

Table 4: Variability of radio sources at C-band.

|  $S_{\text{C,max}}$ ($\mu$Jy) |  $S_{\text{C,min}}$ ($\mu$Jy) |  $S_{\text{C,diff}}$ ($\mu$Jy) |  $S_{\text{C,cutoff}}$ ($\mu$Jy) | % difference
---|---|---|---|---|---
Southern region G14.2-S |  |
VLA-37 | 47.5 $\pm$ 7.4 | 21.3 $\pm$ 4.7 | 26 $\pm$ 12 | 26 | 55 $\pm$ 12
VLA-41 | 38.6 $\pm$ 5.9 | 17.2 $\pm$ 4.0 | 21 $\pm$ 10 | 21 | 56 $\pm$ 12
666 The columns list: $S_{\text{C,max}}$ and $S_{\text{C,min}}$: maximum and
minimum integrated fluxes of the variable sources detected at the C-band;
$S_{\text{C,diff}}$: difference between those two fluxes in $\mu$Jy;
$S_{\text{C,cutoff}}$: cutoff at which the flux difference is considered as
variability; and the relative difference with respect to the maximum value.

Table 5: Variability of radio sources at X-band.

|  $S_{\text{X,max}}$ ($\mu$Jy) |  $S_{\text{X,min}}$ ($\mu$Jy) |  $S_{\text{X,diff}}$ ($\mu$Jy) |  $S_{\text{X,cutoff}}$ ($\mu$Jy) | % difference
---|---|---|---|---|---
Northern region G14.2-N |  |
VLA-03 |  0328.1 $\pm$ 058.7 | 113.1 $\pm$ 19.7 |  0215 $\pm$ 078 | 186 | 66 $\pm$ 9
VLA-08 |  0044.5 $\pm$ 009.8 |  001.8 $\pm$ 01.5 |  0043 $\pm$ 011 | 30 | 96 $\pm$ 4
VLA-32 | 2229.9 $\pm$ 252.1 | 318.4 $\pm$ 47.2 | 1912 $\pm$ 299 | 770 | 86 $\pm$ 3
Southern region G14.2-S |  |
VLA-36 | 486.6 $\pm$ 058.6 | 244.1 $\pm$ 27.5 | 242 $\pm$ 086 | 194 | 50 $\pm$ 8
VLA-46 | 379.9 $\pm$ 107.9 |  001.6 $\pm$ 01.6 | 378 $\pm$ 110 | 324 | 99 $\pm$ 1
VLA-48 |  067.2 $\pm$ 019.1 |  006.5 $\pm$ 03.1 |  061 $\pm$ 022 | 58 | 90 $\pm$ 5
VLA-54 |  051.1 $\pm$ 012.7 |  008.6 $\pm$ 02.0 |  042 $\pm$ 015 | 39 | 83 $\pm$ 6
VLA-60 | 144.7 $\pm$ 044.9 |  003.3 $\pm$ 03.5 | 141 $\pm$ 048 | 135 | 98 $\pm$ 3
777 The columns list: $S_{\text{X,max}}$ and $S_{\text{X,min}}$: maximum and
minimum integrated fluxes of the variable sources detected at the C-band;
$S_{\text{X,diff}}$: difference between those two fluxes in $\mu$Jy;
$S_{\text{X,cutoff}}$: cutoff at which the flux difference is considered as
variability; and the relative difference with respect to the maximum value.

As discussed in Sect. 2, two sources in the outer parts of the observing
fields were found to be very bright and highly variable, and were subtracted
to produce cleaner images. These sources are not shown in Tables 4 and 5, and
their details can be found in Appendix A.

###  3.4 Spectral indices

In order to determine the origin of the radio continuum emission, we have
calculated the spectral indices for the 66 sources detected in G14.2. To do
this, we have used the set of images created with the common (u,v) range and
convolved to the same beam (see Sect. 2). Since the field of view between the
C- and X-band differs, the calculation is limited to those sources within the
common field of view. For example, source VLA-17 is located outside the field
of view at X-band, which prevents us from deriving a reliable spectral index.
For the sources that have been detected in only one of the bands, we assumed a
6$\sigma$ upper limit for the flux density at the non-detected band since the
in-band spectral indices present very large uncertainties. Tables 6 and 7
report the spectral indices for sources in G14.2-N and G14.2-S, respectively.
After that, and taking into account the uncertainties, we classify the sources
as thermal (if $\alpha>-0.1$) or non-thermal (if $\alpha<-0.1$) radio emitters
based on their spectral index (see Sect. 4).

Table 6: Spectral indices of sources detected in G14.2-N.

| $S_{\mathrm{C-band}}$ | $S_{\mathrm{X-band}}$ | Spectral
---|---|---|---
Source |  ($\mu$Jy) |  ($\mu$Jy) |  index ($\alpha$)
VLA-01 |  0162.0 $\pm$ 16.40 | ¡ 79.0 |  ¡ $-$1.4
VLA-02 |  0021.9 $\pm$ 2.800 | ¡ 44.1 |  ¡ $+$1.4
VLA-03∗ |  0305.2 $\pm$ 32.00 |  243.3 $\pm$ 25.0 |  $-$0.44 $\pm$ 0.29
VLA-04 |  0017.3 $\pm$ 1.900 | ¡ 53.7 |  ¡ $+$2.2
VLA-05 |  0019.3 $\pm$ 2.900 | ¡ 10.4 |  ¡ $-$1.2
VLA-06 |  0031.7 $\pm$ 3.600 | ¡ 62.4 |  ¡ $+$1.3
VLA-07 |  0031.1 $\pm$ 3.600 | ¡ 18.9 |  ¡ $-$1
VLA-08∗ |  0042.1 $\pm$ 4.600 |  79.3 $\pm$ 8.1 |  $+$1.24 $\pm$ 0.29
VLA-09 |  0016.2 $\pm$ 1.700 | ¡ 22.6 |  ¡ $+$0.7
VLA-10 |  0045.3 $\pm$ 6.600 | ¡ 41.7 |  ¡ $-$0.2
VLA-11 |  0125.5 $\pm$ 12.70 |  129.6 $\pm$ 13.2 |  $+$0.06 $\pm$ 0.28
VLA-12 |  0057.4 $\pm$ 6.800 | ¡ 19.0 |  ¡ $-$2.2
VLA-13 |  0098.0 $\pm$ 15.70 |  70.0 $\pm$ 9.7 |  $-$0.66 $\pm$ 0.42
VLA-14 |  0040.4 $\pm$ 14.40 |  22.9 $\pm$ 7.8 |  $-$1.11 $\pm$ 0.97
VLA-15 |  0038.7 $\pm$ 2.500 | ¡ 23.9 |  ¡ $-$0.9
VLA-16 |  0014.6 $\pm$ 1.600 | ¡ 17.1 |  ¡ $+$0.3
VLA-18 |  0029.3 $\pm$ 3.000 | ¡ 34.0 |  ¡ $+$0.3
VLA-19 |  0107.5 $\pm$ 27.80 | ¡ 54.4 |  ¡ $-$1.3
VLA-20 |  0021.7 $\pm$ 2.400 |  15.2 $\pm$ 1.6 |  $-$0.7 $\pm$ 0.30
VLA-21 |  0030.4 $\pm$ 3.100 | ¡ 45.0 |  ¡ $+$0.8
VLA-22 |  0040.4 $\pm$ 4.000 |  37.2 $\pm$ 3.7 |  $-$0.16 $\pm$ 0.28
VLA-23 |  0012.9 $\pm$ 1.500 | ¡ 30.7 |  ¡ $+$1.7
VLA-24 |  0038.1 $\pm$ 4.100 |  20.3 $\pm$ 2.2 |  $-$1.23 $\pm$ 0.30
VLA-25 |  0030.6 $\pm$ 3.300 | ¡ 42.6 |  ¡ $+$0.7
VLA-26 |  0086.4 $\pm$ 8.900 | ¡ 75.4 |  ¡ $-$0.3
VLA-27 |  0037.2 $\pm$ 4.000 | ¡ 47.8 |  ¡ $+$0.5
VLA-28 |  0048.8 $\pm$ 7.100 | ¡ 24.1 |  ¡ $-$1.4
VLA-29 |  0024.7 $\pm$ 2.500 | ¡ 32.0 |  ¡ $+$0.5
VLA-30 |  0042.7 $\pm$ 5.000 | ¡ 51.8 |  ¡ $+$0.4
VLA-31 |  0096.0 $\pm$ 10.30 | ¡ 92.3 |  ¡ $-$0.1
VLA-32∗ |  2192.3 $\pm$ 225.7 |  1050.0 $\pm$ 195.0 |  $-$1.44 $\pm$ 0.42
VLA-33 |  0555.4 $\pm$ 15.20 |  600.2 $\pm$ 60.6 |  $+$0.15 $\pm$ 0.20
888 VLA-03, VLA-08 and VLA-32 are variable sources and therefore their
spectral index may be inaccurate.

Table 7: Spectral indices of sources detected in G14.2-S.

| $S_{\mathrm{C-band}}$ | $S_{\mathrm{X-band}}$ | Spectral
---|---|---|---
Source |  ($\mu$Jy) |  ($\mu$Jy) |  index ($\alpha$)
VLA-32∗ |  2192.3 $\pm$ 225.7 |  1050.0 $\pm$ 195.0 |  $-$1.44 $\pm$ 0.42
VLA-33 |  555.4 $\pm$ 15.2 |  600.2 $\pm$ 60.6 |  $+$0.15 $\pm$ 0.2
VLA-34 |  33.1 $\pm$ 4.0 | ¡ 59.4 |  ¡ $+$1.1
VLA-35 |  114.2 $\pm$ 14.1 |  161.0 $\pm$ 16.6 |  $+$0.67 $\pm$ 0.32
VLA-36∗ |  203.4 $\pm$ 24.0 |  172.5 $\pm$ 20.9 |  $-$0.32 $\pm$ 0.33
VLA-37∗ |  134.7 $\pm$ 14.1 | ¡ 11.3 |  ¡ $-$4.9
VLA-38 |  2384.8 $\pm$ 243.7 |  1556.5 $\pm$ 160.8 |  $-$0.83 $\pm$ 0.28
VLA-39 | ¡ 30.0 |  17.3 $\pm$ 2.1 |  ¿ $-$1.1
VLA-40 |  65.7 $\pm$ 8.2 |  68.5 $\pm$ 8.3 |  $+$0.08 $\pm$ 0.34
VLA-41∗ |  59.2 $\pm$ 6.5 | ¡ 61.9 |  ¡ $+$0.1
VLA-42 |  70.1 $\pm$ 7.1 |  35.3 $\pm$ 3.6 |  $-$1.35 $\pm$ 0.28
VLA-43 |  34.7 $\pm$ 3.7 | ¡ 45.2 |  ¡ $+$0.5
VLA-44 |  59.1 $\pm$ 6.4 |  26.4 $\pm$ 2.7 |  $-$1.58 $\pm$ 0.29
VLA-45 | ¡ 16.9 |  17.4 $\pm$ 2.2 |  ¿ $+$0.1
VLA-46∗ |  98.1 $\pm$ 9.9 |  137.7 $\pm$ 15.5 |  $+$0.66 $\pm$ 0.3
VLA-47 | ¡ 15.9 |  21.2 $\pm$ 2.2 |  ¿ $+$0.6
VLA-48∗ | ¡ 14.7 |  45.1 $\pm$ 4.6 |  ¿ $+$2.2
VLA-49 | ¡ 30.7 |  33.9 $\pm$ 3.4 |  ¿ $+$0.2
VLA-50 |  215.7 $\pm$ 21.6 |  135.2 $\pm$ 13.6 |  $-$0.91 $\pm$ 0.28
VLA-51 |  157.4 $\pm$ 16.2 |  105.2 $\pm$ 10.6 |  $-$0.79 $\pm$ 0.28
VLA-52 | ¡ 17.3 |  14.1 $\pm$ 1.4 |  ¿ $-$0.4
VLA-53 |  44.5 $\pm$ 4.5 |  17.7 $\pm$ 1.8 |  $-$1.81 $\pm$ 0.28
VLA-54∗ | ¡ 23.8 |  32.3 $\pm$ 3.7 |  ¿ $+$0.6
VLA-55 | ¡ 39.2 |  43.0 $\pm$ 4.3 |  ¿ $+$0.2
VLA-56 | ¡ 8.2 |  16.7 $\pm$ 1.7 |  ¿ $+$1.4
VLA-57 |  20.5 $\pm$ 2.2 | ¡ 22.9 |  ¡ $+$0.2
VLA-58 | ¡ 8.6 |  25.7 $\pm$ 2.6 |  ¿ $+$1.4
VLA-59 | ¡ 35.7 |  42.3 $\pm$ 4.3 |  ¿ $+$0.3
VLA-60∗ | ¡ 52.2 |  54.4 $\pm$ 5.5 |  ¿ $+$0.1
VLA-61 |  31.1 $\pm$ 3.2 |  22.8 $\pm$ 2.3 |  $-$0.61 $\pm$ 0.28
VLA-62 | ¡ 21.8 |  34.1 $\pm$ 3.4 |  ¿ $+$0.9
VLA-63 |  249.3 $\pm$ 25.0 | ¡ 645.3 |  ¡ $+$1.9
VLA-64 |  72.3 $\pm$ 7.5 | ¡ 33.9 |  ¡ $-$1.5
VLA-65 | ¡ 31.8 |  33.7 $\pm$ 3.4 |  ¿ $+$0.1
VLA-66 |  66.4 $\pm$ 6.7 |  176.4 $\pm$ 18.0 |  $+$1.91 $\pm$ 0.28
999 VLA-32, VLA-36, VLA-37, VLA-41, VLA-46, VLA-48, VLA-54 and VLA-60 are
variable sources and therefore their spectral index may be inaccurate.

It is worth noting that there are some factors that may affect the accuracy of
the spectral index estimation. First, the C- and X-band observations were not
carried out simultaneously, so any variation in the emission could have led to
an inaccurate spectral index. We also have to take into account that the
fluxes have been calculated selecting the same region, and the differences in
the spatial emission of the two bands may have introduced errors in the
calculation. It should be remarked that the absence of detection in one of the
frequency bands does not necessarily imply that the continuum radio source has
a featureless spectrum. This can be due to the source being faint at that
frequency, or its signal may be masked by background noise. This highlights
the importance of having observations at multiple frequencies to infer the
origin of the emission of the sources.

As listed in Table 6, we found 14 centimeter sources (corresponding to
$\approx$44% of the radio sources) in G14.2-N with spectral indices clearly
smaller than $-0.1$. There is one source (VLA-33) which has a positive
spectral index. For some sources, the spectral index is very close to the
$-0.1$ limit but we cannot classify them unambiguously, due to the uncertainty
in the measurements. Having this in mind, we consider that sources with an
spectral index between $-0.3$ and $+0.1$ are expected to show a nearly flat
spectrum, indicating emission that remains relatively constant or that
slightly varies with frequency. This behavior is also commonly associated with
thermal emission. Accordingly, in G14.2-N there are two sources (VLA-11 and
VLA-22), corresponding to $\approx$6% of the radio sources, with a flat
spectrum that can be considered as thermal candidates. On the other hand, and
as listed in Table 7, in G14.2-S, we found 8 sources ($\approx$24%) with an
spectral index smaller than $-0.1$. There are 12 sources ($\approx$35%) that
have a spectral index larger than $-0.1$. There is one source (VLA-40) with a
nearly flat spectrum and therefore considered as a thermal candidate. The rest
of the sources are either variable, and therefore have been excluded because
the spectral index is considered unreliable, or the origin of the emission
could not be determined due to the uncertainty or derived limits.

Fig. 8 shows the spectral indices and limits obtained for the sources in
G14.2. In G14.2-N there are more sources, compared to G14.2-S, whose
uncertainty has not allowed us to classify them as thermal or non-thermal
emitters. Interestingly, for those sources for which we can unambiguously
determine the origin of the radio emission, we find a vast majority of non-
thermal objects in G14.2-N ($\approx$70%) compared to G14.2-S ($\approx$40%).
Fig. 9 displays the probability density of the spectral index of the radio
sources for which it has been possible to determine the origin of the radio
emission, corresponding to the black dots shown in Fig. 8. As we can see,
G14.2-N is dominated by non-thermal sources. In G14.2-S, we see a wider range
of spectral indices, although with a tendency towards positive values. We note
that in this figure, the values of the upper and lower limits have been taken
as true values. Since in G14.2-N we have mainly upper limits, while in G14.2-S
we have more lower limits, the difference between non-thermal and thermal
populations in the two regions would be more pronounced if accurate spectral
indices, instead of limits, could be derived for all objects.

Figure 8: Spectral index of the sources detected in G14.2. Filled and open
symbols denote sources located within the 0.4 pc inner region (i. e., hubs) or
outside the 0.4 pc inner region, respectively. Black symbols represent those
sources for which it has been possible to determine the origin of the radio
continuum emission. Grey symbols represent those sources for which it has not
been possible to infer its nature. Arrows denote upper or lower limits for
those sources only detected in one frequency band. Variable sources have been
excluded for this representation. The black dashed line at $-$0.1 draws the
boundary between thermal emission ($\alpha>-0.1$) and non-thermal emission
($\alpha<-0.1$). The grey dashed lines trace the limits where sources show a
nearly flat spectrum, probably associated with thermal emission. The blue- and
orange-shaded regions represent G14.2-N and G14.2-S, respectively. The right
black panels indicate if the sources present a reported counterpart at mm, IR
and/or X-ray, associated maser emission and/or dense gas emission. Figure 9:
Kernel density estimation (KDE) showing the probability distribution of the
spectral index for the sources detected in G14.2 for which it has been
possible to determine the origin of the radio continuum emission. The black
dashed line at $\alpha=-0.1$ draws the boundary between thermal emission and
non-thermal emission. Solid lines show the median value of the spectral index
for G14.2-N (black) and G14.2-S (grey).

###  3.5 Counterparts at other wavelengths

The study of the counterparts at other wavelengths can give us more
information about the evolutionary stage and properties of the radio continuum
sources detected in G14.2. We have searched for counterparts at millimeter,
infrared and X-ray, as well as presence of dense gas (Busquet et al. 2013) and
maser emission (Palagi et al. 1993; Wang et al. 2006; Green et al. 2010;
Sugiyama et al. 2017). For this, we have used the millimeter source catalogues
from Busquet et al. (2016) and Ohashi et al. (2016), which have been completed
by new high-resolution data at 1.3 mm from ALMA (Q. Zhang, priv.
communication); as well as the catalogue of infrared and X-ray sources from
Povich et al. (2016). We established a radius of 2′′ around every source to
consider sources at different wavelengths to be counterparts. It should be
taken into account that we have different fields of view for the observations
at different wavelengths. We note that while the IR and X-ray observations
cover the whole area of G14.2 ($\sim 17^{\prime}$), the mm observations focus
only on smaller regions around the central hubs. The radio observations
presented in this work cover two large pointings ($\sim 7^{\prime}$ and
$4.2^{\prime}$ for C and X-band, respectively). Therefore, there may be
additional counterparts with mm sources that cannot be identified with the
current catalogues. Table 8 lists all the identified counterparts for the
radio sources detected in this work. The stage-system classification taken
from Povich et al. (2016) and introduced by Robitaille et al. (2006) is based
on the physical parameters of the spectral energy distribution (SED) models,
with Stage 0/I objects modeled as an SED with an infalling envelope and Stage
II objects modeled as an SED with only circumstellar disks.

In Povich et al. (2016), some of the objects were classified as diskless,
referring to IR point sources detected in X-rays but with no infrared excess
emission above a normally-reddened stellar photosphere. Most of these are
intermediate-mass pre-main-sequence stars with strong magneto-coronal X-ray
emission but lacking inner dust disks. Therefore, YSOs established by Povich
et al. (2016) as diskless are most likely sources in the process of clearing
up the circumstellar disk material. As shown in Table 8, most of these sources
present variability, which is usually found in sources in a more advanced
evolutionary stage. Moreover, 4 out of the 5 diskless sources detected in our
observations present non-thermal emission. Thus, our results confirm that the
objects classified as diskless by Povich et al. (2016) could be equivalent to
Stage III YSOs.

Busquet et al. (2016) found that the ratio between the number of infrared
sources without a millimeter counterpart and the total number of sources,
within a region of about 0.4 pc in diameter around the center of each hub, is
4 times larger in G14.2-N than in G14.2-S, suggesting a more evolved
population in the northern hub. We have expanded this analysis to include the
radio continuum emission reported in this work as well as the X-ray sources.
When evaluating the inner 0.4 pc region, we have 5 and 9 radio sources in the
G14.2-N and G14.2-S hubs, respectively. Fig. 10 summarizes the number of
sources detected at each wavelength in each hub. Similar to the study by
Busquet et al. (2016), we list in Table 11 the number of sources at each
wavelengths. Computing the ratio of IR sources without a millimeter and/or
centimeter counterpart in each hub, we obtained
$N_{\text{IR}}/N_{\text{radio}}=0.2$ in G14.2-N and
$N_{\text{IR}}/N_{\text{radio}}\simeq 0.05$ in G14.2-S. Thus, the relative
number of infrared sources with respect to the radio sources is larger in the
northern hub by a factor of approximately 4, similar to the results found by
Busquet et al. (2016) using observations at millimeter wavelengths.

Table 8: Counterparts of the radio continuum sources detected in G14.2.

Source | Dense gas | mm | IR | X-rays | Maser |  Radioaa$a$Radio continuum emission classified as thermal, non-thermal, flat, variable (V) and unclassified (U). |  Object typebb$b$Object type: YSO, young stellar object; YSO†, YSO candidates proposed in this work; J, compatible with radio jet; G, compatible with gyrosynchrotron emission. |  Stagecc$c$Evolutionary stage classification (Povich et al. 2016): Stage 0/I = SED model with infalling envelope; Stage II = SED model with only circumstellar disks; Stage III = X-ray sources with no mid-infrared excess but detected as IR point sources; A = Ambiguous (no dominant SED model type) | Catalogue name | References
---|---|---|---|---|---|---|---|---|---|---
Northern region G14.2-N |  |  |  |  |  |
VLA-03 | ✓ | — | ✓ | ✓ | — | V |  YSO† | U | Stage III | G014.2405-00.4991, CXO J181811.60-164830.9 | (1), (2) (3)
VLA-06 | — | — | ✓ | ✓ | — | U |  YSO† | U | Stage III | CXO J181824.90-164901.1 | (1)
VLA-08 | ✓ | — | ✓ | ✓ | — | V |  YSO† | U | Stage III | G014.2360-00.5146, CXO J181814.48-164911.6 | (1), (2) (3)
VLA-09∗ | ✓ | — | ✓ | ✓ | — | U | YSO | J | Stage II | [PW2016] 572, G014.2341-00.5067, | (1), (2), (3)
|  |  |  |  |  |  |  |  |  | CXO J181812.54-164904.6 |
VLA-10 | — | — | ✓ | ✓ | — | non-thermal |  YSO† | G | Stage III | CXO J181807.28-164916.8 | (1)
VLA-11∗ | ✓ | ✓ | ✓ | — | ✓ | flat | YSO | J | Stage 0/I | [OSC2016]N-4, N14, [PW2016] 579, | (1), (2), (3),
|  |  |  |  |  |  |  |  |  | G014.2300-00.5097 | (4), (8), (9),
|  |  |  |  |  |  |  |  |  |  | (10)
VLA-12 | ✓ | — | ✓ | ✓ | — | non-thermal |  YSO† | U | Stage III | CXO J181806.99-164903.3 | (1), (3)
VLA-13∗ | ✓ | ✓ | ✓ | — | ✓ | non-thermal | YSO | J | Stage 0/I | [PW2016] 578, G014.2290-00.5102, | (1), (2), (3),
|  |  |  |  |  |  |  |  |  | [OSC2016] N-19, [BEP2016] MM1g, N12 | (4), (5), (7),
|  |  |  |  |  |  |  |  |  |  | (8),(9), (10)
VLA-14∗ | ✓ | ✓ | ✓ | — | ✓ | non-thermal | YSO | J | Stage 0/I | [OSC2016] N-16, [BEP2016] Hub-N MM1, N24 | (1), (2), (3),
|  |  |  |  |  |  |  |  |  | [PW2016] 564, G014.2286-00.5088, | (4), (5), (6),
|  |  |  |  |  |  |  |  |  |  | (10)
VLA-15 | — | ✓ | ✓ | ✓ | — | non-thermal |  YSO† | U | Stage III | [OSC2016] N-25, CXO J181814.95-164927.5 | (1), (4)
VLA-16∗ | ✓ | ✓ | ✓ | — | ✓ | U | YSO | J | Stage 0/I | [PW2016] 575, G014.2281-00.5105, N16 | (1), (2), (3)
|  |  |  |  |  |  |  |  |  |  | (7), (10)
VLA-21 | — | — | ✓ | — | — | U | YSO | J | Stage II | [PW2016] 404, G014.1996-00.4766 | (1), (2)
VLA-22 | ✓ | ✓ | ✓ | ✓ | — | flat | YSO | G | Stage 0/I | [OSC2016] N-2, G014.2156-00.5151, | (1), (2), 10)
|  |  |  |  |  |  |  |  |  | [PW2016] 563, CXO J181812.21-165017.2, N28 |
VLA-24 | ✓ | ✓ | — | — | — | non-thermal |  YSO† | — | — | [OSC2016] N-7, [BEP2016] MM2, | (3), (4), (5)
VLA-26 | — | — | ✓ | ✓ | — | non-thermal | YSO | G | Stage II | [PW2016] 709, G014.2379-00.5654 | (1), (2)
|  |  |  |  |  |  |  |  |  | CXO J181825.96-165037.4 |
VLA-28 | ✓ | — | ✓ | — | — | non-thermal | YSO | J | Stage 0/I | [PW2016] 465, G014.1901-00.5044 | (1), (2), (3)
VLA-29 | ✓ | — | ✓ | ✓ | — | U |  YSO† | U | Stage III | CXO J181812.33-165126.4 | (1), (3)
VLA-30 | — | — | ✓ | ✓ | — | U |  YSO† | U | Stage III | G014.1750-00.5220, CXO J181808.88-165237.7 | (1), (2)
VLA-31 | — | — | ✓ | ✓ | — | non-thermal | YSO | G | Stage 0/I | [PW2016] 409, G014.1667-00.4990, | (1), (2)
|  |  |  |  |  |  |  |  |  | CXO J181802.60-165245.9 |
VLA-32 | — | ✓ | ✓ | ✓ | — | V |  YSO† | U | Stage III | [OSC2016] N-17, N7, | (1), (2)
|  |  |  |  |  |  |  |  |  | G014.1642-00.5131, CXO J181805.66-165257.0 | (4), (10)
Southern region G14.2-S |  |  |  |  |  |
VLA-34 | — | — | ✓ | ✓ | — | U |  YSO† | U | Stage III | G014.1554-00.5541, CXO J181813.63-165435.1 | (1), (2)
VLA-35 | — | — | ✓ | — | — | thermal | YSO | J | Stage II | [PW2016] 407, G014.1327-00.5170 | (1), (2)
VLA-36 | — | — | ✓ | ✓ | — | V |  YSO† | U | Stage III | CXO J181810.07-165508.0 | (1)
VLA-37 | ✓ | — | ✓ | ✓ | — | V |  YSO† | U | Stage III | G014.1310-00.5609, CXO J181812.23-165602.8 | (1), (2)
VLA-38 | — | — | ✓ | — | — | non-thermal | YSO | J | Stage II | [PW2016] 377, G014.1008-00.5132 | (1), (2)
VLA-39 | — | — | ✓ | ✓ | — | U |  YSO† | U | Stage III | CXO J181811.53-165627.1 | (1)
VLA-40 | ✓ | — | ✓ | — | — | flat | YSO | J | Stage II | [PW2016] 460 G014.1123-00.5449 | (1), (2), (3)
VLA-42∗ | ✓ | — | ✓ | — | — | non-thermal | YSO | J | A | [PW2016] 561, G014.1114-00.5711 | (1), (2)
VLA-43 | — | — | ✓ | — | — | U | YSO | J | Stage 0/I | [PW2016] 451, G014.0945-00.5518 | (1), (2)
VLA-44∗ | ✓ | ✓ | ✓ | — | — | non-thermal | YSO | J | Stage 0/I | [OSC2016] S-18, [BEP2016] MM4 | (1), (2), (3)
|  |  |  |  |  |  |  |  |  | [PW2016] 584, G014.1132-00.5745 | (4),(5)
VLA-45∗ | ✓ | ✓ | — | — | — | thermal |  YSO${}^{{}^{\dagger}}$ | U | — | [OSC2016] S-3, S6 | (3), (4), (10)
VLA-46 | ✓ | — | ✓ | ✓ | — | V |  YSO† | U | Stage III | G014.1074-00.5575, CXO J181808.70-165712.0 | (1), (2), (3)
VLA-47 | ✓ | — | ✓ | — | — | thermal | YSO | J | Stage 0/I | [PW2016] G014.1101-00.5626 | (1), (2)
VLA-48 | ✓ | ✓ | ✓ | ✓ | — | V |  YSO† | U | — | [OSC2016] S-17, CXO J181810.98-165708.9 | (1), (3), (4)
VLA-49∗ | ✓ | ✓ | ✓ | — | — | thermal | YSO | J | Stage 0/I | [BEP2016] MM7a, S3, [PW2016] 594 | (1), (2), (3),
|  |  |  |  |  |  |  |  |  | G014.1126-00.5780 | (5), (10)
VLA-50 | — | — | ✓ | — | — | non-thermal | YSO | J | Stage II | [PW2016] 400, G014.0948-00.5298 | (1), (2)
VLA-52 | — | — | ✓ | ✓ | — | U |  YSO† | U | Stage III | CXO J181820.84-165720.7 | (1)
VLA-53∗ | ✓ | ✓ | — | — | — | non-thermal |  YSO† | — | — | [OSC2016] S-2, [BEP2016] MM2b, S20 | (3), (4), (5),
|  |  |  |  |  |  |  |  |  |  | (10)
VLA-54∗ | ✓ | ✓ | ✓ | — | — | V | YSO | J | Stage 0/I | [BEP2016] MM5b, [PW2016] 587, S14 | (1), (2), (3),
|  |  |  |  |  |  |  |  |  | G014.1142-00.5743 | (5), (10)
VLA-55∗ | ✓ | ✓ | ✓ | — | ✓ | thermal | YSO | J | Stage 0/I | [OSC2016] S-1, [BEP2016] MM5a, S8 | (1), (2), (3),
|  |  |  |  |  |  |  |  |  | [PW2016] 588, G014.1157-00.5737 | (4), (5), (6),
|  |  |  |  |  |  |  |  |  |  | (10)
VLA-56∗ | ✓ | — | ✓ | — | — | thermal | YSO | J | A | [PW2016] 599, G014.1147-00.5783 | (1), (2), (3)
VLA-57 | ✓ | ✓ | ✓ | ✓ | — | U |  YSO† | U | — | [OSC2016] S-9, CXO J181809.15-165728.0 | (1), (3), (4)
VLA-58∗ | ✓ | ✓ | — | — | — | thermal |  YSO† | J | — | [OSC2016] S-4, [BEP2016] MM2a | (3), (4), (5)
VLA-59 | ✓ | — | ✓ | ✓ | — | thermal |  YSO† | U | Stage III | CXO J181812.03-165701.0 | (1), (3)
VLA-60 | ✓ | — | ✓ | ✓ | — | V |  YSO† | U | Stage III | G014.1000-00.5634, CXO J181809.17-165746.3 | (1), (2), (3)
VLA-62 | ✓ | — | ✓ | — | — | thermal | YSO | J | Stage II | [PW2016] 475, G014.1056-00.5537 | (1), (2), (3)
VLA-64 | ✓ | — | ✓ | ✓ | — | non-thermal |  YSO† | G | Stage III | G014.0893-00.5548, CXO J181805.90-165804.4 | (1), (2) (3)
VLA-65 | ✓ | ✓ | ✓ | ✓ | — | thermal |  YSO† | U | Stage III | [OSC2016] S-13, CXO J181805.64-165812.6 | (1), (3), (4)

(1) Povich et al. (2016); (2) Spitzer Science (2009); (3) Busquet et al.
(2013); (4) Ohashi et al. (2016); (5) Busquet et al. (2016); (6) Wang et al.
(2006); (7) Palagi et al. (1993); (8) Green et al. (2010); (9) Sugiyama et al.
(2017); (10) Q. Zhang (priv. communication). 101010 Sources marked with * next
to their names correspond to radio continuum sources located within the inner
0.4 pc region around the center of each hub.

Figure 10: Schematic representation of the sources detected in the 0.4 pc
region around each hub and their counterparts at different wavelengths.
Millimeter sources correspond to the ones detected in Busquet et al. (2016),
Ohashi et al. (2016) and Zhang et al. (private communication). Infrared
sources correspond to those detected in Povich et al. (2016). Centimeter
sources correspond to those detected in this work. Table 9: Number of sources
detected at different wavelengths

Region | ${N}_{\mathrm{mm}}$ | ${N}_{\mathrm{cm}}$ | ${N}_{\mathrm{IR}}$ | ${N}_{\mathrm{IR+}}$ | ${N}_{\mathrm{IR}}/{N}_{\mathrm{radio}}$ | ${N}_{\mathrm{IR^{+}}}/{N}_{\mathrm{radio}}$
---|---|---|---|---|---|---
G14.2-N | 25 | 5 | 5 | 10 | 0.2 | 0.3
G14.2-S | 30 | 9 | 2 | 6 | 0.05 | 0.2
111111 Number of sources within the inner 0.4 pc around each hub.
$N_{\mathrm{mm}}$ is the number of millimeter sources without a centimeter
and/or IR counterpart. $N_{\mathrm{cm}}$ is the number of centimeter sources
detected in this work. $N_{\mathrm{IR}}$ is the number of IR sources without a
millimeter and/or centimeter counterpart. $N_{\mathrm{IR^{+}}}$ is the total
number of IR sources. ${N}_{\mathrm{radio}}$ is the number of radio sources,
that is, $N_{\mathrm{mm}}$+$N_{\mathrm{cm}}$.

##  4 Analysis

As explained in Sect. 1, the radio continuum emission from YSOs can have a
thermal or non-thermal nature and can be originated in different processes (e.
g., free-free emission from thermal radio jets or young H ii regions, non-
thermal gyrosynchrotron and synchrotron emission in magnetically-active YSOs).
In this section, we analyze in detail the origin of the radio continuum
emission for the 37 sources with well constrained spectral indices (see Sect.
3.4) by studying the well-known correlation between the radio luminosity and
the bolometric luminosity for thermal radio jets (see Anglada et al. 2018, for
a review) and the connection between the radio and X-ray luminosities,
expected for non-thermal radio sources with active coronal activity.

###  4.1 Thermal free-free emission: radio jets or H ii regions?

In this section we investigate whether the thermal radio emitters detected in
G14.2 can be explained in terms of photoionization (i. e., H ii regions) or
ionization through shocks associated with outflows and jets. For this, we
computed the number of Lyman-continuum photons per second, $N_{\rm{Ly}}$ (see
Sánchez-Monge et al. 2013a), using the flux densities at 3.6 cm, which for 19
thermal emitters, the radio luminosities are in the range of $0.04$–$0.45$ mJy
kpc2, with a mean value of $\sim 0.16$ mJy kpc2. Adopting an electron
temperature of $T_{\rm{e}}=10^{4}$ K, we obtained values $N_{\rm{Ly}}\sim
3\times 10^{42}$–$3\times 10^{43}$ s-1, which translates to spectral types
B3–B4 assuming as a ionization source a single zero-age main sequence (ZAMS)
star (Panagia 1973; Thompson 1984; Vacca et al. 1996; Diaz-Miller et al. 1998;
Martins et al. 2005). In G14.2, the YSO population detected in the IR present
luminosities much lower, 10–100 $L_{\odot}$, so we expect $N_{\rm{Ly}}\ll
10^{42}$ s-1. Therefore, the emission is likely due shock-induced ionization
for most of the sources.

Fig. 11 presents the relation between the radio luminosity and the bolometric
luminosity for 9 out of the 19 thermal sources, including flat-spectrum
sources, identified in G14.2. We compare them with the sample of radio jets
compiled by Anglada et al. (2018) as reference. Although our sample comprises
a relatively narrow range of luminosities ($\sim$10–800 L☉), there is an
excess of radio emission compared to what is expected for an H ii region, and
hence the radio emission is compatible with the well-known correlation for
thermal radio jets. Hence, we can discard that these sources are H ii regions.
The morphology of these sources appear, in most of the cases, elongated
indicating that they are potential thermal radio jets. In fact, 6 out of the 9
thermal radio sources in G14.2 with measured bolometric luminosities, have
been classified by Povich et al. (2016) as Stage 0/I YSOs, 3 of them are Stage
II and 1 source is classified as Ambiguous. For the Stage III YSOs we do not
have the measured bolometric luminosities. Moreover, the centimeter sources
found in association with H2O and CH3OH masers (Palagi et al. 1993; Wang et
al. 2006; Green et al. 2010; Sugiyama et al. 2017) are classified as Stage
0/I, suggesting that they are potential radio jets.

We additionally explored whether the non-thermal radio sources, as well as the
unclassified radio sources, with an infrared counterpart, hence with measured
bolometric luminosities, follow the empirical correlation for radio jets (see
Fig. 11). For those sources only detected at 6 cm, we estimated the 3.6 cm
radio luminosity assuming a spectral index of $+0.5$ (following the approach
of Anglada et al. 2018). Since we know, however, that most of these radio
sources present a negative spectral index, for well-classified non-thermal
sources, we adopted $\alpha=-0.7$ to extrapolate the flux density at 3.6 cm.
Our sample contains 12 radio sources, 6 of them have been classified as Stage
0/I, 5 correspond to Stage II objects and only 1 is classified as Ambiguous
according the classification of Povich et al. (2016) .

In order to discard that the sources detected in G14.2 could be H ii regions,
we also calculated the expected flux density and thus, the luminosity, from
the number of Lyman-continuum photons per second that are expected for H ii
regions (Panagia 1973; Thompson 1984). As can be seen in Fig. 11, with the
exception of some sources, the rest of them do not follow the expected
relation. In contrast, our sample follows the expected relation between the
radio luminosity and the bolometric luminosity found by Anglada et al. (2018),
suggesting that these sources are also potential radio jets. In fact, several
works find that radio jets can present both thermal and non-thermal emission.
The central and powering source is usually associated with thermal emission
whereas the jet lobes/knots are associated with non-thermal synchrotron
emission from relativistic electrons accelerated in strong shocks (e. g.,
Carrasco-González et al. 2010; Marti et al. 1993; Rodriguez et al. 1989;
Rodríguez et al. 2005; Sanna et al. 2019). However, there are some cases in
which the radio emission from jets, at the current resolution, seems to be
dominated by a non-thermal origin (e. g., Reid et al. 1995; Moscadelli et al.
2016; Kavak et al. 2021). Therefore, the sample of radio sources in G14.2 with
negative spectral indices or the unclassified sources are compatible with
radio emission arising from radio jets although further observations spanning
a wider range of frequencies and in polarization mode would be necessary to
fully confirm their nature.

###  4.2 The radio–X-ray relation

Previous VLA surveys of nearby star-forming regions have reported a
correlation between the radio emission of YSOs and their associated X-ray
emission (see e. g., Pech et al. 2016). Several findings suggest that YSOs
adhere to the empirically Güdel–Benz relation (Guedel & Benz 1993; Benz &
Guedel 1994) for magnetically active stars:

$\dfrac{L_{X}}{L_{R}}=\kappa\,10^{15.5\pm 0.5},$ (2)

with $\kappa\leq 1$, depending on the type of stars. From our VLA
observations, 25 out of 66 sources (i. e., $\sim 38$% of our sample) present a
reported X-ray counterpart but only 9 of them have measured luminosities
(Povich et al. 2016) and do not present variability. The absorption-corrected
luminosities measure the total X-ray band (0.5–8 keV) and the hard X-ray band
(2–-8 keV). For this work, we use the hard X-ray band since it is less
affected by absorption.

Fig. 12 shows the X-ray luminosities and our derived radio luminosities for
thermal, non-thermal, and unclassified radio sources. For simplicity in the
representation, we considered flat sources as thermal emitters. Particularly
for the unclassified sources, our data is poorly correlated to what we
expected and presents a large dispersion, similar to the results found in M17
(Yanza et al. 2022) and in the Orion Nebula Cluster (Forbrich et al. 2016). As
explained in Yanza et al. (2022), the lack of correlation between X-ray and
radio observations can be due to the presence of potential thermal sources in
the data sample. Moreover, the different timescales and high intrinsic
variability of gyrocoronal flares may affect the results since simultaneous
X-ray and radio observations are needed to properly study this relation. In
fact, for most of the radio sources in G14.2 that present an X-ray counterpart
it has not been possible to determine the origin of the emission from the
spectral index. The Güdel-Benz relation is valid for non-thermal sources, so
it might not apply to most of the sources. Moreover, our sample size is small
and thus we cannot infer robust conclusions from the results obtained.

However, if only non-thermal radio sources are considered (i.e., filled black
dots in Fig. 12), our observations seem to reproduce the Güdel-Benz relation
with $\kappa=0.03$. This suggests that the radio emission in those sources is
probably produced by gyrosynchrotron radiation from the mildly relativistic
electrons that are responsible for the X-ray emission. The only thermal source
presented in Fig. 12 is VLA-22, which was originally classified as flat
source. This source is therefore likely to be more compatible with non-thermal
emission and also produced by gyrosynchrotron radiation.

Similar results were found in nearby region such as Ophiuchus (Dzib et al.
2013), Taurus-Aurgia (Dzib et al. 2015) and Perseus (Pech et al. 2016), while
in Orion and Serpens it was found that the X-ray emission of YSOs was
underluminous compared to the Güdel–Benz relation with $\kappa=1$ (Kounkel et
al. 2014; Ortiz-León et al. 2015; Forbrich et al. 2016). Despite these
promising similarities between G14.2 and other nearby star-forming complex,
with only 5 sources in G14.2, we cannot draw firm conclusions regarding the
expected radio-X-ray correlation.

Finally, in G14.2 we have identified 22 non-thermal radio emitters, 36% of
them remain unresolved with our angular resolution ($\sim
0\aas@@fstack{\prime\prime}3$) and, with the exception of VLA-19 whose
emission is very extended, the remaining sources have sizes
$<0\aas@@fstack{\prime\prime}7$. Therefore, based on the compactness of these
radio sources, we suggest that the radio emission of most of the non-thermal
radio population in G14.2 is most likely associated with gyrosynchrotron
radiation from the very active stellar magnetosphere, typically found in Class
II/III YSOs (Feigelson & Montmerle 1985). However, in order to fully confirm
the gyrosynchrotron origin, follow-up polarization studies are needed to
investigate whether these radio sources present some degree of circular
polarization.

Figure 11: Radio luminosity as a function of bolometric luminosity for the
sources with an IR counterpart and a measured bolometric luminosity (Povich &
Whitney 2010; Povich et al. 2016). Triangles represent thermal sources, filled
dots depict non-thermal sources, and open circles represent radio sources with
an unclassified origin of the radio continuum emission in G14.2. For
unclassified radio sources not detected at 3.6 cm we extrapolated the 6 cm
flux density to 3.6 cm adopting two values of the spectral index,
$\alpha=-0.7$ and $\alpha=+0.5$ (see main text). Grey dots show the thermal
radio jets compiled by Anglada et al. (2018). The solid black line corresponds
to the fit done to all radio jets in Anglada et al. (2018). The red dotted
line depicts the radio luminosity at 3.6 cm associated with the Lyman
continuum flux of H ii regions powered by stars of different luminosities (see
Fig. 4 from Sánchez-Monge et al. 2013a). The black dashed line depicts our
$5\sigma$ sensitivity limit in radio luminosity ($\sim 0.02$ mJy kpc2). Figure
12: X-ray luminosity as a function of radio luminosity for the sources in
G14.2 with a measured X-ray luminosity (Povich et al. 2016). The black line
corresponds to the Güdel-Benz relation with $\kappa=1$. The red dashed line
corresponds to the Güdel-Benz relation but with $\kappa=0.03$. Black dots
depict non-thermal sources, black triangles represent the thermal sources, and
unfilled black dots represent the radio sources with an unclassified origin of
radio continuum emission. Variable sources have been excluded for this
representation.

##  5 Discussion

###  5.1 Levels of fragmentation in the G14.2 hubs

Previous observations of the two hubs in G14.2 with the SMA, at an angular
resolution of $\sim 1\aas@@fstack{\prime\prime}5$ revealed different levels of
fragmentation, with G14.2-S being more fragmented than G14.2-N (see Busquet et
al. 2016). Despite these differences in fragmentation, the physical properties
of both hubs such as the density and temperature profiles, the level of
turbulence (Mach number $\sim 5.6$–6.4), the Alfvén Mach number ($\sim
0.4$–0.3), the rotational-to-gravitational energy ratio
($\beta_{\mathrm{rot}}\sim 0.016$–0.015), the mass (979–717 M☉), and the
luminosity (995–531 L☉) are remarkable similar (see Tables 5 and 6 in Busquet
et al. 2016, for further details). As explained in Busquet et al. (2016), the
different levels of fragmentation may be due to different reasons. The first
one is the difference in the magnetic field strength, with G14.2-N having a
stronger magnetic field compared to G14.2-S (see Añez-López et al. 2020). The
second potential cause is the presence of the luminous IRAS 18153$-$1651
source, with a luminosity of $\sim 1.1\times 10^{4}$ $L_{\sun}$ and strong UV
radiation, in G14.2-N. This suggests that the UV radiation from IRAS
18153$-$1651, as well as from the larger number of IR sources in the northern
hub compared to the southern sibling, might be suppressing fragmentation.

However, with our VLA data we do not see significant differences in the number
of sources (or level of fragmentation) in the two hubs as previously studied
in Busquet et al. (2016). In the current work, 32 centimeter sources were
detected in G14.2-N and 34 in G14.2-S. While the detection or non-detection of
radio continuum sources might be related to evolutionary effects,
interestingly, the latest ALMA data at 1.3 mm, with an angular resolution
comparable to the VLA observations (Q. Zhang, priv. communication, see also
Figs. 2 and 3), do not reveal statistical differences in terms of
fragmentation: with 25 millimeter sources without a centimeter and/or IR
counterpart in G14.2-N and 30 millimeter sources in G14.2-S. Therefore, we
conclude that both hubs show similar levels of fragmentation based on the
observations with the VLA and ALMA. Hence, it seems that the different
fragmentation levels reported in Busquet et al. (2016) may have been due to
poor sensitivity in previous SMA observations, or to different effects
controlling fragmentation at different scales. Therefore, although the
magnetic field and UV radiation (from the bright IRAS source) could determine
the level of fragmentation at intermediate scales (i.e. 0.03 pc scale), the
fragmentation at smaller scales (i.e. 0.005 pc) does not seem to be affected
anymore by these effects. Thus, thanks to the new results at high-angular
resolutions in the cm and mm regimes, it is very feasible that G14.2-N and
G14.2-S are twin hubs in terms of fragmentation, as proposed in Busquet et al.
(2016) regarding their large-scale physical properties.

###  5.2 Radio properties of the stellar population

The high sensitivity VLA observations allowed us to detect 66 radio sources in
the IRDC G14.225. Our analysis of the spectral index in the 6–3.6 cm range
reveals that in G14.2 there are 22 sources ($\approx$33%) that clearly present
non-thermal emission and 13 ($\approx$20%) are thermal emitters. There are
also 3 sources ($\approx$5%) presenting a nearly flat emission spectrum, most
likely associated with thermal emission.

One aspect that should be taken into account when examining the origin of the
radio continuum emission based on the spectral index analysis is the
variability of the sources. As mentioned in previous sections, we found ten
sources that are clearly variable at short-time scale (see Tables 4 and 5 and
Figs. 6 and 7 ), but our observations were not designed to carefully
characterize radio variability, and therefore, other sources may be also
variable even if not detected as such in the current observations. Follow-up
simultaneous multi-frequency observations with the VLA, similarly to Liu et
al. (2014) and Coutens et al. (2019), might provide a more detailed insight
into the variability of the radio sources in G14.2 and thus, a better
estimation of their spectral indices and origin of the radio emission.

Despite the high sensitivity of VLA observations, the fraction of radio
detections is low in comparison with the IR and X-ray stellar population
(Povich et al. 2016). Fig. 13 shows the location of the four different
populations in G14.2-N (top panel) and G14.2-S (bottom panel). In each region,
there are between 300 to 400 sources detected at IR and/or X-rays, and only 44
have a radio counterpart. The IR/X-ray sources with no radio counterpart,
could be rather evolved objects (Class II/III) with quiet corona activity, and
hence with no thermal radio jet and no gyrosynchrotron emission.

Regarding the millimeter population (Ohashi et al. 2016; Busquet et al. 2016,
Zhang et al. private communication), Fig. 13 makes more noticeable the
differences in the fields of view, since millimeter observations are centered
on smaller regions around the central hubs. From our study of the
counterparts, we found that four radio sources were only associated with mm
emission without any other counterpart at another wavelength. We have proposed
these four millimeter sources associated with centimeter emission as new YSOs
candidates and it is very likely that these objects are Class 0 or deeply
embedded Class I objects. Since our study of the mm counterparts is limited
only to the central region, we are likely to have more mm sources outside the
hubs.

---
Figure 13: Spatial distribution of the stellar population in G14.2. Top panel
shows the northern region of G14.2, while bottom panel shows the southern
region of G14.2 (G14.2-N and G14.2-S, respectively). Blue symbols indicate
centimeter sources (this work). Green symbols indicate millimeter sources
(Ohashi et al. 2016; Busquet et al. 2016, Zhang et al. private communication).
Red symbols indicate infrared sources (Povich et al. 2016). Black symbols
indicate X-ray sources (Povich et al. 2016). The symbol sizes do not
correspond to the respective angular resolution. The outer and inner dashed
circles represent the field of view at 6 cm ($\sim 7^{\prime}$ at 6 GHz) and
3.6 cm ($\sim 4.2^{\prime}$ at 10 GHz), respectively.

####  5.2.1 Comparison with other nearby star-forming regions

We compare now the properties of the radio sources in G14.2 to other star-
forming complexes from the Gould’s Belt VLA survey where their radio-source
population has been studied in detail, reaching similar sensitivities and
spatial resolutions as for G14.2. In particular, by comparing the radio
spectral indices, which serve as indicators of the emission characteristics,
we can investigate their properties across the different evolutionary stages
of the YSOs. A comparative study of G14.2 with other complexes may unveil
potential differences and shed light on the main characteristics of G14.2.

Figure 14: Mean spectral index as a function of the YSO evolutionary stages in
different star-forming regions (Blue triangles: Taurus-Auriga (Dzib et al.
2015); Green cross: Perseus (Pech et al. 2016); Orange square: Ophiuchus (Dzib
et al. 2013); Pink dot: Serpens (Ortiz-León et al. 2015); Grey dot: IRDC
G14.2, separated in G14.2-N (black dot) and G14.2-S (black diamond)). Note
that black and grey symbols are SED-based Stage classifications (Povich et al.
2016) and the groups could be different if a different classification scheme
was employed. The black dashed line at $\alpha=-0.1$ draws the boundary
between thermal emission and non-thermal emission.

As previously discussed, we adopted the stage categorization in which YSOs
were classified as Stage 0/I (SED modelled with infalling envelopes), Stage II
(SED modelled with only circumstellar disks) or Stage III (X-ray sources with
no mid-IR excess from circumstellar disks) used by Povich et al. (2016) (see
also Robitaille et al. 2006). However, the standard classification of YSOs is
the class categorization based on the spectral index at infrared wavelengths
(Lada 1987; Andre et al. 1993; Gutermuth et al. 2009). For comparison with
other nearby regions we equate Stage 0/I to Class 0/I, Stage II to Class II
and Stage III to Class III. Figure 14 shows the spectral index for different
YSOs in different star forming complexes, with the YSOs classified according
to their evolutionary stage. We compare the results of G14.2 with Ophiucus
(Dzib et al. 2013), Serpens (Ortiz-León et al. 2015), Taurus-Auriga (Dzib et
al. 2015) and Perseus (Pech et al. 2016).

We find that for the detected YSOs in Taurus-Auriga, Ophiuchus and Perseus,
the more evolved objects have a more negative spectral index. Based on this,
it has been proposed that the radio emission towards Class 0/I objects, with
spectral indices between +0.3 and +0.5, is likely dominated by partially
optically thick free-free emission (from thermal radio jets). On the other
hand, Class II and III objects present radio emission consistent with either
optically thin free-free emission or (gyro- )synchrotron radiation (see e.g.
Dzib et al. 2013). This is in agreement with the idea that, for more evolved
sources, we are no longer able to detect the thermal emission from the
surrounding material, since they have already expelled most of it. (e. g.,
Forbrich et al. 2007; Dzib et al. 2010).

Nevertheless, the Serpens star-forming region (Ortiz-León et al. 2015) and the
IRDC G14.2 (this work) do not follow this trend, since younger objects are
associated with non-thermal spectral indices. This might be due to the fact
that these regions are composed of more massive YSOs in which non-thermal
emission may be more dominant (e. g., Carrasco-González et al. 2010;
Rodríguez-Kamenetzky et al. 2017; Kavak et al. 2021). An alternative
explanation for the detection of non-thermal emission in the less evolved
objects might be due to geometrical effects rather than the mass of the YSOs
(e. g., Ortiz-León et al. 2015). According to this scenario, if the star is
seen nearly pole-on or nearly edge-on, the non-thermal emission originating in
the corona might be less absorbed by the surrounding material and can be more
easily observed (Forbrich et al. 2007). This effect could also be obtained
through tidal clearing of circumstellar material in a tight binary system
(Dzib et al. 2010).

Considering that, statistically, one does not expect a preferential
orientation for YSOs, the trend found for the spectral index towards the YSOs
of G14.2 might be explained by the presence of more massive YSOs compared to
regions such as Ophiuchus, Taurus-Auriga or Perseus. This scenario is
plausible for both Serpens and G14.2, since recent studies have confirmed mass
segregation effects for both regions (see Povich et al. 2016; Plunkett et al.
2018), with more massive YSOs located in the central regions of the star-
forming complex and corresponding to those preferentially studied in the radio
observations. Note also that more massive YSOs evolve more quickly, which
could explain why Stage III objects present more negative spectral indices in
G14.2 in comparison with other regions, since they should have stronger
magnetic flaring activity. As shown in Fig. 14, the dominating population of
non-thermal emitters within the less evolved objects is likely to come mainly
from the northern region G14.2-N. By examining Table 8, we can see that in
G14.2-S only one Stage 0/I object clearly shows non-thermal emission. Thus,
our results point to G14.2-N likely containing more massive objects.

###  5.3 Evolution and development of G14.2

The molecular cloud environment in G14 extends more than $1\degr$ to the
southwest of the H ii region, parallel to the galactic mid-plane (Elmegreen &
Lada 1976; Elmegreen et al. 1979). These authors suggested a sequential
massive star formation from the north-eastern side with OB stars in NGC 6618
to the M17 southwest extension, or M17 SWex (Povich et al. 2009; Povich &
Whitney 2010). We discuss now on the possible evolutionary stage of the IRDC
G14.2 in relation to the more developed M17 star-forming complex. For this, we
highlight different aspects regarding the stellar population and physical
properties across the IRDC G14.2.

First, the already-developed and large H ii region associated with the bright
IRAS 18153$-$1651 source is located to the northeast of G14.2 (see Fig. 1),
while the southern region of the cloud appears more quiescent. This suggests a
certain evolutionary gradient from southwest (less evolved) to northeast (more
evolved), in agreement with the large scale age evolution proposed by
Elmegreen & Lada (1976).

A second aspect refers to the stellar population across the IRDC G14.2. The
counterparts of the radio sources at other wavelengths (see Table 11) provide
precious information on the stellar population in both regions, their
properties and evolutionary stages. The number of infrared sources relative to
radio sources in G14.2-N suggests that the northern hub harbours a stellar
population in a more advanced evolutionary stage but still having a deeply
embedded population of protostellar cores (e. g., the case of VLA-14/MM1, see
Appendix D.1). On the other hand, in G14.2-S, we have identified more
millimeter sources without an infrared counterpart, suggesting that there is a
larger population of objects at an earlier evolutionary stage. The large
fraction of non-thermal emitters in G14.2-N could be due to the presence of
relatively evolved YSOs (Class II and/or Class III), consistent with the ratio
of IR versus mm sources. We note however that G14.2-N harbours several sources
at an early evolutionary stage (i. e., classified as Stage 0/I by Povich et
al. 2016; see Table 8), and thus the non-thermal radio emission might also
result from strong shocks produced by radio jets powered by
intermediate-/high-mass objects (Carrasco-González et al. 2010; Rodríguez-
Kamenetzky et al. 2017; Kavak et al. 2021). Both analyses lead us to the
conclusion that there are differences in the evolutionary stages of the two
regions in the IRDC G14.2, and hint towards G14.2-N being more evolved
compared to G14.2-S, and likely containing more massive objects.

The differences, in age and mass, seem to be in agreement with the ‘filament-
halo’ gradient observed by Povich et al. (2016). The proposed scenario to
explain the gradient combines two interrelated star formation processes,
filament-driven star formation with dynamical relaxation (e. g., Bate et al.
2003) coupled with global hierarchical filament collapse (Vázquez-Semadeni et
al. 2019). However, the importance of each process in producing the observed
distribution is still unclear (see Povich et al. 2016, for further
discussion).

One of the possibilities causing these differences could be related to the
proximity of G14.2-N to the brightest IRAS 18153$-$1651 source in the field,
located at about $1.5^{\prime}$ south-east from G14.2-N (Busquet et al. 2013;
Gvaramadze et al. 2017). As mentioned previously, it hosts two B-type stars
(B1 and B3). The discovery of an optical arc near the centre of the nebula
associated with the IRAS source by Gvaramadze et al. (2017) led to the
hypothesis that it might represent a bubble blown by the wind of a young
massive star. This could be an evidence that the northern region is a bit more
evolved compared to Hub-S, which lacks of similar structures.

Finally, we compared our results to the previous work by Yanza et al. (2022)
towards M17 (located north to G14.2 and associated with a bright and well-
developed H ii region). In Yanza et al. (2022), the M17 region is studied
using VLA observations in X-band with the most extended A configuration. They
find a median source size of $\approx 200$ mas. In G14.2, our observations at
X-band result in a median size of $\approx 320$ mas for G14.2-S and $\approx
230$ mas for G14.2-N. Therefore, sources tend to get smaller from G14.2-S to
G14.2-N, and from G14.2-N to M17. This is consistent with a sequence where
centimeter sources are progressively more compact as they tend further north.
When connected with evolution, this would point to more evolved objects having
a more compact radio continuum emission compared to early-stage objects.
Early-stage Class 0/I sources are usually dominated by radio jets, which are
elongated and often resolved at sub-arcsecond resolution, whereas more evolved
Class II/III YSOs are typically associated with very compact and unresolved
radio emission (see Anglada et al. 2018).

Moreover, the compact radio continuum sources in the M17 region are mainly
dominated by non-thermal emission. For the sources for which the in-band
spectral index could be obtained (see Table 4 from Yanza et al. 2022 for
further information), more than 75% of them present spectral indices lower
than $-0.1$. This is in agreement with the results found for G14.2-S and
G14.2-N, where most of the non-thermal radio emitters are found in the more
evolved G14.2-N region. All together, our results combined with the results of
Yanza et al. (2022), confirm an evolutionary sequence starting with G14.2-S,
following with G14.2-N and ending in M17 as it was first proposed by Elmegreen
& Lada (1976). However, in our work we do not found evidences that support
their claim that star formation in M17 SWex is triggered by the presence of
the M17 H ii region.

###  5.4 Can the IRDC G14.2 form massive stars in the future?

Previous works by Povich & Whitney (2010); Povich et al. (2016) have pointed
out the remarkable star formation activity in the IRDC G14.2, characterized by
a high star formation rate (SFR) of $\dot{M}=0.0072$ M☉ yr-1. This value is
even higher than that of the Orion Nebula Cluster (ONC) and NGC 6618, the
cluster ionizing the bright M17 H ii region ($\dot{M}=0.005$ M☉ yr-1).
Interestingly, despite the high SFR, G14.2 lacks of O-type stars ($M>20$ M☉),
which is difficult to explain in the context of a standard Initial Mass
Function (IMF; Salpeter 1955; Kroupa 2001.

Using the N(H2) column density map of G14.2 (Lin et al. 2017) and adopting a
distance of $d\sim 1.6$ kpc to the cloud, we estimate the total mass of G14.2
to be approximately of 12000 M☉. This differs from the previous estimation of
$\sim$ 20000 M☉ (Lin et al. 2017) due to the different distances adopted.
Taking this updated mass estimate into account, and incorporating it into an
analytical model for the cloud’s evolution presented in Camacho et al. (2020)
(see their Figure 13 for further details), G14.2 would be located closer to
the trace of the initial accretion rate of $2.9\times 10^{3}$ M☉ Myr-1 and
thus, it would correspond to a age of 6-7 Myr, younger than the previously
estimated.

These findings shed light on the question raised by Povich et al. (2016)
regarding the late birth of massive stars in the IRDC G14.2. The cloud’s
slightly younger age suggests that it could continue to evolve and potentially
form massive stars in the future. Furthermore, the estimated mass reservoir is
lower than what was previously thought, challenging our previous understanding
of the cloud’s star-forming potential. Assuming a total mass of 12000 M☉ and a
global star formation efficiency (SFE) of 30% (Bontemps et al. 2010), we would
have a total of 3600 M☉ available to be in the stellar cluster. Considering
the IMF described by Kroupa (2001) and 3600 M☉, we would get that the typical
total number of stars in the cluster would be about 8300 $\pm$ 300
stars121212We have used the python tool imf available at
https://github.com/keflavich/imf, with a maximum of 84 $\pm$ 22 M☉ for the
most massive star in the cluster. These values come from 1000 different
generations of clusters, following the IMF from Kroupa (2001), and they
correspond to the median of the number of stars and maximum total mass. The
uncertainty in the values stand for the standard deviation of the 1000 runs.
Therefore, our results suggest that, even considering that the total mass
reservoir estimation is lower, G14.2 could end up forming massive stars in the
future.

##  6 Summary and Conclusions

We have carried out VLA observations in its most extended configurations of
the radio continuum emission at 6 cm (C-band: 4–8 GHz) and 3.6 cm (X-band:
8–12 GHz) towards the IRDC G14.225-0.506, an infrared dark cloud that is
forming stars in two main hubs (G14.2-N and G14.2-S) with similar masses and
luminosities. Our study allowed us to identify a hidden radio-continuum
population of compact sources and relate their properties to G14.2 as a whole.
The main findings obtained in this work can be summarized as follows:

  * •

We detected 66 sources, 32 of which are located in the G14.2-N region and 34
in the G14.2-S region, with two sources detected in both fields. Most of the
detected sources in the IRDC have flux densities around 50 $\mu$Jy and are
compact ($\approx 200$–300 mas, or 320-480 au), specially in G14.2-N.

  * •

The number of radio continuum sources in both hubs is similar, suggesting
similar levels of fragmentation and consistent with the latest mm data
obtained with ALMA, which suggests that the two regions are twin hubs.

  * •

We have identified 10 sources (3 located in G14.2-N and 7 in G14.2-S) to have
a significant variable flux at radio wavelengths over periods of a few days.
We note that variability may be an important factor to consider when detecting
and characterizing these faint and compact objects in future studies.

  * •

We looked for the counterparts at other wavelengths of the detected centimeter
sources. We found that 5 of the radio sources are associated with H2O and
CH3OH maser emission. 23 of the sources were already known YSOs and we
classified 25 sources as YSOs candidates. In the inner 0.4 pc region around
the two main hubs, the relative number of IR sources in front of the radio
sources is larger in G14.2-N by a factor of 4, suggesting that the northern
part is in a more advanced evolutionary stage.

  * •

By examining the spectral index, when possible, we determined the origin of
the radio continuum emission. In G14.2-N we found 14 sources with a non-
thermal origin and only one thermal emitter. Two sources present a flat
spectrum, most likely associated with thermal emission. In G14.2-S we found 8
non-thermal emitters, 11 thermal emitters and 2 sources with a flat spectrum.
The dominant continuum emission in G14.2-N could be an evidence of the
formation of more massive YSOs, resulting in non-thermal emission due to
strong shocks.

  * •

By comparing the bolometric luminosity with the radio luminosity, we found
that the studied sources are compatible with thermal radio jets, and excluded
the presence of embedded H ii regions in G14.2 by comparing our observations
with the expected relation for H ii regions.

  * •

When comparing the radio sources with their counterparts in X-rays, we found
that most of the sources are underluminous with respect to the Güdel-Benz
relation with $\kappa=1$. When examining only the sources classified as non-
thermal emitters, we find that they follow the Güdel-Benz relation with
$\kappa=0.03$, similarly to other star-forming regions. This suggests that
radio and X-ray emission are probably caused by magnetic reconnection in the
stellar coronae.

  * •

We compared the radio properties of the stellar population in G14.2 with other
nearby star-forming complexes, such as Taurus-Auriga, Perseus, Ophiuchus and
Serpens. The objects in G14.2 follow a similar trend as found in Serpens, with
Stage 0/I objects being associated with more non-thermal emission than Stage
II YSOs. Similar to Serpens, this may point to our region being composed of
more massive objects compare to other low-mass star forming complexes.

  * •

A comparison of our results of G14.2 with M17, a more evolved star-forming
region to the north-east of G14.2, confirms a wider evolutionary sequence
starting in G14.2-S and onwards to the most evolved region M17.

  * •

Based on the new distance estimations, G14.2 is slightly younger and harbors a
lower mass reservoir than what was previously though. Our analysis point out
that the complex has the potential to form massive stars in the future.

Currently, conducting deep radio surveys is highly time-consuming, taking
$\sim 11$ hour for a single pointing at X-band, and hence they are limited to
relatively nearby ($d<2$ kpc) star-forming regions. However, the next
generation of radio interferometers, such as the Square Kilometre Array (SKA)
and the Next Generation Very Large Array (ngVLA) are expected to significantly
improve the observations. These advanced radio telescopes will reach the same
sensitivity achieved in G14.2 with just 1 hour of telescope time,
revolutionizing the study of young stellar clusters at radio wavelengths by
performing systematic surveys across the Milky Way. In addition, these new
instruments will allow for systematic studies of short- and long-term
variability in radio emissions. This capability is essential for disentangle
the nature of the radio emission and, when combined with deep X-ray
observations, for investigating coronal-type magnetic activity across a wide
range of stellar masses and evolutionary stages. Finally, it is crucial to
conduct polarization observations to better understand the radio properties of
YSOs. Gyrosynchrotron emission exhibits circular polarization, while
synchrotron emission is linearly polarized. Although there are a few instances
where linear polarization has been detected in radio jets, such as in the case
of HH80-81 with a relatively high degree of polarization (Carrasco-González et
al. 2010), in most cases, the polarization degree is lower than in HH80-81,
only accessible with the next generation of radio interferometers.

###### Acknowledgements.

We are grateful to the anonymous referee for the valuable comments and
suggestions. We are grateful to Vanessa Yanza for useful discussions about the
M17-H ii properties. Project supported by a 2022 Leonardo Grant for
Researchers in Physics from the BBVA Foundation. The BBVA Foundation accepts
no responsibility for the opinions, statements and contents included in the
project and/or the results thereof, which are entirely the responsibility of
the authors. EDM, GB, JMG, ASM and RE acknowledge support from the
PID2020-117710GB-I00 grant funded by MCIN/ AEI /10.13039/501100011033. ASM
acknowledges support from the RyC2021-032892-I grant funded by
MCIN/AEI/10.13039/501100011033 and by the European Union ‘Next
GenerationEU’/PRTR, as well as the program Unidad de Excelencia María de
Maeztu CEX2020-001058-M. AP acknowledges financial support from the UNAM-
PAPIIT IG100223 grant, the Sistema Nacional de Investigadores of CONAHCyT, and
from the CONAHCyT project number 86372 of the ‘Ciencia de Frontera 2019’
program, entitled ‘Citlalcóatl: A multiscale study at the new frontier of the
formation and early evolution of stars and planetary systems’, México. NAL
acknowledges support from the European Research Council synergy grant ECOGAL
(Grant : 855130). HBL is supported by the National Science and Technology
Council (NSTC) of Taiwan (Grant Nos. 111-2112-M-110-022-MY3).

## References

  * Ainsworth et al. (2014) Ainsworth, R. E., Scaife, A. M. M., Ray, T. P., et al. 2014, ApJ, 792, L18
  * Andre et al. (1993) Andre, P., Ward-Thompson, D., & Barsony, M. 1993, ApJ, 406, 122
  * Añez-López et al. (2020) Añez-López, N., Busquet, G., Koch, P. M., et al. 2020, A&A, 644, A52
  * Anglada et al. (2018) Anglada, G., Rodríguez, L. F., & Carrasco-González, C. 2018, A&A Rev., 26, 3
  * Anglada et al. (1998) Anglada, G., Villuendas, E., Estalella, R., et al. 1998, The Astronomical Journal, 116, 2953
  * Ballering et al. (2023) Ballering, N. P., Cleeves, L. I., Haworth, T. J., et al. 2023, ApJ, 954, 127
  * Bate et al. (2003) Bate, M. R., Bonnell, I. A., & Bromm, V. 2003, MNRAS, 339, 577
  * Benz & Guedel (1994) Benz, A. O. & Guedel, M. 1994, A&A, 285, 621
  * Bontemps et al. (2010) Bontemps, S., Motte, F., Csengeri, T., & Schneider, N. 2010, A&A, 524, A18
  * Busquet et al. (2016) Busquet, G., Estalella, R., Palau, A., et al. 2016, ApJ, 819, 139
  * Busquet et al. (2013) Busquet, G., Zhang, Q., Palau, A., et al. 2013, ApJ, 764, L26
  * Camacho et al. (2020) Camacho, V., Vázquez-Semadeni, E., Palau, A., Busquet, G., & Zamora-Avilés, M. 2020, ApJ, 903, 46
  * Carey et al. (2009) Carey, S. J., Noriega-Crespo, A., Mizuno, D. R., et al. 2009, PASP, 121, 76
  * Carrasco-González et al. (2010) Carrasco-González, C., Rodríguez, L. F., Anglada, G., et al. 2010, Science, 330, 1209
  * Chen et al. (2019) Chen, H.-R. V., Zhang, Q., Wright, M. C. H., et al. 2019, ApJ, 875, 24
  * Chini et al. (1980) Chini, R., Elsaesser, H., & Neckel, T. 1980, A&A, 91, 186
  * Cornwell et al. (2008) Cornwell, T. J., Golap, K., & Bhatnagar, S. 2008, IEEE Journal of Selected Topics in Signal Processing, 2, 647
  * Coutens et al. (2019) Coutens, A., Liu, H. B., Jiménez-Serra, I., et al. 2019, A&A, 631, A58
  * Cutri et al. (2003) Cutri, R., Skrutskie, M., Dyk, S., et al. 2003, -1
  * Cutri et al. (2013) Cutri, R. M., Wright, E. L., Conrow, T., et al. 2013, Explanatory Supplement to the AllWISE Data Release Products, Explanatory Supplement to the AllWISE Data Release Products
  * De Pree et al. (2014) De Pree, C. G., Peters, T., Mac Low, M. M., et al. 2014, ApJ, 781, L36
  * Deller et al. (2013) Deller, A. T., Forbrich, J., & Loinard, L. 2013, A&A, 552, A51
  * Diaz-Miller et al. (1998) Diaz-Miller, R. I., Franco, J., & Shore, S. N. 1998, ApJ, 501, 192
  * Dzib et al. (2010) Dzib, S., Loinard, L., Mioduszewski, A. J., et al. 2010, The Astrophysical Journal, 718, 610
  * Dzib et al. (2013) Dzib, S. A., Loinard, L., Mioduszewski, A. J., et al. 2013, ApJ, 775, 63
  * Dzib et al. (2015) Dzib, S. A., Loinard, L., Rodríguez, L. F., et al. 2015, ApJ, 801, 91
  * Dzib et al. (2023) Dzib, S. A., Yang, A. Y., Urquhart, J. S., et al. 2023, A&A, 670, A9
  * Elmegreen & Lada (1976) Elmegreen, B. G. & Lada, C. J. 1976, AJ, 81, 1089
  * Elmegreen et al. (1979) Elmegreen, B. G., Lada, C. J., & Dickinson, D. F. 1979, ApJ, 230, 415
  * Feigelson & Montmerle (1985) Feigelson, E. D. & Montmerle, T. 1985, ApJ, 289, L19
  * Forbrich et al. (2007) Forbrich, J., Massi, M., Ros, E., Brunthaler, A., & Menten, K. M. 2007, A&A, 469, 985
  * Forbrich et al. (2016) Forbrich, J., Rivilla, V. M., Menten, K. M., et al. 2016, ApJ, 822, 93
  * Green et al. (2010) Green, J. A., Caswell, J. L., Fuller, G. A., et al. 2010, Monthly Notices of the Royal Astronomical Society, 409, 913
  * Güdel (2002) Güdel, M. 2002, ARA&A, 40, 217
  * Guedel & Benz (1993) Guedel, M. & Benz, A. O. 1993, ApJ, 405, L63
  * Gutermuth et al. (2009) Gutermuth, R. A., Megeath, S. T., Myers, P. C., et al. 2009, ApJS, 184, 18
  * Gvaramadze et al. (2017) Gvaramadze, V. V., Mackey, J., Kniazev, A. Y., et al. 2017, MNRAS, 466, 1857
  * Hoffmeister et al. (2008) Hoffmeister, V. H., Chini, R., Scheyda, C. M., et al. 2008, ApJ, 686, 310
  * Hofner et al. (2017) Hofner, P., Cesaroni, R., Kurtz, S., et al. 2017, ApJ, 843, 99
  * Irabor et al. (2023) Irabor, T., Hoare, M. G., Burton, M., et al. 2023, MNRAS, 520, 1073
  * Ishihara et al. (2010) Ishihara, D., Onaka, T., Kataza, H., et al. 2010, A&A, 514, A1
  * Jaffe et al. (1981) Jaffe, D. T., Guesten, R., & Downes, D. 1981, ApJ, 250, 621
  * Kavak et al. (2021) Kavak, Ü., Sánchez-Monge, Á., López-Sepulcre, A., et al. 2021, A&A, 645, A29
  * Kounkel et al. (2014) Kounkel, M., Hartmann, L., Loinard, L., et al. 2014, ApJ, 790, 49
  * Kroupa (2001) Kroupa, P. 2001, MNRAS, 322, 231
  * Kurtz et al. (1994) Kurtz, S., Churchwell, E., & Wood, D. O. S. 1994, ApJS, 91, 659
  * Lada (1987) Lada, C. J. 1987, in Star Forming Regions, ed. M. Peimbert & J. Jugaku, Vol. 115, 1
  * Lada & Lada (2003) Lada, C. J. & Lada, E. A. 2003, ARA&A, 41, 57
  * Lin et al. (2017) Lin, Y., Liu, H. B., Dale, J. E., et al. 2017, ApJ, 840, 22
  * Liu et al. (2014) Liu, H. B., Galván-Madrid, R., Forbrich, J., et al. 2014, ApJ, 780, 155
  * Marti et al. (1993) Marti, J., Rodriguez, L. F., & Reipurth, B. 1993, ApJ, 416, 208
  * Martins et al. (2005) Martins, F., Schaerer, D., & Hillier, D. J. 2005, A&A, 436, 1049
  * Medina et al. (2018) Medina, S. N. X., Dzib, S. A., Tapia, M., Rodríguez, L. F., & Loinard, L. 2018, A&A, 610, A27
  * Meng et al. (2019) Meng, F., Sánchez-Monge, Á., Schilke, P., et al. 2019, A&A, 630, A73
  * Moscadelli et al. (2016) Moscadelli, L., Sánchez-Monge, Á., Goddi, C., et al. 2016, A&A, 585, A71
  * Motte et al. (2018) Motte, F., Bontemps, S., & Louvet, F. 2018, ARA&A, 56, 41
  * Ohashi et al. (2016) Ohashi, S., Sanhueza, P., Chen, H.-R. V., et al. 2016, ApJ, 833, 209
  * Ortiz-León et al. (2015) Ortiz-León, G. N., Loinard, L., Mioduszewski, A. J., et al. 2015, ApJ, 805, 9
  * Osorio et al. (2017) Osorio, M., Díaz-Rodríguez, A. K., Anglada, G., et al. 2017, ApJ, 840, 36
  * Padovani et al. (2019) Padovani, M., Marcowith, A., Sánchez-Monge, Á., Meng, F., & Schilke, P. 2019, A&A, 630, A72
  * Palagi et al. (1993) Palagi, F., Cesaroni, R., Comoretto, G., Felli, M., & Natale, V. 1993, A&AS, 101, 153
  * Panagia (1973) Panagia, N. 1973, AJ, 78, 929
  * Pech et al. (2016) Pech, G., Loinard, L., Dzib, S. A., et al. 2016, ApJ, 818, 116
  * Plunkett et al. (2018) Plunkett, A. L., Fernández-López, M., Arce, H. G., et al. 2018, A&A, 615, A9
  * Povich et al. (2009) Povich, M. S., Churchwell, E., Bieging, J. H., et al. 2009, ApJ, 696, 1278
  * Povich et al. (2016) Povich, M. S., Townsley, L. K., Robitaille, T. P., et al. 2016, ApJ, 825, 125
  * Povich & Whitney (2010) Povich, M. S. & Whitney, B. A. 2010, ApJ, 714, L285
  * Pudritz (2002) Pudritz, R. E. 2002, Science, 295, 68
  * Purcell et al. (2013) Purcell, C. R., Hoare, M. G., Cotton, W. D., et al. 2013, The Astrophysical Journal Supplement Series, 205, 1
  * Purser et al. (2021) Purser, S. J. D., Lumsden, S. L., Hoare, M. G., & Kurtz, S. 2021, MNRAS, 504, 338
  * Reid et al. (1995) Reid, M. J., Argon, A. L., Masson, C. R., Menten, K. M., & Moran, J. M. 1995, ApJ, 443, 238
  * Rivilla et al. (2015) Rivilla, V. M., Chandler, C. J., Sanz-Forcada, J., et al. 2015, ApJ, 808, 146
  * Robitaille et al. (2006) Robitaille, T. P., Whitney, B. A., Indebetouw, R., Wood, K., & Denzmore, P. 2006, ApJS, 167, 256
  * Rodríguez (1999) Rodríguez, L. F. 1999, in Star Formation 1999, ed. T. Nakamoto, 257–262
  * Rodriguez et al. (1989) Rodriguez, L. F., Curiel, S., Moran, J. M., et al. 1989, ApJ, 346, L85
  * Rodríguez et al. (2005) Rodríguez, L. F., Garay, G., Brooks, K. J., & Mardones, D. 2005, ApJ, 626, 953
  * Rodríguez et al. (2012) Rodríguez, L. F., González, R. F., Montes, G., et al. 2012, ApJ, 755, 152
  * Rodríguez-Kamenetzky et al. (2017) Rodríguez-Kamenetzky, A., Carrasco-González, C., Araudo, A., et al. 2017, ApJ, 851, 16
  * Rodríguez-Kamenetzky et al. (2016) Rodríguez-Kamenetzky, A., Carrasco-González, C., Araudo, A., et al. 2016, ApJ, 818, 27
  * Rodríguez-Kamenetzky et al. (2019) Rodríguez-Kamenetzky, A., Carrasco-González, C., González-Martín, O., et al. 2019, MNRAS, 482, 4687
  * Rosero et al. (2016) Rosero, V., Hofner, P., Claussen, M., et al. 2016, ApJS, 227, 25
  * Rosero et al. (2019) Rosero, V., Hofner, P., Kurtz, S., et al. 2019, ApJ, 880, 99
  * Salpeter (1955) Salpeter, E. E. 1955, ApJ, 121, 161
  * Sánchez-Monge et al. (2013a) Sánchez-Monge, Á., Beltrán, M. T., Cesaroni, R., et al. 2013a, A&A, 550, A21
  * Sánchez-Monge et al. (2013b) Sánchez-Monge, Á., Kurtz, S., Palau, A., et al. 2013b, ApJ, 766, 114
  * Sanna et al. (2019) Sanna, A., Moscadelli, L., Goddi, C., et al. 2019, A&A, 623, L3
  * Spitzer Science (2009) Spitzer Science, C. 2009, VizieR Online Data Catalog, II/293
  * Sugiyama et al. (2017) Sugiyama, K., Nagase, K., Yonekura, Y., et al. 2017, PASJ, 69, 59
  * Thompson (1984) Thompson, R. I. 1984, ApJ, 283, 165
  * Vacca et al. (1996) Vacca, W. D., Garmany, C. D., & Shull, J. M. 1996, ApJ, 460, 914
  * Vargas-González et al. (2021) Vargas-González, J., Forbrich, J., Dzib, S. A., & Bally, J. 2021, MNRAS, 506, 3169
  * Vázquez-Semadeni et al. (2017) Vázquez-Semadeni, E., González-Samaniego, A., & Colín, P. 2017, MNRAS, 467, 1313
  * Vázquez-Semadeni et al. (2019) Vázquez-Semadeni, E., Palau, A., Ballesteros-Paredes, J., Gómez, G. C., & Zamora-Avilés, M. 2019, MNRAS, 490, 3061
  * Wang et al. (2006) Wang, Y., Zhang, Q., Rathborne, J. M., Jackson, J., & Wu, Y. 2006, ApJ, 651, L125
  * Wu et al. (2014) Wu, Y. W., Sato, M., Reid, M. J., et al. 2014, A&A, 566, A17
  * Xu et al. (2011) Xu, Y., Moscadelli, L., Reid, M. J., et al. 2011, ApJ, 733, 25
  * Yanza et al. (2022) Yanza, V., Masqué, J. M., Dzib, S. A., et al. 2022, AJ, 163, 276
  * Zapata et al. (2004) Zapata, L. A., Rodríguez, L. F., Kurtz, S. E., & O’Dell, C. R. 2004, AJ, 127, 2252
  * Zucker et al. (2020) Zucker, C., Speagle, J. S., Schlafly, E. F., et al. 2020, A&A, 633, A51

##  Appendix A Variable source subtraction

The presence of the highly variable sources during observations generates
artifacts with a psf-like pattern that cannot be properly removed. In order to
use the tclean task correctly, the substraction of the sources had to be done
before. One of the sources is located in G14.2-N at the C-band, while the
other is in G14.2-S at the X-band. The following subsections detail the two
subtraction processes.

###  A.1 G14.2-N C-band

The variable source in G14.2-N is located at R.A.(J2000)=18h18m05.651s and
Dec.(J2000)=$-$16∘52′56.87′′. The flux of this source changes from $0.235$ mJy
to $1.686$ mJy from the data collected on September 25 to the one collected on
September 26, which is a variation of a factor of 6. Therefore, we need to
subtract the source before combining the visibilities of both days to make the
final map. First of all, we tried to subtract the source using the CASA uvsub
command, which worked correctly for 25th September but had some significant
residual flux for the 26th of September. We applied the self-calibration to
the data of 26th September and then we used the same command to subtract the
source. After that we combined both datasets (the 25th of September and the
26th of September) to obtain the final image.

###  A.2 G14.2-S X-band

The source we need to subtract in G14.2-S is located at
R.A.(J2000)=18h18m02.910s and Dec.(J2000)=$-$17∘05′40.73′′. We had to use a
different method for this source since is located outside the field of view of
the VLA observations. The first step was to generate an image with a larger
field of view which had to include the source. This process needed too much
computer processing time, so we used an alternative way, which consisted of
creating a small image around the source, using the CASA tclean option called
outlier. For this small image, we defined a mask around the source, avoiding
the lobes of the dirty beam (psf), that is used to constrain the cleaning
algorithm where the true emission is located.

At the X-band observations, the source had a variability of more than one
order of magnitude and therefore we generated images for the different days
independently. The next step was to subtract the source using the CASA uvsub
command like in the G14.2-N C-band variable source, but as this source is far
from the phase center, a geometric correction for the curvature had to be done
before. This correction takes into account the non-coplanarity of the
baselines as function of the distance from the phase center which results in a
non zero w-term. This results in a phase term that limits the dynamic range of
the final image. This correction projects the sky curvature onto many smaller
planes which is known as w-projection (see Cornwell et al. 2008). The source
was subtracted for every observation day and then we combined all the days to
get the final image.

##  Appendix B X Band recentering

For the G14.2-N X-band data, it was necessary to realign the data for each day
by recentering it due to the discrepancy in the positions of all the sources.
This mismatch was detected while viewing the map of every day of observation
individually.

In order to correct for this mismatch all the data had to be recentered. The
first step was to get the positions of bright sources that had a counterpart
in our G14.2-N C-band image. With these positions, the next step was to check
which day was the one where the measured positions were the closest to the
peak position of the C-band counterparts. Then we used the clean components of
the brightest sources from the selected image as a model for self-calibrating
the other days data. Phase corrections obtained for each day corrects for
atmospheric changes during observations but also correct astrometry to fit the
value used as a model. Finally the new self-calibrated visibilities were used
to obtain a new and corrected image.

##  Appendix C Parameters of the detected sources

Each source’s position, peak intensity, flux density and deconvolved size were
determined by selecting a small region around each source. The uncertainties
in the fluxes are the result of the quadratic sum of the statistical error of
the region, i.e., the rms of the region and the uncertainty in the
determination of the flux itself, which has been considered to be 10% of it.
The sources have been sorted by declination, showing the separation between
G14.2-N and G14.2-S. Table 10 shows the sources that have been detected at
C-band, and Table 11 shows the sources that have been detected at X-band. For
unresolved point-like sources or for sources having extended and non-Gaussian
emission, the peak position and integrated flux were determined by selecting a
region around the emitting region. All fluxes and intensities presented are
corrected for primary beam attenuation.

Table 10: Parameters of the radio sources detected at C-band.

| Position | $I_{\rm peak}$ | $S_{\nu}$ | SizeaaaSizes have been calculated as $\sqrt{\theta_{\text{maj}}\times\theta_{\text{min}}}$, where $\theta_{\text{maj}}$ and $\theta_{\text{min}}$ are the deconvolved major and minor axis, respectively. | PA
---|---|---|---|---|---
Source | R.A.(J2000) 18h | Dec.(J2000) $-16^{\circ}$ | ($\mu$Jy/beam) | ($\mu$Jy) | (mas) | (∘)
Northern region G14.2-N |  |  |
VLA-01 | 18:13.2411 $\pm$ 0.0003 | 46:32.830 $\pm$ 0.010 | 87.7 $\pm$ 8.8 | 162.0 $\pm$ 16.4 | 446 $\pm$ 45 | 8 $\pm$ 2
VLA-02 | 18:06.6380 $\pm$ 0.0030 | 47:59.598 $\pm$ 0.013 | 20.6 $\pm$ 2.3 | 21.9 $\pm$ 2.8 | 104 $\pm$ 10 | 87 $\pm$ 62
VLA-03 | 18:11.6160 $\pm$ 0.0010 | 48:30.997 $\pm$ 0.006 | 296.6 $\pm$ 30.2 | 305.2 $\pm$ 32.3 | point source |
VLA-04 | 18:10.8910 $\pm$ 0.0070 | 48:31.332 $\pm$ 0.027 | 20.7 $\pm$ 2.1 | 17.3 $\pm$ 1.9 | point source |
VLA-05 | 18:05.3939 $\pm$ 0.0002 | 48:39.643 $\pm$ 0.007 | 19.8 $\pm$ 2.0 | 19.3 $\pm$ 2.0 | point source |
VLA-06 | 18:24.9224 $\pm$ 0.0005 | 49:00.898 $\pm$ 0.014 | 24.2 $\pm$ 2.6 | 31.7 $\pm$ 3.6 | point source |
VLA-07 | 18:08.8731 $\pm$ 0.0005 | 49:11.557 $\pm$ 0.015 | 32.3 $\pm$ 3.4 | 31.1 $\pm$ 3.6 | point source |
VLA-08 | 18:14.4820 $\pm$ 0.0010 | 49:11.684 $\pm$ 0.018 | 25.5 $\pm$ 2.6 | 42.1 $\pm$ 4.6 | 376 $\pm$ 38 | 121 $\pm$ 24
VLA-09 | 18:12.4110 $\pm$ 0.0010 | 49:16.070 $\pm$ 0.029 | 13.6 $\pm$ 1.4 | 16.2 $\pm$ 1.7 | 207 $\pm$ 21 | 165 $\pm$ 86
VLA-10 | 18:07.3270 $\pm$ 0.0010 | 49:17.014 $\pm$ 0.030 | 20.7 $\pm$ 2.6 | 45.3 $\pm$ 6.6 | 509 $\pm$ 51 | 109 $\pm$ 85
VLA-11 | 18:12.5702 $\pm$ 0.0002 | 49:22.128 $\pm$ 0.006 | 121.3 $\pm$ 12.2 | 125.5 $\pm$ 12.7 | point source |
VLA-12 | 18:06.8200 $\pm$ 0.0070 | 49:23.119 $\pm$ 0.022 | 27.0 $\pm$ 3.0 | 57.4 $\pm$ 6.8 | 513 $\pm$ 52 | 172 $\pm$ 14
VLA-13 | 18:12.7140 $\pm$ 0.0010 | 49:27.384 $\pm$ 0.021 | 74.9 $\pm$ 9.5 |  098.0 $\pm$ 15.7 | point source |
VLA-14 | 18:12.2910 $\pm$ 0.0020 | 49:28.235 $\pm$ 0.035 |  050.9 $\pm$ 11.2 |  040.4 $\pm$ 14.4 | point source |
VLA-15 | 18:14.8110 $\pm$ 0.0003 | 49:28.778 $\pm$ 0.013 | 35.5 $\pm$ 3.8 | 38.66 $\pm$ 4.59 | 138 $\pm$ 14 | 12 $\pm$ 6
VLA-16 | 18:12.5050 $\pm$ 0.0010 | 49:30.695 $\pm$ 0.034 | 15.0 $\pm$ 1.5 | 14.6 $\pm$ 1.6 | point source |
VLA-17 | 17:54.6870 $\pm$ 0.0010 | 49:42.697 $\pm$ 0.015 | 252.1 $\pm$ 25.8 | 359.1 $\pm$ 37.9 | point source |
VLA-18 | 18:18.9245 $\pm$ 0.0002 | 49:45.559 $\pm$ 0.009 | 21.4 $\pm$ 2.2 | 29.3 $\pm$ 3.0 | 291 $\pm$ 29 | 168 $\pm$ 5
VLA-19 | 18:23.9770 $\pm$ 0.0070 | 49:54.278 $\pm$ 0.225 | 48.2 $\pm$ 5.2 | 107.5 $\pm$ 27.8 | 1093 $\pm$ 109 | 37 $\pm$ 10
VLA-20 | 18:12.1986 $\pm$ 0.0003 | 50:09.309 $\pm$ 0.013 | 24.0 $\pm$ 2.5 | 21.7 $\pm$ 2.4 | point source |
VLA-21 | 17:59.1680 $\pm$ 0.0010 | 50:16.184 $\pm$ 0.018 | 29.1 $\pm$ 2.9 | 30.4 $\pm$ 3.1 | point source |
VLA-22 | 18:12.2000 $\pm$ 0.0030 | 50:17.147 $\pm$ 0.012 | 36.4 $\pm$ 3.6 | 40.4 $\pm$ 4.0 | 134 $\pm$ 13 | 157 $\pm$ 1
VLA-23 | 18:18.1790 $\pm$ 0.0002 | 50:20.696 $\pm$ 0.008 | 19.1 $\pm$ 2.0 | 12.9 $\pm$ 1.5 | point source |
VLA-24 | 18:12.6940 $\pm$ 0.0010 | 50:33.061 $\pm$ 0.018 | 38.9 $\pm$ 4.0 | 38.1 $\pm$ 4.1 | point source |
VLA-25 | 18:06.1755 $\pm$ 0.0004 | 50:35.942 $\pm$ 0.013 | 28.1 $\pm$ 2.9 | 30.6 $\pm$ 3.3 | point source |
VLA-26 | 18:25.9654 $\pm$ 0.0005 | 50:37.329 $\pm$ 0.008 | 71.5 $\pm$ 7.2 | 86.4 $\pm$ 8.9 | point source |
VLA-27 | 18:08.4200 $\pm$ 0.0010 | 50:49.543 $\pm$ 0.014 | 27.8 $\pm$ 2.9 | 37.2 $\pm$ 4.0 | 274 $\pm$ 27 | 42 $\pm$ 41
VLA-28 | 18:06.8150 $\pm$ 0.0020 | 51:19.707 $\pm$ 0.033 | 22.3 $\pm$ 2.8 | 48.8 $\pm$ 7.1 | 509 $\pm$ 51 | 109 $\pm$ 85
VLA-29 | 18:12.3152 $\pm$ 0.0005 | 51:25.829 $\pm$ 0.017 | 24.5 $\pm$ 2.5 | 24.7 $\pm$ 2.5 | point source |
VLA-30 | 18:09.0020 $\pm$ 0.0040 | 52:02.777 $\pm$ 0.017 | 39.9 $\pm$ 4.2 | 42.7 $\pm$ 5.0 | point source |
VLA-31 | 18:02.5890 $\pm$ 0.0010 | 52:45.716 $\pm$ 0.016 | 69.4 $\pm$ 7.2 |  096.0 $\pm$ 10.3 | 255 $\pm$ 26 | 34 $\pm$ 8
VLA-32${}^{\text{S}}$ | 18:05.6480 $\pm$ 0.0010 | 52:56.862 $\pm$ 0.024 | 1197.7 $\pm$ 121.5 | 2192.3 $\pm$ 225.7 | 610 $\pm$ 61 | 155 $\pm$ 1
VLA-33${}^{\text{N}}$ | 18:15.8140 $\pm$ 0.0002 | 53:32.749 $\pm$ 0.007 | 420.0 $\pm$ 42.2 | 554.0 $\pm$ 57.4 | 255 $\pm$ 25 | 174 $\pm$ 4
VLA-33${}^{\text{S}}$ |  |  | 304.3 $\pm$ 30.5 | 494.4 $\pm$ 49.6 | 605 $\pm$ 61 | 8 $\pm$ 1
Southern region G14.2-S |  |  |
VLA-34 | 18:13.6610 $\pm$ 0.0020 | 54:35.194 $\pm$ 0.041 | 33.5 $\pm$ 3.6 | 33.1 $\pm$ 4.0 | point source |
VLA-35 | 18:02.8200 $\pm$ 0.0020 | 54:58.004 $\pm$ 0.039 | 84.4 $\pm$ 9.3 | 114.2 $\pm$ 14.1 | 475 $\pm$ 47 | 135 $\pm$ 14
VLA-36 | 18:10.0710 $\pm$ 0.0020 | 55:51.177 $\pm$ 0.086 | 66.7 $\pm$ 7.4 | 203.4 $\pm$ 24.0 | 1329 $\pm$ 133 | 7 $\pm$ 5
VLA-37 | 18:12.2524 $\pm$ 0.0002 | 56:02.988 $\pm$ 0.008 | 123.0 $\pm$ 12.5 | 134.7 $\pm$ 14.1 | 279 $\pm$ 28 | 156 $\pm$ 42
VLA-38 | 17:58.0390 $\pm$ 0.0020 | 56:25.562 $\pm$ 0.011 | 1439.3 $\pm$ 145.3 | 2384.8 $\pm$ 243.7 | 576 $\pm$ 58 | 107 $\pm$ 2
VLA-40 | 18:06.5210 $\pm$ 0.0010 | 56:47.449 $\pm$ 0.014 | 57.7 $\pm$ 6.3 | 65.7 $\pm$ 8.2 | point source |
VLA-41 | 18:10.8736 $\pm$ 0.0005 | 56:49.420 $\pm$ 0.013 | 57.1 $\pm$ 5.9 | 59.2 $\pm$ 6.5 | point source |
VLA-42 | 18:11.9586 $\pm$ 0.0003 | 57:01.371 $\pm$ 0.012 | 56.9 $\pm$ 5.7 | 70.1 $\pm$ 7.1 | 428 $\pm$ 43 | 138 $\pm$ 5
VLA-43 | 18:05.9117 $\pm$ 0.0030 | 57:07.138 $\pm$ 0.017 | 31.6 $\pm$ 3.3 | 34.7 $\pm$ 3.7 | point source |
VLA-44 | 18:13.0550 $\pm$ 0.0010 | 57:09.695 $\pm$ 0.012 | 21.2 $\pm$ 2.2 | 59.1 $\pm$ 6.5 | 1248 $\pm$ 125 | 7 $\pm$ 4
VLA-46 | 18:08.7120 $\pm$ 0.0010 | 57:12.628 $\pm$ 0.014 | 92.8 $\pm$ 9.3 |  098.1 $\pm$ 10.0 | point source |
VLA-50 | 18:01.2390 $\pm$ 0.0020 | 57:15.700 $\pm$ 0.013 | 144.2 $\pm$ 14.4 | 215.7 $\pm$ 21.7 | 599 $\pm$ 60 | 94 $\pm$ 1
VLA-51 | 18:10.1513 $\pm$ 0.0002 | 57:18.301 $\pm$ 0.006 | 141.3 $\pm$ 14.3 | 157.4 $\pm$ 16.2 | 304 $\pm$ 30 | 109 $\pm$ 33
VLA-53 | 18:12.7680 $\pm$ 0.0010 | 57:19.485 $\pm$ 0.004 | 24.9 $\pm$ 2.6 | 35.4 $\pm$ 4.0 | 533 $\pm$ 53 | 47 $\pm$ 8
VLA-57 | 18:09.1810 $\pm$ 0.0010 | 57:28.051 $\pm$ 0.017 | 22.0 $\pm$ 2.3 | 20.5 $\pm$ 2.2 | point source |
VLA-61 | 18:14.1490 $\pm$ 0.0010 | 57:49.089 $\pm$ 0.022 | 26.7 $\pm$ 2.7 | 31.1 $\pm$ 3.2 | point source |
VLA-63 | 17:58.0902 $\pm$ 0.0007 | 58:00.580 $\pm$ 0.010 | 35.2 $\pm$ 3.6 | 493.8 $\pm$ 49.5 | 29 $\pm$ 22 |
VLA-64 | 18:05.9810 $\pm$ 0.0010 | 58:04.365 $\pm$ 0.016 | 68.1 $\pm$ 6.9 | 72.3 $\pm$ 7.5 | 116 $\pm$ 12 | 75 $\pm$ 11
VLA-66 | 18:02.2220 $\pm$ 0.0030 | 59:22.112 $\pm$ 0.035 | 58.1 $\pm$ 5.8 | 66.4 $\pm$ 6.7 | 323 $\pm$ 32 | 74 $\pm$ 7

131313 The sources between the dashed lines correspond to those that have been
detected at both regions.

Table 11: Parameters of the radio sources detected at X-band.

| Position | $I_{\rm peak}$ | $S_{\nu}$ | SizeaaaSizes have been calculated as $\sqrt{\theta_{\text{maj}}\times\theta_{\text{min}}}$, where $\theta_{\text{maj}}$ and $\theta_{\text{min}}$ are the deconvolved major and minor axis, respectively. | PA
---|---|---|---|---|---
Source | R.A.(J2000) 18h | Dec.(J2000) $-16^{\circ}$ | ($\mu$Jy/beam) | ($\mu$Jy) | (mas) | (∘)
Northern region G14.2-N |  |  |
VLA-03 | 18:11.6166 $\pm$ 0.0005 | 48:31.007 $\pm$ 0.037 | 110.1 $\pm$ 11.3 | 243.3 $\pm$ 25.4 | 444 $\pm$ 44 | 171 $\pm$ 1
VLA-08 | 18:14.4830 $\pm$ 0.0010 | 49:11.620 $\pm$ 0.019 | 37.3 $\pm$ 3.8 | 79.3 $\pm$ 8.1 | 459 $\pm$ 46 | 27 $\pm$ 1
VLA-11 | 18:12.5698 $\pm$ 0.0002 | 49:22.110 $\pm$ 0.008 | 103.1 $\pm$ 10.4 | 129.6 $\pm$ 13.2 | 230 $\pm$ 23 | 3 $\pm$ 2
VLA-13 | 18:12.7130 $\pm$ 0.0010 | 49:27.377 $\pm$ 0.026 | 46.7 $\pm$ 5.5 | 70.0 $\pm$ 9.7 | 262 $\pm$ 26 | 32 $\pm$ 12
VLA-14 | 18:12.3130 $\pm$ 0.0020 | 49:27.937 $\pm$ 0.024 | 26.7 $\pm$ 9.7 | 22.9 $\pm$ 7.8 | point source |
VLA-20 | 18:12.1986 $\pm$ 0.0003 | 50:09.309 $\pm$ 0.013 | 13.7 $\pm$ 1.4 | 15.2 $\pm$ 1.6 | point source |
VLA-22 | 18:12.2000 $\pm$ 0.0010 | 50:17.140 $\pm$ 0.023 | 26.4 $\pm$ 2.6 | 37.2 $\pm$ 3.7 | 313 $\pm$ 31 | 8 $\pm$ 2
VLA-24 | 18:12.6950 $\pm$ 0.0010 | 50:33.071 $\pm$ 0.020 | 17.0 $\pm$ 1.8 | 20.3 $\pm$ 2.2 | 205 $\pm$ 21 | 11 $\pm$ 12
VLA-32${}^{\text{N}}$ | 18:05.6530 $\pm$ 0.0020 | 52:56.872 $\pm$ 0.055 | 182.1 $\pm$ 29.2 | 1050.0 $\pm$ 195.0 | point source |
VLA-33${}^{\text{S}}$ | 18:15.8104 $\pm$ 0.0003 | 53:32.798 $\pm$ 0.018 | 429.5 $\pm$ 43.2 | 600.2 $\pm$ 60.6 | point source |
Southern region G14.2-S |  |  |
VLA-35 | 18:02.8150 $\pm$ 0.0012 | 54:57.921 $\pm$ 0.009 | 142.2 $\pm$ 14.4 | 161.0 $\pm$ 16.6 | 345 $\pm$ 34 | 163 $\pm$ 85
VLA-36 | 18:10.0720 $\pm$ 0.0030 | 55:51.302 $\pm$ 0.071 | 64.6 $\pm$ 7.2 | 172.5 $\pm$ 20.9 | 1202 $\pm$ 120 | 178 $\pm$ 7
VLA-38 | 17:58.0390 $\pm$ 0.0020 | 56:25.562 $\pm$ 0.011 | 1302.5 $\pm$ 132.0 | 1557.5 $\pm$ 160.8 | 392 $\pm$ 39 | 49 $\pm$ 13
VLA-39 | 18:11.5230 $\pm$ 0.0010 | 56:27.282 $\pm$ 0.021 | 13.4 $\pm$ 1.5 | 17.3 $\pm$ 2.1 | point source |
VLA-40 | 18:06.5220 $\pm$ 0.0010 | 56:47.473 $\pm$ 0.007 | 70.0 $\pm$ 7.5 | 68.5 $\pm$ 8.3 | point source |
VLA-42 | 18:11.9610 $\pm$ 0.0010 | 57:01.432 $\pm$ 0.008 | 27.6 $\pm$ 2.8 | 35.3 $\pm$ 3.6 | 497 $\pm$ 50 | 31 $\pm$ 28
VLA-44 | 18:13.0550 $\pm$ 0.0010 | 57:09.695 $\pm$ 0.012 | 20.1 $\pm$ 2.0 | 26.4 $\pm$ 2.7 | 396 $\pm$ 40 | 175 $\pm$ 1
VLA-45 | 18:13.9380 $\pm$ 0.0010 | 57:11.438 $\pm$ 0.025 | 16.0 $\pm$ 1.8 | 17.4 $\pm$ 2.2 | point source |
VLA-46 | 18:08.7040 $\pm$ 0.0020 | 57:12.595 $\pm$ 0.008 | 46.2 $\pm$ 5.0 | 137.7 $\pm$ 15.6 | 1320 $\pm$ 132 | 43 $\pm$ 8
VLA-47 | 18:10.1620 $\pm$ 0.0020 | 57:12.793 $\pm$ 0.019 | 13.3 $\pm$ 1.4 | 21.2 $\pm$ 2.2 | 709 $\pm$ 71 | 92 $\pm$ 10
VLA-48 | 18:11.1420 $\pm$ 0.0010 | 57:13.015 $\pm$ 0.010 | 44.1 $\pm$ 4.4 | 45.1 $\pm$ 4.6 | 65 $\pm$ 7 | 93 $\pm$ 41
VLA-49 | 18:13.8490 $\pm$ 0.0010 | 57:14.848 $\pm$ 0.013 | 23.9 $\pm$ 2.4 | 33.9 $\pm$ 3.4 | point source |
VLA-50 | 18:01.2405 $\pm$ 0.0005 | 57:15.652 $\pm$ 0.004 | 118.4 $\pm$ 11.9 | 135.2 $\pm$ 13.6 | 323 $\pm$ 32 | 74 $\pm$ 7
VLA-51 | 18:10.1526 $\pm$ 0.0004 | 57:18.354 $\pm$ 0.003 | 98.8 $\pm$ 9.9 | 105.2 $\pm$ 10.6 | 232 $\pm$ 23 | 42 $\pm$ 15
VLA-52 | 18:20.9130 $\pm$ 0.0020 | 57:19.476 $\pm$ 0.014 | 15.2 $\pm$ 1.5 | 14.1 $\pm$ 1.4 | point source |
VLA-53 | 18:12.7680 $\pm$ 0.0010 | 57:19.485 $\pm$ 0.004 | 17.1 $\pm$ 1.7 | 26.4 $\pm$ 2.3 | 672 $\pm$ 67 | 164 $\pm$ 5
VLA-54 | 18:13.2020 $\pm$ 0.0060 | 57:22.155 $\pm$ 0.036 | 16.4 $\pm$ 1.8 | 32.3 $\pm$ 3.7 | point source |
VLA-55 | 18:13.3470 $\pm$ 0.0010 | 57:23.950 $\pm$ 0.004 | 28.3 $\pm$ 2.8 | 43.0 $\pm$4.3 | 682 $\pm$ 68 | 5 $\pm$ 1
VLA-56 | 18:14.1640 $\pm$ 0.0020 | 57:24.866 $\pm$ 0.002 | 19.0 $\pm$ 1.9 | 16.7 $\pm$ 1.7 | point source |
VLA-58 | 18:12.3200 $\pm$ 0.0010 | 57:33.786 $\pm$ 0.008 | 25.6 $\pm$ 2.6 | 25.7 $\pm$ 2.6 | point source |
VLA-59 | 18:11.9210 $\pm$ 0.0010 | 57:42.746 $\pm$ 0.011 | 20.7 $\pm$ 2.1 | 42.3 $\pm$ 4.3 | 953 $\pm$ 95 | 174 $\pm$ 3
VLA-60 | 18:09.1710 $\pm$ 0.0010 | 57:46.801 $\pm$ 0.007 | 54.6 $\pm$ 0.4 | 54.4 $\pm$ 5.5 | point source |
VLA-61 | 18:14.1480 $\pm$ 0.0010 | 57:49.143 $\pm$ 0.010 | 24.0 $\pm$ 2.4 | 22.8 $\pm$ 2.3 | point source |
VLA-62 | 18:07.7070 $\pm$ 0.0020 | 57:49.439 $\pm$ 0.018 | 21.2 $\pm$ 2.1 | 34.1 $\pm$ 3.4 | 697 $\pm$ 70 | 146 $\pm$ 1
VLA-65 | 18:05.5760 $\pm$ 0.0010 | 58:13.171 $\pm$ 0.008 | 26.3 $\pm$ 2.6 | 33.7 $\pm$ 3.4 | 440 $\pm$ 44 | 27 $\pm$ 3
VLA-66 | 18:02.2280 $\pm$ 0.0010 | 59:22.077 $\pm$ 0.006 | 115.5 $\pm$ 11.7 | 176.4 $\pm$ 18.0 | 671 $\pm$ 67 | 4 $\pm$ 3

141414 The sources between the dashed lines correspond to those that have been
detected at both regions.

##  Appendix D Comments on individual sources

###  D.1 VLA-14

VLA-14 is associated with the brightest millimeter dust core MM1 of
G14.2-hub-N, with a derived mass $\sim 13$ M☉ (Busquet et al. 2016), and with
H2O maser emission (Wang et al. 2006). In Fig. 15 (left panel) we present the
1.3 mm dust emission observed with the SMA with an angular resolution of $\sim
1\aas@@fstack{\prime\prime}5$ overlaid on the 3.6 cm continuum emission. The
radio emission of VLA-14 has an elongated morphology, extending $\sim
1\aas@@fstack{\prime\prime}8\sim 2800$ au, roughly in the northeast to
southwest direction, reminiscent of a jet with knots. The emission consists of
three peaks, with the northern one coinciding with the dust continuum peak
(MM1a). Figure 15 (right panel) shows the spectral index map obtained from the
6 cm and 3.6 cm images produced with a common $(u,v)$ range (see Sect. 2).
There are significant changes in the spectral index along the radio source.
While the southern knot shows a clear positive spectral index
($\alpha\sim+0.3$), suggesting partially optically thick free-free emission
from thermal radio jets, the central and northern knots are clearly associated
with non-thermal emission, with an spectral index around $-0.7<\alpha<-0.3$.
This behavior, with the driving source having non-thermal emission, is
slightly different to what has been found in well-studied radio jets, with the
radio emission from the jet driving source associated with thermal free-free
emission and the jet knots presenting negative spectral indices (Carrasco-
González et al. 2010; Rodríguez-Kamenetzky et al. 2016, 2017). Nevertheless,
we suggest that VLA-14 is tracing a collimated radio jet powered by MM1a with
the central and northeast radio knots associated with synchrotron emission